Biology subjects

Galardini, M.

Publications and source records attributed to Galardini, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Development of a stable microbial community for the study of plasmid-mediated antimicrobial resistance in a continuous culturing device

Horizontal gene transfer (HGT) is a major contributor to the spread of antimicrobial resistance (AMR) in microbial communities, particularly through conjugative plasmids. The dynamics of the spread of these plasmids in a susceptible microbial community requires a defined and controllable in vitro system, which is currently lacking from existing laboratory evolution systems. Here we describe the development of TriComm, an engineered microbial community of three strains with complementary amino acid auxotrophies, maintained in continuous culture under real-time optical and fluorescence monitoring. We show that two conjugative plasmids carrying resistance genes (blaOXA-48 and mcr-1) generally rescued TriComm from collapse under antimicrobial treatment, and that this protection was dependent on conjugative transfer. Community composition remained stable across most conditions, including after the AMR plasmid had spread through the population. Through mathematical modeling we predict that modulating both drug efficacy and conjugation rate can lead to the collapse of the community, suggesting potential strategies to limit the spread of AMR via HGT.

microbiology↗

bioRxiv2025

Cis non-coding genetic variation drives gene expression changes in the E. coli and P. aeruginosa pangenomes

Bacteria use gene regulation to dynamically adapt to changes in their environment, including resistance to stress and the occupation of new niches. Gene expression is known to vary within a species pangenome, but the extent to which these changes could be explained by genetic variants in cis non-coding regions has so far been poorly investigated. Statistical genetics offers a hypothesis-free approach to this problem, as opposed to mechanistic models, which can be used only for reference isolates that are not representative of the whole species. In this study, we assembled two genomic and transcriptomic datasets for Escherichia coli (N=117) and Pseudomonas aeruginosa (N=413) and identified associations between genetic variants in cis non-coding regions and recorded gene expression variation. We identified at least one associated variant in up to 39% of the tested genes in both species. We partly validated the associations in-silico and in-vitro for E. coli, reinforcing the difficulty of identifying a single mechanism generating gene expression diversity. We then investigated the relevance of non-coding variants in explaining the variability in antimicrobial resistance in both species using two additional publicly available datasets, identifying a large number of these variants across antimicrobial compounds. This work confirms the role of genetic variation in often overlooked regions of bacterial genomes in influencing molecular and clinically relevant phenotypes.

microbiology↗

bioRxiv2024

Pervasive phosphorylation by phage T7 kinase disarms bacterial defenses

Bacteria and bacteriophages are in a constant arms race to develop bacterial defense and phage counter-defense systems. Currently known phage counter-defense systems are specific to (the activity of) the targeted bacterial defense system. Here, we uncover a mechanism by which the T7 bacteriophage broadly counteracts bacterial defenses using protein phosphorylation. We show that the T7 protein kinase (T7K), which was believed to specifically redirect the function of a few host proteins, is in fact a hyper-promiscuous, dual-specificity kinase enacting a massive wave of phosphorylation on virtually all host and phage proteins during infection. The scale of phosphorylation vastly exceeds the number of previously known phosphorylation events in E. coli, has no sequence motif specificity, and results in a higher proteome-wide phosphorylation density than that of mammalian cells which encode [~] 500 kinases. Stoichiometry analysis of phosphorylation sites revealed a strong bias of T7K activity towards nucleic acid-binding substrates, which we show is mediated by its C-terminal DNA-binding domain. This specificity for highly stoichiometric phosphorylation of nucleic acid-binding proteins enables the deactivation of DNA-targeting or - containing bacterial defense systems. We provide mechanistic insight into how T7K weakens two such defense systems, Retron-Eco9 and DarTG1, through specific phosphorylation events, with single phosphomimetic mutations in key sites of the toxins abolishing defense. Finally, by screening a large collection of E. coli strains, we provide evidence of broad counter-defense capacities for T7K in nature, as strains counteracted contain diverse bacterial defense systems.

microbiology↗

bioRxiv2024

A systematic identification of resistance determinants to antisense antibiotics suggests adaptation strategies dependent on the delivery peptide

The rise of antimicrobial resistance (AMR) among human pathogenic microbes is a serious threat to global health, calling for the development of novel treatment strategies. Antibiotics based on programmable antisense oligomers (asobiotics) offer an attractive solution to the "arms-race", as their specificity can be quickly updated and tailored to target resistant bacteria. In order to understand the genetic architecture of resistance to asobiotics, we employed laboratory evolution assays to identify mutations that decrease susceptibility to antisense peptide nucleic acid (PNA) against four major gram-negative pathogens: Escherichia coli, Klebsiella pneumoniae, Salmonella enterica, and Pseudomonas aeruginosa. We observed that the reduction in susceptibility upon asobiotics treatment was dependent on the specific cell penetrating peptide (CPP) being conjugated to the PNAs, suggesting that reduced uptake is a common adaptation strategy only against the (KFF)3-K CPP. We in fact observed that sbmA was frequently mutated in all tested species when treated with (KFF)3-K conjugated PNAs. We further identified mutations related to translation, peptide transport and cell envelope, which provide new hypotheses on cellular response to CPP-PNAs conjugates. Furthermore, for (RXR)4XB-acpP we observed a modest increase in resistance only when mutations in the PNA binding site were induced, which could easily be bypassed by changing the PNA sequence. These findings indicate that the specific identity of the CPP used plays a key role in determining its robustness against the evolution of resistance, and that laboratory evolution can illuminate the remaining gaps in our knowledge on the mechanisms of action of asobiotics.

microbiology↗

bioRxiv2024

microGWAS: a computational pipeline to perform large scale bacterial genome-wide association studies

Identifying genetic variants associated with bacterial phenotypes, such as virulence, host preference, and antimicrobial resistance, has great potential for a better understanding of the mechanisms involved in these traits. The availability of large collections of bacterial genomes has made genome-wide association studies (GWAS) a common approach for this purpose. The need to employ multiple software tools for data pre- and post-processing limits the application of these methods by experienced bioinformaticians. To address this issue, we have developed a pipeline to perform bacterial GWAS from a set of assemblies and annotations, with multiple phenotypes as targets. The associations are run using five sets of genetic variants: unitigs, gene presence/absence, rare variants (i.e. gene burden test), gene cluster specific k-mers, and all unitigs jointly. All variants passing the association threshold are further annotated to identify overrepresented biological processes and pathways. The results can be further augmented by generating a phylogenetic tree and by predicting the presence of antimicrobial resistance and virulence associated genes. We tested the microGWAS pipeline on a previously reported dataset on E. coli virulence, successfully identifying the causal variants, and providing further interpretation on the association results. The microGWAS pipeline integrates the state-of-the-art tools to perform bacterial GWAS into a single, user-friendly, and reproducible pipeline, allowing for the democratization of these analyses. The pipeline can be accessed, together with its documentation, at: https://github.com/microbial-pangenomes-lab/microGWAS.

bioinformatics↗

bioRxiv2024

Uncovering nitroxoline activity spectrum, mode of action and resistance across Gram-negative bacteria

Nitroxoline is a bacteriostatic quinoline antibiotic, considered a metal chelator inhibiting the activity of RNA-polymerase1. Its clinical indications are limited to uncomplicated urinary tract infections (UTIs), with a clinical susceptibility breakpoint only available for Escherichia coli2. By testing > 1,000 clinical isolates, here we demonstrate a much broader activity spectrum and species-specific bactericidal activity, including multidrug-resistant Gram-negative bacteria for which therapeutic options are limited due to resistance. By combining systematic genetic and proteomic approaches with direct measurement of intracellular metals, we dissect nitroxoline perturbation of metal homeostasis and unveil additional effects on bacterial physiology. We show that nitroxoline affects outer membrane integrity, synergizing with large-scaffold antibiotics and resensitizing colistin-resistant Enterobacteriaceae in vitro and in vivo. We further characterise resistance mechanisms across E. coli, Acinetobacter baumannii and Klebsiella pneumoniae, recapitulating known E. coli resistance determinants and uncovering novel and conserved mechanisms across species, demonstrating their common effect on nitroxoline efflux.

microbiology↗

bioRxiv2023

Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections

The emergence and rapid spread of the SARS-CoV-2 virus has highlighted the importance of genomic epidemiology in understanding the evolution of pathogens and for guiding public health interventions. In particular, the Omicron variant underscored the role of epistasis in the evolution of lineages with both higher infectivity and immune escape, and therefore the necessity to update surveillance pipelines to detect them as soon as they emerge. In this study we applied a method based on mutual information (MI) between positions in a multiple sequence alignment (MSA), which is capable of scaling up to millions of samples. We showed how it could reliably predict known experimentally validated epistatic interactions, even when using as little as 10,000 sequences, which opens the possibility of making it a near real-time prediction system. We tested this possibility by modifying the method to account for sample collection date and applied it retrospectively to MSAs for each month between March 2020 and March 2023. We could detect a cornerstone epistatic interaction in the Spike protein between codons 498 and 501 as soon as 6 samples with a double mutation were present in the dataset, thus demonstrating the methods sensitivity. Lastly we provide examples of predicted interactions between genes, which are harder to test experimentally and therefore more likely to be overlooked. This method could become part of continuous surveillance systems tracking present and future pathogen outbreaks.

microbiology↗

bioRxiv2023

Improved interpretability of bacterial genome-wide associations using gene cluster centric k-mers

The wide adoption of bacterial genome sequencing and encoding both core and accessory genome variation using k-mers has allowed bacterial genome wide association studies (GWAS) to identify genetic variants associated with relevant phenotypes such as those linked to infection. Significant limitations still remain as far as the interpretation of association results is concerned, which affects the wider adoption of GWAS methods on microbial data sets. We have developed a simple computational method (panfeed) that explicitly links each k-mer to their gene cluster at base resolution level, which allows us to avoid biases introduced by a global de Bruijn graph as well as more easily map and annotate associated variants. We tested panfeed on two independent data sets, correctly identifying previously characterized causal variants, which demonstrates the precision of the method, as well as its scalable performance. panfeed is a command line tool written in the python programming language and available at https://github.com/microbial-pangenomes-lab/panfeed.

bioinformatics↗

bioRxiv2023

ChemGAPP; A Package for Chemical Genomics Analysis and Phenotypic Profiling.

High-throughput chemical genomic screens produce informative datasets, providing valuable insights into unknown gene function on a genome-wide level. However, there is currently no comprehensive analytic package publicly available. We developed and benchmarked ChemGAPP to bridge this gap. ChemGAPP allows integration of various steps in a streamlined and user-friendly format, including rigorous quality control measures to curate screening data. ChemGAPP provides three sub-packages for different chemical-genomic screens: ChemGAPP Big for handling large-scale high-throughput screens; ChemGAPP Small, designed for small-scale screen analysis and ChemGAPP GI for genetic interaction screen analysis. ChemGAPP is available at https://github.com/HannahMDoherty/ChemGAPP.

bioinformatics↗

bioRxiv2023

The bacterial genetic determinants of Escherichia coli capacity to cause bloodstream infections in humans

Escherichia coli is both a highly prevalent commensal and a major opportunistic pathogen causing bloodstream infections (BSI). A systematic analysis characterizing the genomic determinants of extra-intestinal pathogenic vs. commensal isolates in human populations, which could inform mechanisms of pathogenesis, diagnostics, prevention and treatment is still lacking. We used a collection of 1282 BSI and commensal E. coli isolates collected in France over a 17-year period (2000-2017) and we compared their pangenomes, genetic backgrounds (phylogroups, STs, O groups), presence of virulence-associated genes (VAGs) and antimicrobial resistance genes, finding significant differences in all comparisons between commensal and BSI isolates. A machine learning linear model trained on all the genetic variants derived from the pangenome and controlling for population structure reveals similar differences in VAGs, discovers new variants associated with pathogenicity (capacity to cause BSI), and accurately classifies BSI vs. commensal strains. Pathogenicity is a highly heritable trait, with up to 69% of the variance explained by bacterial genetic variants. Lastly, complementing our commensal collection with an older collection from 1980, we predict that pathogenicity increased steadily from 23% in 1980 to 46% in 2010. Together our findings imply that E. coli exhibit substantial genetic variation contributing to the transition between commensalism and pathogenicity and that this species evolved towards higher pathogenicity.

microbiology↗

bioRxiv2022

High pathogenicity island, aer and sit operons: a "menage a trois" in Escherichia coli extra-intestinal virulence

The intrinsic virulence of extra-intestinal pathogenic Escherichia coli is attributed to numerous chromosome and/or plasmid-borne virulence associated genes (VAGs), encoding diverse functions as adhesins, toxins, protectins and iron capture systems, which occur in specific genetic backgrounds. Little is however known on their respective contribution to virulence. Here, by analyzing genomes of 232 sequence type complex (STc) 58 strains, we show that virulence quantified in a mouse model of sepsis emerged in a sub-group of STc58 due to the presence of the siderophore encoding high-pathogenicity island (HPI). When extending our analysis to 370 Escherichia strains we show that full virulence is associated with the presence of the aer or sit operons, in addition to the HPI. The prevalence of these operons, their co-occurrence and genomic location depend on the strain phylogeny. Selection of lineage-dependent specific associations of VAGs argues for strong epistatic interactions shaping the emergence of virulence in E. coli.

microbiology↗

bioRxiv2020

Bacterial retrons encode tripartite toxin/antitoxin systems

Retrons are genetic retroelements, commonly found in bacterial genomes and recently repurposed as genome editing tools. Their encoded reverse transcriptase (RT) produces a multi-copy single-stranded DNA (msDNA). Despite our understanding of their complex biosynthesis, the function of msDNAs and therefore, the physiological role of retrons has remained elusive. We establish that the retron-Sen2 in Salmonella Typhimurium encodes a toxin, which we have renamed as RcaT (Retron cold-anaerobic Toxin). RcaT is activated when msDNA biosynthesis is perturbed and its toxicity is higher at ambient temperatures or during anaerobiosis. The RT and msDNA form together the antitoxin unit, with the RT binding RcaT, and the msDNA enabling the antitoxin activity. Using another E. coli retron, we establish that this toxin/antitoxin function is conserved, and that RT-toxin interactions are cognate. Altogether, retrons constitute a novel family of tripartite toxin/antitoxin systems.

microbiology↗

bioRxiv2019

Towards a systematic map of the functional role of protein phosphorylation

Phosphorylation is a critical post-translational modification involved in the regulation of almost all cellular processes. However, less than 5% of thousands of recently discovered phosphorylation sites have a known function. Here, we devised a chemical genetic approach to study the functional relevance of phosphorylation in S. cerevisiae. We generated 474 phospho-deficient mutants that, along with the gene deletion library, were screened for fitness in 102 conditions. Of these, 42% exhibited growth phenotypes, suggesting these phosphosites are likely functional. We inferred their function based on the similarity of their growth profiles with that of gene deletions, and validated a subset by thermal proteome profiling and lipidomics. While some phosphomutants showed loss-of-function phenotypes, a higher fraction exhibited phenotypes not seen in the corresponding gene deletion suggestive of a gain-of-function effect. For phosphosites conserved in humans, the severity of the yeast phenotypes is indicative of their human functional relevance. This study provides a roadmap for functionally characterizing phosphorylation in a systematic manner.

systems biology↗

bioRxiv2019

Improved inference and prediction of bacterial genotype-phenotype associations using pangenome-spanning regressions

Discovery of influential genetic variants and prediction of phenotypes such as antibiotic resistance are becoming routine tasks in bacterial genomics. Genome-wide association study (GWAS) methods can be applied to study bacterial populations, with a particular emphasis on alignment-free approaches, which are necessitated by the more plastic nature of bacterial genomes. Here we advance bacterial GWAS by introducing a computationally scalable joint modeling framework, where genetic variants covering the entire pangenome are compactly represented by unitigs, and the model fitting is achieved using elastic net penalization. In contrast to current leading GWAS approaches, which test each genotype-phenotype association separately for each variant, our joint modelling approach is shown to lead to increased statistical power while maintaining control of the false positive rate. Our inference procedure also delivers an estimate of the narrow-sense heritability, which is gaining considerable interest in studies of bacteria. Using an extensive set of state-of-the-art bacterial population genomic datasets we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. We expect that these advances will pave the way for the next generation of high-powered association and prediction studies for an increasing number of bacterial species.

microbiology↗

bioRxiv2019

Major role of the high-pathogenicity island (HPI) in the intrinsic extra-intestinal virulence of Escherichia coli revealed by a genome-wide association study

The genus Escherichia is composed of several species and cryptic clades, including E. coli, which behave as a vertebrate gut commensal, but also as an opportunistic pathogen involved in both diarrheic and extra-intestinal diseases. To characterize the genetic determinants of extra-intestinal virulence within the genus, we carried out an unbiased genome-wide association study (GWAS) on 370 commensal, pathogenic and environmental strains representative of the Escherichia genus phylogenetic diversity and including E. albertii (n=7), E. fergusonii (n=5), Escherichia clades (n=32) and E. coli (n=326), tested in a mouse model of sepsis. We found that the high-pathogenicity island (HPI), a [~]35 kbp gene island encoding the yersiniabactin siderophore, is highly associated with death in mice, surpassing other associated genetic factors also related to iron uptake, such as the aerobactin and the sitABCD operons. We validated the association in vivo by deleting key components of the HPI in E. coli strains in two phylogenetic backgrounds, and found that virulence is correlated in E. coli with growth in the presence of various stressors including several antimicrobials, which hints at collateral sensitivities associated with intrinsic virulence. This study points to the major role of iron capture systems in the extra-intestinal virulence of the genus Escherichia and the collateral effects on cell growth of such systems.

microbiology↗

bioRxiv2018

The impact of the genetic background on gene deletion phenotypes in Saccharomyces cerevisiae

Loss-of-function (LoF) mutations associated with disease dont manifest equally in different individuals, a phenomenon known as incomplete penetrance. The impact of the genetic background on incomplete penetrance remains poorly characterized. Here, we systematically assessed the changes in gene deletion phenotypes for 3,786 gene knockouts in four Saccharomyces cerevisiae strains and 38 conditions. We observed 16% to 42% of deletion phenotypes changing between pairs of strains with a small fraction conserved in all strains. Conditions causing higher WT growth differences and the deletion of pleiotropic genes showed above average changes in phenotypes. We further illustrate how these changes affect the interpretation of the impact of genetic variants across 925 yeast isolates. These results show the high degree of genetic background dependencies for LoF phenotypes.

genetics↗

bioRxiv2018

Comprehensive variant effect predictions of single nucleotide variants in model organisms

The effect of single nucleotide variants (SNVs) in coding and non-coding regions is of great interest in genetics. Although many computational methods aim to elucidate the effects of SNVs on cellular mechanisms, it is not straightforward to comprehensively cover different molecular effects. To address this we compiled and benchmarked sequence and structure-based variant effect predictors and we analyzed the impact of nearly all possible amino acid and nucleotide variants in the reference genomes of H. sapiens, S. cerevisiae and E. coli. Studied mechanisms include protein stability, interaction interfaces, post-translational modifications and transcription factor binding sites. We apply this resource to the study of natural and disease coding variants. We also show how variant effects can be aggregated to generate protein complex burden scores that uncover protein complex to phenotype associations based on a set of newly generated growth profiles of 93 sequenced S. cerevisiae strains in 43 conditions. This resource is available through mutfunc, a tool by which users can query precomputed predictions by providing amino acid or nucleotide-level variants.

genomics↗

bioRxiv2018

pyseer: a comprehensive tool for microbial pangenome-wide association studies

SummaryGenome-wide association studies (GWAS) in microbes face different challenges to eukaryotes and have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.\n\nAvailability and Implementationpyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://pyseer.readthedocs.io.\n\nContactjohn.lees@nyumc.org and marco@ebi.ac.uk\n\nSupplementary informationSupplementary data are available online.

bioinformatics↗