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Antibiotic resistance is a major problem in Salmonella enterica serovar Typhi, the causative agent of typhoid. Multidrug-resistant (MDR) isolates are prevalent in parts of Asia and Africa and are often associated with the dominant H58 haplotype. Reduced susceptibility to fluoroquinolones is also widespread, and sporadic cases of resistance to third-generation cephalosporins or azithromycin have also been reported. Here, we report the first large-scale emergence and spread of a novel S . Typhi clone harboring resistance to three first-line drugs (chloramphenicol, ampicillin, and trimethoprim-sulfamethoxazole) as well as fluoroquinolones and third-generation cephalosporins in Sindh, Pakistan, which we classify as extensively drug resistant (XDR). Over 300 XDR typhoid cases have emerged in Sindh, Pakistan, since November 2016. Additionally, a single case of travel-associated XDR typhoid has recently been identified in the United Kingdom. Whole-genome sequencing of over 80 of the XDR isolates revealed remarkable genetic clonality and sequence conservation, identified a large number of resistance determinants, and showed that these isolates were of haplotype H58. The XDR S . Typhi clone encodes a chromosomally located resistance region and harbors a plasmid encoding additional resistance elements, including the bla CTX-M-15 extended-spectrum β-lactamase, and carrying the qnrS fluoroquinolone resistance gene. This antibiotic resistance-associated IncY plasmid exhibited high sequence identity to plasmids found in other enteric bacteria isolated from widely distributed geographic locations. This study highlights three concerning problems: the receding antibiotic arsenal for typhoid treatment, the ability of S . Typhi to transform from MDR to XDR in a single step by acquisition of a plasmid, and the ability of XDR clones to spread globally. IMPORTANCE Typhoid fever is a severe disease caused by the Gram-negative bacterium Salmonella enterica serovar Typhi. Antibiotic-resistant S . Typhi strains have become increasingly common. Here, we report the first large-scale emergence and spread of a novel extensively drug-resistant (XDR) S . Typhi clone in Sindh, Pakistan. The XDR S . Typhi is resistant to the majority of drugs available for the treatment of typhoid fever. This study highlights the evolving threat of antibiotic resistance in S . Typhi and the value of antibiotic susceptibility testing and whole-genome sequencing in understanding emerging infectious diseases. We genetically characterized the XDR S . Typhi to investigate the phylogenetic relationship between these isolates and a global collection of S . Typhi isolates and to identify multiple genes linked to antibiotic resistance. This S . Typhi clone harbored a promiscuous antibiotic resistance plasmid previously identified in other enteric bacteria. The increasing antibiotic resistance in S . Typhi observed here adds urgency to the need for typhoid prevention measures. Typhoid fever is a severe disease caused by the Gram-negative bacterium Salmonella enterica serovar Typhi. Antibiotic-resistant S . Typhi strains have become increasingly common. Here, we report the first large-scale emergence and spread of a novel extensively drug-resistant (XDR) S . Typhi clone in Sindh, Pakistan. The XDR S . Typhi is resistant to the majority of drugs available for the treatment of typhoid fever. This study highlights the evolving threat of antibiotic resistance in S . Typhi and the value of antibiotic susceptibility testing and whole-genome sequencing in understanding emerging infectious diseases. We genetically characterized the XDR S . Typhi to investigate the phylogenetic relationship between these isolates and a global collection of S . Typhi isolates and to identify multiple genes linked to antibiotic resistance. This S . Typhi clone harbored a promiscuous antibiotic resistance plasmid previously identified in other enteric bacteria. The increasing antibiotic resistance in S . Typhi observed here adds urgency to the need for typhoid prevention measures.

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. Whole genome sequencing data are increasingly becoming routinely available but generating actionable insights is challenging. Here, the authors describe Pathogenwatch, a web tool for genomic surveillance of S. Typhi, and demonstrate its use for antimicrobial resistance assignment and strain risk assessment.

We present CoronaHiT, a platform and throughput flexible method for sequencing SARS-CoV-2 genomes (≤ 96 on MinION or > 96 on Illumina NextSeq) depending on changing requirements experienced during the pandemic. CoronaHiT uses transposase-based library preparation of ARTIC PCR products. Method performance was demonstrated by sequencing 2 plates containing 95 and 59 SARS-CoV-2 genomes on nanopore and Illumina platforms and comparing to the ARTIC LoCost nanopore method. Of the 154 samples sequenced using all 3 methods, ≥ 90% genome coverage was obtained for 64.3% using ARTIC LoCost, 71.4% using CoronaHiT-ONT and 76.6% using CoronaHiT-Illumina, with almost identical clustering on a maximum likelihood tree. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally.

Colorectal cancer (CRC) is the fourth most common cancer and the third leading cause of cancer-related mortality worldwide, with incidence rising among younger populations. The significant clinical and economic burden highlights the need for minimally invasive technologies capable of detecting pre-malignant and early-stage disease. Although liquid biopsy approaches have advanced, they have not achieved sufficient performance for clinical adoption when compared with colonoscopy, the current diagnostic gold standard. CRC is a mucosal pathology, yet current diagnostic methods have not leveraged mucosal biology. Here we demonstrate the clinical utility of rectal mucus specimens, collected using a minimally invasive device in an outpatient setting, without bowel preparation. Through a hologenomic approach integrating host and microbial genomics, we identify genetic and epigenetic aberrations and perturbations in microbial communities that drive the detection of adenomatous polyps and CRC in rectal mucus. Hologenomic integration enables superior stratification of CRC by disease site and stage compared with single-omics methods. In summary, we demonstrate the clinical utility of rectal mucus sampling combined with hologenomic analysis as a translatable prospective tool for diagnostic application. Colorectal cancer is often diagnosed at later stages, leading to poor prognosis. Here, the authors utilise analysis of rectal mucus specimens using host and microbial analysis to detect cancer lesions.

The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant (first detected in November 2021) exhibited a high degree of immune evasion, leading to increased infection rates worldwide. However, estimates of the magnitude of this Omicron wave have often relied on routine testing data, which are prone to several biases. Using data from the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys assessing prevalence of SARS-CoV-2 infection in England, we estimated the dynamics of England’s Omicron wave (from 9 September 2021 to 1 March 2022). We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct variants, intermittent epidemics of similar magnitudes may become the ‘new normal’. This study presents data from the REACT-1 SARS-CoV-2 community sampling study in England from November 2021 to March 2022. They show that the Omicron variant peaked in January with a prevalence of ~7% and that the BA.2 sublineage had a 1.5x higher reproduction number compared to other Omicron sublineages.

Rapid transmission of the SARS-CoV-2 Omicron variant has led to record-breaking case incidence rates around the world. Since May 2020, the REal-time Assessment of Community Transmission-1 (REACT-1) study tracked the spread of SARS-CoV-2 infection in England through RT-PCR of self-administered throat and nose swabs from randomly-selected participants aged 5 years and over. In January 2022, we found an overall weighted prevalence of 4.41% (n = 102,174), three-fold higher than in November to December 2021; we sequenced 2,374 (99.2%) Omicron infections (19 BA.2), and only 19 (0.79%) Delta, with a growth rate advantage for BA.2 compared to BA.1 or BA.1.1. Prevalence was decreasing overall (reproduction number R = 0.95, 95% credible interval [CrI], 0.93, 0.97), but increasing in children aged 5 to 17 years (R = 1.13, 95% CrI, 1.09, 1.18). In England during January 2022, we observed unprecedented levels of SARS-CoV-2 infection, especially among children, driven by almost complete replacement of Delta by Omicron. The REACT-1 study measures the community prevalence of SARS-CoV-2 in England through repeated cross-sectional surveys. Here, the authors present data from REACT-1 that document the increase in infection prevalence, particularly among children, associated with the Omicron variant in January 2022.

Background Clinical metagenomics (CMg) has the potential to be translated from a research tool into routine service to improve antimicrobial treatment and infection control decisions. The SARS-CoV-2 pandemic provides added impetus to realise these benefits, given the increased risk of secondary infection and nosocomial transmission of multi-drug-resistant (MDR) pathogens linked with the expansion of critical care capacity. Methods CMg using nanopore sequencing was evaluated in a proof-of-concept study on 43 respiratory samples from 34 intubated patients across seven intensive care units (ICUs) over a 9-week period during the first COVID-19 pandemic wave. Results An 8-h CMg workflow was 92% sensitive (95% CI, 75–99%) and 82% specific (95% CI, 57–96%) for bacterial identification based on culture-positive and culture-negative samples, respectively. CMg sequencing reported the presence or absence of β-lactam-resistant genes carried by Enterobacterales that would modify the initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus from 4 positive and 39 negative samples. Molecular typing using 24-h sequencing data identified an MDR- K. pneumoniae ST307 outbreak involving 4 patients and an MDR- C. striatum outbreak involving 14 patients across three ICUs. Conclusion CMg testing provides accurate pathogen detection and antibiotic resistance prediction in a same-day laboratory workflow, with assembled genomes available the next day for genomic surveillance. The provision of this technology in a service setting could fundamentally change the multi-disciplinary team approach to managing ICU infections. The potential to improve the initial targeted treatment and rapidly detect unsuspected outbreaks of MDR-pathogens justifies further expedited clinical assessment of CMg.

Salmonella enterica serovar Weltevreden (S. Weltevreden) is an emerging cause of diarrheal and invasive disease in humans residing in tropical regions. Despite the regional and international emergence of this Salmonella serovar, relatively little is known about its genetic diversity, genomics or virulence potential in model systems. Here we used whole genome sequencing and bioinformatics analyses to define the phylogenetic structure of a diverse global selection of S. Weltevreden. Phylogenetic analysis of more than 100 isolates demonstrated that the population of S. Weltevreden can be segregated into two main phylogenetic clusters, one associated predominantly with continental Southeast Asia and the other more internationally dispersed. Subcluster analysis suggested the local evolution of S. Weltevreden within specific geographical regions. Four of the isolates were sequenced using long read sequencing to produce high quality reference genomes. Phenotypic analysis in Hep-2 cells and in a murine infection model indicated that S. Weltevreden were significantly attenuated in these models compared to the classical S. Typhimurium reference strain SL1344. Our work outlines novel insights into this important emerging pathogen and provides a baseline understanding for future research studies.

Bacteria need to survive in a wide range of environments. Currently, there is an incomplete understanding of the genetic basis for mechanisms underpinning survival in stressful conditions, such as the presence of anti-microbials. Transposon directed insertion-site sequencing (TraDIS) is a powerful tool to identify genes and networks which are involved in survival and fitness under a given condition by simultaneously assaying the fitness of millions of mutants, thereby relating genotype to phenotype and contributing to an understanding of bacterial cell biology. A recent refinement of this approach allows the roles of essential genes in conditional stress survival to be inferred by altering their expression. These advancements combined with the rapidly falling costs of sequencing now allows comparisons between multiple experiments to identify commonalities in stress responses to different conditions. This capacity however poses a new challenge for analysis of multiple data sets in conjunction. To address this analysis need, we have developed 'AlbaTraDIS'; a software application for rapid large-scale comparative analysis of TraDIS experiments that predicts the impact of transposon insertions on nearby genes. AlbaTraDIS can identify genes which are up or down regulated, or inactivated, between multiple conditions, producing a filtered list of genes for further experimental validation as well as several accompanying data visualisations. We demonstrate the utility of our new approach by applying it to identify genes used by Escherichia coli to survive in a wide range of different concentrations of the biocide Triclosan. AlbaTraDIS identified all well characterised Triclosan resistance genes, including the primary target, fabI. A number of new loci were also implicated in Triclosan resistance and the predicted phenotypes for a selection of these were validated experimentally with results being consistent with predictions. AlbaTraDIS provides a simple and rapid method to analyse multiple transposon mutagenesis data sets allowing this technology to be used at large scale. To our knowledge this is the only tool currently available that can perform these tasks. AlbaTraDIS is written in Python 3 and is available under the open source licence GNU GPL 3 from

Background The emergence of SARS-CoV-2 variants including the Delta and Omicron along with waning of vaccine-induced immunity over time contributed to increased rates of breakthrough infection specifically among healthcare workers (HCWs). SARS-CoV-2 genomic surveillance is an important tool for timely detection and characterization of circulating variants as well as monitoring the emergence of new strains. Our study is the first national SARS-CoV-2 genomic surveillance among HCWs in Lebanon. Methods We collected 250 nasopharyngeal swabs from HCWs across Lebanon between December 2021 and January 2022. Data on the date of positive PCR, vaccination status, specific occupation, and hospitalization status of participants were collected. Extracted viral RNA from nasopharyngeal swabs was converted to cDNA, library prepped using the coronaHIT method, followed by whole genome sequencing on the Illumina NextSeq 500 platform. Results A total of 133 (57.1%) samples belonging to the Omicron (BA.1.1) sub-lineage were identified, as well as 44 (18.9%) samples belonging to the BA.1 sub-lineage, 28 (12%) belonging to the BA.2 sub-lineage, and only 15 (6.6%) samples belonging to the Delta variant sub-lineage B.1.617.2. These results show that Lebanon followed the global trend in terms of circulating SARS-CoV-2 variants with Delta rapidly replaced by the Omicron variant. Conclusion This study underscores the importance of continuous genomic surveillance programs in Lebanon for the timely detection and characterization of circulating variants. The latter is critical to guide public health policy making and to timely implement public health interventions.