Blocking the binding of the envelope HIV-1 protein to immune cells is a popular concept for development of anti-HIV therapeutics. R5 HIV-1 binds CCR5, X4 HIV-1 binds CXCR4, and dual-tropic HIV-1 can bind either coreceptor for cellular entry. R5 viruses are associated with early infection and over time can evolve to X4 viruses that are associated with immune failure. Dual-tropic HIV-1 is less studied; however, it represents functional antigenic intermediates during the transition of R5 to X4 viruses. Viral tropism is linked partly to the HIV-1 envelope V3 domain, where the amino acid sequence helps dictate the receptor a particular virus will target; however, using V3 sequence information to identify dual-tropic HIV-1 isolates has remained difficult. Our goal in this study was to elucidate features of dual-tropic HIV-1 isolates that assist in the biological understanding of dual-tropism and develop an approach for their detection. Over 1559 HIV-1 subtype B sequences with known tropisms were analyzed. Each sequence was represented by 73 structural, biochemical and regional features. These features were provided to an evolved neural network classifier and evaluated using balanced and unbalanced data sets. The study resolved R5X4 viruses from R5 with an accuracy of 81.8% and from X4 with an accuracy of 78.8%. The approach also identified a set of V3 features (hydrophobicity, structural and polarity) that are associated with tropism transitions. The ability to distinguish R5X4 isolates will improve computational tropism decisions for R5 vs. X4 and assist in HIV-1 research and drug development efforts.

HIV-1 enters immune cells via binding the viral envelope to a host cell CD4 receptor, and then a secondary co-receptor, usually CCR5 (R5) or CXCR4 (X4), and some HIV can utilize both co-receptors (R5X4). Although a small set of amino-acid properties such as charge and sequence length applied to HIV-1 envelope V3 loop sequence data can be used to predict co-receptor usage, we sought to expand the fundamental understanding of the physiochemical basis of tropism by analyzing many, perhaps less obvious, amino-acid properties over a diverse array of HIV sequences. We examined 74 amino-acid physicochemical scales over 1,559 V3 loop sequences with biologically tested tropisms downloaded from the Los Alamos HIV sequence database. Linear regressions were then calculated for each feature relative to three tropism transitions (R5→X4; R5→R5X4; R5X4→X4). Independent correlations were rank ordered to determine informative features. A structural analysis of the V3 loop was performed to better interpret these findings relative to HIV tropism states. Similar structural changes are required for R5 and R5X4 to transition to X4, thus suggesting that R5 and R5X4 types are more similar than either phenotype is to X4. Overall, the analysis suggests a continuum of viral tropism that is only partially related to charge; in fact, the analysis suggests that charge modification may be primarily attributed to decreased R5 usage, and further structural changes, particularly those associated with β-sheet structure, are likely required for full X4 usage.

Despite the development of powerful antiretroviral drugs, HIV-1 associated neurological disorders (HAND) will affect approximately half of those infected with HIV-1. Combined anti-retroviral therapy (cART) targets viral replication and increases T-cell counts, but it does not always control macrophage polarization, brain infection or inflammation. Moreover, it remains difficult to identify those at risk for HAND. New therapies that focus on modulating host immune response by making use of biological pathways could prove to be more effective than cART for the treatment of neuroAIDS. Additionally, while numerous HAND biomarkers have been suggested, they are of little use without methods for appropriate data integration and a systems-level interpretation. Machine learning, could be used to develop multifactorial computational models that provide clinicians and researchers with the ability to identify which factors (in what combination and relative importance) are considered important to outcome.

The current study provides detailed protocols utilized to amplify the complete HIV-1 gp120 and nef genes from single copies of expressed or integrated HIV present in fresh-frozen autopsy tissues of patients who died while on combined antiretroviral therapy (cART) with no detectable plasma viral load (pVL) at death ( Lamers et al., 2016a and 2016b; Rose et al., 2016 ). This method optimizes protocols from previous publications ( Palmer et al., 2005 ; Norström et al., 2012 ; Lamers et al., 2015 ; 2016a and 2016b; Rife et al., 2016 ) to produce single distinct PCR products that can be directly sequenced and includes several cost-saving and time-efficient modifications.

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.

The persistence of HIV infection, even after lengthy and successful combined antiretroviral therapy (cART), has precluded an effective cure. The anatomical locations and biological mechanisms through which the viral population is maintained remain unknown. Much research has focused nearly exclusively on circulating resting T cells as the predominant source of persistent HIV, a strategy with limited success in developing an effective cure strategy. In this study, we review research supporting the importance of anatomical tissues and other immune cells for HIV maintenance and expansion, including the central nervous system, lymph nodes, and macrophages. We present accumulated research that clearly demonstrates the limitations of using blood-derived cells as a proxy for tissue reservoirs and sanctuaries throughout the body. We cite recent studies that have successfully used deep-sequencing strategies to uncover the complexity of HIV infection and the ability of the virus to evolve despite undetectable plasma viral loads. Finally, we suggest new strategies and highlight the importance of tissue banks for future research.

Two innovative studies recently identified functional lymphatic structures in the meninges that may influence the development of HIV-associated neurological disorders (HAND). Until now, blood vessels were assumed to be the sole transport system by which HIV-infected monocytes entered the brain by bypassing a potentially hostile blood-brain barrier through inflammatory-mediated semi-permeability. A cascade of specific chemokine signals promote monocyte migration from blood vessels to surrounding brain tissues via a well-supported endothelium, where the cells differentiate into tissue macrophages capable of productive HIV infection. Lymphatic vessels on the other hand are more loosely organized than blood vessels. They absorb interstitial fluid from bodily tissues where HIV may persist and exchange a variety of immune cells (CD4(+) T cells, monocytes, macrophages, and dendritic cells) with surrounding tissues through discontinuous endothelial junctions. We propose that the newly discovered meningeal lymphatics are key to HIV migration among viral reservoirs and brain tissue during periods of undetectable plasma viral loads due to suppressive combinational antiretroviral therapy, thus redefining the migration process in terms of a blood-lymphatic transport system.

Kaposi's sarcoma (KS) in HIV-infected individuals can have a wide range of clinical outcomes, from indolent skin tumors to a life-threatening visceral cancer. KS tumors contain endothelial-related cells and inflammatory cells that may be HIV-infected. In this study we tested if HIV evolutionary patterns distinguish KS tumor relatedness and progression. Multisite autopsies from participants who died from HIV-AIDS with KS prior to the availability of antiretroviral therapy were identified at the AIDS and Cancer Specimen Resource (ACSR). Two patients (KS1 and KS2) died predominantly from non-KS-associated disease and KS3 died due to aggressive and metastatic KS within one month of diagnosis. Skin and visceral tumor and nontumor autopsy tissues were obtained (n = 12). Single genome sequencing was used to amplify HIV RNA and DNA, which was present in all tumors. Independent HIV tumor clades in phylogenies differentiated KS1 and KS2 from KS3, whose sequences were interrelated by both phylogeny and selection. HIV compartmentalization was confirmed in KS1 and KS2 tumors; however, in KS3, no compartmentalization was observed among sampled tissues. While the sample size is small, the HIV evolutionary patterns observed in all patients suggest an interplay between tumor cells and HIV-infected cells which provides a selective advantage and could promote KS progression.

Over 50% of HIV-infected (HIV+) persons are expected to be over age 50 by 2015. The pathogenic effects of HIV, particularly in cases of long-term infection, may intersect with those of age-related illnesses and prolonged exposure to combined antiretroviral therapy (cART). One potential outcome is an increased prevalence of neurocognitive impairment in older HIV+ individuals, as well as an altered presentation of HIV-associated neurocognitive disorders (HANDs). In this study, we employed stepwise regression to examine 24 features sometimes associated with HAND in 40 older (55-73 years of age) and 30 younger (32-50 years of age) HIV+, cART-treated participants without significant central nervous system confounds. The features most effective in generating a true assessment of the likelihood of HAND diagnosis differed between older and younger cohorts, with the younger cohort containing features associated with drug abuse that were correlated to HAND and the older cohort containing features that were associated with lipid disorders mildly associated with HAND. As the HIV-infected population grows and the demographics of the epidemic change, it is increasingly important to re-evaluate features associated with neurocognitive impairment. Here, we have identified features, routinely collected in primary care settings, that provide more accurate diagnostic value than a neurocognitive screening measure among younger and older HIV individuals.