Biology subjects

Wilson, D. J.

Publications and source records attributed to Wilson, D. J..

At least 19 recordsLinked to original sources

bioRxiv2025

Identification and Characterization of a Small Molecule Ligand for the Huntingtin-HAP40 Complex

Huntingtons disease (HD) is caused by a CAG repeat expansion mutation, giving rise to a polyglutamine expansion in the huntingtin (HTT). However, the explicit molecular functions of HTT and opportunities for direct pharmacological modulation remain incompletely understood. Here, we report the discovery of a small molecule ligand for the full-length HTT protein in complex with its partner, HAP40. Using affinity selection mass spectrometry (AS-MS), we identified a stereoselective binder, whose binding was characterized by surface plasmon resonance, hydrogen-deuterium exchange mass spectrometry, and cryo-electron microscopy at 2.3 [A] resolution. The ligand binds HTT-HAP40 in vitro with single-digit micromolar affinity and one-to-one stoichiometry at a druggable interface previously predicted computationally. In silico studies predicted and experimental analyses confirmed the (R)-enantiomer as the eutomer and initial structure activity relationship was established experimentally. This work details a structurally-validated chemical scaffold and highlights a ligandable pocket which could enable development of chemical probes for probing HTT biology, as well as therapeutics such as degraders and imaging agents for HD.

pharmacology and toxicology↗

bioRxiv2025

Allostery links hACE2 binding, pan-variant neutralisation and helical extension in the SARS-CoV-2 Spike protein

The SARS-CoV-2 spike protein is highly antigenic, with epitopes in three distinct regions of the receptor binding domain (RBD) alone that have known mechanisms of neutralization. In previous work, we predicted a fourth RBD epitope based on allosteric conformational perturbations measured by hydrogen-deuterium exchange mass spectrometry (HDX-MS) upon complexation with the canonical spike protein target, human angiotensin-converting enzyme 2 (hACE2). We subsequently identified a pan-neutralizing antibody (ICO-hu104) with the predicted epitope, however, as the epitope was somewhat distant from the hACE2 binding interface, and our previous work limited to the spike RBD, the neutralization mechanism was unclear. Using HDX-MS, we investigated the binding of ICO-hu104 to the full-length SARS-CoV-2 spike protein from Wuhan, Delta and Omicron variants. We demonstrate that binding of ICO-hu104 at its epitope results in an increase in deuterium uptake in the distant HR1 domain for variants of concern, which in a biological context could be indicative of destabilisation of the helices within this region, promoting S1 shedding or failure of helical extension during S2-mediated fusion. This is supported by our computational modelling, highlighting propagation of allosteric effects to the S2 coiled-coil region. Collectively, this work demonstrates an alternative neutralization mechanism for ICO-hu104 which is distinct from its first-generation predecessors and thus opens alternative avenues targeting non-RBD epitopes through assessment of allosteric perturbations. HighlightsO_LIHDX-MS reveals decreased deuterium uptake within the HR1 region of S2 for SARS-CoV-2 spike protein for variants of concern when bound to ICO-hu104. C_LIO_LIComputational modelling validates high allosteric coupling between ICO-hu104 epitope and HR1 region. C_LIO_LISuggests an alternative neutralization mechanism from its predecessor ICO-hu23, whereby destabilisation of helices within the HR1 region promotes S1 shedding and/or failure of helical extension during S2-mediated fusion. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/635280v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1175bdborg.highwire.dtl.DTLVardef@8fb17borg.highwire.dtl.DTLVardef@1cd13f7org.highwire.dtl.DTLVardef@d9c121_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

The structural influence of the oncogenic driver mutation N642H in the STAT5B SH2 domain

The point mutation N642H of the signal transducer and activator of transcription 5B (STAT5B) protein is associated with aggressive and drug-resistant forms of leukemia. This mutation is thought to promote cancer due to hyperactivation of STAT5B caused by increased stability of the active, parallel dimer state. However, the molecular mechanism leading to this stabilization is not well understood as there is currently no structure of the parallel dimer. To investigate the mutations mechanism of action, we conducted extensive all-atom molecular dynamics simula-tions of multiple oligomeric forms of both STAT5B and STAT5BN642H, including a model for the parallel dimer. The N642H mutation directly affects the hydrogen bonding network within the phosphotyrosine (pY)-binding pocket of the parallel dimer, enhancing the pY-binding in-teraction. The simulations indicate that apo STAT5B is highly flexible, exploring a diverse conformational space. In contrast, apo STAT5BN642H accesses two distinct conformational states, one of which resembles the conformation of the parallel dimer. The simulation predic-tions of the effects of the mutation on structure and dynamics are supported by the results of hydrogen-deuterium exchange (HDX) mass spectrometry measurements carried out on STAT5B and STAT5BN642H in which a phosphopeptide was used to mimic the effects of parallel dimer-ization on the SH2 domain. The molecular-level information uncovered in this work contributes to our understanding of STAT5B hyperactivation by the N642H mutation and could help pave the way for novel therapeutic strategies targeting this mutation.

biophysics↗

bioRxiv2023

Recruitment of FBXO22 for Targeted Degradation of NSD2

Targeted protein degradation (TPD) is an emerging therapeutic strategy that would benefit from new chemical entities with which to recruit a wider variety of ubiquitin E3 ligases to target proteins for proteasomal degradation. Here, we describe a TPD strategy involving the recruitment of FBXO22 to induce degradation of the histone methyltransferase and oncogene NSD2. UNC8732 facilitates FBXO22-mediated degradation of NSD2 in acute lymphoblastic leukemia cells harboring the NSD2 gain of function mutation p.E1099K, resulting in growth suppression, apoptosis, and reversal of drug resistance. The primary amine of UNC8732 is metabolized to an aldehyde species, which engages C326 of FBXO22 in a covalent and reversible manner to recruit the SCFFBXO22 Cullin complex. We further demonstrate that a previously reported alkyl amine-containing degrader targeting XIAP is similarly dependent on SCFFBXO22. Overall, we present a highly potent NSD2 degrader for the exploration of NSD2 disease phenotypes and a novel FBXO22-dependent TPD strategy.

biochemistry↗

bioRxiv2023

In Vitro Safety Signals for Potential Clinical Development of the Anti-Inflammatory Pregnane X Receptor Agonist FKK6

Background and purposeBased on the mimicry of microbial metabolites, functionalized indoles were demonstrated as the ligands and agonists of the pregnane X receptor (PXR). The lead indole, FKK6, displayed PXR-dependent protective effects in DSS-induced colitis in mice and in vitro cytokine-treated intestinal organoid cultures. Here, we performed the initial in vitro pharmacological profiling of FKK6. Experimental approachA complex series of cell-free and cell-based assays were employed. The organic synthesis, and advanced analytical chemistry methods were used. Key resultsFKK6-PXR interactions were characterized by hydrogen-deuterium exchange mass spectrometry. Screening FKK6 against potential cellular off-targets revealed high PXR selectivity. FKK6 has poor aqueous solubility but was highly soluble in simulated gastric and intestinal fluids. FKK6 was bound to plasma proteins and chemically stable in plasma. The partition coefficient of FKK6 was 2.70, and FKK6 moderately partitioned into red blood cells. In Caco2 cells, FKK6 displayed high permeability (A-B: 22.8 x 10-6 cm.s-1) and no active efflux. These data are indicative of essentially complete in vivo absorption of FKK6. FKK6 was rapidly metabolized by cytochromes P450, notably by CYP3A4 in human liver microsomes. Two oxidized FKK6 derivatives, including N6-oxide and C19-phenol, were detected, and these metabolites had 5-7 x lower potency as PXR agonists than FKK6. This implies that despite high intestinal absorption, FKK6 is rapidly eliminated by the liver, and its PXR effects are predicted to be predominantly in the intestines. Conclusion and implicationsThe PXR ligand and agonist FKK6 has a suitable pharmacological profile supporting its potential preclinical development. BULLET POINT SUMMARYWhat is already known: O_LIMicrobial metabolite mimic FKK6 is a hPXR agonist with anti-inflammatory properties in mice and human. C_LIO_LIThe in vitro PXR binding, absorption, and metabolism have not been completely characterized. C_LI What this study adds: O_LIPXR selectivity with unique binding mode, high intestinal cell permeability, rapid and complex microsomal metabolism. C_LIO_LIInitial testing for predicted metabolites shows reduced potency as PXR agonists. C_LI Clinical significance: O_LIPXR effects of FKK6 are predicted to be predominantly in the intestines. C_LIO_LIFKK6 has a suitable pharmacological profile supporting its potential preclinical development. C_LI

biochemistry↗

bioRxiv2023

Microbially Driven Reversible Actuation and Color Changing Materials

A common feature of natural living systems that is underexplored in the field of engineered living materials (ELMs) is macroscale mechanical actuation, as driven by active cellular processes. Here we demonstrate an ELM wherein Escherichia coli drives the reversible swelling and de-swelling actuation of a pH-responsive hydrogel by producing or consuming acidic metabolites. We covalently incorporated a novel synthetic pH indicator dye into the hydrogel network that complements the hydrogel actuation with coordinated color change. Acid production or consumption is controlled by media composition and multiple hydrogel form factors are explored. This approach represents a new form of biologically driven actuation that could be compatible with a range of responsive hydrogel applications.

bioengineering↗

bioRxiv2022

Activation of the fear-responsive anterior hypothalamic area promotes avoidance and triggers compulsive grooming behavior in mice

The anterior hypothalamic area (AHA) is a key brain region for orchestrating defensive behaviors. Here, we first examined AHA activity patterns during fear conditioning using in vivo functional imaging. We observed that neuronal activity in the AHA increases during both foot shock delivery and foot-shock associated auditory cues. Moreover, we used a combination of optogenetics and behavioral assays to determine the functional connectivity between the ventromedial hypothalamus (VMH) and the AHA. We found that photoactivation of the VMH[->]AHA pathway is aversive and triggers compulsive grooming behavior. Furthermore, we observed spatial and temporal changes of grooming behavior during the periods following VMH[->]AHA photoactivation. Interestingly, whole brain metabolic mapping using positron emission tomography (PET) combined with optogenetic activation of the VMH[->]AHA pathway in anesthetized mice revealed the amygdala as a downstream area activated by the stimulation of this pathway. Together, our findings show that the AHA responds to threat and that such increases in activity are sufficient to trigger compulsive grooming behavior. Thus, our results may help to understand some neuropsychiatric disorders characterized by repetitive and compulsive behaviors.

neuroscience↗

bioRxiv2022

Innate Conformational Dynamics Drive Binding Specificity in Anti-Apoptotic Proteins Mcl-1 and Bcl-2

The structurally conserved B-cell Lymphoma 2 (Bcl-2) family of proteins function to promote or inhibit apoptosis through an exceedingly complex web of specific, intrafamilial protein-protein interactions. The critical role of these proteins in lymphomas and other cancers has motivated a widespread interest in understanding the molecular mechanisms that drive specificity in Bcl-2 family interactions. However, the substantial structural similarity amongst Bcl-2 homologues has made it difficult to rationalize the highly specific (and often divergent) binding behavior exhibited by these proteins using conventional structural arguments. In this work, we use millisecond hydrogen deuterium exchange mass spectrometry to explore shifts in conformational dynamics associated with binding partner engagement in Bcl-2 family proteins Bcl-2 and Mcl-1. Using this approach, we reveal that, specifically for Mcl-1, binding specificity arises largely from protein-specific dynamic modes that are accessed in the unbound state. This work has implications for exploring the evolution of internally regulated biological systems composed of structurally similar proteins, and for the development of drugs targeting Bcl-2 family proteins for promotion of apoptosis in cancer. General Interest StatementThis work reveals how a group of proteins, which are highly similar in structure, can form a complex web of highly specific protein-protein interactions that drive programmed cell death (apoptosis) in cancer.

molecular biology↗

bioRxiv2022

Niche-specific genome degradation and convergent evolution shaping Staphylococcus aureus adaptation during severe infections

During severe infections, Staphylococcus aureus moves from its colonising sites to blood and tissues, and is exposed to new selective pressures, thus potentially driving adaptive evolution. Previous studies have shown the key role of the agr locus in S. aureus pathoadaptation, however a more comprehensive characterisation of genetic signatures of bacterial adaptation may enable prediction of clinical outcomes and reveal new targets for treatment and prevention of these infections. Here, we measured adaptation using within-host evolution analysis of 2,590 S. aureus genomes from 396 independent episodes of infection. By capturing a comprehensive repertoire of single-nucleotide and structural genome variations, we found evidence of a distinctive evolutionary pattern within the infecting populations compared to colonising bacteria. These invasive strains had up to 20-fold enrichments for genome degradation signatures and displayed significantly convergent mutations in a distinctive set of genes, linked to antibiotic response and pathogenesis. In addition to agr-mediated adaptation we identified non-canonical, genome-wide significant loci including sucA-sucB and stp1. The prevalence of adaptive changes increased with infection extent, emphasising the clinical significance of these signatures. These findings provide a high-resolution picture of the molecular changes when S. aureus transitions from colonisation to severe infection and may inform correlation of infection outcomes with adaptation signatures.

genomics↗

bioRxiv2021

Genome-wide association studies of global Mycobacterium tuberculosis resistance to thirteen antimicrobials in 10,228 genomes

The emergence of drug resistant tuberculosis is a major global public health concern that threatens the ability to control the disease. Whole genome sequencing as a tool to rapidly diagnose resistant infections can transform patient treatment and clinical practice. While resistance mechanisms are well understood for some drugs, there are likely many mechanisms yet to be uncovered, particularly for new and repurposed drugs. We sequenced 10,228 Mycobacterium tuberculosis (MTB) isolates worldwide and determined the minimum inhibitory concentration (MIC) on a grid of twofold concentration dilutions for 13 antimicrobials using quantitative microtiter plate assays. We performed oligopeptide- and oligonucleotide-based genome-wide association studies using linear mixed models to discover resistance-conferring mechanisms not currently catalogued. Use of MIC over binary resistance phenotypes increased heritability for the new and repurposed drugs by 26-37%, increasing our ability to detect novel associations. For all drugs, we discovered uncatalogued variants associated with MIC, including in the Rv1218c promoter binding site of the transcriptional repressor Rv1219c (isoniazid), upstream of the vapBC20 operon that cleaves 23S rRNA (linezolid) and in the region encoding an -helix lining the active site of Cyp142 (clofazimine, all p<10-7.7). We observed that artefactual signals of cross resistance could be unravelled based on the relative effect size on MIC. Our study demonstrates the ability of very large-scale studies to substantially improve our knowledge of genetic variants associated with antimicrobial resistance in M. tuberculosis.

genomics↗

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↗

bioRxiv2021

Evolutionary processes driving the rise and fall of Staphylococcus aureus ST239, a dominant hybrid pathogen

Staphylococcus aureus ST239 has been one of the most successful epidemic MRSA strains, and one of the leading causes of healthcare-associated MRSA infections. Here we investigate the evolution of ST239 using a combination of computational and experimental approaches. ST239 is thought to have emerged by a large scale chromosomal replacement event in which an ST8 clone acquired approximately 600 kb of DNA from an ST30 clone. Analysis of large-scale genomic data sets allowed us to confirm and refine the model of the origin of ST239. Importantly, we found that ST239 originated between the 1920s and 1945, implying that this MRSA lineage evolved at least 14 years before the clinical introduction of methicillin. Molecular evolution within ST239 has been dominated by purifying selection, although we found some evidence that the acquired region of the genome has evolved rapidly as a result of relaxed selective constraints. Crucially, we found that ST239 isolates have low competitive ability relative to both ST30 and ST8, demonstrating that this hybrid lineage is characterized by low fitness. We also found evidence of positive selection in a small number of genes involved in antibiotic resistance and virulence, suggesting that ST239 has evolved towards an increasingly pathogenic lifestyle. Collectively, these results support the view that low fitness has driven the recent decline of ST239, and highlight the challenge of using evolutionary approaches to understand the dynamics of pathogenic bacteria.

evolutionary biology↗

bioRxiv2021

Extracellular Matrix Dysfunction in Sorsby Patient-Derived Retinal Pigment Epithelium

Sorsby Fundus Dystrophy (SFD) is a rare form of macular degeneration that is clinically similar to age-related macular degeneration (AMD), and a histologic hallmark of SFD is a thick layer of extracellular deposits beneath the retinal pigment epithelium (RPE). Previous studies of SFD patient-induced pluripotent stem cell (iPSC) derived RPE differ as to whether these cultures recapitulate this key clinical feature by forming increased drusenoid deposits. The primary purpose of this study is to examine whether SFD patient-derived iPSC-RPE form basal deposits similar to what is found in affected family member SFD globes and to determine whether SFD iPSC RPE may be more oxidatively stressed. We performed a careful comparison of iPSC RPE from three control individuals, multiple iPSC clones from two SFD patients iPSC RPE, and post-mortem eyes of affected SFD family members. We also examined the effect of CRISPR-Cas9 gene correction of the S204C TIMP3 mutation on RPE phenotype. Finally, targeted metabolomics analysis with liquid chromatography and mass spectrometry analysis and stable isotope-labeled metabolite analysis was performed to determine whether SFD RPE are more oxidatively stressed. We found that SFD iPSC-RPE formed significantly more sub-RPE deposits ([~]6-90 m in height) compared to control RPE at 8 weeks. These deposits were similar in composition to the basal laminar drusen found in SFD family member globes by immunofluorescence staining and TEM imaging. S204C TIMP3 correction by CRISPR-Cas9 gene editing in SFD iPSC RPE cells resulted in significantly reduced basal laminar and sub-RPE calcium deposits. We detected a [~]18-fold increase in TIMP3 accumulation in the extracellular matrix (ECM) of SFD RPE, and targeted metabolomics showed that intracellular 4-hydroxyproline, a major breakdown product of collagen, is significantly elevated in SFD RPE, suggesting increased ECM turnover. Finally, SFD RPE cells have decreased intracellular reduced glutathione and were found to be more vulnerable to oxidative stress. Our findings suggest that elements of SFD pathology can be demonstrated in culture which may lead to insights into disease mechanisms.

cell biology↗

bioRxiv2020

Conformational dynamics of -synuclein during the interaction with phospholipid nanodiscs by Millisecond Hydrogen Deuterium Exchange Mass Spectrometry

Both normal and pathological functions of -synuclein (SN), an abundant protein in the central and peripheral nervous system, have been linked to its interaction with membrane lipid bilayers. The ability to characterize structural transitions of SN upon membrane complexation will clarify molecular mechanisms associated with SN-linked pathologies, including Parkinsons disease (PD), Multiple Systems Atrophy and other synucleinopathies. In this work, Time-Resolved ElectroSpray Ionization Hydrogen/ Deuterium Exchange Mass Spectrometry (TRESI-HDX-MS) was employed to acquire a detailed picture of SNs conformational transitions as it undergoes complexation with nanodisc membrane mimics. Using this approach, SN interactions with DMPC nanodiscs were shown to be rapid exchanging and to have a little impact on the SN conformational ensemble. Interactions with nanodiscs containing lipids known to promote amyloidogenesis (e.g., POPG), on the other hand, were observed to induce substantial and specific changes in the SN conformational ensemble. Ultimately, we identify a region corresponding residues 19-28 and 45-57 of the SN sequence that is uniquely impacted by interactions with amyloidogenic lipid membranes and may therefore play a critical role in pathogenic aggregation.

biochemistry↗

bioRxiv2019

GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters such as dN/dS, but analysing very large datasets poses a major statistical challenge. Here I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: (i) it is fast no matter how large the sample size and (ii) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well-estimated even when genomegaMaps simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in M. tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

genomics↗

bioRxiv2018

Panton-Valentine leukocidin is the key determinant of Staphylococcus aureus pyomyositis in a bacterial genome-wide association study

Pyomyositis is a severe bacterial infection of skeletal muscle, commonly affecting children in tropical regions and predominantly caused by Staphylococcus aureus. To understand the contribution of bacterial genomic factors to pyomyositis, we conducted a genome-wide association study of S. aureus cultured from 101 children with pyomyositis and 417 children with asymptomatic nasal carriage attending the Angkor Hospital for Children in Cambodia. We found a strong relationship between bacterial genetic variation and pyomyositis, with estimated heritability 63.8% (95% CI 49.2-78.4%). The presence of the Panton-Valentine leucocidin (PVL) locus increased the odds of pyomyositis 130-fold (p =10-17.9). The signal of association mapped both to the PVL-coding sequence and the sequence immediately upstream. Together these regions explained > 99.9% of heritability. Our results establish staphylococcal pyomyositis, like tetanus and diphtheria, as critically dependent on expression of a single toxin and demonstrate the potential for association studies to identify specific bacterial genes promoting severe human disease.

microbiology↗

bioRxiv2018

Bayesian inference of ancestral dates on bacterial phylogenetic trees

The sequencing and comparative analysis of a collection of bacterial genomes from a single species or lineage of interest can lead to key insights into its evolution, ecology or epidemiology. The tool of choice for such a study is often to build a phylogenetic tree, and more specifically when possible a dated phylogeny, in which the dates of all common ancestors are estimated. Here we propose a new Bayesian methodology to construct dated phylogenies which is specifically designed for bacterial genomics. Unlike previous Bayesian methods aimed at building dated phylogenies, we consider that the phylogenetic relationships between the genomes have been previously evaluated using a standard phylogenetic method, which makes our methodology much faster and scalable. This two-steps approach also allows us to directly exploit existing phylogenetic methods that detect bacterial recombination, and therefore to account for the effect of recombination in the construction of a dated phylogeny. We analysed many simulated datasets in order to benchmark the performance of our approach in a wide range of situations. Furthermore, we present applications to three different real datasets from recent bacterial genomic studies. Our methodology is implemented in a R package called BactDating which is freely available for download at https://github.com/xavierdidelot/BactDating.

bioinformatics↗

bioRxiv2017

Bayesian Reconstruction of Transmission within Outbreaks using Genomic Variants

Pathogen genome sequencing can reveal details of transmission histories and is a powerful tool in the fight against infectious disease. In particular, within-host pathogen genomic variants identified through heterozygous nucleotide base calls are a potential source of information to identify linked cases and infer direction and time of transmission. However, using such data effectively to model disease transmission presents a number of challenges, including differentiating genuine variants from those observed due to sequencing error, as well as the specification of a realistic model for within-host pathogen population dynamics.\n\nHere we propose a new Bayesian approach to transmission inference, BadTrIP (BAyesian epiDemiological TRansmission Inference from Polymorphisms), that explicitly models evolution of pathogen populations in an outbreak, transmission (including transmission bottlenecks), and sequencing error. BadTrIP enables the inference of host-to-host transmission from pathogen sequencing data and epidemiological data. By assuming that genomic variants are unlinked, our method does not require the computationally intensive and unreliable reconstruction of individual haplotypes. Using simulations we show that BadTrIP is robust in most scenarios and can accurately infer transmission events by efficiently combining information from genetic and epidemiological sources; thanks to its realistic model of pathogen evolution and the inclusion of epidemiological data, BadTrIP is also more accurate than existing approaches. BadTrIP is distributed as an open source package (https://bitbucket.org/nicofmay/badtrip) for the phylogenetic software BEAST2.\n\nWe apply our method to reconstruct transmission history at the early stages of the 2014 Ebola outbreak, showcasing the power of within-host genomic variants to reconstruct transmission events.\n\nAuthor SummaryWe present a new tool to reconstruct transmission events within outbreaks. Our approach makes use of pathogen genetic information, notably genetic variants at low frequency within host that are usually discarded, and combines it with epidemiological information of host exposure to infection. This leads to accurate reconstruction of transmission even in cases where abundant within-host pathogen genetic variation and weak transmission bottlenecks (multiple pathogen units colonising a new host at transmission) would otherwise make inference difficult due to the transmission history differing from the pathogen evolution history inferred from pathogen isolets. Also, the use of within-host pathogen genomic variants increases the resolution of the reconstruction of the transmission tree even in scenarios with limited within-outbreak pathogen genetic diversity: within-host pathogen populations that appear identical at the level of consensus sequences can be discriminated using within-host variants. Our Bayesian approach provides a measure of the confidence in different possible transmission histories, and is published as open source software. We show with simulations and with an analysis of the beginning of the 2014 Ebola outbreak that our approach is applicable in many scenarios, improves our understanding of transmission dynamics, and will contribute to finding and limiting sources and routes of transmission, and therefore preventing the spread of infectious disease.

genetics↗