Animals
Male and female WT C57BL/6 mice were maintained in the Hunan Children’s Research Institute pathogen-free animal facility of Hunan Children’s Hospital (Changsha, Hunan, China). Mice were housed in cages (4–5 mice maximum per cage) at 22–25°C and 50 ± 10% relative humidity with a 12-hour light/dark cycle, periodic air changes, and free access to water and food. Congenic Rag2-/- mice on the C57BL/6 background were obtained from Changzhou Cavens Laboratory Animal Co., Ltd. (Changzhou, Jiangsu, China). All animal procedures and protocols were approved by the Animal Ethics Committee of Hunan Children’s Hospital and followed the guidelines of the Institutional Animal Care and Use Committees of Hunan Children’s Hospital (Changsha, Hunan, China).
Single-cell suspension preparation
A single-cell suspension was prepared as described previously [3]. Mice were anesthetized with 2% pentobarbital sodium, and the heart was slowly perfused with cold phosphate-buffered saline (PBS) administered via the left ventricle with a 5-ml syringe to remove peripheral blood cells. Then, heart tissues were cut into approximately 1-cm2 pieces and digested for 45 min at 37°C in Hank’s solution containing 10% fetal bovine serum (FBS) (Biological Industry, Kibbutz Beit Haemek, Israel), 0.5 mg/ml collagenase I (Sigma-Aldrich, St. Louis, MO, United States), and 0.5 mg/ml collagenase II (Gibco, Waltham, MA, United States). After digestion, the cells were resuspended in 20% Percoll (GE Healthcare, Pittsburgh, PA, United States) in RPMI 1640 medium (Biological Industry, Kibbutz Beit Haemek, Israel) containing 5% FBS and collected after centrifugation (2000 rpm, room temperature, 5 min).
Antibodies and flow cytometry
The antibodies used for flow cytometry were commercially purchased and are listed in Table 1. For surface markers, single-cell suspensions derived from heart tissues were stained by incubating the cells with antibodies in staining buffer (PBS containing 2% mouse serum, 2% horse serum and anti-CD16/CD32 blocking antibodies (eBioscience, San Diego, CA, United States) for 15 min at room temperature in the dark). For life-dead staining, cells were incubated with 7-AAD in apoptosis staining buffer (BioLegend, San Diego, San Diego, CA, United States) for 15 min at 4°C after surface marker staining. Gata3 and Ki67 were stained as recommended by the manufacturer using the Foxp3/Transcription Factor Staining Buffer Set Kit (eBioscience, San Diego, CA, United States). The lineage (Lin) markers included CD3ε and CD19. Isotype-matched control antibodies were used at the same concentration as the corresponding test antibody. All flow cytometry experiments were carried out on a BD LSRFortessa (BD Biosciences, San Diego, CA, United States). Data were analyzed with FlowJo software (version 10.0; FlowJo LLC, Ashland, OR United States).
RNA Isolation and qRT-PCR Analysis
Single-cell suspensions isolated from heart tissues were stimulated with DMSO or 50 ng/ml IL-33 for 4 hours and then were used for RNA extraction by Total RNA Purification Micro Kit (Norgen BioTek Corp, Thorold, ON, Canada). Total RNA was extracted from heart tissue using Trizol (Invitrogen, Waltham, MA, United States), as described previously [3]. Total RNA was then reverse transcribed into cDNA through Evo M-MLV RT Premix (AG Biotechnology (Hunan), Changsha, China). Real-time qPCR was performed using SYBR® Green Premix Pro Tag HS qPCR Kit (AG Biotechnology (Hunan), Changsha, China) with a Roche LightCycler® 480 II. Primer sequences used for qRT-PCR were obtained from reported literatures or designed by Pubmed Primer-BLAST. Primer sequences used for qRT-PCR were obtained designed by Pubmed Primer-BLAST, including: Ar forward, 5’-CAGGAGG TAATCTCCGAAGGC-3’; Ar reverse, 3’-ACAGACACTGCTTTACACAACTC-5’; Esr1 forward, 5’-CCCGCCTTCTACAGGTCTAAT-3’; Esr1 reverse, 3’-CTTTCTCGTTACTGCTGGACAG-5’; Esr2 forward, 5’-CTGTGATGAACTACAGTGTTCCC-3’; Esr2 reverse, 3’-CACATTTGGGCTTGCAGT CTG -5’; Primer sequences used for qRT-PCR were obtained from reported literatures, including IL-33 forward, 5’-CCCTGGTCCCGCCTTGCAAAA-3'; IL-33 reverse, 3’-AGTTCTCTTCATGCTTGGTA CCCGA-5’ [3]; GAPDH forward, 5’-AGGTCGGTGTGAACGGATTTG-3’; GAPDH reverse, 3’ TG TAGACCATGTAGTTGAGGTCA-5’.
Analysis of sex hormone response of heart ILC2s
For the analysis of heart ILC2s response to sex hormones, single-cell suspensions isolated from heart tissues were stimulated with 0, 0.1, 1 and 10 μM 17β-estradiol (17β-E2) and testosterone (Medchem Express, Monmouth Junction, NJ, United States) for 4 hours and then stained for surface markers. All flow cytometry experiments were carried out on a BD LSRFortessa. Data were analyzed with FlowJo software.
IL-4 and IL-5 production
For intracellular IL-5 and IL-4 staining, single-cell suspensions isolated from heart tissues were stimulated with 50 ng/ml IL-33 (BioLegend, San Diego, San Diego, CA, United States) plus BD Golgi Plug protein transport inhibitor (BD Biosciences, San Diego, CA, United States) for 4 hours and then stained for surface markers. After washing, the cells were fixed with the Fixation/Permeabilization Solution Kit (BD Biosciences, San Diego, CA, United States) following the manufacturer’s instructions and stained with anti-IL-4 or anti-IL-5 antibodies. Isotype-matched control antibodies were used at the same concentration as the corresponding test antibody. All flow cytometry experiments were carried out on a BD LSRFortessa. Data were analyzed with FlowJo software.
scRNA-seq analysis of heart ILC2s
Two datasets containing 10 female and male-mixed mouse heart samples (6 normal heart samples) were downloaded from ArraryExpress database [19, 20] for downstream analysis. Cell Ranger version (version 6.0.1) was used to process raw sequencing data. Seurat R package (version 4.0.5) was applied in our study to convert the scRNA-seq data as a Seurat object [29]. Cells that expressed fewer than 300 genes or more than 5000 genes, or had more than 20% mitochondrial genes, were removed at the quality control step. Data were then normalized by SCT transform R package (version 0.3.2) [30]. Next, we used the “RunPCA” function to reduce the dimension of the scRNA-seq data. Subsequently, we used the “RunPCA” function to conduct the UMAP analysis. We also used the “Find Clusters” and “Find All Markers” functions to conduct cell clustering analysis and detect gene expression markers. Afterwards, we used the Single R package and Cell Marker dataset to annotate the cell types in our study [31]. The “subset” function was also applied to extract the sub-cluster for downstream analysis and then annotated and analyzed as described above. Cells with Xist gene expression ≥ 0.1 was identified from female mice. To analyze the DEGs between female and male ILC2s, the value of logFC threshold was set to 0.25 to filter the DEGs, and the heatmap was produced by the Complex Heatmap R package (version 2.11.1). GSVA was used to assess KEGG pathway activation in the GSVA R package (version 1.42.0) [32].
Statistical analysis
All data are expressed as the mean ± SD, and statistical analyses were performed with SPSS software for Windows (Version 23, SPSS Inc., Chicago, IL, United States). Statistical analysis was performed with an unpaired Student’s t-test for comparisons of two independent experimental groups. If the litter effect was very obvious among independent experiments, two-way ANOVA (sex and litter) followed by Dunnett’s test was used [33]. In each analysis, there were n = 5–12 replicates per group, and the results are representative of at least two independent experiments. Statistical significance was defined as P < 0.05. The number of mice used in each group is indicated in the figure legends. All graphs were produced by GraphPad Prism 8.0 for Windows software (GraphPad Software Inc., La Jolla, CA, United States).