Distinct metabolic profiles of circulating plasmacytoid dendritic cells in systemic sclerosis patients stratified by clinical phenotypes

Background: Plasmacytoid dendri Ɵc cells (pDCs) play a key role in systemic sclerosis (SSc) pathophysiology. However, despite the recognised importance of metabolic reprogramming for pDC func Ɵon, their metabolic profile in SSc remains to be elucidated. Thus, our study aimed to invesƟgate the role of pDC metabolism in SSc.

Peripheral blood mononuclear cells (PBMCs) were isolated from the blood of healthy donors and SSc paƟents. SCENITH™, a single-cell flow cytometry-based method, was applied to infer the metabolic profile of circulaƟng pDCs from paƟents with SSc. pDCs (CD304+ Lin-) at steady- state or s Ɵmulated with CpG A were analysed. Toll -like receptor (TLR)9 acƟvaƟon was confirmed by ribosomal protein S6 phosphorylaƟon.

CirculaƟng pDCs from 10 healthy donors and 14 SSc pa Ɵents were analysed. pDCs from an Ɵ-centromere an Ɵbody-posiƟve (ACA +) pa Ɵents displayed higher mitochondrial dependence and lower glycoly Ɵc capacity than those from an Ɵ-topoisomerase I an Ɵbody- posiƟve (ATA+) paƟents. Furthermore, cells from both ACA + paƟents and limited cutaneous SSc (lcSSc) paƟents showed a stronger response towards TLR9 acƟvaƟon than cells from ATA+, anƟ-RNA polymerase III anƟbody-posiƟve (ARA+) or diffuse cutaneous SSc (dcSSc) paƟents.

Our results show that pDCs from ACA + paƟents rely more on oxida Ɵve phosphorylaƟon (OXPHOS) and are more responsive to external sƟmuli, suggesƟng that pDCs from ATA+ paƟents may be more acƟvated or exhausted. These findings point for the possible contribuƟon of pDC metabolism to SSc clinical course, unveiling new poten Ɵal targets for therapeuƟc approaches in SSc.

Systemic Sclerosis, Scleroderma, Immunometabolism, DendriƟc cells, Plasmacytoid DendriƟc Cells 1. IntroducƟon Systemic sclerosis (SSc) is a connecƟve Ɵssue disease characterised by immune dysregulaƟon, vasculopathy and fibrosis of different organs [1]. SSc can be classified in two main subsets, based on the extent of skin involvement. In limited cutaneous SSc (lcSSc), fibrosis primarily affects the skin distal to the elbows or knees, whereas in diffuse cutaneous SSc (dcSSc), the involvement extends to the trunk [2,3] . AddiƟonally, most SSc pa Ɵents exhibit at least one specific serum autoan Ɵbody, namely an Ɵ-centromere, an Ɵ-topoisomerase I and an Ɵ-RNA polymerase III an Ɵbodies (ACA, ATA, ARA respec Ɵvely), which are associated with disease presentaƟon and progression [2,4]. ACA is typically associated with lcSSc, while ATA and ARA are more commonly found in dcSSc cases. Moreover, ATA + paƟents are more prone to .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint developing lung fibrosis, leading to a less favourable prognosis, whereas ARA + paƟents oŌ en present renal crisis [2]. Plasmacytoid dendriƟc cells (pDCs) are professional type I interferon (IFN) producers involved in anƟ-viral responses, but also highly relevant for autoimmunity onset and flairs, parƟcularly in diseases correlated with high IFN signature, such as SSc [5]. It has been reported that pDC numbers are increased in the skin and lung Ɵssues of pa Ɵents with SSc and decreased in circulaƟon compared with healthy donors [6,7] . Also, pDC deple Ɵon in mice models of SSc ameliorates fibrosis and inflamma Ɵon, further underlining their par ƟcipaƟon in disease progression [6,8] . pDCs can promote B cell ac ƟvaƟon and autoan Ɵbody produc Ɵon and secrete high levels of type I IFN and chemokine (C-X-C moƟf) ligand 4 (CXCL4), contribuƟng to inflammaƟon and fibrosis [7,9–11] . This situa Ɵon is correlated with a dysregula Ɵon of the unfolded protein response (UPR) pathway inositol-requiring transmembrane kinase/endoribonuclease 1-alpha (IRE1α), that potenƟates the tricarboxylic acid (TCA) cycle and was shown to contribute to the type I IFN signature observed in SSc paƟents [12]. Several immune cells, such as macrophages, dendri Ɵc cells (DCs), B cells and T cells, rely on metabolic reprogramming for differenƟaƟon and funcƟon [13]. Metabolic reprogramming of pDCs depends on the species and s Ɵmuli. Toll-like receptors (TLR)7/8-acƟvated human pDCs were shown to upregulate oxida Ɵve phosphoryla Ɵon (OXPHOS) dependently on glutaminolysis [14]. On the other hand, human pDCs s Ɵmulated with a TLR7 agonist, such as influenza A virus (IAV) or rhinovirus (RV), display increased glycolysis while OXPHOS was not impacted [15]. Other studies using mouse pDCs demonstrated that type I IFN derived from TLR9 acƟvaƟon contributes to fa Ʃ y acid oxidaƟon (FAO) and OXPHOS [16]. Most recently, it was proposed that chronic acƟvaƟon of pDCs in SSc could be due to dysregulaƟon of metabolic pathways [12]. Nevertheless, the metabolic profile of these cells and its contribu Ɵon to the disease's progression is unknown. Thus, this work aimed to elucidate the metabolic profile of pDCs in SSc and invesƟgate its possible contribuƟon to disease course and prognosis. For that, we used SCENITH™, a single-cell technique that allows for the analysis of the metabolic profile of rare cell populaƟons by flow cytometry, by assessing translaƟon inhibiƟon [17]. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint 2. Methods 2.1. PaƟent inclusion and clinical data Adult pa Ɵents with SSc fulfilling the 2013 American College of Rheumatology/ European League Against RheumaƟsm classificaƟon criteria were included [4]. PaƟents with overlapping syndromes were not considered. A ll par Ɵcipants signed an informed consent form before inclusion and clinical data collected were anonymised. This study was approved by the Ethics CommiƩ ee of Centro Hospitalar do Baixo Vouga (now ULS-RA) (Reference 44-069-2021). Demographic, clinical and laboratory data were extracted from pa Ɵents’ medical records. Demographic informaƟon included gender, birth date, tobacco and alcohol use. Disease onset was defined as the Ɵme of the first occurrence of a non -Raynaud’s symptom of SSc. PaƟents were categorised as lcSSc or dcSSc using LeRoy’s criteria [18]. Clinical data included SSc-related symptoms and signs (Raynaud’s phenomenon, digital ulcers, telangiectasia, puffy hands, sclerodactyly, calcinosis), modified Rodnan skin score (mRSS), and organ involvement. We used consensus definiƟons to characterise each major organ involvement of SSc, which were established in earlier studies [19]. We also included the nailfold videocapillaroscopy (NVC) paƩ ern, the presence of comorbidi Ɵes (arterial hypertension, diabetes mellitus, dyslipidaemia, and depression) and the ong oing treatments (glucocor Ɵcoids, immunomodulators, and vasodilators). An Ɵnuclear autoan Ɵbodies (ANAs) were detected with an indirect immunofluorescence test (IIFT) on human epithelial cells (Hep- 2) and an Ɵ– extractable nuclear anƟgen (ENA) analysis using the commercially available line immunoblot assay [EUROLINE Systemic Sclerosis (Nucleoli) Profile (IgG); Euroimmun, Lübeck, GER]. 2.2. Cell isolaƟon Whole blood (20 mL) was collected in S- MonoveƩ e® Lithium Heparin (Sarstedt, Nümbrecht, GER) tubes, maintained at room temperature (RT) and processed within 1 hour of venepuncture. Following blood centrifuga Ɵon at 400 xg at RT for 10 minutes and plasma recovery, peripheral blood mononucleated cells (PBMCs) were isolated by density gradient centrifugaƟon. Briefly, blood was diluted twice in PBS (Gibco, Thermo Fisher Scien Ɵfic, Waltham, MA, USA), overlaid onto Ficoll-Paque Plus (CyƟva, Marlborough, MA, USA) and cells were separated by centrifugaƟon at 400 xg for 10 minutes at 4 °C in a swinging bucket rotor without brake. The mononuclear cell layer was transferred into a new tube, washed twice with PBS and finally with RPMI 1640 medium with 2 mM L-glutamine (Gibco). .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint 2.3. Cell acƟvaƟon, SCENITH™ and pDC staining To evaluate the metabolic profile of pDCs, we employed the flow cytometry based SCENITH™ method, which relies on the impact of metabolic pathway inhibi Ɵon on protein synthesis levels to infer ATP and GTP availability [17]. SCENITH™ protocol was adapted from its previous descripƟon [17]. A scheme with the key steps of the protocol is presented in Figure 1. IniƟally, 1.5x106 PBMCs were seeded in 170 µL RPMI 1640 with 2 mM L-glutamine (Gibco) supplemented with 10% heat-inacƟvated foetal bovine serum (FBS; Sigma -Aldrich, St. Louis, MO, USA) and 1% Penicillin-Streptomycin (Gibco) in a round- shaped boƩ om 96-well plate in the absence or presence of CpG A (3 µM; InvivoGen, San Diego, CA, USA) for 3 hours. A Ō er acƟvaƟon, cells were treated for 40 minutes with vehicle control (C; DMSO), 2-deoxy-glucose (2-DG; 100 mM), oligomycin (O; 1 µM), a combina Ɵon of 2-DG and O (DGO), and puromycin (10 µg/mL). As a negaƟve control and 15 minutes before puromycin treatment, harringtonine (H) was added (2 µg/mL). A Ō er two washing steps with ice -cold FACS buffer (2% FBS, 2 µM EDTA, PBS) and before surface staining, cells were incubated for 15 minutes at 4 °C in the dark with a combina Ɵon of Human TruStain FcX Fc Receptor Blocking Solu Ɵon (BioLegend, San Diego, CA, USA) and Live/Dead™ (Invitrogen, Thermo Fisher Scien Ɵfic). Surface staining with primary conjugated anƟbodies was performed for 25 minutes at 4 °C in the dark. AŌ er washing with FACS buffer, cells were fixed and permeabilised using Foxp3 TranscripƟon Factor Staining Buffer Set (Invitrogen), according to the manufacturer’s instrucƟons. Cells were incubated for 10 minutes at RT w ith intracellular blocking solu Ɵon [Foxp3 Permeabiliza Ɵon buffer (Invitrogen) with 20% FBS], and puromycin intracellular staining was performed for 1 hour at 4 °C. AŌ er two washing steps with permeabiliza Ɵon buffer, cells were resuspended in FACS buffer. The kit with SCENITH™ reagents [ inhibitors, puromycin and an Ɵ-puromycin anƟbody) was from www.scenith.com. InformaƟon regarding the used an Ɵbodies is shown in Supplementary Table S1. Data were acquired using BD Accuri C6 (BD Biosciences, San Jose, CA, USA). At least 300 CD304+ Lin- events were acquired per condi Ɵon. Data were analysed using FlowJo ™ v10.8.1 SoŌ ware (BD Life Sciences, Franklin Lakes, NJ, USA) and were compensated using single stains with UltraComp eBeads™ Compensa Ɵon Beads ( ref. 01-2222- 41, Invitrogen). The ga Ɵng strategy is shown in Supplementary Figure S1. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Figure 1. Scheme representing the key steps of the methods used. PBMCs isolated from the blood of HCs and SSc patients were seeded in 96-well plates and treated with CpG A for 3 hours, before 40 minute incubation with the SCENITH™ drugs – control (C), 2-deoxy-glucose (2-DG), oligomycin (O), harringtonine (H) and puromycin. Finally, stainings were performed and cells were analysed by flow cytometry. Glucose dependence, mitochondrial dependence, glycolyƟc capacity and faƩ y acid oxidaƟon (FAO)/ amino acid oxida Ɵon (AAO) capacity were calculated as detailed below , using the median fluorescence intensiƟes (MFI) of anƟ-puro-fluorochrome obtained upon treatment. Glucose dependence = 100 ൬ C – 2DG C – DGO൰ Mitochondrial dependence = 100 ൬ C – O C – DGO൰ GlycolyƟc capacity = 100 – Mitochondrial dependence FAO/AAO capacity = 100 – Glucose dependence Glucose and mitochondrial dependences give the propor Ɵon of transla Ɵon dependent on glucose oxidaƟon or OXPHOS, respecƟvely [17]. GlycolyƟc capacity represents the maximum translaƟon sustainability under mitochondrial respira Ɵon inhibi Ɵon, while FAO and AAO capacity represents cell’s ability to use fa Ʃ y acids and amino acids as energy source when glucose oxidaƟon is inhibited [17]. 2.4. p-S6 staining PBMCs were seeded, treated with CpG A and their surface stained as described for the SCENITH™ protocol. Cells were then stained for the intracellular phosphorylated form of ribosomal protein S6. InformaƟon about the used anƟbodies is in Supplementary Table S1. 2.5. StaƟsƟcal analysis .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint StaƟsƟcal analyses were performed using GraphPad Prism So Ō ware version 9.0.0 (GraphPad SoŌ ware, Inc., La Jolla, CA, USA). Data are presented as median and interquarƟle range (IQR). The Shapiro-Wilk test was used to assess data normality. The most appropriate staƟsƟcal test was then chosen according to each data set, as indicated in figure legends. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. 3. Results 3.1. Study cohort characterisaƟon Fourteen SSc paƟents and ten healthy controls (HCs) were enrolled in this study (Table 1), with median ages of 56.5 (interquar Ɵle range, IQR 52.5 -61.8) and 49 (IQR 35.8-53.0) years, respecƟvely. Most were women (78.6% of SSc pa Ɵents and 90% of HC). Median disease duraƟon was 90 months (IQR 45-120). Eight paƟents (57.1%) presented lcSSc, and six (42.9%) presented dcSSc. Nine paƟents (69.2%) had gastrointesƟnal (GI) involvement (100% upper GI tract), and six (46.2%) presented inters ƟƟ al lung disease (ILD). No pa Ɵents with pulmonary arterial hypertension (PAH) or renal or cardiac involvement were included. Six paƟents (42.9%) were posiƟve for ATA, four (28.6%) for ACA, and four (28.6%) for ARA. None of the pa Ɵents was posiƟve for more than one SSc-specific autoanƟbody. Table 1. ParƟ cipant demographics, clinical characterisƟ cs, and current therapies. CharacterisƟ c SSc, n=14 HCs, n=10 Gender (%) Male 3 (21.4) 1 (10) Female 11 (78.6) 9 (90) Age (years) 56.5 (52.5-61.8) 49 (35.8-53.0) Limited cutaneous SSc (%) 8 (57.1) - Diffuse cutaneous SSc (%) 6 (42.9) - Disease duraƟon (months) 90 (45-120) - mRSS 11 (8-15) - Presence of autoanƟbodies ATA (%) 6 (42.9) - ACA (%) 4 (28.6) - ARA (%) 4 (28.6) Organ complicaƟons GI involvement (%) 9 (69.2) - ILD (%) 6 (46.2) - PAH (%) 0 - Cardiac involvement 0 - .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Current therapies Prednisolone (%) 4 (30.8) - Methotrexate (%) 4 (30.8) - Mycophenolate MofeƟl (%) 5 (38.5) - Nintedanib (%) 2 (15.4) - Calcium antagonist (%) (100) - Median and IQR are reported unless otherwise stated. HC: healthy control; mRSS: modified Rodnan skin score; ATA: anƟ-topoisomerase I anƟ body; ACA: anƟ -centromere anƟbody; ARA: anƟ -RNA polymerase III anƟbody; GI: gastrointesƟnal; ILD: intersƟƟ al lung disease; PAH: pulmonary arterial hypertension. 3.2. The percentage of pDCs in circulaƟon varies with disease duraƟon and ANA Ɵtre Treatments were performed on the whole PBMC populaƟon, and pDCs were idenƟfied by flow cytometry as posiƟve for the pDC marker CD304 (also known as BDCA4) and negaƟve for CD3, CD14, CD16, CD19, CD20, CD34 and CD56 (Lin -) ( Figure 2A , ga Ɵng strategy presented in Supplementary Figure S1A). It was confirmed that CD304 + cells are also posiƟve for the pDC markers CD123 and HLA-DR, while events posiƟve for these pDC markers are also Lin- (Figure S1B, C). Figure 2. The percentage of circulating pDCs in SSc patients changes with progression of the disease. (A) Identification of CD304+ Lin- pDCs by flow cytometry. (B-G) The percentage of pDCs was obtained by flow cytometry analysis and comparisons were performed between patient groups. Data are expressed as median and IQR and each dot represents data from one donor. Unpaired t test or one- way ANOVA followed by Tukey’s multiple comparisons test. *p< 0.05. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint No staƟsƟcally significant differences were found in the percentage of pDCs in circulaƟon from paƟents with lcSSc or dcSSc (Figure 2B) and with or without ILD or GI involvement (Figure 2C, D). Nevertheless, paƟents diagnosed for at least ten years showed higher levels of pDCs in circulaƟon ( Figure 2E ). Also, pa Ɵents with higher ANA Ɵtre (1/1280) exhibited a reduced percentage of pDCs among PBMCs ( Figure 2F ), regardless of the subtype of auto anƟbody present (Figure 2G). 3.3. pDCs present a similar metabolic profile in SSc and HCs InhibiƟon of glycolysis and OXPHOS by 2 -deoxy-glucose (2-DG) and oligomycin (O), respecƟvely, led to a reducƟon in translaƟon to levels similar to harringtonine (H), a protein synthesis inhibitor ( Figure 3A , B). This shows that pDCs are suscep Ɵble to metabolic modulaƟon and rely on both glycolysis and OXPHOS for protein synthesis, measured by puromycilaƟon detecƟon and used as a read -out for ATP and GTP availability. Under basal condiƟons, pDCs from HCs and SSc pa Ɵents showed similar transla Ɵon and S6 phosphorylaƟon levels (Figure 3C, D). As expected, TLR9 acƟvaƟon by CpG A led to increased levels of phosphorylated S6 in both HCs and SSc pa Ɵents, even though staƟsƟcal significance is only observed for the la Ʃ er ( Figure 3D ). However, treatment with CpG A did not affect protein synthesis on pDCs, nor their response to metabolic modula Ɵon ( Figure 3A-C ). Moreover, the metabolic profile of pD Cs was not affected by TLR9 ac ƟvaƟon and seemed comparable under both SSc and healthy condiƟons (Figure 3E, F). Given the lack of differences upon TLR9 sƟmulaƟon, the follow-up analysis on the metabolic profile of pDCs was focused on cells in basal condiƟons. 3.4. pDCs from ACA and ATA-posiƟve paƟents have different metabolic profiles During our analysis we noted potenƟal differences among groups of SSc paƟents and decided to segregate pa Ɵents according to their clinical characteris Ɵcs. pDCs from lcSSc pa Ɵents display higher upregulaƟon of S6 phosphorylaƟon and protein synthesis aŌ er treatment with CpG A, in comparison with cells from dcSSc pa Ɵents, suggesƟng higher sensi Ɵvity to TLR9 sƟmulaƟon ( Figure 4A , B). There was also a significant difference in the basal levels of translaƟon associated with GI involvement but not with ILD, disease dura Ɵon or ANA Ɵtre (InformaƟon about the used an Ɵbodies is in Supplementary Figure S2). However, at basal .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint condiƟons, no differences were found in the metabolic profile of cells isolated from lcSSc or dcSSc (Figure 4C), and no correlaƟon with either ANA Ɵtre, disease duraƟon, GI involvement or ILD was found (Supplementary Figure S3). Figure 3. pDCs from HCs and SSc paƟ ents have no major differences in their metabolic profile. (A, B) TranslaƟon levels in pDCs aŌ er treatment with 2-deoxy-glucose (2-DG), oligomycin (O), harringtonine (H) and CpG A. Representa Ɵve histograms for cells not TLR9 -acƟvated. (C) TranslaƟon and (D) S6 phosphorylaƟon (MFI) levels. (E, F) SCENITH™ metabolic profiles. Data expressed as median and IQR; dots represent independent donors. Kruskal- Wallis test followed by Dunnet’s mul Ɵple comparisons test (A, B), one-way ANOVA followed by Sidak’s mulƟple comparisons test (C, D) and two-way ANOVA followed by Sidak’s mulƟple comparisons test (E, F) were used. ***p<0.001; ****p<0.0001. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Figure 4. pDCs from lcSSc paƟ ents are more reacƟ ve to CpG A than cells from dsSSc. (A) p-S6 levels and (B) translaƟon levels at basal and TLR9 -acƟvated condi Ɵons were assessed in pDC from SSc paƟents by flow cytometry. (C) Metabolic profiles. Dash line corresponds to 1. Data are expressed as median and IQR and each dot represents data from one donor. StaƟsƟcal significance was tested with unpaired t test or Mann-Witney test. *p<0.05. However, pDCs from ACA + paƟents exhibited higher mitochondrial dependence and lower glycolyƟc capacity compared to cells from ATA + paƟents (Figure 5A). Moreover, pDCs from ACA+ paƟents showed an upregulaƟon of translaƟon levels aŌ er TLR9 sƟmulaƟon, compared to ATA+ and ARA + paƟents (Figure 5B). There were no sta ƟsƟcally significant differences on levels of p-S6, but there was a tendency for pDCs from ARA + paƟents to display higher p -S6 levels at basal condiƟons (Figure 5C). .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Figure 5. pDCs from ACA + paƟ ents are more dependent on mitochondrial metabolism and have lower glycoly Ɵ c capacity than cells from ATA + paƟ ents. (A) SCENITH™ metabolic profiles, (B) translaƟon levels, and (C) p-S6 levels were determined by flow cytometry for pDCs from paƟents with different pa Ʃ erns of SSc autoan Ɵbodies. Data are expressed as median and IQR and each dot represents data from one donor. Kruskal-Wallis test followed by Dunnet’s mul Ɵple comparisons test was used for (A), one-way ANOVA followed by Tukey’s mulƟple comparisons test for (B) and one-way ANOVA followed by Sidak’s mulƟple comparisons test for (C). *p< 0.05, **p<0.01. 4. Discussion The key role of pDCs in SSc pathphysiology has been highlighted by others [7,10–12], primarily using mouse models of scleroderma that revealed an improvement in fibrosis upon pDC depleƟon [6,8]. Furthermore, pDCs are hyperacƟvated in pa Ɵents with SSc, contribu Ɵng to the characterisƟc type I IFN signature [7,9,10]. As with other immune cells, pDCs heavily rely on metabolic reprogramming for their differen ƟaƟon and func Ɵon [20,21]. A reduced expression of phosphoglycerate dehydrogenase (PHGDH) in pDCs isolated from the blood of SSc paƟents, and the downregula Ɵon of interferon-sƟmulated genes (ISGs) expression upon TCA cycle inhibiƟon were recently reported [12]. Nevertheless, the metabolic profile of pDCs in SSc has not been characterised. In this study, we used SCENITH™, a single- cell resoluƟon

that employs flow cytometry analysis of protein synthesis to infer the metabolic profile of cells [17] . The reliance of cells on glucose oxida Ɵon and OXPHO S for the .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint maintenance of protein synthesis levels is given by glucose and mitochondrial dependences, respecƟvely. Simultaneously, the ability of cells to sustain mRNA translaƟon under condiƟons of mitochondrial respiraƟon or glucose oxida Ɵon inhibiƟon is reflected in the glycoly Ɵc and FAO/AAO capaciƟes, respecƟvely. Due to the importance of cell acƟvaƟon in this context, we analysed both cells at basal condi Ɵons and pre -treated with CpG A, a TLR9 agonist. Cell acƟvaƟon was monitored by phosphorylaƟon of S6, which occurs upon TLR9 ac ƟvaƟon [22]. Treatments were performed in the whole PBMC popula Ɵon, and the analysis focused on CD304+ Lin- cells. The idenƟficaƟon of pDCs by flow cytometry as CD304 + Lin- (CD3, CD14, CD16, CD19, CD20, CD34 and CD56) can be viewed as a possible limitaƟon of this work. Even though we confirmed that these cells were also posi Ɵve for other pDC markers (CD123 and HLA -DR), we cannot certainly exclude a low percentage contaminaƟon by other cells. Moreover, these findings are in circulaƟng pDCs, which may not be the cell popula Ɵon with the highest influence on the disease course. Infiltra Ɵng pDCs likely have a more prominent role in SSc pathogenesis. However, as SSc is a systemic disease, it is also possible that the profile of circula Ɵng pDCs reflects what happens in the affected Ɵssues. Finally, our analyses were performed with a low number of cells and pa Ɵents, due to the rarity of this cell popula Ɵon and disease. However, despite the low number of pa Ɵents included, the sex and age distribu Ɵon of the pa Ɵents included reflects the Portuguese SSc paƟents’ demographics [23]. PaƟents diagnosed for less than ten years at the Ɵme of blood collec Ɵon displayed lower amounts of pDCs in circula Ɵon than those d iagnosed for longer. Typically, pDCs circulate through the blood and are recruited to target Ɵssues upon infecƟon or inflammaƟon [24]. SSc is characterised by an ini Ɵal vascular injury and early inflamma Ɵon phase that contribute to fibrosis development [25,26]. This difference in pDC levels may be due to the early recruitment of pDCs to the inflamed Ɵssues, a phenomenon that could decrease as the disease progresses. Also, paƟents with higher levels of ANAs in circula Ɵon displayed less pDC abundance within PBMCs. ANA Ɵtres are suggested to be associated with disease progression, and in some cases, high Ɵtres are correlated with the disease outcome [27]. Higher ANA Ɵtres may indicate a more robust autoimmune response and inflamma Ɵon, possibly jus Ɵfying these results [28,29]. However, this is a debated theory. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint The acƟvaƟon state of pDCs was evaluated by analysing p-S6 levels and monitoring protein synthesis, which is reported to increase during immune cell ac ƟvaƟon to sustain cellular funcƟon [30–32]. Globally, pDCs from HCs and SSc pa Ɵents seemed to have the same basal acƟvaƟon state since no differences in p-S6 and translaƟon levels were found. However, within the pa Ɵent groups, differences were iden Ɵfied among pa Ɵents with GI involvement, displaying lower translaƟon levels compared to paƟents without this involvement. The exact changes that occur in the GI tract are not fully characterised in SSc [33], making it difficult to find a jus ƟficaƟon for this result. However, it may be speculated that there might be sequestraƟon of cells with higher translaƟon rates in the affected Ɵssues and/or dispariƟes in the microbiome. In response to TLR9 ac ƟvaƟon, pDCs from ACA + paƟents upregulated their translaƟon levels, contrary to what happens with ATA+ or ARA+ paƟents. ATA and ARA are more common in paƟents with dcSSc, while ACA is oŌ en associated with lcSSc. A higher increase in translaƟon upon TLR9 acƟvaƟon was also observed in lcSSc, compared to dcSSc. Although not staƟsƟcally significant, there was a tendency for pDCs from dcSSc and paƟents posiƟve for ATA or ARA to present increased p-S6 at basal condiƟons. Therefore, this suggests that pDCs from dcSSc and ATA+ and ARA+ paƟents have basal acƟvaƟon, which might limit the effect of CpG A. Even though the treatment with CpG A induced S6 phosphorylaƟon, it did not upregulate translaƟon, nor impact the metabolic profile of these cells. Other studies have observed an impact of TLR9 acƟvaƟon in the metabolism of pDCs [16,34], but longer exposure Ɵmes to the agonist were used. As men Ɵoned above, a more recent study exploring the metabolism of pDCs from SSc pa Ɵents used a similar Ɵmepoint and analysed the expression of an enzyme involved in the biosynthesis of serine [12]. Therefore, differences from what is reported in the literature may be due to differences in the agonist and sƟmulaƟon Ɵmes used. InteresƟngly, although pDCs from HCs and SSc pa Ɵents displayed similar metabolic profiles, being dependent on both glycolysis and OXPHOS, varia Ɵons were found among pa Ɵents posiƟve for the different ANAs subtypes. While there were no differences in the acƟvaƟon or metabolic state of pDCs from ATA + and ARA + paƟents, pDCs from ACA + paƟents presented higher mitochondrial dependence and lower glycolyƟc capacity than those from ATA+ paƟents. This suggests that pDCs from ACA + paƟents rely more on OXPHOS for energy producƟon. On the other hand, cells from ATA+ paƟents tended to be more dependent on glycolysis. Usually, acƟvated immune cells and highly proliferaƟng cells shiŌ their metabolism to glycolysis, while .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint OXPHOS is preferred at the resolu Ɵon phase [35]. Thus, the metabolic profile results are concordant with p-S6 readouts and suggest that pDCs from ATA+ paƟents are more acƟvated, relying on glycolysis for energy produc Ɵon. These results are in accordance with the observaƟons for pDCs from lcSSc (which are more commonly ACA +) compared to dcSSc paƟents. On the other hand, although both ATA and ARA are associated with dcSSc, the clinical course differs. While ATA + paƟents are more prone to develop ILD, ARA is associated with scleroderma renal crisis and the co-occurrence of cancer [2,27]. The interacƟon between autoan Ɵbodies and soluble an Ɵgens can form immune complexes (ICs), promoƟng cell acƟvaƟon. ParƟcularly, ICs containing anƟbodies specific for SSc (SSc-ICs) were described to promote the ac ƟvaƟon of skin fibroblasts and endo thelial cells from HCs, having a pro-inflammatory and pro- fibroƟc effect [36,37]. Furthermore, the mixture of sera from SSc paƟents with necroƟc/apoptoƟc material induces pDC acƟvaƟon, apparently by SSc- ICs [38] . Even though not every pa Ɵent’s serum can form ICs capable of inducing an IFN response, this phenomenon was observed with samples from both lcSSc and dcSSc [38]. In these studies, the autoanƟbody composiƟon analyses did not always include the ones present in this work, and the formaƟon of interferogenic ICs in ATA+ sera is controversial [38,39]. Thus, it would be interesƟng to clarify if the differences in the metabolic profile of pDCs and their acƟvaƟon status observed with our data are related to the acƟvaƟon of pDCs by ICs. The presence of these different autoan Ɵbodies is linked with disease progression, and ATA + paƟents tend to have a less favourable prognosis compared to those posi Ɵve for ACA, partly due to the elevated risk of developing ILD, a common cause of death. Crucially, we found that pDCs from ACA+ paƟents had reduced glycolyƟc capacity, associated with a stronger response to in vitro TLR9 ac ƟvaƟon. Together, these results suggest that pDCs more dependent on mitochondrial respiraƟon and less on glycolysis are associated with reduced basal ac ƟvaƟon and a beƩ er prognosis. Thus, we believe that our findings pave the way for understanding the potenƟal involvement of pDC metabolism in the severity and clinical progression of SSc. Future tesƟng of the impact of blocking glycolysis while promoƟng mitochondrial respiraƟon on pDC may contribute to defining new possible therapeuƟc strategies for SSc. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint

We thank all the volunteers, especially the pa Ɵents, and the health professionals (Anabela Barcelos, Maria do Céu Morais, Graça Costa, António José Oliveira) involved in this study. CRediT authorship contribu Ɵon statement : Beatriz H. Ferreira: ConceptualizaƟon, Data curaƟon, Formal analysis, Inves ƟgaƟon, Methodology, VisualizaƟon, WriƟng – original d raŌ , WriƟng – review and e diƟng. Carolina Mazeda: ConceptualizaƟon, Data cura Ɵon, InvesƟgaƟon, Methodology, Resources, WriƟng – review and ediƟng. Eduardo Dourado: Data curaƟon, Method ology, WriƟng – review and e diƟng. João L. Simões: InvesƟgaƟon, Methodology, Resources, WriƟng – review and e diƟng. Ana R. Prata: Data cura Ɵon, Methodology, WriƟng – review and e diƟng. Rafael J. Argüello: Methodology, Resources, WriƟng – review and ediƟng. Iola F. Duarte: Funding acquisiƟon, Methodology, Supervision, WriƟng – review and ediƟng. Philippe Pierre: Funding acquisiƟon, Methodology, Supervision, WriƟng – review and e diƟng. Catarina R. Almeida: ConceptualizaƟon, Funding acquisi Ɵon, InvesƟgaƟon, Methodology, Project administra Ɵon, Supervision, Wri Ɵng – original d raŌ , WriƟng – review and ediƟng. Funding: This work was supported by the World Scleroderma Founda Ɵon and Edith Busch SƟŌ ung (the EBF and WSF Research Grant Programme 2022 -2023). Work developed within the scope of iBiMED – InsƟtute of Biomedicine(UIDB/04501/2020 and UIDP/04501/2020) and CICECO – Aveiro InsƟtute of Materials UIDB/50011/2020 (DOI 10.54499/UIDB/50011/2020), UIDP/50011/2020 (DOI 10.54499/UIDP/50011/2020) & LA/P/0006/2020 (DOI 10.54499/LA/P/0006/2020) and the project with the reference 2022.03217.PTDC (DOI 10.54499/2022.03217.PTDC), financially supported by naƟonal funds (OE), through Fundação para a Ciência e a Tecnologia (FCT)/MCTES. FCT is acknowledged for the individual grant to B.H.F. (SFRH/BD/144706/2019; DOI 10.54499/SFRH/BD/144706/2019) and the research contract under the ScienƟfic Employment SƟmulus to I.F.D. (CEECIND/02387/2018). Conflict of interest statement: No compeƟng interests. Data availability statement: Data are available upon reasonable request. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint

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AnƟ body ConcentraƟ on Reference Source AnƟ-human CD304 PE (Clone: 12C2) 2.5 µL/condiƟon 354504 BioLegend AnƟ-human CD123 FITC (Clone: 6H6) 1.25 µL/condiƟon 306013 BioLegend AnƟ-human HLA-DR Alexa Fluor 647 (Clone: L243) 2.5 µL/condiƟon 307621 BioLegend AnƟ-human CD3 PerCP (Clone: SK7) 2.5 µL/condiƟon 344814 BioLegend AnƟ-human CD14 PerCP (Clone: M5E2) 2.5 µL/condiƟon 301848 BioLegend AnƟ-human CD16 PerCP (Clone 3G8) 1.25 µL/condiƟon 302030 BioLegend AnƟ-human CD19 PerCP (Clone: SJ25C) 1.25 µL/condiƟon 363014 BioLegend AnƟ-human CD20 PerCP (Clone: 2H7) 2.5 µL/condiƟon 302324 BioLegend AnƟ-human CD34 PerCP-Cy 5.5 (Clone: 561) 5 µL/condiƟon 343612 BioLegend AnƟ-human CD56 BB700 (Clone: NCAM16.2) 1.25 µL/condiƟon 566573 BD Biosciences AnƟ-puromycin Alexa Fluor 647 (Clone: R4743L-E8) 1:100 RRID: AB_2827926 [17] AnƟ-phospho-S6 ribosomal protein (Ser235/236) 1:50 2211 Cell Signaling Technology AnƟ-rabbit IgG Alexa Fluor 647 1:5000 A-21245 Invitrogen .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Supplementary Figure S1. Ga Ɵ ng strategy used. (A) Ga Ɵng strategy for iden ƟficaƟon of pDCs as CD304+ Lin - (CD3 - CD14 - CD16- CD19 - CD20 - CD34 - CD56 -). Only live cells acquired during stable flux were included in our analyses. (B, C) ConfirmaƟon that gaƟng on CD304+ Lin- (shown in yellow) allows idenƟficaƟon of pDCs (which are also CD123+ and HLA-DR+). .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Supplementary Figure S2. S6 phosphoryla Ɵ on and transla Ɵ on levels of pDCs from SSc pa Ɵ ents according to their clinical data. (A) GastrointesƟnal (GI) involvement, (B) intersƟƟ al lung disease (ILD), (C) disease duraƟon or (D) ANA Ɵtre. Grey line corresponds to 1. Data are expressed as median and IQR and each dot represents data from one donor. StaƟsƟcal significance was tested with unpaired t test or Mann-Witney test. *p<0.05. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint Supplementary Figure S3. Metabolic profiles of pDC from SSc pa Ɵ ents accordingly to their clinical data. (A) ANA Ɵter, (B) disease duraƟon, (C) gastrointesƟnal (GI) involvement, or (D) intersƟƟ al lung disease (ILD). Data are expressed as median and IQR and each dot represents data from one donor. StaƟsƟcal significance was tested with unpaired t test or Mann-Witney test. .CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for thisthis version posted December 2, 2024. ; https://doi.org/10.1101/2024.11.27.625448doi: bioRxiv preprint