Biology subjects

Colles, F. M.

Publications and source records attributed to Colles, F. M..

7 recordsLinked to original sources

bioRxiv2026

A Life Identification Number Barcoding (LIN Code) System for Neisseria meningitidis: high resolution multi-level typing of meningococci.

Neisseria meningitidis is a commensal member of the human oropharyngeal microbiota that can cause devastating invasive meningococcal disease. This genetically and antigenically diverse accidental pathogen has been a paradigm for the study of bacterial population biology. The meningococcus was the first organism for which a seven-locus multi-locus sequence typing (MLST) scheme was developed. With the addition of sequence-based characterisation of antigen genes, molecular typing has been widely employed to inform surveillance and public health interventions. Following the advent and widespread adoption of whole genome sequencing (WGS), precise delineation of variants is possible. Here, a WGS-based Life Identification Number (LIN) code typing scheme is described, providing a multi-resolution nomenclature for understanding meningococcal population diversity and molecular epidemiology. The LIN codes were developed using a set of 6,131 N. meningitidis genomes, comprising up to 200 isolates from each clonal complex (cc) previously described using MLST. Based on cluster-stability analysis and concordance with ccs, thirteen LIN thresholds described the meningococcal population at different levels of resolution. LIN codes and human-readable nicknames consistent with existent nomenclatures were assigned to the N. meningitidis genomes hosted in the PubMLST. Published outbreaks validated the LIN thresholds, illustrating the potential of this genomic tool in public health management.

microbiology↗

bioRxiv2026

A stable, hierarchical LIN code system for Campylobacter jejuni and Campylobacter coli: A unified genomic nomenclature for lineage-level typing and global surveillance.

Campylobacter remains the leading cause of bacterial gastroenteritis worldwide, with C. jejuni accounting for around 90% of infection and C. coli accounting for most of the rest. Seven-locus multilocus sequence typing (MLST) has improved our understanding of host association and population structure, whilst core genome MLST (cgMLST), enables investigation of transmission events at high-resolution. However, the lack of a stable and standardised nomenclature for clustering of cgMLST data has limited reproducibility and long-term comparability between studies. Here we introduce a joint, hierarchical Life Identification Number (LIN) code system that provides reproducible, multi-level genomic identifiers for C. jejuni and C. coli lineages. Using an updated cgMLST v2 scheme (1,142 loci) and globally representative datasets of high-quality genomes selected from over 53,000 assemblies in the Campylobacter PubMLST database (https://pubmlst.org/organisms/campylobacter-jejunicoli), we firstly defined LIN codes on a dataset of 5,664 genomes. Pairwise allelic distances were computed using MSTclust, and 18 nested thresholds were defined through silhouette, adjusted Wallace and adjusted Rand Index (ARI) statistics to capture the population structure from species to outbreak level resolution. The LIN thresholds were then validated using a second dataset of 1,781 genomes from PubMLST and applied to a large water-associated outbreak dataset from New Zealand in 2016, containing clinical and ecological genomes. Further application of LIN codes was demonstrated by analyses of the C. jejuni ST-21 clonal complex and ST-6175 isolates, as well as the broader population structure of C. coli, using data from PubMLST. Across all datasets, LIN clusters were stable, largely monophyletic, and back-compatible with existing nomenclature, accurately distinguishing host-adapted and outbreak-associated lineages. By embedding cgMLST data within a stable and scalable nomenclature, the Campylobacter LIN system delivers consistent, automated genome-to-lineage assignment. This unified framework bridges population genetics and applied surveillance, enabling robust, real-time comparison of Campylobacter isolates across sources, studies, and time. Impact statementHuman cases of Campylobacter worldwide continue unabated. Tracing the source of Campylobacter infection is particularly challenging given the sporadic or multi-source nature of outbreaks, with potential transmission from foodborne, animal or environmental sources. Seven-locus MLST has greatly improved our broad understanding of Campylobacter population structure. However, whilst high-resolution cgMLST alleles and STs themselves do not change, longitudinal cluster analyses of cgMLST data have lacked a stable nomenclature, rendering them unsuitable for robust and comparable surveillance over time. Life Identification Number (LIN) codes provide a solution to this problem, establishing an automated and scalable nomenclature derived directly from cgMLST profiles, that is stable over time. We have implemented a joint C. jejuni and C. coli LIN code scheme in PubMLST, with scripts for real-time lineage assignment. LIN codes are back-compatible with existing MLST nomenclature, and we demonstrate their added practical value for exploring population structure and high-resolution outbreak investigation. LIN codes support surveillance of Campylobacter in a One Health context, by enabling consistent typing at multiple levels across different sources, laboratories and time. Data summary1. The isolate collections used to develop the LIN codes are publicly available and searchable as individual projects on the PubMLST database (https://pubmlst.org). O_LILIN code development (Dataset 1) (n=5,664 isolates, up to 200 isolates per clonal complex) C_LIO_LILIN code validation (Dataset 2) (n=1,781 isolates), up to 50 isolates per clonal complex C_LIO_LIOutbreak investigation (Dataset 3): New Zealand 2016 Havelock North waterborne outbreak, Gilpin et al (n=161 isolates) [1] C_LIO_LIPopulation structure exploration (clonal complex) (Dataset 4): ST-21 complex (n=1800 isolates, up to 100 isolates randomly selected from each country) C_LIO_LIPopulation structure exploration (sequence type) (Dataset 5): ST-6175 (n=321 isolates, genomes with good cgMLST v2 annotation) C_LI 2. The software for LIN code development is publicly available as follows: O_LIMSTclust for pairwise distance matrices https://gitlab.pasteur.fr/GIPhy/MSTclust [2] C_LIO_LIPython script to define LIN codes in a local dataset; (https://gitlab.pasteur.fr/BEBP/LINcoding) C_LIO_LIBIGSdb Perl script to define LIN codes from cgMLST profiles on the PubMLST database; (https://github.com/kjolley/BIGSdb/blob/develop/scripts/maintenance/lincodes.pl) C_LI

microbiology↗

bioRxiv2022

High resolution parallel sequencing reveals multi-strain Campylobacter in broiler chicken flocks testing 'negative' by conventional culture methods: implications for control of Campylobacter infection.

Contaminated chicken meat is a major source of human Campylobacteriosis and rates of infection remain high, despite efforts to limit the colonisation of broiler (meat) chicken flocks on farms. Using conventional testing methods of culture or qPCR, Campylobacter is typically detected amongst broiler flocks from 3 weeks of age, leading to the assumption that infection is introduced horizontally into chicken rearing houses at this time. In this study, we use parallel sequencing of a fragment of the Campylobacter outer membrane protein, encoded by the porA gene, to test for presence of Campylobacter DNA amongst fresh faecal samples collected from broiler flocks aged 23-28 days. Campylobacter DNA was detected in all of the 290 samples tested using the porA target, and in 48% of samples using 16S bacterial profiling, irrespective of whether or not Campylobacter could be detected using conventional qPCR thresholds. A single porAf2 variant was predominant amongst flocks that would be determined to be Campylobacter positive by conventional means, but a diverse pattern was seen amongst flocks that were Campylobacter negative. The ability to routinely detect low levels of Campylobacter amongst broiler flocks at a much earlier age than would conventionally be identified requires a re-examination of how and when biosecurity measures are best applied for live birds. In addition, it may be useful to investigate why single Campylobacter variants proliferate in some broiler flocks and not others.

microbiology↗

bioRxiv2021

Mechanisms of biodiversity between Campylobacter sequence types in a flock of broiler-breeder chickens.

A long-term study of Campylobacter sequence types was used to investigate the competitive framework of the Campylobacter metacommunity, and understand how multiple sequence types simultaneously co-occur in a flock of chickens. A combination of matrix and patch-occupancy models were used to estimate parameters describing the competition, transmission, and mortality of each sequence type. It was found that Campylobacter sequence types form a strong hierarchical framework within a flock of chickens, and occupied a broad spectrum of transmission-mortality trade-offs. Upon further investigation of how biodiversity is thus maintained within the flock, it was found that the demographic capabilities of Campylobacter, such as mortality and transmission, could not explain the broad biodiversity of sequence types seen, suggesting that external factors such as host-bird health and seasonality are important elements in maintaining biodiversity of Campylobacter sequence types.

microbiology↗

bioRxiv2020

Deep sequencing reveals Campylobacter in commercial meat chickens less than 8 days old.

Campylobacter from contaminated poultry meat is a major source of human gastroenteritis worldwide. To date, attempts to control this zoonotic infection with on-farm biosecurity measures have been inconsistent. A cornerstone of these efforts has been the detection of chicken infection with microbiological culture, which typically does not occur until birds are at least 21 days old. Using molecular methods for detecting Campylobacter presence, 16S microbiome analysis and deep sequencing of the Campylobacter porA gene, Campylobacter can be identified at very low levels in most or all flocks fewer than 8 days old. These young chicks exhibit a much greater diversity of porA types than older birds testing positive for Campylobacter by culture or qPCR. This suggests that, as the bacteria multiply sufficiently to be detected by culture methods, one or two strains, as indicated by porA type, dominate the infection. The findings that (i) most young chicks carry some Campylobacter and (ii) not all flocks become Campylobacter positive by culture, suggests that efforts to control infection should concentrate on how to maintain Campylobacter at low levels by the prevention of the overgrowth of single strains, which ultimately leads to the contamination of food.

microbiology↗

bioRxiv2020

A mathematical modelling approach to uncover factors influencing the spread of Campylobacter in a flock of chickens

Despite continued efforts into improving biosecurity protocol, Campylobacter continues to be detected in the majority of commercial chicken flocks across Europe. Using an extensive data set of Campylobacter prevalence within a chicken breeder flock for over a year, multiple Bayesian models are presented to explore the dynamics of the spread of Campylobacter in response to seasonal variation, species-specificity, bird health and total infection prevalence. It was found that birds within the flock varied greatly in their response to bacterial challenge, and that this phenomena had a large impact in the overall prevalence of different species of Campylobacter. Campylobacter jejuni appeared more frequently in the summer, while Campylobacter coli persisted for a longer duration, amplified by the most susceptible birds in the flock. Our study suggests that strains of Campylobacter that appear most frequently likely possess no demographic advantage, but are instead amplified due to the health of the birds that ingest it.

microbiology↗

bioRxiv2019

Domestication of Campylobacter jejuni NCTC 11168

Reference and type strains of well-known bacteria have been a cornerstone of microbiology research for decades. The sharing of well-characterised isolates among laboratories has parallelised research efforts and enhanced the reproducibility of experiments, leading to a wealth of knowledge about trait variation in different species and the underlying genetics. Campylobacter jejuni strain NCTC 11168, deposited at the National Collection of Type Cultures in 1977, has been adopted widely as a reference strain by researchers worldwide and was the first Campylobacter for which the complete genome was published (in 2000). In this study, we collected 23 C. jejuni NCTC 11168 reference isolates from laboratories across the UK and compared variation in simple laboratory phenotypes with genetic variation in sequenced genomes. Putatively identical isolates identified previously to have aberrant phenotypes varied by up to 281 SNPs (in 15 genes) compared to the most recent reference strain. Isolates also display considerable phenotype variation in motility, morphology, growth at 37{degrees}C, invasion of chicken and human cell lines and susceptibility to ampicillin. This study provides evidence of ongoing evolutionary change among C. jejuni isolates as they are cultured in different laboratories and highlights the need for careful consideration of genetic variation within laboratory reference strains.\n\nImpact statementIn this paper, we comment on the changing role of laboratory reference strains. While the model organism allows basic comparison within and among laboratories, it is important to remember the effect even small differences in isolate genomes can have on the validity and reproducibility of experimental work. We quantify differences in 23 reference Campylobacter genomes and compare them with observable differences in common laboratory phenotypes.\n\nData summaryShort read data are archived on the NCBI SRA associated with BioProject accession PRJNA517467 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517467).\n\nAll assembled genomes are also available on FigShare (doi: 10.6084/m9.figshare.7849268). Phylogeny visualised on microreact: https://microreact.org/project/NCTC11168.\n\nRepositoriesShort read data are archived on the NCBI SRA repository, associated with BioProject accession PRJNA517467 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517467; Table S1).\n\nThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗