Flow cytometric analysis and purification of airway epithelial cell subsets
Abstract The human airway epithelium is essential in homeostasis, and epithelial dysfunction contributes to chronic airway disease. Development of flow cytometric methods to characterize subsets of airway epithelial cells will enable further dissection of airway epithelial biology. Leveraging single cell RNA-sequencing (scRNA-seq) data in combination with known cell type-specific markers, we developed panels of antibodies to characterize and isolate the major airway epithelial subsets (basal, ciliated, and secretory cells) from human bronchial epithelial cell cultures. We also identified molecularly distinct subpopulations of secretory cells and demonstrated cell subset-specific expression of low abundance transcripts and micro-RNAs that are challenging to analyze with current scRNA-seq methods. These new tools will be valuable for analyzing and separating airway epithelial subsets and interrogating airway epithelial biology..
| Medienart: |
|
|---|
Preprint| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
bioRxiv.org - (2022) vom: 22. Okt. Zur Gesamtaufnahme - year:2022 |
|---|
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Bonser, Luke R. [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| doi: |
10.1101/2020.04.20.051383 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
XBI017742439 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | XBI017742439 | ||
| 003 | DE-627 | ||
| 005 | 20230429101723.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 200427s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1101/2020.04.20.051383 |2 doi | |
| 035 | |a (DE-627)XBI017742439 | ||
| 035 | |a (biorXiv)10.1101/2020.04.20.051383 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Bonser, Luke R. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Flow cytometric analysis and purification of airway epithelial cell subsets |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Abstract The human airway epithelium is essential in homeostasis, and epithelial dysfunction contributes to chronic airway disease. Development of flow cytometric methods to characterize subsets of airway epithelial cells will enable further dissection of airway epithelial biology. Leveraging single cell RNA-sequencing (scRNA-seq) data in combination with known cell type-specific markers, we developed panels of antibodies to characterize and isolate the major airway epithelial subsets (basal, ciliated, and secretory cells) from human bronchial epithelial cell cultures. We also identified molecularly distinct subpopulations of secretory cells and demonstrated cell subset-specific expression of low abundance transcripts and micro-RNAs that are challenging to analyze with current scRNA-seq methods. These new tools will be valuable for analyzing and separating airway epithelial subsets and interrogating airway epithelial biology. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Koh, Kyung Duk |e verfasserin |4 aut | |
| 700 | 1 | |a Johansson, Kristina |e verfasserin |4 aut | |
| 700 | 1 | |a Choksi, Semil P. |e verfasserin |4 aut | |
| 700 | 1 | |a Cheng, Dan |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Leqian |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Dingyuan I. |e verfasserin |4 aut | |
| 700 | 1 | |a Zlock, Lorna T. |e verfasserin |4 aut | |
| 700 | 1 | |a Eckalbar, Walter L. |e verfasserin |4 aut | |
| 700 | 1 | |a Finkbeiner, Walter E. |e verfasserin |4 aut | |
| 700 | 1 | |a Erle, David J. |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2022) vom: 22. Okt. |
| 773 | 1 | 8 | |g year:2022 |g day:22 |g month:10 |
| 856 | 4 | 0 | |u https://doi.org/10.1165/rcmb.2020-0149MA |z lizenzpflichtig |3 Volltext |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1101/2020.04.20.051383 |z kostenfrei |3 Volltext |
| 912 | |a GBV_XBI | ||
| 912 | |a SSG-OLC-PHA | ||
| 951 | |a AR | ||
| 952 | |j 2022 |b 22 |c 10 | ||