Prokaryotic taxonomy and nomenclature in the age of big sequence data

The classification of life forms into a hierarchical system (taxonomy) and the application of names to this hierarchy (nomenclature) is at a turning point in microbiology. The unprecedented availability of genome sequences means that a taxonomy can be built upon a comprehensive evolutionary framework, a longstanding goal of taxonomists. However, there is resistance to adopting a single framework to preserve taxonomic freedom, and ever increasing numbers of genomes derived from uncultured prokaryotes threaten to overwhelm current nomenclatural practices, which are based on characterised isolates. The challenge ahead then is to reach a consensus on the taxonomic framework and to adapt and scale the existing nomenclatural code, or create a new code, to systematically incorporate uncultured taxa into the chosen framework.

Bridging 200 years of bacterial classification.

This book chapter briefly takes a historical view of the major steps in bacterial systematics leading to the first reconciliation workshop in 1987 and a re-evaluation of the species concept in 2002. New challenges and concepts developed since then will be outlined. Never before has the future of the prokaryotic taxonomy been at such a critical point. The uncertain future, and whether Plan A or Plan B will prevail, depends totally on the wisdom of the ICSP. Perhaps by the time this book is published the situation will have been clarified, but the current situation is as full of uncertainty as of excitement, and none of the scenarios can be predicted. In April 2020, a majority of the ICSP members decided to reject the proposals to use DNA as type material. Therefore, this rejection leaves the only path for microbial ecologists to go through Plan B. Only time will reveal whether this was the best decision for the future of the taxonomy for prokaryotes.

Summary of Novel Bacterial Isolates Derived from Human Clinical Specimens and Nomenclature Revisions Published in 2018 and 2019

Knowledge of novel prokaryotic taxa discovery and nomenclature revisions is of importance to clinical microbiology laboratory practice, infectious disease epidemiology, and studies of microbial pathogenesis. Relative to bacterial isolates derived from human clinical specimens, we present an in-depth summary of novel taxonomic designations and revisions to prokaryotic taxonomy that were published in 2018 and 2019. Included are several changes pertinent to former designations of or within Propionibacterium spp., Corynebacterium spp., Clostridium spp., Mycoplasma spp., Methylobacterium spp., and Enterobacteriaceae. Future efforts to ascertain clinical relevance for many of these changes may be augmented by a Document Development Committee that has been appointed by the Clinical and Laboratory Standards Institute.

All ANIs are not created equal: implications for prokaryotic species boundaries and integration of ANIs into polyphasic taxonomy

In prokaryotic taxonomy, a set of criteria is commonly used to delineate species. These criteria are generally based on cohesion at the phylogenetic, phenotypic and genomic levels. One such criterion shown to have promise in the genomic era is average nucleotide identity (ANI), which provides an average measure of similarity across homologous regions shared by a pair of genomes. However, despite the popularity and relative ease of using this metric, ANI has undergone numerous refinements, with variations in genome fragmentation, homologue detection parameters and search algorithms. To test the robustness of a 95–96 % species cut-off range across all the commonly used ANI approaches, seven different methods were used to calculate ANI values for intra- and interspecies datasets representing three classes in the Proteobacteria . As a reference point, these methods were all compared to the widely used blast-based ANI (i.e. ANIb as implemented in JSpecies), and regression analyses were performed to investigate the correlation of these methods to ANIb with more than 130000 individual data points. From these analyses, it was clear that ANI methods did not provide consistent results regarding the conspecificity of isolates. Most of the methods investigated did not correlate perfectly with ANIb, particularly between 90 and 100% identity, which includes the proposed species boundary. There was also a difference in the correlation of methods for the different taxon sets. Our study thus suggests that the specific approach employed needs to be considered when ANI is used to delineate prokaryotic species. We furthermore suggest that one would first need to determine an appropriate cut-off value for a specific taxon set, based on the intraspecific diversity of that group, before conclusions on conspecificity of isolates can be made, and that the resulting species hypotheses be confirmed with analyses based on evolutionary history as part of the polyphasic approach to taxonomy.

LINbase: a web server for genome-based identification of prokaryotes as members of crowdsourced taxa

High throughput DNA sequencing in combination with efficient algorithms could provide the basis for a highly resolved, genome phylogeny-based and digital prokaryotic taxonomy. However, current taxonomic practice continues to rely on cumbersome journal publications for the description of new species, which still constitute the smallest taxonomic units. In response, we introduce LINbase, a web server that allows users to genomically circumscribe any group of prokaryotes with measurable DNA similarity and that uses the individual isolate as smallest unit. Since LINbase leverages the concept of Life Identification Numbers (LINs), which are codes assigned to individual genomes based on reciprocal average nucleotide identity, we refer to groups circumscribed in LINbase as LINgroups. Users can associate with each LINgroup a name, a short description, and a URL to a peer-reviewed publication. As soon as a LINgroup is circumscribed, any user can immediately identify query genomes as members and submit comments about the LINgroup. Most genomes currently in LINbase were imported from GenBank, but users can upload their own genome sequences as well. In conclusion, LINbase combines the resolution of LINs with the power of crowdsourcing in support of a highly resolved, genome phylogeny-based digital taxonomy. LINbase is available at http://www.LINbase.org.