Specific amino acids in HIV-1 Vpr are significantly associated with differences in patient neurocognitive status.

Even in the era of combination antiretroviral therapies used to combat human immunodeficiency virus type 1 (HIV-1) infection, up to 50 % of well-suppressed HIV-1-infected patients are still diagnosed with mild neurological deficits referred to as HIV-associated neurocognitive disorders (HAND). The multifactorial nature of HAND likely involves the HIV-1 accessory protein viral protein R (Vpr) as an agent of neuropathogenesis. To investigate the effect of naturally occurring variations in Vpr on HAND in well-suppressed HIV-1-infected patients, bioinformatic analyses were used to correlate peripheral blood-derived Vpr sequences with patient neurocognitive performance, as measured by comprehensive neuropsychological assessment and the resulting Global Deficit Score (GDS). Our studies revealed unique associations between GDS and the presence of specific amino acid changes in peripheral blood-derived Vpr sequences [neuropsychological impairment Vpr (niVpr) variants]. Amino acids N41 and A55 in the Vpr sequence were associated with more pronounced neurocognitive deficits (higher GDS). In contrast, amino acids I37 and S41 were connected to measurably lower GDS. All niVpr variants were also detected in DNA isolated from HIV-1-infected brain tissues. The implication of these results is that niVpr variants alter the genesis and/or progression of HAND through differences in Vpr-mediated effects in the peripheral blood and/or the brain.

Utilization of HIV-1 envelope V3 to identify X4- and R5-specific Tat and LTR sequence signatures.

BACKGROUND: HIV-1 entry is a receptor-mediated process directed by the interaction of the viral envelope with the host cell CD4 molecule and one of two co-receptors, CCR5 or CXCR4. The amino acid sequence of the third variable (V3) loop of the HIV-1 envelope is highly predictive of co-receptor utilization preference during entry, and machine learning predictive algorithms have been developed to characterize sequences as CCR5-utilizing (R5) or CXCR4-utilizing (X4). It was hypothesized that while the V3 loop is predominantly responsible for determining co-receptor binding, additional components of the HIV-1 genome may contribute to overall viral tropism and display sequence signatures associated with co-receptor utilization. RESULTS: The accessory protein Tat and the HlV-1 long terminal repeat (LTR) were analyzed with respect to genetic diversity and compared by Jensen-Shannon divergence which resulted in a correlation with both mean genetic diversity as well as the absolute difference in genetic diversity between R5- and X4-genome specific trends. As expected, the V3 domain of the gp120 protein was enriched with statistically divergent positions. Statistically divergent positions were also identified in Tat amino acid sequences within the transactivation and TAR-binding domains, and in nucleotide positions throughout the LTR. We further analyzed LTR sequences for putative transcription factor binding sites using the JASPAR transcription factor binding profile database and found several putative differences in transcription factor binding sites between R5 and X4 HIV-1 genomes, specifically identifying the C/EBP sites I and II, and Sp site III to differ with respect to sequence configuration for R5 and X4 LTRs. CONCLUSION: These observations support the hypothesis that co-receptor utilization coincides with specific genetic signatures in HIV-1 Tat and the LTR, likely due to differing transcriptional regulatory mechanisms and selective pressures applied within specific cellular targets during the course of productive HIV-1 infection.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.

Investigating the distribution of HIV-1 Tat lengths present in the Drexel Medicine CARES cohort.

Human immunodeficiency virus type 1 (HIV-1) encodes for Tat, a multi-functional regulatory protein involved in transcriptional enhancement and in causing neurotoxicity/central nervous system (CNS) dysfunction. This study examines Sanger sequencing of HIV-1 subtype B Tat from 2006 to 2014 within the Drexel University College of Medicine CNS AIDS Research and Eradication Study (CARES) Cohort to investigate Tat length in patients. The Los Alamos National Laboratory (LANL) database was used as a comparator. Miscoded stop codons were present in the CARES Cohort and LANL and protein variability was highly similar. Tat proteins in CARES and LANL were predominantly 101 residues. There was no observed correlation between Tat length and clinical parameters within the CARES Cohort. Unique Tat lengths found in the CARES Cohort and not in LANL were 31, 36, and 39 residues. When CARES patients were longitudinally examined, sequence lengths of 101 had a low probability of reducing to below 48, and sequences had a high probability of increasing to above 86 residues during their next visit, when below 48 residues in length. This suggests that Tat length is conserved to retain the majority of the proteins function highlighting its importance in viral replication.

Novel gRNA design pipeline to develop broad-spectrum CRISPR/Cas9 gRNAs for safe targeting of the HIV-1 quasispecies in patients.

The CRISPR/Cas9 system has been proposed as a cure strategy for HIV. However, few published guide RNAs (gRNAs) are predicted to cleave the majority of HIV-1 viral quasispecies (vQS) observed within and among patients. We report the design of a novel pipeline to identify gRNAs that target HIV across a large number of infected individuals. Next generation sequencing (NGS) of LTRs from 269 HIV-1-infected samples in the Drexel CARES Cohort was used to select gRNAs with predicted broad-spectrum activity. In silico, D-LTR-P4-227913 (package of the top 4 gRNAs) accounted for all detectable genetic variation within the vQS of the 269 samples and the Los Alamos National Laboratory HIV database. In silico secondary structure analyses from NGS indicated extensive TAR stem-loop malformations predicted to inactivate proviral transcription, which was confirmed by reduced viral gene expression in TZM-bl or P4R5 cells. Similarly, a high sensitivity in vitro CRISPR/Cas9 cleavage assay showed that the top-ranked gRNA was the most effective at cleaving patient-derived HIV-1 LTRs from five patients. Furthermore, the D-LTR-P4-227913 was predicted to cleave a median of 96.1% of patient-derived sequences from other HIV subtypes. These results demonstrate that the gRNAs possess broad-spectrum cutting activity and could contribute to an HIV cure.

Evidence of Divergent Amino Acid Usage in Comparative Analyses of R5- and X4-Associated HIV-1 Vpr Sequences.

Vpr is an HIV-1 accessory protein that plays numerous roles during viral replication, and some of which are cell type dependent. To test the hypothesis that HIV-1 tropism extends beyond the envelope into the vpr gene, studies were performed to identify the associations between coreceptor usage and Vpr variation in HIV-1-infected patients. Colinear HIV-1 Env-V3 and Vpr amino acid sequences were obtained from the LANL HIV-1 sequence database and from well-suppressed patients in the Drexel/Temple Medicine CNS AIDS Research and Eradication Study (CARES) Cohort. Genotypic classification of Env-V3 sequences as X4 (CXCR4-utilizing) or R5 (CCR5-utilizing) was used to group colinear Vpr sequences. To reveal the sequences associated with a specific coreceptor usage genotype, Vpr amino acid sequences were assessed for amino acid diversity and Jensen-Shannon divergence between the two groups. Five amino acid alphabets were used to comprehensively examine the impact of amino acid substitutions involving side chains with similar physiochemical properties. Positions 36, 37, 41, 89, and 96 of Vpr were characterized by statistically significant divergence across multiple alphabets when X4 and R5 sequence groups were compared. In addition, consensus amino acid switches were found at positions 37 and 41 in comparisons of the R5 and X4 sequence populations. These results suggest an evolutionary link between Vpr and gp120 in HIV-1-infected patients.

Bioinformatic analysis of HIV-1 entry and pathogenesis.

The evolution of human immunodeficiency virus type 1 (HIV-1) with respect to co-receptor utilization has been shown to be relevant to HIV-1 pathogenesis and disease. The CCR5-utilizing (R5) virus has been shown to be important in the very early stages of transmission and highly prevalent during asymptomatic infection and chronic disease. In addition, the R5 virus has been proposed to be involved in neuroinvasion and central nervous system (CNS) disease. In contrast, the CXCR4-utilizing (X4) virus is more prevalent during the course of disease progression and concurrent with the loss of CD4(+) T cells. The dual-tropic virus is able to utilize both co-receptors (CXCR4 and CCR5) and has been thought to represent an intermediate transitional virus that possesses properties of both X4 and R5 viruses that can be encountered at many stages of disease. The use of computational tools and bioinformatic approaches in the prediction of HIV-1 co-receptor usage has been growing in importance with respect to understanding HIV-1 pathogenesis and disease, developing diagnostic tools, and improving the efficacy of therapeutic strategies focused on blocking viral entry. Current strategies have enhanced the sensitivity, specificity, and reproducibility relative to the prediction of co-receptor use; however, these technologies need to be improved with respect to their efficient and accurate use across the HIV-1 subtypes. The most effective approach may center on the combined use of different algorithms involving sequences within and outside of the env-V3 loop. This review focuses on the HIV-1 entry process and on co-receptor utilization, including bioinformatic tools utilized in the prediction of co-receptor usage. It also provides novel preliminary analyses for enabling identification of linkages between amino acids in V3 with other components of the HIV-1 genome and demonstrates that these linkages are different between X4 and R5 viruses.