INTERVENTION STRATEGY FOR PREVENTION OR TREATMENT OF DIABETES MELLITUS, AUTOIMMUNE DISEASE, INFLAMMATORY DISEASE OR CARDIOVASCULAR DISEASE

Abstract

An intervention strategy in the prevention or treatment of a subject having an inflammation-related disease such as Diabetes mellitus, autoimmune disease, inflammatory disease or cardiovascular disease. The intervention strategy preferably relates to administration of a chloro-, fluoro-, or bromo-substituted tryptophan, preferably 6-bromotryptophan, and/or a mono- or di-fatty acid substituted glycerol phosphocholine (GPC), preferably chosen from the group consisting of 1-myristoyl-2-arachidonoyl-glycero-phosphocholine (MA-GPC) and 1-arachidonoyl-glycero-phosphocholine (A-GPC), or any derivative or functional equivalent of these. Alternatively, the intervention relates to administration of a Desulfovibrio species, wherein the Desulfovibrio species is preferably chosen from the group consisting of Desulfovibrio piger, Desulfovibrio fairfieldensis, Desulfovibrio desulfuricans, Desulfovibrio indonensis, Desulfovibrio alaskensis, Desulfovibrio vulgaris, Desulfovibrio vietnamensis and Desulfovibrio gigas.

Claims

1.-50. (canceled)

51. A method of preventing or treating a subject for an inflammation-related disease, the disease selected from the group consisting of diabetes mellitus, autoimmune disease, inflammatory disease, and cardiovascular disease, the method comprising: administering to the subject chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan so as to prevent or treat the inflammation-related disease, wherein if the inflammation-related disease is an autoimmune disease, the chloro-substituted tryptophan, fluoro-substituted tryptophan or bromo-substituted tryptophan is 6-bromotryptophan, and wherein if the inflammation-related disease is diabetes mellitus or autoimmune disease, the chloro-substituted tryptophan, fluoro-substituted tryptophan or bromo-substituted tryptophan is not comprised in fecal matter.

52. The method according to claim 51, wherein the Diabetes mellitus is type 1 Diabetes mellitus or type 2 Diabetes mellitus.

53. The method according to claim 51, wherein the autoimmune disease is selected from the group consisting of Type 1 Diabetes mellitus, Hashimoto's disease, Graves' disease, Addison's disease, psoriasis, vitiligo, rheumatoid arthritis, Bechterew's disease, Celiac disease, inflammatory bowel disease, asthma, chronic obstructive pulmonary disease (COPD), Addison's disease, vasculitis, multiple sclerosis (MS), chronic inflammatory demyelinating polyneuropathy (CDIP), and Guillain-Barré syndrome (GBS).

54. The method according to claim 51, wherein the inflammatory disease is selected from the group consisting of cardiovascular inflammation, carditis, endocarditis, myocarditis, pericarditis, vasculitis, arteritis, phlebitis, capillaritis, inflammation of the gastrointestinal tract, esophagitis, gastritis, gastroenteritis, enteritis, colitis, enterocolitis, duodenitis, ileitis, caecitis, appendicitis, proctitis, hepatic inflammation, pulmonary inflammation, skeletal inflammation, systemic inflammatory response syndrome (SIRS), and sepsis.

55. The method according to claim 51, wherein the cardiovascular disease is selected from the group consisting of coronary artery disease, peripheral arterial disease, cerebrovascular disease, atherosclerosis, stenosis, renal artery stenosis, aortic disease, aortic aneurysm, cardiomyopathy, hypertensive heart disease, hypertension, heart failure, pulmonary heart disease, cardiac dysrhythmias, cardiovascular inflammation, inflammatory heart disease, endocarditis, inflammatory cardiomegaly, myocarditis, eosinophilic myocarditis, valvular heart disease, congenital heart disease, and rheumatic heart disease.

56. The method according to claim 51, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is 6-bromotryptophan.

57. The method according to claim 51, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is combined with a tumor necrosis factor alpha (TNFα) inhibitor, infliximab, adalimumab, certolizumab pegol, or golimumab.

58. The method according to claim 51, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is combined with bacteria from the genus Eubacterium, Intestinimonas, Bifidobacteria, Lactobacillales and/or Akkermansia, Bifidobacterium animalis sub lactis, Bifidobacterium breve, Lactobacillus plantarum. Lactobacillus rhamnosus, Lactobacillus acidophilus, Eubacterium hallii, Intestinimonas butyriciproducens, and/or Akkermansia muciniphila.

59. The method according to claim 51, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is administered by enteral, oral, nasal, subcutaneous, intravenous, rectal, and/or nasoduodenal tube administration.

60. The method according to claim 51, comprising administering the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan to the small intestine or duodenum.

61. The method according to claim 51, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in a composition selected from the group consisting of a pharmaceutical composition, a liquid dosage form, a solid dosage form, a capsule, a tablet, and a powder.

62. The method according to claim 60, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in the composition in an amount of at least 1 mg chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan.

63. The method according to claim 51, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in and/or encapsulated by an enteric coating, wherein the enteric coating does not dissolve and/or disintegrate in a gastric environment.

64. The method according to claim 51, wherein the use involves at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 separate administrations of the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan, with intervals of at least 1, 2, 3, 4, 5, 6, 7, or 8 weeks between the separate administrations.

65. The method according to claim 51, wherein the subject to be treated is a mammal.

66. The method according to claim 60, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in the composition in an amount of at least 5 mg chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan.

67. The method according to claim 60, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in the composition in an amount of at least 10 mg chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan.

68. The method according to claim 60, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in the composition in an amount of at least 25 mg chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan.

69. The method according to claim 60, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in the composition in an amount of at least 50 mg chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan.

70. The method according to claim 60, wherein the chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan is comprised in the composition in an amount of at least 100 mg chloro-substituted tryptophan, fluoro-substituted tryptophan, or bromo-substituted tryptophan.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0217] FIG. 1: Top 10 small intestinal microbiota with relative importance that best predicted treatment group allocation (XGBoost predictive modeling algorithm). Percentages are scaled toward the largest, which is set at 100%. The top 4 microbiota stand out with higher relative importance.

[0218] FIG. 2: A: Top 10 metabolites that best predicted treatment group allocation (XGBoost predictive modeling algorithm). Percentages are scaled toward the largest, which is set at 100%. Top 3 metabolites stand out with higher relative importance in the analysis. B-D: Relative abundance of top 3 metabolites plotted against time for each treatment group (in each graph, the line that is predominantly the upper line represents the autologous FMT group; the line that is predominantly the bottom line represents the allogenic FMT group). Medians+−IQR are reported. P-values were calculated using Mann-Whitney U test between groups at 12 months. 1-myristoyl-2-arachidonoyl-GPC is different between groups at 12 months, p-value=0.020. 1-arachidonoyl-GPC is different between groups at 12 months, p-value=0.020. E: Spearman correlation between change in fasting C-peptide and change in 1-myristoyl-2-arachidonoyl-GPC. F: Abundance of fecal D. piger over time. P-values were calculated using Mann-Whitney U test. At 6 months p-value=0.024, at 12 months p-value=0.023. G: Fold change in D. piger between the groups (the predominant upper line represents the autologous FMT group). The delta p-value was calculated by doing Mann-Whitney U test on the delta's between 0 and 12 months of each group, p-value=0.006. H: Spearman correlation plot of delta (0-12 months) fecal D. piger and delta (0-12 months) of fasting C-peptide. I: correlation plot of fecal D. piger and 1-arachidonoyl-GPC. J: correlation plot of fecal D. piger and small intestinal Prevotella 1 K: correlation plot of fecal D. piger and small intestinal Prevotella 2.

[0219] FIG. 3: Predictive modeling output showing top 30 differentially changed fecal microbiota between treatment groups.

[0220] FIG. 4: A: Shows the number of responders at 6 months and at 12 months and how many subjects were in each treatment group. Response was defined as <10% decline in C-peptide AUC compared to baseline. The 12 months responders were used for all analyses. B: Shows individual subject lines of C-peptide AUC over time. C and D: show the abundance of B. caccae and C. catus over time, respectively. In both graphs, the upper line represents responders. P-values were calculated using Mann-Whitney U test between groups at each time point. For B. caccae at baseline the p-value=0.0099, for C. catus at baseline the p-value=0.00049. E: shows the correlation between delta C. catus (0-12 months) and delta C-peptide AUC (0-12 months). Spearman's rho (r) is shown and the p-value was calculated using Spearman's Rank.

[0221] FIG. 5: Predictive modeling output showing top 30 differentially changed fecal microbiota between treatment groups.

[0222] FIG. 6: Abundance over time of five fecal microbiota from the top 10 (see FIG. 3) that at baseline that best differentiated between responders and non-responders (in A, B, and D, the upper line represents responders, the other line non-responders; in C and E, the upper line represents non responders, the other line responders). Strains that were different between responders and non-responders at baseline or during the course of the study were chosen to display. P-values were calculated using Mann-Whitney U test at each time point. A: Paraprevotella spp., p=0.019, B: Eubacterium ramulus, p=0.043, C: Collinsella aerofaciens, p=0.043, D: Bacteroides eggerthii, p=0.006, E: Ruminococcus callidus, p=0.026. Faecalibacterium prausnitzii (10th from the top 10), was not significantly different at baseline (p=0.063).

[0223] FIG. 7: Effect of 6-bromotryptophan (6-BT), 1-arachidonoyl-glycero-phosphocholine (20:0) (A-GPC), 1-palmitoyl-2-linoleoyl-sn-glycero-3-phosphoethanolamine (16:0-18:2 PE), 1-myristoyl-2-arachidonoyl-glycero-phosphocholine (MA-GPC) on NFκB pathway activation at different doses.

[0224] FIG. 8: Effect of 6-BT, MA-GPC, A-GPC on myeloid cells: murine monocytes CD11b+ activated with LPS (10 ng/ml) for 24 hours—TLR4 stimulation.

[0225] FIG. 9: Effect of 6-BT, MA-GPC, A-GPC on myeloid cells: murine monocytes CD11b+ activated with Poly)I:C, analog of dsRNA, for 24 hours—TLR3 stimulation.

[0226] FIG. 10: Effect of 6-BT on human monocytes in LPS stimulation.

[0227] FIG. 11: Effect of 6-BT, A-GPC, MA-GPC on T lymphocytes: murine CD4+ T cells activated with anti-CD3 & anti-CD28 mAbs.

[0228] FIG. 12: INS1e beta-cells treated for 24 hours with 6-BT: gene expression of beta cell differentiation markers.

[0229] FIG. 13: INS1e beta-cells treated for 24 hours with 6-BT: gene expression of beta cell differentiation markers.

[0230] FIG. 14: Murine bone marrow-isolated monocytes (Christ A., Cell 2018) or bone marrow-derived macrophages (Swansen, JEM 2017) were exposed for 24 hours to the indicated concentrations of 6-BT (10-100 μM) in presence or not of 10 ng/ml LPS, 10 μg/ml P3C or 10 μg/ml poly(I:C). By means of ELISA assays, it was found that 6-BT can inhibits the secretion of pro-inflammatory cytokine TNFα upon TLR4 and TLR2 engagements and of IFNbeta upon TLR3 activation.

[0231] FIG. 15: The effect of 6-BT on murine DC was investigated, differentiated with GM-CSF (40 ng/ml) by bone marrow cells. As for the monocytes/macrophages, 6-BT inhibits the secretion of the pro-inflammatory cytokines TNFα and IFNbeta by DC after activation of, respectively, TLR4 (with 100 ng/ml LPS) or TLR3 (10 μg/ml poly(I:C)).

[0232] FIG. 16: Further studied was the impact of 6-BT on CD4 T cells. To mimic antigen presentation, murine CD4 T cells (isolated from spleens; Uchimura T., Immunity 2019) were activated by monoclonal antibodies against CD3 and CD28 (2.5 and 1 μg/ml, respectively). In line with the findings on myeloid cells, 6-BT significantly reduced the production of the Th1 cytokine IFNgamma.

[0233] FIG. 17: It was investigated whether 6-BT can exert a direct effect on beta cells. Indeed, here it is seen that 6-BT induces, in IS1E beta cells, the gene expression of the transcription factors PDX1 and MAFA, which are important for beta cell maturation and functionality. In agreement, 6-BT also promoted insulin secretion at steady-state and during glucose-stimulated insulin secretion (data shown as the difference between insulin release at starving condition [1 mM glucose] and at hyperglycemic state [22 mM]), (Paula S., FASEB J. 2015).

[0234] FIG. 18: 6-BT impact on the activation of the NF-kB pathway, a central pathway in all inflammatory diseases (beyond autoimmunity) was checked. Hence, the expression of the phosphorylated form of the p65 subunit was quantified, regarded as a marker of NFkB activation. Upon T cell activation with PMA (50 ng/ml) and ionomycin (1 μg/ml), 6-BT could inhibit, at very early time-points (5-10 minutes after activation), the NF-kB signaling. This effect was found in both murine and human (Jurkat cells) CD4 T cells.

[0235] FIG. 19: Using the RAW264.7 murine macrophage cell line stably expressing an NFkB luciferase reporter (Groeneweg M., J. Lipid Res. 2006), overnight exposure of macrophages to 6-BT (10-200 μM) inhibits the transcriptional activity of the NFkB complex in a dose-dependent manner upon 2 hours stimulation with LPS (10 ng/ml).

[0236] FIG. 20: In murine CD4 T lymphocytes (isolated from murine spleens; Uchimura T., Immunity 2019), 6-BT, but not tryptophan, exerted inhibitory effect on IFNgamma production upon CD3/CD28 engagement. This indicates that 6-BT and tryptophan elicit distinct biological activities.

[0237] FIG. 21: Exposure of monocytes (isolated from murine bone marrow; Christ A., Cell 2018) to 6-BT or tryptophan, shows that the anti-inflammatory effects are specific for the 6-bromotryptophan molecule and not for tryptophan.

[0238] FIG. 22: It was found that 6-BT (100 μM) promoted the mitochondrial metabolism in murine and human (Jurkat) CD4 T cells. OCR=oxygen consumption rate, used as a proxy of cellular utilization of mitochondrial oxidative phosphorylation. OCR was measured using a Seahorse XF Analyzer Uchimura T., Immunity 2019; Chou, Nature 2021).

[0239] FIG. 23: 6-BT exposure could enhance the mitochondrial metabolism of pro-inflammatory M1 macrophages (differentiated in presence of LPS and IFNgamma; Cheng N., JCI Insight 2018), without affecting the glycolytic flux. Intracellular metabolism measured using a Seahorse XF Analyzer Uchimura T., Immunity 2019; Chou, Nature 2021).

[0240] FIG. 24: It was investigated whether 6-BT may influence the mitochondrial metabolism of beta cells, which rely on ATP and mitochondrial metabolite production for insulin exocytosis. 6-BT increased mitochondria metabolism both at steady-state and under hyperglycemia (25 mM glucose) in beta cells (INS1E beta cells). In addition, the effect of tryptophan on intracellular metabolism was tested and it was found that, as for the inflammatory markers, it exerted a different effect than 6-BT. Intracellular metabolism measured using a Seahorse XF Analyzer Uchimura T., Immunity 2019; Chou, Nature 2021).

[0241] FIG. 25: Relative fecal Desulfovibrio abundance in Diabetes vs non-Diabetes subjects.

[0242] FIG. 26: Diabetes: Effect of Desulfovibrio genus. Odds ratio for Diabetes.

[0243] FIG. 27: Relationship between plasma 6BT levels and fecal Desulfovibrio genus relative abundance in (1) non Diabetes subjects (upper line) and (2) Diabetes patients (lower line).

DETAILED DESCRIPTION

EXAMPLE 1

[0244] Patients with conditions as indicated below are treated with:

[0245] 1. Oral administration, daily for 2 years, of an empty enteric coated capsule.

[0246] 2. Oral administration, daily for 2 years, of an enteric coated capsule comprising ˜1*10.sup.8 cells of an Desulfovibrio species (Desulfovibrio piger, Desulfovibrio desulfuricans, or Desulfovibrio fairfieldensis)

[0247] 3. Oral administration, daily for 2 years, of an enteric coated capsule comprising 50 mg chloro-, fluoro-, or bromo-substituted tryptophan (6-bromotryptophan (6-BT) or 6-fluorotryptophan (6-FT)).

[0248] 4. Oral administration, daily for 2 years, of an enteric coated capsule comprising 50 mg mono- or di-fatty acid substituted glycerol phosphocholine (GPC) (1-myristoyl-2-arachidonoyl-glycero-phosphocholine (MA-GPC) or 1-arachidonoyl-glycero-phosphocholine (A-GPC)).

TABLE-US-00001 TABLE 1 Effect treatment Effect Effect Effect 1 treatment 2 treatment treatment 4 Condition (patient 1) (patient 2) (patient 3) (patient 4) Type 1 No effect (Desulfovibrio (6-BT) (MA-GPC) Diabetes piger) residual residual residual beta cell beta cell beta cell reserve is reserve is reserve is stabilized stabilized stabilized over time, over time, over time, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Type 2 No effect (Desulfovibrio (6-BT) (A-GPC) Diabetes piger) Reduced Reduced Reduced polyuria, polyuria, polyuria, reduced reduced reduced polydipsia, polydipsia, polydipsia, less need of less need of less need of exogenous exogenous exogenous hormone hormone hormone supple- supple- supple- mentation, mentation, mentation, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function, cell function, cell function, less perceived less perceived less perceived fatigability fatigability fatigability Hashimoto's No effect (Desulfovibrio (6-BT) (MA-GPC) disease piger) Slowed down Slowed down Slowed down progression progression progression of disease, of disease, of disease, less need of less need of less need of exogenous exogenous exogenous hormone hormone hormone supple- supple- supple- mentation, mentation, mentation, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function, cell function, cell function, less perceived less perceived less perceived fatigability fatigability fatigability Graves' No effect (Desulfovibrio (6-FT) (A-GPC) disease desulfuricans) Slowed down Slowed down Slowed down progression progression progression of the of the of the disease, disease, disease, reduced reduced reduced enlargement enlargement enlargement of thyroid of thyroid of thyroid gland, less gland, less gland, less risk of risk of risk of remission and remission and remission and radioactive radioactive radioactive iodine iodine iodine treatment treatment treatment need, need, need, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Addison's No effect (Desulfovibrio (6-BT) (MA-GPC) disease piger) Slowed down Slowed down Slowed down progression progression progression of disease, of disease, of disease, less need of less need of less need of exogenous exogenous exogenous hormone hormone hormone supple- supple- supple- mentation, mentation, mentation, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function, cell function, cell function, reduced reduced reduced hyper- hyper- hyper- pigmentation pigmentation pigmentation Psoriasis No effect (Desulfovibrio (6-FT) (A-GPC) fairfieldensis) Slowed down Slowed down Slowed down progression progression progression of disease, of disease, of disease, somewhat somewhat somewhat reduced reduced reduced red inflamed red inflamed red inflamed areas, areas, areas, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Vitiligo No effect (Desulfovibrio (6-FT) (A-GPC) piger) Slowed down Slowed down Slowed down progression of progression of progression of disease, disease, disease, some white some white some white patches on patches on patches on the skin the skin the skin disappear, disappear, disappear, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Rheumatoid No effect (Desulfovibrio (6-BT) (MA-GPC) arthritis piger) Reduced Reduced Reduced progression progression progression of disease of disease of disease symptoms, symptoms, symptoms, and less and less and less pain around pain around pain around joints, less joints, less joints, less need of need of need of exogenous exogenous exogenous medication medication medication including including including DMARDS, DMARDS, DMARDS, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Bechterew's No effect (Desulfovibrio (6-BT) (MA-GPC) disease fairfieldensis) Slowed down Slowed down Slowed down progression of progression of progression of disease, less disease, less disease, less perceived perceived perceived lower back lower back lower back pain, less pain, less pain, less need of need of need of exogenous exogenous exogenous medication medication medication including including including DMARDS, DMARDS, DMARDS, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Celiac Ingestion (Desulfovibrio (6-BT) (MA-GPC) disease of small piger) Ingestion Ingestion amount Ingestion of small of small of gluten of small amount amount leads to amount of gluten of gluten upset of gluten leads to leads to stomach, leads to less upset less upset stomach less upset stomach stomach pain, stomach but no pain, but no pain, inflam- but no pain, less diarrhea, less diarrhea, mation, less diarrhea, less gas, less gas, diarrhea, less gas, less less gas less osteoporosis, osteoporosis, osteoporosis, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Asthma No effect (Desulfovibrio (6-BT) (MA-GPC) piger) Slowed Slowed Slowed down disease down disease down disease progression, progression, progression, less less less episodes of episodes of episodes of coughing, coughing, coughing, shortness shortness shortness of breath of breath of breath (improved (improved (improved reversibility reversibility reversibility of FEVI of FEVI of FEVI upon upon upon broncho- broncho- broncho- dilators), less dilators), less dilators), less need of need of need of exogenous exogenous exogenous medication medication medication including including including synergy with synergy with synergy with broncho- broncho- broncho- dilators, dilators, dilators, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Emphysema No effect (Desulfovibrio (6-BT) (MA-GPC) (COPD) piger) Slowed Slowed Slowed down disease down disease down disease progression, progression, progression, less less less episodes of episodes of episodes of coughing, coughing, coughing, shortness shortness shortness of breath of breath of breath (improved (improved (improved reversibility reversibility reversibility of FEVI of FEVI of FEVI upon upon upon broncho- broncho- broncho- dilators), less dilators), less dilators), less need of need of need of exogenous exogenous exogenous medication medication medication including including including synergy with synergy with synergy with broncho- broncho- broncho- dilators, dilators, dilators, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Vasculitis No effect (Desulfovibrio (6-FT) (A-GPC) piger) Slowed Slowed Slowed down down down progression progression progression of the of the of the disease, disease, disease, perceived perceived perceived severity severity severity of symptoms of symptoms of symptoms is reduced, is reduced, is reduced, i.e., less i.e., less i.e., less fever, fever, fever, fatigue, fatigue, fatigue, weakness, weakness, weakness, weight weight weight loss, general loss, general loss, general aches aches aches and pains, and pains, and pains, numbness, numbness, numbness, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Systemic No effect (Desulfovibrio (6-BT) (MA-GPC) lupus desulfuricans) Slowed Slowed eryth- Slowed down down ematosus down progression progression (SLE) progression of the of the of the disease, disease, disease, less painful less painful less painful and swollen and swollen and swollen joints, joints, joints, fever, chest fever, chest fever, chest pain, hair pain, hair pain, hair loss, mouth loss, mouth loss, mouth ulcers, ulcers, ulcers, swollen swollen swollen lymph nodes, lymph nodes, lymph nodes, and perceived and perceived and perceived fatigue, fatigue, fatigue, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Guillain- No effect (Desulfovibrio (6-BT) (MA-GPC) Barre piger) Slowed down Slowed down syndrome Slowed down progression progression (GBS) progression of the of the of the disease, less disease, less disease, less perceived perceived perceived muscle muscle muscle weakness, weakness, weakness, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Chronic No effect (Desulfovibrio (6-FT) (A-GPC) inflam- piger) Slowed down Slowed down matory Slowed down progression progression demyeli- progression of the of the nating of the disease, disease, poly- disease, less less neuropathy less perceived perceived (CDIP) perceived muscle muscle muscle weakness, weakness, weakness, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Multiple No effect (Desulfovibrio (6-BT) (MA-GPC) sclerosis piger) Slowed down Slowed down (MS) Slowed down progression progression progression of the of the of the disease, less disease, less disease, less perceived perceived perceived muscle muscle muscle weakness, less weakness, less weakness, less trouble with trouble with trouble with sensation and sensation and sensation and coordination, coordination, coordination, beneficial beneficial beneficial changes in changes in changes in T and B T and B T and B cell function cell function cell function Athero- No effect (Desulfovibrio (6-BT) (A-GPC) sclerosis piger) Reduced Reduced Reduced risk of risk of risk of coronary coronary coronary artery artery artery disease, disease, disease, reduced reduced reduced levels of levels of levels of inflammation inflammation inflammation markers markers markers (TNFalfa (TNFalfa (TNFalfa)

[0249] It is expected that results similar to the putative effects as shown in the Table 1 above can be obtained with larger patient cohorts.

EXAMPLE 2

[0250] Recent-onset (<6 weeks) T1D patients were randomized in two groups to receive three autologous or allogenic (healthy donor) fecal microbiota transplantations (FMTs) over a period of 4 months.

[0251] It was found that several (microbiota derived) plasma metabolites and (small) intestinal bacterial strains are linked with improved residual beta cell function in Type 1 Diabetes.

[0252] Materials and Methods

[0253] A double-blind randomized controlled trial was performed in new onset T1D subjects using computerized randomization. The effects were studied of allogenic (healthy donor) compared to autologous (own) gut microbiota infusion on residual beta cell function and autoimmune T cell response in relation to changes in (small) intestinal microbiota during 1 year after treatment.

[0254] Patient Recruitment

[0255] New onset T1D patients were recruited from outpatient clinics in the Amsterdam region. Inclusion criteria for patients were males/females, age 18-35, normal BMI (18.5-25 kg/m.sup.2), and a diagnosis of T1D within a maximum period of six weeks before inclusion, with residual beta cell function (as indicated by plasma C-peptide >0.2 mmol/1 and/or >1.2 ng/mL after MMT). Exclusion criteria were a diagnosis or symptoms of another autoimmune disease (eg hypo- or hyperthyroidism, celiac disease, rheumatoid arthritis or inflammatory bowel), (expected) prolonged compromised immunity (due to recent cytotoxic chemotherapy or HIV infection with a CD4 count <240) as well as antibiotic use in the last 3 months, use of proton pump inhibitors and any other kind of systemic medication barring insulin.

[0256] Donor Recruitment

[0257] Lean (BMI <25 kg/m.sup.2), omnivorous, healthy Caucasian male and females were recruited to serve as fecal donors. They completed questionnaires regarding dietary and bowel habits, travel history, comorbidity including family history of diabetes mellitus and medication use. Donors were screened for the presence of infectious diseases as described previously (van Nood et al., 2013). Blood was screened for human immunodeficiency virus; human T-lymphotropic virus; Hepatitis A, B, and C; cytomegalovirus (CMV); Epstein-Barr virus (EBV); strongyloides; amoebiasis, and lues. Presence of infection resulted in exclusion, although previous and non-active infections with EBV and CMV were allowed. Donors were also excluded if screening of their feces revealed the presence of pathogenic parasites (e.g., blastocystis hominis, dientamoeba fragilis, giardia lamblia), multiresistant bacteria (Shigella, Campylobacter, Yersinia, MRSA, ESBL, Salmonella, enteropathogenic E. coli and Clostridium difficile) or viruses (noro-, rota-, astro-, adeno (40/41/52)-, entero-, parecho- and sapovirus) as previously recommended.

[0258] Study Visits

[0259] Participants were asked to fill out an online nutritional diary for the duration of one week before every study visit to monitor caloric intake including the amount of dietary carbohydrates, fats, proteins and fibers. During the study visit, blood pressure, length, weight and daily insulin use were documented. Fasting blood samples were taken at each visit and upon centrifugation stored at −80° C. for later analyses. Whole blood sodium heparin tubes were kept on room temperature and processed within 24 hours for immunological analyses.

[0260] Three fecal transplantations using freshly produced feces were performed at 0, 2 and 4 months. Mixed-meal tests (for residual beta cell function), intestinal microbiota analyses were performed at 0, 2, 6, 9, and 12 months. Plasma metabolites were measured at 0, 6, and 12 months. Biometric measurements and fasting plasma to monitor safety parameters were performed on all time points.

[0261] Description Per Study Visit

[0262] All visits took place after an overnight fast with subjects taking no long acting insulin the night before. At each visit, blood sampling, fecal and urine sampling and biometric measurements took place. At baseline/0 months, positioning of a nasoduodenal tube was performed. After placement of the tube, when the patient was properly awake, a standardized 2-hour mixed meal test (Nestlé sustacal BOOST®) was performed as previously described (Moran et al., 2013) to study residual beta cell function. At 2, 9, and 12 months, patients again underwent a mixed-meal test for residual beta cell C-peptide secretion. Then, a duodenal tube was placed by means of CORTRAK enteral access and the fecal transplant procedures were repeated.

[0263] At 6 months, the mixed-meal test was performed.

[0264] Fecal Transplant Procedure

[0265] Subjects were allocated randomly to receive three autologous or allogenic fecal transplantations. All patients and investigators were masked to treatment assignment. After admission, a duodenal tube was placed by gastroscopy or CORTRAK enteral access system. Each patient then underwent complete colon lavage with 2-4 L of KLEAN-PREP® (macrogol) by duodenal tube until the researcher judged that the bowel was properly lavaged (i.e., no solid excrement, but clear fluid) for approximately 3 hours. Then, between 200 and 300 grams of donor feces was processed by dilution in 500 ml of 0.9% saline solution and filtered through unfolded cotton gauzes. The filtrate was used for transplantation two hours after the last administration of KLEAN-PREP® by duodenal tube in around 30 minutes using 50 cc syringes. After a short observation period the patient was sent home.

[0266] Mixed Meal Test

[0267] Starting the evening before each mixed meal test, T1D patients paused their long-acting insulin injections. After an overnight fast and without taking their short-acting morning insulin dose, a mixed meal test was performed with Boost High Protein (Nestlé Nutrition, Vervey, Switzerland) at 6 ml/kg body weight with a maximum of 360 ml per person. Subsequent blood sampling for stimulated C-peptide were taken at −10, 0, 15, 30, 45, 60, 90 and 120 minutes. AUC (area under the curve) values were derived according to the trapezoidal rule.

[0268] Plasma Metabolites

[0269] Fasting plasma metabolite measurements were done by Metabolon (Durham, NC), using ultra high performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS). Raw data was normalized to account for inter-day differences. Then, the levels of each metabolite were rescaled to set the median equal to 1 across all samples. Missing values, generally due to the sample measurement falling below the limit of detection, were then imputed with the minimum observed value for the respective metabolite.

[0270] Biochemistry

[0271] Glucose and C-reactive protein (CRP, Roche, Switzerland) were determined in fasted plasma samples. C-peptide was measured by radioimmunoassay (Millipore). Total cholesterol, high density lipoprotein cholesterol (HDLc), and triglycerides (TG) were determined in EDTA-containing plasma using commercially available enzymatic assays (Randox, Antrim, UK and DiaSys, Germany). All analyses were performed using a Selectra autoanalyzer (Sopachem, The Netherlands). Low density lipoprotein cholesterol (LDLc) was calculated using the Friedewald formula. Calprotectin was determined in feces using a commercial ELISA (Bühlmann, Switzerland).

[0272] Fecal sample shotgun sequencing and metagenomic pipeline

[0273] Fecal microbiota were analyzed using shotgun sequencing on donor fecal samples and fecal samples taken at 0, 6 and 12 months after initiation of study. DNA extraction from fecal samples for shotgun metagenomics was performed. Subsequently, shotgun metagenomic sequencing was performed (Clinical Microbiomics, Copenhagen, Denmark.). Before sequencing, the quality of the DNA samples was evaluated using agarose gel electrophoresis, NanoDrop 2000 spectrophotometry and Qubit 2.0 fluorometer quantitation. The genomic DNA was randomly sheared into fragments of around 350 bp. The fragmented DNA was used for library construction using NEBNext Ultra Library Prep Kit for Illumina (New England Biolabs). The prepared DNA libraries were evaluated using Qubit 2.0 fluorometer quantitation and Agilent 2100 Bioanalyzer for the fragment size distribution. Quantitative real-time PCR (qPCR) was used to determine the concentration of the final library before sequencing. The library was sequenced on a Illumina HiSeq platform to produce 2×150 bp paired-end reads. Raw reads were quality filtered using Trimmomatic (v0.38), removing adapters, trimming the first 5 bp, and then quality trimming reads using a sliding window of 4 bp and a minimum Q-score of 15. Reads that were shorter than 70 bp after trimming were discarded. Surviving paired reads were mapped against the human genome (GRCh37_hg19) with bowtie2 (v2.3.4.3) in order to remove human reads. Finally, the remaining quality filtered, non-human reads were sub-sampled to 20 million reads per sample and processed using Metaphlan2 (v2.7.7) to infer metagenomic microbial species composition and Humann2 (v0.11.2) to extract gene counts and functional pathways. In brief, reads were mapped using bowtie2 against microbial pangenomes; unmapped reads were translated and mapped against the full Uniref90 protein database using diamond (v0.8.38). Pathway collection was performed using the MetaCyc database.

[0274] Small Intestinal Microbiota Analyses

[0275] Biopsies were added to a bead-beating tube with 300 μl Stool Transport and Recovery (STAR) buffer, 0.25 g of sterilized zirconia beads (0.1 mm). Six ul of Proteinase K (20 mg/ml; QIAGEN, Venlo, The Netherlands) was added and incubated for 1 hour at 55° C. The biopsies were then homogenized by bead-beating three times (60 s×5.5 ms) followed by incubation for 15 min at 95° C. at 1000 rpm. Samples were then centrifuged for 5 min at 4° C. and 14,000 g and supernatants transferred to sterile tubes. Pellets were re-processed using 200 μl STAR buffer and both supernatants were pooled. DNA purification was performed with a customized kit (AS1220; Promega) using 250 μl of the final supernatant pool. DNA was eluted in 50 μl of DNAse-RNAse-free water and its concentration measured using a DS-11 FX+ Spectrophotometer/Fluorometer (DeNovix Inc., Wilmington, USA) with the Qubit™ dsDNA BR Assay kit (Thermo Scientific, Landsmeer, The Netherlands). The V5-V6 region of 16S ribosomal RNA (rRNA) gene was amplified in duplicate PCR reactions for each sample in a total reaction volume of 50 μl. A first step PCR using the 27F and the 1369R primer were used for primary enrichment. One ul of 10 μM primer, 1 μl dNTPs mixture, 0.5 μl Phusion Green Hot Start II High-Fidelity DNA Polymerase (2 U/μl; Thermo Scientific, Landsmeer, The Netherlands), 10 μl 5× Phusion Green HF Buffer, and 36.5 μl DNAse-RNAse-free water. The amplification program included 30 s of initial denaturation step at 98° C., followed by 5 cycles of denaturation at 98° C. for 30 s, annealing at 52° C. for 40 s, elongation at 72° C. for 90 s, and a final extension step at 72° C. for 7 min. On the PCR product a nested PCR was performed using the master mix containing 1 μl of a unique barcoded primer, 784F-n and 1064R-n (10 μM each per reaction), 1 μl dNTPs mixture, 0.5 μl Phusion Green Hot Start II High-Fidelity DNA Polymerase (2 U/μl; Thermo Scientific, Landsmeer, The Netherlands), 10 μl 5× Phusion Green HF Buffer, and 36.5 μl DNAse-RNAse-free water. The amplification program included 30 s of initial denaturation step at 98° C., followed by 5 cycles of denaturation at 98° C. for 10 s, annealing at 42° C. for 10 s, elongation at 72° C. for 10 s, and a final extension step at 72° C. for 7 min. The PCR product was visualized in 1% agarose gel (˜280 bp) and purified with CleanPCR kit (CleanNA, Alphen aan den Rijn, The Netherlands). The concentration of the purified PCR product was measured with Qubit dsDNA BR Assay Kit (Invitrogen, California, USA) and 200 ng of microbial DNA from each sample were pooled for the creation of the final amplicon library, which was sequenced (150 bp, paired-end) on the Illumina HiSeq. 2500 platform (GATC Biotech, Constance, Germany).

[0276] Raw reads were demultiplexed using the Je software suite (v2.0.) allowing no mismatches in the barcodes. After removing the barcodes, linker and primers, reads were mapped against the human genome using bowtie2 in order to remove human reads. Surviving microbial forward and reverse reads were pipelined separately using DADA2(Callahan et al., 2016) (v1.12.1). Amplicon Sequence Variants (AVSs) inferred from the reverse reads were reverse-complemented and matched against ASVs inferred from the forwards reads. Only non-chimeric forward reads ASVs that matched reverse-complemented reverse reads ASVs were kept. ASV sample counts were inferred from the forward reads. ASV taxonomy was assigned using DADA2 and the SILVA (v132) database. The resulting ASV table and taxonomy assignments were integrated using the phyloseq R package (v1.28.0) and rarefied to 60000 counts per sample.

[0277] Power Calculation and Statistics

[0278] A sample size of 17 patients in each group (34 patients in total) was needed to provide 80% power to detect a 50% difference in the C-peptide AUC (360 mmol/l/min vs 180 mmol/l/min with a standard deviation of 170) between treatment groups at 12 months, with a two-sided test at α=0.Math.05 and 10% dropout. All analyses were based on the pre-specified intention-to-treat cohorts with known measurements (complete case analysis); missing values were assumed to be missing at random. Primary endpoint of the trial was the preservation of residual (MMT stimulated) beta cell function at 6 and 12 months compared to baseline (0 months). Other secondary endpoints were changes during these 12 months in whole blood leukocyte subsets for immunologic markers of autoimmunity, parameters of glycemic control as well as fasting plasma metabolites. Finally, changes between baseline and 6 months after start of the FMT in small intestinal epithelial genes were determined. Analyses were done by intention to treat.

[0279] For baseline differences between groups unpaired Student t-test or the Mann-Whitney U test were used dependent on the distribution of the data. Accordingly, data are expressed as mean±the standard deviation or the median with interquartile range. Post-prandial results (e.g., c-peptide) are described as area under the curves (AUC) for the 2 hour post-prandial follow-up, calculated by using the trapezoidal method. For correlation analyses, Spearman's Rank test was used (as all parameters were non-parametric). For comparison of the primary end point a linear mixed model (LMM) was used (lme4 package in R), where “allocation” and “timepoint” were fixed effects and “patient entry number” was a random effect. The p value for the interaction between “allocation” and “timepoint” was reported. Additionally, parameters were compared between groups at various time points using Mann-Whitney U test. A p-value <0.05 was considered statistically significant. The study was conducted at the Academic Medical Center (Amsterdam), in accordance with the Declaration of Helsinki (updated version 2013). All participants provided written informed consent and all study procedures were approved by the IRB (ethics committee) of the Academic Medical Center. The study was prospectively registered at the Dutch Trial registry (NTR3697).

[0280] Machine Learning and Follow-Up Statistical Analyses

[0281] Extreme Gradient Boosting (XGBoost) machine learning classification algorithm was applied, in combination with a stability selection procedure to identify which parameters (either as values at baseline, or as relative changes) best predicted treatment groups and responders versus non-responders. This technique was used on duodenal microbial composition (16S rRNA sequencing on biopsies), on fecal microbiota composition and metabolic pathway abundance, and on plasma metabolite levels. To predict treatment groups, the relative change (delta) of each parameter between 0 and 12 months was used. For duodenal microbes delta 0 vs 6 months was used. For prediction of responders vs non-responders, baseline values, delta 0 vs 6 months and delta 0 vs 12 months were used. Each analysis produced a ranked list of the top 30 of most discriminative features. The top parameters were selected from each analysis that accurately (i.e., ROC AUC of 0.8 or higher) or moderately (ROC AUC >0.7) predicted group allocation for closer study, using an arbitrary but reasonable cut off. This cut off was generally a relative importance of around 30% or higher. Then, the change in time was visualized of the selected parameters (Wilcoxon's signed rank tests) and between-group differences were studies (Mann-Whitney U tests) at each time point using and finally, using Spearman's rank test, these parameters were correlated with the primary end point and with other key parameters that were identified in this way.

[0282] Results

[0283] Patients were randomly assigned to donor FMT (n=11 subjects) or autologous FMT (n=10 subjects). One participant retracted consent after the first study visit. Due to lack of funding, the trial was stopped after 20 subjects were enrolled and completed the study. Seven healthy lean donors (of whom 3 were used twice) donated for the allogenic gut microbiota transfer to 10 new onset DM1 patients, and the same donor was used for the three consecutive FMT's in each DM1 patient. There were no differences at baseline between both groups and also throughout the follow-up period, there were no serious adverse events or adverse changes in plasma biochemistry in both treatment groups.

[0284] Autologous FMT preserves (stimulated) C-peptide levels better than allogenic FMT

[0285] Mean fasting plasma C-peptide at baseline was similar between groups (327 pmol/l+/−89 in the allogenic group vs 319+/−118 in the autologous group; p=0.86, Student's T-test), but deteriorated in the allogenic FMT group compared to the autologous FMT group at 12 months (202+/−85 vs 348 pmol/l+/−115, Student's T-test p-value=0.0049; LMM p=0.00019). A similar effect was seen in stimulated C-peptide response AUC, which was similar between groups at baseline (361+/−154 mmol/l.Math.min in the allogenic group vs 355+/−97 in the autologous group; p=0.92, Student's T-test), but residual betacell function was significantly more preserved at 12 months after autologous FMT (392+/−124 vs 248+/−153 mmol/1min, Student's T-test p-value=p=0.033, LMM p-value=0.000067). As expected, exogenous insulin treatment lowered HbA1c levels in both groups at 12 months. Despite similar amounts of daily exogenous insulin needs between the allogenic (0.45+/−SD IU/kg/day) and the autologous FMT group (0.47 IU/kg/day), and although not significant improved glycemic control was suggested in the autologous FMT compared to the allogenic FMT group (HbA1c 46 vs 53.5 mmol/mol, MWU p=0.19, LMM p-value=0.12). Glucometabolic parameters at 0, 6 and 12 months were determined. Finally, BMI, fecal calprotectin, microalbuminuria, lipid profiles, and dietary intake (separate assessment of total calories, fat, saturated fat, protein, carbohydrates, and fiber) were not different at baseline nor during the course of the study.

[0286] Treatment success of autologous FMT can be predicted by changes in plasma metabolites as well as microbiota composition.

[0287] Small intestinal microbiota differences between FMT treatment groups

[0288] Alpha diversity of the small intestinal microbiota was not significantly different between treatment groups at baseline, but at 6 months there was a significant difference between autologous and allogenic FMT group (p=0.054), which was in line with a significant increase in diversity in the allogenic FMT group (p=0.009). When plotted along ordination axes in a redundancy analysis (RDA-plot), small intestinal microbiota compositions clustered differently at baseline between groups and also changed differentially between treatment groups. FMT treatment group allocation could be predicted reliably by change in specific small intestinal bacterial strains (AUC ROC 0.89±0.18) including two species of Prevotella and Streptococcus oralis (FIG. 1). However, changes on the phylum, family, genus, and species level showed no major shifts in small intestinal microbiota composition. Relative abundances of all these species decreased after autologous fecal transplantation, but increased after allogenic fecal transplantation. Of note, the relative abundance of Prevotella 1 showed a baseline difference between groups (p=0.033). The delta was significantly different between groups for Prevotella 2 (p=0.048), but not for Prevotella 1 (p=0.069) or S. oralis. Furthermore, a significant inverse correlation was observed between Prevotella 1 relative abundance and stimulated C-peptide AUC (Spearman p=0.015, rho=−0.55).

[0289] Fasting Plasma Metabolite Changes Upon FMT

[0290] Fasting plasma metabolite levels were different between DM1 and donors and were altered upon FMT. Treatment group allocation was reliably predicted by change in fasting plasma metabolites between 0 and 12 months (ROC AUC 0.79±0.23). The relative importance of the ten most predictive metabolites are shown in FIG. 2A. From the top 3 metabolites 1-myristoyl-2-arachidonoyl-GPC (MA-GPC) (p=0.02) and 1-arachidonoyl-GPC (A-GPC)(p=0.02, Mann-Whitney U test), but not 1-(1-enyl-palmitoyl)-2-linoleoyl-GPE (EPL-GPE), were different between groups at 12 months (FIGS. 2B-D). Also, changes in plasma MA-GPC levels correlated significantly with changes in fasting C-peptide (p=0.012, Mann-Whitney U test, FIG. 2E).

[0291] Fecal Microbiota Changes Upon FMT

[0292] Fecal microbiota composition was different between Dm1 and healthy donors at baseline and also changed differentially between treatment groups. However, alpha diversity did not differ significantly between FMT treatment groups at baseline, 6 or 12 months nor between donors and recipients. Some shifts were seen on phylum, family, genus and species level between groups. Group allocation prediction based on fecal microbiota taxonomic changes between 0 and 12 months showed a moderate ROC AUC of 0.72±0.24. Desulfovibrio piger stood out as the most differentiating bacterial strain between treatment groups (FIG. 3). Treatment group prediction based on metabolic pathways showed a relatively poor ROC AUC of 0.68±0.27. Interestingly, abundance of D. piger changed differentially between treatment groups at 6 (p=0.024, MWU) and 12 (p=0.023) months follow-up (FIGS. 2G-H). Furthermore, change in D. piger correlates positively with change in fasting C-peptide (p=0.009, FIG. 2I) and with plasma 1-arachidonoyl-GPC levels (p=0.004, FIG. 2J). Moreover, a change in relative abundance of D. piger was inversely correlated with changes in relative abundance of both Prevotella 1 (FIG. 2K) and Prevotella 2 (FIG. 2L).Furthermore, change in D. piger correlates positively with change in fasting C-peptide (p=0.009, FIG. 2I) and with plasma 1-arachidonoyl-GPC levels (p=0.004, FIG. 2J). Moreover, change in relative abundance of D. piger was inversely correlated with change in relative abundance of both Prevotella 1 (FIG. 2K) and Prevotella 2 (FIG. 2L).

[0293] Baseline Fecal Microbiota Composition Predicts FMT Response.

[0294] As gut microbiota composition was different between healthy and T1D subjects in various age groups, it was also reasoned that FMT per se is an intervention in autoimmune diseases, as FMT introduces fecal material in the small intestine. Thus, a post hoc analysis was performed studying responders compared to non-responders to FMT, irrespective of treatment group. It was thus investigated whether baseline characteristics of T1D patients can predict response to FMT therapy at 12 months follow-up and which bacterial strains and plasma metabolites were associated with this response. Clinical response was defined as <10% decline in beta cell function compared to baseline at 12 months follow-up, which is significantly less than the expected natural 1-year decline of 20% in beta cell function. At 6 months follow-up, 2 months after the final FMT, 12/20 subjects were responders. At 12 months follow-up, clinical response sustained in 10 subjects of whom 3 had received allogenic and 7 had received autologous FMT (FIGS. 4A-B). Responders at 12 months were thus chosen for the analyses because the primary end point (MMT stimulated C-peptide) was significantly different at 12 (but not at 6) months and because interference by the honeymoon phase is less at the 12 vs 6 months time point. Predictive modeling was next used to determine which baseline parameters (either their baseline values or delta 0-12 month values) were predictors of clinical response to FMT.

[0295] Baseline Fecal Microbiota Composition Best Predicts Clinical Response Upon FMT

[0296] Baseline fecal microbiota composition predicted clinical response upon FMT very accurately (AUC ROC 0.93±0.14). In this regard, intestinal levels of Bacteroides caccae and Coprococcus catus stood out as most differentiating microbes (FIG. 5), both of which were significantly more abundant at baseline in responders than in non-responders (FIGS. 4C-D). From the top 10 most differentiating intestinal bacterial strains, Paraprevotella spp, Collinsella aerofaciens, Bacteroides eggerthii and Ruminococcus callidus were also significantly different at baseline between responders and non-responders (FIGS. 6A-E). A significant (negative) correlation was observed between change in C. catus abundance and stimulated C-peptide AUC (p=0.053, r=−0.44, FIG. 4E). Response was predicted less accurately by change in fecal microbiota composition (AUC ROC 0.76±0.23) than by baseline composition suggesting that at T1D diagnosis gut microbiota composition can predict gut microbiota based treatment efficacy. The most differentiating species were Bacteroidales bacterium ph8, Actinomyces viscosus, Bacteroides thetaoitaomicron, Streptococcus salivarius, Ruminococcus bromii and Clostridium leptum, of which B. bacterium ph8 (p=0.015, Mann-Whitney U test) and R. bromii (p=0.013) become less abundant in responders vs non-responders, S. salivarius (p=0.045) becomes more abundant in responders vs non-responders and B. thetaiotaomicron is significantly different at baseline and shows a downward trend in responders.

[0297] Integration of Multiomics Analyses Upon FMT

[0298] Correlations between parameters that were found to be significantly affected by FMT were explored. Since responders were found in both treatment groups, correlations were first explored in the pooled dataset (n=20) and then within treatment groups separately and in clinical responders upon FMT. In the pooled dataset an intertwined cluster of notable parameters was found, which positively and negatively associated with markers of glucose regulation (i.e., C-peptide AUC, fasting C-peptide and HbA1c). On one hand, the highly correlated plasma metabolites MA-GPC and A-GPC accurately predicting preservation of insulin secretion, correlate positively to D. piger, which correlates positively to fasting C-peptide. On the other hand, Prevotella 1, Prevotella 2 and S. oralis correlate negatively to glucose regulation and with metabolites MC-GPC and A-GPC. Analyzing treatment groups separately, preserved beta cell function (high C-peptide) in the autologous group was characterized at baseline by high Coprococcus catus, as well as a subsequent decrease in Ruminococcus bromii. In the allogenic group, preserved beta cell function was characterized by a decrease in fecal Roseburia intestinalis (which incidentally correlates positively with Prevotella 1 and 2). Finally, in clinical responders, preserved beta cell function was characterized by decreases in duodenal Prevotella 1 , Prevotella 2, fecal Coprococcus catus, metabolite EPL-GPE, whereas D. piger increased.

[0299] Analysis

[0300] It is reported here for the first time that FMT can have an effect on residual beta cell function in new onset T1D patients. This accords with recent observational studies supporting a role for the intestinal microbiota in T1D subjects. Contrary to expectations, autologous FMT performed better than healthy donor FMT, while even in the allogenic group the decline in residual beta cell function appeared less than expected without treatment. An appealing explanation would be that beneficial immunological effects of FMT are more pronounced and durable, when the FMT donor microbiota better matches the immunological tone of the host. This to the extent that beneficial effects of healthy donor stool may be dampened by (immuno)incompatibility. Other observations also point toward an immunological regulatory role of specific plasma metabolites that are derived from diet and converted by intestinal microbiota. While the overall clinical effects of FMT were modest and show a wide variety between new onset T1D subjects, the intervention was safe and had no side effects. It is proposed that changes in plasma metabolites, predominantly fatty acids and tryptophan derivatives, as a consequence of the altered intestinal microbiota composition, may explain the observed beneficial effects of FMT on residual beta cell function in patients with new onset T1D.

[0301] Preservation of beta cell function is associated with changes in specific gut microbiota strains.

[0302] D. piger may dampens autoimmunity in T1D via plasma 1-arachidonoyl-GPC. Predictive modeling showed that baseline fecal microbiota taxonomy and metabolic pathways accurately predicted response at 12 months. However, the identified microbes (e.g., B. caccae and C. catus) did not correlate with any of the relevant immune parameters, small intestinal genes or plasma metabolites. This suggests that fecal microbiota composition is consequence rather than cause of the host immunological characteristics that associate with response. The exception to this was D. piger, a sulfate-reducing bacterial strain. Its beneficial effects may be mediated by its production of hydrogen sulfide. Moreover, D. piger was identified as outstanding fecal microbial predictor of FMT treatment group allocation. Interestingly, this small intestinal bacterial strain was also beneficially associated with change in stimulated C-peptide responses upon FMT and its abundance increased in the autologous group and in the overall responders. Interestingly, D. piger correlated positively with levels of plasma 1-arachidonoyl-GPC (FIG. 2J), one of the key metabolites that also associated with improved C-peptide production. In conclusion, D. piger could be a strong candidate to dampen autoimmunity through production of A-GPC, e.g., through uptake by protruding dendrites of immune cells into the intestinal lumen. Interestingly, D. piger was recently cultured from the human intestinal tract, enabling testing this bacterial strain in human T1D (Chen et al. 2019, Letters in Applied Microbiology 68(6) 553-561). Other bacterial species in the duodenum that best differentiated between treatment groups were two unnamed Prevotella spp. and Streptococcus oralis. The explorative integration of multiomics analyses subsequently show that these Prevotella spp. and S. oralis are negatively associated with the key beneficial metabolite MA-GPC, a glycerophospholipid. B. stercoris correlated positively with D. piger and A-GPC and negatively with S. oralis, but did not correlate positively with C-peptide. Finally, changes in Ruminococcus bromii (autologous FMT group) and Roseburia intestinalis (allogenic FMT group) were negatively associated with changes in C-peptide, although both strains are generally regarded as beneficial microbes that thrive during fiber-rich diets, produce SCFA's and promote intestinal integrity.

[0303] Conclusions

[0304] Fecal transplantation of colon-derived microbiome into the host small and large intestine in T1D patients effectively prolongs residual beta cell function and thus honeymoon phase. Moreover, several novel bacterial strains including fecal D. piger and B. stercoris as well as duodenal Prevotella spp. and S. oralis were identified with therapeutic potential. Accordingly, increases in plasma metabolites such as 1-myristoyl-2-arachidonoyl-GPC, 1-arachidonoyl-GPC, and 6-bromotryptophan upon FMT associated with beneficial changes.

EXAMPLE 3

[0305] In this Example, the effects of the following compounds were assessed in cell-based assays: [0306] 6-bromotryptophan (6-BT) [0307] 1-arachidonoyl-glycero-phosphocholine (20:0) (A-GPC) [0308] 1-palmitoyl-2-linoleoyl-sn-glycero-3-phosphoethanolamine (16:0-18:2 PE) [0309] 1-myristoyl-2-arachidonoyl-glycero-phosphocholine (MA-GPC)

[0310] Materials and Methods

[0311] Metabolite Preparation and Cell Culture

[0312] 6-bromotryptophan (6-BT) (Alichem) was purchased as powder and dissolved in DMSO at 50 mM.

[0313] 1-arachidonoyl-glycero-phosphocholine (20:0) (LysoPC(20:0) (Avanti Polar) was purchased as powder and was dissolved in PBS at 0.9 mM.

[0314] 1-palmitoyl-2-linoleoyl-sn-glycero-3-phosphoethanolamine (16:0-18:2 PE) (Avanti Polar) was purchased in chloroform at 10 mg/ml; 200 μl (equivalent to 2 mg) were transferred to a glass tube and chloroform was evaporated under nitrogen flow to obtain a transparent film, which was afterwards dissolved in PBS at 1 mM.

[0315] 1-myristoyl-2-arachidonoyl-glycero-phosphocholine (MA-GPC) (Syncom, custom made synthesized) was purchased as powder and dissolved in DMSO at 10 mM.

[0316] All cell-types were culture at 37° C. in a 5% CO.sub.2 atmosphere and treated with the metabolites for no longer than 24 hours, in control condition the appropriate vehicle (DMSO or PBS) was added in the medium.

[0317] NF-κB Reporter Macrophage and Luciferase Assay

[0318] NF-κB signaling activation was assessed by luciferase activity assay. RAW264.7 cells stably transfected with the 3 ×-κB-luc plasmid (DNA construct containing three NF-κB sites from the Ig κ light chain promoter coupled to the gene encoding firefly luciferase) were grown in DMEM medium supplemented with 10% heat-inactivated fetal bovine serum, penicillin (100 U/ml), streptomycin (100 μg/ml), L-glutamine (2 mM). Cells were seeded in F-bottom 96-well plates at a density of 0.5×10.sup.5 per well and the following day stimulated with LPS (10/100 ng/ml) for 2 hours with/without addition of metabolites at different concentrations (6-BT 0,1-100 μM, LysoPC(20:0) 1-10 μM, 16:0-18:2 PE 1-50 μM, MA-GPC 1-100 μM). Afterwards, cells were lysed with 25 μl/well 1×passive lysis buffer and firefly luciferase activity was measured by LUCIFERASE® Assay System (Promega, E1500) on a GLOMAX®-Multi Detection System (Promega).

[0319] In Vitro Stimulation of Primary Monocytes

[0320] Naïve bone marrow monocytes were isolated from BM cells. Briefly, hind legs were removed from 3 mice, cleaned from surrounding muscles. The femur and tibia bones were trimmed at their extremities, the BM content was flushed out with cold PBS using a 10 ml syringe and a 25G needle and filtered through a 40 μm strainer. Red blood cells (RBC) were lysed with 1× RBC lysis buffer (Biolegend) for 5 min. on ice. CD11b+ monocytes were further purified by positive selection using a cocktail of CD11b magnetic beads (Miltenyi Biotec, #130-049-601) and magnetizing MS columns (Miltenyi Biotec) according to the manufacturer's instructions. Subsequently, monocytes were seeded in F-bottom 96-well plates at 1×10.sup.5 cells per well in RPMI1640 supplemented with 10% heat-inactivated fetal bovine serum, penicillin (100 U/ml), streptomycin (100 μg/ml), L-glutamine (2 mM) and activated with 10 μg/ml poly(I:C). Monocytes were activated with 10 ng/ml LPS (Sigma-Aldrich) and subjected to treatment with 6-BT (10/100 μM), LysoPC(20:0) (10/50 μM), MA-GPC (10/50/100 μM), or appropriate vehicle. Cells were kept in a final volume of 200 μl/well for 24 hours, after which supernatant was harvested and stored at −80° C.

[0321] In Vitro Stimulation of Murine Macrophages/Dendritic Cells (DC)

[0322] Bone marrow-derived macrophages (BMDM) and DC (BMDC) were obtained by differentiating freshly isolated BM cells from femur and tibia bones (as above described) of C57/Bl6 mice (N=3 per experiment). For BMDM, BM cells were seeded at 3×10.sup.6 cells per 10 cm dish and cultured for 7 days in 12 ml RPMI1640 medium with 20% fetal bovine serum, 30% L-929 cell conditioned media, as source of murine macrophage colony-stimulating factor (M-CSF). For BMDC, BM cells were seeded at 0.5×10.sup.6 /ml cells in 25 ml in 10 cm dishes and cultured for 7 days in presence of GM-CSF in 5% FBS-RPMI1640 medium. After differentiation, BMDM/DCs were harvested, counted and seeded at a density of 1×10.sup.5 cells per well in a F-bottom 96-well plate and left to adhere for 20 hours before experiments were performed. Macrophages were activated with 10 μg/ml polyinosinic-polycytidylic acid (poly(I:C) (InvivoGen) for 24 hours in presence or not of 6-BT (10/100 μM), LysoPC(20:0) (10/50 μM), or MA-GPC (10/50/100 μM) in a final volume of 200 μl/well. At the end of the assay, supernatant was harvested and stored at −80° C.

[0323] In Vitro CD4+ T Cell Activation Assay

[0324] Primary CD4+ T cells were freshly isolated by negative selection from spleens of C57/Bl6 mice (N=3 per experiment). Briefly, spleens were smashed in a culture dish and passed twice through a strainer (70 μm and 40 μm, respectively) to obtain a single-cell suspension. After red blood cell lysis (10 min. on ice) with 1× RBC lysis buffer (Biolegend), cells were counted, stained with a cocktail of biotin-conjugated antibodies against CD8a, CD11b, CD11c, CD19, CD45R (B220), CD49b (DX5), CD105, Anti-MHC-class II, Ter-119 and TCRγ/δ and subsequently stained with magnetically labeled with Anti-Biotin MicroBeads.

[0325] Using the negative selection (CD4+ T Cell Isolation kit, Miltenyi Biotec, #130-104-454). Non-CD4 T cells were depleted by retaining them in LS magnetizing column (Miltenyi Biotec).

[0326] Isolated CD4 T cells were cultured in 96-well plates (1×10.sup.5 per well) in RPMI1640 medium supplemented with 10% fetal bovine serum, 100 U/ml penicillin, 100 μg/ml streptomycin, 2 mM L-glutamine. Treatment with the metabolites 6-BT (1/10 μM), LysoPC(20:0) (10/50 μM) or MA-GPC (10/50/100 μM) and activation with 2.5 μg/ml soluble anti-CD3 (145-2C11, eBioscience) and 1 μg/ml soluble anti-CD28 (37.51, eBioscience) antibodies started immediately after seeding in 200 μl/well complete RPMI1640 media for a 24-hour period, at the end of which supernatant was harvested and stored at −80° C.

[0327] In Vitro Stimulation of Human Monocytes

[0328] The mononuclear cell fraction was isolated from the blood of healthy volunteers (Sanquin Bloodbank, Amsterdam, The Netherlands) by density centrifugation using Lymphoprep™ (Axis-Shield) and isolated using human CD14 magnetic beads and MACS® cell separation columns (Miltenyi Biotec) according to the manufacturer's instructions. Isolated primary human monocytes were counted and seeded at 1×10.sup.6 cells/mL in 24-well plates with 1 ml medium supplemented with 10% fetal bovine serum, 100 U/ml penicillin, 100 μg/ml streptomycin, 2 mM L-glutamine. After seeding, cells were stimulated with 10 ng/ml LPS or 25 mM D-glucose (both Sigma-Aldrich) for 24 hours with/without 100 μM 6-BT. Afterwards, cells were lysed with Tripure isolation reagent (Roche) and stored at −80° C. until RNA isolation.

[0329] In Vitro Stimulation of Pancreatic Beta Cells

[0330] INS1E cells (rat pancreatic beta-cell line) were maintained in complete RPMI1640 supplemented with 5% Fetal Bovine Serum, 2 mM L-glutamine, 5 μM beta-mercaptoethanol, 1 mM sodium pyruvate, 10 mM HEPES, 100 units/ml of penicillin and 100 μg/ml streptomycin. INSIE cells were seeded in 48-well plates at a density of 1×10.sup.5 cells per well and left resting for one day. Subsequently, medium was replaced with 0.5 ml/well of INSIE complete RPMI1640 medium containing vehicle or the metabolites: 6-BT (1/10/25 μM), LysoPC(20:0) (5/10/50 μM), or MA-GPC (10/50/100 μM). After 24 hours, cells and supernatant were harvested for further analysis (gene expression and insulin secretion, respectively) and stored at −80° C. Cells were lysed in Tripure isolation reagent (Roche) before storage.

[0331] For glucose-stimulated insulin secretion (GSIS) assay, cells were preincubated in a Krebs-Ringer bicarbonate buffer (KRB) [115 mM NaCl, 5 mM KCl, 2.56 mM CaCl.sub.2, 1 mM MgCl.sub.2, 10 mM NaHCO.sub.3, 15 mM HEPES, and 0.3% of BSA (pH 7.4)] for 30 min at 37° C., following by stimulation with 1 mM glucose in KRB for 1 hour (0.5 ml/well) and stimulation with 22 mM glucose in KRB for another hour (0.5 ml/well) at 37° C. Supernatant was recovered after treatment with 1 mM glucose (Sigma-Aldrich) and 22 mM glucose and cells stored at −80° C. GSIS was performed on beta cells after treatment for 24-hour treatment with 10 μM 6-BT.

[0332] ELISA

[0333] Specific ELISAs (R&D Systems) were utilized to measure the concentration of TNFα, IFNβ, and IFNγ in cell supernatant of murine monocytes, macrophages ad T cells, respectively, according to the manufacturer's instructions. The concentration of insulin after 24-hour treatment with metabolites or after GSIS were determined using Rat insulin ELISA (Mercodia) according to the manufacturer's instructions. GSIS was calculated by subtracting the concentration of insulin at 1 mM glucose to the insulin rate at 22 mM glucose.

[0334] Gene Expression Analysis

[0335] Total RNA was extracted from Tripure isolation reagent cell lysates. RNA was converted to cDNA by with iScript kit (BioRad). Quantitative polymerase chain reaction (qPCR) was performed using SYBR Green-SensiMix (Bioline) on a CFX384 Touch Real-Time PCR Detection System (BioRad). The delta delta Ct method was used to calculate gene expression as fold-change compared to control (unstimulated conditions).

[0336] Statistics

[0337] Statistical analysis was performed using Student t tests for two group comparison and One-Way ANOVA and Dunnett's tests for multiple group comparison. Data are presented as mean and standard error of the mean (SEM). P<0.05 was considered to be significant.

[0338] Results

[0339] The results are shown in FIGS. 7-13: [0340] 6-BT, A-GPC, and MA-GPC can inhibit NFκB pathway activation in macrophages at different doses (FIG. 7). [0341] 6-BT, A-GPC, and MA-GPC halt cytokine secretion by monocytes (FIG. 8); [0342] 6-BT and MA-GPC impair type 1 IFN secretion (FIG. 9); [0343] 6-BT reduces cytokine production by human monocytes (FIG. 10); [0344] 6-BT and A-GPC dampen Th1 responses in CD4 T cells (FIG. 11); [0345] 6-BT enhances pancreatic beta-cell function (FIGS. 12 and 13);

[0346] Of specific interest is 6-bromotryptophan, which thus inhibits NFκB pathway activation, hampers immune responses in monocytes/macrophages and CD4 T cells, and improves pancreatic beta cell function. MA-GPC inhibits NFκB pathway activation, hampers immune responses in monocytes/macrophages and CD4 T cells.

EXAMPLE 4

[0347] Plasma 6-bromotryptophan levels inversely correlate with presence of Type 2 Diabetes mellitus and glycemic control in cross-sectional cohort (n=369 subjects)

[0348] In a 369-subject cohort, evidence was found that 6-bromotryptophan may protect against the onset and progression of Type 2 Diabetes mellitus. More specifically, it was found that plasma 6-bromotryptophan levels inversely correlate with presence of Type 2 Diabetes mellitus and glycemic control. This suggests that 6-BT may contribute to Type 2 Diabetes prevention and treatment and thus improved (micro and macrovascular) cardiovascular complications in Type 2 Diabetes. 6-BT may help to reduce macrovascular disease (i.e., cardiovascular disease) and microvascular complications also in non Type 2 Diabetes patients.

[0349] Materials and Methods

[0350] Fasting plasma targeted metabolite measurements were done by Metabolon (Durham, N.C.), using ultra high performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS), as previously described [Koh A, Molinaro A, Stahlman M, et al. Microbially Produced Imidazole Propionate Impairs Insulin Signaling through mTORC1. Cell 2018; 175:947-961.e17. doi:10.1016/j.cell.2018.09.055 ].

[0351] Results

[0352] Results are shown in Tables 2 and 3.

TABLE-US-00002 TABLE 2 Baseline characteristics CKD− CKD+ Total T2DM T2DM Controls p n 369 124 45 200 Age 51.72 52.13 60.24 49.55 <0.001 (mean (SD)) (11.27) (10.98) (6.04) (11.44) Sex = 2 (%) 196 68 19 109 0.294 (53.1) (54.8) (42.2) (54.5) Ethnicity (%) <0.001 Dutch 84 (22.8) 34 (27.4) 0 (0.0) 50 (25.0) South Asian 101 24 27 50 Surinamese (27.4) (19.4) (60.0) (25.0) African 105 37 18 50 Surinamese (28.5) (29.8) (40.0) (25.0) Ghanaian 79 (21.4) 29 (23.4) 0 (0.0) 50 (25.0) BMI 27.48 28.56 30.06 26.22 <0.001 (mean (SD)) (5.18) (5.66) (5.15) (4.48) WHR 0.93 0.94 1.00 0.91 <0.001 (mean (SD)) (0.09) (0.08) (0.08) (0.08) SBP 136.22 141.75 148.43 130.04 <0.001 (mean (SD)) (21.15) (22.56) (22.16) (17.69) DBP 83.23 86.54 83.90 81.03 <0.001 (mean (SD)) (11.52) (13.29) (9.42) (10.24) HT (%) 215 87 39 89 <0.001 (58.3) (70.2) (86.7) (44.5) AntiHT (%) 107 39 28 40 <0.001 (29.0) (31.5) (62.2) (20.0) MDRD 96.03 94.19 89.81 98.58 0.024 (mean (SD)) (21.56) (21.34) (28.91) (19.38) CKDEPI 94.99 93.29 84.31 98.46 <0.001 (mean (SD)) (19.49) (20.02) (23.43) (17.13) Microalb 0.44 0.92 0.96 0.02 <0.001 (mean (SD)) (0.50) (0.27) (0.21) (0.16) HbA1C 40.73 39.52 58.16 37.56 <0.001 (mean (SD)) (9.58) (4.64) (15.74) (4.62) Kreat 78.67 80.17 86.82 75.90 0.006 (mean (SD)) (21.61) (22.23) (36.63) (15.42)

TABLE-US-00003 TABLE 3 Correlations between compounds and presence of Diabetes, BMI value, Glucose value, HbA1c value Diabetes BMI Glucose HbA1c Scale 3-indoxyl sulfate 0.078 0.062 0.020 −0.015  −0.4 6-bromotryptophan −0.177 * −0.069 −0.062 −0.179 * −0.3 C-glycosyltryptophan 0.336 0.177 0.192 0.28  −0.2 indoleacetate 0.061 −0.033 −0.019 0.024 −0.1 indolelactate 0.194 0.028 0.182 0.166 0 indolepropionate −0.141  −0.157 −0.117 −0.125  0.1 kynurenate 0.17  0.123 0.13 0.154 0.2 kynurenine 0.123 0.096 0.048 0.099 0.3 tryptophan −0.100  0.011 −0.016 −0.052  0.4 tryptophan betaine 0.065 −0.115 0.017 0.002 indoleacetoylcamitine * 0.052 0.011 −0.041 −0.021  N-acetyltryptophan 0.124 0.030 0.127 0.101 serotonin 0.009 −0.067 −0.023 −0.018  xanthurenate 0.113 0.146 0.138 0.114 * Correlation is significant at the 0.05 level (2-tailed).

[0353] 6-Bromotryptophan Halts Inflammatory Responses in Myeloid Cells

[0354] 6-BT is a bromoindole derivative of tryptophan, which is known to be metabolized by indigenous gut microbes of the colon as well as of small intestine. So far, the physiological role of 6-BT is completely unknown. Clinical findings suggest a protective function against inflammation and diabetes.

[0355] With a series of in vitro/ex vivo experiments, some of 6-BT functions on immune cells as well as on insulin-producing pancreatic beta cells were elucidated.

[0356] 6-BT can inhibit the secretion of proinflammatory cytokine TNFα upon TLR4 and TLR2 engagements and of IFNbeta upon TLR3 activation

[0357] Here, murine bone marrow-isolated monocytes (Christ A., Western Diet Triggers NLRP3-Dependent Innate Immune Reprogramming. Cell 2018) or bone marrow-derived macrophages (Swanson K V, A noncanonical function of cGAMP in inflammasome priming and activation. JEM 2017) were exposed for 24 hours to the indicated concentrations of 6-BT (10-100 μM) in presence or not of 10 ng/ml LPS, 10 μg/ml P3C or 10 μg/ml poly(I:C). By means of ELISA assays, it has been found that 6-BT can inhibit the secretion of proinflammatory cytokine TNFa upon TLR4 and TLR2 engagements and of IFNbeta upon TLR3 activation. See FIG. 14.

[0358] The inhibition of TLR signaling induced cytokine secretion is particularly important for therapeutic approaches against inflammatory and infectious diseases in which the damage is driven by an excessive inflammatory repose (such as sepsis and systemic inflammatory response syndrome, SIRS).

[0359] 6-BT Inhibits the Secretion of the Proinflammatory Cytokines TNFa and IFNbeta

[0360] As dendritic cells (DC) are the major antigen-presenting cells crucial in the activation of T cells, next investigated was the effect of 6-BT on murine DC, differentiated with GM-CSF (40 ng/ml) by bone marrow cells. As for the monocytes/macrophages, 6-BT inhibits the secretion of the proinflammatory cytokines TNFα and IFNbeta by DC after activation of, respectively, TLR4 (with 100 ng/ml LPS) or TLR3 (10 μg/ml poly(I:C)). See FIG. 15.

[0361] 6-BT Significantly Reduced the Production of the Th1 Cytokine IFNgamma

[0362] Particularly in the context of autoimmune diabetes, the activity of T cells is driving disease onset and progression. Hence, the impact of 6-BT on CD4 T cells was further studied. To mimic antigen presentation, murine CD4 T cells (isolated from spleens; Uchimura T., The Innate Immune Sensor NLRC3 Acts as a Rheostat that Fine-Tunes T Cell Responses in Infection and Autoimmunity. Immunity 2019) were activated by monoclonal antibodies against CD3 and CD28 (2.5 and 1 μg/ml, respectively). In line with the findings on myeloid cells, 6-BT significantly reduced the production of the Th1 cytokine IFNgamma. See FIG. 16.

[0363] 6-BT Stimulates β-Cells Differentiation & Insulin Production

[0364] Given the positive association between plasma 6-BT levels and C-peptide concentrations (found in the clinical study), it was then questioned whether 6-BT can exert a direct effect on beta cells. Indeed, it is seen here that 6-BT induces, in IS1E beta cells, the gene expression of the transcription factors PDX1 and MAFA, which are important for beta cell maturation and functionality. In agreement, 6-BT also promotes insulin secretion at steady-state and during glucose-stimulated insulin secretion (data shown as the difference between insulin release at starving condition [1 mM glucose] and at hyperglycemic state [22 mM]), (Paula S., Exercise increases pancreatic β-cell viability in a model of type 1 diabetes through IL-6 signaling. FASEB J 2015). See FIG. 17.

[0365] Mechanism(s) of Action of 6-Bromotryptophan

[0366] Seeking for the molecular mechanism(s) underlying 6-BT actions, 6-BT impact on the activation of the NF-kB pathway, a central pathway in all inflammatory diseases (beyond autoimmunity) was checked first. Hence, the expression of the phosphorylated form of the p65 subunit, regarded as a marker of NFkB activation has been quantified. Upon T cell activation with PMA (50 ng/ml) and ionomycin (1 μg/ml), 6-BT could inhibit, at very early time-points (5-10 minutes after activation), the NF-kB signaling. This effect was found in both murine and human (Jurkat cells) CD4 T cells. See FIG. 18.

[0367] 6-BT Inhibits the Activation of NFkB in Macrophages

[0368] Similarly to what was observed in lymphocytes, 6-BT inhibits the activation of NFkB in macrophages. Using the RAW264.7 murine macrophage cell line stably expressing an NFkB luciferase reporter (Groeneweg M, Lipopolysaccharide-induced gene expression in murine macrophages is enhanced by prior exposure to oxLDL. J. Lipid Res., 2006), it was disclosed that overnight exposure of macrophages to 6-BT (10-200 μM) inhibits the transcriptional activity of the NFkB complex in a dose-dependent manner upon 2 hours stimulation with LPS (10 ng/ml). See FIG. 19.

[0369] 6-BT and Tryptophan Elicit Distinct Biological Activities

[0370] Next, it was questioned whether the effect of 6-BT are specific or can be exerted by tryptophan as well. In murine CD4 T lymphocytes (isolated from murine spleens; Uchimura T., The Innate Immune Sensor NLRC3 Acts as a Rheostat that Fine-Tunes T Cell Responses in Infection and Autoimmunity. Immunity 2019), 6-BT, but not tryptophan, exerted inhibitory effect on IFNgamma production upon CD3/CD28 engagement. This indicates that 6-BT and tryptophan elicit distinct biological activities. See FIG. 20.

[0371] In agreement with the results on DC, exposure of monocytes (isolated from murine bone marrow; Christ A., Western Diet Triggers NLRP3-Dependent Innate Immune Reprogramming. Cell 2018) to 6-BT or tryptophan, shows that the anti-inflammatory effects are specific for the 6-bromotryptophan molecule and not for tryptophan. See FIG. 21.

[0372] 6-BT Impacts the Intracellular Metabolism

[0373] Finally, it was uncovered that 6-BT also impacts the intracellular metabolism. Particularly it was found that 6-BT (100 uM) promotes the mitochondrial metabolism in murine and human (Jurkat) CD4 T cells. See FIG. 22.

[0374] OCR=oxygen consumption rate, used as a proxy of cellular utilization of mitochondrial oxidative phosphorylation. OCR was measured using a Seahorse XF Analyzer Uchimura T., The Innate Immune Sensor NLRC3 Acts as a Rheostat that Fine-Tunes T Cell Responses in Infection and Autoimmunity. Immunity 2019; Chou, AIM2 in regulatory T cells restrains autoimmune diseases, Nature 2021).

[0375] 6-BT Enhances Mitochondrial Metabolism

[0376] Similarly, 6-BT exposure could enhance the mitochondrial metabolism of pro-inflammatory M1 macrophages (differentiated in presence of LPS and IFNgamma; Cheng et al., JCI Insight. 2018; 3(22):e120638), without affecting the glycolytic flux. Intracellular metabolism measured using a Seahorse XF Analyzer, Uchimura T., The Innate Immune Sensor NLRC3 Acts as a Rheostat that Fine-Tunes T Cell Responses in Infection and Autoimmunity. Immunity 2019; Chou, AIM2 in regulatory T cells restrains autoimmune diseases, nature 2021). See FIG. 23.

[0377] 6-BT could Rescue Beta Cell Dysfunctionality in Both Type 1 and Type 2 Diabetes

[0378] Lastly, it was investigated whether 6-BT may influence the mitochondrial metabolism of beta cells, which rely on ATP and mitochondrial metabolite production for insulin exocytosis. 6-BT increased mitochondria metabolism both at steady-state and under hyperglycemia (25 mM glucose) in beta cells (INS1E beta cells). In addition, the effect of tryptophan on intracellular metabolism was tested and it was found that, as for the inflammatory markers, it exerted a different effect than 6-BT. Intracellular metabolism measured using a Seahorse XF Analyzer Uchimura T., The Innate Immune Sensor NLRC3 Acts as a Rheostat that Fine-Tunes T Cell Responses in Infection and Autoimmunity. Immunity 2019; Chou, AIM2 in regulatory T cells restrains autoimmune diseases, nature 2021).

[0379] Of importance, defects in mitochondria and oxidative metabolism have been reported in T2D (Haythorne, Nature Communications volume 10, Article number: 2474 (2019)), suggesting that 6-BT could rescue beta cell dysfunctionality in both type 1 and type 2 diabetes. Moreover, increase utilization of mitochondria metabolism may counteract ectopic intracellular lipid accumulation and hence counteract obesity.

[0380] In conclusion: [0381] 6-BT exerts pleiotropic effect on multiple cell-types [0382] It has anti-inflammatory effect on myeloid and lymphoid cells [0383] It promotes insulin secretion by beta cells

[0384] Mechanistically, its biological actions are distinct from the ones of tryptophan.

[0385] 6-BT does not act through activation of AhR, but it does inhibit NFκB activation and enhance mitochondrial metabolism. The latter is typically used by cells harboring an anti-inflammatory phenotype.

[0386] Applications

[0387] Because of its broad effects on multiple cell types, its inhibitory action on NFκB signaling and its promotion of mitochondrial metabolism and fitness, 6-BT may be a novel therapeutic not only in the context of type 1 and type 2 diabetes but also in many other inflammation related disorders such as sepsis, Systemic Inflammatory Response Syndrome (SIRS), and cardiovascular diseases.

EXAMPLE 5

[0388] Desulfovibrio genus levels inversely correlate with presence of Type 2 Diabetes mellitus and glycemic control in cross-sectional cohort (n=369 subjects)

[0389] In the same 369-subject cohort as discussed herein previously, evidence was found that bacteria belonging to the Desulfovibrio genus (e.g., Desulfovibrio piger) may protect against the onset and progression of Type 2 Diabetes mellitus. More specifically, it was found that the relative abundance of fecal bacteria belonging to the Desulfovibrio genus inversely correlates with presence of Type 2 Diabetes mellitus and glycemic control. This suggests that administration of Desulfovibrio genus may contribute to Type 2 Diabetes prevention and treatment and thus improved (micro and macrovascular) cardiovascular complications in Type 2 Diabetes. Desulfovibrio genus may help to reduce macrovascular disease (i.e., cardiovascular disease) and microvascular complications also in non-Type 2 Diabetes patients.

[0390] Materials and Methods

[0391] Fasting plasma targeted metabolite measurements were done by Metabolon (Durham, N.C.), using ultra high performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS), as previously described [Koh A., Molinaro A., Stahlman M., et al., Microbially Produced Imidazole Propionate Impairs Insulin Signaling through mTORC1. Cell 2018; 175:947-961.e17. doi:10.1016/j.cell.2018.09.055 ].

[0392] Results

[0393] Results are shown in Table 4 and in FIGS. 25 and 26.

TABLE-US-00004 TABLE 4 Correlations between fecal Desulfovibrio genus relative abundance and presence of Diabetes, BMI value, Glucose value, HbA1c value Diabetes BMI Glucose HbA1c Desulfovibrio genus −0.03* −0.03* 0.02 −0.02 *Correlation is significant at the 0.05 level (2-tailed).

[0394] In addition, in type 2 Diabetes mellitus patients, a clear relationship can be seen between fecal Desulfovibrio relative abundance and plasma 6BT levels. See FIG. 27.

TABLE-US-00005 SEQUENCE LISTING  <160> 1  <170> Patentin version 3.5  <210> 1  <211> 1542  <212> DNA  <213> Desulfovibrio piger  <400> 1  agagtttgat cctggctcag attgaacgct ggcggcgtgc ttaacacatg caagtcgtac   60 gcgaaaggga cttcggtccc gagtaaagtg gcgcacgggt gagtaacacg tggataatct  120 gcctctatga tggggataac agttggaaac gactgctaat accgaatacg ctcatgatga  180 actttgtgag gaaaggtggc ctctgcttgc aagctatcgc atagagatga gtccgcgtcc  240 cattagctag ttggtggggt aacggcctac caaggcaacg atgggtagcc gatctgagag  300 gatgatcggc cacactggaa ctgaaacacg gtccagactc ctacgggagg cagcagtggg  360 gaatattgcg caatgggcga aagcctgacg cagcgacgcc gcgtgaggga tgaaggtctt  420 cggatcgtaa acctctgtca gaagggaaga aactagggtg ttctaatcat catcctactg  480 acggtacctt caaaggaagc accggctaac tccgtgccag cagccgcggt aatacggagg  540 gtgcaagcgt taatcggaat cactgggcgt aaagcgcacg taggctgtta tgtaagtcag  600 gggtgaaagc ccacggctca accgtggaac tgcccttgat actgcacgac tcgaatccgg  660 gagagggtgg cggaattcca ggtgtaggag tgaaatccgt agatatctgg aggaacatca  720 gtggcgaagg cggccacctg gaccggtatt gacgctgagg tgcgaaagcg tggggagcaa  780 acaggattag ataccctggt agtccacgcc gtaaacgatg gatgctagat gtcgggatgt  840 atgtctcggt gtcgtagtta acgcgttaag catcccgcct ggggagtacg gtcgcaaggc  900 tgaaactcaa agaaattgac gggggcccgc acaagcggtg gagtatgtgg tttaattcga  960 tgcaacgcga agaaccttac ctaggtttga catctgggga accctcccga aaatgagggg 1020 tgcccttcgg ggagccccaa gacaggtgct gcatggctgt cgtcagctcg tgtcgtgaga 1080 tgttgggtta agtcccgcaa cgagcgcaac ccctatgcat agttgccagc aagtaaagtt 1140 gggcactcta tgcagactgc ccgggttaac cgggaggaa9 9tggggac9a cgtcaagtca 1200 tcatggccct tacacctagg gctacacacg tactacaatg gcacgcacaa agggcagcga 1260 taccgtgagg tggagccaat cccaaaaaac gtgtcccagt ccggattgca gtctgcaact 1320 cgactgcatg aagtcggaat cgctagtaat tcgaggtcag catactcggg tgaatgcgtt 1380 cccgggcctt gtacacaccg cccgtcacac cacgaaagtc ggttttaccc gaagccggtg 1440 agccaactag caatagaggc agccgtctac ggtagggccg atgattgggg tgaagtcgta 1500 acaaggtagc cgtaggggaa cctgcggctg gatcacctcc tt                    1542