Validation of β-lactam minimum inhibitory concentration predictions for pneumococcal isolates with newly encountered penicillin binding protein (PBP) sequences

Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno and Aytan-Aktug), an ML baseline and the rule-based ResFinder by training and testing each of them across 78 species-antibiotic datasets, using a rigorous benchmarking workflow that integrates three evaluation approaches, each paired with three distinct sample splitting methods. Our analysis revealed considerable variation in the performance across techniques and datasets. Whereas ML methods generally excelled for closely related strains, ResFinder excelled for handling divergent genomes. Overall, Kover most frequently ranked top among the ML approaches, followed by PhenotypeSeeker and Seq2Geno2Pheno. AMR phenotypes for antibiotic classes such as macrolides and sulfonamides were predicted with the highest accuracies. The quality of predictions varied substantially across species-antibiotic combinations, particularly for beta-lactams; across species, resistance phenotyping of the beta-lactams compound, aztreonam, amoxicillin/clavulanic acid, cefoxitin, ceftazidime and piperacillin/tazobactam, alongside tetracyclines demonstrated more variable performance than the other benchmarked antibiotics. By organism, Campylobacter jejuni and Enterococcus faecium phenotypes were more robustly predicted than those of Escherichia coli, Staphylococcus aureus, Salmonella enterica, Neisseria gonorrhoeae, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae and Mycobacterium tuberculosis. In addition, our study provides software recommendations for each species-antibiotic combination. It furthermore highlights the need for optimization for robust clinical applications, particularly for strains that diverge substantially from those used for training.

Optimising machine learning prediction of minimum inhibitory concentrations in Klebsiella pneumoniae

Minimum Inhibitory Concentrations (MICs) are the gold standard for quantitatively measuring antibiotic resistance. However, lab-based MIC determination can be time-consuming and suffers from low reproducibility, and interpretation as sensitive or resistant relies on guidelines which change over time. Genome sequencing and machine learning promise to allow in silico MIC prediction as an alternative approach which overcomes some of these difficulties, albeit the interpretation of MIC is still needed. Nevertheless, precisely how we should handle MIC data when dealing with predictive models remains unclear, since they are measured semi-quantitatively, with varying resolution, and are typically also left- and right-censored within varying ranges. We therefore investigated genome-based prediction of MICs in the pathogen Klebsiella pneumoniae using 4367 genomes with both simulated semi-quantitative traits and real MICs. As we were focused on clinical interpretation, we used interpretable rather than black-box machine learning models, namely, Elastic Net, Random Forests, and linear mixed models. Simulated traits were generated accounting for oligogenic, polygenic, and homoplastic genetic effects with different levels of heritability. Then we assessed how model prediction accuracy was affected when MICs were framed as regression and classification. Our results showed that treating the MICs differently depending on the number of concentration levels of antibiotic available was the most promising learning strategy. Specifically, to optimise both prediction accuracy and inference of the correct causal variants, we recommend considering the MICs as continuous and framing the learning problem as a regression when the number of observed antibiotic concentration levels is large, whereas with a smaller number of concentration levels they should be treated as a categorical variable and the learning problem should be framed as a classification. Our findings also underline how predictive models can be improved when prior biological knowledge is taken into account, due to the varying genetic architecture of each antibiotic resistance trait. Finally, we emphasise that incrementing the population database is pivotal for the future clinical implementation of these models to support routine machine-learning based diagnostics.

Pneumococcal population genomics changes during the early time period of conjugate vaccine uptake in southern India

Streptococcus pneumoniae is a major cause of invasive disease of young children in low- and middle-income countries. In southern India, pneumococcal conjugate vaccines (PCVs) that can prevent invasive pneumococcal disease began to be used more frequently after 2015. To characterize pneumococcal evolution during the early time period of PCV uptake in southern India, genomes were sequenced and selected characteristics were determined for 402 invasive isolates collected from children <5 years of age during routine surveillance from 1991 to 2020. Overall, the prevalence and diversity of vaccine type (VT) and non-vaccine type (NVT) isolates did not significantly change post-uptake of PCV. Individually, serotype 1 and global pneumococcal sequence cluster (GPSC or strain lineage) 2 significantly decreased, whereas serotypes 6B, 9V and 19A and GPSCs 1, 6, 10 and 23 significantly increased in proportion post-uptake of PCV. Resistance determinants to penicillin, erythromycin, co-trimoxazole, fluoroquinolones and tetracycline, and multidrug resistance significantly increased in proportion post-uptake of PCV and especially among VT isolates. Co-trimoxazole resistance determinants were common pre- and post-uptake of PCV (85 and 93 %, respectively) and experienced the highest rates of recombination in the genome. Accessory gene frequencies were seen to be changing by small amounts across the frequency spectrum specifically among VT isolates, with the largest changes linked to antimicrobial resistance determinants. In summary, these results indicate that as of 2020 this pneumococcal population was not yet approaching a PCV-induced equilibrium and they highlight changes related to antimicrobial resistance. Augmenting PCV coverage and prudent use of antimicrobials are needed to counter invasive pneumococcal disease in this region.

Strain features of pneumococcal isolates in the pre- and post-PCV10 era in Pakistan

Pakistan is amongst the four countries with the highest number of pneumococcal deaths. While the PCV10 vaccine was introduced in Pakistan in October 2012, data regarding the impact of the vaccine on the population dynamics of Streptococcus pneumoniae in Pakistan remain obscure. Using whole genome sequencing of 190 isolates (nasopharyngeal carriage=75, disease=113, unknown sites=2) collected between 2002 and 2020, this study presents characteristics of pneumococcal strains in Pakistan in the pre- and post-vaccine era. The isolates were characterized on the basis of serotype distribution, genetic lineages (or Global Pneumococcal Sequence Cluster, GPSC) and antibiotic resistance. A high level of diversity in serotype and genetic lineages of pneumococci was observed in Pakistan. Among 190 isolates, we identified 54 serotypes, 67 GPSCs and 116 sequence types (STs) including 23 new STs. The most prevalent GPSCs and their associated serotypes in nasopharyngeal carriage were GPSC54 (expressing serotype 9V), GPSC5 (15A and 7B, and serogroup 24), GPSC25 (15B/15C), GPSC67 (18C) and GPSC376 (6A and 6D). Similarly, among 113 disease-causing isolates, the most prevalent GPSC/serotype combinations were GPSC2 (serotype 1), GPSC10 (serotypes 14, 10A, 19A and 19F), GPSC43 (serotypes 13, 11A, 23B, 35A and 9V), GPSC67 (serotypes 18A and 18C) and GPSC642 (serotype 11A). Of the 190 isolates, the highest levels of resistance were observed against penicillin (58.9 %, n=122), erythromycin (29.5 %, n=56), clindamycin (13.2 %, n=25), co-trimoxazole (94.2 %, n=179) and tetracycline/doxycycline (53.2 %, n=101). A higher proportion of disease-causing isolates were multidrug resistant as compared to carriage isolates (54 % vs 25 %). Our data suggest limited coverage of PCV10 in nasopharyngeal (21.6 %, 16/74) as well as disease-causing (38.1 %, 16/42) isolates among children ≤5 years old; however, higher valent vaccine PCV13 would increase the coverage rates to 33.8 % in nasopharyngeal and 54.8 % in disease-causing isolates, whereas PCV24/25 would offer the highest coverage rates. Owing to the diversity of serotypes observed during the post-vaccine period, the suggested inclusion of serotype in future vaccine formulations will require investigations with larger data sets with an extended temporal window. This article contains data hosted by Microreact.

Molecular characterization of Streptococcus pneumoniae causing disease among children in Nigeria during the introduction of PCV10 (GSK)

Streptococcus pneumoniae (pneumococcus) is a leading vaccine-preventable cause of childhood invasive disease. Nigeria has the second highest pneumococcal disease burden globally, with an estimated ~49 000 child deaths caused by pneumococcal infections each year. Ten-valent pneumococcal conjugate vaccine (GSK; PCV10) was introduced in December 2014 in a phased approach. However, few studies have characterized the disease-causing pneumococci from Nigeria. This study assessed the prevalence of serotypes, antibiotic susceptibility and genomic lineages using whole genome sequencing and identified lineages that could potentially escape PCV10 (GSK). We also investigated the potential differences in pneumococcal lineage features between children with and without sickle cell disease. A collection of 192 disease-causing pneumococcal isolates was obtained from Kano (n=189) and Abuja (n=3) states, Nigeria, between 1 January 2014 and 31 May 2018. The majority (99 %, 190/192) of specimens were recovered from children aged 5 years or under. Among them, 37 children had confirmed or traits of sickle cell disease. Our findings identified 25 serotypes expressed by 43 Global Pneumococcal Sequence Clusters (GPSCs) and 85 sequence types (STs). The most common serotypes were 14 (18 %, n=35), 6B (16 %, n=31), 1 (9 %, n=17), 5 (9 %, n=17) and 6A (9 %, n=17); all except serotype 6A are included in PCV10 (GSK). PCV10 (SII; PNEUMOSIL) and PCV13 formulations include serotypes 6A and 19A which would increase the overall coverage from 67 % by PCV10 (GSK) to 78 and 82 %, respectively. The pneumococcal lineages were a mix of globally spreading and unique local lineages. Following the use of PCV10 (GSK), GPSC5 expressing serotype 6A, GPSC10 (19A), GPSC26 (12F and 46) and GPSC627 (9L) are non-vaccine type lineages that could persist and potentially expand under vaccine-selective pressure. Approximately half (52 %, 99/192) of the pneumococcal isolates were resistant to the first-line antibiotic penicillin and 44 % (85/192) were multidrug-resistant. Erythromycin resistance was very low (2 %, 3/192). There was no significant difference in clinical manifestation, serotype prevalence or antibiotic resistance between children with and without traits of or confirmed sickle cell disease. In summary, our findings show that a high percentage of the pneumococcal disease were caused by the serotypes that are covered by currently available vaccines. Given the low prevalence of resistance, macrolide antibiotics, such as erythromycin, should be considered as an option to treat pneumococcal disease in Nigeria. However, appropriate use of macrolide antibiotics should be vigilantly monitored to prevent the potential increase in macrolide resistance.

A case report of disseminated Streptococcus pneumoniae infection complicated by infective endocarditis, septic arthritis and epidural abscess in an immunocompetent patient

Streptococcus pneumoniae is a highly virulent, vaccine-preventable pathogen which can cause disease on a spectrum from benign to fatal. Apart from pneumonia, it commonly causes septicaemia and meningitis. This case report describes an unusual range of complications in a 53-year-old Caucasian female presenting to a regional hospital, without any risk known factors for severe disease (such as extremes of age, immunodeficiency or co-morbidities). Progressing from an episode of otitis media, her condition rapidly progressed to mastoid sinusitis, septic arthritis, infective endocarditis, epidural abscesses and multiple subcutaneous abscesses. Following quick identification of S. pneumoniae from a positive blood culture, the patient was treated with high-dose benzylpenicillin and ceftriaxone and aggressive source control by surgery, enabling a good clinical recovery.

A global genomic perspective on the multidrug-resistant Streptococcus pneumoniae 15A-CC63 sub-lineage following pneumococcal conjugate vaccine introduction

The introduction of pneumococcal conjugate vaccines (PCV7, PCV10, PCV13) around the world has proved successful in preventing invasive pneumococcal disease. However, immunization against Streptococcus pneumoniae has led to serotype replacement by non-vaccine serotypes, including serotype 15A. Clonal complex 63 (CC63) is associated with many serotypes and has been reported in association with 15A after introduction of PCVs. A total of 865 CC63 isolates were included in this study, from the USA (n=391) and a global collection (n=474) from 1998-2019 and 1995-2018, respectively. We analysed the genomic sequences to identify serotypes and penicillin-binding protein (PBP) genes 1A, 2B and 2X, and other resistance determinants, to predict minimum inhibitory concentrations (MICs) against penicillin, erythromycin, clindamycin, co-trimoxazole and tetracycline. We conducted phylogenetic and spatiotemporal analyses to understand the evolutionary history of the 15A-CC63 sub-lineage. Overall, most (89.5 %, n=247) pre-PCV isolates in the CC63 cluster belonged to serotype 14, with 15A representing 6.5 % of isolates. Conversely, serotype 14 isolates represented 28.2 % of post-PCV CC63 isolates (n=618), whilst serotype 15A isolates represented 65.4 %. Dating of the CC63 lineage determined the most recent common ancestor emerged in the 1980s, suggesting the 15A-CC63 sub-lineage emerged from its closest serotype 14 ancestor prior to the development of pneumococcal vaccines. This sub-lineage was predominant in the USA, Israel and China. Multidrug resistance (to three or more drug classes) was widespread among isolates in this sub-lineage. We show that the CC63 lineage is globally distributed and most of the isolates are penicillin non-susceptible, and thus should be monitored.

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.

Geographic migration and vaccine-induced fitness changes of Streptococcus pneumoniae

Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location. The extent and mechanisms of spread, and vaccine-driven changes in fitness and antimicrobial resistance (AMR), remain largely unquantified. Using geolocated genome sequences from South Africa (N=6910, 2000-2014) we developed models to reconstruct spread, pairing detailed human mobility data and genomic data. Separately we estimated the population level changes in fitness of strains that are (vaccine type, VT) and are not (non-vaccine type, NVT) included in the vaccine, first implemented in 2009, as well as differences in strain fitness between those that are and are not resistant to penicillin. We estimated that pneumococci only become homogenously mixed across South Africa after about 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Further, in the years following vaccine implementation the relative fitness of NVT compared to VT strains increased (RR: 1.29 [95% CI 1.20-1.37]) - with an increasing proportion of these NVT strains becoming penicillin resistant. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in AMR may be transient.

Predicting β-lactam susceptibility from the genome of Streptococcus pneumoniae and other mitis group streptococci

Introduction

For Streptococcus pneumoniae, β-lactam susceptibility can be predicted from the amino acid sequence of the penicillin-binding proteins PBP1a, PBP2b, and PBP2x. The combination of PBP-subtypes provides a PBP-profile, which correlates to a phenotypic minimal inhibitory concentration (MIC). The non-S. pneumoniae Mitis-group streptococci (MGS) have similar PBPs and exchange pbp-alleles with S. pneumoniae. We studied whether a simple BLAST analysis could be used to predict phenotypic susceptibility in Danish S. pneumoniae isolates and in internationally collected MGS.

Method

Isolates with available WGS and phenotypic susceptibility data were included. For each isolate, the best matching PBP-profile was identified by BLAST analysis. The corresponding MICs for penicillin and ceftriaxone was retrieved. Category agreement (CA), minor-, major-, and very major discrepancy was calculated. Genotypic-phenotypic accuracy was examined with Deming regression.

Results

Among 88 S. pneumoniae isolates, 55 isolates had a recognized PBP-profile, and CA was 100% for penicillin and 98.2% for ceftriaxone. In 33 S. pneumoniae isolates with a new PBP-profile, CA was 90.9% (penicillin) and 93.8% (ceftriaxone) using the nearest recognized PBP-profile. Applying the S. pneumoniae database to non-S. pneumoniae MGS revealed that none had a recognized PBP-profile. For Streptococcus pseudopneumoniae, CA was 100% for penicillin and ceftriaxone in 19 susceptible isolates. In 33 Streptococcus mitis isolates, CA was 75.8% (penicillin) and 86.2% (ceftriaxone) and in 25 Streptococcus oralis isolates CA was 8% (penicillin) and 100% (ceftriaxone).

Conclusion

Using a simple BLAST analysis, genotypic susceptibility prediction was accurate in Danish S. pneumoniae isolates, particularly in isolates with recognized PBP-profiles. Susceptibility was poorly predicted in other MGS using the current database.

Invasive Group A Streptococcal Penicillin Binding Protein 2× Variants Associated with Reduced Susceptibility to β-Lactam Antibiotics in the United States, 2015-2021

All known group A streptococci [GAS] are susceptible to β-lactam antibiotics. We recently identified an invasive GAS (iGAS) variant (emm43.4/PBP2x-T553K) with unusually high minimum inhibitory concentrations (MICs) for ampicillin and amoxicillin, although clinically susceptible to β-lactams. We aimed to quantitate PBP2x variants, small changes in β-lactam MICs, and lineages within contemporary population-based iGAS. PBP2x substitutions were comprehensively identified among 13,727 iGAS recovered during 2015-2021, in the USA. Isolates were subjected to antimicrobial susceptibility testing employing low range agar diffusion and PBP2x variants were subjected to phylogenetic analyses. Fifty-five variants were defined based upon substitutions within an assigned PBP2x transpeptidase domain. Twenty-nine of these variants, representing 338/13,727 (2.5%) isolates and 16 emm types, exhibited slightly elevated β-lactam MICs, none of which were above clinical breakpoints. The emm43.4/PBP2x-T553K variant, comprised of two isolates, displayed the most significant phenotype (ampicillin MIC 0.25 μg/ml) and harbored missense mutations within 3 non-PBP genes with known involvement in antibiotic efflux, membrane insertion of PBP2x, and peptidoglycan remodeling. The proportion of all PBP2x variants with elevated MICs remained stable throughout 2015-2021 (<3.0%). The predominant lineage (emm4/PBP2x-M593T/ermT) was resistant to macrolides/lincosamides and comprised 129/340 (37.9%) of isolates with elevated β-lactam MICs. Continuing β-lactam selective pressure is likely to have selected PBP2x variants that had escaped scrutiny due to MICs that remain below clinical cutoffs. Higher MICs exhibited by emm43.4/PBP2x-T553K are probably rare due to the requirement of additional mutations. Although elevated β-lactam MICs remain uncommon, emm43.4/PBP2x-T553K and emm4/PBP2x-M593T/ermT lineages indicate that antibiotic stewardship and strain monitoring is necessary.

Key features of pneumococcal isolates recovered in Central and Northwestern Russia in 2011–2018 determined through whole-genome sequencing

Invasive pneumococcal disease remains one of the leading causes of morbidity and mortality worldwide. In Russia, 13- valent pneumococcal conjugate vaccine (PCV13) was introduced into the childhood immunization programme nationwide in 2014. As part of the Global Pneumococcal Sequencing Project (GPS), we used genome data to characterize 179 pneumococcal isolates collected from Russia in 2011–2018 to investigate the circulating pneumococcal strains using a standardized genomic definition of pneumococcal lineages (global pneumococcal sequence clusters, GPSCs), prevalent serotypes and antimicrobial resistance profiles.

We observed high serotype and lineage diversity among the 179 isolates recovered from cerebrospinal fluid (n=77), nasopharyngeal swabs (n=99) and other non-sterile site swabs (n=3). Overall, 60 GPSCs were identified, including 48 clonal complexes (CCs) and 14 singletons, and expressed 42 serotypes (including non-typable). Among PCV13 serotypes, 19F, 6B and 23F were the top three serotypes while 11A, 15B/C and 8 were the top three among non-PCV13 serotypes in the collection. Two lineages (GPSC6 and GPSC47) expressed both PCV13 and non-PCV13 serotypes that caused invasive disease, and were penicillin- and multidrug-resistant (MDR), highlighting their potential to adapt and continue to cause infections under vaccine and antibiotic selective pressure. PCV13 serotypes comprised 92 % (11/12) of the CSF isolates from the children aged below 5 years; however, the prevalence of PCV13 serotype isolates dropped to 53 % (31/58) among the nasopharyngeal isolates. Our analysis showed that 59 % (105/179) of the isolates were predicted to be non-susceptible to at least one class of antibiotics and 26 % (46/179) were MDR. Four MDR lineages (GPSC1, GPSC6, GPSC10 and GPSC47) accounted for 65 % (30/46) of the MDR isolates and expressed PCV13 serotypes (93 %, 28/30).

This study provides evidence of high genetic and serotype diversity contributed by a mix of globally spreading and regionally circulating lineages in Russia. The observations suggest that the PCV13 vaccine could be important in reducing both invasive disease and antimicrobial resistance. We also identify potential lineages (GPSC6 and GPSC47) that may evade the vaccine.

Genetic background of Cambodian pneumococcal carriage isolates following pneumococcal conjugate vaccine 13

Streptococcus pneumoniae (the pneumococcus) is a leading cause of childhood mortality globally and in Cambodia. It is commensal in the human nasopharynx, occasionally resulting in invasive disease. Monitoring population genetic shifts, characterized by lineage and serotype expansions, as well as antimicrobial-resistance (AMR) patterns is crucial for assessing and predicting the impact of vaccination campaigns. We sought to elucidate the genetic background (global pneumococcal sequence clusters; GPSCs) of pneumococci carried by Cambodian children following perturbation by pneumococcal conjugate vaccine (PCV) 13. We sequenced pre-PCV13 (01/2013-12/2015, N=258) and post-PCV13 carriage isolates (01/2016-02/2017, N=428) and used PopPUNK and SeroBA to determine lineage prevalence and serotype composition. Following PCV13 implementation in Cambodia, we saw expansions of non-vaccine type (NVT) serotypes 23A (GPSC626), 34 (GPSC45) and 6D (GPSC16). We predicted antimicrobial susceptibility using the CDC-AMR pipeline and determined concordance with phenotypic data. The CDC-AMR pipeline had >90 % concordance with the phenotypic antimicrobial-susceptibility testing. We detected a high prevalence of AMR in both expanding non-vaccine serotypes and residual vaccine serotype 6B. Persistently high levels of AMR, specifically persisting multidrug-resistant lineages, warrant concern. The implementation of PCV13 in Cambodia has resulted in NVT serotype expansion reflected in the carriage population and driven by specific genetic backgrounds. Continued monitoring of these GPSCs during the ongoing collection of additional carriage isolates in this population is necessary.

Population genomics of pneumococcal carriage in South Africa following the introduction of the 13-valent pneumococcal conjugate vaccine (PCV13) immunization

Streptococcus pneumoniae is a major human pathogen responsible for over 317000 deaths in children <5 years of age with the burden of the disease being highest in low- and middle-income countries including South Africa. Following the introduction of the 7-valent and 13-valent pneumococcal conjugate vaccine (PCV) in South Africa in 2009 and 2011, respectively, a decrease in both invasive pneumococcal infections and asymptomatic carriage of vaccine-type pneumococci were reported. In this study, we described the changing epidemiology of the pneumococcal carriage population in South Africa, by sequencing the genomes of 1825 isolates collected between 2009 and 2013. Using these genomic data, we reported the changes in serotypes, Global Pneumococcal Sequence Clusters (GPSCs), and antibiotic resistance before and after the introduction of PCV13. The pneumococcal carriage population in South Africa has a high level of diversity, comprising of 126 GPSCs and 49 serotypes. Of the ten most prevalent GPSCs detected, six were predominantly found in Africa (GPSC22, GPSC21, GPSC17, GPSC33, GPSC34 and GPSC52). We found a significant decrease in PCV7 serotypes (19F, 6B, 23F and 14) and an increase in non-vaccine serotypes (NVT) (16F, 34, 35B and 11A) among children <2 years of age. The increase in NVTs was driven by pneumococcal lineages GPSC33, GPSC34, GPSC5 and GPSC22. Overall, a decrease in antibiotic resistance for 11 antimicrobials was detected in the PCV13 era. Further, we reported a higher resistance prevalence among vaccine types (VTs), as compared to NVTs; however, an increase in penicillin resistance among NVT was observed between the PCV7 and PCV13 eras. The carriage isolates from South Africa predominantly belonged to pneumococcal lineages, which are endemic to Africa. While the introduction of PCV resulted in an overall reduction of resistance in pneumococcal carriage isolates, an increase in penicillin resistance among NVTs was detected in children aged between 3 and 5 years, driven by the expansion of penicillin-resistant clones associated with NVTs in the PCV13 era.

Extensive/Multidrug-Resistant Pneumococci Detected in Clinical Respiratory Tract Samples in Southern Sweden Are Closely Related to International Multidrug-Resistant Lineages

Background/Objective

The frequencies of non-susceptibility against common antibiotics among pneumococci vary greatly across the globe. When compared to other European countries antibiotic resistance against penicillin and macrolides has been uncommon in Sweden in recent years. Multidrug resistance (MDR) is, however, of high importance since relevant treatment options are scarce. The purpose of this study was to characterize the molecular epidemiology, presence of resistance genes and selected virulence genes of extensively drug-resistant (XDR) (n=15) and MDR (n=10) Streptococcus pneumoniae detected in clinical respiratory tract samples isolated from patients in a southern Swedish county 2016-2018. With the aim of relating them to global MDR pneumococci.

Methods

Whole genome sequencing (WGS) was performed to determine molecular epidemiology, resistance genes and presence of selected virulence factors. Antimicrobial susceptibility profiles were determined using broth microdilution testing. Further analyses were performed on isolates from the study and from the European nucleotide archive belonging to global pneumococcal sequence cluster (GPSC) 1 (n=86), GPSC9 (n=55) and GPSC10 (n=57). Bacteria were analyzed regarding selected virulence determinants (pilus islet 1, pilus islet 2 and Zinc metalloproteinase C) and resistance genes.

Results

Nineteen of 25 isolates were related to dominant global MDR lineages. Seventeen belonged to GPSC1, GPSC9 or GPSC10 with MDR non-PCV serotypes in GPSC9 (serotype 15A and 15C) as well as GPSC10 (serotype 7B, 15B and serogroup 24). Pilus islet-1 and pilus islet-2 were present in most sequence types belonging to GPSC1 and in two isolates within GPSC9 but were not detected in isolates belonging to GPSC10. Zinc metalloproteinase C was well conserved within all analyzed isolates belonging to GPSC9 but were not found in isolates from GPSC1 or GPSC10.

Conclusions

Although MDR S. pneumoniae is relatively uncommon in Sweden compared to other countries, virulent non-PCV serotypes that are MDR may become an increasing problem, particularly from clusters GPSC9 and GPSC10. Since the incidence of certain serotypes (3, 15A, and 19A) found among our MDR Swedish study isolates are persistent or increasing in invasive pneumococcal disease further surveillance is warranted.

Invasive pneumococcal disease clusters disproportionally impact persons experiencing homelessness, injecting drug users, and the western United States

BACKGROUND

Invasive pneumococcal disease (IPD) isolates forming genomic clusters can reflect rapid disease transmission between vulnerable individuals.

METHODS

We performed whole genome sequencing of 2820 IPD isolates recovered during 2019 through CDC's Active Bacterial Core surveillance (ABCs) to provide strain information (serotypes, resistance, genotypes), and 2778 of these genomes were analyzed to detect highly related genomic clusters.

RESULTS

Isolates from persons experiencing homelessness (PEH) were more often within genomic clusters than those from persons not experiencing homelessness (PNEH) (105/198, 53.0% vs 592/2551, 23.2%, p<0.001). The 4 western sites accounted for 33.4% (929/2778) of isolates subjected to cluster analysis yet accounted for 48.7% (343/705) of clustering isolates (p<0.001) and 150/198 (75.8%) isolates recovered from PEH (p<0.001). Serotypes most frequent among PEH were (in rank order) 12F, 4, 3, 9N, 8, 20, and 22F, all of which were among the 10 serotypes exhibiting the highest proportions of clustering isolates among all cases. These serotypes accounted for 44.9% (1265/2820) of all IPD cases and are included within available vaccines.

CONCLUSIONS

We identified serotype-specific and geographic differences in IPD transmission. We show the vulnerability of PEH within different regions to rapidly spreading IPD transmission networks representing several pneumococcal serotypes included in available vaccines.

Transition of Serotype 35B Pneumococci From Commensal to Prevalent Virulent Strain in Children

In our community-based prospective cohort study in young children, we observed a significant increase in pneumococcal serotype 35B nasopharyngeal (NP) commensal colonization during the 2011–2014 timeframe, but these strains were not associated with disease. Beginning in 2015 and continuing through to the present, the serotype 35B virulence changed, and it became the dominant bacteria isolated and associated with pneumococcal acute otitis-media (AOM) in our cohort. We performed comparative analyses of 250 35B isolates obtained from 140 children collected between 2006 and 2019. Changes in prevalence, clonal-complex composition, and antibiotic resistance were analyzed. Seventy-two (29%) of 35B isolates underwent whole-genome sequencing to investigate genomic changes associated with the shift in virulence that resulted in increased rates of 35B-associated AOM disease. 35B strains that were commensals and AOM disease-causing were mainly associated with sequence type (ST) 558. Antibiotic concentrations of β-lactams and ofloxacin necessary to inhibit growth of 35B strains rose significantly (2006–2019) (p<0.005). However, only isolates from the 35B/ST558 showed significant increases in MIC₅₀ of penicillin and ofloxacin between the years 2006–2014 and 2015–2019 (p=0.007 and p<0.0001). One hundred thirty-eight SNPs located in 34 different genes were significantly associated with post-2015 strains. SNPs were found in nrdG (metal binding, 10%); metP and metN (ABC transporter, 9%); corA (Mg²⁺ transporter, 6%); priA (DNA replication, 5%); and on the enzymic gene ldcB (LD-carboxypeptidase, 3%). Pneumococcal serotype 35B strains was a common NP commensal during 2010–2014. In 2015, a shift in increasing number of AOM cases occurred in young children caused by 35B, that was associated with changes in genetic composition and antibiotic susceptibility.

Genomic surveillance of invasive Streptococcus pneumoniae isolates in the period pre-PCV10 and post-PCV10 introduction in Brazil

In 2010, Brazil introduced the 10-valent pneumococcal conjugate vaccine (PCV10) into the national children’s immunization programme. This study describes the genetic characteristics of invasive Streptococcus pneumoniae isolates before and after PCV10 introduction. A subset of 466 [pre-PCV10 (2008–2009): n=232, post-PCV10 (2012–2013): n=234;<5 years old: n=310, ≥5 years old: n=156] pneumococcal isolates, collected through national laboratory surveillance, were whole-genome sequenced (WGS) to determine serotype, pilus locus, antimicrobial resistance and genetic lineages. Following PCV10 introduction, in the <5 years age group, non-vaccine serotypes (NVT) serotype 3 and serotype 19A were the most frequent, and serotypes 12F, 8 and 9 N in the ≥5 years old group. The study identified 65 Global Pneumococcal Sequence Clusters (GPSCs): 49 (88 %) were GPSCs previously described and 16 (12 %) were Brazilian clusters. In total, 36 GPSCs (55 %) were NVT lineages, 18 (28 %) vaccine serotypes (VT) and 11 (17 %) were both VT and NVT lineages. In both sampling periods, the most frequent lineage was GPSC6 (CC156, serotypes 14/9V). In the <5 years old group, a decrease in penicillin (P=0.0123) and cotrimoxazole (P<0.0001) resistance and an increase in tetracycline (P=0.019) were observed. Penicillin nonsusceptibility was predicted in 40 % of the isolates; 127 PBP combinations were identified (51 predicted MIC≥0.125 mg l⁻¹); cotrimoxazole (folA and/or folP alterations), macrolide (mef and/or ermB) and tetracycline (tetM, tetO or tetS/M) resistance were predicted in 63, 13 and 21.6 % of pneumococci studied, respectively. The main lineages associated with multidrug resistance in the post-PCV10 period were composed of NVT, GPSC1 (CC320, serotype 19A), and GPSC47 (ST386, serotype 6C). The study provides a baseline for future comparisons and identified important NVT lineages in the post-PCV10 period in Brazil.

Population genetic structure, serotype distribution and antibiotic resistance of Streptococcus pneumoniae causing invasive disease in children in Argentina

Invasive disease caused by Streptococcus pneumoniae (IPD) is one of the leading causes of morbidity and mortality in young children worldwide. In Argentina, PCV13 was introduced into the childhood immunization programme nationwide in 2012 and PCV7 was available from 2000, but only in the private market. Since 1993 the National IPD Surveillance Programme, consisting of 150 hospitals, has conducted nationwide pneumococcal surveillance in Argentina in children under 6 years of age, as part of the SIREVA II-OPS network. A total of 1713 pneumococcal isolates characterized by serotype (Quellung) and antimicrobial resistance (agar dilution) to ten antibiotics, belonging to three study periods: pre-PCV7 era 1998-1999 (pre-PCV), before the introduction of PCV13 2010-2011 (PCV7) and after the introduction of PCV13 2012-2013 (PCV13), were available for inclusion. Fifty-four serotypes were identified in the entire collection and serotypes 14, 5 and 1 represented 50 % of the isolates. Resistance to penicillin was 34.9 %, cefotaxime 10.6 %, meropenem 4.9 %, cotrimoxazole 45 %, erythromycin 21.5 %, tetracycline 15.4 % and chloramphenicol 0.4 %. All the isolates were susceptible to levofloxacin, rifampin and vancomycin. Of 1713 isolates, 1061 (61.9 %) were non-susceptible to at least one antibiotic and 235(13.7 %) were multidrug resistant. A subset of 413 isolates was randomly selected and whole-genome sequenced as part of Global Pneumococcal Sequencing Project (GPS). The genome data was used to investigate the population structure of S. pneumoniae defining pneumococcal lineages using Global Pneumococcal Sequence Clusters (GPSCs), sequence types (STs) and clonal complexes (CCs), prevalent serotypes and their associated pneumococcal lineages and genomic inference of antimicrobial resistance. The collection showed a great diversity of strains. Among the 413 isolates, 73 known and 36 new STs were identified belonging to 38 CCs and 25 singletons, grouped into 52 GPSCs. Important changes were observed among vaccine types when pre-PCV and PCV13 periods were compared; a significant decrease in serotypes 14, 6B and 19F and a significant increase in 7F and 3. Among non-PCV13 types, serogroup 24 increased from 0 % in pre-PCV to 3.2 % in the PCV13 period. Our analysis showed that 66.1 % (273/413) of the isolates were predicted to be non-susceptible to at least one antibiotic and 11.9 % (49/413) were multidrug resistant. We found an agreement of 100 % when comparing the serotype determined by Quellung and WGS-based serotyping and 98.4 % of agreement in antimicrobial resistance. Continued surveillance of the pneumococcal population is needed to reveal the dynamics of pneumococcal isolates in Argentina in post-PCV13. This article contains data hosted by Microreact.

Streptococcus pneumoniae serotypes that frequently colonise the human nasopharynx are common recipients of penicillin-binding protein gene fragments from Streptococcus mitis

Streptococcus pneumoniae is an important global pathogen that causes bacterial pneumonia, sepsis and meningitis. Beta-lactam antibiotics are the first-line treatment for pneumococcal disease, however, their effectiveness is hampered by beta-lactam resistance facilitated by horizontal genetic transfer (HGT) with closely related species. Although interspecies HGT is known to occur among the species of the genus Streptococcus, the rates and effects of HGT between Streptococcus pneumoniae and its close relatives involving the penicillin binding protein (pbp) genes remain poorly understood. Here we applied the fastGEAR tool to investigate interspecies HGT in pbp genes using a global collection of whole-genome sequences of Streptococcus mitis, Streptococcus oralis and S. pneumoniae. With these data, we established that pneumococcal serotypes 6A, 13, 14, 16F, 19A, 19F, 23F and 35B were the highest-ranking serotypes with acquired pbp fragments. S. mitis was a more frequent pneumococcal donor of pbp fragments and a source of higher pbp nucleotide diversity when compared with S. oralis. Pneumococci that acquired pbp fragments were associated with a higher minimum inhibitory concentration (MIC) for penicillin compared with pneumococci without acquired fragments. Together these data indicate that S. mitis contributes to reduced β-lactam susceptibility among commonly carried pneumococcal serotypes that are associated with long carriage duration and high recombination frequencies. As pneumococcal vaccine programmes mature, placing increasing pressure on the pneumococcal population structure, it will be important to monitor the influence of antimicrobial resistance HGT from commensal streptococci such as S. mitis.

Prediction of Minimal Inhibitory Concentration of Meropenem Against Klebsiella pneumoniae Using Metagenomic Data

Minimal inhibitory concentration (MIC) is defined as the lowest concentration of an antimicrobial agent that can inhibit the visible growth of a particular microorganism after overnight incubation. Clinically, antibiotic doses for specific infections are determined according to the fraction of MIC. Therefore, credible assessment of MICs will provide a physician valuable information on the choice of therapeutic strategy. Early and precise usage of antibiotics is the key to an infection therapy. Compared with the traditional culture-based method, the approach of whole genome sequencing to identify MICs can shorten the experimental time, thereby improving clinical efficacy. Klebsiella pneumoniae is one of the most significant members of the genus Klebsiella in the Enterobacteriaceae family and also a common non-social pathogen. Meropenem is a broad-spectrum antibacterial agent of the carbapenem family, which can produce antibacterial effects of most Gram-positive and -negative bacteria. In this study, we used single-nucleotide polymorphism (SNP) information and nucleotide k-mers count based on metagenomic data to predict MICs of meropenem against K. pneumoniae. Then, features of 110 sequenced K. pneumoniae genome data were combined and modeled with XGBoost algorithm and deep neural network (DNN) algorithm to predict MICs. We first use the XGBoost classification model and the XGBoost regression model. After five runs, the average accuracy of the test set was calculated. The accuracy of using nucleotide k-mers to predict MICs of the XGBoost classification model and XGBoost regression model was 84.5 and 89.1%. The accuracy of SNP in predicting MIC was 80 and 81.8%, respectively. The results show that XGBoost regression is better than XGBoost classification in both nucleotide k-mers and SNPs to predict MICs. We further selected 40 nucleotide k-mers and 40 SNPs with the highest correlation with MIC values as features to retrain the XGBoost regression model and DNN regression model. After 100 and 1,000 runs, the results show that the accuracy of the two models was improved. The accuracy of the XGBoost regression model for k-mers, SNPs, and k-mers & SNPs was 91.1, 85.2, and 91.3%, respectively. The accuracy of the DNN regression model was 91.9, 87.1, and 91.8%, respectively. Through external verification, some of the selected features were found to be related to drug resistance.

Streptococcus pneumoniae genomic datasets from an Indian population describing pre-vaccine evolutionary epidemiology using a whole genome sequencing approach

Globally, India has a high burden of pneumococcal disease, and pneumococcal conjugate vaccine (PCV) has been rolled out in different phases across the country since May 2017 in the national infant immunization programme (NIP). To provide a baseline for assessing the impact of the vaccine on circulating pneumococci in India, genetic characterization of pneumococcal isolates detected prior to introduction of PCV would be helpful. Here we present a population genomic study of 480 Streptococcus pneumoniae isolates collected across India and from all age groups before vaccine introduction (2009–2017), including 294 isolates from pneumococcal disease and 186 collected through nasopharyngeal surveys. Population genetic structure, serotype and antimicrobial susceptibility profile were characterized and predicted from whole-genome sequencing data. Our findings revealed high levels of genetic diversity represented by 110 Global Pneumococcal Sequence Clusters (GPSCs) and 54 serotypes. Serotype 19F and GPSC1 (CC320) was the most common serotype and pneumococcal lineage, respectively. Coverage of PCV13 (Pfizer) and 10-valent Pneumosil (Serum Institute of India) serotypes in age groups of ≤2 and 3–5 years were 63–75 % and 60–69 %, respectively. Coverage of PPV23 (Merck) serotypes in age groups of ≥50 years was 62 % (98/158). Among the top five lineages causing disease, GPSC10 (CC230), which ranked second, is the only lineage that expressed both PCV13 (serotypes 3, 6A, 14, 19A and 19F) and non-PCV13 (7B, 13, 10A, 11A, 13, 15B/C, 22F, 24F) serotypes. It exhibited multidrug resistance and was the largest contributor (17 %, 18/103) of NVTs in the disease-causing population. Overall, 42 % (202/480) of isolates were penicillin-resistant (minimum inhibitory concentration ≥0.12 µg ml⁻¹) and 45 % (217/480) were multidrug-resistant. Nine GPSCs (GPSC1, 6, 9, 10, 13, 16, 43, 91, 376) were penicillin-resistant and among them six were multidrug-resistant. Pneumococci expressing PCV13 serotypes had a higher prevalence of antibiotic resistance. Sequencing of pneumococcal genomes has significantly improved our understanding of the biology of these bacteria. This study, describing the pneumococcal disease and carriage epidemiology pre-PCV introduction, demonstrates that 60–75 % of pneumococcal serotypes in children ≤5 years are covered by PCV13 and Pneumosil. Vaccination against pneumococci is very likely to reduce antibiotic resistance. A multidrug-resistant pneumococcal lineage, GPSC10 (CC230), is a high-risk clone that could mediate serotype replacement.

Large-scale genomic analysis of antimicrobial resistance in the zoonotic pathogen Streptococcus suis

BACKGROUND

Antimicrobial resistance (AMR) is among the gravest threats to human health and food security worldwide. The use of antimicrobials in livestock production can lead to emergence of AMR, which can have direct effects on humans through spread of zoonotic disease. Pigs pose a particular risk as they are a source of zoonotic diseases and receive more antimicrobials than most other livestock. Here we use a large-scale genomic approach to characterise AMR in Streptococcus suis, a commensal found in most pigs, but which can also cause serious disease in both pigs and humans.

RESULTS

We obtained replicated measures of Minimum Inhibitory Concentration (MIC) for 16 antibiotics, across a panel of 678 isolates, from the major pig-producing regions of the world. For several drugs, there was no natural separation into 'resistant' and 'susceptible', highlighting the need to treat MIC as a quantitative trait. We found differences in MICs between countries, consistent with their patterns of antimicrobial usage. AMR levels were high even for drugs not used to treat S. suis, with many multidrug-resistant isolates. Similar levels of resistance were found in pigs and humans from regions associated with zoonotic transmission. We next used whole genome sequences for each isolate to identify 43 candidate resistance determinants, 22 of which were novel in S. suis. The presence of these determinants explained most of the variation in MIC. But there were also interesting complications, including epistatic interactions, where known resistance alleles had no effect in some genetic backgrounds. Beta-lactam resistance involved many core genome variants of small effect, appearing in a characteristic order.

CONCLUSIONS

We present a large dataset allowing the analysis of the multiple contributing factors to AMR in S. suis. The high levels of AMR in S. suis that we observe are reflected by antibiotic usage patterns but our results confirm the potential for genomic data to aid in the fight against AMR.

Phylogeography and resistome of pneumococcal meningitis in West Africa before and after vaccine introduction

Despite contributing to the large disease burden in West Africa, little is known about the genomic epidemiology of Streptococcus pneumoniae which cause meningitis among children under 5 years old in the region. We analysed whole-genome sequencing data from 185 S. pneumoniae isolates recovered from suspected paediatric meningitis cases as part of the World Health Organization (WHO) invasive bacterial diseases surveillance from 2010 to 2016. The phylogeny was reconstructed, accessory genome similarity was computed and antimicrobial-resistance patterns were inferred from the genome data and compared to phenotypic resistance from disc diffusion. We studied the changes in the distribution of serotypes pre- and post-pneumococcal conjugate vaccine (PCV) introduction in the Central and Western sub-regions separately. The overall distribution of non-vaccine, PCV7 (4, 6B, 9V, 14, 18C, 19F and 23F) and additional PCV13 serotypes (1, 3, 5, 6A, 19A and 7F) did not change significantly before and after PCV introduction in the Central region (Fisher's test P value 0.27) despite an increase in the proportion of non-vaccine serotypes to 40 % (n=6) in the post-PCV introduction period compared to 21.9 % (n=14). In the Western sub-region, PCV13 serotypes were more dominant among isolates from The Gambia following the introduction of PCV7, 81 % (n=17), compared to the pre-PCV period in neighbouring Senegal, 51 % (n=27). The phylogeny illustrated the diversity of strains associated with paediatric meningitis in West Africa and highlighted the existence of phylogeographical clustering, with isolates from the same sub-region clustering and sharing similar accessory genome content. Antibiotic-resistance genotypes known to confer resistance to penicillin, chloramphenicol, co-trimoxazole and tetracycline were detected across all sub-regions. However, there was no discernible trend linking the presence of resistance genotypes with the vaccine introduction period or whether the strain was a vaccine or non-vaccine serotype. Resistance genotypes appeared to be conserved within selected sub-clades of the phylogenetic tree, suggesting clonal inheritance. Our data underscore the need for continued surveillance on the emergence of non-vaccine serotypes as well as chloramphenicol and penicillin resistance, as these antibiotics are likely still being used for empirical treatment in low-resource settings. This article contains data hosted by Microreact.

Using genomics to examine the persistence of Streptococcus pneumoniae serotype 19A in Ireland and the emergence of a sub-clade associated with vaccine failures

BACKGROUND

Streptococcus pneumoniae serotype 19A remains a significant cause of invasive pneumococcal disease (IPD) in Ireland despite the successful introduction of a 13-valent pneumococcal conjugate vaccine (PCV13) in 2010 which reduced the overall incidence of IPD in children.

METHODS

Invasive Streptococcus pneumoniae serotype 19A isolates from the Irish reference laboratory between 2007-08 and 2017-18 were analysed using whole genome sequencing (WGS) to investigate the persistence of this vaccine-preventable serotype. We compared the entire national 19A collection to other international collections using a standardised nomenclature of Global Pneumococcal Sequencing Clusters (GPSC).

RESULTS

Expansion of GPSCs and clonal complexes (CCs) may have been associated with vaccine introduction and antimicrobial prescribing policies. A sub-clade of GPSC1-CC320 (n = 25) unique to Ireland, included five of the ten vaccine failures/breakthrough cases identified (p = 0.0086). This sub-clade was not observed in a global GPSC1-CC320 collection. All isolates within the sub-clade (n = 25) contained a galE gene variant rarely observed in a global pneumococcal collection (n = 37/13454, p < 0.001) nor within GPSC1-CC320 (n = 19/227) (p < 0.001). The sub-clade was estimated to have emerged at the start of the PCV-vaccine era (ancestral origin 2000, range 1995-2004) and expanded in Ireland, with most isolated after PCV13 introduction (n = 24/25).

CONCLUSIONS

The identification of a sub-clade/variant of serotype 19A highlights the benefit of using WGS to analyse genotypes associated with persistence of a preventable serotype of S. pneumoniae. Particularly as this sub-clade identified was more likely to be associated with IPD in vaccinated children than other 19A genotypes. It is possible that changes to the galE gene, which is involved in capsule production but outside of the capsular polysaccharide biosynthesis locus, may affect bacterial persistence within the population. Discrete changes associated with vaccine-serotype persistence should be further investigated and may inform vaccine strategies.

The role of interspecies recombination in the evolution of antibiotic-resistant pneumococci

Multidrug-resistant Streptococcus pneumoniae emerge through the modification of core genome loci by interspecies homologous recombinations, and acquisition of gene cassettes. Both occurred in the otherwise contrasting histories of the antibiotic-resistant S. pneumoniae lineages PMEN3 and PMEN9. A single PMEN3 clade spread globally, evading vaccine-induced immunity through frequent serotype switching, whereas locally circulating PMEN9 clades independently gained resistance. Both lineages repeatedly integrated Tn916-type and Tn1207.1-type elements, conferring tetracycline and macrolide resistance, respectively, through homologous recombination importing sequences originating in other species. A species-wide dataset found over 100 instances of such interspecific acquisitions of resistance cassettes and flanking homologous arms. Phylodynamic analysis of the most commonly sampled Tn1207.1-type insertion in PMEN9, originating from a commensal and disrupting a competence gene, suggested its expansion across Germany was driven by a high ratio of macrolide-to-β-lactam consumption. Hence, selection from antibiotic consumption was sufficient for these atypically large recombinations to overcome species boundaries across the pneumococcal chromosome.

Invasive Pneumococcal Strain Distributions and Isolate Clusters Associated With Persons Experiencing Homelessness During 2018

BACKGROUND

We aimed to characterize invasive pneumococcal disease (IPD) isolates collected from multistate surveillance in the United States during 2018 and examine within-serotype propensities of isolates to form related clusters.

METHODS

We predicted strain features using whole genome sequencing obtained from 2885 IPD isolates obtained through the Center for Disease Control and Prevention's Active Bacterial Core surveillance (ABCs), which has a surveillance population of approximately 34.5 million individuals distributed among 10 states. Phylogenetic analysis was provided for serotypes accounting for ≥27 isolates.

RESULTS

Thirteen-valent pneumococcal conjugate vaccine (PCV13) serotypes together with 6C accounted for 23 of 105 (21.9%) of isolates from children aged <5 years and 820 of 2780 (29.5%) isolates from those aged ≥5 years. The most common serotypes from adult IPD isolates were serotypes 3 (413/2780 [14.9%]), 22F (291/2780 [10.5%]), and 9N (191/2780 [6.9%]). Among child IPD isolates, serotypes 15BC (18/105 [17.1%]), 3 (11/105 [10.5%]), and 33F (10/105 [9.5%]) were most common. Serotypes 4, 12F, 20, and 7F had the highest proportions of isolates that formed related clusters together with the highest proportions of isolates from persons experiencing homelessness (PEH). Among 84 isolates from long-term care facilities, 2 instances of highly related isolate pairs from co-residents were identified.

CONCLUSIONS

Non-PCV13 serotypes accounted for >70% of IPD in ABCs; however, PCV13 serotype 3 is the most common IPD serotype overall. Serotypes most common among PEH were more often associated with temporally related clusters identified both among PEH and among persons not reportedly experiencing homelessness.

A mosaic tetracycline resistance gene tet(S/M) detected in an MDR pneumococcal CC230 lineage that underwent capsular switching in South Africa

OBJECTIVES

We reported tet(S/M) in Streptococcus pneumoniae and investigated its temporal spread in relation to nationwide clinical interventions.

METHODS

We whole-genome sequenced 12 254 pneumococcal isolates from 29 countries on an Illumina HiSeq sequencer. Serotype, multilocus ST and antibiotic resistance were inferred from genomes. An SNP tree was built using Gubbins. Temporal spread was reconstructed using a birth-death model.

RESULTS

We identified tet(S/M) in 131 pneumococcal isolates and none carried other known tet genes. Tetracycline susceptibility testing results were available for 121 tet(S/M)-positive isolates and all were resistant. A majority (74%) of tet(S/M)-positive isolates were from South Africa and caused invasive diseases among young children (59% HIV positive, where HIV status was available). All but two tet(S/M)-positive isolates belonged to clonal complex (CC) 230. A global phylogeny of CC230 (n=389) revealed that tet(S/M)-positive isolates formed a sublineage predicted to exhibit resistance to penicillin, co-trimoxazole, erythromycin and tetracycline. The birth-death model detected an unrecognized outbreak of this sublineage in South Africa between 2000 and 2004 with expected secondary infections (effective reproductive number, R) of ∼2.5. R declined to ∼1.0 in 2005 and <1.0 in 2012. The declining epidemic could be related to improved access to ART in 2004 and introduction of pneumococcal conjugate vaccine (PCV) in 2009. Capsular switching from vaccine serotype 14 to non-vaccine serotype 23A was observed within the sublineage.

CONCLUSIONS

The prevalence of tet(S/M) in pneumococci was low and its dissemination was due to an unrecognized outbreak of CC230 in South Africa. Capsular switching in this MDR sublineage highlighted its potential to continue to cause disease in the post-PCV13 era.

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.

Two multi-fragment recombination events resulted in the β-lactam-resistant serotype 11A-ST6521 related to Spain9V-ST156 pneumococcal clone spreading in south-western Europe, 2008 to 2016

BackgroundThe successful pneumococcal clone Spain9V-ST156 (PMEN3) is usually associated with vaccine serotypes 9V and 14.AimOur objective was to analyse the increase of a serotype 11A variant of PMEN3 as cause of invasive pneumococcal disease (IPD) in Spain and its spread in south-western Europe.MethodsWe conducted a prospective multicentre study of adult IPD in Spain (2008-16). Furthermore, a subset of 61 penicillin-resistant serotype 11A isolates from France, Italy, Portugal and Spain were subjected to whole genome sequencing (WGS) and compared with 238 genomes from the European Nucleotide Archive (ENA).ResultsAlthough the incidence of serotype 11A in IPD was stable, a clonal shift was detected from CC62 (penicillin-susceptible) to CC156 (penicillin-resistant). By WGS, three major 11A-CC156 lineages were identified, linked to ST156 (n = 5 isolates; France, Italy and Portugal), ST166 (n = 4 isolates; France and Portugal) and ST838/6521 (n = 52 isolates; France, Portugal and Spain). Acquisition of the 11A capsule allowed to escape vaccine effect. AP200 (11A-ST62) was the donor for ST156 and ST838/6521 but not for ST166. In-depth analysis of ST838/6521 lineage showed two multi-fragment recombination events including four and seven fragments from an 11A-ST62 and an NT-ST344 representative, respectively.ConclusionThe increase in penicillin-resistant serotype 11A IPD in Spain was linked to the spread of a vaccine escape PMEN3 recombinant clone. Several recombination events were observed in PMEN3 acquiring an 11A capsule. The most successful 11A-PMEN3 lineage spreading in south-western Europe appeared after two multi-fragment recombination events with representatives of two major pneumococcal clones (11A-ST62 and NT-ST344).

Pneumococcal carriage among children aged 4 - 12 years in Angola 4 years after the introduction of a pneumococcal conjugate vaccine

Children in Angola are affected by a high burden of disease caused by pneumococcal infections. The 13-valent pneumococcal conjugate vaccine (PCV13) was introduced in the childhood immunization programme in 2013 but the serotype distribution of Streptococcus pneumoniae and antimicrobial susceptibility patterns are unknown. We did a cross-sectional nasopharyngeal carriage study in Luanda and Saurimo, Angola (PCV13 3rd dose coverage 67% and 84%, respectively) during November to December 2017 comprising 940 children aged 4-12 years. The main objective was to assess vaccine serotype coverage and antimicrobial susceptibility rates for S. pneumoniae. Our secondary aim was to characterize colonizinig strains of Haemophilus influenzae and Moraxella catarrhalis. Pneumococcal colonization was found in 35% (95% CI 32-39%) of children (n = 332), with 41% of serotypes covered by PCV13. The most common serotypes were 3 (8%), 18C (6%), 23F (6%), 11A (6%), 34 (6%), 19F (5%) and 16 (5%). Carriage of H. influenzae and M. catarrhalis was detected in 13% (95% CI 11-15%) and 15% (95% CI 13-17%) of children, respectively. Non-susceptibility to penicillin was common among pneumococci (40%), particularly among PCV13-included serotypes (50% vs. 33%; p = 0.003), although the median minimal inhibitory concentration was low (0.19 µg/mL, IQR 0.13-0.25 µg/mL). Most pneumococci and H. influenzae were susceptible to amoxicillin (99% and 88%, respectively). Furthermore, resistance to trimethoprim-sulfamethoxazole was>70% among all three species. Multidrug-resistant pneumococci (non-susceptible to ≥ 3 antibiotics; 7% [n = 24]) were further studied with whole genome sequencing to investigate clonality as an underlying cause for this phenotype. No clearly dominating clone(s) were, however, detected. The results indicate that continued use of PCV13 may have positive direct and herd effects on pneumococcal infections in Angola as carriage of vaccine serotypes was common in the non-vaccinated age group. Finally, amoxicillin is assessed to be a feasible empirical treatment of respiratory tract infections in Angola.

Amino Acid k-mer Feature Extraction for Quantitative Antimicrobial Resistance (AMR) Prediction by Machine Learning and Model Interpretation for Biological Insights

Machine learning algorithms can learn mechanisms of antimicrobial resistance from the data of DNA sequence without any a priori information. Interpreting a trained machine learning algorithm can be exploited for validating the model and obtaining new information about resistance mechanisms. Different feature extraction methods, such as SNP calling and counting nucleotide k-mers have been proposed for presenting DNA sequences to the model. However, there are trade-offs between interpretability, computational complexity and accuracy for different feature extraction methods. In this study, we have proposed a new feature extraction method, counting amino acid k-mers or oligopeptides, which provides easier model interpretation compared to counting nucleotide k-mers and reaches the same or even better accuracy in comparison with different methods. Additionally, we have trained machine learning algorithms using different feature extraction methods and compared the results in terms of accuracy, model interpretability and computational complexity. We have built a new feature selection pipeline for extraction of important features so that new AMR determinants can be discovered by analyzing these features. This pipeline allows the construction of models that only use a small number of features and can predict resistance accurately.

Upsurge of Conjugate Vaccine Serotype 4 Invasive Pneumococcal Disease Clusters Among Adults Experiencing Homelessness in California, Colorado, and New Mexico

After 7-valent pneumococcal conjugate vaccine introduction in the United States in 2000, invasive pneumococcal disease (IPD) due to serotype 4 greatly decreased in children and adults. Starting in 2013, serotype 4 IPD incidence increased among adults within 3 of 10 Active Bacterial Core surveillance sites. Of 325 serotype 4 cases among adults in 2010-2018, 36% were persons experiencing homelessness (PEH); incidence of serotype 4 IPD among PEH was 100-300 times higher than in the general population within these 3 areas. Genome sequencing for isolates recovered 2015-2018 (n = 246), revealed that increases in serotype 4 IPD were driven by lineages ST10172, ST244, and ST695. Within each lineage, clusters of near-identical isolates indicated close temporal relatedness. Increases in serotype 4 IPD were limited to Colorado, California, and New Mexico, with highest increases among PEH, who were at increased risk for exposure to and infections caused by these strains.

Systematic analysis of supervised machine learning as an effective approach to predicate β-lactam resistance phenotype in Streptococcus pneumoniae

Streptococcus pneumoniae is the most common human respiratory pathogen, and β-lactam antibiotics have been employed to treat infections caused by S. pneumoniae for decades. β-lactam resistance is steadily increasing in pneumococci and is mainly associated with the alteration in penicillin-binding proteins (PBPs) that reduce binding affinity of antibiotics to PBPs. However, the high variability of PBPs in clinical isolates and their mosaic gene structure hamper the predication of resistance level according to the PBP gene sequences. In this study, we developed a systematic strategy for applying supervised machine learning to predict S. pneumoniae antimicrobial susceptibility to β-lactam antibiotics. We combined published PBP sequences with minimum inhibitory concentration (MIC) values as labelled data and the sequences from NCBI database without MIC values as unlabelled data to develop an approach, using only a fragment from pbp2x (750 bp) and a fragment from pbp2b (750 bp) to predicate the cefuroxime and amoxicillin resistance. We further validated the performance of the supervised learning model by constructing mutants containing the randomly selected pbps and testing more clinical strains isolated from Chinese hospital. In addition, we established the association between resistance phenotypes and serotypes and sequence type of S. pneumoniae using our approach, which facilitate the understanding of the worldwide epidemiology of S. pneumonia.

Molecular Diagnostics in Pulmonary Infections

Infection of the lung parenchyma, or pneumonia, accounts for over four million deaths per year worldwide (Ferkol and Schraufnagel, Ann Am Thorac Soc 11:404–406, 2014). The condition is common, but also over-diagnosed, in part due to relatively poor laboratory and radiographic diagnostics. Indeed, we continue to rely on antiquated tools such as sputum culture and chest X-ray – the former of which lacks speed and sensitivity, and the latter specificity (Albaum et al. Chest 110:343–50, 1996). The resulting presumptive diagnoses of pneumonia lead to excessive use of empiric broad spectrum antibiotics; indeed, by some estimates, 30–70% of antibiotic prescriptions for lower respiratory tract infection are inappropriate (Kraus, PLoS One 12(3): e0174584, 2017). This approach begets microbial resistance, exposes patients to medication side effects, and puts patients at risk of potentially life-threatening complications including Clostridium difficile colitis.

To improve diagnostic certainty in patients with suspected pneumonia, we must begin to consider and implement emerging technologies for efficient and accurate characterization of host responses to infection and identification of pathogens. In this chapter, we will discuss precision diagnostics already in common practice and those poised to be, and how these tools may ultimately enable personalization in the diagnosis of pneumonia.

Genomic epidemiology of penicillin-non-susceptible Streptococcus pneumoniae

Penicillin-non-susceptible Streptococcus pneumoniae (PNSP) were first detected in the 1960s, and are now common worldwide, predominantly through the international spread of a limited number of strains. Extant PNSP are characterized by mosaic pbp2x, pbp2b and pbp1a genes generated by interspecies recombinations, with the extent of these alterations determining the range and concentrations of β-lactams to which the genotype is non-susceptible. The complexity of the genetics underlying these phenotypes has been the subject of both molecular microbiology and genome-wide association and epistasis analyses. Such studies can aid our understanding of PNSP evolution and help improve the already highly-performing bioinformatic methods capable of identifying PNSP from genomic surveillance data.

Multistate population and whole genome sequence-based strain surveillance of invasive pneumococci recovered in the USA during 2017

OBJECTIVES

We aimed to provide population-based and whole-genome sequence (WGS) -based characterization of invasive pneumococcal disease isolates collected from multistate surveillance in the USA during 2017.

METHODS

We obtained short-read WGS from 2881 isolates with associated bioinformatics pipeline strain feature predictions. For quality control, capsular serotypes and antimicrobial MICs were also obtained conventionally from 442 isolates. Annotated WGS were provided (inclusive of serotypes, MICs, multilocus sequence types, pilus type(s)) from 2723 isolates. For 158 isolates with suboptimal WGS, antimicrobial MICs were obtained conventionally.

RESULTS

There were 127 isolates from children <5 years of age and 2754 isolates from those ≥5 years old in 2017. One of 43 different serotypes was predicted for 2877 of the 2881 isolates. Serotypes in the 13-valent conjugate vaccine together with 6C (PCV13+6C) accounted for 816 (28.3%) isolates, with PCV13 serotype 3 being the most common serotype overall. Non-PCV13-6C- serotypes accounted for 2065 (71.7%) isolates, comprising 96 (75.6%) isolates from children < 5 years old and 1969 (61.4%) isolates from those aged ≥5 years. Of 36 different categories of recently emerged serotype-switch variants, three showed marked increases relative to 2015-2016 in that the number from 2017 surpassed the number from 2015-2016 combined. Two of these included antimicrobial-resistant serotype 11A and 35B serotype-switch variants of the ST156 clonal complex.

CONCLUSIONS

PCV13+6C strains are still identified in 2017 but non-PCV13-type strains impose a considerable burden. This well-annotated year 2017 WGS/strain data set will prove useful for a broad variety of analyses and improved our understanding of invasive pneumococcal disease-causing strains in the post-PCV13 era.

Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics.

Pneumococcal lineages associated with serotype replacement and antibiotic resistance in childhood invasive pneumococcal disease in the post-PCV13 era: an international whole-genome sequencing study

BACKGROUND

Invasive pneumococcal disease remains an important health priority owing to increasing disease incidence caused by pneumococci expressing non-vaccine serotypes. We previously defined 621 Global Pneumococcal Sequence Clusters (GPSCs) by analysing 20 027 pneumococcal isolates collected worldwide and from previously published genomic data. In this study, we aimed to investigate the pneumococcal lineages behind the predominant serotypes, the mechanism of serotype replacement in disease, as well as the major pneumococcal lineages contributing to invasive pneumococcal disease in the post-vaccine era and their antibiotic resistant traits.

METHODS

We whole-genome sequenced 3233 invasive pneumococcal disease isolates from laboratory-based surveillance programmes in Hong Kong (n=78), Israel (n=701), Malawi (n=226), South Africa (n=1351), The Gambia (n=203), and the USA (n=674). The genomes represented pneumococci from before and after pneumococcal conjugate vaccine (PCV) introductions and were from children younger than 3 years. We identified predominant serotypes by prevalence and their major contributing lineages in each country, and assessed any serotype replacement by comparing the incidence rate between the pre-PCV and PCV periods for Israel, South Africa, and the USA. We defined the status of a lineage as vaccine-type GPSC (≥50% 13-valent PCV [PCV13] serotypes) or non-vaccine-type GPSC (>50% non-PCV13 serotypes) on the basis of its initial serotype composition detected in the earliest vaccine period to measure their individual contribution toward serotype replacement in each country. Major pneumococcal lineages in the PCV period were identified by pooled incidence rate using a random effects model.

FINDINGS

The five most prevalent serotypes in the PCV13 period varied between countries, with only serotypes 5, 12F, 15B/C, 19A, 33F, and 35B/D common to two or more countries. The five most prevalent serotypes in the PCV13 period varied between countries, with only serotypes 5, 12F, 15B/C, 19A, 33F, and 35B/D common to two or more countries. These serotypes were associated with more than one lineage, except for serotype 5 (GPSC8). Serotype replacement was mainly mediated by expansion of non-vaccine serotypes within vaccine-type GPSCs and, to a lesser extent, by increases in non-vaccine-type GPSCs. A globally spreading lineage, GPSC3, expressing invasive serotypes 8 in South Africa and 33F in the USA and Israel, was the most common lineage causing non-vaccine serotype invasive pneumococcal disease in the PCV13 period. We observed that same prevalent non-vaccine serotypes could be associated with distinctive lineages in different countries, which exhibited dissimilar antibiotic resistance profiles. In non-vaccine serotype isolates, we detected significant increases in the prevalence of resistance to penicillin (52 [21%] of 249 vs 169 [29%] of 575, p=0·0016) and erythromycin (three [1%] of 249 vs 65 [11%] of 575, p=0·0031) in the PCV13 period compared with the pre-PCV period.

INTERPRETATION

Globally spreading lineages expressing invasive serotypes have an important role in serotype replacement, and emerging non-vaccine serotypes associated with different pneumococcal lineages in different countries might be explained by local antibiotic-selective pressures. Continued genomic surveillance of the dynamics of the pneumococcal population with increased geographical representation in the post-vaccine period will generate further knowledge for optimising future vaccine design.

FUNDING

Bill & Melinda Gates Foundation, Wellcome Sanger Institute, and the US Centers for Disease Control.

Personalizing the Management of Pneumonia

Pneumonia is a highly prevalent disease with considerable morbidity and mortality. However, diagnosis and therapy still rely on antiquated methods, leading to the vast overuse of antimicrobials, which carries risks for both society and the individual. Furthermore, outcomes in severe pneumonia remain poor. Genomic techniques have the potential to transform the management of pneumonia through deep characterization of pathogens as well as the host response to infection. This characterization will enable the delivery of selective antimicrobials and immunomodulatory therapy that will help to offset the disorder associated with overexuberant immune responses.

International genomic definition of pneumococcal lineages, to contextualise disease, antibiotic resistance and vaccine impact

BACKGROUND

Pneumococcal conjugate vaccines have reduced the incidence of invasive pneumococcal disease, caused by vaccine serotypes, but non-vaccine-serotypes remain a concern. We used whole genome sequencing to study pneumococcal serotype, antibiotic resistance and invasiveness, in the context of genetic background.

METHODS

Our dataset of 13,454 genomes, combined with four published genomic datasets, represented Africa (40%), Asia (25%), Europe (19%), North America (12%), and South America (5%). These 20,027 pneumococcal genomes were clustered into lineages using PopPUNK, and named Global Pneumococcal Sequence Clusters (GPSCs). From our dataset, we additionally derived serotype and sequence type, and predicted antibiotic sensitivity. We then measured invasiveness using odds ratios that relating prevalence in invasive pneumococcal disease to carriage.

FINDINGS

The combined collections (n = 20,027) were clustered into 621 GPSCs. Thirty-five GPSCs observed in our dataset were represented by >100 isolates, and subsequently classed as dominant-GPSCs. In 22/35 (63%) of dominant-GPSCs both non-vaccine serotypes and vaccine serotypes were observed in the years up until, and including, the first year of pneumococcal conjugate vaccine introduction. Penicillin and multidrug resistance were higher (p < .05) in a subset dominant-GPSCs (14/35, 9/35 respectively), and resistance to an increasing number of antibiotic classes was associated with increased recombination (R2 = 0.27 p < .0001). In 28/35 dominant-GPSCs, the country of isolation was a significant predictor (p < .05) of its antibiogram (mean misclassification error 0.28, SD ± 0.13). We detected increased invasiveness of six genetic backgrounds, when compared to other genetic backgrounds expressing the same serotype. Up to 1.6-fold changes in invasiveness odds ratio were observed.

INTERPRETATION

We define GPSCs that can be assigned to any pneumococcal genomic dataset, to aid international comparisons. Existing non-vaccine-serotypes in most GPSCs preclude the removal of these lineages by pneumococcal conjugate vaccines; leaving potential for serotype replacement. A subset of GPSCs have increased resistance, and/or serotype-independent invasiveness.

Genome-Based Prediction of Bacterial Antibiotic Resistance

Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences.

Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences. We examine differences between calling antibiotic resistance profiles by the simple presence or absence of previously known genes and single-nucleotide polymorphisms (SNPs) against approaches that deploy machine learning and statistical models. Often, the limitations to genome-based prediction arise from limitations of accuracy of culture-based AST in addition to an incomplete knowledge of the genetic basis of resistance. However, we need to maintain phenotypic testing even as genome-based prediction becomes more widespread to ensure that the results do not diverge over time. We argue that standardization of WGS-AST by challenge with consistently phenotyped strain sets of defined genetic diversity is necessary to compare the efficacy of methods of prediction of antibiotic resistance based on genome sequences.

Streptococcus infantis, Streptococcus mitis, and Streptococcus oralis Strains With Highly Similar cps5 Loci and Antigenic Relatedness to Serotype 5 Pneumococci

Streptococcus pneumoniae is a highly impactful bacterial pathogen on a global scale. The principal pneumococcal virulence factor and target of effective vaccines is its polysaccharide capsule, of which there are many structurally distinct forms. Here, we describe four distinct strains of three Mitis group commensal species (Streptococcus infantis, Streptococcus mitis, and Streptococcus oralis) recovered from upper respiratory tract specimens from adults in Kenya and the United States that were PCR-positive for the pneumococcal serotype 5 specific gene, wzy5. For each of the four strains, the 15 genes comprising the capsular polysaccharide biosynthetic gene cluster (cps5) shared the same order found in serotype 5 pneumococci, and each of the serotype 5-specific genes from the serotype 5 pneumococcal reference strain shared 76-99% sequence identity with the non-pneumococcal counterparts. Double-diffusion experiments demonstrated specific reactivity of the non-pneumococcal strains with pneumococcal serotype 5 typing sera. Antiserum raised against S. mitis strain KE67013 specifically reacted with serotype 5 pneumococci for a positive Quellung reaction and stimulated serotype 5 specific opsonophagocytic killing of pneumococci. Four additional commensal strains, identified using PCR serotyping assays on pharyngeal specimens, revealed loci highly homologous to those of pneumococci of serotypes 12F, 15A, 18C, and 33F. These data, in particular the species and strain diversity shown for serotype 5, highlight the existence of a broad non-pneumococcal species reservoir in the upper respiratory tract for the expression of capsular polysaccharides that are structurally related or identical to those corresponding to epidemiologically significant serotypes. Very little is known about the genetic and antigenic capsular diversity among the vast array of commensal streptococcal strains that represent multiple diverse species. The discovery of serotype 5 strains within three different commensal species suggests that extensive capsular serologic overlap exists between pneumococci and other members of the diverse Mitis group. These findings may have implications for our current understanding of naturally acquired immunity to S. pneumoniae and pneumococcal serotype distributions in different global regions. Further characterization of commensal strains carrying homologs of serotype-specific genes previously thought to be specific for pneumococci of known serotypes may shed light on the evolution of these important loci.

From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Hospitals worldwide are facing an increasing incidence of hard-to-treat infections. Limiting infections and providing patients with optimal drug regimens require timely strain identification as well as virulence and drug-resistance profiling. Additionally, prophylactic interventions based on the identification of environmental sources of recurrent infections (e.g., contaminated sinks) and reconstruction of transmission chains (i.e., who infected whom) could help to reduce the incidence of nosocomial infections. WGS could hold the key to solving these issues. However, uptake in the clinic has been slow. Some major scientific and logistical challenges need to be solved before WGS fulfils its potential in clinical microbial diagnostics. In this review we identify major bottlenecks that need to be resolved for WGS to routinely inform clinical intervention and discuss possible solutions.

A Population-Based Descriptive Atlas of Invasive Pneumococcal Strains Recovered Within the U.S. During 2015-2016

Invasive pneumococcal disease (IPD) has greatly decreased since implementation in the U.S. of the 7 valent conjugate vaccine (PCV7) in 2000 and 13 valent conjugate vaccine (PCV13) in 2010. We used whole genome sequencing (WGS) to predict phenotypic traits (serotypes, antimicrobial phenotypes, and pilus determinants) and determine multilocus genotypes from 5334 isolates (~90% of cases) recovered during 2015–2016 through Active Bacterial Core surveillance. We identified 44 serotypes; 26 accounted for 98% of the isolates. PCV13 serotypes (inclusive of serotype 6C) accounted for 1503 (28.2%) isolates, with serotype 3 most common (657/5334, 12.3%), while serotypes 1 and 5 were undetected. Of 305 isolates from children <5 yrs, 60 (19.7%) were of PCV13 serotypes 19A, 19F, 3, 6B, and 23F (58/60 were 19A, 19F, or 3). We quantitated MLST-based lineages first detected during the post-PCV era (since 2002) that potentially arose through serotype-switching. The 7 predominant emergent post-PCV strain complexes included 23B/CC338, 15BC/CC3280, 19A/CC244, 4/CC439, 15A/CC156, 35B/CC156, and 15BC/CC156. These strains accounted for 332 isolates (6.2% of total) and were more frequently observed in children <5 yrs (17.7%; 54/305). Fifty-seven categories of recently emerged (in the post PCV7 period) putative serotype-switch variants were identified, accounting for 402 isolates. Many of these putative switch variants represented newly emerged resistant strains. Penicillin-nonsusceptibility (MICs > 0.12 μg/ml) was found among 22.4% (1193/5334) isolates, with higher penicillin MICs (2–8 μg/ml) found in 8.0% (425/5334) of isolates that were primarily (372/425, 87.5%) serotypes 35B and 19A. Most (792/1193, 66.4%) penicillin-nonsusceptible isolates were macrolide-resistant, 410 (34.4%) of which were erm gene positive and clindamycin-resistant. The proportion of macrolide-resistant isolates increased with increasing penicillin MICs; even isolates with reduced penicillin susceptibility (MIC = 0.06 μg/ml) were much more likely to be macrolide-resistant than basally penicillin-susceptible isolates (MIC < 0.03 μg/ml). The contribution of recombination to strain diversification was assessed through quantitating 35B/CC558-specific bioinformatic pipeline features among non-CC558 CCs and determining the sizes of gene replacements. Although IPD has decreased greatly and stabilized in the post-PCV13 era, the species continually generates recombinants that adapt to selective pressures exerted by vaccines and antimicrobials. These data serve as a baseline for monitoring future changes within each invasive serotype.

A k-mer-based method for the identification of phenotype-associated genomic biomarkers and predicting phenotypes of sequenced bacteria

We have developed an easy-to-use and memory-efficient method called PhenotypeSeeker that (a) identifies phenotype-specific k-mers, (b) generates a k-mer-based statistical model for predicting a given phenotype and (c) predicts the phenotype from the sequencing data of a given bacterial isolate. The method was validated on 167 Klebsiella pneumoniae isolates (virulence), 200 Pseudomonas aeruginosa isolates (ciprofloxacin resistance) and 459 Clostridium difficile isolates (azithromycin resistance). The phenotype prediction models trained from these datasets obtained the F1-measure of 0.88 on the K. pneumoniae test set, 0.88 on the P. aeruginosa test set and 0.97 on the C. difficile test set. The F1-measures were the same for assembled sequences and raw sequencing data; however, building the model from assembled genomes is significantly faster. On these datasets, the model building on a mid-range Linux server takes approximately 3 to 5 hours per phenotype if assembled genomes are used and 10 hours per phenotype if raw sequencing data are used. The phenotype prediction from assembled genomes takes less than one second per isolate. Thus, PhenotypeSeeker should be well-suited for predicting phenotypes from large sequencing datasets. PhenotypeSeeker is implemented in Python programming language, is open-source software and is available at GitHub (https://github.com/bioinfo-ut/PhenotypeSeeker/).

Global Distribution of Invasive Serotype 35D Streptococcus pneumoniae Isolates following Introduction of 13-Valent Pneumococcal Conjugate Vaccine

A newly recognized pneumococcal serotype, 35D, which differs from the 35B polysaccharide in structure and serology by not binding to factor serum 35a, was recently reported. The genetic basis for this distinctive serology is due to the presence of an inactivating mutation in wciG, which encodes an O-acetyltransferase responsible for O-acetylation of a galactofuranose. Here, we assessed the genomic data of a worldwide pneumococcal collection to identify serotype 35D isolates and understand their geographical distribution, genetic background, and invasiveness potential. Of 21,980 pneumococcal isolates, 444 were originally typed as serotype 35B by PneumoCaT. Analysis of the wciG gene revealed 23 isolates from carriage (n = 4) and disease (n = 19) with partial or complete loss-of-function mutations, including mutations resulting in premature stop codons (n = 22) and an in-frame mutation (n = 1). These were selected for further analysis. The putative 35D isolates were geographically widespread, and 65.2% (15/23) of them was recovered after the introduction of pneumococcal conjugate vaccine 13 (PCV13). Compared with serotype 35B isolates, putative serotype 35D isolates have higher invasive disease potentials based on odds ratios (OR) (11.58; 95% confidence interval[CI], 1.42 to 94.19 versus 0.61; 95% CI, 0.40 to 0.92) and a higher prevalence of macrolide resistance mediated by mefA (26.1% versus 7.6%; P = 0.009). Using the Quellung reaction, 50% (10/20) of viable isolates were identified as serotype 35D, 25% (5/20) as serotype 35B, and 25% (5/20) as a mixture of 35B/35D. The discrepancy between phenotype and genotype requires further investigation. These findings illustrated a global distribution of an invasive serotype, 35D, among young children post-PCV13 introduction and underlined the invasive potential conferred by the loss of O-acetylation in the pneumococcal capsule.