Regulation of metabolic genes in human skeletal muscle by short-term exercise and diet manipulation

Changes in dietary macronutrient intake alter muscle and blood substrate availability and are important for regulating gene expression. However, few studies have examined the effects of diet manipulation on gene expression in human skeletal muscle. The aim of this study was to quantify the extent to which altering substrate availability impacts on subsequent mRNA abundance of a subset of carbohydrate (CHO)- and fat-related genes. Seven subjects consumed either a low- (LOW; 0.7 g/kg body mass CHO) or high- (HIGH; 10 g/kg body mass CHO) CHO diet for 48 h after performing an exhaustive exercise bout to deplete muscle glycogen stores. After intervention, resting muscle and blood samples were taken. Muscle was analyzed for the gene abundances of GLUT4, glycogenin, pyruvate dehydrogenase kinase-4 (PDK-4), fatty acid translocase (FAT/CD36), carnitine palmitoyltransferase I (CPT I), hormone-sensitive lipase (HSL), β-hydroxyacyl-CoA dehydrogenase (΄β-HAD), and uncoupling binding protein-3 (UCP3), and blood samples for glucose, insulin, and free fatty acid (FFA) concentrations. Glycogen-depleting exercise and HIGH-CHO resulted in a 300% increase in muscle glycogen content (P < 0.001) relative to the LOW-CHO condition. FFA concentrations were twofold higher after LOW- vs. HIGH-CHO (P < 0.05). The exercise-diet manipulation exerted a significant effect on transcription of all carbohydrate-related genes, with an increase in GLUT4 and glycogenin mRNA abundance and a reduction in PDK-4 transcription after HIGH-CHO (all P < 0.05). FAT/CD36 (P < 0.05) and UCP3 (P < 0.01) gene transcriptions were increased following LOW-CHO. We conclude that 1) there was a rapid capacity for a short-term exercise and diet intervention to exert coordinated changes in the mRNA transcription of metabolic related genes, and 2) genes involved in glucose regulation are increased following a high-carbohydrate diet.

RRHGE: a novel approach to classify the estrogen receptor based breast cancer subtypes

Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification.

Genetic interactions of yeast eukaryotic translation initiation factor 5a (eIF5A) reveal connections to poly(A)-binding protein and protein kinase C signaling

The highly conserved eukaryotic translation initiation factor eIF5A has been proposed to have various roles in the cell, from translation to mRNA decay to nuclear protein export. To further our understanding of this essential protein, three temperature-sensitive alleles of the yeast TIF51A gene have been characterized. Two mutant eIF5A proteins contain mutations in a proline residue at the junction between the two eIFSA domains and the third, strongest allele encodes a protein with a single mutation in each domain, both of which are required for the growth defect. The stronger tif51A alleles cause defects in degradation of short-lived mRNAs, supporting a role for this protein in mRNA decay. A multicopy suppressor screen revealed six genes, the overexpression of which allows growth of a tif51A-1 strain at high temperature; these genes include PAB1, PKC1, and PKC1 regulators WSC1, WSC2, and WSC3. Further results suggest that eIFSA may also be involved in ribosomal synthesis and the WSC/PKC1 signaling pathway for cell wall integrity or related processes.

The Deoxyhypusine Synthase Mutant dys1-1 Reveals the Association of eIF5A and Asc1 with Cell Wall Integrity

The putative eukaryotic translation initiation factor 5A (eIF5A) is a highly conserved protein among archaea and eukaryotes that has recently been implicated in the elongation step of translation. eIF5A undergoes an essential and conserved posttranslational modification at a specific lysine to generate the residue hypusine. The enzymes deoxyhypusine synthase (Dys1) and deoxyhypusine hydroxylase (Lia1) catalyze this two-step modification process. Although several Saccharomyces cerevisiae eIF5A mutants have importantly contributed to the study of eIF5A function, no conditional mutant of Dys1 has been described so far. In this study, we generated and characterized the dys1-1 mutant, which showed a strong depletion of mutated Dys1 protein, resulting in more than 2-fold decrease in hypusine levels relative to the wild type. The dys1-1 mutant demonstrated a defect in total protein synthesis, a defect in polysome profile indicative of a translation elongation defect and a reduced association of eIF5A with polysomes. The growth phenotype of dys1-1 mutant is severe, growing only in the presence of 1 M sorbitol, an osmotic stabilizer. Although this phenotype is characteristic of Pkc1 cell wall integrity mutants, the sorbitol requirement from dys1-1 is not associated with cell lysis. We observed that the dys1-1 genetically interacts with the sole yeast protein kinase C (Pkc1) and Asc1, a component of the 40S ribosomal subunit. The dys1-1 mutant was synthetically lethal in combination with asc1Δ and overexpression of TIF51A (eIF5A) or DYS1 is toxic for an asc1Δ strain. Moreover, eIF5A is more associated with translating ribosomes in the absence of Asc1 in the cell. Finally, analysis of the sensitivity to cell wall-perturbing compounds revealed a more similar behavior of the dys1-1 and asc1Δ mutants in comparison with the pkc1Δ mutant. These data suggest a correlated role for eIF5A and Asc1 in coordinating the translational control of a subset of mRNAs associated with cell integrity. © 2013 Galvão et al.

No evidence for association of the CD40, CD40L and BLYS polymorphisms, B-cell co-stimulatory molecules, with Brazilian endemic Plasmodium vivax malaria

Background: Plasmodium vivax is the most prevalent malaria species in Brazil. The parasite-host coevolutionary process can be viewed as an 'arms race', in which adaptive genetic changes in one are eventually matched by alterations in the other. Methods: Following the candidate gene approach we analyzed the CD40, CD40L and BLYS genes that participate in B-cell co-stimulation, for associations with P. vivax malaria. The study sample included 97 patients and 103 controls. We extracted DNA using the extraction and purification commercial kit and identified the following SNPs: 21C.T in the CD40 gene, 2726T.C in the CD40L gene and the 2871C.T in the BLyS gene using PCR-RFLP. We analyzed the genotype and allele frequencies by direct counting. We also compared the observed with the expected genotype frequencies using the Hardy-Weinberg equilibrium. Results: The allele and genotype frequencies for these SNPs did not differ statistically between patient and control groups. Gene-gene interactions were not observed between the CD40 and BLYS and between the CD40L and BLYS genes. Overall, the genes were in Hardy-Weinberg equilibrium. Significant differences were not observed among the frequencies of antibody responses against P. vivax sporozoite and erythrocytic antigens and the CD40 and BLYS genotypes. Conclusions: The results of this study show that, although the investigated CD40, CD40L and BLYS alleles differ functionally, this variation does not alter the functionality of the molecules in a way that would interfere in susceptibility to the disease. The variants of these genes may influence the clinical course rather than simply increase or decrease susceptibility. © Royal Society of Tropical Medicine and Hygiene 2013. All rights reserved.

Análise da expressão gênica no músculo esquelético de bovinos das raças Nelore e Aberdeen Angus e sua relação com o desenvolvimento muscular e a maciez da carne

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Association of AXIN2 with Non-syndromic Oral Clefts in Multiple Populations

We have previously shown the association of AXIN2 with oral clefts in a US population. Here, we expanded our study to explore the association of 11 AXIN2 markers in 682 cleft families from multiple populations. Alleles for each AXIN2 marker were tested for transmission distortion with clefts by means of the Family-based Association Test. We observed an association with SNP rs7224837 and all clefts in the combined populations (p = 0.001), and with SNP rs3923086 and cleft lip and palate in Asian populations (p = 0.004). We confirmed our association findings in an additional 528 cleft families from the United States (p < 0.009). We tested for gene-gene interaction between AXIN2 and additional cleft susceptibility loci. We assessed and detected Axin2 mRNA and protein expression during murine palatogenesis. In addition, we also observed co-localization of Axin2 with Irf6 proteins, particularly in the epithelium. Our results continue to support a role for AXIN2 in the etiology of human clefting. Additional studies should be performed to improve our understanding of the biological mechanisms linking AXIN2 to oral clefts.

Preimplantation development regulatory pathway construction through a text-mining approach

Background: The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms. Results: In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements. Conclusions: The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as “seeds” for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.

Xenobiotic Metabolism Genes and Clubfoot

Idiopathic or isolated clubfoot is a common orthopedic birth defect that affects approximately 135,000 children worldwide. It is characterized by equinus, varus and adductus deformities of the ankle and foot. Correction of clubfoot involves months of serial manipulations, castings and bracing, with surgical correction needed in forty percent of cases. Multifactorial etiology has been suggested in numerous studies with both environmental and genetic factors playing an etiologic role. Maternal smoking during pregnancy is the only common environmental factor that has consistently been shown to increase the risk for clubfoot. Moreover, a positive family history of clubfoot and maternal smoking increases the risk of clubfoot twenty fold. These findings suggest that genetic variation in smoking metabolism genes may increase susceptibility to clubfoot. Based on this reasoning, we interrogated eight candidate genes, chosen based on their involvement in phase 1 and 2 cigarette smoke metabolism. Twenty-two SNPs and two null alleles in eight genes (CYP1A1, CYP1A2, CYP1B1, CYP2A6, EPHX1, NAT2, GSTM1 and GSTT1) were genotyped in a dataset composed of nonHispanic white and Hispanic multiplex and simplex families. Only one SNP in CYP1A1, rs1048943, had significantly altered transmission in the aggregate and multiplex NHW datasets (p=0.003 and p=0.009). Perturbation of CYP1A1 by rs1048943 polymorphism causes an increase in the amount of harmful, adduct forming metabolic intermediates. A significant gene interaction between EPHX1 and NAT2 was also found (p=0.007). This interaction may affect the metabolism of harmful metabolic intermediates. Additionally, marginal interactions were found for other xenobiotic genes and these interactions may play a contributory role in clubfoot. Importantly, for CYP1A2, significant maternal (p=0.03; RR=1.24; 95% CI: 1.04-1.44) and fetal (p=0.01; RR=1.33; 95% CI: 1.13-1.54) genotypic effects were identified suggesting that both maternal and fetal genotypes impact normal limb development. No association was found for maternal smoking status and tobacco metabolism genes. Together, these results suggest that xenobiotic metabolism genes may play a contributory role in the etiology of clubfoot regardless of maternal smoking status and may impact foot development through perturbation of tobacco metabolic pathways.

Genetic polymorphisms associated with the inflammatory response in bacterial meningitis.

BACKGROUND Bacterial meningitis (BM) is an infectious disease that results in high mortality and morbidity. Despite efficacious antibiotic therapy, neurological sequelae are often observed in patients after disease. Currently, the main challenge in BM treatment is to develop adjuvant therapies that reduce the occurrence of sequelae. In recent papers published by our group, we described the associations between the single nucleotide polymorphisms (SNPs) AADAT +401C > T, APEX1 Asn148Glu, OGG1 Ser326Cys and PARP1 Val762Ala and BM. In this study, we analyzed the associations between the SNPs TNF -308G > A, TNF -857C > T, IL-8 -251A > T and BM and investigated gene-gene interactions, including the SNPs that we published previously. METHODS The study was conducted with 54 BM patients and 110 healthy volunteers (as the control group). The genotypes were investigated via primer-introduced restriction analysis-polymerase chain reaction (PIRA-PCR) or polymerase chain reaction-based restriction fragment length polymorphism (PCR-RFLP) analysis. Allelic and genotypic frequencies were also associated with cytokine and chemokine levels, as measured with the x-MAP method, and cell counts. We analyzed gene-gene interactions among SNPs using the generalized multifactor dimensionality reduction (GMDR) method. RESULTS We did not find significant association between the SNPs TNF -857C > T and IL-8 -251A > T and the disease. However, a higher frequency of the variant allele TNF -308A was observed in the control group, associated with changes in cytokine levels compared to individuals with wild type genotypes, suggesting a possible protective role. In addition, combined inter-gene interaction analysis indicated a significant association between certain genotypes and BM, mainly involving the alleles APEX1 148Glu, IL8 -251 T and AADAT +401 T. These genotypic combinations were shown to affect cyto/chemokine levels and cell counts in CSF samples from BM patients. CONCLUSIONS In conclusion, this study revealed a significant association between genetic variability and altered inflammatory responses, involving important pathways that are activated during BM. This knowledge may be useful for a better understanding of BM pathogenesis and the development of new therapeutic approaches.

Modifier genes and susceptibility to colorectal cancer in individuals with Lynch syndrome

Lynch syndrome, is caused by inherited germ-line mutations in the DNA mismatch repair genes resulting in cancers at an early age, predominantly colorectal (CRC) and endometrial cancers. Though the median age at onset for CRC is about 45 years, disease penetrance varies suggesting that cancer susceptibility may be modified by environmental or other low-penetrance genes. Genetic variation due to polymorphisms in genes encoding metabolic enzymes can influence carcinogenesis by alterations in the expression and activity level of the enzymes. Variation in MTHFR, an important folate metabolizing enzyme can affect DNA methylation and DNA synthesis and variation in xenobiotic-metabolizing enzymes can affect the metabolism and clearance of carcinogens, thus modifying cancer risk. ^ This study examined a retrospective cohort of 257 individuals with Lynch syndrome, for polymorphisms in genes encoding xenobiotic-metabolizing enzymes-- CYP1A1 (I462V and MspI), EPHX1 (H139R and Y113H), GSTP1 (I105V and A114V), GSTM1 and GSTT1 (deletions) and folate metabolizing enzyme--MTHFR (C677T and A1298C). In addition, a series of 786 cases of sporadic CRC were genotyped for CYP1A1 I462V and EPHX1 Y113H to assess gene-gene interaction and gene-environment interaction with smoking in a case-only analysis. ^ Prominent findings of this study were that the presence of an MTHFR C677T variant allele was associated with a 4 year later age at onset for CRC on average and a reduced age-associated risk for developing CRC (Hazard ratio: 0.55; 95% confidence interval: 0.36–0.85) compared to the absence of any variant allele in individuals with Lynch syndrome. Similarly, Lynch syndrome individuals heterozygous for CYP1A1 I462V A>G polymorphism developed CRC an average of 4 years earlier and were at a 78% increased age-associated risk (Hazard ratio for AG relative to AA: 1.78; 95% confidence interval: 1.16-2.74) than those with the homozygous wild-type genotype. Therefore these two polymorphisms may be additional susceptibility factors for CRC in Lynch syndrome. In the case-only analysis, evidence of gene-gene interaction was seen between CYP1A1 I462V and EPHX1 Y113H and between EPHX1 Y113H and smoking suggesting that genetic and environmental factors may interact to increase sporadic CRC risk. Implications of these findings are the ability to identify subsets of high-risk individuals for targeted prevention and intervention. ^

Differential Micro RNA Expression in PBMC from Multiple Sclerosis Patients

Differences in gene expression patterns have been documented not only in Multiple Sclerosis patients versus healthy controls but also in the relapse of the disease. Recently a new gene expression modulator has been identified: the microRNA or miRNA. The aim of this work is to analyze the possible role of miRNAs in multiple sclerosis, focusing on the relapse stage. We have analyzed the expression patterns of 364 miRNAs in PBMC obtained from multiple sclerosis patients in relapse status, in remission status and healthy controls. The expression patterns of the miRNAs with significantly different expression were validated in an independent set of samples. In order to determine the effect of the miRNAs, the expression of some predicted target genes of these were studied by qPCR. Gene interaction networks were constructed in order to obtain a co-expression and multivariate view of the experimental data. The data analysis and later validation reveal that two miRNAs (hsa-miR-18b and hsa-miR-599) may be relevant at the time of relapse and that another miRNA (hsa-miR-96) may be involved in remission. The genes targeted by hsa-miR-96 are involved in immunological pathways as Interleukin signaling and in other pathways as wnt signaling. This work highlights the importance of miRNA expression in the molecular mechanisms implicated in the disease. Moreover, the proposed involvement of these small molecules in multiple sclerosis opens up a new therapeutic approach to explore and highlight some candidate biomarker targets in MS

Genetic and Cultural Transmission of Smoking Initiation: An Extended Twin Kinship Model

Background Considerable evidence from twin and adoption studies indicates that genetic and shared environmental factors play a significant role in the initiation of smoking behavior. Although twin and adoption designs are powerful to detect genetic and environmental influences, they do not provide information on the processes of assortative mating and parent–offspring transmission and their contribution to the variability explained by genetic and/or environmental factors. Methods We examined the role of genetic and environmental factors for smoking initiation using an extended kinship design. This design allows the simultaneous testing of additive and non-additive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission. A dichotomous lifetime smoking measure was obtained from twins and relatives in the Virginia 30,000 sample. Results Results demonstrate that both genetic and environmental factors play a significant role in the liability to smoking initiation. Major influences on individual differences appeared to be additive genetic and unique environmental effects, with smaller contributions from assortative mating, shared sibling environment, twin environment, cultural transmission and resulting genotype–environment covariance. The finding of negative cultural transmission without dominance led us to investigate more closely two possible mechanisms for the lower parent–offspring correlations compared to the sibling and DZ twin correlations in subsets of the data: (i) age × gene interaction, and (ii) social homogamy. Neither mechanism provided a significantly better explanation of the data, although age regression was significant. Conclusions This study showed significant heritability, partly due to assortment, and significant effects of primarily non-parental shared environment on smoking initiation.

Entropy Based Approach to Finding Interacting Genes Responsible for Complex Human Disease

2000 Mathematics Subject Classification: 62P10, 92D10, 92D30, 94A17, 62L10.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.