Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection

HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments' influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies

An integrated modelling approach for R5-X4 mutation and HAART therapy assessment

We have modelled the within-patient evolutionary process during HIV infection using different methodologies. New viral strains arise during the course of HIV infection. These multiple strains of the virus are able to use different coreceptors, in particular the CCR5 and the CXCR4 (R5 and X4 phenotypes, respectively)influence the progression of the disease to the AIDS phase. We present a model of HIV early infection and CTLs response which describes the dynamics of R5 quasispecies, specifying the R5 to X4 switch and effects of immune response. We illustrate dynamics of HIV multiple strains in the presence of multidrug HAART therapy. The HAART combined with X4 strain blocker drugs might help to reduce infectivity and lead to slower progression of disease. On the methodology side, our model represents a paradigm of integrating formal methods and mathematical models as a general framework to study HIV multiple strains during disease progression, and will inch towards providing help in selecting among vaccines and drug therapies. The results presented here are one of the rare cases of methodological cross comparison (stochastic and deterministic) and a novel implementation of model checking in therapy validation

Stochastic modeling of an HIV/AIDS epidemic with treatment

>Magister Scientiae - MScThe HIV/AIDS epidemic continues to be among the most devastating diseases in human history despite the new scientific advances and serious public health interventions. The greatest burden of HIV/AIDS is still in sub-Saharan Africa, and within this specific region, women are severely affected. Despite an increase in prevention interventions, including such as ARV treatment and pre-exposure prophylaxis (PrEP), behavioural change remains a key role in the transmission of HIV/AIDS. In this thesis, we investigate several related models for the population dynamics of HIV/AIDS epidemic model with treatment. We start off with a four compartmental HIV deterministic model with stages of HIV infection and with inflow of HIV infectives. Thereafter, we impose stochastic perturbations on the underlying HIV/AIDS deterministic model without inflow of infectives. For this version of HIV stochastic model, we prove global existence and positivity of solutions to the HIV/AIDS-perturbed model. Some useful properties such as boundedness property, stochastic permanence property and asymptotic stability have been derived

Stochastic modelling of cellular populations: Effects of latency and feedbackl

[cat]L'objectiu principal d'aquesta tesi doctoral és l'estudi de l'efecte de les fluctuacions en poblacions acoblades en sistemes biològics, on cèl·lules en estat latent juguen un paper important. Intentant trobar el significat biològic de la dinàmica dels sistemes. Els punts específics que volem abordar i la organització de la tesi estan explicats a continuació. En el Capítol 2, estudiem el comportament de les poblacions de cèl·lules amb estructura jeràrquica des del punt de vista de les propietats d'estabilitat, En particular: - 1. Divisió simètrica contra asimètrica en el compartiment de les cèl·lules mare. Estudiem la robustesa de les poblacions amb estructura jeràrquica, depenent de si les cèl·lules mare es divideixen simètricament, asimètricament o de les dues maneres. Estudiem com la divisió simètrica afecta a l'estabilitat de la població, ja que això té una gran importància en la progressió del càncer. - 2. La competició entre dues poblacions amb diferents tipus de divisió de les cèl·lules mare. Això és crucial per trobar estratègies òptimes que maximitzin la robustesa (supervivència a llarg termini, resistència a invasions i habilitat per invadir) de poblacions amb estructura jeràrquica. - 3. La influència de paràmetres com son la duplicació i el ritme de mort de cèl·lules mare, el temps de vida mitjà de les cèl·lules completament diferenciades, la longitud de les cadenes de diferenciació i les fluctuacions al compartiment de les cèl·lules mare en la robustesa i arquitectura òptima de les cascades de diferenciació. En el Capítol 3 presentem un model homogeni de combinació de HAART amb teràpies d'activació de les cèl·lules latents del VIH-1 a la sang. Estem interessats en: - 1. L'efecte del ritme d'activació de les cèl·lules latents en el temps mitjà de vida de la infecció. En particular analitzem si les teràpies basades en incrementar aquest ritme són capaces de suprimir la infecció en un temps raonable. - 2. La importància de l'eficiència de les teràpies antiretrovirals, incloent els casos límit en que l'eficàcia és del 100%, en la quantitat de càrrega viral. - 3. La formulació d'una teoria asimptòtica basada en l'aproximació semi-clàssica amb aproximacions quasi estacionàries per descriure la dinàmica del procés. La precisió d'aquest mètode asimptòtic és comparat amb simulacions multi-scale proposades pel Cao et al. En el Capítol 4, estenem el model proposat pel Rong i el Perelson a un model no homogeni de la dinàmica del VIH-1 en el corrent sanguini, considerant que les cèl·lules i els virus no estan distribuïts de manera uniforme en la sang. Els punts específics que volem estudiar són: - 1. El mecanisme que fa que apareguin els episodis de virèmia per sobre els límits de detecció, coneguts com viral blips. En particular volem investigar si són producte de fluctuacions estocàstiques degudes a la inhomogenietat o un altre mecanisme ha de ser considerat. - 2. Si l'aparició dels viral blips està afectada pels procediments duts a terme en el laboratori, com el temps d'espera entre les extraccions i les observacions. - 3. Si la probabilitat, l'amplitud i la freqüència dels viral blips es veu afectada pels diferents possibles tipus de producció viral, és a dir, continua vs burst. En el Capítol 5 presentem i discutim els resultats obtinguts, i comparem, quan és possible, amb altres models o amb resultats experimentals, i discutim el treball que deixem pel futur. Els detalls relatius a qüestions metodològiques, això com una introducció a la modelització estocàstica fent servir equacions mestres es donen en els apèndixs. Per a aquells que no estan familiaritzats amb els models basats en equacions mestres, l'autor recomana llegir primer l'apèndix A que proporciona la base matemàtica per entendre el capítol 2. Els Apèndixs B, C i D juntament amb l'Apèndix A donen la base matemàtica necessària per seguir el capítol 3 i el capítol 4

항레트로바이러스 감염 역학에 관한 모델링연구.

학위논문 (박사)-- 서울대학교 대학원 : 자연과학대학 협동과정 계산과학전공, 2018. 2. 신동우.A focus of this thesis is to develop a mathematical modeling approach to analyze the clinical data of Human immunodeficiency virus(HIV) acute infection. From the several studies, a remarkable stability of the HIV latent reservoir is detected despite the long-term treatment and advances in anti–retroviral therapy, and it has been recognized as a major barrier to HIV cure. We analyze several nonlinear mathematical models including the one that contains latent reservoir effect which provides consecutive viral replication and derive reproductive number (R0) which is a key index on HIV dynamics. For a quantitative analysis, we estimated parameters best describe time-series viral load measurements, obtained from published clinical study. We implement an efficient estimation method for the relevant parameters and numerical algorithm to solve the HIV infection dynamics. By using a nonlinear least square method for parameter estimation, analysis on the sensitivity parameters are performed for each model. In addition, we can obtain the total contribution of the reservoir processes to the productively infected T lymphocyte cells is also examined. We also propose a new model for HIV infection dynamics. There has been some researches that some influencing fractions on the dynamics of blood flow have been associated with the severity of HIV infection. In order to explain the rheological behavior of HIV infection in T lymphocyte populations we attempt to modify Latent cell model with fractional order differentiation of order α ∈ (0, 1]. The hemorheological parameters and fractional-order derivative in HIV system embody essential features of influencing fractions on the dynamics of blood flow associated with the severity of HIV infection. We show that the modified model has non-negative, bounded solutions and stable equilibrium points. Optimal fractional order and kinetic parameters are estimated by using the nonlinear weighted least-square method, the Levenberg-Marquardt algorithm, and Adams-type predictor-corrector method is employed for the numerical solution. The numerical results confirm that a value of fractional order (α) representing the rheological behavior in plasma is significantly related with a density of lymphocyte population.Chapter 1 Introduction 1 1.1 Infection mechanism of HIV and Antiretroviral treatment 2 1.2 Latent reservoir and drug-resistant mutant in HIV infection 6 1.3 Modeling HIV infection dynamics in lymphocyte 9 1.4 Thesis overview 12 Chapter 2 Mathematical models for HIV infection dynamics 14 2.1 Models and their analysis 14 2.1.1 Three-component model 16 2.1.2 Chronical infection model 39 2.1.3 Latent infection model 46 2.2 Parameter estimation 52 2.2.1 Description of measurement data and their clinical result 53 2.2.2 An algorithm for parameter estimation 56 2.2.3 Initial guess for initial state density and model parameters 60 2.2.4 Analysis of parameter sensitivity 61 2.3 Numerical result 64 2.3.1 Sensitivity equations 64 2.3.2 Numerical simulation 66 2.4 Conclusion 70 Chapter 3 A fractional-order model for HIV infection 77 3.1 The fractional calculus 78 3.2 Motivation 80 3.3 Model derivation 83 3.4 Numerical methods 93 3.4.1 The fractional Adams method 94 3.4.2 Sensitivity equations 99 3.4.3 Initial guess for paramters and the fractional order 102 3.5 Numerical results: model fits and sample predictions 102 3.6 Conclusion 107Docto

Bioinformatics Techniques for Studying Drug Resistance In HIV and Staphylococcus Aureus

The worldwide HIV/AIDS pandemic has been partly controlled and treated by antivirals targeting HIV protease, integrase and reverse transcriptase, however, drug resistance has become a serious problem. HIV-1 drug resistance to protease inhibitors evolves by mutations in the PR gene. The resistance mutations can alter protease catalytic activity, inhibitor binding, and stability. Different machine learning algorithms (restricted boltzmann machines, clustering, etc.) have been shown to be effective machine learning tools for classification of genomic and resistance data. Application of restricted boltzmann machine produced highly accurate and robust classification of HIV protease resistance. They can also be used to compare resistance profiles of different protease inhibitors. HIV drug resistance has also been studied by enzyme kinetics and X-ray crystallography. Triple mutant HIV-1 protease with resistance mutations V32I, I47V and V82I has been used as a model for the active site of HIV-2 protease. The effects of four investigational antiviral inhibitors was measured for Triple mutant. The tested compounds had significantly worse inhibition of triple mutant with Ki values of 17-40 nM compared to 2-10 pM for wild type protease. The crystal structure of triple mutant in complex with GRL01111 was solved and showed few changes in protease interactions with inhibitor. These new inhibitors are not expected to be effective for HIV-2 protease or HIV-1 protease with changes V32I, I47V and V82I. Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen that causes hospital and community-acquired infections. Antibiotic resistance occurs because of newly acquired low-affinity penicillin-binding protein (PBP2a). Transcriptome analysis was performed to determine how MuM (mutated PBP2 gene) responds to spermine and how Mu50 (wild type) responds to spermine and spermine–β-lactam synergy. Exogenous spermine and oxacillin were found to alter some significant gene expression patterns with major biochemical pathways (iron, sigB regulon) in MRSA with mutant PBP2 protein

Hybrid epidemic spreading - from Internet worms to HIV infection

Epidemic phenomena are ubiquitous, ranging from infectious diseases, computer viruses, to information dissemination. Epidemics have traditionally been studied as a single spreading process, either in a fully mixed population or on a network. Many epidemics, however, are hybrid, employing more than one spreading mechanism. For example, the Internet worm Conficker spreads locally targeting neighbouring computers in local networks as well as globally by randomly probing any computer on the Internet. This thesis aims to investigate fundamental questions, such as whether a mix of spreading mechanisms gives hybrid epidemics any advantage, and what are the implications for promoting or mitigating such epidemics. We firstly propose a general and simple framework to model hybrid epidemics. Based on theoretical analysis and numerical simulations, we show that properties of hybrid epidemics are critically determined by a hybrid tradeoff, which defines the proportion of resource allocated to local and global spreading mechanisms. We then study two distinct examples of hybrid epidemics: the Internet worm Conficker and the Human Immunodeficiency Virus (HIV) infection within the human body. Using Internet measurement data, we reveal how Conficker combines ineffective spreading mechanisms to produce a serious outbreak on the Internet. We propose a mathematical model that can accurately recapitulate the entire HIV infection course as observed in clinical trials. Our study provides novel insights into the two parallel infection channels of HIV, i.e. cell-free spreading and cell-to-cell spreading, and their joint effect on HIV infection and treatment. In summary, this thesis has advanced our understanding of hybrid epidemics. It has provided mathematical frameworks for future analysis. It has demonstrated, with two successful case studies, that such research can have a significant impact on important issues such as cyberspace security and human health