Biology subjects

Fenk, M.

Publications and source records attributed to Fenk, M..

4 recordsLinked to original sources

bioRxiv2025

Colonization, translocation, and evolution of opportunistic pathogens during hospital-associated infections

Many commensal bacteria that peacefully reside in the human microbiome are also able to cause acute opportunistic infections. Emerging evidence suggests that within-host evolution contributes to infection, but the genetic mechanisms facilitating the progression of opportunistic pathogens from carriage to acute infection remain unknown. Here, we prospectively collected native samples from four microbiome niches of 13 critically ill patients to assess the evolutionary dynamics leading up to infection. Among three patients we have observed eleven healthcare-associated infections (HAI) caused by nine pathogen species. Leveraging a culture-based approach, we demonstrate that the microbiome is frequently (73%) colonized by the pathogen lineage already before or at the time of diagnosis. Moreover, we identify a short-lived, non-synonymous mutation (F126L) within the fimbriae regulator gene fimZ of Enterobacter hormaechei, first detectable within the gut and subsequently associated with HAI before becoming replaced by body-wide sweeps of independent treatment-associated mutations. Despite fimZ [F126L] being globally undetected, we can show in vitro and in vivo that the F126L mutation leads to elevated biofilm formation, cell adhesion and virulence, suggesting a role during HAI. Our work highlights the power of prospective, population-wide investigation of pathogens to elucidate rapid evolution linked to disease.

microbiology↗

bioRxiv2025

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstructing transmission events, and identifying antimicrobial resistance mutations. While many tools have been developed to identify single nucleotide variants (SNVs) from whole-genome sequencing, they often suffer from high false positive rates due to the complexity of bacterial genomes and the need for different filtering cutoffs across sample types and sequencing depths. As datasets increase in size, the manual filtering required for high accuracy presents a significant obstacle. Here, we present AccuSNV, a novel deep learning-based tool for high-precision and automated bacterial SNV calling. Unlike traditional methods that process one sample at a time, AccuSNV leverages a convolutional neural network (CNN) that integrates alignment information across multiple samples, enhancing precision through learned across-sample patterns. We evaluated AccuSNV against seven popular SNV calling tools using simulated data from six bacterial species with varied sequencing depths, numbers of isolates, mutations, and divergence levels. To further validate its real-world utility, we tested AccuSNV on multiple curated bacterial datasets containing reported SNVs. In both simulated and real-world scenarios, AccuSNV consistently achieved the best performance. Moreover, AccuSNV provides comprehensive user-friendly downstream analysis modules and outputs, including mutation annotation information, phylogenetic inference, dN/dS calculations, and optional manual filtering. Together with the automated deep learning-based calling, these features make AccuSNV broadly accessible to users with different levels of computational expertise.

bioinformatics↗

bioRxiv2023

Uncovering the temporal dynamics and regulatory networks of thermal stress response in a hyperthermophile using transcriptomics and proteomics

Extremophiles, such as the hyperthermophilic archaeon Pyrococcus furiosus, thrive under extreme conditions and must rapidly adapt to changes in the physical parameters of their natural environment for short-term and long-term survival. When inhabiting hydrothermal vents, these organisms face substantial temperature gradients, necessitating the evolution of adaptive thermal stress mechanisms. However, the dynamics and coordination of cellular responses at the transcriptome and proteome levels remain underexplored. This study presents an integrated analysis of RNA-sequencing and mass spectrometry data to elucidate the transcriptomic and proteomic responses to heat and cold shock stress and recovery in P. furiosus. Our results reveal surprisingly rapid and dynamic changes in gene and protein expression patterns associated with these stress responses. Heat shock triggers extensive transcriptome reprogramming, orchestrated by the transcriptional regulator Phr, which targets a broader gene repertoire than previously demonstrated. For heat shock signature genes, RNA levels swiftly return to baseline upon recovery, while protein levels remain persistently upregulated, reflecting a rapid but more sustained response. Intriguingly, cold shock at 4{degrees}C elicits distinct short-term and long-term responses at both RNA and protein levels. By conducting a cluster analysis, we identified gene sets with either congruent or contrasting trends in RNA and protein changes. Notably, these clusters represent well-separated arCOG groups and appear to be tailored to their individual cellular responses. Our study provides a comprehensive overview of the cellular response to temperature stress, advancing our understanding of stress response mechanisms in hyperthermophilic archaea and provide valuable insights into the molecular adaptations that facilitate life in extreme environments.

microbiology↗

bioRxiv2019

Nanopore-based native RNA sequencing provides insights into prokaryotic transcription, operon structures, rRNA maturation and modifications

The prokaryotic transcriptome is shaped by transcriptional and posttranscriptional events that define the characteristics of an RNA, including transcript boundaries, the base modification status, and processing pathways to yield mature RNAs. Currently, a combination of several specialised short-read sequencing approaches and additional biochemical experiments are required to describe all transcriptomic features. In this study, we present native RNA sequencing of bacterial (E. coli) and archaeal (H. volcanii, P. furiosus) transcriptomes employing the Oxford Nanopore sequencing technology. Based on this approach, we could address multiple transcriptomic characteristics simultaneously with single-molecule resolution. Taking advantage of long RNA reads provided by the Nanopore platform, we could (re-)annotate large transcriptional units and boundaries. Our analysis of transcription termination sites suggests that diverse termination mechanisms are in place in archaea. Moreover, we shed additional light on the poorly understood rRNA processing pathway in Archaea. One of the key features of native RNA sequencing is that RNA modifications are retained. We could confirm this ability by analysing the well-known KsgA-dependent methylation sites and mapping of N4-acetylcytosines modifications in rRNAs. Notably, we were able to follow the relative timely order of the installation of these modifications in the rRNA processing pathway.

microbiology↗