Abstract
Identifying emerging viral pathogens and characterizing their transmission is essential to developing effective public health measures in response to an epidemic. Phylogenetics, though currently the most popular tool used to characterize the likely host of a virus, can be ambiguous when studying species very distant to known species and when there is very little reliable sequence information available in the early stages of the outbreak of disease. Motivated by an existing framework for representing biological sequence information, we learn sparse, tree-structured models, built from decision rules based on subsequences, to predict viral hosts from protein sequence data using popular discriminative machine learning tools. Furthermore, the predictive motifs robustly selected by the learning algorithm are found to show strong host-specificity and occur in highly conserved regions of the viral proteome.
Highlights
Emerging pathogens constitute a continuous threat to our society, as it is notoriously difficult to perform a realistic assessment of optimal public health measures when little information on the pathogen is available
The viral genome usually contains about 1–2 Open Reading Frames (ORF), each coding for protein sequences about 2000–3000 amino acids long
We have presented a supervised learning algorithm that learns a model to classify viruses according to their host and identifies a set of highly discriminative oligopeptide motifs
Summary
Emerging pathogens constitute a continuous threat to our society, as it is notoriously difficult to perform a realistic assessment of optimal public health measures when little information on the pathogen is available. Recent outbreaks include the West Nile virus in New York (1999); SARS coronavirus in Hong Kong (2002–2003); LUJO virus in Lusaka (2008); H1N1 influenza pandemic virus in Mexico and the US (2009); and cholera in Haiti (2010). In all these cases, an outbreak of unusual clinical diagnoses triggered a rapid response, and an essential part of this response is the accurate identification and characterization of the pathogen. LUJO was identified as a novel, very distinct virus after the sequence of its genome was compared to other arenaviruses [1]. Arenaviruses are zoonotic agents usually transmitted from rodents
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