US20190032014A1

US20190032014A1 - Using microbiota metabolites to differentiate naïve t-cells and related methods to induce or prevent inflammatory conditions

Info

Publication number: US20190032014A1
Application number: US16/085,926
Authority: US
Inventors: Robert C. Alaniz; Arul Jayaraman; Kyongbum Lee
Original assignee: Texas A&M University System; Tufts University
Current assignee: Texas A&M University System; Tufts University
Priority date: 2016-03-18
Filing date: 2017-03-17
Publication date: 2019-01-31
Also published as: US20190083462A1; WO2017161301A1; EP3430395A4; US11612586B2; US20200123498A1; EP3429361A4; EP3430128A1; EP3430128A4; WO2017161268A1; EP3429361A1; EP3430395A1; WO2017161307A1

Abstract

Disclosed are compositions derived from the commensal microbiota and related methods for inducing and differentiating naive T cells. In some embodiments, the compositions and methods can be selectively used to generate stable regulatory T-cells (Tregs or iTregs) or stabilize such Tregs to prevent inflammatory responses and instead promote antigen tolerance. Alternatively, in other aspects, select compositions can be used to promote pro-inflammatory T cell development, such as through the induced development and stabilization of Th1 and Th7 cells.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of Provisional Application No. 62/310,643, filed Mar. 18, 2016, Provisional Application No. 62/310,648, filed Mar. 18, 2016, Provisional Application No. 62/310,606, filed Mar. 18, 2016, and Provisional Application No. 62/310,630, filed Mar. 18, 2016, each of which is expressly incorporated herein by reference in its entirety.

STATEMENT OF GOVERNMENT LICENSE RIGHTS

This invention was made with Government support under GM106251 awarded by The National Institutes of Health, National Institute of General Medical Sciences; AI110642 awarded by The National Institutes of Health, National Institute of Allergy and Infectious Disease; A095788 awarded by The National Institutes of Health, National Institute of Allergy and Infectious Disease; and MCB-1120827, awarded by the National Science Foundation. The Government has certain rights in the invention.

FIELD OF THE INVENTION

This disclosure relates to compositions derived from the commensal microbiota and related methods for inducing and differentiating naïve T cells. In some embodiments, the compositions and methods can be selectively used to generate stable regulatory T-cells (Tregs or iTregs) to prevent inflammatory responses and instead promote antigen tolerance. Alternatively, in other embodiments, select compositions can be used to promote pro-inflammatory T cell development.

BACKGROUND

Naïve T cells are lymphocytes that are typically derived from the thymus and express T cell receptors and typically have yet to encounter their cognate antigens. Depending on the signaling environment, naïve T cells can develop along several different differentiation pathways resulting in different lineages of mature T cells, such as Th1, Th2, Th17, and Treg lineages. Each lineage is characterized by distinct expression profiles and functions in vivo, which can lead to very distinct immune responses. Manipulating the differentiation of naïve T cells can be useful to influence the appropriate responses to various antigens and avoid inappropriate immune responses.
For example, regulatory T-cells (Tregs) are an indispensable class of immune cells (lymphocytes) that are able to promote immune tolerance and prevent unwanted autoimmune and inflammatory responses. Tregs promote immune tolerance in peripheral tissues through cytokine secretion and cell-contact inhibition of dysregulated immune responses. Methods exist to selectively expand patient Tregs in vivo/ex vivo in the presence of recombinant TGF-β, which is essential for Treg development, and re-infuse to patients for therapeutic inhibition of inflammation. Patients predicted to benefit from Treg transfer include those suffering from autoimmunity, inflammatory bowel disease, psoriasis, graft-versus-host disease and other pathology characterized by excessive inflammation. However, major hurdles still exist in the safe translation of this therapeutic strategy from lab bench to bedside. For example, the clinical and commercial application is hampered due to the inefficient expansion of suitable numbers of patient Treg cells. Furthermore, the functional phenotype of the expanded Tregs after transfer to patients with acute or chronic inflammation may transition from the anti-inflammatory Treg phenotype to a pro-inflammatory phenotype (e.g., Th17) is unstable under the influence of inflammatory cytokines such as IL-6 that are present in the patient. Tregs that fail to function or that revert to a pro-inflammatory T-cell in vivo can be especially deleterious to the patient.
However, in other situations, such as with parasitic/microbial infections and cancer, inflammatory response might be desired. In such cases, it would be preferable to reduce Treg populations and instead promote development of naïve T cells into other T cell lineages such as Th1 cells (e.g., to combat intracellular pathogens), Th2 cells (e.g., to combat extracellular pathogens), and Th17 cells (for mucosal immune responses and recruitment of polymorphonuclear leukocytes (PMNs)).
Accordingly, a need remains to routinely and reliably influence the differentiation of naïve T cells and promote their expansion into the mature T cell type of interest. For example, a need remains to differentiate and expand Treg populations that possess a stable regulatory phenotype and function when introduced into an inflammatory microenvironment. Such expanded populations of stable Treg cells would greatly enhance the clinical adoptive iTreg transfer efficacy and safety. Alternatively, a need remains to differentiate and expand pro-inflammatory T cells to facilitate responses against infections or cancers. The present disclosure addresses these and related needs.

SUMMARY

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
In one aspect, the disclosure provides a method of activating a naïve T cell in vitro. The method comprises contacting the naïve T cell with a tryptophan derived microbiota metabolite (TDMM). In one embodiment, the naïve T cell is differentiated into a cell with increased expression of FoxP3 compared to the naïve T cell. In one embodiment, the naïve T cell is differentiated into a T regulatory cell (Treg). In one embodiment, the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7 hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole. In one embodiment, the naïve T cell is differentiated into a Th17 cell. In one embodiment, the TDMM is 5 hydroxyindole. In one embodiment, the naïve T cell is contacted in vitro in a culture medium.
In another aspect, the disclosure provides a method of producing a Treg cell, comprising contacting a naïve T cell in vitro with a tryptophan derived microbiota metabolite (TDMM). In one embodiment, the naïve T cell is contacted with the TDMM in a culture medium.
In another aspect, the disclosure provides a induced T regulatory cell (iTreg), produced by the methods described herein.
In another aspect, the disclosure provides a method of treating, preventing, ameliorating, attenuating and/or reducing inflammation in a subject in need thereof, comprising administering to the subject an iTreg, as described herein. In one embodiment, the subject suffers from or is susceptible to excessive inflammation. In one embodiment, the subject has or is susceptible to allergies, inflammatory bowel disease, colitis, NSAID-enteropathy/ulceration, psoriasis, rheumatism, graft-versus-host disease, and the like. In one embodiment, the iTreg is administered by intra-peritoneal (IP), intravenous (IV), topical, parenteral, intradermal, transdermal, oral (e.g., via liquid or pill), or respiratory (e.g., intranasal mist) routes. In one embodiment, the subject is a mammal, such as a human, mouse, or rat.
In another aspect, the disclosure provides a T cell culture medium that promotes activation of a naïve T cell, comprising a tryptophan derived microbiota metabolite (TDMM). In one embodiment, the medium further comprises one or more additional Treg promoting compounds, such as short-chain fatty acids, bile acids, polysaccharide A, n3 polyunsaturated fatty acids, retinoic acid, VitD, VitC, polyphenols, quercetin, resveratrol, NSAIDS, TGF β, rapamycin, and/or IL 2.
In another aspect, the disclosure provides a method of treating or reducing a condition characterized by excessive inflammation in a subject in need thereof, comprising administering to the subject an effective amount of a Treg-skewing TDMM, or a precursor, prodrug, or acceptable salt thereof. In one embodiment, the condition is an allergy, or autoimmune disease, such as colitis, inflammatory bowel disease (IBD), psoriasis, rheumatoid arthritis, multiple sclerosis, fibrosis, enteropathy, graft-versus-host disease, and the like.
In another aspect, the disclosure provides a method of increasing the stability of a Treg cell, comprising contacting the Treg cell or a precursor thereof with an effective amount of a Treg-skewing TDMM, or a precursor, prodrug, or acceptable salt thereof. In one embodiment, the Treg is an induced Treg cell (iTreg). In one embodiment, the Treg is a natural Treg cell (nTreg). In one embodiment, the nTreg is first isolated from a subject before the contacting step. In one embodiment, the method further comprises administering the Treg cell to a subject in need thereof. In one embodiment, the method further comprises administering the TDMM to a subject that has an endogenous nTreg population in vivo.
In another aspect, the disclosure provides a method of producing a pro-inflammatory T cell, comprising contacting a naïve T cell with a pro-inflammatory tryptophan derived microbiota metabolite (TDMM). In one embodiment, the contacting occurs in vitro or ex vivo. In one embodiment, the pro-inflammatory TDMM is 5 hydroxyindole (5 HI). In one embodiment, the pro-inflammatory T cell expresses ROR γ or IL 17. In one embodiment, the pro-inflammatory T cell is a Th17 cell.
In another aspect, the disclosure provides a induced Th17 cell (iT17), produced by the method described herein.
In another aspect, the disclosure provides a method of treating, preventing, ameliorating, attenuating and/or reducing a condition in a subject treatable by inducing or increasing an inflammation response, comprising administering to the subject an iTh17 cell as described herein.
In another aspect, the disclosure provides a method of treating, preventing, ameliorating, attenuating and/or reducing a condition in a subject treatable by inducing or increasing an inflammation response, comprising administering to the subject a pro-inflammatory tryptophan derived microbiota metabolite (TDMM), or a precursor, prodrug, or acceptable salt thereof, in an amount sufficient to induce development of or stabilize Th17 cells from a naïve T cell precursor. In one embodiment, the pro-inflammatory TDMM is 5-HI.

DESCRIPTION OF THE DRAWINGS

The foregoing aspects and many of the attendant advantages of this invention will become more readily appreciated as the same become better understood by reference to the following detailed description, when taken in conjunction with the accompanying drawings, wherein:

FIG. 1 is a cartoon representation of pathways involved in T cell decision-making and differentiation;

FIGS. 2A-2B illustrate the potent Treg augmenting (increased % and FoxP3 and decreased % of IL-17) properties of indole. The effect of 1 mM indole on Treg and Th17 cell under Th0 or Th17 conditions development was assessed with a FACS sorter directed to the relevant marker to determine the proportion of the T cells for each marker. Shown are the percentages of CD4 T cells expressing FoxP3 (FIG. 2A) or IL-17 (FIG. 2B). Data shown are mean±SEM from 3 independent experiments. Numbers adjacent to the bars indicate the mean fluorescence intensity (MFI) for the different conditions;

FIG. 3 graphically illustrates the dramatic Treg promoting effects of indole that are revealed when levels of TGF-β are limiting. Indole doubles the expansion of Tregs (Foxp3+ %) at standard TGF-β dose. When levels of TGF-β are reduced below a threshold for Treg induction, indole maintains Foxp3 expression to high levels. This demonstrates the potent accessory signaling induced by indole for optimal Treg induction;

FIGS. 4A-4C illustrate that indole-induced iTregs are functional based on increased suppression of effector T cell proliferation, which is the hallmark of T cell function. FOXP3-EGFP naïve CD4+ CD25− cells cultured in αCD3/28-coated wells with Treg-skew cytokines and indole or solvent control were cultured for 72 hours, and assessed for FoxP3 expression and proliferation by CFSE dilution. Indole-induced iTreg cells have a higher per-cell expression of FOXP3 (GFP) both pre- and post-sort (FIG. 4A). Indole-conditioned Tregs suppress effector T cell proliferation function in a 72-hour suppression assay and secrete more TGF-β than conventional control iTregs (DMF) after overnight re-stimulation with αCD3 (FIGS. 4B and 4C). These results demonstrate the in vitro functionality of indole-induced iTregs as bona fide Tregs;

FIGS. 5A and 5B graphically illustrates that indole does not significantly affect the skew of Th1 (FIG. 5A) or Th2 (FIG. 5B) cells, thus indicating specificity of indole's effects on Treg and Th17 cells;

FIG. 6 is a series of FACS results showing the effect of a panel of TDMM on naïve T cells differentiation into FoxP3+ Treg cells;

FIGS. 7A and 7B graphically illustrate the skewing effect of indole on naïve T cell differentiation into Th17 (IL-17+) (FIG. 7A) and Treg (FoxP3+) (FIG. 7B) cells. Data shown are mean±SEM from 3 independent experiments;

FIGS. 8A-8D graphically illustrate the skewing effect of 5-hydroxyindole (5-HI) on naïve T cell differentiation into Th1 cells (INF-γ+) (FIG. 8A), Th2 cells (IL-4+) (FIG. 8B), Th17 cells (IL-17+) (FIG. 9C), and Treg cells (FoxP3+) (FIG. 9C) cells. The data show that 5-HI promotes Th1 and Th17 differentiation and strongly inhibits Treg differentiation. Data shown are mean±SEM from 3 independent experiments;

FIGS. 9A-9F graphically illustrate the skewing effect of 1-butyrate on naïve T cell differentiation. FIG. 9A shows the % INF-γ+ cells after exposure to increasing concentrations of 1-butyrate, indicating an induction of Th1 differentiation. FIG. 9B shows the % IL-4+ cells after exposure to increasing concentrations of 1-butyrate, indicating an inhibition of Th2 differentiation. FIGS. 9C and 9D show the % INF-γ+ cells after exposure to 1-butyrate with and without indole under Th0 and Th2-skewing conditions, respectively. FIGS. 9E and 9F show the % IL-4+ cells after exposure to 1-butyrate with and without indole under Th17 and Treg-skewing conditions, respectively. Data shown are mean±SEM from 3 independent experiments;

FIG. 10 graphically illustrates the effect of indole on gut homing markers detectable on induced Treg (iTreg) cells. Indole increases the % of α4β7+ of FoxP3+ cells, and that the effect is amplified when combined with retinoic acid (RA) indicating synergy between indole and RA. Data shown are mean±SEM from 3 independent experiments;

FIG. 11 graphically illustrates the effect on additional functional Treg markers detectable on iTreg cells. Shown is the fold increase of CD62L+ on FoxP3+ cells caused by indole with and without combination with retinoic acid (RA). Data shown are mean±SEM from 3 independent experiments;

FIGS. 12A-12C graphically illustrate the expression of gut homing marker α4β7 (% α4β7+) on iTreg cells conditioned with indole and with different concentrations of short chain fatty acids (SCFAs) acetate (FIG. 12A), propionate (FIG. 12B), and butyrate (FIG. 12C). Data shown are mean±SEM from 3 independent experiments;

FIG. 13 graphically illustrates the results of a suppression assay, showing the suppression of T-cell proliferation as determined by IL-2 production (an essential marker of T-cell proliferation) with increased proportions of Tregs added to co-cultures with effector T-cells. This data indicates that indole-induced iTregs function in a superior manner than traditional iTregs induced by butyrate or “natural” Tregs isolated from the thymus (nTregs). Data shown are mean±SEM from 3 independent experiments;

FIGS. 14A-14C graphically illustrate iTreg cytokine expression when conditioned with indole or butyrate using purified FoxP3+-GFP+ cells. FIG. 14A shows the GFP MFI of GFP+ cells pre- and post-sorting. FIGS. 14B and 14C show the TGF-β and IL-10 levels produced by the cells conditioned with indole or butyrate. Indole-conditioned iTregs increased TGF-β expression over butyrate-conditioned iTregs, whereas indole conditioning uniquely resulted in inhibition of IL-10 expression. Data shown are mean±SEM from 3 independent experiments;

FIG. 15A graphically illustrates effect of 5-HI on skewing the development of naïve T cells. Exposure to 5HI with increasing titrations of IL-6 increased the % IL-17+ cells. This demonstrates that 5-HI induces Th17 T cells when IL-6 is below its respective concentration threshold for Th17 induction. Data shown are mean±SEM from 3 independent experiments;

FIG. 15B graphically illustrates effect of indole on skewing the development of naïve T cells. Exposure to indole with increasing titrations of TGF-β increased the % FoxP3+ cells. This demonstrates that indole induces iTregs when TGF-β is below its respective concentration threshold for iTreg induction. Data shown are mean±SEM from 3 independent experiments;

FIG. 16A-16D illustrate the effects of indole and 5-HI conditioning on pSMAD2/3 and pSTAT3 activity. FIG. 16A graphically illustrates the % TGF-β receptor+ cell levels when conditioned with indole or 5-HI. FIG. 16B graphically illustrates % pSMAD2/3+ cells conditioned with indole or 5-HI. This indicates that indole augments the TGF-β induced SMAD2/3 activation. FIG. 16C graphically illustrates the % IL-6 receptor+ cell levels when conditioned with indole or 5-HI.

FIG. 16D graphically illustrates % pSTAT3+ cells conditioned with indole or 5-HI. This indicates that indole inhibits the IL-6 receptor expression and IL-6 induced stat3 activation, whereas 5-HI augments the IL-6 induced stat3 expression. Data shown are mean±SEM from 3 independent experiments;

FIG. 17 graphically illustrates the FoxP3+ % of wild-type or AhR KO T cells after conditioning with indole. This indicates that indole augments Treg development in an AhR-dependent manner. Data shown are mean±SEM from 3 independent experiments;

FIG. 18 graphically illustrates the IL-17+ % of wild-type or AhR KO T cells after conditioning with indole. This indicates that indole inhibits Th17 development in an AhR-dependent manner. Data shown are mean±SEM from 3 independent experiments;

FIGS. 19A and 19B graphically illustrate expression of iTreg homing markers, CD62L (FIG. 19A) and α4β7 (FIG. 19B) in FoxP3+ wild-type or AhR KO T cells after conditioning with indole with or without RA. This indicates that indole augments Treg α4β7 expression and CD62L in an AhR-independent manner. Data shown are mean±SEM from 3 independent experiments;

FIG. 20 graphically illustrates the % of IFN-γ+T cells (i.e., Th1 skew) in wild-type or AhR KO T cells after conditioning with 5-HI. This indicates that 5-HI augmentation of Th1 differentiation is AhR-independent. Data shown are mean±SEM from 3 independent experiments;

FIG. 21 graphically illustrates the % of IL-17+T cells (i.e., Th17 skew) in wild-type or AhR KO T cells after conditioning with 5-HI. This indicates that 5-HI augmentation of Th17 differentiation is AhR-independent. Data shown are mean±SEM from 3 independent experiments;

FIG. 22 graphically illustrates the % FoxP3+ T cells when wild-type or AhR KO cells were conditioned with 5-HI. This indicates that 5-HI inhibits Tregs in an Ahr-independent manner. Data shown are mean±SEM from 3 independent experiments;

FIG. 23 graphically illustrates the mTOR activation by indole and 5-HI. The % P-S6 is illustrated from T cells conditioned with 5-HI or indole. This illustrates that indole inhibits mTor activity as indicated by lowered P-S6%. Data shown are mean±SEM from 3 independent experiments;

FIGS. 24A-24C graphically illustrate indole and 5-HI interactions in T cell differentiation. FIG. 24A illustrates the % IFN-γ+ cells after conditioning with indole, 5-HI, or both. FIG. 24B illustrates the % IL-17+ cells after conditioning with indole, 5-HI, or both. FIG. 24C illustrates the % FoxP3+ cells after conditioning with indole, 5-HI, or both. These data illustrate that indole, when exposed along with 5-HI, overrides and negates the influence of 5-HI. Data shown are mean±SEM from 3 independent experiments;

FIGS. 25A-25C graphically illustrate indole, 5-HI, and SCFA (butyrate) interactions in T cell differentiation. FIG. 25A illustrates the % IFN-γ+ cells after conditioning in Th1-skewing conditions and with treatments with indole, 5-HI, or both, in the presence of varying amounts of butyrate. This indicates that under Th1 skewing conditions, indole is dominant over the effects of 5-HI. FIG. 24B illustrates the % IL-17+ cells after conditioning in Th17-skewing conditions and with treatments with indole, 5-HI, or both, in the presence of varying amounts of butyrate. This indicates that under Th17 skewing conditions, indole is dominant over the effects of 5-HI. FIG. 24C illustrates the % FoxP3+ cells after conditioning in Treg-skewing conditions and with treatments with indole, 5-HI, or both, in the presence of varying amounts of butyrate. This indicates that under Treg skewing conditions, indole is dominant over the effects of 5-HI. These data illustrate that indole, when exposed along with 5-HI, overrides and negates the influence of 5-HI. Data shown are mean±SEM from 3 independent experiments;

FIGS. 26A-26C graphically illustrate the in vivo T cell activation in spleens stimulated by indole, butyrate and αCD3. Generally, mice were administered amounts of αCD3, indole, and/or butyrate at 0 and 48 hrs. After 52 additional hours, the spleens were harvested and homogenized. Cells were plated, stimulated with PMA/lonomycin, stained for the indicated T cell markers, and subjected to FACS analysis. The graphs show the % IFN-γ+ CD4+ cells (FIG. 26A), the % IFN-γ+ CD4+ CD44^lowcells (FIG. 26B), and the % IFN-γ+ CD4+ CD44^highcells (FIG. 26C) resulting from the various treatments. These data show that butyrate augments Th1 differentiation in vivo, but indole suppresses butyrate induction of Th1 cells in vivo. Data shown are mean±SEM from 3 independent experiments;

FIGS. 27A-27C also graphically illustrate the in vivo T cell activation in mesenteric lymph nodes (MLN) when stimulated by indole, butyrate and αCD3. Mice were administered amounts of αCD3, indole, and/or butyrate at 0 and 48 hrs, as described above, except the MLN were harvested and homogenized. Cells were plated, stimulated with PMA/lonomycin, stained for the indicated T cell markers, and subjected to FACS analysis. The graphs show the % IFN-γ+ CD4+ cells (FIG. 27A), the % IFN-γ+ CD4+ CD44^lowcells (FIG. 27B), and the % IFN-γ+ CD4+ CD44^highcells (FIG. 27C) resulting from the various treatments. These data show that butyrate augments Treg differentiation in vivo, and that indole synergizes with butyrate for the induction of Treg cells in vivo. Data shown are mean±SEM from 3 independent experiments;

FIG. 28 graphically illustrates the weight change (% from starting weight) in a murine colitis model. As shown, indole inhibits the Th17 transfer colitis in vivo, whereas 5-HI exacerbates Th17 transfer colitis in vivo. Data shown are mean±SEM from 3 independent experiments;

FIGS. 29A and 29B graphically illustrate the % FoxP3+ T cells (FIG. 29A) and FoxP3+ levels (FIG. 29B) obtained from the MLN of a Th17 transfer colitis model at D15 and D45. The data demonstrate that indole induces early Treg differentiation in vivo during Th17 transfer colitis;

FIGS. 30A and 30B graphically illustrate the % IL-17+ T cells (FIG. 30A) and Th17/Treg balance (FIG. 30B) obtained from the MLN of a Th17 transfer colitis model at D15 and D45. The data demonstrate that indole induces suppresses Th17 differentiation in vivo by the end point of Th17 transfer colitis model, whereas 5-HI increases the number of Th17 differentiation in vivo by the end point of Th17 transfer colitis model;

FIGS. 31A and 31B graphically illustrate the % INF-γ+ T cells (FIG. 31A) and Th1/Treg balance (FIG. 31B) obtained from the MLN of a Th17 transfer colitis model at D15 and D45. The data demonstrate that indole induces suppresses Th1 differentiation in vivo by the end point of Th17 transfer colitis model, whereas 5-HI increases the number of Th17 differentiation in vivo by the end point of Th17 transfer colitis model;

FIGS. 32A and 32B graphically illustrate that indole inhibits colitis in a T-cell-dependent manner. FIG. 32A: Wild-type C57B16 mice were treated with 5% DSS, or not, in drinking water for 7 days. At this point, mice were treated with indole or not for an additional 7 days. Individual mouse weight was recorded daily throughout experiment as a measure of inflammation. FIG. 32B: Mice were treated as in FIG. 32A, only mice were Rag-deficient mice, which lack lymphocytes (T- and B-cells).

DETAILED DESCRIPTION

The present disclosure is generally directed to the activation of naïve T cells, such as differentiation of naïve T cells into stable mature T cells using related compounds derived from the commensal microbiota.
In one aspect, the disclosure addresses differentiation of naïve T cells into stable regulatory T-cells (Tregs), using indole and related compounds derived from the commensal microbiota. This disclosure is based, in part, on the observation that a healthy, abundant, and diverse endogenous commensal microbiota is essential in humans to induce in vivo optimal numbers of highly functional Tregs. Accordingly, the inventors investigated the microbiota as potential source for potential therapeutic compounds. The inventors used a high-resolution drug discovery platform and first-order functional screens of the commensal microbial metabolome (i.e., the aggregate of all metabolites produced by the collective commensal microbes) to identify and validate a panel of small molecules with potent properties for inducing the development and augmenting the function of regulatory T-cells (Tregs). In another aspect, the disclosure addresses differentiation of naïve T cells into stable pro-inflammatory T-cells useful to invoke appropriate responses against infections and diseases such as cancers.
The results, described in more detail below, disrupt general paradigms of drug discovery and suggest that the commensal microbes that live within humans (or other therapeutic subjects) are a source of therapeutic compounds, which can be used to treat a variety of diseases. As the utility of this approach has become clear, one likely advantage to such therapeutic compounds is the enhanced likelihood for tolerance (e.g., reduced toxicity and side-effects) in the human (or other) subject considering that the commensal source microorganisms have been selected over millennia for tolerance by the human (or other) host. In a specific aspect, select microbiota metabolites can be useful to improve commercial application of clinical adoptive Treg therapy, such as by augmenting ex vivo expansion of stable Tregs that possess stable anti-inflammatory function in vivo.
As described in more detail below, the inventors have established that multiple tryptophan derived microbiota metabolites (TDMMs) have an effect on the activation and further development of naïve T cells. Accordingly, in one aspect, the present disclosure is directed to a method of activating a naïve T cell in vitro. The method comprises contacting a naïve T cell with a tryptophan derived microbiota metabolite (TDMM), or a precursor, prodrug, or acceptable salt thereof.
As used herein, the term “naïve T cells” refers to lymphocytes that are typically derived from the thymus and express T cell receptors. The naïve T cells have typically undergone the basic development in the bone marrow and further undergone the positive and negative processes of selection in the thymus. However, naïve T cells have not encountered their cognate antigens yet in the periphery. The terms “activating” and/or “differentiation” refers to the process in which the naïve T cell are caused to further develop into one of at least four distinct lineages of T cells characterized by distinct expression profiles and functions in vivo. See, e.g., FIG. 1. The term “activated” and/or “differentiated” can refer to the cell that had previously been naïve but now has had an induction of specific gene expression such that it is identifiable as a particular activated/differentiated lineage. The terms can also refer to cells produced from the expansion of a T cell into a multitude of progeny cells by cell-division and which retain the identifiable markers for the particular activated/differentiated lineage. Thus, “activating a naïve T cell” can refer to the production of an expanded cell population of differentiated T cells from the initial naïve T cell, as well as the initial T cell after gene transcription has been induced.
As used herein, the term “tryptophan derived microbiota metabolite” (“TDMM”) refers to metabolites produced by microorganisms of the commensal microbiota that resides in the intestinal tract. The individuals of the microbiota inhabit the space of the intestines and exist in homeostasis with the healthy vertebrate host. Thus, presumably, the metabolite products produced by the individuals of the microbiota have been selected over time to avoid triggering inflammatory immune responses in the mucosa. The specific metabolites referred to by the term TDMM are derivatives of tryptophan and include compounds such as indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 5-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole. Many of these are being shown to be AhR ligands, which as demonstrated in the present disclosure relating to indole, has a role in Treg/Th17 differentiation. The TDMM encompasses such molecules that have been directly obtained from microbiota individuals. Such TDMMs can be isolated, purified, or partially purified through well-established methods. However, the term TDMM, while referring to the feature of a “microbiota metabolite,” is not necessarily limited to the specific source as one or more individual organisms of the commensal microbiota. Instead, it merely refers to the fact that the commensal microbiota are known to produce such a compound. Thus, the TDMM used as part of this disclosure can also be obtained from an organism that is not typically considered to be a member of a commensal microbiota of a vertebrate organism (whether the vertebrate individual is the source of the naïve T cell or not). Instead, the TDMM can be produced by known methods, such as typical recombinant approaches, in preferred laboratory strains of bacteria, and the like. Furthermore, the TDMM can be produced synthetically, as appropriate through known methods of synthetic chemistry. In any of the above embodiments, the cell can be contacted with a composition that is a precursor to, prodrug of, or acceptable salt of any of the potential TDMM compound embodiments.
For any embodiment, it can be readily determined the minimal amount of TDMM required to effect activation of the naïve T cell into the desired differentiated T cell. For example, as described in more detail below, illustrative assays can run to determine the effect of TDMMs on the activation of naïve T cells using 0.01 to 1.0 mM of the TDMM in the culture medium.
In one embodiment, the naïve T cell is differentiated into a cell with increased expression of FoxP3 compared to the naïve T cell. The term “FoxP3” refers to a transcription factor also referred to as “forkhead box P3” or “scurfin”. While the precise control mechanism has not yet been established, FoxP3 protein belongs to the forkhead/winged-helix family of transcriptional regulators. In regulatory T cell model systems, FoxP3 occupies the promoters for genes involved in regulatory T-cell function, and may repress transcription of key genes following stimulation of T cell receptors. Accordingly, FoxP3 is known as a master regulator in the development of regulatory T cells (Tregs), which are involved in tolerance of antigens in the periphery and generally promote a protection against an inflammatory response. Examples of the FoxP3 protein include human (Entrez #: 50943; RefSeq (mRNA): NM_001114377; RefSeq (amino acid): NP_001107849) and mouse (Entrez #: 20371; RefSeq (mRNA): NM_001199347; RefSeq (amino acid): NP_001186276). Many other FoxP3 protein and gene homologs are known for vertebrate animals, and their expression can be readily determined. As used herein, the term “increased” refers to a level of expression of the FoxP3 transcription factor that is detectably greater than that in a naïve T cell, such as the initial naïve T cell that is being differentiated, or other naïve T cell obtained from the same individual (or an individual of the same species) as that as the initial naïve T cell. Increased expression can be determined in terms of transcription of the underlying foxp3 gene or levels of functional FoxP3, using routine and established methods known in the art.
In one embodiment, the naïve T cell is differentiated into a T regulatory cell (Treg). The term “Treg” refers to a lineage of T cells that promote or maintain tolerance to antigens, typically to self-antigens. Tregs have been previously referred to as “suppressor T cells.” Tregs generally suppress or downregulate induction and proliferation of effector T cells. As indicated above, Treg cells are typically characterized by the positive or increased expression of FoxP3. Tregs are also characterized by the additional positive or increased expression of CD4 and CD25. Thus, in one embodiment, the Treg is characterized by a state of CD4+, CD25+ and FoxP3+ expression.
As discussed in more detail below, the inventors have demonstrated that the TDMMs such as indole and indolepyruvate have resulted in the activation of naïve T cells into differentiated Treg cells. Accordingly, in one embodiment, the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole. In one embodiment, the TDMM is indole or indolepyruvate. In such embodiments, the naïve T cell is differentiated into a Treg and/or a T cell that otherwise expresses FoxP3.
In one embodiment, the TDMM is indole, which is typically represented with the following structure:
In other embodiments, the contacting of the naïve T cell results in an inhibition of a “Th17” inflammation phenotype by the differentiated T cells. For instance, the contacting of the naïve T cell results in an inhibition or decrease in the expression of RORγT, which is a marker for the Th17 (pro-inflammatory) phenotype of activated T cell normally involved in mucosal immunity (see FIG. 1).
The inventors also demonstrated that some TDMMs, such as 5-hydroxyindole, induce differentiation of the naïve T cell into a T cell with a Th17 (pro-inflammatory) phenotype (referred to herein as a “Th17 cell”). Therefore, in another embodiment, the contacting of the T cell with the TDMM results in the differentiated T cell having a pro-inflammatory phenotype. In a further embodiment, the differentiated T cell expresses RORγT. In one embodiment, the naïve T cell is differentiated into a Th17 cell. In one embodiment, contacting of the T cell with the TDMM results in the differentiated cell having Th1 characteristics. In one embodiment, contacting of the T cell with the TDMM results in the differentiated cell able to inhibit Treg cells. In one embodiment, the TDMM is 5-hydroxyindole. It may also be shown that related hydroxyindoles may have such an effect in some environments.
In any embodiment herein, the naïve T cell can be contacted in vitro in a culture medium. Typically, the culture medium contains factors commonly known to support and maintain T cell viability. An exemplary description for the isolation, culture, in vitro differentiation of naïve T cells is provided below in Examples 1-3. The medium can also contain additional ingredients that are also known to promote T cell activation toward the desired differentiated lineage. Such additional ingredients are often referred to as “skewing” ingredients. Exemplary skewing factors are indicated in FIG. 1. For example, as indicated in FIG. 1 and described in more detail below, Treg skewing factors include any FDA-approved drug or antibiotic known to promote Treg development/stability. Skewing factors can also include other microbiota metabolites (such as short-chain fatty acids, bile acids, polysaccharide A), dietary derived compounds (such as n3 polyunsaturated fatty acids, retinoic acid, and other vitamin-derivatives (VitD, VitC, etc.), polyphenols, quercetin, resveratrol, NSAIDS, TGF-β, IL-10, rapamycin, and IL-2. Other skewing factors that are useful for this purpose include curcumin, metformin/AMPK activators, PI3-kinase/Akt inhibitors, and PPAR agonists, as are known in the art.
In another aspect, the present disclosure provides a method of producing a Treg cell. In one embodiment, the method comprises contacting a naïve T cell in vitro with a TDMM, as described above. In specific embodiments, the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole. The TDMM can be contacted with the naïve T cell as a component (e.g., additive) of a standard culture medium, as described above. The method can comprise the further culture and/or expansion of the activated T cell in its differentiated Treg state.
In another embodiment, the TDMM, or a precursor, prodrug, or acceptable salt thereof, can be administered to a subject with naïve T cells in an appropriate manners such that the naïve T cells are contacted with an effective amount of TDMM, or a precursor, prodrug, or acceptable salt thereof, to result in a Treg cell.
As described below, the inventors have demonstrated that the Tregs that are induced in vitro (“iTregs”) using the disclosed TDMMs possess new features over induced Tregs (“iTregs”) produced using existing techniques. For example, the inventors have demonstrated that the iTregs resulting from the application of the TDMMs, such as indole, resulted in a stable iTreg that did not revert to a Th17 phenotype even in a “pro-inflammation” environment. Thus, in another aspect, the disclosure provides an induced T regulatory cell (iTreg). The iTreg is produced by the methods described herein. In some embodiments, the iTreg is produced by contacting a naïve T cell with a TDMM selected from In specific embodiments, the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole. The iTreg can be the initial T cell after activation has occurred or a progeny cell in the differentiated state after expansion has occurred through one or more rounds of cell division from the initial T cell. In some embodiments, the iTreg exhibits increased stability in the Treg lineage as compared to iTregs that are induced using conventional means. For example, IL-4, IL-6, and IL-23 are all known to reduce typical Treg stability. This obstacle is overcome by iTregs. Accordingly, the iTreg lineage is less susceptible to induced instability by IL-4, IL-6, and IL-23. In some embodiments, the conventional means useful for comparison include or comprise using DMF as a Treg skewing factor.
In some embodiments, the iTregs are distinguished from typical Tregs by a relative increased expression of CTLA4, CD62L, CD25, higher Foxp3, alpha4beta7, and/or CCR9, which can readily be determined by routine testing.
In another aspect, the present disclosure provides a method of increasing the stability of Treg cells. This refers to the lowered susceptibility of the Tregs to alter the Treg specific expression profiles in the context of pro-inflammatory cytokines and signaling, such as IL-4, IL-6, and IL-23, and the like. The Treg cells can be induced Tregs (iTregs) such as produced by the novel methods described herein or by existing methods in the art. Alternatively, the Tregs can be naturally occurring Tregs (nTregs). The term “nTregs” refers to the Tregs existing in vivo without prior in vitro intervention or transfer and are typically obtained from the thymus in humans. This method can be carried out in vitro by isolating and the Treg population, or alternatively expanding an iTreg population already ex vivo, and exposing the Tregs to the TDMMs, or a precursor, prodrug, or acceptable salt thereof, as described herein. In some cases, if the target population is an iTreg population produced by the novel methods described herein, the iTregs will have already been exposed to the TDMMs, or a precursor, prodrug, or acceptable salt thereof, and may or may not have additional exposure.
In another aspect, the present disclosure provides a method of reducing, preventing, ameliorating, attenuating, and/or otherwise treating inflammation in a subject in need thereof. General methods of using isolated or ex vivo/in vitro—differentiated Treg cells as part of adoptive T cell therapy to address inflammatory-related diseases are known. See, e.g., Riley, J. L., et al., “Human T regulatory cells as therapeutic agents: Take a billion or so of these and call me in the morning,” Immunity 30(5):656-665 (2009), incorporated herein by reference in its entirety. The method of the present aspect comprises administering to the subject the iTreg described immediately above, i.e., which is produced by contacting a naïve T cell with a TDMM.
In some embodiments, the subject suffers from or is susceptible to excessive or deleterious inflammation. In some embodiments, the subject has or is susceptible to allergies, inflammatory bowel disease, colitis, NSAID-enteropathy/ulceration, psoriasis, rheumatism, graft-versus-host disease, lupus, multiple sclerosis, and the like. In some embodiments, the subject has or is susceptible to a disease characterized by the role of mTor, stat3, akt, erk, jnk, stat5, and/or smad2/3, which are targets of indole. Additionally or alternatively, the subject may suffer from deleterious inflammation due to a cancer or infection from a microbial or parasitic pathogen.
The iTreg can be formulated for administration through any appropriate route according to known standards and methods. For example, the iTregs can be formulated for intra-peritoneal (IP), intravenous (IV), topical, parenteral, intradermal, transdermal, oral (e.g., via liquid or pill), inhaled (e.g., intranasal mist), and other appropriate routes of administration. In some embodiments, administration is directly to a mucosal region of the subject, such as in the digestive tract.
In some embodiments, the method comprises inducing the development of Tregs in vivo as described herein. In such embodiments, the subject can be administered an effective amount of TDMM, or a precursor, prodrug, or acceptable salt thereof. Administration of the TDMM can be in any appropriate route of administration. For example, the TDMM can be administered by intra-peritoneal (IP), intravenous (IV), topical, parenteral, intradermal, transdermal, oral (e.g., via liquid or pill), rectal, or respiratory (e.g., intranasal mist) routes. In preferred embodiments, the TDMM is ingested, e.g., via liquid or pill, etc. to facilitate delivery of the TDMM to the intestinal tract where the microbiota reside.
The effective amount of TDMM, or a precursor, prodrug, or acceptable salt thereof, can depend on factors pertaining to the subject and the route of administration, etc., and can be readily determined according to the skill of the ordinary artisan. In some embodiments, a single administration (of potentially one or multiple administrations) comprises at least about 1 mg/kg, 5 mg/kg, 15 mg/kg, 20 mg/kg, 25 mg/kg, 30 mg/kg, 35 mg/kg, 40 mg/kg, 45 mg/kg, 50 mg/kg, 55 mg/kg, 60 mg/kg, 65 mg/kg, 70 mg/kg, 75 mg/kg, 80 mg/kg, 85 mg/kg, 90 mg/kg, 95 mg/kg, 100 mg/kg, or more. Dosing can be readily determined for any particular subject based on routine cell and animal toxicity studies so as to avoid deleterious effects of high concentrations, while still achieving the desired effect.
In some embodiments, the microbiota of the subject is induced to produce elevated levels of the appropriate TDMM, such as indole. In this regard, additional microbiota organisms that are known to produce high levels of the TDMM can be administered to the subject. In some embodiments, the administered microbiota organisms can be artificially selected or genetically engineered to produce higher levels of the TDMM when residing in the GI tract of the subject. For example, in some embodiments the genetically engineered microorganisms are engineered to express, stably or transiently, higher levels of a tnaA gene, which encodes the enzyme responsible for tryptophan metabolism and production of indole. Alternatively or additionally, the subject can be provided with elevated levels of tryptophan, such as in dietary supplements, so as to allow the microbiota to produce higher levels of TDMMs. These embodiments are typically more appropriate for subjects suffering from chronic over-inflammation and, thus, would benefit from stable increases of Treg promoting TDMMs rather than occasional transient doses.
In some embodiments, the subject is a mammal, such as a primate, rodent, feline, canine, or domesticated farm animal. In some embodiments, the subject is a human, mouse, rat, cat, dog, cow, horse, goat, sheep, and the like.
In another aspect, the present disclosure provides a T cell culture medium that promotes activation of a naïve T cell. The T cell culture medium comprising a tryptophan derived microbiota metabolite (TDMM). In one embodiment, the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 5-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole.
In one embodiment, the T cell culture medium promotes activation of the naïve T cell into a Treg cell (iTreg). In one embodiment, the Treg cell exhibits increased stability of the Treg cell as compared to an iTreg produced by conventional methods, as described above. In another embodiment, the T cell culture medium promotes greater stability of the Treg (iTreg or nTreg) to maintain its Treg expression profile even in pro-inflammatory environments. In one embodiment, the iTreg cell of this aspect is characterized by increased FoxP3 expression. In one embodiment, the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole. In one embodiment, the T cell culture medium further comprises one or more additional Treg promoting compounds (also referred to as Treg “skewing” factors). Such additional skewing factors can include any FDA-approved drug or antibiotic known to promote Treg development/stability. Skewing factors can also include other microbiota metabolites (such as short-chain fatty acids, bile acids, polysaccharide A), dietary derived compounds (such as n3 polyunsaturated fatty acids, retinoic acid, and other vitamin-derivatives (VitD, VitC, etc.), polyphenols, quercetin, resveratrol, NSAIDS, TGF-β, rapamycin, IL-10, and IL-2. Other skewing factors that are useful for this purpose include curcumin, metformin/AMPK activators, PI3-kinase/Akt inhibitors, and PPAR agonists, as are known in the art. The T cell culture medium can also comprise any commonly known culture ingredients and factors that are known to maintain the viability of T cells in vitro at known concentrations. Exemplary methods for isolation, culturing, and stimulation of T cells are provided in more detail below. See, e.g., Examples 1-3.
As indicated above, the inventors also demonstrated that some TDMMs, such as 5-hydroxyindole (5-HI), induce differentiation of the naïve T cell into a T cell with a Th17 (pro-inflammatory) phenotype (referred to herein as a “Th17 cell”). Therefore, in another aspect, the disclosure provides a method of producing a Th17 cell, comprising contacting the naïve T cell with the TDMM, which results in the Th17 cell having a pro-inflammatory phenotype. In a further embodiment, the differentiated T cell expresses RORγT. In one embodiment, contacting of the T cell with the TDMM results in the differentiated cell having Th1 characteristics. In one embodiment, contacting of the T cell with the TDMM results in the differentiated cell able to inhibit Treg cells. In one embodiment, the TDMM is 5-hydroxyindole. It may also be shown that related hydroxyindoles may have such an effect in some environments.
In some embodiments, the naïve T cell is contacted with the pro-inflammatory TDMM (e.g., 5-HI, or a precursor, prodrug, or acceptable salt thereof, in vitro/ex vivo. In another embodiment, the pro-inflammatory TDMM (e.g., 5-HI, or a precursor, prodrug, or acceptable salt thereof, is administered to a subject in an amount such that the naïve T cell is contacted in vivo with an effective amount of the pro-inflammatory TDMM (e.g., 5-HI), or a precursor, prodrug, or acceptable salt thereof.
In another aspect, the disclosure provides a method of promoting a pro-inflammatory environment in a subject in need thereof. Such subject can, for example, be suffering from an infection or certain cancers where a pro-inflammatory response is desirable for therapeutic effect. The method can comprise promoting the differentiation of pro-inflammatory T cells (e.g., Th17 and Th1 cells) from naïve T cells by contacting the naïve T cells with a pro-inflammatory TDMM (e.g., 5-HI), or a precursor, prodrug, or acceptable salt thereof. The naïve T cells can be contacted with a pro-inflammatory TDMM (e.g., 5-HI, or a precursor, prodrug, or acceptable salt thereof, in vivo by direct administration of the TDMM (e.g., 5-HI), or a precursor, prodrug, or acceptable salt thereof. Alternatively, the naïve T cells can be contacted with a pro-inflammatory TDMM (e.g., 5-HI), or a precursor, prodrug, or acceptable salt thereof, in vitro/ex vivo and have expanded pro-inflammatory T cells administered to the subject. In another embodiment, the method is described as promoting the function of pro-inflammatory T cells (e.g., Th17 and Th1 cells). In this context, the method comprises contacting the naïve T cells and/or already differentiated Th17 and Th1 cells with a pro-inflammatory TDMM (e.g., 5-HI), or a precursor, prodrug, or acceptable salt thereof. In this embodiment, exposure to the pro-inflammatory TDMM (e.g., 5-HI), or a precursor, prodrug, or acceptable salt thereof, enhances the pro-inflammatory function of the cell, including providing more robust pro-inflammatory signaling.
Unless specifically defined herein, all terms used herein have the same meaning as they would to one skilled in the art of the present invention. Practitioners are particularly directed to Sambrook J., et al. (eds.) Molecular Cloning: A Laboratory Manual, 3rd ed., Cold Spring Harbor Press, Plainsview, N.Y. (2001); Ausubel F. M., et al. (eds.), Current Protocols in Molecular Biology, John Wiley & Sons, New York (2010); and Coligan J. E., et al. (eds.), Current Protocols in Immunology, John Wiley & Sons, New York (2010) for definitions and terms of art.
The use of the term “or” in the claims is used to mean “and/or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and/or.”
Following long-standing patent law, the words “a” and “an,” when used in conjunction with the word “comprising” in the claims or specification, denotes one or more, unless specifically noted.
Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like, are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to indicate, in the sense of “including, but not limited to.” Words using the singular or plural number also include the plural and singular number, respectively. Additionally, the words “herein,” “above,” and “below,” and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of the application.
Disclosed are materials, compositions, and components that can be used for, can be used in conjunction with, can be used in preparation for, or are products of the disclosed methods and compositions. It is understood that, when combinations, subsets, interactions, groups, etc., of these materials are disclosed, each of various individual and collective combinations is specifically contemplated, even though specific reference to each and every single combination and permutation of these compounds may not be explicitly disclosed. This concept applies to all aspects of this disclosure including, but not limited to, steps in the described methods. Thus, specific elements of any foregoing embodiments can be combined or substituted for elements in other embodiments. For example, if there are a variety of additional steps that can be performed, it is understood that each of these additional steps can be performed with any specific method steps or combination of method steps of the disclosed methods, and that each such combination or subset of combinations is specifically contemplated and should be considered disclosed. Additionally, it is understood that the embodiments described herein can be implemented using any suitable material such as those described elsewhere herein or as known in the art.
Publications cited herein and the subject matter for which they are cited are hereby specifically incorporated by reference in their entireties.
The following is a description of an investigation demonstrating the identification and use of tryptophan derived microbiota metabolites (TDMMs), such as indole, as potent regulators of T cell differentiation. Specifically, TDMMs are demonstrated as influencing the differentiation of T cells into robust, stable Treg cells, which are useful in therapeutic applications to address inflammatory diseases.

BRIEF SUMMARY

Regulatory T cells (Tregs) comprise a heterogeneous class of lymphocytes that are able to promote immune tolerance in peripheral tissue through cytokine secretion, cytolysis, metabolic disruption and modulation of dendritic cell function. Despite the limited comprehensive understanding of Treg biology, methods exist to selectively expand Tregs in vitro in presence of TGF-β (induced or iTregs) and transfer to patients for therapeutic inhibition of inflammation. Patients predicted to benefit from iTreg transfer include those suffering from inflammatory bowel disease, graft-versus-host disease and other pathology characterized by excessive inflammation. Although the adoptive transfer of iTregs has the promise to be safe in the clinic, major hurdles still exist in the translation of this therapeutic strategy from lab bench to bedside. For example, the iTregs transferred into a patient with acute or chronic inflammation may transition from the anti-inflammatory, iTreg phenotype to a pro-inflammatory, Th17 phenotype under the influence of inflammatory cytokines present in the microenvironment (such as IL-6), and thereby, negatively contribute to the inflammatory state. Therefore, iTregs that possess a stable regulatory phenotype and function when introduced into an inflammatory microenvironment will greatly enhance the adoptive iTreg transfer efficacy and safety.
Several studies link in vivo Treg development to the presence of an abundant and diverse microbiota in the intestinal tract. The microbiota is in homeostasis with the host in healthy individuals, and changes in abundance or diversity (dysbiosis) has been linked to several disorders (i.e., inflammatory disorders), both in the intestinal tract and systemically. Although the microbiota's precise role in physiologic immune tolerance is poorly understood, a prevalent hypothesis is that the microbiota produce specific factors that promote Treg induction and modulate gut immunity towards a tolerant state. In line with this notion, we have demonstrated that indole, a tryptophan derived microbiota metabolite (TDMM) that is present in the GI tract of both healthy mice and humans, attenuates indicators of inflammation. Data from our investigations show that, after conditioning in vitro in the presence of indole and under iTreg-skewing conditions, CD4+ CD25− naïve T cells dramatically expand into Foxp3+ iTregs; and under Th17-skewing conditions, indole reciprocally inhibit Th17 cell development; the indole-induced iTregs suppress effector T cell proliferation; and this effect is specific to Treg and Th17 cells.

INTRODUCTION

T Cells in the Intestinal Tissue During Physiologic and Pathologic Inflammatory Conditions
A substantial portion of the host immune system is located within the proximity of the GI tract. CD4+ T helper cells are found in organized gut associated lymphoid tissue (GALT), such as the Peyer's patches and isolated lymphoid follicles, as well as the epithelium and lamina propria of the GI tract [Koboziev, I., F. Karlsson, and M. B. Grisham, Ann NY Acad Sci, 1207 Suppl 1, pp. E86-93 (2010); Shale, M., C. Schiering, and F. Powrie, Immunol Rev 252:164-182 (2013)]. Both naïve and memory/effector T cells are present in the GI tract [Shale, M., C. Schiering, and F. Powrie, Immunol Rev 252:164-182 (2013)]. Activation of naïve T cells in the GALT or mesenteric lymph nodes by antigen presenting cells (APCs) conditioned in the unique cytokine/metabolite milieu of the GI tract promotes immune tolerance in physiologic conditions [Coombes, J. L. and F. Powrie, Nat Rev Immunol 8(6):435-46 (2008)]. Although anti-inflammatory T cells (i.e., Tregs) are found in abundance in the GI tract, pro-inflammatory Th cells are also present in large numbers [Shale, M., C. Schiering, and F. Powrie, Immunol Rev 252:164-182 (2013)].
The intestinal microbiota comprises ˜10¹⁴bacteria and other microbes and provides a constant onslaught of potentially inflammatory signals near the GALT [Hill, D. A. and D. Artis, Annu Rev Immunol 28:623-67 (2010)]. However, in a majority of people, excessive inflammation is avoided in the GI tract, and thus, a major function of the mucosal immune system is to promote homeostasis and avoid an overzealous immune response against commensal species of the microbiota [Izcue, A., J. L. Coombes, and F. Powrie, Annu Rev Immunol 27:313-38 (2009)]. On the other hand, the mucosal immune system is also able to mount potent attacks against invading pathogens in the GI tract, and it follows that the immune system must be able to mediate either noninflammatory tolerance or pro-inflammatory clearance of specific antigens [Maynard, C. L., et al., Nature 489(7415):231-41 (2012)]. Physiologically, Treg cells in the gastrointestinal tract promote long-term tolerance of commensal antigen derived from microbiota species [Lathrop, S. K., et al., Nature 478(7368):250-4 (2011)]. Treg cells are essential for maintaining homeostasis with the commensal microbiota, and they orchestrate a complex network of cytokine signaling mediated by both intestinal epithelial cells, innate and adaptive immune cells [Rescigno, M., U. Lopatin, and M. Chieppa, Curr Opin Immunol 20(6):669-75 (2008)]. In order to respond to pathogens, immune cells in the GALT are able to activate an antigen-specific immune response against a pathogen [Carvalho, F. A., et al., Annu Rev Physiol 74:177-98 (2012)], illustrating the necessary dichotomy of readily available proinflammatory as well as anti-inflammatory adaptive immune cells. The mechanisms that regulate the immune system's ability to co-exist and tolerate commensal antigen are not fully understood, and one hypothesis is that commensal microbiota species promote immune tolerance via the production of immunomodulatory metabolites [Arpaia, N., et al., Nature 504(7480):451-5 (2013); Furusawa, Y., et al., Nature 504(7480):446-50 (2013)].
T Cell Differentiation
The activation of naïve T cells normally involves differentiation of the activated T cell towards at least 4 different lineages based on cytokine signals received during activation (FIG. 1). IL-12 promotes expression of the master transcription regulator TBET, which induces a phenotype (Th1) that promotes cell-mediated immunity. IL-4 promotes expression of the master transcription regulator GATA3, which induces a phenotype (Th2) that promotes humoral immunity. TGF-β, a cytokine prominent in mucosal tissue, in the context of proinflammatory cytokines such as IL-6 promote expression of the master transcription regulator RORγT, which induces a phenotype (Th17) that promotes mucosal inflammation. On the other hand, TGF-β in the context of homeostatic cytokines such as IL-2 promotes expression of the master transcription regulator FOXP3, which induces a phenotype (Treg) that promotes tolerance to antigen and homeostasis.
While the role of host cytokines in T cell lineage decision has been extensively studied, the effects of microbiota-derived molecules on T-cell function and fate are not fully characterized (FIG. 1). The microbiota is a community of ˜10¹⁴symbiotic microbes that naturally inhabit the gastrointestinal (GI) tract and a majority of the host lymphoid tissue. However, the mechanisms that mediate communication between this microbial population and the host immune system have yet to be fully elucidated. Given the major role of the microbiota in host metabolism [Wikoff, W. R., et al., Proc Natl Acad Sci USA 106(10):3698-703 (2009)], one hypothesis is that microbiota-produced metabolites modulate the host immune response and is supported by studies showing that Treg development is linked to a diverse microbiota composition in vivo [Atarashi, K., et al., Science 331(6015):337-41 (2011); Ishikawa, H., et al., Clin Exp Immunol 153(1):127-35 (2008)]. Previous research has demonstrated that metabolites produced by the microbiota such as short-chain fatty acids (SCFAs), vitamins A and D, can influence immune function [Mora, J. R., M. Iwata, and U. H. von Andrian, Nat Rev Immunol 8(9):685-98 (2008); Kau, A. L., et al., Nature 474(7351): p. 327-36 (2011); Szeles, L., et al., J Immunol 182(4):2074-83 (2009)]. Recently, Arpaia et al. [Arpaia, N., et al., Nature 504(7480):451-5 (2013); Furusawa, Y., et al., Nature 504(7480):446-50 (2013)] recently reported that the SCFA butyrate and propionate promoted differentiation of naïve T cells to Treg cells. Similarly, Furusawa et al. [Furusawa, Y., et al., Nature 504(7480):446-50 (2013)] also showed that butyrate induces colonic differentiation of Tregs in mice. Despite these studies largely focused on a single SCFA metabolite, the effects of other classes of microbiota-derived metabolites on T cell differentiation are not fully understood.
In our previous work, we revealed that indole, a microbiota-derived metabolite from tryptophan, inhibits NF-κB activation and attenuates indicators of inflammation in intestinal epithelial cells (IECs) [Bansal, T., et al., Proc Natl Acad Sci USA 107(1):228-33 (2010)]. We have also recently made the observation that indole (a tryptophan-derived, microbiota metabolite; TDMM), in addition to its effects on IECs, strongly induces and augments naïve T cell differentiation to iTregs and reciprocally inhibits Th17 development (FIG. 3). This study seeks to determine if TDMMs such as indole can be used to control T cell differentiation and promote their differentiation to Treg cells.
Treg and Th17 Function in Health and Disease
Treg and Th17 T-cells are two major T cell lineages found at mucosal sites, such as the GI tract [Shale, M., C. Schiering, and F. Powrie, Immunol Rev 252:164-182 (2013)]. Tregs are an essential cellular determinant of immune homeostasis in most tissues. Tregs comprise a heterogeneous lineage of T lymphocytes that induce immune tolerance by cytokine secretion and modulation of either APC or effector lymphocyte function [Sakaguchi, S., et al., Nat Rev Immunol 10(7):490-500 (2010); Vignali, D. A., L. W. Collison, and C. J. Workman, Nat Rev Immunol 8(7):523-32 (2008)]. Tregs are classified based on FOXP3 expression, CD25HI expression and a number of other surface or functional markers, and are functionally identified by their suppression of effector T-cells in vitro and in vivo [Sakaguchi, S., et al., Nat Rev Immunol 10(7):490-500 (2010)]. In the thymus, “natural” Tregs (nTregs) are produced when FOXP3 is induced in developing T lymphocytes that bind tightly with thymic stromal cell self peptide-MHC complex; in the periphery, “induced” Tregs (iTregs) are produced when Th cells are activated by antigen presenting cells in the presence of IL-2 and TGF-β [Sakaguchi, S., et al., Cell 133(5):775-87 (2008)]. Perturbation of the Treg population in circulation and affected tissue is linked to autoimmune disorders [Baecher-Allan, C. and D. A. Hafler, Immunol Rev 212:203-216 (2006)] and IBD [Eastaff-Leung, N., et al., J Clin Immunol 30(1):80-9 (2010)].
Th17 cells play an important role in autoimmune and aberrant inflammatory responses of mucosal surfaces in the GI tract [Weaver, C. T., et al., Annu Rev Pathol 8:477-512 (2013)]. Th17 cells comprise a class of activated Th cells that express high levels of RORγT, IL-17, IL-17F, IL-21, and IL-22; in addition, Th17 cells are reported to readily differentiate to IFN-γ+, Tbet+ Th1-like cells in vivo [Zfiiga, L. A., et al., Immunol Rev 252:78-88 (2013)]. In the periphery, Th17 cells are produced when Th cell activation occurs in the presence of TGF-β and inflammatory cytokines such as IL-113, IL-6, and IL-23 [Shale, M., C. Schiering, and F. Powrie, Immunol Rev 252:164-182 (2013)]. Th17 cells and their secreted cytokines are increased in IBD [Eastaff-Leung, N., et al., J Clin Immunol 30(1):80-9 (2010)], and genome-wide association studies have linked IBD and polymorphisms in the receptor for IL-23, a main driver of pro-inflammatory Th17 differentiation [Weaver, C. T., et al., Annu Rev Pathol 8:477-512 (2013)]. Mouse models of IBD have shown a similar importance for Th17 cells in pathogenesis [Ahern, P. P., et al., Immunol Rev 226:147-159 (2008)]. Promotion of a Th17 response and subsequent inhibition of Tregs is thought to be important in the pathogenesis of aberrant inflammation in the GI tract [Ahern, P. P., et al., Immunol Rev 226:147-159 (2008); Ahern, P. P., et al., Immunity 33(2):279-288 (2010)].
A healthy microbiota is an essential factor in full development of the Treg compartment and homeostasis in the GI tract [Atarashi, K., et al., Science 331(6015):337-41 (2011); Ishikawa, H., et al., Clin Exp Immunol 153(1):127-35 (2008)]. Th17 cells are similarly dependent on microbiota (i.e., segmented filamentous bacteria, SFB) presence for proliferation in the GI tract, but the role of Th17 cells is reported to be clearance, rather than tolerance, of antigen [Shale, M., C. Schiering, and F. Powrie, Immunol Rev 252:164-182 (2013); Basu, R., R. D. Hatton, and C. T. Weaver, Immunol Rev 252:89-103 (2013)]. In addition to responding to foreign antigen, Th17 cells may also contribute to epithelial barrier integrity [Rutz, S., C. Eidenschenk, and W. Ouyang, Immunol Rev 252:116-132 (2013)]. The balance between Treg and Th17 responses in the GI tract relies on multiple regulatory nodes that when altered can lead to pathologic inflammation, that includes epithelial insult, microbiota dysbiosis, and development of genetic or epigenetic abnormalities in immune signaling pathways.
Adoptive Transfer Therapy and its Shortcomings
Environmental insult coupled with genetic predisposition can disrupt the homeostatic maintenance of immune tolerance, leading to inflammatory bowel disease (IBD) [Chassaing, B. and A. Darfeuille-Michaud, Gastroenterology 140(6):1720-28 (2011); Cho, J. H., Nat Rev Immunol 8(6):458-66 (2008); Kaur, N., et al., Gut Microbes 2(4):211-6 (2011); Tamboli, C. P., et al., Gut 53:1-4 (2004)], where normally beneficial pathways of innate immune cytokine signaling and adaptive immunity become pathologic [Kaser, A., S. Zeissig, and R. S. Blumberg, Annu Rev Immunol 28:573-621 (2010); Maloy, K. J. and F. Powrie, Nature 474(7351):298-306 (2011)], contributing to increased and chronic pro-inflammatory cytokine production and activation of inflammatory adaptive immune responses targeting commensal antigens [Man, S. M., N. O. Kaakoush, and H. M. Mitchell, Nat Rev Gastroenterol Hepatol 8(3):152-68 (2011)]. Ultimately, this results in chronic inflammation and tissue wounding that is only transiently relieved by current therapeutics, thus often requiring surgery [Baumgart, D. C. and W. J. Sandborn, The Lancet 369(9573):1641-1657 (2007)]. In addition, current general immunosuppressive treatments have major side effects such as immune deficiency, and thus, more selective immunosuppressive treatments, such as cell-based adoptive regulatory T cell therapy, could improve treatment for IBD patients [Fischbach, M. A., J. A. Bluestone, and W. A. Lim, Sci Transl Med 5(179):1-6 (2013); Himmel, M. E., et al., Immunology 136(2):115-22 (2012)].
Cell-based adoptive Treg therapy is at the leading-edge of clinical science with a number of promising features, as well as hurdles to be cleared, before successful implementation in the hospital setting. Unique features of adoptive Treg therapy compared to currently available small-molecule and biological drug treatments include the ability of the transferred Tregs to perform complex biological tasks, malleable selectivity in their action, ability to deliver therapeutic-benefit in a targeted manner and with a control circuit such that inter-patient genetic variability has a less variable effect than drug delivery and other current treatments, and finally, adoptive cellular therapy offers a wide variety of potential targets for bio-engineering. On the other hand, uncontrolled cell proliferation, revertant-differentiation, migration, and off-target tissue effects, and a substantially increased complexity for generating the Treg therapeutic, all provide ample challenge for researchers to overcome before this treatment can be used to its full potential [Fischbach, M. A., J. A. Bluestone, and W. A. Lim, Sci Transl Med 5(179):1-6 (2013)].
Based on studies in mouse models and preliminary clinical trials, adoptive transfer of Tregs as therapy for aberrant inflammation is a variation of cell-based therapy with data demonstrating benefit for a number of pathologies, including IBD, graft-versus host disease, type I diabetes, and a range of other auto-inflammatory disorders, [Himmel, M. E., et al., Immunology 136(2):115-22 (2012); Fantini, M. C., et al., Gut 55(5):671-80 (2006); Haribhai, D., et al., J Immunol 182(6):3461-8 (2009); Hippen, K. L., et al., Semin Immunol 23(6):462-8 (2011); Hippen, K. L., et al., Am J Transplant 11(6):1148-57 (2011); Roncarolo, M. G. and M. Battaglia, Nat Rev Immunol 7(8):585-98 (2007); Brunstein, C. G., et al., Blood 117(3):1061-70 (2011)]. The evidence that adoptive Treg transfer for IBD treatment is based in part on clinical and experimental data demonstrating that during IBD, the balance of pro-inflammatory Th17 cells and anti-inflammatory Treg cells is shifted towards pro-inflammatory Th17 cells causing aberrant inflammation [Eastaff-Leung, N., et al., J Clin Immunol 30(1):80-9 (2010)]. The current treatment options for IBD patients have drawbacks of non-specific and/or toxic mechanisms [Kalden, J. R. and H. Burkhardt, Autoimmune Disease: Treatment, in eLS2001, John Wiley & Sons, Ltd.]. While cell-based adoptive therapy has the potential to provide a more specific treatment with fewer side effects for these patients, inconsistent induction of a homogeneously tolerogenic Treg population [Roncarolo, M. G. and M. Battaglia, Nat Rev Immunol 7(8):585-98 (2007)] and the loss of regulatory phenotype of Tregs after transfer [Schmitt, E. G., et al., J Immunol 189(12):5638-48 (2012)] limit clinical implementation. Furthermore, the induction of Tregs in the GI tract and the relative functional importance of different pathways for Treg induction are not completely understood. A better understanding of the role of natural physiologic signals that promote Treg induction (e.g., microbiota metabolites) will provide the additional understanding necessary to fully develop Treg adoptive transfer as a viable therapeutic in IBD treatment.
A recent study by Atarashi et al. [Atarashi, K., et al., Nature 500(7461):232-6 (2013)] demonstrated that oral administration of a mixture of 17 Clostridia strains was able to induce expansion of Treg cells and attenuate inflammation in a colitis model. The present work demonstrates that specific metabolites produced by the intestinal bacteria can be used ex vivo to condition T-cells and promote Treg stability and expansion in vivo.
Stability of Treg and Th17 phenotypes under inflammatory conditions: Both Th17 and iTreg cells are induced by TGF-β, and this is the basis for the reciprocal nature of their differentiation. Th17 lineage T-cells will develop in the presence of additional pro-inflammatory cytokines (e.g., IL-1β, IL-6). In contrast, in the presence of TGF-β and IL-2, and host-metabolites in dendritic cells (e.g. retinoic acid), iTreg develop [Yamane, H. and W. E. Paul, Immunol Rev 252:12-23 (2013)]. Experimentally, investigators report that iTregs can revert to pro-inflammatory, Th17 cells in an inflamed environment [Yang, X. O., et al., Immunity 29(1):44-56 (2008); Zhou, L., et al., Nature 453(7192):236-40 (2008); Bailey-Bucktrout, S. L. and J. A. Bluestone, Trends Immunol 32(7):301-6 (2011)], suggesting that after transfer, revertant-iTregs may exacerbate the inflammation they were intended to resolve.
Although the mechanisms of Treg plasticity are unresolved, one theory is that iTregs induced in vitro, in contrast to nTregs or iTregs produced in vivo, switch to a pro-inflammatory, Th17 phenotype in the presence of inflammatory cytokines such as IL-113, IL-6, IL-23 despite the presence of anti-inflammatory cytokines in the GI tract (e.g. TGF-β); this notion is supported by data demonstrating epigenetic features of stable-Tregs are modified [Ohkura, N., Y. Kitagawa, and S. Sakaguchi, Immunity 38(3):414-23 (2013)]. Specifically, it has been proposed that stable Treg induction relies on both FOXP3 expression mediated by TCR signaling as well as demethylation of the FOXP3 promoter region, in addition to other Treg signature genes [Zheng, Y., et al., Nature 463(7282):808-12 (2010); Kim, H. P. and W. J. Leonard, J Exp Med 204(7):1543-51 (2007); Polansky, J. K., et al., Eur J Immunol 38(6): p. 1654-63 (2008); Ohkura, N., et al., Immunity 37(5): p. 785-99 (2012)]. This theory is attractive because it provides potential criteria by which to judge whether or not iTregs produced in vitro will be stable when reintroduced into the host.
Neural Network Modeling of Cellular Responses
Although the signaling pathways activated by individual cytokines such as TGF-β and IL-2 are known, interactions between these pathways are not fully understood [Arias, C. F., et al., J Theor Biol 349:109-20 (2014)]. Moreover, microbial metabolites such as indole are unlikely to bind to a single receptor or activate a single signaling pathway, which further complicates the signaling interactions. Therefore, T-cell differentiation modeling, such as the work of Hong et al., [Hong, T., et al., PLoS Comput Biol 7(7):e1002122 (2011)] has been largely phenomenological due to the lack of sufficient mechanistic and kinetic information [Hong, T., et al., PLoS Comput Biol 7(7):e1002122 (2011); Arias, C. F., et al., J Theor Biol 349:109-20 (2014); Reynolds, J., et al., Front Immunol 4:434 (2013)]. To-date, models on T-cell development have focused on the differentiation process per se and not on using the inputs to regulate the proportion of Tregs and Th17 (focus of our work). While our recent work [Jin, U. H., et al., Mol Pharmacol 85(5):777-88 (2014)] demonstrated that indole acts as both an agonist and antagonist for the aryl hydrocarbon receptor (AhR) in intestinal epithelial cells, unpublished data from our lab using AhR knockout mice show that some of the effects of indole are not AhR dependent. In the absence of a complete and accurate map of the molecular regulatory networks, develop a purely mechanistic model is unlikely.
Accordingly, neural networks are employed to develop a model. Empirical models have been extensively used for these types of problems [Gerlee, P. and A. R. A. Anderson, Biosystems 95:166-174 (2009); Huang, S., et al., Physical Review Letters 94:128701 (2005); Weng, G., U.S. Bhalla, and R. Iyengar, Science 284(5411):92-6 (1999)] as they do not require a detailed understanding of the mechanism and instead rely on accurately reproducing input-output data corresponding to measured quantities. One of the advantages of neural networks is that they are very flexible and can represent nonlinear or even dynamic behavior very well, assuming that an appropriate model structure and data set for training are available [Weng, G., U.S. Bhalla, and R. Iyengar, Science 284(5411):92-6 (1999)].
Results
Previously, signals known to promote iTreg induction in vitro include cytokines such as TGF-β and IL-2, exogenous dietary-derived, host-produced metabolites such as all-trans retinoic acid (vitamin A), pharmaceuticals such as rapamycin and short-lived T-cell receptor (TCR) stimulation (e.g. via anti-CD3 and anti-CD28 antibody treatment). Combinations of these conditions have been reported to induce Treg differentiation with varying stability [Hippen, K. L., et al., Am J Transplant 11(6):1148-57 (2011), Chen, W., et al., J Exp Med 198(12):1875-86 (2003); Jonuleit, H., et al., J Exp Med 192(9):1213-1222 (2000); Lu, L., et al., Plos One 6(9):e24590 (2011)]. Recent studies show that the microbiota also promote Treg development in the GI tract [Frei, R., et al., Allergy 67(4):451-61 (2012)], and microbiota-produced metabolites (e.g., SCFAs) are important for gut immune homeostasis [Kau, A. L., et al., Nature 474(7351):327-36 (2011)]. We have shown that indole, a TDMM that is present in the GI tract of both healthy mice and humans, attenuates indicators of inflammation [Bansal, T., et al., Proc Natl Acad Sci USA 107(1):228-33 (2010)]. However, the effect of TDMMs on Treg differentiation has not been previously addressed.
We addressed the utility and increased efficiency of incorporating indole into an expansion medium to produce differentiated Tregs from naïve T cells in vitro that may be suitable for clinical transfer to patients in need thereof.
First, we demonstrated the potent Treg augmenting (increased % and Foxp3 MFI) properties of indole. Our data show that addition of indole during differentiation of CD4+ CD25− naïve T cells (sorted to 98% purity) in Treg skewing conditions leads to a significant increase in the proportion of FoxP3+ iTregs (68.8% with 1 mM indole vs. 25% for the solvent control). Similarly, under Th17-skewing conditions, addition of 1 mM indole reciprocally inhibits the expansion of Th17 cells (13.5% with the solvent control to 1.4% with indole). FIG. 2A shows that the effect of indole on the increase in the proportion of FoxP3+ cells is dose-dependent. FIG. 2B shows that the effect of indole on the decrease in the proportion of IL-17+ cells is dose-dependent. Importantly, the levels of FoxP3 and IL-17 expression (MFI) are also significantly increased and decreased, respectively, by indole. The fact that indole induced FoxP3 even under Th0 conditions indicates that indole promotes Treg differentiation independently of TGFβ.
Next, we demonstrate how indole promotes robust Treg (Foxp3+ cells) development even when levels of TGF-β alone are below a threshold that can induce Tregs. Indole was administered to cells along with reduced titers of TGF-β, and Foxp3 was assessed to determine the Treg status. FIG. 3 illustrates that Treg induction occurs notwithstanding low levels of TGF-β, thus, demonstrating the potent accessory signaling induced by indole for optimal Treg induction.
Further, we demonstrated that the indole-induced iTregs are functional based on increased suppression of effector T cell proliferation, which is the hallmark of T cell function (FIGS. 4A-4C). FOXP3-EGFP naïve CD4+ CD25− cells cultured in αCD3/28 coated wells with Treg-skew cytokines and indole or solvent control were cultured for 72 hours, and assessed for FoxP3 expression and proliferation by CFSE dilution. Indole-induced iTreg cells have a higher per-cell expression of FOXP3 (GFP) both pre- and post-sort (FIG. 4D). Indole-conditioned Tregs suppress effector T cell proliferation function in a 72-hour suppression assay and secrete more TGF-β than conventional control iTregs (DMF) after overnight re-stimulation with αCD3 (FIGS. 4B and 4C). These results demonstrate the in vitro functionality of indole-induced iTregs as bona fide Tregs.
Furthermore, our preliminary data also show that indole's effect is specific for Treg and Th17 only (FIG. 5). When naïve CD4+ CD25− cells were cultured 72 hours in αCD3/28 coated wells with Th0-, Th1- or Th2-skew cytokines and indole or solvent control, followed by stimulation with PMA, Ionomycin and Golgi Plug for the last 5 hours of culture, no effect on the % of Th1 and Th2 cells was observed (in contrast to the significant effect that indole has on Treg and Th17 cells; see FIGS. 2A and 2B).
We also demonstrated that indole increases the stability of iTreg FoxP3 expression in vitro. We observed that FoxP3 expression is gradually lost in iTregs without continuous conditioning by Treg-skewing cytokines and upon TCR stimulation (αCD3/28). While control iTregs (DMF induced Tregs) lost FoxP3 expression after TCR stimulation, FoxP3 expression is maintained to a greater level when control iTregs are stimulated in the presence of indole (44.7 to 9.3% vs. 52.8 to 26.1%). In contrast, indole-induced iTregs increased FoxP3 stability when cultured for three days with 1 mM indole than with DMF (63 to 24.9% vs. 64.2 to 52.2%; rows 3 and 4). Furthermore, indole-induced iTregs maintain greater FoxP3 expression, compared to control iTregs with or without TCR stimulation. This data (not shown) demonstrate that indole during or after Treg development promotes increased FoxP4 stability.
The initial data described above were generated using indole to direct the differentiation of Tregs from naïve T cells. However, indole is but one of a broad-range of tryptophan derived microbiota metabolites (TDMMs) that are generated in vivo. Recent work from our laboratories [Jin, U. H., et al., Mol Pharmacol 85(5):777-88 (2014)] quantified the levels of a panel of six TDMMs, indole, hydroxyindole, indole-3-acetate, indolepyruvate, indole-3-acetamide, and tryptamine, in murine cecal contents using quantitative multiple reaction monitoring mass spectrometry. In a further study, we investigated if two other TDMMs, 5-hydroxyindole and indolepyruvate, exert similar effects on T cell differentiation as indole. Table 7 shows that 5-hydroxyindole has the opposite effect as indole, i.e., it increases Th17 cells while decreasing the Treg population. On the other hand, indolepyruvate behaves similar to indole as it leads to a modest (but significant) decrease in Th17 while increasing Treg cells. These data suggest that not all TDMMs exert the same effect and underscore the importance of investigating a panel of TDMMs.

TABLE 7

Preliminary TDMM screen results

TDMM	Treg Induction	Th17 Inhibition

DMF control	Baseline	Baseline
Indole	+	+
5-hydroxyindole	−	−
(5-HI)
Indole-3-pyruvate	+	+

To determine the optimal induction conditions for Treg differentiation in vitro without independently varying each potential parameter (e.g., pro- and anti-inflammatory cytokines, concentrations of medium components, culture conditions, etc.), an integrated experimental/computational approach was employed. Specifically, optimization of Treg induction and Th17 attenuation conditions and assessing their function upon transplantation was performed using neural network analysis. Neural networks can be used as model structures as they are very flexible and can represent data with nonlinearities well [Gerlee, P. and A. R. A. Anderson, Biosystems 95:166-174 (2009); Huang, Z. and J. Hahn, Chem Eng Sci 64(9):2044-2056 (2009); Pearson, R. K. and B. Ogunnaike, Nonlinear Process Identification, in Nonlinear Process Control, M. K. Henson and D. Seborg (eds.), p. 11-57 (1996)]. Furthermore, neural networks have been previously shown to be useful for these types of complex problems as the details of the signaling mechanism(s) underlying the effect of indole on T cells are not known [Weng, G., U.S. Bhalla, and R. Iyengar, Science 284(5411):92-6 (1999)].
We carried out a preliminary study to demonstrate that the % Treg and Th17 data described above is suitable for developing a neural network model. Since IL4 is known to attenuate Treg differentiation and our initial data (FIGS. 2A and 2B) show that indole enhances Treg development, we carried out a preliminary Treg skew experiment where CD4+ CD25− naïve T cells were exposed to different concentrations of indole and IL-4 and the % of Treg cells formed determined using ICS flow cytometry. Part of the data was used to develop a neural network with two hidden layers (one with 3 neurons and the other one with 2 neurons). The identified neural network led to two predictions: (i) the % of iTreg cells does not linearly increase between exposure to 500 LM and 1000 LM of indole. Instead, the model predicts a higher % Treg cells with 500 LM than at 1000 μM, at low concentrations of IL-4; and (ii) for concentrations of indole less than 500 μM, a moderate-to-low concentration of IL-4 (<5 ng/mL) inhibits % Tregs more than a higher dose (10 ng/mL). The model predictions were also verified experimentally. We verified that in the absence of IL-4, an indole concentration of 750 μM results in a 4% increase in the % of FOXP3+ cells compared to cells exposed to 1 mM indole (not shown). Similarly, with indole concentrations of less than 500 μM, an IL-4 concentration of 6 ng/mL leads to a higher reduction in the % of FOXP3+ cells compared to 10 ng/mL of IL-4 (25% vs. 28% FoxP3+ cells, respectively; not shown). These data clearly demonstrate the feasibility of this computational approach to optimizing in vitro Treg differentiation conditions and that data such as described above can be used to develop a neural network model useful to predict the proportion of Treg cells.
Based on the initial results described above, we pursued expanded assays to further characterize the effects of TDMMs on differentiation of naïve T cells and the impact on in vivo disease models. The following is a brief description of results generated in the expanded study. The methodologies used are similar to what has been described herein above and in the Examples.
First, an expanded panel of TDMMs was assessed for effect on naïve T cell maturation. Naïve T cells were conditioned with DMF and a panel of six different TDMMs predicted to have an influence on maturation. Cells were stained for markers of Treg cells (i.e., FoxP3) and Th17 (IL-17) cells and counted with FACS. FIG. 6 is a series of illustrative FACS results showing the effect of the panel of TDMM on naïve T cells differentiation into FoxP3+ Treg cells. The screen shows that indole has a strong pro-Treg response and inhibits a Th17 response, whereas 5-HI has a pro-Th17 response and inhibits a Treg response. Other tested TDMMs also show varying degrees of pro-Treg responses.
Indole was again assessed for its ability to skew differentiation of naïve T cells. Cell surface markers characteristic for Th1, Th2, Th17 and Treg cells were assessed using FACS in activated T cells that had previously been conditioned with indole. Confirming the result described above for FIGS. 5A and 5B, indole did not influence the development of Th1 and Th2 cells. However, as indicated in FIGS. 7A and 7B, indole has a significant skewing effect on naïve T cell differentiation into Th17 (IL-17+) (FIG. 7A) and Treg (FoxP3+) (FIG. 7B) cells. Indole significantly decreased the % of IL-17+ cells and significantly increased the % of FoxP3+ cells. This indicates that the skewing effects of indole is specific to the Treg/Th17 balance and does not affect Th1 or Th2.
5-hydroxyindole (5-HI) was similarly assayed. FIGS. 8A-8D graphically illustrate the skewing effect of 5-hydroxyindole (5-HI) on naïve T cell differentiation into Th1 cells (INF-γ+) (FIG. 8A), Th2 cells (IL-4+) (FIG. 8B), Th17 cells (IL-17+) (FIG. 9C), and Treg cells (FoxP3+) (FIG. 9C) cells. The data show that 5-HI promotes Th1 and Th17 differentiation and strongly inhibits Treg differentiation.
Moreover, other compositions, namely a panel short chain fatty acids (SCFAs), were assessed for their influence on naïve T cell differentiation. SFCAs, which are also produced by the microbiota, are thought to have potent skewing effects on maturing T cells. Specifically, butyrate, acetate, and propionate were used to condition naïve T cells under traditional Th0, Treg, and Th17 skewing conditions. The cells were counted in FACS for IL-17 and FoxP3 expression. The results indicated that propionate increases Treg and Th17 development, acetate increases Th17 development but with no effect on Treg development, and butyrate increases both Th17 and Treg development. Butyrate was selected for additional characterization. As shown in FIGS. 9A-9F, 1-butyrate has a skewing effect on naïve T cell differentiation. FIG. 9A shows the % INF-γ+ cells after exposure to increasing concentrations of 1-butyrate, indicating an induction of Th1 differentiation. FIG. 9B shows the % IL-4+ cells after exposure to increasing concentrations of 1-butyrate, indicating an inhibition of Th2 differentiation. Moreover, FIGS. 9C and 9D show the % INF-γ+ cells after exposure to 1-butyrate with and without indole under Th0 and Th2-skewing conditions, respectively. FIGS. 9E and 9F show the % INF-γ+ cells after exposure to 1-butyrate with and without indole under Th17 and Treg-skewing conditions, respectively.
Next, the iTregs induced by indole were further characterized. First, the effect of indole-based induction was assessed for known gut homing markers in Treg cells. As shown in FIG. 10, indole increases the % of α4β7+ in FoxP3+ cells, and that the effect is amplified when combined with retinoic acid (RA), indicating synergy between indole and RA. Furthermore, as shown in FIG. 11, indole results in an increase of CD62L+ on FoxP3+ cells with and without combination with retinoic acid (RA). Thus, the effect is independent of RA.
The interaction of indole with various SCFAs was assessed on the expression of Treg gut homing marker α4β7+. Tregs were differentiated in multiple concentrations of indole and acetate, propionate, and butyrate, and assessed for α4β7+ presence. As shown in FIGS. 12A-12C, which illustrate the expression of marker α4β7 (% α4β7+) on iTreg cells conditioned with indole and with different concentrations of short chain fatty acids (SCFAs) acetate (FIG. 12A), propionate (FIG. 12B), and butyrate (FIG. 12C), indole increases α4β7 in the presence of SCFAs, except for high levels of butyrate.
Next, a suppression assay was performed, demonstrating that indole-induced iTregs perform better, i.e., have stronger suppressive characteristics, than nTregs or iTregs induced by butyrate. Specifically, FIG. 13 graphically illustrates the results of the suppression assay, showing the suppression of T-cell proliferation as determined by IL-2 production (an essential marker of T-cell proliferation) with increased proportions of Tregs added to co-cultures with effector T-cells.. This data indicates that indole-induced iTregs function in a superior manner than traditional iTregs induced by butyrate or “natural” Tregs isolated from the thymus (nTregs).
The iTregs were next assessed for cytokine production when conditioned with indole or butyrate. FIG. 14A shows the GFP MFI of GFP+ cells pre- and post-sorting. As shown in FIGS. 14B and 14C, the indole-conditioned iTregs increased TGF-β expression over butyrate-conditioned iTregs, whereas indole conditioning uniquely resulted in inhibition of IL-10 expression.
Next, 5-HI and indole were assessed for their respective effects on Th17 and Treg cells, in the context of other skewin agents as such as IL-6 and TGF-β. As shown in FIG. 15A, exposure to 5HI with low and high titrations of IL-6 increased the % IL-17+ cells. This demonstrates that 5-HI induces Th17 T cells when IL-6 is below its respective concentration threshold for Th17 induction. Similarly, as shown in FIG. 15B, exposure to indole with low and high titrations of TGF-β increased the % FoxP3+ cells. This demonstrates that indole induces iTregs even when TGF-β is below its respective concentration threshold for iTreg induction.
Indole and 5-HI were assessed for impact on TGF-β receptor expression and SMAD2/3 activity. As shown in FIG. 16A, the % TGF-β receptor+ cell levels significantly increase when conditioned with indole, but not with 5-HI. As shown in FIG. 16B, the % of pSMAD2/3+ cells is higher when conditioned with indole as compared to 5-HI or DMF control. This indicates that indole augments the TGF-β induced SMAD2/3 activation. Indole and 5-HI were also assessed for impact on IL-6 receptor levels and subsequent STAT3 activity. As shown in FIG. 16C, the % IL-6 receptor+cell levels decrease when conditioned with indole, but not with 5-HI. As shown in FIG. 16D, the % pSTAT3+ cells decrease when conditioned with indole, as compared to control and 5-HI. These data indicate that indole inhibits the IL-6 receptor expression and IL-6 induced stat3 activation, whereas 5-HI augments the IL-6 induced stat3 expression.
The aryl hydrocarbon receptor (AhR) is implicated in the differentiation of Treg and Th17 cells. The role of AhR was assessed with respect to indole's effect on Treg augmentation. Wild-type and AhR KO naïve T-cells were conditioned with increasing amounts of indole and then assessed for % of FoxP3 expression. As shown in FIG. 17, FoxP3+ % increased significantly more in wild-type over AhR KO T cells after conditioning with indole. This indicates that indole augments Treg development in an AhR-dependent manner. Additionally, the role of AhR was assessed with respect to indole's effect on Th17 inhibition. As shown in FIG. 18, the % IL-17+ decreased significantly more in wild-type over AhR KO T cells after conditioning with indole. This indicates that indole inhibits Th17 development in an AhR-dependent manner.
The AhR knockout was further investigated for iTreg homing markers, CD62L and α4β7, as described above. As illustrated in FIGS. 19A and 19B, expression of CD62L and α4β7 in FoxP3+ wild-type or AhR KO T cells after conditioning with indole, with or without RA, was roughly equivalent with only minor differences. This indicates that indole augments Treg α4β7 expression and CD62L in an AhR-independent manner.
Next, the AhR knockout was further investigated for the impact of AhR on 5-HI-mediated T cell differentiation. As shown in FIG. 20, the increase of % of IFN-γ+ T cells (i.e., Th1 skew) in AhR KO T cells is not significantly different than in wild-type cells after conditioning with 5-HI. This indicates that 5-HI augmentation of Th1 differentiation is AhR-independent. As shown in FIG. 21, the % of IL-17+T cells (i.e., Th17 skew) in AhR KO T cells is significantly increased over wild-type cells after conditioning with 5-HI. This indicates that 5-HI augmentation of Th17 differentiation is AhR-independent. As shown in FIG. 22, the % FoxP3+ T cells decreases similarly in wild-type and AhR KO cells when conditioned with 5-HI. This indicates that 5-HI inhibits Tregs in an Ahr-independent manner.
The mechanistic target of rapamycin (mTOR) is a core component in multiple protein complexes that have significant influence on various cellular processes including cell growth, differentiation, and even enteropathies in the intestine. Accordingly, the interaction of indole and 5-HI on mTor activation was investigated. As shown in FIG. 23, mTOR activation by indole and 5-HI, as determined by % P-S6 in matured T cells conditioned with 5-HI or indole, is significantly reduced for indole-conditioned T cells but not 5-HI conditioned T cells. This illustrates that indole inhibits mTor activity.
Considering that indole and 5-HI has opposing effects, their mutual interactions were investigated on naïve T cells when under Th1, Th17, and Treg skewing conditions. As shown in FIG. 24A, indole did not affect the Th1 skewing of Th1 cells. However, the increase in % IFN-γ+ cells in Th1 skewing conditions observed after conditioning with 5-HI alone is negated when 5-HI is combined with indole. As illustrated in FIG. 24B, indole inhibits the development of illustrates % IL-17+ cells, confirming preliminary data described above. Moreover, the significant increase in % IL-17+ cells after conditioning 5-HI is not just negated, but actually reversed, when conditioned in combination with indole. As shown in FIG. 24C, indole significantly increased the % FoxP3+ cells, whereas 5-HI decreased the % FoxP3+ cells. When combined, indole negated the inhibitory effects of 5-HI on % FoxP3+ cells. These data illustrate that indole, when exposed along with 5-HI, overrides and negates the influence of 5-HI.
Along the same approach, the interaction of indole and 5-HI on T cell differentiation was further investigated of butyrate exposure. FIG. 25 A shows T cell differentiation under Th1 skewing conditions. As shown, butyrate alone results in increased % IFN-γ+ cells, whereas when combined with indole, the % IFN-γ+ cells decreases, regardless of 5-HI presence. This indicates that under Th1 skewing conditions, indole is dominant over the effects of 5-HI and butyrate. As shown in FIG. 24B, butyrate and 5-HI each cause an increase in % IL-17+ cells, which is generally reversed after conditioning with indole. This indicates that indole is also dominant over the effects of 5-HI and butyrate under Th17 skewing conditions. As shown in FIG. 24C, the % FoxP3+ cells increased with both butyrate and indole, but decreased with 5-HI. When all were combined, the % FoxP3+ increased again. This indicates that under Treg skewing conditions, indole is dominant over the effects of 5-HI. These data illustrate that indole, when exposed along with 5-HI, overrides and negates the influence of 5-HI even in the presence of butyrate.
The skewing effects of indole and 5-HI on Tregs and Th17 cells, described above were recapitulated on naïve T cells obtained from humans, demonstrating the consistency of the observed effects described above between the murine model and humans and indicating that therapeutic utility can be realized for human-derived cells and human subjects.
The presentation describes a study of inducing Treg activation in vivo by administering indole and/or butyrate directly to the mice followed by a characterization of cell harvested from the spleen and lymph nodes. These results indicate indole can augment Treg development in vivo when administered to the subject directly. Additionally, it indicates that the co-administration of SCFAs with the indole can provide at least an additive if not synergistic effect toward skewing development of T cells towards iTregs. Exemplary SCFAs include but are not limited by butyrate and propionate. FIGS. 26A-26C graphically illustrate the in vivo activation of Th1 cells in spleens after administration by indole, butyrate and αCD3. Generally, mice were administered amounts of αCD3, indole, and/or butyrate at 0 and 48 hrs. After 52 additional hours, the spleens were harvested and homogenized. Cells were plated, stimulated with PMA/lonomycin, stained for the indicated T cell markers, and subjected to FACS analysis. The graphs show the % IFN-γ+ CD4+ cells (FIG. 26A), the % IFN-γ+ CD4+ CD44^lowcells (FIG. 26B), and the % IFN-γ+ CD4+ CD44^highcells (FIG. 26C) resulting from the various treatments. These data demonstrate that butyrate augments Th1 differentiation in vivo, but indole suppresses butyrate induction of Th1 cells in vivo. FIGS. 27A-27C graphically illustrate the in vivo Treg cell activation in mesenteric lymph nodes (MLN) when stimulated by indole, butyrate and αCD3. Mice were administered amounts of αCD3, indole, and/or butyrate as described above, except the MLN were harvested and homogenized, and analyzed as described. The graphs show the % IFN γ+ CD4+ cells (FIG. 27A), the % IFN γ+ CD4+ CD44low cells (FIG. 27B), and the % IFN γ+ CD4+ CD44high cells (FIG. 27C) resulting from the various treatments. These data show that butyrate augments Treg differentiation in vivo, and that indole synergizes with butyrate for the induction of Treg cells in vivo.
Finally, the presentation describes a study of the effects of an indole-induced iTreg skew on the course of colitis in a Th17 transfer colitis murine model. The results indicated that indole inhibited Th17 transfer colitis in vivo, at least via Treg skewing, whereas 5-HI exacerbates the transfer colitis condition. Briefly, naïve T-cells (CD4+CD25−) were cultured in vitro with cytokines to skew function towards a Th17 phenotype, in the presence of indole or 5-HI, or not. The skewed cultures were transferred to Rag-null mice (lack T- and B-lymphocytes); control mice received no T-cells. Mice were monitored for weight loss (as a measure of inflammation) over several weeks and assessed at indicated timepoints for T-cell phenotype.
The body weight of the mice was monitored from the time of cell transfer to the end point of day 49. As shown in FIG. 28, the weight change (% from starting weight) declined precipitously for mice receiving DMF or 5-HI conditioned Th17 T cells around day 43, wherein mice receiving indole conditioned Th17 T cells had an increase in body weight. Thus, indole inhibits the Th17 transfer colitis in vivo, whereas 5-HI exacerbates Th17 transfer colitis in vivo. Next, the Treg, Th17, and Th1 differentiation was assessed in cells obtained from the mesenteric lymph nodes (MLN) of mice administered directly with indole, 5-HI and control. These cells were determined/assayed by FACS for phenotype directly ex vivo from mice that were treated as in FIG. 28. As shown in FIGS. 29A and 29B, exposure to indole induced early differentiation of Treg differentiation in vivo during Th17 transfer colitis increase, as indicated by an increase in % FoxP3+ T cells and FoxP3+ levels, respectively. The % IL-17+ T cells and Th17/Treg balance obtained from the MLN of a Th17 transfer colitis model at D15 and D45 are shown in FIGS. 30A and 30B, respectively. The data demonstrate that indole induces suppresses Th17 differentiation in vivo by the end point of Th17 transfer colitis model, whereas 5-HI increases the number of Th17 differentiation in vivo by the end point of Th17 transfer colitis model. The % INF-γ+ T cells and Th1/Treg balance obtained from the MLN of a Th17 transfer colitis model at D15 and D45 are shown in FIGS. 31A and 31B, respectively. The data demonstrate that indole induces suppresses Th1 differentiation in vivo by the end point of Th17 transfer colitis model, whereas 5-HI increases the number of Th17 differentiation in vivo by the end point of Th17 transfer colitis model.
Finally, FIGS. 32A and 32B graphically illustrate that indole inhibits colitis in a T-cell-dependent manner. For FIG. 32A, wild-type C57B16 mice were treated with 5% DSS, or not, in drinking water for 7 days. At this point, mice were treated with indole or not for an additional 7 days. Individual mouse weight was recorded daily throughout experiment as a measure of inflammation. For FIG. 32B, Rag-deficient mice, which lack lymphocytes (T- and B-cells), were treated as in FIG. 32A and individual weight was recorded.
The following examples provide descriptions of illustrative methodologies related to the present disclosure and are not limiting to the scope thereof.

Example 1

The following is a description of methodology to isolate naïve T cells and assay the effect of any TDMM on the potential differentiation into Treg (or other) cell type.
Mesenteric lymph node (MLN) and spleen are harvested from WT or FOXP3^EGFPC57Bl/6 mice and homogenized. Spleen tissue is subjected to red blood cell lysis and pooled into a single cell suspension for counting. Counted cells are resuspended in sterile FACS buffer (PBS++ with 05% bovine serum albumin) at a concentration of ˜5×10⁷cells/mL and stained for 45 minutes at 4° C. with anti-CD4 and anti-CD25 fluorophore-conjugated monoclonal antibodies (mAb). After two washes, the stained cells are resuspended at ˜6×10⁶cells/mL in FACS buffer and immediately sorted. High purity (>95%) CD4+ CD25− naïve T cells (1×10⁶cells/mL) are cultured in anti-CD3 mAb (5 μg/mL) and anti-CD28 mAb (2 μg/mL) coated plates in the presence of TGF-β (5 ng/mL), IL-2 (100 U/mL), and desired TDMMs or a solvent control for at least 72 hours. TDMMs are solubilized in DMF at 2 M and used at desired concentrations (e.g., 0.01, 0.1, 0.5 and 1.0 mM) in growth media; DMF in growth media (0.05%) is used as a solvent control.
The % of Treg or Th17 cells are determined based on the expression of signature transcription factors, FoxP3 and Rorγt, respectively. In addition, signature cytokine markers for Treg and Th17, TGFβ or IL-17, respectively, among others are measured using intracellular cytokine staining. Since it is possible that a cell could be positive for FoxP3 and still express some IL-17, the final % of Tregs are determined as the cell population that is FoxP3+TGFβ+ Rorγt-IL-17−. Similarly, the % of Th17 cells are determined as the population that is FoxP3-TGFβ− Rorγt+IL-17+.

Example 2

The following is an additional description of an exemplary procedure that was used to isolate naïve T cells and induce differentiation in vitro.
Cell Isolation
CD4+ CD25− T cells were isolated to high purity (>98%) from the pooled spleen and mesenteric lymph nodes of C57BL/6 mice (Jackson Labs) with a BD FACS Aria II flow cytometer. Fc Block (BD), αCD4-efluor450 (eBioscience clone GK1.5) and αCD25-PECy7 (eBioscience clone PC61.5) antibodies were used for staining before sorting.
In Vitro T Cell Differentiation
Isolated cells were cultured at an initial concentration of 1×10⁵cells/well in RPMI 1640 supplemented with 2-mercaptoethanol, gentamicin, penicillin, streptomycin, and 10% FCS (all from Life Technologies) in a 96-well round bottom plate (Falcon) coated with 5 μg/mL αCD3 (BioXcell clone 145-2C11) and 2 μg/mL αCD28 (BioXcell clone 37.51) for 72 hours. For Th1-skew: 5 ng/mL IL-12 (Peprotech cat. #210-12) and 10 g/mL αIL-4 (BioXCell clone 11B11) were added to culture. For Th2-skew: 10 ng/mL IL-4 (Peprotech) and 10 μg/mL αIFN-γ (BioXCell clone R4-6A2) were added to culture. For Th17-skew: 10 ng/mL IL-6 (Peprotech), 5 ng/mL IL-23 (R&D), 0.5 ng/mL TGF-β (Peprotech), 10 μg/mL al-4 (BioXCell clone 11B11), and 10 μg/mL αIFN-γ (BioXCell clone R4-6A2) were added to culture. For Treg-skew: 2 ng/mL TGF-β (Peprotech) and 100 U/mL IL-2 (Roche) were added to culture. Sodium Propionate, sodium acetate, sodium butyrate and sodium chloride (all from Sigma-Aldrich) were solubilized in media and added to culture. Indole was solubilized in DMF (both from Sigma-Aldrich) at 2M and brought to final concentration in media. MGCD0103 (Selleck Chemicals) was solubilized in DMF at 2 mM and brought to final concentration in media. A 0.05% DMF solvent control was used for all experiments.

Example 3

The following is a description of methodology to characterize the subset of stimulation conditions and resulting differentiated iTreg cells.
Naïve T cells are cultured for 3 days using concentrations of cytokines and TDMMs that resulting in a significant increase in the levels of iTreg cells. After 72 h, cells are stimulated with PMA/ionomycin (10 ng/mL PMA, 1 mM ionomycin). For flow cytometry, cells are treated with Golgi plug (Brefeldin A) for four hours and then stained with fluorophore-conjugated mAbs against both inflammatory (e.g., IL-6, IL-12, IL-17, TNF-α) and anti-inflammatory (e.g., IL-10, IL-35, TGF-β) cytokines. Samples are stained with the maximum number of antibodies. Furthermore, expression of established Treg markers (FOXP3, CD25hi, CD103, CD62L, GITR, PD-1, CD152, CD127, ICOS, Granzyme-B) [Vignali, D. A., L. W. Collison, and C. J. Workman, Nat Rev Immunol 8(7):523-32. (2008); Chen, J., et al., Int Immunopharmacol 11(5):610-7 (2011)] and markers of an inflammatory phenotype (RORγT) can be analyzed. For ELISA of secreted cytokines, culture supernatants are collected after 18 hours of PMA/ionomycin stimulation and stored at −20° C. until analysis for secreted cytokines. For all conditions, Tregs generated without the TDMM can be used as the control. The effect of the TDMMs on suppression of effector T cell proliferation is determined as described for FIG. 4. Such assays permit determination of whether the iTregs generated with different TDMMs are functional as natural Tregs.

Example 4

The following is a description of methodology to determine the resistance or susceptibility of TDMM-conditioned iTregs to inflammatory stimuli.
As described above in Example 2, any subset of conditions that results in increased Treg cells can be tested for the cells' response to inflammatory cytokines. For example, TDMM- and control-induced Treg cultures from CD4+ CD25− GFP− naïve T cells of FOXP3EGFP mice are sorted based on GFP fluorescence. GFP+ cells (˜1×10⁶cells/mL) are cultured in the presence of pro-inflammatory cytokines IL-1, IL-6, IL-21 and IL-23 ±TCR stimulation on an anti-CD3/CD28 mAb coated plate for 24, 48 and 72 hours [Yang, X. O., et al., Immunity 29(1): p. 44-56 (2008); Zhou, L., et al., Nature 453(7192): p. 236-40 (2008)]. This mimics in vitro adoptive transfer of induced Tregs into an inflammatory environment, which is a major hurdle in Treg transfer therapy. Next, the stability (as measured by expression of FOXP3, RORγT, TGF-β, IL-10, IL-35 and IL-17) of TDMM-conditioned Tregs is analyzed compared to control-induced Tregs by ELISA of supernatants or 4 h treatment with Golgi plug (for cytokine staining) and subsequent intracellular staining with fluorophore-conjugated mAbs and flow cytometry.

Example 5

The following is an overview of an illustrative methodology to determine the phenotypic and functional properties of TDMM- and control-induced Th17 cells.
An important objective is to minimize the proportion of Th17 cells produced under the Treg skewing conditions because both Tregs and Th17 cells may be present in the same population. Although functional readouts for Th17 cells are less well described than Tregs, Th17 cells are known to express high levels of multiple IL-17 class of cytokines and also IL-22 [Rutz, S., C. Eidenschenk, and W. Ouyang, Immunol Rev 252:116-132 (2013)]. Therefore, using flow cytometry or ELISA, the levels of the IL-17 family of cytokines and IL-22 produced by TDMM- and control-induced Th17 cells can be determined. In addition, the expression level of the master Th17 transcription factor Rorγt can be determined, as unpublished data from our laboratories show that indole also inhibits Rorγt expression in Th17 cells to identify TDMM and skew conditions that lead to attenuation of Th17 responses. As with Examples 3 and 4, such experiments can be carried out with conditions that are demonstrated to give a positive response (increased iTregs or attenuated Th17).

Example 6

The following is an overview of an illustrative methodology to determine the function and stability of TDMM-induced iTregs and TDMM-attenuated Th17 cells after transfer to an in vivo environment.
Rationale: Treg cell-based therapy is largely dependent on the in vivo function and stability of the transferred cells. Thus, the stability of indole- and control-induced iTreg cells can be examined in vivo. Murine models of colitis have decreased severity after either iTreg transfer [Fantini, M. C., et al., Gut 55(5):671-80 (2006); Haribhai, D., et al., J Immunol 182(6):3461-8 (2009); Schmitt, E. G., et al., J Immunol 189(12): p. 5638-48 (2012)] or Treg expansion in vivo via biological administration [Chen, J., et al., Int Immunopharmacol 11(5):610-7 (2011)], so the DSS-induced colitis model [Cooper, H. S., et al., Laboratory investigation; a journal of technical methods and pathology 69(2): p. 238-249 (1993); Wirtz, S., et al., Nat Protoc 2(3):541-6 (2007)] can be used as a background inflammatory state on which to test the indole-induced iTregs produced in Example 1. Furthermore, control and indole iTregs to can be transferred to lymphopenic mice to examine indole-induced Tregs' stability during homeostatic proliferation.
Generally, differentiate TDMM- and control-induced Tregs are differentiated from CD4+ CD25− GFP− naïve T cells from WT or FOXP3EGFP mice on a C57Bl/6 background. Initially, the optimal TDMM concentrations predicted from the neural network to carry out preliminary iTreg transplantation experiments. As data from these in vivo experiments become available, it can be continuously used for model development/refinement by neural network optimization. Sorted CD4+ CD25− GFP− naïve T cells from the spleen and MLN are cultured for at least 72 hours with TCR stimulation on an anti-CD3/CD28 mAb coated plate and Treg skewing conditions±TDMMs, as described in Example 1. When appropriate, cells are sorted based on GFP fluorescence, selecting GFP+ cells for subsequent adoptive transfer. Thy1.1+ congenic C57Bl/6 mice can be used as recipients for Thy1.2+ GFP+ control- or indole-induced Treg transfer in experiments to analyze transferred cells. Analysis of transferred cells can include stability assays. Specifically, cervical and axillary lymph nodes, spleen, gut associated lymph tissue and intestinal lamina propria cells are harvested in order to analyze the presence and/or expansion of transferred Tregs via flow cytometry, ELISA and in vitro effector T cell suppression assays.

Example 7

The following is a description of an illustrative methodology to determine therapeutic efficacy of TDMM-induced iTregs after adoptive transfer to hosts with experimental colitis.
The experimental design involves two cell types (TDMM or solvent-treated iTregs) and two treatment groups (DSS and control). WT C57Bl/6 mice (n=10 per group) are given 5% DSS in drinking water for 7 days and regular water for 7 days of recovery. Body weights are recorded daily. At either day 6 or when mice have lost 10% of initial body weight (whichever comes first), 1×10⁶TDMM- or control-induced GFP+ Tregs (generated as described above) is administered via I.P. injection. Control DSS-treated mice receive a sham injection, and control H₂O-treated mice (i.e., no DSS injury) receive either 1×10⁶TDMM- or control-induced GFP+ Tregs or a sham injection. Mice are sacrificed 14 days after the start of the experiment. Serum is collected for quantification of inflammatory cytokines (e.g., IL-17, IFN-γ, TNF-α). Colon weight and length is recorded, and processed for histopathological scoring [Wirtz, S., et al., Nat Protoc 2(3):541-6 (2007)]. Therapeutic efficacy can be determined as decreased overall weight loss, decreased stool hematocrit, decreased inflammatory monocyte/granulocyte infiltration to colon, and decreased epithelial hyperplasia compared to control DSS-treated mice.

Example 8

The following is a description of an illustrative methodology to determine the stability and persistence of TDMM-induced iTregs after transfer to normal and colitic hosts.
Thy1.1+ congenic C57Bl/6 mice (n=10 per group) are given 5% DSS drinking water for 7 days and regular water for 7 days of recovery. At either day 6 or when mice have lost 10% of initial body weight, 1×10⁶Thy1.2+ TDMM- or control-induced GFP+ Tregs (generated as described above) are administered via I.P. injection. Control DSS-treated mice receive a sham injection, and H₂O-treated mice receive 1×10⁶Thy 1.2+ TDMM- or control-induced GFP+ Tregs or a sham injection. Axillary and cervical lymph nodes, spleen, gut associated lymphoid tissue and intestinal lamina propria cells are harvested for analysis of donor Thy1.2+ cells from the transferred population at, e.g., 1, 3, 5 and 7 days post-transfer. These cells can be analyzed via flow cytometry for GFP fluorescence as well as expression of Treg signature proteins after TCR stimulation in vitro (e.g. IL-10, CTLA-4, GITR, ICOS). In addition, the recovered transferred cells' ability to inhibit CD4+ CD25− naïve T cell proliferation in vitro can be investigated as described above (see FIG. 4).

Example 9

The following is a description of an illustrative methodology to determine stability and expansion of TDMM-induced iTregs after adoptive transfer to lymphopenic hosts.
Lymphopenic Rag1−/− Thy1.2+ mice (n=10 per group) receive 1×10⁶Thy1.2+ TDMM- or control induced GFP+ Tregs (generated as described above) labeled with 5 μM CFSE for 5 minutes via I.P. injection. At day 1, 3, 5 and 7 post-transfer, axillary and cervical lymph nodes, spleen, gut associated lymphoid tissue and intestinal lamina propria cells are harvested for analysis of Thy1.2+ cells from the transferred population. These cells can be analyzed via flow cytometry, ELISA and in vitro inhibition of effector T cell proliferation, as described in Example 1 (see FIG. 4).

Example 10

The following is a description of an illustrative methodology to compare the molecular signature of TDMM- to control-induced iTregs and Th17 cells.
Three conserved non-coding sequences (CNS) are located in the FOXP3 locus and are thought to mediate FOXP3 expression. Of these, CNS2 is activated by FOXP3 and important for stable Treg FOXP3 expression [Zheng, Y., et al., Nature 463(7282):808-12 (2010)]. Indeed, it has been shown that demethylation of CNS2 increases stability of Tregs produced in vivo [Kitagawa, Y., N. Ohkura, and S. Sakaguchi, Front Immunol 4:106 (2013)], and methylation of CNS2 is associated with the unstable iTregs induction in vitro [Ohkura, N., et al., Immunity 37(5):785-99 (2012); Floess, S., et al., PLoS Biol 5(2):e38 (2007)]. Therefore, a test for whether TDMMs increase stability of iTregs through demethylation of CNS2 can be performed. DNA can be isolated from iTreg cells generated using both the optimal and non-optimal induction conditions predicted by a computational (e.g., neural network) model, as well as from the in vivo transplantation experiments, and analyzed using methylated DNA immunoprecipitation (MeDIP) [Taiwo, O., et al., Nat Protoc 7(4):617-36 (2012)]. Natural thymic Tregs and CNS3 can be used as controls. The isolated DNA will be characterized (“typed”) using restriction analysis and mass spectrometry. Mass spectrometry, such as a QTRAP 3200 mass spectrometer, can be used for this analysis. In order to identify important pathways affected by TDMMs not revealed phenotypically, the molecular signature of TDMM- and control-induced Tregs and Th17 cells can be characterized using RNA-seq [Mortazavi, A., et al., Nature Methods 5:621-628 (2008)].

Example 11

The following is an overview of a neural network design to model Treg induction conditions that provide optimal performance upon transplantation into a subject in need thereof.
Model development can be carried out using experimental data regarding Treg differentiation in vitro (e.g., % of Treg cells, % of Th17 cells, TDMM concentration; see FIG. 6 for selection criteria) and Treg implantation in vivo. The data is separately used to develop two neural network models, one model for predicting the % of Treg and Th17 cells upon exposure to specific TDMMs in vitro and, one model for predicting the function and stability of the iTregs and attenuated Th17 cells in vivo after transplantation. The two models are then combined where the outputs of one model serves as the input to the other model to describe the relationship between induction conditions of Tregs and the stability and function of Tregs after transplantation. An optimization of this combined model is then performed to determine optimal induction conditions. The combined model predictions can be experimentally validated using in vivo data. The two significant advantages that this approach has are that the number of in vivo experiments is significantly lower than the number of in vitro experiments but also that the model can be extended in future work to other metabolites without requiring new in vivo data.

Example 12

The following is an expanded description of an illustrative design of a neural network useful for modelling Treg induction conditions that provide optimal performance upon transplantation into a subject in need thereof.
As described in Example 10, two models from the in vitro data and in vivo data are separately developed. These data are generated using a 2k factorial design. For example, with 5 inputs (e.g., IL-2, IL-23, IL-6, TGFβ, and TDMMs), we can carry out 2⁵=32 experiments for developing the in vitro model. Similarly, data from 2²=4 experiments for developing the in vivo model can be used. These data are used for training the models. Additional data sets with 16 and 2 different input combinations, respectively, can be used for testing model predictions.
Every neural network is composed of inputs, an output layer, and one or more hidden layers that are responsible for capturing the input-output relationship. Furthermore, there can be feedback loops inside the neural network to represent dynamic relationships (as is likely to be the case for the current experimental system). Therefore, it is very important to choose an appropriate size and structure of the neural network, and this is usually determined by the number of hidden layers and the number of neurons within each hidden layer. The number of neurons in the input layer is equal to the number of inputs and the number of neurons in the output layer is equal to the number of outputs. Input and output layers can have linear relationships in each node and radial basis functions can be used as transfer functions for the hidden layers. The size of the neural network is determined by fitting different neural network structures/sizes to the training set and then evaluating each of the candidate networks on the testing set via a cross validation procedure. Using cross validation, one data set that contains ⅔ of the data points, corresponding to the 32 in vitro experiments or the 8 in vivo experiments mentioned above, can be used to fit the neural network and the remaining ⅓ of the data points can be used to evaluate model prediction accuracy as measured by the sum of squared errors. The routine used for estimating the parameters of the neural network is ‘trainlm’ in MATLAB, which uses a Levenberg-Marquardt algorithm; the standard suggested parameters for estimation by the toolbox (1000 epochs, 1E-7 minimum performance gradient) can be used as these have traditionally been found to work well [Zhou, Y., et al., ISA Transactions 42:651-664 (2003); Hahn, J., et al., AlChE J 48(6):1353-1357 (2002); Sun, C. and J. Hahn, J Process Contr 15(6):639-650 (2005)]. This procedure is repeated multiple times by randomly choosing another ⅔ of the data set for fitting and ⅓ for evaluation. The goal of such an approach is to determine a model size and structure that has the best prediction accuracy, as prediction and not fitting is the key for deriving a good model. This approach avoids overfitting of the data by selecting a neural network with too many parameters, which is the most common problem associated with neural networks.
The neural networks to be tested can have one or two hidden layers and up to five neurons in each hidden layer. The neural network model describing the in vitro data will be larger than the model describing the in vivo data due to the likely larger number of inputs and amount of collected data. Furthermore, networks which have feedback elements from the second hidden layer to the first one to capture dynamic behavior can be tested. The neural network that describes the effect of different induction conditions on the Treg phenotype (i.e., model 1) can have, e.g., TGF-β, IL-6, IL-23, IL-2 and TDMM concentration, as inputs and can have two outputs corresponding to, e.g., the % Treg (i.e., FOXP3+ TGFβ+ RORγt− IL-17− cells) and % Th17 cells (i.e., FOXP3− TGFβ− RORγt+ IL-17+ cells) as identified by ICS flow cytometry. Similarly, the neural network that describes the function and stability of TDMM-induced iTregs and TDMM-attenuated Th17 cells after transplantation in vivo (i.e., model 2) can have two inputs and outputs corresponding to the measurement of, e.g., TGFβ, IL-10 (established key functional mediators for Treg function) [Schmitt, E. G., et al., J Immunol 189(12):5638-48 (2012); Apostolou, I., et al., J Clin Immunol 28(6):619-24 (2008); Chinen, T., et al., J Exp Med 207(11):2323-30 (2010); Horwitz, D. A., et al., Eur J Immunol 38(4):912-5 (2008); Ishigame, H., et al., Proc Natl Acad Sci USA 110(17):6961-6, 96-99 (2013)] and expression of Treg signature proteins. After both models have been individually identified, they can be combined by correlating the outputs from the first neural network model with the inputs of the second neural network model. This approach would allow description of the entire effect of the different stimuli used for induction on stability after transplantation using the integrated experimental/computational approach.

Example 13

The following is a description of steps to optimize the integrated neural network model for Treg induction conditions.
Once an integrated model that combines the two neural network models described in Example 11 is developed, it can be used for optimizing Treg function and stability. Treg function and stability after transplantation are maximized as indicated by the TGFβ and IL-10 production, and expression of Treg signature proteins in mice given adoptive transfer of indole-induced Tregs, which is the output of the model. A sequential quadratic programming (SQP) algorithm can be used to find the optimal induction conditions that maximize the stability after transplantation. As neural network models should not be used for extrapolation, bounds on the input variables are incorporated where the bounds are set to the largest and smallest values used in the experiments that generated the data. As it is unlikely that there is one optimal induction condition, a panel of 3-5 optimal induction conditions (maximum % Treg and minimum Th17 cells) and 3-5 non-optimal conditions (minimum % Treg and maximum % Th17 cells) are generated. The different predictions are tested experimentally using the methodologies described above for the in vitro and in vivo assays. The expected outcome is that the optimal induction conditions will result in higher stability and function and will be superior to the non-optimal conditions that they are compared against with a statistical significance.

Example 14

The following is a description an exemplary protocol that was used to demonstrate the ability to elicit acute T cell activation in vivo through administration of a TDMM (e.g., indole).
Fifteen μg of αCD3 (BioXcell clone 145-2C11) was administered via intra-peritoneal injection at 0 and 48 hours. Along with αCD3; butyrate, indole, a combination of butyrate and indole, or a 17% DMSO (all from Sigma-Aldrich) vehicle control were co-administered in the same injection at 0 and 48 hours. At 52 hours, spleen and mesenteric lymph nodes were isolated and plated individually at a concentration of 1×10⁶cells/well with RPMI media supplemented with 2-mercaptoethanol, gentamicin, penicillin, and streptomycin+10% FCS (all from Life Technologies) in a 96-well round bottom plate (Falcon). Cells were immediately stimulated for 4 hours and stained. Specifically, for the last four hours of culture, cells were treated with golgi plug (BD), PMA and ionomycin (both from Sigma-Aldrich). Cells were fixed with the FOXP3 fixation buffer (eBioscience) or 4% paraformaldehyde (Sigma-Aldrich), treated with permeabilization buffer (eBioscience) and stained with appropriate combinations of the following antibodies: αIL-17a-PE or -APC (eBioscience clone eBio17B7), αFOXP3-APC or -FITC (eBioscience clone FJK-16s), αIL-4-FITC (eBioscience clone BVD6-24G2), and αIFN-γ-PE or -APC (eBioscience clone XMG1.2).
While illustrative embodiments have been illustrated and described, it will be appreciated that various changes can be made therein without departing from the spirit and scope of the invention.

Claims

The embodiments of the invention in which an exclusive property or privilege is claimed are defined as follows:

1. A method of activating a naïve T cell in vitro, comprising contacting the naive T cell with a tryptophan derived microbiota metabolite (TDMM).

2. The method of claim 1, wherein the naïve T cell is differentiated into a cell with increased expression of FoxP3 compared to the naïve T cell.

3. The method of claim 1, wherein the naïve T cell is differentiated into a T regulatory cell (Treg).

4. The method of claim 2 or 3, wherein the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole.

5. The method of claim 1, wherein the naïve T cell is differentiated into a Th17 cell.

6. The method of claim 5, wherein the TDMM is 5-hydroxyindole.

7. The method of claim 1, wherein the naïve T cell is contacted in vitro in a culture medium.

8. A method of producing a Treg cell, comprising contacting a naïve T cell in vitro with a tryptophan derived microbiota metabolite (TDMM).

9. The method of claim 8, wherein the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole.

10. The method of claim 8, wherein the naïve T cell is contacted with the TDMM in a culture medium.

11. An induced T regulatory cell (iTreg), produced by the method recited in claim 8.

12. A method of treating, preventing, ameliorating, attenuating and/or reducing inflammation in a subject in need thereof, comprising administering to the subject an iTreg as recited in claim 11.

13. The method of claim 12, wherein the subject suffers from or is susceptible to excessive inflammation.

14. The method of claim 13, wherein the subject has or is susceptible to allergies, inflammatory bowel disease, colitis, NSAID-enteropathy/ulceration, psoriasis, rheumatism, graft-versus-host disease, and the like.

15. The method of claim 12, wherein the iTreg is administered by intra-peritoneal (IP), intravenous (IV), topical, parenteral, intradermal, transdermal, oral (e.g., via liquid or pill), or respiratory (e.g., intranasal mist) routes.

16. The method of claim 12, wherein the subject is a mammal.

17. The method of claim 16, wherein the subject is a human, mouse, or rat.

18. A T cell culture medium that promotes activation of a naïve T cell, comprising a tryptophan derived microbiota metabolite (TDMM).

19. The culture medium of claim 18, wherein the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 5-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole.

20. The culture medium of claim 18, wherein the medium further comprises one or more additional Treg promoting compounds, such as short-chain fatty acids, bile acids, polysaccharide A, n3 polyunsaturated fatty acids, retinoic acid, VitD, VitC, polyphenols, quercetin, resveratrol, NSAIDS, TGF-β, rapamycin, and/or IL-2.

21. A method of treating or reducing a condition characterized by excessive inflammation in a subject in need thereof, comprising administering to the subject an effective amount of a Treg-skewing TDMM, or a precursor, prodrug, or acceptable salt thereof.

22. The method of claim 21, wherein the condition is an allergy, or autoimmune disease, such as colitis, inflammatory bowel disease (IBD), psoriasis, rheumatoid arthritis, multiple sclerosis, fibrosis, enteropathy, graft-versus-host disease, and the like.

23. The method of claim 21, wherein the the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole.

24. The method of claim 21, wherein the TDMM is administered by intra-peritoneal (IP), intravenous (IV), topical, parenteral, intradermal, transdermal, oral (e.g., via liquid or pill), or respiratory (e.g., intranasal mist) routes.

25. A method of increasing the stability of a Treg cell, comprising contacting the Treg cell or a precursor thereof with an effective amount of a Treg-skewing TDMM, or a precursor, prodrug, or acceptable salt thereof.

26. The method of claim 25, wherein the TDMM is selected from indole, hydroxyindole (e.g., 2-hydroxyindole, 3-hydroxyindole, 7-hydroxyindole), 1-(2-carboxyphenylamino)-1-deoxy-D-ribulose-5-phosphate, 5-Hydroxy-L-tryptophan, Indoleglycerol phosphate, indolepyruvate, N-(5-Phospho-D-ribosyl)anthranilate, tryptamine, indole-3-acetate, L-formylkynurenine, L-Tryptophanyl-tRNA(Trp), indole-3-acetamide, indole-3-pyruvate, indole-3-lactic acid, tryptophol, indole-3-acetaldehyde, indole-3-aldehyde, isatin (indole-2,3-dione), isoindigo, indirubin, indoxyl-sulfate, and 2-oxyindole.

27. The method of claim 25, wherein the Treg is an induced Treg cell (iTreg).

28. The method of claim 25, wherein the Treg is a natural Treg cell (nTreg).

29. The method of claim 25, wherein the nTreg is first isolated from a subject before the contacting step.

30. The method of one of claims 27 and 29, further comprising administering the Treg cell to a subject in need thereof.

31. The method of claim 28, comprising administering the TDMM to a subject that has an endogenous nTreg population in vivo.

32. A method of producing a pro-inflammatory T cell, comprising contacting a naïve T cell with a pro-inflammatory tryptophan derived microbiota metabolite (TDMM).

33. The method of claim 32, wherein the contacting occurs in vitro or ex vivo.

34. The method of claim 32, wherein the pro-inflammatory TDMM is 5-hydroxyindole (5-HI).

35. The method of claim 32, wherein the pro-inflammatory T cell expresses ROR-γ or IL-17.

36. The method of claim 32, wherein the pro-inflammatory T cell is a Th17 cell.

37. An induced Th17 cell (iT17), produced by the method recited in claim 32.

38. A method of treating, preventing, ameliorating, attenuating and/or reducing a condition in a subject treatable by inducing or increasing an inflammation response, comprising administering to the subject an iTh17 cell as recited in claim 37.

39. A method of treating, preventing, ameliorating, attenuating and/or reducing a condition in a subject treatable by inducing or increasing an inflammation response, comprising administering to the subject a pro-inflammatory tryptophan derived microbiota metabolite (TDMM), or a precursor, prodrug, or acceptable salt thereof, in an amount sufficient to induce development of or stabilize Th17 cells from a naïve T cell precursor.

40. The method of claim 39, wherein the pro-inflammatory TDMM is 5-HI.