Dataset Information

Reconstructing the temporal progression of HIV-1 immune response pathways.

ABSTRACT:

Motivation

Most methods for reconstructing response networks from high throughput data generate static models which cannot distinguish between early and late response stages.

Results

We present TimePath, a new method that integrates time series and static datasets to reconstruct dynamic models of host response to stimulus. TimePath uses an Integer Programming formulation to select a subset of pathways that, together, explain the observed dynamic responses. Applying TimePath to study human response to HIV-1 led to accurate reconstruction of several known regulatory and signaling pathways and to novel mechanistic insights. We experimentally validated several of TimePaths' predictions highlighting the usefulness of temporal models.

Availability and implementation

Data, Supplementary text and the TimePath software are available from http://sb.cs.cmu.edu/timepath

Contact

zivbj@cs.cmu.edu

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Jain S

PROVIDER: S-EPMC4908338 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Publications

Reconstructing the temporal progression of HIV-1 immune response pathways.

Jain Siddhartha S Arrais Joel J Venkatachari Narasimhan J NJ Ayyavoo Velpandi V Bar-Joseph Ziv Z

Bioinformatics (Oxford, England) 20160601 12

<h4>Motivation</h4>Most methods for reconstructing response networks from high throughput data generate static models which cannot distinguish between early and late response stages.<h4>Results</h4>We present TimePath, a new method that integrates time series and static datasets to reconstruct dynamic models of host response to stimulus. TimePath uses an Integer Programming formulation to select a subset of pathways that, together, explain the observed dynamic responses. Applying TimePath to stu ...[more]

PMID: 27307624

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Project description:BackgroundThe relationship between host microRNAs (miRNA), viral control and immune response has not yet been elucidated in the field of HIV. The aim of this study was to assess the differential miRNA profile in CD8+ T-cells between HIV-infected individuals who differ in terms of viral replication control and immune response.MethodsmiRNA profile from resting and CD3/CD28-stimulated CD8+ T-cells from uninfected individuals (HIV-, n = 11), Elite Controllers (EC, n = 15), Viremic Controllers (VC, n = 15), Viremic Progressors (VP, n = 13) and HIV-infected patients on therapy (ART, n = 14) was assessed using Affymetrix miRNA 3.1 arrays. After background correction, quantile normalization and median polish summarization, normalized data were fit to a linear model. The analysis comprised: resting samples between groups; stimulated samples between groups; and stimulated versus resting samples within each group. Enrichment analyses of the putative target genes were perfomed using bioinformatic algorithms.ResultsA downregulated miRNA pattern was observed when resting samples from all infected groups were compared to HIV-. A miRNA downregulation was also observed when stimulated samples from EC, ART and HIV- groups were compared to VP, being hsa-miR-4492 the most downregulated. Although a preferential miRNA downregulation was observed when stimulated samples were compared to the respective resting samples, VP presented a differential miRNA expression pattern. In fact, hsa-miR-155 and hsa-miR-181a were downregulated in VP whereas in the other groups, either an upregulation or no differences were observed after stimulation, respectively. Overall, functional enrichment analysis revealed that the predicted target genes were involved in signal transduction pathways, metabolic regulation, apoptosis, and immune response.ConclusionsResting CD8+ T-cells do not exhibit a differential miRNA expression between HIV-infected individuals but they do differ from non-infected individuals. Moreover, a specific miRNA pattern is present in stimulated CD8+ T-cells from VP which could reflect a detrimental pattern in terms of CD8+ T-cell immune response.

Project description:BackgroundIn HIV discordant couples (one parther is HIV-infected, another is HIV-uninfected) HIV-negative partners often remain uninfected for a long time despite long, stable, often unprotected sexual contacts with HIV-infected partner. The increase of time of living together accompanying the decrease of the incidence of HIV infection in HIV-negative partner. The features of HIV-specific immune response in HIV discorgant couples was investigated.MethodsThirty-three HIV discordant couples from Moscow region living together <1 year (2 couples), 1 to 3 years (18 couples), 4 to 5 years (9 couples), 6 to 10 years (4 couples) were included in the investigation. Sera of 33 HIV-uninfected partners from HIV discordant couples (17 men and 16 women) were tested for HIV-specific antibodies by enzyme immunoassay and immunoblot. Viral load was estimated by polymerase chain reaction (PCR).ResultsAntibodies against HIV gp160 were detected in 3 persons (9,1%), against p68/66—in 3 persons (9,1%), against p52/51—in 3 persons (9,1%), against g34/31—in 3 persons (9,1%); total—in 6 persons (18,2%). All of them were defined as HIV-uninfected by PCR. In 4 of 6 persons HIV-specific antibodies were not detected after finishing of risk behavior.ConclusionsIt is possible to suggest that detected antibodies against HIV gp160, p68/66, p52/51, p34/31 in HIV-uninfected people are caused by contact with HIV (according to literature data, non-specific stimulation may cause the appearance of antibodies binding the other HIV antigens: p55, p24/25 and g18) and may contribute to maintainance of HIV-negative status of uninfected partners in HIV-discordant couples. The cohort of high exposed but HIV-uninfected people was formed during immunological monitoring of HIV discordant couples in Moscow region. This cohort is available for systematic observation and is perspective for further investigation of mechanisms of resistance to HIV infection and correlates of immune protection. Now the cohort is expanded.

Dataset Information

Reconstructing the temporal progression of HIV-1 immune response pathways.

Motivation

Results

Availability and implementation

Contact

Supplementary information

Publications

Reconstructing the temporal progression of HIV-1 immune response pathways.

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