bioRxiv Science⌕ Search

Biology subjects

Dyson, Z. A.

Publications and source records attributed to Dyson, Z. A..

15 recordsLinked to original sources

AMRgen: an R package for antimicrobial resistance genotype-phenotype analysis

Microbial whole-genome sequence data is now generated at scale, including to support antimicrobial resistance (AMR) surveillance and understand resistance mechanisms, yet analytical infrastructure for systematically linking AMR genotypes to measured phenotypes remains fragmented. Here we present AMRgen, an R package to support systematic AMR genotype-phenotype analysis. AMRgen imports and harmonises genotypic data from common bioinformatics tools, alongside phenotypic data from automated antimicrobial susceptibility testing instruments and public repositories. It supports common analyses linking data to reference distributions, modelling associations, quantifying concordance, and producing publication-ready visualisations including UpSet plots that jointly display genotypic marker combination frequencies and associated phenotypic distributions. We demonstrate AMRgens utility using publicly available surveillance data for World Health Organization priority AMR pathogens, Neisseria gonorrhoeae, Klebsiella pneumoniae, Escherichia coli and Salmonella enterica. AMRgen, available free and open-source at https://AMRgen.org, provides a reproducible end-to-end foundation for genotype-phenotype research in AMR genomics, clinical microbiology, and public health surveillance.

microbiology↗

EnviroAmpDesigner, a tool for designing high specificity multiplex PCR primer panels for detecting and subtyping a target organism in environmental surveillance samples

BackgroundAmplicon sequencing is a popular method for understanding the diversity of bacterial communities in environmental or similar samples as exemplified by 16S rRNA sequencing. This approach has been extended into multiplex amplicon sequencing in which multiple targets are amplified in the same PCR reaction such as virus sequencing using tiled amplicons. Multiple tools exist to design PCR primers, and some support design of multiplex panels. However, despite increasing interest in the use of environmental or wastewater sampling for detecting and typing specific antimicrobial resistant (AMR) bacteria such as typhoid or cholera agents, we were unable to find a tool for designing a multiplex PCR panel for environmental samples that not only focused on detection of a specific organism, but also on amplifying lineage-specific or AMR-associated alleles of the target organism while minimising amplification of off-target genomes present in the sample. We found that existing tools either depend on the target organism being very distinct from the rest of the organisms in the sample, or focus on detection rather than genotyping of the organism of interest. We have developed EnviroAmpDesigner (v0.1.3, DOI: 10.5281/zenodo.14967337) to fill this gap, which we used to design a multiplex amplicon panel for detection, genotyping and AMR profiling of the typhoidal pathogens Salmonella enterica serovars Typhi and Paratyphi A. EnviroAmpDesigner can design amplicons for both short and long-read sequencing. The software first identifies single nucleotide polymorsphisms (SNPs) that distinguish individual genotypes of the target pathogen (in our case, S. Typhi). It then identifies SNPs that distinguish the target organism from others. Finally, the software designs primers that simultaneously target genotyping SNPs and have at least one primer with a 3 end at each SNP that distinguishes the target organism. The purpose of the latter condition is to increase the specificity of the primers, to minimise amplification of homologous sequences in non-target organisms. While our use case focuses on S. Typhi and Paratyphi A, the tool is organism agnostic and should work for any haploid organism. The tool is freely available via Bioconda and GitHub (https://github.com/AntonS-bio/EnviroAmpDesigner). Impact statementWe have developed EnviroAmpDesigner (v 0.1.3) software to design a multiplexed panel of long-read amplicons for detection and lineage typing of bacteria in environmental samples. We apply this tool to Salmonella Typhi and Paratyphi A, the bacterial agents of typhoid fever, but the tool is organism agnostic. The tool is computationally efficient and can be used on mid-range laptop. It has potential to support more widespread deployment of sequencing-based surveillance for bacterial pathogens in environmental and wastewater samples. Data SummaryFor the purposes of designing primers for S. Typhi and Paratyphi A we used 13,134 samples from the Global Typhoid Genomics Consortium data (target organisms) (1) and 1,810 publicly available Enterobacterales genomes from NCBIs RefSeq database (representing off-target related organisms) (2). To validate the primers, we applied an amplicon sequencing protocol (3) to DNA extracted from two S. Typhi isolates (NCBI accessions SRR5949979 and SRR7165748) provided by Satheesh Nair (UKHSA) (4), and a pooled DNA sample of American Type Culture Collection (ATCC) isolates S. Paratyphi A (ATCC 9150D), S. Paratyphi B (ATCC-BAA-1250D), S. Paratyphi C (ATCC-BAA-1715D), Aeromonas hydrophila (ATCC-7965D), Klebsiella pneumoniae (ATCC-BAA-1706D), and Citrobacter freundii (ATCC-8090D) chosen for their close relationship to S. Typhi. The resulting amplicon sequence data was deposited in European Nucleotide Archive (project accession: PRJEB81565).

bioinformatics↗

AmpliconTyper tool for analysing ONT multiplex PCR data from environmental and other mixed sources

Amplicon sequencing is a popular method for understanding the diversity of bacterial communities in mixed samples as exemplified by 16S rRNA metagenome sequencing. This approach has been extended into multiplex amplicon sequencing in which multiple targets are amplified in the same polymerase chain reaction (PCR). Multiple tools exist to process the sequencing data produced via the short-read Illumina platform, but there are fewer options for long-read Oxford Nanopore Technologies (ONT) sequencing, or for processing data from environmental surveillance or other sources with many different organisms. We have developed AmpliconTyper (v0.1.28, DOI: 10.5281/zenodo.14621928) for analysing multiplex amplicon sequencing data from environmental (e.g. wastewater) or similarly contaminated samples, generated using ONT devices. The software tool uses machine learning to classify sequencing reads into target and non-target organisms with very high specificity and sensitivity. The user can train models using public and/or user-generated data, which can subsequently be applied to analyse new data. The tool can also generate amplicon consensus sequences, as well as identify single nucleotide polymorphisms (SNPs) and report their genotype implications, such as association with lineages or antimicrobial resistance (AMR). The tool is freely available via Bioconda and GitHub (https://github.com/AntonS-bio/AmpliconTyper). AmpliconTyper allows robust identification of target organism reads in ONT sequenced environmental samples, and can identify user-specified lineage or AMR markers. Impact statementAmpliconTyper (v0.1.28) is a software package that enables users to analyse amplicon sequences generated by targeted amplification followed by ONT sequencing, for environmental or other similarly contaminated samples. The analysis includes mapping of reads to target amplicon sequences, classification of each sequenced read as either originating from a target or non-target organism, followed by identification of user-specified SNPs and generation of an interactive report summarising the findings. The strength of AmpliconTyper lies in its ability to train a machine learning model using public data to create sequencing read classification models tailored to a users application. AmpliconTyper is designed specifically to work with extremely noisy data that includes a large share of off-target amplification reads such as those encountered in environmental surveillance applications. Data SummaryFor the purpose of designing and testing AmpliconTyper we have used two datasets. The first consisted of 69 Salmonella enterica serovar. Typhi (S. Typhi) and 10,303 other Enterobacteriaceae WGS ONT nanopore sequencing libraries (Supp. Data 1) from NCBI Sequence Read Archive (SRA) (1). We used these data to evaluate the performance of different classifier models and to train a model for our use-case, i.e. amplicon-based detection of S. Typhi from environmental surveillance samples (2). In addition, to further evaluate the performance of AmpliconTyper in our use case, we have applied an amplicon sequencing protocol (2) to generate amplicon data for S. Typhi using two S. Typhi isolates (NCBI accessions SRR5949979 and SRR7165748) provided by Satheesh Nair (UKHSA) (3). We also used same protocol to the pooled sample of American Type Culture Collection (ATCC) consisting of S. Paratyphi A (ATCC 9150D), S. Paratyphi B (ATCC-BAA-1250D), S. Paratyphi C (ATCC-BAA-1715D), Aeromonas hydrophila (ATCC-7965D), Klebsiella pneumoniae (ATCC-BAA-1706D), and Citrobacter freundii (ATCC-8090D) chosen for their close relationship to S. Typhi. The test data for classification is available at https://github.com/AntonS-bio/AmpliconTyper/tree/main/test_data. Newly generated data was deposited in European Nucleotide Archive project PRJEB81565.

genomics↗

Typhi Mykrobe: fast and accurate lineage identification and antimicrobial resistance genotyping directly from sequence reads for the typhoid fever agent Salmonella Typhi

BackgroundTyphoid fever results from systemic infection with Salmonella enterica serovar Typhi (Typhi) and causes 10 million illnesses annually. Disease control relies on prevention (water, sanitation, and hygiene interventions or vaccination) and effective antimicrobial treatment. Antimicrobial resistant (AMR) Typhi lineages have emerged and become established in many parts of the world. Knowledge of local pathogen populations informed by genomic surveillance, including of lineages (defined by the GenoTyphi scheme) and AMR determinants, is increasingly used to inform local treatment guidelines and to inform vaccination strategy. Current tools for genotyping Typhi require multiple read alignment or assembly steps and have not been validated for analysis of data generated with Oxford Nanopore Technologies (ONT) long-read sequencing devices. Here, we introduce Typhi Mykrobe, a command line software tool for rapid genotyping of Typhi lineages, AMR determinants, and plasmid replicons direct from sequencing reads. ResultsWe validated Typhi Mykrobe lineage genotyping by comparison with the current standard read mapping-based approach and demonstrated 99.8% concordance across nearly 13,000 genomes sequenced with Illumina platforms. For the few isolates with discordant calls, we show that Typhi Mykrobe results are better supported by the evidence from raw sequence read data than the results generated using the mapping-based approach. We also demonstrate 99.9% concordance for detection of AMR determinants compared with the current standard assembly-based approach, with similar results for plasmid marker detection. Typhi Mykrobe predicts clinical resistance categorisation (S/I/R) for eight drug classes, and we show strong agreement with phenotypic categorisations generated from reference laboratory minimum inhibitory concentration (MIC) data for n=1,572 Illumina-sequenced isolates (>99% agreement within one doubling dilution). We show strong concordance (>96% for genotype and >98% for AMR and plasmid) between calls made from ONT reads and those made from Illumina reads for isolates sequenced on both platforms (n =93 genomes). Typhi Mykrobe takes less than a minute per sample and is available at https://github.com/typhoidgenomics/genotyphi. ConclusionsTyphi Mykrobe provides rapid and sensitive genotyping of Typhi genomes direct from Illumina and ONT reads, although lower accuracy was observed for R9 ONT data. It demonstrated accurate assignment of GenoTyphi lineage, detection of AMR determinants and prediction of corresponding AMR phenotypes, and identification of plasmid replicons.

microbiology↗

The TyphiNET data visualisation dashboard: Unlocking Salmonella Typhi genomics data to support public health

BackgroundSalmonella enterica subspecies enterica serovar Typhi (abbreviated as Typhi) is the bacterial agent of typhoid fever. Effective antimicrobial therapy reduces complications and mortality; however, antimicrobial resistance (AMR) is a major problem in many endemic countries. Prevention through vaccination is possible through recently-licensed Gavi-supported typhoid conjugate vaccines (TCVs), and national immunisation programs are currently being considered or deployed in several countries where AMR prevalence is known to be high. Pathogen whole genome sequence data are a rich source of information on Typhi variants (genotypes or lineages), AMR prevalence, and mechanisms. However, this information is currently not readily accessible to non-genomics experts, including those driving vaccine implementation or empirical therapy guidance. ResultsWe developed TyphiNET (https://www.typhi.net), an interactive online dashboard for exploring Typhi genotype and AMR distributions derived from publicly available pathogen genome sequences. TyphiNET allows users to explore country-level summaries such as the frequency of pathogen lineages, temporal trends in resistance to clinically relevant antimicrobials, and the specific variants and mechanisms underlying emergent AMR trends. User-driven plots and session reports can be downloaded for ease of sharing. Importantly, TyphiNET is populated by high-quality genome data curated by the Global Typhoid Pathogen Genomics Consortium, analysed using the Pathogenwatch platform, and identified as coming from non-targeted sampling frames that are suitable for estimating AMR prevalence amongst Typhi infections (no personal data is included in the platform). As of February 2024, data from a total of n=11,836 genomes from 101 countries are available in TyphiNET. We outline case studies illustrating how the dashboard can be used to explore these data and gain insights of relevance to both researchers and public health policy-makers. ConclusionsThe TyphiNET dashboard provides an interactive platform for accessing genome-derived data on pathogen variant frequencies to inform typhoid control and intervention strategies. The platform is extensible in terms of both data and features, and provides a model for making complex bacterial genome-derived data accessible to a wide audience.

microbiology↗

Acquisition of a large virulence plasmid (pINV) promoted temperature-dependent virulence and global dispersal of O96:H19 enteroinvasive Escherichia coli

Enteroinvasive Escherichia coli (EIEC) and Shigella are closely related agents of bacillary dysentery. It is widely viewed that EIEC and Shigella species evolved from E. coli via independent acquisitions of a large virulence plasmid (pINV) encoding a type three secretion system (T3SS). Sequence Type (ST)99 O96:H19 E. coli is an emergent clone of EIEC responsible for recent outbreaks in Europe and South America. Here, we reconstruct the evolutionary history of ST99 E. coli using BactDating, revealing distinct phylogenomic clusters of pINV-positive and -negative isolates. To study the impact of pINV acquisition on the virulence of this clone, we developed an EIEC-zebrafish infection model showing that virulence of ST99 EIEC is thermoregulated. Strikingly, zebrafish infection using the oldest available pINV-negative isolate reveals a separate, temperature-independent mechanism of virulence, indicating that ST99 non-EIEC strains were virulent before pINV acquisition. Taken together, these results suggest that an already pathogenic E. coli acquired pINV and that virulence of ST99 isolates became thermoregulated once pINV was acquired. ImportanceEnteroinvasive Escherichia coli (EIEC) and Shigella are etiological agents of bacillary dysentery. Sequence Type (ST)99 is an emergent clone of EIEC hypothesised to cause human disease by the recent acquisition of pINV, a large plasmid encoding a type three secretion system (T3SS) that confers the ability to invade human cells. Here, using phylogenomic reconstruction and zebrafish larvae infection, we show that the virulence of ST99 EIEC isolates is highly dependent on temperature, while pINV-negative isolates encode a separate temperature-independent mechanism of virulence. These results highlight that ST99 non-EIEC isolates may have been virulent before pINV acquisition and highlight an important role for pINV acquisition in the emergence of ST99 EIEC in humans, allowing wider dissemination across Europe and South America.

microbiology↗

Five years of GenoTyphi: updates to the global Salmonella Typhi genotyping framework

In 2016 a whole genome sequence (WGS) based genotyping framework (GenoTyphi) was developed providing a phylogenetically informative nomenclature for lineages of Salmonella Typhi, the aetiological agent of typhoid fever. Subsequent surveillance studies have revealed additional epidemiologically important subpopulations, necessitating the definition of new genotypes and extension of associated software to facilitate the detection of antimicrobial resistance (AMR) mutations. Analysis of 4,632 WGS provide an updated overview of the global S. Typhi population structure and genotyping framework, revealing the widespread nature of H58 (4.3.1) genotypes and the diverse range of genotypes carrying AMR mutations.

microbiology↗

Multiple introductions of multidrug-resistant typhoid associated with acute infection and asymptomatic carriage, Kenya

Understanding the dynamics of infection and carriage of typhoid in endemic settings is critical to finding solutions to prevention and control. In a 3 year case-control study, we investigated typhoid among children aged <16 years (4,670 febrile cases and 8,549 age matched controls) living in an informal settlement, Nairobi, Kenya. 148 S. Typhi isolates from cases and 95 from controls (stool culture) were identified; a carriage frequency of 1%. Whole-genome sequencing showed 97% of cases and 88% of controls were genotype 4.3.1 (Haplotype58), with the majority of each (76% and 88%) being multidrug-resistant strains in 3 sublineages of H58 genotype (East Africa 1 (EA1), EA2, and EA3), with sequences from cases and carriers intermingled. The high rate of multidrug-resistant H58 S. Typhi, and the close phylogenetic relationships between carriers and controls, provides evidence for the role of carriers as a reservoir for the community spread of typhoid in this setting.

physiology↗

Spontaneous emergence of azithromycin resistance in independent lineages of Salmonella Typhi in Northern India

BackgroundThe emergence and spread of antimicrobial resistance (AMR) pose a major threat to the effective treatment and control of typhoid fever. The ongoing outbreak of extensively drug resistant (XDR) Salmonella Typhi (S. Typhi) in Pakistan has left azithromycin as the only remaining broadly efficacious oral antimicrobial for typhoid in South Asia. Ominously, azithromycin resistant S. Typhi organisms have been subsequently reported in Bangladesh, Pakistan, and Nepal. MethodsHere, we aimed to understand the molecular basis of AMR in 66 S. Typhi isolated in a cross-sectional study performed in a suburb of Chandigarh in Northern India using whole genome sequencing (WGS) and phylogenetic analysis. ResultsWe identified seven S. Typhi organisms with the R717Q mutation in the acrB gene that was recently found to confer resistance to azithromycin in Bangladesh. Six out of the azithromycin-resistant S. Typhi isolates also exhibited triple mutations in gyrA (S83F and D87N) and parC (S80I) genes and were resistant to ciprofloxacin. These contemporary ciprofloxacin/azithromycin-resistant isolates were phylogenetically distinct from each other and from those reported from Bangladesh, Pakistan, and Nepal. ConclusionsThe independent emergence of azithromycin resistant typhoid in Northern India reflects an emerging broader problem across South Asia and illustrates the urgent need for the introduction of typhoid conjugate vaccines (TCVs) in the region. Key pointsWe identified ciprofloxacin/azithromycin-resistant Salmonella Typhi (S. Typhi) in Chandigarh in Northern India. The independent emergence of ciprofloxacin/azithromycin-resistant typhoid in Bangladesh, Pakistan, Nepal, and India and the continued spread of extensively-drug resistant (XDR) typhoid in Pakistan highlight the limitations of licensed oral treatments for typhoid fever in South Asia.

genomics↗

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↗

A novel therapeutic antibody screening method using bacterial high-content imaging reveals functional antibody binding phenotypes of Escherichia coli ST131

The increase of antimicrobial resistance (AMR), and lack of new classes of licensed antimicrobials, have made alternative treatment options for AMR pathogens increasingly attractive. Recent studies have demonstrated anti-bacterial efficacy of a humanised monoclonal antibody (mAb) targeting the O25b O-antigen of Escherichia coli ST131. To evaluate the phenotypic effects of antibody binding to diverse clinical E. coli ST131 O25b bacterial isolates in high-throughput, we designed a novel mAb screening method using high-content imaging (HCI) and image-based morphological profiling to screen a mAb targeting the O25b O-antigen. Screening the antibody against a panel of 86 clinical E. coli ST131 O25:H4 isolates revealed 4 binding phenotypes: no binding (18.60%), weak binding (4.65%), strong binding (69.77%) and strong agglutinating binding (6.98%). Impaired antibody binding could be explained by the presence of insertion sequences or mutations in O-antigen or lipopolysaccharide core biosynthesis genes, affecting the amount, structure or chain length of the O-antigen. The agglutinating binding phenotype was linked with lower O-antigen density, enhanced antibody-mediated phagocytosis and increased serum susceptibly. This study highlights the need to screen candidate mAbs against large panels of clinically relevant isolates, and that HCI can be used to evaluate mAb binding affinity and potential functional efficacy against AMR bacteria.

microbiology↗

Population structure and antimicrobial resistance patterns of Salmonella Typhi isolates in Bangladesh from 2004 to 2016

BackgroundMulti-drug resistant typhoid fever remains an enormous public health threat in low and middle-income countries. However, we still lack a detailed understanding of the epidemiology and genomics of S. Typhi in many regions. Here we have undertaken a detailed genomic analysis of typhoid in Bangladesh to unravel the population structure and antimicrobial resistance patterns in S. Typhi isolated in between 2004-2016.\n\nPrincipal findingsWhole genome sequencing of 202 S. Typhi isolates obtained from three study locations in urban Dhaka revealed a diverse range of S. Typhi genotypes and AMR profiles. The bacterial population within Dhaka were relatively homogenous with little stratification between different healthcare facilities or age groups. We also observed evidence of transmission of Bangladeshi genotypes with neighboring South Asian countries (India, Pakistan and Nepal) suggesting these are circulating throughout the region. This analysis revealed a decline in H58 (genotype 4.3.1) isolates from 2011 onwards, coinciding with a rise in a diverse range of non-H58 genotypes and a simultaneous rise in isolates with reduced susceptibility to fluoroquinolones, potentially reflecting a change in treatment practices. We identified a novel S. Typhi genotype, subclade 3.3.2 (previously defined only to clade level, 3.3), which formed two localised clusters (3.3.2.Bd1 and 3.3.2.Bd2) associated with different mutations in the Quinolone Resistance Determining Region (QRDR) of gene gyrA.\n\nSignificanceOur analysis of S. Typhi isolates from Bangladesh isolated over a twelve year period identified a diverse range of AMR profiles and genotypes. The observed increase in non-H58 genotypes associated with reduced fluoroquinolone susceptibility may reflect a change in treatment practice in this region and highlights the importance of continued molecular surveillance to monitor the ongoing evolution of AMR in Bangladesh. We have defined new genotypes and lineages of Bangladeshi S. Typhi which will facilitate identification of these emerging AMR clones in future surveillance efforts.\n\nAuthor SummaryTyphoid fever, caused by Salmonella enterica serovar Typhi, is an acute and often life-threatening febrile illness in developing countries. Until recently, there have been limited studies focusing on the epidemiology and disease burden of typhoid in poor resource settings including Bangladesh. This study highlights the urgent need for sustained genomics based surveillance studies to monitor the population structure and ongoing evolution of AMR. Our data revealed a diverse range of S. Typhi genotypes and AMR patterns among 202 isolates collected from three urban areas in Dhaka. Moreover, we defined a new genotype, subclade 3.3.2 (previously typed only to clade level, 3.3) with two Bangladesh-localiased clades 3.3.2.Bd1 and 3.3.2.Bd2 showing reduced susceptibility to fluoroquinolones. Our data shows a significant increase in non-H58 genotypes carrying QRDR mutations from 2012 onwards, replacing MDR H58 genotypes. Our data suggest that a shift in treatment practice towards third generation cephalosporins to control typhoid might be beneficial, in addition to the introduction of vaccination programs and improvements in water sanitation and hygiene (WASH) in Bangladesh.

genomics↗

Informal genomic surveillance of regional distribution of Salmonella Typhi genotypes and antimicrobial resistance via returning travellers

Salmonella enterica serovar Typhi (S. Typhi) is the causative agent of typhoid fever, a systemic human infection with a burden exceeding 20 million cases each year that occur disproportionately among children in low and middle income countries. Antimicrobial therapy is the mainstay for treatment, but resistance to multiple agents is common. Here we report genotypes and antimicrobial resistance (AMR) determinants detected from routine whole-genome sequencing (WGS) of 533 S. Typhi isolates referred to Public Health England between April 2014 and April 2017, 488 (92%) of which had accompanying patient travel information obtained via an enhanced surveillance questionnaire. The majority of cases involved S. Typhi 4.3.1 (H58) linked with travel to South Asia (58%). Travel to East and West Africa were associated with genotypes 4.3.1 and 3.3.1, respectively. Point mutations in the quinolone resistance determining region (QRDR), associated with reduced susceptibility to fluoroquinolones, were very common (85% of all cases) but the frequency varied significantly by region of travel: 95% in South Asia, 43% in East Africa, 27% in West Africa. QRDR triple mutants, resistant to ciprofloxacin, were restricted to 4.3.1 lineage II and associated with travel to India, accounting for 23% of cases reporting travel to the country. Overall 24% of isolates were MDR, however the frequency varied significantly by region and country of travel: 27% in West Africa, 52% in East Africa, 55% in Pakistan, 24% in Bangladesh, 3% in India. MDR determinants were plasmid-borne (IncHI1 PST2 plasmids) in S. Typhi 3.1.1 linked to West Africa, but in all other regions MDR was chromosomally integrated in 4.3.1 lineage I. We propose that routine WGS data from travel-associated cases in industrialised countries could serve as informal sentinel AMR genomic surveillance data for countries where WGS is not available or routinely performed.\n\nAuthor SummaryOur data demonstrate how routine WGS data produced by Public Health England can be further mined for informal passive surveillance of Salmonella Typhi circulating in different geographical regions where typhoid is endemic. We have shown the public health utility of a simplified approach to WGS reporting based on the GenoTyphi genotyping framework and nomenclature, which doesnt require the generation of a phylogenetic tree or other phylogenetic analysis. These approaches yielded results consistent with previously reported antimicrobial resistance (AMR) patterns of S. Typhi, including prevalence of multi-drug resistant (MDR) and fluoroquinolone resistance in different regions in association with different pathogen variants. These data provide a rationale and framework for the extraction and reporting of geographically stratified genotype and AMR data from public health labs in non-endemic countries. Prospective analysis and reporting of such data could potentially detect shifts in regional S. Typhi populations, such as replacement or spread of different subclades and the emergence and dissemination of MDR, fluoroquinolone resistant and/or extensively drug resistant S. Typhi, providing valuable data to inform typhoid control measures in low and middle income countries that are still building their genomics capacity.

microbiology↗

Laboratory and Molecular Surveillance of Paediatric Typhoidal Salmonella in Nepal: Antimicrobial Resistance and Implications for Vaccine Policy

BackgroundChildren are substantially affected by enteric fever in most settings with a high burden of the disease, which could be due to immune naivety, or enhanced risk of exposure to the pathogen. Although Nepal is a high burden setting for enteric fever, the bacterial population structure and transmission dynamics are poorly delineated in young children, the proposed target group for immunization programs.\n\nMethodsBlood culture surveillance amongst children aged 2 months to 15 years of age was conducted at Patan Hospital between 2008 and 2016. A total of 198 S. Typhi and 66 S. Paratyphi A isolated from children treated in both inpatient and outpatient settings were subjected to whole genome sequencing and antimicrobial susceptibility testing. Demographic and clinical data were also collected from the inpatients. The resulting data were used to place these paediatric Nepali isolates into a worldwide context, based on their phylogeny and carriage of molecular determinants of antimicrobial resistance (AMR).\n\nResultsChildren aged [&le;]4 years made up >40% of the inpatient population. The majority of isolates (78 %) were S. Typhi, comprising several distinct genotypes but dominated by 4.3.1 (H58). Several distinct S. Typhi genotypes were identified, but the globally disseminated S. Typhi clade 4.3.1 (H58) dominated. The majority of isolates (86%) were insusceptible to fluoroquinolones. This was mainly associated with S. Typhi H58 Lineage II and S. Paratyphi A; non-susceptible strains from these two genotypes accounted for 50% and 25% of all enteric fever cases. Multi-drug resistance (MDR) was rare (3.5% of S. Typhi, 0 S. Paratyphi A) and restricted to chromosomal insertions of AMR genes in H58 lineage I strains. Comparison to global data sets showed the local S. Typhi and S. Paratyphi A strains had close genetic relatives in other South Asian countries, indicating regional strain circulation.\n\nConclusionsThese data indicate that enteric fever in Nepal continues to be a major public health issue with ongoing inter- and intra-country transmission, and highlights the need for regional coordination of intervention strategies. The absence of a S. Paratyphi A vaccine is cause for concern, given its prevalence as an enteric fever agent in this setting, and the large proportion of isolates displaying fluoroquinolone resistance. This study also highlights an urgent need for routine laboratory and molecular surveillance to monitor the epidemiology of enteric fever and evolution of antimicrobial resistance within the bacterial population as a means to facilitate public health interventions in prevention and control of this febrile illness.

molecular biology↗

Inferring demographic parameters in bacterial genomic data using Bayesian and hybrid phylogenetic methods

BackgroundRecent developments in sequencing technologies make it possible to obtain genome sequences from a large number of isolates in a very short time. Bayesian phylogenetic approaches can take advantage of these data by simultaneously inferring the phylogenetic tree, evolutionary timescale, and demographic parameters (such as population growth rates), while naturally integrating uncertainty in all parameters. Despite their desirable properties, Bayesian approaches can be computationally intensive, hindering their use for outbreak investigations involving genome data for a large numbers of pathogen isolates. An alternative to using full Bayesian inference is to use a hybrid approach, where the phylogenetic tree and evolutionary timescale are estimated first using maximum likelihood. Under this hybrid approach, demographic parameters are inferred from estimated trees instead of the sequence data, using maximum likelihood, Bayesian inference, or approximate Bayesian computation. This can vastly reduce the computational burden, but has the disadvantage of ignoring the uncertainty in the phylogenetic tree and evolutionary timescale.\n\nResultsWe compared the performance of a fully Bayesian and a hybrid method by analysing six whole-genome SNP data sets from a range of bacteria and simulations. The estimates from the two methods were very similar, suggesting that the hybrid method is a valid alternative for very large datasets. However, we also found that congruence between these methods is contingent on the presence of strong temporal structure in the data (i.e. clocklike behaviour), which is typically verified using a date-randomisation test in a Bayesian framework. To reduce the computational burden of this Bayesian test we implemented a date-randomisation test using a rapid maximum likelihood method, which has similar performance to its Bayesian counterpart.\n\nConclusionsHybrid approaches can produce reliable inferences of evolutionary timescales and phylodynamic parameters in a fraction of the time required for fully Bayesian analyses. As such, they are a valuable alternative in outbreak studies involving a large number of isolates.

bioinformatics↗