Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage

HIV-1 cell entry commonly uses, in addition to CD4, one of the chemokine receptors CCR5 or CXCR4 as coreceptor. Knowledge of coreceptor usage is critical for monitoring disease progression as well as for supporting therapy with the novel drug class of coreceptor antagonists. Predictive methods for inferring coreceptor usage based on the third hypervariable (V3) loop region of the viral gene coding for the envelope protein gp120 can provide us with these monitoring facilities while avoiding expensive phenotypic tests. All simple heuristics (such as the 11/25 rule) as well as statistical learning methods proposed to date predict coreceptor usage based on sequence features of the V3 loop exclusively. Here, we show, based on a recently resolved structure of gp120 with an untruncated V3 loop, that using structural information on the V3 loop in combination with sequence features of V3 variants improves prediction of coreceptor usage. In particular, we propose a distance-based descriptor of the spatial arrangement of physicochemical properties that increases discriminative performance. For a fixed specificity of 0.95, a sensitivity of 0.77 was achieved, improving further to 0.80 when combined with a sequence-based representation using amino acid indicators. This compares favorably with the sensitivities of 0.62 for the traditional 11/25 rule and 0.73 for a prediction based on sequence information as input to a support vector machine and constitutes a statistically significant improvement. A detailed analysis and interpretation of structural features important for classification shows the relevance of several specific hydrogen-bond donor sites and aliphatic side chains to coreceptor specificity towards CCR5 or CXCR4. Furthermore, an analysis of side chain orientation of the specificity-determining residues suggests a major role of one side of the V3 loop in the selection of the coreceptor. The proposed method constitutes the first approach to an improved prediction of coreceptor usage based on an original integration of structural bioinformatics methods with statistical learning

Characterization of Novel HIV Drug Resistance Mutations Using Clustering, Multidimensional Scaling and SVM-Based Feature Ranking

We present a case study on the discovery of clinically relevant domain knowledge in the field of HIV drug resistance. Novel mutations in the HIV genome associated with treatment failure were identified by mining a relational clinical database. Hierarchical cluster analysis suggests that two of these mutations form a novel mutational complex, while all others are involved in known resistance-conferring evolutionary pathways. The clustering is shown to be highly stable in a bootstrap procedure. Multidimensional scaling in mutation space indicates that certain mutations can occur within multiple pathways. Feature ranking based on support vector machines and matched genotype-phenotype pairs comprehensively reproduces current domain knowledge. Moreover, it indicates a prominent role of novel mutations in determining phenotypic resistance and in resensitization effects. These effects may be exploited deliberately to reopen lost treatment options. Together, these findings provide valuable insight into the interpretation of genotypic resistance tests

Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve

We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire instance space. Rather, it depends on the instance at hand. This is motivated by applications in molecular biology, where it is frequently observed that the effect of a particular mutational pattern depends on the genetic background in which it occurs. We assume in our model that the effect of a given pattern of mutations will be very similar only among sequences that are also highly similar to each other. On the other hand, a pattern might have very different effects in different genetic backgrounds

Numerical modeling of unsteady and non-equilibrium sediment transport in rivers

Thesis (Master)--Izmir Institute of Technology, Civil Engineering, Izmir, 2008Includes bibliographical references (leaves: 118-128)Text in English; Abstract: Turkish and Englishxiii, 135 leavesManagement of soil and water resources is one of the most critical environmental issues facing many countries. For that reason, dams, artificial channels and other water structures have been constructed. Management of these structures encounters fundamental problems: one of these problems is sediment transport.Theoretical and numerical modeling of sediment transport has been studied by many researchers. Several empirical formulations of transported suspended load, bed load and total load have been developed for uniform flow conditions. Equilibrium sediment transport under unsteady flow conditions has been just recently numerically studied. The main goal of this study is to develop one dimensional unsteady and nonequilibrium numerical sediment transport models for alluvial channels.Within the scope of this study, first mathematical models based on the kinematic, diffusion and dynamic wave approach are developed under unsteady and equilibrium flow conditions. The transient bed profiles in alluvial channels are simulated for several hypothetical cases involving different particle velocity and particle fall velocity formulations and sediment concentration characteristics. Three bed load formulations are compared under kinematic and diffusion wave models. Kinematic wave model was also successfully tested by laboratory flume data. Secondly, a mathematical model developed based on kinematic wave theory under unsteady and nonequilibrium conditions. The model satisfactorily simulated transient bed forms observed in laboratory experiments. Finally, nonuniform sediment transport model was developed under unsteady and nonequilibrium flow based on diffusion wave approach.The results implied that the sediment with mean particle diameter and the sediments with nonuniform particle diameters gave different solutions under unsteady flow conditions

Applied statistical methods for prediction modelling of upper limb functional recovery after stroke

Stroke is the third largest cause of death in the world, with a significant contribution to disability. Motor function impairment, encompassing upper limb impairment, is the most significant post-stroke impairment. Such an impairment contributes to reducing a person’s ability to complete daily activities, thus affecting their quality of life. Effective interventions, specifically targeted at upper limb recovery, are important, just as much as predictions of patient’s post-stroke. Predictions have become essential in making accurate clinical decisions in stroke management, including selection of appropriate rehabilitation programs, referring into appropriate services, setting realistic goals by therapists and clinicians and predicting the level of dependence following discharge from the hospital. This research focuses on the prediction of upper limb recovery and function. Despite the current and widely used traditional statistical methods of prediction, the research here presents a developed modern method which focuses on prediction models of regression methods. This is because traditional methods have been shown to lack clinical usefulness and do not have meaningful acceptance in clinical practice. The modern method developed and adopted aims to give more beneficial and valid results from the prediction model

Applied statistical methods for prediction modelling of upper limb functional recovery after stroke

Stroke is the third largest cause of death in the world, with a significant contribution to disability. Motor function impairment, encompassing upper limb impairment, is the most significant post-stroke impairment. Such an impairment contributes to reducing a person’s ability to complete daily activities, thus affecting their quality of life. Effective interventions, specifically targeted at upper limb recovery, are important, just as much as predictions of patient’s post-stroke. Predictions have become essential in making accurate clinical decisions in stroke management, including selection of appropriate rehabilitation programs, referring into appropriate services, setting realistic goals by therapists and clinicians and predicting the level of dependence following discharge from the hospital. This research focuses on the prediction of upper limb recovery and function. Despite the current and widely used traditional statistical methods of prediction, the research here presents a developed modern method which focuses on prediction models of regression methods. This is because traditional methods have been shown to lack clinical usefulness and do not have meaningful acceptance in clinical practice. The modern method developed and adopted aims to give more beneficial and valid results from the prediction model

In vitro and in vivo diversity of HIV-1 subtype C envelope proteins and correlation with changes in biological properties of viral isolates.

Student Number : 0114163J - PhD thesis - Faculty of Health SciencesHIV-1 gains entry into host cells by binding to CD4 and a coreceptor, predominantly CCR5 or CXCR4. Viruses that use CCR5 are termed R5, those able to use CXCR4 are termed X4 while viruses able to use both coreceptors are referred to as R5X4. Accelerated CD4 decline and disease progression within an infected HIV-1 subtype B infected individual is often associated with the emergence of viruses able to use CXCR4. However, CXCR4 coreceptor usage appears to occur less frequently among HIV-1 subtype C viruses, the most predominant strain circulating globally, including South Africa. The aim of this study was to investigate the genetic determinants of CXCR4 usage in HIV-1 subtype C isolates. The V3 region of the envelope glycoprotein is the major determinant of coreceptor usage. In Chapter 2, 32 subtype C isolates with known phenotypes (16 R5, 8 R5X4 and 8 X4 isolates) were assessed using a subtype C specific V3-heteroduplex tracking assay. Results indicated that there were sufficient genetic differences to discriminate between R5 viruses and those able to use CXCR4 (both R5X4 and X4). In general, R5 isolates had a mobility ratio >0.9 whereas CXCR4-using isolates were usually <0.9. Sequence analysis of the V3 region showed that CXCR4-using viruses were often associated with an increased positive amino acid charge, insertions and loss of a glycosylation site, similar to HIV-1 subtype B. In contrast, where subtype B consensus V3 has a GPGR crown motif irrespective of coreceptor usage, all 16 subtype C R5 viruses had a conserved GPGQ sequence at the tip of the loop, while 12 of the 16 (75%) CXCR4-using viruses had substitutions in this motif, most commonly arginine (R). Thus, the rare occurrence of CXCR4-using viruses in subtype C may be due to the highly conserved nature of the GPGQ crown that may limit the potential for the development of X4 viruses. The usefulness of available genotype-based methods for predicting viral phenotypes in subtype C was explored in Chapter 3. Results indicated that commonly used prediction methods could detect R5 viruses, but were not very sensitive at identifying X4 viruses. We therefore developed a subtype C specific predictor based on position specific scoring matrices (PSSM). Similar methodology, as used in developing the subtype B PSSM, was applied on a training set of 280 subtype C sequences of known phenotype (229 NSI/CCR5 and 51 SI/CXCR4). The C-PSSM had a specificity of 94% (C.I. [92%-96%]) and sensitivity of 75% (C.I. [68%-82%]), indicating that the C-PSSM had improved sensitivity in predicting CXCR4 usage. This method also highlighted amino acid positions within V3 that could contribute differentially to phenotype prediction in subtypes B and C. A reliable phenotype prediction method, such as the C-PSSM, could provide a rapid and less expensive approach to identifying CXCR4 variants, and thus increase our knowledge of subtype C coreceptor usage. In Chapter 4 we examined the genetic changes in full-length gp160 envelope genes of 23 sequential isolates from 5 patients followed for two to three years. Three of the patients' isolates used CCR5 at all time points while 2 patients underwent a coreceptor switch with disease progression. The genetic changes observed over time indicated changes in length of variable loops particularly the V1, V4 and V5 and shifting N-glycosylation sites, particularly in the 2 patients that used CXCR4. Changes in the V3 were only noted in the 2 patients’ that used CXCR4 which included substitutions of specific amino acids including those in the crown and increased amino acid charge in the V3 region. Both of these patients were dually infected suggesting that recombination may contribute to the rapid emergence of X4 viruses. The in vitro and in vivo development of CXCR4 usage was analysed in a pediatric patient that experienced a coreceptor switch during disease progression (Chapter 5). Biological and molecular clones were generated and the V1-V5 regions sequenced. Analyses of the V3 region indicated that the evolution to CXCR4 usage happens in a step-wise manner that included increased charge and changes in the crown motif. The intermediate variants with predicted dualtropism were also associated with increased V1-V2 lengths, suggesting that other regions may contribute to coreceptor switching. Furthermore, the development of CXCR4 usage within this patient was due to two mutational pathways, in which one resulted in R5X4 viruses and the other X4 variants. In Chapter 6, the impact and treatment of acute TB on HIV-1 diversity in co-infected patients was investigated, specifically to determine the genetic characteristics of the viral populations present before, during and after TB treatment. Plasma samples from 18 HIV-1 infected patients were analysed using the C2V3 region, six of whom showed a high degree of variation using a V3-HTA and were selected for further analyses. All patients were predicted as R5 with no evidence of coreceptor switching over time. There was no correlation between the degree of genetic diversity and viral load, although both showed fluctuations over time. Phylogenetic and pairwise genetic distance analysis indicated that there was amplification of existing variants in 3 patients while in the other 3 patients there were dramatic shifts in viral populations suggesting selection of viral sub-populations over time. Thus in some co-infected patients, TB can affect HIV-1 genetic heterogeneity although there was no evidence of a shift towards CXCR4 usage despite the presence of an AIDS defining illness. Observations in this study have shown that the V3 region is the major determinant of coreceptor usage within HIV-1 subtype C, similar to HIV-1 subtype B. Characteristics such as increased charge length variability of the V3 region and loss of the glycosylation site within this region are associated with CXCR4 usage. The limited number of X4 viruses in subtype C does suggest some restricting mechanisms for CXCR4 usage. In this study we looked at genetic determinants and found that the rare occurrence of CXCR4-using viruses in subtype C, may be due to the highly conserved nature of the GPGQ crown that may limit the potential for the development of subtype C X4 viruses. Furthermore, the development of CXCR4 usage happened in a step-wise manner, with R5X4 viruses intermediates, in which an increased V1-V2 was observed suggesting that other regions within the envelope protein do contribute to coreceptor usage. Thus, regions such as V1-V2 and V4-V5 did contribute to coreceptor usage, but the V3 region remained the most important determinant of coreceptor usage in HIV-1 subtype C isolates. Collectively these findings have provided important data on the genetic determinants of CXCR4 usage in HIV-1 subtype C and an understanding of how they might evolve within a patient