BACKGROUND: Clusters of invasive group A streptococcal (iGAS) infection, linked to genomically closely related group A streptococcal (GAS) isolates (referred to as genomic clusters), pose public health threats, and are increasingly identified through whole-genome sequencing (WGS) analysis. In this study, we aimed to assess the risk of genomic cluster formation among iGAS cases not already part of existing genomic clusters. METHODS: In this WGS and population-based surveillance study, we analysed iGAS case isolates from the Active Bacterial Core surveillance (ABCs), which is part of the US Centers for Disease Control and Prevention's Emerging Infections Program, in ten US states from Jan 1, 2015, to Dec 31, 2019. We included all residents in ABCs sites with iGAS infections meeting the case definition and excluded non-conforming GAS infections and cases with whole-genome assemblies of the isolate containing fewer than 1·5 million total bases or more than 150 contigs. For iGAS cases we collected basic demographics, underlying conditions, and risk factors for infection from medical records, and for isolates we included emm types, antimicrobial resistance, and presence of virulence-related genes. Two iGAS cases were defined as genomically clustered if their isolates differed by three or less single-nucleotide variants. An iGAS case not clustered with any previous cases at the time of detection, with a minimum trace-back time of 1 year, was defined as being at risk of cluster formation. We monitored each iGAS case at risk for a minimum of 1 year to identify any cluster formation event, defined as the detection of a subsequent iGAS case clustered with the case at risk. We used the Kaplan-Meier method to estimate the cumulative incidence of cluster formation events over time. We used Cox regression to assess associations between features of cases at risk upon detection and subsequent cluster formation. We developed a random survival forest machine-learning model based on a derivation cohort (random selection of 50% of cases at risk) to predict cluster formation risk. This model was validated using a validation cohort consisting of the remaining 50% of cases at risk. FINDINGS: We identified 2764 iGAS cases at risk from 2016 to 2018, of which 656 (24%) formed genomic clusters by the end of 2019. Overall, the cumulative incidence of cluster formation was 0·057 (95% CI 0·048-0·066) at 30 days after detection, 0·12 (0·11-0·13) at 90 days after detection, and 0·16 (0·15-0·18) at 180 days after detection. A higher risk of cluster formation was associated with emm type (adjusted hazard ratio as compared with emm89 was 2·37 [95% CI 1·71-3·30] for emm1, 2·72 [1·82-4·06] for emm3, 2·28 [1·49-3·51] for emm6, 1·47 [1·05-2·06] for emm12, and 2·21 [1·38-3·56] for emm92), homelessness (1·42 [1·01-1·99]), injection drug use (2·08 [1·59-2·72]), residence in a long-term care facility (1·78 [1·29-2·45]), and the autumn-winter season (1·34 [1·14-1·57]) in multivariable Cox regression analysis. The machine-learning model stratified the validation cohort (n=1382) into groups at low (n=370), moderate (n=738), and high (n=274) risk. The 90-day risk of cluster formation was 0·03 (95% CI 0·01-0·05) for the group at low risk, 0·10 (0·08-0·13) for the group at moderate risk, and 0·21 (0·17-0·25) for the group at high risk. These results were consistent with the cross-validation outcomes in the derivation cohort. INTERPRETATION: Using population-based surveillance data, we found that pathogen, host, and environment factors of iGAS cases were associated with increased likelihood of subsequent genomic cluster formation. Groups at high risk were consistently identified by a predictive model which could inform prevention strategies, although future work to refine the model, incorporating other potential risk factors such as host contact patterns and immunity to GAS, is needed to improve its predictive performance. FUNDING: Centers for Disease Control and Prevention.

Invasive pneumococcal disease (IPD) due to non-vaccine serotypes after the introduction of pneumococcal conjugate vaccines (PCV) remains a global concern. This study used pathogen genomics to evaluate changes in invasive pneumococcal lineages before, during and after vaccine introduction in South Africa. We included genomes (N = 3104) of IPD isolates from individuals aged <18 years (2005-20), spanning four periods: pre-PCV, PCV7, early-PCV13, and late-PCV13. Significant incidence reductions occurred among vaccine-type lineages in the late-PCV13 period compared to the pre-PCV period. However, some vaccine-type lineages continued to cause invasive disease and showed increasing effective population size trends in the post-PCV era. A significant increase in lineage diversity was observed from the PCV7 period to the early-PCV13 period (Simpson's diversity index: 0.954, 95% confidence interval 0.948-0.961 vs 0.965, 0.962-0.969) supporting intervention-driven population structure perturbation. Increases in the prevalence of penicillin, erythromycin, and multidrug resistance were observed among non-vaccine serotypes in the late-PCV13 period compared to the pre-PCV period. In this work we highlight the importance of continued genomic surveillance to monitor disease-causing lineages post vaccination to support policy-making and future vaccine designs and considerations.

Streptococcus pneumoniae is an opportunistic pathogen that, while usually carried asymptomatically, can cause severe invasive diseases like meningitis and bacteremic pneumonia. A central goal in S. pneumoniae public health management is to identify which serotypes (immunologically distinct strains) pose the most risk of invasive disease. The most common invasiveness metrics use cross-sectional data (i.e., invasive odds ratios (IOR)), or longitudinal data (i.e., attack rates (AR)). To assess the reliability of these metrics we developed an epidemiological model of carriage and invasive disease. Our mathematical analyses illustrate qualitative failures with the IOR metric (e.g., IOR can decline with increasing invasiveness parameters). Fitting the model to both longitudinal and cross-sectional data, our analysis supports previous work indicating that invasion risk is maximal at or near time of colonization. This pattern of early invasive disease risk leads to substantial (up to 5-fold) biases when estimating underlying differences in invasiveness from IOR metrics, due to the impact of carriage duration on IOR. Together, these results raise serious concerns with the IOR metric as a basis for public health decision-making and lend support for multiple alternate metrics including AR.

Group A streptococcal strains potentially acquire new M protein gene types through genetic recombination (emm switching). To detect such variants, we screened 12,596 invasive GAS genomes for strains of differing emm types that shared the same multilocus sequence type (ST). Through this screening we detected a variant consisting of 16 serum opacity factor (SOF)-positive, emm pattern E, emm82 isolates that were ST36, previously only associated with SOF-negative, emm pattern A, emm12. The 16 emm82/ST36 isolates were closely interrelated (pairwise SNP distance of 0-43), and shared the same emm82-containing recombinational fragment. emm82/ST36 isolates carried the sof12 structural gene, however the sof12 indel characteristic of emm12 strains was corrected to confer the SOF-positive phenotype. Five independent emm82/ST36 invasive case isolates comprised two sets of genetically indistinguishable strains. The emm82/ST36 isolates were primarily macrolide resistant (12/16 isolates), displayed at least 4 different core genomic arrangements, and carried 11 different combinations of virulence and resistance determinants. Phylogenetic analysis revealed that emm82/ST36 was within a minor (non-clade 1) portion of ST36 that featured almost all ST36 antibiotic resistance. This work documents emergence of a rapidly diversifying variant that is the first confirmed example of an emm pattern A strain switched to a pattern E strain.

From 2015-2018 to 2019‒2021, hypertoxigenic M1(UK) lineage among invasive group A Streptococcus increased in the United States (1.7%, 21/1,230 to 11%, 65/603; p<0.001). M1(UK) was observed in 9 of 10 states, concentrated in Georgia (n = 41), Tennessee (n = 13), and New York (n = 13). Genomic cluster analysis indicated recent expansions.

Objective We reported a novel tetracycline-resistant gene in Streptococcus pneumoniae and investigated its temporal spread in relation to nationwide clinical interventions.Methods We whole genome sequenced 12,254 pneumococcal isolates from twenty-nine countries on an Illumina HiSeq Sequencer. Serotypes, sequence types and antibiotic resistance were inferred from genomes. Phylogeny was built based on single-nucleotide variants. Temporal changes of spread were reconstructed using a birth-death model.Results We identified tet(S/M) in 131 pneumococcal isolates, 97 (74%) caused invasive pneumococcal diseases among young children (59% HIV-positive, where HIV status was available) in South Africa. A majority of tet(S/M)-positive isolates (129/131) belong to clonal complex (CC)230. A global phylogeny of CC230 (n=389) revealed that tet(S/M)-positive isolates formed a sub-lineage that exhibited multidrug-resistance. Using the genomic data and a birth-death model, we detected an unrecognised outbreak of this sub-lineage in South Africa between 2000 and 2004 with an expected secondary infections (R) of ~2.5. R declined to ~1.0 in 2005 and &lt;1.0 in 2012. The declining epidemic coincided and could be related to the nationwide implementation of anti-retroviral treatment (ART) for HIV-infected individuals in 2004 and PCVs in late 2000s. Capsular switching from vaccine serotype 14 to non-vaccine serotype 23A was observed within the sub-lineage.Conclusions The prevalence of tet(S/M) in pneumococci was low and its dissemination was due to an unrecognised outbreak of CC230 in South Africa prior to ART and PCVs. However, capsular switching in this multidrug-resistant sub-lineage highlighted its potential to continue to cause disease in the post-PCV13 era.

Streptococcus pneumoniae serotype 3 remains a significant cause of morbidity and mortality worldwide, despite inclusion in the 13-valent pneumococcal conjugate vaccine (PCV13). Serotype 3 increased in carriage since the implementation of PCV13 in the United States, while invasive disease rates remain unchanged. We investigated the persistence of serotype 3 in carriage and disease, through genomic analyses of a global sample of 301 serotype 3 isolates of the Netherlands3–31 (PMEN31) clone CC180, combined with associated patient data and PCV utilization among countries of isolate collection. We assessed phenotypic variation between dominant clades in capsule charge (zeta potential), capsular polysaccharide shedding, and susceptibility to opsonophagocytic killing, which have previously been associated with carriage duration, invasiveness, and vaccine escape. We identify a recent shift in the CC180 population attributed to a lineage termed Clade II, which was estimated by Bayesian coalescent analysis to have first appeared in 1968 [95% HPD: 1939–1989] and increased in prevalence and effective population size thereafter. Clade II isolates are divergent from the pre-PCV13 serotype 3 population in non-capsular antigenic composition, competence, and antibiotic susceptibility, the last resulting from the acquisition of a Tn916-like conjugative transposon. Differences in recombination rates among clades correlated with variations in the ATP-binding subunit of Clp protease as well as amino acid substitutions in the comCDE operon. Opsonophagocytic killing assays elucidated the low observed efficacy of PCV13 against serotype 3. Variation in PCV13 use among sampled countries was not independently correlated with the CC180 population shift; therefore, genotypic and phenotypic differences in protein antigens and, in particular, antibiotic resistance may have contributed to the increase of Clade II. Our analysis emphasizes the need for routine, representative sampling of isolates from disperse geographic regions, including historically under-sampled areas. We also highlight the value of genomics in resolving antigenic and epidemiological variations within a serotype, which may have implications for future vaccine development.Author Summary Streptococcus pneumoniae is a leading cause of bacterial pneumoniae, meningitis, and otitis media. Despite inclusion in the most recent pneumococcal conjugate vaccine, PCV13, serotype 3 remains epidemiologically important globally. We investigated the persistence of serotype 3 using whole-genome sequencing data form 301 isolates collected among 24 countries from 1993–2014. Through phylogenetic analysis, we identified three distinct lineages within a single clonal complex, CC180, and found one has recently emerged and grown in prevalence. We then compared genomic difference among lineages as well as variations in pneumococcal vaccine use among sampled countries. We found that the recently emerged lineage, termed Clade II, has a higher prevalence of antibiotic resistance compared to other lineages, diverse surface protein antigens, and a higher rate of recombination, a process by which bacteria can uptake and incorporate genetic material from its surroundings. Differences in vaccine use among sampled countries did not appear to be associated with the emergence of Clade II. We highlight the need to routine, representative sampling of bacterial isolates from diverse geographic areas and show the utility of genomic data in resolving epidemiological differences within a pathogen population.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. METHODS: We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study. RESULTS: The benchmark datasets focus on the two most widely used sequencing platforms: long read sequencing data from the Oxford Nanopore Technologies platform and short read sequencing data from the Illumina platform. There are six datasets: three were derived from recent publications; two were derived from data mining public databases to answer common questions not covered by published datasets; one unique dataset representing common sequence failures was obtained by rigorously scrutinizing data that did not pass quality checks. The dataset summary table, data mining script and quality control (QC) values for all sequence data are publicly available on GitHub: https://github.com/CDCgov/datasets-sars-cov-2. DISCUSSION: The datasets presented here were generated to help public health laboratories build sequencing and bioinformatics capacity, benchmark different workflows and pipelines, and calibrate QC thresholds to ensure sequencing quality. Together, improvements in these areas support accurate and timely outbreak investigation and surveillance, providing actionable data for pandemic management. Furthermore, these publicly available and standardized benchmark data will facilitate the development and adjudication of new pipelines.

We analyzed 9630 invasive Group A Streptococci (iGAS) surveillance isolates in the USA. From 2015-2017 to 2018-2019, significant increases in erythromycin-nonsusceptibility (18% vs. 25%) and clindamycin-nonsusceptibility (17% vs. 24%) occurred, driven mainly by rapid expansions of genomic subclones. Prevention and control of clustered infections appear key to containing antimicrobial resistance.

BACKGROUND: The genomic features and transmission link of circulating Group A streptococcus (GAS) strains causing different disease types, such as pharyngitis and invasive disease, are not well understood. METHODS: We used whole-genome sequencing (WGS) to characterize GAS isolates recovered from persons with pharyngitis and invasive disease in the Denver metropolitan area from June 2016 to April 2017. RESULTS: GAS isolates were cultured from 236 invasive and 417 pharyngitis infections. WGS identified 34 emm types. Compared to pharyngitis isolates, invasive isolates were more likely to carry the erm family genes (23% vs. 7.4%, p<0.001), which confer resistance to erythromycin and clindamycin (including inducible resistance), and covS gene inactivation (7% vs. 0.5%, p<0.001). WGS identified 97 genomic clusters (433 isolates; 2-65 isolates per cluster) that consisted of genomically closely related isolates (median SNP (IQR) = 3 (1-4) within cluster). Thirty genomic clusters (200 isolates; 31% of all isolates) contained both pharyngitis and invasive isolates and were found in 11 emm types. CONCLUSIONS: In the Denver metropolitan population, mixed disease types were commonly seen in clusters of closely related isolates, indicative of overlapping transmission networks. Antibiotic-resistance and covS inactivation was disproportionally associated with invasive disease.

BACKGROUND: Invasive group B Streptococcus (iGBS) isolates with mutations in the pbp2x gene that encodes penicillin binding protein 2x can have reduced beta-lactam susceptibility (RBLS) when susceptible by Clinical and Laboratory Standards Institute (CLSI) criteria. We assessed the emergence and characteristics of RBLS strains in US iGBS isolates. METHODS: We analyzed iGBS isolates from 8 multistate population-based surveillance sites from 1998 to 2018. During 1998-2014, phenotypic antimicrobial susceptibility was determined by broth microdilution; criteria for 6 antibiotics were used to identify RBLS, followed by whole-genome sequencing (WGS). WGS for all isolates was added in 2015; we used phenotypic and genotypic results of >2000 isolates to validate phenotypic RBLS criteria and genotypic predictions. Since 2016, WGS has been used to screen for RBLS with broth microdilution confirmation of predicted RBLS isolates. RESULTS: Of 28 269 iGBS isolates, 28 (0.1%) were nonsusceptible by CLSI criteria; 137 (0.5%) met RBLS criteria. RBLS isolates were detected in all Active Bacterial Core surveillance sites. The RBLS proportion increased, especially since 2013 (odds ratio, 1.17; 95% CI, 1.03-1.32); the proportion that were nonsusceptible remained stable. CONCLUSIONS: The RBSL proportion was low but increasing among US iGBS isolates. Ongoing monitoring is needed to detect emerging threats to prevention and treatment of GBS infections.

OBJECTIVES: We aimed to characterize invasive pneumococcal disease (IPD) isolates collected from multistate surveillance in the USA during 2018 and examine within-serotype propensities of isolates to form related clusters. METHODS: We predicted strain features using whole genome sequence obtained from 2885 IPD isolates obtained through the Center for Disease Control and Prevention's Active Bacterial Core surveillance (ABCs) that 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 conjugate vaccine (PCV13) serotypes together with 6C accounted for 23/105 (21.9%) of isolates from children aged <5 years and 820/2780 (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 children 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 highest proportions of isolates from persons experiencing homelessness (PEH). Among 84 isolates from long-term care facilities, two instances of highly related isolate pairs from co-residents were identified. CONCLUSIONS: Non-PCV13 serotypes accounted for more than 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.

After 7-valent pneumococcal conjugate vaccine introduction in the US 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 >18 years old within three of ten Active Bacterial Core surveillance sites. Of 325 serotype 4 cases among adults in 2010-2018, 36% were from 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 during 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 observed among PEH, who were at increased risk for exposure to and infections caused by these strains.

Background: Streptococcus pyogenes is a major cause of severe, invasive infections in humans. The bacterial pathogen harbors a wide array of virulence factors and exhibits high genomic diversity. Rapid changes of circulating strains in a community are common. Understanding the current prevalence and dynamics of S. pyogenes lineages could inform vaccine development and disease control strategies. Methods: We used whole-genome sequencing (WGS) to characterize all invasive S. pyogenes isolates obtained through the United States Center for Disease Control and Prevention’s Active Bacterial Core surveillance (ABCs) in 2016 and 2017. We determined the distribution of strain features, including emm type, antibiotic resistance determinants, and selected virulence factors. Changes in strain feature distribution between years 2016 and 2017 were evaluated. Phylogenetic analysis was used to identify expanding lineages within emm type. Results: Seventy-one emm types were identified from 3873 isolates characterized. The emm types targeted by a 30-valent M protein-based vaccine accounted for 3230 (89%) isolates. The relative frequencies of emm types collected during the 2 years were similar. While all isolates were penicillin-susceptible, erythromycin-resistant isolates increased from 273 (16% of 2016 isolates) to 432 (23% of 2017 isolates), mainly driven by increase of the erm-positive emm types 92 and 83. The prevalence of 24 virulence factors, including 11 streptococcal pyrogenic toxins, ranged from 6 to 90%. In each of three emm types (emm 49, 82, and 92), a subgroup of isolates significantly expanded between 2016 and 2017 compared to isolates outside of the subgroup (P-values < 0.0001). Specific genomic sequence changes were associated with these expanded lineages. Conclusions: While the overall population structure of invasive S. pyogenes isolates in the United States remained stable, some lineages, including several that were antibiotic-resistant, increased between 2016 and 2017. Continued genomic surveillance can help monitor and characterize bacterial features associated with emerging strains from invasive infections.

Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemination of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20 kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here.

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 approximately 2.5. R declined to approximately 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.

The term group A Streptococcus is considered synonymous for the species Streptococcus pyogenes. We describe an emergent invasive S. dysgalactiae subspecies equisimilis lineage that obtained the group A antigen through a single ancestral recombination event between a group C S. dysgalactiae subsp. equisimilis strain and a group A S. pyogenes strain.

Bacterial mutations predisposing pneumococcus to causing meningitis, a more severe form of invasive pneumococcal disease (IPD), are largely unknown. Knowledge of such mutations may improve our understanding of pathogenesis and inform preventive strategies. Here we report a pneumococcal pbp1b gene mutation (pbp1bA641C causing N214T change in PBP1b transglycosylase domain) that is associated with meningitis in an exploratory cohort of IPD patients (n = 2054, p = 6.8 x 10(-6)), in an independent confirmatory cohort (n = 2518, p = 2.3 x 10(-6)), and in a combined analysis (n = 4572, p = 3.0 x 10(-10)). Patients infected by the pbp1b641C genotype pneumococci show 2.8-fold odds (95% CI 1.7 to 4.8) of meningitis compared to those infected by non-pbp1b641C pneumococci, after controlling for pneumococcal serotype, antibiotic resistance, and patient age. The pbp1bA641C change results in longer time needed for bacterial killing by antibiotic treatment and shows evidence of being under positive selection. Thus, a pneumococcal mutation conferring increased antibiotic tolerance is associated with meningitis among IPD patients.

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 mug/ml) was found among 22.4% (1193/5334) isolates, with higher penicillin MICs (2-8 mug/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 mug/ml) were much more likely to be macrolide-resistant than basally penicillin-susceptible isolates (MIC < 0.03 mug/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.

Streptococcus pneumoniae serotype 3 remains a significant cause of morbidity and mortality worldwide, despite inclusion in the 13-valent pneumococcal conjugate vaccine (PCV13). Serotype 3 increased in carriage since the implementation of PCV13 in the USA, while invasive disease rates remain unchanged. We investigated the persistence of serotype 3 in carriage and disease, through genomic analyses of a global sample of 301 serotype 3 isolates of the Netherlands3-31 (PMEN31) clone CC180, combined with associated patient data and PCV utilization among countries of isolate collection. We assessed phenotypic variation between dominant clades in capsule charge (zeta potential), capsular polysaccharide shedding, and susceptibility to opsonophagocytic killing, which have previously been associated with carriage duration, invasiveness, and vaccine escape. We identified a recent shift in the CC180 population attributed to a lineage termed Clade II, which was estimated by Bayesian coalescent analysis to have first appeared in 1968 [95% HPD: 1939-1989] and increased in prevalence and effective population size thereafter. Clade II isolates are divergent from the pre-PCV13 serotype 3 population in non-capsular antigenic composition, competence, and antibiotic susceptibility, the last of which resulting from the acquisition of a Tn916-like conjugative transposon. Differences in recombination rates among clades correlated with variations in the ATP-binding subunit of Clp protease, as well as amino acid substitutions in the comCDE operon. Opsonophagocytic killing assays elucidated the low observed efficacy of PCV13 against serotype 3. Variation in PCV13 use among sampled countries was not independently correlated with the CC180 population shift; therefore, genotypic and phenotypic differences in protein antigens and, in particular, antibiotic resistance may have contributed to the increase of Clade II. Our analysis emphasizes the need for routine, representative sampling of isolates from disperse geographic regions, including historically under-sampled areas. We also highlight the value of genomics in resolving antigenic and epidemiological variations within a serotype, which may have implications for future vaccine development.

OBJECTIVES: Multiple invasive group A streptococcal (GAS) infections were reported to public health by a skilled nursing facility (Facility A) in Illinois between May 2014 and August 2016. Cases continued despite interventions including antibiotic prophylaxis for all residents and staff. Two other geographically close facilities reported contemporaneous outbreaks of GAS. We investigated potential reasons for ongoing transmission. METHODS: We obtained epidemiologic data from chart review of cases and review of facility and public health records from previous investigations into the outbreak. Infection control practices at Facility A were observed and evaluated. Whole genome sequencing (WGS) followed by phylogenetic analysis was performed on available isolates from the 3 facilities. RESULTS: From 2014-2016, 19 invasive and 60 non-invasive GAS infections were identified at Facility A occurring in 3 clusters. Infection control evaluations during clusters 2 and 3 identified hand hygiene compliance rates of 14-25%, appropriate PPE use in only 33% of observed instances, and deficient wound care practices. GAS isolates from residents and staff of all three facilities were subtype emm89.0; on phylogenetic analysis, Facility-A isolates were monophyletic and distinct. CONCLUSIONS: Inadequate infection control and improper wound care practices likely led to this 28-month long outbreak of severe infections in a skilled nursing facility. WGS and phylogenetic analysis suggested that intra-facility transmission of a single highly transmissible GAS strain was responsible for the outbreak in Facility A. Integration of genomic epidemiology tools with traditional epidemiology and infection control assessments was helpful in investigation of a facility-wide outbreak.

Group A streptococci (GAS) are genetically diverse. Determination of strain features can reveal associations with disease and resistance and assist in vaccine formulation. We employed whole-genome sequence (WGS)-based characterization of 1,454 invasive GAS isolates recovered in 2015 by Active Bacterial Core Surveillance and performed conventional antimicrobial susceptibility testing. Predictions were made for genotype, GAS carbohydrate, antimicrobial resistance, surface proteins (M family, fibronectin binding, T, R28), secreted virulence proteins (Sda1, Sic, exotoxins), hyaluronate capsule, and an upregulated nga operon (encodes NADase and streptolysin O) promoter (Pnga3). Sixty-four M protein gene (emm) types were identified among 69 clonal complexes (CCs), including one CC of Streptococcus dysgalactiae subsp. equisimilisemm types predicted the presence or absence of active sof determinants and were segregated into sof-positive or sof-negative genetic complexes. Only one "emm type switch" between strains was apparent. sof-negative strains showed a propensity to cause infections in the first quarter of the year, while sof+ strain infections were more likely in summer. Of 1,454 isolates, 808 (55.6%) were Pnga3 positive and 637 (78.9%) were accounted for by types emm1, emm89, and emm12 Theoretical coverage of a 30-valent M vaccine combined with an M-related protein (Mrp) vaccine encompassed 98% of the isolates. WGS data predicted that 15.3, 13.8, 12.7, and 0.6% of the isolates were nonsusceptible to tetracycline, erythromycin plus clindamycin, erythromycin, and fluoroquinolones, respectively, with only 19 discordant phenotypic results. Close phylogenetic clustering of emm59 isolates was consistent with recent regional emergence. This study revealed strain traits informative for GAS disease incidence tracking, outbreak detection, vaccine strategy, and antimicrobial therapy.IMPORTANCE The current population-based WGS data from GAS strains causing invasive disease in the United States provide insights important for prevention and control strategies. Strain distribution data support recently proposed multivalent M type-specific and conserved M-like protein vaccine formulations that could potentially protect against nearly all invasive U.S. strains. The three most prevalent clonal complexes share key polymorphisms in the nga operon encoding two secreted virulence factors (NADase and streptolysin O) that have been previously associated with high strain virulence and transmissibility. We find that Streptococcus pyogenes is phylogenetically subdivided into loosely defined multilocus sequence type-based clusters consisting of solely sof-negative or sof-positive strains; with sof-negative strains demonstrating differential seasonal preference for infection, consistent with the recently demonstrated differential seasonal preference based on phylogenetic clustering of full-length M proteins. This might relate to the differences in GAS strain compositions found in different geographic settings and could further inform prevention strategies.

BACKGROUND: Genomic sequence-based deduction of antibiotic minimum inhibitory concentration (MIC) has great potential to enhance the speed and sensitivity of antimicrobial susceptibility testing. We previously developed a penicillin-binding protein (PBP) typing system and two methods (Random Forest (RF) and Mode MIC (MM)) that accurately predicted beta-lactam MICs for pneumococcal isolates carrying a characterized PBP sequence type (phenotypic beta-lactam MICs known for at least one isolate of this PBP type). This study evaluates the prediction performance for previously uncharacterized (new) PBP types and the probability of encountering new PBP types, both of which impact the overall prediction accuracy. RESULTS: The MM and RF methods were used to predict MICs of 4309 previously reported pneumococcal isolates in 2 datasets and the results were compared to the known broth microdilution MICs to 6 beta-lactams. Based on a method that specifically evaluated predictions for new PBP types, the RF results were more accurate than MM results for new PBP types and showed percent essential agreement (MICs agree within +/-1 dilution) >97%, percent category agreement (interpretive results agree) >93%, major discrepancy (sensitive isolate predicted as resistant) rate < 1.2%, and very major discrepancy (resistant isolate predicted as sensitive) rate < 1.4% for all 6 beta-lactams. The identification of new PBP types over time was well approximated by a diminishingly increasing curve (Pearson's r = 0.99) and minimally impacted overall MIC prediction performance. CONCLUSIONS: MIC prediction using the RF method could be an accurate alternative of phenotypic susceptibility testing even in the presence of previously uncharacterized PBP types.

Before PCV7 introduction, invasive pneumococcal disease (IPD) was responsible for approximately 12,000-18,000 deaths annually among children <5years in Latin America. In Peru, PCV7 was introduced in 2009. We used whole genome sequencing to deduce key features of invasive strains collected in Lima, Peru from 2006 to 2011. We sequenced 212 IPD isolates from 16 hospitals in Lima pre (2006-2009; n=133) and post (2010-2011; n=79) PCV7 introduction; 130 (61.3%) isolates were from children≤5years old. CDC's Streptococcus lab bioinformatics pipeline revealed serotypes, sequence types (STs), pilus genes, PBP types and other resistance determinants. During the pre-PCV7 period, serotype 14 was the most common serotype (24.8%), followed by 6B (20.3%), 19F (10.5%), and 23F (6.8%). Post-PCV7, the proportion of PCV7 serotype 6B decreased significantly (to 6.3%), while 19F (16.3%), 14 (15.0%), 23F (7.5%), and 19A (7.5%) were the most common serotypes; only serotypes 3 and 10A increased significantly. Overall, 82% (n=173) of all isolates carried at least one resistance determinant, including 72 (34%) isolates that carried resistance determinants against 3 or more antimicrobial classes; of these 72 isolates, 56 (78%) belonged to a PCV7 serotype. Eighty-two STs were identified, with 53 of them organized in 14 clonal complexes. ST frequencies were distributed differently pre and post-PCV7 introduction, with only 18 of the 57 STs identified in years 2006-2009 isolates also observed in years 2010-2011 isolates. The apparent expansion of a 19F/ST1421 lineage with predicted β-lactam resistance (PBP type 13:16:20) and carrying resistance determinants against four additional antimicrobial classes was observed.

In September 2016, the Oregon Health Authority was notified of a case of late-onset group B Streptococcus agalactiae (GBS) bacteremia in an infant that began 5 days after completion of treatment for early-onset GBS bacteremia. The infant was born at term following an uncomplicated pregnancy; maternal GBS vaginal/rectal screening culture at 37 weeks’ gestation was negative. Shortly after birth, the infant developed signs of respiratory distress and was transferred to the neonatal intensive care unit where blood and cerebrospinal fluid (CSF) were obtained for culture; antibiotics were initiated for presumed sepsis. The blood culture was positive for penicillin-sensitive, clindamycin-intermediate GBS. CSF culture was negative. The infant was discharged and went home after completing an 11-day course of ampicillin (200 mg/kg/day). | Five days later, the infant was taken to the emergency department because of irritability and was admitted to a second hospital. A blood culture yielded penicillin-sensitive, clindamycin-sensitive GBS. CSF was sterile, expressed breast milk did not yield GBS, and serial exams did not reveal a source. | Three days into the infant’s admission to the second hospital, the treating physician was notified by a physician from the birth hospital that the mother had requested release of the placenta at the time of delivery. The mother confirmed that she had registered with Company A to pick up and encapsulate her placenta for ingestion. Three days after the infant’s birth, the mother had received the dehydrated, encapsulated placenta and began ingesting two capsules three times daily. The physician instructed the mother to stop consuming the capsules. A sample of the capsules was cultured, yielding penicillin-sensitive, clindamycin-sensitive GBS. The infant was treated with ampicillin (300 mg/kg/day) for 14 days and gentamicin (3 mg/kg/daily) for the first 6 days and discharged home.

We used whole-genome sequencing to characterize 199 nonvaccine serotype 35B pneumococcal strains that caused invasive pneumococcal disease (IPD) in the United States during 2015-2016 and related these findings to previous serotype 35B IPD data obtained by Active Bacterial Core surveillance. Penicillin-nonsusceptible 35B IPD increased during post-pneumococcal 7-valent conjugate vaccine years (2001-2009) and increased further after implementation of pneumococcal 13-valent conjugate vaccine in 2010. This increase was caused primarily by the 35B/sequence type (ST) 558 lineage. 35B/ST558 and vaccine serotype 9V/ST156 lineages were implicated as cps35B donor and recipient, respectively, for a single capsular switch event that generated emergent 35B/ST156 progeny in 6 states during 2015-2016. Three additional capsular switch 35B variants were identified, 2 of which also involved 35B/ST558 as cps35B donor. Spread of 35B/ST156 is of concern in view of past global predominance of pathogenic ST156 vaccine serotype strains. Protection against serotype 35B should be considered in next-generation pneumococcal vaccines.

Background: Streptococcus agalactiae (Group B Streptococcus, GBS) is a leading cause of meningitis, sepsis and pneumonia in neonates in the United States. GBS also causes invasive disease in older infants, pregnant women, children and young adults with underlying medical conditions, and older adults. Resistance to lincosamides in the absence of erythromycin resistance is rare in GBS, but has been previously reported in clinical isolates, both on its own or in combination with resistance to streptogramins A and pleuromutilins (L/LSA/LSAP phenotypes). Objectives: To retrospectively screen the Active Bacterial Core surveillance (ABCs) GBS isolate collection for these phenotypes in order to identify the causal genetic determinants and determine whether their frequency is increasing. Methods: Based on MIC data, 65 (0.31%) isolates susceptible to erythromycin (MIC ≤0.25 mg/L) and non-susceptible to clindamycin (MIC ≥0.5 mg/L) were identified among 21186 GBS isolates. Genomic DNA was extracted and WGS was performed. The presence of 10 genes previously associated with LSA resistance was investigated by read mapping. Results: Forty-nine (75%) isolates carried the lsa (C) gene and expressed the LSAP phenotype, and 12 (18%) carried both the lnu (B) and lsa (E) genes and expressed the LSAP phenotype. The four remaining isolates were negative for all determinants investigated. Conclusions: While the overall observed frequency of these phenotypes among our GBS isolates was quite low (0.31%), this frequency has increased in recent years. To the best of our knowledge, this is the first time the LSAP phenotype has been reported among GBS isolates from the USA.

OBJECTIVES: Our objective was to evaluate and exploit a whole genome sequence (WGS) bioinformatics pipeline for predicting antimicrobial resistance and capsular serotypes from invasive group B streptococci (iGBS). METHODS: For 1975 iGBS recovered during 2015 from CDC's Active Bacterial Core surveillance, we compared pipeline predictions to broth dilution testing. Fifty-six isolates from earlier surveillance were included for testing beta-lactams.. Conventional serotyping was compared to WGS-based assignments for 302 isolates. RESULTS: All 28 isolates with reduced susceptibility to beta-lactam antibiotics harbored one of 19 rare PBP2x types. Resistances to erythromycin/clindamycin (808/1975 isolates, 41.0%), erythromycin (235/1975, 11.9%), and lincosamide/streptogramin A/pleuromutilins (56/1975, 2.8%) were predicted by presence of erm-methylase, mef, and lsa determinants, respectively (41 of 56 lsa gene positive isolates also contained lnu, erm, and/or mef genes). Presence of both erm and lsa determinants (25 isolates) predicted nonsusceptibility to quinupristin/dalfopristin. Most isolates (1680/1975, 85.1%) were tet gene-positive, although 41/1565 (2.6%) tetM-positive isolates were tetracycline-susceptible. All 53 fluoroquinolone-resistant isolates contained ParC and/or GyrA substitutions. Resistances to rifampin (8 isolates), trimethoprim, chloramphenicol and vancomycin (2 isolates each) were predicted by the pipeline. Resistance to macrolides/lincosamides without pipeline prediction was rare and correlated to divergent resistance genes or rRNA A2062G substitution. A selection of 267 isolates assigned WGS-based serotypes were also conventionally serotyped. Of these, 246 (92.1%) were in agreement, with the remaining 21 (7.8%) conventionally non-serotypeable. For thirty-two of 1975 isolates (1.6%), WGS-based serotypes could not be assigned. CONCLUSION: WGS-based assignment of iGBS resistance features and serotypes is an accurate substitute for phenotypic testing.

OBJECTIVES: We assessed our whole genome sequence (WGS) pipeline for accurate prediction of current antimicrobial phenotypes. METHODS: For 2316 invasive pneumococcal isolates (IPD) recovered during 2015 we compared WGS pipeline data to broth dilution testing (BDT) for 18 antimicrobials. RESULTS: For 11 antimicrobials categorical discrepancies were assigned when WGS-predicted minimum inhibitory concentrations (MICs) and BDT MICs resulted in different predictions for susceptibility, intermediate-resistance or resistance, ranging from 0.9% (tetracycline) to 2.9% (amoxicillin). For beta-lactam antibiotics, the occurrence of >4-fold MIC differences ranged from 0.2% (meropenem) to 1.0 % (penicillin), although phenotypic retesting resolved 25 - 78% of these discrepancies. Nonsusceptibility to penicillin, predicted by penicillin binding protein types, was 2.7% (non-meningitis criteria) and 23.8% (meningitis criteria). Other common resistance determinants included mef (475 isolates), ermB (191 isolates), ermB + mef (48 isolates), tetM (261 isolates) and cat (51 isolates). Additional accessory resistance genes (tetS, tet32, aphA-3, sat4) were rarely detected (in 1- 3 isolates). Rare core genome mutations conferring erythromycin-resistance included a 2 codon rplD insertion (rplD69-KG-70) and the 23S rRNA A2061G substitution (6 total isolates). Intermediate cotrimoxazole-resistance was associated with 1-2 codon insertions within folP (238 isolates) or the folA I100L substitution (38 isolates), while full cotrimoxazole-resistance was attributed to alterations in both genes (172 isolates). Levofloxacin-resistance (2 isolates) was associated with parC and/or gyrA mutations. Of 11 remaining isolates with moderately elevated MICs to both ciprofloxacin and levofloxacin, 7 contained parC or gyrA mutations. The two rifampin-resistant isolates contained rpoB mutations. CONCLUSIONS: WGS-based MIC prediction was an informative alternative to BDT for current IPD isolates.

beta-Lactam antibiotics are the drugs of choice to treat pneumococcal infections. The spread of beta-lactam-resistant pneumococci is a major concern in choosing an effective therapy for patients. Systematically tracking beta-lactam resistance could benefit disease surveillance. Here we developed a classification system in which a pneumococcal isolate is assigned to a "PBP type" based on sequence signatures in the transpeptidase domains (TPDs) of the three critical penicillin-binding proteins (PBPs), PBP1a, PBP2b, and PBP2x. We identified 307 unique PBP types from 2,528 invasive pneumococcal isolates, which had known MICs to six beta-lactams based on broth microdilution. We found that increased beta-lactam MICs strongly correlated with PBP types containing divergent TPD sequences. The PBP type explained 94 to 99% of variation in MICs both before and after accounting for genomic backgrounds defined by multilocus sequence typing, indicating that genomic backgrounds made little independent contribution to beta-lactam MICs at the population level. We further developed and evaluated predictive models of MICs based on PBP type. Compared to microdilution MICs, MICs predicted by PBP type showed essential agreement (MICs agree within 1 dilution) of >98%, category agreement (interpretive results agree) of >94%, a major discrepancy (sensitive isolate predicted as resistant) rate of <3%, and a very major discrepancy (resistant isolate predicted as sensitive) rate of <2% for all six beta-lactams. Thus, the PBP transpeptidase signatures are robust indicators of MICs to different beta-lactam antibiotics in clinical pneumococcal isolates and serve as an accurate alternative to phenotypic susceptibility testing. IMPORTANCE: The human pathogen Streptococcus pneumoniae is a leading cause of morbidity and mortality worldwide. beta-Lactam antibiotics such as penicillin and ceftriaxone are the drugs of choice to treat pneumococcal infections. Some pneumococcal strains have developed beta-lactam resistance through altering their penicillin-binding proteins (PBPs) and have become a major concern in choosing effective patient therapy. To systematically track and predict beta-lactam resistance, we obtained the sequence signatures of PBPs from a large collection of clinical pneumococcal isolates using whole-genome sequencing data and found that these "PBP types" were predictive of resistance levels. Our findings can benefit the current era of strain surveillance when whole-genome sequencing data often lacks detailed resistance information. Using PBP positions that we found are always substituted within highly resistant strains may lead to further refinements. Sequence-based predictions are accurate and may lead to the ability to extract critical resistance information from nonculturable clinical specimens.