Search bioRxiv⌕ Search

Biology subjects

Torrent, M.

Publications and source records attributed to Torrent, M..

5 recordsLinked to original sources

Seven amino acids gate transcriptional activation by a minimal MarA Helix turn-helix DNA-binding domain

Prokaryotic transcription factors (TFs) lie at the core of antimicrobial resistance, controlling genes that let bacteria survive antibiotic exposure. The AraC/XylS family of TFs is defined by a ~99-residue DNA-binding domain composed of two helix-turn-helix (HTH) motifs. While this two-motif architecture is considered the minimal functional unit, the striking sequence and structural similarity between both HTH motifs raises the question of whether it evolved from a single ancestral HTH domain. Here, we designed two C-terminal truncations of MarA, comprising a single HTH motif, differing by seven-residues (IRSRKMT). Electrophoretic-mobility shift assays reveal that both constructs specifically bind the marbox sequence as reconstituted dimers, while size-exclusion chromatography shows they exist in a monomer-dimer equilibrium in solution. Despite retaining DNA-binding capacity, the truncations diverge functionally: while MarA64 (including IRSRKMT) activates transcription and confers regular erythromycin tolerance, MarA57 (lacking IRSRKMT) yields a transcriptionally inactive complex that suppresses reporter expression below baseline, suggesting competitive promoter occupancy. Molecular dynamics simulations and AlphaFold models suggest that the IRSRKMT extension forms an -helical element stabilizing a transcriptionally productive dimer interface. Conversely, its loss disrupts quaternary assembly, alters DNA bending, and misaligns RNA polymerase-contacting residues. Furthermore, free dimers explore non-productive conformations, suggesting that functional dimerization occurs upon DNA engagement. These findings establish that a single, correctly dimerized HTH domain is sufficient for both DNA binding and transcriptional activation, providing a structural rationale for short AraC/XylS-like proteins and offering a tuneable scaffold for synthetic biology and novel anti-virulence strategies.

molecular biology↗

The N-terminal helix of MarA as a key element in the mechanism of DNA binding

Efflux is one of the mechanisms employed by Gram-negative bacteria to become resistant to routinely used antibiotics. The inhibition of efflux by targeting their regulators is a promising strategy to re-sensitise bacterial pathogens to antibiotics. AcrAB-TolC is the main Resistance-Nodulation-Division efflux pump in Enterobacteriaceae. MarA is an AraC/XylS family global regulator that regulates more than 40 genes related to the antimicrobial resistance phenotype, including acrAB. The aim of this work was to understand the role of the N-terminal helix of MarA in the mechanism of DNA binding. An N-terminal deletion of MarA showed that the N-terminal helix has a role in the recognition of the functional marboxes. By engineering two double cysteine variants of MarA, and combining in vitro electrophoretic mobility assays and in vivo measurements of acrAB transcription with molecular dynamic simulations, it was shown that the immobilization of the N-terminal helix of MarA prevents binding to DNA. This new mechanism of inhibition seems to be universal for the monomeric members of the AraC/XylS family, as suggested by additional molecular dynamics simulations of the two-domain protein Rob. These results point to the N-terminal helix of the AraC/XylS family monomeric regulators as a promising target for the development of inhibitors.

molecular biology↗

Mining the heparinome for cryptic antimicrobial peptides that selectively kill gram-negative bacteria

Glycosaminoglycan (GAG)-binding proteins regulating essential processes such as cell growth and migration are essential for cell homeostasis. As both GAGs and the lipid A disaccharide core of gram-negative bacteria contain negatively charged disaccharide units, we hypothesized that GAG-binding proteins could also recognize LPS and enclose cryptic antibiotic motifs. Here, we report novel antimicrobial peptides (AMPs) derived from heparin-binding proteins (HBPs), with specific activity against gram-negative bacteria and high LPS binding. We used computational tools to locate antimicrobial regions in 82% of HBPs, most of those colocalizing with putative heparin binding sites. To validate these results, we synthesized five candidates [HBP1-5] that showed remarkable activity against gram-negative bacteria, as well as a strong correlation between heparin and LPS binding. Structural characterization of these AMPs shows that heparin or LPS recognition promotes a conformational arrangement that favors binding. Among all analogs, HBP-5 displayed the highest affinity for both heparin and LPS, with antimicrobial activities against gram-negative bacteria at the nanomolar range. These results suggest that GAG-binding proteins are involved in LPS recognition, which allows them to act also as antimicrobial proteins. Some of the peptides reported here, particularly HBP-5, constitute a new class of AMPs with specific activity against gram-negative bacteria.

systems biology↗

Structural assembly of the bacterial essential interactome

The study of protein interactions in living organisms is fundamental to understanding biological processes and central metabolic pathways. However, our understanding of the bacterial interactome remains limited, hindering the identification of new drug targets and the development of new therapeutic strategies. Here, we predict the assembly of the essential proteins in bacteria using the deep learning protein folding algorithm Alphafold2. We modeled 1089 interactions between essential proteins in bacteria and generated 115 high-accuracy models. Our analysis reveals previously unknown details about the assembly mechanisms of these complexes, highlighting the importance of specific structural features in their stability and function. Furthermore, we identify several novel protein-protein interactions that provide new targets for drug development. Our work provides a framework for predicting the interactome of other bacteria and highlights the potential of deep learning algorithms in advancing our understanding of the complex biology of living organisms.

biochemistry↗

Bacteria Use Structural Imperfect Mimicry To Hijack The Host Interactome

Bacteria use protein-protein interactions to infect their hosts and hijack fundamental pathways, which ensures their survival and proliferation. Hence, the infectious capacity of the pathogen is closely related to its ability to interact with host proteins. Here, we show that hubs in the host-pathogen interactome are isolated in the pathogen network by adapting the geometry of the interacting interfaces. An imperfect mimicry of the eukaryotic interfaces allows pathogen proteins to actively bind to the hosts target while preventing deleterious effects on the pathogen interactome. Understanding how bacteria recognize eukaryotic proteins may pave the way for the rational design of new antibiotic molecules.

microbiology↗