READ ME File For 'Dataset for The role of airway tissue-resident memory T cells in severe asthma' Dataset DOI: https://doi.org/10.5258/SOTON/D3495 Date that the file was created: May, 2025 ------------------- GENERAL INFORMATION ------------------- ReadMe Author: HEENA MOHANBHAI MISTRY, University of Southampton, ORCID ID 0000-0003-2679-1122 This dataset supports the thesis entitled 'The Role of Airway Tissue-Resident Memory T Cells in Severe Asthma' AWARDED BY: University of Southampton DATE OF AWARD: 2025 DESCRIPTION OF THE DATA ----------------------- This dataset contains all the experimental data used to generate figures including statistical calculations, gene expression data and descriptions in my PhD thesis, as well as supplementary figures and tables for the corresponding published article titled 'Cytotoxic CD4+ tissue-resident memory T cells are associated with asthma severity', https://doi.org/10.1016/j.medj.2023.09.003. This dataset contains 2 zipped file folders: 1. 'AirwayCD4CTL_Paper_SupplementaryData' zipped folder (contains 1 PDF and 4 Excel files): (Data for Chapter 5 The Molecular Role of Airway CD4+ Tissue-resident Memory T Cells in Asthma, and the corresponding journal article publication titled 'Cytotoxic CD4+ tissue-resident memory T cells are associated with asthma severity', https://doi.org/10.1016/j.medj.2023.09.003). # AirwayCD4CTL_Paper_SupplementalFigures PDF file contains Supplemental Figures S1 to S5 used in Chapter 5 of the PhD thesis and the corresponding published article 'Cytotoxic CD4+ tissue-resident memory T cells are associated with asthma severity', https://doi.org/10.1016/j.medj.2023.09.003 Figure S1. Single-cell clustering analysis using Seurat Figure S2. Single-cell cluster proportions, flow cytometry gating strategy to isolate CD4+ T cells and subsets, and correlation of single-cell cluster proportions with clinical features Figure S3. Expression of differentially expressed genes in CD103+ TRM subset, and bulk RNA-seq and TCR analysis of sorted airway CD4+ T cells in resting condition Figure S4. Qualitative changes in gene expression of airway CD4+ T cell subsets in relation to disease severity and sex Figure S5. Single-cell analysis of CD4+ T cells upon stimulation # AirwayCD4CTL_Paper_SupplementaryTable1 Excel file contains Tables 1A to 1G for Study design and experimental details: 1A - Clinical characterization of subjects with severe and mild asthma 1B - Modified asthma severity score 1C - Experimental and sample details 1D - FACS quantitative analysis in resting condition 1E - Clinical correlations 1F - FACS quantitative analysis of published datasets 1G - Soluble protein levels measured by multiplex ELISA from BAL supernatants # AirwayCD4CTL_Paper_SupplementaryTable2 Excel file contains Tables 2A to 2T for all single cell RNA-seq analyses of BAL CD4+ T cells: 2A - CD4+ cluster cell counts and proportions for each donor in resting and stimulation conditions 2B - Post-sequencing and aggregation quality controls from Cell Ranger 2C - Single-cell differential gene expression analysis (scDGEA) in resting condition 2D - scDGEA comparing CD103+ TRM vs CD103– TRM clusters using sex as covariate 2E - scDGEA comparing CD103+ TRM vs CD103– TRM clusters in male and female asthmatic patients separately 2F - scDGEA comparing CD103+ TRM vs CD103– TRM clusters using treatment as covariate 2G - Gene lists of differential gene expression analysis between CD103+ TRM and CD103– TRM clusters using sex or treatment as covariate 2H - Gene set variation analysis (GSVA) per donor and cluster for lists: TCR signaling, Cytotoxicity, cAMP signaling 2I - scDGEA of CD103+ TRM cluster comparing OCS vs No OCS treatment using sex as covariate 2J - scDGEA of CD103+ TRM cluster comparing Biologics vs No Biologics treatment using sex as covariate 2K - Proportion of GZMB+ cells in comparison to published datasets 2L - scDGEA between disease groups, separated by sex, for each cluster 2M - scDGEA between disease group for each cluster regardless of sex 2N - scDGEA between resting and stimulated cells (all clusters considered) 2O - scDGEA between disease groups for stimulated cells only 2P - scDGEA between disease groups, separated by sex, for all stimulated cells 2Q - Proportion of GZMB+ cells in stimulated data separated by disease 2R - scDGEA of GZMB+ cells vs GZMB– cells using sex as covariate in stimulated data 2S - scDGEA of GZMB+ cells comparing severe vs mild asthma, using sex as covariate, in stimulated data 2T - Coexpression analysis with GZMB-positive cells in stimulation condition # AirwayCD4CTL_Paper_SupplementaryTable3 Excel file contains Tables 3A to 3C for Gene Signatures from single cell RNA-seq analyses of BAL CD4+ T cells: 3A - Gene lists utilized for Gene Set Enrichment Analysis (GSEA) and Signature Modules Scores 3B - Ingenuity Pathway Analysis (IPA) for CD103+ TRM cluster 3C - Pathway enrichment analysis for genes upregulated post-stimulation # AirwayCD4CTL_Paper_SupplementaryTable4 Excel file contains Tables 4A to 4E for DGEA in bulk RNA-seq populations: 4A - Resting bulk populations DGEA between 3 cell types: CD103+ TRM, CD103- TRM, Non-TRM 4B - TCR diversity indexes for CD103+ TRM, CD103- TRM and non-TRM cells 4C - TCR clonotype sharing between CD103+ TRM, CD103- TRM and non-TRM cells 4D - Stimulated bulk populations DGEA between 3 cell types: CD103+ TRM, CD103- TRM and Non-TRM 4E - DGEA between CD103+ TRM in resting and stimulation conditions 2. 'Chapter6_AirwayCD8TCells_SupplementaryTables_Dataset' zipped folder (5 Excel files): (Data for Chapter 6 The Molecular Role of Airway CD8+ Tissue-resident Memory T Cells in Asthma) # AirwayCD8TRM_SupplementaryTable1_ClinicalMetadata_ExperimentalDesign Excel file contains Tables 1a to 1c: 1a - Donor Clinical Metadata (Clinical characterisation of subjects with severe and mild asthma) 1b - Modified asthma severity score 1c - Experimental and sample details # AirwayCD8TRM_SupplementaryTable2_FACS Excel file contains Table 2a: 2a - Flow cytometry of unstimulated CD8+ T cells and CD8+ TRM cells # AirwayCD8TRM_SupplementaryTable3_BulkRNA-seq Excel file contains Tables 3a to 3c for all bulk RNA-seq data analyses of BAL CD8+ TRM cells: 3a - Bulk RNA-seq DGEA between unstimulated and stimulated CD8+ TRM cells 3b - Bulk RNA-seq DGEA of unstimulated CD8+ TRM cells according to asthma severity 3c - Bulk RNA-seq DGEA of stimulated CD8+ TRM cells according to asthma severity # AirwayCD8TRM_SupplementaryTable4_SingleCellRNA-seq Excel file contains Tables 4a to 4h for all single cell RNA-seq data analyses of BAL CD8+ T cells: 4a - Post-sequencing QCs from Cell Ranger (v2.0.0) analysis report of single cell RNA-seq 4b - FACS and single cell cluster proportions for unstimulated and stimulated BAL CD8+ T cells 4c - Activation score gene list for separation of stimulated CD8+ T cells 4d - Single cell DGEA (scDGEA) between unstimulated BAL CD8+ T single cell clusters 4e - scDGEA of unstimulated CD8+ T single cell clusters according to asthma severity 4f - TRM signature score gene list 4g - scDGEA between stimulated and unstimulated BAL CD8+ T cells (all clusters considered) 4h - scDGEA between disease groups for stimulated BAL CD8+ T cells only (sex as covariate) # AirwayCD8TRM_SupplementaryTable5_GSEA Excel file contains Table 5a: 5a - List of genes used for GSEA of unstimulated CD8+ T single cell clusters If data was derived from another source, list source: IBM SPSS 26 (NY, USA) for clinical metadata, GraphPad Prism (v9.1.2) (La Jolla, USA) for generating charts, FlowJo software for FACS data, R software, Python software, STAR aligner (v2.7.3a), Qlucore Omics Explorer (v3.5), 10x Genomics Cell Ranger (v3.1.0) and Seurat (v3.0.2) for all single-cell RNA-seq and bulk RNA-seq data analyses. Date of data collection: AUGUST 2017 - DECEMBER 2023 Information about geographic location of data collection: University of Southampton, U.K., The David Hide Asthma and Allergy Centre, Isle of Wight, U.K., La Jolla Institute for Immunology, San Diego, California, U.S.A. Related projects/Funders: Epigenetics of Severe Asthma. National Institutes of Health. Arshad, Syed Hasan (PI) 01/04/2017 - 31/03/2022 at University of Southampton, U.K., and Pandurangan, Vijayanand (PI) at La Jolla Institute for Immunology, San Diego, California, U.S.A. Grant Number: 2R01HL114093-06A1 FAIN: R01HL114093 -------------------------- SHARING/ACCESS INFORMATION -------------------------- Licence: CC-BY 4.0 license Recommended citation for the data: This dataset supports the thesis: Heena Mistry (2025) "The Role of Airway Tissue-Resident Memory T Cells in Severe Asthma", University of Southampton, Clinical and Experimental Sciences, Faculty of Medicine, PhD Thesis, 1-299. Related publications: Naftel J*, Mistry H*, Mitchell FA, Belson J, Kyyaly MA, Barber C, Haitchi HM, Dennison P, Djukanovic R, Seumois G, Vijayanand P, Arshad SH, Kurukulaaratchy RJ. How Does Mild Asthma Differ Phenotypically from Difficult-to-Treat Asthma? J Asthma Allergy. 2023;16:1333-1345. doi:10.2147/JAA.S430183 Herrera-De La Mata S*, Ramírez-Suástegui C*, Mistry H*, Castañeda-Castro FE, Kyyaly MA, Simon H, Liang S, Lau L, Barber C, Mondal M, Zhang H, Arshad SH, Kurukulaaratchy RJ, Vijayanand P, Seumois G. Cytotoxic CD4+ tissue-resident memory T cells are associated with asthma severity. Med. 2023;4(12):875-897. https://doi.org/10.1016/j.medj.2023.09.003 Mistry H*, Soberanis HM*, Kyyaly MA, Azim A, Barber C, Knight D, Newell C, Haitchi HM, Wilkinson T, Howarth P, Seumois G, Vijayanand P, Arshad SH, Kurukulaaratchy RJ. The clinical implications of Aspergillus fumigatus sensitization in difficult-to-treat asthma patients. The Journal of Allergy and Clinical Immunology: In Practice. 2021;9(12):4254-4267. doi:10.1016/j.jaip.2021.08.038 Kurukulaaratchy RJ*, Mistry H*. New Real-World Insights Into Severe Asthma: All About the Eosinophil? Chest. 2021;160(3):789-790. Azim A, Freeman A, Lavenu A, Mistry H, Haitchi HM, Newell C, Cheng Y, Thirlwall Y, Harvey M, Barber C, Pontoppidan K, Dennison P, Arshad SH, Djukanovic R, Howarth P, Kurukulaaratchy RJ. New perspectives on difficult asthma; sex and age of asthma-onset based phenotypes. The Journal of Allergy and Clinical Immunology: In Practice. 2020;8(10):3396-3406. doi.org/10.1016/j.jaip.2020.05.053 Azim A*, Mistry H*, Freeman A, Barber C, Newell C, Gove K, Thirlwall Y, Harvey M, Bentley K, Knight D, Long K, Mitchell F, Cheng Y, Varkonyi-Sepp J, Grabau W, Dennison P, Haitchi HM, Arshad SH, Djukanovic R, Wilkinson T, Howarth P, Kurukulaaratchy RJ. Protocol for the Wessex AsThma CoHort of difficult asthma (WATCH): a pragmatic real-life longitudinal study of difficult asthma in the clinic. BMC Pulmonary Medicine. 2019;19:1-11. doi.org/10.1186/s12890-019-0862-2