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Background Comparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical display. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some cases, programming skills. Results Here, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide the largest panel of interactive visualizations among the applications that are currently available. SHAMAN is specifically designed for non-expert users. A strong benefit is to use an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at http://shaman.pasteur.fr/, and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman. Using two different datasets (a mock community sequencing and a published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis. Conclusions With SHAMAN, we aim at providing the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.

Funding Information: E.M.A. gratefully acknowledges funding by the U.K. Biotechnology and Biological Sciences Research Council (BBSRC); this research was funded by the BBSRC Institute Strategic Programme Gut Microbes and Health BB/R012490/1 and its constituent projects BBS/E/F/000PR10353 and BBS/E/F/000PR10356. A.J.D. is supported by the U.K. Medical Research Council (MC_UU_12014/3). B.E.D. is supported by Netherlands Organization for Scientific Research (NWO) Vidi grant 864.14.004. B.H. is supported by the National Research, Development and Innovation Office—NKFIH (NN128309). N.J.K. is partially supported by core funding provided by the Biotechnology and Biological Sciences Research Council, UK. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an Equal Opportunity Provider and Employer. This work was supported in part through Laulima Government Solutions, LLC prime contract with the US National Institute of Allergy and Infectious Diseases (NIAID) under Contract No. HHSN272201800013C. J.H.K. performed this work as an employee of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC under Contract No. HHSN272201800013C. A.R.M. is a Program Director at the U.S. National Science Foundation (NSF); the statements and opinions expressed herein are made in a personal capacity and do not constitute endorsement by NSF or the government of the United States. H.M.O was supported by the University of Helsinki and Academy of Finland by funding for FINStruct and Instruct Centre FI, part of Biocenter Finland and Instruct-ERIC. D.L.R. is supported by the U.K. Medical Research Council (MC_UU_1201412). R.J.O. and D.B.S. are supported by the Wellcome Trust (WT108418AIA). S.S. acknowledges partial support from the Special Research Initiative (MAFES), Mississippi State University, and from the National Institute of Food and Agriculture, US Department of Agriculture, Hatch Project 1021494. Except for Donald M. Dempsey, R. Curtis Hendrickson, Richard J. Orton and Donald B. Smith, the authors were members of the ICTV Executive Committee during the relevant period. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the US Department of Health and Human Services, or of the institutions and companies affiliated with the authors. Publisher Copyright: © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply. This article reports the changes to virus taxonomy approved and ratified by the International Committee on Taxonomy of Viruses (ICTV) in March 2021. The entire ICTV was invited to vote on 290 taxonomic proposals approved by the ICTV Executive Committee at its meeting in October 2020, as well as on the proposed revision of the International Code of Virus Classification and Nomenclature (ICVCN). All proposals and the revision were ratified by an absolute majority of the ICTV members. Of note, ICTV mandated a uniform rule for virus species naming, which will follow the binomial 'genus-species' format with or without Latinized species epithets. The Study Groups are requested to convert all previously established species names to the new format. ICTV has also abolished the notion of a type species, i.e., a species chosen to serve as a name-bearing type of a virus genus. The remit of ICTV has been clarified through an official definition of ‘virus’ and several other types of mobile genetic elements. The ICVCN and ICTV Statutes have been amended to reflect these changes. publishersversion inpress

International audience; This article reports the changes to virus classification and taxonomy approved and ratified by the International Committee on Taxonomy of Viruses (ICTV) in March 2020. The entire ICTV was invited to vote on 206 taxonomic proposals approved by the ICTV Executive Committee at its meeting in July 2019, as well as on the proposed revision of the ICTV Statutes. All proposals and the revision of the Statutes were approved by an absolute majority of the ICTV voting membership. Of note, ICTV has approved a proposal that extends the previously established realm Riboviria to encompass nearly all RNA viruses and reverse-transcribing viruses, and approved three separate proposals to establish three realms for viruses with DNA genomes.

Microbiomes from every environment contain a myriad of uncultivated archaeal and bacterial viruses, but studying these viruses is hampered by the lack of a universal, scalable taxonomic framework. We present vConTACT v.2.0, a network-based application utilizing whole genome gene-sharing profiles for virus taxonomy that integrates distance-based hierarchical clustering and confidence scores for all taxonomic predictions. We report near-identical (96%) replication of existing genus-level viral taxonomy assignments from the International Committee on Taxonomy of Viruses for National Center for Biotechnology Information virus RefSeq. Application of vConTACT v.2.0 to 1,364 previously unclassified viruses deposited in virus RefSeq as reference genomes produced automatic, high-confidence genus assignments for 820 of the 1,364. We applied vConTACT v.2.0 to analyze 15,280 Global Ocean Virome genome fragments and were able to provide taxonomic assignments for 31% of these data, which shows that our algorithm is scalable to very large metagenomic datasets. Our taxonomy tool can be automated and applied to metagenomes from any environment for virus classification. ispartof: NATURE BIOTECHNOLOGY vol:37 issue:6 pages:632-+ ispartof: location:United States status: published

International audience; This special issue of Systematic Biology contains review articles contributed by keynote speakers at the “Mathematical and Computational EvolutionaryBiology” conference (MCEB; see web sites below), held in 2015. This is the seventh conference in this series, the first being held in Paris in 2003 with keynote addresses from such notables as Joe Felsenstein, Ziheng Yang, and Walter Fitch. Oxford University Press published two books based on the 2003 and 2005 Paris meetings (Gascuel 2005; Gascuel and Steel 2007).

International audience; This article lists the changes to virus taxonomy approved and ratified by the International Committee on Taxonomy of Viruses (ICTV) in April 2016.Changes to virus taxonomy (the Universal Scheme of Virus Classification of the International Committee on Taxonomy of Viruses [ICTV]) now take place annually and are the result of a multi-stage process. In accordance with the ICTV Statutes ( http://www.ictvonline.org/statutes.asp ), proposals submitted to the ICTV Executive Committee (EC) undergo a review process that involves input from the ICTV Study Groups (SGs) and Subcommittees (SCs), other interested virologists, and the EC. After final approval by the EC, proposals are then presented for ratification to the full ICTV membership by publication on an ICTV web site ( http://www.ictvonline.org/ ) followed by an electronic vote. The latest set of proposals approved by the EC was made available on the ICTV website by January 2016 ( https://talk.ictvonline.org/files/proposals/ ). A list of these proposals was then emailed on 28 March 2016 to the 148 members of ICTV, namely the EC Members, Life Members, ICTV Subcommittee Members (including the SG chairs) and ICTV National Representatives. Members were then requested to vote on whether to ratify the taxonomic proposals (voting closed on 29 April 2016).

International audience; Satellite viruses encode structural proteins required for the formation of infectious particles but depend on helper viruses for completing their replication cycles. Because of this unique property, satellite viruses that infect plants, arthropods, or mammals, as well as the more recently discovered satellite-like viruses that infect protists (virophages), have been grouped with other, so-called "sub-viral agents." For the most part, satellite viruses are therefore not classified. We argue that possession of a coat-protein-encoding gene and the ability to form virions are the defining features of a bona fide virus. Accordingly, all satellite viruses and virophages should be consistently classified within appropriate taxa. We propose to create four new genera - Albetovirus, Aumaivirus, Papanivirus, and Virtovirus - for positive-sense single-stranded (+) RNA satellite viruses that infect plants and the family Sarthroviridae, including the genus Macronovirus, for (+)RNA satellite viruses that infect arthopods. For double-stranded DNA virophages, we propose to establish the family Lavidaviridae, including two genera, Sputnikvirus and Mavirus.

International audience; Fossil-based estimates of diversity and evolutionary dynamics mainly rely on the study of morphological variation. Unfortunately, organism remains are often altered by post-mortem taphonomic processes such as weathering or distortion. Such a loss of information often prevents quantitative multivariate description and statistically-controlled comparisons of extinct species based on morphometric data. A common way to deal with missing data involves imputation methods that directly fill the missing cases with model estimates. Over the last years, several empirically-determined thresholds for the maximum acceptable proportion of missing values have been proposed in the literature, whereas other studies showed that this limit actually depends on various properties of the study data set and of the selected imputation method, and is by no way generalizable. We evaluate the relative performances of seven multiple imputation (MI) techniques through a simulation-based analysis under three distinct patterns of missing data distribution. Overall, Fully Conditional Specification and Expectation-Maximization algorithms provide the best compromises between imputation accuracy and coverage probability. MI techniques appear remarkably robust to the violation of basic assumptions such as the occurrence of taxonomically or anatomically biased patterns of missing data distribution, making differences in simulation results between the three patterns of missing data distribution much smaller than differences between the individual MI techniques. Based on these results, rather than proposing a new (set of) threshold value(s), we develop an approach combining the use of MIs with procrustean superimposition of principal component analysis results, in order to directly visualize the effect of individual missing data imputation on an ordinated space. We provide an R function for users to implement the proposed procedure.

The task of international expert groups is to recommend the classification and naming of viruses. The International Committee on Taxonomy of Viruses Filoviridae Study Group and other experts have recently established an almost consistent classification and nomenclature for filoviruses. Here, further guidelines are suggested to include their natural genetic variants. First, this term is defined. Second, a template for full-length virus names (such as “Ebola virus H.sapiens-tc/COD/1995/Kikwit-9510621”) is proposed. These names contain information on the identity of the virus (e.g., Ebola virus), isolation host (e.g., members of the species Homo sapiens), sampling location (e.g., Democratic Republic of the Congo (COD)), sampling year, genetic variant (e.g., Kikwit), and isolate (e.g., 9510621). Suffixes are proposed for individual names that clarify whether a given genetic variant has been characterized based on passage zero material (-wt), has been passaged in tissue/cell culture (-tc), is known from consensus sequence fragments only (-frag), or does (most likely) not exist anymore (-hist). We suggest that these comprehensive names are to be used specifically in the methods section of publications. Suitable abbreviations, also proposed here, could then be used throughout the text, while the full names could be used again in phylograms, tables, or figures if the contained information aids the interpretation of presented data. The proposed system is very similar to the well-known influenzavirus nomenclature and the nomenclature recently proposed for rotaviruses. If applied consistently, it would considerably simplify retrieval of sequence data from electronic databases and be a first important step toward a viral genome annotation standard as sought by the National Center for Biotechnology Information (NCBI). Furthermore, adoption of this nomenclature would increase the general understanding of filovirus-related publications and presentations and improve figures such as phylograms, alignments, and diagrams. Most importantly, it would counter the increasing confusion in genetic variant naming due to the identification of ever more sequences through technological breakthroughs in high-throughput sequencing and environmental sampling.

Background Recent advances in sequencing strategies make possible unprecedented depth and scale of sampling for molecular detection of microbial diversity. Two major paradigm-shifting discoveries include the detection of bacterial diversity that is one to two orders of magnitude greater than previous estimates, and the discovery of an exciting 'rare biosphere' of molecular signatures ('species') of poorly understood ecological significance. We applied a high-throughput parallel tag sequencing (454 sequencing) protocol adopted for eukaryotes to investigate protistan community complexity in two contrasting anoxic marine ecosystems (Framvaren Fjord, Norway; Cariaco deep-sea basin, Venezuela). Both sampling sites have previously been scrutinized for protistan diversity by traditional clone library construction and Sanger sequencing. By comparing these clone library data with 454 amplicon library data, we assess the efficiency of high-throughput tag sequencing strategies. We here present a novel, highly conservative bioinformatic analysis pipeline for the processing of large tag sequence data sets. Results The analyses of ca. 250,000 sequence reads revealed that the number of detected Operational Taxonomic Units (OTUs) far exceeded previous richness estimates from the same sites based on clone libraries and Sanger sequencing. More than 90% of this diversity was represented by OTUs with less than 10 sequence tags. We detected a substantial number of taxonomic groups like Apusozoa, Chrysomerophytes, Centroheliozoa, Eustigmatophytes, hyphochytriomycetes, Ichthyosporea, Oikomonads, Phaeothamniophytes, and rhodophytes which remained undetected by previous clone library-based diversity surveys of the sampling sites. The most important innovations in our newly developed bioinformatics pipeline employ (i) BLASTN with query parameters adjusted for highly variable domains and a complete database of public ribosomal RNA (rRNA) gene sequences for taxonomic assignments of tags; (ii) a clustering of tags at k differences (Levenshtein distance) with a newly developed algorithm enabling very fast OTU clustering for large tag sequence data sets; and (iii) a novel parsing procedure to combine the data from individual analyses. Conclusion Our data highlight the magnitude of the under-sampled 'protistan gap' in the eukaryotic tree of life. This study illustrates that our current understanding of the ecological complexity of protist communities, and of the global species richness and genome diversity of protists, is severely limited. Even though 454 pyrosequencing is not a panacea, it allows for more comprehensive insights into the diversity of protistan communities, and combined with appropriate statistical tools, enables improved ecological interpretations of the data and projections of global diversity.

International audience; Recently, several theoretical and applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological studies. However, these systems have not yet fully reached the biological community mainly because there are few freely available dedicated computer programs, and Bayesian clustering algorithms are known to be time consuming, which limits their usefulness when using personal computers. To overcome these limitations, we developed AutoClass@IJM, a computational resource with a web interface to AutoClass, a powerful unsupervised Bayesian classification system developed by the Ames Research Center at N.A.S.A. AutoClass has many powerful features with broad applications in biological sciences: (i) it determines the number of classes automatically, (ii) it allows the user to mix discrete and real valued data, (iii) it handles missing values. End users upload their data sets through our web interface; computations are then queued in our cluster server. When the clustering is completed, an URL to the results is sent back to the user by e-mail. AutoClass@IJM is freely available at: http://ytat2.ijm.univ-paris-diderot.fr/AutoclassAtIJM.html.

International audience; Wolbachia are endosymbiotic bacteria that may alter the reproductive mechanisms of arthropod hosts. Eusocial termites provide considerable scope for Wolbachia studies owing to their ancient origin, their great diversity and their considerable ecological, biological and behavioral plasticity. This article describes the phylogenetic distribution of Wolbachia infecting termites of the Cubitermes genus, which are particularly abundant soil-feeders in equatorial Africa. Fourteen colonies of the Cubitermes sp. affinis subarquatus complex of species were screened using five bacterial genes (wsp, ftsZ, coxA, fbpA and 16S rRNA genes) and a striking diversity of Wolbachia strains was identified within these closely related species. In the host complex, three Wolbachia variants were found that were not in the super groups usually reported for termites (F and H), each infecting one or two Cubitermes species.

International audience; The taxonomic and phylogenetic status of Echinococcus granulosus strains are still controversial and under discussion. In the present study, we investigated the genetic polymorphism of E. granulosus isolates originating from three countries of Africa, including a region of Algeria, where the common G1 sheep and the camel G6 strains coexist sympatrically. Seventy-one hydatid cysts were collected from sheep, cattle, camels, and humans. Two mitochondrial markers (cox1 and nad1) were used for strain identification. Two nuclear markers (actII and hbx2) were used to study the possible occurrence of cross-fertilization. Despite the heterogeneity observed among the G1 isolates, they were all localized within one robust cluster. A second strong cluster was also observed containing all of the G6 isolates. Both strains appeared as two distinct groups, and no cases of interbreeding were found. Thus, the attribution of a species rank can be suggested. We also found the Tasmanian sheep G2 strain for the first time in Africa. Because of the slight variations observed between the common sheep and the Tasmanian sheep strains, further studies should be carried out to elucidate the epidemiological relevance of this genetic discrimination.

International audience; Four male Long-Evans rats were trained to discriminate between synthetic vowel sounds using a GO/NOGO response choice task. The vowels were characterized by an increase in fundamental frequency correlated with an upward shift in formant frequencies. In an initial phase we trained the subjects to discriminate between two vowel categories using two exemplars from each category. In a subsequent phase the ability of the rats to generalize the discrimination between the two categories was tested. To test whether rats might exploit the fact that attributes of training stimuli covaried, we used non-standard stimuli with a reversed relation between fundamental frequency and formants. The overall results demonstrate that rats are able to generalize the discrimination to new instances of the same vowels. We present evidence that the performance of the subjects depended on the relation between fundamental and formant frequencies that they had previously been exposed to. Simple simulation results with artificial neural networks could reproduce most of the behavioral results and support the hypothesis that equivalence classes for vowels are associated with an experience-driven process based on general properties of peripheral auditory coding mixed with elementary learning mechanisms. These results suggest that rats use spectral and temporal cues similarly to humans despite differences in basic auditory capabilities.