Biology subjects

Palma, F.

Publications and source records attributed to Palma, F..

6 recordsLinked to original sources

bioRxiv2026

An N, S-acetylated L-cysteine-cysteamine conjugate hinders pyocyanin redox cycling to weaken Pseudomonas aeruginosa biofilm and dampens LPS-driven acute pulmonary inflammation

The persistence of P. aeruginosa infections is largely driven by the secretion of several factors during invasion, including the redox-active phenazine pyocyanin (PYO), which promotes biofilm formation and oxidative stress. Biofilms contribute to chronic infections and antibiotic resistance, limiting the efficacy of conventional therapies. We found that a synthetic compound, I-152, a conjugate of N-acetyl-L-cysteine (NAC) and S-acetylcysteamine (also known as S-acetyl-{beta}-mercaptoethylamine; SMEA), effectively restored colistin susceptibility against P. aeruginosa by altering biofilm nanomechanical properties. These perturbations in matrix integrity were associated with I-152s ability to hinder the phenazine redox cycle, shifting PYO to a reduced state as well as enabling S-conjugate formation. The compound decreased PYO accumulation in bacterial cultures and PYO-generated reactive oxygen species (ROS) in macrophage cells. Together with PYO, LPS is another driver of ROS-dependent inflammatory signaling in the host, which leads to an uncontrolled cytokine response and organ damage, especially in patients with cystic fibrosis. I-152 treatment downregulated the expression of LPS-induced inflammatory cytokines, i.e., IL-6 and TNF-, in bone marrow-derived macrophages (BMDM) isolated from transgenic CFTR-/- and CFTR+/+ mice. Consistently, I-152 partially counteracted the inflammatory response in the P. aeruginosa LPS-induced acute lung injury murine model. Taken together, these results support I-152 as an adjunctive treatment for P. aeruginosa respiratory infections through a dual mechanism: combating antimicrobial resistance in biofilms and dampening host inflammation in the respiratory system. HighlightsO_LII-152 potentiates colistin activity against P. aeruginosa by compromising the biofilm surface C_LIO_LII-152 rewires the pyocyanin (PYO) redox state and forms covalent adducts with it C_LIO_LIPYO accumulation and PYO-induced ROS generation in macrophages is impaired by I-152 C_LIO_LIEx vivo, I-152 dampens excessive pro-inflammatory response to P. aeruginosa LPS in CFTR-/- and CFTR+/+ BM-derived macrophages C_LIO_LII-152 (140 mg/Kg) attenuates LPS-driven inflammation and lung damage in CFTR+/+ mice C_LI

pharmacology and toxicology↗

bioRxiv2025

Large-scale phenotyping and comparative genomics reveal genetic features of Listeria persistence in epithelial cells

During infection in epithelial cells, after invading the cytosol, multiplying, and spreading, Listeria monocytogenes (Lm) ceases to produce ActA and becomes trapped in Listeria-containing vacuoles (LisCVs). These persistence acidic vacuoles harbor bacterial subpopulations that resist to stress in a metabolically dormant state. Although LisCVs have been proposed as a hallmark of Lm persistence in epithelial cells, their prevalence across strains and the bacterial factors underlying their formation remain uncharacterized. Given the significant genetic diversity within the species, it is important to consider this variability when studying persistence phenotype. Therefore, we screened over one hundred Lm isolates spanning two major evolutionary lineages and belonging to 23 clonal complexes from diverse ecological origins. Strikingly, the vast majority of strains, including both clinical and environmental isolates, were capable of forming LisCVs, suggesting that vacuolar persistence is a widespread and conserved feature of Lm pathogenesis. Nevertheless, among the group of hypo-virulent strains mostly associated with food and carrying a truncated InlA, we identified four isolates with an altered persistence phenotype. Two of them showed defects in the early stages of infection and carried mutations in key virulence genes (hly and gshF). The other two, instead, were specifically affected in the persistence by showing a reduced ability to form LisCVs. Comparative genomic analysis revealed that a mutation in the folP gene, required for folate biosynthesis, was responsible for impaired persistence. Live-imaging and microscopy analysis highlighted a reduced bacterial motility and intercellular spreading of the folP mutant, although the level of ActA at the bacterial surface was increased. Together, our work identifies folate biosynthesis as a critical metabolic pathway governing Lm persistence by regulating ActA levels and activity. Downregulation of ActA at the bacterial surface is therefore a crucial event for the establishment of the intracellular persistent niche during long-term infection of epithelial cells. Author SummaryLong regarded as a strictly cytosolic pathogen, Listeria monocytogenes is now revealing a dual lifestyle that includes intracellular vacuoles. Recent evidence shows that in epithelial cells this bacterium can enter a dormant state within acidic vacuoles, termed LisCVs, potentially contributing to silent carriage and antibiotic treatment failure. Here, we reveal that vacuolar persistence is a widespread and conserved feature among diverse Listeria strains. Strikingly, we identify folate metabolism as a key regulator of this phenotypic switch, linking metabolic cues to the shutdown of bacterial motility. Our findings uncover a novel connection between central metabolism and intracellular niche adaptation, shedding new light on how Listeria survives and hides within the host.

microbiology↗

bioRxiv2024

Bacterial strain nomenclature in the genomic era: Life Identification Numbers using a gene-by-gene approach

Unified strain taxonomies are needed for the epidemiological surveillance of bacterial pathogens and international communication in microbiological research. Core genome multilocus sequence typing (cgMLST) holds great promise for standardized high-resolution strain genotyping. However, this approach faces challenges including classification instability and disconnection of new nomenclature from widely adopted classical MLST identifiers. This essay discusses the cgMLST-based Life Identification Number (LIN) method, recently proposed as a stable multilevel strain taxonomy system applicable to most bacterial pathogens. We describe how LIN codes are implemented and used in practice for precise strain definitions and epidemiological tracking. Glossary Multilocus sequence typing (MLST)A genotyping method applied mostly to microbial strains to study population structure and epidemiology, based on comparing the nucleotide sequences of a small number (typically seven) of housekeeping protein-coding genes. In MLST, allele numbers are assigned to each sequence variant (allele) of a given gene. The MLST genotype of a bacterial strain is defined by the combination of the allele numbers observed at the genes that are included in the genotyping scheme. A sequence type (ST) is assigned to each unique combination of alleles, called an MLST profile. MLST was invented in 1998 and became a de-facto standard taxonomy of bacterial strains, albeit at low resolution. Core genome MLSTAn extension of MLST that analyzes sequence variation across hundreds to thousands of conserved (core) genes, shared by all strains of a species, providing higher resolution typing for genomic epidemiology and evolutionary studies. cgMLST schemes typically comprise 2000 to 4000 genes, depending on the genome size and genetic variation (in terms of presence/absence of genes) within bacterial species. A core genome sequence type (cgST) can be assigned to unique cgMLST profiles, i.e., a unique combination of cgMLST allelic numbers. Whole Genome Sequencing (WGS)A method that determines the complete DNA sequence of an organisms genome in a single process, providing comprehensive information for comparative genetic analyses based on cgMLST or other analytic methods. Single Nucleotide Polymorphisms (SNPs)Variations at a single base position in the DNA sequence among individuals isolates, strains or species, used as genetic markers for studying for example, evolutionary relationships or strain identity. Average nucleotide identity (ANI)A measure of genomic similarity between two organisms, calculated as the average percentage of identical nucleotides in orthologous genomic regions; commonly used to assess species-level relatedness in prokaryotes. TaxonomyHere, we apply the word taxonomy to bacterial strains as a system of classifying, naming and identifying strains based on shared genetic characteristics as defined by e.g., cgMLST.

microbiology↗

bioRxiv2023

Default Values And Read-Across Proposal For Dermal Absorption Based On Human Skin In Vitro Studies Dataset With Pesticides

The skin is the main route of exposure to plant protection products for operators, workers, residents, and bystanders. Assessing dermal absorption is key for evaluating pesticide exposure. The initial approach to risk assessment involves using default dermal absorption values or applying read-across data from experimental results from different formulations. In this way, to support non-dietary pesticide risk assessment focused but not limited to Brazil, this project evaluated 759 GLP-compliant in vitro human skin dermal absorption studies covering 25 formulation types and 248 active substances at multiple concentrations using interpretable machine learning techniques. Bayesian Additive Regression Trees - BART method indicated that Log Pow and molecular weight have the highest importance when predicting dermal absorption; both parameters exhibit moderate interaction uncertainty within each other and with formulation groups water-based and organic-solvent based and with tested form (concentrates or dilutions). The default values for each formulation group were determined using the upper bound of a non-parametric confidence interval for a specified quantile, with calculations conducted via bootstrapping methods; the proposed values correspond to the upper limit of the 95% confidence interval for the 95th percentile: for concentrates, 10% for organic-solvent based, 4% for water-based and 3% for solid formulations. For dilutions, 42% for organic-solvent based, 37% for water-based and 39% for solid formulations. Organic-solvent based dermal absorption values from experimental data can be used as conservative surrogates for solid and water-based formulations. When no experimental data is available for higher spray dilutions of a given formulation type, a pro-rated correction is proposed to a 2 to 5-fold concentration difference, limited to the respective formulation group default value.

pharmacology and toxicology↗

bioRxiv2019

AB_SA: Tracing the source of bacterial strains based on accessory genes. Application to Salmonella Typhimurium environmental strains

The partitioning of pathogenic strains isolated in environmental or human cases to their original source is challenging. The pathogens usually colonize multiple animal hosts, including livestock, which contaminate food-producing and environment (e.g. soil and water), posing additional public health burden and major challenges in the identification of the source. Genomic data opens new opportunities for the development of statistical models aiming to infer the likely source of pathogen contamination. Here, we propose a computationally fast and efficient multinomial logistic regression (MLR) source attribution classifier to predict the animal source of bacterial isolates based on \"source-enriched\" loci extracted from the accessory-genome profiles of a pangenomic dataset. Depending on the accuracy of the models self-attribution step, the modeler selects the number of candidate accessory genes that better fit the model for calculating the likelihood of (source) category membership. The accessory genes-based source attribution (AB_SA) method was applied on a dataset of strains of Salmonella Typhimurium and its monophasic variants (S. 1,4,[5],12:i:-). The model was trained on 69 strains with known animal source categories (i.e., poultry, ruminant, and pig). The AB_SA method helped to identify eight genes as predictors among the 2,802 accessory genes. The self-attribution accuracy was 80%. The AB_SA model was then able to classify 25 over 29 S. Typhimurium and S. 1,4,[5],12:i:-isolates collected from the environment (considered as unknown source) into a specific category (i.e., animal source), with more than 85% of probability. The AB_SA method herein described provides a user-friendly and valuable tool to perform source attribution studies in few steps. AB_SA is written in R and freely available at https://github.com/lguillier/AB_SA.\n\nAuthor NotesAll supporting data, code, and protocols have been provided within the article and through supplementary data files.\n\nSupplementary material is available with the online version of this article.\n\nAbbreviationsAB_SA, accessory-based source attribution; MLR, multinomial logistic regression; SNPs, single nucleotide polymorphisms; GFF, general feature format; AIC, Akaike information criteria.\n\nData SummaryO_LIThe AB_SA model is written in R, open-source and freely available Github under the GNU GPLv3 licence (https://github.com/lguillier/AB_SA).\nC_LIO_LIAll sequencing reads used to generate the assemblies analyzed in this study have been deposited in the European Nucleotide Archive (ENA) (http://www.ebi.ac.uk/ena) under project number PRJEB16326. Genome metadata and ENA run accession ID for all the assemblies are reported in the supplementary material.\nC_LI\n\nImpact StatementThis article describes AB_SA (\"Accessory-Based Source Attribution method\"), a novel approach for source attribution based on \"source enriched\" accessory genomics data and unsupervised multinomial logistic regression. We demonstrate that the AB_SA method enables the animal source prediction of large-scale datasets of bacterial populations through rapid and easy identification of source predictors from the non-core genomic regions. Herein, AB_SA correctly self-attribute the animal source of a set of S. Typhimurium and S. 1,4,[5],12:i:- isolates and further classifies the 84% of strains contaminating natural environments in the pig category (with high probability ranging between [~]85 and [~]99%).

microbiology↗

bioRxiv2018

Rapid Identification of Stable Clusters in Bacterial Populations Using the Adjusted Wallace Coefficient

Whole-genome sequencing (WGS) of microbial pathogens has become an essential part of modern epidemiological investigations. Although WGS data can be analyzed using a number of different approaches, such as traditional phylogenetic methods, a critical requirement for global systems for pathogen surveillance is the development of approaches for transforming sequence data into WGS-based subtypes, which creates a nomenclature that describes their higher-order relationships to one another. To this end, subtype similarity thresholds are needed to define clusters of subtypes representing lineages of interest. WGS-based subtyping presents a challenge since both the addition of novel genome sequences and small adjustments in similarity thresholds can have a dramatic impact on cluster composition and stability. We present the Neighbourhood Adjusted Wallace Coefficient (nAWC), a method for evaluating cluster stability based on computing cluster concordance between neighbouring similarity thresholds. The nAWC can be used to identify areas in in which distance thresholds produce robust clusters. Using datasets from Salmonella enterica and Campylobacter jejuni, representing strongly and weakly clonal bacterial species respectively, we show that clusters generated using such thresholds are both stable and reflect basic units in their overall population structure. Our results suggest that the nAWC could be useful for defining robust clusters compatible with nomenclatures for global WGS-based surveillance networks, which require stable clusters to be defined that both harness the discriminatory power of WGS data while allowing for long-term tracking of strains of interest.

genomics↗