Peter Juvan

Epistasis analysis with global transcriptional phenotypes

Classical epistasis analysis can determine the order of function of genes in pathways using morphological, biochemical and other phenotypes. It requires knowledge of the pathways phenotypic output and a variety of experimental expertise and so is unsuitable for genome-scale analysis. Here we used microarray profiles of mutants as phenotypes for epistasis analysis. Considering genes that regulate activity of protein kinase A in Dictyostelium, we identified known and unknown epistatic relationships and reconstructed a genetic network with microarray phenotypes alone. This work shows that microarray data can provide a uniform, quantitative tool for large-scale genetic network analysis.

GenePath: a System for Automated Construction of Genetic Networks from Mutant Data

MOTIVATION Genetic networks are often used in the analysis of biological phenomena. In classical genetics, they are constructed manually from experimental data on mutants. The field lacks formalism to guide such analysis, and accounting for all the data becomes complicated when large amounts of data are considered. RESULTS We have developed GenePath, an intelligent assistant that automates the analysis of genetic data. GenePath employs expert-defined patterns to uncover gene relations from the data, and uses these relations as constraints in the search for a plausible genetic network. GenePath formalizes genetic data analysis, facilitates the consideration of all the available data in a consistent manner, and the examination of the large number of possible consequences of planned experiments. It also provides an explanation mechanism that traces every finding to the pertinent data. AVAILABILITY GenePath can be accessed at http://genepath.org. SUPPLEMENTARY INFORMATION Supplementary material is available at http://genepath.org/bi-.supp.

Tools and data services registry: a community effort to document bioinformatics resources

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand. Here we present a community-driven curation effort, supported by ELIXIR—the European infrastructure for biological information—that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners. As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.

Acrolein consumption induces systemic dyslipidemia and lipoprotein modification

Aldehydes such as acrolein are ubiquitous pollutants present in automobile exhaust, cigarette, wood, and coal smoke. Such aldehydes are also constituents of several food substances and are present in drinking water, irrigation canals, and effluents from manufacturing plants. Oral intake represents the most significant source of exposure to acrolein and related aldehydes. To study the effects of short-term oral exposure to acrolein on lipoprotein levels and metabolism, adult mice were gavage-fed 0.1 to 5 mg acrolein/kg bwt and changes in plasma lipoproteins were assessed. Changes in hepatic gene expression related to lipid metabolism and cytokines were examined by qRT-PCR analysis. Acrolein feeding did not affect body weight, blood urea nitrogen, plasma creatinine, electrolytes, cytokines or liver enzymes, but increased plasma cholesterol and triglycerides. Similar results were obtained with apoE-null mice. Plasma lipoproteins from acrolein-fed mice showed altered electrophoretic mobility on agarose gels. Chromatographic analysis revealed elevated VLDL cholesterol, phospholipids, and triglycerides levels with little change in LDL or HDL. NMR analysis indicated shifts from small to large VLDL and from large to medium-small LDL with no change in the size of HDL particles. Increased plasma VLDL was associated with a significant decrease in post-heparin plasma hepatic lipase activity and a decrease in hepatic expression of hepatic lipase. These observations suggest that oral exposure to acrolein could induce or exacerbate systemic dyslipidemia and thereby contribute to cardiovascular disease risk.

Novel Insights into the Downstream Pathways and Targets Controlled by Transcription Factors CREM in the Testis

The essential role of the Crem gene in normal sperm development is widely accepted and is confirmed by azoospermia in male mice lacking the Crem gene. The exact number of genes affected by Crem absence is not known, however a large difference has been observed recently between the estimated number of differentially expressed genes found in Crem knock-out (KO) mice compared to the number of gene loci bound by CREM. We therefore re-examined global gene expression in male mice lacking the Crem gene using whole genome transcriptome analysis with Affymetrix microarrays and compared the lists of differentially expressed genes from Crem−/− mice to a dataset of genes where binding of CREM was determined by Chip-seq. We determined the global effect of CREM on spermatogenesis as well as distinguished between primary and secondary effects of the CREM absence. We demonstrated that the absence of Crem deregulates over 4700 genes in KO testis. Among them are 101 genes associated with spermatogenesis 41 of which are bound by CREM and are deregulated in Crem KO testis. Absence of several of these genes in mouse models has proven their importance for normal spermatogenesis and male fertility. Our study showed that the absence of Crem plays a more important role on different aspects of spermatogenesis as estimated previously, with its impact ranging from apoptosis induction to deregulation of major circadian clock genes, steroidogenesis and the cell-cell junction dynamics. Several new genes important for normal spermatogenesis and fertility are down-regulated in KO testis and are therefore possible novel targets of CREM.

GenePath: a system for inference of genetic networks and proposal of genetic experiments

A genetic network is a formalism that is often used in biology to represent causalities and reason about biological phenomena related to genetic regulation. We present GenePath, a computer-based system that supports the inference of genetic networks from a set of genetic experiments. Implemented in Prolog, GenePath uses abductive inference to elucidate network constraints based on background knowledge and experimental results. Additionally, it can propose genetic experiments that may further refine the discovered network and establish relations between genes that could not be related based on the original experimental data. We illustrate GenePaths approach and utility on analysis of data on aggregation and sporulation of the soil amoeba Dictyostelium discoideum.

Cumulus Cells Gene Expression Profiling in Terms of Oocyte Maturity in Controlled Ovarian Hyperstimulation Using GnRH Agonist or GnRH Antagonist

In in vitro fertilization (IVF) cycles controlled ovarian hyperstimulation (COH) is established by gonadotropins in combination with gonadotropin-releasing hormone (GnRH) agonists or antagonists, to prevent premature luteinizing hormone (LH) surge. The aim of our study was to improve the understanding of gene expression profile of cumulus cells (CC) in terms of ovarian stimulation protocol and oocyte maturity. We applied Affymetrix gene expression profiling in CC of oocytes at different maturation stages using either GnRH agonists or GnRH antagonists. Two analyses were performed: the first involved CC of immature metaphase I (MI) and mature metaphase II (MII) oocytes where 359 genes were differentially expressed, and the second involved the two GnRH analogues where no differentially expressed genes were observed at the entire transcriptome level. A further analysis of 359 differentially genes was performed, focusing on anti-Müllerian hormone receptor 2 (AMHR2), follicle stimulating hormone receptor (FSHR), vascular endothelial growth factor C (VEGFC) and serine protease inhibitor E2 (SERPINE2). Among other differentially expressed genes we observed a marked number of new genes connected to cell adhesion and neurotransmitters such as dopamine, glycine and γ-Aminobutyric acid (GABA). No differential expression in CC between the two GnRH analogues supports the findings of clinical studies where no significant difference in live birth rates between both GnRH analogues has been proven.

The human primary hepatocyte transcriptome reveals novel insights into atorvastatin and rosuvastatin action

Objectives With particular emphasis on interactions between cholesterol homeostasis and drug metabolism we investigate the transcriptome of human primary hepatocytes treated by two commonly prescribed cholesterol lowering drugs atorvastatin and rosuvastatin and by rifampicin that serves as an outgroup as well as a model substance for induction of nuclear pregnane X receptor. Methods Hepatocytes from human donors have been treated with rosuvastatin, atorvastatin, and rifampicin for 12, 24, and 48 h. Expression profiling with cholesterol and drug metabolism enriched low density Steroltalk cDNA and whole genome Affymetrix HG-U133 Plus 2.0 arrays has been applied. Differential expression (DE) of genes and gene set enrichment analysis of KEGG pathways were performed. Lists of differentially expressed genes and gene sets were cross-compared. Selected genes were confirmed by quantitative real-time PCR. Results Statins lead to: (a) upregulation of cholesterol-related genes indicating an increased LDL uptake and storage of esterified cholesterol, elevated bile acid/drug export and lower capacity to form HDL; (b) perturbation of genes in glucose and fatty acid homeostasis, influencing acetyl-CoA pools, promoting gluconeogenesis and glucose export; (c) elevated expression of ADIPOR2 suggesting increased sensitivity to adiponectin; (d) perturbations in genes of lipoprotein particle formation, differently for each statin; (e) perturbed expression of many metabolic genes that are directly controlled by nuclear receptors constitutive androstan and/or pregnane X. Conclusion These data provide a novel global insight into hepatic effects of statins, offering biochemical explanations for higher blood glucose in statin-treated patients, and for drug-induced secondary fatty liver disease.

Transcriptional Activation of PPARα by Phenobarbital in the Absence of CAR and PXR

The nuclear receptors CAR (constitutive androstane receptor) and PXR (pregnane X receptor) mediate the effects of phenobarbital on gene transcription. To investigate the relative contribution of these nuclear receptors to the expression of specific genes we studied the effect of phenobarbital in livers of wild type, CAR(-/-), PXR(-/-) and CAR/PXR(-/-) knockout mice. Spotted Steroltalk v1 cDNA arrays were applied containing probes for genes involved in drug metabolism, sterol biosynthesis, steroid synthesis/transport and heme synthesis. In the absence of CAR and PXR, phenobarbital unexpectedly induced mRNAs of several nuclear receptors, including PPARalpha and its target genes Cyp4a10 and Cyp4a14. Interestingly, in primary cultures of hepatocytes isolated from CAR/PXR(-/-) knockout mice, phenobarbital increased HNF-4alpha levels. In further experiments in these hepatocyte cultures we provide evidence that phenobarbital directly induces transcription of the PPARalpha gene via its HNF-4alpha response element, and indirectly by lack of inhibitory crosstalk of AMPK, CAR and PXR with HNF-4alpha. Our results provide further insight into CAR and PXR-independent effects of phenobarbital and the crosstalk between different nuclear receptor signaling pathways.

The sterolgene v0 cDNA microarray: A systemic approach to studies of cholesterol homeostasis and drug metabolism

BackgroundCholesterol homeostasis and xenobiotic metabolism are complex biological processes, which are difficult to study with traditional methods. Deciphering complex regulation and response of these two processes to different factors is crucial also for understanding of disease development. Systems biology tools as are microarrays can importantly contribute to this knowledge and can also discover novel interactions between the two processes.ResultsWe have developed a low density Sterolgene v0 cDNA microarray dedicated to studies of cholesterol homeostasis and drug metabolism in the mouse. To illustrate its performance, we have analyzed mouse liver samples from studies focused on regulation of cholesterol homeostasis and drug metabolism by diet, drugs and inflammation. We observed down-regulation of cholesterol biosynthesis during fasting and high-cholesterol diet and subsequent up-regulation by inflammation. Drug metabolism was down-regulated by fasting and inflammation, but up-regulated by phenobarbital treatment and high-cholesterol diet. Additionally, the performance of the Sterolgene v0 was compared to the two commercial high density microarray platforms: the Agilent cDNA (G4104A) and the Affymetrix MOE430A GeneChip. We hybridized identical RNA samples to the commercial microarrays and showed that the performance of Sterolgene is comparable to commercial arrays in terms of detection of changes in cholesterol homeostasis and drug metabolism.ConclusionUsing the Sterolgene v0 microarray we were able to detect important changes in cholesterol homeostasis and drug metabolism caused by diet, drugs and inflammation. Together with its next generations the Sterolgene microarrays represent original and dedicated tools enabling focused and cost effective studies of cholesterol homeostasis and drug metabolism. These microarrays have the potential of being further developed into screening or diagnostic tools.