Rapid expansion and international spread of M1UK in the post-pandemic UK upsurge of Streptococcus pyogenes.

The UK observed a marked increase in scarlet fever and invasive group A streptococcal infection in 2022 with severe outcomes in children and similar trends worldwide. Here we report lineage M1UK to be the dominant source of invasive infections in this upsurge. Compared with ancestral M1global strains, invasive M1UK strains exhibit reduced genomic diversity and fewer mutations in two-component regulator genes covRS. The emergence of M1UK is dated to 2008. Following a bottleneck coinciding with the COVID-19 pandemic, three emergent M1UK clades underwent rapid nationwide expansion, despite lack of detection in previous years. All M1UK isolates thus-far sequenced globally have a phylogenetic origin in the UK, with dispersal of the new clades in Europe. While waning immunity may promote streptococcal epidemics, the genetic features of M1UK point to a fitness advantage in pathogenicity, and a striking ability to persist through population bottlenecks.

Presence of phage-plasmids in multiple serovars of Salmonella enterica.

Evidence is accumulating in the literature that the horizontal spread of antimicrobial resistance (AMR) genes mediated by bacteriophages and bacteriophage-like plasmid (phage-plasmid) elements is much more common than previously envisioned. For instance, we recently identified and characterized a circular P1-like phage-plasmid harbouring a bla CTX-M-15 gene conferring extended-spectrum beta-lactamase (ESBL) resistance in Salmonella enterica serovar Typhi. As the prevalence and epidemiological relevance of such mechanisms has never been systematically assessed in Enterobacterales, in this study we carried out a follow-up retrospective analysis of UK Salmonella isolates previously sequenced as part of routine surveillance protocols between 2016 and 2021. Using a high-throughput bioinformatics pipeline we screened 47 784 isolates for the presence of the P1 lytic replication gene repL, identifying 226 positive isolates from 25 serovars and demonstrating that phage-plasmid elements are more frequent than previously thought. The affinity for phage-plasmids appears highly serovar-dependent, with several serovars being more likely hosts than others; most of the positive isolates (170/226) belonged to S. Typhimurium ST34 and ST19. The phage-plasmids ranged between 85.8 and 98.2 kb in size, with an average length of 92.1 kb; detailed analysis indicated a high amount of diversity in gene content and genomic architecture. In total, 132 phage-plasmids had the p0111 plasmid replication type, and 94 the IncY type; phylogenetic analysis indicated that both horizontal and vertical gene transmission mechanisms are likely to be involved in phage-plasmid propagation. Finally, phage-plasmids were present in isolates that were resistant and non-resistant to antimicrobials. In addition to providing a first comprehensive view of the presence of phage-plasmids in Salmonella, our work highlights the need for a better surveillance and understanding of phage-plasmids as AMR carriers, especially through their characterization with long-read sequencing.

RecGraph: recombination-aware alignment of sequences to variation graphs.

MOTIVATION: Bacterial genomes present more variability than human genomes, which requires important adjustments in computational tools that are developed for human data. In particular, bacteria exhibit a mosaic structure due to homologous recombinations, but this fact is not sufficiently captured by standard read mappers that align against linear reference genomes. The recent introduction of pangenomics provides some insights in that context, as a pangenome graph can represent the variability within a species. However, the concept of sequence-to-graph alignment that captures the presence of recombinations has not been previously investigated. RESULTS: In this paper, we present the extension of the notion of sequence-to-graph alignment to a variation graph that incorporates a recombination, so that the latter are explicitly represented and evaluated in an alignment. Moreover, we present a dynamic programming approach for the special case where there is at most a recombination-we implement this case as RecGraph. From a modeling point of view, a recombination corresponds to identifying a new path of the variation graph, where the new arc is composed of two halves, each extracted from an original path, possibly joined by a new arc. Our experiments show that RecGraph accurately aligns simulated recombinant bacterial sequences that have at most a recombination, providing evidence for the presence of recombination events. AVAILABILITY: Our implementation is open source and available at https://github.com/AlgoLab/RecGraph. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epistasis, core-genome disharmony, and adaptation in recombining bacteria.

Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome's co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background-facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.IMPORTANCEGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox: 0n one hand, promoting adaptation by conferring novel functionality; on the other, potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyze natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in functional networks in a recipient genome. The positive impact of two-gene interactions appears to be adaptive by expanding metabolic capacity and facilitating niche shifts through interspecific hybridization. This challenges conventional ideas and highlights the possibility of multiple-step evolution of multi-gene traits by interspecific introgression.

Understanding the potential role of whole genome sequencing (WGS) in managing patients with gonorrhoea: A systematic review of WGS use on human pathogens in individual patient care.

OBJECTIVES: The utility of whole genome sequencing (WGS) to inform sexually transmitted infection (STI) patient management is unclear. Timely WGS data might support clinical management of STIs by characterising epidemiological links and antimicrobial resistance profiles. We conducted a systematic review of clinical application of WGS to any human pathogen that may be transposable to gonorrhoea. METHODS: We searched six databases for articles published between 01/01/2010-06/02/2023 that reported on real/near real-time human pathogen WGS to inform clinical intervention. All article types from all settings were included. Findings were analysed using narrative synthesis. RESULTS: We identified 12,179 articles, of which eight reported applications to inform tuberculosis (n = 7) and gonorrhoea (n = 1) clinical patient management. WGS data were successfully used as an adjunct to clinical and epidemiological data to enhance contact-tracing (n = 2), inform antimicrobial therapy (n = 5) and identify cross-contamination (n = 1). WGS identified gonorrhoea transmission chains that were not established via partner notification. Future applications could include insights into pathogen exposure detected within sexual networks for targeted patient management. CONCLUSIONS: While there was some evidence of WGS use to provide individualised tuberculosis and gonorrhoea treatment, the eight identified studies contained few participants. Future research should focus on testing WGS intervention effectiveness and examining ethical considerations of STI WGS use.

KmerAperture: Retaining k-mer synteny for alignment-free extraction of core and accessory differences between bacterial genomes.

By decomposing genome sequences into k-mers, it is possible to estimate genome differences without alignment. Techniques such as k-mer minimisers, for example MinHash, have been developed and are often accurate approximations of distances based on full k-mer sets. These and other alignment-free methods avoid the large temporal and computational expense of alignment. However, these k-mer set comparisons are not entirely accurate within-species and can be completely inaccurate within-lineage. This is due, in part, to their inability to distinguish core polymorphism from accessory differences. Here we present a new approach, KmerAperture, which uses information on the k-mer relative genomic positions to determine the type of polymorphism causing differences in k-mer presence and absence between pairs of genomes. Single SNPs are expected to result in contiguous of k unique k-mers per genome. On the other hand, contiguous series > k may be caused by accessory differences of length S-k+1; when the start and end of the sequence are contiguous with homologous sequence. Alternatively, they may be caused by multiple SNPs within k bp from each other and KmerAperture can determine whether that is the case. To demonstrate use cases KmerAperture was benchmarked using datasets including a very low diversity simulated population with accessory content independent from the number of SNPs, a simulated population were SNPs are spatially dense, a moderately diverse real cluster of genomes (Escherichia coli ST1193) with a large accessory genome and a low diversity real genome cluster (Salmonella Typhimurium ST34). We show that KmerAperture can accurately distinguish both core and accessory sequence diversity without alignment, outperforming other k-mer based tools.

Detection of a historic reservoir of bedaquiline/clofazimine resistance-associated variants in Mycobacterium tuberculosis.

BACKGROUND: Drug resistance in tuberculosis (TB) poses a major ongoing challenge to public health. The recent inclusion of bedaquiline into TB drug regimens has improved treatment outcomes, but this advance is threatened by the emergence of strains of Mycobacterium tuberculosis (Mtb) resistant to bedaquiline. Clinical bedaquiline resistance is most frequently conferred by off-target resistance-associated variants (RAVs) in the mmpR5 gene (Rv0678), the regulator of an efflux pump, which can also confer cross-resistance to clofazimine, another TB drug. METHODS: We compiled a dataset of 3682 Mtb genomes, including 180 carrying variants in mmpR5, and its immediate background (i.e. mmpR5 promoter and adjacent mmpL5 gene), that have been associated to borderline (henceforth intermediate) or confirmed resistance to bedaquiline. We characterised the occurrence of all nonsynonymous mutations in mmpR5 in this dataset and estimated, using time-resolved phylogenetic methods, the age of their emergence. RESULTS: We identified eight cases where RAVs were present in the genomes of strains collected prior to the use of bedaquiline in TB treatment regimes. Phylogenetic reconstruction points to multiple emergence events and circulation of RAVs in mmpR5, some estimated to predate the introduction of bedaquiline. However, epistatic interactions can complicate bedaquiline drug-susceptibility prediction from genetic sequence data. Indeed, in one clade, Ile67fs (a RAV when considered in isolation) was estimated to have emerged prior to the antibiotic era, together with a resistance reverting mmpL5 mutation. CONCLUSIONS: The presence of a pre-existing reservoir of Mtb strains carrying bedaquiline RAVs prior to its clinical use augments the need for rapid drug susceptibility testing and individualised regimen selection to safeguard the use of bedaquiline in TB care and control.

Integrated analysis of patient networks and plasmid genomes reveals a regional, multi-species outbreak of carbapenemase-producing Enterobacterales carrying both blaIMP and mcr-9 genes.

BACKGROUND: Carbapenemase-producing Enterobacterales (CPE) are challenging in healthcare, with resistance to multiple classes of antibiotics. This study describes the emergence of IMP-encoding CPE amongst diverse Enterobacterales species between 2016 and 2019 across a London regional network. METHODS: We performed a network analysis of patient pathways, using electronic health records, to identify contacts between IMP-encoding CPE positive patients. Genomes of IMP-encoding CPE isolates were overlayed with patient contacts to imply potential transmission events. RESULTS: Genomic analysis of 84 Enterobacterales isolates revealed diverse species (predominantly Klebsiella spp, Enterobacter spp, E. coli); 86% (72/84) harboured an IncHI2 plasmid carrying blaIMP and colistin resistance gene mcr-9 (68/72). Phylogenetic analysis of IncHI2 plasmids identified three lineages showing significant association with patient contacts and movements between four hospital sites and across medical specialities, which was missed on initial investigations. CONCLUSIONS: Combined, our patient network and plasmid analyses demonstrate an interspecies, plasmid-mediated outbreak of blaIMPCPE, which remained unidentified during standard investigations. With DNA sequencing and multi-modal data incorporation, the outbreak investigation approach proposed here provides a framework for real-time identification of key factors causing pathogen spread. Plasmid-level outbreak analysis reveals that resistance spread may be wider than suspected, allowing more interventions to stop transmission within hospital networks.

Genomic epidemiology of the clinically dominant clonal complex 1 in the Listeria monocytogenes population in the UK.

Listeria monocytogenes is a food-borne pathogen, typically affecting the elderly, immunocompromised patients and pregnant women. The aim of this study was to determine the population structure of L. monocytogenes clonal complex 1 (CC1) in the UK and describe the genomic epidemiology of this clinically significant CC. We interrogated a working dataset of 4073 sequences of L. monocytogenes isolated between January 2015 and December 2020 from human clinical specimens, food and/or food-production environments. A minimum spanning tree was reconstructed to determine the population structure of L. monocytogenes in the UK. Subsequent analysis focused on L. monocytogenes CC1, as the cause of the highest proportion of invasive listeriosis in humans. Sequencing data was integrated with metadata on food and environmental isolates, and information from patient questionnaires, including age, sex and clinical outcomes. All isolates either belonged to lineage I (n=1299/4073, 32%) or lineage II (n=2774/4073, 68%), with clinical isolates from human cases more likely to belong to lineage I (n=546/928, 59%) and food isolates more likely to belong to lineage II (n=2352/3067, 77%). Of the four largest CCs, CC1 (n=237) had the highest proportion of isolates from human cases of disease (CC1 n=160/237, 67.5 %; CC121 n=13/843, 2 %; CC9 n=53/360, 15 %; CC2 n=69/339, 20%). Within CC1, most cases were female (n=95/160, 59%, P=0.01771) and the highest proportion of cases were in people >60 years old (39/95, 41%, P=1.314×10-6) with a high number of them aged 20-39 years old (n=35/95, 37%) most linked to pregnancy-related listeriosis (n=29/35, 83%). Most of the male cases were in men aged over 60 years old (40/65, 62%), and most of the fatal cases in both males and females were identified in this age group (42/55, 76%). Phylogenetic analysis revealed 23 5 SNP single linkage clusters comprising 80/237 (34 %) isolates with cluster sizes ranging from 2 to 19. Five 5 SNP clusters comprised isolates from human cases and an implicated food item. Expanding the analysis to 25 SNP single linkage clusters resolved an additional two clusters linking human cases to a potential food vehicle. Analysis of demographic and clinical outcome data identified CC1 as a clinically significant cause of invasive listeriosis in the elderly population and in women of child-bearing age. Phylogenetic analysis revealed the population structure of CC1 in the UK comprised small, sparsely populated genomic clusters. Only clusters containing isolates from an implicated food vehicle, or food processing or farming environments, were resolved, emphasizing the need for clinical, food and animal-health agencies to share sequencing data in real time, and the importance of a One Health approach to public-health surveillance of listeriosis.

Inference of Infectious Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes Per Host.

In recent times, pathogen genome sequencing has become increasingly used to investigate infectious disease outbreaks. When genomic data is sampled densely enough amongst infected individuals, it can help resolve who infected whom. However, transmission analysis cannot rely solely on a phylogeny of the genomes but must account for the within-host evolution of the pathogen, which blurs the relationship between phylogenetic and transmission trees. When only a single genome is sampled for each host, the uncertainty about who infected whom can be quite high. Consequently, transmission analysis based on multiple genomes of the same pathogen per host has a clear potential for delivering more precise results, even though it is more laborious to achieve. Here, we present a new methodology that can use any number of genomes sampled from a set of individuals to reconstruct their transmission network. Furthermore, we remove the need for the assumption of a complete transmission bottleneck. We use simulated data to show that our method becomes more accurate as more genomes per host are provided, and that it can infer key infectious disease parameters such as the size of the transmission bottleneck, within-host growth rate, basic reproduction number, and sampling fraction. We demonstrate the usefulness of our method in applications to real datasets from an outbreak of Pseudomonas aeruginosa amongst cystic fibrosis patients and a nosocomial outbreak of Klebsiella pneumoniae.

A smooth tubercle bacillus from Ethiopia phylogenetically close to the Mycobacterium tuberculosis complex.

The Mycobacterium tuberculosis complex (MTBC) includes several human- and animal-adapted pathogens. It is thought to have originated in East Africa from a recombinogenic Mycobacterium canettii-like ancestral pool. Here, we describe the discovery of a clinical tuberculosis strain isolated in Ethiopia that shares archetypal phenotypic and genomic features of M. canettii strains, but represents a phylogenetic branch much closer to the MTBC clade than to the M. canettii strains. Analysis of genomic traces of horizontal gene transfer in this isolate and previously identified M. canettii strains indicates a persistent albeit decreased recombinogenic lifestyle near the emergence of the MTBC. Our findings support that the MTBC emergence from its putative free-living M. canettii-like progenitor is evolutionarily very recent, and suggest the existence of a continuum of further extant derivatives from ancestral stages, close to the root of the MTBC, along the Great Rift Valley.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks.

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

During an infectious disease outbreak, tracing who infected whom allows public health scientists to see how a pathogen is spreading and to establish effective control measures. Traditionally, this involves identifying the individuals an infected person comes into contact with and monitoring whether they also become unwell. However, this information is not always available and can be inaccurate. One alternative is to track the genetic data of pathogens as they spread. Over time, pathogens accumulate mutations in their genes that can be used to distinguish them from one another. Genetically similar pathogens are more likely to have spread during the same outbreak, while genetically dissimilar pathogens may have come from different outbreaks. However, there are limitations to this approach. For example, some pathogens accumulate genetic mutations very slowly and may not change enough during an outbreak to be distinguishable from one another. Additionally, some pathogens can spread rapidly, leaving less time for mutations to occur between transmission events. To overcome these challenges, Torres Ortiz et al. developed a more sensitive approach to pathogen genetic testing that took advantage of the multiple pathogen populations that often coexist in an infected patient. Rather than tracking only the most dominant genetic version of the pathogen, this method also looked at the less dominant ones. Torres Ortiz et al. performed genome sequencing of SARS-CoV-2 (the virus that causes COVID-19) samples from 451 healthcare workers, patients, and patient contacts at participating London hospitals. Analysis showed that it was possible to detect multiple genetic populations of the virus within individual patients. These subpopulations were often more similar in patients that had been in contact with one another than in those that had not. Tracking the genetic data of all viral populations enabled Torres Ortiz et al. to trace transmission more accurately than if only the dominant population was used. More accurate genetic tracing could help public health scientists better track pathogen transmission and control outbreaks. This may be especially beneficial in hospital settings where outbreaks can be smaller, and it is important to understand if transmission is occurring within the hospital or if the pathogen is imported from the community. Further research will help scientists understand how pathogen population genetics evolve during outbreaks and may improve the detection of subpopulations present at very low frequencies.

Analysis of Escherichia coli O157 strains in cattle and humans between Scotland and England & Wales: implications for human health.

For the last two decades, the human infection frequency of Escherichia coli O157 (O157) in Scotland has been 2.5-fold higher than in England and Wales. Results from national cattle surveys conducted in Scotland and England and Wales in 2014/2015 were combined with data on reported human clinical cases from the same time frame to determine if strain differences in national populations of O157 in cattle could be associated with higher human infection rates in Scotland. Shiga toxin subtype (Stx) and phage type (PT) were examined within and between host (cattle vs human) and nation (Scotland vs England and Wales). For a subset of the strains, whole genome sequencing (WGS) provided further insights into geographical and host association. All three major O157 lineages (I, II, I/II) and most sub-lineages (Ia, Ib, Ic, IIa, IIb, IIc) were represented in cattle and humans in both nations. While the relative contribution of different reservoir hosts to human infection is unknown, WGS analysis indicated that the majority of O157 diversity in human cases was captured by isolates from cattle. Despite comparable cattle O157 prevalence between nations, strain types were localized. PT21/28 (sub-lineage Ic, Stx2a+) was significantly more prevalent in Scottish cattle [odds ratio (OR) 8.7 (2.3-33.7; P<0.001] and humans [OR 2.2 (1.5-3.2); P<0.001]. In England and Wales, cattle had a significantly higher association with sub-lineage IIa strains [PT54, Stx2c; OR 5.6 (1.27-33.3); P=0.011] while humans were significantly more closely associated with sub-lineage IIb [PT8, Stx1 and Stx2c; OR 29 (4.9-1161); P<0.001]. Therefore, cattle farms in Scotland were more likely to harbour Stx2a+O157 strains compared to farms in E and W (P<0.001). There was evidence of limited cattle strain migration between nations and clinical isolates from one nation were more similar to cattle isolates from the same nation, with sub-lineage Ic (mainly PT21/28) exhibiting clear national association and evidence of local transmission in Scotland. While we propose the higher rate of O157 clinical cases in Scotland, compared to England and Wales, is a consequence of the nationally higher level of Stx2a+O157 strains in Scottish cattle, we discuss the multiple additional factors that may also contribute to the different infection rates between these nations.

Estimating the fitness cost and benefit of antimicrobial resistance from pathogen genomic data.

Increasing levels of antibiotic resistance in many bacterial pathogen populations are a major threat to public health. Resistance to an antibiotic provides a fitness benefit when the bacteria are exposed to this antibiotic, but resistance also often comes at a cost to the resistant pathogen relative to susceptible counterparts. We lack a good understanding of these benefits and costs of resistance for many bacterial pathogens and antibiotics, but estimating them could lead to better use of antibiotics in a way that reduces or prevents the spread of resistance. Here, we propose a new model for the joint epidemiology of susceptible and resistant variants, which includes explicit parameters for the cost and benefit of resistance. We show how Bayesian inference can be performed under this model using phylogenetic data from susceptible and resistant lineages and that by combining data from both we are able to disentangle and estimate the resistance cost and benefit parameters separately. We applied our inferential methodology to several simulated datasets to demonstrate good scalability and accuracy. We analysed a dataset of Neisseria gonorrhoeae genomes collected between 2000 and 2013 in the USA. We found that two unrelated lineages resistant to fluoroquinolones shared similar epidemic dynamics and resistance parameters. Fluoroquinolones were abandoned for the treatment of gonorrhoea due to increasing levels of resistance, but our results suggest that they could be used to treat a minority of around 10% of cases without causing resistance to grow again.

Model design for nonparametric phylodynamic inference and applications to pathogen surveillance.

Inference of effective population size from genomic data can provide unique information about demographic history and, when applied to pathogen genetic data, can also provide insights into epidemiological dynamics. The combination of nonparametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for nonparametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on nonparametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. Our methodology is implemented in a new R package entitled mlesky. We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the methodology to a dataset of HIV-1 in the USA. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.

Phylogenetic analysis of the origin and spread of plague in Madagascar.

BACKGROUND: Plague is a zoonotic disease caused by the bacterium Yersinia pestis, highly prevalent in the Central Highlands, a mountainous region in the center of Madagascar. After a plague-free period of over 60 years in the northwestern coast city of Mahajanga, the disease reappeared in 1991 and caused several outbreaks until 1999. Previous research indicates that the disease was reintroduced to the city of Mahajanga from the Central Highlands instead of reemerging from a local reservoir. However, it is not clear how many reintroductions occurred and when they took place. METHODOLOGY/PRINCIPAL FINDINGS: In this study we applied a Bayesian phylogeographic model to detect and date migrations of Y. pestis between the two locations that could be linked to the re-emergence of plague in Mahajanga. Genome sequences of 300 Y. pestis strains sampled between 1964 and 2012 were analyzed. Four migrations from the Central Highlands to Mahajanga were detected. Two resulted in persistent transmission in humans, one was responsible for most of the human cases recorded between 1995 and 1999, while the other produced plague cases in 1991 and 1992. We dated the emergence of the Y. pestis sub-branch 1.ORI3, which is only present in Madagascar and Turkey, to the beginning of the 20th century, using a Bayesian molecular dating analysis. The split between 1.ORI3 and its ancestor lineage 1.ORI2 was dated to the second half of the 19th century. CONCLUSIONS/SIGNIFICANCE: Our results indicate that two independent migrations from the Central Highlands caused the plague outbreaks in Mahajanga during the 1990s, with both introductions occurring during the early 1980s. They happened over a decade before the detection of human cases, thus the pathogen likely survived in wild reservoirs until the spillover to humans was possible. This study demonstrates the value of Bayesian phylogenetics in elucidating the re-emergence of infectious diseases.

Phylogenetic Analysis of Bacterial Pathogen Genomes.

The development of high-throughput sequencing technology has led to a significant reduction in the time and cost of sequencing whole genomes of bacterial pathogens. Studies can sequence and compare hundreds or even thousands of genomes within a given bacterial population. A phylogenetic tree is the most frequently used method of depicting the relationships between these bacterial pathogen genomes. However, the presence of homologous recombination in most bacterial pathogen species can invalidate the application of standard phylogenetic tools. Here we describe a method to produce phylogenetic analyses that accounts for the disruptive effect of recombination. This allows users to investigate the recombination events that have occurred, as well as to produce more meaningful phylogenetic analyses which recover the clonal genealogy representing the clonal relationships between genomes.

Penicillin Binding Protein Substitutions Cooccur with Fluoroquinolone Resistance in Epidemic Lineages of Multidrug-Resistant Clostridioides difficile.

Clostridioides difficile remains a key cause of healthcare-associated infection, with multidrug-resistant (MDR) lineages causing high-mortality (≥20%) outbreaks. Cephalosporin treatment is a long-established risk factor, and antimicrobial stewardship is a key control. A mechanism underlying raised cephalosporin MICs has not been identified in C. difficile, but among other species, this is often acquired via amino acid substitutions in cell wall transpeptidases (penicillin binding proteins [PBPs]). Here, we investigated five C. difficile transpeptidases (PBP1 to PBP5) for recent substitutions, associated cephalosporin MICs, and co-occurrence with fluoroquinolone resistance. Previously published genome assemblies (n = 7,096) were obtained, representing 16 geographically widespread lineages, including healthcare-associated ST1(027). Recent amino acid substitutions were found within PBP1 (n = 50) and PBP3 (n = 48), ranging from 1 to 10 substitutions per genome. ß-Lactam MICs were measured for closely related pairs of wild-type and PBP-substituted isolates separated by 20 to 273 single nucleotide polymorphisms (SNPs). Recombination-corrected phylogenies were constructed to date substitution acquisition. Key substitutions such as PBP3 V497L and PBP1 T674I/N/V emerged independently across multiple lineages. They were associated with extremely high cephalosporin MICs; 1 to 4 doubling dilutions >wild-type, up to 1,506 µg/mL. Substitution patterns varied by lineage and clade, showed geographic structure, and occurred post-1990, coincident with the gyrA and/or gyrB substitutions conferring fluoroquinolone resistance. In conclusion, recent PBP1 and PBP3 substitutions are associated with raised cephalosporin MICs in C. difficile. Their co-occurrence with fluoroquinolone resistance hinders attempts to understand the relative importance of these drugs in the dissemination of epidemic lineages. Further controlled studies of cephalosporin and fluoroquinolone stewardship are needed to determine their relative effectiveness in outbreak control. IMPORTANCE Fluoroquinolone and cephalosporin use in healthcare settings has triggered outbreaks of high-mortality, multidrug-resistant C. difficile infection. Here, we identify a mechanism associated with raised cephalosporin MICs in C. difficile comprising amino acid substitutions in two cell wall transpeptidase enzymes (penicillin binding proteins). The higher the number of substitutions, the greater the impact on phenotype. Dated phylogenies revealed that substitutions associated with raised cephalosporin and fluoroquinolone MICs were co-acquired immediately before clinically important outbreak strains emerged. PBP substitutions were geographically structured within genetic lineages, suggesting adaptation to local antimicrobial prescribing. Antimicrobial stewardship of cephalosporins and fluoroquinolones is an effective means of C. difficile outbreak control. Genetic changes associated with raised MIC may impart a "fitness cost" after antibiotic withdrawal. Our study therefore identifies a mechanism that may explain the contribution of cephalosporin stewardship to resolving outbreak conditions. However, due to the co-occurrence of raised cephalosporin MICs and fluoroquinolone resistance, further work is needed to determine the relative importance of each.

Genomic Diversity among Actinomyces naeslundii Strains and Closely Related Species.

The aim of this study was to investigate and clarify the ambiguous taxonomy of Actinomyces naeslundii and its closely related species using state-of-the-art high-throughput sequencing techniques, and, furthermore, to determine whether sub-clusters identified within Actinomyces oris and Actinomyces naeslundii in a previous study by multi locus sequence typing (MLST) using concatenation of seven housekeeping genes should either be classified as subspecies or distinct species. The strains in this study were broadly classified under Actinomyces naeslundii group as A. naeslundii genospecies I and genospecies II. Based on MLST data analysis, these were further classified as A. oris and A. naeslundii. The whole genome sequencing of selected strains of A. oris (n = 17) and A. naeslundii (n = 19) was carried out using Illumina Genome Analyzer IIxe and Roche 454 allowing paired-end and single-reads sequencing, respectively. The sequences obtained were aligned using CLC Genomic workbench version 5.1 and annotated using RAST (Rapid Annotation using Subsystem Technology) release version 59 accessible online. Additionally, genomes of seven publicly available strains of Actinomyces (k20, MG1, c505, OT175, OT171, OT170, and A. johnsonii) were also included. Comparative genomic analysis (CGA) using Mauve, Progressive Mauve, gene-by-gene, Core, and Pan Genome, and finally Digital DNA-DNA homology (DDH) analysis was carried out. DDH values were obtained using in silico genome-genome comparison. Evolutionary analysis using ClonalFrame was also undertaken. The mutation and recombination events were compared using chi-square test among A. oris and A. naeslundii isolates (analysis methods are not included in the study). CGA results were consistent with previous traditional classification using MLST. It was found that strains of Actinomyces k20, MG1, c505, and OT175 clustered in A. oris group of isolates, while OT171, OT170, and A. johnsonii appeared as separate branches. Similar clustering to MLST was observed for other isolates. The mutation and recombination events were significantly higher in A. oris than A. naeslundii, highlighting the diversity of A. oris strains in the oral cavity. These findings suggest that A. oris forms six distinct groups, whereas A. naeslundii forms three. The correct designation of isolates will help in the identification of clinical Actinomyces isolates found in dental plaque. Easily accessible online genomic sequence data will also accelerate the investigation of the biochemical characterisation and pathogenesis of this important group of micro-organisms.

Epidemiological impacts of the NHS COVID-19 app in England and Wales throughout its first year.

The NHS COVID-19 app was launched in England and Wales in September 2020, with a Bluetooth-based contact tracing functionality designed to reduce transmission of SARS-CoV-2. We show that user engagement and the app's epidemiological impacts varied according to changing social and epidemic characteristics throughout the app's first year. We describe the interaction and complementarity of manual and digital contact tracing approaches. Results of our statistical analyses of anonymised, aggregated app data include that app users who were recently notified were more likely to test positive than app users who were not recently notified, by a factor that varied considerably over time. We estimate that the app's contact tracing function alone averted about 1 million cases (sensitivity analysis 450,000-1,400,000) during its first year, corresponding to 44,000 hospital cases (SA 20,000-60,000) and 9,600 deaths (SA 4600-13,000).