Penicillin-Binding Protein Transpeptidase Signatures for Tracking and Predicting β-Lactam Resistance Levels in Streptococcus pneumoniae

Holistic understanding of trimethoprim resistance in Streptococcus pneumoniae using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning

Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to investigate trimethoprim (TMP) resistance in the key pathogen Streptococcus pneumoniae. We explored a collection of 662 S. pneumoniae genomes by conducting a genome-wide association study (GWAS), followed by functional validation using resistance reconstruction experiments, combined with machine learning (ML) approaches to predict TMP minimum inhibitory concentration (MIC). Our study showed that multiple additive mutations in the folA and sulA loci are responsible for TMP non-susceptibility in S. pneumoniae and can be used as key features to build ML models for digital MIC prediction, reaching an average accuracy within ±1 twofold dilution factor of 86.3%. Our roadmap of in silico analysis-wet-lab validation-diagnostic tool building could be adapted to explore AMR in other combinations of bacteria-antibiotic.

IMPORTANCE

In the age of next-generation sequencing (NGS), while data-driven methods such as genome-wide association study (GWAS) and machine learning (ML) excel at finding patterns, functional validation can be challenging due to the high numbers of candidate variants. We designed an integrative approach combining a GWAS on S. pneumoniae clinical isolates, followed by whole-genome transformation coupled with NGS to functionally characterize a large set of GWAS candidates. Our study validated several phenotypic folA mutations beyond the standard Ile100Leu mutation, and showed that the overexpression of the sulA locus produces trimethoprim (TMP) resistance in Streptococcus pneumoniae. These validated loci, when used to build ML models, were found to be the best inputs for predicting TMP minimal inhibitory concentrations. Integrative approaches can bridge the genotype-phenotype gap by biological insights that can be incorporated in ML models for accurate prediction of drug susceptibility.

Clonal Expansion of a Streptococcus pneumoniae Serotype 3 Capsule Variant Sequence Type 700 With Enhanced Vaccine Escape Potential After 13-Valent Pneumococcal Conjugate Vaccine Introduction

BACKGROUND

Streptococcus pneumoniae serotype 3 remains a problem globally. Malawi introduced 13-valent pneumococcal conjugate vaccine (PCV13) in 2011, but there has been no direct protection against serotype 3 carriage. We explored whether vaccine escape by serotype 3 is due to clonal expansion of a lineage with a competitive advantage.

METHODS

The distribution of serotype 3 Global Pneumococcal Sequence Clusters (GPSCs) and sequence types (STs) globally was assessed using sequences from the Global Pneumococcal Sequencing Project. Whole-genome sequences of 135 serotype 3 carriage isolates from Blantyre, Malawi (2015-2019) were analyzed. Comparative analysis of the capsule locus, entire genomes, antimicrobial resistance, and phylogenetic reconstructions were undertaken. Opsonophagocytosis was evaluated using serum samples from vaccinated adults and children.

RESULTS

Serotype 3 GPSC10-ST700 isolates were most prominent in Malawi. Compared with the prototypical serotype 3 capsular polysaccharide locus sequence, 6 genes are absent, with retention of capsule polysaccharide biosynthesis. This lineage is characterized by increased antimicrobial resistance and lower susceptibility to opsonophagocytic killing.

CONCLUSIONS

A serotype 3 variant in Malawi has genotypic and phenotypic characteristics that could enhance vaccine escape and clonal expansion after post-PCV13 introduction. Genomic surveillance among high-burden populations is essential to improve the effectiveness of next-generation pneumococcal vaccines.

Geographical migration and fitness dynamics of Streptococcus pneumoniae

Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location1,2. The extent and mechanisms of spread and vaccine-driven changes in fitness and antimicrobial resistance remain largely unquantified. Here using geolocated genome sequences from South Africa (n = 6,910, collected from 2000 to 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 included (vaccine type (VT)) and not included (non-vaccine type (NVT)) in pneumococcal conjugate vaccines, first implemented in South Africa in 2009. Differences in strain fitness between those that are and are not resistant to penicillin were also evaluated. We found that pneumococci only become homogenously mixed across South Africa after 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Furthermore, in the years following vaccine implementation, the relative fitness of NVT compared with VT strains increased (relative risk of 1.68; 95% confidence interval of 1.59-1.77), with an increasing proportion of these NVT strains becoming resistant to penicillin. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in antimicrobial resistance may be transient.

Diagnostics for Public Health - Infectious Disease Surveillance and Control

AbstractAccurate diagnostics are critical in public health to ensure successful disease tracking, prevention, and control. Many of the same characteristics are desirable for diagnostic procedures in both medicine and public health: for example, low cost, high speed, low invasiveness, ease of use and interpretation, day-to-day consistency, and high accuracy. This review lays out five principles that are salient when the goal of diagnosis is to improve the overall health of a population rather than that of a particular patient, and it applies them in two important use cases: pandemic infectious disease and antimicrobial resistance.

High-resolution genomics identifies pneumococcal diversity and persistence of vaccine types in children with community-acquired pneumonia in the UK and Ireland

BACKGROUND

Streptococcus pneumoniae is a global cause of community-acquired pneumonia (CAP) and invasive disease in children. The CAP-IT trial (grant No. 13/88/11; https://www.capitstudy.org.uk/ ) collected nasopharyngeal swabs from children discharged from hospitals with clinically diagnosed CAP, and found no differences in pneumococci susceptibility between higher and lower antibiotic doses and shorter and longer durations of oral amoxicillin treatment. Here, we studied in-depth the genomic epidemiology of pneumococcal (vaccine) serotypes and their antibiotic resistance profiles.

METHODS

Three-hundred and ninety pneumococci cultured from 1132 nasopharyngeal swabs from 718 children were whole-genome sequenced (Illumina) and tested for susceptibility to penicillin and amoxicillin. Genome heterogeneity analysis was performed using long-read sequenced isolates (PacBio, n = 10) and publicly available sequences.

RESULTS

Among 390 unique pneumococcal isolates, serotypes 15B/C, 11 A, 15 A and 23B1 were most prevalent (n = 145, 37.2%). PCV13 serotypes 3, 19A, and 19F were also identified (n = 25, 6.4%). STs associated with 19A and 19F demonstrated high genome variability, in contrast to serotype 3 (n = 13, 3.3%) that remained highly stable over a 20-year period. Non-susceptibility to penicillin (n = 61, 15.6%) and amoxicillin (n = 10, 2.6%) was low among the pneumococci analysed here and was independent of treatment dosage and duration. However, all 23B1 isolates (n = 27, 6.9%) were penicillin non-susceptible. This serotype was also identified in ST177, which is historically associated with the PCV13 serotype 19F and penicillin susceptibility, indicating a potential capsule-switch event.

CONCLUSIONS

Our data suggest that amoxicillin use does not drive pneumococcal serotype prevalence among children in the UK, and prompts consideration of PCVs with additional serotype coverage that are likely to further decrease CAP in this target population. Genotype 23B1 represents the convergence of a non-vaccine genotype with penicillin non-susceptibility and might provide a persistence strategy for ST types historically associated with vaccine serotypes. This highlights the need for continued genomic surveillance.

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.

Streptococcus suis serotype 9 in Italy: genomic insights into high-risk clones with emerging resistance to penicillin

BACKGROUND

Streptococcus suis is an important pig pathogen and an emerging zoonotic agent. In a previous study, we described a high proportion of penicillin-resistant serotype 9 S. suis (SS9) isolates on pig farms in Italy.

OBJECTIVES

We hypothesized that resistance to penicillin emerged in some SS9 lineages characterized by substitutions at the PBPs, contributing to the successful spread of these lineages in the last 20 years.

METHODS

Sixty-six SS9 isolates from cases of streptococcosis in pigs were investigated for susceptibility to penicillin, ceftiofur and ampicillin. The isolates were characterized for ST, virulence profile, and antimicrobial resistance genes through WGS. Multiple linear regression models were employed to investigate the associations between STs, year of isolation, substitutions at the PBPs and an increase in MIC values to β-lactams.

RESULTS

MIC values to penicillin increased by 4% each year in the study period. Higher MIC values for penicillin were also positively associated with ST123, ST1540 and ST1953 compared with ST16. The PBP sequences presented a mosaic organization of blocks. Within the same ST, substitutions at the PBPs were generally more frequent in recent isolates. Resistance to penicillin was driven by substitutions at PBP2b, including K479T, D512E and K513E, and PBP2x, including T551S, while reduced susceptibility to ceftiofur and ampicillin were largely dependent on substitutions at PBP2x.

CONCLUSIONS

Here, we identify the STs and substitutions at the PBPs responsible for increased resistance of SS9 to penicillin on Italian pig farms. Our data highlight the need for monitoring the evolution of S. suis in the coming years.

Disease-Associated Streptococcus pneumoniae Genetic Variation

Streptococcus pneumoniae is an opportunistic pathogen that causes substantial illness and death among children worldwide. The genetic backgrounds of pneumococci that cause infection versus asymptomatic carriage vary substantially. To determine the evolutionary mechanisms of opportunistic pathogenicity, we conducted a genomic surveillance study in China. We collected 783 S. pneumoniae isolates from infected and asymptomatic children. By using a 2-stage genomewide association study process, we compared genomic differences between infection and carriage isolates to address genomic variation associated with pathogenicity. We identified 8 consensus k-mers associated with adherence, antimicrobial resistance, and immune modulation, which were unevenly distributed in the infection isolates. Classification accuracy of the best k-mer predictor for S. pneumoniae infection was good, giving a simple target for predicting pathogenic isolates. Our findings suggest that S. pneumoniae pathogenicity is complex and multifactorial, and we provide genetic evidence for precise targeted interventions.

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.

Genotypic characterization of Streptococcus didelphis causative of fatal infection in white-eared opossums

Streptococcus didelphis was once reported as related to severe infections in opossums. Thus, we present the first comprehensive whole-genome characterization of clinical S. didelphis strains isolated from white-eared opossums (Didelphis albiventris). Long-read whole-genome sequencing was performed using the MinION platform, which allowed the prediction of several genomic features. We observed that S. didelphis genomes harbor a cluster for streptolysin biosynthesis and a conserved genomic island with genes involved in transcriptional regulation (arlR) and transmembrane transport (bcrA). Antimicrobial resistance genes for several drug classes were found, including beta-lactam, which is the main antimicrobial class used in Streptococcus spp. infections; however, no phenotypical resistance was observed. In addition, we predicted the presence of 33 virulence factors in the analyzed genomes. High phylogenetic similarity was observed between clinical and reference strains, yet no clonality was suggested. We also proposed dnaN, gki, pros, and xpt as housekeeping candidates to be used in S. didelphis sequence typing. This is the first whole-genome characterization of S. didelphis, whose data provide important insights into its pathogenicity.

Comparison of contemporary invasive and non-invasive Streptococcus pneumoniae isolates reveals new insights into circulating anti-microbial resistance determinants

Streptococcus pneumoniae is a major human pathogen with a high burden of disease. Non-invasive isolates (those found in non-sterile sites) are thought to be a key source of invasive isolates (those found in sterile sites) and a reservoir of anti-microbial resistance (AMR) determinants. Despite this, pneumococcal surveillance has almost exclusively focused on invasive isolates. We aimed to compare contemporaneous invasive and non-invasive isolate populations to understand how they interact and identify differences in AMR gene distribution. We used a combination of whole-genome sequencing and phenotypic anti-microbial susceptibility testing and a data set of invasive (n = 1,288) and non-invasive (n = 186) pneumococcal isolates, collected in Victoria, Australia, between 2018 and 2022. The non-invasive population had increased levels of antibiotic resistance to multiple classes of antibiotics including beta-lactam antibiotics penicillin and ceftriaxone. We identified genomic intersections between the invasive and non-invasive populations and no distinct phylogenetic clustering of the two populations. However, this analysis revealed sub-populations overrepresented in each population. The sub-populations that had high levels of AMR were overrepresented in the non-invasive population. We determined that WamR-Pneumo was the most accurate in silico tool for predicting resistance to the antibiotics tested. This tool was then used to assess the allelic diversity of the penicillin-binding protein genes, which acquire mutations leading to beta-lactam antibiotic resistance, and found that they were highly conserved (≥80% shared) between the two populations. These findings show the potential of non-invasive isolates to serve as reservoirs of AMR determinants.

Integrated genomic analysis of antibiotic resistance and virulence determinants in invasive strains of Streptococcus pneumoniae

Introduction

Streptococcus pneumoniae is an important human pathogen that may cause severe invasive pneumococcal diseases (IPDs) in young children and the elderly. A comprehensive comparative whole-genome analysis of invasive and non-invasive serotype strains offers great insights that are applicable to vaccine development and disease control.

Methods

In this study, 58 invasive (strains isolated from sterile sites) and 71 non-invasive (serotypes that have not been identified as invasive in our study) pneumococcal isolates were identified among the 756 pneumococcal isolates obtained from seven hospitals in Zhejiang, China (2010-2022). Serotyping, antimicrobial resistance tests, and genomic analyses were conducted to characterize these strains.

Results and discussion

The three most invasive serotypes were 23F, 14, and 6B. The invasive pneumococcal isolates' respective resistance rates against penicillin, ceftriaxone, tetracycline, and erythromycin were 34.5%, 15.5%, 98.3%, and 94.7%. Whole-genome sequencing indicated that the predominant invasive clonal complexes were CC271, CC876, and CC81. The high rate of penicillin non-susceptible Streptococcus pneumoniae (PNSP) is related to the clonal distribution of resistance-conferring penicillin-binding proteins (PBP). Interestingly, we found a negative correlation between invasiveness and resistance in the invasive pneumococcal serotype strains, which might be due to the proclivity of certain serotypes to retain their β-lactam resistance. Moreover, the mutually exclusive nature of zmpC and rrgC+srtBCD suggests their intricate and potentially redundant roles in promoting the development of IPD. These findings reveal significant implications for pneumococcal vaccine development in China, potentially informing treatment strategies and measures to mitigate disease transmission.

Genomic classification and antimicrobial resistance profiling of Streptococcus pneumoniae and Haemophilus influenza isolates associated with paediatric otitis media and upper respiratory infection

Acute otitis media (AOM) is the most common childhood bacterial infectious disease requiring antimicrobial therapy. Most cases of AOM are caused by translocation of Streptococcus pneumoniae or Haemophilus influenzae from the nasopharynx to the middle ear during an upper respiratory tract infection (URI). Ongoing genomic surveillance of these pathogens is important for vaccine design and tracking of emerging variants, as well as for monitoring patterns of antibiotic resistance to inform treatment strategies and stewardship.In this work, we examined the ability of a genomics-based workflow to determine microbiological and clinically relevant information from cultured bacterial isolates obtained from patients with AOM or an URI. We performed whole genome sequencing (WGS) and analysis of 148 bacterial isolates cultured from the nasopharynx (N = 124, 94 AOM and 30 URI) and ear (N = 24, all AOM) of 101 children aged 6-35 months presenting with AOM or an URI. We then performed WGS-based sequence typing and antimicrobial resistance profiling of each strain and compared results to those obtained from traditional microbiological phenotyping.WGS of clinical isolates resulted in 71 S. pneumoniae genomes and 76 H. influenzae genomes. Multilocus sequencing typing (MSLT) identified 33 sequence types for S. pneumoniae and 19 predicted serotypes including the most frequent serotypes 35B and 3. Genome analysis predicted 30% of S. pneumoniae isolates to have complete or intermediate penicillin resistance. AMR predictions for S. pneumoniae isolates had strong agreement with clinical susceptibility testing results for beta-lactam and non beta-lactam antibiotics, with a mean sensitivity of 93% (86-100%) and a mean specificity of 98% (94-100%). MLST identified 29 H. influenzae sequence types. Genome analysis identified beta-lactamase genes in 30% of H. influenzae strains, which was 100% in agreement with clinical beta-lactamase testing. We also identified a divergent highly antibiotic-resistant strain of S. pneumoniae, and found its closest sequenced strains, also isolated from nasopharyngeal samples from over 15 years ago.Ultimately, our work provides the groundwork for clinical WGS-based workflows to aid in detection and analysis of H. influenzae and S. pneumoniae isolates.

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.

Accelerating bioinformatics implementation in public health

We have adopted an open bioinformatics ecosystem to address the challenges of bioinformatics implementation in public health laboratories (PHLs). Bioinformatics implementation for public health requires practitioners to undertake standardized bioinformatic analyses and generate reproducible, validated and auditable results. It is essential that data storage and analysis are scalable, portable and secure, and that implementation of bioinformatics fits within the operational constraints of the laboratory. We address these requirements using Terra, a web-based data analysis platform with a graphical user interface connecting users to bioinformatics analyses without the use of code. We have developed bioinformatics workflows for use with Terra that specifically meet the needs of public health practitioners. These Theiagen workflows perform genome assembly, quality control, and characterization, as well as construction of phylogeny for insights into genomic epidemiology. Additonally, these workflows use open-source containerized software and the WDL workflow language to ensure standardization and interoperability with other bioinformatics solutions, whilst being adaptable by the user. They are all open source and publicly available in Dockstore with the version-controlled code available in public GitHub repositories. They have been written to generate outputs in standardized file formats to allow for further downstream analysis and visualization with separate genomic epidemiology software. Testament to this solution meeting the requirements for bioinformatic implementation in public health, Theiagen workflows have collectively been used for over 5 million sample analyses in the last 2 years by over 90 public health laboratories in at least 40 different countries. Continued adoption of technological innovations and development of further workflows will ensure that this ecosystem continues to benefit PHLs.

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.

A review of penicillin binding protein and group A Streptococcus with reduced-β-lactam susceptibility

With the widespread use of antibiotics, antimicrobial resistance (AMR) has become a global problem that endangers public health. Despite the global high prevalence of group A Streptococcus (GAS) infections and the global widespread use of β-lactams, β-lactams remain the first-line treatment option for GAS infection. β-hemolytic streptococci maintain a persistent susceptibility to β-lactams, which is an extremely special phenomenon in the genus Streptococci, while the exact current mechanism is not known. In recent years, several studies have found that the gene encoding penicillin binding protein 2X (pbp2x) is associated with GAS with reduced-β-lactam susceptibility. The purpose of this review is to summarize the current published data on GAS penicillin binding proteins and β-lactam susceptibility, to explore the relationship between them, and to be alert to the emergence of GAS with reduced susceptibility to β-lactams.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

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.

Advances in the Microbiological Diagnosis of Prosthetic Joint Infections

A significant number of prosthetic joint infections (PJI) are culture-negative and/or misinterpreted as aseptic failures in spite of the correct implementation of diagnostic culture techniques, such as tissue sample processing in a bead mill, prolonged incubation time, or sonication of removed implants. Misinterpretation may lead to unnecessary surgery and needless antimicrobial treatment. The diagnostic value of non-culture techniques has been investigated in synovial fluid, periprosthetic tissues, and sonication fluid. Different feasible improvements, such as real-time technology, automated systems and commercial kits are now available to support microbiologists. In this review, we describe non-culture techniques based on nucleic acid amplification and sequencing methods. Polymerase chain reaction (PCR) is a frequently used technique in most microbiology laboratories which allows the detection of a nucleic acid fragment by sequence amplification. Different PCR types can be used to diagnose PJI, each one requiring the selection of appropriate primers. Henceforward, thanks to the reduced cost of sequencing and the availability of next-generation sequencing (NGS), it will be possible to identify the whole pathogen genome sequence and, additionally, to detect all the pathogen sequences present in the joint. Although these new techniques have proved helpful, strict conditions need to be observed in order to detect fastidious microorganisms and rule out contaminants. Specialized microbiologists should assist clinicians in interpreting the result of the analyses at interdisciplinary meetings. New technologies will gradually be made available to improve the etiologic diagnoses of PJI, which will remain an important cornerstone of treatment. Strong collaboration among all specialists involved is essential for the correct diagnosis of PJI.

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.

Characterization of integrative and conjugative elements carrying antibiotic resistance genes of Streptococcus suis isolated in China

Streptococcus suis, an emerging zoonotic pathogen, is important reservoirs of antibiotic resistance genes that play critical roles in the horizontal transfer of corresponding resistances. In the present study, 656 antibiotic resistance (AR) genes were detected in 154 of 155 genomes of S. suis strains isolated from the nasopharynx of slaughtered pigs and the lungs of diseased pigs in China. The AR genes were clustered into 11 categories, consisting of tetracycline, macrolides, lincosamide, streptogramin, aminoglycoside, trimethoprim, amphenicols, nucleoside, quinupristin/dalfopristin, glycopeptide, and oxazolidinones resistance genes. In order to investigate the transmission patterns of the AR genes, AR genes-associated the mobile genetic elements (MGEs) were extracted and investigated. Twenty ICEs, one defective ICE, one tandem ICE, and ten prophages were found, which mainly carried tetracycline, macrolides/lincosamides/streptogramin (MLS), and aminoglycosides resistance genes. Three types of DNA cargo with AR genes were integrated into specific sites of ICEs: integrative mobilizable elements (IMEs), cis-IMEs (CIMEs), and transposon Tn916. Obvious differences in AR gene categories were found among the three cargo types. IMEs mainly harbored tetracycline and MLS resistance genes. CIMEs mainly carried aminoglycoside resistance genes, while transposon Tn916 carried only the tet (M) gene. Nearly all AR genes in ICEs were carried by IMEs and CIMEs. IMEs were prevalent and were also detected in additional 29 S. suis genomes. The horizontal transfer of IMEs and CIMEs may play critical role in ICE evolution and AR gene transmission in the S. suis population. Our findings provide novel insights into the transmission patterns of AR genes and the evolutionary mechanisms of ICEs in S. suis.

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.

Distinct Streptococcus pneumoniae cause invasive disease in Papua New Guinea

Streptococcus pneumoniae is a key contributor to childhood morbidity and mortality in Papua New Guinea (PNG). For the first time, whole genome sequencing of 174 isolates has enabled detailed characterisation of diverse S. pneumoniae causing invasive disease in young children in PNG, 1989-2014. This study captures the baseline S. pneumoniae population prior to the introduction of 13-valent pneumococcal conjugate vaccine (PCV13) into the national childhood immunisation programme in 2014. Relationships amongst lineages, serotypes and antimicrobial resistance traits were characterised, and the population was viewed in the context of a global collection of isolates. The analyses highlighted adiverse S. pneumoniae population associated with invasive disease in PNG, with 45 unique Global Pneumococcal Sequence Clusters (GPSCs) observed amongst the 174 isolates reflecting multiple lineages observed in PNG that have not been identified in other geographic locations. The majority of isolates were from children with meningitis, of which 52% (n=72) expressed non-PCV13 serotypes. Over a third of isolates were predicted to be resistant to at least one antimicrobial. PCV13 serotype isolates had 10.1 times the odds of being multidrug-resistant (MDR) compared to non-vaccine serotype isolates, and no isolates with GPSCs unique to PNG were MDR. Serotype 2 was the most commonly identified serotype; we identified a highly clonal cluster of serotype 2 isolates unique to PNG, and a distinct second cluster indicative of long-distance transmission. Ongoing surveillance, including whole-genome sequencing, is needed to ascertain the impact of the national PCV13 programme upon the S. pneumoniae population, including serotype replacement and antimicrobial resistance traits.

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.

Antimicrobial Susceptibility Testing of Porcine Bacterial Pathogens: Investigating the Prospect of Testing a Representative Drug for Each Antimicrobial Family

Antimicrobial susceptibility testing is necessary to carry out antimicrobial stewardship but a limited number of drugs belonging to each antimicrobial family has to be tested for technical limitations and economic resources. In this study, we have determined the minimal inhibitory concentration, using microdilution following international standards (CLSI), for 490 Actinobacillus pleuropneumoniae, 285 Pasteurella multocida, 73 Bordetella bronchiseptica, 398 Streptococcus suis and 1571 Escherichia coli strains from clinical cases collected in Spain between 2018 and 2020. The antimicrobial susceptibility pattern was deciphered using a principal component analysis for each bacterium and a matrix correlation (high > 0.8, medium 0.5−0.8 and low < 0.5) was obtained for each pair of antimicrobials. No significant associations were observed between MIC patterns for different antimicrobial families, suggesting that co-selection mechanisms are not generally present in these porcine pathogens. However, a high correlation was observed between the fluroquinolones (marbofloxacin and enrofloxacin) for all mentioned pathogens and for ceftiofur and cefquinome for E. coli and S. suis. Moreover, a significant association was also observed for tetracyclines (doxycycline and oxytetracycline) and B. bronchiseptica and tildipirosin/tulathromycin for P. multocida. These results suggest that generally, a representative drug per antimicrobial class cannot be selected, however, for some drug−bug combinations, MIC values from one representative drug could be extrapolated to the whole antimicrobial family.

Genetic characterization of penicillin-binding proteins of nonencapsulated Streptococcus pneumoniae in the postpneumococcal conjugate vaccine era in Japan

OBJECTIVES

Nonencapsulated Streptococcus pneumoniae (NESp) is emerging after the introduction of pneumococcal conjugate vaccines (PCVs). This study aimed to elucidate the genetic characteristics of penicillin-binding proteins (PBPs; PBP1a, 2b, and 2x) associated with penicillin nonsusceptibility in emergent NESp.

METHODS

A total of 71 NESp isolates that were identified in our previous study during the PCV era in Japan (2011-2019) were analyzed for their amino acid sequences of transpeptidase domain in PBP 1a, 2b, and 2x.

RESULTS

Overall, we identified 21 different PBP profiles (1a-2b-2x), all of which represent novel PBP profiles. The dominant PBP profiles were 13-16-ne1 (32.4%, n = 23), ne1-16-ne2 (14.1%, n = 10), and 13-7-ne4 (7.0%, n = 5) (novel PBP type was numbered with "ne" denoting "nonencapsulated"), accounting for 53.5% of all isolates. All isolates with the PBP profiles 13-16-ne1 and 13-7-ne4 and those having PBP1a type-13 and -131, PBP2b type-7, -ne1, and -ne2 showed nonsusceptibility to penicillin. A high degree of genetic diversity was found in PBP2x, with most of them (81.7%) being new types.

CONCLUSIONS

Our current study identified the 21 novel PBP profiles and remarkable mutations in the PBPs, which may be potentially associated with penicillin nonsusceptibility in NESp.

Rectovaginal Colonization with Serotypes of Group B Streptococci with Reduced Penicillin Susceptibility among Pregnant Women in León, Nicaragua

Group B Streptococci (GBS) are important causes of neonatal sepsis and meningitis globally. To elucidate the potential benefits of maternal GBS vaccines, data is needed on the epidemiology of maternal GBS rectovaginal colonization, distribution of serotypes, and resistance to intrapartum antibiotic prophylaxis (IAP). We collected rectal and vaginal samples from 305 pregnant women in León, Nicaragua between 35 and 40 weeks gestation. Samples were cultured for GBS and confirmed using latex agglutination. GBS isolates underwent serotyping by quantitative polymerase chain reaction, and antimicrobial susceptibility testing by disk diffusion and microdilution following Clinical Laboratory Standard Institute guidelines. Sixty-three women (20.7%) were colonized with GBS in either the rectum or the vagina. Of 91 GBS isolates collected from positive cultures, most were serotypes II (28.6%), Ia (27.5%), and III (20.9%). Most GBS isolates (52.9%) were resistant to penicillin, the first-line prophylactic antibiotic. Penicillin resistance was highly correlated with resistance to vancomycin, ceftriaxone, and meropenem. The results of our study suggest that one-fifth of pregnant women in the urban area of León, Nicaragua are colonized with GBS and risk transmitting GBS to their offspring during labor. High resistance to commonly available antibiotics in the region suggests that prophylactic maternal GBS vaccination would be an effective alternative to IAP.

Population structure of ocular Streptococcus pneumoniae is highly diverse and formed by lineages that escape current vaccines

Streptococcus pneumoniae is a leading cause of ocular infections including serious and sight-threatening conditions. The use of pneumococcal conjugate vaccines (PCV) has substantially reduced the incidence of pneumonia and invasive pneumococcal diseases, but has had limited impact on ocular infections. Additionally, widespread vaccine use has resulted in ongoing selective pressure and serotype replacement in carriage and disease. To gain insight into the population structure of pneumococcal isolates causing ocular infections in a post-PCV-13 time period, we investigated the genomic epidemiology of ocular S. pneumoniae isolates (n=45) collected at Massachusetts Eye and Ear between 2014 and 2017. By performing a series of molecular typing methods from draft genomes, we found that the population structure of ocular S. pneumoniae is highly diverse with 27 sequence types (grouped into 18 clonal complexes) and 17 serotypes being identified. Distribution of these lineages diverged according to the site of isolation, with conjunctivitis being commonly caused by isolates grouped in the Epidemic Conjunctivitis Cluster-ECC (60 %), and ST448 (53.3 %) being most frequently identified. Conversely, S. pneumoniae keratitis cases were caused by a highly diverse population of isolates grouping within 15 different clonal complexes. Serotyping inference demonstrated that 95.5 % of the isolates were non-PCV-13 vaccine types. Most of the conjunctivitis isolates (80 %) were unencapsulated, with the remaining belonging to serotypes 15B, 3 and 23B. On the other hand, S. pneumoniae causing keratitis were predominantly encapsulated (95.2 %) with 13 different serotypes identified, mostly being non-vaccine types. Carriage of macrolide resistance genes was common in our ocular S. pneumoniae population (42.2 %), and usually associated with the mefA +msrD genotype (n=15). These genes were located in the Macrolide Efflux Genetic Assembly cassette and were associated with low-level in vitro resistance to 14- and 15-membered macrolides. Less frequently, macrolide-resistant isolates carried an ermB gene (n=4), which was co-located with the tetM gene in a Tn-916-like transposon. Our study demonstrates that the population structure of ocular S. pneumoniae is highly diverse, mainly composed by isolates that escape the PCV-13 vaccine, with patterns of tissue/niche segregation, adaptation and specialization. These findings suggest that the population structure of ocular pneumococcus may be shaped by multiple factors including PCV-13 selective pressure, microbial-related and niche-specific host-associated features.

Integrative Reverse Genetic Analysis Identifies Polymorphisms Contributing to Decreased Antimicrobial Agent Susceptibility in Streptococcus pyogenes

Identification of genetic polymorphisms causing increased antibiotic resistance in bacterial pathogens traditionally has proceeded from observed phenotype to defined mutant genotype. The availability of large collections of microbial genome sequences that lack antibiotic susceptibility metadata provides an important resource and opportunity to obtain new information about increased antimicrobial resistance by a reverse genotype-to-phenotype bioinformatic and experimental workflow. We analyzed 26,465 genome sequences of Streptococcus pyogenes, a human pathogen causing 700 million infections annually. The population genomic data identified amino acid changes in penicillin-binding proteins 1A, 1B, 2A, and 2X with signatures of evolution under positive selection as potential candidates for causing decreased susceptibility to β-lactam antibiotics. Construction and analysis of isogenic mutant strains containing individual amino acid replacements in penicillin-binding protein 2X (PBP2X) confirmed that the identified residues produced decreased susceptibility to penicillin. We also discovered the first chimeric PBP2X in S. pyogenes and show that strains containing it have significantly decreased β-lactam susceptibility. The novel integrative reverse genotype-to-phenotype strategy presented is broadly applicable to other pathogens and likely will lead to new knowledge about antimicrobial agent resistance, a massive public health problem worldwide. IMPORTANCE The recent demonstration that naturally occurring amino acid substitutions in Streptococcus pyogenes PBP2X are sufficient to cause severalfold reduced susceptibility to multiple β-lactam antibiotics in vitro raises the concern that these therapeutic agents may become compromised. Substitutions in PBP2X are common first-step mutations that, with the incremental accumulation of additional adaptive mutations within the PBPs, can result in high-level resistance. Because β-lactam susceptibility testing is not routinely performed, the nature and extent of such substitutions within the PBPs of S. pyogenes are poorly characterized. To address this knowledge deficit, polymorphisms in the PBPs were identified among the most comprehensive cohort of S. pyogenes genome sequences investigated to date. The mutational processes and selective forces acting on the PBPs were assessed to identify specific substitutions likely to influence β-lactam susceptibility and to evaluate factors posited to be impediments to resistance emergence.

Emergence of Meropenem Resistance Among Cefotaxime Non-susceptible Streptococcus pneumoniae: Evidence and Challenges

The principal causative agent of acute bacterial meningitis (ABM) in children and the elderly is Streptococcus pneumoniae, with a widespread increase in penicillin resistance. Resistance is due to non-synonymous single-nucleotide polymorphisms (nsSNPs) that alter the penicillin-binding proteins (PBPs), the targets for all β-lactam drugs. Hence, resistance against one β-lactam antibiotic may positively select another. Since meropenem is an alternative to cefotaxime in meningeal infections, we aim to identify whether nsSNPs in the PBPs causing penicillin and cefotaxime resistance can decrease the pneumococcal susceptibility to meropenem. Comparison of the nsSNPs in the PBPs between the cefotaxime-resistant Indian (n = 33) and global isolates (n = 28) revealed that nsSNPs in PBP1A alone elevated meropenem minimal inhibitory concentrations (MICs) to 0.12 μg/ml, and nsSNPs in both PBP2X and 2B combined with PBP1A increases MIC to ≥ 0.25 μg/ml. Molecular docking confirmed the decrease in the PBP drug binding affinity due to the nsSNPs, thereby increasing the inhibition potential and the MIC values, leading to resistance. Structural dynamics and thermodynamic stability pattern in PBPs as a result of mutations further depicted that the accumulation of certain nsSNPs in the functional domains reduced the drug affinity without majorly affecting the overall stability of the proteins. Restricting meropenem usage and promoting combination therapy with antibiotics having non-PBPs as targets to treat cefotaxime non-susceptible S. pneumoniae meningitis can prevent the selection of β-lactam resistance.

Pneumococcal within-host diversity during colonization, transmission and treatment

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.

A Bayesian approach to modeling antimicrobial multidrug resistance

Multidrug resistance (MDR) has been a significant threat to public health and effective treatment of bacterial infections. Current identification of MDR is primarily based upon the large proportions of isolates resistant to multiple antibiotics simultaneously, and therefore is a belated evaluation. For bacteria with MDR, we expect to see strong correlations in both the quantitative minimum inhibitory concentration (MIC) and the binary susceptibility as classified by the pre-determined breakpoints. Being able to detect correlations from these two perspectives allows us to find multidrug resistant bacteria proactively. In this paper, we provide a Bayesian framework that estimates the resistance level jointly for antibiotics belonging to different classes with a Gaussian mixture model, where the correlation in the latent MIC can be inferred from the Gaussian parameters and the correlation in binary susceptibility can be inferred from the mixing weights. By augmenting the laboratory measurement with the latent MIC variable to account for the censored data, and by adopting the latent class variable to represent the MIC components, our model was shown to be accurate and robust compared with the current assessment of correlations. Applying the model to Salmonella heidelberg samples isolated from human participants in National Antimicrobial Resistance Monitoring System (NARMS) provides us with signs of joint resistance to Amoxicillin-clavulanic acid & Cephalothin and joint resistance to Ampicillin & Cephalothin. Large correlations estimated from our model could serve as a timely tool for early detection of MDR, and hence a signal for clinical intervention.

Whole-genome analysis-based phylogeographic investigation of Streptococcus pneumoniae serotype 19A sequence type 320 isolates in Japan

After the introduction of the seven-valent pneumococcal conjugate vaccine, the global spread of multidrug-resistant serotype 19A-sequence type 320 (ST320) strains of Streptococcus pneumoniae became a public health concern. In Japan, the main genotype of serotype 19A was ST3111, and the identification rate of ST320 was low. Although the isolates were sporadically detected in both adults and children, their origin remains unknown. Thus, by combining pneumococcal isolates collected in three nationwide pneumococcal surveillance studies conducted in Japan between 2008 and 2020, we analyzed 56 serotype 19A-ST320 isolates along with 931 global isolates, using whole-genome sequencing to uncover the transmission route of the globally distributed clone in Japan. The clone was frequently detected in Okinawa Prefecture, where the United States returned to Japan in 1972. Phylogenetic analysis demonstrated that the isolates from Japan were genetically related to those from the United States; therefore, the common ancestor may have originated in the United States. In addition, Bayesian analysis suggested that the time to the most recent common ancestor of the isolates from Japan and the U.S. was approximately the 1990s to 2000, suggesting the possibility that the common ancestor could have already spread in the United States before the Taiwan 19F-14 isolate was first identified in a Taiwanese hospital in 1997. The phylogeographical analysis supported the transmission of the clone from the United States to Japan, but the analysis could be influenced by sampling bias. These results suggested the possibility that the serotype 19A-ST320 clone had already spread in the United States before being imported into Japan.

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.

Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases

In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms that resist conventional antibiotic treatment has steadily increased. Thus, it is now unquestionable that infectious diseases are significant global burdens that urgently require innovative treatment strategies. Emerging studies have demonstrated that artificial intelligence (AI) can transform drug delivery to promote effective treatment of infectious diseases. In this review, we propose to evaluate the significance, essential principles, and popular tools of AI in drug delivery for infectious disease treatment. Specifically, we will focus on the achievements and key findings of current research, as well as the applications of AI on drug delivery throughout the whole antimicrobial treatment process, with an emphasis on drug development, treatment regimen optimization, drug delivery system and administration route design, and drug delivery outcome prediction. To that end, the challenges of AI in drug delivery for infectious disease treatments and their current solutions and future perspective will be presented and discussed.

Linear regression equations to predict β-lactam, macrolide, lincosamide and fluoroquinolone minimum inhibitory concentrations from molecular antimicrobial resistance determinants in Streptococcus pneumoniae

Antimicrobial resistance in Streptococcus pneumoniae represents a threat to public health and monitoring the dissemination of resistant strains is essential to guiding health policy. Multiple-variable linear regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to antimicrobial minimum inhibitory concentration (MIC) for penicillin, ceftriaxone, erythromycin, clarithromycin, clindamycin, levofloxacin, and trimethoprim/sulfamethoxazole. Training data sets consisting of Canadian S. pneumoniae isolated from 1995 to 2019 were used to generate multiple-variable linear regression equations for each antimicrobial. The regression equations were then applied to validation data sets of Canadian (n=439) and USA (n=607 and n=747) isolates. The MIC for β-lactam antimicrobials were fully explained by amino acid substitutions in motif regions of the penicillin binding proteins PBP1a, PPB2b, and PBP2x. Accuracy of predicted MICs within one doubling dilution to phenotypically determined MICs for penicillin was 97.4%, ceftriaxone 98.2%; erythromycin 94.8%; clarithromycin 96.6%; clindamycin 98.2%; levofloxacin 100%; and trimethoprim/sulfamethoxazole 98.8%; with an overall sensitivity of 95.8% and specificity of 98.0%. Accuracy of predicted MICs to the phenotypically determined MICs was similar to phenotype-only MIC comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular determinants will facilitate the transition from routine phenotypic testing to whole genome sequencing analysis and can fill the surveillance gap in an era of increased reliance on nucleic acid assay diagnostics to better monitor the dynamics of S. pneumoniae.

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.

Complete Genome Sequence of Streptococcus pneumoniae Strain BVJ1JL, a Serotype 1 Carriage Isolate from Malawi

Streptococcus pneumoniae is a leading cause of pneumonia, meningitis, and bacteremia. Serotype 1 is rarely carried but is commonly associated with invasive pneumococcal disease, and in the African "meningitis belt," it is prone to cause cyclical epidemics. We report the complete genome sequence of S. pneumoniae serotype 1 strain BVJ1JL, isolated in Malawi.

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.

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.

Predictive Antibiotic Susceptibility Testing by Next-Generation Sequencing for Periprosthetic Joint Infections: Potential and Limitations

Joint replacement surgeries are one of the most frequent medical interventions globally. Infections of prosthetic joints are a major health challenge and typically require prolonged or even indefinite antibiotic treatment. As multidrug-resistant pathogens continue to rise globally, novel diagnostics are critical to ensure appropriate treatment and help with prosthetic joint infections (PJI) management. To this end, recent studies have shown the potential of molecular methods such as next-generation sequencing to complement established phenotypic, culture-based methods. Together with advanced bioinformatics approaches, next-generation sequencing can provide comprehensive information on pathogen identity as well as antimicrobial susceptibility, potentially enabling rapid diagnosis and targeted therapy of PJIs. In this review, we summarize current developments in next generation sequencing based predictive antibiotic susceptibility testing and discuss potential and limitations for common PJI pathogens.

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.