Digging Deeper Into Hepatitis C Virus Outbreaks

Methods for investigating outbreaks of hepatitis C virus (HCV) have evolved since the discovery of the virus in 1989. Early investigations focused on epidemiological evidence such as likelihood of exposure, risk factors, temporal information, and serological evidence to identify members of an outbreak [1–3]. Streamlined nucleic acid sequencing methods provided an important means of verifying suspected transmission events, and, over time, sequencing has become a standard outbreak investigation tool [4–6]. When the viral sequences from different individuals are found to be identical or very similar, the probability is very high that those individuals are part of the same transmission chain. Unfortunately, interpreting the relationship between viral sequences in different individuals is not always straightforward. RNA viruses such as HCV mutate very rapidly causing the sequences between the source and recipient of a transmission to quickly diverge. The magnitude of this divergence depends on the amount of time elapsed and on the region of the virus sequenced. This story is further complicated by the fact that, because of this rapid evolutionary rate, individuals are actually infected with entire swarms of nonidentical but closely related HCV variants, termed quasispecies [7]. Quasispecies are composed of one or a few majority variants, alongwith severalminority variants. Sanger-based consensus sequencing can be used to identify the major HCVvariants in an individual, but it is not always the major variants that establish infection in a new host following transmission [8, 9]. These features complicate HCV outbreak investigations, hampering efforts to develop standard methods for differentiating outbreaks from sporadic or unrelated infections. The report by Campo et al in this issue of The Journal of Infectious Diseases attempts to tackle these issues by using an impressive sample set comprising 127 cases from 32 previously well-characterized HCV outbreaks. In the past, many HCV outbreaks have been investigated using sequencing; however, the viral genes sequenced, the analytical methods used, and the criteria used to define members of an outbreak varied from study to study [4, 5, 10, 11]. The study by Campo et al is the first comprehensive sequencing-based analysis that attempts to evaluate a large number of well-defined HCV outbreaks to identify standard genetic criteria that can be applied to investigate future outbreaks. In addition to this rare sample set, the authors used end-point limiting-dilution polymerase chain reaction analysis to obtain sequences from multiple clones of theHCV hypervariable 1 region in each individual (approximately 40 clones/individual). This resulted in a data set that represents the quasispecies population in each individual more accurately than consensus sequencing. The relationship between each person’s population of sequences was evaluated using 3measures of genetic distance: (1) Hamming distance, (2) Nei-Tamura distance, and (3) patristic distance. The minimal distance between all variants, the average distance, and the distance between major variants was determined for each of the 3 measures. The goal was to determine which criteria allowed for the greatest differentiation between members of an outbreak versus unrelated cases. As expected, many sequences (20.86%) from different people within the same outbreak were identical; however, many sequences differed by 1 or more nucleotides. When the genetic distances between different sequence populations were compared, minimal Hamming distance andminimal patristic distancewere found to have the greatest ability to differentiate outbreak from nonoutbreak cases. This finding has important implications for future outbreak investigations. Firstly, the finding that Hamming distance (ie, the number of nucleotide differences between 2 sequences) performs just as well as patristic distance and simplifies the process of future outbreak investigations. Currently, many sequence-based outbreak investigations use phylogenetic methods, including considerationof patristic distance, to investigate the relationship between Received and accepted 11 November 2015; published online 17 November 2015. Correspondence: A. D. Olmstead, The University of British Columbia and The BC Centre for Disease Control, 655 W 12th Ave, Vancouver, BC V5Z4R4, Canada (andrea.olmstead@bccdc. ca). The Journal of Infectious Diseases 2016;213:880–2 © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, contact journals. [email protected]. DOI: 10.1093/infdis/jiv543