In Vivo Molecular Dissection of the Effects of HIV-1 in Active Tuberculosis

Abstract

Increased risk of tuberculosis (TB) associated with HIV-1 infection is primarily attributed to deficient T helper (Th)1 immune responses, but most people with active TB have robust Th1 responses, indicating that these are not sufficient to protect against disease. Recent findings suggest that favourable outcomes following Mycobacterium tuberculosis infection arise from finely balanced inflammatory and regulatory pathways, achieving pathogen control without immunopathology. We hypothesised that HIV-1 and antiretroviral therapy (ART) exert widespread changes to cell mediated immunity, which may compromise the optimal host protective response to TB and provide novel insights into the correlates of immune protection and pathogenesis. We sought to define these effects in patients with active TB by transcriptional profiling of tuberculin skin tests (TST) to make comprehensive molecular level assessments of in vivo human immune responses at the site of a standardised mycobacterial challenge. We showed that the TST transcriptome accurately reflects the molecular pathology at the site of human pulmonary TB, and used this approach to investigate immune dysregulation in HIV-1/TB co-infected patients with distinct clinical phenotypes associated with TST reactivity or anergy and unmasking TB immune reconstitution inflammatory syndrome (IRIS) after initiation of ART. HIV-1 infected patients with positive TSTs exhibited preserved Th1 responses but deficient immunoregulatory IL10-inducible responses. Those with clinically negative TSTs revealed profound anergy of innate as well as adaptive immune responses, except for preservation of type 1 interferon activity, implicated in impaired anti-mycobacterial immunity. Patients with unmasking TB IRIS showed recovery of Th1 immunity to normal levels, but exaggerated Th2-associated responses specifically. These mechanisms of immune dysregulation were localised to the tissue microenvironment and not evident in peripheral blood. TST molecular profiling categorised different mechanisms of immunological dysfunction in HIV-1 infection beyond the effects on CD4 T cells, each associated with increased risk of TB disease and amenable to host-directed therapies.

Validation of Immune Cell Modules in Multicellular Transcriptomic Data

“…Modules have been mostly used to describe relative cell and pathway enrichment in whole blood or peripheral blood mononuclear cells (PBMC) [8,9]. We previously identified transcriptional modules which could decipher cell and innate immune response enrichment from human skin [11]. In the current manuscript we extend these observations further, demonstrating their applicability across a range of human tissue types.…”

“…First, by identifying transcripts with >2-fold increased expression in the cell of interest compared to all other cells common across multiple datasets from purified cells. Second, by using validated cell type specific ‘markers’ as baits to identify co-correlated genes and assemble modules with the genes that were common to all the co-correlated lists in multiple data sets [11]. These modules are listed in S3 Table.…”

“…We interpret this to mean that the best performing modules represent core transcriptional programs independent of differential cellular activation states. Although we and others have described cytokine and innate immune stimulus specific gene expression modules to represent functional biological activity beyond cellular composition [11,25,26], comprehensive data from which to derive transcriptional modules representing cell-type specific activation states are not presently available, and may well require multiparametric flow cytometry to resolve accurately. Likewise, transcriptional data to discriminate between closely related cell subsets, such as CD4 and CD8 naïve or memory T cells are the focus for future work.…”

“…This approach reduces noise from individual constituent genes whilst allowing comparative assessments between samples [5,6]. Modules have been used successfully to reveal relative enrichment of immune cell types in blood transcriptomic datasets [4,7–9], as well as confirming cellular infiltration in tissue inflammation, such as the site of the tuberculin skin test (TST) [10,11]. …”

“…These include manually curated lists of genes [10], identification of genes which are differentially expressed between purified cell types [12,13], semi-supervised approaches that identify genes co-correlated with putative cell markers [11] and entirely unsupervised network analyses of purified cell types [14] or peripheral blood samples [4]. Consequently, there are now many published modules that share similar cellular annotations [4,12–14] but may vary in their constituent genes.…”