Standing In Nomenclature Research Articles

Four new Microbacterium species isolated from seaweeds and reclassification of five Microbacterium species with a proposal of Paramicrobacterium gen. nov. under a genome-based framework of the genus Microbacterium.

The taxonomic relationships of 10 strains isolated from seaweeds collected from two beaches in Republic of Korea were studied by sequencing and analyses of 16S rRNA genes and whole genomes. For the construction of a more reliable and robust 16S rRNA gene phylogeny, the authentic and nearly complete 16S rRNA gene sequences of all the Microbacterium type strains were selected through pairwise comparison of the sequences contained in several public databases including the List of Prokaryotic names with Standing in Nomenclature (LPSN). The clustering of the ten study strains into five distinct groups was apparent in this single gene-based phylogenetic tree. In addition, the 16S rRNA gene sequences of a few type strains were shown to be incorrectly listed in LPSN. An overall phylogenomic clustering of the genus Microbacterium was performed with a total of 113 genomes by core genome analysis. As a result, nine major (≥ three type strains) and eight minor (two type strains) clusters were defined mostly at gene support index of 92 and mean intra-cluster OrthoANIu of >80.00%. All of the study strains were assigned to a Microbacterium liquefaciens clade and distributed further into four subclusters in the core genome-based phylogenetic tree. In vitro phenotypic assays for physiological, biochemical, and chemotaxonomic characteristics were also carried out with the ten study strains and seven closely related type strains. Comparison of the overall genomic relatedness indices (OGRI) including OrthoANIu and digital DNA-DNA hybridization supported that the study strains constituted four new species of the genus Microbacterium. In addition, some Microbacterium type strains were reclassified as members of preexisting species. Moreover, some of them were embedded in a new genus of the family Microbacteriaceae based on their distinct separation in the core genome-based phylogenetic tree and amino acid identity matrices. Based on the results here, four new species, namely, Microbacterium aurugineum sp. nov., Microbacterium croceum sp. nov., Microbacterium galbinum sp. nov., and Microbacterium sufflavum sp. nov., are described, along with the proposal of Paramicrobacterium gen. nov. containing five reclassified Microbacterium species from the "Microbacterium agarici clade", with Paramicrobacterium agarici gen. nov., comb. nov. as the type species.

A long-awaited taxogenomic investigation of the family Halomonadaceae.

The family Halomonadaceae is the largest family composed of halophilic bacteria, with more than 160 species with validly published names as of July 2023. Several classifications to circumscribe this family are available in major resources, such as those provided by the List of Prokaryotic names with Standing in Nomenclature (LPSN), NCBI Taxonomy, Genome Taxonomy Database (GTDB), and Bergey's Manual of Systematics of Archaea and Bacteria (BMSAB), with some degree of disagreement between them. Moreover, regardless of the classification adopted, the genus Halomonas is not phylogenetically consistent, likely because it has been used as a catch-all for newly described species within the family Halomonadaceae that could not be clearly accommodated in other Halomonadaceae genera. In the past decade, some taxonomic rearrangements have been conducted on the Halomonadaceae based on ribosomal and alternative single-copy housekeeping gene sequence analysis. High-throughput technologies have enabled access to the genome sequences of many type strains belonging to the family Halomonadaceae; however, genome-based studies specifically addressing its taxonomic status have not been performed to date. In this study, we accomplished the genome sequencing of 17 missing type strains of Halomonadaceae species that, together with other publicly available genome sequences, allowed us to re-evaluate the genetic relationship, phylogeny, and taxonomy of the species and genera within this family. The approach followed included the estimate of the Overall Genome Relatedness Indexes (OGRIs) such as the average amino acid identity (AAI), phylogenomic reconstructions using amino acid substitution matrices customized for the family Halomonadaceae, and the analysis of clade-specific signature genes. Based on our results, we conclude that the genus Halovibrio is obviously out of place within the family Halomonadaceae, and, on the other hand, we propose a division of the genus Halomonas into seven separate genera and the transfer of seven species from Halomonas to the genus Modicisalibacter, together with the emendation of the latter. Additionally, data from this study demonstrate the existence of various synonym species names in this family.

The gender gap in names of prokaryotes honouring persons.

The aim of this study is to analyse prokaryotic names which honour persons, eponyms, from a gender perspective. Data were retrieved from the List of Prokaryotic names with Standing in Nomenclature. Excluding new combinations, the etymologies of 23 315 unique names at the rank of genus, species and subspecies were analysed. A total of 2018 (8.7 %) names honour persons (eponyms), for which the development of the female share over time was further investigated. Women started to be honoured very recently (1947) compared to men (1823). Moreover, only 14.8 % of all prokaryotic eponyms refer to females. This ratio has hardly improved since 1947, although the number of women whose contributions to microbiology could have been recognized has increased over time. In contrast, about 50 % of prokaryotic names derived from mythological characters refer to females. To reduce this gender gap, we encourage authors proposing new taxon names to honour female scientists who can serve as role models for new generations.

Genome Taxonomy Database and SeqCode: Microbial Taxonomy and Nomenclature in the Age of Big Sequence Data

Genome Taxonomy Database and SeqCode: Microbial Taxonomy and Nomenclature in the Age of Big Sequence Data

Genome-based classification of the class Halobacteria and description of Haladaptataceae fam. nov. and Halorubellaceae fam. nov.

Currently, there are four mainstream taxonomic opinions on the classification of the class Halobacteria at the family and order levels. The International Committee on Systematics of Prokaryotes Subcommittee on the Taxonomy of Halobacteria (ICSP), List of Prokaryotic names with Standing in Nomenclature (LPSN) and National Centre for Biotechnology Information (NCBI) adopted taxonomies have three to four orders and up to eight families, while the Genome Taxonomy Database (GTDB) taxonomy proposes only one order with nine families. To resolve the taxonomic inconsistency, phylogenomic analyses based on concatenated single-copy orthologous proteins and 122 concatenated conserved single-copy marker proteins were conducted to infer the taxonomic status of the current representatives of the class Halobacteria at the family and order levels. The current 76 genera with validly published names of the class Halobacteria were able to be assigned into eight families in one order. On the basis of these results, it is proposed that the current species with validly published names of the class Halobacteria should be remerged into the order Halobacteriales, then assigned to eight families, Haladaptataceae, Haloarculaceae, Halobacteriaceae, Halococcaceae, Haloferacaceae, Natronoarchaeaceae, Natrialbaceae and Halorubellaceae. Thus, Haladaptataceae fam. nov. is described based on Haladaptatus, Halomicrococcus and Halorussus and Halorubellaceae fam. nov. is proposed incorporating Haloarchaeobius and Halorubellus, respectively.

Automating microbial taxonomy workflows with PHANTASM: phylogenomic analyses for the taxonomy and systematics of microbes.

The nucleotide sequences of 16S ribosomal RNA (rRNA) genes have been used to inform the taxonomic placement of prokaryotes for several decades. Whole-genome approaches can better resolve evolutionary relationships of organisms, but these analyses often require computational proficiencies that are uncommon among microbiologists. PHANTASM is a new tool capable of automating these workflows. This tool was designed to work for a wide range of prokaryotes and is the first example of an automated reconciliation of NCBI's Taxonomy database with that of the List of Prokaryotic names with Standing in Nomenclature (LPSN). In this study, we describe the workflow of PHANTASM and provide several examples of results generated by it. The source code is freely-available on GitHub. In order to facilitate the ease-of-access for researchers, PHANTASM is also available as a Docker image. While other tools exist to facilitate starting points for these analyses, PHANTASM provides users with a greater degree of control and produces outputs that can be used to make publication-quality figures.

Helping map the taxonomical position of the Nontuberculous Mycobacteria (NTM) in cystic fibrosis.

Nontuberculous mycobacteria (NTMs) have now emerged as important opportunistic bacterial pathogens, particularly among patients with cystic fibrosis (CF). The development of improved molecular technologies and bioinformatics and the adoption of whole-genome sequencing to more isolates have allowed for a reanalysis of the existing taxa within the genus Mycobacterium, resulting in the renaming of some existing NTM Mycobacterium species to three novel genera, viz., Mycolicibacterium gen. nov., Mycolicibacter gen. nov. and Mycobacteroides gen. nov. This has resulted in controversy, particularly within the clinical community, accompanied by a reluctance to adopt and employ these new bacterial names. Therefore, the aims of this study were (i) to identify NTM organisms associated with CF lung disease that have been reported previously in the published literature, (ii) to examine the realignment of NTM organisms previously described in CF within the revised new mycobacterial taxonomy and renaming, and (iii) to identify and explore online taxonomical tools to help educate clinical medicine about recent changes in NTM taxonomy. Three tasks were performed, namely (i) to identify NTM organisms previously associated with people with CF, (ii) to examine the extent and scope of the reclassification of CF-related NTM species affected by changes in recent taxonomy and nomenclature, and (iii) to identify and examine the educational utility of online taxonomical educational tools/software (LifeMap [http://lifemap.univ-lyon1.fr/]; National Center for Biotechnology Information [NCBI] Taxonomy browser [https://www.ncbi.nlm.nih. gov/guide/taxonomy/]; and List of Prokaryotic names with Standing in Nomenclature [LPSN] [https://lpsn.dsmz.de/]). Mycobacterium (Mycobacteroides) abscessus was selected as the species to evaluate the application of these tools. Twenty-one NTM species have been reported that have been associated with CF lung disease. Of these, two have been reclassified into the Mycobacteroides genus, two into the Mycolicibacter genus, and seven into the Mycolicibacterium genus. LifeMap, NCBI Taxonomy browser, and LPSN offered interactive visual support to better understand the taxonomy and nomenclature of NTM organisms. We, therefore, advocate that clinical and scientific parties employ these online tools to gain a better insight into the familiarization and understanding of such evolving NTM classification, thereby aiding a better lexicon and communication among all stakeholders.

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.

Pseudomonas Species in Soil as a Natural Resource for Plant Growth Promotion and Biocontrol Characteristics - An Overview

Plant growth-promoting Pseudomonads regulate plant growth by several direct and indirect mechanisms; direct mechanisms include producing phytohormones, increasing nutrient availability and indirect mechanisms include suppressing soil-borne plant pathogens by the production of siderophores, antibiotics, inducing systemic resistance and competing with pathogens. Pseudomonas spp. in soil has been reported from diverse ecological niches and has been well-documented as a model organism for regulating plant growth promotion. These bacteria are endowed with tremendous genetic and metabolic diversity and serve multiple ecological functions in the soil ecosystem. This versatile genus is one of the most commercially exploited bacteria in agriculture. The potential of the different species of Pseudomonas has not been realized sufficiently and requires emphasis on sustainable agriculture for the benefit of humankind. Research in the past decade has revealed that several species of Pseudomonas other than the common species such as P. fluorescens, P. putida, P. aeruginosa, have both plant growth promotion and biocontrol characteristics and have not been commercially exploited. According to the recent List of Prokaryotic names with Standing in Nomenclature (LPSN) there are 507 species of Pseudomonas and the present literature review brings out that 7.29% of them posses plant growth promotion (PGP) and biocontrol traits and thus can be utilized as biofertilizers in the field of agriculture. The role of different Pseudomonas spp. in the supply of plant nutrients and biocontrol of soilborne plant pathogens are covered in this review.

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.

The number of domains in the ribosomal protein S1 as a hallmark of the phylogenetic grouping of bacteria.

The family of ribosomal proteins S1 contains about 20% of all bacterial proteins including the S1 domain. An important feature of this family is multiple copies of structural domains in bacteria, the number of which changes in a strictly limited range from one to six. In this study, the automated exhaustive analysis of 1453 sequences of S1 allowed us to demonstrate that the number of domains in S1 is a distinctive characteristic for phylogenetic bacterial grouping in main phyla. 1453 sequences of S1 were identified in 25 out of 30 different phyla according to the List of Prokaryotic Names with Standing in Nomenclature. About 62% of all records are identified as six-domain S1 proteins, which belong to phylum Proteobacteria. Four-domain S1 are identified mainly in proteins from phylum Firmicutes and Actinobacteria. Records belonging to these phyla are 33% of all records. The least represented two-domain S1 are about 0.6% of all records. The third and fourth domains for the most representative four- and six-domain S1 have the highest percentage of identity with the S1 domain from polynucleotide phosphorylase and S1 domains from one-domain S1. In addition, for these groups, the central part of S1 (the third domain) is more conserved than the terminal domains.

LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on.

The List of Prokaryotic Names with Standing in Nomenclature (LPSN) was established in 1997 as the List of Bacterial Names with Standing in Nomenclature (LBSN); it quickly became a key online resource for anyone interested in bacterial and archaeal nomenclature and classification. This review looks at numbers of prokaryotic names published since the Approved Lists of Bacterial Names, current usage of LPSN and future developments.

The 2014Nucleic Acids ResearchDatabase Issue and an updated NAR online Molecular Biology Database Collection

The 2014 Nucleic Acids Research Database Issue includes descriptions of 58 new molecular biology databases and recent updates to 123 databases previously featured in NAR or other journals. For convenience, the issue is now divided into eight sections that reflect major subject categories. Among the highlights of this issue are six databases of the transcription factor binding sites in various organisms and updates on such popular databases as CAZy, Database of Genomic Variants (DGV), dbGaP, DrugBank, KEGG, miRBase, Pfam, Reactome, SEED, TCDB and UniProt. There is a strong block of structural databases, which includes, among others, the new RNA Bricks database, updates on PDBe, PDBsum, ArchDB, Gene3D, ModBase, Nucleic Acid Database and the recently revived iPfam database. An update on the NCBI’s MMDB describes VAST+, an improved tool for protein structure comparison. Two articles highlight the development of the Structural Classification of Proteins (SCOP) database: one describes SCOPe, which automates assignment of new structures to the existing SCOP hierarchy; the other one describes the first version of SCOP2, with its more flexible approach to classifying protein structures. This issue also includes a collection of articles on bacterial taxonomy and metagenomics, which includes updates on the List of Prokaryotic Names with Standing in Nomenclature (LPSN), Ribosomal Database Project (RDP), the Silva/LTP project and several new metagenomics resources. The NAR online Molecular Biology Database Collection, http://www.oxfordjournals.org/nar/database/c/, has been expanded to 1552 databases. The entire Database Issue is freely available online on the Nucleic Acids Research website (http://nar.oxfordjournals.org/).

LPSN—list of prokaryotic names with standing in nomenclature

The List of Prokaryotic Names with Standing in Nomenclature (LPSN; http://www.bacterio.net) is a database that lists the names of prokaryotes (Bacteria and Archaea) that have been validly published in the International Journal of Systematic and Evolutionary Microbiology directly or by inclusion in a Validation List, under the Rules of International Code of Nomenclature of Bacteria. Currently there are 15 974 taxa listed. In addition, LPSN has an up-to-date classification of prokaryotes and information on prokaryotic nomenclature and culture collections.

Concordance between whole-cell matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry and multilocus sequence analysis approaches in species discrimination within the genus Pseudomonas

Multilocus sequence analysis (MLSA) is one of the most accepted methods for the phylogenetic assignation of Pseudomonas strains to their corresponding species. Furthermore, updated databases are essential for correct bacterial identification and the number of Pseudomonas species is increasing continuously. Currently, 127 species are validly described in Euzéby's List of Species with Standing in Nomenclature, and 29 novel species have been described since the publication of the last comprehensive MLSA phylogenetic study based on the sequences of the 16S rDNA, gyrB, rpoB and rpoD genes. Therefore, an update of the sequence database is presented, together with the analysis of the phylogeny of the genus Pseudomonas. Whole-cell matrix-assisted laser-desorption/ionization time-of-flight (WC-MALDI-TOF) mass spectrometry (MS) analysis has been applied very recently to the identification of bacteria and is considered to be a fast and reliable method. A total of 133 type strains of the recognized species and subspecies in the genus Pseudomonas, together with other representative strains, were analyzed using this new technique, and the congruence between the WC-MALDI-TOF MS and MLSA techniques was assessed for the discrimination and correct species identification of the strains. The utility of both methods in the identification of environmental and clinical strains is discussed.

Phylogenetic assessment of culture collection strains of Thiobacillus thioparus, and definitive 16S rRNA gene sequences for T. thioparus, T. denitrificans, and Halothiobacillus neapolitanus

The 16S rRNA gene sequences of 12 strains of Thiobacillus thioparus held by different culture collections have been compared. A definitive sequence for the reference type strain (Starkey; ATCC 8158(T)) was obtained. The sequences for four examples of the Starkey type strain were essentially identical, confirming their sustained identity after passage through different laboratories. One strain (NCIMB 8454) was reassigned as a strain of Halothiobacillus neapolitanus, and a second (NCIMB 8349) was a species of Thermithiobacillus. These two strains have been renamed in their catalog by the National Collection of Industrial and Marine Bacteria. The 16S rRNA gene sequence of the type strain of Halothiobacillus neapolitanus (NCIMB 8539(T)) was determined and used to confirm the identity of other culture collection strains of this species. The reference sequences for the type strains of Thiobacillus thioparus and Halothiobacillus neapolitanus have been added to the online List of Prokaryotic Names with Standing in Nomenclature. Comparison of the 16S rRNA gene sequences available for strains of Thiobacillus denitrificans indicated that the sequence for the type strain (NCIMB 9548(T)) should always be used as the reference sequence for new and existing isolates.

Towards large-scale FAME-based bacterial species identification using machine learning techniques

In the last decade, bacterial taxonomy witnessed a huge expansion. The swift pace of bacterial species (re-)definitions has a serious impact on the accuracy and completeness of first-line identification methods. Consequently, back-end identification libraries need to be synchronized with the List of Prokaryotic names with Standing in Nomenclature. In this study, we focus on bacterial fatty acid methyl ester (FAME) profiling as a broadly used first-line identification method. From the BAME@LMG database, we have selected FAME profiles of individual strains belonging to the genera Bacillus, Paenibacillus and Pseudomonas. Only those profiles resulting from standard growth conditions have been retained. The corresponding data set covers 74, 44 and 95 validly published bacterial species, respectively, represented by 961, 378 and 1673 standard FAME profiles. Through the application of machine learning techniques in a supervised strategy, different computational models have been built for genus and species identification. Three techniques have been considered: artificial neural networks, random forests and support vector machines. Nearly perfect identification has been achieved at genus level. Notwithstanding the known limited discriminative power of FAME analysis for species identification, the computational models have resulted in good species identification results for the three genera. For Bacillus, Paenibacillus and Pseudomonas, random forests have resulted in sensitivity values, respectively, 0.847, 0.901 and 0.708. The random forests models outperform those of the other machine learning techniques. Moreover, our machine learning approach also outperformed the Sherlock MIS (MIDI Inc., Newark, DE, USA). These results show that machine learning proves very useful for FAME-based bacterial species identification. Besides good bacterial identification at species level, speed and ease of taxonomic synchronization are major advantages of this computational species identification strategy.

Proposal of a neotype strain (A1-86) for Eubacterium rectale. Request for an Opinion

Eubacterium rectale is one of the most abundant bacterial species recovered from human faeces. E. rectale (Hauduroy et al. 1937) appears in the 'List of Bacterial Names with Standing in Nomenclature', but it is noted that the originally proposed type strain, VPI 0989(T), has been lost and its possible replacement by another strain (VPI 0990) from the same faecal sample has never been formally proposed. It is therefore proposed that strain A1-86 (=DSM 17629=NCIMB 14373), isolated from human adult faeces, be formally recognized as the neotype strain of Eubacterium rectale.

Genus Megamonas should be placed in the lineage of Firmicutes; Clostridia; Clostridiales; ‘Acidaminococcaceae’; Megamonas

Megamonas hypermegale is the sole species of the genus Megamonas included in the List of Prokaryotic Names with Standing in Nomenclature and in the databases of DDBJ, EBI/EMBL and NCBI/GenBank it is placed in the lineage of Bacteroidetes; Bacteroidetes (class); 'Bacteroidales'; Bacteroidaceae; Megamonas. Phylogenetic analysis based on comparative 16S rRNA gene sequencing showed that this species clustered with species of the family 'Acidaminococcaceae' but not with those of the Bacteroidaceae. The genus Megamonas should be placed in the lineage of Firmicutes; Clostridia; Clostridiales; 'Acidaminococcaceae'; Megamonas.

Spelling of Emerging Pathogens

To the Editor: Language is about comprehension; provided the parties in a discussion can understand each other, variations in pronunciation of individual words may be tolerated or disregarded. In modern English, numerous examples of variant pronunciations exist that cause no problems of comprehension (e.g., either, tomato, laboratory, fertile). These arise from several causes; regional practice is likely the most important factor, but the speaker's education and social background, personal preferences, and even etymologic theories also play a part. It would be futile and, some would feel, undesirable to attempt to impose uniformity by prescribing approved pronunciations if communication is not endangered. Moreover, both language and pronunciation are subject to constant change. The same is not true regarding the spelling of organisms' names. Although we accept variation in pronunciation, we should not accept variation in the spelling of binomial names. Common spelling variants and the citation frequency (PubMed) of 4 organisms, Acinetobacter baumannii, Coccidioides immitis (the fungal causal agent of coccidioidomycosis), Coxiella burnetii (the causal agent of Q fever), and Tropheryma whipplei (the causal agent of Whipple disease), are detailed in the Table. Common spelling mistakes occur with double letters (e.g., nn, ii), as well as complicated strings of consecutive vowels (e.g., Coccidioides). However, a defense to such criticism is that various authors have adopted the spelling of a previous taxonomic description that has become outdated, e.g., C. burneti (previous) and C. burnetii (current). Historic change in the spelling of these names is the primary reason they are published and cited in PubMed with different spellings. However, even disregarding historic taxonomic variants, ≈14.8% of Tropheryma whipplei, 14.3% of Acinetobacter baumannii, 12.3% of Coxiella burnetii, and 1.9% of Coccidioides citations are spelled incorrectly in PubMed. These relatively large percentages may mean that relevant literature is overlooked in searches. Table Common spellings of binomial names of organisms* Authors should be aware that previous taxonomic spelling of binomial names exist and check their historic evolution in the List of Prokaryotic Names with Standing in Nomenclature (http://www.bacterio.cict.fr). Authors should cite previous spelling when such a change has been recent and they may wish to include previous spellings in literature searches. Additionally, the most current and formally accepted spelling must be used when preparing a manuscript for publication. The origins of incorrect and variant spellings of binomial names may lie in an array of sources, including original mispronunciation with subsequent incorrect phonetic transcription. Written language is rarely a phonetic transcript of vocal acoustics, however, it interfaces with several factors that prevent us from spelling words the way they sound. Orthography, which promotes the practice of writing words with the proper letters according to standard usage and conventionally correct spelling, is further complicated by the use of Greek or Latin words, each with their own linguistic peculiarities. Although we may not be able to standardize phonetic pronunciation of binomial names locally, nationally, or internationally, we should be constantly conscious of their spelling. As authors and peer reviewers, we should strive to achieve uniformity in written media to promote enhanced communication with our peers in infectious diseases.