Biology subjects

Marenda, M.

Publications and source records attributed to Marenda, M..

5 recordsLinked to original sources

bioRxiv2026

Ribosome Quality Control Mitigates Proteotoxic Stress in Aneuploid Cells

Aneuploidy is widespread in tumors, but how cancer cells adapt to aneuploidy-induced cellular stresses remains poorly understood. Here, we focus on the mechanisms employed to cope with proteostasis disruption, a major stress caused by aneuploidy. We show that aneuploid cells exhibit a significant accumulation of ribosomes enclosed within autophagosomes, ultimately degraded through lysosome-mediated processes. Our data also indicate that limited folding capacity of newly synthesized polypeptides leads to lysosome-mediated degradation of ribosomes. We also found that the E3 ligase ZNF598 marks these ribosomes for degradation, thus clearing translationally-impaired ribosomes. Importantly, highly aneuploid tumors display a positive correlation with ZNF598 expression, while being negatively associated with ribosomal signatures. This suggests that ribosome-associated quality control is crucial for cancer cell survival under proteotoxic stress. Our study uncovers molecular events in response to proteotoxic stress in aneuploid cells and suggests that components of ribosome-associated quality control, including ZNF598, could serve as promising targets in cancer therapy.

cell biology↗

bioRxiv2024

Nuclear RNA forms an interconnected network of transcription-dependent and tunable microgels

Living cells are organised through active, non-equilibrium processes, yet the physical principles governing their material states remain unclear. The cell nucleus has been described as either fluid-like or solid-like, but these behaviours have not been reconciled within a single framework. Here we show that nascent RNA and the multivalent RNA-binding protein SAF-A assemble into a nucleus-spanning microgel network maintained near the sol-gel transition. This active network exhibits scale- and time-dependent viscoelasticity and naturally reconciles solid-like and fluid-like responses. By integrating super-resolution imaging with mechanistic polymer modelling, we identify RNA production and degradation as control parameters that tune network connectivity. The model predicts enhanced susceptibility to modest perturbations near criticality, which we confirm experimentally by shifting the system between sol-like and gel-like regimes. Measurements of molecular transport, combined with simulations, reveal size-dependent diffusion and transient trapping within gel pores, establishing direct physical consequences of the near-critical state. Our results identify RNA metabolism as an energy-driven regulator of nuclear material properties and position the nucleus as a living example of an active microgel poised near criticality.

molecular biology↗

bioRxiv2023

HlyF, an underestimated virulence factor of uropathogenic Escherichia coli

Urinary tract infections (UTIs) are predominantly caused by uropathogenic Escherichia coli (UPEC). By analysing a representative collection of UPEC strains from community-acquired infections, we showed that 20 % of these strains had the ability to produce the protein HlyF. These hlyF+ UPEC strains were the most virulent, mostly responsible for pyelonephritis, often with bloodstream infections. Using a mouse model of UTI, we showed that HlyF was associated with the ability of UPEC to develop a urosepsis, with the presence of bacteria in the spleen and an exacerbated inflammatory response. In contrast to archetypical UPEC strains, hlyF+ UPEC strains are not restricted to phylogroup B2 and harbor a specific repertoire of virulence factors reflecting the fact that HlyF is encoded by conjugative ColV-like plasmids. These plasmids also carry antimicrobial resistance genes, which may facilitate their selection and spreading amongst people receiving antimicrobial therapy. Overall, our data suggest that HlyF is a virulence factor in UPEC and spreading of ColV-like plasmids encoding hlyF warrants further investigation.

microbiology↗

bioRxiv2022

DNMT3B PWWP mutations cause hypermethylation of heterochromatin

The correct establishment of DNA methylation patterns is vital for mammalian development and is achieved largely by the de novo DNA methyltransferases DNMT3A and DNMT3B. Mutations in DNMT3B can cause immunodeficiency-centromeric instability-facial anomalies type 1 (ICF1) syndrome which is characterised by hypomethylated heterochromatin. However, in the genome, DNMT3B primarily localises to actively transcribing gene bodies through the interaction of its PWWP domain with the histone modification H3K36me3 and it is unclear how it is recruited to heterochromatin. Here we show that in DNMT3B knockout cells, loss of DNA methylation predominantly occurs in heterochromatic domains marked by H3K9me3. We also find that PWWP domain mutations which disrupt DNMT3Bs interaction with H3K36me3 result in striking increases of DNA methylation in H3K9me3-marked heterochromatin. Gains of methylation are also observed when the PWWP domain of DNMT3B is deleted. In contrast, we find that the ICF1 syndrome-causing PWWP mutation, S270P, does not result in hypermethylation of heterochromatin and destabilises the protein. We also show that removal of the N-terminus region of DNMT3B affects its recruitment to chromatin and ability to methylate H3K9me3 marked regions. Our results suggest that DNMT3B is recruited to H3K9me3 marked heterochromatin in a PWWP-independent manner and that this recruitment is facilitated by the proteins N-terminus. More generally, we suggest that DNMT3B plays a role in DNA methylation homeostasis at heterochromatin, a process which is disrupted in ICF syndrome, cancer and aging.

genetics↗

bioRxiv2020

SuperStructure: a Parameter-Free Super-Structure Identifier for SMLM Data

Single-Molecule Localisation Microscopy (SMLM) allows the quantitative mapping of molecules at high resolution. However, understanding the non-random interaction of proteins requires the identification of more complex patterns than those typified by standard clustering tools. Here we introduce SuperStructure, a parameter-free algorithm to quantify structures made of inter-connected clusters, such as protein gels. SuperStructure works without a priori assumptions and is thus an ideal methodology for standardised analysis of SMLM data.

bioinformatics↗