dc.contributor.author | Lilian, Mbaisi Ang'ang'o | |
dc.contributor.author | Jeremy, Herren | |
dc.contributor.author | Ozlem, Tastan Bishop | |
dc.date.accessioned | 2023-04-05T06:43:20Z | |
dc.date.available | 2023-04-05T06:43:20Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12562/1805 | |
dc.description | publication | en_US |
dc.description.abstract | Microsporidia are spore-forming eukaryotes that are related to fungi but have unique traits that set them apart. They have compact genomes as a result of evolutionary gene loss associated with their complete dependency on hosts for survival. Despite having a relatively small number of genes, a disproportionately high percentage of the genes in microsporidia genomes code for proteins whose functions remain unknown (hypothetical proteins—HPs). Computational annotation of HPs has become a more efficient and cost-effective alternative to experimental investigation. This research developed a robust bioinformatics annotation pipeline of HPs from Vittaforma corneae, a clinically important microsporidian that causes ocular infections in immunocompromised individuals. Here, we describe various steps to retrieve sequences and homologs and to carry out physicochemical characterization, protein family classification, identification of motifs and domains, protein–protein interaction network analysis, and homology modelling using a variety of online resources. Classification of protein families produced consistent findings across platforms, demonstrating the accuracy of annotation utilizing in silico methods. A total of 162 out of 2034 HPs were fully annotated, with the bulk of them categorized as binding proteins, enzymes, or regulatory proteins. The protein functions of several HPs from Vittaforma corneae were accurately inferred. This improved our understanding of microsporidian HPs despite challenges related to the obligate nature of microsporidia, the absence of fully characterized genes, and the lack of homologous genes in other systems. | en_US |
dc.description.sponsorship | Organization for Women in Science for the Developing World (OWSD) Swedish International Development Cooperation Agency (SIDA) Open Philanthropy (SYMBIOVECTOR Track A) Bill and Melinda Gates Foundation Swiss Agency for Development and Cooperation (SDC) Australian Centre for International Agricultural Research (ACIAR) Federal Democratic Republic of Ethiopia Government of the Republic of Kenya | en_US |
dc.publisher | MDPI-Molecular sciences | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | microsporidia | en_US |
dc.subject | unknown proteins | en_US |
dc.subject | computational annotation | en_US |
dc.subject | protein function prediction | en_US |
dc.title | Structural and Functional Annotation of Hypothetical Proteins from the Microsporidia Species Vittaforma corneae ATCC 50505 Using in silico Approaches | en_US |
dc.type | Article | en_US |
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