Viral Reassortment As an Information Exchange Between Viral Segments
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Viral reassortment as an information exchange between viral segments Benjamin D. Greenbauma,1, Olive T. W. Lib, Leo L. M. Poonb, Arnold J. Levinea, and Raul Rabadanc,d aThe Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540; bState Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, School of Public Health, University of Hong Kong, Hong Kong; and cCenter for Computational Biology and Bioinformatics and dDepartment of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York, NY 10032 Edited by Robert A. Lamb, Northwestern University, Evanston, IL, and approved January 10, 2012 (received for review August 17, 2011) Viruses have an extraordinary ability to diversify and evolve. For uncovers new aspects of the process of reassortment, demonstrat- segmented viruses, reassortment can introduce drastic genomic ing significant combinations that occur commonly in several dif- and phenotypic changes by allowing a direct exchange of genetic ferent crosses of viral strains. We show that virus strain and host material between coinfecting strains. For instance, multiple influ- cell-type influence outcomes. We include a novel experiment with enza pandemics were caused by reassortments of viruses typically the latest pandemic strain, 2009 pdm, and the seasonal H1N1 found in separate hosts. What is unclear, however, are the under- strain circulating prior to its introduction, expanding the number lying mechanisms driving these events and the level of intrinsic of reassortment examples analyzed to date and comparing this bias in the diversity of strains that emerge from coinfection. To ad- case to other analogous experiments within our framework. dress this problem, previous experiments looked for correlations Information theory is a general mathematical framework for between segments of strains that coinfect cells in vitro. Here, quantifying the transmission and exchange of information (15, we present an information theory approach as the natural math- 16). Within this framework, we can separate multiple levels of ematical framework for this question. We study, for influenza and information transfer and exchange within viral segment replication other segmented viruses, the extent to which a virus’s segments and reassortment. At the same time, this formalism allows us to can communicate strain information across an infection and among show how these different levels constrain one another and to relate one another. Our approach goes beyond previous association stu- information theoretic quantities, such as entropy and mutual infor- dies and quantifies how much the diversity of emerging strains is mation, to the likely diversity of viral populations produced by BIOPHYSICS AND altered by patterns in reassortment, whether biases are consistent a host coinfection. We further provide a nonparametric permuta- COMPUTATIONAL BIOLOGY across multiple strains and cell types, and if significant information tion test to assess the statistical significance of these quantities. We is shared among more than two segments. We apply our approach show which segments share meaningful amounts of information to a new experiment that examines reassortment patterns be- across all experiments, implying general segregation rules in influ- tween the 2009 H1N1 pandemic and seasonal H1N1 strains, contex- enza, and which segments only share significant information for tualizing its segmental information sharing by comparison with particular strain pairings. Significantly, we quantify how much previously reported strain reassortments. We find evolutionary information they actually share—a key component in determining patterns across classes of experiments and previously unobserved the diversity of progeny. Finally, we extend our method to reo- higher-level structures. Finally, we show how this approach can be viruses, a member of the reoviridae family, which includes rota- combined with virulence potentials to assess pandemic threats. virus, the leading cause of acute childhood diarrhea worldwide (17). viral evolution ∣ systems biology ∣ emerging infectious disease In a typical experiment, a relevant cell type is coinfected with two different strains, and the repertoire of progeny viruses is eassortment of segmented viruses is a key mechanism for explored. These experiments separate intrinsic biases from those Rrapid novel virus creation. At least two human influenza pan- observed in circulating strains, in refs. 11 and 12, that may have demics in the last century were linked to lineages where some additional causes. Suppose two strains are introduced to cells number of genomic segments reassorted with a genome of non- in culture at equal multiplicities of infection (MOI), a typical ex- human origin (1, 2). This fact was reinforced by the emergence of perimental scenario. MOI is defined as the ratio of infectious the 2009 H1N1 pandemic (2009 pdm) virus (3–5). Novel reassor- agents to host targets, so each strain, ideally, is equally likely to tant strains can evade adaptive immunity by introducing antigens infect a target cell. After an experiment, the output probability to a naïve host population or overly stimulate innate immunity that a segment comes from a given parental strain may no longer by presenting a new host with abundant nonself molecular signals be the input value of one-half. We quantify this effect as the en- (6–10). Moreover, both sequence database studies and in vitro ex- tropy change per segment between the input probability distribu- periments have shown that genome reassortment between strains tion that a segment came from a given strain versus the output happens nonrandomly: If two strains coinfect the same cell, their distribution. progeny may not sample all possible strain/segment combinations If bias exists toward how pairs of segments appear together in uniformly (11–14). These analyses focused on whether it is more the output virus, such as may arise from packaging effects, this likely that pairs of segments from the same strain appear together will be captured by the mutual information shared between those in reassortments, typically using chi-square tests to establish signif- two segments. The entropy per segment constrains this quantity: icance. Because influenza has eight segments, there are 256 possible Author contributions: B.D.G., O.T.W.L., L.L.P., A.J.L., and R.R. designed research; B.D.G. and reassortant viruses when a cell is coinfected by two strains. Each O.T.W.L. performed research; B.D.G., O.T.W.L., L.L.P., A.J.L., and R.R. analyzed data; and strain type and host cellular environment can influence reassort- B.D.G., O.T.W.L., L.L.P., A.J.L., and R.R. wrote the paper. ment differently, so it would seem impossible to predict whether The authors declare no conflict of interest. a new pandemic strain can form. However, not every possible This article is a PNAS Direct Submission. progeny combination may occur or survive. As we show, this pro- Freely available online through the PNAS open access option. blem can be reformulated using information theory, determining 1To whom correspondence should be addressed. E-mail: [email protected]. ’ the information content of a segment s strain of origin distribu- This article contains supporting information online at www.pnas.org/lookup/suppl/ tion and the information shared among segments. Our approach doi:10.1073/pnas.1113300109/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1113300109 PNAS Early Edition ∣ 1of6 Downloaded by guest on October 2, 2021 The mutual information between segments is always less than the M H − p s p s minimum entropy per segment. For these quantities we have de- n ¼ ∑ nð Þ log2ð nð ÞÞ signed a nonparametric “channel scrambling” test for generating s¼1 p values. Furthermore, we use the total correlation to capture the entropy change for that segment will be structures of a higher order than pairwise, a feature not found in previous analyses. A hypothetical case is represented in Fig, 1, ΔHn ¼ log2ðMÞ − Hn: where segments 2, 3, and 7 have a significant total correlation. In this case the segments, taken individually, are equally likely to Typically, there are two equally probable coinfecting strains and come from the same strain of origin. Yet, if one segment has a the first term will then be equal to 1. The above quantity measures given strain of origin, the other two segments will also come from how much the output distribution deviates from uniformity. For a the same strain. given segment, a value near zero would indicate that, in the out- By formalizing the mathematical analysis for this process and put viruses, one is equally likely to see a segment come from testing that analysis on both new and existing reassortment data, either strain. If the value is close to 1, it indicates that this seg- we may better understand reassortment outcomes and predict ment is dominantly from one of the two input strains in the output limitations upon which virus will emerge, resulting in better pre- viruses. Hence, a change in entropy implies that one type of pro- geny virus is now more likely to appear than another, whereas paredness. That is the goal of this program. While a full explora- previously that was not the case. tion of the true set of reassortment biases requires a large-scale We analyze this quantity for an original experiment in which exploration of all combinations of infecting strains, infected cell MDCK cells were coinfected at MOI of 1 PFU/cell of seasonal type, and cell-type