Population genomics of pneumococcal carriage in Massachusetts children following introduction of PCV-13

Prediction of post-PCV13 pneumococcal evolution using invasive disease data enhanced by inverse-invasiveness weighting

After introducing pneumococcal conjugate vaccines (PCVs), serotype replacement occurred in Streptococcus pneumoniae. Predicting which pneumococcal strains will become common in carriage after vaccination can enhance vaccine design, public health interventions, and understanding of pneumococcal evolution. Invasive pneumococcal isolates were collected during 1998-2018 by the Active Bacterial Core surveillance (ABCs). Carriage data from Massachusetts (MA) and Southwest United States were used to calculate weights. Using pre-vaccine data, serotype-specific inverse-invasiveness weights were defined as the ratio of the proportion of the serotype in carriage to the proportion in invasive data. Genomic data were processed under bioinformatic pipelines to define genetically similar sequence clusters (i.e., strains), and accessory genes (COGs) present in 5-95% of isolates. Weights were applied to adjust observed strain proportions and COG frequencies. The negative frequency-dependent selection (NFDS) model predicted strain proportions by calculating the post-vaccine strain composition in the weighted invasive disease population that would best match pre-vaccine COG frequencies. Inverse-invasiveness weighting increased the correlation of COG frequencies between invasive and carriage data in linear or logit scale for pre-vaccine, post-PCV7, and post-PCV13; and between different epochs in the invasive data. Weighting the invasive data significantly improved the NFDS model's accuracy in predicting strain proportions in the carriage population in the post-PCV13 epoch, with the adjusted R2 increasing from 0.254 before weighting to 0.545 after weighting. The weighting system adjusted invasive disease data to better represent the pneumococcal carriage population, allowing the NFDS mechanism to predict strain proportions in carriage in the post-PCV13 epoch. Our methods enrich the value of genomic sequences from invasive disease surveillance.IMPORTANCEStreptococcus pneumoniae, a common colonizer in the human nasopharynx, can cause invasive diseases including pneumonia, bacteremia, and meningitis mostly in children under 5 years or older adults. The PCV7 was introduced in 2000 in the United States within the pediatric population to prevent disease and reduce deaths, followed by PCV13 in 2010, PCV15 in 2022, and PCV20 in 2023. After the removal of vaccine serotypes, the prevalence of carriage remained stable as the vacated pediatric ecological niche was filled with certain non-vaccine serotypes. Predicting which pneumococcal clones, and which serotypes, will be most successful in colonization after vaccination can enhance vaccine design and public health interventions, while also improving our understanding of pneumococcal evolution. While carriage data, which are collected from the pneumococcal population that is competing to colonize and transmit, are most directly relevant to evolutionary studies, invasive disease data are often more plentiful. Previously, evolutionary models based on negative frequency-dependent selection (NFDS) on the accessory genome were shown to predict which non-vaccine strains and serotypes were most successful in colonization following the introduction of PCV7. Here, we show that an inverse-invasiveness weighting system applied to invasive disease surveillance data allows the NFDS model to predict strain proportions in the projected carriage population in the post-PCV13/pre-PCV15 and pre-PCV20 epoch. The significance of our research lies in using a sample of invasive disease surveillance data to extend the use of NFDS as an evolutionary mechanism to predict post-PCV13 population dynamics. This has shown that we can correct for biased sampling that arises from differences in virulence and can enrich the value of genomic data from disease surveillance and advance our understanding of how NFDS impacts carriage population dynamics after both PCV7 and PCV13 vaccination.

Prediction of post-PCV13 pneumococcal evolution using invasive disease data enhanced by inverse-invasiveness weighting

Background

After introduction of pneumococcal conjugate vaccines (PCVs), serotype replacement occurred in the population of Streptococcus pneumoniae. Predicting which pneumococcal clones and serotypes will become more common in carriage after vaccination can enhance vaccine design and public health interventions, while also improving our understanding of pneumococcal evolution. We sought to use invasive disease data to assess how well negative frequency-dependent selection (NFDS) models could explain pneumococcal carriage population evolution in the post-PCV13 epoch by weighting invasive data to approximate strain proportions in the carriage population.

Methods

Invasive pneumococcal isolates were collected and sequenced during 1998-2018 by the Active Bacterial Core surveillance (ABCs) from the Centers for Disease Control and Prevention (CDC). To predict the post-PCV13 population dynamics in the carriage population using a NFDS model, all genomic data were processed under a bioinformatic pipeline of assembly, annotation, and pangenome analysis to define genetically similar sequence clusters (i.e., strains) and a set of accessory genes present in 5% to 95% of the isolates. The NFDS model predicted the strain proportion by calculating the post-vaccine strain composition in the weighted invasive disease population that would best match pre-vaccine accessory gene frequencies. To overcome the biases of invasive disease data, serotype-specific inverse-invasiveness weights were defined as the ratio of the proportion of the serotype in the carriage data to the proportion in the invasive data, using data from 1998-2001 in the United States, before conjugate vaccine introduction. The weights were applied to adjust both the observed strain proportion and the accessory gene frequencies.

Results

Inverse-invasiveness weighting increased the correlation of accessory gene frequencies between invasive and carriage data with reduced residuals in linear or logit scale for pre-vaccine, post-PCV7, and post-PCV13. Similarly, weighting increased the correlation of accessory gene frequencies between different time periods in the invasive data. By weighting the invasive data, we were able to use the NFDS model to predict strain proportions in the carriage population in the post-PCV13 epoch, with the adjusted R-squared between predicted and observed strain proportions increasing from 0.176 to 0.544 after weighting.

Conclusions

The weighting system adjusted the invasive disease surveillance data to better represent the carriage population of S. pneumoniae. The NFDS mechanism predicted the strain proportions in the projected carriage population as estimated from the weighted invasive disease frequencies in the post-PCV13 epoch. Our methods enrich the value of genomic sequences from invasive disease surveillance, which is readily available, easy to collect, and of direct interest to public health.

Comparative genomic epidemiology of serotype 3 IPD and carriage isolates from Southampton, UK between 2005 and 2017

Serotype 3 pneumococci remains a significant cause of disease despite its inclusion in PCV13. Whilst clonal complex 180 (CC180) represents the major clone, recent studies have refined the population structure into three clades: Iα, Iβ and II, with the last being a recent divergent and more antibiotic-resistant. We present a genomic analysis of serotype 3 isolates from paediatric carriage and all-age invasive disease, collected between 2005 and 2017 in Southampton, UK. Forty-one isolates were available for analysis. Eighteen were isolated during the annual cross-sectional surveillance of paediatric pneumococcal carriage. The remaining 23 were isolated from blood/cerebrospinal fluid specimens at the University Hospital Southampton NHS Foundation Trust laboratory. All carriage isolates were CC180 GPSC12. Greater diversity was seen with invasive pneumococcal disease (IPD) with three GPSC83 (ST1377: n=2, ST260: n=1) and one GPSC3 (ST1716). For both carriage and IPD, Clade Iα was dominant (94.4 and 73.9 % respectively). Two isolates were Clade II with one from carriage (a 34-month-old, October 2017) and one invasive isolate (49-year-old, August 2015). Four IPD isolates were outside the CC180 clade. All isolates were genotypically susceptible to penicillin, erythromycin, tetracycline, co-trimoxazole and chloramphenicol. Two isolates (one each from carriage and IPD; both CC180 GPSC12) were phenotypically resistant to erythromycin and tetracycline; the IPD isolate was also resistant to oxacillin.In the Southampton area, carriage and invasive disease associated with serotype 3 is predominantly caused by Clade Iα CC180 GPSC12.

Complete Genome Sequences of Nine Streptococcus pneumoniae Serotype 3 Clonal Complex 180 Strains

We announce the complete genomes of nine Streptococcus pneumoniae strains belonging to serotype 3 clonal complex 180 (CC180). The genomes consist of a single circularized contig with an average length of 2.033 Mbp. Pangenome analysis identified 1,762 core genes and 412 accessory genes. These genomes are the basis for future population genomic studies.

Heuristic and Hierarchical-Based Population Mining of Salmonella enterica Lineage I Pan-Genomes as a Platform to Enhance Food Safety

The recent incorporation of bacterial whole-genome sequencing (WGS) into Public Health laboratories has enhanced foodborne outbreak detection and source attribution. As a result, large volumes of publicly available datasets can be used to study the biology of foodborne pathogen populations at an unprecedented scale. To demonstrate the application of a heuristic and agnostic hierarchical population structure guided pan-genome enrichment analysis (PANGEA), we used populations of S. enterica lineage I to achieve two main objectives: (i) show how hierarchical population inquiry at different scales of resolution can enhance ecological and epidemiological inquiries; and (ii) identify population-specific inferable traits that could provide selective advantages in food production environments. Publicly available WGS data were obtained from NCBI database for three serovars of Salmonella enterica subsp. enterica lineage I (S. Typhimurium, S. Newport, and S. Infantis). Using the hierarchical genotypic classifications (Serovar, BAPS1, ST, cgMLST), datasets from each of the three serovars showed varying degrees of clonal structuring. When the accessory genome (PANGEA) was mapped onto these hierarchical structures, accessory loci could be linked with specific genotypes. A large heavy-metal resistance mobile element was found in the Monophasic ST34 lineage of S. Typhimurium, and laboratory testing showed that Monophasic isolates have on average a higher degree of copper resistance than the Biphasic ones. In S. Newport, an extra sugE gene copy was found among most isolates of the ST45 lineage, and laboratory testing of multiple isolates confirmed that isolates of S. Newport ST45 were on average less sensitive to the disinfectant cetylpyridimium chloride than non-ST45 isolates. Lastly, data-mining of the accessory genomic content of S. Infantis revealed two cryptic Ecotypes with distinct accessory genomic content and distinct ecological patterns. Poultry appears to be the major reservoir for Ecotype 1, and temporal analysis further suggested a recent ecological succession, with Ecotype 2 apparently being displaced by Ecotype 1. Altogether, the use of a heuristic hierarchical-based population structure analysis that includes bacterial pan-genomes (core and accessory genomes) can (1) improve genomic resolution for mapping populations and accessing epidemiological patterns; and (2) define lineage-specific informative loci that may be associated with survival in the food chain.

Rising Pneumococcal Antibiotic Resistance in the Post-13-Valent Pneumococcal Conjugate Vaccine Era in Pediatric Isolates From a Primary Care Setting

BACKGROUND

Antibiotic-resistant Streptococcus pneumoniae strains may cause infections that fail to respond to antimicrobial therapy. Results reported from hospitalized patients with invasive, bacteremic infections may not be the same as those observed in a primary care setting where young children receive care for noninvasive infections. Young children experience the highest burden of pneumococcal disease. The aim of this study was to determine the antibiotic susceptibility of S. pneumoniae strains isolated from children in a primary care setting in the post-13-valent pneumococcal conjugate vaccine (PCV13) era.

METHODS

This was a prospective collection of 1201 isolates of S. pneumoniae from 2006 through 2016 in a primary care setting. Antibiotic susceptibility testing to 16 different antibiotics of 10 classes was performed. Participants were children aged 6-36 months. Nasopharyngeal swabs were obtained from patients during acute otitis media (AOM) visits and routine healthy visits. Middle ear fluid was obtained by tympanocentesis.

RESULTS

After introduction of PCV13, antibiotic susceptibility of pneumococci, especially to penicillin, initially improved largely due to disappearance of serotype 19A, included in PCV13. However, beginning in 2013, antibiotic susceptibility among pneumococcal strains began decreasing due to new serotypes not included in PCV13. In addition to reduced susceptibility to penicillin, the most recent isolates show reduced susceptibility to third-generation cephalosporins, fluoroquinolones, and carbapenems, antibiotics commonly used to treat life-threatening, invasive pneumococcal diseases.

CONCLUSIONS

In recent years, pneumococcal nasopharyngeal and AOM isolates from children exhibit reduced susceptibility to penicillin, third-generation cephalosporin, fluoroquinolone, and carbapenem antibiotics. The new strains have a different profile of resistance compared to the pre-PCV13 era.

A Narrative Review of the Molecular Epidemiology and Laboratory Surveillance of Vaccine Preventable Bacterial Meningitis Agents: Streptococcus pneumoniae, Neisseria meningitidis, Haemophilus influenzae and Streptococcus agalactiae

This narrative review describes the public health importance of four most common bacterial meningitis agents, Streptococcus pneumoniae, Neisseria meningitidis, Haemophilus influenzae, and S. agalactiae (group B Streptococcus). Three of them are strict human pathogens that normally colonize the nasopharynx and may invade the blood stream to cause systemic infections and meningitis. S. agalactiae colonizes the genito-gastrointestinal tract and is an important meningitis agent in newborns, but also causes invasive infections in infants or adults. These four bacteria have polysaccharide capsules that protect them against the host complement defense. Currently licensed conjugate vaccines (against S. pneumoniae, H. influenza, and N. meningitidis only but not S. agalactiae) can induce protective serum antibodies in infants as young as two months old offering protection to the most vulnerable groups, and the ability to eliminate carriage of homologous serotype strains in vaccinated subjects lending further protection to those not vaccinated through herd immunity. However, the serotype-specific nature of these vaccines have driven the bacteria to adapt by mechanisms that affect the capsule antigens through either capsule switching or capsule replacement in addition to the possibility of unmasking of strains or serotypes not covered by the vaccines. The post-vaccine molecular epidemiology of vaccine-preventable bacterial meningitis is discussed based on findings obtained with newer genomic laboratory surveillance methods.

Global genomic epidemiology of Streptococcus pyogenes

Streptococcus pyogenes is one of the Top 10 human infectious disease killers worldwide causing a range of clinical manifestations in humans. Colonizing a range of ecological niches within its sole host, the human, is key to the ability of this opportunistic pathogen to cause direct and post-infectious manifestations. The expansion of genome sequencing capabilities and data availability over the last decade has led to an improved understanding of the evolutionary dynamics of this pathogen within a global framework where epidemiological relationships and evolutionary mechanisms may not be universal. This review uses the recent publication by Davies et al., 2019 as an updated global framework to address S. pyogenes population genomics, highlighting how genomics is being used to gain new insights into evolutionary processes, transmission pathways, and vaccine design.

Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae

Predicting how pathogen populations will change over time is challenging. Such has been the case with Streptococcus pneumoniae, an important human pathogen, and the pneumococcal conjugate vaccines (PCVs), which target only a fraction of the strains in the population. Here, we use the frequencies of accessory genes to predict changes in the pneumococcal population after vaccination, hypothesizing that these frequencies reflect negative frequency-dependent selection (NFDS) on the gene products. We find that the standardized predicted fitness of a strain, estimated by an NFDS-based model at the time the vaccine is introduced, enables us to predict whether the strain increases or decreases in prevalence following vaccination. Further, we are able to forecast the equilibrium post-vaccine population composition and assess the invasion capacity of emerging lineages. Overall, we provide a method for predicting the impact of an intervention on pneumococcal populations with potential application to other bacterial pathogens in which NFDS is a driving force.

Evolution of Streptococcus pneumoniae Serotype 3 in England and Wales: A Major Vaccine Evader

Despite its inclusion in pneumococcal conjugate vaccine 13 (PCV13), Streptococcus pneumoniae serotype 3 remains a major cause of invasive pneumococcal disease in England and Wales. Previous studies have indicated that there are distinct lineages within serotype 3 clonal complex 180 and the clade distributions have shifted in recent years with the emergence of clade II. We undertook whole genome sequencing and genomic analysis of 616 serotype 3 isolates from England and Wales between 2003 and 2018, including invasive and carriage isolates. Our investigations showed that clade II has expanded since 2014 and now represents 50% of serotype 3 invasive pneumococcal disease (IPD) isolates in England and Wales. Genomic analysis of antibiotic resistance and protein antigen genes showed that distinct profiles are present within the clades which could account for the recent emergence of this clade. This investigation highlights the importance and utility of routine whole genome sequencing and its ability to identify new and emerging variation at the single nucleotide level which informs surveillance and will impact future vaccine development.

The Genomics of Streptococcus Pneumoniae Carriage Isolates from UK Children and Their Household Contacts, Pre-PCV7 to Post-PCV13

We used whole genome sequencing (WGS) analysis to investigate the population structure of 877 Streptococcus pneumoniae isolates from five carriage studies from 2002 (N = 346), 2010 (N = 127), 2013 (N = 153), 2016 (N = 187) and 2018 (N = 64) in UK households which covers the period pre-PCV7 to post-PCV13 implementation. The genomic lineages seen in the population were determined using multi-locus sequence typing (MLST) and PopPUNK (Population Partitioning Using Nucleotide K-mers) which was used for local and global comparisons. A Roary core genome alignment of all the carriage genomes was used to investigate phylogenetic relationships between the lineages. The results showed an influx of previously undetected sequence types after vaccination associated with non-vaccine serotypes. A small number of lineages persisted throughout, associated with both non-vaccine and vaccine types (such as ST199), or that could be an example of serotype switching from vaccine to non-vaccine types (ST177). Serotype 3 persisted throughout the study years, represented by ST180 and Global Pneumococcal Sequencing Cluster (GPSC) 12; the local PopPUNK analysis and core genome maximum likelihood phylogeny separated them into two clades, one of which is only seen in later study years. The genomic data showed that serotype replacement in the carriage studies was mostly due to a change in genotype as well as serotype, but that some important genetic lineages, previously associated with vaccine types, persisted.