Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes.

Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.

[1]  Andrew L. Ferguson,et al.  Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design. , 2013, Immunity.

[2]  Bette Korber,et al.  Design and Pre-Clinical Evaluation of a Universal HIV-1 Vaccine , 2007, PloS one.

[3]  Nisheeth K. Vishnoi,et al.  Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold , 2012, PLoS Comput. Biol..

[4]  E. Jaynes Information Theory and Statistical Mechanics , 1957 .

[5]  Tarazona Error thresholds for molecular quasispecies as phase transitions: From simple landscapes to spin-glass models. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[6]  Andrew R. Jones,et al.  Allele frequency net: a database and online repository for immune gene frequencies in worldwide populations , 2010, Nucleic Acids Res..

[7]  Dennis R. Burton,et al.  Toward an AIDS Vaccine , 2008, Science.

[8]  Huang,et al.  Surface ordering and finite-size effects in liquid-crystal films. , 1991, Physical review. B, Condensed matter.

[9]  Eric O. Postma,et al.  Dimensionality Reduction: A Comparative Review , 2008 .

[10]  Gregory W. Corder,et al.  Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach , 2009 .

[11]  Michael W Deem,et al.  Sequence space localization in the immune system response to vaccination and disease. , 2003, Physical review letters.

[12]  K. Binder,et al.  Spin glasses: Experimental facts, theoretical concepts, and open questions , 1986 .

[13]  Claus O Wilke,et al.  Quasispecies theory in the context of population genetics , 2005, BMC Evolutionary Biology.

[14]  L. Wilkinson Immunity , 1891, The Lancet.

[15]  Philip J. R. Goulder,et al.  HIV and SIV CTL escape: implications for vaccine design , 2004, Nature Reviews Immunology.

[16]  R. Feynman,et al.  Quantum Mechanics and Path Integrals , 1965 .

[17]  Yi-Cheng Zhang QUASISPECIES EVOLUTION OF FINITE POPULATIONS , 1997 .

[18]  Christian L. Althaus,et al.  Dynamics of Immune Escape during HIV/SIV Infection , 2008, PLoS Comput. Biol..

[19]  Sebastian Bonhoeffer,et al.  Exploring the Complexity of the HIV-1 Fitness Landscape , 2012, PLoS genetics.

[20]  A. Perelson,et al.  HIV-1 Dynamics in Vivo: Virion Clearance Rate, Infected Cell Life-Span, and Viral Generation Time , 1996, Science.

[21]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[22]  Eric J. Arts,et al.  Variable Fitness Impact of HIV-1 Escape Mutations to Cytotoxic T Lymphocyte (CTL) Response , 2009, PLoS pathogens.

[23]  Sebastian Bonhoeffer,et al.  Stochastic or deterministic: what is the effective population size of HIV-1? , 2006, Trends in microbiology.

[24]  M. Eigen Selforganization of matter and the evolution of biological macromolecules , 1971, Naturwissenschaften.

[25]  Chin-Kun Hu,et al.  Exact solution of the Eigen model with general fitness functions and degradation rates. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Nisheeth K. Vishnoi,et al.  A Finite Population Model of Molecular Evolution: Theory and Computation , 2012, J. Comput. Biol..

[27]  A. E. Hirsh,et al.  The application of statistical physics to evolutionary biology. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[28]  Anthony D. Kelleher,et al.  Human Immunodeficiency Virus Type 1-Specific CD8+ T-Cell Responses during Primary Infection Are Major Determinants of the Viral Set Point and Loss of CD4+ T Cells , 2009, Journal of Virology.

[29]  L. Peliti,et al.  Population dynamics in a spin-glass model of chemical evolution , 1989, Journal of Molecular Evolution.

[30]  Feng Gao,et al.  Diversity Considerations in HIV-1 Vaccine Selection , 2002, Science.

[31]  Michael W Deem,et al.  Physical theory of the competition that allows HIV to escape from the immune system. , 2006, Physical review letters.

[32]  Michael W Deem,et al.  Quasispecies theory for finite populations. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[33]  Radford M. Neal Pattern Recognition and Machine Learning , 2007, Technometrics.

[34]  Todd M. Allen,et al.  Escape from the Dominant HLA-B27-Restricted Cytotoxic T-Lymphocyte Response in Gag Is Associated with a Dramatic Reduction in Human Immunodeficiency Virus Type 1 Replication , 2007, Journal of Virology.

[35]  David W. Haas,et al.  HLA-Associated Immune Escape Pathways in HIV-1 Subtype B Gag, Pol and Nef Proteins , 2009, PloS one.

[36]  Michael W Deem,et al.  Quantifying influenza vaccine efficacy and antigenic distance. , 2005, Vaccine.

[37]  Huldrych F. Günthard,et al.  Whole Genome Deep Sequencing of HIV-1 Reveals the Impact of Early Minor Variants Upon Immune Recognition During Acute Infection , 2012, PLoS pathogens.

[38]  Todd M. Allen,et al.  Coordinate linkage of HIV evolution reveals regions of immunological vulnerability , 2011, Proceedings of the National Academy of Sciences.

[39]  I. Leuthäusser,et al.  Statistical mechanics of Eigen's evolution model , 1987 .

[40]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[41]  C. Petropoulos,et al.  Evidence for Positive Epistasis in HIV-1 , 2004, Science.

[42]  J. Coffin,et al.  Linkage disequilibrium test implies a large effective population number for HIV in vivo. , 1999, Proceedings of the National Academy of Sciences of the United States of America.