Biology subjects

Coll, F.

Publications and source records attributed to Coll, F..

6 recordsLinked to original sources

bioRxiv2026

Accounting for allelic diversity and multicopy gene detection improves the accuracy of antibiotic resistance genotypic determination

BackgroundGenomic prediction of antimicrobial resistance (AMR) relies on the accurate detection of resistance genes or allelic variants of core genes from raw or assembled genomes sequences. For several bacterial species and antibiotics, AMR genotype-phenotype discrepancies are common, indicating that important sources of error remain unresolved. For Enterococcus faecium, we focused on identifying the sources of discrepancies for tetracycline resistance, for which genotypic detection had shown particularly low accuracy. We investigated the effect of structural variation in antibiotic resistance genes (ARGs)--including gene duplications, truncations, interruptions, and mixed configurations of complete and partial gene copies-- as a source of genotype-phenotype discrepancies from short{square}read data. We conduct further extended investigations to other antibiotic families and into another bacterial species: Escherichia coli. MethodsWe analyzed collections of E. faecium and E. coli genomes, integrating high{square}quality complete assemblies, simulated Illumina short reads, and matched AMR phenotypic data. The integrity, copy number, and allelic diversity of ARGs were examined for multiple antibiotic classes, and their impact on ARG detection and accuracy of AMR determination was assessed using several commonly used bioinformatic tools (SRST2, ARIBA and AMRFinderPlus). ResultsFor E. faecium, after ruling out the effect of specific tet allelic variants on tetracycline susceptibility, we found that the integrity and copy number of tet(M) had a major effect on detection accuracy. Duplicated and incomplete ARGs are also common in E. faecium genomes, particularly for macrolides (erm(B)) and aminoglycosides (ant(6)-Ia and aph(3)-IIIa). In E. coli, similar patterns were observed for tet(A), erm(B) and aminoglycoside{square}associated genes (aph(3{square})-IIIa and ant(6)-Ia). Across ARGs in both species, short-read mapping methods wrongly reported interrupted genes as complete in some instances, while assembly{square}based methods often failed to resolve complete copies of duplicated genes. Detection accuracy improved when tools were adapted to account for gene integrity and when extended AMR databases incorporating species{square}specific alleles were included. ConclusionsOur findings reveal that bioinformatic limitations in dealing with ARG copy number and completeness, and in accounting for allelic variation, underly a substantial source of genotype-phenotype errors, highlighting the need for improved AMR databases and bioinformatic tools that consider these factors to achieve reliable genomic prediction of AMR.

bioinformatics↗

bioRxiv2025

In host mutational adaptation of Mycobacterium tuberculosis complex strains

BackgroundTuberculosis (TB) is the second leading cause of death from an infectious disease worldwide. Mycobacterium tuberculosis complex (MTBC), the causative bacteria of TB, is becoming increasingly resistant to anti-TB drugs, resulting in poorer treatment outcomes. The mutations arising in MTBC strains during infection provide a record of bacterial diversification and adaptation, and indirect evidence on the selective pressures and conditions that MTBC encountered in vivo, such as those exerted by the immune system and antibiotic therapies. MethodsWe conducted a meta-analysis of MTBC sequenced strains with multiple clinical isolates sequenced from the same patient, from published studies and TB Portals. We applied stringent genomic QC criteria to keep only clonal isolates and applied robust genomic pipelines to identify mutations arising de novo during infection. A convergent evolution approach was applied to identify heavily mutated genes, operons, and candidate promoter across strains of multiple patients. We estimated the frequency of drug resistance acquisition during treatment for the subset of patients with available drug treatment data. ResultUsing 5,899 high-quality genomes from 1,056 TB patients after ensuring clonality of isolate genomes we identified limited within-host diversity was identified including 3,296 fixed mutations across 501 patients. A total of 21 genes, 25 operons and 27 promoter regions were statistically enriched by mutations compared to the rest of the genome, and additional loci with established or plausible adaptive roles approaching statistical significance. Significantly, this included multiple loci known to be involved in resistance to first-, second-, and last-line anti-TB drugs. Fluoroquinolone resistance was acquired more frequently during treatment than resistance to any other anti-TB drug. Previously reported candidate drug-resistance and -tolerance genes (prpR, Rv2571c, fadD11, helY, ndhA, Rv0139, fadE5, and mce1 operon) were also identified. Genes encoding regulators (phoR, whiB6 and mycP1) and effectors (espK and eccE1) of the virulence ESX-1 locus were frequently mutated in host. ConclusionsHere we analysed a large dataset of MTBC within-host genetic diversity. We show that frequently mutated genes in MTBC during infection reveal known and biologically plausible in host adaptations, predominantly associated drug resistance, but also in genes involved in pathogenesis. The higher resistance acquisition rate observed for fluoroquinolones may have important clinical relevance. We reveal a list of candidate loci which will require mechanistic characterisation and whose impact on disease progression will need to be investigated.

genomics↗

bioRxiv2023

The mutational landscape of Staphylococcus aureus during colonisation

Staphylococcus aureus is an important human pathogen but is primarily a commensal of the human nose and skin. Survival during colonisation is likely one of the major drivers of S. aureus evolution. Here we use a genome-wide mutation enrichment approach to analyse a genomic dataset of 3,060 S. aureus isolates from 791 individuals to show that despite limited within-host genetic diversity, an excess of protein-altering mutations can be found in genes encoding key metabolic pathways, in regulators of quorum-sensing and in known antibiotic targets. Nitrogen metabolism and riboflavin synthesis are the metabolic processes with strongest evidence of adaptation. Further evidence of adaptation to nitrogen availability was revealed by enrichment of mutations in the assimilatory nitrite reductase and urease, including mutations that enhance growth with urea as the sole nitrogen source. Inclusion of an additional 4,090 genomes from 802 individuals revealed eight additional genes including sasA/sraP, pstA, and rsbU with signals adaptive variation that warrant further characterisation. Our study provides the most comprehensive picture to date of the heterogeneity of adaptive changes that occur in the genomes of S. aureus during colonisation, revealing the likely importance of nitrogen metabolism, loss of quorum sensing and antibiotic resistance for successful human colonisation.

genomics↗

bioRxiv2018

One Health genomic surveillance of Escherichia coli demonstrates distinct lineages and mobile genetic elements in isolates from humans versus livestock

Livestock have been proposed as a reservoir for drug-resistant Escherichia coli that infect humans. We isolated and sequenced 431 E. coli (including 155 ESBL-producing isolates) from cross-sectional surveys of livestock farms and retail meat in the East of England. These were compared with the genomes of 1517 E. coli associated with bloodstream infection in the United Kingdom. Phylogenetic core genome comparisons demonstrated that livestock and patient isolates were genetically distinct, indicating that E. coli causing serious human infection do not directly originate from livestock. By contrast, we observed highly related isolates from the same animal species on different farms. Analysis of accessory (variable) genomes identified a virulence cassette associated previously with cystitis and neonatal meningitis that was only present in isolates from humans. Screening all 1948 isolates for accessory genes encoding antibiotic resistance revealed 41 different genes present in variable proportions of humans and livestock isolates. We identified a low prevalence of shared antimicrobial resistance genes between livestock and humans based on analysis of mobile genetic elements and long-read sequencing. We conclude that in this setting, there was limited evidence to support the suggestion that antimicrobial resistant pathogens that cause serious infection in humans originate from livestock.\n\nImportanceThe increasing prevalence of E. coli bloodstream infections is a serious public health problem. We used genomic epidemiology in a One Health study conducted in the East of England to examine putative sources of E. coli associated with serious human disease. E. coli from 1517 patients with bloodstream infection were compared with 431 isolates from livestock farms and meat. Livestock-associated and bloodstream isolates were genetically distinct populations based on core genome and accessory genome analyses. Identical antimicrobial resistance genes were found in livestock and human isolates, but there was little overlap in the mobile elements carrying these genes. In addition, a virulence cassette found in humans isolates was not identified in any livestock-associated isolate. Our findings do not support the idea that E. coli causing invasive disease or their resistance genes are commonly acquired from livestock.

genomics↗

bioRxiv2018

rPinecone: Define sub-lineages of a clonal expansion via a phylogenetic tree

The ability to distinguish between pathogens is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances, remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this program was demonstrated using genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically-confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes.\n\nDATA SUMMARYO_LISource code for rPinecone is available on GitHub under the open source licence GNU GPL 3; (url: https://github.com/alexwailan/rpinecone).\nC_LIO_LINewick format files for both phylogenetic trees have been deposited in Figshare; (url: https://doi.org/10.6084/m9.figshare.7022558)\nC_LIO_LIGeographical analysis of the S. Typhi Dataset using Microreact is available at https://microreact.org/project/r1IqkrN1X.\nC_LIO_LIAccession numbers, meta data and sample lineage results of both datasets used in this paper are listed in the supplementary tables.\nC_LI\n\nI/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. {boxtimes}\n\nIMPACT STATEMENTWhole genome sequence data from bacterial pathogens is increasingly used in the epidemiological investigation of infectious disease, both in outbreak and endemic situations. However, distinguishing bacterial species which are both very similar and which are likely to come from a small geographical and temporal range presents a major technical challenge for epidemiologists. rPinecone was designed to address this challenge and utilises phylogenetic data to define lineages within bacterial populations that have limited variation. This approach is therefore of great interest to epidemiologists as it adds a further level of clarity above and beyond that which is offered by existing approaches which have not been designed to consider bacterial isolates containing variation that only transiently exist, but which is epidemiologically informative. rPinecone has the flexibility to be applied to multiple pathogens and has direct application for investigations of clinical outbreaks and endemic disease to understand transmission dynamics or geographical hotspots of disease.

genomics↗

bioRxiv2017

Population-based analysis of ocular Chlamydia trachomatis in trachoma-endemic West African communities identifies genomic markers of disease severity

Chlamydia trachomatis (Ct) is the most common infectious cause of blindness and bacterial sexually transmitted infection worldwide. Using Ct whole genome sequences obtained directly from conjunctival swabs, we studied Ct genomic diversity and associations between Ct genetic polymorphisms with ocular localization and disease severity in a treatment-naive trachoma-endemic population in Guinea Bissau, West Africa. All sequences fall within the T2 ocular clade phylogenetically. This is consistent with the presence of the characteristic deletion in trpA resulting in a truncated non-functional protein and the ocular tyrosine repeat regions present in tarP associated with ocular tissue localization. We have identified twenty-one Ct non-synonymous single nucleotide polymorphisms (SNPs) associated with ocular localization, including SNPs within pmpD (OR=4.07, p*=0.001) and tarP (OR=0.34, p*=0.009). Eight SNPs associated with disease severity were found in yjfH (rlmB) (OR=0.13, p*=0.037), CTA0273 (OR=0.12, p*=0.027), trmD (OR=0.12, p*=0.032), CTA0744 (OR=0.12, p*=0.041), glgA (OR=0.10, p*=0.026), alaS (OR=0.10, p*=0.032), pmpE (OR=0.08, p*=0.001) and the intergenic region CTA0744-CTA0745 (OR=0.13, p*=0.043). This study demonstrates the extent of genomic diversity within a naturally circulating population of ocular Ct, and the first to describe novel genomic associations with disease severity. These findings direct investigation of host-pathogen interactions that may be important in ocular Ct pathogenesis and disease transmission.

genomics↗