Commensal bacteria maintain a Qa-1b-restricted unconventional CD8+ T population in gut epithelium
Data files
Dec 12, 2023 version files 45.93 KB
Abstract
Intestinal intraepithelial lymphocytes (IELs) are characterized by an unusual phenotype and developmental pathway, yet their specific ligands and functions remain largely unknown. Here by analysis of QFL T cells, a population of CD8+ T cells critical for monitoring the MHC I antigen processing pathway, we established that unconventional Qa-1b-restricted CD8+ T cells are abundant in intestinal epithelium. We found that QFL T cells showed a Qa-1b-dependent unconventional phenotype in the spleen and small intestine of naïve wild-type mice. The splenic QFL T cells showed innate-like functionality exemplified by rapid response to cytokines or antigens, while the gut population was refractory to stimuli. Microbiota was required for the maintenance, but not the initial gut homing of QFL T cells. Interestingly, monocolonization with Pediococcus pentosaceus, which expresses a peptide that cross-activated QFL T cells, was sufficient to maintain QFL T cells in the intestine. Thus, microbiota is critical for shaping the Qa-1b-restricted IEL landscape.
README: Commensal Bacteria Maintain a Qa-1b-restricted Unconventional CD8+ T Population in Gut Epithelium
https://doi.org/10.5061/dryad.vq83bk40q
1. Author Information
A. Corresponding Author Contact Information
Name: Jian Guan
Institution: Department of Pathology and the Institute of Cell Engineering, Johns Hopkins University School of Medicine
Address: Baltimore, MD 21287 USA
Email: jian.guan.cc@outlook.com
B. Co-corresponding Author Contact Information
Name: Scheherazade Sadegh-Nasseri
Institution: Department of Pathology and the Institute of Cell Engineering, Johns Hopkins University School of Medicine
Address: Baltimore, MD 21287 USA
Email: ssadegh@jhmi.edu
2. Information about funding sources that supported the collection of the data: This work was supported by grants R01AI130210, R37AI060040 and R01AI149341 from the National Institutes of Health to NS.
3. DATA & FILE OVERVIEW
File name: RawData_Figure_SPF vs GF QFL-T
The file contains data acquired through flow cytometry for analysis of various populations of immune cells in SPF/GF WT and SPF ERAP1-KO, Qa-1b-KO, TAP-KO mice. These data were used for analysis presented in Figure 1,2,3, 5 and 7. Mice information is indicated by the sheet names. Sample information is indicated in the 'Sample' column. Population information is indicated in the first row of each sheet.
The absolute QFL T numbers per tissue were calculated using counting beads (absolute_QFL_T_number = sample_QFL_T_number/number_animal_pool; sample_QFL_T_number = QFL_T_count/fraction_acquired; fraction_acquired = beads_count/beads_added).
4. SHEET-SPECIFIC INFORMATION
1) Sheet name: ’SPF Sp QFL-T’, ‘GF Sp QFL-T’
Data List:
\* Sample: sample ID (date of collection_strain_<experiment name>.fcs)
\* QFL/organ/animal: number of QFL T cells per organ per tissue
\* Age: age of mouse (weeks)
\* %QFL-T Va3.2: percentage of Va3.2+ in QFL T
\* %Total Va3.2: percentage of Va3.2+ in total CD8
\* % QFL-T CD44: percentage of CD44hi in QFL T
\* %Total CD44: percentage of CD44hi in total CD8
\* no. CD4 QFL-T: number of CD4+ QFL T
2) Sheet Name: ‘SPF IEL’, ‘GF IEL’
Data List:
\* Sample: sample ID (date of collection_strain_<experiment name>.fcs)
\* QFL/organ/animal: number of QFL T cells per organ per tissue
\* Age: age of mouse (weeks)
\* %QFL-T Va3.2: percentage of Va3.2+ in QFL T
\* %CD8aa in Va3.2+QFL: percentage of CD8aa+ in Va3.2+ QFL T
\* %CD8ab in Va3.2+QFL: percentage of CD8ab+ in Va3.2+ QFL T
\* No.Va3.2+QFL: number of Va3.2+ QFL T
\* No.CD8aa Va3.2+QFL: number of CD8aa+ Va3.2+ QFL T
\* No. CD8ab Va3.2+QFL: number of CD8ab+ Va3.2+ QFL T
\* No.Va3.2-QFL: number of Va3.2- QFL T
\* %CD8aa in Va3.2-QFL: percentage of CD8aa+ in Va3.2- QFL T
\* %CD8ab in Va3.2-QFL: percentage of CD8ab+ in Va3.2- QFL T
\* No.CD8aa Va3.2-QFL: number of CD8aa+ Va3.2- QFL T
\* No. CD8ab Va3.2-QFL: number of CD8ab+ Va3.2- QFL T
3) Sheet name: ‘SPF strains IEL QFL T number’, ‘SPF strains Sp QFL T number’
Data List:
\* Sample: sample ID (date of collection_strain_<experiment name>.fcs)
\* Beads| Count: number of beads in aquired
\* No. Of Beads Added: number of Beads Added
\* Fraction Aquired: ‘Beads| Count’ divided by ‘No. Of Beads Added’
\* Lymphocytes/Single Cells/CD45+CD19-/TCRb+CD4-/QFL-T | Count: number of QFL T in gate
\* No. of animals pooled: number of animals pooled
\* Panel : antibody panel used for analysis
\* QFL/organ/animal: number of QFL T cells per organ per tissue
4) Sheet name: ‘Total spleen Va3.2 CD44’
Data List:
\* Sample: sample ID (date of collection_strain_<experiment name>.fcs)
\* Beads| Count: number of beads in aquired
\* No. Of Beads Added: number of Beads Added
\* Fraction Aquired: ‘Beads| Count’ divided by ‘No. Of Beads Added’
\* Lymphocytes/Single Cells/CD45+CD19-/TCRb+CD4-/Va3.2+/CD8ab/CD44hi | Count: number of total Va3.2+CD8+CD44hi in gate
\* Lymphocytes/Single Cells/CD45+CD19-/TCRb+CD4-/Va3.2-/CD8ab/CD44hi | Count: number of total Va3.2-CD8+CD44hi in gate
\* Va3.2+ CD44hi No.: number of Va3.2+CD8+CD44hi per animal per tissue
\* Va3.2- CD44hi No. : number of Va3.2-CD8+CD44hi per animal per tissue
5. Missing data codes: None
6. Specialized formats or other abbreviations used: Qa-1b-ko(Qko/Q-ko), ERAAP-KO (EKO), Tap-KO(TKO), Before enrichment (Bf), Enriched(Er), Germ-free(GF)
Methods
The raw data were collected from flow cytometry analysis. The numbers were calculated in Excel.