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

Fourier-transform infrared spectroscopy for rapid Streptococcus pneumoniae serotyping in a tertiary care general hospital

Streptococcus pneumoniae is the leading cause of community-acquired pneumonia and remains a significant contributor to bacteremia and meningitis, collectively known as invasive pneumococcal disease (IPD). Certain serotypes are more strongly associated with severe illness and antimicrobial resistance. Accurate serotyping is essential for effective IPD surveillance and vaccine development. Fourier-transform infrared (FTIR) spectroscopy has emerged as a valuable tool for differentiating among serotypes across various isolates. We analyzed 150 pneumococcal strains isolated from a tertiary hospital in Barcelona, Catalonia, Spain, between 2016 and 2023, representing 32 serotypes associated with IPD. Forty-nine samples (33%) exhibited serotypes included in PCV13 vaccine. Each strain was classified using (A) FTIR-based clustering and (B) FTIR machine-learning-based PneumoClassifier algorithm. The results were compared to the Quellung reaction, the gold standard methodology. Clustering method grouped correctly PCV13-serotypes 1, 3, and 19F and non-PCV13 serotypes 6C, 7BC, 17F, 24F, 31, and 35B (48/150). PneumoClasifier algorithm successfully grouped all PCV13-serotypes (49/49) including some of the most virulent described serotypes, such as 1, 6B, 7F, and 14. Among non-PCV13 serotypes, it correctly classified 73 out of 101 isolates (72.3%). However, 12F, 15AB, 16F, 17F, 23A, and 24F were misclassified. Overall, PneumoClassifier achieved an accuracy of 122/150 (79.80%) in serotyping pneumococcal strains, demonstrating higher concordance with Quellung (adjusted Rand index: 0.717, adjusted Wallace coefficient: 0.636) compared to the clustering approach (0.397 and 0.378, respectively) (p < 0.001). FTIR has proven to be a rapid, user-friendly, cost-effective, and practical technique, making it a promising first-line tool for S. pneumoniae serotyping.

Update on the evolving landscape of pneumococcal capsule types: new discoveries and way forward

SUMMARYStreptococcus pneumoniae (the "pneumococcus") is a significant human pathogen. The key determinant of pneumococcal fitness and virulence is its ability to produce a protective polysaccharide (PS) capsule, and anti-capsule antibodies mediate serotype-specific opsonophagocytic killing of bacteria. Notably, immunization with pneumococcal conjugate vaccines (PCVs) has effectively reduced the burden of disease caused by serotypes included in vaccines but has also spurred a relative upsurge in the prevalence of non-vaccine serotypes. Recent advancements in serotyping and bioinformatics surveillance tools coupled with high-resolution analytical techniques have enabled the discovery of numerous new capsule types, thereby providing a fresh perspective on the dynamic pneumococcal landscape. This review offers insights into the current pneumococcal seroepidemiology highlighting important serotype shifts in different global regions in the PCV era. It also comprehensively summarizes newly discovered serotypes from 2007 to 2024, alongside updates on revised chemical structures and the de-novo determinations of structures for previously known serotypes. Furthermore, we spotlight emerging evidence on non-pneumococcal Mitis-group strains that express capsular PS that are serologically and biochemically related to the pneumococcal capsule types. We further discuss the implications of these recent findings on capsule nomenclature, pneumococcal carriage detection, and future PCV design. The review maps out the current status and also outlines the course for future research and vaccine strategies, ensuring a continued effective response to the evolving pneumococcal challenge.

Evaluating methods for identifying and quantifying Streptococcus pneumoniae co-colonization using next-generation sequencing data

Detection of multiple pneumococcal serotype carriage can enhance monitoring of pneumococcal vaccine impact, particularly among high-burden childhood populations. We assessed methods for identifying co-carriage of pneumococcal serotypes from whole-genome sequences. Twenty-four nasopharyngeal samples were collected during community carriage surveillance from healthy children in Blantyre, Malawi, which were then serotyped by microarray. Pneumococcal DNA from culture plate sweeps were sequenced using Illumina MiSeq, and genomic serotyping was carried out using SeroCall and PneumoKITy. Their sensitivity was calculated in reference to the microarray data. Local maxima in the single-nucleotide polymorphism (SNP) density distributions were assessed for their correspondence to the relative abundance of serotypes. Across the 24 individuals, the microarray detected 77 non-unique serotypes, of which 42 occurred at high relative abundance (>10%) (per individual, median, 3; range, 1-6 serotypes). The average sequencing depth was 57X (range: 21X-88X). The sensitivity of SeroCall for identifying high-abundance serotypes was 98% (95% CI, 0.87-1.00), 20% (0.08-0.36) for low abundance (<10%), and 62% (0.50-0.72) overall. PneumoKITy's sensitivity was 86% (0.72-0.95), 20% (0.06-0.32), and 56% (0.42-0.65), respectively. Local maxima in the SNP frequency distribution were highly correlated with the relative abundance of high-abundance serotypes. Six samples were resequenced, and the pooled runs had an average fourfold increase in sequencing depth. This allowed genomic serotyping of two of the previously undetectable seven low-abundance serotypes. Genomic serotyping is highly sensitive for the detection of high-abundance serotypes in samples with co-carriage. Serotype-associated reads may be identified through SNP frequency, and increased read depth can increase sensitivity for low-abundance serotype detection.IMPORTANCEPneumococcal carriage is a prerequisite for invasive pneumococcal disease, which is a leading cause of childhood pneumonia. Multiple carriage of unique pneumococcal serotypes at a single time point is prevalent among high-burden childhood populations. This study assessed the sensitivity of different genomic serotyping methods for identifying pneumococcal serotypes during co-carriage. These methods were evaluated against the current gold standard for co-carriage detection. The results showed that genomic serotyping methods have high sensitivity for detecting high-abundance serotypes in samples with co-carriage, and increasing sequencing depth can increase sensitivity for low-abundance serotypes. These results are important for monitoring vaccine impact, which aims to reduce the prevalence of specific pneumococcal serotypes. By accurately detecting and identifying multiple pneumococcal serotypes in carrier populations, we can better evaluate the effectiveness of vaccination programs.

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.

Estimating pneumococcal carriage dynamics in adults living with HIV in a mature infant pneumococcal conjugate vaccine programme in Malawi, a modelling study

BACKGROUND

Adults living with human immunodeficiency virus (ALWHIV) receiving antiretroviral therapy (ART) exhibit higher pneumococcal carriage prevalence than adults without HIV (HIV-). To assess factors influencing high pneumococcal carriage in ALWHIV, we estimated pneumococcal carriage acquisition and clearance rates in a high transmission and disease-burdened setting at least 10 years after introducing infant PCV13 in routine immunisation.

METHODS

We collected longitudinal nasopharyngeal swabs from individuals aged 18-45 in Blantyre, Malawi. The study group included both HIV- individuals and those living with HIV, categorised based on ART duration as either exceeding 1 year (ART > 1y) or less than 3 months (ART < 3 m). Samples were collected at baseline and then weekly for 16 visits. To detect pneumococcal carriage, we used classical culture microbiology, and to determine pneumococcal serotypes, we used latex agglutination. We modelled trajectories of serotype colonisation using multi-state Markov models to capture pneumococcal carriage dynamics, adjusting for age, sex, number of under 5 year old (< 5y) children, social economic status (SES), and seasonality.

RESULTS

We enrolled 195 adults, 65 adults in each of the study groups. 51.8% were females, 25.6% lived with more than one child under 5 years old, and 41.6% lived in low socioeconomic areas. The median age was 33 years (IQR 25-37 years). The baseline pneumococcal carriage prevalence of all serotypes was 31.3%, with non-PCV13 serotypes (NVT) at 26.2% and PCV13 serotypes (VT) at 5.1%. In a multivariate longitudinal analysis, pneumococcal carriage acquisition was higher in females than males (hazard ratio [HR], NVT [1.53]; VT [1.96]). It was also higher in low than high SES (NVT [1.38]; VT [2.06]), in adults living with 2 + than 1 child < 5y (VT [1.78]), and in ALWHIV on ART > 1y than HIV- adults (NVT [1.43]). Moreover, ALWHIV on ART > 1y cleared pneumococci slower than HIV- adults ([0.65]). Residual VT 19F and 3 were highly acquired, although NVT remained dominant.

CONCLUSIONS

The disproportionately high point prevalence of pneumococcal carriage in ALWHIV on ART > 1y is likely due to impaired nasopharyngeal clearance, which results in prolonged carriage. Our findings provide baseline estimates for comparing pneumococcal carriage dynamics after implementing new PCV strategies in ALWHIV.

A narrative review of genomic characteristics, serotype, immunogenicity, and vaccine development of Streptococcus pneumoniae capsular polysaccharide

This narrative review describes genomic characteristic, serotyping, immunogenicity, and vaccine development of Streptococcus pneumoniae capsular polysaccharide (CPS). CPS is a primary virulence factor of S. pneumoniae. The genomic characteristics of S. pneumoniae CPS, including the role of biosynthetic gene and genetic variation within cps (capsule polysaccharide) locus which may lead to serotype replacement are still being investigated. One hundred unique serotypes of S. pneumoniae have been identified through various methods of serotyping using phenotypic and genotypic approach. The advantages and limitations of each method are various, emphasizing the need for accurate and comprehensive serotyping for effective disease surveillance and vaccine targeting. In addition, we elaborate the critical role of CPS in vaccine development by providing an overview of immunogenicity, ongoing research of pneumococcal vaccines, and the impact on disease burden.

Streptococcus pneumoniae serotype 33G: genetic, serological, and structural analysis of a new capsule type

IMPORTANCE

Streptococcus pneumoniae (the pneumococcus) is a bacterial pathogen with the greatest burden of disease in Asia and Africa. The pneumococcal capsular polysaccharide has biological relevance as a major virulence factor as well as public health importance as it is the target for currently licensed vaccines. These vaccines have limited valency, covering up to 23 of the >100 known capsular types (serotypes) with higher valency vaccines in development. Here, we have characterized a new pneumococcal serotype, which we have named 33G. We detected serotype 33G in nasopharyngeal swabs (n = 20) from children and adults hospitalized with pneumonia, as well as healthy children in Mongolia. We show that the genetic, serological, and biochemical properties of 33G differ from existing serotypes, satisfying the criteria to be designated as a new serotype. Future studies should focus on the geographical distribution of 33G and any changes in prevalence following vaccine introduction.

The Molecular Approaches and Challenges of Streptococcus pneumoniae Serotyping for Epidemiological Surveillance in the Vaccine Era

Streptococcus pneumoniae (pneumococcus) belongs to the Gram-positive cocci. This bacterium typically colonizes the nasopharyngeal region of healthy individuals. It has a distinct polysaccharide capsule - a virulence factor allowing the bacteria to elude the immune defense mechanisms. Consequently, it might trigger aggressive conditions like septicemia and meningitis in immunocompromised or older individuals. Moreover, children below five years of age are at risk of morbidity and mortality. Studies have found 101 S. pneumoniae capsular serotypes, of which several correlate with clinical and carriage isolates with distinct disease aggressiveness. Introducing pneumococcal conjugate vaccines (PCV) targets the most common disease-associated serotypes. Nevertheless, vaccine selection pressure leads to replacing the formerly dominant vaccine serotypes (VTs) by non-vaccine types (NVTs). Therefore, serotyping must be conducted for epidemiological surveillance and vaccine assessment. Serotyping can be performed using numerous techniques, either by the conventional antisera-based (Quellung and latex agglutination) or molecular-based approaches (sequetyping, multiplex PCR, real-time PCR, and PCR-RFLP). A cost-effective and practical approach must be used to enhance serotyping accuracy to monitor the prevalence of VTs and NVTs. Therefore, dependable pneumococcal serotyping techniques are essential to precisely monitor virulent lineages, NVT emergence, and genetic associations of isolates. This review discusses the principles, associated benefits, and drawbacks of the respective available conventional and molecular approaches, and potentially the whole genome sequencing (WGS) to be directed for future exploration.

PneumoKITy: A fast, flexible, specific, and sensitive tool for Streptococcus pneumoniae serotype screening and mixed serotype detection from genome sequence data

Determination of serotypes of Streptococcus pneumoniae is essential for monitoring current vaccine programmes. Since October 2017, pneumococcal serotypes in England have been derived from whole genome sequencing (WGS) data using our bioinformatic tool PneumoCaT. That tool was designed for serotype determination from pure cultures in a reference laboratory. To help determine multiple serotypes in pneumococcal carriage samples, we developed a new software tool named PneumoKITy (Pneumococcal K-mer Integrated Typing) that uses the powerful Mash k-mer screening method for pneumococcal serotyping. Mash k-mer screening is more sequence specific and much faster than the mapping method used in PneumoCaT and can determine 54 (58.1  %) of the 93 serotypes in the SSI Diagnostica phenotypical serotyping scheme to type level with the remainder called to serogroup or subgroup level (e.g., 11A/D). PneumoKITy can be run on both FastQ and assembly input, requiring up to 11× less memory and running up to 29× faster than the current version of PneumoCaT (1.2.1) on FastQ files. PneumoKITy can be used as a rapid, flexible serotype screening method which adds sensitive detection of mixed serotypes, e.g., for nasopharyngeal carriage studies where the presence of multiple serotypes is common. PneumoKITy's ability to function from assembly file, for pure culture serotype detection, increases its speed. This speed potentially enables the software to be run using low infrastructure overhead via web-based platforms. PneumoKITy could be used as a fast initial screening method with other tools used for those serotypes that could not be fully determined to type level if necessary. PneumoKITy was found to be highly accurate and sensitive when run on a panel of FastQ files derived from mixed cultures with all serotypes in 47/51 (92.2  %) of samples being accurately detected. PneumoKITy was also able to accurately estimate the relative abundance of serotypes in the same sample. Estimates being within a mean relative abundance of 1.5 % of the expected abundance in mixtures with known concentrations. PneumoKITy was able to detect minor serotypes with expected abundance of 1 % in the known mixture serotypes. PneumoKITy is a rapid, flexible tool with wide-ranging applications outside of the pure-culture, reference laboratory serotyping remit of PneumoCaT.

Validation of Fourier Transform Infrared Spectroscopy for Serotyping of Streptococcus pneumoniae

Fourier transform infrared (FT-IR) spectroscopy (IR Biotyper; Bruker) allows highly discriminatory fingerprinting of closely related bacterial strains. In this study, FT-IR spectroscopy-based capsular typing of Streptococcus pneumoniae was validated as a rapid, cost-effective, and medium-throughput alternative to the classical phenotypic techniques. A training set of 233 strains was defined, comprising 34 different serotypes and including all 24 vaccine types (VTs) and 10 non-vaccine types (NVTs). The acquired spectra were used to (i) create a dendrogram where strains clustered together according to their serotypes and (ii) train an artificial neural network (ANN) model to predict unknown pneumococcal serotypes. During validation using 153 additional strains, we reached 98.0% accuracy for determining serotypes represented in the training set. Next, the performance of the IR Biotyper was assessed using 124 strains representing 59 non-training set serotypes. In this setting, 42 of 59 serotypes (71.1%) could be accurately categorized as being non-training set serotypes. Furthermore, it was observed that comparability of spectra was affected by the source of the Columbia medium used to grow the pneumococci and that this complicated the robustness and standardization potential of FT-IR spectroscopy. A rigorous laboratory workflow in combination with specific ANN models that account for environmental noise parameters can be applied to overcome this issue in the near future. The IR Biotyper has the potential to be used as a fast, cost-effective, and accurate phenotypic serotyping tool for S. pneumoniae.

Global genomic pathogen surveillance to inform vaccine strategies: a decade-long expedition in pneumococcal genomics

Vaccines are powerful agents in infectious disease prevention but often designed to protect against some strains that are most likely to spread and cause diseases. Most vaccines do not succeed in eradicating the pathogen and thus allow the potential emergence of vaccine evading strains. As with most evolutionary processes, being able to capture all variations across the entire genome gives us the best chance of monitoring and understanding the processes of vaccine evasion. Genomics is being widely adopted as the optimum approach for pathogen surveillance with the potential for early and precise identification of high-risk strains. Given sufficient longitudinal data, genomics also has the potential to forecast the emergence of such strains enabling immediate or pre-emptive intervention. In this review, we consider the strengths and challenges for pathogen genomic surveillance using the experience of the Global Pneumococcal Sequencing (GPS) project as an early example. We highlight the multifaceted nature of genome data and recent advances in genome-based tools to extract useful information relevant to inform vaccine strategies and treatment options. We conclude with future perspectives for genomic pathogen surveillance.

Carriage Dynamics of Pneumococcal Serotypes in Naturally Colonized Infants in a Rural African Setting During the First Year of Life

Streptococcus pneumoniae (the pneumococcus) carriage precedes invasive disease and influences population-wide strain dynamics, but limited data exist on temporal carriage patterns of serotypes due to the prohibitive costs of longitudinal studies. Here, we report carriage prevalence, clearance and acquisition rates of pneumococcal serotypes sampled from newborn infants bi-weekly from weeks 1 to 27, and then bi-monthly from weeks 35 to 52 in the Gambia. We used sweep latex agglutination and whole genome sequencing to serotype the isolates. We show rapid pneumococcal acquisition with nearly 31% of the infants colonized by the end of first week after birth and quickly exceeding 95% after 2 months. Co-colonization with multiple serotypes was consistently observed in over 40% of the infants at each sampling point during the first year of life. Overall, the mean acquisition time and carriage duration regardless of serotype was 38 and 24 days, respectively, but varied considerably between serotypes comparable to observations from other regions. Our data will inform disease prevention and control measures including providing baseline data for parameterising infectious disease mathematical models including those assessing the impact of clinical interventions such as pneumococcal conjugate vaccines.