Doctor of Philosophy / Department of Diagnostic Medicine/Pathobiology / Wenjun Ma / Influenza A virus (IAV) is a negative sense, single-stranded, segmented RNA virus with eight gene segments. It is an important respiratory pathogen which causes annual epidemics and occasional pandemics worldwide in humans and leads to considerable economic problems for the livestock industry. To control and prevent this significant disease, understanding the pathogenesis of IAVs is critical. Although some molecular mechanisms regarding virulence have been determined, IAV pathogenesis is not completely understood and is difficult to predict. The eight viral gene segments of IAV were thought to encode for 10 viral proteins. Since 2001, eight additional viral proteins have been identified, including PB1-F2, PB1-N40, PA-X, NS3, PA-N155, PA-N182, M42, and PB2-S1. However, the functions of these novel proteins in influenza virus replication as well as pathogenesis have not been fully elucidated. Although PB1-F2 protein is an important virulence factor of IAV, the effects of this protein on viral pathogenicity of swine influenza virus (SIV) remain unclear. In Chapter 2, we investigated the contribution of the PB1-F2 protein to viral pathogenicity of a virulent triple-reassortant (TR) H1N1 SIV in different hosts, pigs and mice. Our data indicate that PB1-F2 expression in virulent TR H1N1 SIV modulates virus replication and pathogenicity in the natural host, pigs, but not in mice. In addition, single amino acid (aa) substitution at position 66 (N/S) in the PB1-F2 has a critical role in virulence in mice but no effect was found in pigs. A novel IAV protein, PA-X consists of the N-terminal 191aa of PA protein and a unique C-terminal 41 (truncated form) or 61 (full-length form) aa residues encoded by +1 ribosomal frameshifting. Although several studies have demonstrated the PA-X protein as an important immune modulator and virulence factor, the impact of different expressions of PA-X protein including full-length, truncated or PA-X deficient forms on viral pathogenicity and host response remains unclear. In Chapter 3, we showed that expression of either truncated or full-length PA-X protein in 2009 human pandemic H1N1 (pH1N1) viruses suppresses host antiviral response by host shutoff activity which promotes viral growth and virulence in mice when compared to loss of PA-X expression. Furthermore, full-length PA-X expression displayed stronger impact on viral pathogenicity and host immune response compared to truncated PA-X expression. Taken together, our results provide new insights into the impact of PB1-F2 and PA-X proteins on virus replication, pathogenicity and modulation of host immune responses. This knowledge is important for better understanding of IAV pathogenesis.

Avec l’entrée d’internet dans notre quotidien, avec les réseaux sociaux, dans un monde de plus en plus numérique et mobile, le recours à la communication par internet est indispensable dans les stratégies de communication, et particulièrement en communication de crise. Une enquête, auprès d’universités françaises, permet d’analyser, à partir de l’exemple de la grippe A, comment internet est devenu un outil majeur dans la communication des universités en situation de crise. La communication par internet est d’abord une aide. Elle permet de diffuser largement les messages d’information et de prévention. A ce titre, elle est une communication interne. Elle aide aussi l’établissement à assurer la continuité du service public d’enseignement, grâce aux outils numériques qu’il développe. Mais la communication par internet présente aussi des risques. Elle peut être brouillée, altérant ainsi les effets attendus, comme il a été constaté lors de la campagne de communication sur la vaccination. Elle peut aussi être victime d’attaques, parce que toute communication empruntant la voie internet est menacée, posant ainsi le problème de la sécurité des systèmes d’information. En cas de crise, les établissements seraient confrontés, d’une part à la nécessité de maîtriser les techniques de communication, d’autre part aux besoins liés à l’utilisation des outils numériques ; mais aussi aux risques pesant sur les systèmes d’information. Prévoir, dans la mesure du possible, la survenance de problèmes qui pourraient se poser en cas de crise, est nécessaire. En se préparant à l’avance à la gestion de crise, grâce notamment à la mutualisation des moyens et à une prise de conscience des risques, les universités pourraient mieux maîtriser ces difficultés. / Internet communication is now generally acknowledged as indispensable in communication strategies, and particularly in crisis communication. A survey of French universities makes it possible to analyze, through the example of the H1N1 flu pandemic, how the Internet became a major tool for the communication of universities in a crisis. At the internal level, Internet communication appears as a reliable resource, allowing the diffusion of informative and preventive messages. It also helps the institution to ensure the continuity of public educational services through digital tools. But Internet communication also involves risks. Messages can be blurred, thus altering their expected effects, as became clear during the communication campaign on immunization. Messages can also be the victim of attacks, because any communication via the Internet channel may be threatened in various ways. This poses the problem of the security of information systems. In sum, institutions in crisis must face not only the necessity to master digital techniques of communication, and to comply with the requirements inherent in the use of digital tools, but also to manage risks that are specific to digital information systems. Anticipating, so far as is possible, the occurrence of problems that might arise in a crisis is essential. By preparing to cope with crises, including through the pooling of resources and the awareness of risks, universities may better control these difficulties. The study of this crisis reveals not only the pertinent issues, but also how such preparation might be most effectively undertaken.

Submitted by Celso Magalhaes (celsomagalhaes@ufrrj.br) on 2017-05-19T12:03:19Z No. of bitstreams: 1 2016 - Pablo Amauri Carvalho de Ara?jo e Souza.pdf: 3429164 bytes, checksum: c1da6eb8bb41fc96de0b7e5ca2a9570f (MD5) / Made available in DSpace on 2017-05-19T12:03:19Z (GMT). No. of bitstreams: 1 2016 - Pablo Amauri Carvalho de Ara?jo e Souza.pdf: 3429164 bytes, checksum: c1da6eb8bb41fc96de0b7e5ca2a9570f (MD5) Previous issue date: 2016-06-13 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / This work highlights the importance of well administrated vaccination as prophylactic activity, making it a key element of mathematical modeling about the spreading of an infection by Influenza H1N1 virus in a human population. The model counts with Optimal Control theory to achieve a vaccination strategy that balance infection?s prevention and your own cost in a hypothetical population exposed to a virus. The numerical solutions of ordinary differential equations systems generated by model is given via Finite Difference Method, that reveals the populational dynamics during the time while the vaccine is distributed, in various different situations of virus exposition and vaccination cost. / Este trabalho ressalta a import?ncia da vacina??o bem administrada como atividade profil?tica, tornando-a elemento chave da modelagem matem?tica do espalhamento da infec??o pelo v?rus Influenza H1N1 em uma popula??o humana. O modelo conta com a teoria de Controle ?timo para alcan?ar uma estrat?gia de vacina??o, que equilibre a preven??o da infec??o e seu pr?prio custo em uma popula??o hipot?tica exposta ao v?rus. As solu??es num?ricas dos sistemas de equa??es diferenciais ordin?rias gerados pelo modelo ficam a cargo do M?todo das Diferen?as Finitas, revelando a din?mica populacional no per?odo de tempo em que a vacina ? distribu?da, em distintas situa??es de exposi??o ao v?rus e custo da vacina??o.

Introdução: A Imunodeficiência Comum Variável (ICV) faz parte de um grupo de imunodeficiências primárias na qual os pacientes apresentam defeitos na maturação e diferenciação dos linfócitos B (LB), resultando em distúrbios funcionais além de alterações na distribuição de seus subtipos. Consequentemente, estes pacientes apresentam hipogamaglobulinemia, susceptibilidade a infecções e ausência de produção de anticorpos a antígenos específicos. Na tentativa de reduzir os episódios de infecções recorrentes, alguns trabalhos têm recomendado a vacinação com patógenos mortos ou subunidades e em trabalho anterior demonstramos a eficácia clínica da vacinação de pacientes com ICV, porém, a experiência com a administração de vacinas em imunocomprometidos é limitada. Objetivos: Avaliar a cinética da distribuição das subpopulações de linfócitos B antes e após a vacinação com antígenos proteicos e polissacarídicos em pacientes com ICV acompanhados no Ambulatório de Imunodeficiências Primárias do Hospital das Clínicas, FMUSP, além da produção de anticorpos específicos aos antígenos vacinais. Pacientes e Métodos: Um grupo de 35 pacientes com ICV e 16 controles foram vacinados contra Influenza, H1N1 e S. pneumoniae. Após as coletas nos tempos pré e pós 1, 3 e 6 meses foram realizados a separação de PBMC e cultura de linfócitos com lisado viral e hemaglutinina de Influenza, além da citometria de fluxo para identificação das subpopulações de LB naive, zona marginal (MZB), memória com troca de isotipo (SMB) e plasmoblastos (PBL). Foram dosados os anticorpos específicos e no grupo dos pacientes foi aplicado um score de sintomas antes e após a imunização. Resultados: Apesar da redução significativa na pontuação do score de sintomas, a maioria dos pacientes não produziu anticorpos específicos para Influenza, H1N1 e S. pneumoniae. A análise da cinética das subpopulações de LB revelou que em indivíduos saudáveis, a resposta contra Influenza apresentou duração de 6 meses, observada por meio da redução da subpopulação naive e aumento gradual da frequência de SMB a partir do primeiro mês. Observamos também redução da população de memória por volta do 3º mês, com aumento da população de PBL que permaneceu elevada até o 6º mês. Por outro lado, a despeito de os pacientes apresentarem aumento de SMB no primeiro mês após a vacinação, sua frequência foi inferior ao observado nos controles, decaindo ao terceiro mês. A população de PBL apresentou aumento precoce no primeiro mês após a vacinação, também muito menor do que observado nos controles, não sendo mantido no terceiro mês. Ainda, observamos uma correlação entre o aumento da expressão destas duas subpopulações no primeiro mês. Apenas a população de MZB apresentou aumento significativo no terceiro mês nos pacientes quando comparados aos controles. Ao dividirmos os pacientes de acordo com a expressão de SMB e PBL após 1 mês da administração das vacinas, observamos que os pacientes que apresentaram aumento na expressão de células B de memória foram os que exibiram uma melhora clínica mais expressiva, soroconverteram e desenvolveram soroproteção para H1N1.Conclusões: Apesar de não apresentarem eficaz diferenciação em células de memória e efetoras, resultando na resposta precoce e de curta duração, observamos que os pacientes foram capazes de reconhecer e responder às vacinas. Além disso, a elevada expressão de MZB no terceiro mês após a vacinação pode sugerir a atuação desta subpopulação na apresentação para os LT. Estes achados reforçam a necessidade de uma melhor compreensão da ativação do sistema imune em pacientes com ICV, para uma adequada subdivisão de acordo com o perfil de resposta após a vacinação / Introduction: Common Variable Immunodeficiency (CVID) is a primary antibody deficiency characterized by defects in B lymphocyte maturation, resulting in disturbed differentiation, distribution and functional variations on its subtypes. As a result , CVID patients have hypogammaglobulinemia and poor antibody response to specific antigens with increased susceptibility to infections. In an effort to minimize the recurrent episodes of infections, some studies have recommended immunization with inactivated pathogens or subunits and in a former study we have shown the clinical improvement determined by immunization in CVID patients, but the experience with vaccines\' administration to immunodeficient patients is limited. Objectives: To evaluate the changes in distribution of B cell subtypes before and after vaccination of CVID patients followed at the Division of Clinical Immunology and Allergy of University of São Paulo Medical School with protein and polysaccharide antigens, as well as specific antibody production . Methods: A group of 35 CVID patients and 16 controls were vaccinated against Influenza, H1N1 and S. pneumoniae vaccines. Blood samples were collected before and 1, 3 and 6 months post vaccination. PBMCs were stimulated with Influenza viral lysate and hemagglutinin peptide. Flow cytometry was performed to identify naïve B cells, marginal zone (MZB), switched memory B cells (SMB) and plasmablasts (PBL). Specific antibody production was measured and a symptoms score was applied for clinical evaluation before and after immunization. Results: In spite of the significant reduction in symptoms score after vaccination, most patients didn\'t produce specific antibodies to Influenza, H1N1 and S. pneumoniae. The analyzes of B cell subtypes changes in healthy individuals upon in vitro Influenza stimulation showed that the response endured up to 6 months post immunization. We observed a reduction in naïve B cell frequency while gradual increase in SMB frequency occurred already at 1 month after vaccination. Moreover, as the memory cell population declined, PBL population increased at the third month post vaccination until the sixth month. Although patients had an increase of SMB on the first month after vaccination, it was lower than that observed in controls, decreasing by the third month post vaccination. Plasmablast frequency had an early increase on the first month, also much lower than the observed in controls decreasing by the third month. In addition, we observed a correlation between the increased expression of SMB and PBL on the first month post vaccination. In patients, only MZB subtype presented a significant increase on the third month when compared to controls. We divided the patients according SMB and PBL expression after 1 month post vaccination and we observed that patients who were able to produce memory B cells showed a better clinical improvement, developed H1N1 seroconversion and seroprotection. Conclusion: Despite the defect on differentiation into memory and effector B cells resulting in early response with lowduration, we observed that patients were able to recognize and respond to vaccines. In addition, the over expression of MZB on the third month after vaccination may suggest the role of this subpopulation as an antigen presenting cell for T cells. These findings reinforce the need of a better understanding of immune system activation and response in CVID patients to propose a division according to vaccine (antigen) responders and non responders

This thesis describes how transmission of the 2009 A/H1N1 influenza pandemic in the United States varied geographically, with emphasis on population distribution and age structure. This is made possible by the availability of medical claims records maintained in the private sector that capture the weekly incidence of influenza-like illness in 834 US cities. First, a probabilistic method is developed to infer each city's outbreak onset time. This reveals a clear wave-like pattern of transmission originating in the south-eastern US. Then, a mechanistic mathematical model is constructed to describe the between-city transmission of the epidemic. A model selection procedure reveals that transmission to a city is modulated by its population size, surrounding population density, and possibly by students mixing in schools. Geographic variation in transmissibility is explored further by nesting a latent Gaussian process within the mechanistic transmission model, revealing a possible region of elevated transmissibility in the south-eastern US. Then, using the mechanistic model and a probabilistic back-tracing procedure, the geographic introduction sites (the `transmission hubs') of the outbreak are identified. The transmission hubs of the 2009 pandemic were generally mid-sized cities, contrasting with the conventional perspective that major outbreaks should start in large population centres with high international connectivity. Transmission is traced forward from these hubs to identify `basins of infection', or regions where outbreaks can be attributed with high probability to a particular hub. The city-level influenza data is also separated into 12 age categories. Techniques adapted from signal processing reveal that school-aged children may have been key drivers of the epidemic. Finally, to provide a point of comparison, the procedures described above are applied to the 2003-04 and 2007-08 seasonal influenza outbreaks. Since the 2007-08 outbreak featured three antigenically distinct strains of influenza, it is possible to identify which antigenic strains may have been responsible for infecting each transmission hub. These strains are identified using a probabilistic model that is joined with the geographic transmission model, providing a link between population dynamics and molecular surveillance.

Introdução: A Imunodeficiência Comum Variável (ICV) faz parte de um grupo de imunodeficiências primárias na qual os pacientes apresentam defeitos na maturação e diferenciação dos linfócitos B (LB), resultando em distúrbios funcionais além de alterações na distribuição de seus subtipos. Consequentemente, estes pacientes apresentam hipogamaglobulinemia, susceptibilidade a infecções e ausência de produção de anticorpos a antígenos específicos. Na tentativa de reduzir os episódios de infecções recorrentes, alguns trabalhos têm recomendado a vacinação com patógenos mortos ou subunidades e em trabalho anterior demonstramos a eficácia clínica da vacinação de pacientes com ICV, porém, a experiência com a administração de vacinas em imunocomprometidos é limitada. Objetivos: Avaliar a cinética da distribuição das subpopulações de linfócitos B antes e após a vacinação com antígenos proteicos e polissacarídicos em pacientes com ICV acompanhados no Ambulatório de Imunodeficiências Primárias do Hospital das Clínicas, FMUSP, além da produção de anticorpos específicos aos antígenos vacinais. Pacientes e Métodos: Um grupo de 35 pacientes com ICV e 16 controles foram vacinados contra Influenza, H1N1 e S. pneumoniae. Após as coletas nos tempos pré e pós 1, 3 e 6 meses foram realizados a separação de PBMC e cultura de linfócitos com lisado viral e hemaglutinina de Influenza, além da citometria de fluxo para identificação das subpopulações de LB naive, zona marginal (MZB), memória com troca de isotipo (SMB) e plasmoblastos (PBL). Foram dosados os anticorpos específicos e no grupo dos pacientes foi aplicado um score de sintomas antes e após a imunização. Resultados: Apesar da redução significativa na pontuação do score de sintomas, a maioria dos pacientes não produziu anticorpos específicos para Influenza, H1N1 e S. pneumoniae. A análise da cinética das subpopulações de LB revelou que em indivíduos saudáveis, a resposta contra Influenza apresentou duração de 6 meses, observada por meio da redução da subpopulação naive e aumento gradual da frequência de SMB a partir do primeiro mês. Observamos também redução da população de memória por volta do 3º mês, com aumento da população de PBL que permaneceu elevada até o 6º mês. Por outro lado, a despeito de os pacientes apresentarem aumento de SMB no primeiro mês após a vacinação, sua frequência foi inferior ao observado nos controles, decaindo ao terceiro mês. A população de PBL apresentou aumento precoce no primeiro mês após a vacinação, também muito menor do que observado nos controles, não sendo mantido no terceiro mês. Ainda, observamos uma correlação entre o aumento da expressão destas duas subpopulações no primeiro mês. Apenas a população de MZB apresentou aumento significativo no terceiro mês nos pacientes quando comparados aos controles. Ao dividirmos os pacientes de acordo com a expressão de SMB e PBL após 1 mês da administração das vacinas, observamos que os pacientes que apresentaram aumento na expressão de células B de memória foram os que exibiram uma melhora clínica mais expressiva, soroconverteram e desenvolveram soroproteção para H1N1.Conclusões: Apesar de não apresentarem eficaz diferenciação em células de memória e efetoras, resultando na resposta precoce e de curta duração, observamos que os pacientes foram capazes de reconhecer e responder às vacinas. Além disso, a elevada expressão de MZB no terceiro mês após a vacinação pode sugerir a atuação desta subpopulação na apresentação para os LT. Estes achados reforçam a necessidade de uma melhor compreensão da ativação do sistema imune em pacientes com ICV, para uma adequada subdivisão de acordo com o perfil de resposta após a vacinação / Introduction: Common Variable Immunodeficiency (CVID) is a primary antibody deficiency characterized by defects in B lymphocyte maturation, resulting in disturbed differentiation, distribution and functional variations on its subtypes. As a result , CVID patients have hypogammaglobulinemia and poor antibody response to specific antigens with increased susceptibility to infections. In an effort to minimize the recurrent episodes of infections, some studies have recommended immunization with inactivated pathogens or subunits and in a former study we have shown the clinical improvement determined by immunization in CVID patients, but the experience with vaccines\' administration to immunodeficient patients is limited. Objectives: To evaluate the changes in distribution of B cell subtypes before and after vaccination of CVID patients followed at the Division of Clinical Immunology and Allergy of University of São Paulo Medical School with protein and polysaccharide antigens, as well as specific antibody production . Methods: A group of 35 CVID patients and 16 controls were vaccinated against Influenza, H1N1 and S. pneumoniae vaccines. Blood samples were collected before and 1, 3 and 6 months post vaccination. PBMCs were stimulated with Influenza viral lysate and hemagglutinin peptide. Flow cytometry was performed to identify naïve B cells, marginal zone (MZB), switched memory B cells (SMB) and plasmablasts (PBL). Specific antibody production was measured and a symptoms score was applied for clinical evaluation before and after immunization. Results: In spite of the significant reduction in symptoms score after vaccination, most patients didn\'t produce specific antibodies to Influenza, H1N1 and S. pneumoniae. The analyzes of B cell subtypes changes in healthy individuals upon in vitro Influenza stimulation showed that the response endured up to 6 months post immunization. We observed a reduction in naïve B cell frequency while gradual increase in SMB frequency occurred already at 1 month after vaccination. Moreover, as the memory cell population declined, PBL population increased at the third month post vaccination until the sixth month. Although patients had an increase of SMB on the first month after vaccination, it was lower than that observed in controls, decreasing by the third month post vaccination. Plasmablast frequency had an early increase on the first month, also much lower than the observed in controls decreasing by the third month. In addition, we observed a correlation between the increased expression of SMB and PBL on the first month post vaccination. In patients, only MZB subtype presented a significant increase on the third month when compared to controls. We divided the patients according SMB and PBL expression after 1 month post vaccination and we observed that patients who were able to produce memory B cells showed a better clinical improvement, developed H1N1 seroconversion and seroprotection. Conclusion: Despite the defect on differentiation into memory and effector B cells resulting in early response with lowduration, we observed that patients were able to recognize and respond to vaccines. In addition, the over expression of MZB on the third month after vaccination may suggest the role of this subpopulation as an antigen presenting cell for T cells. These findings reinforce the need of a better understanding of immune system activation and response in CVID patients to propose a division according to vaccine (antigen) responders and non responders

Cytotoxic T-lymphocytes (CTLs) are important components of the adaptive immune system and function by scanning the intracellular environment so as to detect and de-stroy infected cells. CTL responses play a major role in controlling virus-infected cells such as in HIV or influenza and cells infected with intracellular bacteria such as in tuberculosis. To do so they require the antigens to be presented to them, which is fulfilled by the major histocompatibility complex (MHC), commonly known as human leukocyte antigen or HLA molecules in humans. Recognition of antigenic peptides to Class-1 HLA molecules is a prerequisite for triggering CTL immune responses. Individuals differ significantly in their ability to respond to an infection. Among the factors that govern the outcome of an infection, HLA polymorphism in the host is one of the most important. Despite a large body of work on HLA molecules, much remains to be understood about the relationship between HLA diversity and disease susceptibility. High complexity arises due to HLA allele polymorphism, extensive antigen cross-presentability, and host-pathogen heterogeneity. A given allele can recognize a number of different peptides from various pathogens and a given peptide can also bind to a number of different individuals. Thus, given the plurality in peptide-allele pairs and the large number of alleles, understanding the differences in recognition profiles and the implications that follow for disease susceptibilities require mathematical modelling and computational analysis. The main objectives of the thesis were to understand heterogeneity in antigen presentation by HLA molecules at different scales and how that heterogeneity translates to variations in disease susceptibilities and finally the disease dynamics in different populations. Towards this goal, first the variations in HLA alleles need to be characterized systematically and their recognition properties understood. A structure-based classification of all known HLA class-1 alleles was therefore attempted. In the process, it was also of interest to see if understanding of sub-structures at the binding grooves of HLA molecules could help in high confidence prediction of epitopes for different alleles. Next, the goal was to understand how HLA heterogeneity affect disease susceptibilities and disease spread in populations. This was studied at two different levels. Firstly, modelling the HLA genotypes and CTL responses in different populations and assessing how they recognized epitopes from a given virus. The second approach involved modelling the disease dynamics given the predicted susceptibilities in different populations. Influenza H1N1 infection was used as a case study. The specific objectives addressed are: (a) To develop a classification scheme for all known HLA class-1 alleles that can explain epitope recognition profiles and further to dissect the physic-chemical features responsible for differences in peptide specificities, (b) A statistical model has been derived from a large dataset of HLA-peptide complexes. The derived model was used to identify the interdependencies of residues at different peptide and thereby, rationalize the HLA class-I allele binding specificity at a greater detail, (c) To understand the effect of HLA heterogeneity on CTL mediated disease response. A model of HLA genotypes for different populations was required for this, which was constructed and used for estimating disease response to H1N1 via the prediction of epi-topes and (d) To model disease dynamics in different populations with the knowledge of the CTL response-grouping and to evaluate the effect of heterogeneity on different vaccination strategies. Each of the four objectives listed above are described subsequently in chapters 2 to 5, followed by Chapter 6 which summarises the findings from the thesis and presents future directions. Chapter 1 presents an introduction to the importance of the function of HLA molecules, describes structural bioinformatics as a discipline and the methods that are available for it. The chapter also describes different mathematical modelling strategies available to study host immune responses. Chapter 2 describes a novel method for structure-based hierarchical classification of HLA alleles. Presently, more than 2000 HLA class-I alleles are reported, and they vary only across peptide-binding grooves. The polymorphism they exhibit, enables them to bind to a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern due to multiplicity in their associations. Thus, a powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. The study reports a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification with 7 supergroups was derived, each further categorized to yield a total of 72 groups. An independent clustering scheme based only on the similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explains the basis for the observed clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues that contribute to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants. The results are presented in an interactive web- server http://proline.iisc.ernet.in/hlaclassify. In Chapter 3, the knowledge of structural features responsible for generating peptide recognition specificities are first analysed and then utilized for predicting T-cell epi-topes for any class-1 HLA allele. Since identification of epitopes is critical and central to many of the questions in immunology, a study of several HLA-peptide complexes is carried out at the structural level and factors are identified that discriminate good binder peptides from those that do not. T-cell epitopes serve as molecular keys to initiate adaptive immune responses. Identification of T-cell epitopes is also a key step in rational vaccine design. Most available methods are driven by informatics, critically dependent on experimentally obtained training data. Analysis of the training set from IEDB for several alleles indicate that sampling of the peptide space is extremely sparse covering only a tiny fraction of all possible nonamer space, and also heavily skewed, thus restricting the range of epitope prediction. A new epitope prediction method is therefore developed. The method has four distinct modules, (a) structural modelling, estimating statistical pair-potentials and constraint derivation, (b) implicit modelling and interaction profiling, (c) binding affinity prediction through feature representation and (d) use of graphical models to extract peptide sequence signatures to predict epitopes for HLA class I alleles . HLaffy is a novel and efficient epitope prediction method that predicts epitopes for any HLA Class-1 allele, by estimating binding strengths of peptide-HLA complexes which is achieved through learning pair-potentials important for peptide binding. It stands on the strength of mechanistic understanding of HLA-peptide recognition and provides an estimate of the total ligand space for each allele. The method is made accessible through a webserver http://proline.biochem.iisc.ernet.in/HLaffy. In chapter 4, the effect of genetic heterogeneity on disease susceptibilities are investigated. Individuals differ significantly in their ability to respond to an infection. Among the factors that govern the outcome of an infection, HLA polymorphism in the host is one of the most important. Despite a large body of work on HLA molecules, much remains to be understood about how host HLA diversity affects disease susceptibilities. High complexity due to polymorphism, extensive cross-presentability among HLA alleles, host and pathogen heterogeneity, demands for an investigation through computational approaches. Host heterogeneity in a population is modelled through a molecular systems approach starting with mining ‘big data’ from literature. The in-sights derived through this is used to investigate the effect of heterogeneity in a population in terms of the impact it makes on recognizing a pathogen. A case study of influenza virus H1N1 infection is presented. For this, a comprehensive CTL immunome is defined by taking a consensus prediction by three distinct methods. Next, HLA genotypes are constructed for different populations using a probabilistic method. Epidemic incidences in general are observed to correlate with poor CTL response in populations. From this study, it is seen that large populations can be classified into a small number of groups called response-types, specific to a given viral strain. Individuals of a response type are expected to exhibit similar CTL responses. Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity. Overall, the study presents a conceptual advance towards understanding how genetic heterogeneity influences disease susceptibility in individuals and in populations. Lists of top-ranking epitopes and proteins are also derived, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which pro- vide ready short-lists for rational vaccine design (flutope). Next, in Chapter 5, the effect of genetic heterogeneity on disease dynamics has been investigated. A mathematical framework has been developed to incorporate the heterogeneity information in the form of response-types described in the previous chap-ter. The spread of a disease in a population is a complex process, controlled by various factors, ranging from molecular level recognition events to socio-economic causes. The ‘response-typing’ described in the previous chapter allows identification of distinct groups of individuals, each with a different extent of susceptibility to a given strain of the virus. 3 different approaches are used for modelling: (i) an SIR model where different response types are considered as partitions of each S, I and R compartment. Initially SIR models are developed, such that the S compartment is sub-divided into further groups based on the ‘response-types’ obtained in the previous chapter. This analysis shows an effect in infection sweep time, i.e., how long the infection stays in the population. A stochastic model incorporates the environmental noise due to random variation in population influx, due to birth, death or migration. The system is observed to show higher stability in the presence of genetic heterogeneity. As the contagion spreads only through direct host to host contact. The topology of the contact network, plays major role in deciding the extent of disease dynamics. An agent based computational framework has been developed for modelling disease spread by considering spatial distribution of the agents, their movement patterns and resulting contact probabilities. The agent-based model (ABM) incorporates the temporal patterns of contacts. The ABM is based on a city block model and captures movement of individuals parametrically. A new concept of system ‘characteristic time’ has been introduced in context of a time-evolving network. ‘Characteristic time’ is the minimum time required to ensure, every individual is connected to all other individuals, in the time aggregated contact network. For any given temporal system, disease time must exceed ‘characteristic time’ in order to spread throughout the population. Shorter ‘characteristic time’ of the system is suggestive of faster spread of the disease. A disease spread network is constructed which shows how the disease spreads from one infected individual to others in the city, given the contact rules and their relative susceptibilities to that viral strain. A high degree of population heterogeneity is seen to results in longer disease residence time. Susceptible individuals preferentially get infected first thereby exposing more susceptible individuals to the disease. Vaccination strategies are derived from the model, which indicates that vaccinating only 20% of the agents, who are hub nodes or highly central nodes and who also have a high degree to susceptible agents, lead to high levels of herd immunity and can confer protection to the rest of the population. Overall, the thesis has provided biologically meaningful classification of all known HLA class-1 alleles and has unravelled the physico-chemical basis for their peptide recognition specificities. The thesis also presents a new algorithm for estimating pep-tide binding affinities and consequently predicting epitopes for all alleles. Finally the thesis presents a conceptual advance in relating HLA diversity to disease susceptibilities and explains how different populations can respond differently to a given infection. A case study with the influenza H1N1 virus identified populations who are most susceptible and those who are least susceptible, in the process identifying important epitopes and responder alleles, providing important pointers for vaccine design. The influence of heterogeneity and response-typing on disease dynamics is also presented for influenza H1N1 infection, which has led to the rational identification of effective vaccination strategies. The methods and concepts developed here are fairly generic and can be adapted easily for studying other infectious diseases as well. Three new web-resources, a) HLAclassify, b) HLaffy and c) Flutope have been developed, which host pre-computed results as well as allow interactive querying to an user to perform analysis with a specific allele, peptide or a pathogenic genome sequence.