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Immunosuppressive Functions of M2 Macrophages Derived from iPSCs of Patients with ALS and Healthy Controls.

ABSTRACT: Amyotrophic lateral sclerosis (ALS) is a disorder with immune alterations that augment disease severity. M2 macrophages benefit diabetic and nephrotic mice by suppressing the pro-inflammatory state. However, neither have M2 cells been investigated in ALS nor have human induced pluripotent stem cell (iPSC)-derived M2 cells been thoroughly studied for immunosuppressive potentials. Here, iPSCs of C9orf72 mutated or sporadic ALS patients were differentiated into M2 macrophages, which suppressed activation of pro-inflammatory M1 macrophages as well as proliferation of ALS CD4⁺CD25^- Tc (Teffs). M2 cells converted ALS Teffs into CD4⁺CD25⁺Foxp3⁺ regulatory T cells (Tregs) and rescued Tregs of ALS patients from losing CD25 and Foxp3. Furthermore, Tregs induced or rescued by iPSC-derived M2 had strong suppressive functions. ALS iPSC-derived M2 cells including those with C9orf72 mutation had similar immunomodulatory activity as control iPSC-derived M2 cells. This study demonstrates that M2 cells differentiated from iPSCs of ALS patients are immunosuppressive, boost ALS Tregs, and may serve as a candidate for immune-cell-based therapy to mitigate inflammation in ALS.

SUBMITTER: Zhao W

PROVIDER: S-EPMC7286967 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Immunosuppressive Functions of M2 Macrophages Derived from iPSCs of Patients with ALS and Healthy Controls.

Zhao Weihua W Beers David R DR Thonhoff Jason R JR Thome Aaron D AD Faridar Alireza A Wang Jinghong J Wen Shixiang S Ornelas Loren L Sareen Dhruv D Goodridge Helen S HS Svendsen Clive N CN Appel Stanley H SH

iScience 20200523 6

Amyotrophic lateral sclerosis (ALS) is a disorder with immune alterations that augment disease severity. M2 macrophages benefit diabetic and nephrotic mice by suppressing the pro-inflammatory state. However, neither have M2 cells been investigated in ALS nor have human induced pluripotent stem cell (iPSC)-derived M2 cells been thoroughly studied for immunosuppressive potentials. Here, iPSCs of C9orf72 mutated or sporadic ALS patients were differentiated into M2 macrophages, which suppressed acti ...[more]

PMID: 32521508

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Project description:BackgroundIn rheumatoid arthritis (RA), macrophages play an important role in modulating the immunoinflammatory response through their polarisation into "classically" (M1) or "alternatively activated" (M2) phenotypes. In RA, CTLA4-Ig (abatacept) reduces the inflammatory activity of macrophages by interacting with the costimulatory molecule CD86. The study aimed to investigate the efficacy of CTLA4-Ig treatment to induce an M2 phenotype both in M1-polarised monocyte-derived macrophages (MDMs) obtained from healthy subjects (HS) and in cultured MDMs obtained from active RA patients.MethodsCultured MDMs were obtained from peripheral blood mononuclear cells of 7 active RA patients and from 10 HS after stimulation with phorbol myristate acetate (5 ng/mL) for 24 h. HS-MDMs were then stimulated with lipopolysaccharide (LPS, 1 mg/mL) for 4 h to induce M1-MDMs. M1-MDMs and RA-MDMs were treated with CTLA4-Ig (100 μM and 500 μM) for 3, 12, 24, and 48 h. The gene expression of CD80, CD86, and TLR4 (M1 markers); CD163, CD204, and CD206 (surface M2 markers); and MerTK (functional M2 marker) was evaluated by qRT-PCR. The protein synthesis of surface M2 markers was investigated by Western blotting. The statistical analysis was performed by the Wilcoxon t-test.ResultsIn LPS-induced HS-M1-MDMs, CTLA4-Ig 100 μM and 500 μM significantly downregulated the gene expression of M1 markers (3 h p<0.01 for all molecules; 12 h p<0.05 for TLR4 and CD86) and significantly upregulated that of M2 markers, primarily after 12 h of treatment (CD163: p < 0.01 and p < 0.05; CD206: p < 0.05 and p < 0.01; CD204: p < 0.05 by 100 mg/mL). Moreover, in these cells, CTLA4-Ig 500 μM increased the protein synthesis of surface M2 markers (p < 0.05). Similarly, in RA-MDMs, the CTLA4-Ig treatment significantly downregulated the gene expression of M1 markers at both concentrations primarily after 12 h (p < 0.05). Furthermore, both concentrations of CTLA4-Ig significantly upregulated the gene expression of CD206 (after 3 h of treatment; p < 0.05), CD163, and MerTK (after 12 h of treatment, p < 0.05), whereas CD204 gene expression was significantly upregulated by the high concentration of CTLA4-Ig (p < 0.05). The protein synthesis of all surface markers was increased primarily by CTLA4-Ig 500 μM, significantly for CD204 and CD206 after 24 h of treatment (p < 0.05).ConclusionsCTLA4-Ig treatment seems to induce the in vitro shift from M1 to M2 macrophages, of both HS-M1-MDMs and RA-MDMs, as observed by the significant downregulation exerted on selected M1 markers and the upregulation of selected M2 markers suggesting an additional mechanism for its modulation of the RA inflammatory process.

Project description:Introduction Given its wide availability and cost-effectiveness, multidimensional flow cytometry (mFC) became a core method in the field of immunology allowing for the analysis of a broad range of individual cells providing insights into cell subset composition, cellular behavior, and cell-to-cell interactions. Formerly, the analysis of mFC data solely relied on manual gating strategies. With the advent of novel computational approaches, (semi-)automated gating strategies and analysis tools complemented manual approaches. Methods Using Bayesian network analysis, we developed a mathematical model for the dependencies of different obtained mFC markers. The algorithm creates a Bayesian network that is a HC tree when including raw, ungated mFC data of a randomly selected healthy control cohort (HC). The HC tree is used to classify whether the observed marker distribution (either patients with amyotrophic lateral sclerosis (ALS) or HC) is predicted. The relative number of cells where the probability q is equal to zero is calculated reflecting the similarity in the marker distribution between a randomly chosen mFC file (ALS or HC) and the HC tree. Results Including peripheral blood mFC data from 68 ALS and 35 HC, the algorithm could correctly identify 64/68 ALS cases. Tuning of parameters revealed that the combination of 7 markers, 200 bins, and 20 patients achieved the highest AUC on a significance level of p < 0.0001. The markers CD4 and CD38 showed the highest zero probability. We successfully validated our approach by including a second, independent ALS and HC cohort (55 ALS and 30 HC). In this case, all ALS were correctly identified and side scatter and CD20 yielded the highest zero probability. Finally, both datasets were analyzed by the commercially available algorithm ‘Citrus’, which indicated superior ability of Bayesian network analysis when including raw, ungated mFC data. Discussion Bayesian network analysis might present a novel approach for classifying mFC data, which does not rely on reduction techniques, thus, allowing to retain information on the entire dataset. Future studies will have to assess the performance when discriminating clinically relevant differential diagnoses to evaluate the complementary diagnostic benefit of Bayesian network analysis to the clinical routine workup.

Dataset Information

Immunosuppressive Functions of M2 Macrophages Derived from iPSCs of Patients with ALS and Healthy Controls.

Publications

Immunosuppressive Functions of M2 Macrophages Derived from iPSCs of Patients with ALS and Healthy Controls.

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