Gregory Lefebvre

Perinatal Exposure to Bisphenol A Increases Adult Mammary Gland Progesterone Response and Cell Number

Bisphenol A [BPA, 2,2,-bis (hydroxyphenyl) propane] is one of the highest-volume chemicals produced worldwide. It is detected in body fluids of more than 90% of the human population. Originally synthesized as an estrogenic compound, it is currently utilized to manufacture food and beverage containers resulting in uptake with food and drinks. There is concern that exposure to low doses of BPA, defined as less than or equal to 5 mg/kg body weight /d, may have developmental effects on various hormone-responsive organs including the mammary gland. Here, we asked whether perinatal exposure to a range of low doses of BPA is sufficient to alter mammary gland hormone response later on in life, with a possible impact on breast cancer risk. To mimic human exposure, we added BPA to the drinking water of C57/Bl6 breeding pairs. Analysis of the mammary glands of their daughters at puberty showed that estrogen-dependent transcriptional events were perturbed and the number of terminal end buds, estrogen-induced proliferative structures, was altered in a dose-dependent fashion. Importantly, adult females showed an increase in mammary epithelial cell numbers comparable to that seen in females exposed to diethylbestrol, a compound exposure to which was previously linked to increased breast cancer risk. Molecularly, the mRNAs encoding Wnt-4 and receptor activator of nuclear factor κB ligand, two key mediators of hormone function implicated in control of mammary stem cell proliferation and carcinogenesis, showed increased induction by progesterone in the mammary tissue of exposed mice. Thus, perinatal exposure to environmentally relevant doses of BPA alters long-term hormone response that may increase the propensity to develop breast cancer.

Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver

Significance Rhythmic gene regulation in mouse liver results from an intertwined relationship between feeding cycles and the circadian clock. Significant efforts have been made to understand this interaction but a complete picture of the resulting diurnal transcription–translation processes is still missing. Through the simultaneous quantification of temporal transcription, accumulation, and translation of mRNA in the liver, we investigated the regulatory landscape of mice with intact or deficient circadian clock subjected to different feeding regimens. We showed that circadian clock and feeding rhythms coordinate rhythmic transcription to drive downstream rhythmic mRNA accumulation and translation. However, a subset of genes harboring 5′-Terminal Oligo Pyrimidine tract or Translation Initiator of Short 5′-UTR elements encoding proteins involved in translation and mitochondrial activity, respectively, present a transcription-independent rhythmic translation mainly regulated by feeding. Diurnal oscillations of gene expression are a hallmark of rhythmic physiology across most living organisms. Such oscillations are controlled by the interplay between the circadian clock and feeding rhythms. Although rhythmic mRNA accumulation has been extensively studied, comparatively less is known about their transcription and translation. Here, we quantified simultaneously temporal transcription, accumulation, and translation of mouse liver mRNAs under physiological light–dark conditions and ad libitum or night-restricted feeding in WT and brain and muscle Arnt-like 1 (Bmal1)-deficient animals. We found that rhythmic transcription predominantly drives rhythmic mRNA accumulation and translation for a majority of genes. Comparison of wild-type and Bmal1 KO mice shows that circadian clock and feeding rhythms have broad impact on rhythmic gene expression, Bmal1 deletion affecting surprisingly both transcriptional and posttranscriptional levels. Translation efficiency is differentially regulated during the diurnal cycle for genes with 5′-Terminal Oligo Pyrimidine tract (5′-TOP) sequences and for genes involved in mitochondrial activity, many harboring a Translation Initiator of Short 5′-UTR (TISU) motif. The increased translation efficiency of 5′-TOP and TISU genes is mainly driven by feeding rhythms but Bmal1 deletion also affects amplitude and phase of translation, including TISU genes. Together this study emphasizes the complex interconnections between circadian and feeding rhythms at several steps ultimately determining rhythmic gene expression and translation.

Analysis of HIV-1 expression level and sense of transcription by high-throughput sequencing of the infected cell

ABSTRACT Next-generation sequencing offers an unprecedented opportunity to jointly analyze cellular and viral transcriptional activity without prerequisite knowledge of the nature of the transcripts. SupT1 cells were infected with a vesicular stomatitis virus G envelope protein (VSV-G)-pseudotyped HIV vector. At 24 h postinfection, both cellular and viral transcriptomes were analyzed by serial analysis of gene expression followed by high-throughput sequencing (SAGE-Seq). Read mapping resulted in 33 to 44 million tags aligning with the human transcriptome and 0.23 to 0.25 million tags aligning with the genome of the HIV-1 vector. Thus, at peak infection, 1 transcript in 143 is of viral origin (0.7%), including a small component of antisense viral transcription. Of the detected cellular transcripts, 826 (2.3%) were differentially expressed between mock- and HIV-infected samples. The approach also assessed whether HIV-1 infection modulates the expression of repetitive elements or endogenous retroviruses. We observed very active transcription of these elements, with 1 transcript in 237 being of such origin, corresponding on average to 123,123 reads in mock-infected samples (0.40%) and 129,149 reads in HIV-1-infected samples (0.45%) mapping to the genomic Repbase repository. This analysis highlights key details in the generation and interpretation of high-throughput data in the setting of HIV-1 cellular infection.

HTSstation: A Web Application and Open-Access Libraries for High-Throughput Sequencing Data Analysis

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

Medium-chain fatty acids inhibit mitochondrial metabolism in astrocytes promoting astrocyte–neuron lactate and ketone body shuttle systems

Medium‐chain triglycerides have been used as part of a ketogenic diet effective in reducing epileptic episodes. The health benefits of the derived medium‐chain fatty acids (MCFAs) are thought to result from the stimulation of liver ketogenesis providing fuel for the brain. We tested whether MCFAs have direct effects on energy metabolism in induced pluripotent stem cell‐derived human astrocytes and neurons. Using single‐cell imaging, we observed an acute pronounced reduction of the mitochondrial electrical potential and a concomitant drop of the NAD(P)H signal in astrocytes, but not in neurons. Despite the observed effects on mitochondrial function, MCFAs did not lower intracellular ATP levels or activate the energy sensor AMP‐activated protein kinase. ATP concentrations in astrocytes were unaltered, even when blocking the respiratory chain, suggesting compensation through accelerated glycolysis. The MCFA decanoic acid (300 μM) promoted glycolysis and augmented lactate formation by 49.6%. The shorter fatty acid octanoic acid (300 μM) did not affect glycolysis but increased the rates of astrocyte ketogenesis 2.17‐fold compared with that of control cells. MCFAs may have brain health benefits through the modulation of astrocyte metabolism leading to activation of shuttle systems that provide fuel to neighboring neurons in the form of lactate and ketone bodies.—Thevenet, J., De Marchi, U., Santo Domingo, J., Christinat, N., Bultot, L., Lefebvre, G., Sakamoto, K., Descombes, P., Masoodi, M., Wiederkehr, A. Medium‐chain fatty acids inhibit mitochondrial metabolism in astrocytes promoting astrocyte‐neuron lactate and ketone body shuttle systems. FASEB J. 30, 1913–1926 (2016). www.fasebj.org

PyroTRF-ID: a novel bioinformatics methodology for the affiliation of terminal-restriction fragments using 16S rRNA gene pyrosequencing data

BackgroundIn molecular microbial ecology, massive sequencing is gradually replacing classical fingerprinting techniques such as terminal-restriction fragment length polymorphism (T-RFLP) combined with cloning-sequencing for the characterization of microbiomes. Here, a bioinformatics methodology for pyrosequencing-based T-RF identification (PyroTRF-ID) was developed to combine pyrosequencing and T-RFLP approaches for the description of microbial communities. The strength of this methodology relies on the identification of T-RFs by comparison of experimental and digital T-RFLP profiles obtained from the same samples. DNA extracts were subjected to amplification of the 16S rRNA gene pool, T-RFLP with the HaeIII restriction enzyme, 454 tag encoded FLX amplicon pyrosequencing, and PyroTRF-ID analysis. Digital T-RFLP profiles were generated from the denoised full pyrosequencing datasets, and the sequences contributing to each digital T-RF were classified to taxonomic bins using the Greengenes reference database. The method was tested both on bacterial communities found in chloroethene-contaminated groundwater samples and in aerobic granular sludge biofilms originating from wastewater treatment systems.ResultsPyroTRF-ID was efficient for high-throughput mapping and digital T-RFLP profiling of pyrosequencing datasets. After denoising, a dataset comprising ca. 10′000 reads of 300 to 500 bp was typically processed within ca. 20 minutes on a high-performance computing cluster, running on a Linux-related CentOS 5.5 operating system, enabling parallel processing of multiple samples. Both digital and experimental T-RFLP profiles were aligned with maximum cross-correlation coefficients of 0.71 and 0.92 for high- and low-complexity environments, respectively. On average, 63±18% of all experimental T-RFs (30 to 93 peaks per sample) were affiliated to phylotypes.ConclusionsPyroTRF-ID profits from complementary advantages of pyrosequencing and T-RFLP and is particularly adapted for optimizing laboratory and computational efforts to describe microbial communities and their dynamics in any biological system. The high resolution of the microbial community composition is provided by pyrosequencing, which can be performed on a restricted set of selected samples, whereas T-RFLP enables simultaneous fingerprinting of numerous samples at relatively low cost and is especially adapted for routine analysis and follow-up of microbial communities on the long run.

Processing and analyzing ChIP-seq data: from short reads to regulatory interactions

Chromatin-immunoprecipitation and sequencing (ChIP-seq) is a rapidly maturing technology that draws on the power of high-throughput short-read sequencing to decipher chromatin states with unprecedented precision and breadth. Although some aspects of the experimental protocol require careful tuning, the bottleneck currently firmly lies with the downstream data analysis. We give an overview of the better-established aspects of genome mapping and data normalization and we describe the more recent progress in peak calling and their statistical analysis and provide a brief overview of popular follow-up analyses such as genomic feature categorization and motif search.

Transcriptome profiling from adipose tissue during a low-calorie diet reveals predictors of weight and glycemic outcomes in obese, nondiabetic subjects

Background: A low-calorie diet (LCD) reduces fat mass excess, improves insulin sensitivity, and alters adipose tissue (AT) gene expression, yet the relation with clinical outcomes remains unclear.Objective: We evaluated AT transcriptome alterations during an LCD and the association with weight and glycemic outcomes both at LCD termination and 6 mo after the LCD.Design: Using RNA sequencing (RNAseq), we analyzed transcriptome changes in AT from 191 obese, nondiabetic patients within a multicenter, controlled dietary intervention. Expression changes were associated with outcomes after an 8-wk LCD (800-1000 kcal/d) and 6 mo after the LCD. Results were validated by using quantitative reverse transcriptase-polymerase chain reaction in 350 subjects from the same cohort. Statistical models were constructed to classify weight maintainers or glycemic improvers.Results: With RNAseq analyses, we identified 1173 genes that were differentially expressed after the LCD, of which 350 and 33 were associated with changes in body mass index (BMI; in kg/m2) and Matsuda index values, respectively, whereas 29 genes were associated with both endpoints. Pathway analyses highlighted enrichment in lipid and glucose metabolism. Classification models were constructed to identify weight maintainers. A model based on clinical baseline variables could not achieve any classification (validation AUC: 0.50; 95% CI: 0.36, 0.64). However, clinical changes during the LCD yielded better performance of the model (AUC: 0.73; 95% CI: 0.60, 0.87]). Adding baseline expression to this model improved the performance significantly (AUC: 0.87; 95% CI: 0.77, 0.96; Delongs P = 0.012). Similar analyses were performed to classify subjects with good glycemic improvements. Baseline- and LCD-based clinical models yielded similar performance (best AUC: 0.73; 95% CI: 0.60, 0.86). The addition of expression changes during the LCD improved the performance substantially (AUC: 0.80; 95% CI: 0.69, 0.92; P = 0.058).Conclusions: This study investigated AT transcriptome alterations after an LCD in a large cohort of obese, nondiabetic patients. Gene expression combined with clinical variables enabled us to distinguish weight and glycemic responders from nonresponders. These potential biomarkers may help clinicians understand intersubject variability and better predict the success of dietary interventions. This trial was registered at clinicaltrials.gov as NCT00390637.

Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator

Thousands of genetic variants have been associated with complex traits through genome-wide association studies. However, the functional variants or mechanistic consequences remain elusive. Intermediate traits such as gene expression or protein levels are good proxies of the metabolic state of an organism. Proteome analysis especially can provide new insights into the molecular mechanisms of complex traits like obesity. The role of genetic variation in determining protein level variation has not been assessed in obesity. To address this, we design a large-scale protein quantitative trait locus (pQTL) analysis based on a set of 1129 proteins from 494 obese subjects before and after a weight loss intervention. This reveals 55 BMI-associated cis-pQTLs and trans-pQTLs at baseline and 3 trans-pQTLs after the intervention. We provide evidence for distinct genetic mechanisms regulating BMI-associated proteins before and after weight loss. Finally, by functional analysis, we identify and validate FAM46A as a trans regulator for leptin.Although many genetic variants are known for obesity, their function remains largely unknown. Here, in a weight-loss intervention cohort, the authors identify protein quantitative trait loci associated with BMI at baseline and after weight loss and find FAM46A to be a regulator of leptin in adipocytes.

Network Analysis of Metabolite GWAS Hits: Implication of CPS1 and the Urea Cycle in Weight Maintenance

Background and Scope Weight loss success is dependent on the ability to refrain from regaining the lost weight in time. This feature was shown to be largely variable among individuals, and these differences, with their underlying molecular processes, are diverse and not completely elucidated. Altered plasma metabolites concentration could partly explain weight loss maintenance mechanisms. In the present work, a systems biology approach has been applied to investigate the potential mechanisms involved in weight loss maintenance within the Diogenes weight-loss intervention study. Methods and Results A genome wide association study identified SNPs associated with plasma glycine levels within the CPS1 (Carbamoyl-Phosphate Synthase 1) gene (rs10206976, p-value = 4.709e-11 and rs12613336, p-value = 1.368e-08). Furthermore, gene expression in the adipose tissue showed that CPS1 expression levels were associated with successful weight maintenance and with several SNPs within CPS1 (cis-eQTL). In order to contextualize these results, a gene-metabolite interaction network of CPS1 and glycine has been built and analyzed, showing functional enrichment in genes involved in lipid metabolism and one carbon pool by folate pathways. Conclusions CPS1 is the rate-limiting enzyme for the urea cycle, catalyzing carbamoyl phosphate from ammonia and bicarbonate in the mitochondria. Glycine and CPS1 are connected through the one-carbon pool by the folate pathway and the urea cycle. Furthermore, glycine could be linked to metabolic health and insulin sensitivity through the betaine osmolyte. These considerations, and the results from the present study, highlight a possible role of CPS1 and related pathways in weight loss maintenance, suggesting that it might be partly genetically determined in humans.