Biology subjects

Hopkins, S.

Publications and source records attributed to Hopkins, S..

8 recordsLinked to original sources

bioRxiv2025

Nanopore long-read only genome assembly of clinical Enterobacterales isolates is complete and accurate

Whole bacterial genome sequence reconstruction using Oxford Nanopore Technologies ("Nanopore") long-read only sequencing may offer a lower-cost, higher-throughput alternative for pathogen surveillance to hybrid assembly with recent improvements in Nanopore sequencing accuracy. We evaluated the accuracy, including plasmid reconstruction, of Nanopore long-read only genome assemblies of Enterobacterales. We sequenced 92 genomes from clinical Enterobacterales isolates, collected in England under a national surveillance program, with long-read Nanopore (R10.4.1, Dorado v5.0.0 super-high-accuracy basecalled) and short-read Illumina (NovaSeq) sequencing approaches. Genomes were assembled using three long-read only (Flye; Hybracter long; Autocycler), and three hybrid assemblers (Hybracter hybrid; Unicycler normal; bold). Three polishing modalities (Medaka v2 with subsampled or un-subsampled long-reads; Polypolish + Pypolca with short-reads) were investigated. Autocycler circularised the most chromosomes (87/92 [95%]). Plasmid sequence reconstruction was comparable between all assemblers except Flye, all recovering 90-96% of plasmids, although the ground truth was uncertain. Flye performed worse than other assemblers on almost all metrics. Autocycler + Medaka (un-subsampled long-reads) was the most accurate long-read only assembler/polisher combination, comparable to hybrid assemblies (median 0 [IQR:0-0] SNPs and 0 [IQR:0-1] indels per genome; quality value/Q score, 100 [IQR: 64-100]), with only 4/92 genome sequences having >10 SNPs/indels. Medaka polishing with un-subsampled long-reads resulted in small improvements in indels but not SNPs for both Flye and Autocycler assemblies. Seven-locus MLST, antimicrobial resistance, virulence, and stress gene annotation was equivalent across assembler/polisher combinations. Nanopore long-read only bacterial genome assembly with Autocycler combined with Medaka polishing (using un-subsampled reads) is similarly accurate and possibly more complete than hybrid assemblies, representing a viable alternative for incorporating high-quality genomic data, including plasmids, into Enterobacterales surveillance. Data SummaryNanopore long-reads and Illumina short-reads from the 92 Enterobacterales isolates from this study have been uploaded to ENA (BioProject accession: PRJEB93885). Code for the Nextflow assembly pipeline, downstream analysis scripts, and R statistical analysis scripts are available on GitHub (https://github.com/oxfordmmm/NEKSUS_ont_hybrid_assembly_comparison). The following supplementary data tables are available on FigShare (https://figshare.com/account/home#/projects/253775): O_LIENA Sample accessions and sample metadata (accessions_and_metadata.csv) C_LIO_LISeqkit stats summaries of the Illumina and Nanopore reads (raw_qc_sup.cav) C_LIO_LISummary of assembly contig features (contigs_summary_sup_cleaned.csv) C_LIO_LIPairwise mash distances between contigs (mash_cleaned.csv) C_LIO_LIPlasmids matching across different assemblers compared to the Hybracter (hybrid) and manually-curated reference sets (plasmids_match_hybracter_mash.csv; plasmids_match_manual_mash.csv, respectively) C_LIO_LISeven-locus multi-locus sequence type annotation (mlst_cleaned.csv) C_LIO_LICheckM2 summaries of assemblies (checkm2_cleaned.csv) C_LIO_LINucleotide-level accuracy of assemblies (SNP, Indels, and Quality value compared to short-read mapping; assembly_nucleotide_accuracy_cleaned.csv) C_LIO_LIBakta annotation (bakta_by_contig_cleaned.csv) C_LIO_LIAMRFinderPlus annotations of contigs (amrfinder_plus_cleaned.csv) C_LIO_LIMOB-suite annotation summaries of contigs (mobsuite_cleaned.csv) C_LI Impact StatementNanopore long-reads have historically been too error-prone to use alone for accurate bacterial genome assembly, necessitating additional Illumina short-reads to achieve structurally complete and accurate hybrid genome assemblies for public health surveillance. This increases cost and complexity. Previous studies have shown that recent improvements in Nanopore chemistry (R10.4.1 flowcell) and basecalling (super-high accuracy) allow high-quality long-read only assemblies on a small number of laboratory reference strains. This is the first evaluation, to our knowledge, to assess Nanopore long-read only genome assembly compared with hybrid assembly on a large number of clinical isolates. In addition, this is the first large-scale evaluation of the recently released automated consensus long-read assembly tool, Autocycler. We show that Autocycler long-read only assemblies are more structurally complete for chromosomal sequences, while reconstructing a similar number of plasmids to other long-read and hybrid assemblers. Most long-read polished, Autocycler-assembled genome sequences have 0 errors (median: 0 SNPs/indels) relative to a short-read polished (hybrid) Autocycler assemblies, enabling accurate annotation of key genes.

bioinformatics↗

bioRxiv2023

A workflow for the detection of antibiotic residues, measurement of water chemistry and preservation of hospital sink drain samples for metagenomic sequencing

Structured summaryO_ST_ABSBackgroundC_ST_ABSHospital sinks are environmental reservoirs that harbour healthcare-associated (HCA) pathogens. Selective pressures in sink environments, such as antibiotic residues, nutrient waste and hardness ions, may promote antibiotic resistance gene (ARG) exchange between bacteria. However, cheap and accurate sampling methods to characterise these factors are lacking. AimTo validate a workflow to detect antibiotic residues and evaluate water chemistry using dipsticks. Secondarily, to validate boric acid to preserve the taxonomic and ARG ("resistome") composition of sink trap samples for metagenomic sequencing. MethodsAntibiotic residue dipsticks were validated against serial dilutions of ampicillin, doxycycline, sulfamethoxazole and ciprofloxacin, and water chemistry dipsticks against serial dilutions of chemical calibration standards. Sink trap aspirates were used for a "real-world" pilot evaluation of dipsticks. To assess boric acid as a preservative of microbial diversity, the impact of incubation with and without boric acid at [~]22{degrees}C on metagenomic sequencing outputs was evaluated at Day 2 and Day 5 compared with baseline (Day 0). FindingsThe limits of detection for each antibiotic were: 3{micro}g/L (ampicillin), 10{micro}g/L (doxycycline), 20{micro}g/L (sulfamethoxazole) and 8{micro}g/L (ciprofloxacin). The best performing water chemistry dipstick correctly characterised 34/40 (85%) standards in a concentration-dependent manner. One trap sample tested positive for the presence of tetracyclines and sulfonamides. Taxonomic and resistome composition were largely maintained after storage with boric acid at [~]22{degrees}C for up to five days. ConclusionsDipsticks can be used to detect antibiotic residues and characterise water chemistry in sink trap samples. Boric acid was an effective preservative of trap sample composition, representing a low-cost alternative to cold-chain transport.

microbiology↗

bioRxiv2022

Genome-first detection of emerging resistance to novel therapeutic agents for SARS-CoV-2

Some COVID-19 patients are unable to clear their infection or are at risk of severe disease, requiring treatment with neutralising monoclonal antibodies (nmAb) and/or antivirals. The rapid roll-out of novel therapeutics means there is limited understanding of the likely genetic barrier to drug resistance. Unprecedented genomic surveillance of SARS-CoV-2 in the UK has enabled a genome-first approach to the detection of emerging drug resistance. Here we report the accrual of mutations in Delta and Omicron cases treated with casirivimab+imdevimab and sotrovimab respectively. Mutations occur within the epitopes of the respective nmAbs. For casirivimab+imdevimab these are present on contiguous raw reads, simultaneously affecting both components. Using surface plasmon resonance and pseudoviral neutralisation assays we demonstrate these mutations reduce or completely abrogate antibody affinity and neutralising activity, suggesting they are driven by immune evasion. In addition, we show that some mutations also reduce the neutralising activity of vaccine-induced serum.

genetics↗

bioRxiv2021

Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on Escherichia coli

2.Several bioinformatics genotyping algorithms are now commonly used to characterise antimicrobial resistance (AMR) gene profiles in whole genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance, and SRST2, run with the ResFinder database) and their outputs compared. For simulations tests where 3,079 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for 3,076 (99.9%) simulations, ABRicate for 3,054 (99.2%), ARIBA for 2,783 (90.4%) and SRST2 for 2,108 (68.5%). For simulations tests where two closely related gene variants were inserted into random sequence constructs, KmerResistance the correct alleles in 35,338/46,318 (76.3%) ABRicate identified in 11,842/46,318 (25.6%) of simulations, ARIBA in 1679/46,318 (3.6%), and SRST2 in 2000/46,318 (4.3%). In real data, across all methods, 1392/1818 (76%) isolates had discrepant allele calls for at least one gene. Our evaluations revealed poor performance in scenarios that would be expected to be challenging (e.g. identification of AMR genes at <10x coverage, discriminating between closely related AMR gene sequences), but also identified systematic sequence classification (i.e. naming) errors even in straightforward circumstances, which contributed to 1081/3092 (35%) errors in our most simple simulations and at least 2530/4321 (59%) discrepancies in real data. Further, many of the remaining discrepancies were likely "artefactual" with reporting cut-off differences accounting for at least 1430/4321 (33%) discrepants. Comparing outputs generated by running multiple algorithms on the same dataset can help identify and resolve these artefacts, but ideally new and more robust genotyping algorithms are needed. 3. Impact statementWhole-genome sequencing is widely used for studying the epidemiology of antimicrobial resistance (AMR) genes in bacteria; however, there is some concern that outputs are highly dependent on the bioinformatics methods used. This work evaluates these concerns in detail by comparing four different, commonly used AMR gene typing methods using large simulated and real datasets. The results highlight performance issues for most methods in at least one of several simulated and real-life scenarios. However most discrepancies between methods were due to differential labelling of the same sequences related to the assumptions made regarding the underlying structure of the reference resistance gene database used (i.e. that resistance genes can be easily classified in well-defined groups). This study represents a major advance in quantifying and evaluating the nature of discrepancies between outputs of different AMR typing algorithms, with relevance for historic and future work using these algorithms. Some of the discrepancies can be resolved by choosing methods with fewer assumptions about the reference AMR gene database and manually resolving outputs generated using multiple programs. However, ideally new and better methods are needed.

microbiology↗

bioRxiv2021

Probiotic bacteria and bile acid profile are modulated by prebiotic diet and associate with facilitated diurnal clock/sleep realignment after chronic disruption of rhythms

Chronic disruption of rhythms (CDR) impacts sleep and can result in circadian misalignment of physiological systems, which in turn is associated with increased disease risk. Exposure to repeated or severe stressors also disturbs sleep and diurnal rhythms. Prebiotic nutrients produce favorable changes in gut microbial ecology, the gut metabolome, and reduce several negative impacts of acute severe stressor exposure, including disturbed sleep, core body temperature rhythmicity, and gut microbial dysbiosis. This study tested the hypothesis whether prebiotics can also reduce the negative impacts of CDR by facilitating light/dark realignment of sleep/wake, core body temperature, and locomotor activity; and whether prebiotic-induced changes in bacteria and bile acid profiles are associated with these effects. Male, Sprague Dawley rats were fed diets enriched in prebiotic substrates or calorically matched control chow. After 5 weeks on diet, rats were exposed to CDR (12h light/dark reversal, weekly for 8 weeks) or remained on undisturbed normal light/dark cycles (NLD). Sleep EEG, core body temperature, and locomotor activity were recorded via biotelemetry in freely moving rats. Fecal samples were collected on experimental days -33, 0 (day of onset of CDR), and 42. Taxonomic identification and relative abundances of gut microbes were measured in fecal samples using 16S rRNA gene sequencing and shotgun metagenomics. Fecal primary, bacterially-modified secondary, and conjugated bile acids were measured using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Prebiotic diet produced rapid and stable increases in the relative abundances of Parabacteroides distasonis and Ruminiclostridium 5. Shotgun metagenomics analyses confirmed reliable increases in relative abundances of Parabacteroides distasonis and Clostridium leptum, a member of the Ruminiclostridium genus. Prebiotic diet also modified fecal bile acid profiles; and based on correlational and step-wise regression analyses, Parabacteroides distasonis and Ruminiclostridium 5 were positively associated with each other and negatively associated with secondary and conjugated bile acids. Prebiotic diet, but not CDR, impacted beta diversity. Measures of alpha diversity evenness were decreased by CDR and prebiotic diet prevented that effect. Rats exposed to CDR while eating prebiotic, compared to control diet, more quickly realigned NREM sleep and core body temperature (ClockLab) diurnal rhythms to the altered light/dark cycle. Finally, both cholic acid and Ruminiclostridium 5 prior to CDR were associated with time to realign CBT rhythms to the new light/dark cycle after CDR; whereas both Ruminiclostridium 5 and taurocholic acid prior to CDR were associated with NREM sleep recovery after CDR. These results suggest that ingestion of prebiotic substrates is an effective strategy to increase the relative abundance of health promoting microbes, alter the fecal bile acid profile, and facilitate the recovery and realignment of sleep and diurnal rhythms after circadian disruption.

physiology↗

bioRxiv2021

Flanker: a tool for comparative genomics of gene flanking regions

Analysing the flanking sequences surrounding genes of interest is often highly relevant to understanding the role of mobile genetic elements (MGEs) in horizontal gene transfer, particular for antimicrobial resistance genes. Here, we present Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of MGEs without prior knowledge of their structure. These clusters, known as flank patterns, are based on Mash distances, allowing for easy comparison of similarity across sequences. Additionally, Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence. We apply Flanker to two recent datasets describing plasmid-associated carriage of important carbapenemase genes (blaOXA-48 and blaKPC-2/3) and show that it successfully identifies distinct clusters of flank patterns, including both known and previously uncharacterised structural variants. For example, Flanker identified four Tn4401 profiles that could not be sufficiently characterised using TETyper or MobileElementFinder, demonstrating the utility of Flanker for flanking gene characterisation. Similarly, using a large (n=226) European isolate dataset, we confirm findings from a previous smaller study demonstrating association between Tn1999.2 and blaOXA-48 upregulation and demonstrate 17 flank patterns (compared to the 5 previously identified). More generally the demonstration in this study that flank patterns are associated with to geographical regions and antibiotic susceptibility phenotypes suggests that they may be useful as epidemiological markers. Flanker is freely available under an MIT license at https://github.com/wtmatlock/flanker. Data SummaryNCBI accession numbers for all sequencing data used in this study is provided in Supplementary Table 1. The analysis performed in this manuscript can be reproduced in a binder environment provided on the Flanker Github page (https://github.com/wtmatlock/flanker).

bioinformatics↗

bioRxiv2019

Selection and co-selection of antibiotic resistances among Escherichia coli by antibiotic use in primary care: an ecological analysis

The majority of studies that link antibiotic usage and resistance focus on simple associations between the resistance against a specific antibiotic and the use of that specific antibiotic. However, the relationship between antibiotic use and resistance is more complex. Here we evaluate which antibiotics, including those mainly prescribed for respiratory tract infections, are associated with increased resistance among Escherichia coli isolated from urinary samples.\n\nMonthly primary care prescribing data were obtained from National Health Service (NHS) Digital. Positive E. coli records from urine samples in English primary care (n=888,207) between April 2014 and January 2016 were obtained from the Second Generation Surveillance System. Elastic net regularization was used to evaluate associations between prescribing of different antibiotic groups and resistance against amoxicillin, cephalexin, ciprofloxacin, co-amoxiclav and nitrofurantoin at the clinical commissioning group (CCG) level. England is divided into 209 CCGs, with each NHS practice prolonging to one CCG.\n\nAmoxicillin prescribing (measured in DDD/ 1000 inhabitants / day) was positively associated with amoxicillin (RR 1.03, 95% CI 1.01 - 1.04) and ciprofloxacin (RR 1.09, 95% CI 1.04 - 1.17) resistance. In contrast, nitrofurantoin prescribing was associated with lower levels of resistance to amoxicillin (RR 0.92, 95% CI 0.84 - 0.97). CCGs with higher levels of trimethoprim prescribing also had higher levels of ciprofloxacin resistance (RR 1.34, 95% CI 1.10 - 1.59).\n\nAmoxicillin, which is mainly (and often unnecessarily) prescribed for respiratory tract infections is associated with increased resistance against various antibiotics among E. coli causing urinary tract infections. Our findings suggest that when predicting the potential impact of interventions on antibiotic resistances it is important to account for use of other antibiotics, including those typically used for other indications.\n\nAuthor summaryAntibiotic resistance is increasingly recognised as a threat to modern healthcare. Effective antibiotics are crucial for treatment of serious bacterial infections and are necessary to avoid that complicated surgical procedures and chemotherapy becoming life-threatening. Antibiotic use is one of the main drivers of antibiotic resistance. The majority of antibiotic prescriptions are prescribed in primary care, however, a large proportion of these antibiotic prescriptions are unnecessary. Understanding which antibiotics are causing antibiotic resistance to what extent is needed to prevent under- or over-investment in interventions lowering use of specific antibiotics, such as rapid diagnostic tests for respiratory tract infection.\n\nWe have statistically evaluated which antibiotics are associated with higher and lower levels of antibiotic resistance against common antibiotics among Escherichia coli bacteria sampled from the urinary tract by comparing antibiotic prescribing and resistance in different geographical areas in England. Our model shows that amoxicillin, the most commonly used antibiotic in England and mainly used for respiratory tract infections, is associated with increased resistance against several other antibiotics among bacteria causing urinary tract infections. The methods used in this study, that overcome several of the limitations of previous studies, can be used to explore the complex relationships between antibiotic use and antibiotic resistance in other settings.

epidemiology↗

bioRxiv2019

When do big problems far away become smaller than the problems closer to home: Lessons for antimicrobial resistance from Father Ted

Infection prevention and control strategies aimed at reducing the occurrence of Carbapenemase-Producing Enterobacteriaceae (CPE) and other antimicrobial-resistant organisms often include advice about screening patients coming from hospitals with a known resistance problem, to prevent introductions into new hospitals by shared patients. We argue that, despite being an efficient method of identifying cases, admission screening for introduction prevention is only effective if the absolute number of imported cases from other hospitals outnumbers the cases coming from the hospitals own patient population, and therefore is only a feasible control strategy during the start of an epidemic. When determining whether import screening is still advisable, we therefore need to be continuously reminded of how Father Ted so eloquently summarised the principles of perspective: "These are small, but the ones out there are far away".

epidemiology↗