| Literature DB >> 33013834 |
Tae Kang Kim1,2, June-Chul Lee3, Sin-Hyeog Im3,4, Myung-Shik Lee1.
Abstract
Type 1 autoimmune diabetes is an autoimmune disease characterized by specific destruction of pancreatic β-cells producing insulin. Recent studies have shown that gut microbiota and immunity are closely linked to systemic immunity, affecting the balance between pro-inflammatory and regulatory immune responses. Altered gut microbiota may be causally related to the development of immune-mediated diseases, and probiotics have been suggested to have modulatory effects on inflammatory diseases and immune disorders. We studied whether a probiotic combination that has immunomodulatory effects on several inflammatory diseases can reduce the incidence of diabetes in non-obese diabetic (NOD) mice, a classical animal model of human T1D. When Immune Regulation and Tolerance 5 (IRT5), a probiotic combination comprising Lactobacillus acidophilus, Lactobacillus casei, Lactobacillus reuteri, Bifidobacterium bifidium, and Streptococcus thermophiles, was administered 6 times a week for 36 weeks to NOD mice, beginning at 4 weeks of age, the incidence of diabetes was significantly reduced. Insulitis score was also significantly reduced, and β-cell mass was conversely increased by IRT5 administration. IRT5 administration significantly reduced gut permeability in NOD mice. The proportion of total regulatory T cells was not changed by IRT5 administration; however, the proportion of CCR9+ regulatory T (Treg) cells expressing gut-homing receptor was significantly increased in pancreatic lymph nodes (PLNs) and lamina propria of the small intestine (SI-LP). Type 1 T helper (Th1) skewing was reduced in PLNs by IRT5 administration. IRT5 could be a candidate for an effective probiotic combination, which can be safely administered to inhibit or prevent type 1 diabetes (T1D).Entities:
Keywords: autoimmune diabetes; gut homing receptor; gut permeability; probiotics; regulatory T cells
Mesh:
Year: 2020 PMID: 33013834 PMCID: PMC7496355 DOI: 10.3389/fimmu.2020.01832
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561
Figure 1Incidence of diabetes in female NOD mice. (A) IRT5 was administered since 4 weeks of age for 36 weeks, and the incidence of diabetes was monitored. Control group was treated with solvent only in the same manner (n = 10 for NOD-PBS and 24 for NOD-IRT5). (B,C) Changes of pancreatic islets. Insulitis score (B) and relative β-cell mass (C) were determined after 12 weeks of IRT5 administration as described in the MATERIALS AND METHODS (n = 8 for NOD-PBS and 9 for NOD-IRT5 in B; n = 7 for NOD-PBS and 8 for NOD-IRT5 in C). (D) Serum level of insulin autoantibody (IAA) was determined in NOD-PBS and NOD-IRT5 using ELISA (n = 6 for NOD-PBS and 6 for NOD-IRT (**p < 0.01; *p < 0.05).
Figure 2Changes of gut permeability in NOD mice treated with IRT5. (A) The expression of tight junction proteins was evaluated by real-time RT-PCR using mRNA from paraffin-embedded tissues and specific primers (n = 7 for NOD-PBS and 5 for NOD-IRT5). (B) The expression of ZO-1 protein was evaluated by immunohistochemistry. (C) Gut permeability was determined by measuring serum FITC fluorescence 4 h after oral administration of FITC-dextran (n = 5 for NOD-PBS and 5 for NOD-IRT5) (*p < 0.05; ns, not significant).
Figure 3Treg cells in NOD mice treated with IRT5. (A) Cells from pancreatic lymph nodes (PLNs), mesenteric lymph nodes (MLNs), or lamina propria of the small intestine (SI-LP) of NOD mice that were treated with IRT5 for 12 weeks were stained with anti-CD4 and -FOXP3 mAbs for flow cytometry gated on CD3 and CD4. The percentages of CD4+FOXP3+ cells among CD3+CD4+ cells were compared (bottom). Representative scattergrams are shown (top). The numbers in the top right quadrants represent the percentage of CD4+FOXP3+ Treg cells among CD3+CD4+ cells analyzed (n = 6 for NOD-PBS and 7 for NOD-IRT5 in PLNs; n = 6 for NOD-PBS and 7 for NOD-IRT5 in MLNs; n = 9 for NOD-PBS and 9 for NOD-IRT5 in SI-LP). (B) Cells prepared as in (A) were stained with anti-CD4 and -CCR9 mAbs for flow cytometry gated on CD3 and CD4. The percentages of CD4+CCR9+ cells among CD3+CD4+ cells were compared (bottom). Representative scattergrams are shown (top). The numbers in the top right quadrants represent the percentage of CD4+CCR9+ Treg cells among CD3+CD4+ cells analyzed (n = 8 for NOD-PBS and 8 for NOD-IRT5 in PLNs; n = 10 for NOD-PBS and 8 for NOD-IRT5 in MLNs; n = 7 for NOD-PBS and 7 for NOD-IRT5 in SI-LP). (C) Cells prepared as in (A) were stained with anti-FOXP3 and -CCR9 mAbs for flow cytometry gated on CD4 and FOXP3. The percentages of CCR9+FOXP3+ cells among CD4+FOXP3+ cells were compared (bottom). Representative scattergrams are shown (top). The numbers in the top right quadrants represent the percentage of CCR9+FOXP3+ Treg cells among CD4+FOXP3+ cells analyzed (n = 7 for NOD-PBS and 12 for NOD-IRT5 in PLNs; n = 7 for NOD-PBS and 12 for NOD-IRT5 in MLNs; n = 9 for NOD-PBS and 10 for NOD-IRT5 in SI-LP). (D) The numbers of CCR9+CD4+FOXP3+ cells were calculated from the total numbers of lymphocytes, the percentages of CD3+CD4+ cells among total lymphocytes and that of CCR9+FOXP3+ cells among CD3+CD4+ cells (*p < 0.05; ns, not significant).
Figure 4Th1/Th17 skewing in NOD mice treated with IRT5 for 12 weeks. (A) CD4+ Th cell skewing in PLNs, MSLs, or SI-LP was evaluated by flow cytometry. The proportions of IFN-γ+ cells and IL-17+ cells among CD3+CD4+ T cells (right). Representative scattergrams are shown (left) (n = 5 for NOD-PBS and 5 for NOD-IRT5 in PLNs; n = 5 for NOD-PBS and 4 for NOD-IRT5 in MLNs; n = 5 for NOD-PBS and 5 for NOD-IRT5 in SI-LP). (B) CD8+ Tc cell skewing in PLNs, MSLs, or SI-LP was evaluated by flow cytometry. The proportions of IFN-γ+ cells and IL-17+ cells among CD3+CD8+ T cells (right). Representative scattergrams are shown (left) (n = 5 for NOD-PBS and 5 for NOD-IRT5 in PLNs; n = 5 for NOD-PBS and 5 for NOD-IRT5 in MLNs; n = 5 for NOD-PBS and 5 for NOD-IRT5 in SI-LP) (*p < 0.05; ns, not significant).