Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets

A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at pathogenwatch.

As whole-genome sequencing capacity becomes increasingly decentralized, there is a growing opportunity for collaboration and the sharing of surveillance data within and between countries to inform typhoid control policies. This vision requires free, community-driven tools that facilitate access to genomic data for public health on a global scale. Here we present the Pathogenwatch scheme for Salmonella enterica serovar Typhi (S. Typhi), a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data. We show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are highly concordant with phenotypic susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from >4,300 public genomes available in the application. Pathogenwatch provides an intuitive entry point to monitor of the emergence and spread of S. Typhi high risk clones

Unlocking the Potential of Genomic Data to Inform Typhoid Fever Control Policy: Supportive Resources for Genomic Data Generation, Analysis, and Visualization

The global response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic demonstrated the value of timely and open sharing of genomic data with standardized metadata to facilitate monitoring of the emergence and spread of new variants. Here, we make the case for the value of Salmonella Typhi (S. Typhi) genomic data and demonstrate the utility of freely available platforms and services that support the generation, analysis, and visualization of S. Typhi genomic data on the African continent and more broadly by introducing the Africa Centres for Disease Control and Prevention's Pathogen Genomics Initiative, SEQAFRICA, Typhi Pathogenwatch, TyphiNET, and the Global Typhoid Genomics Consortium

Integrating whole-genome sequencing within the National Antimicrobial Resistance Surveillance Program in the Philippines

Funding: This work was funded by the Newton Fund, Medical Research Council (UK) grant MR/N019296/1, Philippine Council for Health Research and Development project number FP160007. J.S. was partially supported by research grants RR025040 and U01CA207167 from the National Institutes of Health (NIH). S.A. and D.M.A. were additionally supported by the National Institute for Health Research (UK) Global Health Research Unit on genomic Surveillance of AMR(16_136_111) and by the Centre for Genomic Pathogen Surveillance (http://pathogensurveillance.net).National networks of laboratory-based surveillance of antimicrobial resistance (AMR) monitor resistance trends and disseminate these data to AMR stakeholders. Whole-genome sequencing (WGS) can support surveillance by pinpointing resistance mechanisms and uncovering transmission patterns. However, genomic surveillance is rare in low- and middle-income countries. Here, we implement WGS within the established Antimicrobial Resistance Surveillance Program of the Philippines via a binational collaboration. In parallel, we characterize bacterial populations of key bug-drug combinations via a retrospective sequencing survey. By linking the resistance phenotypes to genomic data, we reveal the interplay of genetic lineages (strains), AMR mechanisms, and AMR vehicles underlying the expansion of specific resistance phenotypes that coincide with the growing carbapenem resistance rates observed since 2010. Our results enhance our understanding of the drivers of carbapenem resistance in the Philippines, while also serving as the genetic background to contextualize ongoing local prospective surveillance.Publisher PDFPeer reviewe

A cluster-randomized trial of hydroxychloroquine for prevention of Covid-19

Background: current strategies for preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are limited to nonpharmacologic interventions. Hydroxychloroquine has been proposed as a postexposure therapy to prevent coronavirus disease 2019 (Covid-19), but definitive evidence is lacking. Methods: we conducted an open-label, cluster-randomized trial involving asymptomatic contacts of patients with polymerase-chain-reaction (PCR)-confirmed Covid-19 in Catalonia, Spain. We randomly assigned clusters of contacts to the hydroxychloroquine group (which received the drug at a dose of 800 mg once, followed by 400 mg daily for 6 days) or to the usual-care group (which received no specific therapy). The primary outcome was PCR-confirmed, symptomatic Covid-19 within 14 days. The secondary outcome was SARS-CoV-2 infection, defined by symptoms compatible with Covid-19 or a positive PCR test regardless of symptoms. Adverse events were assessed for up to 28 days. Results: the analysis included 2314 healthy contacts of 672 index case patients with Covid-19 who were identified between March 17 and April 28, 2020. A total of 1116 contacts were randomly assigned to receive hydroxychloroquine and 1198 to receive usual care. Results were similar in the hydroxychloroquine and usual-care groups with respect to the incidence of PCR-confirmed, symptomatic Covid-19 (5.7% and 6.2%, respectively; risk ratio, 0.86 [95% confidence interval, 0.52 to 1.42]). In addition, hydroxychloroquine was not associated with a lower incidence of SARS-CoV-2 transmission than usual care (18.7% and 17.8%, respectively). The incidence of adverse events was higher in the hydroxychloroquine group than in the usual-care group (56.1% vs. 5.9%), but no treatment-related serious adverse events were reported. Conclusions: postexposure therapy with hydroxychloroquine did not prevent SARS-CoV-2 infection or symptomatic Covid-19 in healthy persons exposed to a PCR-positive case patient. (Funded by the crowdfunding campaign YoMeCorono and others; BCN-PEP-CoV2 ClinicalTrials.gov number, NCT04304053.)

A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at pathogenwatch.

As whole-genome sequencing capacity becomes increasingly decentralized, there is a growing opportunity for collaboration and the sharing of surveillance data within and between countries to inform typhoid control policies. This vision requires free, community-driven tools that facilitate access to genomic data for public health on a global scale. Here we present the Pathogenwatch scheme for Salmonella enterica serovar Typhi (S. Typhi), a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data. We show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are highly concordant with phenotypic susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from >4,300 public genomes available in the application. Pathogenwatch provides an intuitive entry point to monitor of the emergence and spread of S. Typhi high risk clones

Global diversity and antimicrobial resistance of typhoid fever pathogens: insights from a meta-analysis of 13,000 Salmonella Typhi genomes

Background: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). Methods: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. Results: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal ‘sentinel’ surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. Conclusions: The consortium’s aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies

Rapid Genomic Characterization and Global Surveillance of Klebsiella Using Pathogenwatch.

BACKGROUND: Klebsiella species, including the notable pathogen K. pneumoniae, are increasingly associated with antimicrobial resistance (AMR). Genome-based surveillance can inform interventions aimed at controlling AMR. However, its widespread implementation requires tools to streamline bioinformatic analyses and public health reporting. METHODS: We developed the web application Pathogenwatch, which implements analytics tailored to Klebsiella species for integration and visualization of genomic and epidemiological data. We populated Pathogenwatch with 16 537 public Klebsiella genomes to enable contextualization of user genomes. We demonstrated its features with 1636 genomes from 4 low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR. RESULTS: Using Pathogenwatch, we found that GHRU genomes were dominated by a small number of epidemic drug-resistant clones of K. pneumoniae. However, differences in their distribution were observed (eg, ST258/512 dominated in Colombia, ST231 in India, ST307 in Nigeria, ST147 in the Philippines). Phylogenetic analyses including public genomes for contextualization enabled retrospective monitoring of their spread. In particular, we identified hospital outbreaks, detected introductions from abroad, and uncovered clonal expansions associated with resistance and virulence genes. Assessment of loci encoding O-antigens and capsule in K. pneumoniae, which represent possible vaccine candidates, showed that 3 O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse. CONCLUSIONS: Pathogenwatch provides a free, accessible platform for real-time analysis of Klebsiella genomes to aid surveillance at local, national, and global levels. We have improved representation of genomes from GHRU participant countries, further facilitating ongoing surveillance

Whole genome sequencing identifies independent outbreaks of Shigellosis in 2010 and 2011 in La Pampa Province, Argentina

AbstractShigella sonnei is an emergent cause of diarrheal disease in middle-income countries. The organism causes endemic disease and is also associated with sporadic outbreaks in susceptible populations. In 2010 and 2011 there were two suspected outbreaks of diarrheal disease caused by S. sonnei in La Pampa province in central Argentina. Aiming to confirm these as outbreaks and provide insight into the relationship of the strains causing these infections we combined antimicrobial susceptibility testing and pulsed field gel electrophoresis (PFGE) with whole genome sequencing (WGS). Antimicrobial susceptibility testing suggested the two events were unrelated; organisms isolated in 2010 exhibited resistance to trimethoprim sulphate whereas the 2011 S. sonnei were non-susceptible against ampicillin, trimethoprim sulphate and cefpodoxime. PFGE profiling confirmed the likelihood of two independent outbreaks, separating the isolates into two main XbaI restriction profiles. We additionally performed WGS on 17 isolates associated with these outbreaks. The resulting phylogeny confirmed the PFGE structure and separated the organisms into two comparatively distantly related clones. Antimicrobial resistant genes were common, and the presence of an OXA-1 was likely associated with resistance to cefpodoxime in the second outbreak. We additionally identified novel horizontally transferred genetic material that may impinge on the pathogenic phenotype of the infecting strains. Our study shows that even with a lack of supporting routine data WGS is an indispensible method for the tracking and surveillance of bacterial pathogens during outbreaks and is becoming a vital tool for the monitoring of antimicrobial resistant strains of S. sonnei.</jats:p