Chrispin Chaguza

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.

Existing licensed pneumococcal vaccines, including Prevnar-13 and its higher-valency successors, have played a major role in reducing invasive pneumococcal disease worldwide. However, their effectiveness is increasingly threatened by the rise of multidrug-resistant strains and the shift in circulating serotypes toward those not targeted by current vaccines—a trend known as serotype replacement. These evolving challenges underscore the urgent need for next-generation vaccines with broader, serotype-independent protection—long considered the holy grail of pneumococcal vaccine development. Here, we report the discovery and preclinical evaluation of ZPY-CpG-Ch, a broad-coverage protein-based pneumococcal vaccine formulation. We assessed the protective efficacy and immunogenicity of ZPY-CpG-Ch in translational murine models, using both adult and neonatal mice, and tested various adjuvants, protein combinations, and doses, followed by challenge experiments with both vaccine- and non–vaccine-covered serotypes. Prevnar-13 was included as a benchmark. While Prevnar-13 ^® demonstrated robust efficacy, our results show that ZPY-CpG-Ch achieves greater cross-serotype protection. We attribute this enhanced efficacy primarily to T _H 17 (T helper 7)–biased immune responses. Together, these findings highlight the promise of genome-guided, protein-based vaccines in overcoming the limitations of current serotype-based approaches and represent a meaningful step toward a truly universal pneumococcal vaccine.

Quantifying short-term evolutionary rates of microbial genomes is essential for understanding the processes that shape within-host evolution and for establishing thresholds needed to track transmission. In studies of short-term evolutionary rates, samples are often collected from closely related clusters (e.g. longitudinally from the same host or from transmission pairs), with substantial time intervals separating genomes between clusters. Distinguishing strain replacement from persistence presents is also difficult in these studies. In addition, many public health and metagenomic bacterial strain tracking pipelines output pairwise SNP distances rather than the multiple sequence alignments required by common substitution rate estimation pipelines. This makes it hard to estimate within-host evolutionary rates in many commensal bacterial species that are difficult to culture and isolate. To address these challenges, we introduce MxSure , a tool for estimating substitution rates and transmission thresholds while accounting for strain replacement from pairwise SNP distance data, as commonly generated by transmission tracking and metagenomic analysis pipelines. We demonstrate the accuracy of MxSure through extensive simulations and by analysing species with previously estimated substitution rates from longitudinal metagenomic datasets. Using MxSure , we estimated within-host substitution rates and transmission SNP thresholds for multiple commensal bacterial species including Bifidobacterium longum and Bifidobacterium bifidum from a longitudinal study of the infant gut microbiome.

Streptococcus pneumoniae ( Sp ) is an opportunistic pathogen that colonizes the mucosal surfaces of the human upper respiratory tract. While transcriptomic studies of Sp have become more common, most have focused on laboratory-adapted strains such as D39 or TIGR4. These strains, though widely used in research, may not fully capture the biology of clinical isolates, particularly the hypervirulent serotype 1 (S1). S1 is clinically significant due to its association with invasive disease, epidemic outbreaks and a distinct global distribution, particularly in regions with a high pneumococcal disease burden. Unlike many other serotypes, S1 is frequently linked to hypervirulence and a propensity for rapid spread, making it a high-priority target for understanding the molecular mechanisms underpinning pneumococcal pathogenesis. In this study, we conducted a comprehensive in vitro transcriptomic analyses of Sp S1 strains, positioning this work as a valuable resource for the pneumococcal research community. Using a straightforward approach, we cultured three distinct S1 strains – ST306, ST217 and ST615, representing European, African and South American S1 lineages, respectively – in Brain Heart Infusion medium and compared transcriptomic profiles during exponential growth to those of the well-characterized laboratory-adapted D39 strain. Our analysis revealed significant differential expression of 292 genes in all three S1 isolates compared to D39. Among these, 151 genes had higher expression, including those involved in competence pathways and purine metabolism, while 141 genes exhibited lower expression, particularly those linked to lactose metabolism and iron/amino acid transport. These findings underscore the distinct molecular features of S1 strains, which likely contribute to the unique pathogenic properties of this serotype. The identification of the distinct transcriptional signatures of hypervirulent S1 strains paves the way for future efforts to design targeted therapeutics against pneumococcal S1 infections.

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.

In 2022, consecutive sweeps of highly transmissible SARS-CoV-2 Omicron-derived lineages (B.1.1.529*) maintained viral transmission despite extensive antigen exposure from both vaccinations and infections. To better understand Omicron variant emergence in the context of the dynamic fitness landscape of 2022, we aimed to explore putative drivers behind SARS-CoV-2 lineage replacements. Variant fitness is determined through its ability to either outrun previously dominant lineages or more efficiently circumvent host immune responses to previous infections and vaccinations. By analyzing data collected through our local genomic surveillance program from Connecticut, USA, we compared emerging Omicron lineages’ growth rates, estimated infections, effective reproductive rates, average viral copy numbers, and likelihood for causing infections in recently vaccinated individuals. We find that newly emerging Omicron lineages outcompeted dominant lineages through a combination of enhanced viral shedding or advanced immune escape depending on the population-level exposure state. This analysis integrates individual-level sequencing data with demographic, vaccination, laboratory, and epidemiological data and provides further insights into host–pathogen dynamics beyond public aggregate data.

Streptococcus pneumoniae is a significant cause of bacterial infections, including pneumonia, meningitis and septicemia, primarily affecting children, the elderly and immunocompromised individuals. This study aimed to elucidate the serotype and lineage distribution and molecular mechanisms underlying pneumococcal invasiveness through a comprehensive pangenomic analysis of 1416 isolates from Malawi. Our analysis comprised 810 isolates from asymptomatic carriers and 606 isolates from patients with bacteraemia or meningitis. We identified 58 serotypes, with serotypes 1, 5 and 12F exhibiting significantly higher prevalence among patients. These serotypes likely exhibit reduced nasopharyngeal colonization and demonstrate rapid dissemination to sterile sites. Notably, these serotypes form a distinct lineage with distinct genomic characteristics, including the absence of V-type ATP synthase. The pangenome analysis revealed two highly conserved surface protein complexes, F-type ATP synthase and SecA1-SecY, which deserve further investigation as potential targets for novel therapeutic interventions.

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 vitr o 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.

Streptococcus mitis is a leading cause of infective endocarditis (IE). However, our understanding of the genomic epidemiology and pathogenicity of IE-associated S. mitis is hampered by low IE incidence. Here we use whole genome sequencing of 129 S. mitis bloodstream infection (BSI) isolates collected between 2001–2016 from clinically diagnosed IE cases in the UK to investigate genetic diversity, antimicrobial resistance, and pathogenicity. We show high genetic diversity of IE-associated S. mitis with virtually all isolates belonging to distinct lineages indicating no predominance of specific lineages. Additionally, we find a highly variable distribution of known pneumococcal virulence genes among the isolates, some of which are overrepresented in disease when compared to carriage strains. Our findings suggest that S. mitis in patients with clinically diagnosed IE is not primarily caused by specific hypervirulent or antimicrobial resistant lineages, highlighting the accidental pathogenic nature of S. mitis in patients with clinically diagnosed IE.

Malawi experienced its deadliest Vibrio cholerae (Vc) outbreak following devastating cyclones, with >58,000 cases and >1700 deaths reported between March 2022 and May 2023. Here, we use population genomics to investigate the attributes and origin of the Malawi 2022–2023 Vc outbreak isolates. Our results demonstrate the predominance of ST69 clone, also known as the seventh cholera pandemic El Tor (7PET) lineage, expressing O1 Ogawa (~ 80%) serotype followed by Inaba (~ 16%) and sporadic non-O1/non-7PET serogroups (~ 4%). Phylogenetic reconstruction revealed that the Malawi outbreak strains correspond to a recent importation from Asia into Africa (sublineage AFR15). These isolates harboured known antimicrobial resistance and virulence elements, notably the ICE^GEN/ICEVchHai1/ICEVchind5 SXT/R391-like integrative conjugative elements and a CTXφ prophage with the ctxB7 genotype compared to historical Malawian Vc isolates. These data suggest that the devastating cyclones coupled with the recent importation of 7PET serogroup O1 strains, may explain the magnitude of the 2022–2023 cholera outbreak in Malawi.