Expression, Activity, and Regulation of Phosphorylating Enzymes in Tissues and Cells Relevant to HIV-1 Sexual Transmission

HIV-1 性传播相关组织和细胞中磷酸化酶的表达、活性及调控

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作者:Minlu Hu, Guru R Valicherla, Tian Zhou, Sharon L Hillier, Lisa C Rohan

Abstract

Phosphorylating enzymes (PEs) are responsible for activating nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) such as tenofovir (TFV) and are critical for their conversion to obtain intracellular antiviral activity. However, there are limited data available regarding the expression of PEs and their activity in the female genital tract. This work compared the messenger RNA (mRNA) expression levels of PEs in human female genital tissue, immune cells, and animal models that are commonly used in human immunodeficiency virus (HIV) research. Furthermore, the effect of contraceptive hormones and proinflammatory cytokines on tenofovir diphosphate (TFV-DP) formation and efficacy in human vaginal, epithelial, and immune cells was also evaluated. We found that human vaginal and ectocervical tissues had similar mRNA expression for seven PEs tested. Polymerase chain reaction results revealed that creatine kinase brain (CKB), mitochondrial creatine kinase 1 (CKMT1), mitochondrial creatine kinase 2 (CKMT2), adenylate kinase AK3L1 (AK4), and nucleoside diphosphate kinase 1 (NME1) exhibited a 10- to 10,000-fold higher expression level in a vaginal epithelial cell line, VK2, compared with CD4+ T cells (p < .05). Medroxyprogesterone acetate (MPA)/progesterone (P4) and IL-1β/IL-8 treatment resulted in altered TFV-DP levels in VK2 and PM1 cells. MPA and P4 at concentrations above 0.1 μM, as well as IL-1β and IL-8 at concentrations above 10 ng/mL, significantly decreased HIV-1BaL inhibition in PM1 cells when 1 μM TFV was added. However, this observed effect of hormones and cytokines was abrogated when TFV concentration was raised to 1 mM. These in vitro results elucidate the role of PEs in TFV metabolism and provide information regarding differences in PE tissue expression for animal models commonly used in HIV testing. This information can be applied to better understand and interpret data obtained using these models.

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