Biology subjects

Weinberger, D. M.

Publications and source records attributed to Weinberger, D. M..

12 recordsLinked to original sources

bioRxiv2026

The global evolutionary dynamics of natural capsule switching in a human-restricted bacterial pathogen

Exchange of genetic loci encoding extracellular capsular polysaccharides in bacteria can change capsular antigens or serotype, which, in turn, can lead to evasion of vaccines targeting the capsule. However, the evolutionary dynamics and drivers of bacterial capsule switching remain poorly understood. Here, we investigate the evolutionary dynamics and correlates of capsule switching in bacteria, using the human-restricted bacterial pathogen Streptococcus pneumoniae as an example, using 10,558 genetically and geographically diverse whole-genome sequences. Our phylogenomic and ancestral state reconstruction analysis revealed that the propensity for capsule switching varies by capsule type and genetic background. We found capsule switches only between ~4% of all possible capsule-type pairs, varying by specific pairs and switching direction. We also found associations between capsule switching patterns and genetic and ecological factors, including nasopharyngeal carriage duration, capsule biosynthesis locus size, and capsule thickness. Furthermore, the genetic similarity of the replacing and replaced capsule loci was primarily associated with the frequency of switching between specific capsule type pairs. Although a few specific non-capsule genomic loci were associated with the propensity for capsule switching across distinct lineages, the collective effect of the genetic background appears to influence capsule switching more strongly. These findings shed light on how bacterial capsule types and lineages undergo capsule switching influenced by genetic and ecological factors, informing our understanding of the emergence of novel capsule-genotype combinations that may impact the design of capsule-targeting glycoconjugate vaccines.

microbiology↗

bioRxiv2024

Tiled Amplicon Sequencing Enables Culture-free Whole-Genome Sequencing of Pathogenic Bacteria From Clinical Specimens

Pathogen sequencing is an important tool for disease surveillance and demonstrated its high value during the COVID-19 pandemic. Viral sequencing during the pandemic allowed us to track disease spread, quickly identify new variants, and guide the development of vaccines. Tiled amplicon sequencing, in which a panel of primers is used for multiplex amplification of fragments across an entire genome, was the cornerstone of SARS-CoV-2 sequencing. The speed, reliability, and cost-effectiveness of this method led to its implementation in academic and public health laboratories across the world and adaptation to a broad range of viral pathogens. However, similar methods are not available for larger bacterial genomes, for which whole-genome sequencing typically requires in vitro culture. This increases costs, error rates and turnaround times. The need to culture poses particular problems for medically important bacteria such as Mycobacterium tuberculosis, which are slow to grow and challenging to culture. As a proof of concept, we developed two novel whole-genome amplicon panels for M. tuberculosis and Streptococcus pneumoniae. Applying our amplicon panels to clinical samples, we show the ability to classify pathogen subgroups and to reliably identify markers of drug resistance without culturing. Development of this work in clinical settings has the potential to dramatically reduce the time of diagnosis of drug resistance for multiple drugs in parallel, enabling earlier intervention for high priority pathogens.

genomics↗

bioRxiv2024

The capsule and genetic background, rather than specific loci, strongly influence pneumococcal growth kinetics

Bacterial growth characteristics intrinsic to each strain can impact and influence gene expression, antibiotic susceptibility, and disease pathogenesis. However, little is known about specific genomic variations that influence these bacterial growth features. Here, we investigate the impact of Streptococcus pneumoniae genetics on its in vitro growth features to shed light on genes that may be important targets in the development of vaccines and therapeutics. We use statistical models to estimate growth features and demonstrate that they varied significantly across capsular serotypes and lineages, were strongly correlated with phylogeny, and showed high heritability, highlighting a strong genetic basis. Despite this, genome-wide association studies revealed no specific genomic loci statistically associated with the growth features independently of the genetic background, including those in the locus responsible for capsular polysaccharide synthesis. Our findings suggest that the serotype and lineage, as well as a combination of genomic loci, influence intrinsic pneumococcal growth kinetics, which may have implications for pneumococcal disease pathogenesis.

microbiology↗

bioRxiv2021

Magnetic Bead-Based Separation (MBS) of Pneumococcal Serotypes

The separation of pneumococcal serotypes from a complex polymicrobial mixture may be required for different applications. For instance, a minority strain could be present at a low frequency in a clinical sample, making it difficult to identify and isolate by traditional culture-based methods. We therefore developed an assay to separate mixed pneumococcal samples using serotype-specific antiserum and a magnetic bead-based separation method. Using qPCR and colony counting methods, we first show that serotypes (12F, 23F, 3, 14, 19A and 15A) present at [~]0.1% of a dual serotype mixture can be enriched to between 10% and 90% of the final sample. We demonstrate two applications for this method: extraction of a known pneumococcal serotype from saliva samples and efficient purification of capsule switch variants from experimental transformation experiments. Moreover, this method may have further laboratory or clinical applications when the selection of specific serotypes is required.

microbiology↗

bioRxiv2019

Correlates of non-random patterns of capsule switching in pneumococcus

BackgroundPneumococcus is a diverse pathogen, with >90 serotypes, each of which has a distinct polysaccharide capsule. Pneumococci can switch capsules, evading vaccine pressure. Certain serotype pairs are more likely to switch, but the drivers of these patterns are not well understood.\n\nMethodsWe used the PubMLST and Global Pneumococcal Sequencing (GPS) databases to quantify the number of genetic lineages on which different serotype pairs co-occur. We also quantified the genetic diversity of each serotype. Regression models evaluated the relationship between shared polysaccharide structural components and the frequency of serotype switching and diversity.\n\nResultsA number of serotype pairs co-occurred on the same genetic lineage more commonly than expected. Co-occurrence of between-serogroup pairs was more common when both serotypes had glucose as a component of the capsule (and, potentially, glucuronic acid). Diversity also varied markedly by serotype and was lower for serotypes with glucuronic acid in the capsule and higher for those with galactose in the capsule.\n\nConclusionsCertain pairs of serotypes are more likely to occur on the same genetic background, and these patterns were correlated with shared polysaccharide components. This might indicate adaptation of strains to produce capsules with particular characteristics.

microbiology↗

bioRxiv2019

Determining the serotype composition of mixed samples of pneumococcus using whole genome sequencing

Serotyping of Streptococcus pneumoniae is a critical tool in the surveillance of the pathogen and development and evaluation of vaccines. Whole-genome DNA sequencing and analysis is becoming increasingly common and is an effective method for pneumococcal serotype identification of pure isolates. However, because of the complexities of the pneumococcal capsular loci, current analysis software requires samples to be pure (or nearly pure) and only contain a single pneumococcal serotype. We introduce a new software tool called SeroCall, which can identify and quantitate the serotypes present in samples, even when several serotypes are present. The sample preparation, library preparation and sequencing follow standard laboratory protocols. The software runs as fast or faster than existing identification tools on typical computing servers and is freely available under an open source license at https://github.com/knightjimr/serocall. Using samples with known concentrations of different serotypes as well as blinded samples, we were able to accurately quantify the abundance of different serotypes of pneumococcus in mixed cultures, with 100% accuracy for detecting the major serotype and up to 86% accuracy for detecting minor serotypes. We were also able to track changes in serotype frequency over time in an experimental setting. This approach could be applied in both epidemiologic field studies of pneumococcal colonization as well as in experimental lab studies and could provide a cheaper and more efficient method for serotyping than alternative approaches.

bioinformatics↗

bioRxiv2019

Estimating serotype-specific efficacy of pneumococcal conjugate vaccines using hierarchical models

Pneumococcal conjugate vaccines (PCVs) target 10 or 13 specific serotypes. To evaluate vaccine efficacy for these products, the vaccine-targeted serotypes are typically aggregated into a single group to estimate an overall effect. However, it is often desirable to evaluate variations in effects for different serotypes. These serotype-specific estimates are often based on small numbers, resulting in a high degree of uncertainty and instability in the individual estimates. A better approach is to use a Bayesian hierarchical statistical model, which estimates an overall effectiveness of the vaccine across all vaccine-targeted serotypes but also allows the effect to vary by serotype. We re-analyzed published data from a large randomized controlled trial on the efficacy of PCV13 against non-bacteremic community-acquired pneumonia caused by vaccine-targeted serotype. This model provides a potential framework for obtaining more credible and stable estimates of serotype-specific vaccine efficacy and effectiveness.

epidemiology↗

bioRxiv2019

Google searches accurately forecast RSV hospitalizations

BackgroundHospitalization of children with respiratory syncytial virus (RSV) is common and costly. Traditional sources of hospitalization data, useful for public health decision-makers and physicians to make decisions, are themselves costly to acquire and are subject to delays from gathering to publication. Here we use Google searches for RSV as a proxy for RSV hospitalizations.\n\nMethodsSearches for \"RSV\" and numbers of RSV hospitalizations in WA, MD, FL, and CT were examined from 2004-2018. Running correlation coefficients and phase angles between search and hospitalizations were calculated. Various machine learning models were compared to assess the ability of searches to forecast hospitalizations. Using search data from all 50 US states, we use K-means clustering to identify RSV transmission clusters. We calculate the timing of the optimal timing of RSV prophylaxis initiation as the week beginning the 24-week period covering 95% of all RSV cases.\n\nResultsHigh correlations (> 0.95) and low phase differences were seen between counts of hospitalizations and search volume in WA, MD, FL, and CT. Searching for RSV began in FL and radiated outward and three distinct transmission clusters were identified: the south and northeast, the northwest and Appalachia, and the center of the country. Calculated initiation dates for prophylaxis closely followed those calculated using traditional data sources (correlation = 0.84).\n\nConclusionsThis work validates searches as a proxy for RSV hospitalizations. Search query surveillance of RSV is a rapid and no-cost addition to traditional RSV hospitalization surveillance and may be useful for medical and public health decision-making.

epidemiology↗

bioRxiv2018

Response of pneumococcus to changes in temperature and oxygen varies by serotype, lineage, and site of isolation

BackgroundPneumococcus, a bacterium that typically resides in the nasopharynx, is exposed to a variety of temperature and oxygen levels in the upper respiratory tract and as it invades the lung, tissues, and blood. The response to these variations likely varies by strain and could influence the fitness of a strain and its virulence. We sought to determine the effect of environmental variability on the growth characteristics of pneumococcus and to evaluate correlations between variability in growth characteristics between strains and biological and epidemiological characteristics. MethodsWe evaluated the effect of temperature and oxygen on the growth of 256 pneumococcal isolates representing 53 serotypes, recovered from healthy carriers and from disease patients. Strains were grown at a range of temperatures anaerobically or in ambient air with and without catalase and were monitored by reading the optical density. Regression models were used to evaluate bacterial and environmental factors associated with characteristics of the growth curves. ResultsMost isolates grew to the maximal density at the temperature of the nasopharynx (~33C) and under aerobic conditions (with catalase). Maximum density achieved was positively associated with the presence of N-acetylated sugars in the capsule and negatively associated with the presence of uronic acids. Reaching a greater density at an early time point was positively associated with the prevalence of serotypes among healthy carriers in the pre-vaccine period. DiscussionEnvironmental variability affects the growth of pneumococcus, with notable differences between isolates and by serotype. Such variability could be influenced by characteristics of the capsule and might affect virulence and transmissibility.

microbiology↗

bioRxiv2018

Challenges in estimating the impact of vaccination with sparse data

BackgroundThe synthetic control (SC) model is a powerful tool to quantify the population-level impact of vaccines, because it can adjust for trends unrelated to vaccination using a composite of control diseases. Because vaccine impact studies are often conducted using smaller subnational datasets, we evaluated the performance of SC models with sparse time series data. To obtain more robust estimates of vaccine effects from noisy time series, we proposed a possible alternative approach, \"STL+PCA\" method (seasonal-trend decomposition plus principal component analysis), which first extracts smoothed trends from the control time series and uses them to adjust the outcome.\n\nMethodsUsing both the SC and STL+PCA models, we estimated the impact of 10-valent pneumococcal conjugate vaccine (PCV10) on pneumonia hospitalizations among cases <12 months and 80+ years of age during 2004-2014 at the subnational level in Brazil. The performance of these models was also compared using simulation analyses.\n\nResultsThe SC model was able to adjust for trends unrelated to PCV10 in larger states but not in smaller states. The simulation analysis confirmed that the SC model failed to select an appropriate set of control diseases when the time series were sparse and noisy, thereby generating biased estimates of the impact of vaccination when secular trends were present. The STL+PCA approach decreased bias in the estimates for smaller populations.\n\nConclusionsEstimates from the SC model might be biased when data are sparse. The STL+PCA model provides more accurate evaluations of vaccine impact in smaller populations.

epidemiology↗

bioRxiv2018

Decline in pneumococcal disease in unimmunized adults is associated with vaccine-associated protection against colonization in toddlers and preschool-aged children

Vaccinating children with pneumococcal conjugate vaccines disrupts transmission, reducing disease rates in unvaccinated adults. When considering changes in vaccination strategies (e.g., removing doses), it is critical to understand which groups of children contribute most to transmission. We used data from Israel to evaluate how the build-up of vaccine-associated immunity in children was associated with declines in IPD due to vaccine-targeted serotypes in unimmunized adults. Data on vaccine uptake and prevalence of colonization with PCV-targeted serotypes were obtained from a unique study conducted among children visiting an emergency department in southern Israel and from surveys of colonization from central Israel. Data on invasive pneumococcal disease in adults were obtained from a nationwide surveillance study. We compared the trajectory of decline of IPD due to PCV-targeted serotypes in adults with the trajectory of decline of colonization prevalence and trajectory of increase in vaccine-derived protection against pneumococcal carriage among different age groupings of children. The declines in IPD in adults were most closely associated with the declines in colonization and increased vaccination coverage in children in the range of 36-59 months of age. This suggests that preschool-aged children, rather than infants, are responsible for maintaining the indirect benefits of PCVs.

epidemiology↗

bioRxiv2018

Do pneumococcal conjugate vaccines (PCVs) reduce childhood pneumonia mortality? An assessment across socioeconomic groups in Brazil

BackgroundUnderstanding the real-world impact of pneumococcal conjugate vaccines (PCVs) on pneumonia mortality is critical, given the expectation that PCVs can substantially reduce the burden of pneumonia deaths in children under five years. However, surprisingly few post-vaccine introduction studies have estimated the benefit of PCVs for childhood mortality, and results have been inconsistent.\n\nMethodsWe investigated the long-term trends in child pneumonia mortality in Brazil (1980-present) and assessed the impact of PCV10 on childhood pneumonia mortality, both nationally and in municipalities stratified by socioeconomic status (SES), after the vaccine was introduced in Brazil in 2010.\n\nFindingsBetween 1980 and 2010, a period when Brazils Human Development Index (HDI) rose from 0.55 to 0.71, national pneumonia mortality in children under five decreased 10-fold. Despite rapid uptake of PCV10 following its introduction in 2010, our primary analytical method found no significant decline in national childhood pneumonia mortality, although a secondary analysis found a 10 percent decline in some but not all strata. However, at the municipal level we found significant reductions in childhood pneumonia mortality of up to 24% in low SES strata.\n\nInterpretationContrary to expectations, we found that PCV use led to at best modest savings in childhood pneumonia mortality at the national level in a middle-income country. In contrast, we found evidence that PCV led to larger reductions in low-income settings; a similar benefit might occur when PCVs are introduced in other low-SES settings. The long-term findings underscore that improvements in nutrition, hygiene, education, and healthcare play a major role in reducing pneumonia mortality.\n\nFundingThis work was funded by a grant from the Bill & Melinda Gates Foundation (OPP1114733). DMW also acknowledges support from the Bill and Melinda Gates Foundation (OPP1176267) and the National Institute of Allergy and Infectious Diseases (R01AI123208)

epidemiology↗