A universal protocol to generate consensus level genome sequences for foot-and-mouth disease virus and other positive-sense polyadenylated RNA viruses using the Illumina MiSeq

BACKGROUND: Next-Generation Sequencing (NGS) is revolutionizing molecular epidemiology by providing new approaches to undertake whole genome sequencing (WGS) in diagnostic settings for a variety of human and veterinary pathogens. Previous sequencing protocols have been subject to biases such as those encountered during PCR amplification and cell culture, or are restricted by the need for large quantities of starting material. We describe here a simple and robust methodology for the generation of whole genome sequences on the Illumina MiSeq. This protocol is specific for foot-and-mouth disease virus (FMDV) or other polyadenylated RNA viruses and circumvents both the use of PCR and the requirement for large amounts of initial template. RESULTS: The protocol was successfully validated using five FMDV positive clinical samples from the 2001 epidemic in the United Kingdom, as well as a panel of representative viruses from all seven serotypes. In addition, this protocol was successfully used to recover 94% of an FMDV genome that had previously been identified as cell culture negative. Genome sequences from three other non-FMDV polyadenylated RNA viruses (EMCV, ERAV, VESV) were also obtained with minor protocol amendments. We calculated that a minimum coverage depth of 22 reads was required to produce an accurate consensus sequence for FMDV O. This was achieved in 5 FMDV/O/UKG isolates and the type O FMDV from the serotype panel with the exception of the 5′ genomic termini and area immediately flanking the poly(C) region. CONCLUSIONS: We have developed a universal WGS method for FMDV and other polyadenylated RNA viruses. This method works successfully from a limited quantity of starting material and eliminates the requirement for genome-specific PCR amplification. This protocol has the potential to generate consensus-level sequences within a routine high-throughput diagnostic environment

Transmission tree of the highly pathogenic avian influenza (H5N1) epidemic in Israel, 2015

The transmission tree of the Israeli 2015 epidemic of highly pathogenic avian influenza (H5N1) was modelled by combining the spatio-temporal distribution of the outbreaks and the genetic distance between virus isolates. The most likely successions of transmission events were determined and transmission parameters were estimated. It was found that the median infectious pressure exerted at 1 km was 1.59 times (95% CI 1.04, 6.01) and 3.54 times (95% CI 1.09, 131.75) higher than that exerted at 2 and 5 km, respectively, and that three farms were responsible for all seven transmission events. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13567-016-0393-2) contains supplementary material, which is available to authorized users

Reconstruction of the Transmission History of RNA Virus Outbreaks Using Full Genome Sequences: Foot-and-Mouth Disease Virus in Bulgaria in 2011

<div><p>Improvements to sequencing protocols and the development of computational phylogenetics have opened up opportunities to study the rapid evolution of RNA viruses in real time. In practical terms, these results can be combined with field data in order to reconstruct spatiotemporal scenarios that describe the origin and transmission pathways of viruses during an epidemic. In the case of notifiable diseases, such as foot-and-mouth disease (FMD), these analyses provide important insights into the epidemiology of field outbreaks that can support disease control programmes. This study reconstructs the origin and transmission history of the FMD outbreaks which occurred during 2011 in Burgas Province, Bulgaria, a country that had been previously FMD-free-without-vaccination since 1996. Nineteen full genome sequences (FGS) of FMD virus (FMDV) were generated and analysed, including eight representative viruses from all of the virus-positive outbreaks of the disease in the country and 11 closely-related contemporary viruses from countries in the region where FMD is endemic (Turkey and Israel). All Bulgarian sequences shared a single putative common ancestor which was closely related to the index case identified in wild boar. The closest relative from outside of Bulgaria was a FMDV collected during 2010 in Bursa (Anatolia, Turkey). Within Bulgaria, two discrete genetic clusters were detected that corresponded to two episodes of outbreaks that occurred during January and March-April 2011. The number of nucleotide substitutions that were present between, and within, these separate clusters provided evidence that undetected FMDV infection had occurred. These conclusions are supported by laboratory data that subsequently identified three additional FMDV-infected livestock premises by serosurveillance, as well as a number of antibody positive wild boar on both sides of the border with Turkish Thrace. This study highlights how FGS analysis can be used as an effective on-the-spot tool to support and help direct epidemiological investigations of field outbreaks.</p> </div

Vaccination against Foot-and-mouth disease : do initial conditions affect its benefit?

When facing incursion of a major livestock infectious disease, the decision to implement a vaccination programme is made at the national level. To make this decision, governments must consider whether the benefits of vaccination are sufficient to outweigh potential additional costs, including further trade restrictions that may be imposed due to the implementation of vaccination. However, little consensus exists on the factors triggering its implementation on the field. This work explores the effect of several triggers in the implementation of a reactive vaccination-to-live policy when facing epidemics of foot-and-mouth disease. In particular, we tested whether changes in the location of the incursion and the delay of implementation would affect the epidemiological benefit of such a policy in the context of Scotland. To reach this goal, we used a spatial, premises-based model that has been extensively used to investigate the effectiveness of mitigation procedures in Great Britain. The results show that the decision to vaccinate, or not, is not straightforward and strongly depends on the underlying local structure of the population-at-risk. With regards to disease incursion preparedness, simply identifying areas of highest population density may not capture all complexities that may influence the spread of disease as well as the benefit of implementing vaccination. However, if a decision to vaccinate is made, we show that delaying its implementation in the field may markedly reduce its benefit. This work provides guidelines to support policy makers in their decision to implement, or not, a vaccination-to-live policy when facing epidemics of infectious livestock disease

Discovering the Phylodynamics of RNA Viruses

The advent of extremely high throughput DNA sequencing ensures that genomic data from microbial organisms can be acquired in unprecedented quantities and with remarkable rapidity. Although this genomic revolution will affect all microbes alike, our focus here is on RNA viruses, as the rapidity of their evolution, which is observable over the time scale of human observation, allows phylodynamic inferences to be made with great precision. In the foreseeable future it is likely that complete genome sequencing will become the standard method of viral characterization, providing the highest possible resolution for phylogenetic studies. The rapidity with which genome sequence data were generated from the ongoing epidemic of swine-origin H1N1 influenza A virus [1] is testament to the power of this technology

Quantifying the Risk of Localised Animal Movement Bans for Foot-and-Mouth Disease

The maintenance of disease-free status from Foot-and-Mouth Disease is of significant socio-economic importance to countries such as the UK. The imposition of bans on the movement of susceptible livestock following the discovery of an outbreak is deemed necessary to prevent the spread of what is a highly contagious disease, but has a significant economic impact on the agricultural community in itself. Here we consider the risk of applying movement restrictions only in localised zones around outbreaks in order to help evaluate how quickly nation-wide restrictions could be lifted after notification. We show, with reference to the 2001 and 2007 UK outbreaks, that it would be practical to implement such a policy provided the basic reproduction ratio of known infected premises can be estimated. It is ultimately up to policy makers and stakeholders to determine the acceptable level of risk, involving a cost benefit analysis of the potential outcomes, but quantifying the risk of spread from different sized zones is a prerequisite for this. The approach outlined is relevant to the determination of control zones and vaccination policies and has the potential to be applied to future outbreaks of other diseases

Quantitative Assessment of the Sensitivity of Various Commercial Reverse Transcriptases Based on Armored HIV RNA

The in-vitro reverse transcription of RNA to its complementary DNA, catalyzed by the enzyme reverse transcriptase, is the most fundamental step in the quantitative RNA detection in genomic studies. As such, this step should be as analytically sensitive, efficient and reproducible as possible, especially when dealing with degraded or low copy RNA samples. While there are many reverse transcriptases in the market, all claiming to be highly sensitive, there is need for a systematic independent comparison of their applicability in quantification of rare RNA transcripts or low copy RNA, such as those obtained from archival tissues.We performed RT-qPCR to assess the sensitivity and reproducibility of 11 commercially available reverse transcriptases in cDNA synthesis from low copy number RNA levels. As target RNA, we used a serially known number of Armored HIV RNA molecules, and observed that 9 enzymes we tested were consistently sensitive to ∼1,000 copies, seven of which were sensitive to ∼100 copies, while only 5 were sensitive to ∼10 RNA template copies across all replicates tested. Despite their demonstrated sensitivity, these five best performing enzymes (Accuscript, HIV-RT, M-MLV, Superscript III and Thermoscript) showed considerable variation in their reproducibility as well as their overall amplification efficiency. Accuscript and Superscript III were the most sensitive and consistent within runs, with Accuscript and Superscript II ranking as the most reproducible enzymes between assays.We therefore recommend the use of Accuscript or Superscript III when dealing with low copy number RNA levels, and suggest purification of the RT reactions prior to downstream applications (eg qPCR) to augment detection. Although the results presented in this study were based on a viral RNA surrogate, and applied to nucleic acid lysates derived from archival formalin-fixed paraffin embedded tissue, their relative performance on RNA obtained from other tissue types may vary, and needs future evaluation

Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled &lsquo;reservoir' host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers

Evolutionary Analysis of Inter-Farm Transmission Dynamics in a Highly Pathogenic Avian Influenza Epidemic

Phylogenetic studies have largely contributed to better understand the emergence, spread and evolution of highly pathogenic avian influenza during epidemics, but sampling of genetic data has never been detailed enough to allow mapping of the spatiotemporal spread of avian influenza viruses during a single epidemic. Here, we present genetic data of H7N7 viruses produced from 72% of the poultry farms infected during the 2003 epidemic in the Netherlands. We use phylogenetic analyses to unravel the pathways of virus transmission between farms and between infected areas. In addition, we investigated the evolutionary processes shaping viral genetic diversity, and assess how they could have affected our phylogenetic analyses. Our results show that the H7N7 virus was characterized by a high level of genetic diversity driven mainly by a high neutral substitution rate, purifying selection and limited positive selection. We also identified potential reassortment in the three genes that we have tested, but they had only a limited effect on the resolution of the inter-farm transmission network. Clonal sequencing analyses performed on six farm samples showed that at least one farm sample presented very complex virus diversity and was probably at the origin of chronological anomalies in the transmission network. However, most virus sequences could be grouped within clearly defined and chronologically sound clusters of infection and some likely transmission events between farms located 0.8–13 Km apart were identified. In addition, three farms were found as most likely source of virus introduction in distantly located new areas. These long distance transmission events were likely facilitated by human-mediated transport, underlining the need for strict enforcement of biosafety measures during outbreaks. This study shows that in-depth genetic analysis of virus outbreaks at multiple scales can provide critical information on virus transmission dynamics and can be used to increase our capacity to efficiently control epidemics

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging