[System]
You are a **scientific‐rigor auditor**. You will receive the parsed contents of a research paper. Your job is to identify **only** those errors or flaws that directly undermine the **scientific validity** of the paper’s methods, analyses, or conclusions.

Your sole focus is to identify flaws—such as errors in experimental design, data integrity, calculations, statistical inference, or reproducibility—that directly call into question the validity of a specific claim, paragraph, or the paper as a whole.

**Do not** report issues that are purely presentational, rhetorical, stylistic, or related to citation practices.

---

After you’ve done a **detailed walkthrough** of the paper, output exactly in this format—no extra keys or commentary:

```
<analysis>
{detailed walk‑through of how you checked each section/figure and why you flagged (or did not flag) any flaw}
</analysis>

<response>
{
  "has_error": <true|false>,
  "errors": [
    {
      "location": "Section 2.1",
      "description": "Claim that ‘all X are Y’ is contradicted by citation [5], which shows examples of non‑Y X."
    },
    {
      "location": "Figure 3",
      "description": "XAxis labeled ‘Time (s)’ but units appear to be milliseconds; scale bar mismatches caption."
    }
    // …more entries…
  ]
}
</response>
```

- **Do not** include any other keys or prose outside these two tagged blocks.
- **Do not** report stylistic or citation issues.
- Be as precise as possible about **where** (section ID or figure/table) and **what** the scientific flaw is.
- Each description for the errors must be rooted in a scientific rationale explaining why it is 'wrong' (not how it could be improved).

Begin your analysis now.

[User]
Here, we show that GLP-1R is expressed by T cells, and its signaling prolongs allograft survival and mitigates alloimmunity. Notably, GLP-1R antagonism triggered anti-tumor immunity in a mouse model of colorectal cancer. GLP-1R acts as a T cell-negative costimulatory molecule.

Moufida Ben Nasr, Vera Usuelli, Sergio Dellepiane, ..., Reza Abdi, Franco Folli, Paolo Fiorina

franco.folli@unimi.it (F.F.), paolo.fiorina@childrens.harvard.edu (P.F.)

Glucagon-like peptide-1 receptor (GLP-1R) is a key regulator of glucose metabolism known to be expressed by pancreatic β cells. We herein investigated the role of GLP-1R on T lymphocytes during immune response. Our data showed that a subset of T lymphocytes expresses GLP-1R, which is upregulated during alloimmune response, similarly to PD-1. When mice received islet or cardiac allotransplantation, an expansion of GLP-1R^pos^ T cells occurred in the spleen and was found to infiltrate the graft. Additional single-cell RNA sequencing (scRNA-seq) analysis conducted on GLP-1R^pos^ and GLP-1R^neg^ CD3+ T cells unveiled the existence of molecular and functional dissimilarities between both subpopulations, as the GLP-1R^pos^ are mainly composed of exhausted CD8 T cells. GLP-1R acts as a T cell-negative costimulatory molecule, and GLP-1R signaling prolongs allograft survival, mitigates alloimmune response, and reduces T lymphocyte graft infiltration. Notably, GLP-1R antagonism triggered anti-tumor immunity when tested in a preclinical mouse model of colorectal cancer.

Glucagon-like peptide-1 (GLP-1) regulates glucose metabolism by signaling through its receptor (GLP-1R), which is expressed by pancreatic β cells, gastric mucosa, the hypothalamic appetite center, and skeletal muscle.¹⁻⁸ GLP-1R agonists reduce the incidence and severity of severe diabetes complications, including cardiovascular events and diabetic kidney disease.⁹ Beside these well-known metabolic effects, an increasing body of literature suggests that GLP-1R may have a role in regulating the immune system.¹⁰⁻¹² GLP-1R mRNA expression has been detected in various populations of immune cells, including dendritic cells and T lymphocytes; authors have suggested that its signaling may have immunological properties.¹¹ More recently, GLP-1R expression was confirmed in a subset of gut intra-epithelial T lymphocytes.¹³ These cells control the systemic metabolism by modulating hormone incretion from the enteroendocrine epithelial cells. However, there is no conclusive evidence about a possible immunological role of GLP-1R and its signaling. In patients affected simultaneously by diabetes and psoriasis, evidence of an improvement of dermatological symptoms after treatment with the GLP-1R agonist Exendin-4 was reported.¹⁴ Of note, after some patients discontinued the drug as consequence of mild adverse events, psoriasis symptoms substantially worsened but improved again when Exendin-4 was restarted. In non-obese diabetic (NOD) mice, a strain prone to autoimmune diabetes, Exendin-4 treatment delayed diabetes onset as well as islet allograft rejection in a fully mismatched model of islet allotransplantation.¹⁵ ¹⁶ More recently, the administration of GLP-1R agonist, Liraglutide, was shown to mitigate nephrotoxic serum nephritis in mice by dampening renal infiltration and the proliferation of effector T cells.¹⁷ In this study, we seek to clarify GLP-1R role in T lymphocytes as we hypothesize that it may act as a negative costimulatory molecule. If proven correct, our study may serve for the basis of the clinical use of GLP-1R antagonists as immune checkpoint inhibitors to stimulate anti-tumor immunity, while agonists may facilitate immune regulation.

First, we broadly assessed the expression of GLP-1R on lymphocytes by a variety of techniques. Murine CD4⁺ and CD8⁺ cells obtained from C57BL/6 mice expressed GLP-1R at protein and mRNA level, and in all experiments, murine islets were used as control (Figures 1A–1G). Additionally, to confirm the specificity of the GLP-1R expression by T cells, we conducted a due diligence assessment of Glp-1r expression at the mRNA level on ≈ CD4⁺, CD8⁺ T cells, respectively, as compared with a mouse beta cell line (BTC6 cells), used as a positive control (Figures 1H, 1I, S1A, and S1B). We first designed exon junction-spanning primers to amplify a 334 bp-long target amplicon of the murine Glp-1r gene from cDNAs obtained from CD4⁺, CD8⁺, and BTC6 cells, respectively. The correct amplification of the expected target amplicon size (334 bp) was confirmed/visualized by both melt curve analysis and by agarose gel electrophoresis and subsequent Sanger sequencing, which further confirmed the identity and conformity of Glp-1r mRNA in all tested samples (CD4⁺, CD8⁺ T cells, and BTC6 cells) (Figures 1H and 1I). Then the alignment of the PCR endpoint product sequences with nucleotides 950–1,296 of the Glp-1r reference cDNA (NM_021332.2) further confirmed the expression of Glp-1r in murine CD4⁺ and CD8⁺ T cells (Figure S1C). Nearly 5%–6% of CD4⁺ and CD8⁺ T lymphocytes expressed GLP-1R on their surface, while control islets are 40%–42% positive (Figures 1A–1D). GLP-1R expression on T lymphocytes was also confirmed by immunohistochemistry staining; indeed, GLP-1R expression was also identified in the thymus and as expected, in pancreatic islets (Figures 1J₁–1K₂). We then investigated whether the expression of GLP-1R varied across the different CD4⁺ and CD8⁺ subsets. Although no GLP-1R expression was evident on CD4⁺ or CD8⁺ naive T cells, and it was scanty (less than 5%) on memory cells, nearly 10%–13% of CD4⁺ and CD8⁺ effector T cells and 14% of regulatory T cells appeared to be GLP-1R^pos (Figures 1L–1O, S2A, and S2B). We then challenged CD3⁺ T cells isolated from naive C57BL/6 wild-type (WT) mice with anti-CD3/anti-CD28 mAbs, and GLP-1R expression was determined in a time course manner (Figures 1P and 1Q). A substantial increase in GLP-1R expression, confirmed also by immunofluorescence, was evident (Figures 1P–1S). Notably, upon T cell activation, GLP-1R increased in expression matches PD-1 upregulation (Figures S2C–S2H). Finally, we investigated GLP-1R expression on several components of innate immunity and noticed an expression of GLP-1R by mainly natural killer T (NKT) cells, NK cells, CD11c⁺ cells, and CD11b⁺ cells, always with a similar pattern to what was observed for PD-1 expression (Figures S2I–S2K).

Then in order to probe the existence of a unique GLP-1R interactome specific for T cells, we immunoprecipitated GLP-1R from activated CD3⁺ T cells followed by mass spectrometry. Using fingerprinting, we identified 20 peptides significantly interacting with GLP-1R, and by spectral counting, we assessed the relative quantification of the 20 identified peptides (Figure 2A; Table S1). Within the 20 peptides, we identified 4 (ZN503 [zinc finger protein 503], PURB [transcriptional regulator protein Pur-beta], MBD2 [methyl-CpG-binding domain protein 2], and bromodomain adjacent to zinc-finger domain protein 2A [BAZ2A]) that were reported to be transcriptional repressor and play a role in gene silencing (Table S1). Interestingly, by bioinformatic analysis (www.uniprot.org, www.genevisible.com, www.gee.org, and www.ebi.ac.uk/gxa/home), we compared the T cell GLP-1R-interactome with those obtained from β cells and other tissues confirming some unique interactors (peptides) for T cells (Figure 2B). After a deeper selection, we delineated 2 unique T cell proteins: CCG8_MOUSE (voltage-dependent calcium channel gamma-8 subunit, a known modulator of AMPA receptors containing TARP-γ8¹⁸) and BAZ2A_MOUSE (Figure 2C). Next, we demonstrated that, similarly to PD-1, proliferating cells showed a significant increase in GLP-1R protein expression (Figures 2D, 2E, and S2C–S2H). Interestingly, GLP-1R^neg CD3⁺ T cells revealed an abundant GLP-1R intracellular expression, although to a lower extent than that observed from their counterparts GLP-1R^pos CD3⁺ T cells (Figure 2F). This may appear to be a reservoir for a rapid conversion of GLP-1R^neg CD3⁺ T cells into GLP-1R^pos CD3⁺ T cells (Figures 2G₁ and 2G₂).

(A and B) Representative dot plot of GLP-1R expression by murine splenic CD4+ and CD8+ cells.
(C) Representative dot plots of GLP-1R expression by murine pancreatic β cells.

(TGFB1 [transforming growth factor-beta 1], TNFSF10 [tumor necrosis factor ligand superfamily member 10], and LGALS3 [galectin-3]) (Figure 2U). Additionally, most of the downregulated genes in GLP-1R^POS^ CD4^+^ T cells belong to mitotic cell-cycle G1/S phase transition, cellular activation, and cytokine production (Figure 2V). The transcriptomic analysis on in GLP-1R^POS^ CD8^+^ T cells revealed the upregulation of genes associated with T cell/Th1 pathway activation, while those downregulated genes were associated with response to oxidative stress and to protein phosphorylation (Figures 2W and 2X). Altogether, our findings suggested that GLP-1R signaling may confer an anergic and exhausted state in activated T lymphocytes and unveil a potential interactor network involved in GLP-1R signaling into T cells.

The molecular profiling by single-cell RNA sequencing (scRNA-seq) identified 13 clusters in GLP-1R^POS^ and 7 clusters in GLP-1R^NEG^ (Figures 3A and 3B). Annotation with SingleR provided major insights into cell types composing each cluster (Figures S3A and S3B), while manually curated annotation, based on the expression of top marker genes for each cluster revealed the presence of distinct T cell subpopulations, all confirmed by an integrated analysis performed with Seurat standard pipeline (Figures 3C–3G). Our data analysis suggested the presence of a heterogeneous T cell subpopulation within GLP-1R^POS^ CD3^+^ T cells, with the main dominating subset composed of CD8 exhausted T cells, as depicted in the uniform manifold approximation and projection (UMAP) and heatmap (Figures 3D and S3C–S3J). By contrast, the analysis of the GLP-1R^NEG^ CD3^+^ T cell subpopulation highlighted the presence of a dominating subset composed of CD8 effector memory T cells, with higher expression of the NK cell gene (Figures S3K–S3P). Additionally, the 11 clusters identified in the integrated dataset were further inspected with manually cured annotation, revealing T cell subpopulations such as CD4, CD8 naive, memory cells, CD4 regulatory T cells, and exhausted T cells (Figures 3F and

Abbreviations: GLP-1R, glucagon-like peptide 1 receptor; BTC6, beta TC-6 cell line; qRT-PCR, two-step quantitative reverse transcriptase PCR; −RT, minus reverse transcriptase; H&E, hematoxylin and eosin; FACS, fluorescence-activated cell sorter scan; Abs, antibodies; EM, effector memory; and CM, central memory.

(A) Proteomic analysis showing the 20 peptides discovered to immunoprecipitate with GLP-1R on activated CD3+ T cells.
(B) Schematic Venn diagram depicting the GLP-1R interactome on T cells, versus those known on other tissues.

3G). Overall, our scRNA-seq analysis showed the existence of molecular and functional dissimilarities and heterogeneity between GLP-1R-expressing cells and their negative counterparts, with the former being mainly composed of CD8-exhausted T cells.

In order to understand the molecular basis of GLP-1R signaling, we performed a phosphoproteomic arrays, with over 1,500 of known proteins tested for expression and activation during a T cell in vitro challenge with GLP-1R agonist. GLP-1R signaling in T cells altered several signaling molecules involved in senescence and exhaustion and in T cell receptor (TCR) signaling (Figures 4A and 4B). GLP-1R signaling with Exe-4 significantly reduced the number of IFN-γ producing cells by mitogen-stimulated murine splenocytes (Figure S4A), while the addition of Exe-9 significantly hampered the overseen effects. Exe-4 significantly increased cell death of CD4+ and CD8+ T cells, while the addition of Exe-9 reduced the effect (Figures S4B1–S4C2). To extend the importance of the data implicating CCG8 and BAZ2A into GLP-1R signaling on T cells, we tested the effect of their inhibition. Our data indicate that the addition of the BAZ2A inhibitor BAZ2-ICR, but not of CCG8-inhibitor JNJ 55511118, prevented the immunoregulatory effect of Exe-4 on activated CD3+ T cells and reinstated their IFN-γ production (Figure 4C). Exe-4 treatment slightly modulated the proliferation rate of GLP-1Rpos but not of GLP-1Rneg CD3+ T cells (Figure 4D). GLP-1Rpos CD3+ T cells appeared significantly more apoptotic as compared with their counterparts GLP-1Rneg CD3+ T cells, independently of Exe-4 treatment (Figure 4E). Although Exe-4 treatment reduced the migratory potential of GLP-1Rneg CD3+ T cells only, no evident effect was observed on IFN-γ expression, with the GLP-1Rpos CD3+ T cells migrating less and retaining lower IFN-γ expression (Figures 4F and 4G). Notably, the challenge of resting and activated GLP-1Rpos and GLP-1Rneg CD3+ T cells with multiple doses of Exe-4 showed reduced maximal respiration particularly of the former (Figures 4H and 4I). We further assessed the concentration of total GLP-1 in different assays, and we never detected the presence of GLP-1 (Figures S4D). We then wondered whether signaling through GPL-1R may influence Treg induction, function, and stability and upon co-culture with Exe-4. Our data indicate no substantial differences upon addition of Exe-4 to naive CD4+CD25- T cells during Treg induction assay (Figures S4E1 and S4E2). Additionally, we observed some effect on iTreg stability upon addition of Exe-4 with a significant reduction of Ror-γT and Tbet (Figures S4F1–S4G2). Finally, when iTregs were generated in the presence of Exe-4 at a ratio of 1:4 to effector T cells, a significantly reduced suppression was observed as compared with when untreated iTregs were added at the same ratio (Figures S4H1–S4H4).

Next, we sought to determine the effect of GLP-1R genetic gain of function; indeed, GLP-1R cDNA was transduced by using a pRetroG-CMV-GLP-1R retroviral vector into CD3+ T cells (GLP-1Rtg CD3+ T cells), and upregulation of GLP-1R expression was confirmed by FACS (Figure S4I1) and by western blot analysis (Figure S4I2). Exe-4 treatment has no effect on the proliferation of both untransduced-mock and pmY-GLP-1R transduced CD3+ T cells (Figure 4J), while a significantly increased apoptosis was observed in pmY-GLP-1R transduced CD3+ T cells only (Figure 4K). Moreover, Exe-4 treatment reduced the migratory ability in response to SDF-1 in both untransduced-mock and pmY-GLP-1R transduced CD3+ T cells (Figure 4L) without any effect on IFN-γ expression in both groups (Figure 4M). In pmY-GLP-1R transduced CD3+ T cells, a reduced maximal respiration was observed as compared with untransduced-mock CD3+ T cells (Figures 4N and 4O).

(C) Strategy used to dissect the T cell-relevant interactome.
(D and E) GLP-1R expression by FACS analysis and related quantification of activated and dividing CD3+ T cells as compared with non-dividing CD3+ T cells.
(F and G1) GLP-1Rneg CD3+ appeared to have a significant intracellular GLP-1R expression by FACS analysis (F) and by electron microscopy in (G1) where GLP-1R is present in cellular cytoplasm, predominantly in vesicles (arrows), but is absent in cell membrane (magnification: X50000 by electron microscopy).
(G2) GLP1R is present both in cytoplasmic vesicles (arrows) and in cell membrane (stars) of GLP-1Rpos CD3+ (magnification: X50000).
(H and I) Representative FACS plots of proliferating GLP-1Rpos and GLP-1Rneg CD3+ T cells with related quantification.
(J) GLP-1Rpos CD3+ T cells appeared significantly more apoptotic as compared with their negative counterparts.
(K) The percentage of GLP-1Rpos CD3+ T cells migrating to SDF-1 gradient was significantly higher as compared with their negative counterparts.
(L) Bar graph depicting the quantification of the percentage of IFN-γ on activated GLP-1Rpos CD3+ T cells and on their negative counterparts.
(M and N) Higher OCR, maximal respiration, and spare capacity after mitochondrial membrane uncoupler BAM15 addition were observed in GLP-1Rneg CD3+ T cells as compared with GLP-1Rpos CD3+ T cells.
(O and P) Extracellular acidification rate (ECAR) and proton efflux rate (PER) measurements normalized to cell number, performed on GLP-1Rpos and GLP-1Rneg CD3+ T cells are shown. All respiratory parameters shown in (M)–(P) are obtained from 3 independent experiments, and data are presented as mean ± standard error of the mean (SEM). A two-way ANOVA test was used to determine statistical significance.
(Q and R) GLP-1R expression by FACS analysis and related quantification was depicted on activated and dividing CD4+ and CD8+ T cells as compared with non-dividing CD4+ and CD8+ T cells.
(S) GLP-1Rpos CD4+ and CD8+ T cells were more apoptotic as compared with their negative counterparts.
(T) Bar graph showing the quantification of the percentage of IFN-γ on GLP-1Rpos CD4+ and CD8+ and on their negative counterparts.
(U–X) Volcano plots and their related pathway analysis showing differently expressed genes in GLP-1Rpos CD4+ cells versus GLP-1Rneg CD4+ T cells and in GLP-1Rpos CD8+ cells versus GLP-1Rneg CD8+ T cells. In (V) and (X), the main biological function/pathway analysis of the dataset related to upregulated and downregulated genes on (U) GLP-1Rpos CD4+ and on (W) GLP-1Rpos CD8+ T cells are shown. Data are representative of at least n = 2 independent experiments. Data are expressed as mean ± standard error of the mean (SEM). Data are representative of at least n = 3 mice. *p < 0.05; **p < 0.01; ***p < 0.001.
See also Figure S2 and Table S1.
Abbreviations: GLP-1R, glucagon-like peptide 1 receptor; OCR, oxygen consumption rate; SRC, spare respiratory capacity; CT, cell trace; FACS, fluorescence-activated cell sorter; IFN-γ, interferon gamma; ECAR, extracellular acidification rate; PER, proton efflux rate.

Cell Metabolism 36, 1302–1319, June 4, 2024 1307

# Cell Metabolism Article

## Figure 3. scRNA-seq of GLP-1Rpos T cells

|                   |                   |                 |
| ----------------- | ----------------- | --------------- |
| A GLP-1RposCD3+   | B GLP-1RnegCD3+   | C Integration   |
| D GLP-1RposCD3+   | E GLP-1RnegCD3+   | F Integration   |
| G                 |                   |                 |

(A and B) Uniform manifold approximation and projection (UMAP) for, respectively, sorted GLP-1Rpos and GLP-1Rneg CD3+ T cells showing 13 cell clusters in the former (A) and 7 main clusters in the latter (B) by using 30 nPCs and 0.5 resolution and 0.2 resolution, respectively.

(C) UMAP showing the clustering of the integrated dataset.

(D–F) Annotation of different T cell subtypes composing each cluster related to, respectively, GLP-1Rpos and GLP-1Rneg CD3+ T cells, and the integrated dataset is shown.

(G) Heatmap showing the top marker genes for each cluster within the integrated dataset.

See also Figure S3.

Abbreviations: scRNA-seq, single-cell RNA sequencing; GLP-1R, glucagon-like peptide 1 receptor; and UMAP, uniform manifold approximation and projection.

## GLP-1R genetic loss of function

To extend our findings into an in vivo setting, we used GLP-1R knockout (KO) mice (Figure S4J), and the absence of GLP-1R was confirmed within several immune organs (Figures S4K1–S4O2 and S4P1–S4P3). A reduced CD3+ T cell apoptotic rate with an increased percentage of IFN-γ+CD3+ T cells was seen

1308 Cell Metabolism 36, 1302–1319, June 4, 2024

# Cell Metabolism
## Article

This page contains multiple graphs and charts presenting data from various experiments related to cell metabolism. I'll describe the key components in markdown format:

### A-B: Phospho Explorer Array on CD3+-Exe 4

Two scatter plots showing gene expression changes. Plot A shows Log2(Fold change) vs -Log10(p-value), while Plot B shows a heatmap-style representation with a legend indicating various cellular processes and signaling pathways.

### C-G: Bar Charts

These charts show various measurements under different conditions:

| Chart | Measurement                    | Conditions                                    |
| ----- | ------------------------------ | --------------------------------------------- |
| C     | IFNγ+ CD3+ T cells (%)         | Anti-CD3/28, Exe-4, BazZA-IC, JNJ 55511118    |
| D     | Proliferating CD3+ T cells (%) | GLP-1R⁺/⁺ and GLP-1R⁻/⁻                       |
| E     | G1-S/G2-M (%)                  | Annexin V⁺/7AAD⁻ cells (%)                    |
| F     | Hypoxic CD3+ T cells (%)       | GLP-1R⁺/⁺ and GLP-1R⁻/⁻, Medium, SDF-1, Exe-4 |
| G     | Fhv+ CD3+ T cells (%)          | GLP-1R⁺/⁺ and GLP-1R⁻/⁻, Medium, Exe-4        |

### H-K: Additional Bar Charts

These charts show various metabolic measurements under different conditions:

| Chart | Measurement                              | Conditions                                                    |
| ----- | ---------------------------------------- | ------------------------------------------------------------- |
| H-I   | Maximal respiration (pmol/min/10⁶ cells) | GLP-1R⁺/⁺ and GLP-1R⁻/⁻, Unt, Exe-4 at various concentrations |
| J     | Proliferating CD3+ T cells (%)           | mock, Pmy-GLP-1R                                              |
| K     | Annexin V⁺/7AAD⁻ cells (%)               | mock, Pmy-GLP-1R                                              |

### L-O: More Bar Charts and Line Graph

| Chart | Measurement              | Conditions                                                                        |
| ----- | ------------------------ | --------------------------------------------------------------------------------- |
| L     | Hypoxic CD3+ T cells (%) | mock, pmy-GLP-1R, Medium, SDF-1, Exe-4                                            |
| M     | Fhv+ CD3+ T cells (%)    | mock, pmy-GLP-1R, Medium, Exe-4                                                   |
| N     | OCR (pmol/min/10⁶ cells) | Line graph showing Oligomycin, BAM15, and Rotenone A treatments                   |
| O     | OCR (pmol/min/10⁶ cells) | Bar chart comparing Unt-mock and Unt-pmyGLP-1R for various respiratory parameters |

### P-Z: Survival Curve, Microscopy Images, and Additional Bar Charts

P: Survival curve comparing BALB/c into KO-BB + sCTLA-4-Ig and BALB/c into B6 + sCTLA-4-Ig

Q-R: Microscopy images comparing KO and WT conditions

S-Z: Bar charts comparing various cellular parameters between KO and WT conditions:

| Chart | Measurement                   |
| ----- | ----------------------------- |
| S     | Cell count (A.U.)             |
| V     | Apoptotic cells (%)           |
| W     | CD8⁺ T cells (%)              |
| X     | IFNγ⁺CD8⁺ T cells (%)         |
| Y     | IL-17⁺CD4⁺ T cells (%)        |
| Z     | Foxp3⁺ CD4⁺/CD25⁺ T cells (%) |

(legend on next page)

Cell Metabolism 36, 1302–1319, June 4, 2024 1309

when GLP-1R is genetically knocked down (Figures S4Q–S4S and S4T1). Moreover, the percentage of CD3+ T cells from GLP-1R KO mice migrating to SDF-1 gradient was significantly lower as compared with their counterparts from WT mice (Figure S4T2). We then tested the effect of lacking a viable GLP-1R signaling in an in vivo murine model of allograft tolerance in the tolerogenic low-dose CTLA4-Ig model. Although WT recipients showed an extended survival of the allograft (MST = 58 days), an acceleration of heart allograft rejection was observed in the GLP-1R KO mice (MST = 28 days) (Figure 4P). Pathology of allograft showed a severe and accentuated infiltration of CD3+ and CD8+ T cells (Figures 4Q–4S, S4U1–S4V2, and S4W), with an increase in the degree of fibrosis in the GLP-1R KO group (Figures 4T–4V). A substantial increase in CD4 effector T cells as well as significant increases in the percentages of IFN-γ+ CD4+ T cells and IL-17+ CD4+ T cells (Figures 4W–4Y) and slightly in CD8 effector T cells (Figure S4X) were evident in the GLP-1R KO mice. Importantly, significant increase in the percentage of IL-17+ CD8+ T cells, but not of IFN-γ+CD8+ T cells, was observed in GLP-1R KO recipients as compared with WT recipients (Figures S4Y and S4Z), with a marked decrease in CD4+ Tregs in the GLP-1R KO group (Figure 4Z). Our results indicate that GLP-1R signaling may modulate the alloimmune response.

GLP-1R and islet allograft
In an in vivo murine models of islet allotransplantation, GLP-1R expression was confirmed on splenic CD4+ and CD8+ T cells at baseline without infiltration (Figures 5A–5D and S5A–S5D). At day 14, all mice displayed acute allograft rejection associated with an increase in GLP-1Rpos cells among both splenic and islet allograft infiltrating CD4+ and CD8+ T cells (Figures 5A–5D and S5A–S5D). The presence of graft-infiltrating GLP-1RposT lymphocytes at day 14 was further confirmed by confocal microscopy and immunohistochemistry analysis (Figures 5D1–5F). Interestingly, the administration of low dose of the GLP-1R agonist (Exe-4) resulted in a prolongation of islet survival up to 100 days in 20% of the recipients ([MST] = 41 days), while 60% of those that received high doses of Exe-4 preceded by a pre-treatment showed a prolongation of islet survival up to 100 days ([MST] = 67 days) (Figure 5G). The co-administration of Exe-4 and rapamycin was associated with 100% of graft survival at the end of follow-up (day 100) (Figure 5G). The beneficial effects of Exe-4 were partly abolished by the co-administration of its antagonist Exe-9 (Figure S5E). A decreased graft infiltration was evident in Exe-4-treated mice, while the co-administration of Exe-9 restored the graft infiltration (Figures S5F1–S5J). Notably, SDF-1 immunostaining revealed a mild SDF-1 expression within islet allograft infiltrate, matching CXCR4 expression by GLP-1Rpos cells (Figures S5K1–S5L2). Taken together, our results confirmed that GLP-1R is upregulated on T cells during islet allograft rejection and GLP-1R signaling has immunoregulatory effect.

GLP-1R and heart allograft
Because of the wide range of effects that GLP-1R has on islets, which may confound the immunological effect, we next sought to confirm the islet-independent immunoregulation of GLP-1R signaling by using a major histocompatibility complex (MHC)-fully mismatched model of heart transplantation. At day 7, all

Figure 4. GLP-1R modulates T cell activation

(A and B) Differential profiling analysis of phosphoproteomic array performed on murine CD3+ T cells challenged with Exe-4 (1 nM) as compared with their counterparts untreated; volcano plot depicting main differences in phosphoproteomics between the 2 groups of cells (A); the bubble chart of the reactome analysis of the main 60 phosphoproteomics dysregulated during Exe-4 treatment (B). Data represent n = 3 samples per conditions.

(C) BAZ2A inhibitor BAZ2-ICR, but not of CCG8-inhibitor JNJ 55511118, prevented the immunoregulatory effect of Exe-4 on activated CD3+ T cells and reinstated their IFN-γ production.

(D) Exe-4-treatment slightly modulated the proliferation rate of GLP-1RposT cells.

(E) GLP-1Rpos CD3+ T cells appeared significantly more apoptotic as compared with their negative counterparts.

(F) Exe-4-treatment reduced the migratory potential of GLP-1Rneg CD3+ T cells only.

(G) GLP-1Rpos CD3+ T cells retained lower IFN-γ expression as compared with their negative counterparts.

(H and I) Exe-4 treatment reduced the maximal respiration of resting and activated GLP-1RposCD3+ T cells.

(J) Exe-4 treatment has no effect on the proliferation of both untransduced-mock and pmY-GLP-1R transduced CD3+ T cells.

(K) Exe-4 treatment increased significantly apoptosis in pmY-GLP-1R transduced CD3+ T cells only.

(L) Exe-4 treatment reduced the migratory ability in response to SDF-1 in both untransduced-mock and pmY-GLP-1R transduced CD3+ T cells.

(M) No effect on IFN-γ expression was observed in both untransduced-mock and pmY-GLP-1R transduced CD3+ T cells in response to Exe-4 treatment.

(N and O) In pmY-GLP-1R transduced CD3+ T cells, a reduced maximal respiration was observed as compared with untransduced-mock CD3+ T cells. Data are representative of at least n = 3/group and are expressed as mean ± standard error of the mean (SEM). Statistical significance was assessed by two-way ANOVA. *p < 0.05; **p < 0.01; ***p < 0.001.

(P) Heart allograft survival curves from GLP-1R-/- mice or from WT recipients' mice of heart allograft from fully mismatched BALB/c mice and treated with low-dose CTLA4-Ig.

(Q–S) Micrographs of CD3 staining in heart allograft sections from either WT or GLP-1R KO recipients; in (S) bar graph shows the relative quantification of heart infiltrating CD3+ cells in both groups.

(T–V) Representative Masson-trichrome histology staining of heart allografts, respectively, from GLP-1R KO or from WT recipients' mice; the average area of fibrosis in heart allografts from both groups of recipients' mice is shown in (V).

(W) Bar graph depicting the quantification of CD4+ effector-memory splenocytes in GLP-1R KO or WT recipients' mice.

(X) Bar graph depicting the quantification of IFN-γ+CD4+ T cells in GLP-1R KO or WT recipients' mice.

(Y) Bar graph depicting the quantification of IL-17+CD4+ T cells in GLP-1R KO or WT recipients' mice.

(Z) Bar graph depicting the quantification of CD4+ regulatory splenocytes in both groups of mice that underwent heart allograft transplantation. Data are representative of at least n = 3 mice and are expressed as mean ± standard error of the mean (SEM). *p < 0.05; **p < 0.01; ***p < 0.001.

See also Figure S4.

Abbreviations: GLP-1R, glucagon-like peptide 1 receptor; Exe-4, exendin-4; Exe-9, exendin-9-39; FACS, fluorescence-activated cell sorter scan; BAZ2A, bromodomain adjacent to zinc-finger domain 2A; CCG8, voltage-dependent calcium channel gamma-8 subunit; WT, wild type; IFN-γ, interferon gamma; CTLA4, cytotoxic T lymphocyte antigen 4; BAM15 (N5,N6-bis(2-Fluorophenyl)[1,2,5]oxadiazolo[3,4-b]pyrazine-5,6-diamine); and FoxP3, forkhead box P3.

(legend continued on next page)

mice displayed acute allograft rejection associated with an increase in GLP-1R^pos cells among both splenic (Figures 5H, 5I, S5M, and S5N) and heart allograft infiltrating CD4^+ and CD8^+ T cells (Figures 5J, 5K, S5O, and S5P). The presence of graft-infiltrating GLP-1R^pos T lymphocytes at day 7 was confirmed by immunohistochemistry analysis, while cardiomyocytes and other parenchymal cells appeared negative for GLP-1R staining (Figures 5L1–5M). Moreover, while untreated recipients rejected cardiac allograft within a range of 7 days ([MST] = 7 days) (Figure 5N), Exe-4-treated recipients receiving either a low or a high dose of Exe-4 proceeded or not with pre-treatment showed a significant delay in allograft rejection (respectively [MST] = 9 and 10 days) (Figure 5N). Notably, transplanted mice receiving a combination therapy with Exe-4 and rapamycin showed indefinite long-term cardiac transplant survival in almost 20% of recipients ([MST] = 39 days) (Figure 5N). The beneficial effects of Exe-4 were partly abolished by the co-administration of Exe-9 (Figure S5Q). A decrease of graft infiltration was shown in Exe-4-treated mice and abolished by Exe-9 co-administration (Figures S5R1–S5V). We also confirmed that total/active GLP-1 and Exe-4 peripheral levels were not affected by allotransplantation, while GLP-1, but not Exe-4 levels, increased in Exe-4-treated mice (Figures S5W–S5Y). In a tentative to test the effect of GLP-1R on a more selective way, we performed a series of adoptive transfer studies of WT and GLP-1R KO T cells in a model of heterotopic intra-abdominal heart transplantation, where recipients C57BL/6 Rag1^−/− mice received a heart transplant from BALB/c. On the day of transplant, all recipients received an adoptive transfer of either splenic WT CD3^+ T cells or of splenic GLP-1R KO CD3^+ T cells in the latter accelerating allograft rejection in the Rag1^−/− group (Figure S5Z1). Furthermore, genetic loss of function of GLP-1R did not affect alloantibody formation neither the levels of circulating follicular helper T cells (cTfh) in both groups (Figures S5Z2 and S5Z3). Heart transplantation data confirmed what is obtained in the islet model and further suggested the relevance of GLP-1R signaling for T cell compartment.

GLP-1R antagonism triggers antitumor immunity
To investigate the hypothesis that GLP-1R may play a role as an immune checkpoint, we studied the tumor response to a systemic administration of a GLP-1R antagonist, Exendin-9-39 (Exe-9), in an experimental murine model of colorectal cancer. In this model, we injected MC38 colorectal cancer cells into the distal posterior rectum as described previously,19 a group of mice (n = 8) were assigned to receive 2 μg of Exe-9 once a day for 14 days; another group of mice (n = 6) were left untreated (Figures 6A and 6B). Indeed, mice treated with Exe-9 showed a significantly reduced tumor size (Figure 6C) and mesenteric lymph nodes volume (Figure 6D), while no differences were observed comparing spleen weight and colon length in both groups (Figures 6E and 6F). Pathological examination of the tumors in both groups revealed a significant intratumoral infiltration of CD3^+ T cells within Exe-9-treated group (Figures 6G–6I). Additional mechanistic studies on the tumors from both groups further confirmed the increased infiltration of CD3^+ T cells in the Exe-9-treated group (Figure 6J) and of particularly activated effector memory CD8^+ T cells (Figures 6K–6M). However, no major differences were observed comparing CD3^+ and CD8^+ effector memory T cells within the spleen and mesenteric lymph nodes of both groups (Figures 6N–6Q). Altogether, our data showed an evident proof of concept that GLP-1R antagonist may trigger T cell-mediated anti-tumor activity.

GLP-1R in human T cells
Our data confirmed the expression of GLP-1R on human CD4^+ and CD8^+ T cells (Figures 7A–7D). Human peripheral blood mononuclear cells (PBMCs) extracted from healthy individuals revealed at FACS analysis an average GLP-1R expression on CD4^+ and CD8^+ T cells of about 6.1% ± 1.2% and 28.3% ± 4.1%, respectively (Figures 7A–7D), while human islets express GLP-1R at an average of 46.3% ± 0.2% (Figures 7C and 7D). GLP-1R expression on T cells was further confirmed at protein level and at mRNA transcript (Figures 7E–7G). Consistently with murine data, GLP-1R expression was found by immunohistochemistry in human thymus and pancreas (Figures 7H1–7I2). In situ hybridization confirmed the expression of GLP-1R mRNA in human thymus and spleen (Figures S6A and S6B). Notably, GLP-1R expression was evident in human regulatory CD4^+ T cells (Figures S6C and S6D), in effector memory CD4^+ and CD8^+ T cells (Figures 7J–7M), although central memory CD4 and CD8 T cells appeared to express GLP-1R at a lower extent (Figures 7J–7M). Importantly, CD4^+/CD8^+ terminally differentiated effector memory T cells appeared highly positive for GLP-1R (Figures 7J–7M). Paralleling our findings in murine studies, we sought to determine whether GLP-1R plays a role during

(F) Bar graph displaying the quantification of CD3^+ and GLP-1R^pos cells in islet allograft.
(G) Islet allograft survival curves from mice treated with different doses of exenatide (dashed line) or saline (continuous line).
(H) Representative zebra plot of GLP-1R expression by splenic murine CD4^+ T lymphocytes obtained from mice in basal condition or after heart allotransplantation.
(I) Bar graph representing quantification of (H).
(J) Representative zebra plot of GLP-1R expression by heart allograft infiltrating CD4^+ T lymphocytes obtained from mice in basal condition or after heart allotransplantation.
(K) Bar graph representing the quantification of (J).
(L) (L1) Hematoxylin and eosin histology staining depicts the immune infiltrate within the heart allograft at day 7.
(L2) Heart allograft immunohistochemistry for CD3^+ cells (arrows).
(L3) Heart allograft immunohistochemistry for GLP-1R^pos cells (arrows).
(M) Bar graph displaying the quantification of CD3^+ and GLP-1R^pos cells in heart allograft.
(N) Heart allograft survival curves from mice treated with different doses of exenatide (dashed line) or saline (continuous line). Data are representative of at least n = 3 mice and are expressed as mean ± standard error of the mean (SEM). *p < 0.05; **p < 0.01; ***p < 0.001.
See also Figure S5.
Abbreviations: GLP-1R, glucagon-like peptide 1 receptor; FACS, fluorescence-activated cell sorter scan; H&E, hematoxylin and eosin.

(G–I) Representative immunohistochemical images showing intratumoral CD3 staining from vehicle-treated or Exe-9–treated mice and their related quantification are shown in (I).

(J–M) Quantitative bar graph depicting FACS quantification of tumor-infiltrating CD3+ T cells, CD8+ effector memory T cells, and activated CD8+ T cells within total CD3+ T cells (J) or within CD8+ effector memory T cells (M), extracted from vehicle-treated or Exe-9–treated mice.

(N–Q) Quantitative bar graph depicting FACS quantification of total splenic CD3+ T cells and CD8+ effector memory T cells or CD3+ T cells and total CD8+ effector memory T cells extracted from MLNs of vehicle-treated or Exe-9–treated mice. Data are representative of, respectively, n = 6 and n = 8 samples from vehicle-treated and Exe-9–treated mice and are expressed as mean ± standard error of the mean (SEM). *p < 0.05; **p < 0.01; ***p < 0.001.

(C–F) Quantitative bar graph depicting tumor volume, mesenteric lymph nodes (MLN) weight, spleen weight, and colon weight of vehicle-treated or Exe-9–treated mice.

(A and B) Representative dot plot of GLP-1R expression by human circulating CD4+ and CD8+ cells.
(C) Representative dot plots of GLP-1R expression by human pancreatic islets (positive control).

relevance and the presence of GLP-1R in a series of graft-rejecting biopsies obtained from individuals recipients of kidney, heart, or lung allografts (Figure S7; Tables S2 and S3). We first evaluated the expression of GLP-1R in human renal biopsies obtained from patients experiencing allograft rejection. Significant GLP-1R^POS^ CD3^+^ T cell intragraft infiltration was observed, while no evidence of GLP-1R^POS^ CD3^+^ T cells was found neither in control biopsies nor in cases of antibody-mediated kidney rejection (Figures S7A_1_–B_3_ and S7I–S7L_3_). We then confirmed the relevance of GLP-1R^POS^ CD3^+^ T cells in heart and lung allograft rejection. Particularly, GLP-1R^POS^ CD3^+^ T cells were observed in biopsies obtained from cardiac-transplanted patients, with and without features of cardiac allograft rejection and vasculopathy (Figures S7C_1_–S7D_3_). Additionally, we reported the presence of intragraft GLP-1R^POS^ CD3^+^ T cells in lung biopsies obtained from cases with chronic lung allograft rejection (Figures S7E_1_–S7F_3_). Taken together, our clinical finding further reinforced and confirmed the relevance of GLP-1R in clinical allograft rejection.

DISCUSSION

Our study demonstrated that GLP-1R receptor is expressed by a variety of T cell subsets, and it has a role in controlling T cell activation, IFN-γ production, cell metabolism, and death, thus acting as a negative costimulatory molecule. Recent evidence suggested that GLP-1R may have a role in immune response^20^; indeed the use of several GLP-1R agonists (exenatide and liraglutide) offered substantial benefits in a wide range of inflammatory diseases.^14,16,21,22^ We detected a discrete population of GLP-1R^POS^ cells, mainly located within CD4^+^ and CD8^+^ effector memory T cells, which increased substantially after alloimmune response. Interestingly, we also show that the use of GLP-1R agonist modulate the T cell alloimmune response and preserve allograft survival. The presence of GLP-1R on T cells is associated with a shift toward an anergic profile, as confirmed by the substantial expression of exhaustion and anergy-related genes, which may support the hypothesis that GLP-1R plays a role of negative costimulatory molecule during immune response. GLP-1R modulation is a successful therapeutic strategy for patients affected by type 2 diabetes.^23–25^ Either the direct receptor agonists or the inhibitors of GLP-1 inactivating enzyme (DPP4) are effective, safe, and associated with a variety of beneficial effects not always connected to glycemic control.^26–29^ In parallel, the wide distribution of GLP-1R outside of the endocrine and digestive tissues has been associated in clinical trials with a variety of intriguing findings, again not associated with glycemic control. Exenatide therapy was able to improve Parkinson disease symptoms,^30^ was able to resolve non-alcoholic steatohepatitis (NASH) in a higher percentage of patients as compared with placebo,^31^ and was able to reduce myocardial infarct size after revascularization,^32^ and in diabetic patients, it may have prevented chronic kidney disease independently from the glycemic control.^33^ The first clinical proof of the role of GLP-1R in the immune system was a serendipity finding: a small series of patients, affected by both psoriasis and diabetes, experienced a substantial improvement of dermatitis with Exenatide therapy.^14,34^ Subsequently, symptoms worsened when Exenatide was discontinued, due to nausea, and improved again when it was restarted. After this report, different authors investigated the anti-inflammatory properties of GLP-1R: several studies focused on macrophages^35^ and some on T lymphocytes.^11,13,16,36–38^ The importance of GLP-1R in limiting gut intraepithelial-lymphocyte-related inflammation has been reportedly described by suppressing their effector function and dampening TCR proximal signaling in a PKA-dependent manner.^39^ In vivo, Exenatide was able to delay diabetes onset and to prolong islet transplantation in NOD mice.^15,16^ Our data showed that GLP-1R expression is limited to CD4 and CD8 effector-memory and regulatory T cells and is not detectable in central-memory and naive subsets. Furthermore, our study showed that a population of terminally differentiated effector memory CD4^+^ and CD8^+^ T cells (i.e., EMRA T cells) expresses GLP-1R at the highest levels; indeed, terminally differentiated effector memory T cells are described in the literature as having high tendency to apoptosis and cytotoxic activity, and their active role in allotransplant rejection has been established.^40,41^ On the contrary, most of the quiescent T cells do not express GLP-1R. Interestingly, the existence of a large GLP-1R reservoir within T cells, which can be mobilized at time during T cell activation and during in vitro assays, may render some of the assays themselves less reproducible. Although, several cellular compartments of innate immunity

(D) Bar graph depicts results of flow cytometric analysis of GLP-1R expression by CD4+/CD8+ T lymphocytes and pancreatic islets.
(E and F) Western blot analysis and associated quantification confirm GLP-1R expression on CD4+/CD8+ T lymphocytes and pancreatic islets.
(G) Bar graph representing normalized mRNA expression of GLP-1R in CD4+/CD8+ T lymphocytes and pancreatic islets.
(H and I) (H_1_–I_2_) Representative images of hematoxylin and eosin histology staining and immunoreactive GLP-1R^POS^ cells in human thymus and pancreas, respectively.
(J) Representative dot plots for gating strategy and GLP-1R expression by CD4^+^CD45RA^+^CD27^+^CCR7^+^ naive T cells, CD4^+^CD45RA^-^CD27^+^CCR7^+^ central memory T cells, CD4^+^CD45RA^-^CD27^-^CCR7^-^ effector memory T cells, and CD4^+^CD45RA^+^CD27^-^CCR7^-^ terminally differentiated effector memory T cells.
(K) Quantification of flow cytometric analysis from (J).
(L) Representative dot plots for gating strategy and GLP-1R expression by CD8^+^CD45RA^+^CD27^+^CCR7^+^ naive T cells, CD8^+^CD45RA^+^CD27^+^CCR7^+^ central memory T cells, CD8^+^CD45RA^+^CCR7^-^ effector memory T cells, and CD8^+^CD45RA^+^CD27^-^CCR7^-^ terminally differentiated effector memory T cells.
(M) Quantification of flow cytometric analysis from (L).
(N and O) Representative dot plots for FACS analysis of activated cell trace violet-labeled CD3^+^ T cells after, respectively, 24, 72, and 120 h (N) and their corresponding bar graphs (O).
(P) Immunofluorescence staining depicting GLP-1R expression on CD3^+^ T cells at baseline.
(Q) Immunofluorescence staining depicting GLP-1R expression on activated CD3^+^ T cells. Data are representative of at least n = 3 samples and are expressed as mean ± standard error of the mean (SEM). *p < 0.05; **p < 0.01; ***p < 0.001.
See also Figures S6 and S7 and Tables S2 and S3.
Abbreviations: GLP-1R, glucagon-like peptide 1 receptor; Abs, antibodies; FACS, fluorescence-activated cell sorter scan; EM, effector memory; CM, central memory; EMRA, terminally differentiated effector memory expressing CD45RA.

express GLP-1R at a moderate level.42–44 GLP-1R^pos CD4 and CD8 cells infiltrate the graft at high percentage and are expanded in the spleen of transplanted mice, while the treatment with GLP-1R agonist was able to prevent heart and islet graft infiltration and to prolong graft survival. Pharmacological and genetic modulation of GLP-1R all confirm that the signaling through the receptor is immunoregulatory, while the absence of GLP-1R accelerate the rejection in chronic heart transplant model of CTLA4-Ig-induced tolerance. Interestingly, GLP-1R expression and function mimick those shown by PD-1; indeed, GLP-1R antagonism applied into a relevant murine cancer model in vivo was able to trigger an anti-tumor immune response. Gain-of-function experiments confirmed the aforementioned GLP-1R-mediated effects; indeed, GLP-1R showed a unique interactome in T cells involving many rRNA gene repressors including Baz2a, which appeared mandatory for the delivery of the negative costimulatory effect. A scRNA-seq study clarified the deep difference and specificity of GLP-1R^pos T cells as compared with their negative counterparts. In conclusion, in this paper, we demonstrated that the expression of GLP-1R delineates a subset of activated T lymphocytes. GLP-1R^pos T lymphocytes are expanded during the alloimmune response, and GLP-1R signaling strives a T cell-negative costimulatory signal mimicking those shown by PD-145–49 but through an rRNA gene repressor interactome, which recognizes Baz2a as main player.

Limitations of the study
Our study demonstrated that GLP-1R is a key regulator of lymphocyte activation during immune response, and it may act as a T cell-negative costimulatory molecule. However, we should consider that because of the wide expression of GLP-1R, some of the observed effects may not be entirely related to the targeting of T cells but of other immune cells. We then demonstrated that the antagonism of GLP-1R triggers an anti-tumor immunity, whereas only one model of murine cancer was tested, and we cannot assure that the mechanism is replicable in other murine cancer models. Moreover, it is interesting to observe that because the expression of GLP-1R parallel the expression of PD-1, the interaction between GLP-1R and other costimulatory molecules (i.e., CTLA-4, ICOS, and CD160) may explain some of the effects seen in our system, and thus, the results might be redundantly over-reported. We injected 2 μg of Exendin (9–39) two times a day for 14 days in a colorectal murine cancer model; however, it is possible that this amount may increase glycemic levels in mice and reduce insulin levels, thus inducing glucose toxicity, which may interfere with tumor growth. Finally, some of the in vitro experimental data may be suffering by the presence of a large GLP-1R intracytoplasmic reservoir, rendering the intracytoplasmic GLP-1R dynamic hard to be understood, creating a potential confounder of the study.

STAR★METHODS

Detailed methods are provided in the online version of this paper and include the following:

- KEY RESOURCES TABLE
- RESOURCE AVAILABILITY
- Lead contact
- Materials availability

EXPERIMENTAL MODEL AND SUBJECT DETAILS
- Human studies
- Murine studies

METHOD DETAILS
- Human PBMCs isolation
- Human flow cytometric analysis
- Immunohistochemistry staining
- Immunohistochemistry staining on kidney, lung, and heart biopsies
- Murine islet allotransplantation and interventional studies
- Murine cardiac allotransplantation and interventional studies
- Colorectal tumor model
- Adoptive transfer of CD3+ T cells from GLP-1R KO mice or from naïve C57BL/6 mice
- Donor Specific Alloantibody Measurement
- Treg induction assay
- Heart tissue digestion and leukocyte isolation
- Histology and immunohistochemistry
- SDF-1 staining on islet allograft
- Immunofluorescence and confocal imaging of GLP-1R+/CD3+ T cells on islet allograft
- ELISA GLP-1 total and active and Exe-4
- Flow cytometry
- ELISpot assay
- Western blot
- qRT-PCR
- Transcriptomic array of GLP-1Rpos and GLP-1Rneg CD4+/CD8+ T cells
- Phosphoproteomic screen of CD3+ T cells
- Immunoprecipitation of GL-P1R on CD3+ T cells
- Immunofluorescence of GLP-1R on CD3+ T cells
- Immunoelectron microscopy
- Mass Spectrometry
- GLP-1R transfection of T cells
- Transwell migration assays
- Bioenergetic analysis
- scRNA seq of GLP-1Rpos and GLP-1Rneg CD3+ T cells
- mRNA GLP-1R due diligence assessment on T cells

QUANTIFICATION AND STATISTICAL ANALYSIS

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.cmet.2024.05.001.

ACKNOWLEDGMENTS

We thank Dr. Thorens for providing us with the anti-GLP-1R antibody used for pathology studies. We thank "Fondazione Romeo and Enrica Invernizzi" for their extraordinary support. F.D. was supported by the Italian Ministry of Health grant RF-2021-12372897 and by the Italian Ministry of University and Research grant 2022JY9CP. R.A. is supported by the NIH grant K24 AI116925. P.F., C.L., and M.B.N. are supported by the Italian Ministry of University Research grants 20229ZA2YF, 2022NH9MXB, and 20225HWJMB, respectively.

AUTHOR CONTRIBUTIONS

M.B.N., S. Dellepiane, and F.F. designed and performed experiments, analyzed data, and wrote and edited the paper. V.U., T.V.F., F.D., A.J.S., E.F., C.X., Y.X., H.B.B., E.C.-L., L.L., A.M., E.A., C.L., A.A., B.E.E., G.S., A.P., G.D., E.S., I.P., M.E.L., L.C., M.V., L.K., K.M.L., G.V., R.A., J.F.M., J.Y., S. Danese, Z.W., and G.V.Z. performed experiments, analyzed data, and coordinated research. S.U., S.M., S.L.R., D.C., D.M., M.I., and G.C. helped with pathology. P.F. conceived the study, designed research, wrote, and edited the paper. All authors reviewed and edited the paper.

The authors declare no competing interests.

Received: July 27, 2023
Revised: December 6, 2023
Accepted: May 2, 2024
Published: June 4, 2024

Liraglutide and exenatide enhance microvascular perfusion in individuals with and without type 2 diabetes. Diabetologia 62, 1701–1711. https://doi.org/10.1007/s00125-019-4918-x.

Dependent Proinflammatory and Migratory Responses. J. Am. Soc. Nephrol. 33, 2211–2231. https://doi.org/10.1681/ASN.2022030286.

Monocytes. Methods Mol. Biol. 2244, 233–246. https://doi.org/10.1007/978-1-0716-1111-1_12

poor cardiac allograft outcomes. J. Clin. Invest. 128, 3490–3503. https://doi.org/10.1172/JCI94524.

# STAR+METHODS

## KEY RESOURCES TABLE

| REAGENT or RESOURCE                      | SOURCE           | IDENTIFIER                           |
| ---------------------------------------- | ---------------- | ------------------------------------ |
| Antibodies                               |                  |                                      |
| PE Anti-IgG Antibody                     | Southern Biotech | Cat#1030-09
RRID: AB_2794298     |
| Hamster Anti-CD3e Antibody               | BD Biosciences   | Cat#553058
RRID: AB_394591       |
| Rat Anti-IL-4 Antibody                   | Invitrogen       | Cat#16-7041-81
RRID: AB_469208   |
| Mouse Anti-IFN gamma Antibody            | Invitrogen       | Cat#AHC4032
RRID: AB_2536278     |
| Rat Anti-IFN gamma Antibody              | Invitrogen       | Cat#16-7311-81
RRID: AB_469242   |
| Brilliant Violet 421 Anti-T-bet Antibody | BD Biosciences   | Cat#563318
RRID: AB_2687543      |
| PE Anti-RORγt Antibody                   | BD Biosciences   | Cat#562607
RRID: AB_11153137     |
| Rabbit Anti-GLP-1R Antibody              | Alomone Lab      | Cat#AGR-021
RRID: AB_10917158    |
| FITC Anti-GLP-1R Antibody                | Alomone Lab      | Cat#AGR-021-F
RRID: AB_2756626   |
| Mouse Anti-CXCL12 Antibody               | Invitrogen       | Cat#MA5-23759
RRID: AB_2608711   |
| APC Anti-CD62L Antibody                  | BD Biosciences   | Cat#553152
RRID: AB_398533       |
| PE Anti-CD44 Antibody                    | BD Biosciences   | Cat#553134
RRID: AB_394649       |
| PerCP Anti-CD4 Antibody                  | BioLegend        | Cat#100538
RRID: AB_893325       |
| PerCP Anti-CD8a Antibody                 | BioLegend        | Cat#100734
RRID: AB_2075238      |
| APC Anti-Insulin Antibody                | R&D Systems      | Cat#IC1417A
RRID: N/A            |
| BUV737 Anti-CD4 Antibody                 | BD Biosciences   | Cat#612761
RRID: N/A             |
| BUV395 Anti-CD8a Antibody                | BD Biosciences   | Cat#563786
RRID: AB_2732919      |
| Brilliant Blue 700 Anti-CD4 Antibody     | BD Biosciences   | Cat#742099
RRID: AB_2871375      |
| Pacific Blue Anti-NK-1.1 Antibody        | BioLegend        | Cat#108722
RRID: AB_2132712      |
| Brilliant Violet 605 Anti-CD127 Antibody | BD Biosciences   | Cat#569295
RRID: N/A             |
| PE Anti-CD44 Antibody                    | BD Biosciences   | Cat#553134
RRID: AB_394649       |
| FITC Anti-CD279 (PD-1) Antibody          | BioLegend        | Cat#135214
RRID: AB_10680238     |
| Brilliant Violet 786 Anti-CD45 Antibody  | BD Biosciences   | Cat#564225
RRID: AB_2716861      |
| Brilliant Blue 700 Anti-CD3e Antibody    | BD Biosciences   | Cat#566494
RRID: AB_2744393      |

(Continued on next page)

| REAGENT or RESOURCE                              | SOURCE                    | IDENTIFIER                           |
| ------------------------------------------------ | ------------------------- | ------------------------------------ |
| Brilliant Blue 700 Anti-CD3 Antibody             | BD Biosciences            | Cat#745836
RRID: AB_2871412      |
| Brilliant Blue 700 Anti-CD45 Antibody            | BD Biosciences            | Cat#566440
RRID: AB_2744406      |
| Brilliant Violet 786 CD11c Antibody              | BD Biosciences            | Cat#563735
RRID: AB_2738394      |
| eFluor 450 CD11b Antibody                        | Invitrogen                | Cat#48-0112-82
RRID: AB_1582236  |
| PE-CF594 Anti-CD45 Antibody                      | BD Biosciences            | Cat#562313
RRID: AB_11151901     |
| Brilliant Violet 786 Anti-CD335 (NKp46) Antibody | BD Biosciences            | Cat#569694
RRID: N/A             |
| Brilliant Violet 650 Anti-CD49a Antibody         | BD Biosciences            | Cat#740519
RRID: AB_2740235      |
| Brilliant Blue 700 Anti-CD117 Antibody           | BD Biosciences            | Cat#566415
RRID: N/A             |
| PE Anti-IL33R (ST2) Antibody                     | BD Biosciences            | Cat#566312
RRID: AB_2744490      |
| Brilliant Violet 711 Anti-IL23R Antibody         | BD Biosciences            | Cat#744372
RRID: AB_2742186      |
| PE Anti-CD184 (CXCR4) Antibody                   | BD Biosciences            | Cat#551966
RRID: AB_394305       |
| Brilliant Violet 605 Anti-CX3CR1 Antibody        | BD Biosciences            | Cat#567822
RRID: N/A             |
| Brilliant Violet 421 Anti-CD192 (CCR2) Antibody  | BD Biosciences            | Cat#747963
RRID: AB_2872424      |
| Brilliant Violet 650 Anti-CD195 (CCR5) Antibody  | BD Biosciences            | Cat#743698
RRID: AB_2741680      |
| BV786 Anti-CD197 (CCR7) Antibody                 | BD Biosciences            | Cat#564355
RRID: AB_2738765      |
| Brilliant Blue 700 Anti-CD183 (CXCR3) Antibody   | BD Biosciences            | Cat#742274
RRID: AB_2871450      |
| Brilliant Blue 711 Anti-CD186 (CXCR6) Antibody   | BioLegend                 | Cat#151111
RRID: AB_2721558      |
| BUV395 Anti-CD27 Antibody                        | BD Biosciences            | Cat#563815
RRID: AB_2744349      |
| Brilliant Violet 510 Anti-CD45RA Antibody        | BD Biosciences            | Cat#563031
RRID: AB_2722499      |
| Brilliant Violet 711 Anti-CD197 (CCR7) Antibody  | BD Biosciences            | Cat#563712
RRID: AB_2738386      |
| Brilliant Blue 700 Anti-CD4 Antibody             | BD Biosciences            | Cat#566392
RRID: AB_2744421      |
| Brilliant Violet 605 Anti-CD8 Antibody           | BD Biosciences            | Cat#564116
RRID: AB_2869551      |
| Brilliant Violet 421 Anti-CD25 Antibody          | BD Biosciences            | Cat#564033
RRID: AB_2738555      |
| PE Anti-FoxP3 Antibody                           | BD Biosciences            | Cat#560046
RRID: AB_1645508      |
| FITC Anti-Rabbit IgG Antibody                    | BioLegend                 | Cat#406403
RRID: AB_893531       |
| Mouse Anti-CD3 Antibody                          | Dako                      | Cat#M725401-2
RRID: N/A          |
| Rabbit Anti-GAPDH (D16H11) Antibody              | Cell Signaling Technology | Cat#5174S
RRID: N/A              |

| REAGENT or RESOURCE                    | SOURCE                    | IDENTIFIER                          |
| -------------------------------------- | ------------------------- | ----------------------------------- |
| Mouse Anti-CTLA-4 (CD152) Antibody     | Bio X Cell                | Cat# BE0164
RRID: AB_10949609   |
| PE Anti-GLP-1R Antibody                | Abcam                     | Cat# ab274122
RRID: N/A         |
| Goat Anti-IgG, HRP-linked Antibody     | Cell Signaling Technology | Cat# 7074
RRID: N/A             |
| Rabbit anti-GAPDH (D16H11) XP Antibody | Cell Signaling Technology | Cat# 5174
RRID: N/A             |
| Hamster Anti-CD28 Antibody             | BD Biosciences            | Cat# 553295
RRID: AB_394764     |
| DyLight 488 Anti-IgM Antibody          | Invitrogen                | Cat# SA5-10010
RRID: AB_2556590 |
| DyLight 650 Anti-IgG (H+L) Antibody    | Invitrogen                | Cat# SA5-10041
RRID: AB_2556621 |
| Mouse Anti-IFN gamma Antibody          | Invitrogen                | Cat# AHC4032
RRID: AB_2536278   |

| Bacterial and virus strains | SOURCE                        | IDENTIFIER                  |
| -------------------------- | ----------------------------- | ---------------------------|
| Retro-CMV Blank Retrovirus | Applied Biological Materials  | Cat# RVP001                |

| Biological samples     | SOURCE                                                                         | IDENTIFIER |
| --------------------- | ------------------------------------------------------------------------------ | ---------- |
| Healthy human blood   | Boston Children's Hospital
IRB & Luigi Sacco Hospital                      | N/A        |
| Patient renal tissue  | Fondazione IRCCS Ca' Granda
Ospedale Maggiore
Policlinico Hospital     | N/A        |
| Patient cardiac tissue| De Gasperis Cardio Center and Transplant Center,
Niguarda Hospital         | N/A        |
| Patient lung tissue   | Pulmonary Division, Boston Children's Hospital                                 | N/A        |

| Chemicals, peptides, and recombinant proteins                   | SOURCE            | IDENTIFIER                              |
| -------------------------------------------------------------- | ----------------- | --------------------------------------- |
| Recombinant Mouse IL-2 Protein                                 | Bio-techne        | Cat# 402-ML                             |
| Recombinant Mouse TGF-beta 1 Protein                           | Bio-techne        | Cat# 7666-MB                            |
| Exendin-4                                                      | Merck             | Cat# E7144                              |
| Exendin Fragment 9-39                                          | Merck             | Cat# E7269                              |
| Phorbol 12-myristate 13-acetate                                | Merck             | Cat# P8139                              |
| Ionomycin calcium salt                                         | Merck             | Cat# I0634                              |
| BD GolgiStop Protein Transport Inhibitor                       | BD Biosciences    | Cat# 554724                             |
| Collagenase Type IV                                            | Merck             | Cat# C4-BIOC                            |
| Collagenase from Clostridium histolyticum                      | Merck             | Cat# C9891
CAS: 9001-12-1           |
| CD8a (Ly-2) MicroBeads                                         | Miltenyi Biotec   | Cat# 130-117-044                        |
| Dynabeads Protein G                                            | Invitrogen        | Cat# 10003D                             |
| Recombinant Mouse CXCL12/SDF-1 alpha Protein                   | Bio-Techne        | Cat# 460-SD-010/CF                      |
| Seahorse XF RPMI medium                                        | Agilent           | Cat# 103576-100                         |
| DTSSP (3,3'-dithiobis(sulfosuccinimidyl propionate))           | Thermo Fisher     | Cat# 21578                              |
| PowerUp SYBR Green Master Mix                                  | Thermo Fisher     | Cat# A25742                             |
| SuperPicture Polymer Detection Kit                             | Thermo Fisher     | Cat# 10364213                           |
| BD Cytofix/Cytoperm Plus Fixation/Permeabilization Solution Kit| BD Biosciences    | Cat# 555028
RRID: AB_2869013        |
| ELISPOT AEC Substrate Set                                      | BD Biosciences    | Cat# 551951
RRID: AB_2868954        |

(Continued on next page)

| REAGENT or RESOURCE                                     | SOURCE                   | IDENTIFIER                                       |
| ------------------------------------------------------- | ------------------------ | ------------------------------------------------ |
| ELISPOT HRP Streptavidin                                | BD Biosciences           | Cat#557630                                       |
| Fixable Viability Stain 510                             | BD Biosciences           | Cat#564406
RRID: AB_2869572                  |
| CellTrace Violet Cell Proliferation Kit                 | Invitrogen               | Cat#C34557                                       |
| Mouse IFN-γ ELISPOT Pair                                | BD Biosciences           | Cat#551881                                       |
| Ficoll Paque Plus                                       | Merck                    | Cat#GE17-1440-03                                 |
| Percoll                                                 | Merck                    | Cat#P1644                                        |
| Hoechst 33342                                           | Bio-Techne               | Cat#5117
CAS: 875756-97-1                    |
| CD8a+ T Cell Isolation Kit                              | Miltenyi Biotec          | Cat#130-104-075                                  |
| RPMI 1640                                               | Euroclone                | Cat#ECB9006LX10                                  |
| BAZ2A-ICR                                               | Merck                    | Cat#SML1276                                      |
| JNJ55511118                                             | Bio-Techne               | Cat#6278
CAS: 2036081-86-2                   |
| CFSE                                                    | BD Biosciences           | Cat#565082
RRID: AB_2869649                  |
| CD4+CD25+ Regulatory T Cell Isolation Kit               | Miltenyi Biotec          | Cat#130-091-041                                  |
| CD4 (L3T4) MicroBeads                                   | Miltenyi Biotec          | Cat#130-117-043                                  |
| Hyaluronidase from bovine testes                        | Merck                    | Cat#H3506
CAS: 37326-33-3                    |
| DNase I                                                 | Roche                    | Cat#10104159001                                  |
| Dispase II                                              | Roche                    | Cat#4942078001                                   |
| TEG                                                     | De la Fuente et al.50    | DOI: https://doi.org/10.1016/j.xpro.2021.100841  |
| Pan T Cell Isolation Kit II                             | Miltenyi Biotec          | Cat#130-095-130                                  |
| SuperPicture Polymer Detection Kit, HRP, broad spectrum | Fisher Scientific        | Cat#878963                                       |
| L-Glutamine                                             | Gibco                    | Cat#878963                                       |
| Penicillin-Streptomycin                                 | Gibco                    | Cat#15140122                                     |
| Fetal Bovine Serum                                      | CliniSciences            | Cat#FBS-22B                                      |
| Polybrene                                               | Santa Cruz Biotechnology | Cat#sc-134220
CAS: 28728-55-4                |
| Pierce BCA Protein Assay Kits                           | Thermo Fisher            | Cat#23227                                        |

| Critical commercial assays                           | SOURCE                         | IDENTIFIER                        |
| ---------------------------------------------------- | ------------------------------ | --------------------------------- |
| RNeasy Plus Kits                                     | Qiagen                         | Cat#74136                         |
| QuantiNova Reverse Transcription Kit                 | Qiagen                         | Cat#205411                        |
| Phospho Explorer Antibody Array                      | Full Moon Biosystems           | Cat#PEX100                        |
| EMbed 812 Embedding Kit                              | Electron Microscopy Sciences   | Cat#14120                         |
| Seahorse XF T Cell Metabolic Profiling Kit           | Agilent                        | Cat#103772-100                    |
| Seahorse XF Glycolytic Rate Assay Kit                | Agilent                        | Cat#103344-100                    |
| SuperScript III First-Strand Synthesis System        | Invitrogen                     | Cat#18080051                      |
| Glucagon-Like Peptide-1 (Active) ELISA Kit           | Merck                          | Cat#EGLP-35K                      |
| Exendin-4 ELISA kit                                  | Duotech                        | Cat#ABIN627775                    |
| GLP-1 Total ELISA Kit                                | Merck                          | Cat#EZGLP1T-36K                   |
| Lineage Cell Depletion Kit                           | Miltenyi Biotec                | Cat#130-090-858                   |
| Direct-zol RNA Miniprep Kits                         | Zymo Research                  | Cat#R2052                         |
| Zymoclean Gel DNA Recovery Kit                       | Zymo Research                  | Cat#D4008                         |
| PE / RPhycoerythrin Conjugation Kit - Lightning-Link | Abcam                          | Cat#ab102918                      |
| Mouse IFNγ ELISPOT Set                               | BD Biosciences                 | Cat#551083
RRID: AB_2868922   |

(Continued on next page)

Cell Metabolism 36, 1302–1319.e1–e12, June 4, 2024   e4

*(Continued on next page)*

Additional information and requests for resources and reagents should be addressed to the lead contact, Paolo Fiorina (paolo.fiorina@childrens.harvard.edu).

1. C57BL/6 and BALB/c mice were obtained from the Jackson Laboratory (Bar Harbor, Maine). Experiment with GLP-1R KO mice, were performed in Wuhan at the J. Yang Lab and all procedures involving these animals were performed and monitored in accordance with the guidelines of Tongji Animal Use Regulations and approved by the Institutional Animal Care and Use Committee of Tongji Medical College. All mice were cared for and used in accordance with Harvard Medical School institutional guidelines and housed 2 weeks in Boston Children Hospital pathogen-free animal house in isolated cages with 12-hr light/dark cycle and ad libitum access to food and water before undergoing experiments. Spleen, heart and renal cells were obtained by collagenase tissue digestion as previously described.⁵⁴ Lymphocytes were extracted from murine spleen by apposite CD4 or CD8 mAb-coated microbeads (Miltenyi).

2. To assess GLP-1R expression on human T cell subsets, peripheral blood mononuclear cell fractions isolated from healthy subjects were stained. The following antibodies were used for flow cytometric analysis in human studies: FITC-conjugated anti-human GLP-1R, BUV395-conjugated anti-human CD27, BV510-conjugated anti-human CD45RA, BV711-conjugated anti-human CCR7, BB700-conjugated anti-human CD4, BV605-conjugated anti-human-CD8, BV421-conjugated anti-human CD25, and PE-conjugated anti-human FoxP3. Antibodies were purchased from BD Biosciences, Alomone (Israel). FITC-conjugated donkey anti-rabbit IgG was used as related isotype controls. A BD Celesta flow cytometer (BD Biosciences) was used to analyze cells with the light scatter properties of stem cells or lymphocytes. Background staining was determined using nonreactive isotype-matched control mAbs with gates positioned to exclude 99% of non-reactive cells. FlowJo software version 10.6.2 (BD Biosciences) was used for analysis.

3. For characterization of GLP-1R on human T lymphocytes, human peripheral blood mononuclear cells (PBMCs) were isolated from healthy donors’ blood. Study protocol was approved by Boston Children’s Hospital IRB. For immunohistochemistry staining on kidney, lung and heart biopsies, human renal biopsies obtained from patients experiencing allograft rejection were obtained from Nephrology, dialysis and renal transplantation, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico Hospital, all patients’ characteristics as well as their immunosuppressive regimen are described in Table S2. As regarding cardiac samples used in this study, samples were obtained from the right side of the interventricular septum of cardiac transplant recipients at De Gasperis Cardio Center and Transplant Center, Niguarda Hospital, Milan, Italy. Samples were then formalin-fixed, paraffin-embedded, sectioned, and histologically graded by a cardiac pathologist according to the International Society for Heart and Lung Transplantation criteria as previously reported.⁵³ The Additional characteristics of patients and the immunosuppressive regimen are depicted in Table S3. As far regarding the lung samples used in this study obtained from Pulmonary Division, Boston Children’s Hospital, the cases were blinded samples, with chronic lung allograft rejection, where evidences of obliterative bronchiolitis and the presence of lymphocytic bronchitis, epithelial cell injury and necrosis, have been confirmed. All patients provided informed consent prior to participation in the study, and all related procedures were performed with the approval of the internal review and ethics boards of the indicated hospitals.

4. Immunohistochemistry was performed with 4-μm-thick formalin-fixed, paraffin-embedded tissue sections. Photomicrographs (400X) were obtained using an Olympus BX41 microscope (Olympus, Center Valley, PA). The following primary antibodies were used: anti-GLP-1R, anti-CD3 (respectively from Alomone [Israel], Abcam [Cambridge, MA], and BD Biosciences [San Jose, CA]).

5. Blood samples were obtained from healthy controls in accordance with Institutional Review Board committee approval. Peripheral blood mononuclear cell fractions were isolated by Lymphoprep density gradient medium (Stem Cell Technology, Vancouver, BC–Canada) and processed for further analysis for FACS staining. In other assays, lymphocytes were extracted by apposite CD4 or CD8 mAb-coated microbeads (Miltenyi Biotec, Bergisch Gladbach – Germany) as previously described.⁵⁵

The renal biopsies from transplant patients were paraffin-embedded following hospital standard protocol: paraformaldehyde (PFA) 4% for 30’, dH2O for 5’, ethanol (ETOH) 95% (10’x 3 times), ETOH 100% (10’x 3 times), Xylene (10’x 3 times). Three different renal biopsies from transplant patients of 3 μm thick were evaluated for Haematoxylin Eosin (H&E Bioptica, Milan, Italy), CD3 (mouse anti-human Dako 1:20), and GLP-1R (rabbit Alomone Labs, Israel, 1:100) with the following final diagnosis f: i) Renal biopsies without major histological abnormalities, ii) Renal biopsies showing antibody-mediated rejection, ii) Renal biopsies showing T cell-mediated rejection. The hematoxylin & eosin was performed using a standard protocol and histochemistry was performed using super picture HRP polymer conjugated broad spectrum (Invitrogen, CA, United States). Images were acquired by AxioVision software 4.8 (Carl Zeiss). The IMAGE J program was used for the CD3 and GLP-1R quantification (n=18 region of interest).

Pancreatic islets from BALB/c mice were isolated by collagenase digestion and density gradient separation as previously described.56,57 Subsequently, four to five hundred islets were inoculated under the renal capsule of each C57BL/6 recipient rendered diabetic with streptozotocin (STZ) (200 mg/kg, administered i.p. Sigma-Aldrich). Islet transplantation success was confirmed by glycaemia normalization. Rejection of islet allografts was defined as blood glucose levels >250 mg/dl for at least 2 consecutive days.58 Treatment modalities were the following: transplanted mice were intraperitoneally injected according to the following protocols: 1) Exendin-4 (Exe-4) (Amylin Pharmaceuticals, San Diego, CA–USA) 0.2mg twice/day for two weeks after transplant; 2) Exe-4 0.2mg twice/day from the day before until two weeks after transplant; 3) Exendin-4 2mg twice/day from the day before until two weeks after transplant; 4) Exendin-4 2mg twice/day + Exendin-9-39 (Exe-9) (Sigma-Aldrich) 2mg twice/day from the day before until two weeks after transplant; 5) Exendin-4 2mg twice/day from the day before until two weeks after transplant + Rapamycin 0.1mg/die for two weeks; 6) saline 0.5ml twice/day for two weeks. The follow-up of the transplanted mice was for 100 days.

Cardiac allografts from BALB/c mice were transplanted intra-abdominally in C57BL/6 mice using microsurgical techniques as described.55 Rejection was determined as complete cessation of cardiac contractility and was confirmed by direct visualization. Transplanted mice were intraperitoneally injected according to the following protocols: 1) Exendin-4 (Exe-4) (Amylin Pharmaceuticals, San Diego, CA –USA) 0.2mg twice/day for two weeks after transplant; 2) Exe-4 0.2mg twice/day from the day before until two weeks after transplant; 3) Exe-4 2mg twice/day from the day before until two weeks after transplant; 4) Exe-4 2mg twice/day + Exendin-9-39 (Exe-9) (Sigma-Aldrich) 2mg twice/day from the day before until two weeks after transplant; 5) Exe-4 2mg twice/day from the day before until two weeks after transplant + Rapamycin 0.1mg/die for two weeks; 6) saline 0.5ml twice/day for two weeks.

Female C57BL/6 mice were anesthetized with 100 mg/kg of ketamine and 50 mg/kg of xylazine. Next, by using a 29-gauge syringe, 2x10^5 MC38 cells were injected submucosally into the distal posterior rectum in a final volume of 50 mL, as described previously.19,51 MC38-injected mice were randomly assigned into 2 groups: (i) Exe-9-treated group (n=8), where all mice received an intraperitoneal injection of 2 μg of Exendin-9-39 (Exe-9) starting by Day1 for a total of 14 days; (ii) untreated-group (n=6), where all mice received an IP injection of PBS starting by day 1 and for a total of 14 days. Tumour growth was visually monitored daily. After animals’ sacrifice, tumours were measured by a digital calliper measuring tumour length, width, and height and were weighted using a digital scale. Procedures involving mice were conformed to institutional guidelines in agreement with national and international law and were approved by the ethics committee by the Ministry of Health.

2-4x10^6 CD3^+ T cells obtained from naïve C57BL/6 mice and 2-4x10^6 CD3^+ T cells obtained from GLP-1R KO mice, were injected into BALB/c cardiac-transplanted C57BL/6 Rag1^-/- mice, and survival was assessed as previously described.54

At day 7 post heart allotransplantation, we collected sera from all the recipients and determined the levels of donor-specific alloantibodies (DSA) using splenocytes from C57BL/6 donors as probes. In brief, splenic tissues were ground and filtered through a 70-μm cell strainer. The resulting splenocytes were then resuspended in PBS, seeded at 5×10^5 per well into 96-well plates, incubated with an equal volume of fetal bovine serum (FBS) for 10 minutes to block nonspecific binding, washed with PBS containing 2% FBS, and then incubated with serum (1:8, 1:16 and 1:32 dilution) for 20 min at 4°C in the dark. Next, cells were washed twice and incubated for 20 minutes with PE-conjugated anti-mouse IgG (Southern Biotech, Birmingham, AL, USA; Cat# 1030-09). The level of donor-specific IgG was then determined by FACS analysis and is presented as the mean fluorescence intensity (MFI).

Naïve CD4^+ CD25^- T cells were selected and activated for 5 days with 1 μg/ml of plate-bound soluble anti-CD3 and anti-CD28 antibodies (BD Biosciences). Cells were cultured for 5-days in the presence of IL-2 (10ng/ml; R&D Systems) and TGFβ (2ng/mL; R&D Systems), anti-IL-4 (0.5μg/ml; PeproTech) and anti-IFNγ (2μg/mL; PeproTech) and were treated with Exe-4 (1nM) or left untreated. Then, cells were washed, pulsed for 4-hrs with phorbol myristate acetate (PMA; 50ng/mL; Sigma-Aldrich), ionomycin

(500 ng/mL; Sigma-Aldrich) and Golgi-stop (1.0 μL/mL; BD Biosciences) and then analyzed by FACSCelesta (BD Biosciences) for the expression of Foxp3, Tbet and RorγT as previously reported.

Hearts were removed and washed with saline solution (PBS). For preparing single cell suspensions, heart tissue was minced with surgical scissors and incubated in 1 mg/mL collagenase type IV (Sigma-Aldrich, St. Louis, MO) in DMEM medium (Lonza, Walkersville, MD, USA) for 20 minutes at 37°C with gentle agitation. Cells were filtered through 70 μm filters and centrifuged (5 minutes at 4°C, 300 g). Cell pellets were resuspended in 33% Percoll solution (Sigma-Aldrich) and separated by gradient centrifugation by layering the cell suspension on top of a 66% Percoll solution before centrifugation for 20 minutes at 4°C. Cells at the interphase of the two solutions were carefully collected, washed in PBS and re-suspended in appropriate buffer for further experiments.

Immunohistochemistry was performed on formalin-fixed, paraffin-embedded tissue (23). Photomicrographs were taken using an Olympus BX41 microscope (Center Valley, PA - USA). Dr. Bernard Thorens kindly provided us with the anti-GLP-1R antibody for pathology studies. An expert pathologist evaluated selected micrographs.

Harvested islet allografts were fixed in PFA and paraffin-embedded. Tissues were cut into 5 μm sections, and respectively de-paraffinized, rehydrated and antigen-retrieved. Then, sections were incubated with the following antibody: mouse anti-CXCL12 monoclonal antibody (1:300, Thermofisher Scientific, MA5-23759). Images were acquired on an Olympus BX41 microscope (Center Valley, PA) and analyzed by an expert pathologist.

Primary antibodies against CD3 (mouse CD3 antibody (MAB4841), R&D Systems, dilution 1:100) and GLP-1R (mouse GLP-1R (Mab 3F52), Developmental Studies Hybridoma Bank, Iowa City, IA, USA, dilution 1:50) were tested in a 3 mm-thick histological section to identify the receptor positivity in T lymphocytes. Immunoreactive signals were detected using fluorescently labeled secondary antibodies (goat anti-rat 488 (SA5-10010), Invitrogen dilution 1:70 and Donkey anti-rabbit 650 (SA5-10041), Sigma Aldrich, St. Louis, MO, USA, dilution 1:70, respectively). This section was viewed by confocal microscopy (Stellaris 5; Leica, Wetzlar, Germany) through a x63 oil objective. Images were acquired in a multi-track mode, using consecutive and independent optical pathways and observed by the Las X software (Leica, Wetzlar, Germany).

Total GLP-1, active GLP-1 and Exendin-4 levels were assessed in the individual serum of all groups of treated and untreated mice using commercially available ELISA kits, according to the manufacturer's instructions (BlueGene E03E0022). Briefly, the Exen4 ELISA kit applies the quantitative sandwich enzyme immunoassay technique. The microtiter plate is already pre-coated with a monoclonal antibody specific for Exen4. Standards and samples are then added to the microtiter plate wells and Exen4 if present, will bind to the antibody pre-coated wells. In order to quantitatively determine the amount of Exen4 present in the sample, a standardized preparation of horseradish peroxidase (HRP)-conjugated polyclonal antibody, specific for Exen4 are added to each well. The microtiter plate undergoes incubation (1 hour at 37°C), and then the wells are thoroughly washed to remove all unbound components. Next, substrate solutions are added to each well. The enzyme (HRP) and substrate are allowed to react over a short incubation period (15-20 minutes at 37°C). The enzyme-substrate reaction is terminated by addition of a sulphuric acid solution and the color change is measured spectrophotometrically at a wavelength of 450 nm.

FACS analysis was performed with a FACSCelesta (BD Bioscience) on murine splenocytes or on single cells suspension prepared upon collagenase-digestion of grafted organs. We used the following antibodies: APC conjugated Rat anti-mouse CD62L, PE conjugated Rat anti-mouse CD44, PerCp conjugated Rat anti-mouse CD4 or PerCp conjugated Rat anti-mouse CD8, (Biolegend, San Diego, CA, USA), and APC conjugated anti-mouse/human insulin (R&D, Minneapolis, MN - USA). GLP-1R was detected by indirect staining; the primary antibody was purchased from Alomone Lab (Jerusalem, Israel) and variably associated with FITC or APC-conjugated anti-isotype Ab (BD and Biolegend respectively). For intracellular staining, splenocytes were isolated from BL6 mice were incubated with and w/o anti CD3/CD28 used both at 0.5 μg/ml, Exe-4 (0.1 nM, 1 nM and 10 nM) or with Exe-4+Exe-9-39 (0.1 nM, 1 nM and 10 nM). After 24 hours incubation, cells were collected, washed and plated in RPMI 10% FBS, then stimulated with 50 ng/ml PMA (Sigma Aldrich), 500 ng/ml ionomycin (Sigma Aldrich) and Golgi Stop as recommended by the manufacturer (BD Biosciences, San Diego, CA, USA) for 4h in a humidified incubator 37°C, 5% CO2. After incubation, cells were collected, washed and stained for surface markers, i.e. CD4 BUV737, CD8 BUV395, (BD Biosciences, San Diego, CA, USA) and GLP-1R FITC (Alomone Lab, Jerusalem, Israel). They were further fixed, permeabilized using the BD Cytofix/Cytoperm Kit (BD Biosciences, San Diego, CA, USA), and stained with a mAb against IFN-γ (eBioscience). Finally, CD4+ GLP-1R+ IFN-γ+ and CD8+ GLP-1R+ IFN-γ+ T cells were assessed by flow cytometry analysis. For the expression of GLP-1R on innate immune cells, the following antibodies were used: CD4 BB700, NK1.1 BV421, CD127 BV605, CD44 PE, GLP-1R FITC/PD1 FITC, Viability Dye BV510 (NKT subset); CD45 BV786, CD3 BB700, NK1.1

BV421, GLP-1R FITC/PD1 FITC, Viability Dye BV510 (NK subset); CD45 BB700, CD11c BV786, CD11b BV421, GLP-1R FITC/PD1 FITC, Viability Dye BV510; CD45 PE-CF594, CD127 BV605, NK1.1 BV421, CD335 BV786, CD49a BV650, CD117 BB700, IL33R PE, IL23R BV711, GLP-1R FITC/PD1 FITC, Viability Dye BV510 (LCs subset). For the determination of the chemokine receptors profile of GLP-1R+ CD3+ T cells, the following antibodies were used: GLP-1R FITC, CXCR4 PE, CX3CR1 BV605, CCR2 BV421, CCR5 BV650, CCR7 BV786, CXCR3 BB700, CXCR6 BV711, Viability Dye BV510.

An ELISPOT assay was used to measure the number of IFN-γ-producing cells according to the manufacturer's protocol (BD Biosciences) as previously performed by our group. To test the role of GLP-1R-driven immunity on the anti-CD3/28 non-autoimmune specific response, 1x10⁶ splenocytes isolated from C57BL/6 mice were cultured in a microwell plate (BD Biosciences) coated with IFN-γ capture antibody (Ab) in the presence of the following soluble anti-CD3 and anti-CD28 at 0.5 µg/ml for 24 hours. Exe-4 and/or Exe-4+Exe-9-39 at concentrations of 0.1, 1 or 10 nM were added to the culture. After 24 hours, bound secondary Ab was visualized using HRP-streptavidin and the AEC substrate kit (BD Biosciences). Spots were counted using an Immunospot analyzer (Cellular Technology Ltd., Cleveland, OH) and expressed as the number of cytokine-producing spots per 1x10⁶ cells. After 24 hours, ELISpot plates were developed and acquired on an ELISpot reader, as previously described.

Western Blot was performed with protein lysates from human and murine islets or CD4 and CD8 cells purified with magnetic beads (Miltenyi) from murine spleen or human. Protein concentration in cell lysates was measured using a Bradford assay (Bio-rad, Hercules, CA). After an SDS polyacrylamide gel electrophoresis, proteins were transferred to a nitrocellulose membrane and incubated with primary GLP-1R (Alomone) or GAPDH (Cell Signaling Technology, Danvers, MA-USA) detecting Ab. The secondary incubation was performed with HRP-conjugated anti-isotype Ab (Cell Signaling). Quantification of band size was performed using ImageJ software and was normalized for GAPDH expression.

Total RNA was extracted from human or murine immune cells. RNA was purified by using RNeasy kit (Qiagen, Valencia, CA), then reverse-transcribed into cDNA using Superscript III (Invitrogen, Carlsbad, CA). Transcripts were amplified using a 7300 Real-Time PCR System and analyzed by the ΔCT method; GAPDH was used as the internal reference. Both GLP-1R and GAPDH primers were obtained from Applied Biosystems (Foster City, CA).

Transcriptomic array was performed on samples the following samples of GLP-1R^POS CD4+, GLP-1R^NEG CD4+ T cells, GLP-1R^POS CD8+ and GLP-1R^NEG CD8+ T cells isolated from splenocytes of C57BL/6 mice. 1 µg of RNA was reverse transcribed using a Quantinova Reverse Transcription Kit (Qiagen, Hilden, Germany) following the manufacturer instructions. The obtained cDNA of each sample was then analyzed by quantitative real time PCR analysis using a SYBR green-based Quantinova LNA murine custom panel (Qiagen) according to the manufacturer's instruction. Relative quantification of each gene in the panel was calculated by delta-Ct method using averaged levels of ACTB, B2M, GAPDH, HSP90AB1 genes for data normalization. Volcano plot shows statistical significance log (P value) versus difference (fold change).

Isolated CD3+ T cells from splenocytes were treated with Exendin-4 (Exe-4) for 24 hrs or left untreated. Total soluble proteins from both cell extracts, approximately 7x10^6 cells per conditions were used, all steps were performed using the Phospho Explorer Antibody Array kit (Full Moon Biosystems, PEX100) as recommended by the manufacturer. Next, soluble extracted proteins were biotinylated and were next incubated with a mixture of Cy3-streptavidin-detection buffer and the array slides were incubated on a rotating shaker for 30 min at RT. After, several washing steps, the array slides were allowed to dry by centrifugation. Dry array slides were analyzed by a slide-based microarray scanner as recommended by the manufacturer.

Protein lysates were extracted from murine CD3+ T cells (30 mg per sample), previously selected from splenocytes of C57BL/6 mice and stimulated for 24 hours with anti-CD3/anti-CD28 (1 µg/each). We first added GLP-1R antibody to the Dynabeads and incubated for 10 min at room temperature. Then, we crosslinked the antibody to the Dynabeads Protein G (Invitrogen) magnetic beads before immunoprecipitation in order to avoid co-elution of the antibody. Immunoprecipitation was then carried out overnight at 4°C by adding protein lysate to Ab-Dynabeads complex. Material was eluted from the Ab-Dynabeads complex using Elution Buffer (50 mM glycine pH 2.8) for 2 min at room temperature, to dissociate the complex, and was separated by SDS/PAGE and respectively visualized using silver staining/Coomassie staining. Gel bands that were unique to lanes containing GLP-1R as well as the corresponding areas in the control lane were excised and subjected to in-gel digestion with trypsin and to analysis by MS/MS as previously described.

For electron microscopy immunocytochemistry, the pellets of lymphocytes were fixed for 2 hrs at 4°C in a mixture of 2% paraformaldehyde and 1.25% glutaraldehyde in 0.05 M (pH 7.3) cacodylate buffer, post-fixed in 1% osmium tetroxide and embedded in EMBed-812 embedding kit (Electron Microscopy Sciences Hatfield, PA, UK). Thin sections were incubated with GLP-1R primary antibody (Alomone labs) diluted 1:10, then with colloidal gold conjugated anti-rabbit antibody diluted 1:50 (EY laboratories, San Mateo CA USA), and, after counterstaining with uranyl acetate and lead citrate, were examined with a TEM Jeol 1010 (Jeol, Tokyo, Japan), of Centro Grandi Attrezzature of Varese Insubria University.

Bioenergetic parameters were calculated using the following formulas:

Basal Respiration = mitoOCR = OCR_basal - OCR_rot/ant

Maximal Respiration = OCR_BAM15 - OCR_rot/ant

Spare respiratory capacity = OCR_BAM15 - OCR_basal

ATP linked Respiration = OCR_basal - OCR_oligo

Proton Leak = OCR_oligo - OCR_rot/ant

Non-mitochondrial respiration = OCR_rot/ant

Basal glycolysis = PER_basal - mitoPER

mitoPER = mitoOCR * CCF; CCF = 0.61

Compensatory glycolysis = PER_rot/ant

Live GLP-1R^pos and GLP-1R^neg CD3^+ T cells isolated from splenocytes of C57BL/6 mice were FACS sorted through a BD FACSAria Fusion and were then washed and recovered in PBS containing 0.04% BSA. Recovered cells were counted and a viability >90% was verified and the 2 cell suspensions (GLP-1R^pos and GLP-1R^neg CD3^+ T cells) were then concentrated at a concentration of 1000 cells/μl and were subsequently used for library preparation. scRNA seq libraries were prepared using "Chromium scRNA 3’NEXTGEM 3.1" (10x GENOMIX) at the Center for Omics Sciences (COSR), IRCCS San Raffaele Scientific Institute, Italy, following manufacturer’s instructions. Prepared libraries were then sequenced through an Illumina NovaSeq6000 on a S1 flow cell at 100 cycles.

UMItool v.1.0.0 was used to map the raw reads to the mouse genome (vs mm10) and to obtain the gene expression level for each cell, annotated with Genecode, release M22. The counts were then imported in the R environment v.4.0.3 and analyzed with the Seurat package v.4.3.0 (https://satijalab.org/seurat/). The two samples were first analyzed individually, following the standard Seurat pipeline. Cells with a total number of detected genes <200 or >5000 were filtered out, as well as cells with a relative count of mitochondrial genes >0.1. Counts were then normalized with the Seurat global-scaling normalization method “LogNormalize” with a 10,000 scale factor. The FindVariableFeatures function was used to identify a subset of features that exhibit high cell-to-cell variation that were then used as input for the RunPCA function to perform the principal component analysis (PCA). Both the datasets were then scaled with the ScaleData function, regressing out the number of features and the percentage of mitochondrial genes to obtain equal weight in downstream analysis. CellCycleScoring was employed to assess cell cycle scores on scaled data and the distribution of the variable genes resulted to be unaffected by the cell cycle phases. Clustering was carried out through the FindCluster function, using the original Louvain algorithm and considering 1–30 principal components. Resolutions equal to 0.5 and 0.2 for sample GLP-1R^pos and sample GLP-1R^neg, respectively, were considered. The integrated analysis was performed with the standard Seurat pipeline. The two single samples were combined selecting the integration anchors through the SelectIntegrationFeatures and FindIntegrationAnchors functions. The final integration step was then performed with the IntegrateData function. Data were scaled as described above and the new integrated matrix was employed for clustering and visualization with a 0.3 resolution.

The function FindAllMarkers was used to perform a Wilcoxon test and to determine the genes differentially expressed in each cluster compared to the rest of the cells (logfc.threshold = 0.25, min.pct = 0.25). This allowed to detect the top marker genes for each cluster.

Cells were first classified using the SingleR package, with the ImmGen database Aran et al.^67 Then, a more detailed manually cured annotation was performed, considering the top marker genes for each cluster.

In order to confirm the expression of GLP-1R on T cells, total RNA was extracted from CD4+ and CD8+ T cells isolated by positive selection with microbeads (CD8a+ T Cell Isolation Kit, mouse and LT34 for CD4 isolation; MiltenyiBiotech.com) and from Beta-TC-6 cell line (BTC6), a murine beta cell line initially derived from insulinoma and used here as a positive control for GLP-1R expression. RNA was extracted by using the Direct-zol RNA Kit (Zymo Research, Irvin, CA, USA) following manufacturer's instructions and then quality checked and quantified by spectrophotometry. A total of 10 ng RNA from the aforementioned cells was retrotranscribed into cDNA with the Superscript III kit (Life Technologies) and Glp-1r expression was quantified by qPCR using PowerUp SYBR Green Master Mix 2X (Life Technologies) on a QuantStudio S6 Real-Time PCR System (Thermo Fisher Scientific). Specificity of the amplifications was assessed by melt curve analysis. Primers for murine Glp-1r amplification (Fw: 5’-TGCTATCGGCGTCAACTTTCT-3’; Rv: 5’-ATTCAAGTGCTCCAGCCTCC-3’) were designed in-house by an online tool (https://www.primer3plus.com), to yield a 334 bp long amplicon from Glp-1r mRNA. Murine Gapdh mRNA was amplified in parallel using specific primers (Fw: 5’-CCAGGGCTGCCATTTGCAGTGGCAAAGTGG-3’; Rv: 5’-CCTGGAAGATGGTGATGGGVTTCCCGTTGA-3’) to be used as positive internal control. Reactions in which reverse transcriptase was omitted (-RT) were run in parallel to test for potential DNA contamination. PCR products were separated on a 0.8% agarose gel in TAE buffer. Bands corresponding to the putative Glp-1r amplicon (334 bp) were excised from the gel and DNA was extracted using the Gel DNA Recovery Kit (Zymo Research, Irvin, CA, USA). Both strands of recovered DNA were then sequenced by the Sanger method with the same forward and reverse primers used for gene amplification. The obtained amplicon sequences were aligned with that of nucleotides 950-1296 of murine Glp-1r mRNA NCBI Reference sequence NM_021332.2 by the Clustal Omega Multiple Sequence Alignment tool (https://www.ebi.ac.uk/Tools/msa/clustalo).

Data are expressed as mean ± SEM. Kaplan-Meier analysis was used for analysis of survival. When two groups were compared, a two-sided unpaired Student t test (for parametric data) or a Mann-Whitney test (for nonparametric data) was used. A P value < 0.05 (by two-tailed testing) was considered an indicator of statistical significance and were reported within the corresponding panels of the figure legends. Graphs were generated using GraphPad Prism 10 software (GraphPad Software, San Diego, CA).

Cell Metabolism, Volume 36

Moufida Ben Nasr, Vera Usuelli, Sergio Dellepiane, Andy Joe Seelam, Teresa Vanessa Fiorentino, Francesca D'Addio, Emma Fiorina, Cong Xu, Yanan Xie, Hari Baskar Balasubramanian, Eduardo Castillo-Leon, Lara Loreggian, Anna Maestroni, Emma Assi, Cristian Loretelli, Ahmed Abdelsalam, Basset El Essawy, Silvia Uccella, Ida Pastore, Maria Elena Lunati, Gianmarco Sabiu, Adriana Petrazzuolo, Giacomo Ducci, Elena Sacco, Lucia Centofanti, Massimo Venturini, Serena Mazzucchelli, Deborah Mattinzoli, Masami Ikehata, Giuseppe Castellano, Gary Visner, Liu Kaifeng, Kang Mi Lee, Zhimin Wang, Domenico Corradi, Stefano La Rosa, Silvio Danese, Jun Yang, James F. Markmann, Gian Vincenzo Zuccotti, Reza Abdi, Franco Folli, and Paolo Fiorina

Supplemental Information:

## Inventory of Supplemental information

### Supplemental Data_Figures

- Figure S1. Glp-1r mRNA expression in T cells was confirmed by Sanger sequencing, related to Figure 1.

- Figure S2. GLP-1R expression and murine immune cells, related to Figures 1 and 2.

- Figure S3. scRNAseq analysis reveals heterogeneity of GLP-1R^pos T cells, related to Figure 3.

- Figure S4. GLP-1R signaling modulates T cell function, related to Figure 4.

- Figure S5. GLP-1R signaling modulates the alloimmune response in vivo, related to Figure 5.

- Figure S6. GLP-1R is expressed by human T cells, related to Figure 7.

- Figure S7. Expansion of GLP-1R^pos T cells during human allograft rejection, related to Figure 7.

### Supplemental Data_Tables

- Table S1. Relative quantification of the immunoprecipitated GLP-1R^pos CD3+ T cells, related to Figure 2.

- Table S2. Characteristics of kidney-transplanted patients, related to Figure S7 and to STAR Methods.

- Table S3. Characteristics of heart-transplanted patients, related to Figure S7 and to STAR Methods.

Figure S1. Glp-1r mRNA expression in T cells was confirmed by Sanger sequencing, related to Figure 1. A: Melting curve plots of qRT-PCR products showing a single peak at ~84°C confirming a unique amplification product obtained when the cDNA of BTC6, respectively 2 biological replicates of murine CD4⁺ and CD8⁺ T cells and CD3⁺ T cells was used. B: Representative electropherograms showing the 5’-to-3’ sequence of the amplified Glp-1r region spanning exons 11 to 13 in murine CD4⁺, CD8⁺, CD3⁺ T cells and BTC6 cells obtained by Sanger sequencing. C: Sequence alignment of nucleotides 950-1296 of murine Glp-1r mRNA reference sequence NM_021332.2 to that of the qRT-PCR products obtained from RNA of CD4⁺, CD8⁺, CD3⁺ T cells and of BTC6 cells, further confirming the amplification of Glp-1r in these cells.

# A. Melt Curve Plot of qPCR products

Temperature (°C)

# B.

exon 11 | exon 12 | exon 13 | exon 11 | exon 12 | exon 13

[Chromatogram data - multiple rows of colored peaks representing DNA sequences]

Murine Glp-1r amplicon sequence alignment

# C.

```
CD4+ T cells  --------------------------------------------------------GTACCCTCGCCCCACGCAGAAGGG
CD8+ T cells  --------------------------------------------------------GTACCCTCGCCCCACGCAGAAGGG
CD3+ T cells  --------------------------------------------------------GTACCCTCGCCCCACGCAGAAGGG
BTC6 cells    --------------------------------------------------------GTACCCTCGCCCCACGCAGAAGGG
NM_021332.2/950-1296  CACCTGGAACTCCGGCTCCTCAACTCCTCACTGGGCTTCCTCCTCTGCGTACCCTCGCCCCACGCAGAAGGG

CD4+ T cells  GAATCTCGTCGTCCTCCTCTTCCTCTTCGGGCTCAGCGTGCTCCTCATCCTCATCCTCTTTGCCATCATCGTGGTCGTCA
CD8+ T cells  GAATCTCGTCGTCCTCCTCTTCCTCTTCGGGCTCAGCGTGCTCCTCATCCTCATCCTCTTTGCCATCATCGTGGTCGTCA
CD3+ T cells  GAATCTCGTCGTCCTCCTCTTCCTCTTCGGGCTCAGCGTGCTCCTCATCCTCATCCTCTTTGCCATCATCGTGGTCGTCA
BTC6 cells    GAATCTCGTCGTCCTCCTCTTCCTCTTCGGGCTCAGCGTGCTCCTCATCCTCATCCTCTTTGCCATCATCGTGGTCGTCA
NM_021332.2/950-1296  GAATCTCGTCGTCCTCCTCTTCCTCTTCGGGCTCAGCGTGCTCCTCATCCTCATCCTCTTTGCCATCATCGTGGTCGTCA

CD4+ T cells  TCATCCTGGTCCGCTTCCTCTGCAACACCGTCAACGCCTCCCTTCTGCAGCGCCTGCGCGACATCATCCGCATCTACCTG
CD8+ T cells  TCATCCTGGTCCGCTTCCTCTGCAACACCGTCAACGCCTCCCTTCTGCAGCGCCTGCGCGACATCATCCGCATCTACCTG
CD3+ T cells  TCATCCTGGTCCGCTTCCTCTGCAACACCGTCAACGCCTCCCTTCTGCAGCGCCTGCGCGACATCATCCGCATCTACCTG
BTC6 cells    TCATCCTGGTCCGCTTCCTCTGCAACACCGTCAACGCCTCCCTTCTGCAGCGCCTGCGCGACATCATCCGCATCTACCTG
NM_021332.2/950-1296  TCATCCTGGTCCGCTTCCTCTGCAACACCGTCAACGCCTCCCTTCTGCAGCGCCTGCGCGACATCATCCGCATCTACCTG

CD4+ T cells  GTCAAGAACTGCCTCGTGAATGTCATCCTGATGGCCAGCGTGCTGCTCATCGTGCTCCTCTGCATCCACATCCACCTGGT
CD8+ T cells  GTCAAGAACTGCCTCGTGAATGTCATCCTGATGGCCAGCGTGCTGCTCATCGTGCTCCTCTGCATCCACATCCACCTGGT
CD3+ T cells  GTCAAGAACTGCCTCGTGAATGTCATCCTGATGGCCAGCGTGCTGCTCATCGTGCTCCTCTGCATCCACATCCACCTGGT
BTC6 cells    GTCAAGAACTGCCTCGTGAATGTCATCCTGATGGCCAGCGTGCTGCTCATCGTGCTCCTCTGCATCCACATCCACCTGGT
NM_021332.2/950-1296  GTCAAGAACTGCCTCGTGAATGTCATCCTGATGGCCAGCGTGCTGCTCATCGTGCTCCTCTGCATCCACATCCACCTGGT

CD4+ T cells  GGTCCGAATGCAGTTTCTGCGGCCAGAATGCCGGGATGCTGCGGAAACCCGAGCAAGAA---------------------
CD8+ T cells  GGTCCGAATGCAGTTTCTGCGGCCAGAATGCCGGGATGCTGCGGAAACCCGAGCAAGAA---------------------
CD3+ T cells  GGTCCGAATGCAGTTTCTGCGGCCAGAATGCCGGGATGCTGCGGAAACCCGAGCAAGAA---------------------
BTC6 cells    GGTCCGAATGCAGTTTCTGCGGCCAGAATGCCGGGATGCTGCGGAAACCCGAGCAAGAA---------------------
NM_021332.2/950-1296  GGTCCGAATGCAGTTTCTGCGGCCAGAATGCCGGGATGCTGCGGAAACCCGAGCAAGAACCCGCTGCAGACTATCTTCATC
```

Supplemental Figure S1

3

Abbreviations: BTC6, Beta-TC-6 cell line; qRT-PCR, Two-step quantitative reverse transcriptase-PCR; cDNA, complementary DNA.

Figure S2. GLP-1R expression and murine immune cells, related to Figures 1 and 2.

A: Representative dot plots for gating strategy and GLP-1R expression by CD4⁺CD25⁺FoxP3⁺ regulatory cells.
B: Quantification of flow cytometric analysis from A and comparison with whole CD4⁺ population.
C-D: Cell trace violet-labelled CD3⁺ T cells were activated with anti-CD3/CD28 Abs. After 24 hours, 72 hours and 120 hours cells were harvested and stained for PD-1; representative dot plots for FACS analysis related to each time point (24, 72 and 120 hours) are shown in (C) and their corresponding bargraphs are shown in (D).
E-F: PD-1 expression was depicted after 72 hours of stimulation with anti-CD3/CD28 Abs on dividing CD3⁺ T cells as compared to non-dividing CD3⁺ T cells; the quantification of PD-1 expression in both sub-populations is shown in (F).
G-H: PD-1 expression was depicted after 72 hours of stimulation with anti-CD3/CD28 Abs on dividing CD4⁺ and CD8⁺ T cells as compared to non-dividing CD4⁺/CD8⁺ T cells, the quantification of PD-1 expression in both sub-populations is shown in (H). Data are representative of at least n=3 samples and are expressed as mean ± standard error of the mean (SEM). *P<0.05; **P<0.01; ***P<0.001.
I-K: A head-to-head comparison of GLP-1R and PD-1 expression on cells of innate immunity.
I: GLP-1R expression was assessed by FACS analysis on respectively CD11b⁺ cells, CD11c⁺ cells, NK cells defined as CD3-/NK1.1⁺, NKT cells defined as CD4⁺/NK1.1⁺/CD44⁺/CD127⁺ and by ILCs (ILC1: NK1.1⁺/CD127⁺/CD49a⁺/CD335⁺; ILC2: CD117⁺/CD127⁺/IL33R⁺, ILC3: CD117⁺/CD127⁺/IL23R⁺); all derived from splenocytes isolated from C57BL/6 mice.
J: PD-1 expression by the aforementioned cells of innate immunity are shown.
K: Gating strategy delineating the expression of GLP-1R on CD11b⁺, CD11c⁺ and NK cells of innate immunity.

L: The profile of several chemokine receptors (CXCR4, CCR2, CCR5, CCR7, CXCR3, CXCR6 and CX3CR1) was explored on GLP-1R^pos CD3⁺ T cells.
M: FACS gating strategy of IFN-γ expression on GLP-1R^pos / GLP-1R^neg CD3⁺ T cells.
N-Q: FACS gating strategy and quantitative bargraph of IL-4/IL-10 expression on GLP-1R^pos / GLP-1R^neg CD3⁺ T cells. Data

are representative of at least n=3 samples and are expressed as mean ± standard error of the mean (SEM). *P<0.05; **P<0.01; ***P<0.001.

Abbreviations: GLP-1R, Glucagon-like peptide 1 receptor; FoxP3, forkhead box P3; Abs, antibodies; FACS, fluorescence-activated cell sorter scan; CT, cell trace; ILCs, Innate Lymphoid Cells.

Figure S3. scRNAseq analysis reveals heterogeneity of GLP-1Rpos T cells, related to Figure 3. alloimmune response
A: Barplot of the sorted GLP-1Rpos CD3+ T cells showing the SingleR annotation for the 13 identified clusters, using 30 nPCs and 0.5 resolution.
B: Barplot of the sorted GLP-1Rneg CD3+ T cells showing the SingleR annotation for the 7 identified clusters, using 30 nPCs and 0.2 resolution.
C: Heat-map showing the most relevant genes present within the GLP-1Rpos CD3+ subset.
D-J: UMAPs delineating the main gene/markers identified in the GLP-1Rpos CD3+ T cell-scRNAseq dataset.
K: Heat-map showing the most relevant genes present within the GLP-1Rneg CD3+ subset.
L-P: UMAPs delineating the main gene/markers identified in the GLP-1Rneg CD3+ T cell-scRNAseq dataset.

A | B
--- | ---
Bar chart A | Bar chart B

C
----
Heatmap C

D | E | F | J
--- | --- | --- | ---
UMAP Tnfrsf4 | UMAP Ncl | UMAP Lef1 | UMAP Ctla4

G | H | I
--- | --- | ---
UMAP Dusp10 | UMAP Dusp1 | UMAP Dapl1

K
----
Heatmap K

L | M | P
--- | --- | ---
UMAP Cxcr6 | UMAP Ly6c2 | UMAP Ctla4

N | O
--- | ---
UMAP Cd4 | UMAP Cd8a

Q

Abbreviations: GLP-1R, Glucagon-like peptide 1 receptor; ATP, adenosine triphosphate; UMAP, Uniform manifold approximation and projection; scRNAseq, single cell RNA sequencing.

Figure S4. GLP-1R signaling modulates T cell function, related to Figure 4. A: Exe-4 significantly reduced the number of IFN-γ producing cells by mitogen-stimulated splenocytes, which was dampened upon co-culture with GLP-1R antagonist Exendin-9-39 (Exe-9) (one-way ANOVA, P<0.05).

B₁-B₂: Exe-4 treatment induced cell death on activated CD4⁺ and CD8⁺ T cells (p<0.05 in Exe-4 (1 nM) treated CD4⁺ T cells vs. medium, p<0.01 in medium vs. Exe-4 (1 nM) treated CD4⁺ T cells).

C₁-C₂: No differences were observed comparing the percentages of proliferating (or cell trace positive) CD4⁺ and CD8⁺ T cells stimulated with anti-CD3/CD28 Abs upon their challenge with Exe-4 neither with the addition of the antagonist Exe-9.

D: Total GLP-1 concentration measured in different assays with GLP-1R⁺ or GLP-1R⁻ CD3⁺ T cells, untransduced mock or pmY-GLP-1R CD3⁺ T cells with or without Exe-4 as compared to that measured when using BTC6 cell line, as a positive control.

E₁-E₂: Representative FACS dot plots showing the percentage of FoxP3⁺CD4⁺CD25⁺ Tregs during Treg induction assay in response to Exe-4 treatment; the quantitative bargraph is shown in (E₂).

F₁-F₂: Representative FACS dot plots showing the percentage of Ror-γT on FoxP3⁺CD4⁺CD25⁺ Tregs during Treg induction assay in response to Exe-4 treatment; the quantitative bargraph is shown in (F₂).

G₁-G₂: Representative FACS dot plots showing the percentage of Tbet on FoxP3⁺CD4⁺CD25⁺ Tregs during Treg induction assay in response to Exe-4 treatment; the quantitative bargraph is shown in (G₂).

H₁-H₄: Representative FACS histograms reflecting effector T cell suppression shown as CTV dilution upon co-culture of untreated-iTregs or Exe-4-treated iTregs at respectively the following ratios: 1:1, 2:1, and 4:1; quantitative bargraph reflecting the percentage of effector T cell suppression is shown in (H₄).

I₁-I₂: GLP-1R upregulation is verified by respectively FACS analysis (I₁) and western blot analysis (I₂), in pmY-GLP-1R-transduced CD3⁺ T cells as compared to their counterparts untransduced.

J: The baseline phenotype of GLP-1R KO mice is shown on agarose gel, where Wildtype are identified by the presence of 518 bp band, Heterozygous by the presence of

respectively 518 bp and 599 bp bands and the Mutant allele is distinguished by the presence of 599 bp band. K₁-K₂: Knockdown of GLP-1R within heart was confirmed by western blot analysis. L₁-L₂ and M₁-M₂: Knockdown of GLP-1R within spleen of GLP-1R KO mice was confirmed by western blot analysis (L₁ and L₂); the absolute numbers of CD4⁺ and CD8⁺ T cells were assessed by FACS analysis within spleen of GLP-1R KO mice as compared to WT mice and shown in (M₁ and M₂). N₁-N₂, O₁-O₂ and P₁-P₃: The knockdown of GLP-1R was confirmed in CD4/CD8 T cells in the thymus of GLP-1R KO mice (N₁ and N₂ and O₁-O₂); the absolute numbers of respectively CD4⁺, CD8⁺ and CD4⁺CD8⁺ T cells were assessed by FACS analysis within the thymus of GLP-1R KO mice as compared to WT mice and shown in (P₁-P₃). Q-S: Apoptosis assay of CD3⁺ T cells from GLP-1R KO mice at baseline and after mitogenic stimulation as compared to their counterparts from WT mice, the quantification of apoptotic cells in both groups and at baseline and/or after mitogen stimulation is shown in (S).

T₁: Quantitative bargraph depicting the percentage of splenic IFN-γ⁺CD3⁺ T cells from GLP-1R KO mice as compared to WT mice at baseline and in response to mitogen stimulation. T₂: The percentage of CD3⁺ T cells from GLP-1R KO mice migrating to SDF-1 gradient was significantly lower as compared to their counterparts from WT mice. U₁-U₂: Hematoxylin and eosin staining in heart allografts obtained from C57BL/6 WT mice transplanted with BALB/c hearts and treated with low dose CTLA4-Ig and from C57BL/6 GLP-1R KO mice recipients of BALB/c hearts and treated with low dose CTLA4-Ig, (magnification 20X, and scale bar 100 μm). V₁-V₂ and W: CD8 staining in heart allografts obtained from C57BL/6 WT mice transplanted with BALB/c hearts and treated with low dose CTLA4-Ig and from C57BL/6 GLP-1R KO mice recipients of BALB/c hearts and treated with low dose CTLA4-Ig, (magnification 20X, and scale bar 100 μm); the relative quantification of CD8 infiltrating cells in both groups of transplanted mice is shown in (W). X-Z: Bargraphs depicting the quantification of respectively CD8 effector T cells as well as the significant increase in the

percentages of IL-17⁺ CD8⁺ T cells in splenocytes from both groups of transplanted mice as aforementioned. Data are representative of at least n=3 samples and are expressed as mean ± standard error of the mean (SEM). *P<0.05; **P<0.01; ***P<0.001. Data are representative of at least n=3 samples and are expressed as mean ± standard error of the mean (SEM). *P<0.05; **P<0.01; ***P<0.001.

A
| Condition | RFU (arbitrary units) |
|-----------|----------------------|
| Medium    | ~400                 |
| Exe-4     | ~600                 |
| GLP-1R-/- | ~200                 |

B1
| Condition | CD25+ FoxP3+ (%) |
|-----------|------------------|
| Medium    | ~5               |
| Exe-4     | ~12              |

B2
| Condition | CD25+ FoxP3+ (%) |
|-----------|------------------|
| Medium    | ~12              |
| Exe-4     | ~14              |

C1
| Condition | CD4+ RORγT+ (%) |
|-----------|-----------------|
| Medium    | ~25             |
| Exe-4     | ~25             |

C2
| Condition | CD8+ RORγT+ (%) |
|-----------|-----------------|
| Medium    | ~55             |
| Exe-4     | ~55             |

D
| Condition               | Concentration (pg/ml) |
|-------------------------|----------------------|
| Medium                  | ~50                  |
| BTSC cells              | ~100                 |
| GLP-1R+/+ CD3+ T cells  | ~150                 |
| GLP-1R-/- CD3+ T cells  | ~100                 |
| + weak CD3+ T cells     | ~125                 |
| + strong CD3+ T cells   | ~175                 |

E1-E2: Flow cytometry plots for FoxP3 expression (Untreated and Exe-4 conditions)

F1-F2: Flow cytometry plots for RORγT expression (Untreated and Exe-4 conditions)

G1-G2: Flow cytometry plots for Tbet expression (Untreated and Exe-4 conditions)

H1-H3: T cell proliferation assay histograms for different Teff:Treg ratios (1:1, 2:1, 4:1)

I1: GFP expression levels under different transduction conditions
I2: Protein blots for GLP-1R and GAPDH

J: Gel electrophoresis image for genotyping
Wildtype: 518 bp
Heterozygous: 518 bp and 599 bp
Mutant: 599 bp

K1: Protein expression in heart tissue (WT and KO)

L1-O2: Protein expression in spleen and thymus (WT and KO samples)

P1-P3: CD4+ cell percentages in thymus under different conditions

Q-R: Flow cytometry plots for CD3+ cells from WT and KO

S: CD28 and CD28 (Exe-4) expression levels

T1-T2: Bar charts of cell percentages under different conditions

U1-V2: Histological images of tissue in KO and WT

W-X: Bar charts quantifying histological cell populations

Abbreviations: GLP-1R, Glucagon-like peptide 1 receptor; FACS, fluorescence-activated cell sorter scan; IFN-γ, interferon gamma; FoxP3, forkhead box P3; CTV, cell trace violet; iTregs, induced T regulatory cells; Exe-4, Exendin 4/Exenatide; WT, wildtype.

Figure S5. GLP-1R signaling modulates the alloimmune response in vivo, related to Figure 5.

A: Representative zebra plot of GLP-1R expression by splenic murine CD8⁺ T lymphocytes in basal condition and after islet allotransplantation; FACS plots are associated to related isotype control.

B: Bar graph representing quantification of GLP-1R expression by spleen CD8⁺ lymphocytes in basal condition and after islet allotransplantation.

C: Representative zebra plot of GLP-1R expression by murine CD8⁺ T lymphocytes in basal condition and after islet allotransplantation under kidney capsule; the plots are associated to related isotype control.

D: Bar graph representing quantification of GLP-1R expression by CD8⁺ lymphocytes in normal kidneys and after islet allograft.

E: Islet allograft survival curves from mice treated with GLP-1R agonist Exenatide (Exe-4, dashed line), a combination of Exe-4 and Exendin 9-39 (dotted line) or saline (dashed line); statistical analysis was performed using Student's t-test with Welch's correction.

F₁–F₃: Representative hematoxylin and eosin histology staining of day-14 islet allografts from mice treated with saline, Exenatide 2 μg twice/day, or both Exenatide and Exendin 9-39 2 μg twice/day.

G: Immune infiltrate quantification after hematoxylin and eosin histology staining in islet allografts from mice treated with saline, Exenatide 2 μg twice/day, or both Exenatide and Exendin 9-39 2 μg twice/day.

H–J: Bar graph depicting the quantification of splenic CD4⁺ effector-memory, CD8⁺ effector-memory T cells or splenic CD4⁺ regulatory T cells in mice who underwent islet allograft and were treated with saline, Exenatide 2 μg twice/day, or both Exenatide and Exendin 9-39 2 μg twice/day.

K₁: Representative immunohistochemistry staining for SDF-1 kidney at baseline, (magnification: 10X, scale bar: 300 μm).

K₂: Representative H&E histology staining on kidney at baseline (magnification: 10X, scale bar: 300 μm).

L₁: Representative immunohistochemistry staining for SDF-1 on islet allograft at day 14 post-transplant; the positive immunosignal (arrows) in the islet implant area is located in the inflammatory foci (black arrows), (magnification: 20X, scale bar: 300 μm).

L₂: Representative H&E histology

staining on islet allograft at baseline and at day 14 post-transplant, the islet implant site is thickened by a collagen fiber deposition encompassing both inflammatory foci and islet epithelial cells (magnification: 10X, scale bar: 300 μm).

M: Representative FACS zebra plot of GLP-1R expression by splenic murine CD8⁺ T lymphocytes in basal condition and after heart allotransplantation; the plots are associated to related isotype control.

N: Bar graph representing quantification of GLP-1R expression by spleen CD8⁺ lymphocytes in basal condition and after heart allotransplantation.

O: Representative zebra plot of GLP-1R expression by murine heart infiltrating CD8⁺ T lymphocytes in basal condition and in heart allograft; the plots are associated to related isotype control.

P: Bar graph representing quantification of GLP-1R expression by heart infiltrating CD8⁺ lymphocytes in basal condition and in heart allograft.

Q: Heart allograft survival curves from mice treated with GLP-1R agonist Exenatide/Exendin-4 (Exe-4, dashed line), a combination of Exe-4 and Exendin 9-39 (dotted line) or saline (dashed line); statistical analysis was performed using Student's t-test with Welch's correction.

R₁-R₃: Representative hematoxylin and eosin (H&E) histology staining of day-7 heart allograft from mice treated with saline, Exenatide 2 μg twice/day, or both Exenatide and Exendin 9-39 2 μg twice/day.

S: Immune infiltrate quantification after hematoxylin and eosin histology staining in heart allografts from mice treated with saline, Exenatide 2 μg twice/day, or both Exenatide and Exendin 9-39 2 μg twice/day.

T-V: Bar graph depicting the quantification of splenic CD4⁺ effector-memory and CD8⁺ effector-memory T cells or splenic CD4⁺ regulatory T cells in mice who underwent heart allograft and were treated with saline, Exenatide 2 μg twice/day, or both Exenatide and Exendin 9-39 2 μg twice/day.

W-Y: Total/active GLP-1 and Exe-4 peripheral levels are shown in respectively, untreated, heart transplanted (syngeneic and allogeneic) and Exe-4-treated mice, at least n = 3 mice per group.

Z₁: Heart allograft survival curves from Rag1⁻/⁻ mice that received heart allograft from BALB/c mice and were adoptively transferred with either CD3⁺ T cells from GLP-1R KO mice or from

WT mice; statistical analysis was performed using Student’s t-test with Welch’s correction.

Z₂: Donor specific alloantibody levels (DSA) shown here as MFI in WT mice or from GLP-1R KO mice that received a heart allograft from BALB/c mice. Z₃: Quantitative bargraph showing the percentage of circulating T follicular helper cells were assessed on PBMCs from WT mice or from GLP-1R KO mice that received a heart allograft from BALB/c mice. Data are representative of at least n=3 samples and are expressed as mean ± standard error of the mean (SEM). *P<0.05; **P<0.01; ***P<0.001.

**Abbreviations:** GLP-1R, Glucagon-like peptide 1 receptor; FACS, fluorescence-activated cell sorter scan; Exe-4, Exenatide or exendin-4; FoxP3, forkhead box P3; WT, wild type; DSA;

donor specific alloantibody; MFI, mean fluorescence intensity; cTfh, circulating follicular helper T cells; PBMCs, peripheral blood mononuclear cells.

Figure S6. GLP-1R is expressed by human T cells, related to Figure 7. A-B: Images depicting Chromogenic in situ hybridization of GLP-1R on thymus, GLP-1R mRNA (red probe) in human thymus and spleen and co-localization with CD4 (green). C: Representative dot plots for gating strategy and GLP-1R expression by CD4⁺CD25⁺FoxP3⁺ regulatory cells. D: Quantification of flow cytometric analysis from (C) and comparison with whole CD4⁺ population. E-F: GLP-1R expression was depicted after 72 hours of stimulation with anti-CD3/CD28 Abs on dividing human CD3⁺ T cells or Cell trace Violet⁺ cells as compared to non-dividing CD3⁺ T cells; the quantification of GLP-1R expression in both sub-populations is shown in (F). G-H: GLP-1R expression was depicted after 72 hours of stimulation with anti-CD3/CD28 Abs on dividing non-dividing CD4⁺/CD8⁺ T cells, the quantification of GLP-1R expression in both sub-populations is shown in (H); experiments were performed in triplicates, and results are representative of one experiment.

A | B
--- | ---
Thymus CD4 microscopy image | Spleen CD4 microscopy image

C | D
--- | ---
Flow cytometry plots | Bar graph of CD4+ Tregs (%)

E | F
--- | ---
αCD3/CD28 stimulation assay plots | Bar graph of GLP-1R+ cells (%)

G | H
--- | ---
αCD3/CD28 stimulation assay plots | Bar graph of GLP-1R+ (%) for CD4+ and CD8+ cells

Abbreviations: GLP-1R, Glucagon-like peptide 1 receptor;

Figure 7. A₁-A₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human renal biopsies from kidney-transplanted non-rejecting cases, (magnification: 20X, scale bar: 200 μm). B₁-B₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human renal biopsies from kidney-transplanted TCMR-rejecting cases, (magnification: 10X, scale bar: 200 μm). C₁-C₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human heart biopsies from heart-transplanted non-CAV cases, (magnification: 40X, scale bar: 1 mm). D₁-D₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human heart biopsies from heart-transplanted CAV cases, (magnification: 40X, scale bar: 1mm). E₁-E₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human lungs biopsies from non-transplanted cases, (magnification: 40X, scale bar: 1mm). F₁-F₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human lungs biopsies from lung-transplanted chronic rejecting cases, (magnification: 40X, scale bar: 1mm). G₁-G₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human renal biopsies from normal kidney cases, (magnification: 20X, scale bar: 200 μm). H₁-H₃: Hematoxylin and eosin, CD3 and GLP-1R staining on human renal biopsies from antibody-mediated-rejecting cases (AMR), (magnification: 10X, scale bar: 200 μm). I-J: The quantification of CD3+/GLP-1R+ in T cell-mediated-rejecting cases (TCMR) and no-rejecting cases is shown. Data are representative of at least n=3 samples and are expressed as mean ± standard error of the mean (SEM). *P<0.05; **P<0.01; ***P<0.001.

| Lung - Chronic rejection | Lung - not rejecting | Heart - Chronic rejection (CAV) | Heart - not rejecting (NO CAV) | Kidney - AMR | Kidney - normal | Kidney - Chronic rejection (TCMR) | Kidney - not rejecting |
|-------------------------|----------------------|---------------------------------|--------------------------------|--------------|-----------------|------------------------------------|-----------------------|
| H                       | G                    | F                               | E                              | D            | C               | B                                  | A                     |
| H                       | G                    | F                               | E                              | D            | C               | B                                  | A                     |
| H                       | G                    | F                               | E                              | D            | C               | B                                  | A                     |

H&E

CD3

GLP-1R

CD3+ cells (A.U.)
Not-rejecting [small bar]
TCMR [larger bar]

GLP-1R+ cells (A.U.)
Not-rejecting [small bar]
TCMR [larger bar]

24

Abbreviations: GLP-1R, Glucagon-like peptide 1 receptor; TCMR, T cell-mediated rejection; CAV, chronic allograft vasculopathy.

| rank | Accession | Peptide |
|------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 1    | tr|H2A2P9|H2A2P9_MUHV1 gpmDB | psyt | snap [1/0] protein peptide
Small capsomere-interacting protein {ECO:0000256|HAMAP-Rule:MF_04021}; | MSTNVSSAAS GGGSSGASSG GGGGGGGGGS GG
STNVSSAASG GGSSGASSGG GGGGGGGGSG GSSK
TNVSSAASGG GSSGASSGGG GGGGGGGSGG SSKKEEE
NVSSAASGGG SSGASSGGGG GGGGGGSGGS
VSSAASGGGS SGASSGGGGG GGGGGSGGSS KKE
AASGGGSSGA SSGGGGGGGG GGSG
SGGGSSGASS GGGGGGGGGG SGGS
SGGGSSGASS GGGGGGGGGG SGGSS
SGGGSSGASS GGGGGGGGGG SGGSSKK
GGGSSGASSG GGGGGGGGGS GGSS
SSGASSGGGG GGGGGGSGGS S
ASSGGGGGGG GGGSGGSS
SGGGGGGGGG GSGGSSKKEE |
| 2    | sp|Q80U70|SUZ12_MOUSE gpmDB | psyt | snap [1/0] homo (1/1) protein peptide
Polycomb protein Suz12; Suppressor of zeste 12 protein homolog; | APQKHGGGGG GGSGPSAGSG GGG
PQKHGGGGGG GSGPSAGSGG GGFGGSAAAV
HGGGGGGGSG PSAGSGGGGF GGSAA
HGGGGGGGSG PSAGSGGGGF GGSAAAVAAA ASGGK
GGSGPSAGSG GGGFGGSAAA VAAAASGGKS GGG
GPSAGSGGGG FGGSAAAVAA AASGGKSGGG GCG
GGSAAAVAAA ASGGKSGGGG CGGGGSYSAS S
AAAASGGKSG GGGCGGGGSY
AAAASGGKSG GGGCGGGGSY SA
AAASGGKSGG GGCGGGGSYS ASSSSAAAAA AAAGAA
ASGGKSGGGG CGGGGSYS
KSGGGGCGGG GSYSASSSSA AAAAAAAGAA V |
| 3    | sp|E9Q3L2|PI4KA_MOUSE gpmDB | psyt | snap [1/0] homo (1/1) protein peptide
Phosphatidylinositol 4-kinase alpha; PI4-kinase alpha; PI4K-alpha; PtdIns-4-kinase alpha; EC 2.7.1.67 {ECO:0000250|UniProtKB:P42356}; | MAAAGARGGG GGGGGGGGGG SGSSSGSSTS RGF
AAGARGGGGG GGGGGGGGSG SSSG
AGARGGGGGG GGGGGGGSGS SSGS
AGARGGGGGG GGGGGGGSGS SSGSSTSRGF Y
GARGGGGGGG GGGGGGSGSS
ARGGGGGGGG GGGGGSGS
ARGGGGGGGG GGGGGSGSSS GSS
GGGGGGGGGG GGSGSSSGS
GGGGGGGGGG GSGSSSGS
GGGGGGGGGG SGSSSGSS |
| 4    | sp|Q7TMA2|ZN503_MOUSE gpmDB | psyt | snap [1/0] protein peptide
Zinc finger protein 503; Zinc finger protein Nolz-1; | SKHSGGGGGG GGGGGSGGGS ADPAWTSALS GNCSG
KHSGGGGGGG GGGGSGG
KHSGGGGGGG GGGGSGGGS
HSGGGGGGGG GGGSGGGSAD PAW
SGGGGGGGGG GGSGGGSADP AWTSALSGNC SGHGPG
SALSGNCSGH G
KPDPSPSSKL SSVASNGGGA GGAGNGAGGD K
EPGGGGGGGG GGGGGGGVAA EKSGFR
PEAGGGGSSK GSGGASADGV PAGLGHG |
| 5    | sp|Q8VD62|CK068_MOUSE gpmDB | psyt | snap [1/0] protein peptide
UPF0696 protein C11orf68 homolog; Basophilic leukemia-expressed protein Bles03; Protein WF-3; | MAAAAAAVAG AGRGGGGGGG GGGAAD
AAAAAVAGAG RGGGGGGGGG GAADPGQERS RAR
AAAAVAGAGR GGGGGGGGGG AADPGQER
AAAVAGAGRG GGGGGGGGGA AD
AVAGAGRGGG GGGGGGGAAD PGQERS
GRGGGGGGGG GGAADPG
GGGGGGGGGA ADP |
| 6    | sp|Q8VDI9|ALG9_MOUSE gpmDB | psyt | snap [1/0] homo (2/2) protein peptide
Alpha-1,2-mannosyltransferase ALG9 {ECO:0000305}; EC 2.4.1.259 {ECO:0000250|UniProtKB:Q9H6U8}; EC 2.4.1.261 {ECO:0000250|UniProtKB:Q9H6U8}; Dol-P-Man:Man(6)GlcNAc(2)-PP-Dol alpha-1,2-mannosyltransferase {ECO:0000305}; Dol-P-Man:Man(8)GlcNAc(2)-PP-Dol alpha-1,2-mannosyltransferase {ECO:0000305}; | RQRLKGGGGG GGGGGDAGPA AEKLEQ
QRLKGGGGGG GGGGDAGPAA EKLEQLGS
LKGGGGGGGG GGDAGPA
LKGGGGGGGG GGDAGPAAEK
LKGGGGGGGG GGDAGPAAEK LE
KGGGGGGGGG GDAGPAA |

| No. | Protein Information                                                                                | Sequence                                                                                | | | | |
| --- | ------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------- |---|---|---|---|
| 7   | sp|P25444|RS2_MOUSE gpmDB | psyt | snap [1/0] homo (9/11) protein peptide
no protein information available           | DAGAAGGPGG PGGPGLGG AAGGPGGPGG PGLGGRGGFR AGGPGGPLIP APRGTGIVSA PVPK                                                            |
| 8   | tr|A0A2Z4EYB3|A0A2Z4EYB3_MUHV1 gpmDB | psyt | snap [1/0] protein peptide
no protein information available            | MSTNVSSAAS GGGSSGGGSSGMSTNVSSAAS GGGSSGGGSSGASSGGGSSS KKSGGGSSGGGS SGASSGGGSS SGASSGGGSSS                                       |
| 9   | tr|B1AVK5|B1AVK5_MOUSE gpmDB | psyt | snap [1/0] homo (1/1) protein peptide
no protein information available         | GDKGPIGVPG FVGISGIPG GLPGLPGEKG HDGPIGDGGK VGITGDPGFP GSPGLGTHGT PGASITGVPGP AGLPGPKGER                                        |
| 10  | sp|D3YWQ0|DGKI_MOUSE gpmDB | psyt | snap [1/0] homo (2/2) protein peptide
no protein information available           | LSPTGLCSGT TSASFAAPT GLCSGTTSAS FAAAGAVAMN PSSSAGEERG ATTSASFAAA GAVAMNPSSSA GEERGATGGSSC CLGAEGGAD PRGAGAAAAA ALEEPAAAGQKEK    |
| 11  | sp|O35295|PURB_MOUSE gpmDB | psyt | snap [1/0] protein peptide
no protein information available                      | MADGDSGSER GGGGGGGGGP GGFQPAPAD GDSGSERGGG GGGGGGGPGG FQPAPRGGDG DSDSGSERGG GGGGGGGPGGF QPAPRGGSER GGGGGGGPGG FQPAPRGGSERGGG  |
| 12  | sp|Q8BLX7|COGA1_MOUSE gpmDB | psyt | snap [1/0] homo (1/3) protein peptide
no protein information available          | ESNVTLGPSG LKGGKGERGL TGPSGPKGA IGPMGPPGAG VSGPPGQKGL TGLTGDKGEP GPPGQPGPPG PQGPPGYGK                                          |
| 13  | sp|P09084|PAX1_MOUSE gpmDB | psyt | snap [1/0] homo (0/1) protein peptide
no protein information available           | VSWERAAAAA AGPGAGGALG SGSLRVSSR AAAAAAGPGA GGALGSGSLR GPRLARALPL CLSGGGGARA LP                                                  |
| 14  | sp|Q9Z2E1|MBD2_MOUSE gpmDB | psyt | snap [1/0] protein peptide
no protein information available                      | PEQEEGESAA GGSGAGGDSA IEQGGQGSAL APSPGRGRGR PQSGGSGLG GDGGGGAGG CGGSGGGVAP RR                                                  |
| 15  | tr|A0A1B0GRC0|A0A1B0GRC0_MOUSE gpmDB | psyt | snap [1/0] homo (1/2) protein peptide
no protein information available | PGPYDVIKGE PGLPGPEGPP GLKGLQGEG PPGLKGLQGQ QGVTGSVGLP GPPGVPGFDG APGQK                                                        |
| 16  | (H) sp|P02463|CO4A1_MOUSE gpmDB | psyt | snap [1/0] homo (1/2) protein peptide
no protein information available      | GVPGIPGGQQ GVTGSVGLPG PPGVPGFDG APGQKHTSAG AEGSGQALAS PGSCL EEFR                                                                  |
| 17  | sp|Q8VHW2|CCG8_MOUSE gpmDB | psyt | snap [1/0] homo (2/2) protein peptide
no protein information available           | AGGGAGGSGG SGPSAILRGS VAAGLASAG GGGGSGAGVA YGPAPPAPAA PAPTGTLSK                                                                 |
| 18  | sp|Q8C9W3|ATS2_MOUSE gpmDB | psyt | snap [1/0] homo (1/1) protein peptide
no protein information available           | PPASVRLVAA TEPPGGPPGQ GAERILAVPV                                                                                |
| 19  | tr|A0A140LI36|A0A140LI36_MOUSE gpmDB | psyt | snap [1/0] homo (0/3) protein peptide
no protein information available | SEADINAEKW DAGKGGKEKD KTAKSPIDL ISLTTATLDK SQEELAIN EGVAKKGKLP AALR                                                            |
| 20  | sp|Q91YE5|BAZ2A_MOUSE gpmDB | psyt | snap [1/0] homo (9/9) protein peptide
no protein information available          | LPPAPAASGL KPSPSSGEGL YTNGSPMNFL PLEGNPVISA LDCPALSNA NAFSLEETT GGAVAVSGSGD VLK                                                 |

Table S2. Characteristics of kidney-transplanted patients, related to Figure S7 and to STAR Methods.

|                                 | Normal
1 | Normal
2 | Normal
3 | AMR
1 | AMR
2              | AMR
3 | TCMR
1 | TCMR
2 | TCMR
3 |
| ------------------------------- | ------------ | ------------ | ------------ | --------- | ---------------------- | --------- | ---------- | ---------- | ---------- |
| **General Characteristics**     |              |              |              |           |                        |           |            |            |            |
| Age (years)                     | 29           | 52           | 31           | 48        | 69                     | 60        | 53         | 35         | 70         |
| Transplant Age (years)          | 1.3          | 0.1          | 2.2          | 13.9      | 10.3                   | 9.2       | 1.2        | 0.2        | 0.4        |
| Sex (M / F)                     | F            | F            | M            | F         | M                      | M         | M          | F          | F          |
| Hypertension (Yes / No)         | Yes          | No           | No           | Yes       | No                     | Yes       | No         | Yes        | No         |
| Diabetes mellitus (Yes / No)    | No           | No           | No           | No        | Yes                    | Yes       | No         | No         | Yes        |
| **Biochemical Characteristics** |              |              |              |           |                        |           |            |            |            |
| sCr (mg/dl)                     | 2            | 1.54         | 2.36         | 1.91      | 1.24                   | 1.29      | 1.7        | 2.97       | 1.4        |
| eGFR (ml/min/1.73 m²)           | 33           | 38.4         | 35.4         | 30.4      | 58.9                   | 59.9      | 45         | 19.6       | 38         |
| Urea (mmol/l)                   | 95           | 57           | 51           | 90        | 67                     | 39        | 56         | 109        | 54         |
| Glucose (mg/dl)                 | 81           | 86           | 82           | 118       | 161                    | 187       | 83         | 77         | 128        |
| HbA1C (mmol/mol, %)             | 40 (5.8)     | 35 (5.3)     | 38 (5.6)     | 31 (5)    | 47 (6.5)               | 64 (8)    | 45 (6.3)   | 42 (6)     | 53 (7)     |
| WBC (cells/μl)                  | 4950         | 7300         | 8600         | 6700      | 3300                   | 10000     | 6400       | 7900       | 5500       |
| N% / L%                         | 40 / 48      | 89 / 9       | 25 / 68      | 57 / 30   | 53 / 31                | 69 / 22   | 57 / 25    | 76 / 14    | 72 / 10    |
| Hb (g/dl)                       | 9.8          | 10.6         | 11.7         | 11.6      | 12.8                   | 15.3      | 11.8       | 9.9        | 11.7       |
| CRP (mg/l)                      | 0.06         | 0.11         | 0.42         | 0.05      | 0.38                   | 0.21      | 0.16       | 0.08       | 0.63       |
| Tacrolimus levels (ng/ml)       | 6.9          | 9            | 5.9          | 5.2       | 4.6                    | 6.9       | 5.9        | 11.2       | 7.2        |
| DSA (MFI)                       | /            | /            | /            | DQ7 7235  | DQ8 13600, DR53 23000  | DQ4 4000  | Neg        | Neg        | Neg        |
| **Urinary Characteristics**     |              |              |              |           |                        |           |            |            |            |
| Proteinuria (g/24h)             | 0.05         | 0.1          | 0.1          | 0.8       | 0.27                   | 1.9       | 0.06       | 0.39       | 0.9        |
| Urinary Sediment                | Neg          | Low MH       | Neg          | Neg       | Low MH                 | Neg       | Neg        | Low MH     | Neg        |
| Urine Culture                   | Neg          | Neg          | Neg          | Neg       | Neg                    | Neg       | Neg        | Neg        | Neg        |
| **Immunosuppressive therapy**   |              |              |              |           |                        |           |            |            |            |
| Tacrolimus (mg/die)             | 2 + 1        | 4 + 4        | 4 + 5        | 2 + 2     | 1.5 + 1                | 2 + 1     | 5          | 7          | 2.5        |

**Footsteps:** AMR – Antibody Mediated Rejection, TCMR – T-Cell Mediated Rejection, sCr – Serum Creatinine, eGFR – estimated Glomerular Filtration Rate, HbA1C – Glycated Hemoglobin, WBC – White Blood Cells, N% - Percentage of Neutrophils, L% - Percentage of Leukocytes, Hb – Hemoglobin, CRP – C-Reactive Protein, DSA – Donor Specific Antibodies, MH – Microhematuria, MFI – Mean Fluorescent Intensity.

Abbreviations. CAV, chronic allograft vasculopathy; M, male; F, female; ATG, thymoglobulin.