Messengers from the microbiota

doi:10.1126/science.abe0709

GSTDTAP > 气候变化

DOI	10.1126/science.abe0709
	Messengers from the microbiota
	Fyza Y. Shaikh; Cynthia L. Sears
	2020-09-18
发表期刊	Science
出版年	2020
英文摘要	Immunotherapy sometimes leads to stunning therapeutic success in a wide range of cancers. However—except in melanoma, microsatellite instable (MSI) colorectal cancer, Hodgkin's lymphoma, and Merkel cell carcinoma—only ∼15 to 30% of cancer patients respond to treatment. Thus, identification of the determinants of response are under intense investigation, and the gut microbiota is proposed to be a critical determinant for immunotherapy responses. On page 1481 of this issue, Mager et al. ([ 1 ][1]) show that inosine produced by specific gut bacteria, Bifidobacterium pseudolongum or Akkermansia muciniphila , enhances immune checkpoint inhibitor (ICI; a type of immunotherapy) efficacy in numerous mouse models. They propose that impaired gut barrier function from ICI treatment facilitates inosine systemic translocation, resulting in adenosine 2A receptor (A2AR)–dependent activation of T helper 1 (TH1) antitumor effector cells that yield tumor shrinkage. These intriguing data provide a potential framework to directly link microbe-induced metabolite synthesis and ICI therapeutic efficacy. Step-by-step examples of a microbiota, metabolite, immune effector, tumor response (or nonresponse) cascade in humans do not yet exist. However, the complexity presented by the hundreds to thousands of human gut bacteria may be reduced by enhancing the understanding of the biosynthetic metabolite redundancy among bacterial species ([ 2 ][2]). Accruing experimental and human data linking bacterial metabolites to human physiology and disease are encouraging. For example, studies of the interactions of bacterial metabolites and human G protein–coupled receptors (GPCRs), a critical receptor class that mediates drug action, suggest that multiple simple bacterial metabolites, produced by more than one bacterial species, are GPCR agonists and affect immune and neurologic function ([ 3 ][3], [ 4 ][4]). Furthermore, molecular approaches to modify bacterial genomes, such as CRISPR-Cas9–based gene deletion, enable characterization of how single molecules produced by specific bacteria affect host function. For example, using this approach, analysis of a Clostridium sporogenes mutant deficient in the production of branched short chain fatty acids (SCFAs) revealed a previously unknown capacity for branched SCFAs to regulate the numbers of immunoglobulin A (IgA)–producing plasma cells in the small intestine ([ 5 ][5]). Fermentation of dietary fiber by the gut microbiota produces SCFAs (acetate, propionate, and butyrate). SCFAs are the most abundant microbial metabolites in the gut that act through gut mucosal GPCRs (GPCRs 41, 43, and 109A) and are known for their critical role in colon homeostasis. SCFAs regulate the phenotype and/or function of macrophages, neutrophils, dendritic cells, and CD4+ T cells [especially regulatory T cells (Treg cells)] and have recently been found to promote CD8+ T effector function and memory potential ([ 6 ][6], [ 7 ][7]). Early translational studies in cancer patients suggest that SCFAs limit anti–CTLA-4 (cytotoxic T lymphocyte–associated antigen 4) ICI responses but promote anti–PD-1 (programmed cell death protein 1) ICI responses ([ 8 ][8], [ 9 ][9]). ICIs block inhibitory immune cell and tumor molecules to unleash an antitumor immune response. ICIs, particularly anti–CTLA-4, likely alter intestinal barrier function in humans. Altered barrier function is associated with microbiota disruption (dysbiosis) that contributes to acute colitis, inflammatory bowel diseases, as well as colorectal cancer. Thus, better understanding of the effect of ICIs on the gut microbiota, its metabolic capacity, and metabolite-mediated downstream effects on colon mucosal immunity and tumor immune responses is needed. It is clear that untangling which gut microbiota species and metabolites, singly or together, modify human disease and therapeutic outcomes is a difficult challenge. Inosine is another key metabolite produced by the gut bacteria. This endogenous purine nucleoside is formed by deamination of adenosine. Prior data support an immunosuppressive role for inosine, which activates A2AR signaling to limit inflammation, block TH1 cell differentiation, promote Treg cell activity, and thus inhibit tumor immunity in vivo. A2AR is also a GPCR and a target for drug development. Pharmacologic antagonists of A2AR enhance antitumor immunity in multiple mouse models and are currently in oncology clinical trials. Conversely, inosine supplementation was recently reported to enhance the antitumor efficacy of ICI therapy and adoptive T cell transfer in preclinical mouse models, but only in models that used tumor cells unable to catabolize inosine to support cell growth ([ 10 ][10]). These data suggest that, at least in some circumstances, inosine can relieve tumor-imposed metabolic restrictions on T cells. ![Figure][11] Microbial signaling Diet and medications yield microbiota that produce metabolites such as inosine or short chain fatty acids (SCFAs), which regulate mucosal and systemic immune cells. Inosine acts in the tumor microenvironment, through activation of adenosine 2A receptor (A2AR) signaling in T helper 1 (TH1) cells and regulates antitumor immunity in a context-dependent manner. GRAPHIC: C. BICKEL/ SCIENCE Mager et al. build on this theme by showing with in vitro assays that inosine displays context-dependent actions (see the figure). Inosine boosted or inhibited TH1 differentiation of naïve T cells in the presence or absence, respectively, of exogenous interferon-γ. Prior work similarly identified highly context-dependent, oncogenic Treg cell action ([ 11 ][12]). Collectively, these data highlight that “company matters” in the highly pleomorphic and ever-expanding characterization of immune cell function, especially within the tumor microenvironment. Whether context-dependent inosine action is relevant to human TH1 cell differentiation or effector cell biology and/or affects current human cancer therapy trials of A2AR antagonists deserves scrutiny. Further analysis of microbial, serum, and immune cell samples from patients undergoing ICI treatment will clarify the impact of the observations by Mager et al. Despite the exciting explosion of microbiota studies over the past 15 years, pinning down which microbial members or mediators are validated biomarkers for human disease prognosis or therapeutic response, has been elusive. Encouragingly, microbiota-based therapeutics are emerging for the treatment of Clostridioides difficile infection ([ 12 ][13]). Although the highly positive causal findings in microbiota studies in mice are thrilling, perhaps implausibly so, these results contrast sharply with diverse and inconsistent findings in microbiota human studies to date. Diet and drug exposure (antibiotics and nonantibiotics) ([ 13 ][14]), both recent and distant ([ 14 ][15], [ 15 ][16]), seem to modify microbiota-linked human disease outcomes, yet these factors are rarely included as prospectively collected variables in human study analyses. These gaps in outcomes emphasize that to harness the putative power of the microbiota for therapeutic success, well-designed, well-powered human studies tied to translational laboratory studies are needed to define circumstances that are addressable with microbiota-based treatments. 1. [↵][17]1. L. F. Mager et al ., Science 369, 1481 (2020). [OpenUrl][18][Abstract/FREE Full Text][19] 2. [↵][20]1. P. C. Dorrestein, 2. S. K. Mazmanian, 3. R. Knight , Immunity 40, 824 (2014). [OpenUrl][21][CrossRef][22][PubMed][23] 3. [↵][24]1. H. Chen et al ., Cell 177, 1217 (2019). [OpenUrl][25] 4. [↵][26]1. D. A. Colosimo et al ., Cell Host Microbe 26, 273 (2019). [OpenUrl][27] 5. [↵][28]1. C.-J. Guo et al ., Science 366, eaav1282 (2019). [OpenUrl][29][Abstract/FREE Full Text][30] 6. [↵][31]1. M. Luu et al ., Sci. Rep. 8, 14430 (2018). [OpenUrl][32] 7. [↵][33]1. A. Bachem et al ., Immunity 51, 285 (2019). [OpenUrl][34][PubMed][35] 8. [↵][36]1. C. Coutzac et al ., Nat. Commun. 11, 2168 (2020). [OpenUrl][37] 9. [↵][38]1. M. Nomura et al ., JAMA Netw. Open 3, e202895 (2020). [OpenUrl][39] 10. [↵][40]1. T. Wang et al ., Nat. Metab. 2, 635 (2020). [OpenUrl][41] 11. [↵][42]1. A. L. Geis et al ., Cancer Discov. 5, 1098 (2015). [OpenUrl][43][Abstract/FREE Full Text][44] 12. [↵][45]1. B. H. McGovern et al ., Clin. Infect. Dis. ciaa387 10.1093/cid/ciaa387 (2020). 13. [↵][46]1. L. Maier et al ., Nature 555, 623 (2018). [OpenUrl][47][CrossRef][48][PubMed][49] 14. [↵][50]1. L. Derosa et al ., Ann. Oncol. 29, 1437 (2018). [OpenUrl][51][CrossRef][52][PubMed][35] 15. [↵][53]1. J. Zhang et al ., Gut 68, 1971 (2019). [OpenUrl][54][Abstract/FREE Full Text][55] Acknowledgment: The authors thank J. Powell and D. Pardoll for helpful discussions. 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领域	气候变化 ; 资源环境
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文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/295412
专题	气候变化资源环境科学
推荐引用方式 GB/T 7714	Fyza Y. Shaikh,Cynthia L. Sears. Messengers from the microbiota[J]. Science,2020.
APA	Fyza Y. Shaikh,&Cynthia L. Sears.(2020).Messengers from the microbiota.Science.
MLA	Fyza Y. Shaikh,et al."Messengers from the microbiota".Science (2020).