Biology subjects

Abudahab, K.

Publications and source records attributed to Abudahab, K..

13 recordsLinked to original sources

bioRxiv2025

Monitoring of vaccine targets and interventions using global genome data: vaccines.watch

The expansion of pathogen genome sequencing into routine disease surveillance programmes is set to bring rapidly-growing volumes of increasingly structured data on a global scale. This has the potential to deliver exciting opportunities for accelerating vaccine development and monitoring. Here we present an interactive platform, vaccines.watch (https://vaccines.watch), which aims to support decision-making around vaccine formulations and roll-out by enabling interrogation of vaccine target diversity from global genome data. We have initially focused on targets included in existing or prospective multivalent polysaccharide- based vaccines for Streptococcus pneumoniae, Klebsiella pneumoniae (and related species) and Acinetobacter baumannii. The platform currently displays data for >100k high-quality genomes with geotemporal sampling information (post-2010), with new genomes assembled, analysed and incorporated on an ongoing basis (every 4 hours) as public data are newly deposited. Crucially, users can view vaccine target information in the broader context of genotypic variants (e.g. sequence types) and antimicrobial resistance markers. The platform also enables users to review the composite serotypes of pneumococcal vaccine formulations among the available genomes. For example, using data in vaccines.watch from 3 June 2025, we observed that serotypes included in the PCV13 and PCV21 formulations accounted for 36.2% (11,907/32,918) and 87.4% (28,764/32,918) of global public genomes, respectively. The platform also enables continuous review of the global genomic landscape of the included pathogens, enabling identification of gaps (e.g. in geographic coverage) that should be targeted with increased genomic surveillance. Indeed we demonstrate that substantial geographic gaps remain in the coverage of available genomes, with over half of countries contributing no genomes for each of the three pathogens. However, while caution in interpretation is important, as global representativeness of genome data grows, vaccines.watch is positioned to support different stages of the vaccine pipeline, from selection of target antigens to post-rollout monitoring of population changes.

genomics↗

bioRxiv2025

amr.watch - monitoring antimicrobial resistance trends from global genomics data

BackgroundWhole genome sequencing (WGS) is increasingly supporting routine pathogen surveillance at local and national levels, providing comparable data that can inform on the emergence and spread of antimicrobial resistance (AMR) globally. However, the potential for shared WGS data to guide interventions around AMR remains under-exploited, in part due to challenges in collating and transforming the growing volumes of data into timely insights. We present an interactive platform, amr.watch (https://amr.watch), that enables interrogation of AMR trends from public WGS data on an ongoing basis to support research and policy. MethodsThe amr.watch platform incorporates, analyses and visualises high-quality WGS data from WHO-defined priority bacterial pathogens. Analytics are performed using community-standard methods with bespoke species-specific curation of AMR mechanisms. FindingsBy 31 March 2025, amr.watch included data from 620,700 pathogen genomes with geotemporal information, with highly variable representation of different species and geographic regions. By integrating WGS data with sampling information, amr.watch enables users to assess geotemporal trends among genotypic variants (e.g. sequence types) and AMR mechanisms, with implications for interventions including antimicrobial prescribing and drug and vaccine development. Interpretationamr.watch is an information platform for scientists and policy-makers delivering ongoing situational awareness of AMR trends from genomic data. As broad adoption of WGS continues, amr.watch is positioned to monitor both pathogen populations and our global efforts in genomic surveillance, guiding control strategies tailored to each pathogens characteristics. FundingUK National Institute for Health Research & Gates Foundation. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWhole genome sequencing (WGS) approaches enable us to track the spread of bacterial pathogens and antimicrobial resistance (AMR) with high resolution at local, national and global levels. To date, genomic studies assessing AMR dynamics have largely used retrospective data collected for specific research agendas. However, the growing volumes of publicly-shared WGS data, generated increasingly from routine surveillance, provide improved power to detect novel trends and guide interventions. Efforts to collate public bacterial genome data exist, such as AllTheBacteria, although these are aimed at the research community and do not facilitate data usage and interpretation by non-genomics experts, particularly those in public health. To our knowledge, no platforms exist for readily interrogating AMR dynamics from continuously updated public genome data across the array of different WHO priority bacterial pathogens. Of note, however, TyphiNet provides an interactive online dashboard for examining AMR trends exclusively from Salmonella Typhi using a periodically-updated data set from the Pathogenwatch platform. These findings are based on searching PubMed without language restrictions from Jan 1 2000 to December 31 2024, using terms related to "genomic surveillance" and "antimicrobial resistance". Added value of this studyWe have developed amr.watch which, to our knowledge, is the first platform that enables ongoing analysis and visualisation of AMR trends from public genome data across the spectrum of WHO priority bacterial pathogens via an accessible interface. Crucially, the platform incorporates processed genome data via a live always-on stream, enabling insights that are delayed only by the time to data deposition. We reviewed public genomes with available geotemporal information up until 31 March 2025, providing a contemporary global landscape of pathogen genome sequencing. While the number of genomes available annually grew over five-fold globally between 2010 and 2018, we also revealed the extent of differences in geographic representation, with 89.6% of genomes originating from high-income countries and 89 countries contributing no genome data from the priority pathogens. Implications of all the available evidenceRapid generation and sharing of global genome data enables us to more precisely track the spread and define the characteristics of contemporary circulating resistant pathogens. The amr.watch platform provides a solution for retrieving, curating and translating shared genomic data into relevant insights that are accessible and actionable by diverse stakeholders. It thereby forms a basis for monitoring progress in surveillance efforts, alerting on ongoing population changes and guiding enhanced precision for surveillance and interventional development. Additionally, our review of available bacterial genome data highlights the need for additional efforts to increase and sustain the implementation of genomic surveillance of AMR globally, and improve the timely sharing of WGS data and its associated metadata.

genomics↗

bioRxiv2021

Rapid Genomic Characterization and Global Surveillance of Klebsiella Using Pathogenwatch

BackgroundKlebsiella 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. MethodsWe 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 1,636 genomes from four low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR. ResultsUsing 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 (e.g. 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 three O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse. ConclusionsPathogenwatch 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. summaryPathogenwatch is a free web-application for analysis of Klebsiella genomes to aid surveillance at local, national and global levels. We improved the representation of genomes from middle-income countries through the Global Health Research Unit on AMR, further facilitating ongoing surveillance.

genomics↗

bioRxiv2021

Genome Sequencing Identifies Previously Unrecognized Klebsiella pneumoniae Outbreaks in Neonatal Intensive Care Units in the Philippines

BackgroundKlebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least two classes of antibiotics, yet mechanisms and spread of its resistance are not well studied. MethodsA retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam- and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015-2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic and genome-derived data. ResultsPrevalent AMR mechanisms detected include blaCTX-M-15 (76.8%) and blaNDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying blaNDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (ST). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs, K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged <1. ConclusionWGS provided an in-depth understanding of the epidemiology of AMR in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of three previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs. summaryWhole genome sequencing identified three distinct previously unrecognized local outbreaks in a retrospective study in the Philippines, along with an epidemic plasmid carrying antimicrobial resistance genes, highlighting its importance in antimicrobial resistance surveillance, outbreak detection and infection control.

genomics↗

bioRxiv2020

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

BackgroundMicrobial whole-genome sequencing (WGS) is now increasingly used to inform public health investigations of infectious disease. This approach has transformed our understanding of the global population structure of Salmonella enterica serovar Typhi (S. Typhi), the causative agent of typhoid fever. WGS has been particularly informative for understanding the global spread of multi-drug resistant (MDR) typhoid. As WGS capacity becomes more decentralised, there is a growing opportunity for collaboration and sharing of surveillance data within and between countries to inform disease control policies. This requires freely available, community driven tools that reduce the barriers to access genomic data for public health surveillance and that deliver genomic data on a global scale. MethodsHere we present the Pathogenwatch (https://pathogen.watch/styphi) scheme for S. Typhi, a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data to identify high-risk clones at a population level. Data are delivered in single genome reports or in collections of genomes combined with geographic and other data using trees, maps and tables. ResultsWe show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are largely concordant with phenotypic drug susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from over 4,300 public genomes available in the application. ConclusionsPathogenwatch democratises genomic epidemiology of S. Typhi by providing an intuitive entry point for the analysis of WGS and linked epidemiological data, enabling international public health monitoring of the emergence and spread of high risk clones.

genomics↗

bioRxiv2020

A community-driven resource for genomic surveillance of Neisseria gonorrhoeae at Pathogenwatch

BackgroundAntimicrobial resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones, transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance. MethodsHere we present a public health focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch (https://pathogen.watch/ngonorrhoeae). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization. ResultsAMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasizing the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern. ConclusionsThe N. gonorrhoeae scheme in Pathogenwatch provides customized bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.

genomics↗

bioRxiv2020

Genomic Surveillance of Pseudomonas aeruginosa in the Philippines from 2013-2014

Pseudomonas aeruginosa is an opportunistic pathogen often causing nosocomial infections that are resilient to treatment due to an extensive repertoire of intrinsic and acquired resistance mechanisms. In recent years, increasing resistance rates to antibiotics such as carbapenems and extended-spectrum cephalosporins have been reported, as well as multi-drug resistant and possible extremely drug-resistant rates of approximately 21% and 15%, respectively. However, the molecular epidemiology and AMR mechanisms of this pathogen remains largely uncharacterized. We sequenced the whole genomes of 176 P. aeruginosa isolates collected in 2013-2014 by the Antimicrobial Resistance Surveillance Program. The multi-locus sequence type, presence of antimicrobial resistance (AMR) determinants, and relatedness between the isolates were derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. Carbapenem resistance was associated namely with loss-of function of the OprD porin, and acquisition of the metallo-{beta}-lactamase VIM. The concordance between phenotypic and genotypic resistance was 93.27% overall for 6 antibiotics in 3 classes, but varied widely between aminoglycosides. The population of P. aeruginosa in the Philippines was diverse, with clonal expansions of XDR genomes belonging to multi-locus sequence types ST235, ST244, ST309, and ST773. We found evidence of persistence or reintroduction of the predominant clone ST235 in one hospital, as well as transfer between hospitals. Most of the ST235 genomes formed a distinct Philippine lineage when contextualized with international genomes, thus raising the possibility that this is a lineage unique to the Philippines. This was further supported by long-read sequencing of one representative XDR isolate, which revealed the presence of an integron carrying multiple resistance genes, including blaVIM-2, with differences in gene composition and synteny to other P. aeruginosa class 1 integrons described before. We produced the first comprehensive genomic survey of P. aeruginosa in the Philippines, which bridges the gap in genomic data from the Western Pacific region and will constitute the genetic background to contextualize ongoing prospective surveillance. Our results also highlight the importance of infection control interventions aimed to curtail the spread of international epidemic clone ST235 within the country.

genomics↗

bioRxiv2020

Genomic Surveillance of Methicillin-Resistant Staphylococcus aureus in the Philippines from 2013-2014

Methicillin Resistant Staphylococcus aureus (MRSA) remains one of the leading causes of both nosocomial and community infections worldwide. In the Philippines, MRSA rates have remained above 50% since 2010, but resistance to other antibiotics, including vancomycin, is low. The MRSA burden can be partially attributed to pathogen-specific characteristics of the circulating clones, but little was known about the S. aureus circulating clones in the Philippines. We sequenced the whole genomes of 116 S. aureus isolates collected in 2013-2014 by the Antimicrobial Resistance Surveillance Program. The multi-locus sequence type, spa type, SCC-mec type, presence of antimicrobial resistance (AMR) determinants and virulence genes, and relatedness between the isolates were all derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. The MRSA population in the Philippines was composed of a limited number of genetic clones, including several international epidemic clones, such as CC30-spa-t019-SCCmec-IV-PVL+, CC5-SCCmec-typeIV, and ST239-spa-t030-SCCmec-typeIII. The CC30 genomes were related to the South West Pacific clone, but formed a distinct and diverse lineage, with evidence of global dissemination. We showed the independent acquisition of resistance to sulfamethoxazole/trimethoprim across different locations and genetic clones, but mostly in pediatric patients with invasive infections. The concordance between phenotypic and genotypic resistance was 99.68% overall for 8 antibiotics in 7 classes. We produced the first comprehensive genomic survey of S. aureus in the Philippines, which bridges the gap in genomic data from the Western Pacific region and will constitute the genetic background to contextualize ongoing prospective surveillance.

genomics↗

bioRxiv2020

Genomic Surveillance of Neisseria gonorrhoeae in the Philippines from 2013-2014

Antimicrobial-resistant Neisseria gonorrhoeae is a major threat to public health and is of particular concern in the Western Pacific Region, where the incidence of gonorrhoea is high. The Antimicrobial Resistance Surveillance Program (ARSP) has been capturing information on resistant gonorrhoea since 1996, but genomic epidemiology studies on this pathogen are lacking in the Philippines. We sequenced the whole genomes of 21 N. gonorrhoeae isolates collected in 2013-2014 by the ARSP. The multilocus sequence type, multiantigen sequence type, presence of determinants of antimicrobial resistance and relatedness among the isolates were all derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. Ten of 21 isolates were resistant to penicillin, ciprofloxacin and tetracycline, due mainly to the presence of blaTEM gene, the S91F mutation in the gyrA gene and the tetM gene, respectively. None of the isolates was resistant to ceftriaxone or cefixime. The concordance between phenotypic and genotypic resistance was 92.38% overall for five antibiotics in four classes. Despite the small number of isolates studied, they were genetically diverse, as shown by the sequence types, the N. gonorrhoeae multiantigen sequence typing types and the tree. Comparison with global genomes placed the Philippine genomes within global lineage A and led to identification of an international transmission route. This first genomic survey of N. gonorrhoeae isolates collected by ARSP will be used to contextualize prospective surveillance. It highlights the importance of genomic surveillance in the Western Pacific and other endemic regions for understanding the spread of drug-resistant gonorrhoea worldwide.

genomics↗

bioRxiv2019

See and Sequence: Integrating Whole-Genome Sequencing Within the National Antimicrobial Resistance Surveillance Program in the Philippines

Drug-resistant bacterial infections constitute a growing threat to public health globally 1. National networks of laboratory-based surveillance of antimicrobial resistance (AMR) monitor the emergence and spread of resistance and are central to the dissemination of these data to AMR stakeholders 2. Whole-genome sequencing (WGS) can support these efforts by pinpointing resistance mechanisms and uncovering transmission patterns 3, 4. However, genomic surveillance is rare in low- and middle-income countries (LMICs), which are predicted to be the most affected by AMR 5. We implemented WGS within the established Antimicrobial Resistance Surveillance Program (ARSP) of the Philippines via ongoing technology transfer, capacity building in and binational collaboration. In parallel, we conducted an initial large-scale retrospective sequencing survey to characterize bacterial populations and dissect resistance phenotypes of key bug-drug combinations, which is the focus of this article. Starting in 2010, the ARSP phenotypic data indicated increasing carbapenem resistance rates for Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Escherichia coli. We first identified that this coincided with a marked expansion of specific resistance phenotypes. By then linking the resistance phenotypes to genomic data, we revealed the diversity of genetic lineages (strains), AMR mechanisms, and AMR vehicles underlying this expansion. We discovered a previously unreported plasmid-driven hospital outbreak of carbapenem-resistant K. pneumoniae, uncovered the interplay of carbapenem resistance genes and plasmids in the geographic circulation of epidemic K. pneumoniae ST147, and found that carbapenem-resistant E. coli ST410 consisted of diverse lineages of global circulation that carried both international and local plasmids, resulting in a combination of carbapenemase genes variants previously unreported for this organism. Thus, the WGS data provided an enhanced understanding of the interplay between strains, genes and vehicles driving the dissemination of carbapenem resistance in the Philippines. In addition, our retrospective survey served both as the genetic background to contextualize local prospective surveillance, and as a comprehensive dataset for training in bioinformatics and genomic epidemiology. Continued prospective sequencing, capacity building and collaboration will strengthen genomic surveillance of AMR in the Philippines and the translation of genomic data into public-health action. We generated a blueprint for the integration of WGS and genomic epidemiology into an established national system of laboratory-based surveillance of AMR through international collaboration that can be adapted and utilized within other locations to tackle the global challenge of AMR.

genomics↗

bioRxiv2018

Signatures of negative frequency dependent selection in colonisation factors and the evolution of a multi-drug resistant lineage of Escherichia coli

Escherichia coli is a major cause of bloodstream and urinary tract infections globally. The wide dissemination of multi-drug resistant (MDR) strains of extra-intestinal pathogenic E. coli (ExPEC) poses a rapidly increasing public health burden due to narrowed treatment options and increased risk of failure to clear an infection. Here, we present a detailed population genomic analysis of the ExPEC ST131 clone, in which we seek explanations for its success as an emerging pathogenic strain beyond the acquisition of antimicrobial resistance (AMR) genes. We show evidence for evolution towards separate ecological niches for the main clades of ST131 and differential evolution of anaerobic metabolism, key colonisation and virulence factors. We further demonstrate that negative frequency-dependent selection acting across accessory loci is a major mechanism that has shaped the population evolution of this pathogen.

microbiology↗

bioRxiv2017

PANINI: Pangenome Neighbor Identification for Bacterial Populations

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, in the current era of population genomics, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here we introduce PANINI, a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding. PANINI is browser-based and integrates with the Microreact platform for rapid online visualisation and exploration of both core and accessory genome evolutionary signals together with relevant epidemiological, geographic, temporal and other metadata. Several case studies with single-and multi-clone pneumococcal populations are presented to demonstrate ability to identify biologically important signals from gene content data. PANINI is available at http://panini.wgsa.net/ and code at http://gitlab.com/cgps/panini

microbiology↗

bioRxiv2017

Phandango: an interactive viewer for bacterial population genomics.

SummaryFully exploiting the wealth of data in current bacterial population genomics datasets requires synthesising and integrating different types of analysis across millions of base pairs in hundreds or thousands of isolates. Current approaches often use static representations of phylogenetic, epidemiological, statistical and evolutionary analysis results that are difficult to relate to one another. Phandango is an interactive application running in a web browser allowing fast exploration of large-scale population genomics datasets combining the output from multiple genomic analysis methods in an intuitive and interactive manner.\n\nAvailabilityPhandango is a web application freely available for use at https://jameshadfield.github.io/phandango and includes a diverse collection of datasets as examples. Source code together with a detailed wiki page is available on GitHub at https://github.com/jameshadfield/phandango\n\nContactjh22@sanger.ac.uk, sh16@sanger.ac.uk

bioinformatics↗