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Akmal MA, Hassan MA, Muhammad S, Khurshid KS, Mohamed A. An analytical study on the identification of N-linked glycosylation sites using machine learning model. PeerJ Comput Sci 2022; 8:e1069. [PMID: 36262138 PMCID: PMC9575850 DOI: 10.7717/peerj-cs.1069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 07/25/2022] [Indexed: 06/16/2023]
Abstract
N-linked is the most common type of glycosylation which plays a significant role in identifying various diseases such as type I diabetes and cancer and helps in drug development. Most of the proteins cannot perform their biological and psychological functionalities without undergoing such modification. Therefore, it is essential to identify such sites by computational techniques because of experimental limitations. This study aims to analyze and synthesize the progress to discover N-linked places using machine learning methods. It also explores the performance of currently available tools to predict such sites. Almost seventy research articles published in recognized journals of the N-linked glycosylation field have shortlisted after the rigorous filtering process. The findings of the studies have been reported based on multiple aspects: publication channel, feature set construction method, training algorithm, and performance evaluation. Moreover, a literature survey has developed a taxonomy of N-linked sequence identification. Our study focuses on the performance evaluation criteria, and the importance of N-linked glycosylation motivates us to discover resources that use computational methods instead of the experimental method due to its limitations.
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Affiliation(s)
- Muhammad Aizaz Akmal
- Department of Computer Science, University of Engineering and Technology, KSK, Lahore, Punjab, Pakistan
| | - Muhammad Awais Hassan
- Department of Computer Science, University of Engineering and Technology, Lahore, Punjab, Pakistan
| | - Shoaib Muhammad
- Department of Computer Science, University of Engineering and Technology, Lahore, Punjab, Pakistan
| | - Khaldoon S. Khurshid
- Department of Computer Science, University of Engineering and Technology, Lahore, Punjab, Pakistan
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Evolution of Multiple Domains of the HIV-1 Envelope Glycoprotein during Coreceptor Switch with CCR5 Antagonist Therapy. Microbiol Spectr 2022; 10:e0072522. [PMID: 35727047 PMCID: PMC9431240 DOI: 10.1128/spectrum.00725-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
HIV-1 uses CD4 as a receptor and chemokine receptors CCR5 and/or CXCR4 as coreceptors. CCR5 antagonists are a class of antiretrovirals used to inhibit viral entry. Phenotypic prediction algorithms such as Geno2Pheno are used to assess CCR5 antagonist eligibility, for which the V3 region is screened. However, there exist scenarios where the algorithm cannot give an accurate prediction of tropism. The current study examined coreceptor shift of HIV-1 from CCR5-tropic strains to CXCR4-tropic or dual-tropic strains among five subjects in a clinical trial of the CCR5 antagonist vicriviroc. Envelope gene amplicon libraries were constructed and subjected to next-generation sequencing, as well as single-clone sequencing and functional analyses. Approximately half of the amplified full-length single envelope-encoding clones had no significant activity for infection of cells expressing high levels of CD4 and CCR5 or CXCR4. Functional analysis of 9 to 21 individual infectious clones at baseline and at the time of VF were used to construct phylogenetic trees and sequence alignments. These studies confirmed that specific residues and the overall charge of the V3 loop were the major determinants of coreceptor use, in addition to specific residues in other domains of the envelope protein in V1/V2, V4, C3, and C4 domains that may be important for coreceptor shift. These results provide greater insight into the viral genetic determinants of coreceptor shift. IMPORTANCE This study is novel in combining single-genome sequence analysis and next-generation sequencing to characterize HIV-1 quasispecies. The work highlights the importance of mutants present at frequencies of 1% or less in development of drug resistance. This study highlights a critical role of specific amino acid substitutions outside V3 that contribute to coreceptor shift as well as important roles of the V1/V2, V4, C3, and C4 domain residues.
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Judicate GP, Barabona G, Kamori D, Mahiti M, Tan TS, Ozono S, Mgunya AS, Kuwata T, Matsushita S, Sunguya B, Lyamuya E, Tokunaga K, Ueno T. Phenotypic and Genotypic Co-receptor Tropism Testing in HIV-1 Epidemic Region of Tanzania Where Multiple Non-B Subtypes Co-circulate. Front Microbiol 2021; 12:703041. [PMID: 34305873 PMCID: PMC8292895 DOI: 10.3389/fmicb.2021.703041] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 06/08/2021] [Indexed: 11/13/2022] Open
Abstract
HIV human immunodeficiency virus type I (HIV-1) entry inhibitor potency is dependent on viral co-receptor tropisms and thereby tropism determination is clinically important. However, phenotypic tropisms of HIV-1 non-B subtypes have been poorly investigated and the genotypic prediction algorithms remain insufficiently validated. To clarify this issue, we recruited 52 treatment-naïve, HIV-1-infected patients in Tanzania, where multiple HIV-1 non-B subtypes co-circulate. Sequence analysis of 93 infectious envelope clones isolated from their plasma viral RNA revealed the co-circulation of subtypes A1, C, D, and inter-subtype recombinant forms (isRFs). Phenotypic tropism assays revealed that lentivirus reporters pseudotyped with 75 (80.6%) and 5 (5.4%) envelope clones could establish infection toward U87.CD4 cells expressing CCR5 (R5) and CXCR4 (X4), respectively; whereas the remaining 13 (14%) clones could infect both cells. Genotypic analyses by widely used algorithms including V3 net charge, Geno2pheno, WebPSSM, and PhenoSeq showed that almost all phenotypic X4-tropic clones and only 15 of 75 phenotypic R5-tropic clones were concordantly predicted. However, the remaining 60 phenotypic R5-tropic clones were discordantly predicted by at least one algorithm. In particular, 2 phenotypic R5-tropic clones were discordantly predicted by all algorithms tested. Taken together, the results demonstrate the limitation of currently available genotypic algorithms for predicting co-receptor inference among co-circulating multiple non-B subtypes and emerging isRFs. Also, the phenotypic tropism dataset presented here could be valuable for retraining of the widely used genotypic prediction algorithms to enhance their performance.
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Affiliation(s)
- George P Judicate
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan
| | - Godfrey Barabona
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan
| | - Doreen Kamori
- Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Macdonald Mahiti
- Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Toong Seng Tan
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan
| | - Seiya Ozono
- Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
| | | | - Takeo Kuwata
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan
| | - Shuzo Matsushita
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan
| | - Bruno Sunguya
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan.,Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Eligius Lyamuya
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan.,Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Kenzo Tokunaga
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan.,Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
| | - Takamasa Ueno
- Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan.,Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
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