Metagenomic surveillance of viruses at the human-animal interface
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Date
30/11/2020Author
Bogaardt, Carlijn
Metadata
Abstract
Zoonotic viruses are a major contributor to emerging infectious diseases, and continuously
burden public health systems. Early detection and effective response to viral emergence
require an overview of what viruses are circulating in animal hosts, which of these can and
do infect at-risk human populations, and which pose the greatest risk of further spread.
However, knowledge of such epidemiological patterns is generally biased towards known
pathogens of humans and of economically important livestock species. With metagenomic
sequencing, one can begin to address these biases by generating a more representative
picture of what viruses are present in different host species living in a shared environment.
Vietnam is considered a high-risk setting for the emergence of zoonoses, due to its high
population and livestock densities and the prevalence of socio-cultural practices involving
frequent close contacts between humans, livestock and wildlife. The Vietnam Initiative on
Zoonotic Infections (VIZIONS) was established to improve our understanding of zoonotic
emergence in this context. Over 2000 faecal samples and rectal swabs were collected from
humans and a variety of farmed animals, and subjected to metagenomic sequencing. In this
thesis, I use viral taxonomic classification methods to identify and characterise the viruses
present in these samples. I investigate any signals for (putative) zoonotic viruses, and assess
whether they could represent emerging public health threats. I also evaluate the roles and
challenges of metagenomic surveillance for emerging viruses at the human-animal interface.
The first part of this thesis focuses on the development and testing of a viral taxonomic
classification pipeline. I describe the basic steps of this pipeline, and the rationale behind the
chosen methods. Next, I test the pipeline on a subset of samples and viruses for which
diagnostic quantitative PCR (qPCR) data were available for comparison. Receiver operating
characteristic (ROC) curve analysis showed that the pipeline accurately distinguishes qPCR positive from qPCR-negative samples, and read pair counts correlate well with qPCR cycle
threshold values. Investigation of samples with discordant qPCR and metagenomic results
indicated that taxonomic misclassification by the pipeline plays a minor role in these
discrepancies. Additionally, I found that, for each of the tested viruses, negative samples have
variable read pair counts (“background noise”) that correlate with the total number of read
pairs assigned to the virus across all samples of the same sequencing run. I hypothesise that
this is due to “index switching”, a form of cross-contamination, and model the association.
The findings of these investigations allow me to incorporate additional steps into the pipeline
to counteract misclassification, and to use signal thresholds that take into account the effect
of index switching cross-contamination.
In the second part of this thesis, I focus on the characterisation of viruses identified with the
taxonomic classification pipeline. I present an overview of the mammalian viruses found in
samples from humans, swine and rats from Dong Thap province. After removing likely
contaminants, I categorize the remaining viruses according to their zoonotic potential. Seven
of these viruses are known or generally presumed to be zoonotic; three are only found in the
animal study populations, but four – Rotavirus A, Picobirnavirus, Human associated cyclovirus
8, and Mammalian orthoreovirus – are shared between human and animal populations.
Comparison of signals suggests that viral chatter (Rotavirus A) and cross-species transmission
within a more generalist ecology (Picobirnavirus, Human associated cyclovirus 8) are
plausible in this setting. Additionally, three putative novel zoonoses are identified, but
knowledge gaps hinder extensive interpretation. I evaluate the relevance of these 10
zoonotic and putative novel zoonotic viruses as potential emerging public health threats, and
highlight the knowledge gaps that need to be addressed before the risks of these viruses can
be properly assessed.
Finally, I interpret my findings in the general context of disease emergence, and evaluate the
roles and challenges of viral metagenomics as a tool in the surveillance for emerging
infectious disease.