G-protein-coupled receptor P2Y10 facilitates chemokine-induced CD4 T cell migration through autocrine/paracrine mediators

G-protein-coupled receptors (GPCRs), especially chemokine receptors, play a central role in the regulation of T cell migration. Various GPCRs are upregulated in activated CD4 T cells, including P2Y10, a putative lysophospholipid receptor that is officially still considered an orphan GPCR, i.e., a receptor with unknown endogenous ligand. Here we show that in mice lacking P2Y10 in the CD4 T cell compartment, the severity of experimental autoimmune encephalomyelitis and cutaneous contact hypersensitivity is reduced. P2Y10-deficient CD4 T cells show normal activation, proliferation and differentiation, but reduced chemokine-induced migration, polarization, and RhoA activation upon in vitro stimulation. Mechanistically, CD4 T cells release the putative P2Y10 ligands lysophosphatidylserine and ATP upon chemokine exposure, and these mediators induce P2Y10-dependent RhoA activation in an autocrine/paracrine fashion. ATP degradation impairs RhoA activation and migration in control CD4 T cells, but not in P2Y10-deficient CD4 T cells. Importantly, the P2Y10 pathway appears to be conserved in human T cells. Taken together, P2Y10 mediates RhoA activation in CD4 T cells in response to auto-/paracrine-acting mediators such as LysoPS and ATP, thereby facilitating chemokine-induced migration and, consecutively, T cell-mediated diseases.

The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.
For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection no software used Data analysis mRNA sequencing raw reads were assessed for quality, adapter content and duplication rates with FastQC (version 0.11.8) (Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc). Trimmomatic version 0.39 was employed to trim reads after a quality drop below a mean of Q20 in a window of 5 nucleotides 64. Only reads between 30 and 150 nucleotides were cleared for further analyses. Trimmed and filtered reads were aligned versus the Ensembl mouse genome version mm10 (GRCm38) using STAR 2.7.3a with the parameter "--outFilterMismatchNoverLmax 0.1" to increase the maximum ratio of mismatches to mapped length to 10% (Dobin et al., STAR: ultrafast universal RNA-seq aligner). The number of reads aligning to genes was counted with featureCounts 1.6.5 tool from the Subread package 65. Only reads mapping at least partially inside exons were admitted and aggregated per gene. Reads overlapping multiple genes or aligning to multiple regions were excluded. The Ensemble annotation was enriched with UniProt data (release 06.06.2014) based on Ensembl gene identifiers (Activities at the Universal Protein Resource (UniProt)). The raw count matrix was batch corrected using CountClust 66 and then normalized with DESeq2. Differentially expressed genes were identified using DESeq2 version 1.26.0 (Love et al., Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2).
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

April 2020
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability The accession code for mRNA sequencing data is GSE162246 and data are now accessible.

Field-specific reporting
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Life sciences study design
All studies must disclose on these points even when the disclosure is negative.

Sample size
Sample size was determined based on previous experiments of the same type, sample sizes shown in literature, or according to D. Altman (Practical Statistics for Medical Research, 1991) Data exclusions Is some cases individual data from individual mice had to be excluded because re-genotyping of respective mice did not confirm the genotype Randomization Samples were alllocated to their respective groups based on their genetic modification (control vs KO).

Blinding
Invesitigators were blinded to genotype during data collection and analysis.

Validation
For flow cytometry, only standard antibodies were used. The P2Y10 antibody was validated using P2Y10-deficient cells (see Fig. 1c  The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.

Methodology
Sample preparation For the analysis of murine leukocyte populations, lymphatic organs were harvested, minced, filtered and stained with the indicated antibodies. For the analysis of spinal cord infiltrating leukocytes, spinal cords were homogenized with a glass tissue homogenizer in PBS containing 1% glucose and 0.1% BSA. After centrifugation, spinal cords were resuspended in 6 ml of 30 % Percoll (Sigma-Aldrich) and layered on a gradient consisting of 4 ml 45 % Percoll and 2 ml 70 % Percoll. Gradients were spun for 20 minutes (970xg, room temperature, without break) and interphases between the layers harvested. After washing, cells were stained with fluorochrome-labelled antibodies and analyzed by flow cytometry.

Gating strategy
The gating strategies are depicted in Supplemental Figure 11 Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.