WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows.

The inherent diversity of approaches in proteomics research has led to a wide range of software solutions for data analysis. These software solutions encompass multiple tools, each employing different algorithms for various tasks such as peptide-spectrum matching, protein inference, quantification, statistical analysis, and visualization. To enable an unbiased comparison of commonly used bottom-up label-free proteomics workflows, we introduce WOMBAT-P, a versatile platform designed for automated benchmarking and comparison. WOMBAT-P simplifies the processing of public data by utilizing the sample and data relationship format for proteomics (SDRF-Proteomics) as input. This feature streamlines the analysis of annotated local or public ProteomeXchange data sets, promoting efficient comparisons among diverse outputs. Through an evaluation using experimental ground truth data and a realistic biological data set, we uncover significant disparities and a limited overlap in the quantified proteins. WOMBAT-P not only enables rapid execution and seamless comparison of workflows but also provides valuable insights into the capabilities of different software solutions. These benchmarking metrics are a valuable resource for researchers in selecting the most suitable workflow for their specific data sets. The modular architecture of WOMBAT-P promotes extensibility and customization. The software is available at https://github.com/wombat-p/WOMBAT-Pipelines.

Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies.

Omics analyses are powerful methods to obtain an integrated view of complex biological processes, disease progression, or therapy efficiency. However, few studies have compared different disease forms and different therapy strategies to define the common molecular signatures representing the most significant implicated pathways. In this study, we used RNA sequencing and mass spectrometry to profile the transcriptomes and proteomes of mouse models for three forms of centronuclear myopathies (CNMs), untreated or treated with either a drug (tamoxifen), antisense oligonucleotides reducing the level of dynamin 2 (DNM2), or following modulation of DNM2 or amphiphysin 2 (BIN1) through genetic crosses. Unsupervised analysis and differential gene and protein expression were performed to retrieve CNM molecular signatures. Longitudinal studies before, at, and after disease onset highlighted potential disease causes and consequences. Main pathways in the common CNM disease signature include muscle contraction, regeneration and inflammation. The common therapy signature revealed novel potential therapeutic targets, including the calcium regulator sarcolipin. We identified several novel biomarkers validated in muscle and/or plasma through RNA quantification, western blotting, and enzyme-linked immunosorbent assay (ELISA) assays, including ANXA2 and IGFBP2. This study validates the concept of using multi-omics approaches to identify molecular signatures common to different disease forms and therapeutic strategies.

Functional microRNA screen uncovers O-linked N-acetylglucosamine transferase as a host factor modulating hepatitis C virus morphogenesis and infectivity.

OBJECTIVE: Infection of human hepatocytes by the hepatitis C virus (HCV) is a multistep process involving both viral and host factors. microRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression. Given that miRNAs were indicated to regulate between 30% and 75% of all human genes, we aimed to investigate the functional and regulatory role of miRNAs for the HCV life cycle. DESIGN: To systematically reveal human miRNAs affecting the HCV life cycle, we performed a two-step functional high-throughput miRNA mimic screen in Huh7.5.1 cells infected with recombinant cell culture-derived HCV. miRNA targeting was then assessed using a combination of computational and functional approaches. RESULTS: We uncovered miR-501-3p and miR-619-3p as novel modulators of HCV assembly/release. We discovered that these miRNAs regulate O-linked N-acetylglucosamine (O-GlcNAc) transferase (OGT) protein expression and identified OGT and O-GlcNAcylation as regulators of HCV morphogenesis and infectivity. Furthermore, increased OGT expression in patient-derived liver tissue was associated with HCV-induced liver disease and cancer. CONCLUSION: miR-501-3p and miR-619-3p and their target OGT are previously undiscovered regulatory host factors for HCV assembly and infectivity. In addition to its effect on HCV morphogenesis, OGT may play a role in HCV-induced liver disease and hepatocarcinogenesis.

Nxnl2 splicing results in dual functions in neuronal cell survival and maintenance of cell integrity.

The rod-derived cone viability factors, RdCVF and RdCVF2, have potential therapeutical interests for the treatment of inherited photoreceptor degenerations. In the mouse lacking Nxnl2, the gene encoding RdCVF2, the progressive decline of the visual performance of the cones in parallel with their degeneration, arises due to the loss of trophic support from RdCVF2. In contrary, the progressive loss of rod visual function of the Nxnl2-/- mouse results from a decrease in outer segment length, mediated by a cell autonomous mechanism involving the putative thioredoxin protein RdCVF2L, the second spliced product of the Nxnl2 gene. This novel signaling mechanism extends to olfaction as shown by the progressive impairment of olfaction in aged Nxnl2-/- mice and the protection of olfactory neurons by RdCVF2. This study shows that Nxnl2 is a bi-functional gene involved in the maintenance of both the function and the viability of sensory neurons.

KD4v: Comprehensible Knowledge Discovery System for Missense Variant.

A major challenge in the post-genomic era is a better understanding of how human genetic alterations involved in disease affect the gene products. The KD4v (Comprehensible Knowledge Discovery System for Missense Variant) server allows to characterize and predict the phenotypic effects (deleterious/neutral) of missense variants. The server provides a set of rules learned by Induction Logic Programming (ILP) on a set of missense variants described by conservation, physico-chemical, functional and 3D structure predicates. These rules are interpretable by non-expert humans and are used to accurately predict the deleterious/neutral status of an unknown mutation. The web server is available at http://decrypthon.igbmc.fr/kd4v.

Rfx6 is an Ngn3-dependent winged helix transcription factor required for pancreatic islet cell development.

The transcription factor neurogenin 3 (Neurog3 or Ngn3) controls islet cell fate specification in multipotent pancreatic progenitor cells in the mouse embryo. However, our knowledge of the genetic programs implemented by Ngn3, which control generic and islet subtype-specific properties, is still fragmentary. Gene expression profiling in isolated Ngn3-positive progenitor cells resulted in the identification of the uncharacterized winged helix transcription factor Rfx6. Rfx6 is initially expressed broadly in the gut endoderm, notably in Pdx1-positive cells in the developing pancreatic buds, and then becomes progressively restricted to the endocrine lineage, suggesting a dual function in both endoderm development and islet cell differentiation. Rfx6 is found in postmitotic islet progenitor cells in the embryo and is maintained in all developing and adult islet cell types. Rfx6 is dependent on Ngn3 and acts upstream of or in parallel with NeuroD, Pax4 and Arx transcription factors during islet cell differentiation. In zebrafish, the Rfx6 ortholog is similarly found in progenitors and hormone expressing cells of the islet lineage. Loss-of-function studies in zebrafish revealed that rfx6 is required for the differentiation of glucagon-, ghrelin- and somatostatin-expressing cells, which, in the absence of rfx6, are blocked at the progenitor stage. By contrast, beta cells, whose number is only slightly reduced, were no longer clustered in a compact islet. These data unveil Rfx6 as a novel regulator of islet cell development.

Changes in social behavior with MAPK2 and KCTD13/CUL3 pathways alterations in two new outbred rat models for the 16p11.2 syndromes with autism spectrum disorders.

Copy number variations (CNVs) of the human 16p11.2 locus are associated with several developmental/neurocognitive syndromes. Particularly, deletion and duplication of this genetic interval are found in patients with autism spectrum disorders, intellectual disability and other psychiatric traits. The high gene density associated with the region and the strong phenotypic variability of incomplete penetrance, make the study of the 16p11.2 syndromes extremely complex. To systematically study the effect of 16p11.2 CNVs and identify candidate genes and molecular mechanisms involved in the pathophysiology, mouse models were generated previously and showed learning and memory, and to some extent social deficits. To go further in understanding the social deficits caused by 16p11.2 syndromes, we engineered deletion and duplication of the homologous region to the human 16p11.2 genetic interval in two rat outbred strains, Sprague Dawley (SD) and Long Evans (LE). The 16p11.2 rat models displayed convergent defects in social behavior and in the novel object test in male carriers from both genetic backgrounds. Interestingly major pathways affecting MAPK1 and CUL3 were found altered in the rat 16p11.2 models with additional changes in males compared to females. Altogether, the consequences of the 16p11.2 genetic region dosage on social behavior are now found in three different species: humans, mice and rats. In addition, the rat models pointed to sexual dimorphism with lower severity of phenotypes in rat females compared to male mutants. This phenomenon is also observed in humans. We are convinced that the two rat models will be key to further investigating social behavior and understanding the brain mechanisms and specific brain regions that are key to controlling social behavior.

In vivo topoisomerase I inhibition attenuates the expression of hypoxia-inducible factor 1α target genes and decreases tumor angiogenesis.

Topoisomerase I is a privileged target for widely used anticancer agents such as irinotecan. Although these drugs are classically considered to be DNA-damaging agents, increasing evidence suggests that they might also influence the tumor environment. This study evaluates in vivo cellular and molecular modifications induced by irinotecan, a topoisomerase I-directed agent, in patient-derived colon tumors subcutaneously implanted in athymic nude mice. Irinotecan was given intraperitoneally at 40 mg/kg five times every 5 d, and expression profiles were evaluated at d 25 in tumors from treated and untreated animals. Unexpectedly, the in vivo antitumor activity of irinotecan was closely linked to a downregulation of hypoxia-inducible factor-1α (HIF1A) target genes along with an inhibition of HIF1A protein accumulation. The consequence was a decrease in tumor angiogenesis leading to tumor size stabilization. These results highlight the molecular basis for the antitumor activity of a widely used anticancer agent, and the method used opens the way for mechanistic studies of the in vivo activity of other anticancer therapies.

RReportGenerator: automatic reports from routine statistical analysis using R.

UNLABELLED: With the establishment of high-throughput (HT) screening methods there is an increasing need for automatic analysis methods. Here we present RReportGenerator, a user-friendly portal for automatic routine analysis using the statistical platform R and Bioconductor. RReportGenerator is designed to analyze data using predefined analysis scenarios via a graphical user interface (GUI). A report in pdf format combining text, figures and tables is automatically generated and results may be exported. To demonstrate suitable analysis tasks we provide direct web access to a collection of analysis scenarios for summarizing data from transfected cell arrays (TCA), segmentation of CGH data, and microarray quality control and normalization. AVAILABILITY: RReportGenerator, a user manual and a collection of analysis scenarios are available under a GNU public license on http://www-bio3d-igbmc.u-strasbg.fr/~wraff

Filtering genes to improve sensitivity in oligonucleotide microarray data analysis.

Many recent microarrays hold an enormous number of probe sets, thus raising many practical and theoretical problems in controlling the false discovery rate (FDR). Biologically, it is likely that most probe sets are associated with un-expressed genes, so the measured values are simply noise due to non-specific binding; also many probe sets are associated with non-differentially-expressed (non-DE) genes. In an analysis to find DE genes, these probe sets contribute to the false discoveries, so it is desirable to filter out these probe sets prior to analysis. In the methodology proposed here, we first fit a robust linear model for probe-level Affymetrix data that accounts for probe and array effects. We then develop a novel procedure called FLUSH (Filtering Likely Uninformative Sets of Hybridizations), which excludes probe sets that have statistically small array-effects or large residual variance. This filtering procedure was evaluated on a publicly available data set from a controlled spiked-in experiment, as well as on a real experimental data set of a mouse model for retinal degeneration. In both cases, FLUSH filtering improves the sensitivity in the detection of DE genes compared to analyses using unfiltered, presence-filtered, intensity-filtered and variance-filtered data. A freely-available package called FLUSH implements the procedures and graphical displays described in the article.

Analysis of the retinal gene expression profile after hypoxic preconditioning identifies candidate genes for neuroprotection.

BACKGROUND: Retinal degeneration is a main cause of blindness in humans. Neuroprotective therapies may be used to rescue retinal cells and preserve vision. Hypoxic preconditioning stabilizes the transcription factor HIF-1alpha in the retina and strongly protects photoreceptors in an animal model of light-induced retinal degeneration. To address the molecular mechanisms of the protection, we analyzed the transcriptome of the hypoxic retina using microarrays and real-time PCR. RESULTS: Hypoxic exposure induced a marked alteration in the retinal transcriptome with significantly different expression levels of 431 genes immediately after hypoxic exposure. The normal expression profile was restored within 16 hours of reoxygenation. Among the differentially regulated genes, several candidates for neuroprotection were identified like metallothionein-1 and -2, the HIF-1 target gene adrenomedullin and the gene encoding the antioxidative and cytoprotective enzyme paraoxonase 1 which was previously not known to be a hypoxia responsive gene in the retina. The strongly upregulated cyclin dependent kinase inhibitor p21 was excluded from being essential for neuroprotection. CONCLUSION: Our data suggest that neuroprotection after hypoxic preconditioning is the result of the differential expression of a multitude of genes which may act in concert to protect visual cells against a toxic insult.

RETINOBASE: a web database, data mining and analysis platform for gene expression data on retina.

BACKGROUND: The retina is a multi-layered sensory tissue that lines the back of the eye and acts at the interface of input light and visual perception. Its main function is to capture photons and convert them into electrical impulses that travel along the optic nerve to the brain where they are turned into images. It consists of neurons, nourishing blood vessels and different cell types, of which neural cells predominate. Defects in any of these cells can lead to a variety of retinal diseases, including age-related macular degeneration, retinitis pigmentosa, Leber congenital amaurosis and glaucoma. Recent progress in genomics and microarray technology provides extensive opportunities to examine alterations in retinal gene expression profiles during development and diseases. However, there is no specific database that deals with retinal gene expression profiling. In this context we have built RETINOBASE, a dedicated microarray database for retina. DESCRIPTION: RETINOBASE is a microarray relational database, analysis and visualization system that allows simple yet powerful queries to retrieve information about gene expression in retina. It provides access to gene expression meta-data and offers significant insights into gene networks in retina, resulting in better hypothesis framing for biological problems that can subsequently be tested in the laboratory. Public and proprietary data are automatically analyzed with 3 distinct methods, RMA, dChip and MAS5, then clustered using 2 different K-means and 1 mixture models method. Thus, RETINOBASE provides a framework to compare these methods and to optimize the retinal data analysis. RETINOBASE has three different modules, "Gene Information", "Raw Data System Analysis" and "Fold change system Analysis" that are interconnected in a relational schema, allowing efficient retrieval and cross comparison of data. Currently, RETINOBASE contains datasets from 28 different microarray experiments performed in 5 different model systems: drosophila, zebrafish, rat, mouse and human. The database is supported by a platform that is designed to easily integrate new functionalities and is also frequently updated. CONCLUSION: The results obtained from various biological scenarios can be visualized, compared and downloaded. The results of a case study are presented that highlight the utility of RETINOBASE. Overall, RETINOBASE provides efficient access to the global expression profiling of retinal genes from different organisms under various conditions.

Density of points clustering, application to transcriptomic data analysis.

With the increasing amount of data produced by high-throughput technologies in many fields of science, clustering has become an integral step in exploratory data analysis in order to group similar elements into classes. However, many clustering algorithms can only work properly if aided by human expertise. For example, one parameter which is crucial and often manually set is the number of clusters present in the analyzed set. We present a novel stopping rule to find the optimal number of clusters based on the comparison of the density of points inside the clusters and between them. The method is evaluated on synthetic as well as on real transcriptomic data and compared with two current methods. Finally, we illustrate its usefulness in the analysis of the expression profiles of promyelocytic cells before and after treatment with all-trans retinoic acid. Simultaneous clustering for gene regulation and absolute initial expression levels allowed the identification of numerous genes associated with signal transduction revealing the complexity of retinoic acid signaling.

Ubiquitin Receptor Protein UBASH3B Drives Aurora B Recruitment to Mitotic Microtubules.

Mitosis ensures equal segregation of the genome and is controlled by a variety of ubiquitylation signals on substrate proteins. However, it remains unexplored how the versatile ubiquitin code is read out during mitotic progression. Here, we identify the ubiquitin receptor protein UBASH3B as an important regulator of mitosis. UBASH3B interacts with ubiquitylated Aurora B, one of the main kinases regulating chromosome segregation, and controls its subcellular localization but not protein levels. UBASH3B is a limiting factor in this pathway and is sufficient to localize Aurora B to microtubules prior to anaphase. Importantly, targeting Aurora B to microtubules by UBASH3B is necessary for the timing and fidelity of chromosome segregation in human cells. Our findings uncover an important mechanism defining how ubiquitin attachment to a substrate protein is decoded during mitosis.

Retinoic acid determines life span of leukemic cells by inducing antagonistic apoptosis-regulatory programs.

As a single signal, retinoids induce terminal differentiation. This implies that they activate differentiation and apoptosis in a temporally defined order to allow expression of the differentiated phenotype well before death. We report that two apparently contradictory retinoid-induced programs have the capacity to define cellular life span. Anti-apoptotic factors are activated concomitantly with differentiation, while retinoids induce at the same time also pro-apoptotic signaling. We have assessed the roles of two key factors, Bcl2A1 and TRAIL, in the temporal programming of cell death and differentiation. We demonstrate that PLB985 are type II cells in which TRAIL induces apoptosis through the extrinsic and--via Bid activation--also the intrinsic death pathways. Bcl2A1, ectopically over-expressed, or endogenously induced by retinoic acid receptor agonists, protected cells from apoptosis triggered by TRAIL, whose induction required the activation of both the retinoic acid and retinoid X receptors. Bcl2A1 prevented loss of mitochondrial membrane potential and caspase-9, but not caspase-8, activation. The expression of anti-sense Bcl2A1 sensitized PLB985 cells to TRAIL. Co-culture experiments revealed protection from fraternicide if sister cells were pre-exposed to retinoic acid. Collectively, our data support a model in which retinoids orchestrate a life span-regulatory program comprising Bcl2A1 induction to temporally protect against concomitantly induced TRAIL death signaling. Termination of this life span in presence of Bcl2A1 is most likely a consequence of the Bid-independent TRAIL action. Thus, depending on the retinoic acid and retinoid X receptor activation potential of a ligand and the relative efficacies of the intrinsic and extrinsic death pathways in a given cell, a single retinoid triggers the life span of a differentiated phenotype.

The molecular signature of the stroma response in prostate cancer-induced osteoblastic bone metastasis highlights expansion of hematopoietic and prostate epithelial stem cell niches.

The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.

Transcriptomic analysis of human retinal detachment reveals both inflammatory response and photoreceptor death.

BACKGROUND: Retinal detachment often leads to a severe and permanent loss of vision and its therapeutic management remains to this day exclusively surgical. We have used surgical specimens to perform a differential analysis of the transcriptome of human retinal tissues following detachment in order to identify new potential pharmacological targets that could be used in combination with surgery to further improve final outcome. METHODOLOGY/PRINCIPAL FINDINGS: Statistical analysis reveals major involvement of the immune response in the disease. Interestingly, using a novel approach relying on coordinated expression, the interindividual variation was monitored to unravel a second crucial aspect of the pathological process: the death of photoreceptor cells. Within the genes identified, the expression of the major histocompatibility complex I gene HLA-C enables diagnosis of the disease, while PKD2L1 and SLCO4A1 -which are both down-regulated- act synergistically to provide an estimate of the duration of the retinal detachment process. Our analysis thus reveals the two complementary cellular and molecular aspects linked to retinal detachment: an immune response and the degeneration of photoreceptor cells. We also reveal that the human specimens have a higher clinical value as compared to artificial models that point to IL6 and oxidative stress, not implicated in the surgical specimens studied here. CONCLUSIONS/SIGNIFICANCE: This systematic analysis confirmed the occurrence of both neurodegeneration and inflammation during retinal detachment, and further identifies precisely the modification of expression of the different genes implicated in these two phenomena. Our data henceforth give a new insight into the disease process and provide a rationale for therapeutic strategies aimed at limiting inflammation and photoreceptor damage associated with retinal detachment and, in turn, improving visual prognosis after retinal surgery.

EGFR and EphA2 are host factors for hepatitis C virus entry and possible targets for antiviral therapy.

Hepatitis C virus (HCV) is a major cause of liver disease, but therapeutic options are limited and there are no prevention strategies. Viral entry is the first step of infection and requires the cooperative interaction of several host cell factors. Using a functional RNAi kinase screen, we identified epidermal growth factor receptor and ephrin receptor A2 as host cofactors for HCV entry. Blocking receptor kinase activity by approved inhibitors broadly impaired infection by all major HCV genotypes and viral escape variants in cell culture and in a human liver chimeric mouse model in vivo. The identified receptor tyrosine kinases (RTKs) mediate HCV entry by regulating CD81-claudin-1 co-receptor associations and viral glycoprotein-dependent membrane fusion. These results identify RTKs as previously unknown HCV entry cofactors and show that tyrosine kinase inhibitors have substantial antiviral activity. Inhibition of RTK function may constitute a new approach for prevention and treatment of HCV infection.

Multidimensional fitting for multivariate data analysis.

Large multidimensional data matrices are frequent in biology. However, statistical methods often have difficulties dealing with such matrices because they contain very complex data sets. Consequently variable selection and dimensionality reduction methods are often used to reduce matrix complexity, although at the expense of information conservation. A new method derived from multidimensional scaling (MDS) is presented for the case where two matrices are available to describe the same population. The presented method transforms one of the matrices, called the target matrix, with some constraints to make it fit with the second matrix, referred to as the reference matrix. The fitting to the reference matrix is performed on the distances computed for the two matrices, and the transformation depends on the problem at hand. A special feature of this method is that a variable can be only partially modified. The method is applied on the exclusive-or (XOR) problem and then on a biological application with large-scale gene expression data.