Peripheral blood from 15 untreated patients with cutaneous leishmaniasis (CL) attended at the University Hospital (HUCAM) of Universidade Federal do Espírito Santo, Brazil, were investigated in this study. They consisted of eight males and seven females with illness duration ranging from 30 to 120 days, lesion sizes ranging from 200–550 mm² and age of 37 ± 13.6 years. The diagnosis of CL was based on clinical and laboratory criteria and all patients in this study tested positive for the PCR/restriction fragment length polymorphism of L. braziliensis and reported no prior infections or treatments. The control group (HC) consisted of 15 healthy age (41.4 ± 11.9) and gender-matched individuals with no history of leishmaniasis. All participants (patients and healthy volunteers) had seronegative testing for HIV, HBV and HCV infections, and had no history of chemotherapy, radiotherapy or treatment with immunosuppressive medications within the last 6 months. The patient and control samples were obtained before the COVID-19 outbreak. Patients provided written informed consent, and study procedures were performed in accordance with the principles of the Declaration of Helsinki. This study was registered at HUCAM ethical committee reference number 735.274.

PBMC from HC and CL patients were isolated by centrifuging whole blood through a Ficoll-Hypaque (GE Healthcare) gradient followed by hemocytometry to determine the absolute number of viable then cryopreserved. Cells from both controls and patients were thawed in RPMI complete medium supplemented with 10% of fetal calf serum. Viability and recovery were measured using trypan blue dye exclusion.

For phenotypic and functional analysis, at least 10⁶ cells were stained washed and subsequently stained at 4°C for 20 min with the combination of surface antibodies. For intracellular analysis of cytokine secretion, cells were cultured at 37°C in the presence of monensin (used according to the manufacturer’s indication, BioLegend) and brefeldin A (5 mg/ml) (Sigma-Aldrich), added for the last 6 and 4 h of stimulation, respectively. Then, cells were fixed and permeabilized using the Cytofix/Cytoperm kit (BD Pharmingen), stained with NIR viability stain (Invitrogen) followed by cytokine intracellular antibodies on ice for 30 min. Data from 50.000 events obtained within CD3⁺ cells were acquired in a Fortessa X-20 cytometer (BD Biosciences) and analysed using FlowJo software (Treestar). ICRs gates were based on pooled fluorescence minus one control samples and applied identically across all samples. Gate strategy and used antibodies are described in the Supplementary Figure 1 and Table 1 , respectively.

PBMCs were thawed, resuspended in complete media and incubated overnight at 37°C. The following day, cells were incubated with 10 μg/ml each of anti-PD-L1 (29E.2A3.C6) and anti-PD-L2 (24F.10C12.G12, both from Biolegend) antibodies as described previously (24) prior cell activation with anti-CD3 (OKT3, 0.5 μg/ml, Biolegend) or L. braziliensis promastigote antigens (LbAg, 10 μg/ml). After activation, cells were culture for 72 h. 10 μg/ml each of IgG2a (Mg2a-53) and IgG2b (MPC-11) isotype controls (Abcam) were used as control.

Cell culture were stimulated with 10 μg/ml of L. braziliensis promastigote antigens (LbAg) or 0.5 μg/ml plate-coated anti-CD3 (OKT3) and 5 ng/ml rhIL-2, with or without anti-PDL1/2 or isotype control antibodies. Culture supernatants were collected at 72h for the measurement of IFN-γ, TNF-α, and IL-10 by Cytokine Bead Array (CBA) (BD Biosciences) according to the manufacturer’s protocol.

Stimulated PBMC were cultured in the presence of PD-1 blocking or isotype control antibodies and rhIL-2 for 72 h as previously described (24). The proliferation was accessed by intracellular staining for the cell cycle related nuclear antigen Ki67 Alexa Fluor 647 (BD Bioscience) that was performed with Foxp3 Staining Buffer Set (Miltenyi Biotec) and analyzed by flow cytometric analysis.

The RNA-Seq data was obtained from a previous study (29), which is available at the Sequence Read Archive (www.ncbi.nlm.nih.gov). Data as accessed through project accession reference #PRJNA307599, where paired-end reads (100 bp) were obtained through Illumina HiSeq 1500 platform. Samples analysed consisted of skin biopsies from uninfected controls (from endemic areas) (n= 10) and skin biopsies collected from patients infected with Leishmania braziliensis (n= 25). Initially, samples were trimmed using Trimmomatic (v. 0.39) to remove sequence adapters and filter low-quality (threshold of 25) bases at the start or end of reads. Samples were then aligned to the human reference genome (hg38/GRCh38 release 99) obtained from ENSEMBL (https://www.ensembl.org/) using Salmon (v 0.12.0) using the selective alignment option (–validateMappings) and correction for GC content bias (–gcBias). Transcript abundance at the gene-level was then calculated using tximport to obtain the counts table. Non-expressed, weakly expressed and non-protein code genes were removed prior to subsequent analyses, resulting in a count table of 17.668 genes. DESeq2, a package from Bioconductor, was used to define differentially expressed genes (30), considering genes with Benjamini-Hochberg p-adjusted value less than 0.05 as significant. The Variance Stabilizing Transformation (vst), available in the DESeq2 package, was used for visualization and clustering purposes. The function plotPCA, also available on the DESeq2 package, was used for the Principal Component Analysis. The ComplexHeatmap package (31) ggplot2 package (32) were used to generate the heatmap and plots, respectively. The heatmap was constructed to show the relative gene expression, where the vst normalized values were mean-centered across samples.

t-SNE is a non-linear dimensionality reduction method that optimally places cells with similar expression levels near to each other and cells with dissimilar expression levels further apart. Unbiased representations of multi-parameter flow cytometry data were generated using the t-distributed stochastic neighbour embedding (tSNE) algorithm. The R package “Rtsne” available on CRAN (github.com/jkrijthe/Rtsne) was used to perform the Barnes Hut implementation of tSNE on flow cytometry data. FlowJo software was used to export events of interest (in fcs format) for each sample. After using the Bioconductor “flowCore” R package to import.fcs file data and the Logicle transform to scale the data similarly to that displayed in FlowJo. 10,000 events from each sample analyzed in parallel were merged and the relevant fluorescent parameters were used.

Punch biopsies (8 mm in diameter) from the border of lesional skin were obtained from cutaneous leishmaniasis patients. Control skin punch biopsy specimens from healthy volunteers were also obtained. Biopsy specimens were frozen in OCT compound (Sakura, Alphen aan den Riji, The Netherlands). Six-micrometer sections were longitudinally sectioned to expose all skin layers and placed in poly-L-lysine coated slides (Star Frost^®). Tissues were then fixed in acetone and ethanol and stored in -80°C until use.

Frozen sections from HC skin and CL lesions were blocked with 1% bovine serum albumin (BSA) solution and incubated with primary antibodies (described in Supplementary Table 1 ). Staining was detected using Novolink™ Polymer Detection System Kit (Leica, RE7150-K) according to the manufacturer instructions. Slides were then dehydrated with xylol and ethanol and mounted with Entellan^® (MERK, 107960).

Immunofluorescence staining was performed using optimal dilutions of primary antibodies for 18 h at 4°C, followed by an appropriate fluorochrome-conjugated secondary antibody (described in Supplementary Table 1 ) incubation and mounting with Flouroshield Mounting Medium with DAPI (ABCAM, ab104139). Three images of the papillary and reticular dermis were captured at 200x magnification using fluorescence microscopy (Leica DMi8, Wetzlar, Germany). The number of positively stained cells was manually counted using computer-assisted image analysis (National Institutes of Health Image Software ImageJ 1.52j; https://imagej.nih.gov/ij/) and expressed as a percentage.

GraphPad Prism (version 7) was used to perform statistical analysis. Data distribution was verified using the Shapiro-Wilk test. Statistical significance was evaluated using the paired Student t-test. Mann-Whitney with Welch correction or Kruskal-Wallis test was performed for all continuous and nonparametric variables. Differences were considered significant when p was <0.05.

First, we analysed RNA-Seq data from a previous study where skin biopsies from uninfected controls were compared to biopsies collected from the border of lesions from patients infected with Leishmania braziliensis (29). We investigated transcriptional signatures for inhibitory receptors and their ligands in the skin during the active disease. Transcriptional profiles of skin from lesions were very different from healthy skin from control subjects, as demonstrated by principal component analysis (PCA) ( Figure 1A ). We found 9,955 genes identified as differentially expressed between the two groups that included inhibitory checkpoint receptors and their ligands that were uniquely associated with patient skin lesions ( Figures 1B, C ). Many genes associated with cellular exhaustion were increased in lesional skin and this included PD-1 (28.8 fold), TIM-3 (16.4 fold), CTLA-4 (40.9 fold), PDL-1 (32.0 fold), and PDL-2 (13.8 fold) ( Figures 1C, D ).

The expression of ICRs and senescence-associated receptors have been associated with several cell populations in inflammatory and non-inflammatory contexts. We next evaluated the expression of PD-1 and their ligands as well as TIM-3, CTLA-4, CD57, and KLRG1 (Killer cell lectin-like receptor G1) expression on lesional site. Histopathological analysis by H&E staining showed epidermal hyperplasia with a dense and diffuse inflammatory cell infiltrate involving the junction of the epidermis and dermis up to hypodermis, consisting mainly of lymphocytes, macrophages and plasma cells ( Figures 2A, B ). Immunohistochemical analysis revealed that this intense cell infiltration had increased expression of PD-1, TIM-3, and CTLA-4 compared to control skin ( Figures 2C–H ), supporting the RNAseq data. We also found that both CD4⁺ and CD8⁺ T cells were increased in the lesional inflammatory infiltrates compared to control skin ( Supplementary Figure 2A ). Furthermore, significantly greater proportions of these cells in the skin lesions of CL patients expressed PD-1, TIM-3, CTLA-4, CD57 and KLRG1 compared to the skin of healthy controls ( Figures 2I–R and Supplementary Figure 2B ). Moreover, there was increased expression of both PD-1 ligands (PDL-1 and PDL-2) ( Figures 2S–V ) that was found on lesional macrophages (CD68⁺) ( Figures 2W–Y and Supplementary Figure 2C ) and also neutrophils and fibroblasts (data not shown).

Circulating T cells are recruited to the skin during CL (33, 34). We next investigated the heterogeneity of ICRs on circulating T cell compartments. Both CD4⁺ and CD8⁺ T cells from CL patients exhibited elevated frequencies of cells that expressed PD-1, TIM-3, and CTLA-4 individually or combined ( Figures 3A, B ). We confirmed this by the tSNE algorithm that arbitrarily identified two different clusters of healthy control (Green) and cutaneous leishmaniasis patients (Red) groups ( Figure 3C ). In addition, the expression intensities and distribution of markers in each cluster were remarkably associated with both CD4⁺ and CD8⁺ T cells in CL patients.

Taken together these data suggest that T cells of CL patients have increased expression of ICRs that is not observed in healthy individuals. Thus, we next investigated whether there was an association between the level of individual ICRS on T cells in the circulation and in the skin lesions in individuals. We found a strong correlation between PD-1 expression in both compartments that was not observed with either TIM-3 or CTLA-4 ( Figures 3D, E ). This suggested that PD-1 may regulate T cell activity in both tissue compartments of CL patients to the same extent.

PD-1- expressing T cells from CL patients are less responsive to both polyclonal and Ag-specific stimulation. We next investigated whether blockade of PD-1 signaling of circulating CD4⁺ and CD8⁺ T cells from CL patients, using antibodies to its ligands PDL-1 and PDL-2 blockade could enhance specific T cell functions linked to a leishmanicidal response after stimulation with L. braziliensis antigen (LbAg). The addition of anti- PDL1/2 significantly enhanced the proliferative capacity of CD4⁺ and CD8⁺ T cells, compared to cells that were activated in the absences of the blocking antibodies ( Figures 4A, B ). We also performed the same blocking experiment by stimulating T cells from both groups (HC and CL) with anti-CD3 and confirmed that blocking PD-1 signaling enhanced the proliferative capacity of T circulating cells from CL patients ( Supplementary Figure 3 ).

We next investigated whether blocking PD-1 signaling affected cytokine production of CL patients after LbAg stimulation. We found that after blockade, the frequency of both IFN-γ TNF-α producing cells were significantly increased in CD4⁺ and CD8⁺ T cell compartments ( Figures 4C, D ). Interestingly, analysis of these cytokines in supernatants of cultures after LbAg stimulation in the presence or absence of PD-1 blockade demonstrated that only levels of IFN-γ production was significantly enhanced ( Figure 4E ). We also did not observe any effect of PD-1 blockade on the production of IL-10 in the same experiments ( Figure 4E ). The dominant cytokine response after PD-1 blockade was the enhancement of IFN-γ production and the ratio of IFN-γ to TNF-α and IFN-γ to IL-10 were both increased significantly ( Figure 4F ). As IFN-γ production has a role in protective immune responses while TNF-α secretion has an immunopathogenic consequences in this disease (5), the inhibition of PD-1 signaling would shift cytokine production towards immune protection in CL.

We showed previously that the size of skin lesions in CL correlated with the proportion of senescent CD8⁺CD45RA⁺CD27^- T cells in the circulation (34). We therefore investigated whether PD-1 expressing CD8⁺ T cells in peripheral blood were also associated with the cutaneous pathology in the patients. The relative expression of CD45RA and CD27 defined 4 different subsets of CD8⁺ T cells in both healthy controls and CL patients ( Figure 5A ). We investigated PD-1 expression within each of the 4 subsets and showed that PD-1 was significantly increased in all these population compared to healthy controls ( Figure 5B ). However, in both patients and controls, the senescent (CD45RA⁺CD27^-) population expressed significantly less PD-1 compared to central memory (CM) or effector memory (EM) CD8⁺ T cells ( Figure 5B bottom panel). In addition, we found increased frequencies of CM and EM subsets, but not senescent cells expressing PD-1 and CLA ( Figure 5C ). This suggest that a proportion of PD-1⁺ cells in the skin ( Figure 2 ) may be derived from circulating populations. The proportions of total circulating CD4⁺PD1⁺ (data not shown) and CD8⁺PD1⁺ T cells and their subsets do not correlate with lesion size ( Figure 5D ). This suggests that despite the accumulation of PD1-expressing T cells in the circulation and in the skin, these cells may not be associated with the skin pathology that occurs in patients.