Person:

Gabuzda, Dana

Background: CCR5-restricted (R5) human immunodeficiency virus type 1 (HIV-1) variants cause CD4+ T-cell loss in the majority of individuals who progress to AIDS, but mechanisms underlying the pathogenicity of R5 strains are poorly understood. To better understand envelope glycoprotein (Env) determinants contributing to pathogenicity of R5 viruses, we characterized 37 full-length R5 Envs from cross-sectional and longitudinal R5 viruses isolated from blood of patients with asymptomatic infection or AIDS, referred to as pre-AIDS (PA) and AIDS (A) R5 Envs, respectively. Results: Compared to PA-R5 Envs, A-R5 Envs had enhanced fusogenicity in quantitative cell-cell fusion assays, and reduced sensitivity to inhibition by the fusion inhibitor T-20. Sequence analysis identified the presence of Asn 362 (N362), a potential N-linked glycosylation site immediately N-terminal to CD4-binding site (CD4bs) residues in the C3 region of gp120, more frequently in A-R5 Envs than PA-R5 Envs. N362 was associated with enhanced fusogenicity, faster entry kinetics, and increased sensitivity of Env-pseudotyped reporter viruses to neutralization by the CD4bs-directed Env mAb IgG1b12. Mutagenesis studies showed N362 contributes to enhanced fusogenicity of most A-R5 Envs. Molecular models indicate N362 is located adjacent to the CD4 binding loop of gp120, and suggest N362 may enhance fusogenicity by promoting greater exposure of the CD4bs and/or stabilizing the CD4-bound Env structure. Conclusion: Enhanced fusogenicity is a phenotype of the A-R5 Envs studied, which was associated with the presence of N362, enhanced HIV-1 entry kinetics and increased CD4bs exposure in gp120. N362 contributes to fusogenicity of R5 Envs in a strain dependent manner. Our studies suggest enhanced fusogenicity of A-R5 Envs may contribute to CD4+ T-cell loss in subjects who progress to AIDS whilst harbouring R5 HIV-1 variants. N362 may contribute to this effect in some individuals.

The identification of nucleotide sequence variations in viral pathogens linked to disease and clinical outcomes is important for developing vaccines and therapies. However, identifying these genetic variations in rapidly evolving pathogens adapting to selection pressures unique to each host presents several challenges. Machine learning tools provide new opportunities to address these challenges. In HIV infection, virus replicating within the brain causes HIV-associated dementia (HAD) and milder forms of neurocognitive impairment in 20–30% of patients with unsuppressed viremia. HIV neurotropism is primarily determined by the viral envelope (env) gene. To identify amino acid signatures in the HIV env gene predictive of HAD, we developed a machine learning pipeline using the PART rule-learning algorithm and C4.5 decision tree inducer to train a classifier on a meta-dataset (n = 860 env sequences from 78 patients: 40 HAD, 38 non-HAD). To increase the flexibility and biological relevance of our analysis, we included 4 numeric factors describing amino acid hydrophobicity, polarity, bulkiness, and charge, in addition to amino acid identities. The classifier had 75% predictive accuracy in leave-one-out cross-validation, and identified 5 signatures associated with HAD diagnosis (p<0.05, Fisher’s exact test). These HAD signatures were found in the majority of brain sequences from 8 of 10 HAD patients from an independent cohort. Additionally, 2 HAD signatures were validated against env sequences from CSF of a second independent cohort. This analysis provides insight into viral genetic determinants associated with HAD, and develops novel methods for applying machine learning tools to analyze the genetics of rapidly evolving pathogens.

Background: Human peripheral blood monocytes (Mo) consist of subsets distinguished by expression of CD16 (FCγRIII) and chemokine receptors. Classical CD16- Mo express CCR2 and migrate in response to CCL2, while a minor CD16+ Mo subset expresses CD16 and CX3CR1 and migrates into tissues expressing CX3CL1. CD16+ Mo produce pro-inflammatory cytokines and are expanded in certain inflammatory conditions including sepsis and HIV infection. Results: To gain insight into the developmental relationship and functions of CD16+ and CD16- Mo, we examined transcriptional profiles of these Mo subsets in peripheral blood from healthy individuals. Of 16,328 expressed genes, 2,759 genes were differentially expressed and 228 and 250 were >2-fold upregulated and downregulated, respectively, in CD16+ compared to CD16- Mo. CD16+ Mo were distinguished by upregulation of transcripts for dendritic cell (DC) (SIGLEC10, CD43, RARA) and macrophage (MΦ) (CSF1R/CD115, MafB, CD97, C3aR) markers together with transcripts relevant for DC-T cell interaction (CXCL16, ICAM-2, LFA-1), cell activation (LTB, TNFRSF8, LST1, IFITM1-3, HMOX1, SOD-1, WARS, MGLL), and negative regulation of the cell cycle (CDKN1C, MTSS1), whereas CD16- Mo were distinguished by upregulation of transcripts for myeloid (CD14, MNDA, TREM1, CD1d, C1qR/CD93) and granulocyte markers (FPR1, GCSFR/CD114, S100A8-9/12). Differential expression of CSF1R, CSF3R, C1QR1, C3AR1, CD1d, CD43, CXCL16, and CX3CR1 was confirmed by flow cytometry. Furthermore, increased expression of RARA and KLF2 transcripts in CD16+ Mo coincided with absence of cell surface cutaneous lymphocyte associated antigen (CLA) expression, indicating potential imprinting for non-skin homing. Conclusion: These results suggest that CD16+ and CD16- Mo originate from a common myeloid precursor, with CD16+ Mo having a more MΦ – and DC-like transcription program suggesting a more advanced stage of differentiation. Distinct transcriptional programs, together with their recruitment into tissues via different mechanisms, also suggest that CD16+ and CD16- Mo give rise to functionally distinct DC and MΦ in vivo.

We describe here a novel method for integrating gene and miRNA expression profiles in cancer using feed-forward loops (FFLs) consisting of transcription factors (TFs), miRNAs and their common target genes. The dChip-GemiNI (Gene and miRNA Network-based Integration) method statistically ranks computationally predicted FFLs by their explanatory power to account for differential gene and miRNA expression between two biological conditions such as normal and cancer. GemiNI integrates not only gene and miRNA expression data but also computationally derived information about TF–target gene and miRNA–mRNA interactions. Literature validation shows that the integrated modeling of expression data and FFLs better identifies cancer-related TFs and miRNAs compared to existing approaches. We have utilized GemiNI for analyzing six data sets of solid cancers (liver, kidney, prostate, lung and germ cell) and found that top-ranked FFLs account for ∼20% of transcriptome changes between normal and cancer. We have identified common FFL regulators across multiple cancer types, such as known FFLs consisting of MYC and miR-15/miR-17 families, and novel FFLs consisting of ARNT, CREB1 and their miRNA partners. The results and analysis web server are available at http://www.canevolve.org/dChip-GemiNi.

Background: HIV-1 Nef protein contributes to pathogenesis via multiple functions that include enhancement of viral replication and infectivity, alteration of intracellular trafficking, and modulation of cellular signaling pathways. Nef stimulates formation of tunneling nanotubes and virological synapses, and is transferred to bystander cells via these intercellular contacts and secreted microvesicles. Nef associates with and activates Pak2, a kinase that regulates T-cell signaling and actin cytoskeleton dynamics, but how Nef promotes nanotube formation is unknown. Results: To identify Nef binding partners involved in Pak2-association dependent Nef functions, we employed tandem mass spectrometry analysis of Nef immunocomplexes from Jurkat cells expressing wild-type Nef or Nef mutants defective for the ability to associate with Pak2 (F85L, F89H, H191F and A72P, A75P in NL4-3). We report that wild-type, but not mutant Nef, was associated with 5 components of the exocyst complex (EXOC1, EXOC2, EXOC3, EXOC4, and EXOC6), an octameric complex that tethers vesicles at the plasma membrane, regulates polarized exocytosis, and recruits membranes and proteins required for nanotube formation. Additionally, Pak2 kinase was associated exclusively with wild-type Nef. Association of EXOC1, EXOC2, EXOC3, and EXOC4 with wild-type, but not mutant Nef, was verified by co-immunoprecipitation assays in Jurkat cells. Furthermore, shRNA-mediated depletion of EXOC2 in Jurkat cells abrogated Nef-mediated enhancement of nanotube formation. Using bioinformatic tools, we visualized protein interaction networks that reveal functional linkages between Nef, the exocyst complex, and the cellular endocytic and exocytic trafficking machinery. Conclusions: Exocyst complex proteins are likely a key effector of Nef-mediated enhancement of nanotube formation, and possibly microvesicle secretion. Linkages revealed between Nef and the exocyst complex suggest a new paradigm of exocyst involvement in polarized targeting for intercellular transfer of viral proteins and viruses.

In efforts to develop an effective vaccine, sterilizing immunity to primate lentiviruses has only been achieved by the use of live attenuated viruses carrying major deletions in nef and other accessory genes. Although live attenuated HIV vaccines are unlikely to be developed due to a myriad of safety concerns, opportunities exist to better understand the correlates of immune protection against HIV infection by studying rare cohorts of long-term survivors infected with attenuated, nef-deleted HIV strains such as the Sydney blood bank cohort (SBBC). Here, we review studies of viral evolution, pathogenicity, and immune responses to HIV infection in SBBC members. The studies show that potent, broadly neutralizing anti-HIV antibodies and robust CD8+ T-cell responses to HIV infection were not necessary for long-term control of HIV infection in a subset of SBBC members, and were not sufficient to prevent HIV sequence evolution, augmentation of pathogenicity and eventual progression of HIV infection in another subset. However, a persistent T-helper proliferative response to HIV p24 antigen was associated with long-term control of infection. Together, these results underscore the importance of the host in the eventual outcome of infection. Thus, whilst generating an effective antibody and CD8+ T-cell response are an essential component of vaccines aimed at preventing primary HIV infection, T-helper responses may be important in the generation of an effective therapeutic vaccine aimed at blunting chronic HIV infection.

Background: The population of HIV replicating within a host consists of independently evolving and interacting sub-populations that can be genetically distinct within anatomical compartments. HIV replicating within the brain causes neurocognitive disorders in up to 20-30% of infected individuals and is a viral sanctuary site for the development of drug resistance. The primary determinant of HIV neurotropism is macrophage tropism, which is primarily determined by the viral envelope (env) gene. However, studies of genetic aspects of HIV replicating in the brain are hindered because existing repositories of HIV sequences are not focused on neurotropic virus nor annotated with neurocognitive and neuropathological status. To address this need, we constructed the HIV Brain Sequence Database. Results: The HIV Brain Sequence Database is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i) brain, brainstem, and spinal cord; (ii) meninges, choroid plexus, and CSF; (iii) blood and lymphoid; and (iv) other (bone marrow, colon, lung, liver, etc). Patient coding is correlated across studies, allowing sequences from the same patient to be grouped to increase statistical power. Using Cytoscape, we visualized relationships between studies, patients and sequences, illustrating interconnections between studies and the varying depth of sequencing, patient number, and tissue representation across studies. Currently, the database contains 2517 envelope sequences from 90 patients, obtained from 22 published studies. 1272 sequences are from brain; the remaining 1245 are from blood, lymph node, spleen, bone marrow, colon, lung and other non-brain tissues. The database interface utilizes a faceted interface, allowing real-time combination of multiple search parameters to assemble a meta-dataset, which can be downloaded for further analysis. Conclusions: This online resource, which is publicly available at http://www.HIVBrainSeqDB.org, will greatly facilitate analysis of the genetic aspects of HIV macrophage tropism, HIV compartmentalization and evolution within the brain and other tissue reservoirs, and the relationship of these findings to HIV-associated neurological disorders and other clinical consequences of HIV infection.

Background: Breakdown of the gut mucosal barrier during chronic HIV infection allows translocation of bacterial products such as lipopolysaccharides (LPS) from the gut into the circulation. Microbial translocation also occurs in inflammatory bowel disease (IBD). IBD serological markers are useful in the diagnosis of IBD and to differentiate between Crohn's disease (CD) and ulcerative colitis (UC). Here, we evaluate detection of IBD serological markers in HIV-infected patients with advanced disease and their relationship to HIV disease markers.Methods IBD serological markers (ASCA, pANCA, anti-OmpC, and anti-CBir1) were measured by ELISA in plasma from AIDS patients (n = 26) with low CD4 counts (<300 cells/(\mu)l) and high plasma LPS levels, and results correlated with clinical data. For meta-analysis, relevant data were abstracted from 20 articles. Results: IBD serological markers were detected in approximately 65% of AIDS patients with evidence of microbial translocation. An antibody pattern consistent with IBD was detected in 46%; of these, 75% had a CD-like pattern. Meta-analysis of data from 20 published studies on IBD serological markers in CD, UC, and non-IBD control subjects indicated that IBD serological markers are detected more frequently in AIDS patients than in non-IBD disease controls and healthy controls, but less frequently than in CD patients. There was no association between IBD serological markers and HIV disease markers (plasma viral load and CD4 counts) in the study cohort. Conclusions: IBD serological markers may provide a non-invasive approach to monitor HIV-related inflammatory gut disease. Further studies to investigate their clinical significance in HIV-infected individuals are warranted.

Background: The Sydney blood bank cohort (SBBC) of long-term survivors consists of multiple individuals infected with attenuated, nef-deleted variants of human immunodeficiency virus type 1 (HIV-1) acquired from a single source. Long-term prospective studies have demonstrated that the SBBC now comprises slow progressors (SP) as well as long-term nonprogressors (LTNP). Convergent evolution of nef sequences in SBBC SP and LTNP indicates the in vivo pathogenicity of HIV-1 in SBBC members is dictated by factors other than nef. To better understand mechanisms underlying the pathogenicity of nef-deleted HIV-1, we examined the phenotype and env sequence diversity of sequentially isolated viruses (n = 2) from 3 SBBC members. Results: The viruses characterized here were isolated from two SP spanning a three or six year period during progressive HIV-1 infection (subjects D36 and C98, respectively) and from a LTNP spanning a two year period during asymptomatic, nonprogressive infection (subject C18). Both isolates from D36 were R5X4 phenotype and, compared to control HIV-1 strains, replicated to low levels in peripheral blood mononuclear cells (PBMC). In contrast, both isolates from C98 and C18 were CCR5-restricted. Both viruses isolated from C98 replicated to barely detectable levels in PBMC, whereas both viruses isolated from C18 replicated to low levels, similar to those isolated from D36. Analysis of env by V1V2 and V3 heteroduplex tracking assay, V1V2 length polymorphisms, sequencing and phylogenetic analysis showed distinct intra- and inter-patient env evolution. Conclusion: Independent evolution of env despite convergent evolution of nef may contribute to the in vivo pathogenicity of nef-deleted HIV-1 in SBBC members, which may not necessarily be associated with changes in replication capacity or viral coreceptor specificity.

Background: Immune activation is a strong predictor of disease progression in HIV infection. Combinatorial plasma biomarker signatures that represent surrogate markers of immune activation in both viremic and aviremic HIV patients on combination antiretroviral therapy (cART) have not been defined. Here, we identify a plasma inflammatory biomarker signature that distinguishes between both viremic and aviremic HIV patients on cART and healthy controls and examine relationships of this signature to markers of disease progression. Methods: Multiplex profiling and ELISA were used to detect 15 cytokines/chemokines, soluble IL-2R (sIL-2R), and soluble CD14 (sCD14) in plasma from 57 HIV patients with CD4 nadir <300 cells/(\mu)l and 29 healthy controls. Supervised and unsupervised analyses were used to identify biomarkers explaining variance between groups defined by HIV status or drug abuse. Relationships between biomarkers and disease markers were examined by Spearman correlation. Results: The majority (91%) of HIV subjects were on cART, with 38% having undetectable viral loads (VL). Hierarchical clustering identified a biomarker cluster in plasma consisting of two interferon-stimulated gene products (CXCL9 and CXCL10), T cell activation marker (sIL-2R), and monocyte activation marker (sCD14) that distinguished both viremic and aviremic HIV patients on cART from controls (p<0.0001) and were top-ranked in variables important in projection plots. IL-12 and CCL4 were also elevated in viremic and aviremic patients compared to controls (p<0.05). IL-12 correlated with IFN(\alpha), IFN(\gamma), CXCL9, and sIL-2R (p<0.05). CXCL10 correlated positively with plasma VL and percentage of CD16+ monocytes, and inversely with CD4 count (p = 0.001, <0.0001, and 0.04, respectively). Conclusion: A plasma inflammatory biomarker signature consisting of CXCL9, CXCL10, sIL-2R, and sCD14 may be useful as a surrogate marker to monitor immune activation in both viremic and aviremic HIV patients on cART during disease progression and therapeutic responses.