Expanding the genomic encyclopedia of Actinobacteria with 824 isolate reference genomes.

The phylum Actinobacteria includes important human pathogens like Mycobacterium tuberculosis and Corynebacterium diphtheriae and renowned producers of secondary metabolites of commercial interest, yet only a small part of its diversity is represented by sequenced genomes. Here, we present 824 actinobacterial isolate genomes in the context of a phylum-wide analysis of 6,700 genomes including public isolates and metagenome-assembled genomes (MAGs). We estimate that only 30%-50% of projected actinobacterial phylogenetic diversity possesses genomic representation via isolates and MAGs. A comparison of gene functions reveals novel determinants of host-microbe interaction as well as environment-specific adaptations such as potential antimicrobial peptides. We identify plasmids and prophages across isolates and uncover extensive prophage diversity structured mainly by host taxonomy. Analysis of >80,000 biosynthetic gene clusters reveals that horizontal gene transfer and gene loss shape secondary metabolite repertoire across taxa. Our observations illustrate the essential role of and need for high-quality isolate genome sequences.

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 fate of lysine: Non-targeted stable isotope analysis reveals parallel ways for lysine catabolization in Phaeobacter inhibens.

For a detailed investigation of the degradation of lysine in Phaeobacter inhibens DSM 17395, stable isotope experiments with uniformly 13C labeled L-lysine were carried out with lysine adapted cells and the metabolites were analyzed using GC/MS and HPLC/MS. A non-targeted stable isotope analysis was used which compares labeled and not labeled samples to determine the Mass Isotopomer Distribution not only for known metabolites but for all labeled compounds in our GC/MS analysis. We show that P. inhibens uses at least two parallel pathways for the first degradation steps of lysine. Further investigations identified L-pipecolate as an L-lysine degradation intermediate in P. inhibens. The analysis of HPLC/MS data as well as the labeling data of tricarboxylic acid (TCA) cycle intermediates show that L-lysine is not only catabolized directly to acetyl-CoA but also via the ethylmalonyl-CoA-pathway, leading to entry points into the TCA cycle via acetyl-CoA, succinyl-CoA, and malate. Altogether the presented data give a detailed insight into the catabolization of L-lysine following the fate of 13C labeled carbon via several ways into the TCA cycle.

Mobilization and integration of bacterial phenotypic data-Enabling next generation biodiversity analysis through the BacDive metadatabase.

Microbial data and metadata are scattered throughout the scientific literature, databases and unpublished lab notes and thereby often are difficult to access. Hot spots of (meta)data are internal descriptions of culture collections and initial descriptions of novel taxa in primary literature. Here we describe three exemplary mobilization projects which yielded metadata published through the prokaryotic metadatabase BacDive. The Reichenbach collection of myxobacteria includes information on 12,535 typewritten index cards which were digitized. A total of 37,156 data points were extracted by text mining. In the second mobilization project, Analytical Profile Index (API) tests on paper forms were targeted. Overall 6820 API tests were digitized, which provide physiological data of 4524 microbial strains. Thirdly, the extraction of metadata from 523 new species descriptions of the International Journal of Systematic and Evolutionary Microbiology, yielding 35,651 data points, is described. All data sets were integrated and published in BacDive. Thereby these metadata not only became accessible and searchable but were also linked to strain taxonomy, isolation source, cultivation condition, and molecular biology data.

High-throughput screening of a Corynebacterium glutamicum mutant library on genomic and metabolic level.

Due to impressive achievements in genomic research, the number of genome sequences has risen quickly, followed by an increasing number of genes with unknown or hypothetical function. This strongly calls for development of high-throughput methods in the fields of transcriptomics, proteomics and metabolomics. Of these platforms, metabolic profiling has the strongest correlation with the phenotype. We previously published a high-throughput metabolic profiling method for C. glutamicum as well as the automatic GC/MS processing software MetaboliteDetector. Here, we added a high-throughput transposon insertion determination for our C. glutamicum mutant library. The combination of these methods allows the parallel analysis of genotype/phenotype correlations for a large number of mutants. In a pilot project we analyzed the insertion points of 722 transposon mutants and found that 36% of the affected genes have unknown functions. This underlines the need for further information gathered by high-throughput techniques. We therefore measured the metabolic profiles of 258 randomly chosen mutants. The MetaboliteDetector software processed this large amount of GC/MS data within a few hours with a low relative error of 11.5% for technical replicates. Pairwise correlation analysis of metabolites over all genotypes showed dependencies of known and unknown metabolites. For a first insight into this large data set, a screening for interesting mutants was done by a pattern search, focusing on mutants with changes in specific pathways. We show that our transposon mutant library is not biased with respect to insertion points. A comparison of the results for specific mutants with previously published metabolic results on a deletion mutant of the same gene confirmed the concept of high-throughput metabolic profiling. Altogether the described method could be applied to whole mutant libraries and thereby help to gain comprehensive information about genes with unknown, hypothetical and known functions.