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Metcalf, W.

Publications and source records attributed to Metcalf, W..

2 recordsLinked to original sources

Expanding the cultivable human archaeome: Methanobrevibacter intestini sp. nov. and strain Methanobrevibacter smithii GRAZ-2 from human feces

Two mesophilic, hydrogenotrophic methanogens, WWM1085 and M. smithii GRAZ-2 were isolated from human fecal samples. WWM1085 was isolated from an individual in the USA, and represents a novel species with in the genus Methanobrevibacter. M. smithii GRAZ-2 (= DSM 116045) was retrieved from fecal samples of a European, healthy female and represents a novel strain within this genus. Both Methanobrevibacter representatives form non-flagellated, short rods with variable morphologies and the capacity to form filaments. Both isolates showed the typical fluorescence of F420 and methane production. Compared to M. smithii GRAZ-2, WWM1085 did not accumulate formate when grown on H2 and CO2. The optimal growth conditions were at 37{degrees}C, and pH 7. Full genome sequencing revealed a genomic difference of WWM1085 to the type strain of M. smithii PS (type strain; DSM 861), with 93.55% ANI and major differences in the sequence of its mcrA gene (3.3% difference in nucleotide sequence). Differences in the 16S rRNA gene were very minor and thus distinction based on this sequence might not be possible. M. smithii GRAZ-2 was identified as a novel strain within the Methanobrevibacter genus (ANI 99.04 % to M. smithii PS). Due to the major differences of WWM1085 and M. smithii type strain PS in phenotypic, genomic and metabolic features, we propose M. intestini sp. nov. as a novel species with WWM1085 as the type strain (DSM 116060T = CECT 30992).

microbiology↗

A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data

Genome mining has become a key technology to explore and exploit natural product diversity through the identification and analysis of biosynthetic gene clusters (BGCs). Initially, this was performed on a single-genome basis; currently, the process is being scaled up to large-scale mining of pan-genomes of entire genera, complete strain collections and metagenomic datasets from which thousands of bacterial genomes can be extracted at once. However, no bioinformatic framework is currently available for the effective analysis of datasets of this size and complexity. Here, we provide a streamlined computational workflow, tightly integrated with antiSMASH and MIBiG, that consists of two new software tools, BiG-SCAPE and CORASON. BiG-SCAPE facilitates rapid calculation and interactive visual exploration of BGC sequence similarity networks, grouping gene clusters at multiple hierarchical levels, and includes a glocal alignment mode that accurately groups both complete and fragmented BGCs. CORASON employs a phylogenomic approach to elucidate the detailed evolutionary relationships between gene clusters by computing high-resolution multi-locus phylogenies of all BGCs within and across gene cluster families (GCFs), and allows researchers to comprehensively identify all genomic contexts in which particular biosynthetic gene cassettes are found. We validate BiG-SCAPE by correlating its GCF output to metabolomic data across 403 actinobacterial strains. Furthermore, we demonstrate the discovery potential of the platform by using CORASON to comprehensively map the phylogenetic diversity of the large detoxin/rimosamide gene cluster clan, prioritizing three new detoxin families for subsequent characterization of six new analogs using isotopic labeling and analysis of tandem mass spectrometric data.

bioinformatics↗