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Abubucker, S.

Publications and source records attributed to Abubucker, S..

2 recordsLinked to original sources

Tombusvirus p19 captures RNase III-cleaved double-stranded RNAs formed by overlapping sense and antisense transcripts in E. coli

Antisense transcription is widespread in bacteria. By base pairing with overlapping sense RNAs, antisense RNAs (asRNA) can form long double-stranded RNAs (dsRNA), which are cleaved by RNase III, a dsRNA endoribonuclease. Ectopic expression of plant tombusvirus p19 in E. coli stabilizes ~21 bp dsRNA RNase III decay intermediates, which enabled us to characterize otherwise highly unstable asRNA by deep sequencing of p19-captured dsRNA and total RNA. dsRNA formed at most bacterial genes in the bacterial chromosome and in a plasmid. The most abundant dsRNA clusters were mostly formed by divergent transcription of sense and antisense transcripts overlapping at their 5-ends. The most abundant clusters included small RNAs, such as ryeA/ryeB, 4 toxin-antitoxin genes, and 3 tRNAs, and some longer coding genes, including rsd and cspD. The sense and antisense transcripts in abundant dsRNA clusters were more plentiful and had longer half-lives in RNase III mutant strains, suggesting that formation of dsRNAs promoted RNA decay at these loci. However, widespread changes in protein levels did not occur in RNase III mutant bacteria. Nonetheless, some proteins involved in antioxidant responses and glycolysis changed reproducibly. dsRNAs accumulated in bacterial cells lacking RNase III, increasing in stationary phase, and correlated with increased cell death in RNase III mutant bacteria in late stationary phase. The physiological importance of widespread antisense transcription in bacteria remains unclear but it may become important during environmental stress. Ectopic expression of p19 is a sensitive method for identifying antisense transcripts and RNase III cleavage sites in bacteria.

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↗