Biology subjects

Clark, T. G.

Publications and source records attributed to Clark, T. G..

At least 19 recordsLinked to original sources

bioRxiv2026

A Plasmodium falciparum Pangenome Resource to Drive Structural Variant Discovery and to assist Malaria Control

Plasmodium falciparum, the deadliest causative agent of malaria, harbours extensive structural variation that underlies key biological processes including drug resistance and diagnostic evasion. Here, we present PfPan, a P. falciparum pangenome constructed from 13 geographically diverse high-quality reference genomes using Minigraph-Cactus, adding 4.7 Mb of sequence beyond the 3D7 linear reference. We identify over 5,000 structural variants across the reference genomes and demonstrate improved genotyping using the vg toolkit compared to linear reference-based approaches, with comparable performance for small variant discovery. Benchmarking against assembly-derived truth sets confirms pangenome superiority for structural variant detection, particularly at complex and hypervariable loci. Applying PfPan to 878 globally sampled P. falciparum whole-genome sequences, we characterise the population-level frequency of clinically relevant structural variants, including a high-frequency 10.4 kb insertion at the drug resistance-linked gch1 locus, and explore deletions upstream of the gene encoding the diagnostic target HRP2. PfPan provides a foundational resource for reducing reference bias in P. falciparum genomic surveillance and offers a framework for improved detection of variants relevant to drug resistance and malaria control.

genomics↗

bioRxiv2026

Focal inbreeding and clonal transmission of Plasmodium vivax in pre-elimination Vietnam

Although malaria prevalence in Vietnam has markedly declined and the country presses closer to elimination, a highly focal reservoir of Plasmodium vivax malaria persists in its forested and border regions, threatening the countrys 2030 elimination targets. Genomic surveillance of malaria parasites can be a vital tool to produce fine-scale insights into the changing population dynamics of parasite populations, especially in population decline. Here, we analysed the genomic diversity of 18 newly sequenced P. vivax isolates from the Central Highlands, South Central Coast, and Southeastern regions of Vietnam collected in 2019, analysing them alongside 115 publicly available sequences from Vietnam collected between 2009-2016. Over these 10 years, infections became increasingly monoclonal, transmission remained highly focal, and the overall population structure was weak. Geographic factors, and not temporal factors, were a major driver of genetic substructure. Identity-by-descent (IBD) analyses revealed pockets of inbreeding in transmission hotspots, and high relatedness in parasites from within the same or adjacent provinces. Whilst within-population haplotype-based testing revealed minimal selection pressures on the 2009-2016 and 2019 populations, we observed multiple signals of differential selection of genetic variants involved in life-cycle specific processes. Overall, our work provides the most recent assessment of the genomic diversity of P. vivax in Vietnam, revealing relics of evolution in a parasite population in decline. Continued genomic surveillance, especially in outbreak contexts, and with more recent samples will be a crucial strategy to inform malaria elimination activities. Author SummaryPlasmodium vivax is the most geographically widespread malaria parasite and the predominant species in the Greater Mekong Subregion. In Vietnam, P. vivax malaria continues to persist in remote forested settings and along its international borders. Using genomic approaches, we analysed 133 P. vivax genomes from the Central Highlands, South Central Coast, and Southeastern regions of Vietnam, including 18 newly sequenced isolates collected in 2019 and 115 publicly available genomes sampled between 2009 and 2016. Our work describes the evolutionary and genetic consequences of intensive control efforts that have led to decreasing transmission and population decline. We found decreasing infection complexity and increasing clonal inbreeding, which suggests localised transmission of clonal lineages in transmission hotspots. Over the 10-year sampling period, we observed consistent allele frequencies in putative drug resistance loci, suggesting an absence of drug-driven directional selection. Our findings highlight the importance of genomic surveillance in monitoring parasite persistence, which will be critical for guiding public health decisions to sustain progress towards malaria elimination.

genomics↗

bioRxiv2026

Menaquinone depletion resensitises bedaquiline-resistant tuberculosis

Tuberculosis remains a leading cause of global mortality, and rising bedaquiline resistance threatens the effectiveness of current drug-resistant treatment regimens. Bedaquiline resistance typically arises through mutations in Rv0678 that upregulate drug efflux and confer cross-resistance to multiple drug classes. Here, we identify and optimise a chemical series targeting MenG, a central enzyme in the menaquinone biosynthesis pathway, yielding potent bactericidal inhibitors with in vivo efficacy. Strikingly, MenG inhibition restored bedaquiline susceptibility in efflux-mediated resistant strains, an effect confirmed in vivo where combination therapy achieved a 99.8% reduction in bacterial burden compared with bedaquiline alone. Potentiation also extended to pretomanid and other key agents. Disruption of upstream menaquinone and shikimate pathway enzymes produced similar resensitisation, establishing these pathways as tractable targets for restoring drug susceptibility in Mycobacterium tuberculosis. These findings provide a novel strategy to overcome bedaquiline resistance and strengthen future regimens for efflux-mediated drug-resistant tuberculosis.

microbiology↗

bioRxiv2025

The First Chromosome-Scale Genome Assembly for Dermacentor reticulatus: A Key Vector of Tick-Borne Pathogens of Public and Veterinary Health Importance in Europe

BackgroundDermacentor reticulatus is a key tick species across Europe and an established vector of multiple pathogens that affect both human and animal health. Despite its significant role in disease transmission, genomic data for this species remain limited. Here, we present the first chromosome-scale genome assembly of D. reticulatus, constructed using Oxford Nanopore long-read sequencing data. MethodsHigh molecular weight DNA was extracted from a female Dermacentor reticulatus collected in Devon, UK, and sequenced using Oxford Nanopore long-read technology. Genome assemblies were generated using both guided and unguided approaches, followed by repeat masking, gene prediction, and functional annotation. Genome completeness was assessed using BUSCO, and comparative, phylogenetic, and functional analyses were performed against other Dermacentor and tick species. ResultsThis chromosome-scale genome assembly revealed a repeat-rich genome, with approximately 61.9% of the total sequence consisting of repetitive elements. Benchmarking universal single-copy ortholog (BUSCO) analysis demonstrated strong genome completeness, with guided assembly (chromosome) achieving a score of 97.1%, closely matching those of related Dermacentor species. For comparison, unguided assembly (scaffold) yielded a BUSCO score of 96.7%. Gene annotation following repeat masking resulted in BUSCO completeness scores of 95.1% (guided) and 95.0% (unguided). Functional characterisation included Pfam domain assignment and Gene Ontology analysis. Additionally, we assembled the mitochondrial genome (15,103 bp), comprising 38 genes, providing further insight into D. reticulatus phylogenetic placement. ConclusionsThis genomic resource establishes a foundation for functional genomics, evolutionary studies and supports future research in vector biology and the control of tick-borne diseases.

genomics↗

bioRxiv2025

Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants

BACKGROUNDCiprofloxacin resistant Klebsiella pneumoniae is common or emerging in many geographies, and knowledge of local resistance rates is important for empirical therapy. Whilst there are known K. pneumoniae ciprofloxacin resistance determinants, there is a lack of systematic data on the effect of determinants, alone and in combination, and there are no publicly accessible tools for predicting resistance from whole genome sequence data. METHODSThe KlebNET-GSP AMR Genotype-Phenotype Group aggregated a matched genotype-phenotype dataset of n=12,167 K. pneumoniae species complex (KpSC) isolates from 27 countries between 2001-2021. We developed a rules-based classifier to predict ciprofloxacin resistance by categorizing the number of quinolone resistance determining regions mutations in gyrA and parC, the number of plasmid-mediated quinolone resistance genes, and the presence/absence of aac(6')-Ib-cr (which can acetylate ciprofloxacin). Predictive performance was assessed using the discovery dataset, for which we re-phenotyped discrepant isolates; and validated using externally contributed datasets (n=7,030 KpSC isolates). RESULTSThe rules-based classifier predicted R vs S/I with categorical agreement, sensitivity, and specificity >96%, and major/very major error rates <4%. Performance was similar across diverse KpSC sources (human, animal, other), species, and intra-species lineages. External validation of the classifier yielded overall 93.12% categorical agreement [95% confidence interval (CI), 92.50-93.74%], 8.65% major errors [95% CI, 7.34-9.97%], and 6.20% very major errors [95% CI, 5.51-6.90%]. We implemented the classifier in Kleborate, a command-line tool that is integrated into the Pathogenwatch web platform. Using this to assess the global distribution of ciprofloxacin resistance determinants in KpSC genomes available in Pathogenwatch (n=31,319, from 109 countries between years 2000-2023), we observed a significant positive association between national quinolone consumption rates and predicted ciprofloxacin resistance (R2=0.20, p=0.004). CONCLUSIONS Ciprofloxacin resistance phenotypes can be reasonably predicted from genotypes, which is sufficient for informing surveillance. However, unexplained resistance remains and accuracy is insufficient for clinical applications. We demonstrate the value of aggregating genotype-phenotype data to explore resistance mechanisms and develop predictors, but highlight complexities in combining phenotype data from different assays and standards.

genomics↗

bioRxiv2025

A novel tool for designing targeted gene amplicons and an optimised set of primers for high-throughput sequencing in tuberculosis genomic studies

Amplicon sequencing (Amp-Seq) of Mycobacterium tuberculosis genes associated with drug resistance and strain typing offers a cost-effective approach for profiling infections and tailoring the clinical management of tuberculosis. However, Amp-Seq assays require continual updates to incorporate new loci and mutations linked to drug resistance. We introduce TOAST (Tuberculosis Optimised Amplicon Sequencing Tool), a customisable software tool that optimises amplicon design across any loci and sequencing platforms (e.g., Illumina, Oxford Nanopore Technology (ONT)), informed by an integrated and expanding database of mutations from >50K M. tuberculosis isolates. TOAST software allows users to define parameters such as melting temperature, amplicon length, and GC content, while accounting for potential primer interactions like homodimer formation and non-specific binding. To demonstrate its robustness, we designed 33 amplicons in a single multiplex group, prioritising coverage of resistance-associated mutations in the form of insertions, deletions and single nucleotide polymorphisms (SNPs) for 13 different drugs. An efficient experimental protocol was established, resulting in a minimum depth coverage exceeding 50-fold for each amplicon region as validated by ONT sequencing of two clinical samples with multi-drug resistance. TOAST software enables the development of Amp-Seq assays for the rapid detection of drug-resistant TB, enhancing treatment strategies, improving outcomes, and curbing resistant infections. The cost-effectiveness and adaptability of Amp-Seq approaches make it crucial for managing TB in resource-limited settings, advancing global control efforts.

bioinformatics↗

bioRxiv2024

Gametocyte production and transmission fitness of African and Asian Plasmodium falciparum isolates with differential susceptibility to artemisinins

The emergence of Plasmodium falciparum parasites partially resistant to artemisinins (ART-R) poses a significant threat to recent gains in malaria control. ART-R has been associated with PfKelch13 (K13) mutations, which differ in fitness costs. This study investigates the gametocyte production and transmission fitness of African and Asian P. falciparum isolates with different K13 genotypes across multiple mosquito species. We tested three ART-sensitive (ART-S) isolates (NF54, NF135, NF180) and three ART-R isolates (ARN1G, 3815, PAT-023) for sexual conversion and transmission to Anopheles stephensi, An. gambiae and An. coluzzii. ART-R levels were quantified in vitro using the Ring-stage Survival Assay (RSA), and the transmission-reducing effects of dihydroartemisinin (DHA) on mature gametocytes were assessed. Results showed that ART-S parasite lines consistently produced gametocytes and transmitted effectively in all three mosquito species. ART-R isolates showed variability: ARN1G maintained high transmission levels, whereas 3815 showed limited transmission potential despite higher sporozoite loads in An. coluzzii. The African ART-R isolate PAT-023 demonstrated low gametocyte commitment but was transmitted efficiently in both An. gambiae and An. coluzzii. DHA exposure reduced mosquito infectivity for all isolates, regardless of K13 genotype. These findings, based on a limited number of field isolates, suggest that ART-R parasites remain transmissible across different Anopheles species. However, ART-R does not appear to confer a direct transmission advantage. This study highlights the complexity of ART-R dynamics and underscores the need for further research to inform malaria control strategies in regions where ART-R parasites are circulating.

microbiology↗

bioRxiv2024

A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission

BackgroundMixed infection with multiple strains of the same pathogen in a single host can present clinical and analytical challenges. Whole genome sequence (WGS) data can identify signals of multiple strains in samples, though the precision of previous methods can be improved. Here, we present MixInfect2, a new tool to accurately detect mixed samples from Mycobacterium tuberculosis WGS data. We then evaluate three approaches for reconstructing the underlying mixed constituent strain sequences. This allows these samples to be included in downstream analysis to gain insights into the epidemiology and transmission of mixed infections. MethodsWe employed a Gaussian mixture model to cluster allele frequencies at mixed sites (hSNPs) in each sample to identify signals of multiple strains. Building upon our previous tool, MixInfect, we increased the accuracy of classifying in vitro mixed samples through multiple improvements to the bioinformatic pipeline. Major and minor proportion constituent strains were reconstructed using three approaches and assessed by comparing the estimated sequence to the known constituent strain sequence. Lastly, mixed infections in a real-world Mycobacterium tuberculosis population from Moldova were detected with MixInfect2 and clusters of recent transmission that included major and minor constituent strains were built. ResultsAll 36/36 in vitro mixed and 12/12 non-mixed samples were correctly classified with MixInfect2, and major strain proportions estimated with high accuracy, outperforming previous tools. Reconstructed major strain sequences closely matched the true constituent sequence by taking the allele at the highest frequency at hSNPs, while the best performing approach to reconstruct the minor proportion strain sequence was identifying the closest non-mixed isolate in the same population, though no approach was effective when the minor strain proportion was at 5%. Finally, fewer mixed infections were identified in Moldova than previous estimates (6.6% vs 17.4%) and we found multiple instances where the constituent strains of mixed samples were present in transmission clusters. ConclusionsMixInfect2 accurately detects samples with evidence of mixed infection from WGS data and provides an excellent estimate of the mixture proportions. While there are limitations in reconstructing the constituent strain sequences of mixed samples, we present recommendations for the best approach to include these isolates in further analyses.

genomics↗

bioRxiv2024

Diversity, functional classification and genotyping of SHV β-lactamases in Klebsiella pneumoniae

Interpreting phenotypes of blaSHV alleles in Klebsiella pneumoniae genomes is complex. While all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal blaSHV alleles or additional plasmid-borne blaSHV alleles that have extended-spectrum {beta}-lactamase (ESBL) activity and/or {beta}-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/amino acid changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases (e.g., NCBIs Reference Gene Catalog and the {beta}-lactamase database (BLDB)) over the specific functionality of individual SHV protein variants. Therefore, identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific amino-acid substitutions. We then systematically assigned SHV alleles to functional classes (wildtype, ESBL, BLI-resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with current assignments in NCBIs Reference Gene Catalog and/or BLDB (21 to wildtype, 12 to ESBL, 4 to BLI-resistant). Phylogenetic and comparative genomic analyses support that; i) SHV-1 (encoded by blaSHV-1) is the ancestral chromosomal variant; ii) ESBL and BLI-resistant variants have evolved multiple times through parallel substitution mutations; iii) ESBL variants are mostly mobilised to plasmids; iv) BLI-resistant variants mostly result from mutations in chromosomal blaSHV. We used matched genome-phenotype data from the KlebNET-GSP Genotype-Phenotype Group to identify 3,999 K. pneumoniae isolates carrying one or more blaSHV alleles but no other acquired {beta}-lactamases, with which we assessed genotype-phenotype relationships for blaSHV. This collection includes human, animal, and environmental isolates collected between 2001 to 2021 from 24 countries across six continents. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, while most omega-loop substitutions do not. Our data also provide direct support for wildtype assignment of 67 protein variants, including eight that were noted in public databases as ESBL. We reclassified these eight variants as wildtype, because they lack ESBL-associated mutations, and our phenotype data support susceptibility to 3GCs (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164, SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae from genome assemblies), whereby known and novel blaSHV alleles are classified based on causative mutations. Kleborate v2.4.1 was also updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve understanding of resistance mechanisms. Impact statementSince every K. pneumoniae genome has an intrinsic SHV {beta}-lactamase and may also carry additional mobile forms, the correct interpretation of blaSHV genes detected in genome data can be challenging and can lead to K. pneumoniae being misclassified as ESBL-producing. Here, we use matched K. pneumoniae genome and drug susceptibility data contributed from dozens of studies, together with systematic literature review of experimental evidence, to improve our understanding of blaSHV allele variation and mapping of genotype to phenotype. This study shows the value of coordinated data sharing, in this case via the KlebNET-GSP Genotype-Phenotype Group, to improve our understanding of the evolutionary history and functionality of blaSHV genes. The results are captured in an open-source AMR dictionary utilised by the Kleborate genotyping tool, that could easily be incorporated into or used to update other tools and AMR gene databases. This work is part of the wider efforts of the KlebNET-GSP group to develop and support a unified platform tailored for the analysis and interpretation of K. pneumoniae genomes by a wide range of stakeholders. Data summaryBlaSHV allele sequences and class assignments are distributed with Kleborate, v2.4.1, DOI:10.5281/zenodo.10469001. Table S1 provides a summary of blaSHV alleles, including primary accessions, class-modifying mutations, and supporting evidence for class assignments that differ from NCBIs Reference Gene Catalog or BLDB. Whole genome sequence data are publicly available as reads and/or assemblies, individual accessions are given in Table S2; corresponding genotypes and antibiotic susceptibility phenotypes and measurements are available in Tables S3 and S4, respectively.

genomics↗

bioRxiv2024

Uncovering the genetic diversity in Aedes aegypti insecticide resistance genes through global comparative genomics

Insecticides are essential to control the transmission of vector-borne diseases to humans and animals, but their efficacy is being threatened by the spread of resistance across multiple medically important mosquito species. An example of this is Aedes aegypti - a major vector of arboviruses, including Zika, dengue, yellow fever, West Nile, and Chikungunya, with widespread insecticide resistance reported in the Americas and Asia, while data from Africa is more limited. Here we investigate the global genetic diversity in four insecticide resistance associated genes: ace-1, GSTe2, rdl and vgsc. Apart from vgsc, the other genes have been less investigated in Ae. aegypti, and limited genetic diversity information is available. We explore a large whole-genome sequencing dataset of 729 Ae. aegypti across 15 countries including nine in Africa. Among the four genes, we identified 1,829 genetic variants including 474 non-synonymous substitutions, as well as putative copy number variations in GSTe2 and vgsc. Among these are many previously documented insecticide resistance mutations which were present at different frequencies and combinations depending on origin of samples. Global insecticide resistance phenotypic data demonstrated variable resistance in geographic areas with resistant genotypes. These warrant further investigation to assess their functional contribution to insecticide resistant phenotypes and their potential development into genetic panels for operational surveillance. Overall, our work provides the first global catalogue and geographic distribution of known and new amino-acid mutations and duplications that can be used to guide the identification of resistance drivers in Ae. aegypti and thereby support monitoring efforts and strategies for vector control.

genomics↗

bioRxiv2022

Towards environmental detection, quantification, and molecular characterization of Anopheles stephensi and Aedes aegypti from larval breeding sites

The invasion and establishment of An. stephensi mosquitoes in the Horn of Africa represents a significant regional threat, which may jeopardise malaria control, particularly in urban areas which were formally free from disease transmission. Novel vector surveillance methods are urgently needed, both agnostic to mosquito larval morphology, and simple to implement at the sampling stage. Using new multiplex TaqMan assays, specifically targeting An. stephensi and Ae. aegypti, we validated the use of environmental DNA (eDNA) for simultaneous vector detection in shared artificial breeding sites. Study findings demonstrated that An. stephensi and Ae. aegypti eDNA deposited by as few as one second instar larva in 1L of water was detectable. Characterization of molecular insecticide resistance mechanisms, using novel amplicon-sequencing panels for both vector species, was possible from eDNA shed by as few as 32 second instar larvae in 50ml of water. An. stephensi eDNA, derived from emergent pupae for 24 hours, was remarkably stable, and still detectable ~2 weeks later. eDNA surveillance has the potential to be implemented in local endemic communities and points of country entry, to monitor the spread of invasive vector species. Further studies are required to validate the feasibility of this technique under field conditions.

molecular biology↗

bioRxiv2022

A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Pathogen evolution of drug resistance often occurs in a stepwise manner via the accumulation of multiple mutations that in combination have a non-additive impact on fitness, a phenomenon known as epistasis. The evolution of resistance via the accumulation of point mutations in the DHFR genes of Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) has been studied extensively and multiple studies have shown epistatic interactions between these mutations determine the accessible evolutionary trajectories to highly resistant multiple mutations. Here, we simulated these evolutionary trajectories using a model of molecular evolution, parameterized using Rosetta Flex ddG predictions, where selection acts to reduce the target-drug binding affinity. We observe strong agreement with pathways determined using experimentally measured IC50 values of pyrimethamine binding, which suggests binding affinity is strongly predictive of resistance and epistasis in binding affinity strongly influences the order of fixation of resistance mutations. We also infer pathways directly from the frequency of mutations found in isolate data, and observe remarkable agreement with the most likely pathways predicted by our mechanistic model, as well as those determined experimentally. This suggests mutation frequency data can be used to intuitively infer evolutionary pathways, provided sufficient sampling of the population.

evolutionary biology↗

bioRxiv2021

Getting close to nature - Plasmodium knowlesi reference genome sequences from contemporary clinical isolates

Plasmodium knowlesi, a malaria parasite of old-world macaque monkeys, is used extensively to model Plasmodium biology. Recently P. knowlesi was found in the human population of Southeast Asia, particularly Malaysia. P. knowlesi causes un-complicated to severe and fatal malaria in the human host with features in common with the more prevalent and virulent malaria caused by Plasmodium falciparum. As such P. knowlesi presents a unique opportunity to inform an experimental model for malaria with clinical data from same-species human infections. Experimental lines of P. knowlesi represent well characterised genetically static parasites and to maximise their utility as a backdrop for understanding malaria pathophysiology, genetically diverse contemporary clinical isolates, essentially wild-type, require comparable characterization. The Oxford Nanopore PCR-free long-read sequencing platform was used to sequence P. knowlesi parasites from archived clinical samples. The sequencing platform and assembly pipeline was designed to facilitate capturing data on important multiple gene families, including the P. knowlesi schizont-infected cell agglutination (SICA) var genes and the Knowlesi-Interspersed Repeats (KIR) genes. The SICAvar and KIR gene families code for antigenically variant proteins that have been difficult to resolve and characterise. Analyses presented here suggest that the family members have arisen through a process of gene duplication, selection pressure and variation. Highly evolving genes tend to be located proximal to genetic elements that drive change rather than regions that support core gene conservation. For example, the virulence-associated P. falciparum erythrocyte membrane protein (PfEMP1) gene family members are restricted to relatively unstable sub-telomeric regions. In contrast the SICAvar and KIR genes are located throughout the genome but as the study presented here shows, they occupy otherwise gene-sparse chromosomal locations. The novel methods presented here offer the malaria research community new tools to generate comprehensive genome sequence data from small clinical samples and renewed insight into these complex real-world parasites. Author summaryMalaria is a potentially severe disease caused by parasite species within genus Plasmodium. Even though the number of cases is in decline there were over 200 million reported cases of malaria in 2019 that resulted in >400,000 deaths. Despite huge research efforts we still do not understand precisely how malaria makes some individuals very ill and by extension how to successfully augment and manage severe disease. Here we developed a novel method to generate comprehensive robust genome sequences from the malaria parasite Plasmodium knowlesi collected from clinical samples. We propose to use the method and initial data generated here to begin to build a resource to identify disease associated genetic traits of P. knowlesi taken from patients samples. In addition to the methodology, what further sets this work apart is the unique opportunity to utilize same-species experimental P. knowlesi parasites to discover a potential role for particular parasite traits in the differential disease progression we observe in patients with P. knowlesi malaria. While we developed the methods to study severe malaria, they are affordable and accessible, and offer the wider malaria research community the means to add context and insight into real-world malaria parasites.

genomics↗

bioRxiv2021

Tetrahymena thermophila Granule Lattice Protein 3 Improves Solubility of Sexual Stage Malaria Antigens Expressed in Escherichia coli

The requirement for low cost manufacturing makes bacterial cells a logical platform for the production of recombinant subunit vaccines for malaria. However, protein solubility has been a major stumbling block with prokaryotic expression systems. Notable examples include the transmission blocking vaccine candidates, Pfs25 and Pfs48/45, which are almost entirely insoluble when expressed as recombinant proteins in Escherichia coli. Various solubility tags have been used with limited success in improving solubility, although recent studies with granule lattice protein 1 (Grl1p) from the ciliated protozoan, Tetrahymena thermophila, have shown promise. Here, we examine a related solubility tag, granule lattice protein 3 (Grl3p) from T. thermophila, and compare it to both Grl1p and the well-studied maltose binding protein (MBP) used to improve the solubility of multiple protein targets. We find that Grl3p performs comparably to Grl1p when linked to Pfs25 but significantly improves solubility when paired with Pfs48/45.

bioengineering↗

bioRxiv2020

An integrated in silico immuno-genetic analytical platform provides insights into COVID-19 serological and vaccine targets

BackgroundThe COVID-19 pandemic, caused by the SARS-CoV-2 virus, has a major global health and socio-economic burden. It has instigated the mobilisation of resources into the development of control tools, such as diagnostics and vaccines. The poor performance of some diagnostic serological tools has emphasised the need for up to date immune-informatic analyses to inform the selection of viable targets for further study. This requires the integration and analysis of genetic and immunological data for SARS-CoV-2 and its homology with other human coronavirus species to understand cross-reactivity. MethodsWe have developed an online "immuno-analytics" resource to facilitate SARS-CoV-2 research, combining an extensive B/T-cell epitope mapping and prediction meta-analysis, and human CoV sequence homology mapping and protein database annotation, with an updated variant database and geospatial tracking for >7,800 non-synonymous mutation positions derived from >150,000 whole genome sequences. To demonstrate its utility, we present an integrated analysis of SARS-CoV-2 spike and nucleocapsid proteins, both being vaccine and serological diagnostic targets, including an analysis of changes in relevant mutation frequencies over time. ResultsOur analysis reveals that the nucleocapsid protein in its native form appears to be a sub-optimal target for use in serological diagnostic platforms. The most frequent mutations were the spike protein D614G and nsp12 L314P, which were common (>86%) across all the geographical regions. Some mutations in the spike protein (e.g. A222V and L18F) have increased in frequency in Europe during the latter half of 2020, detected using our automated algorithms. The tool also suggests that orf3a proteins may be a suitable alternative target for diagnostic serologic assays in a post-vaccine surveillance setting. ConclusionsThe immuno-analytics tool can be accessed online (http://genomics.lshtm.ac.uk/immuno) and will serve as a useful resource for biological discovery and surveillance in the fight against SARS-CoV-2. Further, the tool may be adapted to inform on biological targets in future outbreaks, including potential emerging human coronaviruses that spill over from animal hosts.

bioinformatics↗

bioRxiv2020

Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world

BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines. MethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure. ResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades. ConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.

genomics↗

bioRxiv2020

Ribosome profiling in Mycobacterium tuberculosis reveals robust leaderless translation

Mycobacterium tuberculosis, which causes tuberculosis, expresses a large proportion of leaderless transcripts lacking the canonical bacterial translation initiation signals. The role leaderless genes play in the physiology of this pathogen, which can undergo prolonged periods of non-replicating persistence in the host, is currently unknown. We have previously demonstrated that levels of leaderless transcription increase under conditions of nutrient starvation. However, little is known about the implications of this for persistent infection. Here, we performed ribosome profiling to characterise the translational landscape of M. tuberculosis in vitro. Our data reveals robust leaderless translation in the pathogen and points towards different mechanisms for their initiation of translation compared to canonical Shine-Dalgarno genes. Furthermore, under conditions of nutrient starvation, we found a significant global up-regulation of leaderless genes in the translatome. Our data represents a rich resource for others seeking to understand translational regulation not only in M. tuberculosis but in bacterial pathogens.

microbiology↗

bioRxiv2019

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

BackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a one-stop test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.\n\nMethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ( participants) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.\n\nResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.\n\nConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

microbiology↗