VICTOR: genome-based phylogeny and classification of prokaryotic viruses

Motivation Bacterial and archaeal viruses are crucial for global biogeochemical cycles and might well be game-changing therapeutic agents in the fight against multi-resistant pathogens. Nevertheless, it is still unclear how to best use genome sequence data for a fast, universal and accurate taxonomic classification of such viruses. Results We here present a novel in silico framework for phylogeny and classification of prokaryotic viruses, in line with the principles of phylogenetic systematics, and using a large reference dataset of officially classified viruses. The resulting trees revealed a high agreement with the classification. Except for low resolution at the family level, the majority of taxa was well supported as monophyletic. Clusters obtained with distance thresholds chosen for maximizing taxonomic agreement appeared phylogenetically reasonable, too. Analysis of an expanded dataset, containing >4000 genomes from public databases, revealed a large number of novel species, genera, subfamilies and families. Availability and implementation The selected methods are available as the easy-to-use web service ‘VICTOR’ at https://victor.dsmz.de. Supplementary information Supplementary data are available at Bioinformatics onlin

TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy

Microbial taxonomy is increasingly influenced by genome-based computational methods. Yet such analyses can be complex and require expert knowledge. Here we introduce TYGS, the Type (Strain) Genome Server, a user-friendly high-throughput web server for genome-based prokaryote taxonomy, connected to a large, continuously growing database of genomic, taxonomic and nomenclatural information. It infers genome-scale phylogenies and state-of-the-art estimates for species and subspecies boundaries from user-defined and automatically determined closest type genome sequences. TYGS also provides comprehensive access to nomenclature, synonymy and associated taxonomic literature. Clinically important examples demonstrate how TYGS can yield new insights into microbial classification, such as evidence for a species-level separation of previously proposed subspecies of Salmonella enterica. TYGS is an integrated approach for the classification of microbes that unlocks novel scientific approaches to microbiologists worldwide and is particularly helpful for the rapidly expanding field of genome-based taxonomic descriptions of new genera, species or subspecies

Whole genome-based taxonomy of Shewanella and Parashewanella

The family Shewanellaceae currently comprises three genera, Shewanella, Parashewanella and Psychrobium, the latter represented by a single species. From the second half of the 1990s, the number of novel species in the Shewanellaceae has steadily increased, suggesting that the true diversity of this family has only begun to emerge. In recent years, efforts to provide a genus-wide, whole genome-based taxonomy for Shewanella have been limited by the lack of numerous type strain genome sequences. To shed light on this question, we sequenced all Shewanella type strains that lacked a publicly available wholegenome sequence. Using state-of-the-art phylogenomic methods, here we provide a genus-wide taxonomy of Shewanella and Parashewanella that resulted in the identification of 48 novel species represented by 73 sequenced isolates, and we propose the correction of 43 misidentified non-type-strain isolates. Our work sets a reference for family-wide comparative genomic studies addressing genetic or ecophysiological aspects of Shewanellaceae, as well as subsequent species descriptions

Sequence-based analysis of the genus Ruminococcus resolves its phylogeny and reveals strong host association

It has become increasingly clear that the composition of mammalian gut microbial communities is substantially diet driven. These microbiota form intricate mutualisms with their hosts, which have profound implications on overall health. For example, many gut microbes are involved in the conversion of host-ingested dietary polysaccharides into host-usable nutrients. One group of important gut microbial symbionts are bacteria in the genus Ruminococcus. Originally isolated from the bovine rumen, ruminococci have been found in numerous mammalian hosts, including other ruminants, and non-ruminants such as horses, pigs and humans. All ruminococci require fermentable carbohydrates for growth, and their substrate preferences appear to be based on the diet of their particular host. Most ruminococci that have been studied are those capable of degrading cellulose, much less is known about non-cellulolytic non-ruminant-associated species, and even less is known about the environmental distribution of ruminococci as a whole. Here, we capitalized on the wealth of publicly available 16S rRNA gene sequences, genomes and large-scale microbiota studies to both resolve the phylogenetic placement of described species in the genus Ruminococcus, and further demonstrate that this genus has largely unexplored diversity and a staggering host distribution. We present evidence that ruminococci are predominantly associated with herbivores and omnivores, and our data supports the hypothesis that very few ruminococci are found consistently in non-host-associated environments. This study not only helps to resolve the phylogeny of this important genus, but also provides a framework for understanding its distribution in natural systems

Phylogenomic study of Burkholderia glathei-like organisms, proposal of 13 novel Burkholderia species and emended descriptions of Burkholderia sordidicola, Burkholderia zhejiangensis, and Burkholderia grimmiae

Partial gyrB gene sequence analysis of 17 isolates from human and environmental sources revealed 13 clusters of strains and identified them as Burkholderia glathei Glade (BGC) bacteria. The taxonomic status of these clusters was examined by whole-genome sequence analysis, determination of the G+C content, whole-cell fatty acid analysis and biochemical characterization. The whole-genome sequence-based phylogeny was assessed using the Genome Blast Distance Phylogeny (GBDP) method and an extended multilocus sequence analysis (MLSA) approach. The results demonstrated that these 17 BGC isolates represented 13 novel Burkholderia species that could be distinguished by both genotypic and phenotypic characteristics. BGC strains exhibited a broad metabolic versatility and developed beneficial, symbiotic, and pathogenic interactions with different hosts. Our data also confirmed that there is no phylogenetic subdivision in the genus Burkholderia that distinguishes beneficial from pathogenic strains. We therefore propose to formally classify the 13 novel BGC Burkholderia species as Burkholderia arvi sp. nov. (type strain LMG 29317(T) = CCUG 68412(T)), Burkholderia hypogeia sp. nov. (type strain LMG 29322(T) = CCUG 68407(T)), Burkholderia ptereochthonis sp. nov. (type strain LMG 29326(T) = CCUG 68403(T)), Burkholderia glebae sp. nov. (type strain LMG 29325(T) = CCUG 68404(T)), Burkholderia pedi sp. nov. (type strain LMG 29323(T) = CCUG 68406(T)), Burkholderia arationis sp. nov. (type strain LMG 29324(T) = CCUG 68405(T)), Burkholderia fortuita sp. nov. (type strain LMG 29320(T) = CCUG 68409(T)), Burkholderia temeraria sp. nov. (type strain LMG 29319(T) = CCUG 68410(T)), Burkholderia calidae sp. nov. (type strain LMG 29321(T) = CCUG 68408(T)), Burkholderia concitans sp. nov. (type strain LMG 29315(T) = CCUG 68414(T)), Burkholderia turbans sp. nov. (type strain LMG 29316(T) = CCUG 68413(T)), Burkholderia catudaia sp. nov. (type strain LMG 29318(T) = CCUG 68411(T)) and Burkholderia peredens sp. nov. (type strain LMG 29314(T) = CCUG 68415(T)). Furthermore, we present emended descriptions of the species Burkholderia sordidicola, Burkholderia zhejlangensis and Burkholderia grimmiae. The GenBank/EMBUDDBJ accession numbers for the 16S rRNA and gyrB gene sequences determined in this study are LT158612-LT158624 and LT158625-LT1158641, respectively

Whole-genome sequencing redefines Shewanella taxonomy

The genus Shewanella encompasses a diverse group of Gram negative, primarily aquatic bacteria with a remarkable ecological relevance, an outstanding set of metabolic features and an emergent clinical importance. The rapid expansion of the genus over the 2000 s has prompted questions on the real taxonomic position of some isolates and species. Recent work by us and others identified inconsistencies in the existing species classification. In this study we aimed to clarify such issues across the entire genus, making use of the genomic information publicly available worldwide. Phylogenomic analyses, including comparisons based on genome-wide identity indexes (digital DNA-DNA hybridization and Average Nucleotide Identity) combined with core and accessory genome content evaluation suggested that the taxonomic position of 64 of the 131 analyzed strains should be revisited. Based on the genomic information currently available, emended descriptions for some Shewanella species are proposed. Our study establishes for the first time a whole-genome based phylogeny for Shewanella spp. including a classification at the subspecific level

Genome sequence-based species delimitation with confidence intervals and improved distance functions

Background For the last 25 years species delimitation in prokaryotes (Archaea and Bacteria) was to a large extent based on DNA-DNA hybridization (DDH), a tedious lab procedure designed in the early 1970s that served its purpose astonishingly well in the absence of deciphered genome sequences. With the rapid progress in genome sequencing time has come to directly use the now available and easy to generate genome sequences for delimitation of species. GBDP (Genome Blast Distance Phylogeny) infers genome-to-genome distances between pairs of entirely or partially sequenced genomes, a digital, highly reliable estimator for the relatedness of genomes. Its application as an in-silico replacement for DDH was recently introduced. The main challenge in the implementation of such an application is to produce digital DDH values that must mimic the wet-lab DDH values as close as possible to ensure consistency in the Prokaryotic species concept. Results Correlation and regression analyses were used to determine the best-performing methods and the most influential parameters. GBDP was further enriched with a set of new features such as confidence intervals for intergenomic distances obtained via resampling or via the statistical models for DDH prediction and an additional family of distance functions. As in previous analyses, GBDP obtained the highest agreement with wet-lab DDH among all tested methods, but improved models led to a further increase in the accuracy of DDH prediction. Confidence intervals yielded stable results when inferred from the statistical models, whereas those obtained via resampling showed marked differences between the underlying distance functions. Conclusions Despite the high accuracy of GBDP-based DDH prediction, inferences from limited empirical data are always associated with a certain degree of uncertainty. It is thus crucial to enrich in-silico DDH replacements with confidence-interval estimation, enabling the user to statistically evaluate the outcomes. Such methodological advancements, easily accessible through the web service at http://ggdc.dsmz.de, are crucial steps towards a consistent and truly genome sequence-based classification of microorganisms

TYGS and LPSN: a database tandem for fast and reliable genome-based classification and nomenclature of prokaryotes

Microbial systematics is heavily influenced by genome-based methods and challenged by an ever increasing number of taxon names and associated sequences in public data repositories. This poses a challenge for database systems, particularly since it is obviously advantageous if such data are based on a globally recognized approach to manage names, such as the International Code of Nomenclature of Prokaryotes. The amount of data can only be handled if accurate and reliable high-throughput platforms are available that are able to both comply with this demand and to keep track of all changes in an efficient and flexible way. The List of Prokaryotic names with Standing in Nomenclature (LPSN) is an expert-curated authoritative resource for prokaryotic nomenclature and is available at https://lpsn.dsmz.de. The Type (Strain) Genome Server (TYGS) is a high-throughput platform for accurate genome-based taxonomy and is available at https://tygs.dsmz.de. We here present important updates of these two previously introduced, heavily interconnected platforms for taxonomic nomenclature and classification, including new high-level facilities providing access to bioinformatic algorithms, a considerable expansion of the database content, and new ways to easily access the data

List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ

The List of Prokaryotic names with Standing in Nomenclature (LPSN) was acquired in November 2019 by the DSMZ and was relaunched using an entirely new production system in February 2020. This article describes in detail the structure of the new site, navigation, page layout, search facilities and new features