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Pollard, A. J.

Publications and source records attributed to Pollard, A. J..

17 recordsLinked to original sources

Global population structure and phase variation of serotype 12F Streptococcus pneumoniae following the introduction of pneumococcal conjugate vaccine

BackgroundAfter the global deployment of pneumococcal conjugate vaccines (PCVs), serotype 12F has become the predominant serotype responsible for invasive pneumococcal disease (IPD) worldwide. As PCVs that include serotype 12F are gradually introduced, we aim to characterise the global population structure and genetic diversity of the 12F capsule locus using whole-genome sequencing. Capsule variants with vaccine evasion potential were further investigated by functional experiments. MethodsA global collection of pneumococcal serotype 12F genomes (n=806) from 37 countries across six continents were included in this study. To characterise the serotype 12F population, Global Pneumococcal Sequence Cluster (GPSC), in silico serotype, and antimicrobial resistance profile were inferred from whole-genome data for each isolate. The capsule biosynthesis (cps) locus was analysed for gene content variations that could alter polysaccharide capsule production or structure, thereby influencing recognition by vaccine-induced antibodies. These isolates were further investigated by assessing their capsule production using immunofluorescence assays and its susceptibility to vaccine-elicited antibody killing by opsonophagocytosis assays. FindingsThe global increase in serotype 12F was driven by both distinct pneumococcal lineages across different continents, and a globally-disseminated and multidrug-resistant lineage GPSC26. We identified six capsule variants in nine isolates that had disruptive mutations in cps genes including wze, wcil, wciJ and fnlA. Most (6/9) of the disruptive mutations were a result of strand-slippage mutations. A convergent strand-slippage mutation disrupting the glycosyltransferase gene wciJ was identified in four isolates from distinct lineages and countries. Despite the truncation, three of four isolates with available Quellung typing results still identified them as 12F, indicating the production of the capsule. We then created a genetically engineered lab strain with wciJ knockout and complemented with wciJ containing the strand-slipppage mutation. The knockout strain did not produce any capsule. In contrast, the lab strain with wciJ containing the strand-slippage mutation produced a mixed population of encapsulated and non-encapsulated pneumococci, even within the same chain of pneumococcal cells. This observation indicated encapsulated subpopulation possesses a functional WciJ and rapidly reversible strand-slippage mutation during replication. Opsonophagocytosis assays indicated that the clinical 12F strain with strand-slippage mutation in wciJ exhibited reduced susceptibility to vaccine-elicited serum killing, compared to a genetically closely related 12F clinical strain with an intact wciJ. However, substantial inter-individual antisera variation limits definitive interpretation. InterpretationOur work revealed the global rise of serotype 12F pneumococci has been driven by both regional-specific lineages, and a globally-disseminated and multidrug-resistant lineage GPSC26. We demonstrated that strand-slippage mutation is one of the major drivers of serotype 12F capsule variants and represents a novel mechanism enabling reversible on-off switching of capsule production. The ability to switch off capsule expression in a subpopulation may enable evasion of antibody-mediated killing but increase susceptibility to innate immune clearance. FundingBill & Melinda Gates Foundation, Wellcome Sanger Institute, and the US Centers for Disease Control and Prevention.

genomics↗

A reusable model of pangenome selection informs optimal surveillance strategies over vaccine introductions

BackgroundThe human pathogen Streptococcus pneumoniae is a major cause of disease, including pneumonia and meningitis. The introduction of Pneumococcal Conjugate Vaccines (PCVs) initially reduced the burden of disease through a reduction of colonisation by vaccine-targeted serotypes. However, since PCVs only target a proportion of pneumococcal serotypes, they shift intraspecific competition, eventually allowing non-targeted types to replace vaccine types. Understanding the host and pathogen factors causing replacement is important for future vaccine development. Mechanistic understanding of vaccine replacement dynamics is crucial for forecasting and optimisation of genomic surveillance strategies to evaluate realised vaccine effectiveness. MethodsWe developed a mathematical model of the genomic and demographic factors which explain vaccine replacement, used this model to replicate serotype-frequency changes, and investigated cost-effective genomic surveillance strategies. We extended a forward-time model based on the Wright-Fisher model, developing a user-friendly model framework that describes the post-vaccine dynamics of S. pneumoniae populations. Our model describes vaccine replacement as a function of vaccine impact, immigration of new strains, and negative frequency-dependent selection (NFDS) on the accessory genome content. ResultsWe used our model to study vaccine replacement in newly sequenced genomic surveillance data from Nepal, and existing data from the US, and the UK, with distinct surveillance strategies. We showed that the model with NFDS better replicates replacement dynamics than a null model without NFDS, and that NFDS likely only acts on part of the S. pneumoniae accessory genome. We found consistent estimates for vaccination effectiveness across the different study locations and country-specific genes under NFDS, highlighting the importance of conducting genomic surveillance in each country of interest. By simulating data from the model, we showed that an optimal surveillance strategy prioritises per-sampling sample size over sampling frequency for small sampling budgets. ConclusionsOur model can be used to predict vaccine replacement dynamics after PCV introduction, and can be easily reapplied to analyse new data from vaccine introductions or new regions. Our model is available in the R package STUBENTIGER (Studying Balancing Evolution (NFDS) To Investigate Genome Replacement) on GitHub https://github.com/bacpop/Stubentiger.

genomics↗

Innate antiviral readiness drives the expansion of protective T stem cell memory against influenza

The development of T-cell-based influenza vaccines relies on eliciting broad CD8+ T-cell immunity, wherein T stem cell-like memory (TSCM) cells serve as the ultimate long-lived reservoir for immune memory, thereby unlocking the potential for durable protection against viral drift and shift. However, the specific immunological cues that drive the robust expansion and functional preservation of this self-renewing, multipotent subset remain unknown. Here, utilizing multi-omic systems immunology in a pediatric cohort immunized with live attenuated influenza vaccine, we identified the determinants governing the expansion of influenza virus-reactive TSCM cells. We show that a pre-existing state of innate antiviral readiness, defined by a plasmacytoid dendritic cell-associated type I interferon signature, is the requisite condition for a robust TSCM expansion. Mechanistically, this baseline innate state enhances antigen priming and enforces a qualitative divergence in T-cell fate, driving responders toward a functionally poised, Th1-dominant phenotype while non-responders default to a dysfunctional, hyper-proliferative state. To determine the clinical relevance of this cellular subset, we analyzed an independent controlled human influenza challenge study. This validation revealed a critical functional division of labor in host defense: whereas pre-existing antibodies primarily mitigated symptom severity, the baseline frequency of influenza virus-reactive TSCM cells was the strongest predictor of rapid viral load clearance. These findings establish that the expansion of durable cellular memory is not stochastic but is predetermined by the innate cytokine environment, providing a predictive biomarker for patient stratification and a validated target for adjuvants designed to expand the TSCM reservoir deliberately.

immunology↗

Typhoid toxin of Salmonella Typhi elicits host antimicrobial response during acute typhoid fever

Salmonella Typhi secretes typhoid toxin that activates cellular DNA damage responses (DDR) during acute typhoid fever. Human infection challenge studies revealed that the toxin suppresses bacteraemia via unknown mechanisms. Using quantitative proteomic analysis on the plasma of bacteraemic participants, we demonstrate that wild-type toxigenic Salmonella induced secretion of lysozyme (LYZ) and apolipoprotein C3 (APOC3). Recombinant typhoid toxin or infection with toxigenic Salmonella recapitulate LYZ and APOC3 secretion in cultured cells, which involved ATM/ATR-dependent DDRs and confirmed observations in typhoid fever. LYZ alone inhibited secretion of virulence effector proteins SipB and SopE. LYZ caused loss of Salmonella morphology characterised by spheroplast formation. Spheroplast formation was mediated by LYZ and enhanced by lactoferrin, which was identified by proteomics in participants with typhoid fever. Our findings may indicate that toxin-induced DDRs elicit antimicrobial responses, which suppress Salmonella bacteraemia during typhoid fever.

microbiology↗

Direct inference and control of genetic population structure from RNA sequencing data

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

bioinformatics↗

Further antibody escape by Omicron BA.4 and BA.5 from vaccine and BA.1 serum

The Omicron lineage of SARS-CoV-2, first described in November 2021, spread rapidly to become globally dominant and has split into a number of sub-lineages. BA.1 dominated the initial wave but has been replaced by BA.2 in many countries. Recent sequencing from South Africas Gauteng region uncovered two new sub-lineages, BA.4 and BA.5 which are taking over locally, driving a new wave. BA.4 and BA.5 contain identical spike sequences and, although closely related to BA.2, contain further mutations in the receptor binding domain of spike. Here, we study the neutralization of BA.4/5 using a range of vaccine and naturally immune serum and panels of monoclonal antibodies. BA.4/5 shows reduced neutralization by serum from triple AstraZeneca or Pfizer vaccinated individuals compared to BA.1 and BA.2. Furthermore, using serum from BA.1 vaccine breakthrough infections there are likewise, significant reductions in the neutralization of BA.4/5, raising the possibility of repeat Omicron infections.

microbiology↗

Genetic Susceptibility to Enteric Fever in Experimentally Challenged Human Volunteers

BackgroundInfection with Salmonella enterica serovars Typhi and Paratyphi A cause an estimated 14 million cases of enteric fever annually. Here the controlled nature of challenge studies is exploited to identify genetic variants associated with enteric fever susceptibility. MethodsHuman challenge participants were genotyped by Illumina OmniExpress-24 BeadChip array (n=176) and/or transcriptionally profiled by RNA-sequencing (n=178). ResultsTwo SNPs within CAPN14 and MIATNB were identified with p<10-5 for association with development of symptoms or bacteraemia following oral S. Typhi or S. Paratyphi A challenge. Imputation of classical human leukocyte antigen (HLA) types from genomic and transcriptomic data identified HLA-B*27:05, previously associated with non-typhoidal Salmonella-induced reactive arthritis, as the HLA type most strongly associated with enteric fever susceptibility (p=0.012). Genes related to the unfolded protein response and heat shock were over-represented in HLA-B*27:05+ participants following challenge (p=0.01). Furthermore, intracellular replication of S. Typhi is higher in C1R cells transfected with HLA-B*27:05 (p=0.02). ConclusionThese data suggest that activation of the unfolded protein response by HLA-B*27:05 misfolding may create an intracellular environment conducive to S. Typhi replication, increasing susceptibility to enteric fever.

genetics↗

Antibody evasion by the Brazilian P.1 strain of SARS-CoV-2

Terminating the SARS-CoV-2 pandemic relies upon pan-global vaccination. Current vaccines elicit neutralizing antibody responses to the virus spike derived from early isolates. However, new strains have emerged with multiple mutations: P.1 from Brazil, B.1.351 from South Africa and B.1.1.7 from the UK (12, 10 and 9 changes in the spike respectively). All have mutations in the ACE2 binding site with P.1 and B.1.351 having a virtually identical triplet: E484K, K417N/T and N501Y, which we show confer similar increased affinity for ACE2. We show that, surprisingly, P.1 is significantly less resistant to naturally acquired or vaccine induced antibody responses than B.1.351 suggesting that changes outside the RBD impact neutralisation. Monoclonal antibody 222 neutralises all three variants despite interacting with two of the ACE2 binding site mutations, we explain this through structural analysis and use the 222 light chain to largely restore neutralization potency to a major class of public antibodies.

microbiology↗

SIMON: open-source knowledge discovery platform

Data analysis and knowledge discovery has become more and more important in biology and medicine with the increasing complexity of the biological datasets, but necessarily sophisticated programming skills and in-depth understanding of algorithms needed pose barriers to most biologists and clinicians to perform such research. We have developed a modular open-source software SIMON to facilitate the application of 180+ state-of-the-art machine learning algorithms to high-dimensional biomedical data. With an easy to use graphical user interface, standardized pipelines, automated approach for machine learning and other statistical analysis methods, SIMON helps to identify optimal algorithms and provides a resource that empowers non-technical and technical researchers to identify crucial patterns in biomedical data.

systems biology↗

Effects of technical noise on bulk RNA-seq differential gene expression inference

MotivationInconsistent, analytical noise introduced either by the sequencing technology or by the choice of read-processing tools can bias bulk RNA-seq analyses by shifting the focus to the variation in expression of low-abundance transcripts; as a consequence these highly-variable genes are often included the differential expression (DE) call and impact the interpretation of results. ResultsTo illustrate the effects of "noise", we present simulated datasets following closely the characteristics of a H.sapiens and a M.musculus dataset, respectively, highlighting the extent of technical-noise in both a high inter-individual variability (H. sapiens) and reduced variability (M. Musculus) setup. The sequencing-induced noise is assessed using correlations of distributions of expression across transcripts; analytical noise is evaluated through side-by-side comparisons of several standard choices. The proportion of genes in the noise-range differs for each tool combi-nation. Data-driven, sample-specific noise-thresholds were applied to reduce the impact of low-level variation. Noise-adjustment reduced the number of significantly DE genes and gave rise to convergent calls across tool combinations. AvailabilityThe code for determining the sequence-derived noise is available for download from: https://github.com/yry/noiseAnalysis/tree/master/noiseDetection_mRNA; the code for running the analysis is available for download from: https://github.com/sheerind/noise_detection.

bioinformatics↗

Targeted metagenomic sequencing enhances the identification of pathogens associated with acute infection.

The routine identification of pathogens during infection remains challenging because it relies on multiple modalities such as culture and nucleic acid amplification and tests that tend to be specific for very few of an enormous number of possible infectious agents. Metagenomics promises single-test identification, but shotgun sequencing remains unwieldy and expensive or in many cases insufficiently sensitive to detect the amount of pathogen material in a clinical sample. Here we present the validation and application of Castanet, a method for metagenomic sequencing with enrichment that exploits clinical knowledge to construct a broad panel of relevant organisms for detection at low cost with sensitivity comparable to PCR. Castanet targets both DNA and RNA, works with small sample volumes, and can be implemented in a high-throughput diagnostic setting. We used Castanet to analyse plasma samples from 573 patients from the GAinS sepsis cohort and CSF samples from 243 patients from the ChiMES meningitis cohort that had been evaluated using standard clinical microbiology methods, identifying relevant pathogens in many cases where no pathogen had previously been detected. Castanet is intended for use in defining the distribution of pathogens in samples, diseases and populations, for large-scale clinical studies and for verifying the performance of routine testing regimens. By providing sequence as output, Castanet combines pathogen identification directly with subtyping and phylo-epidemiology.

microbiology↗

Viral and bacterial infection elicit distinct changes in plasma lipids in febrile children

Fever is the most common reason that children present to Emergency Departments in the UK. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. As a result, many children are prescribed antibiotics often unnecessarily, while others with life-threatening bacterial infections can remain untreated. The omics approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n=20) and confirmed viral infection (n=20). We show for the first time that bacterial and viral infection elicit distinct changes in the host lipidome. Glycerophosphoinositol, sphingomyelin, lysophosphotidylcholine and cholesterol sulfate were increased in the confirmed virus infected group, while fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were increased in cases with confirmed bacterial infection. A combination of three lipids achieved the area under the receiver operating characteristic (ROC) curve of 0.918 (95% CI 0.835 to 1). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics.

systems biology↗

Elevated risk of invasive group A streptococcal disease and host genetic variation in the human leukocyte antigen locus

Invasive group A streptococcal (GAS) disease is uncommon but carries a high case-fatality rate relative to other infectious diseases. Given the ubiquity of mild GAS infections, it remains unclear why healthy individuals will occasionally develop life-threatening infections, raising the possibility of host genetic predisposition. Here, we present the results of a case-control study including 43 invasive GAS cases and 1,540 controls. Using HLA imputation and linear mixed-models, we find each copy of the HLA-DQA1*01:03 allele associates with a two-fold increased risk of disease (odds ratio 2.3, 95% confidence interval 1.3-4.4, P=0.009), an association which persists with classical HLA typing of a subset of cases and analysis with an alternative large control dataset with validated HLA data. Moreover, we propose the association is driven by the allele itself rather than the background haplotype. Overall this finding provides impetus for further investigation of the immunogenetic basis of this devastating bacterial disease.

genetics↗

Incomplete penetrance for isolated congenital asplenia in humans with mutations in translated and untranslated RPSA exons

Isolated congenital asplenia (ICA) is the only known human developmental defect exclusively affecting a lymphoid organ. In 2013, we showed that private deleterious mutations in the protein-coding region of RPSA, encoding ribosomal protein SA, caused ICA by haploinsufficiency with complete penetrance. We reported seven heterozygous protein-coding mutations in 8 of the 23 kindreds studied, including 6 of the 8 multiplex kindreds. We have since enrolled 33 new kindreds, 5 of which are multiplex. We describe here eleven new heterozygous ICA-causing RPSA protein-coding mutations, and the first two mutations in the 5-UTR of this gene, which disrupt mRNA splicing. Overall, 40 of the 73 ICA patients (55%) and 23 of the 56 kindreds (41%) carry mutations located in translated or untranslated exons of RPSA. Eleven of the 43 kindreds affected by sporadic disease (26%) carry RPSA mutations, whereas 12 of the 13 multiplex kindreds (92%) carry RPSA mutations. We also report that six of eighteen (33%) protein-coding mutations and the two (100%) 5-UTR mutations display incomplete penetrance. Three mutations were identified in 2 independent kindreds, due to a hotspot or a founder effect. Lastly, RPSA ICA-causing mutations were demonstrated to be de novo in 7 of the 23 probands. Mutations in RPSA exons can affect the translated or untranslated regions and can underlie ICA with complete or incomplete penetrance.

genetics↗

Diagnostic host gene signature to accurately distinguish enteric fever from other febrile diseases

Misdiagnosis of enteric fever is a major global health problem resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine-learning algorithm to host gene expression profiles, we identified a diagnostic signature which could accurately distinguish culture-confirmed enteric fever cases from other febrile illnesses (AUROC<95%). Applying this signature to a culture-negative suspected enteric fever cohort in Nepal identified a further 12.6% as likely true cases. Our analysis highlights the power of data-driven approaches to identify host-response patterns for the diagnosis of febrile illnesses. Expression signatures were validated using qPCR highlighting their utility as PCR-based diagnostic for use in endemic settings.

molecular biology↗

Global emergence and population dynamics of divergent serotype 3 CC180 pneumococci

Streptococcus pneumoniae serotype 3 remains a significant cause of morbidity and mortality worldwide, despite inclusion in the 13-valent pneumococcal conjugate vaccine (PCV13). Serotype 3 increased in carriage since the implementation of PCV13 in the United States, while invasive disease rates remain unchanged. We investigated the persistence of serotype 3 in carriage and disease, through genomic analyses of a global sample of 301 serotype 3 isolates of the Netherlands3-31 (PMEN31) clone CC180, combined with associated patient data and PCV utilization among countries of isolate collection. We assessed phenotypic variation between dominant clades in capsule charge (zeta potential), capsular polysaccharide shedding, and susceptibility to opsonophagocytic killing, which have previously been associated with carriage duration, invasiveness, and vaccine escape. We identify a recent shift in the CC180 population attributed to a lineage termed Clade II, which was estimated by Bayesian coalescent analysis to have first appeared in 1968 [95% HPD: 1939-1989] and increased in prevalence and effective population size thereafter. Clade II isolates are divergent from the pre-PCV13 serotype 3 population in non-capsular antigenic composition, competence, and antibiotic susceptibility, the last resulting from the acquisition of a Tn916-like conjugative transposon. Differences in recombination rates among clades correlated with variations in the ATP-binding subunit of Clp protease as well as amino acid substitutions in the comCDE operon. Opsonophagocytic killing assays elucidated the low observed efficacy of PCV13 against serotype 3. Variation in PCV13 use among sampled countries was not independently correlated with the CC180 population shift; therefore, genotypic and phenotypic differences in protein antigens and, in particular, antibiotic resistance may have contributed to the increase of Clade II. Our analysis emphasizes the need for routine, representative sampling of isolates from disperse geographic regions, including historically under-sampled areas. We also highlight the value of genomics in resolving antigenic and epidemiological variations within a serotype, which may have implications for future vaccine development.\n\nAuthor SummaryStreptococcus pneumoniae is a leading cause of bacterial pneumoniae, meningitis, and otitis media. Despite inclusion in the most recent pneumococcal conjugate vaccine, PCV13, serotype 3 remains epidemiologically important globally. We investigated the persistence of serotype 3 using whole-genome sequencing data form 301 isolates collected among 24 countries from 1993-2014. Through phylogenetic analysis, we identified three distinct lineages within a single clonal complex, CC180, and found one has recently emerged and grown in prevalence. We then compared genomic difference among lineages as well as variations in pneumococcal vaccine use among sampled countries. We found that the recently emerged lineage, termed Clade II, has a higher prevalence of antibiotic resistance compared to other lineages, diverse surface protein antigens, and a higher rate of recombination, a process by which bacteria can uptake and incorporate genetic material from its surroundings. Differences in vaccine use among sampled countries did not appear to be associated with the emergence of Clade II. We highlight the need to routine, representative sampling of bacterial isolates from diverse geographic areas and show the utility of genomic data in resolving epidemiological differences within a pathogen population.

evolutionary biology↗

Identification of an epitope of limited variability under strong immune selection in the haemagglutinin head domain of H1N1 influenza

Antigenic targets of influenza vaccination are currently seen to be polarised between (i) highly immunogenic (and protective) epitopes of high variability, and (ii) conserved epitopes of low immunogenicity. This requires vaccines directed against the variable sites to be continuously updated, with the only other alternative being seen as the artificial boosting of immunity to invariant epitopes of low natural efficacy. However, theoretical models suggest that the antigenic evolution of influenza is best explained by postulating the existence of highly immunogenic epitopes of limited variability. Here we report the identification of such an epitope of limited variability in the head domain of the H1 haemagglutinin protein. We show that the epitope mediates immunity to historical influenza strains not previously seen by a cohort of young children. Furthermore, vaccinating mice with these epitope conformations can induce immunity to all the human H1N1 influenza strains that have circulated since 1918. The identification of epitopes of limited variability offers a mechanism by which a universal influenza vaccine can be created; these vaccines would also have the potential to protect against newly emerging influenza strains.

epidemiology↗