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Abstract Background The availability of hundreds of bacterial genomes allowed a comparative genomic study of the Type VI Secretion System (T6SS), recently discovered as being involved in pathogenesis. By combining comparative and phylogenetic approaches using more than 500 prokaryotic genomes, we characterized the global T6SS genetic structure in terms of conservation, evolution and genomic organization. Results This genome wide analysis allowed the identification of a set of 13 proteins constituting the T6SS protein core and a set of conserved accessory proteins. 176 T6SS loci (encompassing 92 different bacteria) were identified and their comparison revealed that T6SS-encoded genes have a specific conserved genetic organization. Phylogenetic reconstruction based on the core genes showed that lateral transfer of the T6SS is probably its major way of dissemination among pathogenic and non-pathogenic bacteria. Furthermore, the sequence analysis of the VgrG proteins, proposed to be exported in a T6SS-dependent way, confirmed that some C-terminal regions possess domains showing similarities with adhesins or proteins with enzymatic functions. Conclusion The core of T6SS is composed of 13 proteins, conserved in both pathogenic and non-pathogenic bacteria. Subclasses of T6SS differ in regulatory and accessory protein content suggesting that T6SS has evolved to adapt to various microenvironments and specialized functions. Based on these results, new functional hypotheses concerning the assembly and function of T6SS proteins are proposed.

Abstract Background The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging. Results We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions. Conclusion The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web at http://cbio.ensmp.fr/dsir

Abstract Background A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs. Results GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces. Conclusion GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at academy@genostar.com. A commercial licence form can be obtained for profit company at info@genostar.com. See also http://www.genostar.org.

Quantitative analyses and models are required to connect a plant's cellular organisation with its metabolism. However, quantitative data are often scattered over multiple studies, and finding such data and converting them into useful information is time-consuming. Consequently, there is a need to centralise the available data and to highlight the remaining knowledge gaps. Here, we present a step-by-step approach to manually extract quantitative data from various information sources, and to unify the data format. First, data from Arabidopsis leaf were collated, checked for consistency and correctness and curated by cross-checking sources. Second, quantitative data were combined by applying calculation rules. They were then integrated into a unique comprehensive, referenced, modifiable and reusable data compendium representing an Arabidopsis reference leaf. This atlas contains the metrics of the 15 cell types found in leaves at the cellular and subcellular levels., Competing Interests: The authors declare they have no competing interests., (© The Author(s) 2024.)

Genes are pleiotropic and getting a better knowledge of their function requires a comprehensive characterization of their mutants. Here, we generated multi-level data combining phenomic, proteomic and metabolomic acquisitions from plasma and liver tissues of two C57BL/6 N mouse models lacking the Lat (linker for activation of T cells) and the Mx2 (MX dynamin-like GTPase 2) genes, respectively. Our dataset consists of 9 assays (1 preclinical, 2 proteomics and 6 metabolomics) generated with a fully non-targeted and standardized approach. The data and processing code are publicly available in the ProMetIS R package to ensure accessibility, interoperability, and reusability. The dataset thus provides unique molecular information about the physiological role of the Lat and Mx2 genes. Furthermore, the protocols described herein can be easily extended to a larger number of individuals and tissues. Finally, this resource will be of great interest to develop new bioinformatic and biostatistic methods for multi-omics data integration., (© 2021. The Author(s).)

Acute liver injury (ALI) is a severe disorder resulting from excessive hepatocyte cell death, and frequently caused by acetaminophen intoxication. Clinical management of ALI progression is hampered by the dearth of blood biomarkers available. In this study, a bioinformatics workflow was developed to screen omics databases and identify potential biomarkers for hepatocyte cell death. Then, discovery proteomics was harnessed to select from among these candidates those that were specifically detected in the blood of acetaminophen-induced ALI patients. Among these candidates, the isoenzyme alcohol dehydrogenase 1B (ADH1B) was massively leaked into the blood. To evaluate ADH1B, we developed a targeted proteomics assay and quantified ADH1B in serum samples collected at different times from 17 patients admitted for acetaminophen-induced ALI. Serum ADH1B concentrations increased markedly during the acute phase of the disease, and dropped to undetectable levels during recovery. In contrast to alanine aminotransferase activity, the rapid drop in circulating ADH1B concentrations was followed by an improvement in the international normalized ratio (INR) within 10-48 h, and was associated with favorable outcomes. In conclusion, the combination of omics data exploration and proteomics revealed ADH1B as a new blood biomarker candidate that could be useful for the monitoring of acetaminophen-induced ALI.

Can we understand how plant cell metabolism really works? An integrated large-scale modelling of plant metabolism predictive model would make possible to analyse the impact of disturbances in environmental conditions on cellular functioning and diversity of plant-made molecules of interest. ChloroKB, a Web application initially developed for exploration of Arabidopsis chloroplast metabolic network now covers Arabidopsis mesophyll cell metabolism. Interconnected metabolic maps show subcellular compartments, metabolites, proteins, complexes, reactions, and transport. Data in ChloroKB have been structured to allow for mathematical modelling and will be used as a reference for modelling work dedicated to a particular issue.

Proteo3Dnet is a web server dedicated to the analysis of mass spectrometry interactomics experiments. Given a flat list of proteins, its aim is to organize it in terms of structural interactions to provide a clearer overview of the data. This is achieved using three means: (i) the search for interologs with resolved structure available in the protein data bank, including cross-species remote homology search, (ii) the search for possibly weaker interactions mediated through Short Linear Motifs as predicted by ELM-a unique feature of Proteo3Dnet, (iii) the search for protein-protein interactions physically validated in the BioGRID database. The server then compiles this information and returns a graph of the identified interactions and details about the different searches. The graph can be interactively explored to understand the way the core complexes identified could interact. It can also suggest undetected partners to the experimentalists, or specific cases of conditionally exclusive binding. The interest of Proteo3Dnet, previously demonstrated for the difficult cases of the proteasome and pragmin complexes data is, here, illustrated in the context of yeast precursors to the small ribosomal subunits and the smaller interactome of 14-3-3zeta frequent interactors. The Proteo3Dnet web server is accessible at http://bioserv.rpbs.univ-paris-diderot.fr/services/Proteo3Dnet/., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP's tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.

Background: Accurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes., Results: Our proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data., Conclusions: Peptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu . Data are available via ProteomeXchange under identifier PXD010618.

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis ( Arabidopsis thaliana ) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers., (© 2017 American Society of Plant Biologists. All Rights Reserved.)

The development of resistances to conventional anticancer drugs compromises the efficacy of cancer treatments. In the case of DNA-targeting chemotherapeutic agents, cancer cells may display tolerance to the drug-induced DNA lesions and/or enhanced DNA repair. However, the role of DNA damage response (DDR) and DNA repair in this chemoresistance has yet to be defined. To provide insights in this challenging area, we analyzed the DNA repair signature of 7 cancer cell lines treated by 5 cytotoxic drugs using a recently developed multiplexed functional DNA repair assay. This comprehensive approach considered the complexity and redundancy of the different DNA repair pathways. Data was analyzed using clustering methods and statistical tests. This DNA repair profiling method defined relevant groups based on similarities between different drugs, thus providing information relating to their dominant mechanism of action at the DNA level. Similarly, similarities between different cell lines presumably identified identical functional DDR despite a high level of genetic heterogeneity between cell lines. Our strategy has shed new light on the contribution of specific repair sub-pathways to drug-induced cytotoxicity. Although further molecular characterisations are needed to fully unravel the mechanisms underlying our findings, our approach proved to be very promising to interrogate the complexity of the DNA repair response. Indeed, it could be used to predict the efficacy of a given drug and the chemosensitivity of individual patients, and thus to choose the right treatment for individualised cancer care.

Chemically synthesized small interfering RNA (siRNA) is a widespread molecular tool used to knock down genes in mammalian cells. However, designing potent siRNA remains challenging. Among tools predicting siRNA efficacy, very few have been validated on endogenous targets in realistic experimental conditions. We previously described a tool to assist efficient siRNA design (DSIR, Designer of siRNA), which focuses on intrinsic features of the siRNA sequence. Here, we evaluated DSIR's performance by systematically investigating the potency of the siRNA it designs to target ten cancer-related genes. mRNA knockdown was measured by quantitative RT-PCR in cell-based assays, revealing that over 60% of siRNA sequences designed by DSIR silenced their target genes by at least 70%. Silencing efficacy was sustained even when low siRNA concentrations were used. This systematic analysis revealed in particular that, for a subset of genes, the efficiency of siRNA constructs significantly increases when the sequence is located closer to the 5'-end of the target gene coding sequence, suggesting the distance to the 5'-end as a new feature for siRNA potency prediction. A new version of DSIR incorporating these new findings, as well as the list of validated siRNA against the tested cancer genes, has been made available on the web (http://biodev.extra.cea.fr/DSIR).

Background: The availability of hundreds of bacterial genomes allowed a comparative genomic study of the Type VI Secretion System (T6SS), recently discovered as being involved in pathogenesis. By combining comparative and phylogenetic approaches using more than 500 prokaryotic genomes, we characterized the global T6SS genetic structure in terms of conservation, evolution and genomic organization., Results: This genome wide analysis allowed the identification of a set of 13 proteins constituting the T6SS protein core and a set of conserved accessory proteins. 176 T6SS loci (encompassing 92 different bacteria) were identified and their comparison revealed that T6SS-encoded genes have a specific conserved genetic organization. Phylogenetic reconstruction based on the core genes showed that lateral transfer of the T6SS is probably its major way of dissemination among pathogenic and non-pathogenic bacteria. Furthermore, the sequence analysis of the VgrG proteins, proposed to be exported in a T6SS-dependent way, confirmed that some C-terminal regions possess domains showing similarities with adhesins or proteins with enzymatic functions., Conclusion: The core of T6SS is composed of 13 proteins, conserved in both pathogenic and non-pathogenic bacteria. Subclasses of T6SS differ in regulatory and accessory protein content suggesting that T6SS has evolved to adapt to various microenvironments and specialized functions. Based on these results, new functional hypotheses concerning the assembly and function of T6SS proteins are proposed.

Protocadherins are transmembrane proteins exhibiting homophilic adhesive activities through their extracellular domain. Protocadherin 12 (Pcdh12) is expressed in angiogenic endothelial cells, mesangial cells of kidney glomeruli, and glycogen cells of the mouse placenta. To get insight into the role of this protein in vivo, we analyzed PCDH12-deficient mice and investigated their placental phenotype. The mice were alive and fertile; however, placental and embryonic sizes were reduced compared with wild-type mice. We observed defects in placental layer segregation and a decreased vascularization of the labyrinth associated with a reduction in cell density in this layer. To understand the molecular events responsible for the phenotypic alterations observed in Pcdh12(-/-) placentas, we analyzed the expression profile of embryonic day 12.5 mutant placentas compared with wild-type placentas, using pangenomic chips: 2,289 genes exhibited statistically significant changes in expressed levels due to loss of PCDH12. Functional grouping of modified genes was obtained by GoMiner software. Gene clusters that contained most of the differentially expressed genes were those involved in tissue morphogenesis and development, angiogenesis, cell-matrix adhesion and migration, immune response, and chromatin remodeling. Our data show that loss of PCDH12 leads to morphological alterations of the placenta and to notable changes in its gene expression profile. Specific genes emerging from the microarray screen support the biological modifications observed in PCDH12-deficient placentas.

Background: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging., Results: We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions., Conclusion: The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web at http://cbio.ensmp.fr/dsir.

Background: A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs., Results: GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces., Conclusion: GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at academy@genostar.com. A commercial licence form can be obtained for profit company at info@genostar.com. See also http://www.genostar.org.

Incubation of HepG2 cells in the presence of dibutyryl cAMP (db-cAMP), a cell permeable analogue of cyclic AMP, or forskolin, an agent which elevates intracellular cAMP, resulted in a 50% decrease in apoE mRNA levels within 24 h. Results of nuclear run-on transcription assays showed that db-cAMP down-regulates apoE gene expression at the transcriptional level. By transfection analysis with a plasmid containing the -614/+804 human apoE gene fused to the secreted placental alkaline phosphatase (SPAP) reporter gene, we showed that the SPAP activity was decreased by 50% when HepG2 cells were incubated in the presence of db-cAMP or forskolin, indicating that this promoter region mediated this negative effect. In contrast, when the smaller fragment -200/+1 of apoE promoter was linked to the CAT reporter gene, db-cAMP treatment of HepG2 cells resulted in a 2-fold increase in CAT activity, suggesting that positive cAMP-responsive elements were present in the proximal apoE promoter. These data indicate that transcriptional modulation of apoE gene expression by agents known to elevate the intracellular cAMP level is complex and involves several negative and positive elements located in the -614 to +804 region of the apoE gene whose global effect is negative on apoE gene transcription.

The regulation of apolipoprotein A-I (apo A-I) gene expression by 12-O-tetradecanoylphorbol 13-acetate (TPA) was investigated in the human hepatoma cell line Hep G2. TPA treatment decreased apo A-I mRNA levels in a time-dependent manner, by up to 50% versus control cells within 24 h. Nuclear run-on transcription assays demonstrated a transcriptional effect of TPA. Using transfection analysis with a plasmid construct containing the -1378/+11 apo A-I promoter fused to the secreted placental alkaline phosphatase (SPAP) reporter gene, we showed that the SPAP activity was decreased to 50% when Hep G2 cells were incubated in the presence of TPA. The inhibitory effect of TPA was still maintained when fragment -253 to -4 of apo A-I promoter was linked to the CAT reporter gene. These data indicate that transcriptional modulation of apolipoprotein A-I gene expression following phorbol ester treatment is transduced by gene elements located between -253 and -4 of the apo A-I promoter.

Hyperthyroidism is associated with elevated plasma levels of apolipoprotein AI (apo AI). We have examined the effects of 3,3',-5-triiodothyronine on apo AI mRNA, transcription run-on activity, apo AI mRNA half-life, and the rate of protein synthesis in Hep G2 cells, to understand the molecular mechanism by which thyroid hormone regulates apo AI gene expression. Incubation with thyroid hormone increased the apo AI and apo AII mRNA concentrations twofold. Cycloheximide alone caused a significant increase in apo AI mRNA. Nuclear run-on assays indicate that thyroid hormone did not change the rate of the apo AI gene transcription at 6, 12 or 24 h, showing that thyroid hormone did not modulate apo AI gene transcription. Kinetic studies performed in the presence of actinomycin D showed that the half-life of apo AI mRNA was increased 2-3-fold by thyroid hormone over control cells. Thyroid hormone did not change the incorporation of [35S]methionine into immunoprecipitable apo AI. Pulse-chase experiments demonstrated that there was no change in the secretion and degradation rates of labeled apo AI in response to T3. This suggests that thyroid hormone does not affect the catabolism of apo AI (degradation or/and uptake) and that translation control strongly influences the regulation of apo AI gene expression. The stabilization of apo AI mRNA by thyroid hormone and its role in translation remain to be elucidated.

The regulation of the synthesis and secretion of apolipoprotein E (apoE) is incompletely understood. This study examines the mechanisms responsible for regulating apoE gene expression in HepG2 cells by thyroid hormone (3,3'-5-triiodothyronine). The secretion rate of apoE was by thyroid hormone increased (1.5-1.8-fold) in pulse/chase experiments. Thyroid hormone doubled apoE mRNA concentration as determined by Northern-blot analysis. Inhibition of protein synthesis by cycloheximide increased the thyroid-hormone-induced stimulation of apoE mRNA. This suggests that the synthesis of new protein is not required for thyroid hormone to stimulate apoE mRNA. Actinomycin D was used to inhibit new transcription; there was a more rapid degradation of mature apoE mRNA in thyroid hormone-treated HepG2 cells than in control cells, suggesting that thyroid hormone acts post-transcriptionally to regulate apoE gene expression. Cycloheximide blocked the action of thyroid hormone, suggesting that thyroid hormone regulates the turnover of apoE mRNA via the synthesis of de novo protein. Nuclear run-on transcription assays demonstrated that thyroid hormone stimulated apoE gene transcription threefold in 24 h. These findings indicate that the expression of the apoE gene is controlled at both transcriptional and post-transcriptional loci by the thyroid hormone.