Biology subjects

Parkhill, J.

Publications and source records attributed to Parkhill, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Hantavirus mutagenesis is impacted by mutagens and host antiviral proteins

Hantaviruses are emerging zoonotic viruses that infect humans with high fatality rates. We currently have a poor understanding of the processes that contribute to hantavirus mutagenesis and therefore the potential for viral adaptation. To understand the drivers of mutations in hantaviruses, we calculated and compared mutational spectra across 14 divergent hantavirus species. We found that mutagens that are conserved across host species have a major impact on hantaviruses mutagenesis, contributing to at least six of the 12 possible mutation types. We found differences in mutational signatures across hantaviruses, some of which may be due to variation in host mutagen levels that are known to influence somatic mutations. However, we could find no evidence for differential mutational signatures between viruses associated with distinct diseases in humans and no evidence of tissue tropism differences between reservoir hosts. Using a novel method to quantify the impact of ZAP-mediated selection, we found that ZAP greatly influences mutational patterns in transition mutation types across hantaviruses. We also find evidence that APOBEC family proteins drive mutagenesis in all hantaviruses, with the likely exception of Nova virus. Our results therefore provide strong support that mutagens and host antiviral proteins are major contributors to hantavirus mutagenesis, thereby generating the genetic diversity necessary for viral adaptation.

microbiology↗

bioRxiv2026

A 28-year evolution experiment on Burkholderia pseudomallei survival in nutrient-depleted sterile water

Environmental persistence allows opportunistic pathogens to survive a range of harsh conditions, increasing the likelihood of eventual infection. Burkholderia pseudomallei, the causative agent of melioidosis, can endure long-term nutrient-depletion in the environment, but its adaptive mechanisms remain poorly understood. Here, we investigated the evolutionary trajectory of a clinical B. pseudomallei strain maintained in sterile water since 1994. The strain was inoculated into nine individual tubes at nine initial concentrations (102-1010 CFU/mL) and has remained viable to date. Liquid chromatography-mass spectrometry analysis of the water identified potential carbon sources, including phthalic acid -- a plastic degradation product likely leached from inoculation tubes -- which the strain can metabolise via an intact catabolic operon. Genomic variations accumulated between 1994 and 2022 were characterised using both single-colony and plate-sweep sequencing which provided complementary insights. Across all tubes, we identified 249 single-nucleotide polymorphisms (SNPs), 73 indels, and a large-scale deletion. Cultures from each tube displayed a consistently low mutation rate (3.18 x 10- SNPs per site per year), suggesting that cells entered a dormant or slow-growth state. Of 393 genes with mutations, 193 were independently mutated in more than one tube, particularly those involved in signal transduction, cell wall and membrane biogenesis, and secondary metabolite synthesis. These patterns indicate parallel adaptation to long-term nutrient deprivation through modulation of cell-density-related functions and loss of metabolically costly pathways. Remarkably, B. pseudomallei from this experiment remain viable after nearly three decades, providing a rare natural model for understanding how environmental bacteria endure and adapt in extremely nutrient-depleted conditions.

evolutionary biology↗

bioRxiv2025

Mapping the evolutionary path towards multi-drug resistance in the pandemic Escherichia coli ST131 lineage

Escherichia coli sequence type (ST) 131 is the most widely studied genetic lineage of the species to date, originally identified in the early 2000s as an increasingly common cause of human urinary tract and bloodstream infections worldwide. This lineage is subdivided into four extant main subclades A, B, C1 and C2 that exhibit distinct features in terms of invasiveness, antibiotic resistance and transmissibility. However, the evolutionary pathway from the generally susceptible ST131-B to the drug-resistant ST131-C clades remains poorly mapped. To fill this knowledge gap, we analysed in detail human clinical isolates obtained in Vietnam, designated as belonging to the generally neglected minor clade ST131-B0. We sequenced them using both short- and long-read technology, and combined these data with a recently published high-resolution genomic collection to provide further insight into the evolutionary process and its timeline. Extensive genomic analyses established ST131-B0 as an intermediary progenitor in the evolutionary path leading from ST131-B to the ST131-C clades, associated with multiple type I pili switches, as well as the loss and gain of specific chromosomal genes representing diverse core functions such as metabolism, transcription, DNA binding and type II toxin-antitoxin systems. Furthermore, all Vietnamese isolates of ST131-B0 unprecedentedly harboured blaCTX-M genes encoding extended-spectrum {beta}-lactamases, a trait dominant in ST131-C clades and not previously observed in ST131-B0. Our study supports the hypothesis that the ST131-C clades have gradually evolved from ST131-B by reducing the host range with better adaptation to colonising humans under selective conditions.

evolutionary biology↗

bioRxiv2025

Mutational spectra reveal influenza virus transmission routes and adaptation

Influenza A virus remains a major cause of morbidity and mortality in humans and animals with pandemic potential. While control of outbreaks and spillover events remains a key health priority, the transmission routes and adaptations causing these episodes remain unclear. To understand these processes, we compared mutational spectra across the complete diversity of influenza A virus. We find that niche-specific mutagens cause large convergent shifts in mutational spectrum between gastrointestinal and respiratory lineages, allowing inference of transmission route and site of infection, while additional mutational patterns are host-specific, permitting detection of species responsible for outbreaks. By identifying points of spectrum change in phylogenetic trees, we discover novel adaptive mutations enabling sustained respiratory transmission. We conclude that mutational spectra can enable early detection of lineages with increased potential for spillover and onward transmission, and should be considered as a component of genomic surveillance strategies.

microbiology↗

bioRxiv2025

Phylodynamics and genome-wide association studies reveal the expansion of modern Streptococcus canis in Germany

Streptoccocus canis is a leading canine pathogen causing 22.4% of canine streptococcal infections. However, knowledge of factors contributing to S. canis expansion is limited. This study uses population genetics to structure a S. canis dataset of 585 isolates and identify genetic markers contributing to the success of each dominant lineage. The dataset is composed of canine, feline and bovine isolates primarily from Germany collected between the years 1996 and 2021. We performed Multi-Locus Sequence Typing (MLST) for an initial analysis and clustered the population with fastBAPS based on the whole genome. Dated phylogenies were inferred with BEAST and Genome-Wide Association Studies (GWAS) were conducted with Scoary. MLST showed that in Germany there are two dominant groups of canine S. canis, ST43 (n= 75) and ST9 (n= 51), which were grouped into BAPS-6 and BAPS-5, respectively. The BAPS-6 cluster emerged as early as 1988 with major expansion starting around 2010. We showed via GWAS that this cluster is associated with a putative Streptococcus anginosus derived integrative and conjugative element carrying a putative cysteine protease. Furthermore, the BAPS-5 cluster emerged around 1786 with a bovine/feline subcluster appearing around 1879. This subcluster is associated with a variant of the streptococcal lac operon, which appears to have resulted from an exchange with Streptococcus dysgalactiae. We present the largest population genetics study to date for S. canis where we show that its expansion is associated with genetic exchange with other streptococcal species leading to increased pathogenic potential (BAPS-6) or host adaptation (BAPS-5). ImportanceStreptococcus canis is a bacterium which poses considerable threat to the health of dogs through superficial infections. Current research could benefit from understanding the reasons for its expansion and spread into other hosts. We looked at the genomes of 585 S. canis isolates collected during a 25-year period and identified which parts of the population were the most successful. With powerful statistical methods, we found that two groups of S. canis were the most effective: a canine group which had become more pathogenic by acquiring DNA from Streptococcus anginosus, and another group which spread from dogs into cats and cows by acquiring genetic material for lactose consumption from Streptococcus dysgalactiae. For the first time, we link the expansion of major S. canis groups to genetic exchange events with closely related streptococcal species to understand S. canis evolution and spread.

microbiology↗

bioRxiv2025

Characterisation of Ornithobacterium hominis colonisation dynamics and interaction with the nasopharyngeal microbiome in a South African birth cohort.

Ornithobacterium hominis is a recently described Gram-negative bacterium that colonises the human nasopharynx and may be associated with poor upper respiratory tract health. Here, we describe the isolation of O. hominis from samples collected from a South African birth cohort, creating the first archive of cultured strains of the species from Africa. Sequenced genomes from this archive reveal that South African O. hominis is more similar to Australian strains than those from Southeast Asia, and that it may share genes with other members of the microbiome that are relevant for virulence, colonisation, and antibiotic resistance. Leveraging existing microbiome data from the cohort, O. hominis was found to be closely associated with bacterial co-colonisers that are rare in non-carrier individuals, including Suttonella, Helcococcus, Moraxella spp., and Gracilibacteria. Their collective acquisition has a significant impact on the diversity of nasopharyngeal communities that contain O. hominis. Individuals who have not yet acquired O. hominis have a higher abundance of Moraxella (particularly M. lincolnii) than individuals who never acquire O. hominis, suggesting that this could be a precursor state for successful colonisation. Finally, a novel co-coloniser species, Helcococcus ekapensis, was successfully isolated and sequenced. Data SummaryOrnithobacterium hominis data have been deposited under project accession ERP149886. This comprises genome sequences for isolates SA-OH-C1 (ERR13967269), SA-OH-C2 (ERR13967270), SA-OH-C3 (ERR13967271), SA-OH-C4 (ERR13967272, ERR13967275), SA-OH-C5 (ERR13967273), SA-OH-C6 (ERR13967274, ERR13967276). Previously published 16S rRNA gene data are deposited under project accessions PRJNA790843 and PRJNA548658. Helcococcus ekapensis genome data are deposited under project accession PRJEB85661. Software usedO_LIAMRFinderPlus v3.12.8: https://github.com/ncbi/amr C_LIO_LIAssembleBAC-ONT v1.1.1: https://github.com/avantonder/assembleBAC-ONT C_LIO_LIBAKTA v1.8.1: https://bakta.computational.bio/ C_LIO_LIBLAST v2.16.0: https://blast.ncbi.nlm.nih.gov/Blast.cgi C_LIO_LIComprehensive Antibiotic Resistance Database (CARD) Resistance Gene Identifier (RGI) tool v1.2.1: https://card.mcmaster.ca/analyze/rgi C_LIO_LIDecontam v1.12 (R package): https://github.com/benjjneb/decontam C_LIO_LIEggnog-mapper v2.0.1: http://eggnog-mapper.embl.de/ C_LIO_LIFastANI v1.1.0: https://github.com/ParBLiSS/FastANI C_LIO_LIFlye v2.9.2: https://github.com/fenderglass/Flye C_LIO_LIGuppy v6.5.7: https://community.nanoporetech.com/downloads/guppy/release_notes C_LIO_LIISEScan v1.7.2.3: https://usegalaxy.eu/root?tool_id=toolshed.g2.bx.psu.edu/repos/iuc/isescan/isescan/1.7.2.3+galaxy1 C_LIO_LIMedaka v1.9.1: https://github.com/nanoporetech/medaka C_LIO_LIMEGA11: https://www.megasoftware.net/ C_LIO_LIMMseqs2 v17: https://github.com/soedinglab/MMseqs2 C_LIO_LIMothur v1.44.3: https://github.com/mothur/mothur C_LIO_LINetCoMi v1.2.0 (R package): https://github.com/stefpeschel/NetCoMi C_LIO_LIPanaroo v1.4.3: https://github.com/gtonkinhill/panaroo C_LIO_LIPHASTEST: https://phastest.ca/submissions/new C_LIO_LIProwler (commit ID c3041ba): https://github.com/ProwlerForNanopore/ProwlerTrimmer C_LIO_LIR v4.4.3: https://www.r-project.org/ C_LI Databases usedO_LIComprehensive Antibiotic Resistance Database (CARD): https://card.mcmaster.ca/ C_LIO_LIEuropean Nucleotide Archive: https://www.ebi.ac.uk/ena/ C_LIO_LIGenome Taxonomy Database (GTDB) release 09-RS220: https://gtdb.ecogenomic.org/ C_LIO_LIRefSeq release 228: https://www.ncbi.nlm.nih.gov/refseq/about/prokaryotes/ C_LIO_LISILVA v132: https://www.arb-silva.de/ C_LI Impact statementFirst described in 2019, Ornithobacterium hominis is an understudied bacterium that may be associated with poor respiratory health in children. The study builds upon existing knowledge of O. hominis by describing the first African isolates of the species, its potential as a reservoir of virulence and antibiotic resistance genes in the upper respiratory tract, and the unique microbiome profile of O. hominis carriers.

microbiology↗

bioRxiv2025

Defence systems drive accessory genome interactions in Pseudomonas aeruginosa.

Bacterial genomes represent dynamic ecological systems in which mutational selection and dynamic accessory genome element complements drive evolution. Emerging evidence suggests that bacterial defence systems, which protect against phages and other mobile genetic elements, interact through cooperative, competitive, and antagonistic relationships. These interactions can influence horizontal gene transfer, shape phage susceptibility, and the diversification of genome composition across environments. Recent ecological studies describe non-random co-occurrence and avoidance of defence systems, suggesting that they may emerge from ecological and evolutionary interactions, rather than by chance. This necessitates exploring whether these patterns reflect functional compatibility, shared selection pressures imposed by ecological niche, or if they merely arise from co-localisations of convenience. Understanding these patterns is key to elucidating how the accessory genome evolves and how defence systems constrain or facilitate genome plasticity. To investigate these patterns, in their genomic context, and provide a resource for future investigations, we analysed the distributions of defence systems and other accessory genome elements in a recently curated global dataset of 2,940 Pseudomonas aeruginosa genomes. Genomic defence system content varied by ecological niche, with higher numbers per genome in non-cystic fibrosis derived isolates (average n=7.9) compared to cystic fibrosis-derived isolates (average n=6.5). We identified multiple associations (n=426) and dissociations (n=50) among defence systems, and among other accessory genome elements, many of which had a plausible biological explanation. We also quantitated the relative interactions among accessory genome elements which revealed that defence systems and anti-defence systems engage in the most accessory genome interactions, compared with e.g. antimicrobial resistance genes, plasmids, phages, suggesting that systems are a major driving force in the ecological dynamics of the bacterial accessory genome. Together, these patterns provide new insights into the evolutionary forces shaping bacterial genomes, provide a valuable resource of quantitated interactions in a highly curated Pseudomonas aeruginosa dataset, and establish a framework for future mechanistic and ecological investigations of defence system interactions.

microbiology↗

bioRxiv2025

Minimal machine learning models of resistance identify novel antibiotic resistance discovery opportunities in Klebsiella pneumoniae

Bacterial antimicrobial resistance (AMR) poses a significant public health threat. The advent of global awareness and affordable whole genome sequencing has yielded an ever-growing collection of bacterial genome sequence datasets and corresponding antibiotic resistance metadata. This enables the use of computational techniques, including machine learning (ML), to predict phenotypes and discover novel AMR-associated variants. With the great variety of resistance mechanisms to interrogate and the number of datasets that can be mined, there is a need to identify where novel AMR marker discovery is most necessary. Multiple databases and annotation pipelines exist to identify AMR variants known to be associated with resistance to specific antibiotics or antibiotic classes, however, the completeness of these databases varies and for some antibiotics even the most complete databases remain insufficient for accurate classification. Here, we couple these pipelines with predictive ML models, which we call "minimal models" of resistance. We predict the binary resistance phenotypes of 20 major antimicrobials in the genomically diverse pathogen Klebsiella pneumoniae. We present a detailed comparison of the annotation pipelines and drug resistance databases currently available, and we identify their shortcomings in phenotype prediction, highlighting opportunities for novel marker discovery. We further provide a description of a Bacterial and Viral Bioinformatics Resource Center (BV-BRC) database, highlighting the observed AMR mechanism as the key for phenotype prediction in this dataset. This analysis has relevance for all those seeking to use or improve drug resistance databases. It provides a critical review of the differences in annotation tools and databases commonly used in bacterial AMR studies, identifying existing gaps and novel AMR marker discovery niches. It outlines guidance for the establishment of a real standard dataset for the development and benchmarking of ML models of AMR.

microbiology↗

bioRxiv2024

Latent Diffusion For Conditional Generation of Molecules

AO_SCPLOWBSTRACTC_SCPLOWDesigning a small molecule therapeutic is a challenging multi-parameter optimization problem. Key properties, such as potency, selectivity, bioavailability, and safety must be jointly optimized to deliver an effective clinical candidate. We present COATI-LDM, a novel application of latent diffusion models to the conditional generation of property-optimized, drug-like small molecules. Diffusive generation of latent molecular encodings, rather than direct diffusive generation of molecular structures, offers an appealing way to handle the small and mismatched datasets that are common for molecular properties. We benchmark various diffusion guidance schemes and sampling methods against a pre-trained autoregressive transformer and genetic algorithms to evaluate control over potency, expert preference, and various physicochemical properties. We show that conditional diffusion allows control over the properties of generated molecules, with practical and performance advantages over competing methods. We also apply the recently introduced idea of particle guidance to enhance sample diversity. We prospectively survey a panel of medicinal chemists and determine that we can conditionally generate molecules that align with their preferences via a learned preference score. Finally, we present a partial diffusion method for the local optimization of molecular properties starting from a seed molecule. Conditional generation of small molecules using latent diffusion models on molecular encodings provides a highly practical and flexible alternative to prior molecular generation schemes.

bioinformatics↗

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↗

bioRxiv2023

The landscape of ancient human pathogens in Eurasia from the Stone Age to historical times

Infectious diseases have had devastating impacts on human populations throughout history, but important questions about their origins and past dynamics remain1. To create the first archaeogenetic-based spatiotemporal map of human pathogens, we screened shotgun sequencing data from 1,313 ancient humans covering 37,000 years of Eurasian history. We demonstrate the widespread presence of ancient bacterial, viral and parasite DNA, identifying 5,486 individual hits against 492 species from 136 genera. Among those hits, 3,384 involve known human pathogens2, many of which were detected for the first time in ancient human remains. Grouping the ancient microbial species according to their likely reservoir and type of transmission, we find that most groups are identified throughout the entire sampling period. Intriguingly, zoonotic pathogens are only detected [~]6,500 years ago, peaking [~]5,000 years ago, coinciding with the widespread domestication of livestock3. Our findings provide the first direct evidence that this lifestyle change resulted in an increased infectious disease burden. Importantly, they also suggest that the spread of these pathogens increased substantially during subsequent millenia, coinciding with the pastoralist migrations from the Eurasian Steppe4,5.

evolutionary biology↗

bioRxiv2023

Calculating and applying pathogen mutational spectra using MutTui

Mutational spectra describe the pattern of mutations acquired during evolution and are driven by factors including mutagens, repair processes and selection. Calculating mutational spectra of pathogen genomic datasets may enable analysis of factors that influence these mutational processes, including replication niches, transmission routes and pathogen biology. Here, we introduce MutTui, which can leverage multiple types of sequence data to calculate and compare mutational spectra of DNA and RNA pathogens. MutTui is available at https://github.com/chrisruis/MutTui.

genomics↗

bioRxiv2022

High-throughput transposon mutagenesis in the family Enterobacteriaceae reveals core essential genes and rapid turnover of essentiality

The Enterobacteriaceae are a scientifically and medically important clade of bacteria, containing the gut commensal and model organism Escherichia coli, as well as several major human pathogens including multiple serovars of Salmonella enterica and Klebsiella pneumoniae. Essential gene sets have been determined for several members of the Enterobacteriaceae, with the E. coli Keio single-gene deletion library often regarded as a gold standard for gene essentiality studies. However, it remains unclear how gene essentiality varies between related strains and species. To investigate this, we have assembled a collection of thirteen sequenced high-density transposon mutant libraries from five genera within the Enterobacteriaceae. We first benchmark a number of gene essentiality prediction approaches, investigate the effects of transposon density on essentiality prediction, and identify biases in transposon insertion sequencing data. Based on these investigations we develop a new classifier for gene essentiality. Using this new classifier, we define a core essential genome in the Enterobacteriaceae of 201 universally essential genes, and reconstruct an ancestral essential gene set of 296 genes. Despite the presence of a large cohort of variably essential genes, surprisingly we find an absence of evidence for genus-specific essential genes. A clear example of this sporadic essentiality is given by the set of genes regulating the {sigma}E extracytoplasmic stress response, which appears to have independently become essential multiple times in the Enterobacteriaceae. Finally, we compare our essential gene sets to the natural experiment of gene loss in obligate insect endosymbionts that have emerged from within the Enterobacteriaceae. This isolates a remarkably small set of genes absolutely required for survival, and uncovers several instances of essential stress responses masked by redundancy in free-living bacteria.

microbiology↗

bioRxiv2022

Mutational spectra distinguish SARS-CoV-2 replication niches

Exposure to different mutagens leaves distinct mutational patterns that can allow prediction of pathogen replication niches (Ruis 2022). We therefore hypothesised that analysis of SARS-CoV-2 mutational spectra might show lineage-specific differences, dependant on the dominant site(s) of replication and onwards transmission, and could therefore rapidly infer virulence of emergent variants of concern (VOC; Konings 2021). Through mutational spectrum analysis, we found a significant reduction in G>T mutations in Omicron, which replicates in the upper respiratory tract (URT), compared to other lineages, which replicate in both upper and lower respiratory tracts (LRT). Mutational analysis of other viruses and bacteria indicates a robust, generalisable association of high G>T mutations with replication within the LRT. Monitoring G>T mutation rates over time, we found early separation of Omicron from Beta, Gamma and Delta, while the mutational burden in Alpha varied consistent with changes in transmission source as social restrictions were lifted. This supports the use of mutational spectra to infer niches of established and emergent pathogens.

microbiology↗

bioRxiv2022

Mutational spectra analysis reveals bacterial niche and transmission routes

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to identify disrupted DNA repair processes and niche-specific mutagen exposure. Here we reconstructed mutational spectra for 84 clades from 31 diverse bacterial species, assigned signatures to specific DNA repair pathways using hypermutator lineages, and, by comparing mutational spectra of clades from different environmental and biological locations, extracted reproducible niche-associated mutational signatures. We show that mutational spectra can predict general and specific bacterial niches and therefore reveal the site of infection and types of transmission routes for established and emergent human bacterial pathogens. One sentence summaryVariable mutagen exposure and DNA repair drive differential mutational spectra between bacteria and enable niche inference

microbiology↗

bioRxiv2021

A scalable analytical approach from bacterial genomes to epidemiology

Recent years have seen a remarkable increase in the practicality of sequencing whole genomes from large numbers of bacterial isolates. The availability of this data has huge potential to deliver new insights into the evolution and epidemiology of bacterial pathogens, but the scalability of the analytical methodology has been lagging behind that of the sequencing technology. Here we present a step-by-step approach for such large-scale genomic epidemiology analyses, from bacterial genomes to epidemiological interpretations. A central component of this approach is the dated phylogeny, which is a phylogenetic tree with branch lengths measured in units of time. The construction of dated phylogenies from bacterial genomic data needs to account for the disruptive effect of recombination on phylogenetic relationships, and we describe how this can be achieved. Dated phylogenies can then be used to perform fine-scale or large-scale epidemiological analyses, depending on the proportion of cases for which genomes are available. A key feature of this approach is computational scalability, and in particular the ability to process hundreds or thousands of genomes within a matter of hours. This is a clear advantage of the step-by-step approach described here. We discuss other advantages and disadvantages of the approach, as well as potential improvements and avenues for future research.

microbiology↗

bioRxiv2021

Spatial dynamics and vaccine-induced fitness changes of Bordetella pertussis

Competitive interactions between pathogen strains drive infection risk. Vaccines are thought to perturb strain diversity through shifts in immune pressures, however, this has rarely been measured due to inadequate data and analytical tools. Bordetella pertussis (B. pertussis), responsible for 160,000 deaths annually1, provides a rare natural experiment as many countries have switched from whole cell vaccines to acellular vaccines, which have very different immunogenic properties2,3. Here we use 3,344 sequences from 23 countries and build phylogenetic models to reveal that B. pertussis has substantial diversity within communities, with the relative fitness of local genotypes changing in response to switches in vaccine policy. We demonstrate that the number of transmission chains circulating within subnational regions is strongly associated with host population size. It takes 5-10 years for individual lineages to be homogeneously distributed throughout Europe or the United States. Increased fitness of pertactin-deficient strains following implementation of acellular vaccines, but reduced fitness otherwise, can explain long-term genotype dynamics. These findings highlight the role of national vaccine policies in shifting local diversity of a pathogen that still poses a large burden on global public health.

genetics↗

bioRxiv2021

The pathobiology of Mycobacterium abscessus revealed through phenogenomic analysis

The medical and scientific response to emerging pathogens is often severely hampered by ignorance of the genetic determinants of virulence, drug resistance, and clinical outcomes that could be used to identify therapeutic drug targets and forecast patient trajectories 1-5. Taking the newly emergent multidrug-resistant bacteria Mycobacterium abscessus as an example 6, we show that combining high dimensional phenotyping with whole genome sequencing in a phenogenomic analysis can rapidly reveal actionable systems-level insights into bacterial pathobiology. Using in vitro and in vivo phenotyping, we discovered three distinct clusters of isolates, each associated with a different clinical outcome. We combined genome-wide association studies (GWAS) with proteome-wide computational structural modelling 7 to define likely causal variants, and employed direct coupling analysis (DCA) 8 to identify co-evolving, and therefore potentially epistatic, gene networks. We then used in vivo CRISPR-based silencing to validate our findings, defining a novel secretion system controlling virulence in M. abscessus, and illustrating how phenogenomics can reveal critical pathways within emerging pathogenic bacteria.

microbiology↗