ABSTRACT
Understanding how antimicrobial resistance spreads is critical for optimal application of new treatments. In the naturally competent human pathogen Streptococcus pneumoniae, resistance to ß-lactam antibiotics is mediated by recombination events in genes encoding the target proteins, resulting in reduced drug binding affinity. However, for the front-line antibiotic amoxicillin, the exact mechanism of resistance still needs to be elucidated. Through successive rounds of transformation with genomic DNA from a clinically resistant isolate, we followed amoxicillin resistance development. Using whole genome sequencing, we showed that multiple recombination events occurred at different loci during one round of transformation. We found examples of non-contiguous recombination, and demonstrated that this could occur either through multiple D-loop formation from one donor DNA molecule, or by the integration of multiple DNA fragments. We also show that the final minimum inhibitory concentration (MIC) differs depending on recipient genome, explained by differences in the extent of recombination at key loci. Finally, through back transformations of mutant alleles and fluorescently labelled penicillin (bocillin-FL) binding assays, we confirm that pbp1a, pbp2b, pbp2x, and murM are the main resistance determinants for amoxicillin resistance, and that the order of allele uptake is important for successful resistance evolution. We conclude that recombination events are complex, and that this complexity contributes to the highly diverse genotypes of amoxicillin-resistant pneumococcal isolates.
Subject(s)
Amoxicillin , Streptococcus pneumoniae , Amoxicillin/metabolism , Amoxicillin/pharmacology , Anti-Bacterial Agents/metabolism , Anti-Bacterial Agents/pharmacology , Bacterial Proteins/genetics , Bacterial Proteins/metabolism , Gene Transfer, Horizontal , Humans , Microbial Sensitivity Tests , Penicillin Resistance/genetics , Penicillin-Binding Proteins/genetics , Streptococcus pneumoniae/metabolismABSTRACT
Despite the magnitude of the Ebola virus disease (EVD) outbreak in West Africa, there is still a fundamental lack of knowledge about the pathophysiology of EVD. In particular, very little is known about human immune responses to Ebola virus. Here we evaluate the physiology of the human T cell immune response in EVD patients at the time of admission to the Ebola Treatment Center in Guinea, and longitudinally until discharge or death. Through the use of multiparametric flow cytometry established by the European Mobile Laboratory in the field, we identify an immune signature that is unique in EVD fatalities. Fatal EVD was characterized by a high percentage of CD4(+) and CD8(+) T cells expressing the inhibitory molecules CTLA-4 and PD-1, which correlated with elevated inflammatory markers and high virus load. Conversely, surviving individuals showed significantly lower expression of CTLA-4 and PD-1 as well as lower inflammation, despite comparable overall T cell activation. Concomitant with virus clearance, survivors mounted a robust Ebola-virus-specific T cell response. Our findings suggest that dysregulation of the T cell response is a key component of EVD pathophysiology.
Subject(s)
Ebolavirus/immunology , Hemorrhagic Fever, Ebola/immunology , Hemorrhagic Fever, Ebola/physiopathology , T-Lymphocytes/immunology , CTLA-4 Antigen/metabolism , Female , Flow Cytometry , Guinea/epidemiology , Hemorrhagic Fever, Ebola/mortality , Humans , Inflammation Mediators/immunology , Longitudinal Studies , Lymphocyte Activation , Male , Patient Discharge , Programmed Cell Death 1 Receptor/metabolism , Survivors , T-Lymphocytes/metabolism , Viral LoadABSTRACT
The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths. Genome sequencing in viral outbreaks is desirable to characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10(-3) and 1.42 × 10(-3) mutations per site per year. This is equivalent to 16-27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic. Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions. Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities. To address this problem, here we devise a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15-60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.
Subject(s)
Ebolavirus/genetics , Epidemiological Monitoring , Genome, Viral/genetics , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/virology , Sequence Analysis, DNA/instrumentation , Sequence Analysis, DNA/methods , Aircraft , Disease Outbreaks/statistics & numerical data , Ebolavirus/classification , Ebolavirus/pathogenicity , Guinea/epidemiology , Humans , Mutagenesis/genetics , Mutation Rate , Time FactorsABSTRACT
Homologous recombination in the genetic transformation model organism Streptococcus pneumoniae is thought to be important in the adaptation and evolution of this pathogen. While competent pneumococci are able to scavenge DNA added to laboratory cultures, large-scale transfers of multiple kb are rare under these conditions. We used whole genome sequencing (WGS) to map transfers in recombinants arising from contact of competent cells with non-competent 'target' cells, using strains with known genomes, distinguished by a total of ~16,000 SNPs. Experiments designed to explore the effect of environment on large scale recombination events used saturating purified donor DNA, short-term cell assemblages on Millipore filters, and mature biofilm mixed cultures. WGS of 22 recombinants for each environment mapped all SNPs that were identical between the recombinant and the donor but not the recipient. The mean recombination event size was found to be significantly larger in cell-to-cell contact cultures (4051 bp in filter assemblage and 3938 bp in biofilm co-culture versus 1815 bp with saturating DNA). Up to 5.8% of the genome was transferred, through 20 recombination events, to a single recipient, with the largest single event incorporating 29,971 bp. We also found that some recombination events are clustered, that these clusters are more likely to occur in cell-to-cell contact environments, and that they cause significantly increased linkage of genes as far apart as 60,000 bp. We conclude that pneumococcal evolution through homologous recombination is more likely to occur on a larger scale in environments that permit cell-to-cell contact.
Subject(s)
Cell Communication/genetics , Recombination, Genetic/genetics , Streptococcus pneumoniae/genetics , Cell Communication/physiology , DNA/genetics , DNA/physiology , Evolution, Molecular , Gene Rearrangement/genetics , Genome, Bacterial/genetics , Homologous Recombination/genetics , Polymorphism, Single Nucleotide/genetics , Whole Genome Sequencing/methodsABSTRACT
BACKGROUND: In 2015, the laboratory at the Ebola treatment center in Coyah, Guinea, confirmed Ebola virus disease (EVD) in 286 patients. The cycle threshold (Ct) of an Ebola virus-specific reverse transcription-polymerase chain reaction assay and 13 blood chemistry parameters were measured on admission and during hospitalization. Favipiravir treatment was offered to patients with EVD on a compassionate-use basis. METHODS: To reduce biases in the raw field data, we carefully selected 163 of 286 patients with EVD for a retrospective study to assess associations between potential risk factors, alterations in blood chemistry findings, favipiravir treatment, and outcome. RESULTS: The case-fatality rate in favipiravir-treated patients was lower than in untreated patients (42.5% [31 of 73] vs 57.8% [52 of 90]; P = .053 by univariate analysis). In multivariate regression analysis, a higher Ct and a younger age were associated with survival (P < .001), while favipiravir treatment showed no statistically significant effect (P = .11). However, Kaplan-Meier analysis indicated a longer survival time in the favipiravir-treated group (P = .015). The study also showed characteristic changes in blood chemistry findings in patients who died, compared with survivors. CONCLUSIONS: Consistent with the JIKI trial, this retrospective study revealed a trend toward improved survival in favipiravir- treated patients; however, the effect of treatment was not statistically significant, except for its influence on survival time.
Subject(s)
Amides/therapeutic use , Antiviral Agents/therapeutic use , Ebolavirus/drug effects , Hemorrhagic Fever, Ebola/drug therapy , Pyrazines/therapeutic use , Adolescent , Adult , Child , Child, Preschool , Compassionate Use Trials/methods , Female , Guinea , Hemorrhagic Fever, Ebola/virology , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Retrospective Studies , Viral Load/drug effects , Young AdultABSTRACT
On 11 May 2015, the Dubréka prefecture, Guinea, reported nine laboratory-confirmed cases of Ebola virus disease (EVD). None could be epidemiologically linked to cases previously reported in the prefecture. We describe the epidemiological and molecular investigations of this event. We used the Dubréka EVD registers and the Ebola treatment centre's (ETC) records to characterise chains of transmission. Real-time field Ebola virus sequencing was employed to support epidemiological results. An epidemiological cluster of 32 cases was found, of which 27 were laboratory confirmed, 24 were isolated and 20 died. Real-time viral sequencing on 12 cases demonstrated SL3 lineage viruses with sequences differing by one to three nt inside a single phylogenetic cluster. For isolated cases, the average time between symptom onset and ETC referral was 2.8 days (interquartile range (IQR): 1-4). The average time between sample collection and molecular results' availability was 3 days (IQR: 2-5). In an area with scarce resources, the genetic characterisation supported the outbreak investigations in real time, linking cases where epidemiological investigation was limited and reassuring that the responsible strain was already circulating in Guinea. We recommend coupling thorough epidemiological and genomic investigations to control EVD clusters.
Subject(s)
DNA, Viral/genetics , Ebolavirus/genetics , Ebolavirus/isolation & purification , Hemorrhagic Fever, Ebola/diagnosis , Hemorrhagic Fever, Ebola/transmission , Contact Tracing , Disease Outbreaks/prevention & control , Genomics , Guinea/epidemiology , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/virology , Humans , Phylogeny , Real-Time Polymerase Chain ReactionABSTRACT
In July 2014, an outbreak of Shiga toxin-producing Escherichia coli (STEC) O55:H7 in England involved 31 patients, 13 (42%) of whom had hemolytic uremic syndrome. Isolates were sequenced, and the sequences were compared with publicly available sequences of E. coli O55:H7 and O157:H7. A core-genome phylogeny of the evolutionary history of the STEC O55:H7 outbreak strain revealed that the most parsimonious model was a progenitor enteropathogenic O55:H7 sorbitol-fermenting strain, lysogenized by a Shiga toxin (Stx) 2a-encoding phage, followed by loss of the ability to ferment sorbitol because of a non-sense mutation in srlA. The parallel, convergent evolutionary histories of STEC O157:H7 and STEC O55:H7 may indicate a common driver in the evolutionary process. Because emergence of STEC O157:H7 as a clinically significant pathogen was associated with acquisition of the Stx2a-encoding phage, the emergence of STEC O55:H7 harboring the stx2a gene is of public health concern.
Subject(s)
Bacterial Proteins/genetics , Disease Outbreaks , Escherichia coli Infections/epidemiology , Genome, Bacterial , Hemolytic-Uremic Syndrome/epidemiology , Shiga Toxin 2/biosynthesis , Shiga-Toxigenic Escherichia coli/genetics , Bacterial Proteins/metabolism , Coliphages/genetics , Coliphages/metabolism , Escherichia coli Infections/microbiology , Escherichia coli Infections/pathology , Escherichia coli Infections/transmission , Evolution, Molecular , Fermentation , Gene Deletion , Gene Expression , Hemolytic-Uremic Syndrome/microbiology , Hemolytic-Uremic Syndrome/pathology , High-Throughput Nucleotide Sequencing , Humans , Lysogeny , Phylogeny , Shiga-Toxigenic Escherichia coli/classification , Shiga-Toxigenic Escherichia coli/isolation & purification , Shiga-Toxigenic Escherichia coli/virology , Sorbitol/metabolism , United Kingdom/epidemiologyABSTRACT
In England in 2015, Shigella sonnei isolates from men who have sex with men produced extended-spectrum ß-lactamases and exhibited macrolide resistance. Whole-genome sequencing showed a close relationship among the isolates, which harbored a plasmid that was previously identified in a shigellosis outbreak among this population but has acquired a mobile element.
Subject(s)
Drug Resistance, Bacterial , Dysentery, Bacillary/epidemiology , Dysentery, Bacillary/microbiology , Homosexuality, Male , Macrolides/pharmacology , Shigella sonnei/drug effects , Shigella sonnei/genetics , beta-Lactamases/genetics , Anti-Bacterial Agents/pharmacology , Dysentery, Bacillary/drug therapy , Dysentery, Bacillary/history , England/epidemiology , Genome, Bacterial , History, 21st Century , Humans , Male , Microbial Sensitivity Tests , Phylogeny , Polymorphism, Single Nucleotide , Shigella sonnei/classification , Whole Genome Sequencing , beta-Lactamases/biosynthesisABSTRACT
BACKGROUND: National surveillance of gastrointestinal pathogens, such as Shiga toxin-producing Escherichia coli O157 (STEC O157), is key to rapidly identifying linked cases in the distributed food network to facilitate public health interventions. In this study, we used whole-genome sequencing (WGS) as a tool to inform national surveillance of STEC O157 in terms of identifying linked cases and clusters and guiding epidemiological investigation. METHODS: We retrospectively analyzed 334 isolates randomly sampled from 1002 strains of STEC O157 received by the Gastrointestinal Bacteria Reference Unit at Public Health England, Colindale, in 2012. The genetic distance between each isolate, as estimated by WGS, was calculated and phylogenetic methods were used to place strains in an evolutionary context. RESULTS: Estimates of linked clusters representing STEC O157 outbreaks in England and Wales increased by 2-fold when WGS was used instead of traditional typing techniques. The previously unidentified clusters were often widely geographically distributed and small in size. Phylogenetic analysis facilitated identification of temporally distinct cases sharing common exposures and delineating those that shared epidemiological and temporal links. Comparison with multi locus variable number tandem repeat analysis (MLVA) showed that although MLVA is as sensitive as WGS, WGS provides a more timely resolution to outbreak clustering. CONCLUSIONS: WGS has come of age as a molecular typing tool to inform national surveillance of STEC O157; it can be used in real time to provide the highest strain-level resolution for outbreak investigation. WGS allows linked cases to be identified with unprecedented specificity and sensitivity that will facilitate targeted and appropriate public health investigations.
Subject(s)
Escherichia coli Infections/microbiology , Genome, Bacterial/genetics , Public Health Surveillance , Shiga-Toxigenic Escherichia coli/genetics , DNA, Bacterial/analysis , DNA, Bacterial/genetics , Disease Outbreaks , Humans , Phylogeny , Retrospective Studies , Sequence Analysis, DNA , Shiga-Toxigenic Escherichia coli/classificationABSTRACT
BACKGROUND: Shiga toxin producing Escherichia coli O157 can cause severe bloody diarrhea and haemolytic uraemic syndrome. Phage typing of E. coli O157 facilitates public health surveillance and outbreak investigations, certain phage types are more likely to occupy specific niches and are associated with specific age groups and disease severity. The aim of this study was to analyse the genome sequences of 16 (fourteen T4 and two T7) E. coli O157 typing phages and to determine the genes responsible for the subtle differences in phage type profiles. RESULTS: The typing phages were sequenced using paired-end Illumina sequencing at The Genome Analysis Centre and the Animal Health and Veterinary Laboratories Agency and bioinformatics programs including Velvet, Brig and Easyfig were used to analyse them. A two-way Euclidian cluster analysis highlighted the associations between groups of phage types and typing phages. The analysis showed that the T7 typing phages (9 and 10) differed by only three genes and that the T4 typing phages formed three distinct groups of similar genomic sequences: Group 1 (1, 8, 11, 12 and 15, 16), Group 2 (3, 6, 7 and 13) and Group 3 (2, 4, 5 and 14). The E. coli O157 phage typing scheme exhibited a significantly modular network linked to the genetic similarity of each group showing that these groups are specialised to infect a subset of phage types. CONCLUSION: Sequencing the typing phage has enabled us to identify the variable genes within each group and to determine how this corresponds to changes in phage type.
Subject(s)
Bacteriophages/genetics , Escherichia coli O157/virology , Genome, Viral , Bacteriophage T4/genetics , Bacteriophage Typing , Cluster Analysis , Computational Biology , DNA, Viral/analysis , DNA, Viral/isolation & purification , High-Throughput Nucleotide Sequencing , Sequence Analysis, DNAABSTRACT
The use of k-mers to capture genetic variation in bacterial genome-wide association studies (bGWAS) has demonstrated its effectiveness in overcoming the plasticity of bacterial genomes by providing a comprehensive array of genetic variants in a genome set that is not confined to a single reference genome. However, little attempt has been made to interpret k-mers in the context of genome rearrangements, partly due to challenges in the exhaustive and high-throughput identification of genome structure and individual rearrangement events. Here, we present GWarrange, a pre- and post-bGWAS processing methodology that leverages the unique properties of k-mers to facilitate bGWAS for genome rearrangements. Repeat sequences are common instigators of genome rearrangements through intragenomic homologous recombination, and they are commonly found at rearrangement boundaries. Using whole-genome sequences, repeat sequences are replaced by short placeholder sequences, allowing the regions flanking repeats to be incorporated into relatively short k-mers. Then, locations of flanking regions in significant k-mers are mapped back to complete genome sequences to visualise genome rearrangements. Four case studies based on two bacterial species (Bordetella pertussis and Enterococcus faecium) and a simulated genome set are presented to demonstrate the ability to identify phenotype-associated rearrangements. GWarrange is available at https://github.com/DorothyTamYiLing/GWarrange.
Subject(s)
Gene Rearrangement , Genome, Bacterial , Genome-Wide Association Study , Phenotype , Genome-Wide Association Study/methods , Software , Genetic VariationABSTRACT
Accurate annotation to single-nucleotide resolution of the transcribed regions in genomes is key to optimally analyse RNA-seq data, understand regulatory events and for the design of experiments. However, currently most genome annotations provided by GenBank generally lack information about untranslated regions. Additionally, information regarding genomic locations of non-coding RNAs, such as sRNAs, or anti-sense RNAs is frequently missing. To provide such information, diverse RNA-seq technologies, such as Rend-seq, have been developed and applied to many bacterial species. However, incorporating this vast amount of information into annotation files has been limited and is bioinformatically challenging, resulting in UTRs and other non-coding elements being overlooked or misrepresented. To overcome this problem, we present pyRAP (python Rend-seq Annotation Pipeline), a software package that analyses Rend-seq datasets to accurately resolve transcript boundaries genome-wide. We report the use of pyRAP to find novel transcripts, transcript isoforms, and RNase-dependent sRNA processing events. In Bacillus subtilis we uncovered 63 novel transcripts and provide genomic coordinates with single-nucleotide resolution for 2218 5'UTRs, 1864 3'UTRs and 161 non-coding RNAs. In Escherichia coli, we report 117 novel transcripts, 2429 5'UTRs, 1619 3'UTRs and 91 non-coding RNAs, and in Staphylococcus aureus, 16 novel transcripts, 664 5'UTRs, 696 3'UTRs, and 81 non-coding RNAs. Finally, we use pyRAP to produce updated annotation files for B. subtilis 168, E. coli K-12 MG1655, and S. aureus 8325 for use in the wider microbial genomics research community.
Subject(s)
Bacillus subtilis , Genome, Bacterial , Molecular Sequence Annotation , Software , Bacillus subtilis/genetics , Escherichia coli/genetics , RNA, Bacterial/genetics , Staphylococcus aureus/genetics , Computational Biology/methods , Sequence Analysis, RNA/methods , RNA-Seq/methodsABSTRACT
BACKGROUND: Young adults affected by cancer face physical and psychological challenges and desire online supportive care. Yoga can be delivered online and may improve physical and psychological outcomes. Yet, yoga has rarely been studied with young adults affected by cancer. To address this, an 8-week yoga intervention was developed, and a pilot study was deemed necessary to explore feasibility, acceptability, implementation, and potential benefits. METHODS: A mixed-methods, single-arm hybrid effectiveness-implementation pilot study evaluating the yoga intervention was conducted. Feasibility was assessed by tracking enrollment, retention, attendance, completeness of data, and adverse events. Acceptability was explored through interviews. Implementation metrics included training time, delivery resources, and fidelity. Potential effectiveness was evaluated by exploring changes in physical (i.e., balance, flexibility, range of motion, functional mobility) and psychological (i.e., quality of life, fatigue, resilience, posttraumatic growth, body image, mindfulness, perceived stress) outcomes at pre- (week 0), post- (week 8), and follow-up (week 16) time points. Data were analyzed with descriptive statistics, repeated measures analysis of variance, and content analysis. RESULTS: Thirty young adults participated in this study (recruitment rate = 33%). Retention to study procedures was 70%, and attendance ranged from 38 to 100%. There were little missing data (< 5%) and no adverse events. Though most participants were satisfied with the yoga intervention, recommendations for improvement were shared. Sixty study-specific training hours and > 240 delivery and assessment hours were accrued and fidelity was high. Functional mobility, flexibility, quality of life (energy/fatigue, social well-being), body image (appearance evaluation), mindfulness (non-reactivity), and perceived stress improved significantly over time (all p< 0.050; [Formula: see text]). No other significant changes were observed (all p> 0.050; [Formula: see text]). CONCLUSIONS: The yoga intervention may confer physical and psychological benefits, though intervention and study-specific modifications are required to improve feasibility and acceptability. Requiring study participation and providing greater scheduling flexibility could enhance recruitment and retention. Increasing the frequency of classes offered each week and offering more opportunities for participant interaction could improve satisfaction. This study highlights the value of doing pilot work and provides data that has directly informed intervention and study modifications. Findings could also be used by others offering yoga or supportive care by videoconference to young adults affected by cancer. TRIAL REGISTRATION: Not available-not registered.
ABSTRACT
Salmonella enterica serovar Enteritidis is one of the most frequent causes of Salmonellosis globally and is commonly transmitted from animals to humans by the consumption of contaminated foodstuffs. In the UK and many other countries in the Global North, a significant proportion of cases are caused by the consumption of imported food products or contracted during foreign travel, therefore, making the rapid identification of the geographical source of new infections a requirement for robust public health outbreak investigations. Herein, we detail the development and application of a hierarchical machine learning model to rapidly identify and trace the geographical source of S. Enteritidis infections from whole genome sequencing data. 2313 S. Enteritidis genomes, collected by the UKHSA between 2014-2019, were used to train a 'local classifier per node' hierarchical classifier to attribute isolates to four continents, 11 sub-regions, and 38 countries (53 classes). The highest classification accuracy was achieved at the continental level followed by the sub-regional and country levels (macro F1: 0.954, 0.718, 0.661, respectively). A number of countries commonly visited by UK travelers were predicted with high accuracy (hF1: >0.9). Longitudinal analysis and validation with publicly accessible international samples indicated that predictions were robust to prospective external datasets. The hierarchical machine learning framework provided granular geographical source prediction directly from sequencing reads in <4 min per sample, facilitating rapid outbreak resolution and real-time genomic epidemiology. The results suggest additional application to a broader range of pathogens and other geographically structured problems, such as antimicrobial resistance prediction, is warranted.
Subject(s)
Salmonella Infections , Salmonella enterica , Animals , Humans , Salmonella enteritidis/genetics , Prospective Studies , Salmonella Infections/epidemiology , Disease Outbreaks , Machine LearningABSTRACT
Shigella sonnei causes shigellosis, a severe gastrointestinal illness that is sexually transmissible among men who have sex with men (MSM). Multidrug resistance in S. sonnei is common including against World Health Organisation recommended treatment options, azithromycin, and ciprofloxacin. Recently, an MSM-associated outbreak of extended-spectrum ß-lactamase producing, extensively drug resistant S. sonnei was reported in the United Kingdom. Here, we aimed to identify the genetic basis, evolutionary history, and international dissemination of the outbreak strain. Our genomic epidemiological analyses of 3,304 isolates from the United Kingdom, Australia, Belgium, France, and the United States of America revealed an internationally connected outbreak with a most recent common ancestor in 2018 carrying a low-fitness cost resistance plasmid, previously observed in travel associated sublineages of S. flexneri. Our results highlight the persistent threat of horizontally transmitted antimicrobial resistance and the value of continuing to work towards early and open international sharing of genomic surveillance data.
Subject(s)
Sexual and Gender Minorities , Shigella , Male , Humans , Shigella sonnei/genetics , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Homosexuality, Male , Travel , Drug Resistance, Bacterial/genetics , Microbial Sensitivity TestsABSTRACT
Reviewing the genetics underlying the arms race between bacteria and bacteriophages can offer an interesting insight into the development of bacterial resistance and phage co-evolution. This study shows how the natural development of resistances to the K1F bacteriophage, a phage which targets the K1 capsule of pathogenic Escherichia coli, can come about through insertion sequences (IS). Of the K1F resistant mutants isolated, two were of particular interest. The first of these showed full resistance to K1F and was found to have disruptions to kpsE, the product of which is involved in polysialic acid translocation. The second, after showing an initial susceptibility to K1F which then developed to full resistance, had disruptions to neuC, a gene involved in one of the early steps of polysialic acid biosynthesis. Both of these mutations came with a fitness cost and produced considerable phenotypic differences in the completeness and location of the K1 capsule when compared with the wild type. Sequential treatment of these two K1F resistant mutants with T7 resulted in the production of a variety of isolates, many of which showed a renewed susceptibility to K1F, indicating that these insertion sequence mutations are reversible, as well as one isolate that developed resistance to both phages. IMPORTANCE Bacteriophages have many potential uses in industry and the clinical environment as an antibacterial control measure. One of their uses, phage therapy, is an appealing alternative to antibiotics due to their high specificity. However, as with the rise in antimicrobial resistance (AMR), it is critical to improve our understanding of how resistance develops against these viral agents. In the same way as bacteria will evolve and mutate antibiotic receptors so they can no longer be recognized, resistance to bacteriophages can come about via mutations to phage receptors, preventing phage binding and infection. We have shown that Escherichia coli will become resistant to the K1F bacteriophage via insertion element reshufflings causing null mutations to elements of the polysialic acid biosynthetic cluster. Exposure to the T7 bacteriophage then resulted in further changes in the position of these IS elements, further altering their resistance and sensitivity profiles.
Subject(s)
Bacteriophages , Escherichia coli Proteins , Escherichia coli , Bacteriophages/genetics , DNA Transposable Elements , Escherichia coli/genetics , Escherichia coli/virology , Escherichia coli Proteins/genetics , Membrane Transport Proteins/genetics , Multigene Family , Sialic AcidsABSTRACT
Shigellosis in men who have sex with men (MSM) is caused by multidrug resistant Shigellae, exhibiting resistance to antimicrobials including azithromycin, ciprofloxacin and more recently the third-generation cephalosporins. We sequenced four blaCTX-M-27-positive MSM Shigella isolates (2018-20) using Oxford Nanopore Technologies; three S. sonnei (identified as two MSM clade 2, one MSM clade 5) and one S. flexneri 3a, to explore AMR context. All S. sonnei isolates harboured Tn7/Int2 chromosomal integrons, whereas S. flexneri 3a contained the Shigella Resistance Locus. All strains harboured IncFII pKSR100-like plasmids (67-83kbp); where present blaCTX-M-27 was located on these plasmids flanked by IS26 and IS903B, however blaCTX-M-27 was lost in S. flexneri 3a during storage between Illumina and Nanopore sequencing. IncFII AMR regions were mosaic and likely reorganised by IS26; three of the four plasmids contained azithromycin-resistance genes erm(B) and mph(A) and one harboured the pKSR100 integron. Additionally, all S. sonnei isolates possessed a large IncB/O/K/Z plasmid, two of which carried aph(3')-Ib/aph(6)-Id/sul2 and tet(A). Monitoring the transmission of mobile genetic elements with co-located AMR determinants is necessary to inform empirical treatment guidance and clinical management of MSM-associated shigellosis.
Subject(s)
Bacterial Proteins/genetics , Dysentery, Bacillary/transmission , Homosexuality, Male , Plasmids/genetics , Sexual and Gender Minorities , Shigella/genetics , beta-Lactamases/genetics , Adult , Anti-Bacterial Agents/therapeutic use , DNA, Bacterial , Dysentery, Bacillary/drug therapy , Humans , Male , Middle Aged , Nanopores , Shigella/classification , Shigella sonnei/genetics , Shigella sonnei/isolation & purification , United Kingdom , Virulence/genetics , Young AdultABSTRACT
Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook 'Data for Good' and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel.
Subject(s)
COVID-19/transmission , Cell Phone/statistics & numerical data , Genome, Viral/genetics , SARS-CoV-2/genetics , Social Media/statistics & numerical data , Bangladesh/epidemiology , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/virology , Disease Outbreaks/prevention & control , Disease Outbreaks/statistics & numerical data , Genomics , Health Policy/legislation & jurisprudence , Humans , Phylogeny , Population Dynamics/statistics & numerical data , SARS-CoV-2/classification , Travel/legislation & jurisprudence , Travel/statistics & numerical dataABSTRACT
Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both Streptococcus pneumoniae and Neisseria gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in the determination of resistance within 10 min (91% sensitivity and 100% specificity for S. pneumoniae and 81% sensitivity and 100% specificity for N. gonorrhoeae from isolates with a representative database) of starting sequencing, and within 4 h of sample collection (75% sensitivity and 100% specificity for S. pneumoniae) for clinical metagenomic sputum samples. This flexible approach has wide application for pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.
Subject(s)
Anti-Bacterial Agents/pharmacology , Bacterial Typing Techniques/methods , Drug Resistance, Multiple, Bacterial/drug effects , Drug Resistance, Multiple, Bacterial/genetics , Genomics , Databases, Factual , Humans , Microbial Sensitivity Tests/methods , Molecular Epidemiology , Neisseria gonorrhoeae/drug effects , Neisseria gonorrhoeae/genetics , Neisseria gonorrhoeae/isolation & purification , Phenotype , Sensitivity and Specificity , Streptococcus pneumoniae/drug effects , Streptococcus pneumoniae/genetics , Streptococcus pneumoniae/isolation & purificationABSTRACT
Bacterial-host interactions are non-linear and actually threefold, involving significant selection through predatory lytic bacteriophages in the host environment. In studies of human and animal gut microbiome bacteria, it is important to consider phage in all host-pathogen interactions. We use an important zoonotic pathogen, Shiga toxigenic Escherichia coli (STEC) O157:H7, to investigate this. Our study provides evidence that phage resistance profiles are well maintained at the sub-lineage level with variation in profiles within sub-lineages uncommon. This indicates that phage resistance heterogeneity happened early on in the STEC O157:H7 natural history and that occasional "wobbles" do not often outcompete the stable lineage unless combined with a competitive advantage. We discuss an example of this in the acquisition of stx2a that, while an important virulence factor, also conveys increased phage cross-resistance. We also discuss the role of phage resistance in co-occurrence of the three stable lineages worldwide and whether differing phage resistance is maintaining diversity.