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Review
. 2019 Aug 20;51(2):225-239.
doi: 10.1016/j.immuni.2019.08.002.

Pursuing Human-Relevant Gut Microbiota-Immune Interactions

Affiliations
Review

Pursuing Human-Relevant Gut Microbiota-Immune Interactions

Sean P Spencer et al. Immunity. .

Abstract

The gut microbiota is a complex and plastic network of diverse organisms intricately connected with human physiology. Recent advances in profiling approaches of both the microbiota and the immune system now enable a deeper exploration of immunity-microbiota connections. An important next step is to elucidate a human-relevant "map" of microbial-immune wiring while focusing on animal studies to probe a prioritized subset of interactions. Here, we provide an overview of this field's current status and discuss two approaches for establishing priorities for detailed investigation: (1) longitudinal intervention studies in humans probing the dynamics of both the microbiota and the immune system and (2) the study of traditional populations to assess lost features of human microbial identity whose absence may be contributing to the rise of immunological disorders. These human-centered approaches offer a judicious path forward to understand the impact of the microbiota in immune development and function.

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Conflict of interest statement

Declaration of Interests:

The authors declare no conflicts of interest

Figures

Figure 1:
Figure 1:. The complexity of the microbial landscape
An array of bacterial taxa (different colors represent different species) colonize the length of the gastrointestinal tract, the majority of which reside in the large intestine. Bacteria also may preferentially colonize the intestinal lumen, the mucus, or intestinal crypts in the epithelium. Bacteria of the same species may contain different genetic components as well as differential expression of genes (zoomed in box) allowing it to differentially process substrates and produce distinct metabolites, denoted by X and Y below box. Bacteria produce a variety of metabolites (pink hexagons) that modulate other bacteria as well as traffic across the intestinal barrier to influence the host. These diverse metabolites, including short-chain fatty acids (SCFA), indolepropionic acid (IPA)(Dodd et al., 2017) tryptamine(Bhattarai et al., 2018) and secondary bile acids (example chemical structures shown) modulate host cells both locally and systemically to influence host physiology as well as immune activation. Host receptors for sensing metabolites are broadly expressed: SCFA (formate, acetate, propionate, butyrate) via GPCR41, GPR43 and GPR109A, IPA via pregnane X receptor (PXR)(Venkatesh et al., 2014), tryptamine via GPCR serotonin receptor-4 (5-HT4R)(Bhattarai et al., 2018), secondary bile acids via the GPCR TGR5, the farnesoid X receptor (FXR), the liver X receptor (LXR), and the vitamin D receptor (VDR)(Fiorucci and Distrutti, 2015; Ridlon et al., 2006), microbial derived histamine via the GPCR histamine receptors (H1–H4)(Palm et al., 2014), commendamide via GPCR132(Cohen et al., 2015), tryptophan metabolites via aryl hydrocarbon receptor (AhR)(Zelante et al., 2013). Additional metabolites likely activate a large and diverse number of other GPCRs in interactions that remain to be identified(Chen et al., 2019).
Figure 2:
Figure 2:. Human-based approaches for studying microbiota-immune interactions
2A, Top panel: Longitudinal intervention studies in humans. A suggested model for microbiota-immune studies: starting with a cohort of participants that undergo a lifestyle intervention that perturbs the microbiota (diet, weight loss, antibiotic use, etc.). Participants are monitored over time, donating samples for both microbiota and immune system profiling. Candidate interactions between microbiota and immune features are identified using machine learning or other means. These interactions can then be studied in a mouse model and in vitro to elucidate their mechanistic underpinnings. 2A, Bottom panel: Traditional v. industrialized population studies. A suggested model for identifying microbes/microbial functionality relevant to lifestyle-related immune disorders: comparing the microbiome of individuals along a gradient of industrialized lifestyles. Focus should be placed on microbial elements that are shared across geographically distinct populations of similar lifestyles, but vary along a gradient of industrialization rather than geography. Once identified, those microbes along with their microbial genetic elements (Yellow markers in figure) or metabolites can be studied mechanistically in murine and in vitro models for their role in immune health or dysregulation. 2B: Ecological concepts applied to microbiota states(Costello et al., 2012). A suggested model for understanding microbial communities: Ancestral microbiomes represent stable communities different from those found in industrialized settings, with changes seen in overall diversity and in carbohydrate utilization capacity. Proposed drivers for this change over time are: dietary changes, more widespread use of antibiotics, increased sanitation contribute to microbiome configuration seen in industrialized settings. To restore beneficial aspects of our microbiota absent in western guts, we propose dietary changes, strain re-introduction, or possibly even Fecal Microbiota Transplant (FMT).

References

    1. Ahern PP, Faith JJ, and Gordon JI (2014). Mining the human gut microbiota for effector strains that shape the immune system. Immunity 40, 815–823. - PMC - PubMed
    1. Arpaia N, Campbell C, Fan X, Dikiy S, van der Veeken J, deRoos P, Liu H, Cross JR, Pfeffer K, Coffer PJ, et al. (2013). Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature 504, 451–455. - PMC - PubMed
    1. Atarashi K, Tanoue T, Shima T, Imaoka A, Kuwahara T, Momose Y, Cheng G, Yamasaki S, Saito T, Ohba Y, et al. (2011). Induction of colonic regulatory T cells by indigenous Clostridium species. Science 331, 337–341. - PMC - PubMed
    1. Ayeni FA, Biagi E, Rampelli S, Fiori J, Soverini M, Audu HJ, Cristino S, Caporali L, Schnorr SL, Carelli V, et al. (2018). Infant and Adult Gut Microbiome and Metabolome in Rural Bassa and Urban Settlers from Nigeria. Cell Rep 23, 3056–3067. - PubMed
    1. Bach JF (2002). The effect of infections on susceptibility to autoimmune and allergic diseases. N Engl J Med 347, 911–920. - PubMed

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