Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks

Yang, Xia; Deignan, Joshua L.; Qi, Hongxiu; Zhu, Jun; Su, Qian; Zhong, Judy; Torosyan, Gevork; Majid, Sana; Falkard, Brie; Kleinhanz, Robert; Karlsson, Jenny; Castellani, Lawrence W.; Mumick, Sheena; Wang, Kai; Xie, Tao; Coon, Michael; Zhang, Chunsheng; Estrada-Smith, Daria; Farber, Charles R.; Wang, Susanna S.; Nas, Atila van; Ghazalpour, Anatole; Zhang, Bin; MacNeil, Douglas J.; Lamb, John; Dipple, Katrina M.; Reitman, Marc L.; Mehrabian, Margarete; Lum, Pek Yee; Schadt, Eric E.; Lusis, Aldons J.; Drake, Thomas A.

doi:10.1038/ng.325

Cited by 258 publications

(266 citation statements)

References 49 publications

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“…The promise of genome projects, functional genomics studies, and network biology in providing new molecular targets for pharmaceutical intervention in different disease states is now becoming a reality (33,34). This pharmaceutical intervention is particularly important in the area of infectious diseases, where the dual problems of multidrug resistance and the scarcity of effective therapy for a large number of diseases are well recognized.…”

Section: Discussionmentioning

confidence: 99%

Blueprint for antimicrobial hit discovery targeting metabolic networks

Shen

Liu

Estiú

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

101

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Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strainspecific antiinfective therapy.antibiotics | flux balance analysis | virtual screening T he deciphering of genomes from a variety of organisms holds the promise of significantly increasing the speed and efficiency of drug discovery. The challenge to find "druggable" targets (1) that will have an effect in the complex interaction network of a living organism has been only partially met by genomics and functional genomics approaches (2). For example, systematic gene deletion studies have been widely used to identify essential genes whose protein product could serve as potential antibiotic targets in a given bacterium. This approach yields only growthcondition-specific results, as a molecular target that is found to be essential in one specific environment may not be essential in others. To overcome these limitations and to couple target identification to the identification of small molecules that can affect them, cellular network analysis and computational chemistry approaches may prove highly efficient and scalable methods. By using entirely computational methods in the initial steps of drug discovery, the more expensive and time-consuming experimental methods could be applied in a more focused fashion to smaller sets of targets and hits. Although the potential time and resource savings of this strategy are widely acknowledged and have already yielded interesting results in individual aspects of drug discovery (3, 4), so far there have been no successful examples where computational methods were integrated seamlessly to develop hits toward targets identified and validated by using genomic and systems-level methods.Antibiotic drug resistance significantly eroded the effectiveness of currently available antimicrobial drugs toward disease-causing bacteria (5). As a consequence, today the yearly mortality rate in the United States due to multidrug-resistant Staphylococcus aureus infections is higher than that due to AIDS (6). Here, we provide a proof-of-principle demonstration that the combined use of bacterial metabolic network analysis with virtual screening and subsequent experimental verification is an effective method for the simu...

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Section: Discussionmentioning

confidence: 99%

Blueprint for antimicrobial hit discovery targeting metabolic networks

Shen

Liu

Estiú

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

101

View full text Add to dashboard Cite

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“…GPX2, for example, shows elevated levels of expression, while GPX1, 3 and 4 show Downregulation of glutathione peroxidase 3 is associated with lymph node metastasis and prognosis in cervical cancer XIANGLAN ZHANG 1,6 , ZHENLONG ZHENG 3,7 , SHEN YINGJI 5 , HYEYEON KIM 4 , RENSHUN JIN 1 , decreased expression in multiple types of cancer (2). A recent study also predicted a causal relationship between changes in GPX3 expression and in obesity-related traits (15). Cervical cancer is the second most common cancer in women and identification and establishment of molecular markers for cervical cancer is highly necessary for improved diagnoses and development of therapeutic targets (16).…”

Section: Introductionmentioning

confidence: 91%

Downregulation of glutathione peroxidase 3 is associated with lymph node metastasis and prognosis in cervical cancer

et al. 2014

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Abstract. Glutathione peroxidase 3 (GPX3) is a member of the glutathione peroxidase family of selenoproteins and is one of the key defensive enzymes against oxidative damages to host cells. Downregulation of GPX3 due to its promoter hypermethylation has been documented in several different types of cancer, indicating that GPX3 functions as a possible tumor suppressor. In the present study, we showed that GPX3 is also significantly downregulated in cervical cancer tissues compared to normal cervical tissues by qRT-PCR analyses and immunohistostainings. GPX3 expression was significantly related to lymph node metastasis and prognosis in cervical cancer patients. Treatment of cervical cancer cells with 5-aza-2'-deoxycytidine restored the expression of GPX3 and methylation-specific PCR (MSP) confirmed the CpG methylation of the GPX3 gene. Our results indicate that promoter methylation is one of the major causes of GPX3 downregulation in cervical cancer and GPX3 could serve as a predictive biomarker for lymph node metastasis and prognosis of cervical cancer.

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“…We also acknowledge that one of the limitations of BN approach is that feedback regulation cannot be accommodated. In addition, although we have demonstrated the utility of BNs in predicting how genetic and environmental perturbation signals propagate in biological systems in controlled study populations (Zhu et al 2004(Zhu et al , 2008bSchadt et al 2005;Chen et al 2008;Yang et al 2009), the accuracy to infer causal relationships between genes in a random or uncontrolled study design like the current liver cohort is lower (Wang et al 2009). Furthermore, the directionality of the outcome of any perturbation of genes in a network such as whether the perturbation will raise or lower a phenotypic outcome depends on the genetic background and environmental conditions due to complex network feedbacks (Davey Smith and Ebrahim 2003;Chen et al 2008).…”

Section: à5mentioning

confidence: 98%

Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver

Yang¹,

Zhang²,

Molony³

et al. 2010

Genome Res.

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237

226

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Liver cytochrome P450s (P450s) play critical roles in drug metabolism, toxicology, and metabolic processes. Despite rapid progress in the understanding of these enzymes, a systematic investigation of the full spectrum of functionality of individual P450s, the interrelationship or networks connecting them, and the genetic control of each gene/enzyme is lacking. To this end, we genotyped, expression-profiled, and measured P450 activities of 466 human liver samples and applied a systems biology approach via the integration of genetics, gene expression, and enzyme activity measurements. We found that most P450s were positively correlated among themselves and were highly correlated with known regulators as well as thousands of other genes enriched for pathways relevant to the metabolism of drugs, fatty acids, amino acids, and steroids. Genome-wide association analyses between genetic polymorphisms and P450 expression or enzyme activities revealed sets of SNPs associated with P450 traits, and suggested the existence of both cis-regulation of P450 expression (especially for CYP2D6) and more complex trans-regulation of P450 activity. Several novel SNPs associated with CYP2D6 expression and enzyme activity were validated in an independent human cohort. By constructing a weighted coexpression network and a Bayesian regulatory network, we defined the human liver transcriptional network structure, uncovered subnetworks representative of the P450 regulatory system, and identified novel candidate regulatory genes, namely, EHHADH, SLC10A1, and AKR1D1. The P450 subnetworks were then validated using gene signatures responsive to ligands of known P450 regulators in mouse and rat. This systematic survey provides a comprehensive view of the functionality, genetic control, and interactions of P450s.

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Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks

Cited by 258 publications

References 49 publications

Blueprint for antimicrobial hit discovery targeting metabolic networks

Blueprint for antimicrobial hit discovery targeting metabolic networks

Downregulation of glutathione peroxidase 3 is associated with lymph node metastasis and prognosis in cervical cancer

Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver

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