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Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2., Graphical Abstract Graphical AbstractmiRMaster 2 workflow. The workflow is split into three steps: data selection and compression, data upload and server-side processing.

Isovaleryl coenzyme A (IV-CoA) is an important building block of iso-fatty acids. In myxobacteria, IV-CoA is essential for the formation of signaling molecules involved in fruiting body formation. Leucine degradation is the common source of IV-CoA, but a second, de novo biosynthetic route to IV-CoA termed AIB (alternative IV-CoA biosynthesis) was recently discovered in M. xanthus. The AIB-operon contains the TetR-like transcriptional regulator AibR, which we characterize in this study. We demonstrate that IV-CoA binds AibR with micromolar affinity and show by gelshift experiments that AibR interacts with the promoter region of the AIB-operon once IV-CoA is present. We identify an 18-bp near-perfect palindromic repeat as containing the AibR operator and provide evidence that AibR also controls an additional genomic locus coding for a putative acetyl–CoA acetyltransferase. To elucidate atomic details, we determined crystal structures of AibR in the apo, the IV-CoA- and the IV-CoA-DNA-bound state to 1.7 Å, 2.35 Å and 2.92 Å, respectively. IV-CoA induces partial unfolding of an α-helix, which allows sequence-specific interactions between AibR and its operator. This study provides insights into AibR-mediated regulation and shows that AibR functions in an unusual TetR-like manner by blocking transcription not in the ligand-free but in the effector-bound state.

Multidrug-resistant pathogens represent one of the biggest global healthcare challenges. Molecular diagnostics can guide effective antibiotics therapy but relies on validated, predictive biomarkers. Here we present a novel, universally applicable workflow for rapid identification of antimicrobial resistance (AMR) biomarkers from clinical Escherichia coli isolates and quantitatively evaluate the potential to recover causal biomarkers for observed resistance phenotypes. For this, a metagenomic plasmid library from 1,110 clinical E. coli isolates was created and used for high-throughput screening to identify biomarker candidates against Tobramycin (TOB), Ciprofloxacin (CIP), and Trimethoprim-Sulfamethoxazole (TMP-SMX). Identified candidates were further validated in vitro and also evaluated in silico for their diagnostic performance based on matched genotype-phenotype data. AMR biomarkers recovered by the metagenomics screening approach mechanistically explained 77% of observed resistance phenotypes for Tobramycin, 76% for Trimethoprim-Sulfamethoxazole, and 20% Ciprofloxacin. Sensitivity for Ciprofloxacin resistance detection could be improved to 97% by complementing results with AMR biomarkers that are undiscoverable due to intrinsic limitations of the workflow. Additionally, when combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached promising positive and negative predictive values of up to 97 and 99%, respectively. Finally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms.

To combat the rise of antimicrobial resistance, the discovery of new antibiotics is paramount. Albicidin and cystobactamid are related natural product antibiotics with potent activity against Gram-positive and, crucially, Gram-negative pathogens. AlbA has been reported to neutralize albicidin by binding it with nanomolar affinity. To understand this potential resistance mechanism, we determined structures of AlbA and its complex with albicidin. The structures revealed AlbA to be comprised of two domains, each unexpectedly resembling the multiantibiotic neutralizing protein TipA. Binding of the long albicidin molecule was shared pseudosymmetrically between the two domains. The structure also revealed an unexpected chemical modification of albicidin, which we demonstrate to be promoted by AlbA, and to reduce albicidin potency; we propose a mechanism for this reaction. Overall, our findings suggest that AlbA arose through internal duplication in an ancient TipA-like gene, leading to a new binding scaffold adapted to the sequestration of long-chain antibiotics.