Improved characterisation of MRSA transmission using within-host bacterial sequence diversity

Within-host genomic evolution of methicillin-resistant Staphylococcus aureus in long-term carriers

Assessing the genomic evolution of Staphylococcus aureus can help us understand how the bacteria adapt to its environment. In this study, we aimed to assess the mutation rate within 144 methicillin-resistant Staphylococcus aureus (MRSA) carriers with a carriage time from 4 to 11 years, including some carriers who belonged to the same households. We found that 23 of the 144 individuals had completely different MRSA types over time and were therefore not long-term carriers of the same MRSA. From the remaining 121 individuals, we performed whole-genome sequencing (WGS) on 424 isolates and then compared these pairwise using core genome multilocus sequence typing (cgMLST) and single-nucleotide polymorphism (SNP) analyses. We found a median within-host mutation rate in long-term MRSA carriers of 4.9 (3.4-6.9) SNPs/genome/year and 2.7 (1.8-4.2) allelic differences/genome/year, when excluding presumed recombination. Furthermore, we stratified the cohort into subgroups and found no significant difference between the median mutation rate of members of households, individuals with presumed continued exposure, e.g., from travel and persons without known continued exposure. Finally, we found that SNPs occurred at random within the genes in our cohort. KEY POINTS: • Median mutation rate within long-term MRSA carriers of 4.9 (3.4-6.9) SNPs/genome/year • Similar median mutation rates in subgroups (households, travelers) • No hotspots for SNPs within the genome.

Expanding the use of mathematical modeling in healthcare epidemiology and infection prevention and control

During the coronavirus disease 2019 pandemic, mathematical modeling has been widely used to understand epidemiological burden, trends, and transmission dynamics, to facilitate policy decisions, and, to a lesser extent, to evaluate infection prevention and control (IPC) measures. This review highlights the added value of using conventional epidemiology and modeling approaches to address the complexity of healthcare-associated infections (HAI) and antimicrobial resistance. It demonstrates how epidemiological surveillance data and modeling can be used to infer transmission dynamics in healthcare settings and to forecast healthcare impact, how modeling can be used to improve the validity of interpretation of epidemiological surveillance data, how modeling can be used to estimate the impact of IPC interventions, and how modeling can be used to guide IPC and antimicrobial treatment and stewardship decision-making. There are several priority areas for expanding the use of modeling in healthcare epidemiology and IPC. Importantly, modeling should be viewed as complementary to conventional healthcare epidemiological approaches, and this requires collaboration and active coordination between IPC, healthcare epidemiology, and mathematical modeling groups.

Consideration of within-patient diversity highlights transmission pathways and antimicrobial resistance gene variability in vancomycin-resistant Enterococcus faecium

BACKGROUND

WGS is increasingly being applied to healthcare-associated vancomycin-resistant Enterococcus faecium (VREfm) outbreaks. Within-patient diversity could complicate transmission resolution if single colonies are sequenced from identified cases.

OBJECTIVES

Determine the impact of within-patient diversity on transmission resolution of VREfm.

MATERIALS AND METHODS

Fourteen colonies were collected from VREfm positive rectal screens, single colonies were collected from clinical samples and Illumina WGS was performed. Two isolates were selected for Oxford Nanopore sequencing and hybrid genome assembly to generate lineage-specific reference genomes. Mapping to closely related references was used to identify genetic variations and closely related genomes. A transmission network was inferred for the entire genome set using Phyloscanner.

RESULTS AND DISCUSSION

In total, 229 isolates from 11 patients were sequenced. Carriage of two or three sequence types was detected in 27% of patients. Presence of antimicrobial resistance genes and plasmids was variable within genomes from the same patient and sequence type. We identified two dominant sequence types (ST80 and ST1424), with two putative transmission clusters of two patients within ST80, and a single cluster of six patients within ST1424. We found transmission resolution was impaired using fewer than 14 colonies.

CONCLUSIONS

Patients can carry multiple sequence types of VREfm, and even within related lineages the presence of mobile genetic elements and antimicrobial resistance genes can vary. VREfm within-patient diversity could be considered in future to aid accurate resolution of transmission networks.

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.

Constructing an Interactive and Integrated Analysis and Identification Platform for Pathogenic Microorganisms to Support Surveillance Capacity

INTRODUCTION

Whole genome sequencing (WGS) holds significant promise for epidemiological inquiries, as it enables the identification and tracking of pathogenic origins and dissemination through comprehensive genome analysis. This method is widely preferred for investigating outbreaks and monitoring pathogen activity. However, the effective utilization of microbiome sequencing data remains a challenge for clinical and public health experts. Through the National Pathogen Resource Center, we have constructed a dynamic and interactive online analysis platform to facilitate the in-depth analysis and use of pathogen genomic data, by public health and associated professionals, to support infectious disease surveillance framework building and capacity warnings.

METHOD

The platform was implemented using the Java programming language, and the front-end pages were developed using the VUE framework, following the MVC (Model-View-Controller) pattern to enable interactive service functionalities for front-end data collection and back-end data computation. Cloud computing services were employed to integrate biological information analysis tools for conducting fundamental analysis on sequencing data.

RESULT

The platform achieved the goal of non-programming analysis, providing an interactive visual interface that allows users to visually obtain results by setting parameters in web pages. Moreover, the platform allows users to export results in various formats to further support their research.

DISCUSSION

We have established a dynamic and interactive online platform for bioinformatics analysis. By encapsulating the complex background experiments and analysis processes in a cloud-based service platform, the complex background experiments and analysis processes are presented to the end-user in a simple and interactive manner. It facilitates real-time data mining and analysis by allowing users to independently select parameters and generate analysis results at the click of a button, based on their needs, without the need for a programming foundation.

Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data

Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs - two hosts in which infection was transmitted from one to the other - is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts. In this work, we assess the utility of deep-sequenced genomic surveillance (where genomic regions are sequenced hundreds to thousands of times) using a mouse transmission model involving controlled spread of the pathogenic bacterium Citrobacter rodentium from infected to naïve female animals. We observe that within-host single nucleotide variants (iSNVs) are maintained over multiple transmission steps and present a model for inferring the likelihood that a given pair of sequenced samples are linked by transmission. In this work we show that, beyond the presence and absence of within-host variants, differences arising in the relative abundance of iSNVs (allelic frequency) can infer transmission pairs more precisely. Our approach further highlights the critical role bottlenecks play in reserving the within-host diversity during transmission.

Phylogenetic inference of pneumococcal transmission from cross-sectional data, a pilot study

Background: Inference on pneumococcal transmission has mostly relied on longitudinal studies which are costly and resource intensive. Therefore, we conducted a pilot study to test the ability to infer who infected whom from cross-sectional pneumococcal sequences using phylogenetic inference. Methods: Five suspected transmission pairs, for which there was epidemiological evidence of who infected whom, were selected from a household study. For each pair, Streptococcus pneumoniae full genomes were sequenced from nasopharyngeal swabs collected on the same day. The within-host genetic diversity of the pneumococcal population was used to infer the transmission direction and then cross-validated with the direction suggested by the epidemiological records. Results: The pneumococcal genomes clustered into the five households from which the samples were taken. The proportion of concordantly inferred transmission direction generally increased with increasing minimum genome fragment size and single nucleotide polymorphisms. We observed a larger proportion of unique polymorphic sites in the source bacterial population compared to that of the recipient in four of the five pairs, as expected in the case of a transmission bottleneck. The only pair that did not exhibit this effect was also the pair that had consistent discordant transmission direction compared to the epidemiological records suggesting potential misdirection as a result of false-negative sampling. Conclusions: This pilot provided support for further studies to test if the direction of pneumococcal transmission can be reliably inferred from cross-sectional samples if sequenced with sufficient depth and fragment length.

Diversity and Persistence of MRSA and VRE in Skilled Nursing Facilities: Environmental Screening, Whole Genome Sequencing, Development of a Dispersion Index

BACKGROUND

Environmental contamination with methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) in skilled nursing facilities (SNFs) may contribute to patient acquisition. We assessed diversity and association of MRSA and VRE isolates in a SNF wing and developed a mathematical index to define each strain's tendency to persist in rooms and spread horizontally.

METHODS

Longitudinal study of MRSA and VRE colonization and contamination among successive patient occupancies in a cluster of nine SNF private rooms during eight months characterized by microbiological testing and whole genome isolate typing. 'Dispersion index" of a strain is defined as the number of rooms it was found in (including the patient), divided by the average of times it was found consecutively in the same room.

FINDINGS

MRSA (ten strain types) and VRE (seven types) were recovered from room or patient in 16.4% and 35.6% of the occupancies, respectively. MRSA showed moderate horizontal spread and several episodes of same-room persistence (three distinct strain types) (overall dispersion index: 1.08). VRE showed high tendency towards horizontal spread /new introductions (overall dispersion index: 3.25), and only one confirmed persistence episode.

INTERPRETATION

The emerging picture of high diversity among contaminating strains and high likelihood of room persistence despite terminal cleaning (MRSA) and horizontal spread between rooms (VRE) in this setting calls for improved cleaning practices, heightened contact precautions, and most of all to establish individually tailored facility screening programs to enable informed choices based on local, measurable and actionable epidemiologic parameters.

FUNDING

University of Michigan OAIC REC Scholarship to M.C. National Institutes of Health K24 AG050685 to L.M.

Staphylococcal diversity in atopic dermatitis from an individual to a global scale

Atopic dermatitis (AD) is a multifactorial, chronic relapsing disease associated with genetic and environmental factors. Among skin microbes, Staphylococcus aureus and Staphylococcus epidermidis are associated with AD, but how genetic variability and staphylococcal strains shape the disease remains unclear. We investigated the skin microbiome of an AD cohort (n = 54) as part of a prospective natural history study using shotgun metagenomic and whole genome sequencing, which we analyzed alongside publicly available data (n = 473). AD status and global geographical regions exhibited associations with strains and genomic loci of S. aureus and S. epidermidis. In addition, antibiotic prescribing patterns and within-household transmission between siblings shaped colonizing strains. Comparative genomics determined that S. aureus AD strains were enriched in virulence factors, whereas S. epidermidis AD strains varied in genes involved in interspecies interactions and metabolism. In both species, staphylococcal interspecies genetic transfer shaped gene content. These findings reflect the staphylococcal genomic diversity and dynamics associated with AD.

Staphylococcus aureus host interactions and adaptation

Invasive Staphylococcus aureus infections are common, causing high mortality, compounded by the propensity of the bacterium to develop drug resistance. S. aureus is an excellent case study of the potential for a bacterium to be commensal, colonizing, latent or disease-causing; these states defined by the interplay between S. aureus and host. This interplay is multidimensional and evolving, exemplified by the spread of S. aureus between humans and other animal reservoirs and the lack of success in vaccine development. In this Review, we examine recent advances in understanding the S. aureus-host interactions that lead to infections. We revisit the primary role of neutrophils in controlling infection, summarizing the discovery of new immune evasion molecules and the discovery of new functions ascribed to well-known virulence factors. We explore the intriguing intersection of bacterial and host metabolism, where crosstalk in both directions can influence immune responses and infection outcomes. This Review also assesses the surprising genomic plasticity of S. aureus, its dualism as a multi-mammalian species commensal and opportunistic pathogen and our developing understanding of the roles of other bacteria in shaping S. aureus colonization.

Threshold-free genomic cluster detection to track transmission pathways in health-care settings: a genomic epidemiology analysis

BACKGROUND

A crucial barrier to the routine application of whole-genome sequencing (WGS) for infection prevention is the insufficient criteria for determining whether a genomic linkage is consistent with transmission within the facility. We evaluated the use of single-nucleotide variant (SNV) thresholds, as well as a novel threshold-free approach, for inferring transmission linkages in a high-transmission setting.

METHODS

We did a retrospective genomic epidemiology analysis of samples previously collected in the context of an intervention study at a long-term acute care hospital in the USA. We performed WGS on 435 isolates of Klebsiella pneumoniae harbouring the bla_KPC carbapenemase (KPC-Kp) collected from 256 patients through admission and surveillance culturing (once every 2 weeks) of almost every patient who was admitted to hospital over a 1-year period.

FINDINGS

Our analysis showed that the standard approach of using an SNV threshold to define transmission would lead to false-positive and false-negative inferences. False-positive inferences were driven by the frequent importation of closely related strains, which were presumably linked via transmission at connected health-care facilities. False-negative inferences stemmed from the diversity of colonising populations that were spread among patients, with multiple examples of hypermutator strain emergence within patients and, as a result, putative transmission links separated by large genetic distances. Motivated by limitations of an SNV threshold, we implemented a novel threshold-free transmission cluster inference approach, in which each of the acquired KPC-Kp isolates were linked back to the imported KPC-Kp isolate with which it shared the most variants. This approach yielded clusters that varied in levels of genetic diversity but where 105 (81%) of 129 unique strain acquisition events were associated with epidemiological links in the hospital. Of 100 patients who acquired KPC-Kp isolates that were included in a cluster, 47 could be linked to a single patient who was positive for KPC-Kp at admission, compared with 31 and 25 using 10 SNV and 20 SNV thresholds, respectively. Holistic examination of clusters highlighted extensive variation in the magnitude of onward transmission stemming from more than 100 importation events and revealed patterns in cluster propagation that could inform improvements to infection prevention strategies.

INTERPRETATION

Our results show how the integration of culture surveillance data into genomic analyses can overcome limitations of cluster detection based on SNV-thresholds and improve the ability to track pathways of pathogen transmission in health-care settings.

FUNDING

US Center for Disease Control and Prevention and University of Michigan.

Genomic Epidemiology Suggests Community Origins of Healthcare-Associated USA300 Methicillin-Resistant Staphylococcus aureus

BACKGROUND

Hospital-onset (HO) methicillin-resistant Staphylococcus aureus (MRSA) infections have declined over the past decade due to infection control strategies; community-onset (CO) and healthcare-associated community-onset (HACO) MRSA, particularly USA300, has declined less. We examined the role of community strains to explain the difference.

METHODS

We performed whole-genome sequencing (WGS) on MRSA clinical isolates from Cook County Health patients during 2011-2014. We defined infections as CO, HO, or HACO epidemiologically. We integrated genomic, community exposure, and statewide hospital discharge data to infer MRSA origin.

RESULTS

Among 1020 individuals with available WGS, most were USA300 wound infections (580 CO, 143 HO, 297 HACO). USA300 HO, CO, and HACO infections were intermixed on the USA300 phylogeny, consistent with common strains circulating across community and healthcare settings. Community exposures (eg, substance abuse, incarceration, homelessness) were associated with HACO and HO infections, and genetically linked individuals from both groups had little overlap in healthcare facilities, supporting community origins. Most repeat infections-over months to years-occurred in individuals persistently carrying their own strains. These individuals were more likely to have genetic linkages, suggesting a role of persistent colonization in transmission.

CONCLUSIONS

Efforts to reduce presumed nosocomial USA300 spread may require understanding and controlling community sources and transmission networks, particularly for repeat infections.

Niche-specific genome degradation and convergent evolution shaping Staphylococcus aureus adaptation during severe infections

During severe infections, Staphylococcus aureus moves from its colonising sites to blood and tissues and is exposed to new selective pressures, thus, potentially driving adaptive evolution. Previous studies have shown the key role of the agr locus in S. aureus pathoadaptation; however, a more comprehensive characterisation of genetic signatures of bacterial adaptation may enable prediction of clinical outcomes and reveal new targets for treatment and prevention of these infections. Here, we measured adaptation using within-host evolution analysis of 2590 S. aureus genomes from 396 independent episodes of infection. By capturing a comprehensive repertoire of single nucleotide and structural genome variations, we found evidence of a distinctive evolutionary pattern within the infecting populations compared to colonising bacteria. These invasive strains had up to 20-fold enrichments for genome degradation signatures and displayed significantly convergent mutations in a distinctive set of genes, linked to antibiotic response and pathogenesis. In addition to agr-mediated adaptation, we identified non-canonical, genome-wide significant loci including sucA-sucB and stp1. The prevalence of adaptive changes increased with infection extent, emphasising the clinical significance of these signatures. These findings provide a high-resolution picture of the molecular changes when S. aureus transitions from colonisation to severe infection and may inform correlation of infection outcomes with adaptation signatures.

Whole-genome sequencing surveillance and machine learning for healthcare outbreak detection and investigation: A systematic review and summary

BACKGROUND

Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.

METHODS

We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.

RESULTS

Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.

CONCLUSIONS

WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.

Modelling methicillin-resistant Staphylococcus aureus decolonization: interactions between body sites and the impact of site-specific clearance

Methicillin-resistant Staphylococcus aureus (MRSA) can colonize multiple body sites, and carriage is a risk factor for infection. Successful decolonization protocols reduce disease incidence; however, multiple protocols exist, comprising diverse therapies targeting multiple body sites, and the optimal protocol is unclear. Standard methods cannot infer the impact of site-specific components on successful decolonization. Here, we formulate a Bayesian coupled hidden Markov model, which estimates interactions between body sites, quantifies the contribution of each therapy to successful decolonization, and enables predictions of the efficacy of therapy combinations. We applied the model to longitudinal data from a randomized controlled trial (RCT) of an MRSA decolonization protocol consisting of chlorhexidine body and mouthwash and nasal mupirocin. Our findings (i) confirmed nares as a central hub for MRSA colonization and nasal mupirocin as the most crucial therapy and (ii) demonstrated all components contributed significantly to the efficacy of the protocol and the protocol reduced self-inoculation. Finally, we assessed the impact of hypothetical therapy improvements in silico and found that enhancing MRSA clearance at the skin would yield the largest gains. This study demonstrates the use of advanced modelling to go beyond what is typically achieved by RCTs, enabling evidence-based decision-making to streamline clinical protocols.

The microbial ecology of Escherichia coli in the vertebrate gut

Escherichia coli has a rich history as biology's 'rock star', driving advances across many fields. In the wild, E. coli resides innocuously in the gut of humans and animals but is also a versatile pathogen commonly associated with intestinal and extraintestinal infections and antimicrobial resistance-including large foodborne outbreaks such as the one that swept across Europe in 2011, killing 54 individuals and causing approximately 4000 infections and 900 cases of haemolytic uraemic syndrome. Given that most E. coli are harmless gut colonizers, an important ecological question plaguing microbiologists is what makes E. coli an occasionally devastating pathogen? To address this question requires an enhanced understanding of the ecology of the organism as a commensal. Here, we review how our knowledge of the ecology and within-host diversity of this organism in the vertebrate gut has progressed in the 137 years since E. coli was first described. We also review current approaches to the study of within-host bacterial diversity. In closing, we discuss some of the outstanding questions yet to be addressed and prospects for future research.

Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review

In order to better understand transmission dynamics and appropriately target control and preventive measures, studies have aimed to identify who-infected-whom in actual outbreaks. Numerous reconstruction methods exist, each with their own assumptions, types of data, and inference strategy. Thus, selecting a method can be difficult. Following PRISMA guidelines, we systematically reviewed the literature for methods combing epidemiological and genomic data in transmission tree reconstruction. We identified 22 methods from the 41 selected articles. We defined three families according to how genomic data was handled: a non-phylogenetic family, a sequential phylogenetic family, and a simultaneous phylogenetic family. We discussed methods according to the data needed as well as the underlying sequence mutation, within-host evolution, transmission, and case observation. In the non-phylogenetic family consisting of eight methods, pairwise genetic distances were estimated. In the phylogenetic families, transmission trees were inferred from phylogenetic trees either simultaneously (nine methods) or sequentially (five methods). While a majority of methods (17/22) modeled the transmission process, few (8/22) took into account imperfect case detection. Within-host evolution was generally (7/8) modeled as a coalescent process. These practical and theoretical considerations were highlighted in order to help select the appropriate method for an outbreak.

Molecular characterization of methicillin-resistant Staphylococcus aureus genotype ST764-SCCmec type II in Thailand

Methicillin-resistant Staphylococcus aureus (MRSA) is a significant causative agent of hospital-acquired infections. We characterized MRSA isolated from August 2012 to July 2015 from Thammasat University Hospital. Genotypic characterization of MRSA SCCmec type II and III isolates were scrutinized by whole genome sequencing (WGS). The WGS data revealed that the MRSA SCCmec type II isolates belonged to ST764 previously reported mainly in Japan. All of tested isolates contained ACME Type II′, SaPIn2, SaPIn3, seb, interrupted SA1320, and had a virulence gene profile similar to Japan MRSA ST764. Rigorous surveillance of MRSA strains is imperative in Thailand to arrest its potential spread.

Widespread sharing of pneumococcal strains in a rural African setting: proximate villages are more likely to share similar strains that are carried at multiple timepoints

The transmission dynamics of Streptococcus pneumoniae in sub-Saharan Africa are poorly understood due to a lack of adequate epidemiological and genomic data. Here we leverage a longitudinal cohort from 21 neighbouring villages in rural Africa to study how closely related strains of S. pneumoniae are shared among infants. We analysed 1074 pneumococcal genomes isolated from 102 infants from 21 villages. Strains were designated for unique serotype and sequence-type combinations, and we arbitrarily defined strain sharing where the pairwise genetic distance between strains could be accounted for by the mean within host intra-strain diversity. We used non-parametric statistical tests to assess the role of spatial distance and prolonged carriage on strain sharing using a logistic regression model. We recorded 458 carriage episodes including 318 (69.4 %) where the carried strain was shared with at least one other infant. The odds of strain sharing varied significantly across villages (χ²=47.5, df=21, P-value <0.001). Infants in close proximity to each other were more likely to be involved in strain sharing, but we also show a considerable amount of strain sharing across longer distances. Close geographic proximity (<5 km) between shared strains was associated with a significantly lower pairwise SNP distance compared to strains shared over longer distances (P-value <0.005). Sustained carriage of a shared strain among the infants was significantly more likely to occur if they resided in villages within a 5 km radius of each other (P-value <0.005, OR 3.7). Conversely, where both infants were transiently colonized by the shared strain, they were more likely to reside in villages separated by over 15 km (P-value <0.05, OR 1.5). PCV7 serotypes were rare (13.5 %) and were significantly less likely to be shared (P-value <0.001, OR −1.07). Strain sharing was more likely to occur over short geographical distances, especially where accompanied by sustained colonization. Our results show that strain sharing is a useful proxy for studying transmission dynamics in an under-sampled population with limited genomic data. This article contains data hosted by Microreact.

Infection prevention and control insights from a decade of pathogen whole-genome sequencing

Pathogen whole-genome sequencing has become an important tool for understanding the transmission and epidemiology of infectious diseases. It has improved our understanding of sources of infection and transmission routes for important healthcare-associated pathogens, including Clostridioides difficile and Staphylococcus aureus. Transmission from known infected or colonized patients in hospitals may explain fewer cases than previously thought and multiple introductions of these pathogens from the community may play a greater a role. The findings have had important implications for infection prevention and control. Sequencing has identified heterogeneity within pathogen species, with some subtypes transmitting and persisting in hospitals better than others. It has identified sources of infection in healthcare-associated outbreaks of food-borne pathogens, Candida auris and Mycobacterium chimera, as well as individuals or groups involved in transmission and historical sources of infection. SARS-CoV-2 sequencing has been central to tracking variants during the COVID-19 pandemic and has helped understand transmission to and from patients and healthcare workers despite prevention efforts. Metagenomic sequencing is an emerging technology for culture-independent diagnosis of infection and antimicrobial resistance. In future, sequencing is likely to become more accessible and widely available. Real-time use in hospitals may allow infection prevention and control teams to identify transmission and to target interventions. It may also provide surveillance and infection control benchmarking. Attention to ethical and wellbeing issues arising from sequencing identifying individuals involved in transmission is important. Pathogen whole-genome sequencing has provided an incredible new lens to understand the epidemiology of healthcare-associated infection and to better control and prevent these infections.

Genomic Analysis of Community Transmission Networks for MRSA among Females Entering a Large Inner-City Jail

Background

It is unclear if there are differences in MRSA risk between sexes in high-risk populations.

Methods

Females incarcerated at the Cook County Jail were enrolled within 72 hours of intake. Surveillance cultures (nares, throat, groin) were collected to determine prevalence of MRSA colonization. A survey was administered to identify colonization predictors. Univariate and multivariate analyses were performed to identify predictors of colonization at intake. Genomic sequencing was performed on MRSA colonization and archived clinical isolates.

Results

250 women were enrolled (70% AA, 15% Hispanic) with 70% previously in jail. The prevalence of MRSA colonization at intake was 20%, with 42% of those colonized solely in the throat or groin. Univariate predictors of MRSA colonization at entrance were illicit drug use, unstable housing, engaging in anal sex, recent exchange of sex for drugs/money, and a higher number of recent sexual partners. With multivariate adjustment for race/ethnicity, use of needles for illicit drugs was a significant predictor of MRSA. Use of illicit drugs was also associated with inclusion in a genomic cluster.

Nares colonization was significantly associated with not being in a genomic cluster (18.8% vs 78.6%, p&lt;0.001), whereas exclusive extra-nasal colonization was associated (OR 15.89, p&lt;0.001).

Conclusion

We found that a high proportion (20%) of females entered jail colonized with MRSA, suggesting that previously reported sex disparities of a lower risk in women may not apply to high-risk populations. Our findings suggest high-risk activities or venues in the community for MRSA, with potential for directing sex-specific interventions.

regentrans: a framework and R package for using genomics to study regional pathogen transmission

Increasing evidence of regional pathogen transmission networks highlights the importance of investigating the dissemination of multidrug-resistant organisms (MDROs) across a region to identify where transmission is occurring and how pathogens move across regions. We developed a framework for investigating MDRO regional transmission dynamics using whole-genome sequencing data and created regentrans, an easy-to-use, open source R package that implements these methods (https://github.com/Snitkin-Lab-Umich/regentrans). Using a dataset of over 400 carbapenem-resistant isolates of Klebsiella pneumoniae collected from patients in 21 long-term acute care hospitals over a one-year period, we demonstrate how to use our framework to gain insights into differences in inter- and intra-facility transmission across different facilities and over time. This framework and corresponding R package will allow investigators to better understand the origins and transmission patterns of MDROs, which is the first step in understanding how to stop transmission at the regional level.

Fatal exudative dermatitis in island populations of red squirrels (Sciurus vulgaris): spillover of a virulent Staphylococcus aureus clone (ST49) from reservoir hosts

Fatal exudative dermatitis (FED) is a significant cause of death of red squirrels (Sciurus vulgaris) on the island of Jersey in the Channel Islands where it is associated with a virulent clone of Staphylococcus aureus, ST49. S. aureus ST49 has been found in other hosts such as small mammals, pigs and humans, but the dynamics of carriage and disease of this clone, or any other lineage in red squirrels, is currently unknown. We used whole-genome sequencing to characterize 228 isolates from healthy red squirrels on Jersey, the Isle of Arran (Scotland) and Brownsea Island (England), from red squirrels showing signs of FED on Jersey and the Isle of Wight (England) and a small number of isolates from other hosts. S. aureus was frequently carried by red squirrels on the Isle of Arran with strains typically associated with small ruminants predominating. For the Brownsea carriage, S. aureus was less frequent and involved strains associated with birds, small ruminants and humans, while for the Jersey carriage S. aureus was rare but ST49 predominated in diseased squirrels. By combining our data with publicly available sequences, we show that the S. aureus carriage in red squirrels largely reflects frequent but facile acquisitions of strains carried by other hosts sharing their habitat ('spillover'), possibly including, in the case of ST188, humans. Genome-wide association analysis of the ruminant lineage ST133 revealed variants in a small number of mostly bacterial-cell-membrane-associated genes that were statistically associated with squirrel isolates from the Isle of Arran, raising the possibility of specific adaptation to red squirrels in this lineage. In contrast there is little evidence that ST49 is a common carriage isolate of red squirrels and infection from reservoir hosts such as bank voles or rats, is likely to be driving the emergence of FED in red squirrels.

Longitudinal whole-genome based comparison of carriage and infection associated Staphylococcus aureus in northern Australian dialysis clinics

Background

The study objective was to reveal reservoirs potentially leading to Staphylococcus aureus infections in haemodialysis clinic clients in the tropical north of the Australian Northern Territory (NT). This client population are primarily Aboriginal Australians who have a greater burden of ill health than other Australians. Reservoir identification will enhance infection control in this client group, including informing potential S. aureus decolonisation strategies.

Methods and findings

The study participants were 83 clients of four haemodialysis clinics in the Darwin region of the NT, and 46 clinical staff and researchers who had contact with the clinic clients. The study design was longitudinal, encompassing swabbing of anatomical sites at two month intervals to yield carriage isolates, and also progressive collection of infection isolates. Swab sampling was performed for all participants, and infection isolates collected for dialysis clients only. Analysis was based on the comparison of 139 carriage isolates and 27 infection isolates using whole genome sequencing. Genome comparisons were based on of 20,651 genome-wide orthologous SNPs, presence/absence of the mecA and pvl genes, and inferred multilocus sequence type and clonal complex. Pairs of genomes meeting the definition of “not discriminated” were classed as defining potential transmission events. The primary outcome was instances of potential transmission between a carriage site other than a skin lesion and an infection site, in the same individual. Three such instances were identified. Two involved ST762 (CC1) PVL- MRSA, and one instance ST121 PVL+ MSSA. Three additional instances were identified where the carriage strains were derived from skin lesions. Also identified were six instances of potential transmission of a carriage strains between participants, including transmission of strains between dialysis clients and staff/researchers, and one potential transmission of a clinical strain between participants. There were frequent occurrences of longitudinal persistence of carriage strains in individual participants, and two examples of the same strain causing infection in the same participants at different times.

Strains associated with infections and skin lesions were enriched for PVL and mecA in comparison to strains associated with long term carriage.

Conclusions

This study indicated that strains differ with respect to propensity to stably colonise sites such as the nose, and cause skin infections. PVL+ strains were associated with infection and skin lesions and were almost absent from the carriage sites. PVL- MRSA (mainly CC1) strains were associated with infection and also with potential transmission events involving carriage sites, while PVL- MSSA were frequently observed to stably colonise individuals without causing infection, and to be rarely transmitted. Current clinical guidelines for dialysis patients suggest MRSA decolonisation. Implementation in this client group may impact infections by PVL- MRSA, but may have little effect on infection by PVL+ strains. In this study, the PVL+ strains were predominant causes of infection but rarely colonised typical carriage sites such as the nose, and in the case of ST121, were MSSA. The important reservoirs for infection by PVL+ strains appeared to be prior infections.

Bottleneck size and selection level reproducibly impact evolution of antibiotic resistance

During antibiotic treatment, the evolution of bacterial pathogens is fundamentally affected by bottlenecks and varying selection levels imposed by the drugs. Bottlenecks-that is, reductions in bacterial population size-lead to an increased influence of random effects (genetic drift) during bacterial evolution, and varying antibiotic concentrations during treatment may favour distinct resistance variants. Both aspects influence the process of bacterial evolution during antibiotic therapy and thereby treatment outcome. Surprisingly, the joint influence of these interconnected factors on the evolution of antibiotic resistance remains largely unexplored. Here we combine evolution experiments with genomic and genetic analyses to demonstrate that bottleneck size and antibiotic-induced selection reproducibly impact the evolutionary path to resistance in pathogenic Pseudomonas aeruginosa, one of the most problematic opportunistic human pathogens. Resistance is favoured-expectedly-under high antibiotic selection and weak bottlenecks, but-unexpectedly-also under low antibiotic selection and severe bottlenecks. The latter is likely to result from a reduced probability of losing favourable variants through drift under weak selection. Moreover, the absence of high resistance under low selection and weak bottlenecks is caused by the spread of low-resistance variants with high competitive fitness under these conditions. We conclude that bottlenecks, in combination with drug-induced selection, are currently neglected key determinants of pathogen evolution and outcome of antibiotic treatment.

Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity

Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from host/vector material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective 'genome-wide locus sequence typing' (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/μl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, TcV and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate TcI, TcIII, TcIV and TcV + TcVI and appear to distinguish multiclonal infections within TcI. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research.

Molecular epidemiology in current times

Motivated to find options for prevention or intervention, molecular epidemiology aims to identify the host and microbial factors that determine the transmission, manifestation and progression of infectious disease. The genotyping of cultivatable bacterial strains is performed by either anonymous fingerprinting techniques or sequence-based exploration of variable genomic sites. Multilocus sequence typing of housekeeping genes and allele profiling of the core genome have become standard techniques of bacterial strain typing that may be supplemented by whole genome sequencing to explore all single nucleotide variants and/or the composition of the accessory genome. Next, novel protocols to investigate host and microbiome based upon smart third generation sequencing technologies are being developed for an effective surveillance, rapid diagnosis and real-time tracking of infectious diseases.