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Different Patterns of HIV-1 Replication in MACROPHAGES is Led by Co-Receptor Usage.

ABSTRACT: Background and objectives: To enter the target cell, HIV-1 binds not only CD4 but also a co-receptor ?-chemokine receptor 5 (CCR5) or ? chemokine receptor 4 (CXCR4). Limited information is available on the impact of co-receptor usage on HIV-1 replication in monocyte-derived macrophages (MDM) and on the homeostasis of this important cellular reservoir. Materials and Methods: Replication (measured by p24 production) of the CCR5-tropic 81A strain increased up to 10 days post-infection and then reached a plateau. Conversely, the replication of the CXCR4-tropic NL4.3 strain (after an initial increase up to day 7) underwent a drastic decrease becoming almost undetectable after 10 days post-infection. The ability of CCR5-tropic and CXCR4-tropic strains to induce cell death in MDM was then evaluated. While for CCR5-tropic 81A the rate of apoptosis in MDM was comparable to uninfected MDM, the infection of CXCR4-tropic NL4.3 in MDM was associated with a rate of 14.3% of apoptotic cells at day 6 reaching a peak of 43.5% at day 10 post-infection. Results: This suggests that the decrease in CXCR4-tropic strain replication in MDM can be due to their ability to induce cell death in MDM. The increase in apoptosis was paralleled with a 2-fold increase in the phosphorylated form of p38 compared to WT. Furthermore, microarray analysis showed modulation of proapoptotic and cancer-related genes induced by CXCR4-tropic strains starting from 24 h after infection, whereas CCR5 viruses modulated the expression of genes not correlated with apoptotic-pathways. Conclusions: In conclusion, CXCR4-tropic strains can induce a remarkable depletion of MDM. Conversely, MDM can represent an important cellular reservoir for CCR5-tropic strains supporting the role of CCR5-usage in HIV-1 pathogenesis and as a pharmacological target to contribute to an HIV-1 cure.

SUBMITTER: Borrajo A

PROVIDER: S-EPMC6630780 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Different Patterns of HIV-1 Replication in MACROPHAGES is Led by Co-Receptor Usage.

Borrajo Ana A Ranazzi Alessandro A Pollicita Michela M Bellocchi Maria Concetta MC Salpini Romina R Mauro Maria Vittoria MV Ceccherini-Silberstein Francesca F Perno Carlo Federico CF Svicher Valentina V Aquaro Stefano S

Medicina (Kaunas, Lithuania) 20190621 6

<i>Background and objectives:</i> To enter the target cell, HIV-1 binds not only CD4 but also a co-receptor β-chemokine receptor 5 (CCR5) or α chemokine receptor 4 (CXCR4). Limited information is available on the impact of co-receptor usage on HIV-1 replication in monocyte-derived macrophages (MDM) and on the homeostasis of this important cellular reservoir. <i>Materials and Methods:</i> Replication (measured by p24 production) of the CCR5-tropic 81A strain increased up to 10 days post-infection ...[more]

PMID: 31234437

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Project description:BackgroundHIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-receptors, which interact primarily with the third hypervariable loop (V3 loop) of gp120. Determination of HIV-1 affinity for either the R5 or X4 co-receptor on host cells facilitates the inclusion of co-receptor antagonists as a part of patient treatment strategies. A dataset of 1193 distinct gp120 V3 loop peptide sequences (989 R5-utilizing, 204 X4-capable) is utilized to train predictive classifiers based on implementations of random forest, support vector machine, boosted decision tree, and neural network machine learning algorithms. An in silico mutagenesis procedure employing multibody statistical potentials, computational geometry, and threading of variant V3 sequences onto an experimental structure, is used to generate a feature vector representation for each variant whose components measure environmental perturbations at corresponding structural positions.ResultsClassifier performance is evaluated based on stratified 10-fold cross-validation, stratified dataset splits (2/3 training, 1/3 validation), and leave-one-out cross-validation. Best reported values of sensitivity (85%), specificity (100%), and precision (98%) for predicting X4-capable HIV-1 virus, overall accuracy (97%), Matthew's correlation coefficient (89%), balanced error rate (0.08), and ROC area (0.97) all reach critical thresholds, suggesting that the models outperform six other state-of-the-art methods and come closer to competing with phenotype assays.ConclusionsThe trained classifiers provide instantaneous and reliable predictions regarding HIV-1 co-receptor usage, requiring only translated V3 loop genotypes as input. Furthermore, the novelty of these computational mutagenesis based predictor attributes distinguishes the models as orthogonal and complementary to previous methods that utilize sequence, structure, and/or evolutionary information. The classifiers are available online at http://proteins.gmu.edu/automute.

Dataset Information

Different Patterns of HIV-1 Replication in MACROPHAGES is Led by Co-Receptor Usage.

Publications

Different Patterns of HIV-1 Replication in MACROPHAGES is Led by Co-Receptor Usage.

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