Thesis (Ph. D.)--Cornell University, May, 2007. / Vita. Includes bibliographical references (Leaves 270-320).

The ability to link a particular phenotype to its causative genotype is one of the most challenging objectives for biological research. Although the genetic code provides an explicit formula for determining the sequence of amino acid phenotypes produced by a given nucleotide sequence, identifying specific residues that are functionally important remains problematic. Many computational approaches have been developed that use patterns observed in DNA sequences to identify these critical sites. However, very few research studies have used empirical data to test whether these approaches are truly able to identify sites of interest.In most empirical studies, the actual protein function and selective pressures are unknown; thus it is difficult to assess whether computational approaches are correctly identifying critical sites. Here I present two studies that utilize well-characterized empirical systems to evaluate and compare the performance of several computational approaches. In both cases, the proteins under study have specific amino acid substitutions that are confirmed to alter protein function and expected to be constrained by natural selection. In chapter 2, I examine functional variants in angiopoietin-like protein 4 (ANGPTL4), a protein involved in regulating plasma triglyceride levels; loss-of-function variants in this gene are believed to decrease the risk of cardiovascular disease. I apply several computational approaches to identify functional variants, including phylogenetic approaches for detecting positive selection. In chapter 3, I investigate the emergence of drug-resistance in HIV-1 during the course of antiretroviral drug therapy. I compare the performance of eight selection detection methods in identifying drug-resistant mutations in 109 intrapatient datasets with HIV-1 sequences isolated at multiple timepoints throughout drug treatment.It is critical that we develop methods to detect positively selected sites. The ability to detect these sites in silico, without the need for expensive and time consuming assays, would be invaluable to researchers in evolutionary biology, human genetics, and medicine. Through the research presented in this thesis, I hope to provide insight into the strengths and weaknesses of current approaches, thereby facilitating future research towards the development and improvement of evolutionary models.

HIV/AIDS is widely spread and ranks as the sixth biggest killer all over the world. Moreover, due to the rapid replication rate and the lack of proofreading mechanism of HIV virus, drug resistance is commonly found and is one of the reasons causing the failure of the treatment. Even though the drug resistance tests are provided to the patients and help choose more efficient drugs, such experiments may take up to two weeks to finish and are expensive. Because of the fast development of the computer, drug resistance prediction using machine learning is feasible. In order to accurately predict the HIV drug resistance, two main tasks need to be solved: how to encode the protein structure, extracting the more useful information and feeding it into the machine learning tools; and which kinds of machine learning tools to choose. In our research, we first proposed a new protein encoding algorithm, which could convert various sizes of proteins into a fixed size vector. This algorithm enables feeding the protein structure information to most state of the art machine learning algorithms. In the next step, we also proposed a new classification algorithm based on sparse representation. Following that, mean shift and quantile regression were included to help extract the feature information from the data. Our results show that encoding protein structure using our newly proposed method is very efficient, and has consistently higher accuracy regardless of type of machine learning tools. Furthermore, our new classification algorithm based on sparse representation is the first application of sparse representation performed on biological data, and the result is comparable to other state of the art classification algorithms, for example ANN, SVM and multiple regression. Following that, the mean shift and quantile regression provided us with the potentially most important drug resistant mutants, and such results might help biologists/chemists to determine which mutants are the most representative candidates for further research.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 5 uppsatser.

No description available.

L'une des principales barrières à la prise en charge optimale des patients sous traitement antirétroviral est l'accès limité aux tests de charge virale (CV) et de génotypage particulièrement en milieu décentralisé. Ces tests ne sont généralement disponibles qu'au niveau des structures sanitaires centrales de grandes villes et le plasma en est l'échantillon de référence. Or, son transfert des régions périphériques vers les laboratoires de références est difficile, voire impossible. Pour rapprocher les patients du laboratoire, nous avons démontré la possibilité d'assurer un suivi virologique complet (CV et génotypage) à partir des DBS collectés et acheminés dans des conditions de terrain. Nous avons également pour la première fois, documenté la réponse virologique au traitement antirétroviral et la diversité génétique du VIH-1 chez des patients adultes suivis en milieux décentralisés au Sénégal, au Mali et en Guinée Conakry. Globalement, malgré les défauts d'observance au traitement souligné, les résultats de nos travaux ne montrent pas de différences significatives dans la survenue de l'échec virologique entre patients suivis dans les structures sanitaires centrales et périphériques, ceci quelque soit le pays considéré. Au Sénégal, chez les enfants nés de mères séropositives, la résistance vis à vis des INNTI était plus prépondérante, probablement du fait de l'utilisation systématique de la Névirapine durant la PTME. Par ailleurs, aucune mutation de résistance aux inhibiteurs d'intégrase n'a été observée malgré des taux de résistance élevés chez des patients en échec de première et deuxième ligne de traitement. Nos travaux confirment également une grande diversité génétique des sous-types viraux avec cependant la prédominance du CRF02_AG dans la sous région Ouest Africaine. Ces travaux de thèse mettent en évidence la faisabilité et la pertinence du DBS comme support pour le suivi virologique des patients en milieux décentralisés. Son utilisation a permis de montrer d'autre part des taux d'échecs virologiques élevés indiquant la nécessité de renforcer l'adhérence au traitement. Enfin, nos résultats soulignent l'utilité de prendre davantage en considération les profils de résistance pour initier un traitement de relais. / One of the major barriers to the optimal care of patients undergoing antiretroviral therapy is the limited access to viral load (VL) and genotyping tests, especially in remote areas. These technologies are usually available only at central health facilities in larger cities and plasma is the reference sample. However, plasma or whole blood samples shipment from remote areas to reference lab faces several constraints or even impossible. In order to bring closer patients to reference lab, we have demonstrated the ability of DBS (Dried Blood Spots) collected and shipped in field conditions to provide complete virological monitoring (VL and genotyping). We also documented for the first time, virological outcome of ART and HIV-1 genetic diversity in adult patients followed up in decentralized settings in Senegal, Mali and Guinea Conakry. Overall, despite the low treatment adherence noted sometimes, our findings show no significant differences in the occurrence of virological failure among patients followed up in the central and peripheral health facilities, whatever the country. In Senegal, no integrase inhibitors associated DRM has been found despite the high rate of resistance in patients failing first and second-line treatment. Furthermore, among children born to HIV infected mothers, NNRTI-associated drug resistant mutations (DRM) were more predominant, probably because of systematic use of Nevirapine in MTCT. Our studies also confirm the high genetic diversity of viral subtypes, with the dominance of CRF02_AG in West Africa. This work presented here highlights the feasibility and relevance of DBS as support for the virological monitoring of patients in decentralized settings in West Africa. Furthermore, its use showed high rate of virological failure indicating the need to reinforce adherence to treatment. Finally, our results highlight the utility to considering carefully drug resistance patterns before switching to another ART regimen.