FAIR+E pathogen data for surveillance and research: lessons from COVID-19.

The COVID-19 pandemic has exemplified the importance of interoperable and equitable data sharing for global surveillance and to support research. While many challenges could be overcome, at least in some countries, many hurdles within the organizational, scientific, technical and cultural realms still remain to be tackled to be prepared for future threats. We propose to (i) continue supporting global efforts that have proven to be efficient and trustworthy toward addressing challenges in pathogen molecular data sharing; (ii) establish a distributed network of Pathogen Data Platforms to (a) ensure high quality data, metadata standardization and data analysis, (b) perform data brokering on behalf of data providers both for research and surveillance, (c) foster capacity building and continuous improvements, also for pandemic preparedness; (iii) establish an International One Health Pathogens Portal, connecting pathogen data isolated from various sources (human, animal, food, environment), in a truly One Health approach and following FAIR principles. To address these challenging endeavors, we have started an ELIXIR Focus Group where we invite all interested experts to join in a concerted, expert-driven effort toward sustaining and ensuring high-quality data for global surveillance and research.

RSAT 2022: regulatory sequence analysis tools.

RSAT (Regulatory Sequence Analysis Tools) enables the detection and the analysis of cis-regulatory elements in genomic sequences. This software suite performs (i) de novo motif discovery (including from genome-wide datasets like ChIP-seq/ATAC-seq) (ii) genomic sequences scanning with known motifs, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations and (v) comparative genomics. RSAT comprises 50 tools. Six public Web servers (including a teaching server) are offered to meet the needs of different biological communities. RSAT philosophy and originality are: (i) a multi-modal access depending on the user needs, through web forms, command-line for local installation and programmatic web services, (ii) a support for virtually any genome (animals, bacteria, plants, totalizing over 10 000 genomes directly accessible). Since the 2018 NAR Web Software Issue, we have developed a large REST API, extended the support for additional genomes and external motif collections, enhanced some tools and Web forms, and developed a novel tool that builds or refine gene regulatory networks using motif scanning (network-interactions). The RSAT website provides extensive documentation, tutorials and published protocols. RSAT code is under open-source license and now hosted in GitHub. RSAT is available at http://www.rsat.eu/.

Tuning promoter boundaries improves regulatory motif discovery in nonmodel plants: the peach example.

The identification of functional elements encoded in plant genomes is necessary to understand gene regulation. Although much attention has been paid to model species like Arabidopsis (Arabidopsis thaliana), little is known about regulatory motifs in other plants. Here, we describe a bottom-up approach for de novo motif discovery using peach (Prunus persica) as an example. These predictions require pre-computed gene clusters grouped by their expression similarity. After optimizing the boundaries of proximal promoter regions, two motif discovery algorithms from RSAT::Plants (http://plants.rsat.eu) were tested (oligo and dyad analysis). Overall, 18 out of 45 co-expressed modules were enriched in motifs typical of well-known transcription factor (TF) families (bHLH, bZip, BZR, CAMTA, DOF, E2FE, AP2-ERF, Myb-like, NAC, TCP, and WRKY) and a few uncharacterized motifs. Our results indicate that small modules and promoter window of [-500 bp, +200 bp] relative to the transcription start site (TSS) maximize the number of motifs found and reduce low-complexity signals in peach. The distribution of discovered regulatory sites was unbalanced, as they accumulated around the TSS. This approach was benchmarked by testing two different expression-based clustering algorithms (network-based and hierarchical) and, as control, genes grouped for harboring ChIPseq peaks of the same Arabidopsis TF. The method was also verified on maize (Zea mays), a species with a large genome. In summary, this article presents a glimpse of the peach regulatory components at genome scale and provides a general protocol that can be applied to other species. A Docker software container is released to facilitate the reproduction of these analyses.

Tracing the origins of SARS-COV-2 in coronavirus phylogenies: a review.

SARS-CoV-2 is a new human coronavirus (CoV), which emerged in China in late 2019 and is responsible for the global COVID-19 pandemic that caused more than 97 million infections and 2 million deaths in 12 months. Understanding the origin of this virus is an important issue, and it is necessary to determine the mechanisms of viral dissemination in order to contain future epidemics. Based on phylogenetic inferences, sequence analysis and structure-function relationships of coronavirus proteins, informed by the knowledge currently available on the virus, we discuss the different scenarios on the origin-natural or synthetic-of the virus. The data currently available are not sufficient to firmly assert whether SARS-CoV2 results from a zoonotic emergence or from an accidental escape of a laboratory strain. This question needs to be solved because it has important consequences on the risk/benefit balance of our interactions with ecosystems, on intensive breeding of wild and domestic animals, on some laboratory practices and on scientific policy and biosafety regulations. Regardless of COVID-19 origin, studying the evolution of the molecular mechanisms involved in the emergence of pandemic viruses is essential to develop therapeutic and vaccine strategies and to prevent future zoonoses. This article is a translation and update of a French article published in Médecine/Sciences, August/September 2020 (10.1051/medsci/2020123). Supplementary Information: The online version of this article (10.1007/s10311-020-01151-1) contains supplementary material, which is available to authorized users.

biotoolsSchema: a formalized schema for bioinformatics software description.

BACKGROUND: Life scientists routinely face massive and heterogeneous data analysis tasks and must find and access the most suitable databases or software in a jungle of web-accessible resources. The diversity of information used to describe life-scientific digital resources presents an obstacle to their utilization. Although several standardization efforts are emerging, no information schema has been sufficiently detailed to enable uniform semantic and syntactic description-and cataloguing-of bioinformatics resources. FINDINGS: Here we describe biotoolsSchema, a formalized information model that balances the needs of conciseness for rapid adoption against the provision of rich technical information and scientific context. biotoolsSchema results from a series of community-driven workshops and is deployed in the bio.tools registry, providing the scientific community with >17,000 machine-readable and human-understandable descriptions of software and other digital life-science resources. We compare our approach to related initiatives and provide alignments to foster interoperability and reusability. CONCLUSIONS: biotoolsSchema supports the formalized, rigorous, and consistent specification of the syntax and semantics of bioinformatics resources, and enables cataloguing efforts such as bio.tools that help scientists to find, comprehend, and compare resources. The use of biotoolsSchema in bio.tools promotes the FAIRness of research software, a key element of open and reproducible developments for data-intensive sciences.

RhizoBindingSites, a Database of DNA-Binding Motifs in Nitrogen-Fixing Bacteria Inferred Using a Footprint Discovery Approach.

Basic knowledge of transcriptional regulation is needed to understand the mechanisms governing biological processes, i.e., nitrogen fixation by Rhizobiales bacteria in symbiosis with leguminous plants. The RhizoBindingSites database is a computer-assisted framework providing motif-gene-associated conserved sequences potentially implicated in transcriptional regulation in nine symbiotic species. A dyad analysis algorithm was used to deduce motifs in the upstream regulatory region of orthologous genes, and only motifs also located in the gene seed promoter with a p-value of 1e-4 were accepted. A genomic scan analysis of the upstoream sequences with these motifs was performed. These predicted binding sites were categorized according to low, medium and high homology between the matrix and the upstream regulatory sequence. On average, 62.7% of the genes had a motif, accounting for 80.44% of the genes per genome, with 19613 matrices (a matrix is a representation of a motif). The RhizoBindingSites database provides motif and gene information, motif conservation in the order Rhizobiales, matrices, motif logos, regulatory networks constructed from theoretical or experimental data, a criterion for selecting motifs and a guide for users. The RhizoBindingSites database is freely available online at rhizobindingsites.ccg.unam.mx.

Ancestral state reconstruction of metabolic pathways across pangenome ensembles.

As genome sequencing efforts are unveiling the genetic diversity of the biosphere with an unprecedented speed, there is a need to accurately describe the structural and functional properties of groups of extant species whose genomes have been sequenced, as well as their inferred ancestors, at any given taxonomic level of their phylogeny. Elaborate approaches for the reconstruction of ancestral states at the sequence level have been developed, subsequently augmented by methods based on gene content. While these approaches of sequence or gene-content reconstruction have been successfully deployed, there has been less progress on the explicit inference of functional properties of ancestral genomes, in terms of metabolic pathways and other cellular processes. Herein, we describe PathTrace, an efficient algorithm for parsimony-based reconstructions of the evolutionary history of individual metabolic pathways, pivotal representations of key functional modules of cellular function. The algorithm is implemented as a five-step process through which pathways are represented as fuzzy vectors, where each enzyme is associated with a taxonomic conservation value derived from the phylogenetic profile of its protein sequence. The method is evaluated with a selected benchmark set of pathways against collections of genome sequences from key data resources. By deploying a pangenome-driven approach for pathway sets, we demonstrate that the inferred patterns are largely insensitive to noise, as opposed to gene-content reconstruction methods. In addition, the resulting reconstructions are closely correlated with the evolutionary distance of the taxa under study, suggesting that a diligent selection of target pangenomes is essential for maintaining cohesiveness of the method and consistency of the inference, serving as an internal control for an arbitrary selection of queries. The PathTrace method is a first step towards the large-scale analysis of metabolic pathway evolution and our deeper understanding of functional relationships reflected in emerging pangenome collections.

[Tracing the origins of SARS-COV-2 in coronavirus phylogenies]. / Retrouver les origines du SARS-CoV-2 dans les phylogénies de coronavirus.

SARS-CoV-2 is a new human coronavirus (CoV), which emerged in People's Republic of China at the end of 2019 and is responsible for the global Covid-19 pandemic that caused more than 540 000 deaths in six months. Understanding the origin of this virus is an important issue and it is necessary to determine the mechanisms of its dissemination in order to be able to contain new epidemics. Based on phylogenetic inferences, sequence analysis and structure-function relationships of coronavirus proteins, informed by the knowledge currently available, we discuss the different scenarios evoked to account for the origin - natural or synthetic - of the virus. On the basis of currently available data, it is impossible to determine whether SARS-CoV-2 is the result of a natural zoonotic emergence or an accidental escape from experimental strains. Regardless of its origin, the study of the evolution of the molecular mechanisms involved in the emergence of this pandemic virus is essential to develop therapeutic and vaccine strategies.

TITLE: Retrouver les origines du SARS-CoV-2 dans les phylogénies de coronavirus. ABSTRACT: Le SARS-CoV-2 est un nouveau coronavirus (CoV) humain. Il a émergé en Chine fin 2019 et est responsable de la pandémie mondiale de Covid-19 qui a causé plus de 540 000 décès en six mois. La compréhension de l'origine de ce virus est une question importante et il est nécessaire de déterminer les mécanismes de sa dissémination afin de pouvoir se prémunir de nouvelles épidémies. En nous fondant sur des inférences phylogénétiques, l'analyse des séquences et les relations structure-fonction des protéines de coronavirus, éclairées par les connaissances actuellement disponibles, nous discutons les différents scénarios évoqués pour rendre compte de l'origine - naturelle ou synthétique - du virus.

In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication.

A novel coronavirus, named SARS-CoV-2, emerged in 2019 in China and rapidly spread worldwide. As no approved therapeutics exists to treat COVID-19, the disease associated to SARS-Cov-2, there is an urgent need to propose molecules that could quickly enter into clinics. Repurposing of approved drugs is a strategy that can bypass the time-consuming stages of drug development. In this study, we screened the PRESTWICK CHEMICAL LIBRARY composed of 1,520 approved drugs in an infected cell-based assay. The robustness of the screen was assessed by the identification of drugs that already demonstrated in vitro antiviral effect against SARS-CoV-2. Thereby, 90 compounds were identified as positive hits from the screen and were grouped according to their chemical composition and their known therapeutic effect. Then EC50 and CC50 were determined for a subset of 15 compounds from a panel of 23 selected drugs covering the different groups. Eleven compounds such as macrolides antibiotics, proton pump inhibitors, antiarrhythmic agents or CNS drugs emerged showing antiviral potency with 2 < EC50 ≤ 20 µM. By providing new information on molecules inhibiting SARS-CoV-2 replication in vitro, this study provides information for the selection of drugs to be further validated in vivo. Disclaimer: This study corresponds to the early stages of antiviral development and the results do not support by themselves the use of the selected drugs to treat SARS-CoV-2 infection.

Redefining fundamental concepts of transcription initiation in bacteria.

Despite enormous progress in understanding the fundamentals of bacterial gene regulation, our knowledge remains limited when compared with the number of bacterial genomes and regulatory systems to be discovered. Derived from a small number of initial studies, classic definitions for concepts of gene regulation have evolved as the number of characterized promoters has increased. Together with discoveries made using new technologies, this knowledge has led to revised generalizations and principles. In this Expert Recommendation, we suggest precise, updated definitions that support a logical, consistent conceptual framework of bacterial gene regulation, focusing on transcription initiation. The resulting concepts can be formalized by ontologies for computational modelling, laying the foundation for improved bioinformatics tools, knowledge-based resources and scientific communication. Thus, this work will help researchers construct better predictive models, with different formalisms, that will be useful in engineering, synthetic biology, microbiology and genetics.

RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding.

Gene regulatory regions contain short and degenerated DNA binding sites recognized by transcription factors (TFBS). When TFBS harbor SNPs, the DNA binding site may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in Genome-Wide Association Study (GWAS) studies. In this study, we describe improved versions of the programs Variation-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Variation-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted transcription factor affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Variation-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis.

The bio.tools registry of software tools and data resources for the life sciences.

Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue ( https://bio.tools ) of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information.

Sub-microscopic Plasmodium falciparum infections in matched peripheral, placental and umbilical cord blood samples from asymptomatic Congolese women at delivery.

In malaria-endemic areas, most pregnant women are susceptible to asymptomatic Plasmodium falciparum infections. We present here the results of a cross-sectional study conducted in Madibou, a southern district of Brazzaville in the Republic of Congo, between March 2014 and April 2015. The main aim was to characterize P. falciparum infections. Blood samples corresponding to peripheral, placental and cord from 370 asymptomatic malaria women at delivery were diagnosed for plasmodium infection by thick blood smears (microscopic infection). Sub-microscopic infection was detected by PCR, using the MSP-2 gene as marker. Microscopic infections were detected in peripheral, placental and cord blood samples with a prevalence of respectively 7.3% (27/370), 2.7% (10/370) and 0%. The negative samples were submitted to sub-microscopic detection, with respective prevalence of 25.4% (87/343), 16.7% (60/360) and 9.4% (35/370) (P < 0.001). We further investigated the genetic diversity of the parasite by characterizing MSP2 allelic families 3D7 (24 distinct alleles) and FC27 (20 distinct alleles). The total number of alleles for these two families were 31, 25 and 19 in peripheral, placental and cord samples respectively. The 3D7 MSP-2 was the predominant allelic family. The multiplicity of infections (MOI) in peripheral (mean 1.4 ± 0.01; range 1-4), placental (mean 1.2 ± 0.01; range 1-3) and cord samples (1.4 ± 0.01; range 1-3) were similar (P = 0.9) and are unaffected by age, gravidity or sulfadoxine-pyrimethamine. These results shown a high prevalence of sub-microscopic infection and a high genetic diversity of Plasmodium falciparum strains in Congo. Age, gravidity and doses of preventive treatment based on sulfadoxine-pyrimethamine do not interfere with the multiplicity of infections.

Integrating Bacterial ChIP-seq and RNA-seq Data With SnakeChunks.

Next-generation sequencing (NGS) is becoming a routine approach in most domains of the life sciences. To ensure reproducibility of results, there is a crucial need to improve the automation of NGS data processing and enable forthcoming studies relying on big datasets. Although user-friendly interfaces now exist, there remains a strong need for accessible solutions that allow experimental biologists to analyze and explore their results in an autonomous and flexible way. The protocols here describe a modular system that enable a user to compose and fine-tune workflows based on SnakeChunks, a library of rules for the Snakemake workflow engine. They are illustrated using a study combining ChIP-seq and RNA-seq to identify target genes of the global transcription factor FNR in Escherichia coli, which has the advantage that results can be compared with the most up-to-date collection of existing knowledge about transcriptional regulation in this model organism, extracted from the RegulonDB database. © 2019 by John Wiley & Sons, Inc.

RSAT 2018: regulatory sequence analysis tools 20th anniversary.

RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

Sequanix: a dynamic graphical interface for Snakemake workflows.

Summary: We designed a PyQt graphical user interface-Sequanix-aimed at democratizing the use of Snakemake pipelines in the NGS space and beyond. By default, Sequanix includes Sequana NGS pipelines (Snakemake format) (http://sequana.readthedocs.io), and is also capable of loading any external Snakemake pipeline. New users can easily, visually, edit configuration files of expert-validated pipelines and can interactively execute these production-ready workflows. Sequanix will be useful to both Snakemake developers in exposing their pipelines and to a wide audience of users. Availability and implementation: Source on http://github.com/sequana/sequana, bio-containers on http://bioconda.github.io and Singularity hub (http://singularity-hub.org). Contact: dimitri.desvillechabrol@pasteur.fr or thomas.cokelaer@pasteur.fr. Supplementary information: Supplementary data are available at Bioinformatics online.

Coordinated response of the Desulfovibrio desulfuricans 27774 transcriptome to nitrate, nitrite and nitric oxide.

The sulfate reducing bacterium Desulfovibrio desulfuricans inhabits both the human gut and external environments. It can reduce nitrate and nitrite as alternative electron acceptors to sulfate to support growth. Like other sulphate reducing bacteria, it can also protect itself against nitrosative stress caused by NO generated when nitrite accumulates. By combining in vitro experiments with bioinformatic and RNA-seq data, metabolic responses to nitrate or NO and how nitrate and nitrite reduction are coordinated with the response to nitrosative stress were revealed. Although nitrate and nitrite reduction are tightly regulated in response to substrate availability, the global responses to nitrate or NO were largely regulated independently. Multiple NADH dehydrogenases, transcription factors of unknown function and genes for iron uptake were differentially expressed in response to electron acceptor availability or nitrosative stress. Amongst many fascinating problems for future research, the data revealed a YtfE orthologue, Ddes_1165, that is implicated in the repair of nitrosative damage. The combined data suggest that three transcription factors coordinate this regulation in which NrfS-NrfR coordinates nitrate and nitrite reduction to minimize toxicity due to nitrite accumulation, HcpR1 serves a global role in regulating the response to nitrate, and HcpR2 regulates the response to nitrosative stress.

Transcriptional Profiling of Midguts Prepared from Trypanosoma/T. congolense-Positive Glossina palpalis palpalis Collected from Two Distinct Cameroonian Foci: Coordinated Signatures of the Midguts' Remodeling As T. congolense-Supportive Niches.

Our previous transcriptomic analysis of Glossina palpalis gambiensis experimentally infected or not with Trypanosoma brucei gambiense aimed to detect differentially expressed genes (DEGs) associated with infection. Specifically, we selected candidate genes governing tsetse fly vector competence that could be used in the context of an anti-vector strategy, to control human and/or animal trypanosomiasis. The present study aimed to verify whether gene expression in field tsetse flies (G. p. palpalis) is modified in response to natural infection by trypanosomes (T. congolense), as reported when insectary-raised flies (G. p. gambiensis) are experimentally infected with T. b. gambiense. This was achieved using the RNA-seq approach, which identified 524 DEGs in infected vs. non-infected tsetse flies, including 285 downregulated genes and 239 upregulated genes (identified using DESeq2). Several of these genes were highly differentially expressed, with log2 fold change values in the vicinity of either +40 or -40. Downregulated genes were primarily involved in transcription/translation processes, whereas encoded upregulated genes governed amino acid and nucleotide biosynthesis pathways. The BioCyc metabolic pathways associated with infection also revealed that downregulated genes were mainly involved in fly immunity processes. Importantly, our study demonstrates that data on the molecular cross-talk between the host and the parasite (as well as the always present fly microbiome) recorded from an experimental biological model has a counterpart in field flies, which in turn validates the use of experimental host/parasite couples.