Twitter hashtag: #epph2023
Talks
APOBEC3 deaminase editing in mpox virus as evidence for sustained human transmission since at least 2016 - Aine O'Toole, University of Edinburgh
| Historically, mpox has been characterised as an endemic zoonotic disease that transmits through contact with the reservoir rodent host in West and Central Africa. However, in May 2022, human cases of mpox were detected spreading internationally beyond countries with known endemic reservoirs. When the first cases from 2022 were sequenced, they shared 42 nucleotide differences from the closest mpox virus (MPXV) previously sampled. Nearly all these mutations are characteristic of the action of APOBEC3 deaminases; host-enzymes with antiviral function. Assuming APOBEC3-editing is characteristic of human MPXV infection, we develop a dual process phylogenetic molecular clock that — inferring a rate of ~6 APOBEC3 mutations per year — estimates MPXV has been circulating in humans since 2016. These observations of sustained MPXV transmission present a fundamental shift to the perceived paradigm of MPXV epidemiology as a zoonosis and highlight the need for revising public health messaging around MPXV as well as outbreak management and control. |
Spatial analysis of phylogenetic, population and deprivation data from Scottish SARS-CoV-2 outbreak reveals patterns of the community transmission - Anna Gamza, University of Edinburgh
Authors: Anna Gamża, Samantha Lycett, Will Harvey, Joseph Hughes, Sema Nickbakhsh, David Robertson, Alison Smith Palmer, Anthony Wood, Rowland Kao
Quantifying risk factors for infection transmission in the community is a central challenge for ensuring the effective design of disease control measures. The genetic proximity of sequenced cases indicates the proximity among contacts on an infection transmission tree. Sequencing data may therefore provide direct insight into the contact patterns that drive the spread of infection among individuals in a community. Thus, analyses to determine relationships between phylogenetic data and data about host population structure (e.g. population size, age, commuting patterns or deprivation) can be valuable tools for informing more targeted intervention strategies.
To gain an insight into the factors that can indicate increased transmission in certain fractions of the population we studied which population factors are correlated with the measured genetic proximity. We used an exceptional combination of population data, with SARS-CoV-2 phylogenetic data recorded to the standardised level of Data Zones of which there are 6,976 in Scotland, with each containing approx. 500-1000 residents. Over the three-year period (from March 2020 to March 2023) 12.81% of all positive cases (sum of PCR-positive and antigen positive tests) in Scotland were sequenced; and were found to provide an unbiased representation of all cases and all PCR-positive Scottish cases in terms of sex, age, NHS health boards and Data Zones. The Random Forest modelling shows that both PCR-positive cases and their sequenced portion were biased towards the cases from the Data Zones with higher health deprivation.
Using Random Forest modelling, we compared a suite of known predictors of distributions of SARS-CoV-2 case data across data zones to determine if they were likely to be predictors of genetic proximity. We studied over 4000 sequences from an area which had experienced severe pressure from SARS-CoV-2, the Tayside region (approx. 400 000 residents). Over the analysis period (August 2020-July 2021), we identified various strong predictors of genetic proximity, namely geographical proximity, number of contemporaneous cases, population size and the deprivation of the Data Zones occupied by the sequenced cases. As expected, the genetic distance between cases is positively corelated with geographical proximity and negatively correlated with the number of cases registered in the relevant Data Zones during the 30-day period contemporaneous to each sequence pair.
Population characteristics that drive viral transmission are likely to be indicated by closer genetic proximity for samples taken from individuals residing in Data Zones with those characteristics. As such, our analysis gives insights into the patterns of community transmission it can be used to inform the development of targeted, properly scaled intervention strategies.
Developing a Collaborative Digital One Health Data Framework for Enhanced AMR Surveillance in Uganda - Bryan Wee, University of Edinburgh
Enhanced collaboration among One Health sectors is essential for a better understanding of infectious diseases and addressing challenges like increasing antimicrobial resistance (AMR). Integrating data from different One Health sectors can be challenging due to differences in institutional policies. This pilot project brings together institutions involved in AMR surveillance in Uganda such as the Central Public Health Laboratories, the National Animal Disease Diagnostics and Epidemiology Centre (NADDEC), and the Ministry of Water and Environment. We consulted clinicians, veterinarians, environmental experts, microbiologists, bioethicists, legal experts and epidemiologists from these sectors as part of a trust-building workshop held in September 2023.
Feedback and discussions as part of a workshop between these One Health experts in Uganda allowed us to better understand how AMR surveillance data was generated, used and shared within each institution. This enabled us to design a system to manage data flow, evaluate the risk of revealing sensitive information and modify data when needed to safeguard institutional priorities, commercial interests and individual privacy. This ensures the data remains useful for studying infectious disease patterns. We also explored proper attribution for data generation and sharing.
The goal of this pilot project is to apply the insights from this collaborative effort to design digital solutions that support data management within the FAIR (Findable, Accessible, Interoperable, and Reusable) framework, enhancing data's scientific research potential. These tools should adeptly capture, adjust if required, and manage data flows to establish a collective resource for combined analysis and interpretation. Integrating and sharing One Health data will revolutionize interdisciplinary cooperation. Consolidating data from One Health sectors bolsters our capacity to safeguard the well-being of humans, animals, and the environment from future infectious disease threats.
Variant analysis of avian influenza virus strains using INSaFLU - Carol Leitch, Roslin Institute, University of Edinburgh
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Authors: E. Carol McWilliam Leitch*, Darrell Kapczynski#, Ryan Sweeney#, Paul Digard* and Samantha Lycett* Although highly pathogenic avian influenza (HPAI) viruses in commercial poultry can be directly introduced via wild birds, most outbreaks occur through the evolution of low pathogenic avian influenza (LPAI) H5 or H7 viruses despite control measures that include vaccination. These vaccines, like their human counterparts, are non-sterilising. They provide protection against serious illness and death but do not prevent transmission of the virus. Our overarching aim is to understand the evolutionary mechanisms whereby imperfect vaccines engender an increased viral virulence state over time. |
Using genomics to identify and prevent nosocomial viral transmission - Chris Illingworth, University of Glasgow
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During an outbreak, the evolution of viral genomes provides a window into their patterns of viral transmission, with viruses that are closely linked by direct or indirect transmission having sequences that are more closely evolutionarily related. This insight can be combined with other sources of data and epidemiological models to gain insights that can shape the public health responses to local and global epidemics. The A2B software package comprises methods that facilitate both rapid responses, and more careful retrospective analysis of viral sequence data. We describe the application of these methods to SARS-CoV-2 data collected in Cambridge University Hospitals. Evolutionary analysis formed part of a real-time response to cases of infections on hospital wards, supporting changes in masking practice among health care workers on COVID wards. A mode detailed analysis of data further supported existing decisions in infection prevention and control and identified behaviours associated with an increased risk of viral transmission. In the light of our experience, we discuss future scenarios in which our methods could be applied, and outline potential developments towards the broader implementation of viral genomics in hospital settings. |
Pandemic lessons learned from SARS-CoV-2's emergence and introductions into Scotland - David Robertson, MRC-University of Glasgow Centre for Virus Research (CVR)
| I will present what we know about the natural origin of SARS-CoV-2, the characteristics that contributed to its success as a new human coronavirus emerging in late 2019 and the insights gained from data-driven observations on its evolution within the human population. Importantly, the efficient spread of SARS-CoV-2 in humans was not due to specific adaptations to infect humans. Rather, SARS-CoV-2 has a relatively generalist nature, as evidenced by its frequent transmission to various mammal species. While our understanding is incomplete, the pathway of SARS-CoV-2's emergence in humans in 2019 is unambiguous. Major lessons from this include the need to be careful with our assumptions about what a pandemic virus will look like. Specifically, global control measures were caught out by SARS-CoV-2’s high rate of mild infections and asymptomatic transmission that led to very rapid spread. The subsequent impact on Scotland has been characterised in detail with initially hundreds of introductions associated with international travel. Nonetheless the first 2020 lockdown had essentially eradicated SARS-CoV-2 from Scotland, and it was a return to international travel in the summer of 2020 that reintroduced the virus. Subsequent virus evolution has led to multiple more adapted-human variants, the variants of concern, and we can learn from these what SARS-CoV-2 future evolutionary trajectory will probably look like and where surveillance needs to be targeted. |
Phylo-epidemiology of an outbreak of HIV among people who inject drugs in Northern Ireland - Kathy Li, Belfast Health and Social Care Trust
Background: An increase in the incidence of HIV infection in people who inject drugs (PWID) in Belfast, Northern Ireland was detected in mid-2020. Public health convened a multidisciplinary outbreak control team to implement measures to control this involving HIV clinicians, homeless inclusion health teams, prison and addictions services.
Methods: Routine baseline HIV resistance sequencing offered as part of clinical care provided sequence data that was used to construct a phylogenetic tree. HIV sequence analysis included n=618 partial (gag-pol region) sequences, date range 8/2017 to 9/2023. Maximum likelihood phylogeny and cluster analysis were used to link sequences/cases associated with an epidemiologically defined PWID cluster.
Results: In total there were 26 cases of HIV in PWID, 23 were new diagnosis since August 2020. Median age was 30 y (range 23-43), 50% female. 92% (22/26) were co-infected with HCV and 52% (11/21) had a negative HIV test in the preceding year. We obtained sequences from 80 % (n=21) of these cases. There was a peak of 12 new cases in 2021) and 5 cases detected in 2022. Phylogenetic analysis confirmed that 3/5 of these cases were in a separate cluster.
Discussion: A rapid outbreak response involving increased outreach services to improve engagement in a high risk cohort was implemented in 2020 in NI. The phylogenetic investigations added to the information gathered by outreach teams regarding transmission networks which then informed public health on targeted approaches and response to interventions.
Initiation of a genomics surveillance programme for public health in Northern Ireland - Katie Binley, Public Health Agency, Northern Ireland
| During the COVID-19 pandemic, the Public Health Agency (PHA) set up a new whole genome sequencing (WGS) surveillance programme to monitor COVID-19 variants in Northern Ireland. The WGS Surveillance team used sequencing and genotyping results to produce routine reports on the prevalence of variants, scan for travel-related variants of concern, and provide enhanced information for outbreaks. We were able to link sequencing results to epidemiological information to monitor for signs of increased incidence among specific groups or in particular geographies, as well as potential signs of increased disease severity associated with a variant. Genotyping was used earlier in the pandemic as a rapid screening tool for travel-related variants, and sequencing was used to confirm lineages. Genotyping was ceased following the dominance of Omicron, given its limitation in differentiating between similar lineages. We continue to gather sequencing data to track variant prevalence and for horizon scanning, however given the reduced COVID testing volume, we have a limited data set with which to carry out surveillance on. As a new area of work for the PHA, one of the biggest obstacles was communicating complex concepts and novel terminology to public health colleagues and to the public, while managing media excitement around new variants. As we think about how to expand genomic surveillance beyond COVID-19, we need to consider how we intend to use genomics in public health, as well as considering the limitations: turnaround time of sequencing limits its use cases in an acute setting, the availability of samples for sequencing, and the need for a UK-wide pathogen genomics platform since pathogens don’t respect geographical boundaries. |
Genomic Surveillance in the assessment of risk-based travel policy in Scotland during the COVID-19 pandemic - Kirstin Leslie, Public Health Scotland - Clinical and Protecting Health
Isobel McLachlan*, Selene Huntley*, Kirstin Leslie*, Jennifer Bishop, Christopher Redman, Gonzalo Yebra, Sharif Shaaban, Nicolaos Christofidis, Samantha Lycett, Matthew T.G. Holden, David L. Robertson, Alison Smith-Palmer, Joseph Hughes, Sema Nickbakhsh
* Joint first authors
Background: Travel policies have been used to prevent global spread of novel pathogens, including during the COVID-19 pandemic. Here we investigated the public health effects of a temporary traffic light system introduced in Scotland in 2021, imposing red-amber-green (RAG) status on different countries based on risk assessment. Genomic surveillance data was used to consider the impact the policy had on introductions of novel variants.
Methods: We analysed data on international flight passengers arriving into Scotland, COVID-19 testing surveillance, and SARS-CoV-2 whole genome sequences to quantify effects of the traffic light system on international travel frequency, travel-related SARS-CoV-2 case importations, national SARS-CoV-2 case incidence, and importation of novel SARS-CoV-2 variants.
Results: Amber list countries were the most frequently visited and ranked highly for SARS-CoV-2 importations and contribution to national case incidence. When examined according to travel destination, SARS-CoV-2 importation risks did not strictly follow RAG designations, and red lists did not prevent establishment of novel SARS-CoV-2 variants. For most travel destinations and periods of the epidemic, the most likely imported variant reflected the dominant variant circulating in Scotland. However, some variation in the risk of variant importation was observed across travel destinations, particularly during the period of Alpha variant where multiple introductions were observed, whereas rapid community transmission drove Omicron to become established.
Conclusions: Our findings suggest that country-specific post-arrival screening undertaken in Scotland did not prohibit importation of novel variants into Scotland. Travel rates likely contributed to patterns of high SARS-CoV-2 case importation and population impact.
Levelling up routine surveillance for rabies virus and beyond - Kirstyn Brunker, University of Glasgow
Genomic sequencing is a key component of enhanced pathogen surveillance but is still only widely used for public health emergencies. The COVID pandemic accelerated genomics expertise and resources, particularly in low and middle income countries. There is immense opportunity to translate these resources to tackle the less visible but burdensome endemic diseases that affect disadvantaged communities. Rabies is one of these diseases. Vaccine preventable yet an ever present threat in much of the global south. I will present the successful implementation of accessible genomic surveillance for rabies virus in areas of Africa, Latin America and southeast Asia- and its translation to COVID research when the need arose. We showcase its capacity to provide critical insights to inform outbreak management and rabies elimination programmes, while simultaneously maintaining a platform for pandemic preparedness.
AgentCOVID: a multi-variant model of COVID spread - Louise Matthews, University of Glasgow
Public health preparedness for winter outbreaks benefits from predictive epidemiological models that can capture multiple circulating pathogens such as flu and SarsCoV2. We are tackling this need through the development, in Julia, of agent-based models of disease spread in the Scottish population that allows the simultaneous circulation of 100’s of pathogen variants. Our model AgentCOVID is driven by genomic data used to define antigenically distinct variants and to capture the impact of infection history, vaccination history and the antigenic distance between variants on the spread of infection. Ultimately, this tool will be used to develop predictions of when new variants will successfully spread in the Scottish population and to support winter preparedness by Public Health Scotland.
Establishing high-throughput Illumina Sequencing service for SARS-CoV-2 in NHS Lothian lab - Madhuri Barge, NHS Lothian
| The Viral Sequencing Service (VSS) in Royal Infirmary of Edinburgh, NHS Lothian, provides Whole Genome Sequencing (WGS) of SARS-CoV-2, primarily to diagnostic labs in the East of Scotland. WGS has played a crucial role in identifying emerging and existing SARS-CoV-2 variants; this helps inform patient care and supports public health actions relating to the pandemic. VSS initially used Oxford Nanopore Technology (ONT) for sequencing SARS-CoV-2 genomes manually. On ONT GridION platform, 96 samples can be loaded on one flow cell and it takes 1 day of library preparation by one member of the staff. We have then used Illumina sequencing to manually prepare up to 384 samples for high-throughput sequencing using the NextSeq 2000 Sequencing System. Preparing genomic libraries manually for WGS is a laborious task and involves extensive hands-on time of staff and chances of introducing contamination are high. To meet the high demands of the Viral Sequencing Service, we have installed and validated Hamilton Robots for automation of sample sorting, viral RNA extraction, RT-PCR and Illumina sequencing by Illumina NextSeq 2000. This validation helped to evaluate the performance of the Hamilton STAR/let in comparison with the manual set up method. The genomic libraries prepared by automated method when compared with manual method showed similar level of passed QC percentage, defined as >90% genome completeness. In this verification we also analysed the time it takes to run the automated protocols end-to-end (in succession) to give an indication of the turn-around time of each sample and identify any actions required to allow for the smooth running of the entire process. The introduction of the automated process is likely to reduce the rate and level of contamination in our service. High through put sequencing is a need of an hour in pandemic. Automated WGS helped us to upscale the service to 2000 genomes per week. This work flow can be adapted for any other pathogen sequencing. |
Changes in population immunity to coronaviruses reduce the likelihood of emergence SARS-CoV-X - Pablo Murcia, University of Glasgow
| Sarbecoviruses pose a significant threat to public health as illustrated by outbreaks caused by severe acute respiratory syndrome (SARS-CoV), Middle East respiratory syndrome (MERS-CoV), and the COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since then, a key priority is to identify which animal sarbecoviruses could cause another pandemic. We hypothesised that changes in population immunity to SARS-CoV-2 generated a powerful barrier against the emergence of zoonotic sarbecoviruses antigenically related to SARS-CoV-2 (i.e., SARS-CoV-X). To test our hypothesis we used SARS-CoV as a model of an emerging coronavirus, given its close phylogenetic relationship with SARS-CoV-2, its zoonotic properties and its ability to transmit among humans. Neutralisation assays using pseudotyped viruses show that sera from individuals exposed to SARS-CoV-2 by vaccination and/or natural infection can cross-neutralise SARS-CoV. Using a compartmental epidemiological model, we simulated the introduction and subsequent transmission dynamics of SARS-CoV in the context of SARS-CoV-2 circulation under different scenarios of population cross-immunity. Our data suggest that the likelihood of SARS-CoV-X emergence has been reduced significantly and the main factors driving this reduction were i) the level of cross-immunity elicited by vaccines and circulating strains of SARS-CoV-2; ii) vaccination coverage; iii) COVID-19 prevalence; and iv) the effective reproductive number of SARS-CoV-X. Notably, a reduction in COVID-19 prevalence due to increased vaccine effectiveness may increase the size of SARS-CoV-X outbreaks if the vaccines did not confer cross-protection. Our findings highlight the importance of annual vaccination programs and suggest that non-sterilising vaccines provide more effective cross-protection against antigenically similar viruses with pandemic potential. |
Identifying key genetic characteristics of internal gene segments of recent H5N1 2.3.4.4b lineages - Rute Pinto, Roslin Institute, University of Edinburgh
| Since 2020 the UK has experienced unprecedented numbers of clade 2.3.4.4b highly pathogenic H5Nx avian influenza A virus (IAV) incursions with significant impacts in wild and domesticated bird populations. This calamity correlates with a N8 to N1 genomic segment swap, followed by several reassortment events with other avian IAV serotypes, generating genetic diversity of 2.3.4.4b, particularly in segments 1, 2, 3 and 8. Aiming to understand how the internal gene segments contribute to the increased infectivity of new 2.3.4.4b strains, reverse genetic viruses have been generated to represent the precursor “H5N8-20” and subsequent diversity (“H5N1-20”, “AIV07”, “AIV08”, “AIV09” and “AIV48”) of the UK incursion viruses, all harbouring the glycoproteins of a laboratory adapted strain to allow BSL2 work. H5N8-20, AIV09 and AIV48 viruses showed reduced viral fitness in chicken lung epithelial cells. Conversely, H5N8-20 and AIV48 replicated better in human lung carcinoma cells. Transfection-based subviral assays showed viral polymerase deficits in the H5N8-20 virus that could be traced to the PB2 subunit. The replication deficits of H5N8-20 and AIV48 viruses also correlated with segment 8 swaps that led to reduced ability to suppress cellular gene expression, leading to increased production of type I interferon. Nevertheless, AIV48-like viruses which emerged in mid-2022 continue to circulate widely, predominantly in gulls. We conclude that internal gene swaps contributed to the generation of the current H5N1 epizootic and that continued monitoring is needed to risk assess an evolving outbreak. |
Posters
Combined influence of imperfect vaccines, host genetics, and non-genetic drivers on virus transmission and virulence evolution - Carol Leitch, Roslin Institute, University of Edinburgh
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Authors: Jamie Prentice1, E. Carol McWilliam Leitch1*, Margo Chase-Topping1, Christopher Pooley2, Glenn Marion2, Barbara Shih1,3, Jody Mays4, Jacob Trimpert5, Klaus Osterrieder5,6, Dolapo Enahoro4, John Dunn7, Hans Cheng4, Samantha Lycett1,#, Andrea Doeschl-Wilson1,#. Affilitations: 1Roslin Institute, University of Edinburgh, Scotland, UK; 2Biomathematics and Statistics Scotland, Edinburgh, UK; 3Biomedical and Life Sciences, Lancaster University, UK; 4United States Department of Agriculture, Agricultural Research Service, US National Poultry Research Center, East Lansing, MI 48823, USA; 5Institut für Virologie, Freie Universitat Berlin, Berlin 14163, Germany; 6Department of Infectious Disease and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong; 7United States Department of Agriculture, US National Poultry Research Center, Athens, GA 30605, USA. To enable employment of effective and sustainable disease control strategies, it is extremely important to understand how pathogens like viruses are transmitted and evolve to higher virulence. This requires informative datasets to determine the short- and long-term effectiveness of disease control approaches, that include biosecurity, genetic selection for disease resistance, and widespread vaccination. In this Ecology and Evolution of Infectious Diseases project, an international, interdisciplinary team investigates the impact of these approaches on the spread and evolution of two avian pathogenic viruses – Marek’s disease virus (MDV) and infectious bronchitis virus (IBV) – both of which are primarily controlled by imperfect vaccines. It has been argued that imperfect vaccines like those to MDV and IBV, or host genetic resistance may alter the balance of selection between pathogen transmission and virulence by allowing a few more divergent but still virulent strains to be transmitted at reduced cost. However, these hypotheses have not been proven, and predictive frameworks are lacking for determining the combined influence of host and viral genetics, as well as vaccination on viral transmission and evolution to increased virulence. To address these knowledge gaps, the team carries out a series of transmission experiments that utilize unique resources and data from 7,000+ birds under highly controlled conditions. The primary goal of the project is to generate high-resolution empirical data and use these to establish the role of genome variability on virulence evolution, and to build the next generation of data-informed systems models to assess and predict the combined influence of genetics and vaccination on virus transmission and evolutionary dynamics in different socio-economic settings. This will be achieved through the following scientific tasks: |
Development of a new tiled amplicon method for Whole Genome Sequencing of RSV - Goncalo Fernandes, NHS Lothian
Authors: Goncalo Fernandes (1); Daniel Maloney (1,2); Rebecca Dewar (1); Kate Templeton (1)
Affiliations: (1) NHS Lothian, Edinburgh, UK; (2) Centre for Immunity, Infection and Evolution, University of Edinburgh, UK
Background: Large scale immunisations against RSV are likely to be introduced in the near future. How these will disrupt viral transmission, and how viral genomic variability will affect immunisation effectiveness, remains unknown. Current RSV sequencing approaches rely on a small number of relatively large amplicons which are not easily applicable to sub-optimal samples. We therefore designed a novel short amplicon approach for sequencing complete RSV genomes.
Methods: RSV primer scheme design was based on 6 recent RSV A and RSV B consensus sequences from varying locations and years (GISAID platform). Primalscheme (Quick et al., 2017) was used for multiplex primer design of a two tiling primer amplicon scheme. To allow the use of existing SARS-CoV-2 sequencing infrastructure, ~400bp amplicons were chosen resulting in 50 amplicons per subtype. For validation we selected NHS Lothian (Scotland) RSV samples from 2019 to 2022 and followed the ARTIC-loCost-v3 nanopore library preparation method, with modifications. Data analysis was performed using an in-house version of the “fieldbioinformatics” pipeline.
Results: Both primer schemes successfully amplified clinical RSV samples with genome coverage up to 99%. We tested these in a subsection of our sample pool from 2022 with low Ct values and all results were within expected coverage for the majority of samples.
Conclusion: We have developed an effective, easy-to-use tiled amplicon approach, suitable for a range of samples which can be used with existing SARS-CoV-2 sequencing methodologies. It is likely to be of use to laboratories sequencing RSV globally, particularly those in low- and middle-income countries
Non-Polio enterovirus surveillance from environmental samples - Abby Parker, NHS Lothian
Surveillance of pathogens using wastewater is becoming an increasingly recognized tool to inform public health decisions, as reiterated by a proposed directive from the European Commission (Proposal for a revised Urban Wastewater Treatment Directive (europa.eu)) and is further highlighted by the extensive sequencing efforts using wastewater samples during the SARS-CoV-2 pandemic to monitor variants. Since 2014 UK wastewater has been routinely screened for the presence of poliovirus at 2 sites. Enhanced sampling of UK-wide sites was established by UKHSA in response to the detection of vaccine-derived poliovirus in London wastewater between February and July 2022. Here we discuss the routine use of a previously published PCR-based sequencing protocol for the detection of enteroviruses in wastewater in a subset of 24 sites from England and a further 10 from Scotland. Data within this UK-wide network provide an interesting insight into some of the enteroviruses present in wastewater and potentially circulating throughout the UK during the Autumn-Winter period of 2022.
Development and implementation of a NGS service in a clinical virology laboratory - Lynne Ferguson, West of Scotland Specialist Virology Centre
Authors: Lynne Ferguson and Emily Goldstein
Next generation sequencing has been a powerful tool in diagnostic virology laboratories recently. The SARS-CoV-2 pandemic lead to a global public health response, part of which relied upon genomic surveillance. Commercial sequencing kits were rapidly developed for the genetic characterisation of SARS-CoV-2.
At the West of Scotland Specialist Virology Centre (WoSSVC), NGS technology and workflow was rapidly implemented. Data contributed to the Scottish public health surveillance and response and demonstrated the power and usefulness of these platforms. This has also opened up the opportunity to transition current Sanger methods at WoSSVC to an NGS workflow, namely influneza A & B, RSV and bacterial pathogens. Can the NGS technology and workflow be applied to these pathogens? With limited NGS expertise, training and with the requirement for bioinformatic support, this will be a challenge in a diagnostic laboratory but hijacking current NGS technology reduces upfront cost and has the benefit of the genetic characterisation of these seasonal respiratory viruses and other bacterial pathogens.
One Health genomic epidemiology of Escherichia coli and antimicrobial resistance within the national Malawian poultry supply chain - Vesa Qarkaxhija, University of Edinburgh
Understanding the complex epidemiology of WHO-priority pathogens such as E. coli and their antibiotic resistance patterns relies on holistic One Health approaches. In this study we use a unique strategy, sampling a hierarchical poultry community breeding structure including poultry, farmers, and their environment across the central region of Malawi as designed and implemented by six fellows funded by Fleming Fund. We use 24 antibiotic enriched metagenomes to map the microbial and resistome landscape. Combined with long and short read sequences of 244 phenotyped E. coli isolates to examine the molecular characteristics including but not limited to the role of mobile genetic elements in trafficking antimicrobial resistance (AMR) determinants. Our objective here is to evaluate the contribution of ‘vertical’ transmission of resistance from founder flocks at the apex, down to multipliers and small-scale farmers, compared to ‘horizontal’ introduction, along the supply chain. By regarding antimicrobial resistance genes (ARGs), they're flanking regions and recombination patterns of plasmids to identify potential sharing events between hosts and dynamic AMR. Our preliminary analysis shows enriched metagenomics selecting for low abundance genes to resistance classes of interest. Our long read sequence data allows us to better understand and resolve the genetic context of the ARGs to understand their mobility and sharing patterns across the One Health spectrum. Here, we capture through a combination of structured sampling, long-read sequencing and genome sequencing, the prevalence and transmission of AMR to identify pathways of AMR spread and the potential zoonotic risk of these within a complex environment. I will present for the first time the phenotypic and molecular characteristics of E. coli and its domicile microbiome recovered from a 60-year-old community poultry breeding system in Malawi.
Title not available - Ifeanyi Omah, University of Glasgow
Abstract not available
Financial support
