Adam A. Witney

Horizontal gene transfer (HGT) via generalised transduction is a major driver of antimicrobial resistance (AMR) in Staphylococcus aureus , yet the genetic barriers regulating phage-mediated transfer remain poorly defined. Using a co-culture gene transfer rate assay (COGTRA) that quantifies phage-dependent resistance gene exchange under competitive, antibiotic-free conditions, we screened 1,920 mutants from the Nebraska Transposon Mutant Library for elevated transfer. We identified 32 validated high-transfer mutants that act as HGT barriers, 66% of which clustered within two chromosomal regions that we term S. aureus Transfer Islands (SauTI1 and SauTI2). SauTI loci restricted generalised transduction bidirectionally, and SauTI1 genes were widespread across S. aureus genomes yet showed lineage-specific variation. SauTI1 encodes an SMC2–Cbf1 condensin–nuclease module whose disruption markedly increases generalised transduction and plasmid transfer, resembling Wadjet-like restriction systems. Together, these findings identify clustered defence loci that restrict HGT in S. aureus and identify SauTIs as key regulators of AMR evolution.

Novel antiviral drugs targeting DNA viruses are desirable. Previous studies from our laboratory and others have demonstrated that DNA binding bisbenzimide compounds are capable of inhibiting replication of diverse DNA viruses, such as a herpesvirus and prototype or pandemic potential poxviruses. To further the aforementioned studies, we sought to identify a bisbenzimide compound that had been successfully administered to humans and repurpose that compound as a broadly acting antiviral compound. We found that the previously described bisbenzimide antibiotic Ridinilazole was a potent inhibitor of human cytomegalovirus (HCMV) at sub-micromolar concentrations, with no obvious effect on cell viability. However, inhibition of virus replication by Ridinilazole was selective, as Ridinilazole had no obvious effect on the replication of another DNA virus (herpes simplex virus) or an RNA virus (influenza). Based upon our bioinformatic analysis of viral genome content, we propose that the number of putative Ridinilazole binding sites in a viral DNA genome is important for the antiviral action of Ridinilazole. Western blotting and electron microscopy revealed that Ridinilazole had no obvious effect on HCMV protein production, but did decrease the number of HCMV capsids in the cytoplasm. Overall, we identified an antibiotic compound previously used in humans that could be repurposed as an antiviral compound to efficaciously inhibit replication of HCMV.

Background Delays in accurate diagnosis of drug resistant tuberculosis (DR-TB) can hinder treatment. Whole genome sequencing (WGS) provides more information than standard molecular and phenotypic testing, but commonly used platforms are expensive to implement, and data interpretation requires significant expertise. Aims We aimed to optimise a TB WGS diagnostic pipeline balancing user-friendliness, cost- effectiveness and time to results, whilst ensuring accuracy. Materials and methods Growth conditions, DNA extraction protocols and Oxford Nanopore Technologies (ONT) library preparation kits were compared. Software for basecalling and analysis were evaluated to find the most accurate resistance SNP and lineage predictor. Results Optimally, a spin-column CTAB DNA extraction method was combined with the RBK110.96 library preparation kit, high accuracy basecalling and data analysis using TB-Profiler. Compared with Illumina, the pipeline was concordant for 16/17 (94%) isolates (lineage) and for 17/17 (100%) isolates (resistance SNPs). Our pipeline was 71% (12/17) concordant with phenotypic drug susceptibility test (DST) results. Time-to-diagnosis was around four weeks. Conclusions This optimised TB sequencing pipeline requires less time expertise to run and analyse than Illumina, takes less time than phenotypic DSTs and the results are comparable with Illumina. The cost per sample is comparable with other methods. These features make it an important tool for incorporating into routine DR-TB diagnostic pipelines and larger scale drug resistance surveillance in all settings.

The detection of antimicrobial resistance (AMR) markers directly from genomic or metagenomic data is becoming a standard clinical and public health procedure. This has resulted in the development of a number of different bioinformatic AMR prediction tools. Although many may implement similar principles, these tools differ significantly in their supported inputs, search algorithms, parameterisation, and underlying reference databases. Each of these tools generates a report of detected AMR genes or variants in a distinct, non-standard, format. This presents a huge barrier to the comparison of results and to the modularity of tools for AMR gene prediction within bioinformatic workflows. In collaboration with 17 public health laboratories across 10 countries, the Public Health Alliance for Genomic Epidemiology (PHA4GE) ( https://pha4ge.org ) data structures working group has developed and piloted a standardized output specification for the bioinformatic detection of AMR from microbial genomes. In this report, we discuss hAMRonization, a python package and command-line utility, which implements PHA4GE’s AMR specification to combine the outputs of disparate antimicrobial resistance gene detection tools into a single unified format. hAMRonization can be easily extended and currently supports 18 different tools (both species-agnostic and species-specific) for the detection of genes and/or variants conferring AMR. The harmonized reports are available in tabular form, JSON format or through an interactive HTML file (e.g., https://maguire-lab.github.io/assets/interactive_report_demo.html ) that can be opened within the browser for navigable data exploration. As of 2024-03-07 hAMRonization has been downloaded ∼12,500 times, incorporated into >9 public bioinformatic tools and workflows, and been internally adopted by several national and international public health groups. The hAMRonization tool and underlying specification are open-source and freely available through PyPI, conda and GitHub ( https://github.com/pha4ge/hAMRonization ).

The bacillus Calmette–Guérin (BCG) vaccine has been in use for prevention of tuberculosis for over a century. It remains the only widely available tuberculosis vaccine and its protective efficacy has varied across geographical regions. Since it was developed, the BCG vaccine strain has been shared across different laboratories around the world, where use of differing culture methods has resulted in genetically distinct strains over time. Whilst differing BCG vaccine efficacy around the world is well documented, and the reasons for this may be multifactorial, it has been hypothesized that genetic differences in BCG vaccine strains contribute to this variation. Isolates from an historic archive of lyophilized BCG strains were regrown, DNA was extracted and then whole-genome sequenced using Oxford Nanopore Technologies. The resulting whole-genome data were plotted on a phylogenetic tree and analysed to identify the presence or absence of regions of difference (RDs) and single-nucleotide polymorphisms (SNPs) relating to virulence, growth and cell wall structure. Of 50 strains available, 36 were revived in culture and 39 were sequenced. Morphology differed between the strains distributed before and after 1934. There was phylogenetic association amongst certain geographically classified strains, most notably BCG-Russia, BCG-Japan and BCG-Danish. RD2, RD171 and RD713 deletions were associated with late strains (seeded after 1927). When mapped to BCG-Pasteur 1172, the SNPs in sigK, plaA, mmaA3 and eccC5 were associated with early strains. Whilst BCG-Russia, BCG-Japan and BCG-Danish showed strong geographical isolate clustering, the late strains, including BCG-Pasteur, showed more variation. A wide range of SNPs were seen within geographically classified strains, and as much intra-strain variation as between-strain variation was seen. The date of distribution from the original Pasteur laboratory (early pre-1927 or late post-1927) gave the strongest association with genetic differences in regions of difference and virulence-related SNPs, which agrees with the previous literature.

Microbiota composition in breast milk affects intestinal and respiratory microbiota colonization and the mucosal immune system’s development in infants. The metabolomic content of breast milk is thought to interact with the microbiota and may influence developing infant immunity. One hundred seven Gambian mothers and their healthy, vaginally delivered, exclusively breastfed infants were included in our study. We analyzed 32 breast milk samples, 51 maternal rectovaginal swabs and 30 infants’ rectal swabs at birth. We also analyzed 9 breast milk samples and 18 infants’ nasopharyngeal swabs 60 days post-delivery. We used 16S rRNA gene sequencing to determine the microbiota composition. Metabolomic profiling analysis was performed on colostrum and mature breast milk samples using a multiplatform approach combining 1-H Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry. Bacterial communities were distinct in composition and diversity across different sample types. Breast milk composition changed over the first 60 days of lactation. α-1,4- and α-1,3-fucosylated human milk oligosaccharides, and other 33 key metabolites in breast milk (monosaccharides, sugar alcohols and fatty acids) increased between birth and day 60 of life. This study’s results indicate that infant gut and respiratory microbiota are unique bacterial communities, distinct from maternal gut and breast milk, respectively. Breast milk microbiota composition and metabolomic profile change throughout lactation. These changes may contribute to the infant’s immunological, metabolic, and neurological development and could consist the basis for future interventions to correct disrupted early life microbial colonization.

Background: Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is a continuing global health challenge. Limitations to current national surveillance systems for reporting AMR trends, alongside reduction in culture-based diagnostics and susceptibility testing, has led to an increasing need for rapid diagnostics and identification of circulating N. gonorrhoeae strains. We investigated nanopore based sequencing time and depth needed to accurately identify closely related N. gonorrhoeae isolates, compared to Illumina MiSeq sequencing. Methods: N. gonorrhoeae strains prospectively collected from a London Sexual Health clinic were sequenced on both Illumina MiSeq and Oxford Nanopore Technologies (ONT) MinION platforms. Accuracy was determined by comparing variant calls at 68 nucleotide positions representing 37 pre-characterised resistance associated markers in N. gonorrhoeae . Accuracy at varying MinION sequencing depths were determined through retrospective analysis of time-stamped reads. Results: Of the 22 MinION-MiSeq sequence pairs that reached sufficient depth of coverage for comparison, overall agreement of variant call positions passing quality control criteria was 185/185 (95% CI: 98.0-100.0), 502/503 (95% CI: 98.9-99.9) and 564/565 (95% CI: 99.0-100.0) at 10x, 30x and 40x MinION depth, respectively. Isolates found to be genetically closely related by MiSeq, that is within one yearly evolutionary distance of ≤5 single nucleotide polymorphisms, were accurately identified as such via MinION. Conclusion: Nanopore based sequencing shows utility for use as a rapid surveillance tool to correctly detect closely related N. gonorrhoeae strains, with just 10x sequencing depth, taking a median sequencing time of 29 minutes. This highlights its potential utility for tracking local gonorrhoea transmission and AMR markers.

Background: The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. Results: As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. Conclusions: Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database.

Background: Acquired long QT syndrome (aLQTS) is a serious unpredictable adverse drug reaction. Pharmacogenomic markers may predict risk. Methods: Among 153 aLQTS patients (mean age 58 years [range, 14–88], 98.7% White, 85.6% symptomatic), computational methods identified proteins interacting most significantly with 216 QT-prolonging drugs. All cases underwent sequencing of 31 candidate genes arising from this analysis or associating with congenital LQTS. Variants were filtered using a minor allele frequency <1% and classified for susceptibility for aLQTS. Gene-burden analyses were then performed comparing the primary cohort to control exomes (n=452) and an independent replication aLQTS exome sequencing cohort. Results: In 25.5% of cases, at least one rare variant was identified: 22.2% of cases carried a rare variant in a gene associated with congenital LQTS, and in 4% of cases that variant was known to be pathogenic or likely pathogenic for congenital LQTS; 7.8% cases carried a cytochrome-P450 (CYP) gene variant. Of 12 identified CYP variants, 11 (92%) were in an enzyme known to metabolize at least one culprit drug to which the subject had been exposed. Drug-drug interactions that affected culprit drug metabolism were found in 19% of cases. More than one congenital LQTS variant, CYP gene variant, or drug interaction was present in 7.8% of cases. Gene-burden analyses of the primary cohort compared to control exomes (n=452), and an independent replication aLQTS exome sequencing cohort (n=67) and drug-tolerant controls (n=148) demonstrated an increased burden of rare (minor allele frequency<0.01) variants in CYP genes but not LQTS genes. Conclusions: Rare susceptibility variants in CYP genes are emerging as potentially important pharmacogenomic risk markers for aLQTS and could form part of personalized medicine approaches in the future.

Objectives: A lactobacilli-dominated vaginal microbiome may protect against pelvic inflammatory disease (PID), but one dominated byGardnerellaspecies might increase susceptibility. Not all lactobacilli are equally protective. Recent research suggests that D(−) isomer lactic acid producing lactobacilli (Lactobacillus crispatus, Lactobacillus jenseniiandLactobacillus gasseri) may protect against infection withChlamydia trachomatis, an important cause of PID.Lactobacillus iners,which produces L(+) isomer lactic acid, may be less protective. We investigated the microbiome in stored vaginal samples from participants who did or did not develop PID during the prevention of pelvic infection (POPI) chlamydia screening trial.Methods: Long-read 16S rRNA gene nanopore sequencing was used on baseline vaginal samples (one per participant) from all 37 women who subsequently developed clinically diagnosed PID during 12-month follow-up, and 111 frequency matched controls who did not, matched on four possible risk factors for PID: age L. iners, L. crispatusandGardnerella vaginalis. There was no association between a more diverse,G. vaginalisdominated microbiome and subsequent PID, although increased Shannon diversity was associated with black ethnicity (p=0.002) and bacterial vaginosis (diagnosed by Gram stain p<0.0001). Women who developed PID had similar relative abundance of protective D(−) isomer lactic acid producing lactobacilli to women without PID, but numbers of PID cases were small.Conclusions: In the first-ever community-based prospective study of PID, there was no clear association between the vaginal microbiome and subsequent development of PID. Future studies using serial samples may identify vaginal microbial communities that may predispose to PID.