IL-17 Production from T Helper 17, Mucosal-Associated Invariant T, and γδ Cells in Tuberculosis Infection and Disease

Abstract

IL-17-producing cells have been shown to be important in the early stages of Mycobacterium tuberculosis (Mtb) infection in animal models. However, there are very little data on the role of IL-17 in human studies of tuberculosis (TB). We recruited TB patients and their highly exposed contacts who were further categorized based on results from an IFN-γ-release assay (IGRA): (1) IGRA positive (IGRA+) at recruitment (latently TB infected), (2) IGRA negative (IGRA−) at recruitment and 6 months [non-converters (NC)], and (3) IGRA− at recruitment and IGRA+ at 6 months (converters). Whole blood was stimulated with mycobacterial antigens and analyzed using T helper (Th) 17 multiplex cytokine assays. Th17, Vγ9Vδ2+, and CD161++Vα7.2+ mucosal-associated invariant T (MAIT) cells were analyzed by flow cytometry. The majority of IL-17 was produced by CD26+CD4+ Th17 cells (median 71%) followed by γδ T cells (6.4%) and MAIT cells (5.8%). TB patients had a significantly lower proportion of Th17 cells and CD4+CD161+Vα7.2+ cells producing both IL-17 and IFN-γ compared to LTBI subjects. IGRA NC had significantly lower levels of CD26−CD4+ and CD8+ MAIT cells producing IL-17 compared to IGRA C but had significantly higher levels of IL-17A, IL-17F, IL-21, and IL-23 in ESAT-6/CFP-10-stimulated supernatants compared to IGRA C. These data provide new insights into the role of IL-17 and IL-17-producing cells at three key stages of the Mtb infection spectrum.

Analysis of immunological resistance to primary Mycobacterium tuberculosis infection in humans

“…We have characterised host transcriptomic and antibody responses to Mtb in TST non-converters and converters prior to any signs of infection as determined by current methods. We have previously shown higher levels of soluble IL-17 in non-converters at baseline [12] suggesting they have encountered Mtb and mounted an immune response and are not simply anergic to antigens in the current tests nor is Mtb blocked by physiological barriers. In this study we saw a distinct B It was interesting to see the distinct gene signatures present when infection was defined by QFT rather than TST.…”

Analysis of cellular and soluble profiles in QuantiFERON nonconverters, converters, and reverters in the Gambia

“…IL-17A is associated with Th17 responses with a previous study from our laboratory showing contrasting findings (ie, increased IL-17A in TBR). 22 This difference may be due to the techniques used to classify the groups. In the initial study, an in-house enzymelinked immunosorbent assay (ELISA) was used with only ESAT-6/CFP-10 peptides, whereas the present study used commercial QFT Gold-In Tube, which includes additional peptides of TB7.7.…”

Multimodal memory T cell profiling identifies a reduction in a polyfunctional Th17 state associated with tuberculosis progression

“…Studies examining immunophenotypes in active TB have identified numerous memory T cell changes, including in the CD4+ 12 , activated 13 , exhausted 14-16 , Th1 17,18 , and IL-17+ compartments [19][20][21][22][23] . However, these studies typically profiled patients during ongoing infection and focused on antigen-specific T cells, rather than broad, intrinsic differences in memory T cell composition outside of acute infection or active disease.…”

“…Disease progression is influenced by host immune and genetic factors that implicate T cells, which are major contributors to defense against intracellular pathogens 3-11 . These markedly different outcomes of infection raise the question of whether steady-state differences in T cell composition underlie divergent host response to M.tb.Studies examining immunophenotypes in active TB have identified numerous memory T cell changes, including in the CD4+ 12 , activated 13 , exhausted 14-16 , Th1 17,18 , and IL-17+ compartments [19][20][21][22][23] . However, these studies typically profiled patients during ongoing infection and focused on antigen-specific T cells, rather than broad, intrinsic differences in memory T cell composition outside of acute infection or active disease.Moreover, it is challenging to acquire an adequate sample size, account for confounders influencing T cell composition 24 , and overcome limitations of surface marker or bulk RNA-seq-based technologies that only capture certain cell state changes.Here, we profiled total memory T cells at single-cell resolution from patients more than four years after TB disease in order to identify broad steady-state differences in progressors with minimal interference from acute immune response.…”