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Analysis of within-host evolution of Plasmodium Falciparum during treatment
Antimalarial drugs impose strong selective pressure on Plasmodium falciparum parasite genomes and leave signatures of selection. The evolutionary basis of drug resistant malaria in endemic and epidemic settings continues to remain an ongoing scientific priority whose solution carries a significant e...
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| Format: | Thesis |
| Language: | English |
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Computational Biology Division
2019
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| _version_ | 1867613328326524928 |
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| access_status_str | Open Access |
| author | Okendo, Javan Ochieng |
| author2 | Mulder, Nicola |
| author_browse | Mulder, Nicola Okendo, Javan Ochieng |
| author_facet | Mulder, Nicola Okendo, Javan Ochieng |
| author_sort | Okendo, Javan Ochieng |
| collection | Thesis |
| description | Antimalarial drugs impose strong selective pressure on Plasmodium falciparum parasite genomes and leave signatures of selection. The evolutionary basis of drug resistant malaria in endemic and epidemic settings continues to remain an ongoing scientific priority whose solution carries a significant effect on treatment outcomes. To understand the evolutionary changes in P. falciparum during treatment with ACTs, we used various approaches to test the neutral models of evolution using P. falciparum genomic data which were collected from Kombewa and Maseno in Kisumu, Kenya between 2013 and 2015. The Synonymous/Non-synonymous (dN/dS) ratio was used to predict the effect of selection on protein coding loci of the Pfk13 gene. A logistic regression model was used to test the association between IC50s and the SNPs. mCSM and SDM were used to detect the effects of mutations on the Pfk13 gene while the PRIMO web server was used to locate the SNPs on the Kelch13 propeller domain. Modeller V9.1 was used to predict the structure of the Kelch 13 propeller domain and the Posview webserver used to predict ACT/kelch 13 interactions. Population differentiation was done using Microsatellite analyzer to calculate FST and customized R scripts with the relevant population genetics packages were used in the analysis. For samples collected in 2013, Tajima’s D genomic summary statistic was 4.53194, Fu & Li D* 2.13380, and Fu &Li F* 3.62142. However, in 2015 Tajima’s D was -2.42910, Fu and Li’s D* -5.2712, and Fu and Li’s F* -5.0045. The dN/dS in 2013 was 1.0299, while in 2015 dN/dS was 2.6884. Kenyan P. falciparum SNPs occur on the intra or inter blade domains on the PfK13 propeller domain. The FST analysis showed minimal population differentiation of the parasites during treatment. There was no significant association between SNPs and IC50 values but SNPs at codon D547E showed association with Artesunate and D559E with AQ and MQ IC50 respectively. Even though there is an exponential increase in the number of non-synonymous point mutations in the Pfk13 gene, the Kenyan P. falciparum strains remain sensitive to ACT drugs. Further research needs to be done by deep sequencing this location of chromosome 13 as it will provide more power for finding novel SNPs for further validation. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/29305 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:23.309Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Computational Biology Division |
| publisherStr | Computational Biology Division |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/29305 Analysis of within-host evolution of Plasmodium Falciparum during treatment Okendo, Javan Ochieng Mulder, Nicola Andagalu, Ben Medicine Antimalarial drugs impose strong selective pressure on Plasmodium falciparum parasite genomes and leave signatures of selection. The evolutionary basis of drug resistant malaria in endemic and epidemic settings continues to remain an ongoing scientific priority whose solution carries a significant effect on treatment outcomes. To understand the evolutionary changes in P. falciparum during treatment with ACTs, we used various approaches to test the neutral models of evolution using P. falciparum genomic data which were collected from Kombewa and Maseno in Kisumu, Kenya between 2013 and 2015. The Synonymous/Non-synonymous (dN/dS) ratio was used to predict the effect of selection on protein coding loci of the Pfk13 gene. A logistic regression model was used to test the association between IC50s and the SNPs. mCSM and SDM were used to detect the effects of mutations on the Pfk13 gene while the PRIMO web server was used to locate the SNPs on the Kelch13 propeller domain. Modeller V9.1 was used to predict the structure of the Kelch 13 propeller domain and the Posview webserver used to predict ACT/kelch 13 interactions. Population differentiation was done using Microsatellite analyzer to calculate FST and customized R scripts with the relevant population genetics packages were used in the analysis. For samples collected in 2013, Tajima’s D genomic summary statistic was 4.53194, Fu & Li D* 2.13380, and Fu &Li F* 3.62142. However, in 2015 Tajima’s D was -2.42910, Fu and Li’s D* -5.2712, and Fu and Li’s F* -5.0045. The dN/dS in 2013 was 1.0299, while in 2015 dN/dS was 2.6884. Kenyan P. falciparum SNPs occur on the intra or inter blade domains on the PfK13 propeller domain. The FST analysis showed minimal population differentiation of the parasites during treatment. There was no significant association between SNPs and IC50 values but SNPs at codon D547E showed association with Artesunate and D559E with AQ and MQ IC50 respectively. Even though there is an exponential increase in the number of non-synonymous point mutations in the Pfk13 gene, the Kenyan P. falciparum strains remain sensitive to ACT drugs. Further research needs to be done by deep sequencing this location of chromosome 13 as it will provide more power for finding novel SNPs for further validation. 2019-02-05T07:14:06Z 2019-02-05T07:14:06Z 2018 2019-01-31T09:53:45Z Master Thesis Masters MSc http://hdl.handle.net/11427/29305 eng application/pdf Computational Biology Division Faculty of Health Sciences University of Cape Town |
| spellingShingle | Medicine Okendo, Javan Ochieng Analysis of within-host evolution of Plasmodium Falciparum during treatment |
| thesis_degree_str | Master's |
| title | Analysis of within-host evolution of Plasmodium Falciparum during treatment |
| title_full | Analysis of within-host evolution of Plasmodium Falciparum during treatment |
| title_fullStr | Analysis of within-host evolution of Plasmodium Falciparum during treatment |
| title_full_unstemmed | Analysis of within-host evolution of Plasmodium Falciparum during treatment |
| title_short | Analysis of within-host evolution of Plasmodium Falciparum during treatment |
| title_sort | analysis of within host evolution of plasmodium falciparum during treatment |
| topic | Medicine |
| url | http://hdl.handle.net/11427/29305 |
| work_keys_str_mv | AT okendojavanochieng analysisofwithinhostevolutionofplasmodiumfalciparumduringtreatment |