Search bioRxiv⌕ Search

Biology subjects

Kiemer, A. K.

Publications and source records attributed to Kiemer, A. K..

2 recordsLinked to original sources

Cystobactamid off-target profiling reveals favorable safety, superoxide reduction, and SCARB1 inhibition in eukaryotes

Antimicrobial resistance (AMR) poses a fundamental global threat, necessitating new strategies for effective therapies. Cystobactamids (CYS), a class of antibacterial agents targeting bacterial gyrase and topoisomerase IV, represent a non-traditional chemical scaffold with broad-spectrum activity. For toxicological de-risking, we performed a comprehensive profiling on eukaryotic cells, focusing on cytotoxicity, genotoxicity, and mitochondrial toxicity, demonstrating cellular safety and superoxide scavenging properties. Studies in zebrafish embryos assessed developmental, cardiovascular, and hepatic toxicity, indicating a favorable in vivo safety profile. Metabolism studies revealed glucuronidation and amide bond hydrolysis as key pathways, whereby CYS metabolic stability substantially improved by cobicistat co-treatment. Affinity-based protein profiling identified the cholesterol- and HCV-receptor scavenger receptor class B member 1 (SCARB1) as a primary eukaryotic off-target protein, with cystobactamids shown to inhibit SCARB1s function, preventing hepatitis C virus pseudoparticle entry into cells. These findings suggest a high therapeutic potential for cystobactamids and highlight SCARB1 as a primary eukaryotic target.

pharmacology and toxicology↗

CRUP: A comprehensive framework to predict condition-specific regulatory units

We present the software CRUP (Condition-specific Regulatory Units Prediction) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell lines and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.\n\nAvailabilityhttps://github.com/VerenaHeinrich/CRUP

bioinformatics↗