Biology subjects

Sheppard, S. K.

Publications and source records attributed to Sheppard, S. K..

At least 19 recordsLinked to original sources

bioRxiv2026

Genetic context drives evolution of divergent antibiotic survival phenotypes in Staphylococcus epidermidis

Effective treatment of infections is a global challenge, complicated by bacterias capacity to endure antibiotics. Survival under drug pressure is often driven by interactions between genetic factors rather than single genes. To investigate the genomics underlying antibiotic survival, we analysed Staphylococcus epidermidis isolates from clinical infections and carriage using high-throughput phenotyping, population genomics, and directed evolution. We observed widespread multidrug resistance, with strong links between specific genomic elements and resistance. All isolates harbouring mecA were resistant to oxacillin, though minimum inhibitory concentrations varied significantly, suggesting modulation by additional genetic factors. Directed evolution revealed potentiating mutations that enhanced oxacillin resistance in mecA+ strains. In mecA-isolates, however, evolution of mutations in the same genes conferred increased survival to oxacillin through antibiotic tolerance. These findings show that antibiotic resistance and tolerance can be genetically connected yet phenotypically distinct, and suggest a complex epistatic genetic landscape that shapes antibiotic survival phenotypes in S. epidermidis.

microbiology↗

bioRxiv2026

Insertion sequence elements associated with Staphylococcus epidermidis evolution in persistent orthopaedic device-related infections

BackgroundStaphylococcus epidermidis is a major cause of orthopaedic device-related infections (ODRIs), which are often challenging to treat due to their extensive antimicrobial resistance (AMR) and biofilm formation. It has been hypothesised that S. epidermidis may rapidly adapt to the medical device niche, enhancing persistence, but direct evidence of within-host pathoadaptive evolution remains limited. ResultsTo investigate within-host evolution during chronic infection by S. epidermidis, we analysed isolates from patients with confirmed ODRIs and used a rat infection model to examine the evolution of strains from two distinct epidemic lineages (ST2 and ST23). Our analysis revealed that the replicative transposition of insertion sequence (IS) elements within the accessory genome was the predominant mechanism of genetic diversification. This was largely driven by the IS256 family, which accounted for approximately 25% of all mutational events. However, other than SCCmec deletions resulting in the loss of mecA, no mutations, including those which exhibited parallel evolution, were predicted or observed to influence AMR or biofilm formation. These findings suggest that the strains investigated in this study, which already exhibited high-level multidrug resistance and biofilm-forming ability, were likely pre-adapted epidemic S. epidermidis clones well suited to establishing persistent ODRIs. ConclusionsOur findings highlight the prominent role of IS elements in driving genetic diversification in S. epidermidis, underscoring the need for closer examination of their contribution to pathoadaptation during persistent infection.

genomics↗

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↗

bioRxiv2025

GeneScanner: profiling genetic variation across bacterial populations

Rapid, low-cost genome sequencing has transformed microbiology, advancing efforts to link genetic and phenotypic variation. In laboratory settings, genome-wide functional screens of reference strains are revealing genes and mechanisms underlying important phenotypes. Simultaneously, population-scale comparative genomics describes the breadth of natural genetic and phenotypic diversity across lineages. These approaches provide complementary but contrasting information. Whereas laboratory studies offer causal understanding within simplified systems, population-level analyses capture ecological realism but are largely limited to detecting associations rather than cause-and-effect relationships. Linking laboratory-derived mutations to natural population variation remains challenging, particularly for researchers lacking bioinformatics expertise. Here, we present GeneScanner, a user-friendly tool that facilitates analysis of gene- and protein-level variation across large bacterial genome collections. GeneScanner detects genetic variation and amino acid substitutions in homologous sequence and supports genotype-phenotype association studies. By bridging laboratory functional genomics data with genomic diversity across natural populations, GeneScanner enhances functional interpretation of microbial variation in the real world, supporting research in antimicrobial resistance, virulence, and pathogen surveillance.

bioinformatics↗

bioRxiv2025

Genome co-adaptation and the evolution of methicillin resistant Staphylococcus auerus (MRSA)

BackgroundAntimicrobial resistance (AMR) in bacterial pathogens is a major threat to global health, rendering standard treatments ineffective and increasing the risk of severe infection or death. Resistance is often conferred by genes that are transferred horizontally among species and strains. However, for many bacteria, little is known about the genetic variation that potentiates resistance gene acquisition and accommodates acquired genes in the coadapted recipient genome. ResultsHere we introduce a new bioinformatics genome-wide association study approach with Guided Omission of Linkage Disequilibrium (GOLD-GWAS) that masks covarying alleles explained by coinheritance and genome proximity to reveal genes where covarying sequence likely represents functional linkage between loci, consistent with epistasis. Analysing 806 Staphylococcus aureus isolate genomes, including methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) strains, we identify genes that covary with the presence of the acquired staphylococcal cassette chromosome mec (SCCmec) that houses the mecA resistance gene. ConclusionsUncovering known and new gene-gene associations, we demonstrate how resistance can involve genetic coalitions beyond the well-known AMR genes. Understanding how genome change, here extrinsic resistance cassettes, are integrated within coadapted bacterial genomes is an important step towards mitigating AMR evolution by identifying novel genetic targets for risk prediction, diagnosis and therapy.

microbiology↗

bioRxiv2023

Genomic tailoring of autogenous poultry vaccines to reduce Campylobacter from farm to fork

Campylobacter is a leading cause of food-borne gastroenteritis worldwide, linked to the consumption of contaminated poultry meat. Targeting this pathogen at source, vaccines for poultry can provide short term caecal reductions in Campylobacter numbers in the chicken intestine. However, this approach is unlikely to reduce Campylobacter in the food chain or human incidence. This is likely as vaccines typically target only a subset of the high strain diversity circulating among chicken flocks and rapid evolution diminishes vaccine efficacy over time. To address this, we used a genomic approach to develop a whole-cell autogenous vaccine targeting isolates harbouring genes linked to survival outside of the host. We hyper-immunised a whole major UK breeder farm to passively target offspring colonisation using maternally-derived antibody. Monitoring progeny, broiler flocks revealed a near-complete shift in the post-vaccination Campylobacter population with a [~]50% reduction in isolates harbouring extra-intestinal survival genes and a significant reduction of Campylobacter cells surviving on the surface of meat. Based on these findings, we developed a logistic regression model that predicted that vaccine efficacy could be extended to target 46% of a population of clinically relevant strains. Immuno-manipulation of poultry microbiomes towards less harmful commensal isolates by competitive exclusion, has major potential for reducing pathogens in the food production chain.

microbiology↗

bioRxiv2023

Detecting co-selection through excess linkage disequilibrium in bacterial genomes

Population genomics has revolutionised our ability to study bacterial evolution by enabling data-driven discovery of the genetic architecture of trait variation. Genome-wide association studies (GWAS) have more recently become accompanied by genome-wide epistasis and co-selection (GWES) analysis, which offers a phenotype-free approach to generating hypotheses about selective processes that simultaneously impact multiple loci across the genome. However, existing GWES methods only consider associations between distant pairs of loci within the genome due to the strong impact of linkage-disequilibrium (LD) over short distances. Based on the general functional organisation of genomes it is nevertheless expected that the majority of co-selection and epistasis will act within relatively short genomic proximity, on co-variation occurring within genes and their promoter regions, and within operons. Here we introduce LDWeaver, which enables an exhaustive GWES across both short- and long-range LD, to disentangle likely neutral co-variation from selection. We demonstrate the ability of LDWeaver to efficiently generate hypotheses about co-selection using large genomic surveys of multiple major human bacterial pathogen species and validate several findings using functional annotation and phenotypic measurements. Our approach will facilitate the study of bacterial evolution in the light of rapidly expanding population genomic data.

bioinformatics↗

bioRxiv2023

Urbanization spreads antimicrobial resistant enteric pathogens in wild bird microbiomes

Human behaviour is dramatically changing global ecology. Nowhere is this more apparent than in urbanization, where novel high human density habitats are disrupting long established ecotones. Resultant changes to the transitional areas between organisms, especially enhanced contact between humans and wild animals, provides new opportunities for the spread of zoonotic pathogens, posing a serious threat to global public health. Here, by studying the multi-host enteric pathogen Campylobacter jejuni isolated from the gut of 30 bird species in 8 countries, we investigated how proximity to urbanization influenced the spread of antimicrobial resistant (AMR) strains. Generalized linear models compared multiple behavioural and ecological traits and confirmed a positive correlation between proximity to urbanization and the number of C. jejuni genotypes and AMR genes in wild bird hosts. Wild birds from highly urban areas harboured up to four times more C. jejuni genotypes and six times more AMR genes. This is consistent with increased frequency of transition events. Quantifying zoonotic transmission and gene pool spread is essential for quantitative one health surveillance and control measures against future zoonosis emergences.

genomics↗

bioRxiv2021

Local accessory gene sharing drives lineage-specific acquisition of antimicrobial resistance in Egyptian Campylobacter spp.

Campylobacter is the most common cause of bacterial gastroenteritis worldwide and diarrheal disease is a major cause of child morbidity, growth faltering and mortality in low- and middle-income countries (LMICs). Despite evidence of high incidence and differences in disease epidemiology, there is limited genomic data from studies in developing countries. In this study, we characterised the genetic diversity and accessory genome content of a collection of Campylobacter isolates from Cairo, Egypt. In total, 112 Campylobacter isolates were collected from broiler carcasses (n=31), milk and dairy products (n=24) and patients (n=57) suffering from gastroenteritis. Among the most common sequence types (STs) we identified were the globally disseminated, host generalist ST-21 clonal complex (CC21) and the poultry specialist CC206, CC464 and CC48. Notably, CC45 and the cattle-specialist CC42 were under-represented with a total absence of CC61. Comparative genomics were used to quantify core and accessory genome sharing among isolates from the same country compared to sharing between countries. Lineage-specific accessory genome sharing was significantly higher among isolates from the same country, particularly CC21 which demonstrated greater local geographical clustering. In contrast, no geographic clustering was noted in either the core or accessory genomes of the CC828, suggesting a highly admixed population. A greater proportion of C. coli isolates were multidrug resistant (MDR) compared to C. jejuni. This is a significant public health concern as MDR food chain pathogens are difficult to treat and often pose increased mortality risk demanding enhanced prevention strategies in the Egyptian market to combat such a threat. Impact statementCampylobacter is the leading bacterial cause of gastroenteritis worldwide and despite high incidence in low- and middle-income countries, where infection can be fatal, culture-based isolation is rare and the genotypes responsible for disease are seldom identified. Here, we sequenced the genomes of a collection of isolates from clinical cases and potential infection reservoirs from Cairo in Egypt and characterised their genetic diversity. Among the most common genotypes we identified were globally disseminated lineages implicated in human disease worldwide, including the host generalist ST-21 clonal complex (CC21) and the poultry specialist genotypes CC206, CC464 and CC48. Notably however, some other globally common genotypes were under-represented or entirely absent from our collection, including those from cattle-specialist lineages, CC42 and CC61. By focussing on specific lineages, we demonstrate that there is increased accessory genome sharing in specific clonal complexes. This increased local sharing of genes may have contributed to a greater proportion of C. coli isolates possessing antimicrobial resistance determinants that suggest they could be multidrug resistant (MDR). This is a significant public health concern as MDR food chain pathogens are difficult to treat and often pose increased mortality risk demanding enhanced prevention strategies. Data summaryShort read data are available on the NCBI Sequence Read Archive, associated with BioProject PRJNA576513 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA576513). Assembled genomes, supplementary material and additional analysis files are available from FigShare: https://doi.org/10.6084/m9.figshare.9956597. Phylogenetic trees can be visualised and manipulated on Microreact for C. jejuni (https://next.microreact.org/project/Cjejuni_Egypt) and C. coli (https://next.microreact.org/project/Ccoli_Egypt) separately, or combined Cairo and Oxford data with additional PopPunk network clustering (https://microreact.org/project/Campy-Egypt).

microbiology↗

bioRxiv2021

Host ecology regulates interspecies recombination in bacteria of the genus Campylobacter

Horizontal gene transfer (HGT) can allow traits that have evolved in one bacterial species to transfer to another. This has potential to rapidly promote new adaptive trajectories such as zoonotic transfer or antimicrobial resistance. However, for this to occur requires gaps to align in barriers to recombination within a given time frame. Chief among these barriers is the physical separation of species with distinct ecologies in separate niches. Within the genus Campylobacter there are species with divergent ecologies, from rarely isolated single host specialists to multi-host generalist species that are among the most common global causes of human bacterial gastroenteritis. Here, by characterising these contrasting ecologies, we can quantify HGT among sympatric and allopatric species in natural populations. Analysing recipient and donor population ancestry among genomes from 30 Campylobacter species we show that cohabitation in the same host can lead to a 6-fold increase in HGT between species. This accounts for up to 30% of all SNPs within a given species and identifies highly recombinogenic genes with functions including host adaptation and antimicrobial resistance. As described in some animal and plant species, ecological factors are a major evolutionary force for speciation in bacteria and changes to the host landscape can promote partial convergence of distinct species through HGT.

microbiology↗

bioRxiv2021

Non-serotype 2 isolates from healthy pigs are a potential zoonotic reservoir of Streptococcus suis genetic diversity and antimicrobial resistance

Streptococcus suis is a leading cause of bacterial meningitis in SE Asia, with frequent zoonotic transfer to humans associated with close contact with pigs. A small number of invasive lineages are responsible for endemic infection in the swine industry causing considerable global economic losses. A lack of surveillance and a rising trend in clinical treatment failure has raised concerns of growing antimicrobial resistance (AMR) among invasive S. suis. The source-sink dynamics between healthy and disease isolates is poorly understood and, in this study, we sample and sequence a collection of isolates predominantly from healthy pigs in Chiang Mai province, Northern Thailand. Pangenome comparisons with a selection of invasive serotype 2 isolates identified increased genetic diversity and more frequent AMR carriage in isolates from healthy pigs. Multiple antimicrobial resistance genes were identified conferring resistance to aminoglycosides, lincosamides, tetracycline and macrolides. All isolates were non-susceptinle to three or more different antimicrobial classes, and 75% of non-serotype 2 isolates were non-susceptible to 6 or more classes (compared to 37.5% of serotype 2 isolates). Antimicrobial resistance genes were found on integrative and conjugative elements (ICE) previously observed in other species, suggesting mobile gene pool which can be accessed by invasive disease isolates. Significance statementThe zoonotic pathogen Streptococcus suis causes respiratory disease in pigs and is among the most common causative agents of human clinical bacterial meningitis in SE Asia. We collected isolates from farmed healthy pigs in Northern Thailand, representing a source population from which invasive isolates have recently emerged - linked to the pork production industry. Pangenome characterisation of the isolates revealed a reservoir of genetic diversity and antimicrobial resistance suggesting that One Health approaches may be beneficial in tackling the increase in antimicrobial resistance.

microbiology↗

bioRxiv2021

Cross-species evolutionary rewiring in the enteric bacterium Campylobacter

Significance StatementGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox. On one hand, promoting adaptation by conferring novel functionality, on the other potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyse natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in epistasis in a recipient genome. This challenges conventional ideas and highlights the possibility of single step evolution by saltation. AbstractRecombination of short DNA fragments via horizontal gene transfer (HGT) can both introduce beneficial alleles and create genomic disharmony through negative epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome. By contrast, for the core genome, interspecific recombination is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and Campylobacter coli, that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings (negative epistasis). However, multiple HGT events enable recovery of the genomes co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred and independently reinstated in a new genetic background - facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

microbiology↗

bioRxiv2021

Machine learning to predict the source of campylobacteriosis using whole genome data

Campylobacteriosis is among the worlds most common foodborne illnesses, caused predominantly by the bacterium Campylobacter jejuni. Effective interventions require determination of the infection source which is challenging as transmission occurs via multiple sources such as contaminated meat, poultry, and drinking water. Strain variation has allowed source tracking based upon allelic variation in multi-locus sequence typing (MLST) genes allowing isolates from infected individuals to be attributed to specific animal or environmental reservoirs. However, the accuracy of probabilistic attribution models has been limited by the ability to differentiate isolates based upon just 7 MLST genes. Here, we broaden the input data spectrum to include core genome MLST (cgMLST) and whole genome sequences (WGS), and implement multiple machine learning algorithms, allowing more accurate source attribution. We increase attribution accuracy from 64% using the standard iSource population genetic approach to 71% for MLST, 85% for cgMLST and 78% for kmerized WGS data using machine learning. To gain insight beyond the source model prediction, we use Bayesian inference to analyse the relative affinity of C. jejuni strains to infect humans and identified potential differences, in source-human transmission ability among clonally related isolates in the most common disease causing lineage (ST-21 clonal complex). Providing generalizable computationally efficient methods, based upon machine learning and population genetics, we provide a scalable approach to global disease surveillance that can continuously incorporate novel samples for source attribution and identify fine-scale variation in transmission potential. Author summaryC. jejuni are the most common cause of food-borne bacterial gastroenteritis but the relative contribution of different sources are incompletely understood. We traced the origin of human C. jejuni infections using machine learning algorithms that compare the DNA sequences of bacteria sampled from infected people, contaminated chickens, cattle, sheep, wild birds and the environment. This approach achieved improvement in accuracy of source attribution by 33% over existing methods that use only a subset of genes within the genome and provided evidence for the relative contribution of different infection sources. Sometimes even very similar bacteria showed differences, demonstrating the value of basing analyses on the entire genome when developing this algorithm that can be used for understanding the global epidemiology and other important bacterial infections.

bioinformatics↗

bioRxiv2020

Antimicrobial resistant Salmonella spp. circulating in antibiotic-free organic pig farms of northern-Thailand

We investigated the prevalence of Salmonella circulating in local organic pig farms in northern Thailand and typed isolated clones to better understand the population structure of the underlying Salmonella contamination. In total, 112 samples from 11 organic pig farms were processed from October to December 2018. Salmonella were detected in 9 farms with an overall prevalence of 25.0% (28/112). Prevalence detected in fecal, feeder, and boot swab samples was found to be 32.7% (17/53), 17.7% (6/34), and 20.0% (5/25), respectively. Of the 28 positive strains, Seven Salmonella serotypes were identified, with S. Rissen being the most common (15/28; 53.6%). 89.3% (25/28), 78.6% (22/28) and 71.4% (20/28) of isolated Salmonella were resisted against tetracycline, ampicillin, and sulfamethoxazole-trimethoprim, respectively. From multilocus sequence typing (MLST) analysis, the phylogenetic tree suggests dissemination of specific clones within herds that share routes of pig transportation and point mutations in housekeeping genes within herds. A minimum spanning tree (MST) revealed that Salmonella contamination in organic pig farming is possibly linked with conventional farming. Based on the own results, strictly highly organic practices provide a safe alternative enhancing domestic consumer trust and improve public health safety.

molecular biology↗

bioRxiv2020

Multiple clones of colistin-resistant Salmonella enterica carrying mcr-1 plasmids in meat products and patients in Northern Thailand

Salmonella spp. is an important foodborne pathogen associated with consumption of contaminated food, especially livestock products. Antimicrobial resistance (AMR) in Salmonella has been reported globally and increasing AMR in food production is a major public health issue worldwide. The objective of this study was to describe the genetic relatedness among Salmonella enterica isolates, which displayed identical DNA fingerprint profiles. Ten S. enterica isolates were selected from meat and human cases with an identical rep-PCR profile of serovars Rissen (n=4), Weltevreden (n=4), and Stanley (n=2). We used long-read whole genome sequencing (WGS) on the MinION sequencing platform to type isolates and investigate in silico the presence of specific AMR genes. Antimicrobial susceptibility testing was tested by disk diffusion and gradient diffusion method to corroborate the AMR phenotype. Multidrug resistance and resistance to more than one antimicrobial agent were observed in eight and nine isolates, respectively. Resistance to colistin with an accompanying mcr-1 gene was observed among the Salmonella isolates. The analysis of core genome and whole genome MLST revealed that the Salmonella from meat and human salmonellosis were closely genetic related. Hence, it could be concluded that meat is one of the important sources for Salmonella infection in human. HighlightsO_LIColistin resistance detected in 2 clones from 2 different Salmonella enterica serovars (Rissen and Weltevreden) with accompanying plasmid-borne mcr-1 gene from the food production chain and human clinical salmonellosis. C_LIO_LIHigh prevalence of multidrug resistant isolates and resistance to more than one antimicrobial agent. C_LIO_LIMinION has potential for mobile, rapid and accurate application in veterinary genomic epidemiology studies. C_LI

microbiology↗

bioRxiv2020

Quantifying bacterial evolution in the wild: a birthday problem for Campylobacter lineages

Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the birthday problem. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time-frame - analogous to a shared birthdays - and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species. Author SummaryGrowth and reproduction in living organisms require DNA replication but this process is error prone. Along with variation introduced by horizontal gene transfer, it can lead to alterations in the nucleotide sequence. These nucleotide changes accumulate over time in successive generations at an approximately constant rate termed the molecular clock. Therefore, if this rate is known, one can estimate the date when two or more lineages diverged. In bacteria, this can be informative for understanding the time-scale of emergence and spread of pathogenic strains. Such analyses are robust when the ancestral population is known, such as for obligate pathogens that only infect humans. However, when the bacterium inhabits multiple hosts or niches it is difficult to infer direct ancestry from one strain to another, reducing the accuracy of molecular clock estimates. Here we focus on one such multi-host organism, Campylobacter, a leading cause of food-borne gastroenteritis. Reconstructing the population history by estimating empirical nucleotide change rates from carefully selected isolate pairs, and evaluating the maintenance of multiple lineages over time, we provide information about strain diversification. Our method is a new addition to the bacterial genomics toolkit that will help in understanding the spread of opportunistic pathogens.

genomics↗

bioRxiv2019

Hermes: an ensemble machine learning architecture for protein secondary structure prediction

MotivationProtein structure predictions, that combine theoretical chemistry and bioinformatics, are an increasingly important technique in biotechnology and biomedical research, for example in the design of novel enzymes and drugs. Here, we present a new ensemble bi-layered machine learning architecture, that directly builds on ten existing pipelines providing rapid, high accuracy, 3-State secondary structure prediction of proteins.\n\nResultsAfter training on 1348 solved protein structures, we evaluated the model with four independent datasets: JPRED4 - compiled by the authors of the successful predictor with the same name, and CASP11, CASP12 & CASP13 - assembled by the Critical Assessment of protein Structure Prediction consortium who run biannual experiments focused on objective testing of predictors. These rigorous, pre-established protocols included 7-fold cross-validation and blind testing. This led to a mean Hermes accuracy of 95.5%, significantly (p<0.05) better than the ten previously published models analysed in this paper. Furthermore, Hermes yielded a reduction in standard deviation, lower boundary outliers, and reduced dependency on solved structures of homologous proteins, as measured by NEFF score. This architecture provides advantages over other pipelines, while remaining accessible to users at any level of bioinformatics experience.\n\nAvailability and ImplementationThe source code for Hermes is freely available at: https://github.com/HermesPrediction/Hermes. This page also includes the cross-validation with corresponding models, and all training/testing data presented in this study with predictions and accuracy.

bioinformatics↗

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↗