HIV-1 subtypes maintain distinctive physicochemical signatures in Nef domains associated with immunoregulation.

Autor: Lamers SL; BioInfoExperts , Thibodaux, Louisiana, USA. Electronic address: susanna@bioinfox.com., Fogel GB; Natural Selection, San Diego, California, USA., Liu ES; Natural Selection, San Diego, California, USA., Nolan DJ; BioInfoExperts , Thibodaux, Louisiana, USA., Rose R; BioInfoExperts , Thibodaux, Louisiana, USA., McGrath MS; University of California, San Francisco, California, USA.
Jazyk: angličtina
Zdroj: Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases [Infect Genet Evol] 2023 Nov; Vol. 115, pp. 105514. Date of Electronic Publication: 2023 Oct 11.
DOI: 10.1016/j.meegid.2023.105514
Abstrakt: Background: HIV subtype is associated with varied rates of disease progression. The HIV accessory protein, Nef, continues to be present during antiretroviral therapy (ART) where it has numerous immunoregulatory effects. In this study, we analyzed Nef sequences from HIV subtypes A1, B, C, and D using a machine learning approach that integrates functional amino acid information to identify if unique physicochemical features are associated with Nef functional/structural domains in a subtype-specific manner.
Methods: 2253 sequences representing subtypes A1, B, C, and D were aligned and domains with known functional properties were scored based on amino acid physicochemical properties. Following feature generation, we used statistical pruning and evolved neural networks (ENNs) to determine if we could successfully classify subtypes. Next, we used ENNs to identify the top five key Nef physicochemical features applied to specific immunoregulatory domains that differentiated subtypes. A signature pattern analysis was performed to the assess amino acid diversity in sub-domains that differentiated each subtype.
Results: In validation studies, ENNs successfully differentiated each subtype at A1 (87.2%), subtype B (89.5%), subtype C (91.7%), and subtype D (85.1%). Our feature-based domain scoring, followed by t-tests, and a similar ENN identified subtype-specific domain-associated features. Subtype A1 was associated with alterations in Nef CD4 binding domain; subtype B was associated with alterations with the AP-2 Binding domain; subtype C was associated with alterations in a structural Alpha Helix domain; and, subtype D was associated with alterations in a Beta-Sheet domain.
Conclusions: Recent studies have focused on HIV Nef as a driver of immunoregulatory disease in those HIV infected and on ART. Nef acts through a complex mixture of interactions that are directly linked to the key features of the subtype-specific domains we identified with the ENN. The study supports the hypothesis that varied Nef subtypes contribute to subtype-specific disease progression.
Competing Interests: Declaration of Competing Interest Susanna Lamers, David Nolan, and Rebecca Rose are employed by BioInfoExperts LLC. Gary Fogel and Enoch Liu are employed by Natural Selection Inc. No other competing interests exist.
(Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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