Biology subjects

Wand, M.

Publications and source records attributed to Wand, M..

3 recordsLinked to original sources

bioRxiv2024

C7-substituted Quinolines as Potent Inhibitors of AdeG Efflux Pumps in Acinetobacter baumannii

Efflux, mediated by a series of multidrug efflux pumps, is a major contributor to antibiotic resistance in Gram-negative bacteria. Efflux pump inhibitors (EPIs), which can block efflux, have the potential to be used as adjuvant therapies to re-sensitize bacteria to existing antibiotics. In this study, 36 quinoline-based compounds were synthesized as potential EPIs targeting Resistance Nodulation Division (RND) family pumps in the multidrug-resistant pathogen Acinetobacter baumannii . In A. baumannii strains with overexpressed AdeFGH (chloramphenicol-adapted) and AdeABC (AYE, Ab5075-UW), these compounds enhanced Hoechst dye accumulation, indicating general efflux inhibition, and potentiated chloramphenicol which is an AdeG substrate. The research focused on two generations of quinoline compounds, with modifications at the C-7 position of first-generation compounds to improve hydrophobic interactions with the Phe loop in the AdeG efflux pump, to generate second-generation compounds. The modified quinolines showed strong pump inhibition and significant chloramphenicol potentiation, with MIC reductions of 4- to 64-fold. Notably, compounds 1.8 and 3.8 exhibited the highest inhibitory activity, while compounds 1.3 and 3.3 showed up to 64-fold potentiation, highlighting the importance of specific structural features at the C-7 position for efflux pump inhibition. The study also revealed selective inhibition of AdeFGH over AdeABC, with no potentiation observed for gentamicin, showing the specificity of these quinoline- based inhibitors. Importantly, the compounds showed no toxicity in a Galleria mellonella model at a 50 mg/kg dose level, highlighting their suitability as potential antibiotic adjuvants for combating bacterial resistance.

microbiology↗

bioRxiv2024

Direct CCUT: A Versatile and Standardized Framework to Train 3C Deep Restoration Models

Chromatin Capture Experiments such as Hi-C and Micro-C have become popular methods for genome architecture exploration. Recently, also a protocol for long read sequencing, Pore-C, was introduced, allowing the characterization of three-dimensional chromatin structures using Oxford Nanopore Sequencing Technology. Here, we present a framework that focuses on the efficient reconstruction of low-resolution Pore-C data but can also process all other 3C data, such as Hi-C and Micro-C matrices, using models that can be trained on a consumer GPU. Furthermore, we integrate building blocks of popular super-resolution methods such as SWIN-Transformer or residual-in-residual-blocks to modify or build customized networks on the fly. Pre-built models were trained and evaluated on multiple publicly available gold-standard Micro-C and Pore-C datasets, allowing for fine-scale structure prediction. Our work aims to overcome the drawback of high sequencing costs to construct high resolution contact matrices, as well as the problem of mapping low-coverage libraries to high-resolution structures in the genome. Although there have been major breakthroughs regarding NGS-based methods for the reconstruction of high-resolution chromatin interaction matrices from low-resolution data, for data obtained by long-read sequencing, there is currently no solution to reconstruct missing and sparse information and to improve the quality. AvailabilityThe tool is available at (https://github.com/stasys-hub/CCUT)

bioinformatics↗

bioRxiv2022

Inhibition of Phosphodiesterase 12 results in Antiviral Activity against several RNA Viruses including SARS-CoV-2.

Phosphodiesterase 12 (PDE12) is a negative regulator of the type 1 interferon (IFN) response and here we show that PDE12 inhibitors (lead compounds 63 and 17) are associated with increased RNAseL activity, are well tolerated at the therapeutic range and inhibit, both in vitro and in vivo, the replication of several RNA viruses including hepatitis C virus (HCV), dengue virus (DENV), West Nile Virus (WNV) and SARS-CoV-2.

microbiology↗