Fast and flexible bacterial genomic epidemiology with PopPUNK

Whole-genome sequencing, strain composition, and predicted antimicrobial resistance of Streptococcus pneumoniae causing invasive disease in England in 2017-20: a prospective national surveillance study

BACKGROUND

Surveillance of the invasive disease burden caused by Streptococcus pneumoniae in England is performed by the UK Health Security Agency (UKHSA). In 2017, UKHSA switched from phenotypic methods to whole-genome sequencing (WGS) approaches for pneumococcal surveillance. Here, we present the first results of national WGS surveillance, up to the start of the COVID-19 pandemic, with the aim of describing the population genomics of this important pathogen.

METHODS

We examined prospective national surveillance data from England, using bacterial isolates from cases of invasive pneumococcal disease (IPD) submitted to the national reference laboratory at UKHSA. A bioinformatic pipeline was developed to quality control WGS data and routinely report species and serotype. We assembled isolate data, assigned global pneumococcal sequencing clusters (GPSCs), and predicted antimicrobial resistance (AMR) profiles for isolates that passed further quality control. We collected additional data on patient outcomes and characteristics using enhanced surveillance questionnaires completed by patients' general practitioners. We used logistic regression analysis to assess the effects of various genomic and patient characteristics on the outcomes of IPD.

FINDINGS

In England, between July 1, 2017, and Feb 29, 2020, there were 15 400 cases of IPD. From these cases, 13 749 (89·3%) isolates were sequenced, passed quality control, and were included in analyses. Serotype diversity was high during the study period, with 2751 (20%) isolates serotyped as 13-valent pneumococcal conjugate vaccine (PCV13) types, whereas serotype 8 was the most prevalent serotype (n=3074 [22·4%]) overall. There were 157 GPSCs within the collection, with GSPC3 the most common, encompassing 98·7% (3033 of 3074) of serotype 8 isolates. Most isolates (n=10 198 [74·2%]) did not contain AMR-associated genes. Resistance to co-trimoxazole was the most frequently predicted resistance (n=2331 [17%]), followed by resistance to tetracycline (n=1199 [8·7%]) and β-lactams (n=1149 [8·4%]). Logistic regression analysis found the presence of AMR-associated genes significantly increased the odds of patient death (odds ratio 1·18, 95% CI 1·01-1·38). Some GPSCs were also associated with a significant increase in the odds of patient death, such as GPSC12 (1·88, 1·48-2·38). Isolates from 2018 were associated with a significant increase in the odds of patient death (1·12, 1·00-1·25), whereas younger patient age was significantly associated with a reduction in the odds of patient death compared with being aged 85 years or older.

INTERPRETATION

WGS-based surveillance has allowed us to interrogate country-wide population dynamics driving changes in pneumococcal serotype frequency. Here, we observe a stable but diverse population before the COVID-19 pandemic restrictions were enforced in England, with low rates of AMR. These findings will provide the baseline for pandemic and post-pandemic data, to collectively inform implementation and development of the vaccination programme within the country.

FUNDING

None.

Colonization dynamics of Streptococcus pneumoniae are determined by polymorphisms in the BlpAB transporter

Colonization of the human airways, the first step in the pathogenesis of Streptococcus pneumoniae (Spn), is the determining factor in the ecological spread of the bacterium. Since co-colonization by multiple strains is common, within-host bacterial competition contributes to the success of Spn strains. Competition both between and within strains is mediated by bacteriocin gene clusters, notably the quorum sensing-regulated bacteriocin-like peptide (blp) locus. A key component of this system is the BlpAB transporter that exports pheromones and bacteriocins expressed by the blp locus. However, ~75% of Spn strains lack a functional BlpAB transporter and instead rely on the paralogous ComAB transporter for this export, raising questions about the evolutionary persistence of BlpAB(+) strains. Using molecular barcoding, we demonstrate that BlpAB(+) and BlpAB(-) strains show major differences in population dynamics during colonization modeled in mice. The BlpAB(+) strains exhibit slower loss of clonal diversity as a consequence of intrastrain competition relative to their isogenic BlpAB(-). The contribution of a functional BlpAB transporter was then examined in an association study of >2,000 human carriage isolates from a highly colonized population. The median carriage duration was ~177 days longer for BlpAB(+) relative to BlpAB(-) strains. This increased duration of natural carriage correlates with a competitive advantage for BlpAB(+) strains when tested in the murine model. Thus, our work provides insight into how differences in the population dynamics of Spn mediated by bacterial competition impact host colonization.IMPORTANCESpn is a frequent colonizer of the human upper respiratory tract. Success during colonization is dictated by the arsenal of weapons these bacteria possess, which provides them with an advantage over their competitors. A key example includes the blp bacteriocins that are exported by the cell through both BlpAB and ComAB transporters. While most Spn strains lack a functional BlpAB, a subset of the strains retains it. Given this redundancy in export systems, our study questioned the evolutionary advantage of retaining BlpAB. Herein, we show that a functional BlpAB transporter causes a slower loss of clonal diversity in vivo. This correlates with longer Spn carriage duration in the human population and a competitive advantage during experimental co-colonization. Our work highlights the reasons behind the persistence of Spn with a functional BlpAB. These findings reveal how genetic variability in the blp locus shapes Spn colonization and evolutionary success.

Genetic landscape and evolution of Acinetobacter pittii, an underestimated emerging nosocomial pathogen

As a member of Acinetobacter calcoaceticus-baumannii complex, Acinetobacter pittii has been an emerging concern in nosocomial infection due to its increasing prevalence and multidrug resistance (MDR). However, its population structure remains broadly unknown, hampering efficient tracing of its transmission and evolution. In this study, we developed a distributed core genome multilocus sequence typing (dcgMLST) for A. pittii based on 750 genomes and employed it to map the genetic landscape and evolution of A. pittii. The results demonstrated that two hierarchical clustering (HC) levels effectively correspond to genetic diversity from species (HC1100) to natural populations (HC450), as well as that a predominant lineage, HC1100_4, accounts for 33.9% of A. pittii strains. Subsequent analysis revealed that specific gene gain and loss events within HC1100_4 are linked to adaptations to environmental stress. Moreover, we identified a cluster of multidrug-resistant plasmids PT_712 responsible for the dissemination of blaNDM-1 genes within the genus of Acinetobacter. This study provides a framework for characterizing genetic diversity, evolutionary dynamics, molecular population distribution, and tracing of A. pittii, which has the potential to improve infection control strategies and public health policy.

Rapid Transmission and Divergence of Vancomycin-Resistant Enterococcus faecium Sequence Type 80, China

We investigated genomic evolution of vancomycin-resistant Enterococcus faecium (VREF) during an outbreak in Shenzhen, China. Whole-genome sequencing revealed 2 sequence type 80 VREF subpopulations diverging through insertion sequence-mediated recombination. One subpopulation acquired more antimicrobial resistance and carbohydrate metabolism genes. Persistent VREF transmission underscores the need for genomic surveillance to curb spread.

Integrating Genomic Data into Public Health Surveillance for Multidrug-Resistant Organisms, Washington, USA

Mitigating antimicrobial resistance (AMR) is a public health priority to preserve antimicrobial treatment options. The Washington State Department of Health in Washington, USA, piloted a process to leverage longitudinal genomic surveillance on the basis of whole-genome sequencing (WGS) and a genomics-first cluster definition to enhance AMR surveillance. Here, we outline the approach to collaborative surveillance and describe the pilot using 6 carbapenemase-producing organism outbreaks of 3 species: Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae. We also highlight how we applied the approach to an emerging outbreak. We found that genomic and epidemiologic data define highly congruent outbreaks. By layering genomic and epidemiologic data, we refined linkage hypotheses and addressed gaps in traditional epidemiologic surveillance. With the accessibility of WGS, public health agencies must leverage new approaches to modernize surveillance for communicable diseases.

Multi-country and intersectoral assessment of cluster congruence between pipelines for genomics surveillance of foodborne pathogens

Different laboratories employ different Whole-Genome Sequencing (WGS) pipelines for Food and Waterborne disease (FWD) surveillance, casting doubt on the comparability of their results and hindering optimal communication at intersectoral and international levels. Through a collaborative effort involving eleven European institutes spanning the food, animal, and human health sectors, we aimed to assess the inter-pipeline clustering congruence across all resolution levels and perform an in-depth comparative analysis of cluster composition at outbreak level for four important foodborne pathogens: Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni. We found a general concordance between allele-based pipelines for all species, except for C. jejuni, where the different resolution power of allele-based schemas led to marked discrepancies. Still, we identified non-negligible differences in outbreak detection and demonstrated how a threshold flexibilization favors the detection of similar outbreak signals by different laboratories. These results, together with the observation that different traditional typing groups (e.g., serotypes) exhibit a remarkably different genetic diversity, represent valuable information for future outbreak case-definitions and WGS-based nomenclature design. This study reinforces the need, while demonstrating the feasibility, of conducting continuous pipeline comparability assessments, and opens good perspectives for a smoother international and intersectoral cooperation towards an efficient One Health FWD surveillance.

Comparative genomic analysis of 255 Oenococcus oeni isolates from China: unveiling strain diversity and genotype-phenotype associations of acid resistance

Oenococcus oeni, the only species of lactic acid bacteria capable of fully completing malolactic fermentation under challenging wine conditions, continues to intrigue researchers owing to its remarkable adaptability, particularly in combating acid stress. However, the mechanism underlying its superior adaptation to wine stresses still remains elusive due to the lack of viable genetic manipulation tools for this species. In this study, we conducted genomic sequencing and acid resistance phenotype analysis of 255 O. oeni isolates derived from diverse wine regions across China, aiming to elucidate their strain diversity and genotype-phenotype associations of acid resistance through comparative genomics. A significant correlation between phenotypes and evolutionary relationships was observed. Notably, phylogroup B predominantly consisted of acid-resistant isolates, primarily originating from Shandong and Shaanxi wine regions. Furthermore, we uncovered a noteworthy linkage between prophage genomic islands and acid resistance phenotype. Using genome-wide association studies, we identified key genes correlated with acid resistance, primarily involved in carbohydrates and amino acid metabolism processes. This study offers profound insights into the genetic diversity and genetic basis underlying adaptation mechanisms to acid stress in O. oeni.IMPORTANCEThis study provides valuable insights into the genetic basis of acid resistance in Oenococcus oeni, a key lactic acid bacterium in winemaking. By analyzing 255 isolates from diverse wine regions in China, we identified significant correlations between strain diversity, genomic islands, and acid resistance phenotypes. Our findings reveal that certain prophage-related genomic islands and specific genes are closely linked to acid resistance, offering a deeper understanding of how O. oeni adapts to acidic environments. These discoveries not only advance our knowledge of microbial stress responses but also pave the way for selecting and engineering acid-resistant strains, enhancing malolactic fermentation efficiency and wine quality. This research underscores the importance of genomics in improving winemaking practices and addressing challenges posed by high-acidity wines.

Plasmid-driven strategies for clone success in Escherichia coli

Escherichia coli is the most widely studied microbe in history, but the population structure and evolutionary trends of its extrachromosomal elements known as plasmids remain poorly delineated. Here we used long-read technology to high-resolution sequence the entire plasmidome and the corresponding host chromosomes from an unbiased longitudinal survey covering two decades and over 2000 E. coli isolates. We find that some plasmids have persisted in lineages even for centuries, demonstrating strong plasmid-lineage associations. Our analysis provides a detailed map of recent vertical and horizontal evolutionary events involving plasmids with key antibiotic resistance, competition and virulence determinants. We present genomic evidence of both chromosomal and plasmid-driven success strategies adopted by distant lineages by independently inheriting the same genomic elements. Further, we use in vitro experiments to verify the importance of key bacteriocin-producing plasmids for clone success. Our study has general implications for understanding plasmid biology and bacterial evolutionary strategies.

Comparison of pharyngeal and invasive isolates of Streptococcus pyogenes by whole-genome sequencing in Toronto, Canada

Invasive Group A streptococcal (iGAS) infections are rising in Canada and wordwide. The 2022-2023 Ontario iGAS season was among the highest recorded, a trend continuing in 2023-2024. We sequenced 38 invasive (blood) and 117 non-invasive (pharyngeal) Streptococcus pyogenes clinical isolates from Toronto (January-May 2023) to compare between the two cohorts and against published sequences to determine if any genomic changes accounted for the trend. Results demonstrated limited clustering with one small totally invasive cluster (emm49) with both invasive and non-invasive isolates represented across a diverse set of lineages. Non-invasive isolates were predominantly emm12 (70.1%), whereas invasive isolates included emm12 (26.32%), emm49 (23.68%), and emm1 (13.16%) with most emm1 strains containing the 27 SNPs that define the hypervirulent M1UK clone (58.33%). Although there were no differences in the presence of overall virulence factors/adhesin genes between cohorts, there were statistically more superantigen and DNase genes in non-invasive isolates and a rare phage gene was significantly associated with invasiveness across three emm-types. The prevalence of individual virulence factor/adhesin genes also differed between our cohorts, including a higher likelihood of speA, enn, mrp, ideS/Mac, fbaA, and fbaB in invasive isolates. There were also no significant differences across the 11 antimicrobial resistance genes identified. Finally, pharyngeal isolates had larger hydrolysis and hemolysis zones, and covS deletions were observed in only seven invasive strains. Despite there being no genetic signature that differentiated our isolates, we observed several features that were predominant in invasive strains which provides further insights into the factors that contribute to GAS invasiveness.IMPORTANCEIncreasing rates of invasive Group A streptococcal (iGAS) infections are being seen both in Canada and worldwide, which is leading to a greater disease burden caused by this pathogen. Leveraging whole-genome sequencing gives us an opportunity to better understand the underlying genetic mechanisms of streptococcal disease. By utilizing this technique, we shed light on the circulating invasive and non-invasive strains of Streptococcus pyogenes in the largest urban area in Canada from January to May 2023. GAS strains causing non-invasive disease were found to have a higher abundance of superantigen and DNase genes, whereas invasive isolates were more likely to contain M-like protein genes, the superantigen speA, the protease ideS/Mac, and/or the fibronectin-binding proteins fbaA and fbaB. This work provides valuable insights into iGAS disease which will help with surveillance, epidemiology as well as developing treatment and preventative modalities to help curb the disease burden caused by this globally important pathogen.

Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA)

The study of genomic variants is increasingly important for public health surveillance of pathogens. Traditional variant-calling methods from whole-genome sequencing data rely on reference-based alignment, which can introduce biases and require significant computational resources. Alignment- and reference-free approaches offer an alternative by leveraging k-mer-based methods, but existing implementations often suffer from sensitivity limitations, particularly in high mutation density genomic regions. Here, we present ska lo, a graph-based algorithm that aims to identify within-strain variants in pathogen whole-genome sequencing data by traversing a colored De Bruijn graph and building variant groups (i.e. sets of variant combinations). Through in silico benchmarking and real-world dataset analyses, we demonstrate that ska lo achieves high sensitivity in single-nucleotide polymorphism (SNP) calls while also enabling the detection of insertions and deletions, as well as SNP positioning on a reference genome for recombination analyses. These findings highlight ska lo as a simple, fast, and effective tool for pathogen genomic epidemiology, extending the range of reference-free variant-calling approaches. ska lo is freely available as part of the SKA program (https://github.com/bacpop/ska.rust).

Methicillin-sensitive Staphylococcus aureus lineages contribute towards poor patient outcomes in orthopaedic device-related infections

Staphylococci are the most common cause of orthopaedic device-related infections (ODRIs), with Staphylococcus aureus responsible for a third or more of cases. This prospective clinical and laboratory study investigated the association of genomic and phenotypic variation with treatment outcomes in ODRI isolates. Eighty-six invasive S. aureus isolates were collected from patients with ODRI, and clinical outcome was assessed after a follow-up examination of 24 months. Each patient was then considered to have been 'cured' or 'not cured' based on predefined clinical criteria. Whole-genome sequencing and molecular characterization identified isolates belonging to globally circulating community- and hospital-acquired lineages. Most isolates were phenotypically susceptible to methicillin and lacked the staphylococcal cassette chromosome mec cassette [methicillin-susceptible S. aureus (MSSA); 94%] but contained several virulence genes, including toxins and biofilm genes. Whilst recognizing the role of the host immune response, we identified genetic variance, which could be associated with the infection severity or clinical outcome. Whilst this and several other studies reinforce the role antibiotic resistance [e.g. methicillin-resistant S. aureus (MRSA) infection] has on treatment failure, it is important not to overlook MSSA that can cause equally destructive infections and lead to poor patient outcomes.

Integrated population clustering and genomic epidemiology with PopPIPE

Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations and as an additional source of information when detecting possible transmission events. Due to their variable gene content and order, reference-free methods offer more sensitive detection of genetic differences, especially among closely related samples found in outbreaks. However, across longer genetic distances, frequent recombination can make calculation and interpretation of these differences more challenging, requiring significant bioinformatic expertise and manual intervention during the analysis process. Here, we present a Population analysis PIPEline (PopPIPE) which combines rapid reference-free genome analysis methods to analyse bacterial genomes across these two scales, splitting whole populations into subclusters and detecting plausible transmission events within closely related clusters. We use k-mer sketching to split populations into strains, followed by split k-mer analysis and recombination removal to create alignments and subclusters within these strains. We first show that this approach creates high-quality subclusters on a population-wide dataset of Streptococcus pneumoniae. When applied to nosocomial vancomycin-resistant Enterococcus faecium samples, PopPIPE finds transmission clusters that are more epidemiologically plausible than core genome or multilocus sequence typing (MLST) approaches. Our pipeline is rapid and reproducible, creates interactive visualizations and can easily be reconfigured and re-run on new datasets. Therefore, PopPIPE provides a user-friendly pipeline for analyses spanning species-wide clustering to outbreak investigations.

Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning

Listeria monocytogenes is a potentially severe disease-causing bacteria mainly transmitted through food. This pathogen is of great concern for public health and the food industry in particular. Many countries have implemented thorough regulations, and some have even set 'zero-tolerance' thresholds for particular food products to minimise the risk of L. monocytogenes outbreaks. This emphasises that proper sanitation of food processing plants is of utmost importance. Consequently, in recent years, there has been an increased interest in L. monocytogenes tolerance to disinfectants used in the food industry. Even though many studies are focusing on laboratory quantification of L. monocytogenes tolerance, the possibility of predictive models remains poorly studied. Within this study, we explore the prediction of tolerance and minimum inhibitory concentrations (MIC) using whole genome sequencing (WGS) and machine learning (ML). We used WGS data and MIC values to quaternary ammonium compound (QAC) disinfectants from 1649 L. monocytogenes isolates to train different ML predictors. Our study shows promising results for predicting tolerance to QAC disinfectants using WGS and machine learning. We were able to train high-performing ML classifiers to predict tolerance with balanced accuracy scores up to 0.97 ± 0.02. For the prediction of MIC values, we were able to train ML regressors with mean squared error as low as 0.07 ± 0.02. We also identified several new genes related to cell wall anchor domains, plasmids, and phages, putatively associated with disinfectant tolerance in L. monocytogenes. The findings of this study are a first step towards prediction of L. monocytogenes tolerance to QAC disinfectants used in the food industry. In the future, predictive models might be used to monitor disinfectant tolerance in food production and might support the conceptualisation of more nuanced sanitation programs.

Streptococcus pneumoniae serotype 33H: a novel serotype with frameshift mutations in the acetyltransferase gene wciG

BACKGROUND

Streptococcus pneumoniae (the pneumococcus) is a leading cause of community-acquired pneumonia. Pneumococci are categorised into serotypes, based on the type of capsular polysaccharide produced, which has important implications for virulence, vaccine impact and global surveillance. Recently, we identified a novel serotype, which we named 33G, that is comprised of an O-acetylated hexasaccharide repeat unit. In this study, we report and describe variants of 33G, designated 33G-like, which we isolated from the nasopharynx of two adults hospitalised with pneumonia in Mongolia.

METHODS

Serological comparison of 33G and 33G-like pneumococci were conducted by Quellung serotyping. Genetic analysis of the capsular polysaccharide loci was performed using whole genome sequencing. Polysaccharide composition was determined using 1H nuclear magnetic resonance.

RESULTS

By Quellung serotyping, 33G pneumococci type as both 10B and 33B whereas 33G-like pneumococci type as both 10B and 33F. Genomic analysis of the capsular polysaccharide locus revealed 33G-like loci are identical to 33G, except for frameshift mutations in the wciG gene which encodes an acetyltransferase responsible for the O-acetylation of beta-galactofuranose (β-Galf) in the capsular polysaccharide repeat unit. We constructed an artificial 33G-like by deleting wciG in a 33G strain and confirmed this gene was responsible for the serological differences between 33G and 33G-like pneumococci. Lastly, 1H nuclear magnetic resonance confirmed the O-acetylation present in the 33G polysaccharide is absent in the 33G-like polysaccharide.

CONCLUSIONS

Here, we have provided serological, genetic and biochemical evidence that the 33G-like capsule differs to 33G and all other pneumococcal serotypes, meeting the requirements to be designated as a new serotype, which we have named 33H.

Replicative selfish genetic elements are driving rapid pathogenic adaptation of Enterococcus faecium

Understanding how healthcare-associated pathogens adapt in clinical environments can inform strategies to reduce their burden. Here, we investigate the hypothesis that insertion sequences (IS), prokaryotic transposable elements, are a dominant mediator of rapid genomic evolution in healthcare-associated pathogens. Among 28,207 publicly available pathogen genomes, we find high copy numbers of the replicative ISL3 family in healthcare-associated Enterococcus faecium, Streptococcus pneumoniae and Staphylococcus aureus. In E. faecium, the ESKAPE pathogen with the highest IS density, we find that ISL3 proliferation has increased in the last 30 years. To enable better identification of structural variants, we long read-sequenced a new, single hospital collection of 282 Enterococcal infection isolates collected over three years. In these samples, we observed extensive, ongoing structural variation of the E. faecium genome, largely mediated by active replicative ISL3 elements. To determine if ISL3 is actively replicating in clinical timescales in its natural, gut microbiome reservoir, we long read-sequenced a collection of 28 longitudinal stool samples from patients undergoing hematopoietic cell transplantation, whose gut microbiomes were dominated by E. faecium. We found up to six structural variants of a given E. faecium strain within a single stool sample. Examining longitudinal samples from one individual in further detail, we find ISL3 elements can replicate and move to specific positions with profound regulatory effects on neighboring gene expression. In particular, we identify an ISL3 element that upon insertion replaces an imperfect -35 promoter sequence at a folT gene locus with a perfect -35 sequence, which leads to substantial upregulation of expression of folT, driving highly effective folate scavenging. As a known folate auxotroph, E. faecium depends on other members of the microbiota or diet to supply folate. Enhanced folate scavenging may enable E. faecium to thrive in the setting of microbiome collapse that is common in HCT and other critically ill patients. Together, ISL3 expansion has enabled E. faecium to rapidly evolve in healthcare settings, and this likely contributes to its metabolic fitness and may strongly influence its ongoing trajectory of genomic evolution.

skDER & CiDDER: two scalable approaches for microbial genome dereplication

An abundance of microbial genomes have been sequenced in the past two decades. For fundamental comparative genomic investigations, where the goal is to determine the major gain and loss events shaping the pangenome of a species, it is often unnecessary and computationally onerous to include all available genomes in studies. In addition, over-representation of specific lineages due to sampling and sequencing bias can have undesired effects on evolutionary analyses. To assist users with genomic dereplication, selecting a subset of representative genomes, for downstream comparative genomic investigations, we developed skDER & CiDDER (https://github.com/raufs/skDER). skDER combines recent advances to efficiently estimate average nucleotide identity (ANI) between thousands of microbial genomes with two efficient algorithms for genomic dereplication. Further, CiDDER implements an approach whereby protein clusters are determined across all genomes and genomes are iteratively selected as representatives until a user-defined saturation of the total protein space is achieved. To support ease of use, several auxiliary functionalities are implemented within the two programs, including arguments to: (i) test the number of representative genomes resulting from a variety of clustering parameters, (ii) automate downloading of genomes belonging to a bacterial species or genus by name, (iii) cluster non-representative genomes to their closest representative genomes, and (iv) automatically filter predicted plasmids and phages prior to dereplication. We further assess the effects of filtering mobile genetic elements (MGEs) on ANI and alignment fraction (AF) estimates between pairs of genomes and find that MGEs tend to slightly deflate both metrics in one species.

Rapid, reference-free identification of bacterial pathogen transmission using optimized split k-mer analysis

Infections caused by multidrug-resistant organisms (MDROs) are difficult to treat and often life threatening and place a burden on the healthcare system. Minimizing the transmission of MDROs in hospitals is a global priority with genomics proving to be a powerful tool for identifying the transmission of MDROs. To optimize the utility of genomics for prospective infection control surveillance, results must be available in real time, reproducible and simple to communicate to clinicians. Traditional reference-based approaches suffer from several limitations for prospective genomic surveillance. Whilst reference-free or pairwise genome comparisons avoid some of these limitations, they can be computationally intensive and time consuming. Split k-mer analysis (SKA) offers a viable alternative facilitating rapid reference-free pairwise comparisons of genomic data, but the optimum SKA parameters for the detection of transmission have not been determined. Additionally, the accuracy of SKA-based inferences has not been measured, nor whether modified quality control parameters are required. Here, we explore the performance of 60 SKA parameter combinations across 50 simulations to quantify the false negative and positive SNP proportions for Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae and Staphylococcus aureus. Using the optimum parameter combination, we explore concordance between SKA, multilocus sequence typing (MLST), core genome MLST (cgMLST) and Snippy in a real-world dataset. Lastly, we investigate whether simulated plasmid gain or loss could impact SNP detection with SKA. This work identifies that the use of SKA with sequencing reads, a k-mer length of 19 and a minor allele frequency filter of 0.01 is optimal for MDRO transmission detection. Whilst SNP detection with SKA (when used with sequencing reads) undercalls SNPs compared to Snippy, it is significantly faster, especially with larger datasets. SKA has excellent concordance with MLST and cgMLST and is not impacted by simulated plasmid movement. We propose that the use of SKA for the detection of bacterial pathogen transmission is superior to traditional methodologies, capable of providing results in a much shorter timeframe.

Genomic characterization of Streptococcus pneumoniae isolates obtained from carriage and disease among paediatric patients in Addis Ababa, Ethiopia

Background and aims. Despite the introduction of pneumococcal conjugate vaccines (PCVs), Streptococcus pneumoniae still remains an important cause of morbidity and mortality, especially among children under 5 years in sub-Saharan Africa. We sought to determine the distribution of serotypes, lineages and antimicrobial resistance of S. pneumoniae from carriage and disease among children presenting to health facilities, 5-6 years after the introduction of PCV10 in Ethiopia.Methods. Whole-genome sequencing (WGS) was performed on 103 S. pneumoniae (86 from nasopharyngeal swabs, 4 from blood and 13 from middle ear discharge) isolated from children aged <15 years at 3 healthcare facilities in Addis Ababa, Ethiopia, from September 2016 to August 2017. Using the WGS data, serotypes were predicted, isolates were assigned to clonal complexes, global pneumococcal sequence clusters (GPSCs) were inferred and screening for alleles and mutations that confer resistance to antibiotics was performed using multiple bioinformatic pipelines.Results. The 103 S. pneumoniae isolates were assigned to 38 serotypes (including nontypeable) and 46 different GPSCs. The most common serotype was serotype 19A. Common GPSCs were GPSC1 [14.6% (15/103), sequence type (ST) 320, serotype 19A], GPSC268 [8.7% (9/103), ST 6882 and novel STs; serotypes 16F, 11A and 35A] and GPSC10 [8.7% (9/103), STs 2013, 230 and 8804; serotype 19A]. The four invasive isolates were serotype 19A (n=2) and serotype 33C (n=2). Resistance to penicillin (>0.06 µg ml-1, CLSI meningitis cutoff) was predicted in 57% (59/103) of the isolates, and 43% (25/58) penicillin-binding protein allele combinations were predicted to be associated with penicillin resistance. Resistance mutations in folA (I100L) and/or folP (indel between fifty-sixth and sixty-seventh aa) were identified among 66% (68/103) of the isolates, whilst tetracycline (tetM) and macrolide (ermB and mefA) resistance genes were found in 46.6% (48/103), 20.4% (21/103) and 20.4% (21/103) of the isolates, respectively. Multidrug resistance (MDR) (≥3 antibiotic classes) was observed in 31.1% (32/103) of the isolates. GPSC1 and GPSC10 accounted for 46.8% (15/32) and 18.7% (6/32) of the overall MDR.Conclusion. Five to 6 years after the introduction of PCV10 in Ethiopia, the S. pneumoniae obtained from carriage and disease among paediatric patients showed diverse serotype and pneumococcal lineages. The most common serotype identified was 19A, expressed by the MDR lineages GPSC1 and GPSC10, which is not covered by PCV10 but is included in PCV13. Continued assessment of the impact of PCV on the population structure of S. pneumoniae in Ethiopia is warranted during and after PCV13 introduction.

Investigating two decades of Streptococcus pneumoniae bacteraemia in the Gelderland area, the Netherlands, using whole-genome sequencing

In the Netherlands, the 7-valent pneumococcal conjugate vaccine (PCV) was introduced to the childhood immunization programme in 2006 and replaced by the 10-valent PCV (PCV10, GSK) in 2011. To describe invasive pneumococcal disease in the era of childhood PCV vaccination on pneumococcal bacteraemia across all ages, we collected and sequenced 979 pneumococcal blood isolates from consecutive patients with pneumococcal bacteraemia in the Gelderland area, the Netherlands, between 2000 and 2020. In total, 58% of the bacteraemia cases (n=563/979) occurred in the elderly population. Compared to the pre-PCV period (2000-2005), the odds ratio for non-PCV10 bacteraemia was 17.5 (CI 9.9-31.6; P<0.001) in the late-PCV10 period, showing an overall increase in the proportion of bacteraemia cases being caused by non-vaccine serotype pneumococci (2016-2020). The increase in non-PCV10 serotypes is mainly driven by an expansion of lineage global pneumococcal sequencing cluster 3 (GPSC3) expressing serotype 8, alongside the emergence of serotype 12F that was mediated by multiple lineages (GPSC32/GPSC26/GPSC55). Both serotypes 8 and 12F were included in the latest PCV20 formulation that is licensed to be used in children and adults in Europe. Over 20 years, we observed a low prevalence of antimicrobial resistance (AMR) as predicted by genome data. There were no significant changes in AMR prevalence after vaccine introduction (P>0.05 for all comparisons). We saw a stably low prevalence of reduced penicillin susceptibility, which was observed in multiple pneumococcal lineages, with GPSC10 being the most common in the Gelderland collection, whilst GPSC1 and GPSC6 were common among the penicillin-resistant pneumococcal blood culture isolates provided by the Netherlands Reference Laboratory for Bacterial Meningitis. Comparison to global collections of GPSC10, GPSC1 and GPSC6 isolates favored the likelihood of separate introductions of penicillin-resistant isolates rather than cloncal expansion. Genomic surveillance of pneumococcal bacteraemia in this unbiased population sample in the Netherlands supports the use of higher valency PCVs, such as PCV20, especially in adults, to prevent future bacteraemia cases caused by Streptococcus pneumoniae in the Gelderland area, the Netherlands, while maintaining a low prevalence of AMR in the pneumococcal population.

A national outbreak of Serratia marcescens complex: investigation reveals genomic population structure but no source, Norway, June 2021 to February 2023

We report a national outbreak of Serratia marcescens complex type 755 (ct755) in Norway, with 74 cases identified between June 2021 and February 2023. Careful reviews of patient journals and interviews were performed, involving 33 hospitals throughout Norway. All available clinical isolates of S. marcescens collected between January 2021 and February 2023 (n = 455, including cases) from all involved hospitals were whole genome sequenced. Cases displayed a pattern of opportunistic infections, as usually observed with S. marcescens. No epidemiological links, common exposures or common risk factors were identified. The investigation pointed to an outbreak source present in the community. We suspect a nationally distributed product, possibly a food product, as the source. Phylogenetic analysis revealed a highly diverse bacterial population containing multiple distinct clusters. The outbreak cluster ct755 stands out as the largest and least diverse clone of a continuum, however a second cluster (ct281) also triggered a separate outbreak investigation. This report highlights challenges in the investigation of outbreaks caused by opportunistic pathogens and suggests that the presence of identical strains of S. marcescens in clinical samples is more common than previously recognised.

Complex exchanges among plasmids and clonal expansion of lineages shape the population structure and virulence of Borrelia burgdorferi

Background

In the United States, Borrelia burgdorferi (Bb) is the principal etiologic agent of Lyme disease. The complex structure of Bb genomes has posed challenges for genomic studies because homology among the bacterium's many plasmids, which account for ~40% of the genome by length, has made them difficult to sequence and assemble.

Results

We used long-read sequencing to generate near-complete assemblies of 62 isolates of human-derived Bb and collected public genomes with plasmid sequences. We characterized genetic diversity and population structure in the resulting set of 82 plasmid-complete Borrelia burgdorferi sensu stricto genomes. The Bb core genome is encoded by a chromosome and the conserved plasmids cp26, lp54, and lp17; the accessory genome is encoded by all other plasmids and the distal arm of the chromosome. Near-complete genomes reveal that the most granular Bb genotypes are clonal expansions of complex rearrangements among accessory genome elements. Ribosomal spacer types (RST) represent multiple collections of such genotypes, whereas OspC types are usually clonal. Structural rearrangements are non-randomly distributed throughout the genome, with cp32 plasmids undergoing dense exchanges and most linear plasmids, except lp54, sharing blocks among themselves and with the distal arm of the chromosome. OspC type A strains, known to possess greater virulence in humans, are distinguished by the presence of lp28-1 and lp56. Rearrangements among plasmids tended to preserve gene content, suggesting functional constraints among gene networks. Using k-partite graph decompositions, we identified gene sets with correlation patterns suggestive of conserved functional modules.

Conclusions

Long-read assemblies reveal that Bb population genetic structure results from clonal expansion of lineages that have undergone complex rearrangements among plasmid-encoded accessory genome elements. Genetic structure is preserved among genes even when plasmid rearrangements occur, suggesting that selection among epistatic loci maintains functional genetic networks. The analysis of near-complete genomes assembled using long-read sequencing methods advances our understanding of Bb biology and Lyme disease pathogenesis by providing the first detailed view of population variation in previously inaccessible areas of the Bb genome.

Persistent cross-species transmission systems dominate Shiga toxin-producing Escherichia coli O157:H7 epidemiology in a high incidence region: A genomic epidemiology study

Several areas of the world suffer a notably high incidence of Shiga toxin-producing Escherichia coli. To assess the impact of persistent cross-species transmission systems on the epidemiology of E. coli O157:H7 in Alberta, Canada, we sequenced and assembled E. coli O157:H7 isolates originating from collocated cattle and human populations, 2007-2015. We constructed a timed phylogeny using BEAST2 using a structured coalescent model. We then extended the tree with human isolates through 2019 to assess the long-term disease impact of locally persistent lineages. During 2007-2015, we estimated that 88.5% of human lineages arose from cattle lineages. We identified 11 persistent lineages local to Alberta, which were associated with 38.0% (95% CI 29.3%, 47.3%) of human isolates. During the later period, six locally persistent lineages continued to be associated with human illness, including 74.7% (95% CI 68.3%, 80.3%) of reported cases in 2018 and 2019. Our study identified multiple locally evolving lineages transmitted between cattle and humans persistently associated with E. coli O157:H7 illnesses for up to 13 y. Locally persistent lineages may be a principal cause of the high incidence of E. coli O157:H7 in locations such as Alberta and provide opportunities for focused control efforts.

Linkage-based ortholog refinement in bacterial pangenomes with CLARC

Bacterial genomes exhibit significant variation in gene content and sequence identity. Pangenome analyses explore this diversity by classifying genes into core and accessory clusters of orthologous groups (COGs). However, strict sequence identity cutoffs can misclassify divergent alleles as different genes, inflating accessory gene counts. CLARC (Connected Linkage and Alignment Redefinition of COGs) [https://github.com/IndraGonz/CLARC] improves pangenome analyses by condensing accessory COGs using functional annotation and linkage information. Through this approach, orthologous groups are consolidated into more practical units of selection. Analyzing 8,000+ Streptococcus pneumoniae genomes, CLARC reduced accessory gene estimates by more than 30% and improved evolutionary predictions based on accessory gene frequencies. By refining COG definitions, CLARC offers critical insights into bacterial evolution, aiding genetic studies across diverse populations.

Parameters for one health genomic surveillance of Escherichia coli from Australia

Genomics is a cornerstone of modern pathogen epidemiology yet demonstrating transmission in a One Health context is challenging, as strains circulate and evolve within and between diverse hosts and environments. To identify phylogenetic linkages and better define relevant measures of genomic relatedness in a One Health context, we collated 5471 Escherichia coli genome sequences from Australia originating from humans (n = 2996), wild animals (n = 870), livestock (n = 649), companion animals (n = 375), environmental sources (n = 292) and food (n = 289) spanning over 36 years. Of the 827 multi-locus sequence types (STs) identified, 10 STs were commonly associated with cross-source genomic clusters, including the highly clonal ST131, pandemic zoonotic lineages such as ST95, and emerging human ExPEC ST1193. Here, we show that assessing genomic relationships at ≤ 100 SNP threshold enabled detection of cross-source linkage otherwise obscured when applying typical outbreak-oriented relatedness thresholds ( ≤ 20 SNPs) and should be considered in interrogation of One Health genomic datasets.

PneusPage: A WEB-BASED TOOL for the analysis of Whole-Genome Sequencing Data of Streptococcus pneumonia

With the advent of whole-genome sequencing, opportunities to investigate the population structure, transmission patterns, antimicrobial resistance profiles, and virulence determinants of Streptococcus pneumoniae at high resolution have been increasingly expanding. Consequently, a user-friendly bioinformatics tool is needed to automate the analysis of Streptococcus pneumoniae whole-genome sequencing data, summarize clinically relevant genomic features, and further guide treatment options. Here, we developed PneusPage, a web-based tool that integrates functions for species prediction, molecular typing, drug resistance determination, and data visualization of Streptococcus pneumoniae. To evaluate the performance of PneusPage, we analyzed 80 pneumococcal genomes with different serotypes from the Global Pneumococcal Sequencing Project and compared the results with those from another platform, PathogenWatch. We observed a high concordance between the two platforms in terms of serotypes (100% concordance rate), multilocus sequence typing (100% concordance rate), penicillin-binding protein typing (88.8% concordance rate), and the Global Pneumococcal Sequencing Clusters (98.8% concordance rate). In addition, PneusPage offers integrated analysis functions for the detection of virulence and mobile genetic elements that are not provided by previous platforms. By automating the analysis pipeline, PneusPage makes whole-genome sequencing data more accessible to non-specialist users, including microbiologists, epidemiologists, and clinicians, thereby enhancing the utility of whole-genome sequencing in both research and clinical settings. PneusPage is available at https://pneuspage.minholee.net/.

Tiled Amplicon Sequencing Enables Culture-free Whole-Genome Sequencing of Pathogenic Bacteria From Clinical Specimens

Pathogen sequencing is an important tool for disease surveillance and demonstrated its high value during the COVID-19 pandemic. Viral sequencing during the pandemic allowed us to track disease spread, quickly identify new variants, and guide the development of vaccines. Tiled amplicon sequencing, in which a panel of primers is used for multiplex amplification of fragments across an entire genome, was the cornerstone of SARS-CoV-2 sequencing. The speed, reliability, and cost-effectiveness of this method led to its implementation in academic and public health laboratories across the world and adaptation to a broad range of viral pathogens. However, similar methods are not available for larger bacterial genomes, for which whole-genome sequencing typically requires in vitro culture. This increases costs, error rates and turnaround times. The need to culture poses particular problems for medically important bacteria such as Mycobacterium tuberculosis, which are slow to grow and challenging to culture. As a proof of concept, we developed two novel whole-genome amplicon panels for M. tuberculosis and Streptococcus pneumoniae. Applying our amplicon panels to clinical samples, we show the ability to classify pathogen subgroups and to reliably identify markers of drug resistance without culturing. Development of this work in clinical settings has the potential to dramatically reduce the time of diagnosis of drug resistance for multiple drugs in parallel, enabling earlier intervention for high priority pathogens.

Temporal dynamics of extended-spectrum β-lactamase-producing Escherichia coli and carbapenemase-producing Gram-negative bacteria in hospital wastewater

Hospital wastewater is a reservoir for the environmental spread of clinically relevant antimicrobial-resistant bacteria and resistance genes. The aim of this study was to quantify total Escherichia coli, extended-spectrum β-lactamase (ESBL)-producing E. coli, and carbapenemase-producing organisms (CPOs) and perform whole-genome sequencing-based characterization of these bacterial isolates in hospital wastewater samples collected bimonthly in Japan from January to November 2021. Total E. coli counts were 8.1 × 103-8.8 × 104 colony-forming units (CFU)/mL. ESBL-producing E. coli were detected in the sampling months of January, March, May, and July, with the ratio of ESBL-producing E. coli to total E. coli being remarkably highest (95 %) in July. In contrast, DHA-1 Ambler class C β-lactamase (AmpC)-producing E. coli was detected in September and November, accounting for 28 % and 3 % of total E. coli counts, respectively. All 140 ESBL-producing E. coli isolates harbored the blaCTX-M genes, with blaCTX-M-14 being the most common genotype (94.3 %), the vast majority of which were associated with the human virulent B2-O25b: H4-ST131-fimH30R/non-Rx. In September, E. coli clade I-O8:H33-ST3910-fimH1074 was primarily associated with blaDHA-1. Among 26 representative CPO isolates, Aeromonas caviae (34.6 %) and A. hydrophila subsp. hydrophila (30.8 %) were dominant. The most frequently detected carbapenemase gene was blaIMP-1 (57.7 %), followed by blaGES-24 (34.6 %) and blaGES-4 (7.7 %). Estimated bacterial counts of CPOs ranged from 4.0 × 10-1 to 4.7 × 103 CFU/mL over the six sampling months. blaIMP-1-positive A. hydrophila subsp. hydrophila ST860, which was repeatedly detected over the five sampling months, accounted for the highest total number of this bacterial clone (79 %). Overall, this study provides insights into the overwhelming presence and persistence of E. coli B2-O25b:H4-ST131-H30R/non-Rx with blaCTX-M-14 and Aeromonas spp. with blaIMP-1 in hospital wastewater, and the change in the dynamics of resistance gene prevalence from blaCTX-M-positive E. coli to blaDHA-1-positive E. coli.

Genomic and growth fitness study of extended-spectrum β-lactamase-producing Escherichia coli from bloodstream infections after introduction of a national 4C antimicrobial stewardship policy in Scotland

BACKGROUND

Extended-spectrum β-lactamase-producing Escherichia coli remains a major cause of hospital-acquired bloodstream infections in countries with high antimicrobial stewardship compliance.

METHODS

Isolates from bloodstream infections that occurred between 2010 and 2020 in a tertiary-level hospital in North-East Scotland soon after introduction of the '4C' antimicrobial stewardship policy were analysed for phylogenetic structure, antimicrobial resistance, plasmid, and virulence gene carriage. Growth fitness was measured in kinetic assays. Non-metric-multidimensional-scaling was used to evaluate clonal relationships, antimicrobial resistance, and virulence profiles in early and later years after the 4C policy introduction. Clonal and fitness trends over the study period were determined by generalised additive modelling. The relationship between clonal type, antimicrobial resistance, and fitness was evaluated by linear regression.

RESULTS

Three hierarchical phylogenetic clusters were identified, with the most dominant cluster (O25:H4/fimH30) including all, and nearly exclusively, Clade C ST131 isolates as well as minor non-ST131 sequence types. The prevalence of ST131 was largely stable over the study period. Resistance to aminoglycosides and aztreonam in ST131 was lower (P = 0.019 and P = 0.004, respectively) during later years (2016-2020) by 28% on average compared to early years soon after 4C policy implementation (2010-2014). Carriage of virulence factors involved in bacterial adaptation was higher in ST131 compared to non-ST131 but mostly stable in early vs. later years. Growth fitness of ST131 was lower than non-ST131 and declined steadily in later years (P < 0.0001).

CONCLUSIONS

Despite stable virulence factor carriage, population structure, and resistance to cephalosporins, we show increased susceptibility of ST131 to aminoglycosides and aztreonam and concurrent fitness decline years after the introduction of the 4C policy.

Differential stress responsiveness determines intraspecies virulence heterogeneity and host adaptation in Listeria monocytogenes

Microbial pathogenesis is mediated by the expression of virulence genes. However, as microbes with identical virulence gene content can differ in their pathogenic potential, other virulence determinants must be involved. Here, by combining comparative genomics and transcriptomics of a large collection of isolates of the model pathogen Listeria monocytogenes, time-lapse microscopy, in vitro evolution and in vivo experiments, we show that the individual stress responsiveness of L. monocytogenes isolates determines their respective levels of virulence in vivo and reflects their degree of host adaptation. The transcriptional signature that accounts for the heterogeneity in the virulence of L. monocytogenes species is mediated by the stress response regulator SigB and driven by differential stress responsiveness. The tuning of SigB pathway responsiveness is polygenic and influenced by multiple, individually rare gene variations. This study reveals an overarching determinant of microbial virulence, challenging the paradigm of accessory virulence gene content as the major determinant of intraspecies virulence heterogeneity.

Vibrio cholerae lineage and pangenome diversity varies geographically across Bangladesh over one year

Cholera is a diarrhoeal disease caused by Vibrio cholerae. It remains a major public health challenge in the endemic region around the Bay of Bengal. Over decadal time scales, one lineage typically dominates the others and spreads in global pandemic waves. However, it remains unclear to what extent diverse lineages co-circulate during a single outbreak season. Defining the pool of diversity during finer time scales is important because the selective pressures that impact V. cholerae - namely antibiotics and phages - are dynamic on these time scales. To study the nationwide diversity of V. cholerae, we long-read sequenced 273 V. cholerae genomes from seven hospitals over one year (2018) in Bangladesh. Four major V. cholerae lineages were identified: known lineages BD-1, BD-2a, and BD-2b, and a novel lineage that we call BD-3. In 2022, BD-1 caused a large cholera outbreak in Dhaka, apparently outcompeting BD-2 lineages. We show that, in 2018, BD-1 was already dominant in the five northern regions, including Dhaka, consistent with an origin from India in the north. By contrast, we observed a higher diversity of lineages in the two southern regions near the coast. The four lineages differed in pangenome content, including integrative and conjugative elements (ICEs) and genes involved in resistance to bacteriophages and antibiotics. Notably, BD-2a lacked an ICE and is predicted to be more sensitive to phages and antibiotics, but nevertheless persisted throughout the year-long sampling period. Genes associated with antibiotic resistance in V. cholerae from Bangladesh in 2006 were entirely absent from all lineages in 2018-19, suggesting shifting costs and benefits of encoding these genes. Together, our results highlight the dynamic nature of the V. cholerae pangenome and the geographic structure of its lineage diversity.

Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2

Public health researchers and practitioners commonly infer phylogenies from viral genome sequences to understand transmission dynamics and identify clusters of genetically-related samples. However, viruses that reassort or recombine violate phylogenetic assumptions and require more sophisticated methods. Even when phylogenies are appropriate, they can be unnecessary or difficult to interpret without specialty knowledge. For example, pairwise distances between sequences can be enough to identify clusters of related samples or assign new samples to existing phylogenetic clusters. In this work, we tested whether dimensionality reduction methods could capture known genetic groups within two human pathogenic viruses that cause substantial human morbidity and mortality and frequently reassort or recombine, respectively: seasonal influenza A/H3N2 and SARS-CoV-2. We applied principal component analysis, multidimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection to sequences with well-defined phylogenetic clades and either reassortment (H3N2) or recombination (SARS-CoV-2). For each low-dimensional embedding of sequences, we calculated the correlation between pairwise genetic and Euclidean distances in the embedding and applied a hierarchical clustering method to identify clusters in the embedding. We measured the accuracy of clusters compared to previously defined phylogenetic clades, reassortment clusters, or recombinant lineages. We found that MDS embeddings accurately represented pairwise genetic distances including the intermediate placement of recombinant SARS-CoV-2 lineages between parental lineages. Clusters from t-SNE embeddings accurately recapitulated known phylogenetic clades, H3N2 reassortment groups, and SARS-CoV-2 recombinant lineages. We show that simple statistical methods without a biological model can accurately represent known genetic relationships for relevant human pathogenic viruses. Our open source implementation of these methods for analysis of viral genome sequences can be easily applied when phylogenetic methods are either unnecessary or inappropriate.

MosAIC: An annotated collection of mosquito-associated bacteria with high-quality genome assemblies

Mosquitoes transmit medically important human pathogens, including viruses like dengue virus and parasites such as Plasmodium spp., the causative agent of malaria. Mosquito microbiomes are critically important for the ability of mosquitoes to transmit disease-causing agents. However, while large collections of bacterial isolates and genomic data exist for vertebrate microbiomes, the vast majority of work in mosquitoes to date is based on 16S rRNA gene amplicon data that provides limited taxonomic resolution and no functional information. To address this gap and facilitate future studies using experimental microbiome manipulations, we generated a bacterial Mosquito-Associated Isolate Collection (MosAIC) consisting of 392 bacterial isolates with extensive metadata and high-quality draft genome assemblies that are publicly available, both isolates and sequence data, for use by the scientific community. MosAIC encompasses 142 species spanning 29 bacterial families, with members of the Enterobacteriaceae comprising 40% of the collection. Phylogenomic analysis of 3 genera, Enterobacter, Serratia, and Elizabethkingia, reveal lineages of mosquito-associated bacteria isolated from different mosquito species in multiple laboratories. Investigation into species' pangenomes further reveals clusters of genes specific to these lineages, which are of interest for future work to test for functions connected to mosquito host association. Altogether, we describe the generation of a physical collection of mosquito-associated bacterial isolates, their genomic data, and analyses of selected groups in context of genome data from closely related isolates, providing a unique, highly valuable resource for research on bacterial colonisation and adaptation within mosquito hosts. Future efforts will expand the collection to include broader geographic and host species representation, especially from individuals collected from field populations, as well as other mosquito-associated microbes, including fungi, archaea, and protozoa.

Development of a Providencia stuartii multilocus sequence typing scheme

Introduction

The Providencia genus is assuming greater clinical relevance among infections caused by Enterobacterales also because of its intrinsic and acquired resistance to last-resort antibiotics. However, despite having been known and studied for over 50 years, genomics and taxonomy of the Providencia genus are currently undergoing a deep rearrangement. In this study we aim to outline and characterized the P. stuartii species.

Methods

We retrieved from the GenBank database all genomes labelled as Providencia and performed a comprehensive genome-based species definition founded on average nucleotide identity (ANI) and on alignment-free approaches.

Results

After defining the genomes assuredly identifiable as P. stuartii, we devised a MultiLocus Sequence Typing (MLST) and a core-genome MLST (cgMLST) schemes, based on 7 and 2,296 loci respectively.

Discussion

This work hence provides a framework for understanding the role of P. stuartii and of other members of this genus, which should be considered as emerging multidrug-resistant pathogens.

Seamless, rapid, and accurate analyses of outbreak genomic data using split k-mer analysis

Sequence variation observed in populations of pathogens can be used for important public health and evolutionary genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long-term storage and processing of large files. Here we describe split k-mer analysis (SKA2), a method that supports both reference-free and reference-based mapping to quickly and accurately genotype populations of bacteria using sequencing reads or genome assemblies. SKA2 is highly accurate for closely related samples, and in outbreak simulations, we show superior variant recall compared with reference-based methods, with no false positives. SKA2 can also accurately map variants to a reference and be used with recombination detection methods to rapidly reconstruct vertical evolutionary history. SKA2 is many times faster than comparable methods and can be used to add new genomes to an existing call set, allowing sequential use without the need to reanalyze entire collections. With an inherent absence of reference bias, high accuracy, and a robust implementation, SKA2 has the potential to become the tool of choice for genotyping bacteria. SKA2 is implemented in Rust and is freely available as open-source software.

A genome-based survey of invasive pneumococci in Norway over four decades reveals lineage-specific responses to vaccination

BACKGROUND

Streptococcus pneumoniae is a major cause of mortality globally. The introduction of pneumococcal conjugate vaccines (PCVs) has reduced the incidence of the targeted serotypes significantly, but expansion of non-targeted serotypes, serotype replacement, and incomplete vaccine-targeting contribute to pneumococcal disease in the vaccine era. Here, we characterize the changing population genetic landscape of S. pneumoniae in Norway over a 41-year period (1982-2022).

METHODS

Since 2018, all cases of invasive pneumococcal disease have undergone whole-genome sequencing (WGS) at the Norwegian Institute of Public Health. In order to characterize the changing population over time, historical isolates were re-cultured and sequenced, resulting in a historical WGS dataset. Isolates were assigned to global pneumococcal sequence clusters (GPSCs) using PathogenWatch and assigned to serotypes using in silico (SeroBA) and in vitro methods (Quellung reaction). Temporal phylogenetic analyses were performed on GPSCs of particular interest.

RESULTS

The availability of WGS data allowed us to study capsular variation at the level of individual lineages. We detect highly divergent fates for different GPSCs following the introduction of PCVs. For two out of eight major GPSCs, we identified multiple instances of serotype switching from vaccine types to non-vaccine types. Dating analyses suggest that most instances of serotype switching predated the introduction of PCVs, but expansion occurred after their introduction. Furthermore, selection for penicillin non-susceptibility was not a driving force for the changing serotype distribution within the GPSCs over time.

CONCLUSIONS

PCVs have been major shapers of the Norwegian disease-causing pneumococcal population, both at the level of serotype distributions and the underlying lineage dynamics. Overall, the introduction of PCVs has reduced the incidence of invasive disease. However, some GPSCs initially dominated by vaccine types escaped the effect of vaccination through expansion of non-vaccine serotypes. Close monitoring of circulating lineages and serotypes will be key for ensuring optimal vaccination coverage going forward.

Genetic variation, structural analysis, and virulence implications of BimA and BimC in clinical isolates of Burkholderia pseudomallei in Thailand

Melioidosis is a life-threatening tropical disease caused by an intracellular gram-negative bacterium Burkholderia pseudomallei. B. pseudomallei polymerizes the host cell actin through autotransporters, BimA, and BimC, to facilitate intracellular motility. Two variations of BimA in B. pseudomallei have been reported previously: BimABp and BimA B. mallei-like (BimABm). However, little is known about genetic sequence variations within BimA and BimC, and their potential effect on the virulence of B. pseudomallei. This study analyzed 1,294 genomes from clinical isolates of patients admitted to nine hospitals in northeast Thailand between 2015 and 2018 and performed 3D structural analysis and plaque-forming efficiency assay. The genomic analysis identified 10 BimABp and 5 major BimC types, in the dominant and non-dominant lineages of the B. pseudomallei population structure. Our protein prediction analysis of all BimABp and major BimC variants revealed that their 3D structures were conserved compared to those of B. pseudomallei K96243. Sixteen representative strains of the most distant BimABp types were tested for plaque formation and the development of polar actin tails in A549 epithelial cells. We found that all isolates retained these functions. These findings enhance our understanding of the prevalence of BimABp and BimC variants and their implications for B. pseudomallei virulence.

Prediction of post-PCV13 pneumococcal evolution using invasive disease data enhanced by inverse-invasiveness weighting

After introducing pneumococcal conjugate vaccines (PCVs), serotype replacement occurred in Streptococcus pneumoniae. Predicting which pneumococcal strains will become common in carriage after vaccination can enhance vaccine design, public health interventions, and understanding of pneumococcal evolution. Invasive pneumococcal isolates were collected during 1998-2018 by the Active Bacterial Core surveillance (ABCs). Carriage data from Massachusetts (MA) and Southwest United States were used to calculate weights. Using pre-vaccine data, serotype-specific inverse-invasiveness weights were defined as the ratio of the proportion of the serotype in carriage to the proportion in invasive data. Genomic data were processed under bioinformatic pipelines to define genetically similar sequence clusters (i.e., strains), and accessory genes (COGs) present in 5-95% of isolates. Weights were applied to adjust observed strain proportions and COG frequencies. The negative frequency-dependent selection (NFDS) model predicted strain proportions by calculating the post-vaccine strain composition in the weighted invasive disease population that would best match pre-vaccine COG frequencies. Inverse-invasiveness weighting increased the correlation of COG frequencies between invasive and carriage data in linear or logit scale for pre-vaccine, post-PCV7, and post-PCV13; and between different epochs in the invasive data. Weighting the invasive data significantly improved the NFDS model's accuracy in predicting strain proportions in the carriage population in the post-PCV13 epoch, with the adjusted R2 increasing from 0.254 before weighting to 0.545 after weighting. The weighting system adjusted invasive disease data to better represent the pneumococcal carriage population, allowing the NFDS mechanism to predict strain proportions in carriage in the post-PCV13 epoch. Our methods enrich the value of genomic sequences from invasive disease surveillance.IMPORTANCEStreptococcus pneumoniae, a common colonizer in the human nasopharynx, can cause invasive diseases including pneumonia, bacteremia, and meningitis mostly in children under 5 years or older adults. The PCV7 was introduced in 2000 in the United States within the pediatric population to prevent disease and reduce deaths, followed by PCV13 in 2010, PCV15 in 2022, and PCV20 in 2023. After the removal of vaccine serotypes, the prevalence of carriage remained stable as the vacated pediatric ecological niche was filled with certain non-vaccine serotypes. Predicting which pneumococcal clones, and which serotypes, will be most successful in colonization after vaccination can enhance vaccine design and public health interventions, while also improving our understanding of pneumococcal evolution. While carriage data, which are collected from the pneumococcal population that is competing to colonize and transmit, are most directly relevant to evolutionary studies, invasive disease data are often more plentiful. Previously, evolutionary models based on negative frequency-dependent selection (NFDS) on the accessory genome were shown to predict which non-vaccine strains and serotypes were most successful in colonization following the introduction of PCV7. Here, we show that an inverse-invasiveness weighting system applied to invasive disease surveillance data allows the NFDS model to predict strain proportions in the projected carriage population in the post-PCV13/pre-PCV15 and pre-PCV20 epoch. The significance of our research lies in using a sample of invasive disease surveillance data to extend the use of NFDS as an evolutionary mechanism to predict post-PCV13 population dynamics. This has shown that we can correct for biased sampling that arises from differences in virulence and can enrich the value of genomic data from disease surveillance and advance our understanding of how NFDS impacts carriage population dynamics after both PCV7 and PCV13 vaccination.

Genomic and phenotypic imprints of microbial domestication on cheese starter cultures

Domestication - the artificial selection of wild species to obtain variants with traits of human interest - was integral to the rise of complex societies. The oversupply of food was probably associated with the formalization of food preservation strategies through microbial fermentation. While considerable literature exists on the antiquity of fermented food, only few eukaryotic microbes have been studied so far for signs of domestication, less is known for bacteria. Here, we tested if cheese starter cultures harbour typical hallmarks of domestication by characterising over 100 community samples and over 100 individual strains isolated from historical and modern traditional Swiss cheese starter cultures. We find that cheese starter cultures have low genetic diversity both at the species and strain-level and maintained stable phenotypic traits. Molecular clock dating further suggests that the evolutionary origin of the bacteria approximately coincided with the first archaeological records of cheese making. Finally, we find evidence for ongoing genome decay and pseudogenization via transposon insertion related to a reduction of their niche breadth. Future work documenting the prevalence of these hallmarks across diverse fermented food systems and geographic regions will be key to unveiling the joint history of humanity with fermented food microbes.

Pneumococcal carriage and changes in serotype distribution post- PCV13 introduction in children in Matiari, Pakistan

BACKGROUND

In early 2021, the 10-valent Pneumococcal conjugate vaccine (PCV10) was replaced with 13-valent (PCV13) by the federal directorate of immunization (FDI), Pakistan. We assessed the impact of a higher valent vaccine, PCV13, on the serotype distribution of nasopharyngeal carriage in rural Pakistan.

METHODS

Children <2 years were randomly selected from two rural union councils of Matiari, Sindh in Pakistan between September-October,2022. Clinical, sociodemographic and vaccination histories were recorded. Nasopharyngeal swabs were collected and processed at Infectious Disease Research Laboratory, Aga Khan University, Karachi. Whole genome sequencing was performed on the culture positive isolates.

RESULTS

Of the 200 children enrolled, pneumococcus was detected in 140(70 %) isolates. Majority of age-eligible children (60.1 %,110/183) received 3 PCV13 doses. PCV10 carriage declined from 13.2 %(78/590) in 2017/18 to 7.2 % (10/140) in 2022, additional PCV13 serotypes (3, 6A/6C and 19A) decreased from 18.5 %(109/590) to 11.4 %(16/140) while non-PCV13 serotypes increased from 68.3 %(403/590) to 81.4 %(114/140). There were 88.5 %(n = 124), 80.7 %(n = 113), 55.0 %(n = 77), and 46.0 %(n = 65) isolates predicted to be resistant to cotrimoxazole, penicillin(meningitis cut-off), tetracycline, and erythromycin respectively.

CONCLUSION

Replacing PCV10 with PCV13 rapidly decreased prevalence of PCV13 carriage among vaccinated children in Matiari, Pakistan. Vaccine-driven selection pressure may have been responsible for the increase of non-PCV13 serotypes.

Pan-pathogen deep sequencing of nosocomial bacterial pathogens in Italy in spring 2020: a prospective cohort study

BACKGROUND

Nosocomial infections pose a considerable risk to patients who are susceptible, and this is particularly acute in intensive care units when hospital-associated bacteria are endemic. During the first wave of the COVID-19 pandemic, the surge of patients presented a significant obstacle to the effectiveness of infection control measures. We aimed to assess the risks and extent of nosocomial pathogen transmission under a high patient burden by designing a novel bacterial pan-pathogen deep-sequencing approach that could be integrated with standard clinical surveillance and diagnostics workflows.

METHODS

We did a prospective cohort study in a region of northern Italy that was severely affected by the first wave of the COVID-19 pandemic. Inpatients on both ordinary and intensive care unit (ICU) wards at the San Matteo hospital, Pavia were sampled on multiple occasions to identify bacterial pathogens from respiratory, nasal, and rectal samples. Diagnostic samples collected between April 7 and May 10, 2020 were cultured on six different selective media designed to enrich for Acinetobacter baumannii, Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae, and DNA from each plate with positive growth was deep sequenced en masse. We used mSWEEP and mGEMS to bin sequencing reads by sequence cluster for each species, followed by mapping with snippy to generate high quality alignments. Antimicrobial resistance genes were detected by use of ARIBA and CARD. Estimates of hospital transmission were obtained from pairwise bacterial single nucleotide polymorphism distances, partitioned by within-patient and between-patient samples. Finally, we compared the accuracy of our binned Acinetobacter baumannii genomes with those obtained by single colony whole-genome sequencing of isolates from the same hospital.

FINDINGS

We recruited patients from March 1 to May 7, 2020. The pathogen population among the patients was large and diverse, with 2148 species detections overall among the 2418 sequenced samples from the 256 patients. In total, 55 sequence clusters from key pathogen species were detected at least five times. The antimicrobial resistance gene prevalence was correspondingly high, with key carbapenemase and extended spectrum ß-lactamase genes detected in at least 50 (40%) of 125 patients in ICUs. Using high-resolution mapping to infer transmission, we established that hospital transmission was likely to be a significant mode of acquisition for each of the pathogen species. Finally, comparison with single colony Acinetobacter baumannii genomes showed that the resolution offered by deep sequencing was equivalent to single-colony sequencing, with the additional benefit of detection of co-colonisation of highly similar strains.

INTERPRETATION

Our study shows that a culture-based deep-sequencing approach is a possible route towards improving future pathogen surveillance and infection control at hospitals. Future studies should be designed to directly compare the accuracy, cost, and feasibility of culture-based deep sequencing with single colony whole-genome sequencing on a range of bacterial species.

FUNDING

Wellcome Trust, European Research Council, Academy of Finland Flagship program, Trond Mohn Foundation, and Research Council of Norway.

Impact of pneumococcal conjugate vaccines on invasive pneumococcal disease-causing lineages among South African children

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.

CC180 clade dynamics do not universally explain Streptococcus pneumoniae serotype 3 persistence post-vaccine: a global comparative population genomics study

Background Clonal complex 180 (CC180) is currently the major clone of serotype 3 Streptococcus pneumoniae (Spn). The 13-valent pneumococcal conjugate vaccine (PCV13) does not have significant efficacy against serotype 3 despite polysaccharide inclusion in the vaccine. It was hypothesized that PCV13 may effectively control Clade I of CC180 but that Clades III and IV are resistant, provoking a population shift that enables serotype 3 persistence. This has been observed in the United States, England, and Wales but not Spain. We tested this hypothesis further utilizing a dataset from Portugal. Methods We whole-genome sequenced (WGS) 501 serotype 3 strains from Portugal isolated from patients with pneumococcal infections between 1999-2020. The draft genomes underwent phylogenetic analyses, pangenome profiling, and a genome-wide association study (GWAS). We also completed antibiotic susceptibility testing and compiled over 2,600 serotype 3 multilocus sequence type 180 (MLST180) WGSs to perform global comparative genomics. Findings CC180 Clades I, II, III, IV, and VI distributions were similar when comparing non-invasive pneumonia isolates and invasive disease isolates (Fisher's exact test, P=0.29), and adult and pediatric cases (Fisher's exact test, P=0.074). The serotype 3 CCs shifted post-PCV13 (Fisher's exact test, P<0.0001) and Clade I became dominant. Clade I is largely antibiotic-sensitive and carries the phiOXC141 prophage but the pangenome is heterogenous. Strains from Portugal and Spain, where Clade I remains dominant post-PCV13, have larger pangenomes and are associated with the presence of two genes encoding hypothetical proteins. Interpretation Clade I became dominant in Portugal post-PCV13, despite the burden of the prophage and antibiotic sensitivity. The accessory genome content may mitigate these fitness costs. Regional differences in Clade I prevalence and pangenome heterogeneity suggest that clade dynamics is not a generalizable approach to understanding serotype 3 vaccine escape. Funding National Institute of Child Health and Human Development, Pfizer, and Merck Sharp & Dohme.

Streptococcus pneumoniae carriage, serotypes, genotypes, and antimicrobial resistance trends among children in Portugal, after introduction of PCV13 in National Immunization Program: A cross-sectional study

Streptococcus pneumoniae carriage studies are crucial to monitor changes induced by use of pneumococcal conjugate vaccines and inform vaccination policies. In this cross-sectional study, we examined changes within the pneumococcal population following introduction of PCV13 in 2015 in the National Immunization Program (NIP), in Portugal. In 2018-2020 (NIP-PCV13), we obtained 1450 nasopharyngeal samples from children ≤6 years attending day-care. We assessed serotypes, antimicrobial resistance, and genotypes (MLST and GPSC) and compared findings with earlier periods: 2009-2010 (pre-PCV13), 2011-2012 (early-PCV13), and 2015-2016 (late-PCV13). Pneumococcal carriage prevalence remained stable at 60.2 %. Carriage of PCV13 serotypes was 10.7 %, markedly reduced compared to pre-PCV13 period (47.6 %). The most prevalent PCV13 serotypes were 19F, 3, and 19A all showing a significant decreasing trend compared to the pre-PCV13 period (from 7.1 % to 4.7 %, 10.1 % to 1.8 %, and 14.1 % to 1.8 %, respectively), a notable observation given the described limited effectiveness of PCV13 against serotype 3. Non-vaccinated children and children aged 4-6 years were more likely to carry PCV13 serotypes (2.5-fold, 95 %CI [1.1-5.6], and 2.9-fold, 95 %CI [1.3-6.8], respectively). The most prevalent non-PCV13 serotypes were 15B/C, 11A, 23B, 23A, and NT, collectively accounting for 51.9 % of all isolates. In total, 30.5 % of all pneumococci were potentially covered by PCV20. Resistance to penicillin (low-level) and macrolides increased significantly, from 9.3 % and 13.4 %, respectively, in the late-PCV13 period, to approximately 20 % each, mostly due to lineages expressing non-PCV13 serotypes, nearing pre-PCV13 levels. An expansion of lineages traditionally associated with PCV13 serotypes, like CC156-GPSC6 (serotype 14) and CC193-GPSC11 (serotype 19F), but now predominantly expressing non-PCV13 serotypes (11A, 15B/C, and 24F for GPSC6; and 15A and 21 for GPSC11) was noted. These findings indicate that the pneumococcal population is adapting to the pressures conferred by PCV13 and antimicrobial use and indicate the need to maintain close surveillance.

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.

Population genomics of Streptococcus mitis in UK and Ireland bloodstream infection and infective endocarditis cases

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

Towards quantifying plasmid similarity

Plasmids are extrachromosomal replicons which can quickly spread resistance and virulence genes between clinical pathogens. From the tens of thousands of currently available plasmid sequences we know that overall plasmid diversity is structured, with related plasmids sharing a largely conserved 'backbone' of genes while being able to carry very different genetic cargo. Moreover, plasmid genomes can be structurally plastic and undergo frequent rearrangements. So, how can we quantify plasmid similarity? Answering this question requires practical efforts to sample natural variation as well as theoretical considerations of what defines a group of related plasmids. Here we consider the challenges of analysing and rationalising the current plasmid data deluge to define appropriate similarity thresholds.

Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2

Public health researchers and practitioners commonly infer phylogenies from viral genome sequences to understand transmission dynamics and identify clusters of genetically-related samples. However, viruses that reassort or recombine violate phylogenetic assumptions and require more sophisticated methods. Even when phylogenies are appropriate, they can be unnecessary or difficult to interpret without specialty knowledge. For example, pairwise distances between sequences can be enough to identify clusters of related samples or assign new samples to existing phylogenetic clusters. In this work, we tested whether dimensionality reduction methods could capture known genetic groups within two human pathogenic viruses that cause substantial human morbidity and mortality and frequently reassort or recombine, respectively: seasonal influenza A/H3N2 and SARS-CoV-2. We applied principal component analysis (PCA), multidimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection (UMAP) to sequences with well-defined phylogenetic clades and either reassortment (H3N2) or recombination (SARS-CoV-2). For each low-dimensional embedding of sequences, we calculated the correlation between pairwise genetic and Euclidean distances in the embedding and applied a hierarchical clustering method to identify clusters in the embedding. We measured the accuracy of clusters compared to previously defined phylogenetic clades, reassortment clusters, or recombinant lineages. We found that MDS embeddings accurately represented pairwise genetic distances including the intermediate placement of recombinant SARS-CoV-2 lineages between parental lineages. Clusters from t-SNE embeddings accurately recapitulated known phylogenetic clades, H3N2 reassortment groups, and SARS-CoV-2 recombinant lineages. We show that simple statistical methods without a biological model can accurately represent known genetic relationships for relevant human pathogenic viruses. Our open source implementation of these methods for analysis of viral genome sequences can be easily applied when phylogenetic methods are either unnecessary or inappropriate.

Mobile genetic elements define the non-random structure of the Salmonella enterica serovar Typhi pangenome

Bacterial relatedness measured using select chromosomal loci forms the basis of public health genomic surveillance. While approximating vertical evolution through this approach has proven exceptionally valuable for understanding pathogen dynamics, it excludes a fundamental dimension of bacterial evolution-horizontal gene transfer. Incorporating the accessory genome is the logical remediation and has recently shown promise in expanding epidemiological resolution for enteric pathogens. Employing k-mer-based Jaccard index analysis, and a novel genome length distance metric, we computed pangenome (i.e., core and accessory) relatedness for the globally important pathogen Salmonella enterica serotype Typhi (Typhi), and graphically express both vertical (homology-by-descent) and horizontal (homology-by-admixture) evolutionary relationships in a reticulate network of over 2,200 U.S. Typhi genomes. This analysis revealed non-random structure in the Typhi pangenome that is driven predominantly by the gain and loss of mobile genetic elements, confirming and expanding upon known epidemiological patterns, revealing novel plasmid dynamics, and identifying avenues for further genomic epidemiological exploration. With an eye to public health application, this work adds important biological context to the rapidly improving ways of analyzing bacterial genetic data and demonstrates the value of the accessory genome to infer pathogen epidemiology and evolution.IMPORTANCEGiven bacterial evolution occurs in both vertical and horizontal dimensions, inclusion of both core and accessory genetic material (i.e., the pangenome) is a logical step toward a more thorough understanding of pathogen dynamics. With an eye to public, and indeed, global health relevance, we couple contemporary tools for genomic analysis with decades of research on mobile genetic elements to demonstrate the value of the pangenome, known and unknown, annotated, and hypothetical, for stratification of Salmonella enterica serovar Typhi (Typhi) populations. We confirm and expand upon what is known about Typhi epidemiology, plasmids, and antimicrobial resistance dynamics, and offer new avenues of exploration to further deduce Typhi ecology and evolution, and ultimately to reduce the incidence of human disease.

Pangenome-spanning epistasis and coselection analysis via de Bruijn graphs

Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens Streptococcus pneumoniae and Enterococcus faecalis.

Comprehensive blueprint of Salmonella genomic plasticity identifies hotspots for pathogenicity genes

Understanding the dynamic evolution of Salmonella is vital for effective bacterial infection management. This study explores the role of the flexible genome, organised in regions of genomic plasticity (RGP), in shaping the pathogenicity of Salmonella lineages. Through comprehensive genomic analysis of 12,244 Salmonella spp. genomes covering 2 species, 6 subspecies, and 46 serovars, we uncover distinct integration patterns of pathogenicity-related gene clusters into RGP, challenging traditional views of gene distribution. These RGP exhibit distinct preferences for specific genomic spots, and the presence or absence of such spots across Salmonella lineages profoundly shapes strain pathogenicity. RGP preferences are guided by conserved flanking genes surrounding integration spots, implicating their involvement in regulatory networks and functional synergies with integrated gene clusters. Additionally, we emphasise the multifaceted contributions of plasmids and prophages to the pathogenicity of diverse Salmonella lineages. Overall, this study provides a comprehensive blueprint of the pathogenicity potential of Salmonella. This unique insight identifies genomic spots in nonpathogenic lineages that hold the potential for harbouring pathogenicity genes, providing a foundation for predicting future adaptations and developing targeted strategies against emerging human pathogenic strains.