Project Details
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Human intestinal innate lymphoid cells (ILCs): signatures and polarization signals

Subject Area Gastroenterology
Term from 2016 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 289483678
 
Final Report Year 2019

Final Report Abstract

The immune system responds to pathogen infection by employing distinct effector modules, namely type 1 (Interferon-γ, IFN-γ), type 2 (Interleukin-, IL-4, IL-5 and IL-13) and type 3 (IL-17, IL- 22), which are tailored to eliminate the different infectious agents. This heterogeneity of effector programs has been extensively characterized among CD4+ T helper (Th) cells which can be accordingly dissected in three main subsets, namely Th1, Th2 and Th17 cells. In T cells, such effector programs are induced by activation via T cell receptor (TCR) together with distinct cytokines and/or environmental signals. It is now evident that an emerging family of innate lymphocytes collectively known as innate lymphoid cells (ILCs), exhibit an analogous heterogeneity of effector programs as described for T cells. The ILC family comprises of three main groups of cells: group 1 ILCs (including cytotoxic Natural Killer (NK) cells, ILC2 producing IL-13/IL-5 and ILC3 secreting IL-22/IL-17. ILC effector programs can be activated both after pathogen infection as well as in the course of inflammatory disorders, similar to what has been described for T cells. However, although displaying partially overlapping effector programs, ILCs do not rely on the TCR to display effector functions. Conversely, they rapidly react to cytokines and likely to stress-induced or pathogen-derived ligands. As ILCs can play an important role in inducing and modulating chronic inflammatory diseases, a deeper knowledge of how, where and when during differentiation do ILCs acquire their effector programs is crucial for a better understanding of the pathogenesis of inflammatory disorders. However, the signals responsible for the differentiation toward different ILC subset fate and for the execution of the correspondent effector programs remain largely unclear. To fill this gap, in this project we have established a system in which to generate individual ILC subsets reliably, of which complexity goes beyond cytokine secretion, and which bypasses the limitations of tissue residency and idiosyncrasies which hinder ILC isolation and clinical use. Similar to the T cell generation systems of the 90s, having such a resource precludes the leaps and bounds of advances in the field, and can aid in clarifying and unifying ILC semantics. A thorough description of the cells and flexibility of the system enables not only the study of progenitor pathways and lineage making decisions, but also allows for sufficient numbers of human ILCs to target in functionality analyses, to pave the road for preclinical human ILC adoptive transfer studies. Moreover, we have identified major signals driving the activation and execution of effector functions in a subset of ILCs. In particular, we have shown that NKG2C+ NK cells differentially recognize peptides derived from distinct strains of Cytomegalovirus. These data revealed a previously unrecognized peptide-specificity of a subset of ILCs, highlighting the different recognition strategies employed by innate lymphocytes to trigger effector functions. These data have been published, discussed in the context of other data in several review articles written upon invitation and well-received in the field. We believe our data have contributed to deepen our understanding of ILC biology and to the identification of novel targets to strengthen anti-viral and anti-tumor responses and to modulate inflammatory disorders.

Publications

  • About Training and Memory: NK-Cell Adaptation to Viral Infections. Adv Immunol. 2017;133:171-207
    Hammer Q, Romagnani C
    (See online at https://doi.org/10.1016/bs.ai.2016.10.001)
  • OMIP-039: Detection and analysis of human adaptive NKG2C+ natural killer cells. Cytometry A. 2017 Oct;91(10):997-1000
    Hammer Q, Romagnani C
    (See online at https://doi.org/10.1002/cyto.a.23168)
  • Adaptive Natural Killer Cells Integrate Interleukin-18 during Target-Cell Encounter. Front Immunol. 2018 Jan 17;8:1976
    Hammer Q, Rückert T, Dunst J, Romagnani C
    (See online at https://doi.org/10.3389/fimmu.2017.01976)
  • CD96 expression determines the inflammatory potential of IL-9-producing Th9 cells. Proc Natl Acad Sci USA. 2018 Mar 27;115(13):E2940-E2949
    Stanko K, Iwert C, Appelt C, Vogt K, Schumann J, Strunk FJ, Ahrlich S, Schlickeiser S, Romagnani C, Jürchott K, Meisel C, Willimsky G, Kühl AA, Sawitzki B
    (See online at https://doi.org/10.1073/pnas.1708329115)
  • Clonal expansion and compartmentalized maintenance of rhesus macaque NK cell subsets. Sci Immunol. 2018 Nov 2;3(29)
    Wu C, Espinoza DA, Koelle SJ, Yang D, Truitt L, Schlums H, Lafont BA, Davidson-Moncada JK, Lu R, Kaur A, Hammer Q, Li B, Panch S, Allan DA, Donahue RE, Childs RW, Romagnani C, Bryceson YT, Dunbar CE
    (See online at https://doi.org/10.1126/sciimmunol.aat9781)
  • Innate lymphoid cells in lung infection and immunity. Immunol Rev. 2018 Nov;286(1):102-119
    Stehle C, Hernández DC, Romagnani C
    (See online at https://doi.org/10.1111/imr.12712)
  • Natural killer cell specificity for viral infections. Nat Immunol. 2018 Aug;19(8):800-808
    Hammer Q, Rückert T, Romagnani C
    (See online at https://doi.org/10.1038/s41590-018-0163-6)
  • Peptide-specific recognition of human cytomegalovirus strains controls adaptive natural killer cells. Nat Immunol. 2018 May;19(5):453-463
    Hammer Q, Rückert T, Borst EM, Dunst J, Haubner A, Durek P, Heinrich F, Gasparoni G, Babic M, Tomic A, Pietra G, Nienen M, Blau IW, Hofmann J, Na IK, Prinz I, Koenecke C, Hemmati P, Babel N, Arnold R, Walter J, Thurley K, Mashreghi MF, Messerle M, Romagnani C
    (See online at https://doi.org/10.1038/s41590-018-0082-6)
  • The Role of Natural Killer Group 2, Member D in Chronic Inflammation and Autoimmunity. Front Immunol. 2018 May 30;9:1219
    Babic M, Romagnani C
    (See online at https://doi.org/10.3389/fimmu.2018.01219)
 
 

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