HCA Data Explorer

Single-cell atlas of bronchoalveolar lavage from preschool cystic fibrosis reveals new cell phenotypes

Updated July 11, 2023

Inflammation is a key driver of cystic fibrosis (CF) lung disease, not addressed by current standard care. Improved understanding of the mechanisms leading to aberrant inflammation may assist the development of effective anti-inflammatory therapy. Single-cell RNA sequencing (scRNA-seq) allows profiling of cell composition and function at previously unprecedented resolution. Herein, we seek to use multimodal single-cell analysis to comprehensively define immune cell phenotypes, proportions and functional characteristics in preschool children with CF. We analyzed 42,658 cells from bronchoalveolar lavage of 11 preschool children with CF and a healthy control using scRNA-seq and parallel assessment of 154 cell surface proteins. Validation of cell types identified by scRNA-seq was achieved by assessment of samples by spectral flow cytometry. Analysis of transcriptome expression and cell surface protein expression, combined with functional pathway analysis, revealed 41 immune and epithelial cell populations in BAL. Spectral flow cytometry analysis of over 256,000 cells from a subset of the same patients revealed high correlation in major cell type proportions across the two technologies. Macrophages consisted of 13 functionally distinct sub populations, including previously undescribed populations enriched for markers of vesicle production and regulatory/repair functions. Other novel cell populations included CD4 T cells expressing inflammatory IFNα/β and NFκB signalling genes. Our work provides a comprehensive cellular analysis of the pediatric lower airway in preschool children with CF, reveals novel cell types and provides a reference for investigation of inflammation in early life CF.

Melanie NeelandMurdoch Children’s Research Institute; University of Melbournemelanie.neeland@mcri.edu.au
Jovana Maksimovic1
Shivanthan Shanthikumar2
George Howitt3
Peter Hickey4
William Ho5
Casey Anttila5
Daniel Brown5
Anne Senabouth6
Dominik Kaczorowski6
Daniela Amann-Zalcenstein5
Joseph Powell6
Sarath Ranganathan2
Alicia Oshlack3
Melanie Neeland7
1Peter MacCallum Cancer Centre; Murdoch Children’s Research Institute; University of Melbourne
2Murdoch Children’s Research Institute; University of Melbourne; Royal Children’s Hospital
3Peter MacCallum Cancer Centre; University of Melbourne
4WEHI; University of Melbourne
5WEHI
6Garvan Institute of Medical Research; University of New South Wales
7Murdoch Children’s Research Institute; University of Melbourne
Ida Zucchi

To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/1eba4d0b-2d15-4ba7-bb3c-d4654dd94519

Supplementary links are provided by contributors and represent items such as additional data which can’t be hosted here; code that was used to analyze this data; or tools and visualizations associated with this specific dataset.

1.https://oshlacklab.com/paed-cf-cite-seq/2.https://zenodo.org/record/6651465
None

Downloaded and exported data is governed by the HCA Data Release Policy and licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). For more information please see our Data Use Agreement.

Analysis Portals

None

Project Label

BALPreschoolCF

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

lung

Organ Part

Unspecified

Selected Cell Types

Unspecified

Disease Status (Specimen)

2 disease statuses

Disease Status (Donor)

2 disease statuses

Development Stage

child stage

Library Construction Method

2 library construction methods

Nucleic Acid Source

single cell

Paired End

false

Analysis Protocol

10x_matrix_generation, CITE_matrix_generation

File Format

2 file formats

Cell Count Estimate

42.7k

Donor Count

12
rds.gz2 file(s)xlsx1 file(s)