Microbiota-dependent T-cell response to α-synuclein-derived antigens triggers the development of hypersensitivity and neuroinflammation associated with Parkinson's Disease

doi:10.21203/rs.3.rs-4707767/v1

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Microbiota-dependent T-cell response to α-synuclein-derived antigens triggers the development of hypersensitivity and neuroinflammation associated with Parkinson's Disease

https://doi.org/10.21203/rs.3.rs-4707767/v1

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Background. Previous evidence has shown that both the T-cell response and the microbiota play fundamental roles on the development of Parkinson's Disease (PD), which involves motor impairment and chronic pain. PD physiopathology involves the generation of pathogenic forms of α-synuclein (aSyn), which are associated with abnormal post-translational modifications and aggregation, and represent a source of neoantigens able to trigger an autoreactive T-cell response. Nevertheless, the relationship between the microbiota and the development of this autoreactive T-cell response in PD remains unexplored. Here we studied whether the dysbiosis of the gut microbiota and the T-cell response to aSyn-derived antigens associated to PD are functionally connected.

Methods. We used a transgenic mouse model that involves the overexpression of human a-Syn (SNCA mice). To deplete the microbiota, we used a wide-spectrum antibiotic cocktail. To deplete lymphocytes we generated SNCA mice deficient on recombination-activating gen 1 or deficient on membrane-bound IgM. Microbiome was analysed by sequencing the variable V4 region of the 16S rRNA gene. Co-culture experiments of lymphocytes isolated from cervical or mesenteric lymph nodes and dendritic cells loaded with synthetic peptides were conducted to determine adaptive responses to phosphorylates and nitrated forms of aSyn.

Results. We observed that the depletion of either gut microbiota or T-cells, but not B-cells, abrogated the development of motor deficits, sensory disturbances, neuroinflammation, and gut inflammation. Furthermore, SNCA mice developed an autoreactive T-cell response to a-synuclein-derived neo-antigens accumulated in the gut mucosa, a process that was triggered by the microbiota dysbiosis.

Conclusions. Our findings indicate that the development of both motor and non-motor manifestations as well as neuroinflammation in PD involves a T-cell mediated autoimmune response, which is triggered by changes in the gut microbiota that induce increased intestinal barrier permeability.

Parkinson’s disease

microbiota

T cells

α-synuclein

pain

neuroinflammation

SNCA mice

B cells

dysbiosis

gut-brain axis

Parkinson's disease (PD) is a neurodegenerative disorder classically defined by motor symptoms such as tremor, rigidity, bradykinesia, and postural abnormalities. This motor damage has been correlated with the progressive loss of dopaminergic neurons in the nigrostriatal pathway. Although motor symptomatology is considered a key clinical feature of the disease and constitutes a diagnostic criterion, some non-motor symptoms are highly frequent in PD, including intestinal disturbances and chronic pain. In fact, chronic pain is as frequent as 68–85% in PD patients [1, 2], and is twice more common in PD patients than in individuals without PD even after adjustment for osteoarticular comorbidities [3]. Chronic pain in PD can be musculoskeletal (dystonia, joint pain, spams) or neuropathic. Neuropathic pain in PD has been described to be of central origin but also in many cases due to peripheral neuropathy. In a recent cohort study, 40% of PD patients presented peripheral neuropathy, with a predominance of small fibre neuropathy (SFN) [4, 5]. SFN is characterised by loss of sensory intraepidermal nerve fibres, which commonly produces neuropathic pain. In PD, deposits of phosphorylated α-synuclein (αSyn) have been shown to occur together with a decrease in intraepidermal nerve fibre density. On the other hand, intestinal constipation represents prodromal symptomatology affecting 50–80% of PD patients [6, 7]. Indeed, growing evidence points to that PD begins with early symptoms in the gut, such as inflammation and impaired motility, and then the disease spreads to the brain [8].

PD is characterised by the progressive deposit of inclusions called Lewy Bodies (LB) which are mainly constituted by αSyn, a neuronal protein that is normally associated with the transport of presynaptic vesicles [9]. In PD, αSyn undergoes pathological post-translational modifications, including nitrations, phosphorylations, and aggregation [10, 11]. Importantly, it has been shown that these pathological modifications constitute neo-antigens recognised by the immune system in PD patients and in animal models [10, 12]. Emerging evidence has shown that this autoimmune response is driven by both CD4⁺ and CD8⁺ T-cells [10], which play a critical role favouring chronic neuroinflammation and the consequent dopaminergic neurodegeneration in the substantia nigra (SN) [13, 14]. Despite T-cells play a critical role in the development of neuroinflammation, neurodegeneration and motor impairment, the involvement of B-cells is still controversial. In this regard, many studies have found alterations in peripheral blood B-cells subsets in PD patients, thus suggesting that these lymphocytes might play a role in the pathophysiology of PD. In addition, several works have found auto-antibodies in PD patients, mostly specific to αSyn [15]. However, a recent study conducted in a mouse model of PD induced by the stereotaxic delivery of AAV-A53T found that B-cell deficiency does not protect from dopaminergic neurodegeneration [16]. Moreover, the adoptive transfer of functional B-cells into immunodeficient recipient mice did not alter the development of the disease induced by preformed αSyn fibrils (PFF) treatment [17].

Several works conducted in patients and animal models have consistently shown that PD involves a dysbiosis of the gut microbiota, which might be implicated in the pathogenesis of the disease. Indeed, this dysbiosis has been associated with enhanced intestinal epithelial barrier permeability [18, 19]. This enhanced permeability can trigger intestinal inflammation promoting local oxidative stress in the gut mucosa, favoring αSyn aggregation in enteric neurons [20, 21]. According to Braak hypothesis [22], these pathological αSyn forms might spread from the gut to the brain stem through the vagus nerve, and then triggering neuroinflammation [8]. Accordingly, it has been shown that through the production of bacterial metabolites, the microbiota regulates the proper maturation of microglia. Consequently, significant changes in the microbiota might trigger neuroinflammation [23]. Furthermore, experiments conducted in a mouse model of PD have shown that neuroinflammation, synucleinopathy and motor impairment depend on the presence of gut microbiota, as the disease development was dampened on germ free (GF) animals or those treated with broad-spectrum antibiotic cocktail (ABX) [24]. Moreover, the transfer of faecal microbiota from PD patients into these GF mice rescued the disease development with high severity, whilst the transfer of faecal microbiota from healthy controls into GF mice induced just a mild disease development [24]. Besides, cumulative evidence points towards the fact that pain might be also regulated by gut microbiota in both homeostatic and pathological onsets [25, 26].

Of note, dysbiosis might be associated with changes in the levels of several soluble mediators and metabolites derived from gut microbiota such as dopamine, glutamate, γ-aminobutyric acid, serotonin, short-chain fatty acids (SCFA) and bile acids derivates. Importantly, all these molecules may stimulate their receptors expressed on local enteric neurons and immune cells, thus affecting the initial pathogenesis of the disease [8, 27, 28]. Thus, the microbiota and its dysbiosis might not only communicate with immune system but also modulate its effector actions.

Since PD development depends on the microbiota [24] and on the autoreactive immune response [10], and microbiota might modulate immunity, here we addressed the question of whether the autoimmune response to αSyn is dependent on the microbiota. Moreover we analysed the relative contribution of T-cells and B-cells to the development of the disease and whether the development of pain is dependent on this autoimmune response to αSyn. Using a PD mouse model induced by the overexpression of hαSyn (SNCA mice), we found that the depletion of either gut microbiota or T-cells, but not B-cells, abrogated the development of motor deficits, sensory disturbances, neuroinflammation, and gut inflammation. Moreover, our results show the development of a T-cell response specific to hαSyn-derived neo-antigens generated in the colonic mucosa, a process dependent of the microbiota. We also characterised the gut dysbiosis and confirmed an increased permeability of the intestinal barrier in SNCA mice. Thus, our findings indicate that the autoreactive immune response to αSyn-derived antigens is responsible not only of the motor impairment but also of pain, is mediated by T-cells, but not B-cells, and is triggered by the microbiota in the colonic mucosa.

Mice and treatments

Transgenic male mice that overexpress ~ 4-fold levels of hαSyn over endogenous mouse αSyn levels (C57BL/6N-Tg(Thy1-SNCA)15Mjff/J line 15, here called SNCA), were purchased from The Jackson Laboratories (Bar Harbor, ME). Wild-type mice (C57BL/6J strain, here called WT), mice deficient in the recombination activating gene 1 (B6.129S7-Rag1^tm1Mom/J strain, here called Rag1^−/−) and mice deficient in membrane-bound IgM (B6.129S2-Ighm^tm1Cgn/J strain, here called µMT) were obtained from The Jackson Laboratories. SNCA/Rag1^−/− mice, which are devoid of T and B lymphocytes, were obtained by crossing SNCA with Rag1^−/− mice. SNCA/µMT mice, which are deficient in B lymphocytes, were obtained by crossing SNCA mice with µMT mice. All mouse strains were in the C57/BL6 genetic background and were kept in specific pathogens free (SPF) conditions. ABX treated animals received an antibiotic cocktail that included ampicillin (1 g/L), vancomycin (0.5 g/L), neomycin (0.5 g/L), gentamicin (100 mg/L), and erythromycin (10 mg/L) in the drinking water beginning at week 6 of age [24] until week 20 of age. Microbial sterility was confirmed by 16S rRNA PCR from stool-derived DNA (Fig. S1).

Hindlimb clasping reflex

The animals were gently lifted upwards by the midsection of the tail and were observed for ~ 5–10 s. Animals were assigned a score of 0, 1, 2, or 3 based on the extent to which the hindlimbs contracted medially, as described before [24]. A score of 0 was assigned to those animals that did not show the hindlimb reflex. A score of 1 was assigned to animals that held one hind limb inward for the duration of the restraint or if both paws exhibited a partial inward grasp. A score of 2 was assigned if both legs were crossed inwards during most of the observation time, but still exhibited some flexibility. A score of 3 was assigned if the animals showed complete paralysis of the hindlimbs that immediately contracted inward and showed no signs of flexibility.

Hargreaves test

Thermal sensitivity was assessed by Hargreaves assay (also called Plantar Test) using a Hargreaves Apparatus (Ugo Basile, Cat# 37370). The animals were placed in a transparent box with a dry glass floor and allowed to acclimate for 1 h for each experiment. In this assay, the plantar surface of the right hind paw was heated by an infrared source, and the time elapsed before the mouse lifted the paw (latency) was automatically recorded. The infrared strength used was 40. A total of three measurements with intervals of at least 5 min were taken for each hindpaw, and the average of these three measurements was used for analysis. To prevent thermal injury, an automatic shutoff time of 21.1 sec was set.

Von Frey test

Using von Frey filaments through the up-down method previously described [29]. Briefly, mice were placed in individual acrylic cages on a wire mesh surface and allowed to habituate for up to 1h until major grooming and exploration activities ceased. The von Frey filaments were applied perpendicularly to the plantar surface of the hind paw in an ascending mode with an interval of 5 min between each filament. A response was considered positive if the animal exhibited any nociceptive behaviours, including brisk paw withdrawal, licking, or shaking of the paw, either during the application of the stimulus or immediately after the filament was removed. The first filament that evoked at least one response was assigned as the mechanical withdrawal threshold. The 50% paw withdrawal threshold (the force that elicited a paw withdrawal 50% of the time) for “Up-And-Down” method was calculated using the equation previously proposed [30].

16S rRNA PCR

To confirm microbiota depletion upon ABX treatment, stool samples were collected and stored at -80ºC until processing. Total DNA was extracted using the “GenEluteTM Stool DNA Isolation kit” (Sigma-Aldrich). The conserved region of the 16S rRNA (1500 pb) was amplified by polymerase chain reaction (PCR). Universal 27F and 1492R primer [31] were used at a concentration of 10 mM (sequence details in table S1). We used 30 PCR cycles as follows: initial denaturation of 5 min at 95ºC, denaturation of 30 sec at 94ºC, annealing 30 sec at 58ºC, an extension of 40 sec at 72ºC, and a final extension of 10 min at 72ºC.

Tissue processing

Animals were deeply anesthetised with sevoflurane (Baxter) in two steps, first with a sevoflurane chamber (10 mg/mL) and then by inhalation of sevoflurane (500 mg/mL). By transcardial perfusion, filtered PBS (0.45 µm pore, TCL Group) was delivered at a flow of 10 mL/min for 5 min using a peristaltic pump (Model 7557-12, Cole-Parmer) [32]. The colon, brain, skin, mesenteric lymph nodes (MLN) and cervical lymph nodes (CLN) were removed from each animal. When extracted from the animal, the colon length was measured as the distance between the cecum and the distal end of the colon. The brain, colonic tissue and skin of plantar region were fixed in 4% PFA (Sigma Aldrich) at pH 7.4, dehydrated in a 30% (m/v) sucrose solution (Merk) and preserved in cryoprotection medium [64.25% (v/v) PBS, 2.0% (v/v) DMSO (Merk) and 20% (v/v) glycerin (Merk)] until processing. After dehydration, skin samples were mounted in O.C.T. compound (Sakura Finetek USA, Inc.). When indicated, colonic tissue was embedded in paraffin instead fixed with PFA 4% (see section 2.12). All samples were stored at − 80ºC. MLN and CLN were received in PBS and rapidly processed for coculture with dendritic cells (DCs).

Ex vivo colon slices culture and Cytometric bead array

A colon explant (1 cm²) was cultured in 1 mL IMDM medium (Gibco) for 24 h at 37ºC and 5% CO₂. Culture supernatant was collected and stored at − 80ºC until further analysis by CBA. Cytokine production was analysed using the Mouse Th1/Th2/Th17 Cytokine Kit following the manufacturer’s instructions (BD Biosciences; Cat# 560485). Data was acquired with a FACSCanto II (BD) and results were analysed with FACSDiva (BD) and FlowJo software (Tree Star, Ashlan, OR, USA).

Generation of DCs

Bone marrow-derived DCs from 8-weeks-old WT mice were prepared as previously described [33]. Briefly, bone marrow progenitors were received in red cell lysing buffer ACK (Ammonium Chloride 0.15 M; Potassium bicarbonate 0.01 M; Disodium EDTA 0.1 mM; pH 7.2–7.4) and then were differentiated into DCs using RPMI 1640 medium (Gibco) containing 10% FBS, 2 mM L-Glutamine, 100 U/mL Penicillin, 100 µg/mL Streptomycin and 50 µM β-mercaptoethanol and supplemented with 10 ng/mL recombinant mouse GM-CSF (PeproTech, Rocky Hill, NJ) for 6 days. On day 5 differentiated DCs were loaded with 10 µg of full-length recombinant hαSyn or with 3 µg of hαSyn_{111 − 140} containing all three tyrosine nitrated (3NYhαSyn; Genescript) for 18 h, washed, and used for further experiments. hαSyn and 3NYhαSyn sequences are detailed in Table S1. The full-lenght recombinant hαSyn was produced as described [34] and kindly donated by Dr. Alejandro Rojas, Laboratorio de Biotecnología Médica, Universidad Austral de Chile.

In vitro coculture of DCs and lymph nodes

MLN and CLN were mechanically disrupted and received in PBS, centrifuged, and resuspended in RPMI 1640 medium (Gibco) supplemented with 5% heat-inactivated FBS (Gibco) with a final volume adjustment until reached a concentration of 10⁶ viable cells per mL. Concomitantly, DCs were gently removed from the plates and resuspended at 2x10⁵ viable cells per mL in RPMI 1640 medium. DCs (2x10⁴ cells/well) were cocultured with lymph node cells (10⁵ cells/well) and incubated at 37ºC/CO₂. After 24 h, culture supernatants were collected for IL-2 quantification by ELISA, as described before [33]. After 48 or 120 h of culture, cells were collected for flow cytometry analyses.

Flow cytometry

For surface markers immunostaining, cells were incubated with Zombie aqua (ZAq) fixable viability kit (Biolegend) and immunostained with fluorophore-conjugated monoclonal antibodies (mAbs) for 15 min at RT. For intracellular cytokine staining, cells were stimulated with PMA (50 ng/ml; Sigma) and ionomycin (1 mg/ml; Sigma) in the presence of brefeldin A (5 µg /ml; Biolegend) for 3 h. After staining of surface markers, cells were fixed and permeabilised using the Foxp3 Fixation/Permeabilization solution (eBioscience), according to the manufacturer instructions. Permeabilised cells were incubated with fluorophore-conjugated mAbs to intracelullar markers for 15 min at RT. All flow cytometry analyses were performed by using a FACSCanto II flow cytometer, and collected data were analysed by using FACSDiva (BD Biosciences) and FlowJo software (Tree Star, Ashlan, OR, USA).

Adoptive transfer

ABX-treated SNCA (SNCA_ABX+) or non-treated SNCA/Rag1^−/− (SNCA/Rag1^−/− _ABX−) of 7 weeks of age recipient mice received the i.v. transfer of 10⁷ cells/mouse from the splenocytes isolated from non-treated SNCA (Spl(SNCA_ABX−)) or ABX-treated (Spl(SNCA_ABX+)) SNCA mice. Different wellness parameters were recorded weekly including the body weight. 13 weeks later, mice were euthanaised to obtain colon, brain, skin, MLN, and CLN.

Immunofluorescence and immunohistochemical analysis

Coronary brain sections (40 µm thick) containing the entire area of the striatum were generated by cryostat (Leica CM1860 UV). For microgliosis analysis, striatal sections were immunostained with a rabbit anti-Iba1 pAb (1:1000; Wako, Fujifilm). For astrogliosis analysis, striatal sections were immunostained with a rabbit anti- Glial fibrillary acidic protein (GFAP) pAb (1:1000, Dako). After washing several times, brain sections were incubated with a AlexaFluor 594-conjugated donkey anti-rabbit IgG (H + L) (Invitrogen) secondary antibody. 3–4 striatal fields from six sections (separated by 320 µm of rostrocaudal distance) at 40X per animal were analysed as described before [35]. For analysis of αSyn pathology, the colon tissue was whole-mounted as described before [36]. Colon sections were stained with a mouse anti-phopho-Serine129 αSyn (anti-pSer129 αSyn) mAb (1:300). After washing several times, incubation with AlexaFluor 488-conjugated goat anti-mouse IgG (H + L) (Invitrogen) was performed. Subsequently tissues were washed, and the staining of F-actin and nuclei were conducted with AlexaFluor 647 labeled phalloidin (1: 150) and Hoechst 33343 (1:1000) respectively. For immunostaining of E-cadherine, rat anti-Ecadherine antibody (1:200) was used in intestinal tissue preparations as described before [36]. 3–4 colon fields from 1 section of 5 mm per animal were analysed for pSer129 αSyn and Ecadherine whole-mount analysis. All sections were mounted with Fluoromont (Electron Microscopy Sciences) with DAPI or previously incubated with Hoechst and imaged with LEICA SP8 (HC PL APO CS2 20X dry NA 0,75) confocal microscope.

For determining the presence of nitrated hαSyn (NY- hαSyn) in colonic tissue, we used the 1A11 mAb (see a note in declarations). The colon section were processed with histological technique, and embedded in paraffin. 3 µm sections were processed by immunohistochemistry technique [37]. For immunostaining of NY-hαSyn, incubation with the primary mouse 1A11 mAb (0.5 µg/mL) was followed by incubation with mouse-on-mouse HRP Polymer secondary antibody staining system (Biocare Medical) and then, the ImmPACT DAB chromogenic substrate (Vector, Cat. No. #SK-4105) was used. Immunostained sections were contrasted with hematoxylin nuclear staining and then dehydrated, clarified and mounted for microscopic evaluation. 3 colon fields form 6 sections per animal were analysed for 1A11 reactivity. Bright-field images were taken with Nikon Eclipse E200 (10X, 40X magnification). All samples were analysed with Image-J (http://imagej.nih.gov). Reconstructions of bright field colonic 10X sections were made based on 15–16 photos and photomerged by Adobe Photoshop CS3 (version 10.0.1).

Intraepidermal nerve fibre density

Skin samples embedded in O.C.T. compound (Sakura Finetek USA, Inc.) were snap frozen and cut in 14 µm-thick sections using a cryostat (Leica CM1860 UV). Sections were blocked with 5% fish gelatine (Sigma) for 1 h, and incubated with a rabbit anti-PGP9.5 pAb (1:500, Zytomed systems) overnight at 4°C. After washing with PBS containing 0.1% Triton™ X-100 (Merck), sections were incubated with a Cy3-coupled anti-rabbit (1:500; Jackson ImmunoResearch Laboratories, Inc.) secondary antibody overnight at 4°C. Afterward, sections were washed and mounted with Fluoromont (Electron Microscopy Sciences) and DAPI for analysis. Intraepidermal nerve fibre density (IENFD) was determined by the same observer on three different skin sections per individual using the epifluorescence microscope IX-71 Olympus Life Science, 60X objective. Epidermal fibres crossing the dermal–epidermal junction were considered for quantification, whereas secondary branches and fragments were excluded from quantification [38]. The length of the epidermal surface was measured using ImageJ and IENFD was expressed as fibres per mm of epidermis.

Amplicon sequencing variant generation

Bacterial genomic DNA was extracted using QIAamp DNA stool for whole-community DNA extraction (Qiagen). The 16S rRNA gene sequencing and analysis were conducted in collaboration with the Alkek Center for Metagenomics and Microbiome Research (CMMR) at Baylor College of Medicine. Briefly, the 16S rDNA V4 region was amplified by PCR and sequenced in the MiSeq platform (Illumina) using the 2x250 bp paired-end protocol yielding pair-end reads overlapping almost completely. The primers used for amplification contain adapters for MiSeq sequencing and single-index barcodes so that the PCR products may be pooled and sequenced directly, targeting at least 10,000 reads per sample. The metagenome raw reads obtained from the sequencing of the faecal microbiome were deposited into Sequence Read Archive (SRA) bioproject PRJNA1086841. An in-house pipeline was next used for read processing and analysis. Inference of amplicon sequence variant (ASV) from 16S amplicon sequencing and taxonomic assignment were performed with QIIME2 2024.5 [39]. Briefly, by using the plugin DADA2 R library [40] wrap within QIIME2, the raw sequences were submitted to quality trim and filter (overall quality score above 30), chimera removal, PhiX removal, and paired-end reads joining to generate ASV. Taxonomy was assigned to ASV using the SILVA v138 reference database [41].

Microbiome analysis, alpha and beta diversity

After the resulting ASVs generation, those classified as contaminants (Chloroplast, Mitochondria, or Eukaryota) were removed, as well as taxa with low prevalence (1 ASV in 1 sample). The remaining ASVs were used in R studio v4.2.2 for diversity, abundance and function inference analysis. For alpha diversity, we used rarefaction to account for different library size across samples and then Chao1 richness, Shannon index, and Inverse Simpson index were calculated for each sample using phyloseq v1.42.0 [42]. For group comparison, a Kruskal-Wallis test followed by a Wilcoxon test with Benjamini-Hochberg adjustment for p-value was applied to assess pairwise differences. To infer the beta diversity, rarefied samples were used to carried out principal coordinates analysis (PCoA) based on Bray-Curtis distance using phyloseq v1.42.0 [42]. To evaluate statistical differences between groups a PERMANOVA (permutational multivariate analysis of variance) was performed on the Bray-Curtis distance matrix using the adonis function of the vegan v2.6-4 package. The variance homogeneity assumption was evaluated using the functions betadisper and permutest of the vegan package.

Differentially abundant taxa and function inference

To identify the differential abundance taxa with significant differences between SNCA and WT without antibiotic treatment, we used relative abundance at phylum, family and genus level. To assess pairwise differences, a Wilcoxon test was applied. Additionally, linear discriminant analysis (LDA) effect size (LEfSe) [43] analysis was performed to determine the taxa contributing to the effect size between SNCA and WT, using the microbiomeMarker v1.4.0 package. This analysis incorporated the Kruskal-Wallis sum-rank test for significant differential abundance set at a significance of p = 0.05, followed by LDA to estimate effect size which was set to a cut-off of ≥ 2. To assess the potential functional gene content associated with the differences in community gut microbiome between SNCA and WT, we predicted metagenomic composition from ASV sequences with PICRUSt2 (phylogenetic investigation of communities by reconstruction of unobserved states) [44]. The output provides proportional contributions of each gene which was annotated with MetaCyc database of metabolic pathways categories for each sample [45]. The functional predictions were analysed within the ggpicrust2 package was differentially abundant using edgeR [46] and showed the derived results as relative abundance difference between groups, with fold-change ≥ 2 and p-value < 0.05.

Statistical analyses and sample size estimation

The sample size was estimated with the mean and dispersion obtained from preliminary data using the sample size calculator using the page provided by the University of California, San Francisco, United States: https://www.stat.ubc.ca/~rollin/stats/ssize/n2.html. Where: Standard deviation (σ, sigma) = 1; α value (probability of making a type I statistical error) = 0.05; Statistical power = 0.80; Mu1 (Population mean 1) = 0; Mu2 (Population mean 2) = 1.5. Obtaining in consequence a sample size of 7 and considering a 10% of animal loss, a final sample size of 8 animals per group when approximated. All values are expressed as the mean ± SEM. Statistical analysis was performed with two-tailed unpaired Student’s t-test when comparing only two groups and with one-way ANOVA followed by Sidak’s or Tukey's post-hoc test when comparing more than two groups with only one variable (treatment or genotype). To analyse differences in experiments comparing different genotypes and different treatments, two-way ANOVA followed by Sidak's post-hoc test was performed. Behavioural analyses from adoptive transfer experiments were compared using Dunnett's multiple comparisons test. All analyses were carried out using the GraphPad Prism 10 Software. p-values < 0.05 were considered significant.

The adaptive immune system and microbiota are required for the development of motor and sensory impairment in SNCA mice. To explore whether the development of motor impairment is dependent on the adaptive immunity in SNCA mice, we determined the hindlimb clasping reflex in SNCA mice deficient in the recombination-activating gene 1 (Rag1^−/−), which are devoid of T- and B-cells [47]. The results show that SNCA mice display the onset of motor impairment between weeks 15 and 20 of age, and the severity increased progressively up to week 32 of age (Fig. 1A-B). Importantly, the deficiency of adaptive immunity abrogated the motor decline manifestation, as SNCA/Rag1^−/− mice did not develop motor impairment at any age analysed (Fig. 1A-B, C-E). To address the question of whether T-lymphocytes, B-lymphocytes or both are required for the development of the motor decline in SNCA mice, we next evaluated the hindlimb clasping reflex in SNCA mice harbouring the deficiency of B-cells (SNCA/µMT). Interestingly, SNCA/µMT mice presented a hindlimb clasping reflex score similar to that obtained by SNCA mice (Fig. 1A-B, C-E), indicating that B-cell deficiency does not affect the development of motor impairment in SNCA mice.

Previous evidence has shown that motor impairment manifestation in SNCA mice is dependent on the microbiota [24]. To confirm this in our hands, we treated SNCA mice with a cocktail of broad-spectrum antibiotics (ABX), which was proven to eliminate most bacteria from faeces (Fig. S1). Our analysis show that, indeed, the lack of microbiota abolished the development of motor decline in SNCA mice (Fig. 1F).

Since sensory hypersensitivity is a common symptom in PD patients [1, 2], and pain perception might be regulated by microbiota and adaptive immunity [48] we wondered whether SNCA mice involved sensory disturbances. To this end, we determined the threshold of mechanical sensitivity using the Von Frey test [29]. Interestingly, we observed that SNCA mice presented a marked hypersensitivity as early as at 15 weeks of age (Fig. 2A), and it was extended until week 20 (Fig. 2B) and 32 of age (Fig. S2). Importantly, this mechanical hypersensitivity is not developed in SNCA/Rag1^−/− mice but in SNCA/µMT mice (Fig. 2A-B and Fig. S2), indicating that T-cells, but not B-cells, are required for mechanical hypersensitivity manifestation in SNCA mice. To evaluate whether the sensory disturbance observed in SNCA mice was only associated with mechanical hypersensitivity, or it was also expanded to thermal sensitivity, we next determined the threshold for thermal stimuli of these mice using the Hargreaves test [49]. The results show that SNCA mice also develop a thermal hypersensitivity, which was already present at 15 weeks of age and extended up to week 20 of age (Fig. 2C-D). This thermal hypersensitivity was dependent on the adaptive immunity at 15 and 20 weeks of age (Fig. 2C-D). To address whether these sensory disturbances developed in SNCA mice were dependent or not in the microbiota, we compared thermal and mechanical sensitivity of mice treated or not with ABX. Interestingly, we observed that mechanical hypersensitivity was no affected, whilst thermal hypersensitivity was abrogated by ABX treatment (Fig. 2E-H), indicating that only the development of thermal sensory disturbance had a clear dependence on the microbiota in SNCA mice. To gain a deeper insight in this issue, we analysed the density of sensory intraepidermal fibres using a pan-neuronal marker (PGP 9.5) [50]. According to the nociceptive disturbances observed in SNCA mice (Fig. 2A-H), we observed a significant reduction in the density of intraepidermal fibres in these mice (Fig. 2I-J). Altogether, these results indicate that the development of motor impairment and thermal sensory disturbances in SNCA mice are dependent on both adaptive immunity and microbiota.

Both microbiota and adaptive immunity play important roles promoting neuroinflammation in SNCA mice. Previous studies using another strain of transgenic SNCA mice (line 61) have shown that microbiota [24] and adaptive immunity [51, 52] favour the development of neuroinflammation. To evaluate whether the mouse strain used in this study (SNCA mice, line 15) develops neuroinflammation with similar requirements, we next determined the extent of microgliosis and astrogliosis in the striatum of SNCA mice devoid of microbiota or adaptive immunity. For this purpose we determined the intensity and distribution of Iba1 and GFAP expression by immunofluorescence analysis along the striatal anteroposterior axis (Fig. 3A-C). Reactive microglia was defined as cells expressing high intensity of Iba1 (Iba1^high) with ameboid shape (Fig. 3D). Compared with WT mice, SNCA mice displayed increased microgliosis, which was evidenced by an enhanced number of Iba1^high cells per area (Fig. 3G and I, left panel) or higher percentage of Iba1^high cells among the total Iba1⁺ cells (Fig. 3H and I, right panel). This microgliosis was not homogeneous across the striatal anteroposterior axis (Fig. 3G, H), but was especially evident at the level of section 3 (Fig. 3A, G, H). Interestingly, there was different extent of microgliosis in striatal zones associated with the ventricles and motor cortex (Fig. S3). Importantly, these differences in microgliosis observed between SNCA and WT mice were abrogated upon ABX treatment (Fig. 3G-I, S3). The microgliosis was also affected heterogeneously along the striatal anteroposterior axis by the lack of adaptive immunity (Fig. S4A-B). Importantly, this astrogliosis was abolished in the absence of adaptive immunity in particular areas af the striatum (section 4; Fig. S4C). Astrogliosis was quantified as the mean fluorescence intensity associated to GFAP immunostaining in GFAP⁺ cells (Fig. 3B). Similar to microgliosis, astrogliosis was not homogeneous along the striatal anteroposterior axis (Fig. 3E), but was especially evident at sections 5 and 6 (Fig. 3F). The differences in astrogliosis observed between WT and SNCA mice disappeared upon ABX treatment (Fig. 3E-F). Together, these results indicate that SNCA mice develop a significant neuroinflammatory process in the striatum, which is dependent on the microbiota and adaptive immunity.

Microbiota-primed lymphocytes rescue the disease manifestation in SNCA mice. Since neuroinflammation, motor decline, and sensory disturbances depend on both microbiota and lymphocytes, we next addressed the question of whether the dependence on microbiota was functionally connected with the dependence on adaptive immunity. To this end, we conducted adoptive transfer experiments in which ABX-treated recipient mice received lymphocytes obtained from donors treated or not with ABX (Fig. 4A), and the disease manifestation was determined. The results show that the transfer of splenocytes isolated from non-treated SNCA mice, containing microbiota-primed lymphocytes, into ABX-treated SNCA mice induced a motor decline, although it was not statistically significant (Fig. 4B). Interestingly, the transfer of microbiota-primed lymphocytes into ABX-treated SNCA mice did not affect the mechanical hypersensitiviy (Fig. 4C), but it significantly rescued thermal hypersensitivity (Fig. 4D). These results agree with the fact that only thermal, but not mechanical hypersensitivity, was dependent on the microbiota (Fig. 2E-H). To gain more robustness in these findings, we performed a complementary set of adoptive transfer experiments where SNCA/Rag1^−/− recipient mice received the transfer of microbiota-primed (SNCA_ABX−) or non-primed (SNCA_ABX+) splenocytes and the disease manifestation was evaluated at 15 and 20 weeks of age (Fig. S5A). The results show that only microbiota-primed lymphocytes, but not non-primed lymphocytes were able to rescue the disease manifestation at the level of thermal hypersensitivity (Fig. S5D), although no clear effects were observed at the level of mechanical hypersensitivity and motor impairment (Fig. S5B-C). Taken together these results indicate that microbiota-primed lymphocytes are required to induce thermal hypersensitivity in this animal model.

SNCAmice develop a lymphocyte- and microbiota- dependent colonic inflammation. Since the above results indicate that the lymphocyte dependence and the microbiota dependence are connected in the pathophysiology of parkinsonism development in SNCA mice, we wondered how was the mechanism underlying. Several lines of evidence have proposed that PD begins in the gut, an organ of high interaction between lymphocytes and microbiota [8]. Thereby, we next evaluated whether SNCA mice involve gut inflammation. For this purpose, we determined the extent of colon shortening, a macroscopic parameter highly associated with colonic inflammation [53, 54]. The results show that, indeed, SNCA mice present a significant colon shortening at 20 weeks of age. Furthermore, this colon shortening was not observed in SNCA mice deficient on adaptive immunity (Fig. 5A-B) or depleted of microbiota (Fig. 5C-D). Thus, these findings indicate that SNCA mice involve the development of a colonic inflammation that is dependent on lymphocytes and the microbiota. Interestingly, the transfer of splenocytes isolated from non-treated SNCA mice, containing microbiota-primed lymphocytes, into ABX-treated SNCA mice did not rescue the colon shortening (Fig. 5E-F), suggesting that gut inflammation occurs prior to sensory disturbances (Fig. 4D). Gut inflammation in PD has been proposed to be triggered as a consequence of increased epithelial permeability [8]. Accordingly, we next quantified the degree of permeability of the intestinal barrier in SNCA mice by evaluating the luminal accessibility of the adherent junctions protein E-cadherin using confocal microscopy. Luminal accessibility of E-cadherin denotes a loss of intestinal polarity [55]. The results revealed a strong increased permeability of the intestinal barrier in SNCA mice compared to WT controls (Fig. S6). Previous evidence has suggested that the disruption of the integrity of the epithelial layer of the intestinal mucosa might trigger mucosal inflammation, accompanied by reactive oxygen species (ROS), and the consequent development of synuclein pathology [8, 48]. For these reasons, we next evaluated whether SNCA mice display pathogenic forms of the αSyn in the colonic mucosa. Indeed, we found high degree of both nitrated (NY-hαSyn; Fig. 6A, C) and phosphorylated (pSer129 hαSyn; Fig. 6B, D) forms of αSyn in 20 weeks old SNCA mice. Taken together, these results suggest that, due to an increased permeability of the gut barrier, the generation of pathogenic forms of αSyn is induced in the colonic mucosa of SNCA mice, which trigger gut inflammation.

SNCA mice develop a T-cell response specific to αSyn-derived antigens. Since the intestine has been proposed to play an important role in triggering the synuclein pathology [8], and a T-cell response to αSyn-derived antigens has been observed in PD patients [12], we hypothesised that colonic inflammation observed in SNCA mice would be mediated by T-cells specific to αSyn-derived antigens. To address this hypothesis, we conducted experiments in which DCs loaded with antigens derived from unmodified hαSyn or from pathogenic forms of hαSyn (containing the pSer129, or three nitro-tyrosines in the C-terminal; 3NY-hαSyn) [56–58], were co-cultured with T-cells obtained from the mesenteric lymph nodes (MLN; Fig. S7) or from the cervical lymph nodes (CLN; Fig. S8), which drain antigens coming from the colonic mucosa or from the CNS, respectively. In these experiments we determined the generation of IFN-γ-producing and IL-17-producing effector T-cells in response to hαSyn-derived antigens, and the ability of hαSyn-derived antigens to induce T-cell activation, as determined by the surface expression of CD69 (Fig. S9 and S10). We detected a clear effector T-cell response to pSer129-hαSyn in CLN of SNCA mice, characterised by Th1, Th17 and IL-17-producing CD8⁺ T-cells (Fig. 7), although we did not observe a significant T-cell response to 3NY-hαSyn or unmodified hαSyn in these lymph nodes (Fig. 7). Nevertheless, we observed a significant CD4⁺ and CD8⁺ T-cell activation in reponse to 3NY-hαSyn in CLN from those ABX-treated SNCA mice receiving the transfer of microbiota-primed splenocytes (Fig. S10C). Importantly, we detected a significant effector CD4⁺ (Th1 and Th17) and CD8⁺ (IL-17-producing) T-cell response to pSer129-hαSyn in the MLN of SNCA mice (Fig. 7). In addition, we detected the generation of effector CD8⁺ T-cells producing IFN-γ in response to unmodified and 3NY-hαSyn in the MLN (Fig. 7). Strikingly, we observed a strong and selective activation of CD4⁺ and CD8⁺ T-cells specific to 3NY-hαSyn but not to unmodified hαSyn in MLN in those ABX-treated recipient mice receiving microbiota-primed lymphocytes (Fig. S10D), indicating that the T-cell response generated to hαSyn-derived antigens in SNCA mice is dependent on the microbiota. Supporting this idea, T-cells from the MLN increased the secretion of IL-2, another parameter associated with T-cell activation, in response to hαSyn-derived antigens, an effect that was abrogated when mice were exposed to ABX (Fig. S11). A similar effect was observed with T-cells isolated from the CLN, although it was not statistically significant (Fig. S11). Moreover, we observed a significant increase in the production of IL-2 in colonic explants from SNCA mice compared with those obtained from WT mice, an effect abolished by the ABX treatment (Fig. S12). Altogether, these results indicate that SNCA mice develop an inflammatory T-cell response specific to hαSyn-derived antigens in the colon, which is dependent on the microbiota.

SNCA mice harbour a dysbiosis involving the selective reduction of beneficial bacteria. The above results indicate that microbiota is required to trigger a T-cell response, gut inflammation, sensory disturbances, neuroinflammation and motor decline in SNCA mice. Accordingly, we hypothesised that SNCA mice harbour a dysbiosis involving increased inflammatory bacteria, decreased anti-inflammatory bacteria, or both. To address this possibility, we compared the microbiome of SNCA mice and WT littermates obtained from faecal samples. Beta-diversity analysis revealed that SNCA mice display a significantly different bacterial composition compared to WT littermates (Fig. 8A). As controls for principal components analyses, we also used samples obtained from ABX-treated mice from both genotypes. As expected, ABX-treatment abrogated differences observed between genotypes (Fig. 8A). The analysis of microbial composition at the phylum level shows a significant and selective reduction of the representation of the Verrucomicrobiota in SNCA mice (Fig. 8B), with no differences in other phyla (Fig. S13B). Interestingly, at the level of genera, the analysis revealed a selective reduction of Faecalibaculum and Akkermansia, but not other genera (Fig. 8C). This was confirmed by linear discriminant analysis (LDA) score of effect size (Lefse) at different taxonomic levels (Fig. 8D), including order, family, genus and specie. Of note, species from Akkermansia spp., have been reported to exert anti-inflammatory and beneficial effects in PD [59]. Moreover, Faecalibaculum genus is considered a beneficial SCFA producer which reduces inflammation by stimulating the development of Tregs in the colon [60], thus promoting immune tolerance and maintaining intestinal homeostasis. Finally, we performed a differential abundance analysis using “edgeR” for data transformation on MetaCyc pathways and observed that SNCA mice are enriched in bacteria assotiated with metabolic pathways related to acetate (Fig. 8D). This is congruent with previous reports of bacterial SCFA producers unbalance along with the dysbiosis [24]. These analyses also revealed a reduction of bacterial populations related to the superpathway of L-tryptophan biosynthesis in SNCA mice (Fig. 8D), which is known by its anti-inflammatory and anti-nociceptive actions in experimental models of colitis or migraine [61–63]. Thereby, our results indicate that SNCA mice harbour a dysbiosis involving the reduction of bacterial populations with beneficial properties, which might be the trigger for gut barrier disruption, inflammation and synuclein pathology.

Our results here revealed how the development of motor and non-motor symptomatology triggered by microbiota is mediated by a T-cell response specific to αSyn-derived antigens in a PD mouse model that develops the disease spontaneously with age. Our findings indicate an important role of T-cells, but not B-cells, in the development of the disease in the SNCA mouse model. Consistently, previous studies conducted in rodent PD models have shown that CD4⁺ and CD8⁺ T-cells infiltrate the brain during the disease development, including genetic- [52], drugs-induced [64], and virus-induced models [65]. Moreover, the deficiency of adaptive immunity [66], or specific depletion of CD4⁺ [64, 67] or CD8⁺ [67] T-cells in the PD mouse model induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) abrogated the development of neurodegeneration. Similarly, the genetic deficiency of CD4⁺ T-cells decreases the neurodegeneration induced by AAV-hαSyn [68]. These studies indicate a key role of T-cells in PD development. Nevertheless, the relevance of B-cells in PD is controversial. A recent study conducted in the PD mouse model induced by AAV-A53T found that B-cells deficiency does not protect from dopaminergic neurodegeneration [16]. Moreover, the adoptive transfer of functional B-cells into immunodeficient recipient mice did not alter the development of the disease induced by preformed αSyn fibrils (PFF) treatment [17]. Conversely, another study in the PD model induced by 6-OHDA found that B-cell deficiency (µMT mice) or B-cell depletion (using anti-CD20 antibodies) resulted in exacerbated neurodegeneration, suggesting that B-cells may play a protective role in PD [69]. The different conclusions obtained in the latter study and in the present work might be due to the different pathogenic mechanisms associated with the models used; here we used the SNCA mouse model which involves the spontaneous development of gut-to-brain PD, whilst the oher study used the 6-OHDA model that involves the direct administration of a neurotoxin in the brain [69].

We observed here that thermal and mechanical hyperalgesia were developed prior to the motor symptoms in the SNCA model. This was congruent with the idea of an early primary affectation of the peripheral nervous system with a late secondary affection of the central nervous system with motor symptoms, as seen in patients [70]. Interestingly, our findings show that thermal hypersensitivity was abolished in ABX-treated SNCA mice. Conversely, the manifestation of mechanical sensory disturbances was not dependent on microbiota. In contrast, previous studies using mouse models of somatic neuropathic pain induced by chronic constriction injury (CCI) of the sciatic nerves, oxaliplatin (OXA) chemotherapy, and streptozocin (STZ)-induced diabetes have shown that the depletion of microbiota by ABX treatment strongly reduces the mechanical allodynia and thermal hyperalgesia [71]. Similar findings were found in OXA-induced mechanical hyperalgesia in GF and antibiotic treated mice [72]. Discrepances between these studies and our results might be due to that CCI- OXA- and STZ- induced sensory disturbances and mechanical hypersensitivity observed in the SNCA mouse model used here may involve different cellular and molecular mechanisms. Of note, the role of immune system has been extensively explored on pain pathways, which has demonstrated being determinant in both inflammatory and neuropathic pain [73]. Altogether, these observations support the idea that there is crosstalk between T-cells and microbiota on the development of sensory symptoms, as shown here in our splenocytes transfer experiments. Interestingly, our data suggest that mechanical and thermal sensitivity are differentially affected by this cross-talk between T-cells and microbiota. Further studies are necessary to address the mechanisms underlying this differential regulation of thermal and mechanical sensitivity by the collaboration of microbiota and T-cells.

Pain is a common non-motor manifestation in PD patients [1, 2]. Supporting this, here we found that the SNCA mouse model develops both mechanical and thermal disturbances. Accordingly, it has also been observed in other PD rodent models. Mechanical and thermal hyperalgesia have been previously described in the rat PD model induced by 6-OHDA [74–79] and in mouse PD models induced by MPTP [80] or by the Pitx3^416insG mutation [81]. In contrast, αSyn knock-out mice showed reduction of acute and cold nociception and decreased in neuropathic induced mechanical allodynia [82]. Of note, our study represents the first work describing sensory disturbances in the SNCA mouse model. Moreover, this is the first study describing a causal relationship between the microbiota and the development of pain in an animal model of PD.

Our results show that sensory disturbances were associated with lower IENFD in the skin of SNCA mice. Analogously, most PD patients display small fibre neuropathy (SFN), which involves reduced IENFD [83] and sensory disturbances [84]. The reduction of IENFD observed in PD might be related with the cutaneous deposition of pathogenic forms of αSyn [85, 86], which could promote peripheral nerve neurodegeneration. Nevertheless, this hypothesis should be addressed in future research. An interesting question that arises is how decreased IENFD is relatated with pain hypersensitivity. In this regard, peripheral sensitization and hyperexcitability might be caused by peripheral nerve injury, involving inflammation and release of pro-nociceptive mediators, such as cytokines, ATP, and prostanglandins [48]. In addition, changes in channel expression and composition in peripheral nerve might also contribute to nociceptive hypersensitivity, including the increased expression of voltage-gated sodium and calcium channels, toll-like receptor 4, transient receptor potential channels, α1 adrenergic receptors, acid-sensing ion channels, and decreased expression of voltage-gated potassium channels [87]. Importantly, our results revealed two important changes that might contribute to pain hypersensitivity developed in SNCA mice: increased IFNγ and dysbiosis. In this regard, IFNγ derived from T-cells upon recognition of αSyn-derived antigens might exert pro-nociceptive activity [88]. On the other hand, dysbiosis might involve significant changes in bacterial metabolites that affect directly or indirectly nociceptive activity [48].

Accordingly, we observed that the microbiome from SNCA mice displays a reduction in bacteria related to L-tryptophan metabolism, which can generate indole-derived metabolites [89]. Many indole-derived metabolites are ligands of the aryl hydrocarbon receptor (AhR), which plays a key role in host-microbiota cross talk and in the pathogenesis of inflammatory disorders [90]. Various reports have shown that bacterial tryptophan-derived metabolites play an anti-inflammatory role in intestinal inflammation via AhR stimulation [61, 91]. Moreover, there is evidence that AhR stimulation is involved in nociception through the activation of anti-inflammatory pathways since global AhR deficient mice develop neuropathic pain, whilst AhR activation is protective dampening neuroinflammation in a nerve injury model [92]. In addition to the L-tryptophan metabolism, the dysbiosis observed in SNCA mice also showed alterations in bacteria assotiated with the metabolism of SCFAs. Unbalanced composition of SCFAs has been previously described in PD patients and experimental models as well as in other neurodegenerative diseases [24, 93, 94]. Interestingly, acetate has been reported to increase IFN-γ production in T CD8⁺ lymphocytes [95], and favouring Th1 and Th17 responses [96]. Conversely, other studies have shown that acetate might attenuate proinflammatory signalling in microglia [97] and astrocytes [98]. These studies highlight the double-edge sword potential of SCFAs regulating inflammation [99]. Altogether, our results suggest that the inflammatory response and the peripheral neuropathy observed in SNCA mice might involve the unbalance of key bacterial metabolites, including AhR ligands and SCFA.

Importantly, our results revealed a dysbiosis of intestinal microbiota, which correlates with an increased permeabilization of the gut epithelial barrier in SNCA mice. In this regard, previous studies have shown that increased representation of some bacteria, such as Proteus mirabilis, might induce the down-regulation of tight junctions expression in the intestinal epithelium, thus increasing gut permeability [100]. Of note, the disruption of the epithelial layer of the intestinal mucosa might trigger inflammation, which is accompanied by oxidative stress and the consequent aggregation of αSyn present in the neurons of the enteric nervous system [101, 102]. Thus, a dysbiosis of the gut microbiota might potentially initiate the αSyn pathology in the gut mucosa. Moreover, evidence from rodents has shown that αSyn aggregation might propagate from the intestinal mucosa through the vagus nerve, contributing to αSyn pathology in the brain [103].

Our results revealed how the development of motor and non-motor symptomatology triggered by microbiota is mediated by an autoimmune T-cell response specific to pathogenic forms of αSyn in a PD mouse model that develops the disease spontaneously with age. Considering the results in this study and previous evidence, we propose the following working model in the development of gut-to-brain pathology in the SNCA mouse model: Gut dysbiosis increases the permeability of the gut epithelial barrier, triggering gut inflammation and the generation of pathogenic forms of αSyn, including nitrated and phosphorylated αSyn. These pathogenic forms of αSyn, which represent neo-antigens, would trigger the subsequent T-cell mediated chronic inflammation, first in the gut and then in the brain (Fig. 9).

Ethics approval

All procedures and housing complied with the recommendations in the 8^th edition of the Guide for the Care and Use of Laboratory Animals and with the United States Public Health Service Policy. The IACUC of Fundación Ciencia & Vida approved the protocols for this study (Code Number: P041/2022).

Consent for publications

Not applicable

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The metagenome raw reads obtained from the sequencing of the faecal microbiome were deposited into Sequence Read Archive (SRA) bioproject PRJNA1086841.

Competing interest

All authors declare that they do not have any financial or non-financial competing interests. However, V.U. and R.P. are named inventors on a pending PCT patent application describing the diagnostic and therapeutic use of the 1A11 mAb for Parkinson’s diseases. The PCT application has not yet been published and is currently under review. The 1A11 mAb was developed internally by our laboratory following the publication of our initial findings. This antibody specifically targets the C-terminus of human aSynuclein (residues 111-140) containing nitro-tyrosines and has been validated through ELISA and immunohistochemistry. It is not currently available commercially. For further details or collaboration inquiries, please contact Rodrigo Pacheco at [email protected].

Funding

This work was supported by “Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia de ANID” Centro Ciencia & Vida [FB210008] (to Fundación Ciencia & Vida), and IMPACT [FB210024] by “Agencia Nacional de Investigación y Desarrollo de Chile (ANID)” [FONDECYT-1210013] (to R.P.), [FONDECYT-1220823] (to M.C.), [FONDECYT-1191526] (to E.R.), [FONDECYT-1220196] (to A.M.), [FONDECYT-1190074] (to A.M.), and FONDEF [ID22I10070] (to R.P.), the Millennium Nucleus for the Study of Pain to MC (MiNuSPain is a Millennium Nucleus supported by the Millennium Science Initiative of the Ministry of Science, Technology, Knowledge and Innovation, Chile), and by the Michael J. Fox Foundation for Parkinson’s Research [MJFF-021112] (to RP).

Author contributions

R.P. developed the concept of this study; R.P., M.C. and Z.M. designed the study, Z.M., V.U., C.P., P.C-C., O.C-V., A.E., S.V., and M.R. conducted experiments and acquired data, Z.M., C.P., P.C-C., O.C-V., I.V., J.E.M-H., A.J.M.M. and R.P. analysed data, E.R. and J.P. provided new reagents, Z.M. and R.P. wrote the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We thank Drs. Alejandro Rojas and Constanza Salinas for donation of recombinant haSyn. We thank Sebastián Belmar and Miguel Vargas form MERKEN biotech for their technical help in histological analysis of the 1A11 mAb immunoreactivity in colonic tissue. We also thank María José Fuenzalida for her technical assistance in cell sorting and flow cytometry.

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Microbiota-dependent T-cell response to α-synuclein-derived antigens triggers the development of hypersensitivity and neuroinflammation associated with Parkinson's Disease

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Version 1

Abstract

Figures

BACKGROUND

METHODS

Mice and treatments

Hindlimb clasping reflex

Hargreaves test

Von Frey test

16S rRNA PCR

Tissue processing

Generation of DCs

Flow cytometry

Adoptive transfer

Immunofluorescence and immunohistochemical analysis

Intraepidermal nerve fibre density

Amplicon sequencing variant generation

Microbiome analysis, alpha and beta diversity

Differentially abundant taxa and function inference

Statistical analyses and sample size estimation

RESULTS

DISCUSSION

CONCLUSIONS

Declarations

References

Supplementary Files

Status:

Version 1