A role for gene duplication and natural variation of gene expression in the evolution of metabolism.

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Daniel J Kliebenstein

Full Text Available BACKGROUND: Most eukaryotic genomes have undergone whole genome duplications during their evolutionary history. Recent studies have shown that the function of these duplicated genes can diverge from the ancestral gene via neo- or sub-functionalization within single genotypes. An additional possibility is that gene duplicates may also undergo partitioning of function among different genotypes of a species leading to genetic differentiation. Finally, the ability of gene duplicates to diverge may be limited by their biological function. METHODOLOGY/PRINCIPAL FINDINGS: To test these hypotheses, I estimated the impact of gene duplication and metabolic function upon intraspecific gene expression variation of segmental and tandem duplicated genes within Arabidopsis thaliana. In all instances, the younger tandem duplicated genes showed higher intraspecific gene expression variation than the average Arabidopsis gene. Surprisingly, the older segmental duplicates also showed evidence of elevated intraspecific gene expression variation albeit typically lower than for the tandem duplicates. The specific biological function of the gene as defined by metabolic pathway also modulated the level of intraspecific gene expression variation. The major energy metabolism and biosynthetic pathways showed decreased variation, suggesting that they are constrained in their ability to accumulate gene expression variation. In contrast, a major herbivory defense pathway showed significantly elevated intraspecific variation suggesting that it may be under pressure to maintain and/or generate diversity in response to fluctuating insect herbivory pressures. CONCLUSION: These data show that intraspecific variation in gene expression is facilitated by an interaction of gene duplication and biological activity. Further, this plays a role in controlling diversity of plant metabolism.

Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis.

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Eugene Lin

Full Text Available Increased risk of developing metabolic syndrome (MetS has been associated with the circadian clock genes. In this study, we assessed whether 29 circadian clock-related genes (including ADCYAP1, ARNTL, ARNTL2, BHLHE40, CLOCK, CRY1, CRY2, CSNK1D, CSNK1E, GSK3B, HCRTR2, KLF10, NFIL3, NPAS2, NR1D1, NR1D2, PER1, PER2, PER3, REV1, RORA, RORB, RORC, SENP3, SERPINE1, TIMELESS, TIPIN, VIP, and VIPR2 are associated with MetS and its individual components independently and/or through complex interactions in a Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing MetS and its individual components. A total of 3,000 Taiwanese subjects from the Taiwan Biobank were assessed in this study. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured. Our data showed a nominal association of MetS with several single nucleotide polymorphisms (SNPs in five key circadian clock genes including ARNTL, GSK3B, PER3, RORA, and RORB; but none of these SNPs persisted significantly after performing Bonferroni correction. Moreover, we identified the effect of GSK3B rs2199503 on high fasting glucose (P = 0.0002. Additionally, we found interactions among the ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, RORA rs8034880, and RORB rs972902 SNPs influenced MetS (P < 0.001 ~ P = 0.002. Finally, we investigated the influence of interactions between ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, and RORB rs972902 with environmental factors such as alcohol consumption, smoking status, and physical activity on MetS and its individual components (P < 0.001 ~ P = 0.002. Our study indicates that circadian clock genes such as ARNTL, GSK3B, PER3, RORA, and RORB genes may contribute to the risk of MetS independently as well as through gene-gene and gene-environment interactions.

Methylobacterium-plant interaction genes regulated by plant exudate and quorum sensing molecules

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Manuella Nóbrega Dourado

2013-12-01

Full Text Available Bacteria from the genus Methylobacterium interact symbiotically (endophytically and epiphytically with different plant species. These interactions can promote plant growth or induce systemic resistance, increasing plant fitness. The plant colonization is guided by molecular communication between bacteria-bacteria and bacteria-plants, where the bacteria recognize specific exuded compounds by other bacteria (e.g. homoserine molecules and/or by the plant roots (e.g. flavonoids, ethanol and methanol, respectively. In this context, the aim of this study was to evaluate the effect of quorum sensing molecules (N-acyl-homoserine lactones and plant exudates (including ethanol in the expression of a series of bacterial genes involved in Methylobacterium-plant interaction. The selected genes are related to bacterial metabolism (mxaF, adaptation to stressful environment (crtI, phoU and sss, to interactions with plant metabolism compounds (acdS and pathogenicity (patatin and phoU. Under in vitro conditions, our results showed the differential expression of some important genes related to metabolism, stress and pathogenesis, thereby AHL molecules up-regulate all tested genes, except phoU, while plant exudates induce only mxaF gene expression. In the presence of plant exudates there is a lower bacterial density (due the endophytic and epiphytic colonization, which produce less AHL, leading to down regulation of genes when compared to the control. Therefore, bacterial density, more than plant exudate, influences the expression of genes related to plant-bacteria interaction.

A global evolutionary and metabolic analysis of human obesity gene risk variants.

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Castillo, Joseph J; Hazlett, Zachary S; Orlando, Robert A; Garver, William S

2017-09-05

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution. Copyright © 2017. Published by Elsevier B.V.

Association of peroxisome proliferator-activated receptor single-nucleotide polymorphisms and gene-gene interactions with the lipoprotein(a)

Institute of Scientific and Technical Information of China (English)

解惠坚

2014-01-01

Objective To examine the associations of 10 singlenucleotide polymorphisms(SNPs)in peroxisome proliferator-activated receptor(PPARs)gene with lipoprotein(a)level,and to investigate if there is gene-gene interaction among the SNPs on lipoprotein(a)level.Methods Totally 644 subjects(234 men and 410 women)were enrolled from Prevention of Multiple Metabolic Disorders and Metabolic Syndrome Study Cohort,which was an urban community survey study conducted in Jiangsu province.Ten SNPs in PPARα(rs135539,rs4253778,

Novel genes in LDL metabolism

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Christoffersen, Mette; Tybjærg-Hansen, Anne

2015-01-01

PURPOSE OF REVIEW: To summarize recent findings from genome-wide association studies (GWAS), whole-exome sequencing of patients with familial hypercholesterolemia and 'exome chip' studies pointing to novel genes in LDL metabolism. RECENT FINDINGS: The genetic loci for ATP-binding cassette......-exome sequencing and 'exome chip' studies have additionally suggested several novel genes in LDL metabolism including insulin-induced gene 2, signal transducing adaptor family member 1, lysosomal acid lipase A, patatin-like phospholipase domain-containing protein 5 and transmembrane 6 superfamily member 2. Most...... of these findings still require independent replications and/or functional studies to confirm the exact role in LDL metabolism and the clinical implications for human health. SUMMARY: GWAS, exome sequencing studies, and recently 'exome chip' studies have suggested several novel genes with effects on LDL cholesterol...

Physiological and molecular implications of plant polyamine metabolism during biotic interactions

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Juan Francisco Jiménez Bremont

2014-03-01

Full Text Available During ontogeny, plants interact with a wide variety of microorganisms. The association with mutualistic microbes results in benefits for the plant. By contrast, pathogens may cause a remarkable impairment of plant growth and development. Both types of plant-microbe interactions provoke notable changes in the polyamine (PA metabolism of the host and/or the microbe, being each interaction a complex and dynamic process. It has been well documented that the levels of free and conjugated PAs undergo profound changes in plant tissues during the interaction with microorganisms. In general, this is correlated with a precise and coordinated regulation of PA biosynthetic and catabolic enzymes. Interestingly, some evidence suggests that the relative importance of these metabolic pathways may depend on the nature of the microorganism, a concept that stems from the fact that these amines mediate the activation of plant defense mechanisms. This effect is mediated mostly through PA oxidation, even though part of the response is activated by non-oxidized PAs. In the last years, a great deal of effort has been devoted to profile plant gene expression following microorganism recognition. In addition, the phenotypes of transgenic and mutant plants in PA metabolism genes have been assessed. In this review, we integrated the current knowledge on this field and analyze the possible roles of these amines during the interaction of plants with microbes.

Assessing SNP-SNP interactions among DNA repair, modification and metabolism related pathway genes in breast cancer susceptibility.

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Yadav Sapkota

Full Text Available Genome-wide association studies (GWASs have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii to replicate these SNPs in an independent set of breast cancer cases and controls; and iii to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412 in logistic regression that conferred elevated risks for breast cancer (P(interaction<7.3 × 10(-3. Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943 (P(permutation = 2.4 × 10(-3. SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P

A study for association and interaction analysis to metabolic syndrome and the ESR1 gene on cardiovascular autonomic neuropathy in a Chinese Han population.

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Zeng, Fangfang; Zhou, Linuo; Tang, Zihui

2016-01-01

The aim of this study was to investigate the association and interaction of metabolic syndrome (MetS) and estrogen receptor alpha 1 (ESR1) gene polymorphisms on cardiovascular autonomic neuropathy (CAN). A large-scale, population-based study was conducted to analyze the interaction of MetS and ESR1 gene polymorphisms to CAN, including a total of 1977 Chinese subjects. The most common studied single nucleotide polymorphism of ESR1 gene-rs9340799, was genotyped. Multiple logistic regression (MLR) was performed to evaluate the interaction effect of environmental variables and gene polymorphisms. Interaction on an additive scale can be calculated by using the relative excess risk due to interaction (RERI), the proportion attributable to interaction (AP), and the synergy index (S). After controlling potential confounders, MLR showed that significant association between MetS and CAN (p interaction was estimated by using RETI = 0.396 (95 % CI 0.262 to 0.598), AP = 0.216 (95 % CI -0.784 to 1.216) and S = 1.906 (95 % CI 0.905 to 4.015). The present findings suggest that MetS is significantly associated with CAN and provide evidence for the hypothesis that MetS and ESR1 gene polymorphism (rs9340799) have interactive effects on CAN. ClinicalTrials gov Identifier NCT02461342.

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk

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Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P

2016-01-01

and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...

Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.

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Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

2016-05-01

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Interaction between prenatal pesticide exposure and a common polymorphism in the PON1 gene on DNA methylation in genes associated with cardio-metabolic disease risk-an exploratory study

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Declerck, Ken; Remy, Sylvie; Wohlfahrt-Veje, Christine

2017-01-01

BACKGROUND: Prenatal environmental conditions may influence disease risk in later life. We previously found a gene-environment interaction between the paraoxonase 1 (PON1) Q192R genotype and prenatal pesticide exposure leading to an adverse cardio-metabolic risk profile at school age. However...... was observed in prenatally pesticide exposed children carrying the PON1 192R-allele. Differentially methylated genes were enriched in several neuroendocrine signaling pathways including dopamine-DARPP32 feedback (appetite, reward pathways), corticotrophin releasing hormone signaling, nNOS, neuregulin signaling...

Differential retention of metabolic genes following whole-genome duplication.

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Gout, Jean-François; Duret, Laurent; Kahn, Daniel

2009-05-01

Classical studies in Metabolic Control Theory have shown that metabolic fluxes usually exhibit little sensitivity to changes in individual enzyme activity, yet remain sensitive to global changes of all enzymes in a pathway. Therefore, little selective pressure is expected on the dosage or expression of individual metabolic genes, yet entire pathways should still be constrained. However, a direct estimate of this selective pressure had not been evaluated. Whole-genome duplications (WGDs) offer a good opportunity to address this question by analyzing the fates of metabolic genes during the massive gene losses that follow. Here, we take advantage of the successive rounds of WGD that occurred in the Paramecium lineage. We show that metabolic genes exhibit different gene retention patterns than nonmetabolic genes. Contrary to what was expected for individual genes, metabolic genes appeared more retained than other genes after the recent WGD, which was best explained by selection for gene expression operating on entire pathways. Metabolic genes also tend to be less retained when present at high copy number before WGD, contrary to other genes that show a positive correlation between gene retention and preduplication copy number. This is rationalized on the basis of the classical concave relationship relating metabolic fluxes with enzyme expression.

The interactive effects of mercury and selenium on metabolic profiles, gene expression and antioxidant enzymes in halophyte Suaeda salsa.

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Liu, Xiaoli; Lai, Yongkai; Sun, Hushan; Wang, Yiyan; Zou, Ning

2016-04-01

Suaeda salsa is the pioneer halophyte in the Yellow River Delta and was consumed as a popular vegetable. Mercury has become a highly risky contaminant in the sediment of intertidal zones of the Yellow River Delta. In this work, we investigated the interactive effects of mercury and selenium in S. salsa on the basis of metabolic profiling, antioxidant enzyme activities and gene expression quantification. Our results showed that mercury exposure (20 μg L(-1)) inhibited plant growth of S. salsa and induced significant metabolic responses and altered expression levels of INPS, CMO, and MDH in S. salsa samples, together with the increased activities of antioxidant enzymes including SOD and POD. Overall, these results indicated osmotic and oxidative stresses, disturbed protein degradation and energy metabolism change in S. salsa after mercury exposures. Additionally, the addition of selenium could induce both antagonistic and synergistic effects including alleviating protein degradation and aggravating osmotic stress caused by mercury. © 2014 Wiley Periodicals, Inc.

Conservation of lipid metabolic gene transcriptional regulatory networks in fish and mammals.

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Carmona-Antoñanzas, Greta; Tocher, Douglas R; Martinez-Rubio, Laura; Leaver, Michael J

2014-01-15

Lipid content and composition in aquafeeds have changed rapidly as a result of the recent drive to replace ecologically limited marine ingredients, fishmeal and fish oil (FO). Terrestrial plant products are the most economic and sustainable alternative; however, plant meals and oils are devoid of physiologically important cholesterol and long-chain polyunsaturated fatty acids (LC-PUFA), eicosapentaenoic (EPA), docosahexaenoic (DHA) and arachidonic (ARA) acids. Although replacement of dietary FO with vegetable oil (VO) has little effect on growth in Atlantic salmon (Salmo salar), several studies have shown major effects on the activity and expression of genes involved in lipid homeostasis. In vertebrates, sterols and LC-PUFA play crucial roles in lipid metabolism by direct interaction with lipid-sensing transcription factors (TFs) and consequent regulation of target genes. The primary aim of the present study was to elucidate the role of key TFs in the transcriptional regulation of lipid metabolism in fish by transfection and overexpression of TFs. The results show that the expression of genes of LC-PUFA biosynthesis (elovl and fads2) and cholesterol metabolism (abca1) are regulated by Lxr and Srebp TFs in salmon, indicating highly conserved regulatory mechanism across vertebrates. In addition, srebp1 and srebp2 mRNA respond to replacement of dietary FO with VO. Thus, Atlantic salmon adjust lipid metabolism in response to dietary lipid composition through the transcriptional regulation of gene expression. It may be possible to further increase efficient and effective use of sustainable alternatives to marine products in aquaculture by considering these important molecular interactions when formulating diets. © 2013.

Gene-Diet Interaction and Precision Nutrition in Obesity

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Yoriko Heianza

2017-04-01

Full Text Available The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.

Enantiomeric metabolic interactions and stereoselective human methadone metabolism.

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Totah, Rheem A; Allen, Kyle E; Sheffels, Pamela; Whittington, Dale; Kharasch, Evan D

2007-04-01

Methadone is administered as a racemate, although opioid activity resides in the R-enantiomer. Methadone disposition is stereoselective, with considerable unexplained variability in clearance and plasma R/S ratios. N-Demethylation of methadone in vitro is predominantly mediated by cytochrome P450 CYP3A4 and CYP2B6 and somewhat by CYP2C19. This investigation evaluated stereoselectivity, models, and kinetic parameters for methadone N-demethylation by recombinant CYP2B6, CYP3A4, and CYP2C19, and the potential for interactions between enantiomers during racemate metabolism. CYP2B6 metabolism was stereoselective. CYP2C19 was less active, and stereoselectivity was opposite that for CYP2B6. CYP3A4 was not stereoselective. With all three isoforms, enantiomer N-dealkylation rates in the racemate were lower than those of (R)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (R-methadone) or (S)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (S-methadone) alone, suggesting an enantiomeric interaction and mutual metabolic inhibition. For CYP2B6, the interaction between enantiomers was stereoselective, with S-methadone as a more potent inhibitor of R-methadone N-demethylation than R-of S-methadone. In contrast, enantiomer interactions were not stereoselective with CYP2C19 or CYP3A4. For all three cytochromes P450, methadone N-demethylation was best described by two-site enzyme models with competitive inhibition. There were minor model differences between cytochromes P450 to account for stereoselectivity of metabolism and enantiomeric interactions. Changes in plasma R/S methadone ratios observed after rifampin or troleandomycin pretreatment in humans in vivo were successfully predicted by CYP2B6- but not CYP3A4-catalyzed methadone N-demethylation. CYP2B6 is a predominant catalyst of stereoselective methadone metabolism in vitro. In vivo, CYP2B6 may be a major determinant of methadone metabolism and disposition, and CYP2B6 activity and stereoselective metabolic

Influence of IL1B, IL6 and IL10 gene variants and plasma fatty acid interaction on metabolic syndrome risk in a cross-sectional population-based study.

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Maintinguer Norde, Marina; Oki, Erica; Ferreira Carioca, Antonio Augusto; Teixeira Damasceno, Nágila Raquel; Fisberg, Regina Mara; Lobo Marchioni, Dirce Maria; Rogero, Marcelo Macedo

2018-04-01

Metabolic syndrome (MetS) is a cluster of interrelated risk factors for type 2 diabetes mellitus, and cardiovascular disease, with underlying inflammatory pathophysiology. Genetic variations and diet are well-known risk factor for MetS, but the interaction between these two factors is less explored. The aim of the study was to evaluate the influence of interaction between SNP of inflammatory genes (encoding interleukin (IL)-6, IL-1β and IL-10) and plasma fatty acids on the odds of MetS, in a population-based cross-sectional study. Among participants of the Health Survey - São Paulo, 301 adults (19-59 y) from whom a blood sample was collected were included. Individuals with and without MetS were compared according to their plasma inflammatory biomarkers, fatty acid profile, and genotype frequency of the IL1B (rs16944, rs1143623, rs1143627, rs1143634 and rs1143643), IL6 (rs1800795, rs1800796 and rs1800797) and IL10 (rs1554286, rs1800871, rs1800872, rs1800890 and rs3024490) genes SNP. The influence of gene-fatty acids interaction on MetS risk was investigated. IL6 gene SNP rs1800795 G allele was associated with higher odds for MetS (OR = 1.88; p = 0.017). Gene-fatty acid interaction was found between the IL1B gene SNP rs116944 and stearic acid (p inter = 0.043), and between rs1143634 and EPA (p inter = 0.017). For the IL10 gene SNP rs1800896, an interaction was found for arachidonic acid (p inter = 0.007) and estimated D5D activity (p inter = 0.019). The IL6 gene SNP rs1800795 G allele is associated with increased odds for MetS. Plasma fatty acid profile interacts with the IL1B and IL10 gene variants to modulate the odds for MetS. This and other interactions of risk factors can account for the unexplained heritability of MetS, and their elucidation can lead to new strategies for genome-customized prevention of MetS. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Case-only study of interactions between metabolic enzymes and smoking in colorectal cancer

International Nuclear Information System (INIS)

Fan, Chunhong; Jin, Mingjuan; Chen, Kun; Zhang, Yongjing; Zhang, Shuangshuang; Liu, Bing

2007-01-01

Gene-gene and gene-environment interactions involved in the metabolism of carcinogens may increase the risk of cancer. Our objective was to measure the interactions between common polymorphisms of P450 (CYP1A2, CYP1B1, CYP2E1), GSTM1 and T1, SULT1A1 and cigarette smoking in colorectal cancer (CRC). A case-only design was conducted in a Chinese population including 207 patients with sporadic CRC. Unconditional logistic regression analysis was performed adjusting for age, gender, alcohol consumption, and cigarette smoking. The interaction odds ratio (COR) for the gene-gene interaction between CYP1B1 1294G and SULT1A1 638A allele was 2.68 (95% CI: 1.16–6.26). The results of the gene-environment analyses revealed that an interaction existed between cigarette smoking and the CYP1B1 1294G allele for CRC (COR = 2.62, 95%CI: 1.01–6.72), the COR for the interaction of CYP1B1 1294G and smoking history > 35 pack-years was 3.47 (95%CI: 1.12–10.80). No other significant gene-gene and gene-environment interactions were observed. Our results showed that the interaction between polymorphisms in CYP1B1 1294G and SULT1A1*2 may play a significant role on CRC in the Chinese population. Also, it is suggested that the association between cigarette smoking and CRC could be differentiated by the CYP1B1 1294G allele

Metabolic network modeling of microbial interactions in natural and engineered environmental systems

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Octavio ePerez-Garcia

2016-05-01

Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

Association and Interaction Effect of AGTR1 and AGTR2 Gene Polymorphisms with Dietary Pattern on Metabolic Risk Factors of Cardiovascular Disease in Malaysian Adults.

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Yap, Roseline Wai Kuan; Shidoji, Yoshihiro; Yap, Wai Sum; Masaki, Motofumi

2017-08-09

Gene-diet interaction using a multifactorial approach is preferred to study the multiple risk factors of cardiovascular disease (CVD). This study examined the association and gene-diet interaction effects of the angiotensin II type 1 receptor ( AGTR1 ) gene (rs5186), and type 2 receptor ( AGTR2 ) gene (rs1403543) polymorphisms on metabolic risk factors of CVD in Malaysian adults. CVD parameters (BMI, blood pressure, glycated hemoglobin, total cholesterol (TC), triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), and TC/HDL-C ratio), and constructed dietary patterns "vegetables, fruits, and soy diet" (VFSD), and "rice, egg, and fish diet" (REFD) were obtained from previous studies. Genotyping analysis was performed by real-time PCR using Taqman probes. The subjects were 507 adults (151 Malays; 179 Chinese; and 177 Indians). Significant genetic associations were obtained on blood lipids for rs5186 in Malays and Chinese, and rs1403543 in Chinese females. The significant gene-diet interaction effects after adjusting for potential confounders were: rs5186 × VFSD on blood pressure in Malays ( p = 0.016), and in Chinese on blood lipids for rs5186 × REFD ( p = 0.009-0.023), and rs1403543 × VFSD in female subjects ( p = 0.001-0.011). Malays and Chinese showed higher risk for blood pressure and/or lipids involving rs5186 and rs1403543 SNPs together with gene-diet interactions, but not Indians.

Genomewide Expression and Functional Interactions of Genes under Drought Stress in Maize

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Nepolean Thirunavukkarasu

2017-01-01

Full Text Available A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype than in PC3 (a drought sensitive genotype, indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.

Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS.

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Pan, David Z; Garske, Kristina M; Alvarez, Marcus; Bhagat, Yash V; Boocock, James; Nikkola, Elina; Miao, Zong; Raulerson, Chelsea K; Cantor, Rita M; Civelek, Mete; Glastonbury, Craig A; Small, Kerrin S; Boehnke, Michael; Lusis, Aldons J; Sinsheimer, Janet S; Mohlke, Karen L; Laakso, Markku; Pajukanta, Päivi; Ko, Arthur

2018-04-17

Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development. Here we perform promoter Capture Hi-C in human adipocytes to investigate interactions between gene promoters and distal elements as a transcription-regulating mechanism contributing to these phenotypes. We find that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis-regulated gene expression. We further intersect these data with published genome-wide association studies for BMI and BMI-related metabolic traits to identify the genes that are under genetic cis regulation in human adipocytes via chromosomal interactions. This integrative genomics approach identifies four cis-eQTL-eGene relationships associated with BMI or obesity-related traits, including rs4776984 and MAP2K5, which we further confirm by EMSA, and highlights 38 additional candidate genes.

Epistasis Analysis for Estrogen Metabolic and Signaling Pathway Genes on Young Ischemic Stroke Patients

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Hsieh, Yi-Chen; Jeng, Jiann-Shing; Lin, Huey-Juan; Hu, Chaur-Jong; Yu, Chia-Chen; Lien, Li-Ming; Peng, Giia-Sheun; Chen, Chin-I; Tang, Sung-Chun; Chi, Nai-Fang; Tseng, Hung-Pin; Chern, Chang-Ming; Hsieh, Fang-I; Bai, Chyi-Huey; Chen, Yi-Rhu; Chiou, Hung-Yi; Jeng, Jiann-Shing; Tang, Sung-Chun; Yeh, Shin-Joe; Tsai, Li-Kai; Kong, Shin; Lien, Li-Ming; Chiu, Hou-Chang; Chen, Wei-Hung; Bai, Chyi-Huey; Huang, Tzu-Hsuan; Chi-Ieong, Lau; Wu, Ya-Ying; Yuan, Rey-Yue; Hu, Chaur-Jong; Sheu, Jau- Jiuan; Yu, Jia-Ming; Ho, Chun-Sum; Chen, Chin-I; Sung, Jia-Ying; Weng, Hsing-Yu; Han, Yu-Hsuan; Huang, Chun-Ping; Chung, Wen-Ting; Ke, Der-Shin; Lin, Huey-Juan; Chang, Chia-Yu; Yeh, Poh-Shiow; Lin, Kao-Chang; Cheng, Tain-Junn; Chou, Chih-Ho; Yang, Chun-Ming; Peng, Giia-Sheun; Lin, Jiann-Chyun; Hsu, Yaw-Don; Denq, Jong-Chyou; Lee, Jiunn-Tay; Hsu, Chang-Hung; Lin, Chun-Chieh; Yen, Che-Hung; Cheng, Chun-An; Sung, Yueh-Feng; Chen, Yuan-Liang; Lien, Ming-Tung; Chou, Chung-Hsing; Liu, Chia-Chen; Yang, Fu-Chi; Wu, Yi-Chung; Tso, An-Chen; Lai, Yu- Hua; Chiang, Chun-I; Tsai, Chia-Kuang; Liu, Meng-Ta; Lin, Ying-Che; Hsu, Yu-Chuan; Chen, Chih-Hung; Sung, Pi-Shan; Chern, Chang-Ming; Hu, Han-Hwa; Wong, Wen-Jang; Luk, Yun-On; Hsu, Li-Chi; Chung, Chih-Ping; Tseng, Hung-Pin; Liu, Chin-Hsiung; Lin, Chun-Liang; Lin, Hung-Chih; Hu, Chaur-Jong

2012-01-01

Background Endogenous estrogens play an important role in the overall cardiocirculatory system. However, there are no studies exploring the hormone metabolism and signaling pathway genes together on ischemic stroke, including sulfotransferase family 1E (SULT1E1), catechol-O-methyl-transferase (COMT), and estrogen receptor α (ESR1). Methods A case-control study was conducted on 305 young ischemic stroke subjects aged ≦ 50 years and 309 age-matched healthy controls. SULT1E1 -64G/A, COMT Val158Met, ESR1 c.454−397 T/C and c.454−351 A/G genes were genotyped and compared between cases and controls to identify single nucleotide polymorphisms associated with ischemic stroke susceptibility. Gene-gene interaction effects were analyzed using entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional multiple regression models. Results COMT Val158Met polymorphism showed a significant association with susceptibility of young ischemic stroke among females. There was a two-way interaction between SULT1E1 -64G/A and COMT Val158Met in both MDR and CART analysis. The logistic regression model also showed there was a significant interaction effect between SULT1E1 -64G/A and COMT Val158Met on ischemic stroke of the young (P for interaction = 0.0171). We further found that lower estradiol level could increase the risk of young ischemic stroke for those who carry either SULT1E1 or COMT risk genotypes, showing a significant interaction effect (P for interaction = 0.0174). Conclusions Our findings support that a significant epistasis effect exists among estrogen metabolic and signaling pathway genes and gene-environment interactions on young ischemic stroke subjects. PMID:23112845

Mediterranean dietary pattern and VEGF +405 G/C gene polymorphisms in patients with metabolic syndrome: An aspect of gene-nutrient interaction.

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Hajiluian, Ghazaleh; Abbasalizad Farhangi, Mahdieh; Jahangiry, Leila

2017-01-01

To evaluate the relationship between Mediterranean dietary pattern, anthropometric and metabolic biomarkers and vascular endothelial growth factor (VEGF) +405 G/C gene polymorphism in patient with metabolic syndrome (Mets). In this study 150 patients with Mets and 50 healthy subjects were enrolled. Dietary intakes were evaluated with a semi-quantitative food-frequency questionnaire (FFQ) and Mediterranean dietary quality index (Med-DQI) was assessed. Anthropometric assessments and blood pressure measurement were performed. Biochemical assays including fasting serum glucose (FSG), matrix metalloproteinase-3 (MMP-3), liver enzymes and lipid profiles were also assessed. Polymorphism of +405 G/C VEGF gene was determined utilizing polymerase chain reaction-restriction fragments length polymorphism (PCR-RFLP) method. Serum high density lipoprotein-cholesterol (HDL-C) was significantly lower and low density lipoprotein cholesterol (LDL-C), triglyceride (TG), total cholesterol (TC) concentrations and FSG were significantly higher in metabolic syndrome patients compared with control group (P consumption of "cholesterol" had significantly upper serum TG; also high consumption of "fish" and "vegetables-fruits" was associated with a significantly lower serum LDL concentrations. In metabolic syndrome patients with CC genotype, mean score of "saturated fatty acid" subgroup was significantly higher compared with other genotypes; whereas, in healthy individuals, mean score of "fruit-vegetable" subgroup in individuals of CC and GG genotype was significantly higher (P<0.05). Our findings indicated a significant relationship between Mediterranean dietary quality index and both anthropometric and metabolic risk factors. We also indicated a higher "saturated fatty acid" intake in CC genotype among metabolic syndrome patients.

Deep-Sea Hydrothermal Vent Viruses Compensate for Microbial Metabolism in Virus-Host Interactions.

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He, Tianliang; Li, Hongyun; Zhang, Xiaobo

2017-07-11

Viruses are believed to be responsible for the mortality of host organisms. However, some recent investigations reveal that viruses may be essential for host survival. To date, it remains unclear whether viruses are beneficial or harmful to their hosts. To reveal the roles of viruses in the virus-host interactions, viromes and microbiomes of sediment samples from three deep-sea hydrothermal vents were explored in this study. To exclude the influence of exogenous DNAs on viromes, the virus particles were purified with nuclease (DNase I and RNase A) treatments and cesium chloride density gradient centrifugation. The metagenomic analysis of viromes without exogenous DNA contamination and microbiomes of vent samples indicated that viruses had compensation effects on the metabolisms of their host microorganisms. Viral genes not only participated in most of the microbial metabolic pathways but also formed branched pathways in microbial metabolisms, including pyrimidine metabolism; alanine, aspartate, and glutamate metabolism; nitrogen metabolism and assimilation pathways of the two-component system; selenocompound metabolism; aminoacyl-tRNA biosynthesis; and amino sugar and nucleotide sugar metabolism. As is well known, deep-sea hydrothermal vent ecosystems exist in relatively isolated environments which are barely influenced by other ecosystems. The metabolic compensation of hosts mediated by viruses might represent a very important aspect of virus-host interactions. IMPORTANCE Viruses are the most abundant biological entities in the oceans and have very important roles in regulating microbial community structure and biogeochemical cycles. The relationship between virus and host microbes is broadly thought to be that of predator and prey. Viruses can lyse host cells to control microbial population sizes and affect community structures of hosts by killing specific microbes. However, viruses also influence their hosts through manipulation of bacterial metabolism. We found

Genetic polymorphisms in CYP1A1, GSTM1, GSTP1 and GSTT1 metabolic genes and risk of lung cancer in Asturias

International Nuclear Information System (INIS)

López-Cima, M Felicitas; Álvarez-Avellón, Sara M; Pascual, Teresa; Fernández-Somoano, Ana; Tardón, Adonina

2012-01-01

Metabolic genes have been associated with the function of metabolizing and detoxifying environmental carcinogens. Polymorphisms present in these genes could lead to changes in their metabolizing and detoxifying ability and thus may contribute to individual susceptibility to different types of cancer. We investigated if the individual and/or combined modifying effects of the CYP1A1 MspI T6235C, GSTM1 present/null, GSTT1 present/null and GSTP1 Ile105Val polymorphisms are related to the risk of developing lung cancer in relation to tobacco consumption and occupation in Asturias, Northern Spain. A hospital-based case–control study (CAPUA Study) was designed including 789 lung cancer patients and 789 control subjects matched in ethnicity, age, sex, and hospital. Genotypes were determined by PCR or PCR-RFLP. Individual and combination effects were analysed using an unconditional logistic regression adjusting for age, pack-years, family history of any cancer and occupation. No statistically significant main effects were observed for the carcinogen metabolism genes in relation to lung cancer risk. In addition, the analysis did not reveal any significant gene-gene, gene-tobacco smoking or gene-occupational exposure interactions relative to lung cancer susceptibility. Lastly, no significant gene-gene combination effects were observed. These results suggest that genetic polymorphisms in the CYP1A1, GSTM1, GSTT1 and GSTP1 metabolic genes were not significantly associated with lung cancer risk in the current study. The results of the analysis of gene-gene interactions of CYP1A1 MspI T6235C, GSTM1 present/null, GSTT1 present/null and GSTP1 Ile105Val polymorphisms in lung cancer risk indicate that these genes do not interact in lung cancer development

GeneChip expression profiling reveals the alterations of energy metabolism related genes in osteocytes under large gradient high magnetic fields.

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Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong

2015-01-01

The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis.

GeneChip expression profiling reveals the alterations of energy metabolism related genes in osteocytes under large gradient high magnetic fields.

Directory of Open Access Journals (Sweden)

Yang Wang

Full Text Available The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF, which can provide three apparent gravity levels (μ-g, 1-g, and 2-g, was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84 were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis.

Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

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Lun Yang

Full Text Available Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

Functional genomics tools applied to plant metabolism: a survey on plant respiration, its connections and the annotation of complex gene functions

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Wagner L. Araújo

2012-09-01

Full Text Available The application of post-genomic techniques in plant respiration studies has greatly improved our ability to assign functions to gene products. In addition it has also revealed previously unappreciated interactions between distal elements of metabolism. Such results have reinforced the need to consider plant respiratory metabolism as part of a complex network and making sense of such interactions will ultimately require the construction of predictive and mechanistic models. Transcriptomics, proteomics, metabolomics and the quantification of metabolic flux will be of great value in creating such models both by facilitating the annotation of complex gene function, determining their structure and by furnishing the quantitative data required to test them. In this review we highlight how these experimental approaches have contributed to our current understanding of plant respiratory metabolism and its interplay with associated process (e.g. photosynthesis, photorespiration and nitrogen metabolism. We also discuss how data from these techniques may be integrated, with the ultimate aim of identifying mechanisms that control and regulate plant respiration and discovering novel gene functions with potential biotechnological implications.

Sugar Lego: gene composition of bacterial carbohydrate metabolism genomic loci.

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Kaznadzey, Anna; Shelyakin, Pavel; Gelfand, Mikhail S

2017-11-25

Bacterial carbohydrate metabolism is extremely diverse, since carbohydrates serve as a major energy source and are involved in a variety of cellular processes. Bacterial genes belonging to same metabolic pathway are often co-localized in the chromosome, but it is not a strict rule. Gene co-localization in linked to co-evolution and co-regulation. This study focuses on a large-scale analysis of bacterial genomic loci related to the carbohydrate metabolism. We demonstrate that only 53% of 148,000 studied genes from over six hundred bacterial genomes are co-localized in bacterial genomes with other carbohydrate metabolism genes, which points to a significant role of singleton genes. Co-localized genes form cassettes, ranging in size from two to fifteen genes. Two major factors influencing the cassette-forming tendency are gene function and bacterial phylogeny. We have obtained a comprehensive picture of co-localization preferences of genes for nineteen major carbohydrate metabolism functional classes, over two hundred gene orthologous clusters, and thirty bacterial classes, and characterized the cassette variety in size and content among different species, highlighting a significant role of short cassettes. The preference towards co-localization of carbohydrate metabolism genes varies between 40 and 76% for bacterial taxa. Analysis of frequently co-localized genes yielded forty-five significant pairwise links between genes belonging to different functional classes. The number of such links per class range from zero to eight, demonstrating varying preferences of respective genes towards a specific chromosomal neighborhood. Genes from eleven functional classes tend to co-localize with genes from the same class, indicating an important role of clustering of genes with similar functions. At that, in most cases such co-localization does not originate from local duplication events. Overall, we describe a complex web formed by evolutionary relationships of bacterial

Metabolic Phase I (CYPs) and Phase II (GSTs) Gene Polymorphisms and Their Interaction with Environmental Factors in Nasopharyngeal Cancer from the Ethnic Population of Northeast India.

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Singh, Seram Anil; Ghosh, Sankar Kumar

2017-09-26

Multiple genetic and environmental factors and their interaction are believed to contribute in the pathogenesis of Nasopharyngeal Cancer (NPC). We investigate the role of Metabolic Phase I (CYPs) and Phase II (GSTs) gene polymorphisms, gene-gene and gene-environmental interaction in modulating the susceptibility to NPC in Northeast India. To determine the association of metabolic gene polymorphisms and environmental habits, 123 cases and 189 controls blood/swab samples were used for PCR and confirmed by Sanger sequencing. Analysis for GSTM1 and GSTT1 gene polymorphism was done by multiplex PCR. The T3801C in the 3'- flanking region of CYP1A1 gene was detected by PCR-RFLP method. The Logistic regression analysis was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI). The GSTM1 null genotype alone (OR = 2.76) was significantly associated with NPC risk (P < 0.0001). The combinations of GSTM1 null and GSTT1 null genotypes also higher, 3.77 fold (P < 0.0001), risk of NPC, while GSTM1 null genotype along with CYP1A1 T3801C TC + CC genotype had 3.22 (P = 0.001) fold risk. The most remarkable risk was seen among individual carrying GSTM1 null, GSTT1 null genotypes and CYP1A1 T3801C TC + CC genotypes (OR = 5.71, P = 0.001). Further; analyses demonstrate an enhanced risk of NPC in smoked meat (OR = 5.56, P < 0.0001) and fermented fish consumers (OR = 5.73, P < 0.0001) carrying GSTM1 null genotype. An elevated risk of NPC was noted in smokers (OR = 12.67, P < 0.0001) and chewers (OR = 5.68, P < 0.0001) with GSTM1 null genotype. However, smokers had the highest risk of NPC among individuals carrying GSTT1 null genotype (OR = 4.46, P = 0.001) or CYP1A1 T3801C TC + CC genotype (OR = 7.13, P < 0.0001). The association of null genotypes and mutations of metabolic neutralizing genes along with the environmental habits (tobacco smokers and chewers, smoke meat, fermented fishes) can be used as a possible biomarker for

Co-ordinate regulation of lactate metabolism genes in yeast: the role of the lactate permease gene JEN1.

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Lodi, T; Fontanesi, F; Guiard, B

2002-01-01

In the yeast Saccharomyces cerevisiae, the first step in lactate metabolism is its transport across the plasma membrane, a proton symport process mediated by the product of the gene JEN1. Under aerobic conditions, the expression of JEN1 is regulated by the carbon source: the gene is repressed by glucose and induced by non-fermentable substrates. JEN1 expression is also controlled by oxygen availability, but is unaffected by the absence of haem biosynthesis. JEN1 is negatively regulated by the repressors Mig1p and Mig2p, and requires Cat8p for full derepression. In this report we demonstrate that, in addition to these regulators, the Hap2/3/4/5 complex interacts specifically with a CAAT-box element in the JEN1 promoter, and acts to derepress JEN1 expression. We also provide evidence for transcriptional stimulation of JEN1 by the protein kinase Snf1p. Data are presented which provide a better understanding of the molecular mechanisms implicated in the co-regulation of genes involved in the metabolism of lactate.

The Association of Polymorphisms in Leptin/Leptin Receptor Genes and Ghrelin/Ghrelin Receptor Genes With Overweight/Obesity and the Related Metabolic Disturbances: A Review.

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Ghalandari, Hamid; Hosseini-Esfahani, Firoozeh; Mirmiran, Parvin

2015-07-01

Leptin and ghrelin are two important appetite and energy balance-regulating peptides. Common polymorphisms in the genes coding these peptides and their related receptors are shown to be associated with body weight, different markers of obesity and metabolic abnormalities. This review article aims to investigate the association of common polymorphisms of these genes with overweight/obesity and the metabolic disturbances related to it. The keywords leptin, ghrelin, polymorphism, single-nucleotide polymorphism (SNP), obesity, overweight, Body Mass Index, metabolic syndrome, and type 2 diabetes mellitus (T2DM) (MeSH headings) were used to search in the following databases: Pubmed, Sciencedirect (Elsevier), and Google scholar. Overall, 24 case-control studies, relevant to our topic, met the criteria and were included in the review. The most prevalent leptin/leptin receptor genes (LEP/LEPR) and ghrelin/ghrelin receptor genes (GHRL/GHSR) single nucleotide polymorphisms studied were LEP G-2548A, LEPR Q223R, and Leu72Met, respectively. Nine studies of the 17 studies on LEP/LEPR, and three studies of the seven studies on GHRL/GHSR showed significant relationships. In general, our study suggests that the association between LEP/LEPR and GHRL/GHSR with overweight/obesity and the related metabolic disturbances is inconclusive. These results may be due to unidentified gene-environment interactions. More investigations are needed to further clarify this association.

Apolipoprotein gene involved in lipid metabolism

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Rubin, Edward; Pennacchio, Len A.

2007-07-03

Methods and materials for studying the effects of a newly identified human gene, APOAV, and the corresponding mouse gene apoAV. The sequences of the genes are given, and transgenic animals which either contain the gene or have the endogenous gene knocked out are described. In addition, single nucleotide polymorphisms (SNPs) in the gene are described and characterized. It is demonstrated that certain SNPs are associated with diseases involving lipids and triglycerides and other metabolic diseases. These SNPs may be used alone or with SNPs from other genes to study individual risk factors. Methods for intervention in lipid diseases, including the screening of drugs to treat lipid-related or diabetic diseases are also disclosed.

Duplicability of self-interacting human genes.

LENUS (Irish Health Repository)

Pérez-Bercoff, Asa

2010-01-01

BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

Recent developments in systems biology and metabolic engineering of plant microbe interactions

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Vishal Kumar

2016-09-01

Full Text Available Microorganisms play a crucial role in the sustainability of the various ecosystems. The characterization of various interactions between microorganisms and other biotic factors is a necessary footstep to understand the association and functions of microbial communities. Among the different microbial interactions in an ecosystem, plant-microbe interaction plays an important role to balance the ecosystem. The present review explores plant microbe interactions using gene editing and system biology tools towards the comprehension in improvement of plant traits. Further, system biology tools like FBA, OptKnock and constrain based modeling helps in understanding such interactions as a whole. In addition, various gene editing tools have been summarized and a strategy has been hypothesized for the development of disease free plants. Furthermore, we have tried to summarize the predictions through data retrieved from various types of sources such as high throughput sequencing data (e.g. single nucleotide polymorphism (SNP detection, RNA-seq, proteomics and metabolic models have been reconstructed from such sequences for species communities. It is well known fact that systems biology approaches and modeling of biological networks will enable us to learn the insight of such network and will also help further in understanding these interactions.

[Gene-gene interaction on central obesity in school-aged children in China].

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Fu, L W; Zhang, M X; Wu, L J; Gao, L W; Mi, J

2017-07-10

Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms ( FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model ( OR =1.24, 95 %CI : 1.06-1.45, P =0.008; OR =1.26, 95 %CI : 1.11-1.43, P =2.98×10(-4); OR =1.18, 95 % CI : 1.06-1.32, P =0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 ( P =0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

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Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

2017-05-01

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

A genetic ensemble approach for gene-gene interaction identification

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Ho Joshua WK

2010-10-01

Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

Functional modules by relating protein interaction networks and gene expression.

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Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

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Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

2017-11-01

The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Research progress in machine learning methods for gene-gene interaction detection.

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Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

2018-03-20

Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

Science.gov (United States)

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

Interaction of pathogens with host cholesterol metabolism.

Science.gov (United States)

Sviridov, Dmitri; Bukrinsky, Michael

2014-10-01

Pathogens of different taxa, from prions to protozoa, target cellular cholesterol metabolism to advance their own development and to impair host immune responses, but also causing metabolic complications, for example, atherosclerosis. This review describes recent findings of how pathogens do it. A common theme in interaction between pathogens and host cholesterol metabolism is pathogens targeting lipid rafts of the host plasma membrane. Many intracellular pathogens use rafts as an entry gate, taking advantage of the endocytic machinery and high abundance of outward-looking molecules that can be used as receptors. At the same time, disruption of the rafts' functional capacity, achieved by the pathogens through a number of various means, impairs the ability of the host to generate immune response, thus helping pathogen to thrive. Pathogens cannot synthesize cholesterol, and salvaging host cholesterol helps pathogens build advanced cholesterol-containing membranes and assembly platforms. Impact on cholesterol metabolism is not limited to the infected cells; proteins and microRNAs secreted by infected cells affect lipid metabolism systemically. Given an essential role that host cholesterol metabolism plays in pathogen development, targeting this interaction may be a viable strategy to fight infections, as well as metabolic complications of the infections.

Inferring metabolic states in uncharacterized environments using gene-expression measurements.

Directory of Open Access Journals (Sweden)

Sergio Rossell

Full Text Available The large size of metabolic networks entails an overwhelming multiplicity in the possible steady-state flux distributions that are compatible with stoichiometric constraints. This space of possibilities is largest in the frequent situation where the nutrients available to the cells are unknown. These two factors: network size and lack of knowledge of nutrient availability, challenge the identification of the actual metabolic state of living cells among the myriad possibilities. Here we address this challenge by developing a method that integrates gene-expression measurements with genome-scale models of metabolism as a means of inferring metabolic states. Our method explores the space of alternative flux distributions that maximize the agreement between gene expression and metabolic fluxes, and thereby identifies reactions that are likely to be active in the culture from which the gene-expression measurements were taken. These active reactions are used to build environment-specific metabolic models and to predict actual metabolic states. We applied our method to model the metabolic states of Saccharomyces cerevisiae growing in rich media supplemented with either glucose or ethanol as the main energy source. The resulting models comprise about 50% of the reactions in the original model, and predict environment-specific essential genes with high sensitivity. By minimizing the sum of fluxes while forcing our predicted active reactions to carry flux, we predicted the metabolic states of these yeast cultures that are in large agreement with what is known about yeast physiology. Most notably, our method predicts the Crabtree effect in yeast cells growing in excess glucose, a long-known phenomenon that could not have been predicted by traditional constraint-based modeling approaches. Our method is of immediate practical relevance for medical and industrial applications, such as the identification of novel drug targets, and the development of

Chronic obstructive pulmonary disease candidate gene prioritization based on metabolic networks and functional information.

Directory of Open Access Journals (Sweden)

Xinyan Wang

Full Text Available Chronic obstructive pulmonary disease (COPD is a multi-factor disease, in which metabolic disturbances played important roles. In this paper, functional information was integrated into a COPD-related metabolic network to assess similarity between genes. Then a gene prioritization method was applied to the COPD-related metabolic network to prioritize COPD candidate genes. The gene prioritization method was superior to ToppGene and ToppNet in both literature validation and functional enrichment analysis. Top-ranked genes prioritized from the metabolic perspective with functional information could promote the better understanding about the molecular mechanism of this disease. Top 100 genes might be potential markers for diagnostic and effective therapies.

A Nonlinear Model for Gene-Based Gene-Environment Interaction

Directory of Open Access Journals (Sweden)

Jian Sa

2016-06-01

Full Text Available A vast amount of literature has confirmed the role of gene-environment (G×E interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

Science.gov (United States)

Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

2015-01-01

Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

Exploring NAD+ metabolism in host-pathogen interactions.

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Mesquita, Inês; Varela, Patrícia; Belinha, Ana; Gaifem, Joana; Laforge, Mireille; Vergnes, Baptiste; Estaquier, Jérôme; Silvestre, Ricardo

2016-03-01

Nicotinamide adenine dinucleotide (NAD(+)) is a vital molecule found in all living cells. NAD(+) intracellular levels are dictated by its synthesis, using the de novo and/or salvage pathway, and through its catabolic use as co-enzyme or co-substrate. The regulation of NAD(+) metabolism has proven to be an adequate drug target for several diseases, including cancer, neurodegenerative or inflammatory diseases. Increasing interest has been given to NAD(+) metabolism during innate and adaptive immune responses suggesting that its modulation could also be relevant during host-pathogen interactions. While the maintenance of NAD(+) homeostatic levels assures an adequate environment for host cell survival and proliferation, fluctuations in NAD(+) or biosynthetic precursors bioavailability have been described during host-pathogen interactions, which will interfere with pathogen persistence or clearance. Here, we review the double-edged sword of NAD(+) metabolism during host-pathogen interactions emphasizing its potential for treatment of infectious diseases.

Significantly increased risk of carotid atherosclerosis with arsenic exposure and polymorphisms in arsenic metabolism genes

International Nuclear Information System (INIS)

Hsieh, Yi-Chen; Lien, Li-Ming; Chung, Wen-Ting; Hsieh, Fang-I; Hsieh, Pei-Fan; Wu, Meei-Maan; Tseng, Hung-Pin; Chiou, Hung-Yi; Chen, Chien-Jen

2011-01-01

Individual susceptibility to arsenic-induced carotid atherosclerosis might be associated with genetic variations in arsenic metabolism. The purpose of this study is to explore the interaction effect on risk of carotid atherosclerosis between arsenic exposure and risk genotypes of purine nucleoside phosphorylase (PNP), arsenic (+3) methyltransferase (As3MT), and glutathione S-transferase omega 1 (GSTO1) and omega 2 (GSTO2). A community-based case-control study was conducted in northeastern Taiwan to investigate the arsenic metabolic-related genetic susceptibility to carotid atherosclerosis. In total, 863 subjects, who had been genotyped and for whom the severity of carotid atherosclerosis had been determined, were included in the present study. Individual well water was collected and arsenic concentration determined using hydride generation combined with flame atomic absorption spectrometry. The result showed that a significant dose-response trend (P=0.04) of carotid atherosclerosis risk associated with increasing arsenic concentration. Non-significant association between genetic polymorphisms of PNP Gly51Ser, Pro57Pro, As3MT Met287Thr, GSTO1 Ala140Asp, and GSTO2 A-183G and the risk for development of carotid atherosclerosis were observed. However, the significant interaction effect on carotid atherosclerosis risk was found for arsenic exposure (>50 μg/l) and the haplotypes of PNP (p=0.0115). A marked elevated risk of carotid atherosclerosis was observed in subjects with arsenic exposure of >50 μg/l in drinking water and those who carried the PNP A-T haplotype and at least either of the As3MT risk polymorphism or GSTO risk haplotypes (OR, 6.43; 95% CI, 1.79-23.19). In conclusion, arsenic metabolic genes, PNP, As3MT, and GSTO, may exacerbate the formation of atherosclerosis in individuals with high levels of arsenic concentration in well water (>50 μg/l). - Highlights: →Arsenic metabolic genes might be associated with carotid atherosclerosis. → A case

Significantly increased risk of carotid atherosclerosis with arsenic exposure and polymorphisms in arsenic metabolism genes

Energy Technology Data Exchange (ETDEWEB)

Hsieh, Yi-Chen [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Lien, Li-Ming [Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (China); School of Medicine, Taipei Medical University, Taipei, Taiwan (China); Department of Neurology, Shin Kong WHS Memorial Hospital, Taipei, Taiwan (China); Chung, Wen-Ting [Department of Neurology, Wanfang Hospital, Taipei Medical University, Taipei, Taiwan (China); Graduate Institute of Clinical Medicine, Taipei Medical University, Taipei, Taiwan (China); Hsieh, Fang-I; Hsieh, Pei-Fan [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Wu, Meei-Maan [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Graduate Institute of Basic Medicine, College of Medicine, Fu-Jen Catholic University, Taipei, Taiwan (China); Tseng, Hung-Pin [Department of Neurology, Lotung Poh-Ai Hospital, I-Lan, Taiwan (China); Chiou, Hung-Yi, E-mail: hychiou@tmu.edu.tw [School of Public Health, College of Public Health and Nutrition, Taipei Medical University, 250 Wusing St., Taipei 11031, Taiwan (China); Chen, Chien-Jen [Genomics Research Center, Academia Sinica, Taipei, Taiwan (China)

2011-08-15

Individual susceptibility to arsenic-induced carotid atherosclerosis might be associated with genetic variations in arsenic metabolism. The purpose of this study is to explore the interaction effect on risk of carotid atherosclerosis between arsenic exposure and risk genotypes of purine nucleoside phosphorylase (PNP), arsenic (+3) methyltransferase (As3MT), and glutathione S-transferase omega 1 (GSTO1) and omega 2 (GSTO2). A community-based case-control study was conducted in northeastern Taiwan to investigate the arsenic metabolic-related genetic susceptibility to carotid atherosclerosis. In total, 863 subjects, who had been genotyped and for whom the severity of carotid atherosclerosis had been determined, were included in the present study. Individual well water was collected and arsenic concentration determined using hydride generation combined with flame atomic absorption spectrometry. The result showed that a significant dose-response trend (P=0.04) of carotid atherosclerosis risk associated with increasing arsenic concentration. Non-significant association between genetic polymorphisms of PNP Gly51Ser, Pro57Pro, As3MT Met287Thr, GSTO1 Ala140Asp, and GSTO2 A-183G and the risk for development of carotid atherosclerosis were observed. However, the significant interaction effect on carotid atherosclerosis risk was found for arsenic exposure (>50 {mu}g/l) and the haplotypes of PNP (p=0.0115). A marked elevated risk of carotid atherosclerosis was observed in subjects with arsenic exposure of >50 {mu}g/l in drinking water and those who carried the PNP A-T haplotype and at least either of the As3MT risk polymorphism or GSTO risk haplotypes (OR, 6.43; 95% CI, 1.79-23.19). In conclusion, arsenic metabolic genes, PNP, As3MT, and GSTO, may exacerbate the formation of atherosclerosis in individuals with high levels of arsenic concentration in well water (>50 {mu}g/l). - Highlights: {yields}Arsenic metabolic genes might be associated with carotid atherosclerosis. {yields

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

DEFF Research Database (Denmark)

Volkov, Petr; Olsson, Anders H; Gillberg, Linn

2016-01-01

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, w...... and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.......Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men......, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5...

Human Metabolism and Interactions of Deployment-Related Chemicals

National Research Council Canada - National Science Library

Hodgson, Ernest

2003-01-01

This study examines the human-metabolism and metabolic interactions of a subset of deployment-related chemicals, including chlorpyrifos, DEET, permethrin, pyridostigmine bromide, and sulfur mustard metabolites...

Photorespiratory metabolism: genes, mutants, energetics, and redox signaling.

Science.gov (United States)

Foyer, Christine H; Bloom, Arnold J; Queval, Guillaume; Noctor, Graham

2009-01-01

Photorespiration is a high-flux pathway that operates alongside carbon assimilation in C(3) plants. Because most higher plant species photosynthesize using only the C(3) pathway, photorespiration has a major impact on cellular metabolism, particularly under high light, high temperatures, and CO(2) or water deficits. Although the functions of photorespiration remain controversial, it is widely accepted that this pathway influences a wide range of processes from bioenergetics, photosystem II function, and carbon metabolism to nitrogen assimilation and respiration. Crucially, the photorespiratory pathway is a major source of H(2)O(2) in photosynthetic cells. Through H(2)O(2) production and pyridine nucleotide interactions, photorespiration makes a key contribution to cellular redox homeostasis. In so doing, it influences multiple signaling pathways, particularly those that govern plant hormonal responses controlling growth, environmental and defense responses, and programmed cell death. The potential influence of photorespiration on cell physiology and fate is thus complex and wide ranging. The genes, pathways, and signaling functions of photorespiration are considered here in the context of whole plant biology, with reference to future challenges and human interventions to diminish photorespiratory flux.

Gene-Environment Interactions in the Development of Complex Disease Phenotypes

Directory of Open Access Journals (Sweden)

Kenneth Olden

2008-03-01

Full Text Available The lack of knowledge about the earliest events in disease development is due to the multi-factorial nature of disease risk. This information gap is the consequence of the lack of appreciation for the fact that most diseases arise from the complex interactions between genes and the environment as a function of the age or stage of development of the individual. Whether an environmental exposure causes illness or not is dependent on the efficiency of the so-called “environmental response machinery” (i.e., the complex of metabolic pathways that can modulate response to environmental perturbations that one has inherited. Thus, elucidating the causes of most chronic diseases will require an understanding of both the genetic and environmental contribution to their etiology. Unfortunately, the exploration of the relationship between genes and the environment has been hampered in the past by the limited knowledge of the human genome, and by the inclination of scientists to study disease development using experimental models that consider exposure to a single environmental agent. Rarely in the past were interactions between multiple genes or between genes and environmental agents considered in studies of human disease etiology. The most critical issue is how to relate exposure-disease association studies to pathways and mechanisms. To understand how genes and environmental factors interact to perturb biological pathways to cause injury or disease, scientists will need tools with the capacity to monitor the global expression of thousands of genes, proteins and metabolites simultaneously. The generation of such data in multiple species can be used to identify conserved and functionally significant genes and pathways involved in geneenvironment interactions. Ultimately, it is this knowledge that will be used to guide agencies such as the U.S. Department of Health and Human Services in decisions regarding biomedical research funding

Elucidation of primary metabolic pathways in Aspergillus species: orphaned research in characterizing orphan genes.

Science.gov (United States)

Andersen, Mikael Rørdam

2014-11-01

Primary metabolism affects all phenotypical traits of filamentous fungi. Particular examples include reacting to extracellular stimuli, producing precursor molecules required for cell division and morphological changes as well as providing monomer building blocks for production of secondary metabolites and extracellular enzymes. In this review, all annotated genes from four Aspergillus species have been examined. In this process, it becomes evident that 80-96% of the genes (depending on the species) are still without verified function. A significant proportion of the genes with verified metabolic functions are assigned to secondary or extracellular metabolism, leaving only 2-4% of the annotated genes within primary metabolism. It is clear that primary metabolism has not received the same attention in the post-genomic area as many other research areas--despite its role at the very centre of cellular function. However, several methods can be employed to use the metabolic networks in tandem with comparative genomics to accelerate functional assignment of genes in primary metabolism. In particular, gaps in metabolic pathways can be used to assign functions to orphan genes. In this review, applications of this from the Aspergillus genes will be examined, and it is proposed that, where feasible, this should be a standard part of functional annotation of fungal genomes. © The Author 2014. Published by Oxford University Press.

Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

Science.gov (United States)

Pierce, Brandon L; Tong, Lin; Argos, Maria; Gao, Jianjun; Farzana, Jasmine; Roy, Shantanu; Paul-Brutus, Rachelle; Rahaman, Ronald; Rakibuz-Zaman, Muhammad; Parvez, Faruque; Ahmed, Alauddin; Quasem, Iftekhar; Hore, Samar K; Alam, Shafiul; Islam, Tariqul; Harjes, Judith; Sarwar, Golam; Slavkovich, Vesna; Gamble, Mary V; Chen, Yu; Yunus, Mohammad; Rahman, Mahfuzar; Baron, John A; Graziano, Joseph H; Ahsan, Habibul

2013-12-01

Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.

Metabolic interaction between toluene, trichloroethylene and n-hexane in humans

DEFF Research Database (Denmark)

Bælum, Jesper; Mølhave, Lars; Hansen, S H

1998-01-01

This human experimental study describes the mutual metabolic interaction between toluene, trichloroethylene, and n-hexane.......This human experimental study describes the mutual metabolic interaction between toluene, trichloroethylene, and n-hexane....

Metagenomic analysis revealed highly diverse microbial arsenic metabolism genes in paddy soils with low-arsenic contents

International Nuclear Information System (INIS)

Xiao, Ke-Qing; Li, Li-Guan; Ma, Li-Ping; Zhang, Si-Yu; Bao, Peng; Zhang, Tong; Zhu, Yong-Guan

2016-01-01

Microbe-mediated arsenic (As) metabolism plays a critical role in global As cycle, and As metabolism involves different types of genes encoding proteins facilitating its biotransformation and transportation processes. Here, we used metagenomic analysis based on high-throughput sequencing and constructed As metabolism protein databases to analyze As metabolism genes in five paddy soils with low-As contents. The results showed that highly diverse As metabolism genes were present in these paddy soils, with varied abundances and distribution for different types and subtypes of these genes. Arsenate reduction genes (ars) dominated in all soil samples, and significant correlation existed between the abundance of arr (arsenate respiration), aio (arsenite oxidation), and arsM (arsenite methylation) genes, indicating the co-existence and close-relation of different As resistance systems of microbes in wetland environments similar to these paddy soils after long-term evolution. Among all soil parameters, pH was an important factor controlling the distribution of As metabolism gene in five paddy soils (p = 0.018). To the best of our knowledge, this is the first study using high-throughput sequencing and metagenomics approach in characterizing As metabolism genes in the five paddy soil, showing their great potential in As biotransformation, and therefore in mitigating arsenic risk to humans. - Highlights: • Use metagenomics to analyze As metabolism genes in paddy soils with low-As content. • These genes were ubiquitous, abundant, and associated with diverse microbes. • pH as an important factor controlling their distribution in paddy soil. • Imply combinational effect of evolution and selection on As metabolism genes. - Metagenomics was used to analyze As metabolism genes in paddy soils with low-As contents. These genes were ubiquitous, abundant, and associated with diverse microbes.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

Science.gov (United States)

Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro

2018-02-16

For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p relation to gene-environment interactions in the prevention of CRC.

Interaction between dietary lipids and gut microbiota regulates hepatic cholesterol metabolism

DEFF Research Database (Denmark)

Caesar, Robert; Nygren, Heli; Orešič, Matej

2016-01-01

The gut microbiota influences many aspects of host metabolism. We have previously shown that the presence of a gut microbiota remodels lipid composition. Here we investigated how interaction between gut microbiota and dietary lipids regulates lipid composition in the liver and plasma, and gene...... of most lipid classes differed between mice fed lard and fish oil. However, the gut microbiota also affected lipid composition. The gut microbiota increased hepatic levels of cholesterol and cholesteryl esters in mice fed lard, but not in mice fed fish oil. Serum levels of cholesterol and cholesteryl...... esters were not affected by the gut microbiota. Genes encoding enzymes involved in cholesterol biosynthesis were downregulated by the gut microbiota in mice fed lard and were expressed at a low level in mice fed fish oil independent of microbial status. In summary, we show that gut microbiota...

Dynamic gene expression for metabolic engineering of mammalian cells in culture.

Science.gov (United States)

Le, Huong; Vishwanathan, Nandita; Kantardjieff, Anne; Doo, Inseok; Srienc, Michael; Zheng, Xiaolu; Somia, Nikunj; Hu, Wei-Shou

2013-11-01

Recombinant mammalian cells are the major hosts for the production of protein therapeutics. In addition to high expression of the product gene, a hyper-producer must also harbor superior phenotypic traits related to metabolism, protein secretion, and growth control. Introduction of genes endowing the relevant hyper-productivity traits is a strategy frequently used to enhance the productivity. Most of such cell engineering efforts have been performed using constitutive expression systems. However, cells respond to various environmental cues and cellular events dynamically according to cellular needs. The use of inducible systems allows for time dependent expression, but requires external manipulation. Ideally, a transgene's expression should be synchronous to the host cell's own rhythm, and at levels appropriate for the objective. To that end, we identified genes with different expression dynamics and intensity ranges using pooled transcriptome data. Their promoters may be used to drive the expression of the transgenes following the desired dynamics. We isolated the promoter of the Thioredoxin-interacting protein (Txnip) gene and demonstrated its capability to drive transgene expression in concert with cell growth. We further employed this Chinese hamster promoter to engineer dynamic expression of the mouse GLUT5 fructose transporter in Chinese hamster ovary (CHO) cells, enabling them to utilize sugar according to cellular needs rather than in excess as typically seen in culture. Thus, less lactate was produced, resulting in a better growth rate, prolonged culture duration, and higher product titer. This approach illustrates a novel concept in metabolic engineering which can potentially be used to achieve dynamic control of cellular behaviors for enhanced process characteristics. © 2013 Published by Elsevier Inc.

Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus

Science.gov (United States)

Monier, Adam; Pagarete, António; de Vargas, Colomban; Allen, Michael J.; Read, Betsy; Claverie, Jean-Michel; Ogata, Hiroyuki

2009-01-01

Interactions between viruses and phytoplankton, the main primary producers in the oceans, affect global biogeochemical cycles and climate. Recent studies are increasingly revealing possible cases of gene transfers between cyanobacteria and phages, which might have played significant roles in the evolution of cyanobacteria/phage systems. However, little has been documented about the occurrence of horizontal gene transfer in eukaryotic phytoplankton/virus systems. Here we report phylogenetic evidence for the transfer of seven genes involved in the sphingolipid biosynthesis pathway between the cosmopolitan eukaryotic microalga Emiliania huxleyi and its large DNA virus EhV. PCR assays indicate that these genes are prevalent in E. huxleyi and EhV strains isolated from different geographic locations. Patterns of protein and gene sequence conservation support that these genes are functional in both E. huxleyi and EhV. This is the first clear case of horizontal gene transfer of multiple functionally linked enzymes in a eukaryotic phytoplankton–virus system. We examine arguments for the possible direction of the gene transfer. The virus-to-host direction suggests the existence of ancient viruses that controlled the complex metabolic pathway in order to infect primitive eukaryotic cells. In contrast, the host-to-virus direction suggests that the serial acquisition of genes involved in the same metabolic pathway might have been a strategy for the ancestor of EhVs to stay ahead of their closest relatives in the great evolutionary race for survival. PMID:19451591

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

Science.gov (United States)

Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

2013-03-28

Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparative gene expression of intestinal metabolizing enzymes.

Science.gov (United States)

Shin, Ho-Chul; Kim, Hye-Ryoung; Cho, Hee-Jung; Yi, Hee; Cho, Soo-Min; Lee, Dong-Goo; Abd El-Aty, A M; Kim, Jin-Suk; Sun, Duxin; Amidon, Gordon L

2009-11-01

The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant gene expressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal gene expression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs.

Environmental confounding in gene-environment interaction studies.

Science.gov (United States)

Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar

2013-07-01

We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.

Community Structure Analysis of Gene Interaction Networks in Duchenne Muscular Dystrophy.

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Tejaswini Narayanan

Full Text Available Duchenne Muscular Dystrophy (DMD is an important pathology associated with the human skeletal muscle and has been studied extensively. Gene expression measurements on skeletal muscle of patients afflicted with DMD provides the opportunity to understand the underlying mechanisms that lead to the pathology. Community structure analysis is a useful computational technique for understanding and modeling genetic interaction networks. In this paper, we leverage this technique in combination with gene expression measurements from normal and DMD patient skeletal muscle tissue to study the structure of genetic interactions in the context of DMD. We define a novel framework for transforming a raw dataset of gene expression measurements into an interaction network, and subsequently apply algorithms for community structure analysis for the extraction of topological communities. The emergent communities are analyzed from a biological standpoint in terms of their constituent biological pathways, and an interpretation that draws correlations between functional and structural organization of the genetic interactions is presented. We also compare these communities and associated functions in pathology against those in normal human skeletal muscle. In particular, differential enhancements are observed in the following pathways between pathological and normal cases: Metabolic, Focal adhesion, Regulation of actin cytoskeleton and Cell adhesion, and implication of these mechanisms are supported by prior work. Furthermore, our study also includes a gene-level analysis to identify genes that are involved in the coupling between the pathways of interest. We believe that our results serve to highlight important distinguishing features in the structural/functional organization of constituent biological pathways, as it relates to normal and DMD cases, and provide the mechanistic basis for further biological investigations into specific pathways differently regulated

Dendrobium nobile Lindl. alkaloids regulate metabolism gene expression in livers of mice.

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Xu, Yun-Yan; Xu, Ya-Sha; Wang, Yuan; Wu, Qin; Lu, Yuan-Fu; Liu, Jie; Shi, Jing-Shan

2017-10-01

In our previous studies, Dendrobium nobile Lindl. alkaloids (DNLA) has been shown to have glucose-lowering and antihyperlipidaemia effects in diabetic rats, in rats fed with high-fat diets, and in mice challenged with adrenaline. This study aimed to examine the effects of DNLA on the expression of glucose and lipid metabolism genes in livers of mice. Mice were given DNLA at doses of 10-80 mg/kg, po for 8 days, and livers were removed for total RNA and protein isolation to perform real-time RT-PCR and Western blot analysis. Dendrobium nobile Lindl. alkaloids increased PGC1α at mRNA and protein levels and increased glucose metabolism gene Glut2 and FoxO1 expression. DNLA also increased the expression of fatty acid β-oxidation genes Acox1 and Cpt1a. The lipid synthesis regulator Srebp1 (sterol regulatory element-binding protein-1) was decreased, while the lipolysis gene ATGL was increased. Interestingly, DNLA increased the expression of antioxidant gene metallothionein-1 and NADPH quinone oxidoreductase-1 (Nqo1) in livers of mice. Western blot on selected proteins confirmed these changes including the increased expression of GLUT4 and PPARα. DNLA has beneficial effects on liver glucose and lipid metabolism gene expressions, and enhances the Nrf2-antioxidant pathway gene expressions, which could play integrated roles in regulating metabolic disorders. © 2017 Royal Pharmaceutical Society.

Growth hormone regulation of metabolic gene expression in muscle: a microarray study in hypopituitary men.

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Sjögren, Klara; Leung, Kin-Chuen; Kaplan, Warren; Gardiner-Garden, Margaret; Gibney, James; Ho, Ken K Y

2007-07-01

Muscle is a target of growth hormone (GH) action and a major contributor to whole body metabolism. Little is known about how GH regulates metabolic processes in muscle or the extent to which muscle contributes to changes in whole body substrate metabolism during GH treatment. To identify GH-responsive genes that regulate substrate metabolism in muscle, we studied six hypopituitary men who underwent whole body metabolic measurement and skeletal muscle biopsies before and after 2 wk of GH treatment (0.5 mg/day). Transcript profiles of four subjects were analyzed using Affymetrix GeneChips. Serum insulin-like growth factor I (IGF-I) and procollagens I and III were measured by RIA. GH increased serum IGF-I and procollagens I and III, enhanced whole body lipid oxidation, reduced carbohydrate oxidation, and stimulated protein synthesis. It induced gene expression of IGF-I and collagens in muscle. GH reduced expression of several enzymes regulating lipid oxidation and energy production. It reduced calpain 3, increased ribosomal protein L38 expression, and displayed mixed effects on genes encoding myofibrillar proteins. It increased expression of circadian gene CLOCK, and reduced that of PERIOD. In summary, GH exerted concordant effects on muscle expression and blood levels of IGF-I and collagens. It induced changes in genes regulating protein metabolism in parallel with a whole body anabolic effect. The discordance between muscle gene expression profiles and metabolic responses suggests that muscle is unlikely to contribute to GH-induced stimulation of whole body energy and lipid metabolism. GH may regulate circadian function in skeletal muscle by modulating circadian gene expression with possible metabolic consequences.

Metabolic regulation in meagre, Argyrosomus regius (Asso, 1801: Study of gene-diet interactions on lipid metabolism

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Francisca Silva-Brito

2014-06-01

stimulates the expression of the fads2. In contrast, Elovl5 is very efficient to convert the desaturated products of ∆6/∆8 and so Elovl5 expression is not enhanced, since the activity of this enzyme is already higher. These findings may explain the differences in the expression of two genes, between hepatic fads2 and elovl5. Furthermore, increased hepatic fads2 expression between FO-S and VO-S treatments was 114 fold. Such induction was much greater than observed in Salmo salad (Zheng et al., 2005. However, Salmo salad has separate and distinct genes for ∆6 and ∆5 desaturases (Zheng et al., 2005 and, due to genome duplication, it has two genes with ∆6 activity (Monroig et al., 2010. Moreover, lipid peroxidation in liver increases with the number of fatty acid (FA double bonds (Haggag, Elsanhoty & Ramadan, 2014. D'Aquino et al. (1991 observed that rats fed diets with fish oil had increased lipid peroxidation. Our results indicate that, in FO-S, selenium may have protected FA from peroxidation, thus dietary HUFA seemed to have been sufficient to maintain the phospholipid turnover and induction of FA metabolism genes did not occur. In FO-NS diet membranes were not protected efficiently from lipid peroxidation, and therefore a higher expression of FA metabolism genes was necessary to offset the damage, consequently, biosynthesis of HUFA was more stimulated. ROS-induced oxidative stress has been associated with expression and protein levels of transcription factors (Okuno et al., 2012. A reduction of ROS (Reactive Oxygen Species has been observed in fish fed VO with selenium, when compared to VO without selenium (data not presented. It is plausible to infer that a stimulation of expression and level of protein SREBP-1 by a reduction of ROS. SREBP-1 play a role on the regulation of genes involved in biosynthesis of HUFA, as fads2 and elovl5 (Jump, Tripathy & Depner, 2013. In conclusion, our results showed that vegetable oils have an effect on expression level of genes

Lactococcus lactis Metabolism and Gene Expression during Growth on Plant Tissues

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Golomb, Benjamin L.

2014-01-01

Lactic acid bacteria have been isolated from living, harvested, and fermented plant materials; however, the adaptations these bacteria possess for growth on plant tissues are largely unknown. In this study, we investigated plant habitat-specific traits of Lactococcus lactis during growth in an Arabidopsis thaliana leaf tissue lysate (ATL). L. lactis KF147, a strain originally isolated from plants, exhibited a higher growth rate and reached 7.9-fold-greater cell densities during growth in ATL than the dairy-associated strain L. lactis IL1403. Transcriptome profiling (RNA-seq) of KF147 identified 853 induced and 264 repressed genes during growth in ATL compared to that in GM17 laboratory culture medium. Genes induced in ATL included those involved in the arginine deiminase pathway and a total of 140 carbohydrate transport and metabolism genes, many of which are involved in xylose, arabinose, cellobiose, and hemicellulose metabolism. The induction of those genes corresponded with L. lactis KF147 nutrient consumption and production of metabolic end products in ATL as measured by gas chromatography-time of flight mass spectrometry (GC-TOF/MS) untargeted metabolomic profiling. To assess the importance of specific plant-inducible genes for L. lactis growth in ATL, xylose metabolism was targeted for gene knockout mutagenesis. Wild-type L. lactis strain KF147 but not an xylA deletion mutant was able to grow using xylose as the sole carbon source. However, both strains grew to similarly high levels in ATL, indicating redundancy in L. lactis carbohydrate metabolism on plant tissues. These findings show that certain strains of L. lactis are well adapted for growth on plants and possess specific traits relevant for plant-based food, fuel, and feed fermentations. PMID:25384484

More to NAD+ than meets the eye: A regulator of metabolic pools and gene expression in Arabidopsis.

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Gakière, Bertrand; Fernie, Alisdair R; Pétriacq, Pierre

2018-01-05

Since its discovery more than a century ago, nicotinamide adenine dinucleotide (NAD + ) is recognised as a fascinating cornerstone of cellular metabolism. This ubiquitous energy cofactor plays vital roles in metabolic pathways and regulatory processes, a fact emphasised by the essentiality of a balanced NAD + metabolism for normal plant growth and development. Research on the role of NAD in plants has been predominantly carried out in the model plant Arabidopsis thaliana (Arabidopsis) with emphasis on the redox properties and cellular signalling functions of the metabolite. This review examines the current state of knowledge concerning how NAD can regulate both metabolic pools and gene expression in Arabidopsis. Particular focus is placed on recent studies highlighting the complexity of metabolic regulations involving NAD, more particularly in the mitochondrial compartment, and of signalling roles with respect to interactions with environmental fluctuations most specifically those involving plant immunity. Copyright © 2018 Elsevier Inc. All rights reserved.

Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

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Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

2014-06-01

Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

Pleiotropic genes for metabolic syndrome and inflammation

DEFF Research Database (Denmark)

Kraja, Aldi T; Chasman, Daniel I; North, Kari E

2014-01-01

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factor...

Increased fat oxidation and regulation of metabolic genes with ultraendurance exercise

DEFF Research Database (Denmark)

Helge, Jørn Wulff; Rehrer, N J; Pilegaard, H

2007-01-01

AIM: Regular endurance exercise stimulates muscle metabolic capacity, but effects of very prolonged endurance exercise are largely unknown. This study examined muscle substrate availability and utilization during prolonged endurance exercise, and associated metabolic genes. METHODS: Data were...... exercise markedly increases plasma fatty acid availability and fat utilization during exercise. Exercise-induced regulation of genes encoding proteins involved in fatty acid recruitment and oxidation may contribute to these changes....

Glucokinase regulatory protein genetic variant interacts with omega-3 PUFA to influence insulin resistance and inflammation in metabolic syndrome.

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Pablo Perez-Martinez

Full Text Available Glucokinase Regulatory Protein (GCKR plays a central role regulating both hepatic triglyceride and glucose metabolism. Fatty acids are key metabolic regulators, which interact with genetic factors and influence glucose metabolism and other metabolic traits. Omega-3 polyunsaturated fatty acids (n-3 PUFA have been of considerable interest, due to their potential to reduce metabolic syndrome (MetS risk.To examine whether genetic variability at the GCKR gene locus was associated with the degree of insulin resistance, plasma concentrations of C-reactive protein (CRP and n-3 PUFA in MetS subjects.Homeostasis model assessment of insulin resistance (HOMA-IR, HOMA-B, plasma concentrations of C-peptide, CRP, fatty acid composition and the GCKR rs1260326-P446L polymorphism, were determined in a cross-sectional analysis of 379 subjects with MetS participating in the LIPGENE dietary cohort.Among subjects with n-3 PUFA levels below the population median, carriers of the common C/C genotype had higher plasma concentrations of fasting insulin (P = 0.019, C-peptide (P = 0.004, HOMA-IR (P = 0.008 and CRP (P = 0.032 as compared with subjects carrying the minor T-allele (Leu446. In contrast, homozygous C/C carriers with n-3 PUFA levels above the median showed lower plasma concentrations of fasting insulin, peptide C, HOMA-IR and CRP, as compared with individuals with the T-allele.We have demonstrated a significant interaction between the GCKR rs1260326-P446L polymorphism and plasma n-3 PUFA levels modulating insulin resistance and inflammatory markers in MetS subjects. Further studies are needed to confirm this gene-diet interaction in the general population and whether targeted dietary recommendations can prevent MetS in genetically susceptible individuals.ClinicalTrials.gov NCT00429195.

Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

National Research Council Canada - National Science Library

Adegoke, Olufemi

2003-01-01

The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...

Nur77 coordinately regulates expression of genes linked to glucose metabolism in skeletal muscle.

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Chao, Lily C; Zhang, Zidong; Pei, Liming; Saito, Tsugumichi; Tontonoz, Peter; Pilch, Paul F

2007-09-01

Innervation is important for normal metabolism in skeletal muscle, including insulin-sensitive glucose uptake. However, the transcription factors that transduce signals from the neuromuscular junction to the nucleus and affect changes in metabolic gene expression are not well defined. We demonstrate here that the orphan nuclear receptor Nur77 is a regulator of gene expression linked to glucose utilization in muscle. In vivo, Nur77 is preferentially expressed in glycolytic compared with oxidative muscle and is responsive to beta-adrenergic stimulation. Denervation of rat muscle compromises expression of Nur77 in parallel with that of numerous genes linked to glucose metabolism, including glucose transporter 4 and genes involved in glycolysis, glycogenolysis, and the glycerophosphate shuttle. Ectopic expression of Nur77, either in rat muscle or in C2C12 muscle cells, induces expression of a highly overlapping set of genes, including glucose transporter 4, muscle phosphofructokinase, and glycogen phosphorylase. Furthermore, selective knockdown of Nur77 in rat muscle by small hairpin RNA or genetic deletion of Nur77 in mice reduces the expression of a battery of genes involved in skeletal muscle glucose utilization in vivo. Finally, we show that Nur77 binds the promoter regions of multiple genes involved in glucose metabolism in muscle. These results identify Nur77 as a potential mediator of neuromuscular signaling in the control of metabolic gene expression.

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

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Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

2016-01-01

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer.

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Angeline S Andrew

Full Text Available Bladder cancer is the 4(th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case-control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene-gene interactions using Multifactor Dimensionality Reduction (MDR and Statistical Epistasis Network analysis. The 3'UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31-2.62. This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06-12.63. The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40-3.25 than females (OR 1.56 95%CI 0.83-2.95, (SNP-gender interaction P = 0.048. We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003. The fact that bladder cancer incidence is 3-4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.

Therapeutic potential of Mediator complex subunits in metabolic diseases.

Science.gov (United States)

Ranjan, Amol; Ansari, Suraiya A

2018-01-01

The multisubunit Mediator is an evolutionary conserved transcriptional coregulatory complex in eukaryotes. It is needed for the transcriptional regulation of gene expression in general as well as in a gene specific manner. Mediator complex subunits interact with different transcription factors as well as components of RNA Pol II transcription initiation complex and in doing so act as a bridge between gene specific transcription factors and general Pol II transcription machinery. Specific interaction of various Mediator subunits with nuclear receptors (NRs) and other transcription factors involved in metabolism has been reported in different studies. Evidences indicate that ligand-activated NRs recruit Mediator complex for RNA Pol II-dependent gene transcription. These NRs have been explored as therapeutic targets in different metabolic diseases; however, they show side-effects as targets due to their overlapping involvement in different signaling pathways. Here we discuss the interaction of various Mediator subunits with transcription factors involved in metabolism and whether specific interaction of these transcription factors with Mediator subunits could be potentially utilized as therapeutic strategy in a variety of metabolic diseases. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Lack of evidence for intermolecular epistatic interactions between adiponectin and resistin gene polymorphisms in Malaysian male subjects

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Cia-Hin Lau

2012-01-01

Full Text Available Epistasis (gene-gene interaction is a ubiquitous component of the genetic architecture of complex traits such as susceptibility to common human diseases. Given the strong negative correlation between circulating adiponectin and resistin levels, the potential intermolecular epistatic interactions between ADIPOQ (SNP+45T > G, SNP+276G > T, SNP+639T > C and SNP+1212A > G and RETN (SNP-420C > G and SNP+299G > A gene polymorphisms in the genetic risk underlying type 2 diabetes (T2DM and metabolic syndrome (MS were assessed. The potential mutual influence of the ADIPOQ and RETN genes on their adipokine levels was also examined. The rare homozygous genotype (risk alleles of SNP-420C > G at the RETN locus tended to be co-inherited together with the common homozygous genotypes (protective alleles of SNP+639T > C and SNP+1212A > G at the ADIPOQ locus. Despite the close structural relationship between the ADIPOQ and RETN genes, there was no evidence of an intermolecular epistatic interaction between these genes. There was also no reciprocal effect of the ADIPOQ and RETN genes on their adipokine levels, i.e., ADIPOQ did not affect resistin levels nor did RETN affect adiponectin levels. The possible influence of the ADIPOQ gene on RETN expression warrants further investigation.

Conserved and divergent rhythms of crassulacean acid metabolism-related and core clock gene expression in the cactus Opuntia ficus-indica.

Science.gov (United States)

Mallona, Izaskun; Egea-Cortines, Marcos; Weiss, Julia

2011-08-01

The cactus Opuntia ficus-indica is a constitutive Crassulacean acid metabolism (CAM) species. Current knowledge of CAM metabolism suggests that the enzyme phosphoenolpyruvate carboxylase kinase (PPCK) is circadian regulated at the transcriptional level, whereas phosphoenolpyruvate carboxylase (PEPC), malate dehydrogenase (MDH), NADP-malic enzyme (NADP-ME), and pyruvate phosphate dikinase (PPDK) are posttranslationally controlled. As little transcriptomic data are available from obligate CAM plants, we created an expressed sequence tag database derived from different organs and developmental stages. Sequences were assembled, compared with sequences in the National Center for Biotechnology Information nonredundant database for identification of putative orthologs, and mapped using Kyoto Encyclopedia of Genes and Genomes Orthology and Gene Ontology. We identified genes involved in circadian regulation and CAM metabolism for transcriptomic analysis in plants grown in long days. We identified stable reference genes for quantitative polymerase chain reaction and found that OfiSAND, like its counterpart in Arabidopsis (Arabidopsis thaliana), and OfiTUB are generally appropriate standards for use in the quantification of gene expression in O. ficus-indica. Three kinds of expression profiles were found: transcripts of OfiPPCK oscillated with a 24-h periodicity; transcripts of the light-active OfiNADP-ME and OfiPPDK genes adapted to 12-h cycles, while transcript accumulation patterns of OfiPEPC and OfiMDH were arrhythmic. Expression of the circadian clock gene OfiTOC1, similar to Arabidopsis, oscillated with a 24-h periodicity, peaking at night. Expression of OfiCCA1 and OfiPRR9, unlike in Arabidopsis, adapted best to a 12-h rhythm, suggesting that circadian clock gene interactions differ from those of Arabidopsis. Our results indicate that the evolution of CAM metabolism could be the result of modified circadian regulation at both the transcriptional and posttranscriptional

Dataset of the human homologues and orthologues of lipid-metabolic genes identified as DAF-16 targets their roles in lipid and energy metabolism.

Science.gov (United States)

Fan, Lavender Yuen-Nam; Saavedra-García, Paula; Lam, Eric Wing-Fai

2017-04-01

The data presented in this article are related to the review article entitled 'Unravelling the role of fatty acid metabolism in cancer through the FOXO3-FOXM1 axis' (Saavedra-Garcia et al., 2017) [24]. Here, we have matched the DAF-16/FOXO3 downstream genes with their respective human orthologues and reviewed the roles of these targeted genes in FA metabolism. The list of genes listed in this article are precisely selected from literature reviews based on their functions in mammalian FA metabolism. The nematode Caenorhabditis elegans gene orthologues of the genes are obtained from WormBase, the online biological database of C. elegans. This dataset has not been uploaded to a public repository yet.

Metabolic gene polymorphism frequencies in control populations

DEFF Research Database (Denmark)

Garte, Seymour; Gaspari, Laura; Alexandrie, Anna-Karin

2001-01-01

Using the International Project on Genetic Susceptibility to Environmental Carcinogens (GSEC) database containing information on over 15,000 control (noncancer) subjects, the allele and genotype frequencies for many of the more commonly studied metabolic genes (CYP1A1, CYP2E1, CYP2D6, GSTM1, GSTT1...

Predictability of Genetic Interactions from Functional Gene Modules

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Jonathan H. Young

2017-02-01

Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

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Richard A Notebaart

2008-01-01

Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.

The WWOX Gene Modulates HDL and Lipid Metabolism

Science.gov (United States)

Iatan, Iulia; Choi, Hong Y.; Ruel, Isabelle; Linga Reddy, M.V. Prasad; Kil, Hyunsuk; Lee, Jaeho; Abu Odeh, Mohammad; Salah, Zaidoun; Abu-Remaileh, Muhannad; Weissglas-Volkov, Daphna; Nikkola, Elina; Civelek, Mete; Awan, Zuhier; Croce, Carlo M.; Aqeilan, Rami I.; Pajukanta, Päivi; Aldaz, C. Marcelo; Genest, Jacques

2014-01-01

Background Low high-density lipoprotein-cholesterol (HDL-C) constitutes a major risk factor for atherosclerosis. Recent studies from our group reported a genetic association between the WW domain-containing oxidoreductase (WWOX) gene and HDL-C levels. Here, through next-generation resequencing, in vivo functional studies and gene microarray analyses, we investigated the role of WWOX in HDL and lipid metabolism. Methods and Results Using next-generation resequencing of the WWOX region, we first identified 8 variants significantly associated and perfectly segregating with the low-HDL trait in two multi-generational French Canadian dyslipidemic families. To understand in vivo functions of WWOX, we used liver-specific Wwoxhep−/− and total Wwox−/− mice models, where we found decreased ApoA-I and ABCA1 levels in hepatic tissues. Analyses of lipoprotein profiles in Wwox−/−, but not Wwox hep−/− littermates, also showed marked reductions in serum HDL-C concentrations, concordant with the low-HDL findings observed in families. We next obtained evidence of a gender-specific effect in female Wwoxhep−/− mice, where an increase in plasma triglycerides and altered lipid metabolic pathways by microarray analyses were observed. We further identified a significant reduction in ApoA-I and LPL, and upregulation in Fas, Angptl4 and Lipg, suggesting that the effects of Wwox involve multiple pathways, including cholesterol homeostasis, ApoA-I/ABCA1 pathway, and fatty acid biosynthesis/triglyceride metabolism. Conclusions Our data indicate that WWOX disruption alters HDL and lipoprotein metabolism through several mechanisms and may account for the low-HDL phenotype observed in families expressing the WWOX variants. These findings thus describe a novel gene involved in cellular lipid homeostasis, which effects may impact atherosclerotic disease development. PMID:24871327

Altered Clock and Lipid Metabolism-Related Genes in Atherosclerotic Mice Kept with Abnormal Lighting Condition

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Zhu Zhu

2016-01-01

Full Text Available Background. The risk of atherosclerosis is elevated in abnormal lipid metabolism and circadian rhythm disorder. We investigated whether abnormal lighting condition would have influenced the circadian expression of clock genes and clock-controlled lipid metabolism-related genes in ApoE-KO mice. Methods. A mouse model of atherosclerosis with circadian clock genes expression disorder was established using ApoE-KO mice (ApoE-KO LD/DL mice by altering exposure to light. C57 BL/6J mice (C57 mice and ApoE-KO mice (ApoE-KO mice exposed to normal day and night and normal diet served as control mice. According to zeitgeber time samples were acquired, to test atheromatous plaque formation, serum lipids levels and rhythmicity, clock genes, and lipid metabolism-related genes along with Sirtuin 1 (Sirt1 levels and rhythmicity. Results. Atherosclerosis plaques were formed in the aortic arch of ApoE-KO LD/DL mice. The serum lipids levels and oscillations in ApoE-KO LD/DL mice were altered, along with the levels and diurnal oscillations of circadian genes, lipid metabolism-associated genes, and Sirt1 compared with the control mice. Conclusions. Abnormal exposure to light aggravated plaque formation and exacerbated disorders of serum lipids and clock genes, lipid metabolism genes and Sirt1 levels, and circadian oscillation.

β-Carotene-9′,10′-Oxygenase Status Modulates the Impact of Dietary Tomato and Lycopene on Hepatic Nuclear Receptor–, Stress-, and Metabolism-Related Gene Expression in Mice123

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Tan, Hsueh-Li; Moran, Nancy E.; Cichon, Morgan J.; Riedl, Ken M.; Schwartz, Steven J.; Erdman, John W.; Pearl, Dennis K.; Thomas-Ahner, Jennifer M.; Clinton, Steven K.

2014-01-01

Tomato and lycopene (ψ, ψ-carotene) consumption is hypothesized to protect against nonalcoholic steatohepatitis and hepatocarcinogenesis, processes that may depend upon diet and gene interactions. To investigate the interaction of tomato or lycopene feeding with β-carotene-9′,10′-monooxygenase (Bco2) on hepatic metabolic and signaling pathways, male wild-type (WT) and Bco2−/− mice (3-wk-old; n = 36) were fed semi-purified control, 10% tomato powder–containing, or 0.25% lycopene beadlet–containing diets for 3 wk. Serum lycopene concentrations were higher in lycopene- and tomato-fed Bco2−/− mice compared with WT (P = 0.03). Tomato- and lycopene-fed mice had detectable hepatic apolipoprotein (apo)-6′-, apo-8′-, and apo-12′-lycopenal concentrations. Hepatic expression of β-carotene-15,15’-monooxygenase was increased in Bco2−/− mice compared with WT (P = 0.02), but not affected by diet. Evaluation of hepatic gene expression by focused quantitative reverse transcriptase-polymerase chain reaction arrays for nuclear receptors and coregulators (84 genes) and stress and metabolism (82 genes) genes indicates that tomato feeding affected 31 genes (≥1.5-fold, P lycopene feeding affected 19 genes, 16 of which were affected by both diets. Lycopene down-regulation of 7 nuclear receptors and coregulators, estrogen-related receptor-α, histone deacetylase 3, nuclear receptor coactivator 4, RevErbA-β, glucocorticoid receptor, peroxisome proliferator-activated receptor (PPAR)-α, and PPAR-γ, coactivator 1 β was dependent upon interaction with Bco2 status. Lycopene and tomato feeding induced gene expression patterns consistent with decreased lipid uptake, decreased cell proliferation and mitosis, down-regulated aryl hydrocarbon receptor signaling, and decreased expression of genes involved in retinoid X receptor heterodimer activation. Tomato feeding also caused expression changes consistent with down-regulation of DNA synthesis and terpenoid

Phylogenomic analysis of secondary metabolism genes sheds light on their evolution in Aspergilli

DEFF Research Database (Denmark)

Theobald, Sebastian; Vesth, Tammi Camilla; Rasmussen, Jane Lind Nybo

.Natural products are encoded by genes located in close proximity, called secondary metabolic gene clusters, which makes them interesting targets for genomic analysis. We use a modified version of the Secondary Metabolite Unique Regions Finder (SMURF) algorithm, combined with InterPro annotations to create...... approximate maximum likelihood trees of conserved domains from secondary metabolic genes across 56 species, giving insights into the secondary metabolism gene diversity and evolution.In this study we can describe the evolution of non ribosomal peptide synthetases (NRPS), polyketide synthases (PKS) and hybrids.......In the aspMine project, we are sequencing and analyzing over 300 species of Aspergilli, agroup of filamentous fungi rich in natural compounds. The vast amount of data obtained from these species challenges the way we were mining for products and requires new pipelines for secondary metabolite analysis...

The role of gene-gene interaction in the prediction of criminal behavior.

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Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle

2014-04-01

A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.

GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes.

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Solovieva, Elena; Shikanai, Toshihide; Fujita, Noriaki; Narimatsu, Hisashi

2018-04-18

Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the

Identifying genes and gene networks involved in chromium metabolism and detoxification in Crambe abyssinica

International Nuclear Information System (INIS)

Zulfiqar, Asma; Paulose, Bibin; Chhikara, Sudesh; Dhankher, Om Parkash

2011-01-01

Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: → Molecular mechanism of Cr uptake and detoxification in plants is not well known. → We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. → 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. → Pathways linked to stress, ion transport, and sulfur assimilation were affected. → This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.

Identifying genes and gene networks involved in chromium metabolism and detoxification in Crambe abyssinica

Energy Technology Data Exchange (ETDEWEB)

Zulfiqar, Asma, E-mail: asmazulfiqar08@yahoo.com [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Paulose, Bibin, E-mail: bpaulose@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Chhikara, Sudesh, E-mail: sudesh@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Dhankher, Om Parkash, E-mail: parkash@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States)

2011-10-15

Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: > Molecular mechanism of Cr uptake and detoxification in plants is not well known. > We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. > 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. > Pathways linked to stress, ion transport, and sulfur assimilation were affected. > This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.

Dataset of the human homologues and orthologues of lipid-metabolic genes identified as DAF-16 targets their roles in lipid and energy metabolism

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Lavender Yuen-Nam Fan

2017-04-01

Full Text Available The data presented in this article are related to the review article entitled ‘Unravelling the role of fatty acid metabolism in cancer through the FOXO3-FOXM1 axis’ (Saavedra-Garcia et al., 2017 [24]. Here, we have matched the DAF-16/FOXO3 downstream genes with their respective human orthologues and reviewed the roles of these targeted genes in FA metabolism. The list of genes listed in this article are precisely selected from literature reviews based on their functions in mammalian FA metabolism. The nematode Caenorhabditis elegans gene orthologues of the genes are obtained from WormBase, the online biological database of C. elegans. This dataset has not been uploaded to a public repository yet.

No association between type 1 diabetes and genetic variation in vitamin D metabolism genes

DEFF Research Database (Denmark)

Thorsen, Steffen U; Mortensen, Henrik B; Carstensen, Bendix

2014-01-01

BACKGROUND: Vitamin D, certain single nucleotide polymorphisms (SNPs) in the vitamin D-receptor (VDR) gene and vitamin D metabolism genes have been associated with type 1 diabetes (T1D). OBJECTIVE: We wanted to examine if the most widely studied SNPs in genes important for production, transport......, and action of vitamin D were associated with T1D or to circulating levels of vitamin D 25-hydroxyvitamin D [25(OH)D] in a juvenile Danish population. METHODS: We genotyped eight SNPs in five vitamin D metabolism genes in 1467 trios. 25(OH)D status were analyzed in 1803 children (907 patients and 896 siblings......). RESULTS: We did not demonstrate association with T1D for SNPs in the following genes: CYP27B1, VDR, GC, CYP2R1, DHCR7, and CYP24A1. Though, variants in the GC gene were significantly associated with 25(OH)D levels in the joint model. CONCLUSION: Some of the most examined SNPs in vitamin D metabolism genes...

Drug Metabolizing Enzyme and Transporter Gene Variation, Nicotine Metabolism, Prospective Abstinence, and Cigarette Consumption.

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Andrew W Bergen

Full Text Available The Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine, has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3. Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

Oxidative Metabolism Genes Are Not Responsive to Oxidative Stress in Rodent Beta Cell Lines

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Faer Morrison

2012-01-01

Full Text Available Altered expression of oxidative metabolism genes has been described in the skeletal muscle of individuals with type 2 diabetes. Pancreatic beta cells contain low levels of antioxidant enzymes and are particularly susceptible to oxidative stress. In this study, we explored the effect of hyperglycemia-induced oxidative stress on a panel of oxidative metabolism genes in a rodent beta cell line. We exposed INS-1 rodent beta cells to low (5.6 mmol/L, ambient (11 mmol/L, and high (28 mmol/L glucose conditions for 48 hours. Increases in oxidative stress were measured using the fluorescent probe dihydrorhodamine 123. We then measured the expression levels of a panel of 90 oxidative metabolism genes by real-time PCR. Elevated reactive oxygen species (ROS production was evident in INS-1 cells after 48 hours (P<0.05. TLDA analysis revealed a significant (P<0.05 upregulation of 16 of the 90 genes under hyperglycemic conditions, although these expression differences did not reflect differences in ROS. We conclude that although altered glycemia may influence the expression of some oxidative metabolism genes, this effect is probably not mediated by increased ROS production. The alterations to the expression of oxidative metabolism genes previously observed in human diabetic skeletal muscle do not appear to be mirrored in rodent pancreatic beta cells.

Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

DEFF Research Database (Denmark)

Dashti, Hassan S; Follis, Jack L; Smith, Caren E

2015-01-01

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs13871...

Gene-environment interactions of circadian-related genes for cardiometabolic traits

Science.gov (United States)

Objective: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153,...

Ontogeny of hepatic energy metabolism genes in mice as revealed by RNA-sequencing.

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Helen J Renaud

Full Text Available The liver plays a central role in metabolic homeostasis by coordinating synthesis, storage, breakdown, and redistribution of nutrients. Hepatic energy metabolism is dynamically regulated throughout different life stages due to different demands for energy during growth and development. However, changes in gene expression patterns throughout ontogeny for factors important in hepatic energy metabolism are not well understood. We performed detailed transcript analysis of energy metabolism genes during various stages of liver development in mice. Livers from male C57BL/6J mice were collected at twelve ages, including perinatal and postnatal time points (n = 3/age. The mRNA was quantified by RNA-Sequencing, with transcript abundance estimated by Cufflinks. One thousand sixty energy metabolism genes were examined; 794 were above detection, of which 627 were significantly changed during at least one developmental age compared to adult liver. Two-way hierarchical clustering revealed three major clusters dependent on age: GD17.5-Day 5 (perinatal-enriched, Day 10-Day 20 (pre-weaning-enriched, and Day 25-Day 60 (adolescence/adulthood-enriched. Clustering analysis of cumulative mRNA expression values for individual pathways of energy metabolism revealed three patterns of enrichment: glycolysis, ketogenesis, and glycogenesis were all perinatally-enriched; glycogenolysis was the only pathway enriched during pre-weaning ages; whereas lipid droplet metabolism, cholesterol and bile acid metabolism, gluconeogenesis, and lipid metabolism were all enriched in adolescence/adulthood. This study reveals novel findings such as the divergent expression of the fatty acid β-oxidation enzymes Acyl-CoA oxidase 1 and Carnitine palmitoyltransferase 1a, indicating a switch from mitochondrial to peroxisomal β-oxidation after weaning; as well as the dynamic ontogeny of genes implicated in obesity such as Stearoyl-CoA desaturase 1 and Elongation of very long chain fatty

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

Science.gov (United States)

Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

[Drug-Drug Interactions with Consideration of Pharmacogenetics].

Science.gov (United States)

Ozawa, Shogo

2018-01-01

　Elderly patients often suffer from a variety of diseases and therefore may be prescribed several kinds of drugs. Interactions between these drugs may cause problems in some patients. Guidelines for drug interactions were released on July 8, 2014 "Drug Interaction Guideline for Drug Development and Labeling Recommendations (Final Draft)". These guidelines include the theoretical basis for evaluating the mechanisms of drug interaction, the possible extent of drug interactions, and take into consideration special populations (e.g., infants, children, elderly patients, patients with hepatic or renal dysfunction, and subjects with minor deficient alleles for drug metabolizing enzymes and drug transporters). In this symposium article, I discuss this last special population: altered drug metabolism and drug interactions in subjects with minor alleles of genes encoding deficient drug metabolizing enzymes. I further discuss a drug label for eliglustat (Cerdelga) with instructions for patients with ultra-rapid, extensive, intermediate, and poor metabolizer phenotypes that arise from different CYP2D6 gene alleles.

Animal models of gene-environment interactions in schizophrenia.

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Ayhan, Yavuz; Sawa, Akira; Ross, Christopher A; Pletnikov, Mikhail V

2009-12-07

The pathogenesis of schizophrenia and related mental illnesses likely involves multiple interactions between susceptibility genes of small effects and environmental factors. Gene-environment interactions occur across different stages of neurodevelopment to produce heterogeneous clinical and pathological manifestations of the disease. The main obstacle for mechanistic studies of gene-environment interplay has been the paucity of appropriate experimental systems for elucidating the molecular pathways that mediate gene-environment interactions relevant to schizophrenia. Recent advances in psychiatric genetics and a plethora of experimental data from animal studies allow us to suggest a new approach to gene-environment interactions in schizophrenia. We propose that animal models based on identified genetic mutations and measurable environment factors will help advance studies of the molecular mechanisms of gene-environment interplay.

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

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Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

2017-10-03

With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms

NARCIS (Netherlands)

Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-01-01

BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric

Integration of liver gene co-expression networks and eGWAs analyses highlighted candidate regulators implicated in lipid metabolism in pigs.

Science.gov (United States)

Ballester, Maria; Ramayo-Caldas, Yuliaxis; Revilla, Manuel; Corominas, Jordi; Castelló, Anna; Estellé, Jordi; Fernández, Ana I; Folch, Josep M

2017-04-19

In the present study, liver co-expression networks and expression Genome Wide Association Study (eGWAS) were performed to identify DNA variants and molecular pathways implicated in the functional regulatory mechanisms of meat quality traits in pigs. With this purpose, the liver mRNA expression of 44 candidates genes related with lipid metabolism was analysed in 111 Iberian x Landrace backcross animals. The eGWAS identified 92 eSNPs located in seven chromosomal regions and associated with eight genes: CROT, CYP2U1, DGAT1, EGF, FABP1, FABP5, PLA2G12A, and PPARA. Remarkably, cis-eSNPs associated with FABP1 gene expression which may be determining the C18:2(n-6)/C18:3(n-3) ratio in backfat through the multiple interaction of DNA variants and genes were identified. Furthermore, a hotspot on SSC8 associated with the gene expression of eight genes was identified and the TBCK gene was pointed out as candidate gene regulating it. Our results also suggested that the PI3K-Akt-mTOR pathway plays an important role in the control of the analysed genes highlighting nuclear receptors as the NR3C1 or PPARA. Finally, sex-dimorphism associated with hepatic lipid metabolism was identified with over-representation of female-biased genes. These results increase our knowledge of the genetic architecture underlying fat composition traits.

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

Science.gov (United States)

Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

2018-03-19

With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

Metabolic aspects of Neuronal – Oligodendrocytic - Astrocytic (NOA interactions

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Ana I Amaral

2013-05-01

Full Text Available Whereas astrocytes have been in the limelight on the metabolic glucose interaction scene for a while, oligodendrocytes are still waiting for a place. We would like to call oligodendrocyte interaction with astrocytes and neurons: NOA (neuron – oligodendrocyte – astrocyte interactions. One of the reasons to find out more about oligodendrocyte interaction with neurons and astrocytes is to detect markers of healthy oligodendrocyte metabolism, to be used in diagnosis and treatment assessment in diseases such as Perinatal hypoxic-ischemic encephalopathy and multiple sclerosis in which oligodendrocyte function is impaired, possibly due to glutamate toxicity. Glutamate receptors are expressed in oligodendrocytes and also vesicular glutamate release in the white matter has received considerable attention. It is also important to establish if the glial precursor cells recruited to damaged areas are developing oligodendrocyte characteristics or those of astrocytes. Thus, it is important to study astrocytes and oligodendrocytes separately to be able to differentiate between them. This is of particular importance in the white matter where the number of oligodendrocytes is considerable. The present review summarizes the not very extensive information published on glucose metabolism in oligodendrocytes in an attempt to stimulate research into this important field.

Differential expression of metabolic genes in tumor and stromal components of primary and metastatic loci in pancreatic adenocarcinoma.

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Nina V Chaika

Full Text Available Pancreatic cancer is the fourth leading cause of cancer related deaths in the United States with a five-year survival rate of 6%. It is characterized by extremely aggressive tumor growth rate and high incidence of metastasis. One of the most common and profound biochemical phenotypes of animal and human cancer cells is their ability to metabolize glucose at high rates, even under aerobic conditions. However, the contribution of metabolic interrelationships between tumor cells and cells of the surrounding microenvironment to the progression of cancer is not well understood. We evaluated differential expression of metabolic genes and, hence, metabolic pathways in primary tumor and metastases of patients with pancreatic adenocarcinoma.We analyzed the metabolic gene (those involved in glycolysis, tri-carboxylic acid pathway, pentose-phosphate pathway and fatty acid metabolism expression profiles of primary and metastatic lesions from pancreatic cancer patients by gene expression arrays. We observed two principal results: genes that were upregulated in primary and most of the metastatic lesions; and genes that were upregulated only in specific metastatic lesions in a site-specific manner. Immunohistochemical (IHC analyses of several metabolic gene products confirmed the gene expression patterns at the protein level. The IHC analyses also revealed differential tumor and stromal expression patterns of metabolic enzymes that were correlated with the metastasis sites.Here, we present the first comprehensive studies that establish differential metabolic status of tumor and stromal components and elevation of aerobic glycolysis gene expression in pancreatic cancer.

Polymorphisms in fatty acid metabolism-related genes are associated with colorectal cancer risk

DEFF Research Database (Denmark)

Hoeft, B.; Linseisen, J.; Beckmann, L.

2010-01-01

as contributing factor to colon carcinogenesis. We examined the association between genetic variability in 43 fatty acid metabolism-related genes and colorectal risk in 1225 CRC cases and 2032 controls participating in the European Prospective Investigation into Cancer and Nutrition study. Three hundred......Colorectal cancer (CRC) is the third most common malignant tumor and the fourth leading cause of cancer death worldwide. The crucial role of fatty acids for a number of important biological processes suggests a more in-depth analysis of inter-individual differences in fatty acid metabolizing genes...... variants with CRC risk. Our results support the key role of prostanoid signaling in colon carcinogenesis and suggest a relevance of genetic variation in fatty acid metabolism-related genes and CRC risk....

Identification of genes specifically required for the anaerobic metabolism of benzene in Geobacter metallireducens

DEFF Research Database (Denmark)

Zhang, Tian; Tremblay, Pier-Luc; Chaurasia, Akhilesh Kumar

2014-01-01

Although the biochemical pathways for the anaerobic degradation of many of the hydrocarbon constituents in petroleum reservoirs have been elucidated, the mechanisms for anaerobic activation of benzene, a very stable molecule, are not known. Previous studies have demonstrated that Geobacter...... metallireducens can anaerobically oxidize benzene to carbon dioxide with Fe(III) as the sole electron acceptor and that phenol is an intermediate in benzene oxidation. In an attempt to identify enzymes that might be involved in the conversion of benzene to phenol, whole-genome gene transcript abundance...... was compared in cells metabolizing benzene and cells metabolizing phenol. Eleven genes had significantly higher transcript abundance in benzene-metabolizing cells. Five of these genes had annotations suggesting that they did not encode proteins that could be involved in benzene metabolism and were not further...

Interactions between epigenetics and metabolism in cancers

International Nuclear Information System (INIS)

Yun, Jihye; Johnson, Jared L.; Hanigan, Christin L.; Locasale, Jason W.

2012-01-01

Cancer progression is accompanied by widespread transcriptional changes and metabolic alterations. While it is widely accepted that the origin of cancer can be traced to the mutations that accumulate over time, relatively recent evidence favors a similarly fundamental role for alterations in the epigenome during tumorigenesis. Changes in epigenetics that arise from post-translational modifications of histones and DNA are exploited by cancer cells to upregulate and/or downregulate the expression levels of oncogenes and tumor suppressors, respectively. Although the mechanisms behind these modifications, in particular how they lead to gene silencing and activation, are still being understood, most of the enzymatic machinery of epigenetics require metabolites as substrates or cofactors. As a result, their activities can be influenced by the metabolic state of the cell. The purpose of this review is to give an overview of cancer epigenetics and metabolism and provide examples of where they converge.

Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions

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Rodríguez-Luna, Stefany Daniela; Cruz Vázquez, Angélica Patricia; Jiménez Suárez, Verónica; Rodríguez-Sanoja, Romina; Alvarez-Buylla, Elena R.; Sánchez, Sergio

2018-01-01

Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions. PMID:29447216

Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions.

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Corina Diana Ceapă

Full Text Available Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

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Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

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Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

2013-01-01

Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

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Ching Lee Koo

2013-01-01

Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

Ketogenic diet and astrocyte/neuron metabolic interactions

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Vamecq Joseph

2007-05-01

Full Text Available The ketogenic diet is an anticonvulsant diet enriched in fat. It provides the body with a minimal protein requirement and a restricted carbohydrate supply, the vast majority of calories (more than 80-90% being given by fat. Though anticonvulsant activity of ketogenic diet has been well documented by a large number of experimental and clinical studies, underlying mechanisms still remain partially unclear. Astrocyte-neuron interactions, among which metabolic shuttles, may influence synaptic activity and hence anticonvulsant protection. The astrocyte-neuron metabolic shuttles may be themselves influenced by the availability in energetic substrates such as hydrates of carbon and fats. Historically, ketogenic diet had been designed to mimic changes such as ketosis occurring upon starvation, a physiological state already known to exhibit anticonvulsant protection and sometimes referred to as “water diet”. For this reason, a special attention should be paid to metabolic features shared in common by ketogenic diet and starvation and especially those features that might result in anticonvulsant protection. Compared to feeding by usual mixed diet, starvation and ketogenic diet are both characterised by increased fat, lowered glucose and aminoacid supplies to cells. The resulting impact of these changes in energetic substrates on astrocyte/neuron metabolic shuttles might have anticonvulsant and/or neuroprotective properties. This is the aim of this communication to review some important astrocyte/neuron metabolic interactions (astrocyte/neuron lactate shuttle, glutamateinduced astrocytic glycolysis activation, glutamate/glutamine cycle along with the neurovascular coupling and the extent to which the way of their alteration by starvation and/or ketogenic diet might result in seizure and/or brain protection.

Insights into significant pathways and gene interaction networks in peripheral blood mononuclear cells for early diagnosis of hepatocellular carcinoma

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Jian Xin Jiang

2016-01-01

Conclusions: Using identified DEGs, significantly changed biological processes such as nucleic acid metabolic process and KEGG pathways such as cytokine-cytokine receptor interaction in PBMCs of HCC patients were identified. In addition, several important hub genes, for example, CUL4A, and interleukin (IL 8 were also uncovered.

Screening for interaction effects in gene expression data.

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Peter J Castaldi

Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

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Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

2008-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

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Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

2009-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

Interactions between epigenetics and metabolism in cancers

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Jihye eYun

2012-11-01

Full Text Available Cancer progression is accompanied by widespread transcriptional changes and metabolic alterations. Although it is widely accepted that the origin of cancer can be traced to the mutations that accumulate over time, relatively recent evidence favors a similarly fundamental role for alterations in the epigenome during tumorigenesis. Changes in epigenetics that arise from post-translational modifications of histones and DNA, are exploited by cancer cells to upregulate and/or downregulate the expression levels of oncogenes and tumor suppressors, respectively. Although the mechanisms behind these modifications, in particular how they lead to gene silencing and activation, are still being understood, many enzymes that carry out post-translational modifications that alter epigenetics require metabolites as substrates or cofactors. As a result, their activities can be influenced by the metabolic state of the cell. The purpose of this review is to give an overview of cancer epigenetics and metabolism and provide examples of where they converge.

Gene-gene, gene-environment, gene-nutrient interactions and single nucleotide polymorphisms of inflammatory cytokines.

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Nadeem, Amina; Mumtaz, Sadaf; Naveed, Abdul Khaliq; Aslam, Muhammad; Siddiqui, Arif; Lodhi, Ghulam Mustafa; Ahmad, Tausif

2015-05-15

Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM.

FCERI AND HISTAMINE METABOLISM GENE VARIABILITY IN SELECTIVE RESPONDERS TO NSAIDS

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Gemma Amo

2016-09-01

Full Text Available The high-affinity IgE receptor (Fcε RI is a heterotetramer of three subunits: Fcε RIα, Fcε RIβ and Fcε RIγ (αβγ2 encoded by three genes designated as FCER1A, FCER1B (MS4A2 and FCER1G, respectively. Recent evidence points to FCERI gene variability as a relevant factor in the risk of developing allergic diseases. Because Fcε RI plays a key role in the events downstream of the triggering factors in immunological response, we hypothesized that FCERI gene variants might be related with the risk of, or with the clinical response to, selective (IgE mediated non-steroidal anti-inflammatory (NSAID hypersensitivity.From a cohort of 314 patients suffering from selective hypersensitivity to metamizole, ibuprofen, diclofenac, paracetamol, acetylsalicylic acid (ASA, propifenazone, naproxen, ketoprofen, dexketoprofen, etofenamate, aceclofenac, etoricoxib, dexibuprofen, indomethacin, oxyphenylbutazone or piroxicam, and 585 unrelated healthy controls that tolerated these NSAIDs, we analyzed the putative effects of the FCERI SNPs FCER1A rs2494262, rs2427837 and rs2251746; FCER1B rs1441586, rs569108 and rs512555; FCER1G rs11587213, rs2070901 and rs11421. Furthermore, in order to identify additional genetic markers which might be associated with the risk of developing selective NSAID hypersensitivity, or which may modify the putative association of FCERI gene variations with risk, we analyzed polymorphisms known to affect histamine synthesis or metabolism, such as rs17740607, rs2073440, rs1801105, rs2052129, rs10156191, rs1049742 and rs1049793 in the HDC, HNMT and DAO genes.No major genetic associations with risk or with clinical presentation, and no gene-gene interactions, or gene-phenotype interactions (including age, gender, IgE concentration, antecedents of atopy, culprit drug or clinical presentation were identified in patients. However, logistic regression analyses indicated that the presence of antecedents of atopy and the DAO SNP rs2052129 (GG

Comparative metabolomics in primates reveals the effects of diet and gene regulatory variation on metabolic divergence.

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Blekhman, Ran; Perry, George H; Shahbaz, Sevini; Fiehn, Oliver; Clark, Andrew G; Gilad, Yoav

2014-07-28

Human diets differ from those of non-human primates. Among few obvious differences, humans consume more meat than most non-human primates and regularly cook their food. It is hypothesized that a dietary shift during human evolution has been accompanied by molecular adaptations in metabolic pathways. Consistent with this notion, comparative studies of gene expression levels in primates have found that the regulation of genes with metabolic functions tend to evolve rapidly in the human lineage. The metabolic consequences of these regulatory differences, however, remained unknown. To address this gap, we performed a comparative study using a combination of gene expression and metabolomic profiling in livers from humans, chimpanzees, and rhesus macaques. We show that dietary differences between species have a strong effect on metabolic concentrations. In addition, we found that differences in metabolic concentration across species are correlated with inter-species differences in the expression of the corresponding enzymes, which control the same metabolic reaction. We identified a number of metabolic compounds with lineage-specific profiles, including examples of human-species metabolic differences that may be directly related to dietary differences.

A kernel regression approach to gene-gene interaction detection for case-control studies.

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Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks

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Chiappino-Pepe, Anush; Ataman, Meriç

2017-01-01

Novel antimalarial therapies are urgently needed for the fight against drug-resistant parasites. The metabolism of malaria parasites in infected cells is an attractive source of drug targets but is rather complex. Computational methods can handle this complexity and allow integrative analyses of cell metabolism. In this study, we present a genome-scale metabolic model (iPfa) of the deadliest malaria parasite, Plasmodium falciparum, and its thermodynamics-based flux analysis (TFA). Using previous absolute concentration data of the intraerythrocytic parasite, we applied TFA to iPfa and predicted up to 63 essential genes and 26 essential pairs of genes. Of the 63 genes, 35 have been experimentally validated and reported in the literature, and 28 have not been experimentally tested and include previously hypothesized or novel predictions of essential metabolic capabilities. Without metabolomics data, four of the genes would have been incorrectly predicted to be non-essential. TFA also indicated that substrate channeling should exist in two metabolic pathways to ensure the thermodynamic feasibility of the flux. Finally, analysis of the metabolic capabilities of P. falciparum led to the identification of both the minimal nutritional requirements and the genes that can become indispensable upon substrate inaccessibility. This model provides novel insight into the metabolic needs and capabilities of the malaria parasite and highlights metabolites and pathways that should be measured and characterized to identify potential thermodynamic bottlenecks and substrate channeling. The hypotheses presented seek to guide experimental studies to facilitate a better understanding of the parasite metabolism and the identification of targets for more efficient intervention. PMID:28333921

Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks.

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Anush Chiappino-Pepe

2017-03-01

Full Text Available Novel antimalarial therapies are urgently needed for the fight against drug-resistant parasites. The metabolism of malaria parasites in infected cells is an attractive source of drug targets but is rather complex. Computational methods can handle this complexity and allow integrative analyses of cell metabolism. In this study, we present a genome-scale metabolic model (iPfa of the deadliest malaria parasite, Plasmodium falciparum, and its thermodynamics-based flux analysis (TFA. Using previous absolute concentration data of the intraerythrocytic parasite, we applied TFA to iPfa and predicted up to 63 essential genes and 26 essential pairs of genes. Of the 63 genes, 35 have been experimentally validated and reported in the literature, and 28 have not been experimentally tested and include previously hypothesized or novel predictions of essential metabolic capabilities. Without metabolomics data, four of the genes would have been incorrectly predicted to be non-essential. TFA also indicated that substrate channeling should exist in two metabolic pathways to ensure the thermodynamic feasibility of the flux. Finally, analysis of the metabolic capabilities of P. falciparum led to the identification of both the minimal nutritional requirements and the genes that can become indispensable upon substrate inaccessibility. This model provides novel insight into the metabolic needs and capabilities of the malaria parasite and highlights metabolites and pathways that should be measured and characterized to identify potential thermodynamic bottlenecks and substrate channeling. The hypotheses presented seek to guide experimental studies to facilitate a better understanding of the parasite metabolism and the identification of targets for more efficient intervention.

Conserved and Divergent Rhythms of Crassulacean Acid Metabolism-Related and Core Clock Gene Expression in the Cactus Opuntia ficus-indica1[C][W

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Mallona, Izaskun; Egea-Cortines, Marcos; Weiss, Julia

2011-01-01

The cactus Opuntia ficus-indica is a constitutive Crassulacean acid metabolism (CAM) species. Current knowledge of CAM metabolism suggests that the enzyme phosphoenolpyruvate carboxylase kinase (PPCK) is circadian regulated at the transcriptional level, whereas phosphoenolpyruvate carboxylase (PEPC), malate dehydrogenase (MDH), NADP-malic enzyme (NADP-ME), and pyruvate phosphate dikinase (PPDK) are posttranslationally controlled. As little transcriptomic data are available from obligate CAM plants, we created an expressed sequence tag database derived from different organs and developmental stages. Sequences were assembled, compared with sequences in the National Center for Biotechnology Information nonredundant database for identification of putative orthologs, and mapped using Kyoto Encyclopedia of Genes and Genomes Orthology and Gene Ontology. We identified genes involved in circadian regulation and CAM metabolism for transcriptomic analysis in plants grown in long days. We identified stable reference genes for quantitative polymerase chain reaction and found that OfiSAND, like its counterpart in Arabidopsis (Arabidopsis thaliana), and OfiTUB are generally appropriate standards for use in the quantification of gene expression in O. ficus-indica. Three kinds of expression profiles were found: transcripts of OfiPPCK oscillated with a 24-h periodicity; transcripts of the light-active OfiNADP-ME and OfiPPDK genes adapted to 12-h cycles, while transcript accumulation patterns of OfiPEPC and OfiMDH were arrhythmic. Expression of the circadian clock gene OfiTOC1, similar to Arabidopsis, oscillated with a 24-h periodicity, peaking at night. Expression of OfiCCA1 and OfiPRR9, unlike in Arabidopsis, adapted best to a 12-h rhythm, suggesting that circadian clock gene interactions differ from those of Arabidopsis. Our results indicate that the evolution of CAM metabolism could be the result of modified circadian regulation at both the transcriptional and posttranscriptional

Maternal obesity disrupts circadian rhythms of clock and metabolic genes in the offspring heart and liver.

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Wang, Danfeng; Chen, Siyu; Liu, Mei; Liu, Chang

2015-06-01

Early life nutritional adversity is tightly associated with the development of long-term metabolic disorders. Particularly, maternal obesity and high-fat diets cause high risk of obesity in the offspring. Those offspring are also prone to develop hyperinsulinemia, hepatic steatosis and cardiovascular diseases. However, the precise underlying mechanisms leading to these metabolic dysregulation in the offspring remain unclear. On the other hand, disruptions of diurnal circadian rhythms are known to impair metabolic homeostasis in various tissues including the heart and liver. Therefore, we investigated that whether maternal obesity perturbs the circadian expression rhythms of clock, metabolic and inflammatory genes in offspring heart and liver by using RT-qPCR and Western blotting analysis. Offspring from lean and obese dams were examined on postnatal day 17 and 35, when pups were nursed by their mothers or took food independently. On P17, genes examined in the heart either showed anti-phase oscillations (Cpt1b, Pparα, Per2) or had greater oscillation amplitudes (Bmal1, Tnf-α, Il-6). Such phase abnormalities of these genes were improved on P35, while defects in amplitudes still existed. In the liver of 17-day-old pups exposed to maternal obesity, the oscillation amplitudes of most rhythmic genes examined (except Bmal1) were strongly suppressed. On P35, the oscillations of circadian and inflammatory genes became more robust in the liver, while metabolic genes were still kept non-rhythmic. Maternal obesity also had a profound influence in the protein expression levels of examined genes in offspring heart and liver. Our observations indicate that the circadian clock undergoes nutritional programing, which may contribute to the alternations in energy metabolism associated with the development of metabolic disorders in early life and adulthood.

Gene-Environment Interactions in Severe Mental Illness

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Rudolf eUher

2014-05-01

Full Text Available Severe mental illness is a broad category that includes schizophrenia, bipolar disorder and severe depression. Both genetic disposition and environmental exposures play important roles in the development of severe mental illness. Multiple lines of evidence suggest that the roles of genetic and environmental depend on each other. Gene-environment interactions may underlie the paradox of strong environmental factors for highly heritable disorders, the low estimates of shared environmental influences in twin studies of severe mental illness and the heritability gap between twin and molecular heritability estimates. Sons and daughters of parents with severe mental illness are more vulnerable to the effects of prenatal and postnatal environmental exposures, suggesting that the expression of genetic liability depends on environment. In the last decade, gene-environment interactions involving specific molecular variants in candidate genes have been identified. Replicated findings include an interaction between a polymorphism in the AKT1 gene and cannabis use in the development of psychosis and an interaction between the length polymorphism of the serotonin transporter gene and childhood maltreatment in the development of persistent depressive disorder. Bipolar disorder has been underinvestigated, with only a single study showing an interaction between a functional polymorphism in BDNF and stressful life events triggering bipolar depressive episodes. The first systematic search for gene-environment interactions has found that a polymorphism in CTNNA3 may sensitise the developing brain to the pathogenic effect of cytomegalovirus in utero, leading to schizophrenia in adulthood. Strategies for genome-wide investigations will likely include coordination between epidemiological and genetic research efforts, systematic assessment of multiple environmental factors in large samples, and prioritization of genetic variants.

Dairy Product Consumption Interacts with Glucokinase (GCK Gene Polymorphisms Associated with Insulin Resistance

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Marine S. Da Silva

2017-08-01

Full Text Available Dairy product intake and a person’s genetic background have been reported to be associated with the risk of type 2 diabetes (T2D. The objective of this study was to examine the interaction between dairy products and genes related to T2D on glucose-insulin homeostasis parameters. A validated food frequency questionnaire, fasting blood samples, and glucokinase (GCK genotypes were analyzed in 210 healthy participants. An interaction between rs1799884 in GCK and dairy intake on the homeostasis model assessment of insulin resistance was identified. Secondly, human hepatocellular carcinoma cells (HepG2 were grown in a high-glucose medium and incubated with either 1-dairy proteins: whey, caseins, and a mixture of whey and casein; and 2-four amino acids (AA or mixtures of AA. The expression of GCK-related genes insulin receptor substrate-1 (IRS-1 and fatty acid synthase (FASN was increased with whey protein isolate or hydrolysate. Individually, leucine increased IRS-1 expression, whereas isoleucine and valine decreased FASN expression. A branched-chain AA mixture decreased IRS-1 and FASN expression. In conclusion, carriers of the A allele for rs1799884 in the GCK gene may benefit from a higher intake of dairy products to maintain optimal insulin sensitivity. Moreover, the results show that whey proteins affect the expression of genes related to glucose metabolism.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups

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S. Pamela K. Shiao

2018-02-01

Full Text Available For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene–environment interactions and predictors of colorectal cancer (CRC by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black. We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls (p < 0.05, on MTHFR C677T, MTR A2756G, MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05 except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike’s information criterion and leave-one-out cross validation methods. Body mass index (BMI and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene–environment interactions in the prevention of CRC.

Metabolic interactions between cysteamine and epigallocatechin gallate.

Science.gov (United States)

Izzo, Valentina; Pietrocola, Federico; Sica, Valentina; Durand, Sylvère; Lachkar, Sylvie; Enot, David; Bravo-San Pedro, José Manuel; Chery, Alexis; Esposito, Speranza; Raia, Valeria; Maiuri, Luigi; Maiuri, Maria Chiara; Kroemer, Guido

2017-02-01

Phase II clinical trials indicate that the combination of cysteamine plus epigallocatechin gallate (EGCG) is effective against cystic fibrosis in patients bearing the most frequent etiological mutation (CFTRΔF508). Here, we investigated the interaction between both agents on cultured respiratory epithelia cells from normal and CFTRΔF508-mutated donors. We observed that the combination of both agents affected metabolic circuits (and in particular the tricarboxylic acid cycle) in a unique way and that cysteamine plus EGCG reduced cytoplasmic protein acetylation more than each of the 2 components alone. In a cell-free system, protein cross-linking activity of EGCG was suppressed by cysteamine. Finally, EGCG was able to enhance the conversion of cysteamine into taurine in metabolic flux experiments. Altogether, these results indicate that multiple pharmacological interactions occur between cysteamine and EGCG, suggesting that they contribute to the unique synergy of both agents in restoring the function of mutated CFTRΔF508.

PPARγ regulates the expression of cholesterol metabolism genes in alveolar macrophages

International Nuclear Information System (INIS)

Baker, Anna D.; Malur, Anagha; Barna, Barbara P.; Kavuru, Mani S.; Malur, Achut G.; Thomassen, Mary Jane

2010-01-01

Peroxisome proliferator-activated receptor-gamma (PPARγ) is a nuclear transcription factor involved in lipid metabolism that is constitutively expressed in the alveolar macrophages of healthy individuals. PPARγ has recently been implicated in the catabolism of surfactant by alveolar macrophages, specifically the cholesterol component of surfactant while the mechanism remains unclear. Studies from other tissue macrophages have shown that PPARγ regulates cholesterol influx, efflux, and metabolism. PPARγ promotes cholesterol efflux through the liver X receptor-alpha (LXRα) and ATP-binding cassette G1 (ABCG1). We have recently shown that macrophage-specific PPARγ knockout (PPARγ KO) mice accumulate cholesterol-laden alveolar macrophages that exhibit decreased expression of LXRα and ABCG1 and reduced cholesterol efflux. We hypothesized that in addition to the dysregulation of these cholesterol efflux genes, the expression of genes involved in cholesterol synthesis and influx was also dysregulated and that replacement of PPARγ would restore regulation of these genes. To investigate this hypothesis, we have utilized a Lentivirus expression system (Lenti-PPARγ) to restore PPARγ expression in the alveolar macrophages of PPARγ KO mice. Our results show that the alveolar macrophages of PPARγ KO mice have decreased expression of key cholesterol synthesis genes and increased expression of cholesterol receptors CD36 and scavenger receptor A-I (SRA-I). The replacement of PPARγ (1) induced transcription of LXRα and ABCG1; (2) corrected suppressed expression of cholesterol synthesis genes; and (3) enhanced the expression of scavenger receptors CD36. These results suggest that PPARγ regulates cholesterol metabolism in alveolar macrophages.

mRNA expression of genes regulating lipid metabolism in ringed seals (Pusa hispida) from differently polluted areas

International Nuclear Information System (INIS)

Castelli, Martina Galatea; Rusten, Marte; Goksøyr, Anders; Routti, Heli

2014-01-01

Highlights: •Genes regulating lipid metabolism were studied in ringed seals. •We compared highly contaminated Baltic seals and less contaminated Svalbard seals. •mRNA expression of hepatic PPARγ was higher in the Baltic seals. •mRNA expression of adipose PPARγ target genes was higher in the Baltic seals. •Contaminant exposure may affect lipid metabolism in the Baltic ringed seals. -- Abstract: There is a growing concern about the ability of persistent organic pollutants (POPs) to influence lipid metabolism. Although POPs are found at high concentrations in some populations of marine mammals, for example in the ringed seal (Pusa hispida) from the Baltic Sea, little is known about the effects of POPs on their lipid metabolism. An optimal regulation of lipid metabolism is crucial for ringed seals during the fasting/molting season. This is a physiologically stressful period, during which they rely on the energy stored in their fat reserves. The mRNA expression levels for seven genes involved in lipid metabolism were analyzed in liver and/or blubber tissue from molting ringed seals from the polluted Baltic Sea and a less polluted reference location, Svalbard (Norway). mRNA expression of genes encoding peroxisome proliferator-activated receptors (PPAR) α and γ and their target genes acyl-coenzyme A oxidase 1 (ACOX1) and cluster of differentiation 36 (CD36) were analyzed in liver. mRNA expression level of genes encoding PPARβ, PPARγ and their target genes encoding fatty acid binding protein 4 (FABP4) and adiponectin (ADIPOQ) were measured in inner and middle blubber layers. In addition, we evaluated the influence of molting status on hepatic mRNA expression of genes encoding PPARs and their target genes in ringed seals from Svalbard. Our results show higher mRNA expression of genes encoding hepatic PPARγ and adipose PPARβ, FABP4, and ADIPOQ in the Baltic seals compared to the Svalbard seals. A positive relationship between mRNA expressions of genes

mRNA expression of genes regulating lipid metabolism in ringed seals (Pusa hispida) from differently polluted areas

Energy Technology Data Exchange (ETDEWEB)

Castelli, Martina Galatea [Norwegian Polar Institute, Fram Centre, 9296 Tromsø (Norway); University of Bergen, Department of Biology, 5020 Bergen (Norway); Rusten, Marte; Goksøyr, Anders [University of Bergen, Department of Biology, 5020 Bergen (Norway); Routti, Heli, E-mail: heli.routti@npolar.no [Norwegian Polar Institute, Fram Centre, 9296 Tromsø (Norway)

2014-01-15

Highlights: •Genes regulating lipid metabolism were studied in ringed seals. •We compared highly contaminated Baltic seals and less contaminated Svalbard seals. •mRNA expression of hepatic PPARγ was higher in the Baltic seals. •mRNA expression of adipose PPARγ target genes was higher in the Baltic seals. •Contaminant exposure may affect lipid metabolism in the Baltic ringed seals. -- Abstract: There is a growing concern about the ability of persistent organic pollutants (POPs) to influence lipid metabolism. Although POPs are found at high concentrations in some populations of marine mammals, for example in the ringed seal (Pusa hispida) from the Baltic Sea, little is known about the effects of POPs on their lipid metabolism. An optimal regulation of lipid metabolism is crucial for ringed seals during the fasting/molting season. This is a physiologically stressful period, during which they rely on the energy stored in their fat reserves. The mRNA expression levels for seven genes involved in lipid metabolism were analyzed in liver and/or blubber tissue from molting ringed seals from the polluted Baltic Sea and a less polluted reference location, Svalbard (Norway). mRNA expression of genes encoding peroxisome proliferator-activated receptors (PPAR) α and γ and their target genes acyl-coenzyme A oxidase 1 (ACOX1) and cluster of differentiation 36 (CD36) were analyzed in liver. mRNA expression level of genes encoding PPARβ, PPARγ and their target genes encoding fatty acid binding protein 4 (FABP4) and adiponectin (ADIPOQ) were measured in inner and middle blubber layers. In addition, we evaluated the influence of molting status on hepatic mRNA expression of genes encoding PPARs and their target genes in ringed seals from Svalbard. Our results show higher mRNA expression of genes encoding hepatic PPARγ and adipose PPARβ, FABP4, and ADIPOQ in the Baltic seals compared to the Svalbard seals. A positive relationship between mRNA expressions of genes

Association of apolipoprotein e gene polymorphisms with blood lipids and their interaction with dietary factors

DEFF Research Database (Denmark)

Shatwan, Israa M.; Winther, Kristian Hillert; Ellahi, Basma

2018-01-01

of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. Methods: The population studied for this investigation included 660 individuals from...... the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ......Background: Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association...

Verticillium dahliae-Arabidopsis Interaction Causes Changes in Gene Expression Profiles and Jasmonate Levels on Different Time Scales

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Sandra S. Scholz

2018-02-01

Full Text Available Verticillium dahliae is a soil-borne vascular pathogen that causes severe wilt symptoms in a wide range of plants. Co-culture of the fungus with Arabidopsis roots for 24 h induces many changes in the gene expression profiles of both partners, even before defense-related phytohormone levels are induced in the plant. Both partners reprogram sugar and amino acid metabolism, activate genes for signal perception and transduction, and induce defense- and stress-responsive genes. Furthermore, analysis of Arabidopsis expression profiles suggests a redirection from growth to defense. After 3 weeks, severe disease symptoms can be detected for wild-type plants while mutants impaired in jasmonate synthesis and perception perform much better. Thus, plant jasmonates have an important influence on the interaction, which is already visible at the mRNA level before hormone changes occur. The plant and fungal genes that rapidly respond to the presence of the partner might be crucial for early recognition steps and the future development of the interaction. Thus they are potential targets for the control of V. dahliae-induced wilt diseases.

Metabolism of very long-chain Fatty acids: genes and pathophysiology.

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Sassa, Takayuki; Kihara, Akio

2014-02-01

Fatty acids (FAs) are highly diverse in terms of carbon (C) chain-length and number of double bonds. FAs with C>20 are called very long-chain fatty acids (VLCFAs). VLCFAs are found not only as constituents of cellular lipids such as sphingolipids and glycerophospholipids but also as precursors of lipid mediators. Our understanding on the function of VLCFAs is growing in parallel with the identification of enzymes involved in VLCFA synthesis or degradation. A variety of inherited diseases, such as ichthyosis, macular degeneration, myopathy, mental retardation, and demyelination, are caused by mutations in the genes encoding VLCFA metabolizing enzymes. In this review, we describe mammalian VLCFAs by highlighting their tissue distribution and metabolic pathways, and we discuss responsible genes and enzymes with reference to their roles in pathophysiology.

The Omics Dashboard for interactive exploration of gene-expression data.

Science.gov (United States)

Paley, Suzanne; Parker, Karen; Spaulding, Aaron; Tomb, Jean-Francois; O'Maille, Paul; Karp, Peter D

2017-12-01

The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets. The Omics Dashboard is organized as a hierarchy of cellular systems. At the highest level of the hierarchy the Dashboard contains graphical panels depicting systems such as biosynthesis, energy metabolism, regulation and central dogma. Each of those panels contains a series of X-Y plots depicting expression levels of subsystems of that panel, e.g. subsystems within the central dogma panel include transcription, translation and protein maturation and folding. The Dashboard presents a visual read-out of the expression status of cellular systems to facilitate a rapid top-down user survey of how all cellular systems are responding to a given stimulus, and to enable the user to quickly view the responses of genes within specific systems of interest. Although the Dashboard is complementary to traditional statistical methods for analysis of gene-expression data, we show how it can detect changes in gene expression that statistical techniques may overlook. We present the capabilities of the Dashboard using two case studies: the analysis of lipid production for the marine alga Thalassiosira pseudonana, and an investigation of a shift from anaerobic to aerobic growth for the bacterium Escherichia coli. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Variable Persister Gene Interactions with (pppGpp for Persister Formation in Escherichia coli

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Shuang Liu

2017-09-01

Full Text Available Persisters comprise a group of phenotypically heterogeneous metabolically quiescent bacteria with multidrug tolerance and contribute to the recalcitrance of chronic infections. Although recent work has shown that toxin-antitoxin (TA system HipAB depends on stringent response effector (pppGppin persister formation, whether other persister pathways are also dependent on stringent response has not been explored. Here we examined the relationship of (pppGpp with 15 common persister genes (dnaK, clpB, rpoS, pspF, tnaA, sucB, ssrA, smpB, recA, umuD, uvrA, hipA, mqsR, relE, dinJ using Escherichia coli as a model. By comparing the persister levels of wild type with their single gene knockout and double knockout mutants with relA, we divided their interactions into five types, namely A “dependent” (dnaK, recA, B “positive reinforcement” (rpoS, pspF, ssrA, recA, C “antagonistic” (clpB, sucB, umuD, uvrA, hipA, mqsR, relE, dinJ, D “epistasis” (clpB, rpoS, tnaA, ssrA, smpB, hipA, and E “irrelevant” (dnaK, clpB, rpoS, tnaA, sucB, smpB, umuD, uvrA, hipA, mqsR, relE, dinJ. We found that the persister gene interactions are intimately dependent on bacterial culture age, cell concentrations (diluted versus undiluted culture, and drug classifications, where the same gene may belong to different groups with varying antibiotics, culture age or cell concentrations. Together, this study represents the first attempt to systematically characterize the intricate relationships among the different mechanisms of persistence and as such provide new insights into the complexity of the persistence phenomenon at the level of persister gene network interactions.

Single nucleotide polymorphisms linked to mitochondrial uncoupling protein genes UCP2 and UCP3 affect mitochondrial metabolism and healthy aging in female nonagenarians.

Science.gov (United States)

Kim, Sangkyu; Myers, Leann; Ravussin, Eric; Cherry, Katie E; Jazwinski, S Michal

2016-08-01

Energy expenditure decreases with age, but in the oldest-old, energy demand for maintenance of body functions increases with declining health. Uncoupling proteins have profound impact on mitochondrial metabolic processes; therefore, we focused attention on mitochondrial uncoupling protein genes. Alongside resting metabolic rate (RMR), two SNPs in the promoter region of UCP2 were associated with healthy aging. These SNPs mark potential binding sites for several transcription factors; thus, they may affect expression of the gene. A third SNP in the 3'-UTR of UCP3 interacted with RMR. This UCP3 SNP is known to impact UCP3 expression in tissue culture cells, and it has been associated with body weight and mitochondrial energy metabolism. The significant main effects of the UCP2 SNPs and the interaction effect of the UCP3 SNP were also observed after controlling for fat-free mass (FFM) and physical-activity related energy consumption. The association of UCP2/3 with healthy aging was not found in males. Thus, our study provides evidence that the genetic risk factors for healthy aging differ in males and females, as expected from the differences in the phenotypes associated with healthy aging between the two sexes. It also has implications for how mitochondrial function changes during aging.

Transcriptional expression changes of glucose metabolism genes after exercise in thoroughbred horses.

Science.gov (United States)

Gim, Jeong-An; Ayarpadikannan, Selvam; Eo, Jungwoo; Kwon, Yun-Jeong; Choi, Yuri; Lee, Hak-Kyo; Park, Kyung-Do; Yang, Young Mok; Cho, Byung-Wook; Kim, Heui-Soo

2014-08-15

Physical exercise induces gene expression changes that trigger glucose metabolism pathways in organisms. In the present study, we monitored the expression levels of LDHA (lactate dehydrogenase) and GYS1 (glycogen synthase 1) in the blood, to confirm the roles of these genes in exercise physiology. LDHA and GYS1 are related to glucose metabolism and fatigue recovery, and these processes could elicit economically important traits in racehorses. We collected blood samples from three retired thoroughbred racehorses, pre-exercise and immediately after 30 min of exercise. We extracted total RNA and small RNA (≤ 200 nucleotide-long) from the blood, and assessed the expression levels of LDHA, GYS1, and microRNAs (miRNAs), by using qRT-PCR. We showed that LDHA and GYS1 were down-regulated, whereas eca-miR-33a and miR-17 were up-regulated, after exercise. We used sequences from the 3' UTR of LDHA and GYS1, containing eca-miR-33a and miR-17 binding sites, to observe the down-regulation activity of each gene expression. We observed that the two miRNAs, namely, eca-miR-33a and miR-17, inhibited LDHA and GYS1 expression via binding to the 3' UTR sequences of each gene. Our results indicate that eca-miR-33a and miR-17 play important roles in the glucose metabolism pathway. In addition, our findings provide a basis for further investigation of the exercise metabolism of racehorses. Copyright © 2014 Elsevier B.V. All rights reserved.

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

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Ueki Masao

2012-05-01

Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

Science.gov (United States)

Santos, Daniel M V; Katzmarzyk, Peter T; Diego, Vincent P; Souza, Michele C; Chaves, Raquel N; Blangero, John; Maia, José A R

2013-01-01

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (pmetabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

Science.gov (United States)

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2017-03-14

Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

The Class II trehalose 6-phosphate synthase gene PvTPS9 modulates trehalose metabolism in Phaseolus vulgaris nodules.

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Aarón Barraza

2016-11-01

Full Text Available Legumes form symbioses with rhizobia, producing nitrogen-fixing nodules on the roots of the plant host. The network of plant signaling pathways affecting carbon metabolism may determine the final number of nodules. The trehalose biosynthetic pathway regulates carbon metabolism and plays a fundamental role in plant growth and development, as well as in plant-microbe interactions. The expression of genes for trehalose synthesis during nodule development suggests that this metabolite may play a role in legume-rhizobia symbiosis. In this work, PvTPS9, which encodes a Class II trehalose-6-phosphate synthase (TPS of common bean (Phaseolus vulgaris, was silenced by RNA interference in transgenic nodules. The silencing of PvTPS9 in root nodules resulted in a reduction of 85% (± 1% of its transcript, which correlated with a 30% decrease in trehalose contents of transgenic nodules and in untransformed leaves. Composite transgenic plants with PvTPS9 silenced in the roots showed no changes in nodule number and nitrogen fixation, but a severe reduction in plant biomass and altered transcript profiles of all Class II TPS genes. Our data suggest that PvTPS9 plays a key role in modulating trehalose metabolism in the symbiotic nodule and, therefore, in the whole plant.

Detection of Gene Interactions Based on Syntactic Relations

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Mi-Young Kim

2008-01-01

Full Text Available Interactions between proteins and genes are considered essential in the description of biomolecular phenomena, and networks of interactions are applied in a system's biology approach. Recently, many studies have sought to extract information from biomolecular text using natural language processing technology. Previous studies have asserted that linguistic information is useful for improving the detection of gene interactions. In particular, syntactic relations among linguistic information are good for detecting gene interactions. However, previous systems give a reasonably good precision but poor recall. To improve recall without sacrificing precision, this paper proposes a three-phase method for detecting gene interactions based on syntactic relations. In the first phase, we retrieve syntactic encapsulation categories for each candidate agent and target. In the second phase, we construct a verb list that indicates the nature of the interaction between pairs of genes. In the last phase, we determine direction rules to detect which of two genes is the agent or target. Even without biomolecular knowledge, our method performs reasonably well using a small training dataset. While the first phase contributes to improve recall, the second and third phases contribute to improve precision. In the experimental results using ICML 05 Workshop on Learning Language in Logic (LLL05 data, our proposed method gave an F-measure of 67.2% for the test data, significantly outperforming previous methods. We also describe the contribution of each phase to the performance.

The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men

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Ming Liu

2016-01-01

Full Text Available Prostate cancer (PCa is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI, smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs = 1.79–4.41. GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032 and 5.33 (p = 0.046, respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007 and 3.11 (p = 0.024, respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041. These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

Regulation of metabolic products and gene expression in Fusarium asiaticum by agmatine addition.

Science.gov (United States)

Suzuki, Tadahiro; Kim, Young-Kyung; Yoshioka, Hifumi; Iwahashi, Yumiko

2013-05-01

The metabolic products resulting from the cultivation of F. asiaticum in agmatine were identified using capillary electrophoresis-time of flight mass spectrometry. Glyoxylic acid was detected from fungal cultures grown in agmatine, while it was absent in control cells. The abundance of other metabolic products of the glycolytic pathway also increased because of agmatine; however, there was no increase in the amounts of pyruvic acid or metabolites from the tricarboxylic acid cycle. Moreover, gene expression levels within Fusarium asiaticum exposed to agmatine were analyzed by DNA microarray. Changes in gene expression levels directed the changes in metabolic products. Our results suggest that acetyl coenzyme A, which is a starting substrate for the biosynthesis of deoxynivalenol (DON), was simultaneously produced by activated β-oxidation. Furthermore, the content of 4-aminobutyrate (GABA) was increased in the agmatine addition culture medium. GABA can be synthesized from agmatine through putrescine and might influence the regulation of DON-related genes.

Icariin Is A PPARα Activator Inducing Lipid Metabolic Gene Expression in Mice

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Yuan-Fu Lu

2014-11-01

Full Text Available Icariin is effective in the treatment of hyperlipidemia. To understand the effect of icariin on lipid metabolism, effects of icariin on PPARα and its target genes were investigated. Mice were treated orally with icariin at doses of 0, 100, 200, and 400 mg/kg, or clofibrate (500 mg/kg for five days. Liver total RNA was isolated and the expressions of PPARα and lipid metabolism genes were examined. PPARα and its marker genes Cyp4a10 and Cyp4a14 were induced 2-4 fold by icariin, and 4-8 fold by clofibrate. The fatty acid (FA binding and co-activator proteins Fabp1, Fabp4 and Acsl1 were increased 2-fold. The mRNAs of mitochondrial FA β-oxidation enzymes (Cpt1a, Acat1, Acad1 and Hmgcs2 were increased 2-3 fold. The mRNAs of proximal β-oxidation enzymes (Acox1, Ech1, and Ehhadh were also increased by icariin and clofibrate. The expression of mRNAs for sterol regulatory element-binding factor-1 (Srebf1 and FA synthetase (Fasn were unaltered by icariin. The lipid lysis genes Lipe and Pnpla2 were increased by icariin and clofibrate. These results indicate that icariin is a novel PPARα agonist, activates lipid metabolism gene expressions in liver, which could be a basis for its lipid-lowering effects and its beneficial effects against diabetes.

Two different secondary metabolism gene clusters occupied the same ancestral locus in fungal dermatophytes of the arthrodermataceae.

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Zhang, Han; Rokas, Antonis; Slot, Jason C

2012-01-01

Dermatophyte fungi of the family Arthrodermataceae (Eurotiomycetes) colonize keratinized tissue, such as skin, frequently causing superficial mycoses in humans and other mammals, reptiles, and birds. Competition with native microflora likely underlies the propensity of these dermatophytes to produce a diversity of antibiotics and compounds for scavenging iron, which is extremely scarce, as well as the presence of an unusually large number of putative secondary metabolism gene clusters, most of which contain non-ribosomal peptide synthetases (NRPS), in their genomes. To better understand the historical origins and diversification of NRPS-containing gene clusters we examined the evolution of a variable locus (VL) that exists in one of three alternative conformations among the genomes of seven dermatophyte species. The first conformation of the VL (termed VLA) contains only 539 base pairs of sequence and lacks protein-coding genes, whereas the other two conformations (termed VLB and VLC) span 36 Kb and 27 Kb and contain 12 and 10 genes, respectively. Interestingly, both VLB and VLC appear to contain distinct secondary metabolism gene clusters; VLB contains a NRPS gene as well as four porphyrin metabolism genes never found to be physically linked in the genomes of 128 other fungal species, whereas VLC also contains a NRPS gene as well as several others typically found associated with secondary metabolism gene clusters. Phylogenetic evidence suggests that the VL locus was present in the ancestor of all seven species achieving its present distribution through subsequent differential losses or retentions of specific conformations. We propose that the existence of variable loci, similar to the one we studied, in fungal genomes could potentially explain the dramatic differences in secondary metabolic diversity between closely related species of filamentous fungi, and contribute to host adaptation and the generation of metabolic diversity.

Novel interactions between vertebrate Hox genes

NARCIS (Netherlands)

Hooiveld, MHW; Morgan, R; Rieden, PID; Houtzager, E; Pannese, M; Damen, K; Boncinelli, E; Durston, AJ

1999-01-01

Understanding why metazoan Hox/HOM-C genes are expressed in spatiotemporal sequences showing colinearity with their genomic sequence is a central challenge in developmental biology. Here, we studied the consequences of ectopically expressing Hox genes to investigate whether Hox-Hox interactions

Integrated in silico Analyses of Regulatory and Metabolic Networks of Synechococcus sp. PCC 7002 Reveal Relationships between Gene Centrality and Essentiality

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Hyun-Seob Song

2015-03-01

Full Text Available Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as “topologically important.” Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as “functionally important” genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

Effect of Microbial Interaction on Urea Metabolism in Chinese Liquor Fermentation.

Science.gov (United States)

Wu, Qun; Lin, Jianchun; Cui, Kaixiang; Du, Rubin; Zhu, Yang; Xu, Yan

2017-12-20

Urea is the primary precursor of the carcinogen ethyl carbamate in fermented foods. Understanding urea metabolism is important for controlling ethyl carbamate production. Using Chinese liquor as a model system, we used metatranscriptome analysis to investigate urea metabolism in spontaneous food fermentation processes. Saccharomyces cerevisiae was dominant in gene transcription for urea biosynthesis and degradation. Lysinibacillus sphaericus was dominant for urea degradation. S. cerevisiae degraded 18% and L. sphaericus degraded 13% of urea in their corresponding single cultures, whereas they degraded 56% of urea in coculture after 12 h. Compared to single cultures, transcription of CAR1, DAL2, and argA, which are related to urea biosynthesis, decreased by 51, 36, and 69% in coculture, respectively. Transcription of DUR1 and ureA, which are related to urea degradation, increased by 227 and 70%, respectively. Thus, coexistence of the two strains promoted degradation of urea via transcriptional regulation of genes related to urea metabolism.

Functional Gene Diversity and Metabolic Potential of the Microbial Community in an Estuary-Shelf Environment

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Yu Wang

2017-06-01

Full Text Available Microbes play crucial roles in various biogeochemical processes in the ocean, including carbon (C, nitrogen (N, and phosphorus (P cycling. Functional gene diversity and the structure of the microbial community determines its metabolic potential and therefore its ecological function in the marine ecosystem. However, little is known about the functional gene composition and metabolic potential of bacterioplankton in estuary areas. The East China Sea (ECS is a dynamic marginal ecosystem in the western Pacific Ocean that is mainly affected by input from the Changjiang River and the Kuroshio Current. Here, using a high-throughput functional gene microarray (GeoChip, we analyzed the functional gene diversity, composition, structure, and metabolic potential of microbial assemblages in different ECS water masses. Four water masses determined by temperature and salinity relationship showed different patterns of functional gene diversity and composition. Generally, functional gene diversity [Shannon–Weaner’s H and reciprocal of Simpson’s 1/(1-D] in the surface water masses was higher than that in the bottom water masses. The different presence and proportion of functional genes involved in C, N, and P cycling among the bacteria of the different water masses showed different metabolic preferences of the microbial populations in the ECS. Genes involved in starch metabolism (amyA and nplT showed higher proportion in microbial communities of the surface water masses than of the bottom water masses. In contrast, a higher proportion of genes involved in chitin degradation was observed in microorganisms of the bottom water masses. Moreover, we found a higher proportion of nitrogen fixation (nifH, transformation of hydroxylamine to nitrite (hao and ammonification (gdh genes in the microbial communities of the bottom water masses compared with those of the surface water masses. The spatial variation of microbial functional genes was significantly correlated

Combining many interaction networks to predict gene function and analyze gene lists.

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Mostafavi, Sara; Morris, Quaid

2012-05-01

In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Polymorphisms in genes related to activation or detoxification of carcinogens might interact with smoking to increase renal cancer risk: Results from The Netherlands Cohort Study on diet and cancer

NARCIS (Netherlands)

Smits, K.M.; Schouten, L.J.; Dijk, B.A.C. van; Houwelingen, K. van; Hulsbergen-Kaa, C.A. van de; Kiemeney, L.A.L.M.; Houwelingen, K. van; Goldbohm, R.A.; Oosterwijk, E.; Brandt, P.A. van den

2008-01-01

Metabolic gene polymorphisms have previously been suggested as risk factors for renal cell carcinoma (RCC). These polymorphisms are involved in activation or detoxification of carcinogens in cigarette smoke which is another RCC risk factor. We evaluated gene-environment interactions between CYP1A1,

The Gene-Lifestyle Interaction on Leptin Sensitivity and Lipid Metabolism in Adults: A Population Based Study.

Science.gov (United States)

Luglio, Harry Freitag; Sulistyoningrum, Dian Caturini; Huriyati, Emy; Lee, Yi Yi; Wan Muda, Wan Abdul Manan

2017-07-07

Obesity has been associated with leptin resistance and this might be caused by genetic factors. The aim of this study was to investigate the gene-lifestyle interaction between -866G/A UCP2 (uncoupling protein 2) gene polymorphism, dietary intake and leptin in a population based study. This is a cross sectional study conducted in adults living at urban area of Yogyakarta, Indonesia. Data of adiposity, lifestyle, triglyceride, high density lipoprotein (HDL) cholesterol, leptin and UCP2 gene polymorphism were obtained in 380 men and female adults. UCP2 gene polymorphism was not significantly associated with adiposity, leptin, triglyceride, HDL cholesterol, dietary intake and physical activity (all p > 0.05). Leptin was lower in overweight subjects with AA + GA genotypes than those with GG genotype counterparts ( p = 0.029). In subjects with AA + GA genotypes there was a negative correlation between leptin concentration ( r = -0.324; p correlation was not seen in GG genotype ( r = -0.111; p = 0.188). In summary, we showed how genetic variation in -866G/A UCP2 affected individual response to leptin production. AA + GA genotype had a better leptin sensitivity shown by its response in dietary intake and body mass index (BMI) and this explained the protective effect of A allele to obesity.

Gene-based testing of interactions in association studies of quantitative traits.

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Li Ma

Full Text Available Various methods have been developed for identifying gene-gene interactions in genome-wide association studies (GWAS. However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene-gene interaction (GGG tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein-protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies.

Nur77 coordinately regulates expression of genes linked to glucose metabolism in skeletal muscle

OpenAIRE

Chao, Lily C.; Zhang, Zidong; Pei, Liming; Saito, Tsugumichi; Tontonoz, Peter; Pilch, Paul F.

2007-01-01

Innervation is important for normal metabolism in skeletal muscle, including insulin-sensitive glucose uptake. However, the transcription factors that transduce signals from the neuromuscular junction to the nucleus and affect changes in metabolic gene expression are not well defined. We demonstrate here that the orphan nuclear receptor Nur77 is a regulator of gene expression linked to glucose utilization in muscle. In vivo, Nur77 is preferentially expressed in glycolytic compared to oxidativ...

Predicting metabolic pathways by sub-network extraction.

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Faust, Karoline; van Helden, Jacques

2012-01-01

Various methods result in groups of functionally related genes obtained from genomes (operons, regulons, syntheny groups, and phylogenetic profiles), transcriptomes (co-expression groups) and proteomes (modules of interacting proteins). When such groups contain two or more enzyme-coding genes, graph analysis methods can be applied to extract a metabolic pathway that interconnects them. We describe here the way to use the Pathway extraction tool available on the NeAT Web server ( http://rsat.ulb.ac.be/neat/ ) to piece together the metabolic pathway from a group of associated, enzyme-coding genes. The tool identifies the reactions that can be catalyzed by the products of the query genes (seed reactions), and applies sub-graph extraction algorithms to extract from a metabolic network a sub-network that connects the seed reactions. This sub-network represents the predicted metabolic pathway. We describe here the pathway prediction process in a step-by-step way, give hints about the main parametric choices, and illustrate how this tool can be used to extract metabolic pathways from bacterial genomes, on the basis of two study cases: the isoleucine-valine operon in Escherichia coli and a predicted operon in Cupriavidus (Ralstonia) metallidurans.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

Science.gov (United States)

Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

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Daniel M V Santos

Full Text Available Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001 for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.

Leveraging gene-environment interactions and endotypes for asthma gene discovery

DEFF Research Database (Denmark)

Bønnelykke, Klaus; Ober, Carole

2016-01-01

, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs......Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also...... heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes...

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

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Takemoto, Kazuhiro; Aie, Kazuki

2017-05-25

Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

Study of obesity associated proopiomelanocortin gene polymorphism: Relation to metabolic profile and eating habits in a sample of obese Egyptian children and adolescents

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Farida El-Baz Mohamed

2017-01-01

Conclusion: This polymorphism was associated with higher fasting insulin levels in the obese patients only. These findings support the hypothesis that the melanocortin pathway may modulate glucose metabolism in obese subjects indicating a possible gene-environment interaction. POMC variant may be involved in the natural history of polygenic obesity, contributing to the link between type 2 diabetes and obesity.

Regulation of Nuclear Receptor Interacting Protein 1 (NRIP1) Gene Expression in Response to Weight Loss and Exercise in Humans

DEFF Research Database (Denmark)

De Marinis, Yang Z; Sun, Jiangming; Bompada, Pradeep

2017-01-01

Objective: Nuclear receptor interacting protein 1 (NRIP1) is an important energy regulator, but few studies have addressed its role in humans. This study investigated adipose tissue and skeletal muscle NRIP1 gene expression and serum levels in response to weight loss and exercise in humans. Methods...... network/module. Conclusions: NRIP1 gene expression and serum levels are strongly associated with metabolic states such as obesity, weight loss, different types of exercise, and peripheral tissue insulin resistance, potentially as a mediator of sedentary effects.......: In patients with obesity, adipose tissue NRIP1 mRNA expression increased during weight loss and weight maintenance and showed strong associations with metabolic markers and anthropometric parameters. Serum NRIP1 protein levels also increased after weight loss. In skeletal muscle, imposed rest increased NRIP1...

Hibiscus chlorotic ringspot virus coat protein upregulates sulfur metabolism genes for enhanced pathogen defense.

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Gao, Ruimin; Ng, Florence Kai Lin; Liu, Peng; Wong, Sek-Man

2012-12-01

In both Hibiscus chlorotic ringspot virus (HCRSV)-infected and HCRSV coat protein (CP) agroinfiltrated plant leaves, we showed that sulfur metabolism pathway related genes-namely, sulfite oxidase (SO), sulfite reductase, and adenosine 5'-phosphosulfate kinase-were upregulated. It led us to examine a plausible relationship between sulfur-enhanced resistance (SED) and HCRSV infection. We broadened an established method to include different concentrations of sulfur (0S, 1S, 2S, and 3S) to correlate them to symptom development of HCRSV-infected plants. We treated plants with glutathione and its inhibitor to verify the SED effect. Disease resistance was induced through elevated glutathione contents during HCRSV infection. The upregulation of SO was related to suppression of symptom development induced by sulfur treatment. In this study, we established that HCRSV-CP interacts with SO which, in turn, triggers SED and leads to enhanced plant resistance. Thus, we have discovered a new function of SO in the SED pathway. This is the first report to demonstrate that the interaction of a viral protein and host protein trigger SED in plants. It will be interesting if such interaction applies generally to other host-pathogen interactions that will lead to enhanced pathogen defense.

Coordinated Expression of Phosphoinositide Metabolic Genes during Development and Aging of Human Dorsolateral Prefrontal Cortex.

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Stanley I Rapoport

Full Text Available Phosphoinositides, lipid-signaling molecules, participate in diverse brain processes within a wide metabolic cascade.Gene transcriptional networks coordinately regulate the phosphoinositide cascade during human brain Development and Aging.We used the public BrainCloud database for human dorsolateral prefrontal cortex to examine age-related expression levels of 49 phosphoinositide metabolic genes during Development (0 to 20+ years and Aging (21+ years.We identified three groups of partially overlapping genes in each of the two intervals, with similar intergroup correlations despite marked phenotypic differences between Aging and Development. In each interval, ITPKB, PLCD1, PIK3R3, ISYNA1, IMPA2, INPPL1, PI4KB, and AKT1 are in Group 1, PIK3CB, PTEN, PIK3CA, and IMPA1 in Group 2, and SACM1L, PI3KR4, INPP5A, SYNJ1, and PLCB1 in Group 3. Ten of the genes change expression nonlinearly during Development, suggesting involvement in rapidly changing neuronal, glial and myelination events. Correlated transcription for some gene pairs likely is facilitated by colocalization on the same chromosome band.Stable coordinated gene transcriptional networks regulate brain phosphoinositide metabolic pathways during human Development and Aging.

Association testing to detect gene-gene interactions on sex chromosomes in trio data

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Yeonok eLee

2013-11-01

Full Text Available Autism Spectrum Disorder (ASD occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the significant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratification. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.

Determinants of human adipose tissue gene expression: impact of diet, sex, metabolic status, and cis genetic regulation.

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Nathalie Viguerie

2012-09-01

Full Text Available Weight control diets favorably affect parameters of the metabolic syndrome and delay the onset of diabetic complications. The adaptations occurring in adipose tissue (AT are likely to have a profound impact on the whole body response as AT is a key target of dietary intervention. Identification of environmental and individual factors controlling AT adaptation is therefore essential. Here, expression of 271 transcripts, selected for regulation according to obesity and weight changes, was determined in 515 individuals before, after 8-week low-calorie diet-induced weight loss, and after 26-week ad libitum weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently controlled AT gene expression. These analyses help understanding the relative importance of environmental and individual factors that control the expression of human AT genes and therefore may foster strategies aimed at improving AT function in metabolic diseases.

Learning-Induced Gene Expression in the Hippocampus Reveals a Role of Neuron -Astrocyte Metabolic Coupling in Long Term Memory

KAUST Repository

Tadi, Monika; Allaman, Igor; Lengacher, Sylvain; Grenningloh, Gabriele; Magistretti, Pierre J.

2015-01-01

We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte)-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA) paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4), alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.

Learning-Induced Gene Expression in the Hippocampus Reveals a Role of Neuron -Astrocyte Metabolic Coupling in Long Term Memory

KAUST Repository

Tadi, Monika

2015-10-29

We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte)-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA) paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4), alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.

Gene expression of transporters and phase I/II metabolic enzymes in murine small intestine during fasting

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van der Meijde Jolanda

2007-08-01

Full Text Available Abstract Background Fasting has dramatic effects on small intestinal transport function. However, little is known on expression of intestinal transport and phase I/II metabolism genes during fasting and the role the fatty acid-activated transcription factor PPARα may play herein. We therefore investigated the effects of fasting on expression of these genes using Affymetrix GeneChip MOE430A arrays and quantitative RT-PCR. Results After 24 hours of fasting, expression levels of 33 of the 253 analyzed transporter and phase I/II metabolism genes were changed. Upregulated genes were involved in transport of energy-yielding molecules in processes such as glycogenolysis (G6pt1 and mitochondrial and peroxisomal oxidation of fatty acids (Cact, Mrs3/4, Fatp2, Cyp4a10, Cyp4b1. Other induced genes were responsible for the inactivation of the neurotransmitter serotonin (Sert, Sult1d1, Dtd, Papst2, formation of eicosanoids (Cyp2j6, Cyp4a10, Cyp4b1, or for secretion of cholesterol (Abca1 and Abcg8. Cyp3a11, typically known because of its drug metabolizing capacity, was also increased. Fasting had no pronounced effect on expression of phase II metabolic enzymes, except for glutathione S-transferases which were down-regulated. Time course studies revealed that some genes were acutely regulated, whereas expression of other genes was only affected after prolonged fasting. Finally, we identified 8 genes that were PPARα-dependently upregulated upon fasting. Conclusion We have characterized the response to fasting on expression of transporters and phase I/II metabolic enzymes in murine small intestine. Differentially expressed genes are involved in a variety of processes, which functionally can be summarized as a increased oxidation of fat and xenobiotics, b increased cholesterol secretion, c increased susceptibility to electrophilic stressors, and d reduced intestinal motility. This knowledge increases our understanding of gut physiology, and may be of relevance

Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

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Sungyoung Lee

2012-12-01

Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Network graph analysis of gene-gene interactions in genome-wide association study data.

Science.gov (United States)

Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

2012-12-01

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Genetic polymorphisms and possible gene-gene interactions in metabolic and DNA repair genes: Effects on DNA damage

Czech Academy of Sciences Publication Activity Database

Naccarati, Alessio; Souček, P.; Štětina, R.; Haufroid, V.; Kumar, R.; Vodičková, Ludmila; Trtková, K.; Dušinská, M.; Hemminki, K.; Vodička, Pavel

2006-01-01

Roč. 593, 1-2 (2006), s. 22-31 ISSN 0027-5107 R&D Projects: GA ČR GA310/03/0437 Institutional research plan: CEZ:AV0Z5039906 Keywords : Single-strand breaks * Genetic polymorphisms * Metabolism Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.111, year: 2006

Double-Bottom Chaotic Map Particle Swarm Optimization Based on Chi-Square Test to Determine Gene-Gene Interactions

Science.gov (United States)

Yang, Cheng-Hong; Chang, Hsueh-Wei

2014-01-01

Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer. PMID:24895547

Inverse gene-for-gene interactions contribute additively to tan spot susceptibility in wheat.

Science.gov (United States)

Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis

2017-06-01

Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.

Adaptive evolution of mitochondrial energy metabolism genes associated with increased energy demand in flying insects.

Science.gov (United States)

Yang, Yunxia; Xu, Shixia; Xu, Junxiao; Guo, Yan; Yang, Guang

2014-01-01

Insects are unique among invertebrates for their ability to fly, which raises intriguing questions about how energy metabolism in insects evolved and changed along with flight. Although physiological studies indicated that energy consumption differs between flying and non-flying insects, the evolution of molecular energy metabolism mechanisms in insects remains largely unexplored. Considering that about 95% of adenosine triphosphate (ATP) is supplied by mitochondria via oxidative phosphorylation, we examined 13 mitochondrial protein-encoding genes to test whether adaptive evolution of energy metabolism-related genes occurred in insects. The analyses demonstrated that mitochondrial DNA protein-encoding genes are subject to positive selection from the last common ancestor of Pterygota, which evolved primitive flight ability. Positive selection was also found in insects with flight ability, whereas no significant sign of selection was found in flightless insects where the wings had degenerated. In addition, significant positive selection was also identified in the last common ancestor of Neoptera, which changed its flight mode from direct to indirect. Interestingly, detection of more positively selected genes in indirect flight rather than direct flight insects suggested a stronger selective pressure in insects having higher energy consumption. In conclusion, mitochondrial protein-encoding genes involved in energy metabolism were targets of adaptive evolution in response to increased energy demands that arose during the evolution of flight ability in insects.

The Gene-Lifestyle Interaction on Leptin Sensitivity and Lipid Metabolism in Adults: A Population Based Study

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Harry Freitag Luglio

2017-07-01

Full Text Available Background: Obesity has been associated with leptin resistance and this might be caused by genetic factors. The aim of this study was to investigate the gene-lifestyle interaction between −866G/A UCP2 (uncoupling protein 2 gene polymorphism, dietary intake and leptin in a population based study. Methods: This is a cross sectional study conducted in adults living at urban area of Yogyakarta, Indonesia. Data of adiposity, lifestyle, triglyceride, high density lipoprotein (HDL cholesterol, leptin and UCP2 gene polymorphism were obtained in 380 men and female adults. Results: UCP2 gene polymorphism was not significantly associated with adiposity, leptin, triglyceride, HDL cholesterol, dietary intake and physical activity (all p > 0.05. Leptin was lower in overweight subjects with AA + GA genotypes than those with GG genotype counterparts (p = 0.029. In subjects with AA + GA genotypes there was a negative correlation between leptin concentration (r = −0.324; p < 0.0001 and total energy intake and this correlation was not seen in GG genotype (r = −0.111; p = 0.188. Conclusions: In summary, we showed how genetic variation in −866G/A UCP2 affected individual response to leptin production. AA + GA genotype had a better leptin sensitivity shown by its response in dietary intake and body mass index (BMI and this explained the protective effect of A allele to obesity.

Novel Interactions between Gut Microbiome and Host Drug-Processing Genes Modify the Hepatic Metabolism of the Environmental Chemicals Polybrominated Diphenyl Ethers

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Li, Cindy Yanfei; Lee, Soowan; Cade, Sara; Kuo, Li-Jung; Schultz, Irvin R.; Bhatt, Deepak K.; Prasad, Bhagwat; Bammler, Theo K.; Cui, Julia Yue

2017-09-01

The gut microbiome is a novel frontier in xenobiotic metabolism. Polybrominated diphenyl ethers (PBDEs), especially BDE-47 and BDE-99, are among the most abundant and persistent environmental contaminants that produce a variety of toxicities. Little is known about how the gut microbiome affects the hepatic metabolism of PBDEs and the PBDE-mediated regulation of drug-processing genes (DPGs) in vivo. The goal of this study was to determine the role of gut microbiome in modulating the hepatic biotransformation of PBDEs. Nine-week-old male C57BL/6J conventional (CV) or germ free (GF) mice were treated with vehicle, BDE-47 or BDE-99 (100 μmol/kg) for four days. Following BDE-47 treatment, GF mice had higher level of 5-OH-BDE-47 but lower levels of 4 other metabolites in liver than CV mice; whereas following BDE-99 treatment, GF mice had lower levels of 4 minor metabolites in liver than CV mice. RNA- Seq demonstrated that the hepatic expression of DPGs was regulated by both PBDEs and enterotypes. Under basal condition, the lack of gut microbiome up-regulated the Cyp2c subfamily but down-regulated the Cyp3a subfamily. Following PBDE exposure, certain DPGs were differentially regulated by PBDEs in a gut microbiome-dependent manner. Interestingly, the lack of gut microbiome augmented PBDE-mediated up- regulation of many DPGs, such as Cyp1a2 and Cyp3a11 in mouse liver, which was further confirmed by targeted metabolomics. The lack of gut microbiome also augmented the Cyp3a enzyme activity in liver. In conclusion, our study has unveiled a novel interaction between gut microbiome and the hepatic biotransformation of PBDEs.

A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype

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Wallace Helen M

2006-10-01

Full Text Available Abstract Background The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required because of the potential importance of gene-gene interactions (epistasis, gene-environment interactions, and conditions that break the 'equal environments' assumption for monozygotic and dizygotic twins. Method A new model for gene-gene and gene-environment interactions is developed that abandons the assumptions of the classical twin study, including Fisher's (1918 assumption that genes act as risk factors for common traits in a manner necessarily dominated by an additive polygenic term. Provided there are no confounders, the model can be used to implement a top-down approach to quantifying the potential utility of genetic prediction and prevention, using twin, family and environmental data. The results describe a solution space for each disease or trait, which may or may not include the classical twin study result. Each point in the solution space corresponds to a different model of genotypic risk and gene-environment interaction. Conclusion The results show that the potential for reducing the incidence of common diseases using environmental interventions targeted by genotype may be limited, except in special cases. The model also confirms that the importance of an individual's genotype in determining their risk of complex diseases tends to be exaggerated by the classical twin studies method, owing to the 'equal environments' assumption and the assumption of no gene-environment interaction. In addition, if phenotypes are genetically robust, because of epistasis

Gene-environment interaction and biological monitoring of occupational exposures

International Nuclear Information System (INIS)

Hirvonen, Ari

2005-01-01

Biological monitoring methods and biological limit values applied in occupational and environmental medicine have been traditionally developed on the assumption that individuals do not differ significantly in their biotransformation capacities. It has become clear, however, that this is not the case, but wide inter-individual differences exist in the metabolism of chemicals. Integration of the data on individual metabolic capacity in biological monitoring studies is therefore anticipated to represent a significant refinement of the currently used methods. We have recently conducted several biological monitoring studies on occupationally exposed subjects, which have included the determination of the workers' genotypes for the metabolic genes of potential importance for a given chemical exposure. The exposure levels have been measured by urine metabolites, adducts in blood macromolecules, and cytogenetic alterations in lymphocytes. Our studies indicate that genetic polymorphisms in metabolic genes may indeed be important modifiers of individual biological monitoring results of, e.g., carbon disulphide and styrene. The information is anticipated to be useful in insuring that the workplace is safe for everyone, including the most sensitive individuals. This knowledge could also be useful to occupational physicians, industrial hygienists, and regulatory bodies in charge of defining acceptable exposure limits for environmental and/or occupational pollutants

GABA metabolism pathway genes, UGA1 and GAD1, regulate replicative lifespan in Saccharomycescerevisiae

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Kamei, Yuka; Tamura, Takayuki [Department of Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 (Japan); Yoshida, Ryo [Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871 (Japan); Ohta, Shinji [Department of Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 (Japan); Fukusaki, Eiichiro [Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871 (Japan); Mukai, Yukio, E-mail: y_mukai@nagahama-i-bio.ac.jp [Department of Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 (Japan)

2011-04-01

Highlights: {yields}We demonstrate that two genes in the yeast GABA metabolism pathway affect aging. {yields} Deletion of the UGA1 or GAD1 genes extends replicative lifespan. {yields} Addition of GABA to wild-type cultures has no effect on lifespan. {yields} Intracellular GABA levels do not differ in longevity mutants and wild-type cells. {yields} Levels of tricarboxylic acid cycle intermediates positively correlate with lifespan. -- Abstract: Many of the genes involved in aging have been identified in organisms ranging from yeast to human. Our previous study showed that deletion of the UGA3 gene-which encodes a zinc-finger transcription factor necessary for {gamma}-aminobutyric acid (GABA)-dependent induction of the UGA1 (GABA aminotransferase), UGA2 (succinate semialdehyde dehydrogenase), and UGA4 (GABA permease) genes-extends replicative lifespan in the budding yeast Saccharomycescerevisiae. Here, we found that deletion of UGA1 lengthened the lifespan, as did deletion of UGA3; in contrast, strains with UGA2 or UGA4 deletions exhibited no lifespan extension. The {Delta}uga1 strain cannot deaminate GABA to succinate semialdehyde. Deletion of GAD1, which encodes the glutamate decarboxylase that converts glutamate into GABA, also increased lifespan. Therefore, two genes in the GABA metabolism pathway, UGA1 and GAD1, were identified as aging genes. Unexpectedly, intracellular GABA levels in mutant cells (except for {Delta}uga2 cells) did not differ from those in wild-type cells. Addition of GABA to culture media, which induces transcription of the UGA structural genes, had no effect on replicative lifespan of wild-type cells. Multivariate analysis of {sup 1}H nuclear magnetic resonance spectra for the whole-cell metabolite levels demonstrated a separation between long-lived and normal-lived strains. Gas chromatography-mass spectrometry analysis of identified metabolites showed that levels of tricarboxylic acid cycle intermediates positively correlated with lifespan

GABA metabolism pathway genes, UGA1 and GAD1, regulate replicative lifespan in Saccharomycescerevisiae

International Nuclear Information System (INIS)

Kamei, Yuka; Tamura, Takayuki; Yoshida, Ryo; Ohta, Shinji; Fukusaki, Eiichiro; Mukai, Yukio

2011-01-01

Highlights: →We demonstrate that two genes in the yeast GABA metabolism pathway affect aging. → Deletion of the UGA1 or GAD1 genes extends replicative lifespan. → Addition of GABA to wild-type cultures has no effect on lifespan. → Intracellular GABA levels do not differ in longevity mutants and wild-type cells. → Levels of tricarboxylic acid cycle intermediates positively correlate with lifespan. -- Abstract: Many of the genes involved in aging have been identified in organisms ranging from yeast to human. Our previous study showed that deletion of the UGA3 gene-which encodes a zinc-finger transcription factor necessary for γ-aminobutyric acid (GABA)-dependent induction of the UGA1 (GABA aminotransferase), UGA2 (succinate semialdehyde dehydrogenase), and UGA4 (GABA permease) genes-extends replicative lifespan in the budding yeast Saccharomycescerevisiae. Here, we found that deletion of UGA1 lengthened the lifespan, as did deletion of UGA3; in contrast, strains with UGA2 or UGA4 deletions exhibited no lifespan extension. The Δuga1 strain cannot deaminate GABA to succinate semialdehyde. Deletion of GAD1, which encodes the glutamate decarboxylase that converts glutamate into GABA, also increased lifespan. Therefore, two genes in the GABA metabolism pathway, UGA1 and GAD1, were identified as aging genes. Unexpectedly, intracellular GABA levels in mutant cells (except for Δuga2 cells) did not differ from those in wild-type cells. Addition of GABA to culture media, which induces transcription of the UGA structural genes, had no effect on replicative lifespan of wild-type cells. Multivariate analysis of 1 H nuclear magnetic resonance spectra for the whole-cell metabolite levels demonstrated a separation between long-lived and normal-lived strains. Gas chromatography-mass spectrometry analysis of identified metabolites showed that levels of tricarboxylic acid cycle intermediates positively correlated with lifespan extension. These results strongly suggest

Disturbed Glucose Metabolism in Rat Neurons Exposed to Cerebrospinal Fluid Obtained from Multiple Sclerosis Subjects

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Deepali Mathur

2017-12-01

Full Text Available Axonal damage is widely accepted as a major cause of permanent functional disability in Multiple Sclerosis (MS. In relapsing-remitting MS, there is a possibility of remyelination by myelin producing cells and restoration of neurological function. The purpose of this study was to delineate the pathophysiological mechanisms underpinning axonal injury through hitherto unknown factors present in cerebrospinal fluid (CSF that may regulate axonal damage, remyelinate the axon and make functional recovery possible. We employed primary cultures of rat unmyelinated cerebellar granule neurons and treated them with CSF obtained from MS and Neuromyelitis optica (NMO patients. We performed microarray gene expression profiling to study changes in gene expression in treated neurons as compared to controls. Additionally, we determined the influence of gene-gene interaction upon the whole metabolic network in our experimental conditions using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING program. Our findings revealed the downregulated expression of genes involved in glucose metabolism in MS-derived CSF-treated neurons and upregulated expression of genes in NMO-derived CSF-treated neurons. We conclude that factors in the CSF of these patients caused a perturbation in metabolic gene(s expression and suggest that MS appears to be linked with metabolic deformity.

Altered Levels of Aroma and Volatiles by Metabolic Engineering of Shikimate Pathway Genes in Tomato Fruits

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Vered Tzin

2015-06-01

Full Text Available The tomato (Solanum lycopersicum fruit is an excellent source of antioxidants, dietary fibers, minerals and vitamins and therefore has been referred to as a “functional food”. Ripe tomato fruits produce a large number of specialized metabolites including volatile organic compounds. These volatiles serve as key components of the tomato fruit flavor, participate in plant pathogen and herbivore defense, and are used to attract seed dispersers. A major class of specialized metabolites is derived from the shikimate pathway followed by aromatic amino acid biosynthesis of phenylalanine, tyrosine and tryptophan. We attempted to modify tomato fruit flavor by overexpressing key regulatory genes in the shikimate pathway. Bacterial genes encoding feedback-insensitive variants of 3-Deoxy-D-Arabino-Heptulosonate 7-Phosphate Synthase (DAHPS; AroG209-9 and bi-functional Chorismate Mutase/Prephenate Dehydratase (CM/PDT; PheA12 were expressed under the control of a fruit-specific promoter. We crossed these transgenes to generate tomato plants expressing both the AroG209 and PheA12 genes. Overexpression of the AroG209-9 gene had a dramatic effect on the overall metabolic profile of the fruit, including enhanced levels of multiple volatile and non-volatile metabolites. In contrast, the PheA12 overexpression line exhibited minor metabolic effects compared to the wild type fruit. Co-expression of both the AroG209-9 and PheA12 genes in tomato resulted overall in a similar metabolic effect to that of expressing only the AroG209-9 gene. However, the aroma ranking attributes of the tomato fruits from PheA12//AroG209-9 were unique and different from those of the lines expressing a single gene, suggesting a contribution of the PheA12 gene to the overall metabolic profile. We suggest that expression of bacterial genes encoding feedback-insensitive enzymes of the shikimate pathway in tomato fruits provides a useful metabolic engineering tool for the modification of

Gene expression in plant lipid metabolism in Arabidopsis seedlings.

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An-Shan Hsiao

Full Text Available Events in plant lipid metabolism are important during seedling establishment. As it has not been experimentally verified whether lipid metabolism in 2- and 5-day-old Arabidopsis thaliana seedlings is diurnally-controlled, quantitative real-time PCR analysis was used to investigate the expression of target genes in acyl-lipid transfer, β-oxidation and triacylglycerol (TAG synthesis and hydrolysis in wild-type Arabidopsis WS and Col-0. In both WS and Col-0, ACYL-COA-BINDING PROTEIN3 (ACBP3, DIACYLGLYCEROL ACYLTRANSFERASE1 (DGAT1 and DGAT3 showed diurnal control in 2- and 5-day-old seedlings. Also, COMATOSE (CTS was diurnally regulated in 2-day-old seedlings and LONG-CHAIN ACYL-COA SYNTHETASE6 (LACS6 in 5-day-old seedlings in both WS and Col-0. Subsequently, the effect of CIRCADIAN CLOCK ASSOCIATED1 (CCA1 and LATE ELONGATED HYPOCOTYL (LHY from the core clock system was examined using the cca1lhy mutant and CCA1-overexpressing (CCA1-OX lines versus wild-type WS and Col-0, respectively. Results revealed differential gene expression in lipid metabolism between 2- and 5-day-old mutant and wild-type WS seedlings, as well as between CCA1-OX and wild-type Col-0. Of the ACBPs, ACBP3 displayed the most significant changes between cca1lhy and WS and between CCA1-OX and Col-0, consistent with previous reports that ACBP3 is greatly affected by light/dark cycling. Evidence of oil body retention in 4- and 5-day-old seedlings of the cca1lhy mutant in comparison to WS indicated the effect of cca1lhy on storage lipid reserve mobilization. Lipid profiling revealed differences in primary lipid metabolism, namely in TAG, fatty acid methyl ester and acyl-CoA contents amongst cca1lhy, CCA1-OX, and wild-type seedlings. Taken together, this study demonstrates that lipid metabolism is subject to diurnal regulation in the early stages of seedling development in Arabidopsis.

Gene-physical activity interactions and their impact on diabetes

DEFF Research Database (Denmark)

Oskari Kilpeläinen, Tuomas; Franks, Paul W

2014-01-01

to an equal bout of physical activity. Individuals with specific genetic profiles are also expected to be more responsive to the beneficial effects of physical activity in the prevention of type 2 diabetes. Identification of such gene-physical activity interactions could give new insights into the biological...... the reader to the recent advances in the genetics of type 2 diabetes, summarize the current evidence on gene-physical activity interactions in relation to type 2 diabetes, and outline how information on gene-physical activity interactions might help improve the prevention and treatment of type 2 diabetes....... Finally, we will discuss the existing and emerging strategies that might enhance our ability to identify and exploit gene-physical activity interactions in the etiology of type 2 diabetes. © 2014 S. Karger AG, Basel....

Learning-Induced Gene Expression in the Hippocampus Reveals a Role of Neuron -Astrocyte Metabolic Coupling in Long Term Memory.

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Monika Tadi

Full Text Available We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4, alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.

Molecular effect of fenofibrate on PBMC gene transcription related to lipid metabolism in patients with metabolic syndrome.

Science.gov (United States)

Moreno-Indias, I; Tinahones, F J; Clemente-Postigo, M; Castellano-Castillo, D; Fernández-García, J C; Macias-Gonzalez, M; Queipo-Ortuño, M I; Cardona, F

2017-06-01

Both fasting and postprandial hypertriglyceridaemia are considered independent risk factors for atherosclerosis. Treatment of hypertriglyceridaemia is based on fibrates, which activate the peroxisome proliferator-activated receptor alpha (PPARα). However, the metabolic pathways that activate or inhibit fibrates, and how the postprandial triglyceride levels are modified, have not yet been fully described. Accordingly, the aim of this study was to determine the feasibility of peripheral blood mononuclear cells (PBMC) to study the effects of fenofibrate in patients with the metabolic syndrome. A fat overload was given to 50 patients before and after treatment with fenofibrate for 3 months. Anthropometric and biochemical variables as well as gene expression in PBMC were analysed. After treatment with fenofibrate, we observed a decrease in both baseline and postprandial (3 h after the fat overload) levels of serum triglycerides, cholesterol and uric acid and an increase in HDL cholesterol and apolipoprotein AI levels. After treatment, there was also a rise in PPARα and RXRα expression and changes in genes regulated by PPARα, both baseline and postprandial. Furthermore, in vitro experiments showed that a PPARα agonist changed the expression of genes related with lipid metabolism. Treatment with fenofibrate reduced fasting and postprandial serum triglyceride levels, possibly through a mechanism related with an increase in the expression of RXRα and PPARα, by activating the pathways involved in the uptake and degradation of triglycerides and increasing the synthesis of apolipoprotein. These results suggest that PBMC may be useful for the easy study of fenofibrate actions. © 2017 John Wiley & Sons Ltd.

PPAR{gamma} regulates the expression of cholesterol metabolism genes in alveolar macrophages

Energy Technology Data Exchange (ETDEWEB)

Baker, Anna D.; Malur, Anagha; Barna, Barbara P.; Kavuru, Mani S. [Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, East Carolina University (United States); Malur, Achut G. [Department of Microbiology and Immunology, East Carolina University (United States); Thomassen, Mary Jane, E-mail: thomassenm@ecu.edu [Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, East Carolina University (United States); Department of Microbiology and Immunology, East Carolina University (United States)

2010-03-19

Peroxisome proliferator-activated receptor-gamma (PPAR{gamma}) is a nuclear transcription factor involved in lipid metabolism that is constitutively expressed in the alveolar macrophages of healthy individuals. PPAR{gamma} has recently been implicated in the catabolism of surfactant by alveolar macrophages, specifically the cholesterol component of surfactant while the mechanism remains unclear. Studies from other tissue macrophages have shown that PPAR{gamma} regulates cholesterol influx, efflux, and metabolism. PPAR{gamma} promotes cholesterol efflux through the liver X receptor-alpha (LXR{alpha}) and ATP-binding cassette G1 (ABCG1). We have recently shown that macrophage-specific PPAR{gamma} knockout (PPAR{gamma} KO) mice accumulate cholesterol-laden alveolar macrophages that exhibit decreased expression of LXR{alpha} and ABCG1 and reduced cholesterol efflux. We hypothesized that in addition to the dysregulation of these cholesterol efflux genes, the expression of genes involved in cholesterol synthesis and influx was also dysregulated and that replacement of PPAR{gamma} would restore regulation of these genes. To investigate this hypothesis, we have utilized a Lentivirus expression system (Lenti-PPAR{gamma}) to restore PPAR{gamma} expression in the alveolar macrophages of PPAR{gamma} KO mice. Our results show that the alveolar macrophages of PPAR{gamma} KO mice have decreased expression of key cholesterol synthesis genes and increased expression of cholesterol receptors CD36 and scavenger receptor A-I (SRA-I). The replacement of PPAR{gamma} (1) induced transcription of LXR{alpha} and ABCG1; (2) corrected suppressed expression of cholesterol synthesis genes; and (3) enhanced the expression of scavenger receptors CD36. These results suggest that PPAR{gamma} regulates cholesterol metabolism in alveolar macrophages.

Thermo-Regulation of Genes Mediating Motility and Plant Interactions in Pseudomonas syringae

Science.gov (United States)

Hockett, Kevin L.; Burch, Adrien Y.; Lindow, Steven E.

2013-01-01

Pseudomonas syringae is an important phyllosphere colonist that utilizes flagellum-mediated motility both as a means to explore leaf surfaces, as well as to invade into leaf interiors, where it survives as a pathogen. We found that multiple forms of flagellum-mediated motility are thermo-suppressed, including swarming and swimming motility. Suppression of swarming motility occurs between 28° and 30°C, which coincides with the optimal growth temperature of P. syringae. Both fliC (encoding flagellin) and syfA (encoding a non-ribosomal peptide synthetase involved in syringafactin biosynthesis) were suppressed with increasing temperature. RNA-seq revealed 1440 genes of the P. syringae genome are temperature sensitive in expression. Genes involved in polysaccharide synthesis and regulation, phage and IS elements, type VI secretion, chemosensing and chemotaxis, translation, flagellar synthesis and motility, and phytotoxin synthesis and transport were generally repressed at 30°C, while genes involved in transcriptional regulation, quaternary ammonium compound metabolism and transport, chaperone/heat shock proteins, and hypothetical genes were generally induced at 30°C. Deletion of flgM, a key regulator in the transition from class III to class IV gene expression, led to elevated and constitutive expression of fliC regardless of temperature, but did not affect thermo-regulation of syfA. This work highlights the importance of temperature in the biology of P. syringae, as many genes encoding traits important for plant-microbe interactions were thermo-regulated. PMID:23527276

Gene-Environment Interaction in Parkinson's Disease: Coffee, ADORA2A, and CYP1A2.

Science.gov (United States)

Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina F; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S; Ritz, Beate

2016-01-01

Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine; thus, gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. In a population-based case-control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and gender-matched controls), we assessed interactions between lifetime coffee consumption and 3 polymorphisms in ADORA2A and CYP1A2 for all subjects, and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction = 0.66 [95% CI 0.46-0.94], p = 0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enroll prevalent PD cases. © 2017 S. Karger AG, Basel.

Analysis of Polymorphism of Angiotensin System Genes (ACE, AGTR1, and AGT) and Gene ITGB3 in Patients with Arterial Hypertension in Combination with Metabolic Syndrome.

Science.gov (United States)

Zotova, T Yu; Kubanova, A P; Azova, M M; Aissa, A Ait; Gigani, O O; Frolov, V A

2016-07-01

Changes in the frequencies of genotypes and mutant alleles of ACE, AGTR1, AGT, and ITGB3 genes were analyzed in patients with arterial hypertension coupled with metabolic syndrome (N=15) and compared with population data and corresponding parameters in patients with isolated hypertension (N=15). Increased frequency of genotype ID of ACE gene (hypertension predictor) was confirmed for both groups. In case of isolated hypertension, M235M genotype (gene AGT) was more frequent, in case of hypertension combined with metabolic syndrome, the frequency of genotypes A1166C and C1166C of the gene AGTR1 was higher in comparison with population data. Comparison of mutant allele frequencies in the two groups showed that at the 90% significance level allele T of the AGT gene was more frequent in hypertension coupled with metabolic syndrome (OR=1.26) and genotype A1166A of the AGTR1 gene was more frequent in the group with isolated hypertension.

Plant-endophytes interaction influences the secondary metabolism in Echinacea purpurea (L.) Moench: an in vitro model.

Science.gov (United States)

Maggini, Valentina; De Leo, Marinella; Mengoni, Alessio; Gallo, Eugenia Rosaria; Miceli, Elisangela; Reidel, Rose Vanessa Bandeira; Biffi, Sauro; Pistelli, Luisa; Fani, Renato; Firenzuoli, Fabio; Bogani, Patrizia

2017-12-05

The influence of the interaction(s) between the medicinal plant Echinacea purpurea (L.) Moench and its endophytic communities on the production of alkamides is investigated. To mimic the in vivo conditions, we have set up an infection model of axenic in vitro E. purpurea plants inoculated with a pool of bacterial strains isolated from the E. purpurea stems and leaves. Here we show different alkamide levels between control (not-inoculated) and inoculated plants, suggesting that the alkamide biosynthesis may be modulated by the bacterial infection. Then, we have analysed the branched-chain amino acids (BCCA) decarboxylase gene (GenBank Accession #LT593930; the enzymatic source for the amine moiety formation of the alkamides) expression patterns. The expression profile shows a higher expression level in the inoculated E. purpurea tissues than in the control ones. These results suggest that the plant-endophyte interaction can influence plant secondary metabolism affecting the therapeutic properties of E. purpurea.

Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model

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Ingkasuwan Papapit

2012-08-01

Full Text Available Abstract Background Starch serves as a temporal storage of carbohydrates in plant leaves during day/night cycles. To study transcriptional regulatory modules of this dynamic metabolic process, we conducted gene regulation network analysis based on small-sample inference of graphical Gaussian model (GGM. Results Time-series significant analysis was applied for Arabidopsis leaf transcriptome data to obtain a set of genes that are highly regulated under a diurnal cycle. A total of 1,480 diurnally regulated genes included 21 starch metabolic enzymes, 6 clock-associated genes, and 106 transcription factors (TF. A starch-clock-TF gene regulation network comprising 117 nodes and 266 edges was constructed by GGM from these 133 significant genes that are potentially related to the diurnal control of starch metabolism. From this network, we found that β-amylase 3 (b-amy3: At4g17090, which participates in starch degradation in chloroplast, is the most frequently connected gene (a hub gene. The robustness of gene-to-gene regulatory network was further analyzed by TF binding site prediction and by evaluating global co-expression of TFs and target starch metabolic enzymes. As a result, two TFs, indeterminate domain 5 (AtIDD5: At2g02070 and constans-like (COL: At2g21320, were identified as positive regulators of starch synthase 4 (SS4: At4g18240. The inference model of AtIDD5-dependent positive regulation of SS4 gene expression was experimentally supported by decreased SS4 mRNA accumulation in Atidd5 mutant plants during the light period of both short and long day conditions. COL was also shown to positively control SS4 mRNA accumulation. Furthermore, the knockout of AtIDD5 and COL led to deformation of chloroplast and its contained starch granules. This deformity also affected the number of starch granules per chloroplast, which increased significantly in both knockout mutant lines. Conclusions In this study, we utilized a systematic approach of microarray

Identification of human disease genes from interactome network using graphlet interaction.

Directory of Open Access Journals (Sweden)

Xiao-Dong Wang

Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

Science.gov (United States)

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

A gene-environment interaction analysis of plasma selenium with prevalent and incident diabetes: The Hortega study.

Science.gov (United States)

Galan-Chilet, Inmaculada; Grau-Perez, Maria; De Marco, Griselda; Guallar, Eliseo; Martin-Escudero, Juan Carlos; Dominguez-Lucas, Alejandro; Gonzalez-Manzano, Isabel; Lopez-Izquierdo, Raul; Briongos-Figuero, Laisa Socorro; Redon, Josep; Chaves, Felipe Javier; Tellez-Plaza, Maria

2017-08-01

Selenium and single-nucleotide-polymorphisms in selenoprotein genes have been associated to diabetes. However, the interaction of selenium with genetic variation in diabetes and oxidative stress-related genes has not been evaluated as a potential determinant of diabetes risk. We evaluated the cross-sectional and prospective associations of plasma selenium concentrations with type 2 diabetes, and the interaction of selenium concentrations with genetic variation in candidate polymorphisms, in a representative sample of 1452 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.2µg/L. 120 participants had diabetes at baseline. Among diabetes-free participants who were not lost during the follow-up (N=1234), 75 developed diabetes over time. The multivariable adjusted odds ratios (95% confidence interval) for diabetes prevalence comparing the second and third to the first tertiles of plasma selenium levels were 1.80 (1.03, 3.14) and 1.97 (1.14, 3.41), respectively. The corresponding hazard ratios (95% CI) for diabetes incidence were 1.76 (0.96, 3.22) and 1.80 (0.98, 3.31), respectively. In addition, we observed significant interactions between selenium and polymorphisms in PPARGC1A, and in genes encoding mitochondrial proteins, such as BCS1L and SDHA, and suggestive interactions of selenium with other genes related to selenoproteins and redox metabolism. Plasma selenium was positively associated with prevalent and incident diabetes. While the statistical interactions of selenium with polymorphisms involved in regulation of redox and insulin signaling pathways provide biological plausibility to the positive associations of selenium with diabetes, further research is needed to elucidate the causal pathways underlying these associations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

C282Y-HFE gene variant affects cholesterol metabolism in human neuroblastoma cells.

Science.gov (United States)

Ali-Rahmani, Fatima; Huang, Michael A; Schengrund, C-L; Connor, James R; Lee, Sang Y

2014-01-01

Although disruptions in the maintenance of iron and cholesterol metabolism have been implicated in several cancers, the association between variants in the HFE gene that is associated with cellular iron uptake and cholesterol metabolism has not been studied. The C282Y-HFE variant is a risk factor for different cancers, is known to affect sphingolipid metabolism, and to result in increased cellular iron uptake. The effect of this variant on cholesterol metabolism and its possible relevance to cancer phenotype was investigated using wild type (WT) and C282Y-HFE transfected human neuroblastoma SH-SY5Y cells. Expression of C282Y-HFE in SH-SY5Y cells resulted in a significant increase in total cholesterol as well as increased transcription of a number of genes involved in its metabolism compared to cells expressing WT-HFE. The marked increase in expression of NPC1L1 relative to that of most other genes, was accompanied by a significant increase in expression of NPC1, a protein that functions in cholesterol uptake by cells. Because inhibitors of cholesterol metabolism have been proposed to be beneficial for treating certain cancers, their effect on the viability of C282Y-HFE neuroblastoma cells was ascertained. C282Y-HFE cells were significantly more sensitive than WT-HFE cells to U18666A, an inhibitor of desmosterol Δ24-reductase the enzyme catalyzing the last step in cholesterol biosynthesis. This was not seen for simvastatin, ezetimibe, or a sphingosine kinase inhibitor. These studies indicate that cancers presenting in carriers of the C282Y-HFE allele might be responsive to treatment designed to selectively reduce cholesterol content in their tumor cells.

Polychlorinated Biphenyl-Xenobiotic Nuclear Receptor Interactions Regulate Energy Metabolism, Behavior, and Inflammation in Non-alcoholic-Steatohepatitis.

Science.gov (United States)

Wahlang, Banrida; Prough, Russell A; Falkner, K Cameron; Hardesty, Josiah E; Song, Ming; Clair, Heather B; Clark, Barbara J; States, J Christopher; Arteel, Gavin E; Cave, Matthew C

2016-02-01

Polychlorinated biphenyls (PCBs) are environmental pollutants associated with non-alcoholic-steatohepatitis (NASH), diabetes, and obesity. We previously demonstrated that the PCB mixture, Aroclor 1260, induced steatohepatitis and activated nuclear receptors in a diet-induced obesity mouse model. This study aims to evaluate PCB interactions with the pregnane-xenobiotic receptor (Pxr: Nr1i2) and constitutive androstane receptor (Car: Nr1i3) in NASH. Wild type C57Bl/6 (WT), Pxr(-/-) and Car(-/-) mice were fed the high fat diet (42% milk fat) and exposed to a single dose of Aroclor 1260 (20 mg/kg) in this 12-week study. Metabolic phenotyping and analysis of serum, liver, and adipose was performed. Steatohepatitis was pathologically similar in all Aroclor-exposed groups, while Pxr(-/-) mice displayed higher basal pro-inflammatory cytokine levels. Pxr repressed Car expression as evident by increased basal Car/Cyp2b10 expression in Pxr(-/-) mice. Both Pxr(-/-) and Car(-/-) mice showed decreased basal respiratory exchange rate (RER) consistent with preferential lipid metabolism. Aroclor increased RER and carbohydrate metabolism, associated with increased light cycle activity in both knockouts, and decreased food consumption in the Car(-/-) mice. Aroclor exposure improved insulin sensitivity in WT mice but not glucose tolerance. The Aroclor-exposed, Pxr(-/-) mice displayed increased gluconeogenic gene expression. Lipid-oxidative gene expression was higher in WT and Pxr(-/-) mice although RER was not changed, suggesting PCB-mediated mitochondrial dysfunction. Therefore, Pxr and Car regulated inflammation, behavior, and energy metabolism in PCB-mediated NASH. Future studies should address the 'off-target' effects of PCBs in steatohepatitis. Published by Oxford University Press on behalf of the Society of Toxicology 2015. This work is written by US Government employees and is in the public domain in the US.

Epigenetics and a new look on metabolic syndrome

Czech Academy of Sciences Publication Activity Database

Kuneš, Jaroslav; Vaněčková, Ivana; Mikulášková, Barbora; Behuliak, Michal; Maletínská, L.; Zicha, Josef

2015-01-01

Roč. 64, č. 5 (2015), s. 611-620 ISSN 0862-8408 R&D Projects: GA MZd(CZ) NV15-25396A; GA ČR(CZ) GA15-08679S Institutional support: RVO:67985823 Keywords : metabolic syndrome * epigenetic s * transgenerational inheritance * gene-environmental interactions * obesity * hypertension Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition Impact factor: 1.643, year: 2015

Effects of castration on expression of lipid metabolism genes in the liver of korean cattle.

Science.gov (United States)

Baik, Myunggi; Nguyen, Trang Hoa; Jeong, Jin Young; Piao, Min Yu; Kang, Hyeok Joong

2015-01-01

Castration induces the accumulation of body fat and deposition of intramuscular fat in Korean cattle, resulting in improved beef quality. However, little is known about the metabolic adaptations in the liver following castration. To understand changes in lipid metabolism following castration, hepatic expression levels of lipid metabolism genes were compared between Korean bulls and steers. Steers had higher (pcastration of bulls. However, we found no differences in the hepatic expression levels of genes related to triglyceride synthesis (mitochondrial glycerol-3-phosphate acyltransferase, diacylglycerol O-acyltransferase 1 and 2) and fatty acid (FA) oxidation (carnitine palmitoyltransferase 1A, C-4 to C-12 straight chain acyl-CoA dehydrogenase, very long chain acyl-CoA dehydrogenase) between bulls and steers. No differences in gene expression for very-low-density lipoprotein (VLDL) secretion, including apolipoprotein B mRNA and microsomal triglyceride transfer protein (MTTP) protein, were observed in the liver although MTTP mRNA levels were higher in steers compared to bulls. In conclusion, FA synthesis may contribute to increased hepatic lipid deposition in steers following castration. However, hepatic lipid metabolism, including triglyceride synthesis, FA oxidation, and VLDL secretion, was not significantly altered by castration. Our results suggest that hepatic lipid metabolism does not significantly contribute to increased body fat deposition in steers following castration.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

Directory of Open Access Journals (Sweden)

Brian R Granger

2016-04-01

Full Text Available The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space, a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

Science.gov (United States)

Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-04-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

The Association of Polymorphisms in Leptin/Leptin Receptor Genes and Ghrelin/Ghrelin Receptor Genes With Overweight/Obesity and the Related Metabolic Disturbances: A Review

OpenAIRE

Ghalandari; Hosseini-Esfahani; Mirmiran

2015-01-01

Context Leptin and ghrelin are two important appetite and energy balance-regulating peptides. Common polymorphisms in the genes coding these peptides and their related receptors are shown to be associated with body weight, different markers of obesity and metabolic abnormalities. This review article aims to investigate the association of common polymorphisms of these genes with overweight/obesity and the metabolic disturbances related to it. E...

Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

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Trey K Sato

2016-10-01

Full Text Available The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3, a component of MAP Kinase (MAPK signaling (HOG1, a regulator of Protein Kinase A (PKA signaling (IRA2, and a scaffolding protein for mitochondrial iron-sulfur (Fe-S cluster biogenesis (ISU1. Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.

Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

Science.gov (United States)

Sato, Trey K; Tremaine, Mary; Parreiras, Lucas S; Hebert, Alexander S; Myers, Kevin S; Higbee, Alan J; Sardi, Maria; McIlwain, Sean J; Ong, Irene M; Breuer, Rebecca J; Avanasi Narasimhan, Ragothaman; McGee, Mick A; Dickinson, Quinn; La Reau, Alex; Xie, Dan; Tian, Mingyuan; Reed, Jennifer L; Zhang, Yaoping; Coon, Joshua J; Hittinger, Chris Todd; Gasch, Audrey P; Landick, Robert

2016-10-01

The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3), a component of MAP Kinase (MAPK) signaling (HOG1), a regulator of Protein Kinase A (PKA) signaling (IRA2), and a scaffolding protein for mitochondrial iron-sulfur (Fe-S) cluster biogenesis (ISU1). Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.

Glucose Metabolism Gene Expression Patterns and Tumor Uptake of 18F-Fluorodeoxyglucose After Radiation Treatment

International Nuclear Information System (INIS)

Wilson, George D.; Thibodeau, Bryan J.; Fortier, Laura E.; Pruetz, Barbara L.; Galoforo, Sandra; Baschnagel, Andrew M.; Chunta, John; Oliver Wong, Ching Yee; Yan, Di; Marples, Brian; Huang, Jiayi

2014-01-01

Purpose: To investigate whether radiation treatment influences the expression of glucose metabolism genes and compromises the potential use of 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) as a tool to monitor the early response of head and neck cancer xenografts to radiation therapy (RT). Methods and Materials: Low passage head and neck squamous cancer cells (UT14) were injected to the flanks of female nu/nu mice to generate xenografts. After tumors reached a size of 500 mm 3 they were treated with either sham RT or 15 Gy in 1 fraction. At different time points, days 3, 9, and 16 for controls and days 4, 7, 12, 21, 30, and 40 after irradiation, 2 to 3 mice were assessed with dynamic FDG-PET acquisition over 2 hours. Immediately after the FDG-PET the tumors were harvested for global gene expression analysis and immunohistochemical evaluation of GLUT1 and HK2. Different analytic parameters were used to process the dynamic PET data. Results: Radiation had no effect on key genes involved in FDG uptake and metabolism but did alter other genes in the HIF1α and glucose transport–related pathways. In contrast to the lack of effect on gene expression, changes in the protein expression patterns of the key genes GLUT1/SLC2A1 and HK2 were observed after radiation treatment. The changes in GLUT1 protein expression showed some correlation with dynamic FDG-PET parameters, such as the kinetic index. Conclusion: 18 F-fluorodeoxyglucose positron emission tomography changes after RT would seem to represent an altered metabolic state and not a direct effect on the key genes regulating FDG uptake and metabolism

Circadian physiology of metabolism.

Science.gov (United States)

Panda, Satchidananda

2016-11-25

A majority of mammalian genes exhibit daily fluctuations in expression levels, making circadian expression rhythms the largest known regulatory network in normal physiology. Cell-autonomous circadian clocks interact with daily light-dark and feeding-fasting cycles to generate approximately 24-hour oscillations in the function of thousands of genes. Circadian expression of secreted molecules and signaling components transmits timing information between cells and tissues. Such intra- and intercellular daily rhythms optimize physiology both by managing energy use and by temporally segregating incompatible processes. Experimental animal models and epidemiological data indicate that chronic circadian rhythm disruption increases the risk of metabolic diseases. Conversely, time-restricted feeding, which imposes daily cycles of feeding and fasting without caloric reduction, sustains robust diurnal rhythms and can alleviate metabolic diseases. These findings highlight an integrative role of circadian rhythms in physiology and offer a new perspective for treating chronic diseases in which metabolic disruption is a hallmark. Copyright © 2016, American Association for the Advancement of Science.

Plant physiology meets phytopathology: plant primary metabolism and plant-pathogen interactions.

Science.gov (United States)

Berger, Susanne; Sinha, Alok K; Roitsch, Thomas

2007-01-01

Phytopathogen infection leads to changes in secondary metabolism based on the induction of defence programmes as well as to changes in primary metabolism which affect growth and development of the plant. Therefore, pathogen attack causes crop yield losses even in interactions which do not end up with disease or death of the plant. While the regulation of defence responses has been intensively studied for decades, less is known about the effects of pathogen infection on primary metabolism. Recently, interest in this research area has been growing, and aspects of photosynthesis, assimilate partitioning, and source-sink regulation in different types of plant-pathogen interactions have been investigated. Similarly, phytopathological studies take into consideration the physiological status of the infected tissues to elucidate the fine-tuned infection mechanisms. The aim of this review is to give a summary of recent advances in the mutual interrelation between primary metabolism and pathogen infection, as well as to indicate current developments in non-invasive techniques and important strategies of combining modern molecular and physiological techniques with phytopathology for future investigations.

Effects of Castration on Expression of Lipid Metabolism Genes in the Liver of Korean Cattle

OpenAIRE

Baik, Myunggi; Nguyen, Trang Hoa; Jeong, Jin Young; Piao, Min Yu; Kang, Hyeok Joong

2015-01-01

Castration induces the accumulation of body fat and deposition of intramuscular fat in Korean cattle, resulting in improved beef quality. However, little is known about the metabolic adaptations in the liver following castration. To understand changes in lipid metabolism following castration, hepatic expression levels of lipid metabolism genes were compared between Korean bulls and steers. Steers had higher (p

Interactions of polyhalogenated aromatic hydrocarbons with thyroid hormone metabolism

NARCIS (Netherlands)

Schuur, A.G.

1998-01-01

This thesis deals with the possible interactions of polyhalogenated aromatic hydrocarbons and/or their metabolites with thyroid hormone metabolism. This chapter summarizes firstly the effects of thyroid hormone on the induction of biotransformation enzymes by PHAHs. Secondly, the results on

Effects of Castration on Expression of Lipid Metabolism Genes in the Liver of Korean Cattle

Directory of Open Access Journals (Sweden)

Myunggi Baik

2015-01-01

Full Text Available Castration induces the accumulation of body fat and deposition of intramuscular fat in Korean cattle, resulting in improved beef quality. However, little is known about the metabolic adaptations in the liver following castration. To understand changes in lipid metabolism following castration, hepatic expression levels of lipid metabolism genes were compared between Korean bulls and steers. Steers had higher (p<0.001 hepatic lipids contents and higher (p<0.01 mRNA levels of lipogenic acetyl-CoA carboxylase. This differential gene expression may, in part, contribute to increased hepatic lipid content following the castration of bulls. However, we found no differences in the hepatic expression levels of genes related to triglyceride synthesis (mitochondrial glycerol-3-phosphate acyltransferase, diacylglycerol O-acyltransferase 1 and 2 and fatty acid (FA oxidation (carnitine palmitoyltransferase 1A, C-4 to C-12 straight chain acyl-CoA dehydrogenase, very long chain acyl-CoA dehydrogenase between bulls and steers. No differences in gene expression for very-low-density lipoprotein (VLDL secretion, including apolipoprotein B mRNA and microsomal triglyceride transfer protein (MTTP protein, were observed in the liver although MTTP mRNA levels were higher in steers compared to bulls. In conclusion, FA synthesis may contribute to increased hepatic lipid deposition in steers following castration. However, hepatic lipid metabolism, including triglyceride synthesis, FA oxidation, and VLDL secretion, was not significantly altered by castration. Our results suggest that hepatic lipid metabolism does not significantly contribute to increased body fat deposition in steers following castration.

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

Science.gov (United States)

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Analysis of gene evolution and metabolic pathways using the Candida Gene Order Browser

LENUS (Irish Health Repository)

Fitzpatrick, David A

2010-05-10

Abstract Background Candida species are the most common cause of opportunistic fungal infection worldwide. Recent sequencing efforts have provided a wealth of Candida genomic data. We have developed the Candida Gene Order Browser (CGOB), an online tool that aids comparative syntenic analyses of Candida species. CGOB incorporates all available Candida clade genome sequences including two Candida albicans isolates (SC5314 and WO-1) and 8 closely related species (Candida dubliniensis, Candida tropicalis, Candida parapsilosis, Lodderomyces elongisporus, Debaryomyces hansenii, Pichia stipitis, Candida guilliermondii and Candida lusitaniae). Saccharomyces cerevisiae is also included as a reference genome. Results CGOB assignments of homology were manually curated based on sequence similarity and synteny. In total CGOB includes 65617 genes arranged into 13625 homology columns. We have also generated improved Candida gene sets by merging\\/removing partial genes in each genome. Interrogation of CGOB revealed that the majority of tandemly duplicated genes are under strong purifying selection in all Candida species. We identified clusters of adjacent genes involved in the same metabolic pathways (such as catabolism of biotin, galactose and N-acetyl glucosamine) and we showed that some clusters are species or lineage-specific. We also identified one example of intron gain in C. albicans. Conclusions Our analysis provides an important resource that is now available for the Candida community. CGOB is available at http:\\/\\/cgob.ucd.ie.

Study on the correlation between KCNJ11 gene polymorphism and metabolic syndrome in the elderly.

Science.gov (United States)

Jiang, Fan; Liu, Ning; Chen, Xiao Zhuang; Han, Kun Yuan; Zhu, Cai Zhong

2017-09-01

The aim of the study was to examine the correlation between KCNJ11 gene polymorphism and metabolic syndrome in elderly patients. From January 2014 to January 2015, 54 elderly patients with metabolic syndrome were enrolled in this study as the observation group. During the same period, 46 healthy elderly individuals were enrolled in this study as the control group. KCNJ11 gene polymorphism (rs28502) was analyzed using polymerase chain reaction-restriction fragment length polymorphism. The expression levels of mRNA in different genotypes were detected using FQ-PCR. ELISA was used to evaluate the KCNJ11 protein expression in different genotypes. KCNJ11 gene polymorphism and metabolic syndrome was studied by measuring the blood pressure levels in patients with different genotypes. Three genotypes of KCNJ11 gene in rs28502 were CC, CT and TT. The CC, CT and TT genotype frequencies in healthy population were 8.5, 9.2 and 82.2%, respectively, while the genotype frequencies in patients with metabolic syndrome were 42.4, 49.8 and 7.8%, respectively. There were significant differences between groups (P≤0.05). However, the genotype frequencies of C/T in healthy individuals and metabolic syndrome patients were 35.3 and 38.3%, respectively. There were no significant differences between groups (P>0.05). FQ-PCR results showed that the KCNJ11 mRNA expression levels in the control and observation groups had no significant differences (P>0.05). However, the results obtained from ELISA analysis revealed that KCNJ11 protein expression level in the observation group was significantly higher than that in the control group (Pmetabolic syndrome in the elderly. Elderly patients with the CC and TT genotypes are more likely to develop metabolic syndrome.

Large-scale extraction of gene interactions from full-text literature using DeepDive.

Science.gov (United States)

Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B

2016-01-01

A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app russ.altman@stanford.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Reveal genes functionally associated with ACADS by a network study.

Science.gov (United States)

Chen, Yulong; Su, Zhiguang

2015-09-15

Establishing a systematic network is aimed at finding essential human gene-gene/gene-disease pathway by means of network inter-connecting patterns and functional annotation analysis. In the present study, we have analyzed functional gene interactions of short-chain acyl-coenzyme A dehydrogenase gene (ACADS). ACADS plays a vital role in free fatty acid β-oxidation and regulates energy homeostasis. Modules of highly inter-connected genes in disease-specific ACADS network are derived by integrating gene function and protein interaction data. Among the 8 genes in ACADS web retrieved from both STRING and GeneMANIA, ACADS is effectively conjoined with 4 genes including HAHDA, HADHB, ECHS1 and ACAT1. The functional analysis is done via ontological briefing and candidate disease identification. We observed that the highly efficient-interlinked genes connected with ACADS are HAHDA, HADHB, ECHS1 and ACAT1. Interestingly, the ontological aspect of genes in the ACADS network reveals that ACADS, HAHDA and HADHB play equally vital roles in fatty acid metabolism. The gene ACAT1 together with ACADS indulges in ketone metabolism. Our computational gene web analysis also predicts potential candidate disease recognition, thus indicating the involvement of ACADS, HAHDA, HADHB, ECHS1 and ACAT1 not only with lipid metabolism but also with infant death syndrome, skeletal myopathy, acute hepatic encephalopathy, Reye-like syndrome, episodic ketosis, and metabolic acidosis. The current study presents a comprehensible layout of ACADS network, its functional strategies and candidate disease approach associated with ACADS network. Copyright © 2015 Elsevier B.V. All rights reserved.

Transcriptome Analysis of Three Sheep Intestinal Regions reveals Key Pathways and Hub Regulatory Genes of Large Intestinal Lipid Metabolism.

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Chao, Tianle; Wang, Guizhi; Ji, Zhibin; Liu, Zhaohua; Hou, Lei; Wang, Jin; Wang, Jianmin

2017-07-13

The large intestine, also known as the hindgut, is an important part of the animal digestive system. Recent studies on digestive system development in ruminants have focused on the rumen and the small intestine, but the molecular mechanisms underlying sheep large intestine metabolism remain poorly understood. To identify genes related to intestinal metabolism and to reveal molecular regulation mechanisms, we sequenced and compared the transcriptomes of mucosal epithelial tissues among the cecum, proximal colon and duodenum. A total of 4,221 transcripts from 3,254 genes were identified as differentially expressed transcripts. Between the large intestine and duodenum, differentially expressed transcripts were found to be significantly enriched in 6 metabolism-related pathways, among which PPAR signaling was identified as a key pathway. Three genes, CPT1A, LPL and PCK1, were identified as higher expression hub genes in the large intestine. Between the cecum and colon, differentially expressed transcripts were significantly enriched in 5 lipid metabolism related pathways, and CEPT1 and MBOAT1 were identified as hub genes. This study provides important information regarding the molecular mechanisms of intestinal metabolism in sheep and may provide a basis for further study.

Artificial neural network inference (ANNI: a study on gene-gene interaction for biomarkers in childhood sarcomas.

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Dong Ling Tong

Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

Epigenetics and a new look on metabolic syndrome

Czech Academy of Sciences Publication Activity Database

Kuneš, Jaroslav; Vaněčková, I.; Mikulášková, Barbora; Behuliak, M.; Maletínská, Lenka; Zicha, J.

2015-01-01

Roč. 64, č. 5 (2015), s. 611-620 ISSN 0862-8408 R&D Projects: GA ČR(CZ) GA15-08679S Institutional support: RVO:61388963 Keywords : metabolic syndrome * epigenetic s * transgenerational inheritance * gene-environmental interactions * obesity * hypertension Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition Impact factor: 1.643, year: 2015 http://www.biomed.cas.cz/physiolres/pdf/64/64_611.pdf

Genetic alterations in fatty acid transport and metabolism genes are associated with metastatic progression and poor prognosis of human cancers.

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Nath, Aritro; Chan, Christina

2016-01-04

Reprogramming of cellular metabolism is a hallmark feature of cancer cells. While a distinct set of processes drive metastasis when compared to tumorigenesis, it is yet unclear if genetic alterations in metabolic pathways are associated with metastatic progression of human cancers. Here, we analyzed the mutation, copy number variation and gene expression patterns of a literature-derived model of metabolic genes associated with glycolysis (Warburg effect), fatty acid metabolism (lipogenesis, oxidation, lipolysis, esterification) and fatty acid uptake in >9000 primary or metastatic tumor samples from the multi-cancer TCGA datasets. Our association analysis revealed a uniform pattern of Warburg effect mutations influencing prognosis across all tumor types, while copy number alterations in the electron transport chain gene SCO2, fatty acid uptake (CAV1, CD36) and lipogenesis (PPARA, PPARD, MLXIPL) genes were enriched in metastatic tumors. Using gene expression profiles, we established a gene-signature (CAV1, CD36, MLXIPL, CPT1C, CYP2E1) that strongly associated with epithelial-mesenchymal program across multiple cancers. Moreover, stratification of samples based on the copy number or expression profiles of the genes identified in our analysis revealed a significant effect on patient survival rates, thus confirming prominent roles of fatty acid uptake and metabolism in metastatic progression and poor prognosis of human cancers.

The Mediator Complex and Lipid Metabolism.

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Zhang, Yi; Xiaoli; Zhao, Xiaoping; Yang, Fajun

2013-03-01

The precise control of gene expression is essential for all biological processes. In addition to DNA-binding transcription factors, numerous transcription cofactors contribute another layer of regulation of gene transcription in eukaryotic cells. One of such transcription cofactors is the highly conserved Mediator complex, which has multiple subunits and is involved in various biological processes through directly interacting with relevant transcription factors. Although the current understanding on the biological functions of Mediator remains incomplete, research in the past decade has revealed an important role of Mediator in regulating lipid metabolism. Such function of Mediator is dependent on specific transcription factors, including peroxisome proliferator-activated receptor-gamma (PPARγ) and sterol regulatory element-binding proteins (SREBPs), which represent the master regulators of lipid metabolism. The medical significance of these findings is apparent, as aberrant lipid metabolism is intimately linked to major human diseases, such as type 2 diabetes and cardiovascular disease. Here, we briefly review the functions and molecular mechanisms of Mediator in regulation of lipid metabolism.

Gene-environment Interactions in Human Health: Case Studies and Strategies for developing new paradigms and research methodologies

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Fatimah L.C. Jackson

2014-08-01

Full Text Available The synergistic effects of genes and the environment on health are explored in three case studies: adult lactase persistence, autism spectrum disorders, and the metabolic syndrome, providing examples of the interactive complexities underlying these phenotypes. Since the phenotypes are the initial targets of evolutionary processes, understanding the specific environmental contexts of the genetic, epigenetic, and proteomic changes associated with these phenotypes is essential in predicting their health implications. Robust databases must be developed on the local scale to deconstruct both the population substructure and the unique components of the environment that stimulate geographically-specific changes in gene expression patterns. To produce these databases and make valid predictions, new, locally-focused and information-dense models are needed that incorporate data on evolutionary ecology, environmental complexity, local geographic patterns of gene expression, and population substructure.

An Approximation to the Temporal Order in Endogenous Circadian Rhythms of Genes Implicated in Human Adipose Tissue Metabolism

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GARAULET, MARTA; ORDOVÁS, JOSÉ M.; GÓMEZ-ABELLÁN, PURIFICACIÓN; MARTÍNEZ, JOSE A.; MADRID, JUAN A.

2015-01-01

Although it is well established that human adipose tissue (AT) shows circadian rhythmicity, published studies have been discussed as if tissues or systems showed only one or few circadian rhythms at a time. To provide an overall view of the internal temporal order of circadian rhythms in human AT including genes implicated in metabolic processes such as energy intake and expenditure, insulin resistance, adipocyte differentiation, dyslipidemia, and body fat distribution. Visceral and subcutaneous abdominal AT biopsies (n = 6) were obtained from morbid obese women (BMI ≥ 40 kg/m2). To investigate rhythmic expression pattern, AT explants were cultured during 24-h and gene expression was analyzed at the following times: 08:00, 14:00, 20:00, 02:00 h using quantitative real-time PCR. Clock genes, glucocorticoid metabolism-related genes, leptin, adiponectin and their receptors were studied. Significant differences were found both in achrophases and relative-amplitude among genes (P 30%). When interpreting the phase map of gene expression in both depots, data indicated that circadian rhythmicity of the genes studied followed a predictable physiological pattern, particularly for subcutaneous AT. Interesting are the relationships between adiponectin, leptin, and glucocorticoid metabolism-related genes circadian profiles. Their metabolic significance is discussed. Visceral AT behaved in a different way than subcutaneous for most of the genes studied. For every gene, protein mRNA levels fluctuated during the day in synchrony with its receptors. We have provided an overall view of the internal temporal order of circadian rhythms in human adipose tissue. PMID:21520059

Comprehensive evaluation of one-carbon metabolism pathway gene variants and renal cell cancer risk.

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Todd M Gibson

Full Text Available Folate and one-carbon metabolism are linked to cancer risk through their integral role in DNA synthesis and methylation. Variation in one-carbon metabolism genes, particularly MTHFR, has been associated with risk of a number of cancers in epidemiologic studies, but little is known regarding renal cancer.Tag single nucleotide polymorphisms (SNPs selected to produce high genomic coverage of 13 gene regions of one-carbon metabolism (ALDH1L1, BHMT, CBS, FOLR1, MTHFR, MTR, MTRR, SHMT1, SLC19A1, TYMS and the closely associated glutathione synthesis pathway (CTH, GGH, GSS were genotyped for 777 renal cell carcinoma (RCC cases and 1,035 controls in the Central and Eastern European Renal Cancer case-control study. Associations of individual SNPs (n = 163 with RCC risk were calculated using unconditional logistic regression adjusted for age, sex and study center. Minimum p-value permutation (Min-P tests were used to identify gene regions associated with risk, and haplotypes were evaluated within these genes.The strongest associations with RCC risk were observed for SLC19A1 (P(min-P = 0.03 and MTHFR (P(min-P = 0.13. A haplotype consisting of four SNPs in SLC19A1 (rs12483553, rs2838950, rs2838951, and rs17004785 was associated with a 37% increased risk (p = 0.02, and exploratory stratified analysis suggested the association was only significant among those in the lowest tertile of vegetable intake.To our knowledge, this is the first study to comprehensively examine variation in one-carbon metabolism genes in relation to RCC risk. We identified a novel association with SLC19A1, which is important for transport of folate into cells. Replication in other populations is required to confirm these findings.

Gene-Lifestyle Interactions in Obesity.

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van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Lagou, Vasiliki

2012-01-01

Obesity is a complex multifaceted disease resulting from interactions between genetics and lifestyle. The proportion of phenotypic variance ascribed to genetic variance is 0.4 to 0.7 for obesity and recent years have seen considerable success in identifying disease-susceptibility variants. Although with the advent of genome-wide association studies the list of genetic variants predisposing to obesity has significantly increased the identified variants only explain a fraction of disease heritability. Studies of gene-environment interactions can provide more insight into the biological mechanisms involved in obesity despite the challenges associated with such designs. Epigenetic changes that affect gene function without DNA sequence modifications may be a key factor explaining interindividual differences in obesity, with both genetic and environmental factors influencing the epigenome. Disentangling the relative contributions of genetic, environmental and epigenetic marks to the establishment of obesity is a major challenge given the complex interplay between these determinants.

Regulators of nonsulfur purple phototrophic bacteria and the interactive control of CO2 assimilation, nitrogen fixation, hydrogen metabolism and energy generation.

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Dubbs, James M; Tabita, F Robert

2004-06-01

For the metabolically diverse nonsulfur purple phototrophic bacteria, maintaining redox homeostasis requires balancing the activities of energy supplying and energy-utilizing pathways, often in the face of drastic changes in environmental conditions. These organisms, members of the class Alphaproteobacteria, primarily use CO2 as an electron sink to achieve redox homeostasis. After noting the consequences of inactivating the capacity for CO2 reduction through the Calvin-Benson-Bassham (CBB) pathway, it was shown that the molecular control of many additional important biological processes catalyzed by nonsulfur purple bacteria is linked to expression of the CBB genes. Several regulator proteins are involved, with the two component Reg/Prr regulatory system playing a major role in maintaining redox poise in these organisms. Reg/Prr was shown to be a global regulator involved in the coordinate control of a number of metabolic processes including CO2 assimilation, nitrogen fixation, hydrogen metabolism and energy-generation pathways. Accumulating evidence suggests that the Reg/Prr system senses the oxidation/reduction state of the cell by monitoring a signal associated with electron transport. The response regulator RegA/PrrA activates or represses gene expression through direct interaction with target gene promoters where it often works in concert with other regulators that can be either global or specific. For the key CO2 reduction pathway, which clearly triggers whether other redox balancing mechanisms are employed, the ability to activate or inactivate the specific regulator CbbR is of paramount importance. From these studies, it is apparent that a detailed understanding of how diverse regulatory elements integrate and control metabolism will eventually be achieved.

Polymorphisms in the LPL and CETP Genes and Haplotype in the ESR1 Gene Are Associated with Metabolic Syndrome in Women from Southwestern Mexico

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José Ángel Cahua-Pablo

2015-09-01

Full Text Available Metabolic syndrome (MetS is a combination of metabolic disorders associated with an increased risk for cardiovascular disease (CVD. Studies in women reported associations between polymorphisms in ESR1, LPL and CETP genes and MetS. Our aim was to evaluate the association between variants in ESR1, LPL and CETP genes with MetS and its components. Four hundred and eighty women were analyzed, anthropometric features and biochemical profiles were evaluated, and genotyping was performed by real-time PCR. We found an association with elevated glucose levels (odds ratio (OR = 2.9; p = 0.013 in carrying the AA genotype of rs1884051 in the ESR1 gene compared with the GG genotype, and the CC genotype of rs328 in the LPL gene was associated with MetS compared to the CG or GG genotype (OR = 2.8; p = 0.04. Moreover, the GA genotype of rs708272 in the CETP gene is associated with MetS compared to the GG or AA genotype (OR = 1.8; p = 0.006. In addition the ACTCCG haplotype in the ESR1 gene is associated with a decrease in the risk of MetS (OR = 0.02; p < 0.001. In conclusion, our results show the involvement of the variants of ESR1, LPL and CETP genes in metabolic events related to MetS or some of its features.

Ketogenic diet and astrocyte/neuron metabolic interactions

OpenAIRE

Vamecq Joseph; Maurois Pierre; Bac Pierre; Delplanque Bernadette; Pages Nicole

2007-01-01

The ketogenic diet is an anticonvulsant diet enriched in fat. It provides the body with a minimal protein requirement and a restricted carbohydrate supply, the vast majority of calories (more than 80-90%) being given by fat. Though anticonvulsant activity of ketogenic diet has been well documented by a large number of experimental and clinical studies, underlying mechanisms still remain partially unclear. Astrocyte-neuron interactions, among which metabolic shuttles, may influence synaptic ac...

Gene-environment interaction in Parkinson’s disease: coffee, ADORA2A, and CYP1A2

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Chuang, Yu-Hsuan; Lill, Christina M.; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina Funch; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S.; Ritz, Beate

2017-01-01

Background and purpose Drinking caffeinated coffee has been reported to protect against Parkinson’s disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine, thus gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. Methods In a population-based case control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and sex- matched controls), we assessed interactions between lifetime coffee consumption and three polymorphisms in ADORA2A and CYP1A2 for all subjects and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. Results We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction=0.66 [0.46–0.94], p=0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. Conclusion We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enrol prevalent PD cases. PMID:28135712

Isoeugenol monooxygenase and its putative regulatory gene are located in the eugenol metabolic gene cluster in Pseudomonas nitroreducens Jin1.

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Ryu, Ji-Young; Seo, Jiyoung; Unno, Tatsuya; Ahn, Joong-Hoon; Yan, Tao; Sadowsky, Michael J; Hur, Hor-Gil

2010-03-01

The plant-derived phenylpropanoids eugenol and isoeugenol have been proposed as useful precursors for the production of natural vanillin. Genes involved in the metabolism of eugenol and isoeugenol were clustered in region of about a 30 kb of Pseudomonas nitroreducens Jin1. Two of the 23 ORFs in this region, ORFs 26 (iemR) and 27 (iem), were predicted to be involved in the conversion of isoeugenol to vanillin. The deduced amino acid sequence of isoeugenol monooxygenase (Iem) of strain Jin1 had 81.4% identity to isoeugenol monooxygenase from Pseudomonas putida IE27, which also transforms isoeugenol to vanillin. Iem was expressed in E. coli BL21(DE3) and was found to lead to isoeugenol to vanillin transformation. Deletion and cloning analyses indicated that the gene iemR, located upstream of iem, is required for expression of iem in the presence of isoeugenol, suggesting it to be the iem regulatory gene. Reverse transcription, real-time PCR analyses indicated that the genes involved in the metabolism of eugenol and isoeugenol were differently induced by isoeugenol, eugenol, and vanillin.

Metabolic Interaction of Helicobacter pylori Infection and Gut Microbiota

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Yao-Jong Yang

2016-02-01

Full Text Available As a barrier, gut commensal microbiota can protect against potential pathogenic microbes in the gastrointestinal tract. Crosstalk between gut microbes and immune cells promotes human intestinal homeostasis. Dysbiosis of gut microbiota has been implicated in the development of many human metabolic disorders like obesity, hepatic steatohepatitis, and insulin resistance in type 2 diabetes (T2D. Certain microbes, such as butyrate-producing bacteria, are lower in T2D patients. The transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome, but the exact pathogenesis remains unclear. H. pylori in the human stomach cause chronic gastritis, peptic ulcers, and gastric cancers. H. pylori infection also induces insulin resistance and has been defined as a predisposing factor to T2D development. Gastric and fecal microbiota may have been changed in H. pylori-infected persons and mice to promote gastric inflammation and specific diseases. However, the interaction of H. pylori and gut microbiota in regulating host metabolism also remains unknown. Further studies aim to identify the H. pylori-microbiota-host metabolism axis and to test if H. pylori eradication or modification of gut microbiota can improve the control of human metabolic disorders.

Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions

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Greene Casey S

2009-09-01

Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be

The metabolic regulator CodY links L. monocytogenes metabolism to virulence by directly activating the virulence regulatory gene, prfA

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Lobel, Lior; Sigal, Nadejda; Borovok, Ilya; Belitsky, Boris R.; Sonenshein, Abraham L.; Herskovits, Anat A.

2015-01-01

Summary Metabolic adaptations are critical to the ability of bacterial pathogens to grow within host cells and are normally preceded by sensing of host-specific metabolic signals, which in turn can influence the pathogen's virulence state. Previously, we reported that the intracellular bacterial pathogen Listeria monocytogenes responds to low availability of branched-chain amino acids (BCAA) within mammalian cells by up-regulating both BCAA biosynthesis and virulence genes. The induction of virulence genes required the BCAA-responsive transcription regulator, CodY, but the molecular mechanism governing this mode of regulation was unclear. In this report, we demonstrate that CodY directly binds the coding sequence of the L. monocytogenes master virulence activator gene, prfA, 15 nt downstream of its start codon, and that this binding results in up-regulation of prfA transcription specifically under low concentrations of BCAA. Mutating this site abolished CodY binding and reduced prfA transcription in macrophages, and attenuated bacterial virulence in mice. Notably, the mutated binding site did not alter prfA transcription or PrfA activity under other conditions that are known to activate PrfA, such as during growth in the presence of glucose-1-phosphate. This study highlights the tight crosstalk between L. monocytogenes metabolism and virulence' while revealing novel features of CodY-mediated regulation. PMID:25430920

Interactions between host metabolism, immune regulation, and the gut microbiota in diet-associated obesity and metabolic dysfunction

DEFF Research Database (Denmark)

Andersen, Daniel

The increase in the prevalence of obesity and obesity-associated complications such as the metabolic syndrome is becoming a global challenge. Dietary habits and nutrient consumption modulates host homeostasis, which manifests in various diet-induced complications marked by changes in host...... metabolism and immune regulation, which are intricately linked. In addition, diet effectively shapes the gut microbiota composition and activity, which in turn interacts with the host to modulate host metabolism and immune regulation. In the three studies included in this PhD thesis, we have explored...... the impact of specific dietary components on host metabolic function, immune regulation and gut microbiota composition and activity. In the first study, we have characterized the effect of a combined high-fat and gliadin-rich diet, since dietary gliadin has been reported to be associated with intestinal...

Plant interactions alter the predictions of metabolic scaling theory.

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Yue Lin

Full Text Available Metabolic scaling theory (MST is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning. Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric, and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.

A Natural Light/Dark Cycle Regulation of Carbon-Nitrogen Metabolism and Gene Expression in Rice Shoots.

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Li, Haixing; Liang, Zhijun; Ding, Guangda; Shi, Lei; Xu, Fangsen; Cai, Hongmei

2016-01-01

Light and temperature are two particularly important environmental cues for plant survival. Carbon and nitrogen are two essential macronutrients required for plant growth and development, and cellular carbon and nitrogen metabolism must be tightly coordinated. In order to understand how the natural light/dark cycle regulates carbon and nitrogen metabolism in rice plants, we analyzed the photosynthesis, key carbon-nitrogen metabolites, and enzyme activities, and differentially expressed genes and miRNAs involved in the carbon and nitrogen metabolic pathway in rice shoots at the following times: 2:00, 6:00, 10:00, 14:00, 18:00, and 22:00. Our results indicated that more CO2 was fixed into carbohydrates by a high net photosynthetic rate, respiratory rate, and stomatal conductance in the daytime. Although high levels of the nitrate reductase activity, free ammonium and carbohydrates were exhibited in the daytime, the protein synthesis was not significantly facilitated by the light and temperature. In mRNA sequencing, the carbon and nitrogen metabolism-related differentially expressed genes were obtained, which could be divided into eight groups: photosynthesis, TCA cycle, sugar transport, sugar metabolism, nitrogen transport, nitrogen reduction, amino acid metabolism, and nitrogen regulation. Additionally, a total of 78,306 alternative splicing events have been identified, which primarily belong to alternative 5' donor sites, alternative 3' acceptor sites, intron retention, and exon skipping. In sRNA sequencing, four carbon and nitrogen metabolism-related miRNAs (osa-miR1440b, osa-miR2876-5p, osa-miR1877 and osa-miR5799) were determined to be regulated by natural light/dark cycle. The expression level analysis showed that the four carbon and nitrogen metabolism-related miRNAs negatively regulated their target genes. These results may provide a good strategy to study how natural light/dark cycle regulates carbon and nitrogen metabolism to ensure plant growth and

A natural light/dark cycle regulation of carbon-nitrogen metabolism and gene expression in rice shoots

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Haixing Li

2016-08-01

Full Text Available Light and temperature are two particularly important environmental cues for plant survival. Carbon and nitrogen are two essential macronutrients required for plant growth and development, and cellular carbon and nitrogen metabolism must be tightly coordinated. In order to understand how the natural light/dark cycle regulates carbon and nitrogen metabolism in rice plants, we analyzed the photosynthesis, key carbon-nitrogen metabolites and enzyme activities, and differentially expressed genes and miRNAs involved in the carbon and nitrogen metabolic pathway in rice shoots at the following times: 2:00, 6:00, 10:00, 14:00, 18:00 and 22:00. Our results indicated that more CO2 was fixed into carbohydrates by a high net photosynthetic rate, respiratory rate and stomatal conductance in the daytime. Although high levels of the nitrate reductase activity, free ammonium and carbohydrates were exhibited in the daytime, the protein synthesis was not significantly facilitated by the light and temperature. In mRNA sequencing, the carbon and nitrogen metabolism-related differentially expressed genes were obtained, which could be divided into eight groups: photosynthesis, TCA cycle, sugar transport, sugar metabolism, nitrogen transport, nitrogen reduction, amino acid metabolism and nitrogen regulation. Additionally, a total of 78,306 alternative splicing events have been identified, which primarily belong to alternative 5' donor sites, alternative 3' acceptor sites, intron retention and exon skipping. In sRNA sequencing, four carbon and nitrogen metabolism-related miRNAs (osa-miR1440b, osa-miR2876-5p, osa-miR1877 and osa-miR5799 were determined to be regulated by natural light/dark cycle. The expression level analysis showed that the four carbon and nitrogen metabolism-related miRNAs negatively regulated their target genes. These results may provide a good strategy to study how natural light/dark cycle regulates carbon and nitrogen metabolism to ensure plant

You've gotta be lucky: Coverage and the elusive gene-gene interaction.

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Reimherr, Matthew; Nicolae, Dan L

2011-01-01

Genome-wide association studies (GWAS) have led to a large number of single-SNP association findings, but there has been, so far, no investigation resulting in the discovery of a replicable gene-gene interaction. In this paper, we examine some of the possible explanations for the lack of findings, and argue that coverage of causal variation not only has a large effect on the loss in power, but that the effect is larger than in the single-SNP analyses. We show that the product of linkage disequilibrium measures, r², between causal and tested SNPs offers a good approximation to the loss in efficiency as defined by the ratio of sample sizes that lead to similar power. We also demonstrate that, in addition to the huge search space, the loss in power due to coverage when using commercially available platforms makes the search for gene-gene interactions daunting. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.

False positive reduction in protein-protein interaction predictions using gene ontology annotations

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Lin Yen-Han

2007-07-01

Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

Glucose Metabolism Gene Expression Patterns and Tumor Uptake of {sup 18}F-Fluorodeoxyglucose After Radiation Treatment

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Wilson, George D., E-mail: george.wilson@beaumont.edu [Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, Michigan (United States); Beaumont BioBank, William Beaumont Hospital, Royal Oak, Michigan (United States); Thibodeau, Bryan J.; Fortier, Laura E.; Pruetz, Barbara L. [Beaumont BioBank, William Beaumont Hospital, Royal Oak, Michigan (United States); Galoforo, Sandra; Baschnagel, Andrew M.; Chunta, John [Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, Michigan (United States); Oliver Wong, Ching Yee [Department of Diagnostic Radiology and Molecular Imaging Medicine, William Beaumont Hospital, Royal Oak, Michigan (United States); Yan, Di; Marples, Brian [Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, Michigan (United States); Huang, Jiayi [Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, Michigan (United States); Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri (United States)

2014-11-01

Purpose: To investigate whether radiation treatment influences the expression of glucose metabolism genes and compromises the potential use of {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) as a tool to monitor the early response of head and neck cancer xenografts to radiation therapy (RT). Methods and Materials: Low passage head and neck squamous cancer cells (UT14) were injected to the flanks of female nu/nu mice to generate xenografts. After tumors reached a size of 500 mm{sup 3} they were treated with either sham RT or 15 Gy in 1 fraction. At different time points, days 3, 9, and 16 for controls and days 4, 7, 12, 21, 30, and 40 after irradiation, 2 to 3 mice were assessed with dynamic FDG-PET acquisition over 2 hours. Immediately after the FDG-PET the tumors were harvested for global gene expression analysis and immunohistochemical evaluation of GLUT1 and HK2. Different analytic parameters were used to process the dynamic PET data. Results: Radiation had no effect on key genes involved in FDG uptake and metabolism but did alter other genes in the HIF1α and glucose transport–related pathways. In contrast to the lack of effect on gene expression, changes in the protein expression patterns of the key genes GLUT1/SLC2A1 and HK2 were observed after radiation treatment. The changes in GLUT1 protein expression showed some correlation with dynamic FDG-PET parameters, such as the kinetic index. Conclusion: {sup 18}F-fluorodeoxyglucose positron emission tomography changes after RT would seem to represent an altered metabolic state and not a direct effect on the key genes regulating FDG uptake and metabolism.

Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario

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Onay Venus

2007-08-01

Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.

Genetic variation in eleven phase I drug metabolism genes in an ethnically diverse population.

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Solus, Joseph F; Arietta, Brenda J; Harris, James R; Sexton, David P; Steward, John Q; McMunn, Chara; Ihrie, Patrick; Mehall, Janelle M; Edwards, Todd L; Dawson, Elliott P

2004-10-01

The extent of genetic variation found in drug metabolism genes and its contribution to interindividual variation in response to medication remains incompletely understood. To better determine the identity and frequency of variation in 11 phase I drug metabolism genes, the exons and flanking intronic regions of the cytochrome P450 (CYP) isoenzyme genes CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4 and CYP3A5 were amplified from genomic DNA and sequenced. A total of 60 kb of bi-directional sequence was generated from each of 93 human DNAs, which included Caucasian, African-American and Asian samples. There were 388 different polymorphisms identified. These included 269 non-coding, 45 synonymous and 74 non-synonymous polymorphisms. Of these, 54% were novel and included 176 non-coding, 14 synonymous and 21 non-synonymous polymorphisms. Of the novel variants observed, 85 were represented by single occurrences of the minor allele in the sample set. Much of the variation observed was from low-frequency alleles. Comparatively, these genes are variation-rich. Calculations measuring genetic diversity revealed that while the values for the individual genes are widely variable, the overall nucleotide diversity of 7.7 x 10(-4) and polymorphism parameter of 11.5 x 10(-4) are higher than those previously reported for other gene sets. Several independent measurements indicate that these genes are under selective pressure, particularly for polymorphisms corresponding to non-synonymous amino acid changes. There is relatively little difference in measurements of diversity among the ethnic groups, but there are large differences among the genes and gene subfamilies themselves. Of the three CYP subfamilies involved in phase I drug metabolism (1, 2, and 3), subfamily 2 displays the highest levels of genetic diversity.

Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions

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Alexandre eBureau

2015-07-01

Full Text Available Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis.

Increased missense mutation burden of Fatty Acid metabolism related genes in nunavik inuit population.

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Zhou, Sirui; Xiong, Lan; Xie, Pingxing; Ambalavanan, Amirthagowri; Bourassa, Cynthia V; Dionne-Laporte, Alexandre; Spiegelman, Dan; Turcotte Gauthier, Maude; Henrion, Edouard; Diallo, Ousmane; Dion, Patrick A; Rouleau, Guy A

2015-01-01

Nunavik Inuit (northern Quebec, Canada) reside along the arctic coastline where for generations their daily energy intake has mainly been derived from animal fat. Given this particular diet it has been hypothesized that natural selection would lead to population specific allele frequency differences and unique variants in genes related to fatty acid metabolism. A group of genes, namely CPT1A, CPT1B, CPT1C, CPT2, CRAT and CROT, encode for three carnitine acyltransferases that are important for the oxidation of fatty acids, a critical step in their metabolism. Exome sequencing and SNP array genotyping were used to examine the genetic variations in the six genes encoding for the carnitine acyltransferases in 113 Nunavik Inuit individuals. Altogether ten missense variants were found in genes CPT1A, CPT1B, CPT1C, CPT2 and CRAT, including three novel variants and one Inuit specific variant CPT1A p.P479L (rs80356779). The latter has the highest frequency (0.955) compared to other Inuit populations. We found that by comparison to Asians or Europeans, the Nunavik Inuit have an increased mutation burden in CPT1A, CPT2 and CRAT; there is also a high level of population differentiation based on carnitine acyltransferase gene variations between Nunavik Inuit and Asians. The increased number and frequency of deleterious variants in these fatty acid metabolism genes in Nunavik Inuit may be the result of genetic adaptation to their diet and/or the extremely cold climate. In addition, the identification of these variants may help to understand some of the specific health risks of Nunavik Inuit.

Connexins, diabetes and the metabolic syndrome.

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Hamelin, Romain; Allagnat, Florent; Haefliger, Jacques-Antoine; Meda, Paolo

2009-02-01

Diabetes and the related metabolic syndrome are multi system disorders that result from improper interactions between various cell types. Even though the underlying mechanism remains to be fully understood, it is most likely that both the long and the short distance range cell interactions, which normally ensure the physiologic functioning of the pancreas, and its relationships with the insulin-targeted organs, are altered. This review focuses on the short-range type of interactions that depend on the contact between adjacent cells and, specifically, on the interactions that are dependent on connexins. The widespread distribution of these membrane proteins, their multiple modes of action, and their interactions with conditions/molecules associated to both the pathogenesis and the treatment of the 2 main forms of diabetes and the metabolic syndrome, make connexins an essential part of the chain of events that leads to metabolic diseases. Here, we review the present state of knowledge about the molecular and cell biology of the connexin genes and proteins, their general mechanisms of action, the roles specific connexin species play in the endocrine pancreas and the major insulin-targeted organs, under physiological and patho-physiological conditions.

Association Study between Ghrelin Gene Polymorphism and Metabolic Syndrome in a Han Chinese Population.

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You, Yueyue; Yu, Yaqin; Wu, Yanhua; Rao, Wenwang; Zhang, Yangyu; Liu, Yingyu; Yang, Guang; Fu, Yingli; Shi, Jieping; Kou, Changgui

2017-01-01

Ghrelin, in humans, is a hormone secreted from the stomach with an orexigenic effect, which is good for digestion and absorption, as well as regulating physical growth, metabolism, and energy balance. It is also involved in the development of metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM). This study assessed the association between single nucleotide variants of the GHRL gene and the risk of metabolic syndrome in a Han Chinese population. A case-control study was performed on 3780 Han Chinese comprising 1813 MetS cases and 1967 controls. Three missense polymorphisms in GHRL (rs26802, rs10490816, and rs696217) were selected, and the association between these polymorphisms and the risk of MetS was investigated. Metabolic syndrome was defined according to the criteria of the International Diabetes Federation (IDF). Using Pearson's 2 test, we found that there were no significant differences in genotype distributions and allele frequencies between cases and controls (all p > 0.05). There were also no significant differences in haplotype distributions between MetS cases and healthy controls. Furthermore, we confirmed that rs26802 of the GHRL gene is associated with body mass index (BMI), waist circumference, systolic blood pressure (SBP), and fasting glucose; rs10490816 is associated with triglycerides (TG) and total cholesterol (TC); while rs696217 is associated with hip circumference and fasting glucose. We concluded that mutations in the GHRL gene did not confer risk for MetS in our study population. Therefore, functional analysis and replication studies in other populations are needed to further investigate the exact role of the GHRL gene in MetS.

Variants of Insulin-Signaling Inhibitor Genes in Type 2 Diabetes and Related Metabolic Abnormalities

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Carlo de Lorenzo

2013-01-01

Full Text Available Insulin resistance has a central role in the pathogenesis of several metabolic diseases, including type 2 diabetes, obesity, glucose intolerance, metabolic syndrome, atherosclerosis, and cardiovascular diseases. Insulin resistance and related traits are likely to be caused by abnormalities in the genes encoding for proteins involved in the composite network of insulin-signaling; in this review we have focused our attention on genetic variants of insulin-signaling inhibitor molecules. These proteins interfere with different steps in insulin-signaling: ENPP1/PC-1 and the phosphatases PTP1B and PTPRF/LAR inhibit the insulin receptor activation; INPPL1/SHIP-2 hydrolyzes PI3-kinase products, hampering the phosphoinositide-mediated downstream signaling; and TRIB3 binds the serine-threonine kinase Akt, reducing its phosphorylation levels. While several variants have been described over the years for all these genes, solid evidence of an association with type 2 diabetes and related diseases seems to exist only for rs1044498 of the ENPP1 gene and for rs2295490 of the TRIB3 gene. However, overall the data recapitulated in this Review article may supply useful elements to interpret the results of novel, more technically advanced genetic studies; indeed it is becoming increasingly evident that genetic information on metabolic diseases should be interpreted taking into account the complex biological pathways underlying their pathogenesis.

Trehalose metabolism genes render rice white tip nematode Aphelenchoides besseyi (Nematoda: Aphelenchoididae) resistant to an anaerobic environment

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Chen, Qiaoli; Zhang, Ruizhi; Ling, Yaming

2018-01-01

ABSTRACT After experiencing anaerobic environments, Aphelenchoides besseyi will enter a state of suspended animation known as anoxybiosis, during which it may use trehalose as an energy supply to survive. To explore the function of trehalose metabolism, two trehalose-6-phosphate synthase (TPS) genes (Ab-tps1 and Ab-tps2) encoding enzymes catalysing trehalose synthesis, and three trehalase (TRE) genes (Ab-ntre1, Ab-ntre2 and Ab-atre) encoding enzymes catalysing the hydrolysis of trehalose, were identified and investigated. Ab-tps1 and Ab-tps2 were active during certain periods of anoxybiosis for A. besseyi, and Ab-tps2, Ab-ntre1, Ab-ntre2 and Ab-atre were active during certain periods of recovery. The results of RNA interference experiments suggested that TRE genes regulated each other and both TPS genes, while a single TPS gene only regulated the other TPS gene. However, two TPS genes together could regulate TRE genes, which indicated a feedback mechanism between these genes. All these genes also positively regulated the survival and resumption of active metabolism of the nematode. Genes functioning at re-aeration have a greater impact on nematode survival, suggesting that these genes could play roles in anoxybiosis regulation, but may function within restricted time frames. Changes in trehalose levels matched changes in TRE activity during the anoxybiosis–re-aeration process, suggesting that trehalose may act as an energy supply source. The observation of up-regulation of TPS genes during anoxybiosis suggested a possible signal role of trehalose. Trehalose metabolism genes could also work together to control trehalose levels at a certain level when the nematode is under anaerobic conditions. PMID:29158222

Obesity and the metabolic syndrome: Impact of gene-diet interaction ...

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Every disease susceptibility or medical condition is caused, regulated or influenced by genes and obesity is no exception. Although overeating in combination with low physical activity is the main cause of obesity, genetically determined influences on energy balance regulation also play an important role. Individuals ...

Differential selection on carotenoid biosynthesis genes as a function of gene position in the metabolic pathway: a study on the carrot and dicots.

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Jérémy Clotault

Full Text Available Selection of genes involved in metabolic pathways could target them differently depending on the position of genes in the pathway and on their role in controlling metabolic fluxes. This hypothesis was tested in the carotenoid biosynthesis pathway using population genetics and phylogenetics.Evolutionary rates of seven genes distributed along the carotenoid biosynthesis pathway, IPI, PDS, CRTISO, LCYB, LCYE, CHXE and ZEP, were compared in seven dicot taxa. A survey of deviations from neutrality expectations at these genes was also undertaken in cultivated carrot (Daucus carota subsp. sativus, a species that has been intensely bred for carotenoid pattern diversification in its root during its cultivation history. Parts of sequences of these genes were obtained from 46 individuals representing a wide diversity of cultivated carrots. Downstream genes exhibited higher deviations from neutral expectations than upstream genes. Comparisons of synonymous and nonsynonymous substitution rates between genes among dicots revealed greater constraints on upstream genes than on downstream genes. An excess of intermediate frequency polymorphisms, high nucleotide diversity and/or high differentiation of CRTISO, LCYB1 and LCYE in cultivated carrot suggest that balancing selection may have targeted genes acting centrally in the pathway.Our results are consistent with relaxed constraints on downstream genes and selection targeting the central enzymes of the carotenoid biosynthesis pathway during carrot breeding history.

Effects of achilline on lipid metabolism gene expression in cell culture

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A. V. Ratkin

2016-01-01

Full Text Available Objective. Evaluation in vitro of the mechanisms of the hypolipidemic effect of sesquiterpene γ-lactone achilline in the hepatoma tissue culture (HTC.Materials and methods.The influence of sesquiterpene γ-lactone achilline and gemfibrozil (comparison drug on the viability, lipid content and expression of key genes of lipid metabolism in the hepatoma tissue culture. The lipid content was assessed by fluorescent method with the vital dye Nile Red, the cell viability was assessed using MTT assay.Results. Cultivation of of cell cultures of rat’s hepatoma cell line HTC for 48 h with achilline in a concentration of from 0.25 to 1.0 mm and gemfibrozil from 0,25 to 0,5 mm did not change cell viability compared to control. In these same concentrations of the test substance reduced the lipid content in the cells, assessed by fluorescent method with the vital dye Nile Red. To study the mechanism of hypolipidemicaction of achillinedetermined the expression of key genes of lipid metabolism in cell culture lines HTC. The possible mechanism of hypolipidemic action of achilline can be attributed to the increased transport and oxidation of long-chain fatty acids in mitochondria, as evidenced by the increase in the gene expression of carnitine-palmitoyltransferase 2 (Cpt2. The decrease in cholesterol level may be due to increased synthesis of bile acids from cholesterol, due to increased gene expression of 7-alphahydroxylase (Cyp7a1. Conclusion. In cell cultures of rat’s hepatoma cell line HTC sesquiterpene γ-lactone achilline reduces the accumulation of lipids in cells, as evidenced by the decrease in the fluorescence of Nile Red, increased gene expression of the carnitine-palmitoyltransferase 2 (Cpt2 gene and 7-alpha-hydroxylase (Cyp7a1.

Association of MEP1A gene variants with insulin metabolism in central European women with polycystic ovary syndrome.

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Lam, Uyen D P; Lerchbaum, Elisabeth; Schweighofer, Natascha; Trummer, Olivia; Eberhard, Katharina; Genser, Bernd; Pieber, Thomas R; Obermayer-Pietsch, Barbara

2014-03-10

Polycystic ovary syndrome (PCOS) shows not only hyperandrogenemia, hirsutism and fertility problems, but also metabolic disturbances including obesity, cardiovascular events and type-2 diabetes. Accumulating evidence suggests some degree of inflammation associated with prominent aspects of PCOS. We aimed to investigate the association of genetic variants 3'UTR rs17468190 (G/T) of the inflammation-associated gene MEP1A (GenBank ID: NM_005588.2) with metabolic disturbances in PCOS and healthy control women. Genetic variants rs17468190 (G/T) of MEP1A gene were analyzed in 576 PCOS women and 206 controls by using the Taqman fluorogenic 5'-exonuclease assay. This polymorphism was tested for association with anthropometric, metabolic, hormonal, and functional parameters of PCOS. There was a borderline significant difference in genotype distribution between PCOS and control women (p=0.046). In overweight/obese PCOS patients, the variants rs17468190 (G/T) in the MEP1A gene are associated with glucose and insulin metabolism. In a dominant model, the GG genotype of the MEP1A gene was more strongly associated with insulin metabolism in overweight/obese PCOS women (body mass index, BMI>25 kg/m(2)), than in GT+TT genotypes. The MEP1A GG-carriers showed a significantly increased homeostatic model assessment - insulin resistance (HOMA-IR) (p=0.003), elevation of fasting insulin (p=0.004) and stimulated insulin (30 min, pdisease modification in PCOS. It might contribute to the abnormalities of glucose metabolism and insulin sensitivity and serve as a diagnostic or therapeutic target gene for PCOS. Copyright © 2014 Elsevier B.V. All rights reserved.

The use of transgenic animals to study lipoprotein metabolism

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Rubin, E.M.; Plump, A.S.

1993-12-01

The application of transgenic technology to lipoprotein metabolism and atherosclerosis was first reported in 1988. Today, a large percentage of the genes involved in lipoprotein metabolism have been overexpressed in mice, and a substantial number of these same genes have been disrupted by homologous recombination in embryonic stem (ES) cells. The utility of animal models of lipoprotein metabolism and atherosclerosis is far-reaching given the complex nature of these systems. There are at least 17 known genes directly involved in lipoprotein metabolism and likely dozens more may be involved. This massive network of interacting factors has necessitated the development of in vivo systems which can be subject to genetic manipulation. The power of overexpression is obvious: elucidating function in a relatively controlled genetic environment in which the whole system is present and operational. The not-so-obvious problem with transgenics is ``background,`` or for purposes of the current discussion, the mouse`s own lipoprotein system. With the advent of gene knockout, we have been given the ability to overcome ``background.`` By recreating the genetic complement of the mouse we can alter a system in essentially any manner desired. As unique tools, and in combination with one another, the overexpression of foreign genes and the targeted disruption or alteration of endogenous genes has already and will continue to offer a wealth of information on the biology of lipoprotein metabolism and its effect on atherosclerosis susceptibility.

Molecular Interaction of Bone Marrow Adipose Tissue with Energy Metabolism.

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Suchacki, Karla J; Cawthorn, William P

2018-01-01

The last decade has seen a resurgence in the study of bone marrow adipose tissue (BMAT) across diverse fields such as metabolism, haematopoiesis, skeletal biology and cancer. Herein, we review the most recent developments of BMAT research in both humans and rodents, including the distinct nature of BMAT; the autocrine, paracrine and endocrine interactions between BMAT and various tissues, both in physiological and pathological scenarios; how these interactions might impact energy metabolism; and the most recent technological advances to quantify BMAT. Though still dwarfed by research into white and brown adipose tissues, BMAT is now recognised as endocrine organ and is attracting increasing attention from biomedical researchers around the globe. We are beginning to learn the importance of BMAT both within and beyond the bone, allowing us to better appreciate the role of BMAT in normal physiology and disease.

Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

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Dai Hongying

2013-01-01

Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.

Fatty acid CoA ligase-4 gene polymorphism influences fatty acid metabolism in metabolic syndrome, but not in depression.

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Zeman, Miroslav; Vecka, Marek; Jáchymová, Marie; Jirák, Roman; Tvrzická, Eva; Stanková, Barbora; Zák, Ales

2009-04-01

The composition of polyunsaturated fatty acids (PUFAs) in cell membranes and body tissues is altered in metabolic syndrome (MetS) and depressive disorder (DD). Within the cell, fatty acid coenzyme A (CoA) ligases (FACLs) activate PUFAs by esterifying with CoA. The FACL4 isoform prefers PUFAs (arachidonic and eicosapentaenoic acid) as substrates, and the FACL4 gene is mapped to Xq23. We have analyzed the association between the common single nucleotide polymorphism (SNP) (rs1324805, C to T substitution) in the first intron of the FACL4 gene and MetS or DD. The study included 113 healthy subjects (54 Males/59 Females), 56 MetS patients (34M/22F) and 41 DD patients (7M/34F). In MetS group, T-carriers and patients with CC or C0 (CC/C0) genotype did not differ in the values of metabolic indices of MetS and M/F ratio. Nevertheless, in comparison with CC/C0, the T-allele carriers were characterized by enhanced unfavorable changes in fatty acid metabolism typical for MetS: higher content of dihomogammalinolenic acid (P phosphatidylcholine (PC) (P = 0.052), lower index of Delta5 desaturation (P insulin, conjugated dienes and index of insulin resistance, but showed no significant association with the studied SNP. The present study shows that the common SNP (C to T substitution) in the first intron of the FACL4 gene is associated with altered FA composition of plasma phosphatidylcholines in patients with MetS.

Expression Profile of Genes Related to Drug Metabolism in Human Brain Tumors.

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Pantelis Stavrinou

Full Text Available Endogenous and exogenous compounds as well as carcinogens are metabolized and detoxified by phase I and II enzymes, the activity of which could be crucial to the inactivation and hence susceptibility to carcinogenic factors. The expression of these enzymes in human brain tumor tissue has not been investigated sufficiently. We studied the association between tumor pathology and the expression profile of seven phase I and II drug metabolizing genes (CYP1A1, CYP1B1, ALDH3A1, AOX1, GSTP1, GSTT1 and GSTM3 and some of their proteins.Using qRT-PCR and western blotting analysis the gene and protein expression in a cohort of 77 tumors were investigated. The major tumor subtypes were meningioma, astrocytoma and brain metastases, -the later all adenocarcinomas from a lung primary.Meningeal tumors showed higher expression levels for AOX1, CYP1B1, GSTM3 and GSTP1. For AOX1, GSTM and GSTP1 this could be verified on a protein level as well. A negative correlation between the WHO degree of malignancy and the strength of expression was identified on both transcriptional and translational level for AOX1, GSTM3 and GSTP1, although the results could have been biased by the prevalence of meningiomas and glioblastomas in the inevitably bipolar distribution of the WHO grades. A correlation between the gene expression and the protein product was observed for AOX1, GSTP1 and GSTM3 in astrocytomas.The various CNS tumors show different patterns of drug metabolizing gene expression. Our results suggest that the most important factor governing the expression of these enzymes is the histological subtype and to a far lesser extent the degree of malignancy itself.

Investigating multiple candidate genes and nutrients in the folate metabolism pathway to detect genetic and nutritional risk factors for lung cancer.

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Michael D Swartz

Full Text Available PURPOSE: Folate metabolism, with its importance to DNA repair, provides a promising region for genetic investigation of lung cancer risk. This project investigates genes (MTHFR, MTR, MTRR, CBS, SHMT1, TYMS, folate metabolism related nutrients (B vitamins, methionine, choline, and betaine and their gene-nutrient interactions. METHODS: We analyzed 115 tag single nucleotide polymorphisms (SNPs and 15 nutrients from 1239 and 1692 non-Hispanic white, histologically-confirmed lung cancer cases and controls, respectively, using stochastic search variable selection (a Bayesian model averaging approach. Analyses were stratified by current, former, and never smoking status. RESULTS: Rs6893114 in MTRR (odds ratio [OR] = 2.10; 95% credible interval [CI]: 1.20-3.48 and alcohol (drinkers vs. non-drinkers, OR = 0.48; 95% CI: 0.26-0.84 were associated with lung cancer risk in current smokers. Rs13170530 in MTRR (OR = 1.70; 95% CI: 1.10-2.87 and two SNP*nutrient interactions [betaine*rs2658161 (OR = 0.42; 95% CI: 0.19-0.88 and betaine*rs16948305 (OR = 0.54; 95% CI: 0.30-0.91] were associated with lung cancer risk in former smokers. SNPs in MTRR (rs13162612; OR = 0.25; 95% CI: 0.11-0.58; rs10512948; OR = 0.61; 95% CI: 0.41-0.90; rs2924471; OR = 3.31; 95% CI: 1.66-6.59, and MTHFR (rs9651118; OR = 0.63; 95% CI: 0.43-0.95 and three SNP*nutrient interactions (choline*rs10475407; OR = 1.62; 95% CI: 1.11-2.42; choline*rs11134290; OR = 0.51; 95% CI: 0.27-0.92; and riboflavin*rs8767412; OR = 0.40; 95% CI: 0.15-0.95 were associated with lung cancer risk in never smokers. CONCLUSIONS: This study identified possible nutrient and genetic factors related to folate metabolism associated with lung cancer risk, which could potentially lead to nutritional interventions tailored by smoking status to reduce lung cancer risk.

Rescue of Metabolic Alterations in AR113Q Skeletal Muscle by Peripheral Androgen Receptor Gene Silencing

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Elisa Giorgetti

2016-09-01

Full Text Available Spinal and bulbar muscular atrophy (SBMA, a progressive degenerative disorder, is caused by a CAG/glutamine expansion in the androgen receptor (polyQ AR. Recent studies demonstrate that skeletal muscle is an important site of toxicity that contributes to the SBMA phenotype. Here, we sought to identify critical pathways altered in muscle that underlie disease manifestations in AR113Q mice. This led to the unanticipated identification of gene expression changes affecting regulators of carbohydrate metabolism, similar to those triggered by denervation. AR113Q muscle exhibits diminished glycolysis, altered mitochondria, and an impaired response to exercise. Strikingly, the expression of genes regulating muscle energy metabolism is rescued following peripheral polyQ AR gene silencing by antisense oligonucleotides (ASO, a therapeutic strategy that alleviates disease. Our data establish the occurrence of a metabolic imbalance in SBMA muscle triggered by peripheral expression of the polyQ AR and indicate that alterations in energy utilization contribute to non-neuronal disease manifestations.

Shift work or food intake during the rest phase promotes metabolic disruption and desynchrony of liver genes in male rats.

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Salgado-Delgado, Roberto C; Saderi, Nadia; Basualdo, María del Carmen; Guerrero-Vargas, Natali N; Escobar, Carolina; Buijs, Ruud M

2013-01-01

In the liver, clock genes are proposed to drive metabolic rhythms. These gene rhythms are driven by the suprachiasmatic nucleus (SCN) mainly by food intake and via autonomic and hormonal pathways. Forced activity during the normal rest phase, induces also food intake, thus neglecting the signals of the SCN, leading to conflicting time signals to target tissues of the SCN. The present study explored in a rodent model of night-work the influence of food during the normal sleep period on the synchrony of gene expression between clock genes and metabolic genes in the liver. Male Wistar rats were exposed to forced activity for 8 h either during the rest phase (day) or during the active phase (night) by using a slow rotating wheel. In this shift work model food intake shifts spontaneously to the forced activity period, therefore the influence of food alone without induced activity was tested in other groups of animals that were fed ad libitum, or fed during their rest or active phase. Rats forced to be active and/or eating during their rest phase, inverted their daily peak of Per1, Bmal1 and Clock and lost the rhythm of Per2 in the liver, moreover NAMPT and metabolic genes such as Pparα lost their rhythm and thus their synchrony with clock genes. We conclude that shift work or food intake in the rest phase leads to desynchronization within the liver, characterized by misaligned temporal patterns of clock genes and metabolic genes. This may be the cause of the development of the metabolic syndrome and obesity in individuals engaged in shift work.

The mRNA expression profile of metabolic genes relative to MHC isoform pattern in human skeletal muscles

DEFF Research Database (Denmark)

Plomgaard, Peter; Penkowa, Milena; Leick, Lotte

2006-01-01

The metabolic profile of rodent muscle is generally reflected in the myosin heavy chain (MHC) fiber-type composition. The present study was conducted to test the hypothesis that metabolic gene expression is not tightly coupled with MHC fiber-type composition for all genes in human skeletal muscle....... Triceps brachii, vastus lateralis quadriceps, and soleus muscle biopsies were obtained from normally physically active, healthy, young male volunteers, because these muscles are characterized by different fiber-type compositions. As expected, citrate synthase and 3-hydroxyacyl dehydrogenase activity...... of a broad range of metabolic genes. The triceps muscle had two- to fivefold higher MHC IIa, phosphofructokinase, and LDH A mRNA content and two- to fourfold lower MHC I, lipoprotein lipase, CD36, hormone-sensitive lipase, and LDH B and hexokinase II mRNA than vastus lateralis or soleus. Interestingly...

Repression of mitochondrial translation, respiration and a metabolic cycle-regulated gene, SLF1, by the yeast Pumilio-family protein Puf3p.

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Marc Chatenay-Lapointe

Full Text Available Synthesis and assembly of the mitochondrial oxidative phosphorylation (OXPHOS system requires genes located both in the nuclear and mitochondrial genomes, but how gene expression is coordinated between these two compartments is not fully understood. One level of control is through regulated expression mitochondrial ribosomal proteins and other factors required for mitochondrial translation and OXPHOS assembly, which are all products of nuclear genes that are subsequently imported into mitochondria. Interestingly, this cadre of genes in budding yeast has in common a 3'-UTR element that is bound by the Pumilio family protein, Puf3p, and is coordinately regulated under many conditions, including during the yeast metabolic cycle. Multiple functions have been assigned to Puf3p, including promoting mRNA degradation, localizing nucleus-encoded mitochondrial transcripts to the outer mitochondrial membrane, and facilitating mitochondria-cytoskeletal interactions and motility. Here we show that Puf3p has a general repressive effect on mitochondrial OXPHOS abundance, translation, and respiration that does not involve changes in overall mitochondrial biogenesis and largely independent of TORC1-mitochondrial signaling. We also identified the cytoplasmic translation factor Slf1p as yeast metabolic cycle-regulated gene that is repressed by Puf3p at the post-transcriptional level and promotes respiration and extension of yeast chronological life span when over-expressed. Altogether, these results should facilitate future studies on which of the many functions of Puf3p is most relevant for regulating mitochondrial gene expression and the role of nuclear-mitochondrial communication in aging and longevity.

Ghrelin Gene Variants Influence on Metabolic Syndrome Components in Aged Spanish Population

OpenAIRE

Mora, Mireia; Adam, Victoria; Palomera, Elisabet; Blesa, Sebastian; Díaz, Gonzalo; Buquet, Xavier; Serra-Prat, Mateu; Martín-Escudero, Juan Carlos; Palanca, Ana; Chaves, Javier Felipe; Puig-Domingo, Manuel

2015-01-01

BACKGROUND: The role of genetic variations within the ghrelin gene on cardiometabolic profile and nutritional status is still not clear in humans, particularly in elderly people. OBJECTIVES: We investigated six SNPs of the ghrelin gene and their relationship with metabolic syndrome (MS) components. SUBJECTS AND METHODS: 824 subjects (413 men/411 women, age 77.31±5.04) participating in the Mataró aging study (n = 310) and the Hortega study (n = 514) were analyzed. Anthropometric variables, ghr...

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

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Adam Alexander Thil Smith

2012-05-01

Full Text Available Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes, a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short. The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

DGIdb 3.0: a redesign and expansion of the drug-gene interaction database.

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Cotto, Kelsy C; Wagner, Alex H; Feng, Yang-Yang; Kiwala, Susanna; Coffman, Adam C; Spies, Gregory; Wollam, Alex; Spies, Nicholas C; Griffith, Obi L; Griffith, Malachi

2018-01-04

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.

Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

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Van Bel, Michiel; Coppens, Frederik

2017-01-01

Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

THE ROLE OF NUTRIGENOMICS IN CORRECTION OF METABOLIC ABNORMALITIES

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I. V. Misnikova

2015-01-01

Full Text Available In some patients, diet and increased physical exercise are not effective enough to prevent the development of type 2 diabetes mellitus. At present, a  new approach is proposed to elaborate the diet with consideration of specific need of an individual. Food components can cause changes in metabolism through their influence on activity of certain genes that subsequently influence human proteome and metabolome. It is assumed that nutrients may influence methylation of deoxyribonucleic acid. A number of studies established an interaction between some foods and genes associated with obesity and type 2 diabetes mellitus. Diet recommendations based on presence of certain gene polymorphisms have been developed. The spectrum of gene polymorphisms that is necessary to assess in individuals with metabolic abnormalities or with high risk of their development has been also defined.

A combination test for detection of gene-environment interaction in cohort studies.

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Coombes, Brandon; Basu, Saonli; McGue, Matt

2017-07-01

Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene. We extend recently developed score statistic based genetic association testing approaches to the G-E interaction testing problem. We also propose tests for interaction using gene-based summary measures that pool variants together. Although it has recently been shown that these summary measures can be biased and may lead to inflated type I error, we show that under several realistic scenarios, we can still provide valid tests of interaction. These tests use significantly less degrees of freedom and thus can have much higher power to detect interaction. Additionally, we demonstrate that the iSeq-aSum-min test, which combines a gene-based summary measure test, iSeq-aSum-G, and an interaction-based summary measure test, iSeq-aSum-I, provides a powerful alternative to test G-E interaction. We demonstrate the performance of these approaches using simulation studies and illustrate their performance to study interaction between the SNPs in several candidate genes and family climate environment on alcohol consumption using the Minnesota Center for Twin and Family Research dataset. © 2017 WILEY PERIODICALS, INC.

Effects of long-term football training on the expression profile of genes involved in muscle oxidative metabolism

DEFF Research Database (Denmark)

Alfieri, A; Martone, D; Randers, Morten Bredsgaard

2015-01-01

and a muscle biopsy from the vastus lateralis were collected at T0 (pre intervention) and at T1 (post intervention). Gene expression was measured by RTqPCR on RNA extracted from muscle biopsies. The expression levels of the genes principally involved in energy metabolism (PPARγ, adiponectin, AMPKα1/α2, TFAM...... to improve the expression of muscle molecular biomarkers that are correlated to oxidative metabolism in healthy males....... are directly or indirectly involved in the glucose and lipid oxidative metabolism. Multiple linear regression analysis revealed that fat percentage was independently associated with NAMPT, PPARγ and adiponectin expression. In conclusion, long-term recreational football training could be a useful tool...

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

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Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-11-28

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.

Interactions between Gut Microbiota, Host Genetics and Diet Modulate the Predisposition to Obesity and Metabolic Syndrome.

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Ussar, Siegfried; Griffin, Nicholas W; Bezy, Olivier; Fujisaka, Shiho; Vienberg, Sara; Softic, Samir; Deng, Luxue; Bry, Lynn; Gordon, Jeffrey I; Kahn, C Ronald

2015-09-01

Obesity, diabetes, and metabolic syndrome result from complex interactions between genetic and environmental factors, including the gut microbiota. To dissect these interactions, we utilized three commonly used inbred strains of mice-obesity/diabetes-prone C57Bl/6J mice, obesity/diabetes-resistant 129S1/SvImJ from Jackson Laboratory, and obesity-prone but diabetes-resistant 129S6/SvEvTac from Taconic-plus three derivative lines generated by breeding these strains in a new, common environment. Analysis of metabolic parameters and gut microbiota in all strains and their environmentally normalized derivatives revealed strong interactions between microbiota, diet, breeding site, and metabolic phenotype. Strain-dependent and strain-independent correlations were found between specific microbiota and phenotypes, some of which could be transferred to germ-free recipient animals by fecal transplantation. Environmental reprogramming of microbiota resulted in 129S6/SvEvTac becoming obesity resistant. Thus, development of obesity/metabolic syndrome is the result of interactions between gut microbiota, host genetics, and diet. In permissive genetic backgrounds, environmental reprograming of microbiota can ameliorate development of metabolic syndrome. Copyright © 2015 Elsevier Inc. All rights reserved.

Evidence for plasticity genotypes in a gene-gene-environment interaction : the TRAILS study

NARCIS (Netherlands)

Nederhof, E; Bouma, Esther; Riese, Harriette; Laceulle, Odilia; Ormel, J.; Oldehinkel, A.J.

2010-01-01

The purpose was to study how functional polymorphisms in the brain derived neurotrophic factor gene (BDNF val66met) and the serotonin transporter gene linked promotor region (5-HTTLPR) interact with childhood adversities in predicting Effortful Control. Effortful Control refers to the ability to

Selection-, age-, and exercise-dependence of skeletal muscle gene expression patterns in a rat model of metabolic fitness.

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Ren, Yu-Yu; Koch, Lauren G; Britton, Steven L; Qi, Nathan R; Treutelaar, Mary K; Burant, Charles F; Li, Jun Z

2016-11-01

Intrinsic aerobic exercise capacity can influence many complex traits including obesity and aging. To study this connection we established two rat lines by divergent selection of untrained aerobic capacity. After 32 generations the high capacity runners (HCR) and low capacity runners (LCR) differed in endurance running distance and body fat, blood glucose, other health indicators, and natural life span. To understand the interplay among genetic differences, chronological age, and acute exercise we performed microarray-based gene expression analyses in skeletal muscle with a 2×2×2 design to simultaneously compare HCR and LCR, old and young animals, and rest and exhaustion. Transcripts for mitochondrial function are expressed higher in HCRs than LCRs at both rest and exhaustion and for both age groups. Expression of cell adhesion and extracellular matrix genes tend to decrease with age. This and other age effects are more prominent in LCRs than HCRs, suggesting that HCRs have a slower aging process and this may be partly due to their better metabolic health. Strenuous exercise mainly affects transcription regulation and cellular response. The effects of any one factor often depend on the other two. For example, there are ∼140 and ∼110 line-exercise "interacting" genes for old and young animals, respectively. Many genes highlighted in our study are consistent with prior reports, but many others are novel. The gene- and pathway-level statistics for the main effects, either overall or stratified, and for all possible interactions, represent a rich reference dataset for understanding the interdependence among lines, aging, and exercise. Copyright © 2016 the American Physiological Society.

A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.

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Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang

2014-04-15

Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.

Parental smoking and risk of childhood brain tumors by functional polymorphisms in polycyclic aromatic hydrocarbon metabolism genes.

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Jessica L Barrington-Trimis

Full Text Available BACKGROUND: A recent meta-analysis suggested an association between exposure to paternal smoking during pregnancy and childhood brain tumor risk, but no studies have evaluated whether this association differs by polymorphisms in genes that metabolize tobacco-smoke chemicals. METHODS: We assessed 9 functional polymorphisms in 6 genes that affect the metabolism of polycyclic aromatic hydrocarbons (PAH to evaluate potential interactions with parental smoking during pregnancy in a population-based case-control study of childhood brain tumors. Cases (N = 202 were ≤10 years old, diagnosed from 1984-1991 and identified in three Surveillance, Epidemiology, and End Results (SEER registries in the western U.S. Controls in the same regions (N = 286 were frequency matched by age, sex, and study center. DNA for genotyping was obtained from archived newborn dried blood spots. RESULTS: We found positive interaction odds ratios (ORs for both maternal and paternal smoking during pregnancy, EPHX1 H139R, and childhood brain tumors (P(interaction = 0.02; 0.10, such that children with the high-risk (greater PAH activation genotype were at a higher risk of brain tumors relative to children with the low-risk genotype when exposed to tobacco smoke during pregnancy. A dose-response pattern for paternal smoking was observed among children with the EPHX1 H139R high-risk genotype only (OR(no exposure = 1.0; OR(≤3 hours/day = 1.32, 95% CI: 0.52-3.34; OR(>3 hours/day = 3.18, 95% CI: 0.92-11.0; P(trend = 0.07. CONCLUSION: Parental smoking during pregnancy may be a risk factor for childhood brain tumors among genetically susceptible children who more rapidly activate PAH in tobacco smoke.

GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.

Science.gov (United States)

Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan

2011-05-01

Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.

[Interaction between CYP450 enzymes and metabolism of traditional Chinese medicine as well as enzyme activity assay].

Science.gov (United States)

Lu, Tu-lin; Su, Lian-lin; Ji, De; Gu, Wei; Mao, Chun-qin

2015-09-01

Drugs are exogenous compounds for human bodies, and will be metabolized by many enzymes after administration. CYP450 enzyme, as a major metabolic enzyme, is an important phase I drug metabolizing enzyme. In human bodies, about 75% of drug metabolism is conducted by CYP450 enzymes, and CYP450 enzymes is the key factor for drug interactions between traditional Chinese medicine( TCM) -TCM, TCM-medicine and other drug combination. In order to make clear the interaction between metabolic enzymes and TCM metabolism, we generally chose the enzymatic activity as an evaluation index. That is to say, the enhancement or reduction of CYP450 enzyme activity was used to infer the inducing or inhibitory effect of active ingredients and extracts of traditional Chinese medicine on enzymes. At present, the common method for measuring metabolic enzyme activity is Cocktail probe drugs, and it is the key to select the suitable probe substrates. This is of great significance for study drug's absorption, distribution, metabolism and excretion (ADME) process in organisms. The study focuses on the interaction between TCMs, active ingredients, herbal extracts, cocktail probe substrates as well as CYP450 enzymes, in order to guide future studies.

Effects of Radiation and Dietary Iron on Expression of Genes and Proteins Involved in Drug Metabolism

Science.gov (United States)

Faust, K. M.; Wotring, V. E.

2014-01-01

Liver function, especially the rate of metabolic enzyme activities, determines the concentration of circulating drugs and the duration of their efficacy. Most pharmaceuticals are metabolized by the liver, and clinically-used medication doses are given with normal liver function in mind. A drug overdose can result in the case of a liver that is damaged and removing pharmaceuticals from the circulation at a rate slower than normal. Alternatively, if liver function is elevated and removing drugs from the system more quickly than usual, it would be as if too little drug had been given for effective treatment. Because of the importance of the liver in drug metabolism, we want to understand any effects of spaceflight on the enzymes of the liver. Dietary factors and exposure to radiation are aspects of spaceflight that are potential oxidative stressors and both can be modeled in ground experiments. In this experiment, we examined the effects of high dietary iron and low dose gamma radiation (individually and combined) on the gene expression of enzymes involved in drug metabolism, redox homeostasis, and DNA repair. METHODS All procedures were approved by the JSC Animal Care and Use Committee. Male Sprague-Dawley rats were divided into 4 groups (n=8); control, high Fe diet (650 mg iron/kg), radiation (fractionated 3 Gy exposure from a Cs- 137 source) and combined high Fe diet + radiation exposure. Animals were euthanized 24h after the last treatment of radiation; livers were removed immediately and flash -frozen in liquid nitrogen. Expression of genes thought to be involved in redox homeostasis, drug metabolism and DNA damage repair was measured by RT-qPCR. Where possible, protein expression of the same genes was measured by western blotting. All data are expressed as % change in expression normalized to reference gene expression; comparisons were then made of each treatment group to the sham exposed/ normal diet control group. Data was considered significant at phigh Fe

Genome-wide analysis of E. coli cell-gene interactions.

Science.gov (United States)

Cardinale, S; Cambray, G

2017-11-23

The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content

Genomic Evidence of Chemotrophic Metabolisms in Deep-Dwelling Chloroflexi Conferred by Ancient Horizontal Gene Transfer Events

Science.gov (United States)

Momper, L. M.; Magnabosco, C.; Amend, J.; Osburn, M. R.; Fournier, G. P.

2017-12-01

The marine and terrestrial subsurface biospheres represent quite likely the largest reservoirs for life on Earth, directly impacting surface processes and global cycles throughout Earth's history. In the deep subsurface biosphere (DSB) organic carbon and energy are often extremely scarce. However, archaea and bacteria are able to persist in the DSB to at least 3.5 km below surface [1]. Understanding how they persist, and by what metabolisms they subsist, are key questions in this biosphere. To address these questions we investigated 5 global DSB environments: one legacy mine in South Dakota, USA, 3 mines in South Africa and marine fluids circulating beneath the Juan de Fuca Ridge. Boreholes within these mines provided access to fluids buried beneath the earth's surface and sampled depths down to 3.1 km. Geochemical data were collected concomitantly with DNA for metagenomic sequencing. We examined genomes of the ancient and deeply branching Chloroflexi for metabolic capabilities and interrogated the geochemical drivers behind those metabolisms with in situ thermodynamic modeling of reaction energetics. In total, 23 Chloroflexi genomes were identified and analyzed from the 5 subsurface sites. Genes for nitrate reduction (nar) and sulfite reduction (dsr) were found in many of the South Africa Chloroflexi but were absent from genomes collected in South Dakota. Indeed, nitrate reduction was among the most energetically favorable reactions in South African fluids (10-14 kJ cell-1 sec -1 per mol of reactant) and sulfur reduction with Fe2+ or H2 was also exergonic [2]. Conversely, genes for nitrite and nitrous oxide reduction (nrf, nir and nos) were found in genomes collected in South Dakota and Juan de Fuca, but not South Africa. We examined the origin of genes conferring these metabolisms in the Chloroflexi genomes. We discovered evidence for horizontal gene transfer (HGT) for all of these putative metabolisms. Retention of these genes in Chloroflexi lineages indicates

Genome-wide search for gene-gene interactions in colorectal cancer.

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Shuo Jiao

Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.

Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli

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Jain Rishi

2009-12-01

Full Text Available Abstract Background RNA viruses are responsible for a variety of illnesses among people, including but not limited to the common cold, the flu, HIV, and ebola. Developing new drugs and new strategies for treating diseases caused by these viruses can be an expensive and time-consuming process. Mathematical modeling may be used to elucidate host-pathogen interactions and highlight potential targets for drug development, as well providing the basis for optimizing patient treatment strategies. The purpose of this work was to determine whether a genome-scale modeling approach could be used to understand how metabolism is impacted by the host-pathogen interaction during a viral infection. Escherichia coli/MS2 was used as the host-pathogen model system as MS2 is easy to work with, harmless to humans, but shares many features with eukaryotic viruses. In addition, the genome-scale metabolic model of E. coli is the most comprehensive model at this time. Results Employing a metabolic modeling strategy known as "flux balance analysis" coupled with experimental studies, we were able to predict how viral infection would alter bacterial metabolism. Based on our simulations, we predicted that cell growth and biosynthesis of the cell wall would be halted. Furthermore, we predicted a substantial increase in metabolic activity of the pentose phosphate pathway as a means to enhance viral biosynthesis, while a break down in the citric acid cycle was predicted. Also, no changes were predicted in the glycolytic pathway. Conclusions Through our approach, we have developed a technique of modeling virus-infected host metabolism and have investigated the metabolic effects of viral infection. These studies may provide insight into how to design better drugs. They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.

Nutrigenetics and Metabolic Disease: Current Status and Implications for Personalised Nutrition

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Phillips, Catherine M.

2013-01-01

Obesity, particularly central adiposity, is the primary causal factor in the development of insulin resistance, the hallmark of the metabolic syndrome (MetS), a common condition characterized by dyslipidaemia and hypertension, which is associated with increased risk of cardiovascular disease (CVD) and type 2 diabetes (T2DM). Interactions between genetic and environmental factors such as diet and lifestyle, particularly over-nutrition and sedentary behavior, promote the progression and pathogenesis of these polygenic diet-related diseases. Their current prevalence is increasing dramatically to epidemic proportions. Nutrition is probably the most important environmental factor that modulates expression of genes involved in metabolic pathways and the variety of phenotypes associated with obesity, the MetS and T2DM. Furthermore, the health effects of nutrients may be modulated by genetic variants. Nutrigenomics and nutrigenetics require an understanding of nutrition, genetics, biochemistry and a range of “omic” technologies to investigate the complex interaction between genetic and environmental factors relevant to metabolic health and disease. These rapidly developing fields of nutritional science hold much promise in improving nutrition for optimal personal and public health. This review presents the current state of the art in nutrigenetic research illustrating the significance of gene-nutrient interactions in the context of metabolic disease. PMID:23306188

Nutrigenetics and Metabolic Disease: Current Status and Implications for Personalised Nutrition

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Catherine M. Phillips

2013-01-01

Full Text Available Obesity, particularly central adiposity, is the primary causal factor in the development of insulin resistance, the hallmark of the metabolic syndrome (MetS, a common condition characterized by dyslipidaemia and hypertension, which is associated with increased risk of cardiovascular disease (CVD and type 2 diabetes (T2DM. Interactions between genetic and environmental factors such as diet and lifestyle, particularly over-nutrition and sedentary behavior, promote the progression and pathogenesis of these polygenic diet-related diseases. Their current prevalence is increasing dramatically to epidemic proportions. Nutrition is probably the most important environmental factor that modulates expression of genes involved in metabolic pathways and the variety of phenotypes associated with obesity, the MetS and T2DM. Furthermore, the health effects of nutrients may be modulated by genetic variants. Nutrigenomics and nutrigenetics require an understanding of nutrition, genetics, biochemistry and a range of “omic” technologies to investigate the complex interaction between genetic and environmental factors relevant to metabolic health and disease. These rapidly developing fields of nutritional science hold much promise in improving nutrition for optimal personal and public health. This review presents the current state of the art in nutrigenetic research illustrating the significance of gene-nutrient interactions in the context of metabolic disease.

Nutrigenetics and metabolic disease: current status and implications for personalised nutrition.

Science.gov (United States)

Phillips, Catherine M

2013-01-10

Obesity, particularly central adiposity, is the primary causal factor in the development of insulin resistance, the hallmark of the metabolic syndrome (MetS), a common condition characterized by dyslipidaemia and hypertension, which is associated with increased risk of cardiovascular disease (CVD) and type 2 diabetes (T2DM). Interactions between genetic and environmental factors such as diet and lifestyle, particularly over-nutrition and sedentary behavior, promote the progression and pathogenesis of these polygenic diet-related diseases. Their current prevalence is increasing dramatically to epidemic proportions. Nutrition is probably the most important environmental factor that modulates expression of genes involved in metabolic pathways and the variety of phenotypes associated with obesity, the MetS and T2DM. Furthermore, the health effects of nutrients may be modulated by genetic variants. Nutrigenomics and nutrigenetics require an understanding of nutrition, genetics, biochemistry and a range of "omic" technologies to investigate the complex interaction between genetic and environmental factors relevant to metabolic health and disease. These rapidly developing fields of nutritional science hold much promise in improving nutrition for optimal personal and public health. This review presents the current state of the art in nutrigenetic research illustrating the significance of gene-nutrient interactions in the context of metabolic disease.

Behavioral science and the study of gene-nutrition and gene-physical activity interactions in obesity research.

Science.gov (United States)

Faith, Myles S

2008-12-01

This report summarizes emerging opportunities for behavioral science to help advance the field of gene-environment and gene-behavior interactions, based on presentations at The National Cancer Institute (NCI) Workshop, "Gene-Nutrition and Gene-Physical Activity Interactions in the Etiology of Obesity." Three opportunities are highlighted: (i) designing potent behavioral "challenges" in experiments, (ii) determining viable behavioral phenotypes for genetics studies, and (iii) identifying specific measures of the environment or environmental exposures. Additional points are underscored, including the need to incorporate novel findings from neuroimaging studies regarding motivation and drive for eating and physical activity. Advances in behavioral science theory and methods can play an important role in advancing understanding of gene-brain-behavior relationships in obesity onset.

Gene interactions and genetics for yield and its attributes in grass ...

Indian Academy of Sciences (India)

A. K. PARIHAR

explaining the manifestation of complex traits such as yield. ... interactions (i, j, l) contributed towards the inheritance of traits in the given crosses. ... Keywords. grass pea; scaling test; gene interactions; gene effects; heritability; Lathyrus sativus.

Comprehensive transcriptome analysis unravels the existence of crucial genes regulating primary metabolism during adventitious root formation in Petunia hybrida.

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Ahkami, Amirhossein; Scholz, Uwe; Steuernagel, Burkhard; Strickert, Marc; Haensch, Klaus-Thomas; Druege, Uwe; Reinhardt, Didier; Nouri, Eva; von Wirén, Nicolaus; Franken, Philipp; Hajirezaei, Mohammad-Reza

2014-01-01

To identify specific genes determining the initiation and formation of adventitious roots (AR), a microarray-based transcriptome analysis in the stem base of the cuttings of Petunia hybrida (line W115) was conducted. A microarray carrying 24,816 unique, non-redundant annotated sequences was hybridized to probes derived from different stages of AR formation. After exclusion of wound-responsive and root-regulated genes, 1,354 of them were identified which were significantly and specifically induced during various phases of AR formation. Based on a recent physiological model distinguishing three metabolic phases in AR formation, the present paper focuses on the response of genes related to particular metabolic pathways. Key genes involved in primary carbohydrate metabolism such as those mediating apoplastic sucrose unloading were induced at the early sink establishment phase of AR formation. Transcriptome changes also pointed to a possible role of trehalose metabolism and SnRK1 (sucrose non-fermenting 1- related protein kinase) in sugar sensing during this early step of AR formation. Symplastic sucrose unloading and nucleotide biosynthesis were the major processes induced during the later recovery and maintenance phases. Moreover, transcripts involved in peroxisomal beta-oxidation were up-regulated during different phases of AR formation. In addition to metabolic pathways, the analysis revealed the activation of cell division at the two later phases and in particular the induction of G1-specific genes in the maintenance phase. Furthermore, results point towards a specific demand for certain mineral nutrients starting in the recovery phase.

In tobacco BY-2 cells xyloglucan oligosaccharides alter the expression of genes involved in cell wall metabolism, signalling, stress responses, cell division and transcriptional control.

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González-Pérez, Lien; Perrotta, Lara; Acosta, Alexis; Orellana, Esteban; Spadafora, Natasha; Bruno, Leonardo; Bitonti, Beatrice M; Albani, Diego; Cabrera, Juan Carlos; Francis, Dennis; Rogers, Hilary J

2014-10-01

Xyloglucan oligosaccharides (XGOs) are breakdown products of XGs, the most abundant hemicelluloses of the primary cell walls of non-Poalean species. Treatment of cell cultures or whole plants with XGOs results in accelerated cell elongation and cell division, changes in primary root growth, and a stimulation of defence responses. They may therefore act as signalling molecules regulating plant growth and development. Previous work suggests an interaction with auxins and effects on cell wall loosening, however their mode of action is not fully understood. The effect of an XGO extract from tamarind (Tamarindus indica) on global gene expression was therefore investigated in tobacco BY-2 cells using microarrays. Over 500 genes were differentially regulated with similar numbers and functional classes of genes up- and down-regulated, indicating a complex interaction with the cellular machinery. Up-regulation of a putative XG endotransglycosylase/hydrolase-related (XTH) gene supports the mechanism of XGO action through cell wall loosening. Differential expression of defence-related genes supports a role for XGOs as elicitors. Changes in the expression of genes related to mitotic control and differentiation also support previous work showing that XGOs are mitotic inducers. XGOs also affected expression of several receptor-like kinase genes and transcription factors. Hence, XGOs have significant effects on expression of genes related to cell wall metabolism, signalling, stress responses, cell division and transcriptional control.

Genes2FANs: connecting genes through functional association networks

Science.gov (United States)

2012-01-01

Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in

The Effect of Selenium Supplementation on Glucose Homeostasis and the Expression of Genes Related to Glucose Metabolism

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Ewa Jablonska

2016-12-01

Full Text Available The aim of the study was to evaluate the effect of selenium supplementation on the expression of genes associated with glucose metabolism in humans, in order to explain the unclear relationship between selenium and the risk of diabetes. For gene expression analysis we used archival samples of cDNA from 76 non-diabetic subjects supplemented with selenium in the previous study. The supplementation period was six weeks and the daily dose of selenium was 200 µg (as selenium yeast. Blood for mRNA isolation was collected at four time points: before supplementation, after two and four weeks of supplementation, and after four weeks of washout. The analysis included 15 genes encoding selected proteins involved in insulin signaling and glucose metabolism. In addition, HbA1c and fasting plasma glucose were measured at three and four time points, respectively. Selenium supplementation was associated with a significantly decreased level of HbA1c but not fasting plasma glucose (FPG and significant down-regulation of seven genes: INSR, ADIPOR1, LDHA, PDHA, PDHB, MYC, and HIF1AN. These results suggest that selenium may affect glycemic control at different levels of regulation, linked to insulin signaling, glycolysis, and pyruvate metabolism. Further research is needed to investigate mechanisms of such transcriptional regulation and its potential implication in direct metabolic effects.

Digestible and indigestible carbohydrates: interactions with postprandial lipid metabolism.

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Lairon, Denis; Play, Barbara; Jourdheuil-Rahmani, Dominique

2007-04-01

The balance between fats and carbohydrates in the human diet is still a matter of very active debate. Indeed, the processing of ordinary mixed meals involves complex processes within the lumen of the upper digestive tract for digestion, in the small intestine mucosa for absorption and resecretion, and in peripheral tissues and in the circulation for final handling. The purpose of this review is to focus on available knowledge on the interactions of digestible or indigestible carbohydrates with lipid and lipoprotein metabolism in the postprandial state. The observations made in humans after test meals are reported and interpreted in the light of recent findings on the cellular and molecular levels regarding possible interplays between carbohydrates and lipid moieties in some metabolic pathways. Digestible carbohydrates, especially readily digestible starches or fructose, have been shown to exacerbate and/or delay postprandial lipemia, whereas some fiber sources can lower it. While interactions between dietary fibers and the process of lipid digestion and absorption have been studied mainly in the last decades, recent studies have shown that dietary carbohydrate moieties (e.g., glucose) can stimulate the intestinal uptake of cholesterol and lipid resecretion. In addition to the well-known glucose/fructose transporters, a number of transport proteins have recently been involved in intestinal lipid processing, whose implications in such interactions are discussed. The potential importance of postprandial insulinemia in these processes is also evaluated in the light of recent findings. The interactions of carbohydrates and lipid moieties in the postprandial state may result from both acute and chronic effects, both at transcriptional and posttranscriptional levels.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

DEFF Research Database (Denmark)

Liu, Gang; Lee, Seunggeun; Lee, Alice W

2018-01-01

test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides power gain compared to the standard logistic regression analysis and better control of Type I error when compared to the analysis......There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances the power for testing multiplicative interaction in case......-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated Type I error in the corresponding tests can occur. This paper extends the empirical Bayes (EB) approach previously developed for multiplicative interaction that trades off between bias and efficiency...

GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

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Radhakrishnan Mahadevan

2012-10-01

With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

Gene-environment interactions involving functional variants

DEFF Research Database (Denmark)

Barrdahl, Myrto; Rudolph, Anja; Hopper, John L

2017-01-01

.36, 95% CI: 1.16-1.59, pint  = 1.9 × 10(-5) ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10...... epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER......) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP 

Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

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Jing Zhao

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions

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Edwards Jeremy S

2000-07-01

Full Text Available Abstract Background Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA. FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information. Results Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains. Conclusions We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation. Supplementary information: http://gcrg.ucsd.edu/supplementary_data/DeletionAnalysis/main.htm

Gene × Smoking Interactions on Human Brain Gene Expression: Finding Common Mechanisms in Adolescents and Adults

Science.gov (United States)

Wolock, Samuel L.; Yates, Andrew; Petrill, Stephen A.; Bohland, Jason W.; Blair, Clancy; Li, Ning; Machiraju, Raghu; Huang, Kun; Bartlett, Christopher W.

2013-01-01

Background: Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets…

NatalieQ: A web server for protein-protein interaction network querying

NARCIS (Netherlands)

El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

2014-01-01

Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

Host genes related to paneth cells and xenobiotic metabolism are associated with shifts in human ileum-associated microbial composition.

Directory of Open Access Journals (Sweden)

Tianyi Zhang

Full Text Available The aim of this study was to integrate human clinical, genotype, mRNA microarray and 16 S rRNA sequence data collected on 84 subjects with ileal Crohn's disease, ulcerative colitis or control patients without inflammatory bowel diseases in order to interrogate how host-microbial interactions are perturbed in inflammatory bowel diseases (IBD. Ex-vivo ileal mucosal biopsies were collected from the disease unaffected proximal margin of the ileum resected from patients who were undergoing initial intestinal surgery. Both RNA and DNA were extracted from the mucosal biopsy samples. Patients were genotyped for the three major NOD2 variants (Leufs1007, R702W, and G908R and the ATG16L1T300A variant. Whole human genome mRNA expression profiles were generated using Agilent microarrays. Microbial composition profiles were determined by 454 pyrosequencing of the V3-V5 hypervariable region of the bacterial 16 S rRNA gene. The results of permutation based multivariate analysis of variance and covariance (MANCOVA support the hypothesis that host mucosal Paneth cell and xenobiotic metabolism genes play an important role in host microbial interactions.

A real-time control system of gene expression using ligand-bound nucleic acid aptamer for metabolic engineering.

Science.gov (United States)

Wang, Jing; Cui, Xun; Yang, Le; Zhang, Zhe; Lv, Liping; Wang, Haoyuan; Zhao, Zhenmin; Guan, Ningzi; Dong, Lichun; Chen, Rachel

2017-07-01

Artificial control of bio-functions through regulating gene expression is one of the most important and attractive technologies to build novel living systems that are useful in the areas of chemical synthesis, nanotechnology, pharmacology, cell biology. Here, we present a novel real-time control system of gene regulation that includes an enhancement element by introducing duplex DNA aptamers upstream promoter and a repression element by introducing a RNA aptamer upstream ribosome binding site. With the presence of ligands corresponding to the DNA aptamers, the expression of the target gene can be potentially enhanced at the transcriptional level by strengthening the recognition capability of RNAP to the recognition region and speeding up the separation efficiency of the unwinding region due to the induced DNA bubble around the thrombin-bound aptamers; while with the presence of RNA aptamer ligand, the gene expression can be repressed at the translational level by weakening the recognition capability of ribosome to RBS due to the shielding of RBS by the formed aptamer-ligand complex upstream RBS. The effectiveness and potential utility of the developed gene regulation system were demonstrated by regulating the expression of ecaA gene in the cell-free systems. The realistic metabolic engineering application of the system has also tested by regulating the expression of mgtC gene and thrombin cDNA in Escherichia coli JD1021 for controlling metabolic flux and improving thrombin production, verifying that the real-time control system of gene regulation is able to realize the dynamic regulation of gene expression with potential applications in bacterial physiology studies and metabolic engineering. Copyright © 2017. Published by Elsevier Inc.

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

Science.gov (United States)

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web

In silico method for modelling metabolism and gene product expression at genome scale

Energy Technology Data Exchange (ETDEWEB)

Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

2012-07-03

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Science.gov (United States)

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-05-01

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

Cholesterol Transporters ABCA1 and ABCG1 Gene Expression in Peripheral Blood Mononuclear Cells in Patients with Metabolic Syndrome

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Zahra Tavoosi

2015-01-01

Full Text Available ABCA1 and ABCG1 genes encode the cholesterol transporter proteins that play a key role in cholesterol and phospholipids homeostasis. This study was aimed at evaluating and comparing ABCA1 and ABCG1 genes expression in metabolic syndrome patients and healthy individuals. This case-control study was performed on 36 patients with metabolic syndrome and the same number of healthy individuals in Hamadan (west of Iran during 2013-2014. Total RNA was extracted from mononuclear cells and purified using RNeasy Mini Kit column. The expression of ABCA1 and ABCG1 genes was performed by qRT-PCR. Lipid profile and fasting blood glucose were measured using colorimetric procedures. ABCG1 expression in metabolic syndrome patients was significantly lower (about 75% compared to that of control group, while for ABCA1 expression, there was no significant difference between the two studied groups. Comparison of other parameters such as HDL-C, FBS, BMI, waist circumference, and systolic and diastolic blood pressure between metabolic syndrome patients and healthy individuals showed significant differences (P<0.05. Decrease in ABCG1 expression in metabolic syndrome patients compared to healthy individuals suggests that hyperglycemia, related metabolites, and hyperlipidemia over the transporter capacity resulted in decreased expression of ABCG1. Absence of a significant change in ABCA1 gene expression between two groups can indicate a different regulation mechanism for ABCA1 expression.

ALK7 Gene Polymorphism is Associated with Metabolic Syndrome Risk and Cardiovascular Remodeling

Energy Technology Data Exchange (ETDEWEB)

Zhang, Wenchao; Wang, Hui; Zhang, Wei [Key Laboratory of Cardiovascular Remodeling and Function Research Chinese Ministry of Education and Chinese Ministry of Public Health, Qilu Hospital of Shandong University, Jinan (China); Lv, Ruijuan [Department of Emergency, Qilu Hospital of Shandong University, Jinan (China); Wang, Zhihao [Key Laboratory of Cardiovascular Remodeling and Function Research Chinese Ministry of Education and Chinese Ministry of Public Health, Qilu Hospital of Shandong University, Jinan (China); Department of Geriatrics, Qilu Hospital of Shandong University, Jinan (China); Shang, Yuanyuan; Zhang, Yun; Zhong, Ming [Key Laboratory of Cardiovascular Remodeling and Function Research Chinese Ministry of Education and Chinese Ministry of Public Health, Qilu Hospital of Shandong University, Jinan (China); Chen, Yuguo; Tang, Mengxiong, E-mail: tangmengxiongsdu8@163.com [Key Laboratory of Cardiovascular Remodeling and Function Research Chinese Ministry of Education and Chinese Ministry of Public Health, Qilu Hospital of Shandong University, Jinan (China); Department of Emergency, Qilu Hospital of Shandong University, Jinan (China)

2013-08-15

Activin receptor-like kinase 7 (ALK7) is a type I receptor for the TGF-β superfamily and has recently been demonstrated to play an important role in the maintenance of metabolic homeostasis. To investigate the association of the ALK7 gene polymorphism with metabolic syndrome (MetS) and cardiovascular remodeling in MetS patients. The single nucleotide polymorphism rs13010956 in the ALK7 gene was genotyped in 351 Chinese subjects undergoing carotid and cardiac ultrasonography. The associations of the ALK7 gene polymorphism with the MetS phenotype, MetS parameters, and cardiovascular ultrasonic features were analyzed. The rs13010956 polymorphism in the ALK7 gene was found to be significantly associated with the MetS phenotype in females (p < 0.05) and was also significantly associated with blood pressure in the total (p < 0.05) and female populations (p < 0.01). Further analysis revealed that rs13010956 was associated with mean intima-media thickness of the carotid arteries in females (p < 0.05). After control for body mass index, blood pressure, fasting blood glucose, and triglycerides, rs13010956 was also found to be significantly associated with left ventricular mass index in the total (p < 0.05) and female populations (p < 0.05). Our findings suggested that the ALK7 gene polymorphism rs13010956 was significantly associated with MetS risk in females and may be involved in cardiovascular remodeling in MetS patients.

ALK7 Gene Polymorphism is Associated with Metabolic Syndrome Risk and Cardiovascular Remodeling

International Nuclear Information System (INIS)

Zhang, Wenchao; Wang, Hui; Zhang, Wei; Lv, Ruijuan; Wang, Zhihao; Shang, Yuanyuan; Zhang, Yun; Zhong, Ming; Chen, Yuguo; Tang, Mengxiong

2013-01-01

Activin receptor-like kinase 7 (ALK7) is a type I receptor for the TGF-β superfamily and has recently been demonstrated to play an important role in the maintenance of metabolic homeostasis. To investigate the association of the ALK7 gene polymorphism with metabolic syndrome (MetS) and cardiovascular remodeling in MetS patients. The single nucleotide polymorphism rs13010956 in the ALK7 gene was genotyped in 351 Chinese subjects undergoing carotid and cardiac ultrasonography. The associations of the ALK7 gene polymorphism with the MetS phenotype, MetS parameters, and cardiovascular ultrasonic features were analyzed. The rs13010956 polymorphism in the ALK7 gene was found to be significantly associated with the MetS phenotype in females (p < 0.05) and was also significantly associated with blood pressure in the total (p < 0.05) and female populations (p < 0.01). Further analysis revealed that rs13010956 was associated with mean intima-media thickness of the carotid arteries in females (p < 0.05). After control for body mass index, blood pressure, fasting blood glucose, and triglycerides, rs13010956 was also found to be significantly associated with left ventricular mass index in the total (p < 0.05) and female populations (p < 0.05). Our findings suggested that the ALK7 gene polymorphism rs13010956 was significantly associated with MetS risk in females and may be involved in cardiovascular remodeling in MetS patients

Genetic dissection in a mouse model reveals interactions between carotenoids and lipid metabolism[S

Science.gov (United States)

Palczewski, Grzegorz; Widjaja-Adhi, M. Airanthi K.; Amengual, Jaume; Golczak, Marcin; von Lintig, Johannes

2016-01-01

Carotenoids affect a rich variety of physiological functions in nature and are beneficial for human health. However, knowledge about their biological action and the consequences of their dietary accumulation in mammals is limited. Progress in this research field is limited by the expeditious metabolism of carotenoids in rodents and the confounding production of apocarotenoid signaling molecules. Herein, we established a mouse model lacking the enzymes responsible for carotenoid catabolism and apocarotenoid production, fed on either a β-carotene- or a zeaxanthin-enriched diet. Applying a genome wide microarray analysis, we assessed the effects of the parent carotenoids on the liver transcriptome. Our analysis documented changes in pathways for liver lipid metabolism and mitochondrial respiration. We biochemically defined these effects, and observed that β-carotene accumulation resulted in an elevation of liver triglycerides and liver cholesterol, while zeaxanthin accumulation increased serum cholesterol levels. We further show that carotenoids were predominantly transported within HDL particles in the serum of mice. Finally, we provide evidence that carotenoid accumulation influenced whole-body respiration and energy expenditure. Thus, we observed that accumulation of parent carotenoids interacts with lipid metabolism and that structurally related carotenoids display distinct biological functions in mammals. PMID:27389691

Comprehensive Transcriptome Analysis Unravels the Existence of Crucial Genes Regulating Primary Metabolism during Adventitious Root Formation in Petunia hybrida

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Ahkami, Amirhossein; Scholz, Uwe; Steuernagel, Burkhard; Strickert, Marc; Haensch, Klaus-Thomas; Druege, Uwe; Reinhardt, Didier; Nouri, Eva; von Wirén, Nicolaus; Franken, Philipp; Hajirezaei, Mohammad-Reza

2014-01-01

To identify specific genes determining the initiation and formation of adventitious roots (AR), a microarray-based transcriptome analysis in the stem base of the cuttings of Petunia hybrida (line W115) was conducted. A microarray carrying 24,816 unique, non-redundant annotated sequences was hybridized to probes derived from different stages of AR formation. After exclusion of wound-responsive and root-regulated genes, 1,354 of them were identified which were significantly and specifically induced during various phases of AR formation. Based on a recent physiological model distinguishing three metabolic phases in AR formation, the present paper focuses on the response of genes related to particular metabolic pathways. Key genes involved in primary carbohydrate metabolism such as those mediating apoplastic sucrose unloading were induced at the early sink establishment phase of AR formation. Transcriptome changes also pointed to a possible role of trehalose metabolism and SnRK1 (sucrose non-fermenting 1- related protein kinase) in sugar sensing during this early step of AR formation. Symplastic sucrose unloading and nucleotide biosynthesis were the major processes induced during the later recovery and maintenance phases. Moreover, transcripts involved in peroxisomal beta-oxidation were up-regulated during different phases of AR formation. In addition to metabolic pathways, the analysis revealed the activation of cell division at the two later phases and in particular the induction of G1-specific genes in the maintenance phase. Furthermore, results point towards a specific demand for certain mineral nutrients starting in the recovery phase. PMID:24978694

Comprehensive transcriptome analysis unravels the existence of crucial genes regulating primary metabolism during adventitious root formation in Petunia hybrida.

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Amirhossein Ahkami

Full Text Available To identify specific genes determining the initiation and formation of adventitious roots (AR, a microarray-based transcriptome analysis in the stem base of the cuttings of Petunia hybrida (line W115 was conducted. A microarray carrying 24,816 unique, non-redundant annotated sequences was hybridized to probes derived from different stages of AR formation. After exclusion of wound-responsive and root-regulated genes, 1,354 of them were identified which were significantly and specifically induced during various phases of AR formation. Based on a recent physiological model distinguishing three metabolic phases in AR formation, the present paper focuses on the response of genes related to particular metabolic pathways. Key genes involved in primary carbohydrate metabolism such as those mediating apoplastic sucrose unloading were induced at the early sink establishment phase of AR formation. Transcriptome changes also pointed to a possible role of trehalose metabolism and SnRK1 (sucrose non-fermenting 1- related protein kinase in sugar sensing during this early step of AR formation. Symplastic sucrose unloading and nucleotide biosynthesis were the major processes induced during the later recovery and maintenance phases. Moreover, transcripts involved in peroxisomal beta-oxidation were up-regulated during different phases of AR formation. In addition to metabolic pathways, the analysis revealed the activation of cell division at the two later phases and in particular the induction of G1-specific genes in the maintenance phase. Furthermore, results point towards a specific demand for certain mineral nutrients starting in the recovery phase.

An interaction map of circulating metabolites, immune gene networks, and their genetic regulation.

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Nath, Artika P; Ritchie, Scott C; Byars, Sean G; Fearnley, Liam G; Havulinna, Aki S; Joensuu, Anni; Kangas, Antti J; Soininen, Pasi; Wennerström, Annika; Milani, Lili; Metspalu, Andres; Männistö, Satu; Würtz, Peter; Kettunen, Johannes; Raitoharju, Emma; Kähönen, Mika; Juonala, Markus; Palotie, Aarno; Ala-Korpela, Mika; Ripatti, Samuli; Lehtimäki, Terho; Abraham, Gad; Raitakari, Olli; Salomaa, Veikko; Perola, Markus; Inouye, Michael

2017-08-01

Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.

Interactions between host genetics and gut microbiome in diabetes and metabolic syndrome

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Siegfried Ussar

2016-09-01

Major conclusions: Understanding these complex interactions will help in the development of novel treatments for microbiome-related metabolic diseases. This article is part of a special issue on microbiota.

Assessment of gene-by-sex interaction effect on bone mineral density

DEFF Research Database (Denmark)

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M

2012-01-01

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and ......Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome...

Homeobox gene Dlx-2 is implicated in metabolic stress-induced necrosis

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Lim Sung-Chul

2011-09-01

Full Text Available Abstract Background In contrast to tumor-suppressive apoptosis and autophagic cell death, necrosis promotes tumor progression by releasing the pro-inflammatory and tumor-promoting cytokine high mobility group box 1 (HMGB1, and its presence in tumor patients is associated with poor prognosis. Thus, necrosis has important clinical implications in tumor development; however, its molecular mechanism remains poorly understood. Results In the present study, we show that Distal-less 2 (Dlx-2, a homeobox gene of the Dlx family that is involved in embryonic development, is induced in cancer cell lines dependently of reactive oxygen species (ROS in response to glucose deprivation (GD, one of the metabolic stresses occurring in solid tumors. Increased Dlx-2 expression was also detected in the inner regions, which experience metabolic stress, of human tumors and of a multicellular tumor spheroid, an in vitro model of solid tumors. Dlx-2 short hairpin RNA (shRNA inhibited metabolic stress-induced increase in propidium iodide-positive cell population and HMGB1 and lactate dehydrogenase (LDH release, indicating the important role(s of Dlx-2 in metabolic stress-induced necrosis. Dlx-2 shRNA appeared to exert its anti-necrotic effects by preventing metabolic stress-induced increases in mitochondrial ROS, which are responsible for triggering necrosis. Conclusions These results suggest that Dlx-2 may be involved in tumor progression via the regulation of metabolic stress-induced necrosis.

Cpt1a gene expression in peripheral blood mononuclear cells as an early biomarker of diet-related metabolic alterations

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Rubén Díaz-Rúa

2016-11-01

Full Text Available Background: Research on biomarkers that provide early information about the development of future metabolic alterations is an emerging discipline. Gene expression analysis in peripheral blood mononuclear cells (PBMC is a promising tool to identify subjects at risk of developing diet-related diseases. Objective: We analysed PBMC expression of key energy homeostasis-related genes in a time-course analysis in order to find out early markers of metabolic alterations due to sustained intake of high-fat (HF and high-protein (HP diets. Design: We administered HF and HP diets (4 months to adult Wistar rats in isocaloric conditions to a control diet, mainly to avoid overweight associated with the intake of hyperlipidic diets and, thus, to be able to characterise markers of metabolically obese normal-weight (MONW syndrome. PBMC samples were collected at different time points of dietary treatment and expression of relevant energy homeostatic genes analysed by real-time reverse transcription-polymerase chain reaction. Serum parameters related with metabolic syndrome, as well as fat deposition in liver, were also analysed. Results: The most outstanding results were those obtained for the expression of the lipolytic gene carnitine palmitoyltransferase 1a (Cpt1a. Cpt1a expression in PBMC increased after only 1 month of exposure to both unbalanced diets, and this increased expression was maintained thereafter. Interestingly, in the case of the HF diet, Cpt1a expression was altered even in the absence of increased body weight but correlated with alterations such as higher insulin resistance, alteration of serum lipid profile and, particularly, increased fat deposition in liver, a feature characteristic of metabolic syndrome, which was even observed in animals fed with HP diet. Conclusions: We propose Cpt1a gene expression analysis in PBMC as an early biomarker of metabolic alterations associated with MONW phenotype due to the intake of isocaloric HF diets, as

An integrated analysis of genes and pathways exhibiting metabolic differences between estrogen receptor positive breast cancer cells

International Nuclear Information System (INIS)

Mandal, Soma; Davie, James R

2007-01-01

The sex hormone estrogen (E2) is pivotal to normal mammary gland growth and differentiation and in breast carcinogenesis. In this in silico study, we examined metabolic differences between ER(+)ve breast cancer cells during E2 deprivation. Public repositories of SAGE and MA gene expression data generated from E2 deprived ER(+)ve breast cancer cell lines, MCF-7 and ZR75-1 were compared with normal breast tissue. We analyzed gene ontology (GO), enrichment, clustering, chromosome localization, and pathway profiles and performed multiple comparisons with cell lines and tumors with different ER status. In all GO terms, biological process (BP), molecular function (MF), and cellular component (CC), MCF-7 had higher gene utilization than ZR75-1. Various analyses showed a down-regulated immune function, an up-regulated protein (ZR75-1) and glucose metabolism (MCF-7). A greater percentage of 77 common genes localized to the q arm of all chromosomes, but in ZR75-1 chromosomes 11, 16, and 19 harbored more overexpressed genes. Despite differences in gene utilization (electron transport, proteasome, glycolysis/gluconeogenesis) and expression (ribosome) in both cells, there was an overall similarity of ZR75-1 with ER(-)ve cell lines and ER(+)ve/ER(-)ve breast tumors. This study demonstrates integral metabolic differences may exist within the same cell subtype (luminal A) in representative ER(+)ve cell line models. Selectivity of gene and pathway usage for strategies such as energy requirement minimization, sugar utilization by ZR75-1 contrasted with MCF-7 cells, expressing genes whose protein products require ATP utilization. Such characteristics may impart aggressiveness to ZR75-1 and may be prognostic determinants of ER(+)ve breast tumors

From metabolism to ecology: cross-feeding interactions shape the balance between polymicrobial conflict and mutualism.

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Estrela, Sylvie; Trisos, Christopher H; Brown, Sam P

2012-11-01

Polymicrobial interactions are widespread in nature and play a major role in maintaining human health and ecosystems. Whenever one organism uses metabolites produced by another organism as energy or nutrient sources, it is called cross-feeding. The ecological outcomes of cross-feeding interactions are poorly understood and potentially diverse: mutualism, competition, exploitation, or commensalism. A major reason for this uncertainty is the lack of theoretical approaches linking microbial metabolism to microbial ecology. To address this issue, we explore the dynamics of a one-way interspecific cross-feeding interaction in which food can be traded for a service (detoxification). Our results show that diverse ecological interactions (competition, mutualism, exploitation) can emerge from this simple cross-feeding interaction and can be predicted by the metabolic, demographic, and environmental parameters that govern the balance of the costs and benefits of association. In particular, our model predicts stronger mutualism for intermediate by-product toxicity because the resource-service exchange is constrained to the service being neither too vital (high toxicity impairs resource provision) nor dispensable (low toxicity reduces need for service). These results support the idea that bridging microbial ecology and metabolism is a critical step toward a better understanding of the factors governing the emergence and dynamics of polymicrobial interactions.

Expression profiling of Crambe abyssinica under arsenate stress identifies genes and gene networks involved in arsenic metabolism and detoxification

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Kandasamy Suganthi

2010-06-01

Full Text Available Abstract Background Arsenic contamination is widespread throughout the world and this toxic metalloid is known to cause cancers of organs such as liver, kidney, skin, and lung in human. In spite of a recent surge in arsenic related studies, we are still far from a comprehensive understanding of arsenic uptake, detoxification, and sequestration in plants. Crambe abyssinica, commonly known as 'abyssinian mustard', is a non-food, high biomass oil seed crop that is naturally tolerant to heavy metals. Moreover, it accumulates significantly higher levels of arsenic as compared to other species of the Brassicaceae family. Thus, C. abyssinica has great potential to be utilized as an ideal inedible crop for phytoremediation of heavy metals and metalloids. However, the mechanism of arsenic metabolism in higher plants, including C. abyssinica, remains elusive. Results To identify the differentially expressed transcripts and the pathways involved in arsenic metabolism and detoxification, C. abyssinica plants were subjected to arsenate stress and a PCR-Select Suppression Subtraction Hybridization (SSH approach was employed. A total of 105 differentially expressed subtracted cDNAs were sequenced which were found to represent 38 genes. Those genes encode proteins functioning as antioxidants, metal transporters, reductases, enzymes involved in the protein degradation pathway, and several novel uncharacterized proteins. The transcripts corresponding to the subtracted cDNAs showed strong upregulation by arsenate stress as confirmed by the semi-quantitative RT-PCR. Conclusions Our study revealed novel insights into the plant defense mechanisms and the regulation of genes and gene networks in response to arsenate toxicity. The differential expression of transcripts encoding glutathione-S-transferases, antioxidants, sulfur metabolism, heat-shock proteins, metal transporters, and enzymes in the ubiquitination pathway of protein degradation as well as several unknown