Harnessing single-cell genomics to improve the physiological fidelity of organoid-derived cell types.
Authors | |
Keywords | |
Abstract | BACKGROUND: Single-cell genomic methods now provide unprecedented resolution for characterizing the component cell types and states of tissues such as the epithelial subsets of the gastrointestinal tract. Nevertheless, functional studies of these subsets at scale require faithful in vitro models of identified in vivo biology. While intestinal organoids have been invaluable in providing mechanistic insights in vitro, the extent to which organoid-derived cell types recapitulate their in vivo counterparts remains formally untested, with no systematic approach for improving model fidelity. RESULTS: Here, we present a generally applicable framework that utilizes massively parallel single-cell RNA-seq to compare cell types and states found in vivo to those of in vitro models such as organoids. Furthermore, we leverage identified discrepancies to improve model fidelity. Using the Paneth cell (PC), which supports the stem cell niche and produces the largest diversity of antimicrobials in the small intestine, as an exemplar, we uncover fundamental gene expression differences in lineage-defining genes between in vivo PCs and those of the current in vitro organoid model. With this information, we nominate a molecular intervention to rationally improve the physiological fidelity of our in vitro PCs. We then perform transcriptomic, cytometric, morphologic and proteomic characterization, and demonstrate functional (antimicrobial activity, niche support) improvements in PC physiology. CONCLUSIONS: Our systematic approach provides a simple workflow for identifying the limitations of in vitro models and enhancing their physiological fidelity. Using adult stem cell-derived PCs within intestinal organoids as a model system, we successfully benchmark organoid representation, relative to that in vivo, of a specialized cell type and use this comparison to generate a functionally improved in vitro PC population. We predict that the generation of rationally improved cellular models will facilitate mechanistic exploration of specific disease-associated genes in their respective cell types. |
Year of Publication | 2018
|
Journal | BMC Biol
|
Volume | 16
|
Issue | 1
|
Pages | 62
|
Date Published | 2018 06 05
|
ISSN | 1741-7007
|
DOI | 10.1186/s12915-018-0527-2
|
PubMed ID | 29871632
|
PubMed Central ID | PMC5989470
|
Links | |
Grant list | HHMI / Howard Hughes Medical Institute / United States
1R33CA202820 / NH / NIH HHS / United States
R01 HL095722 / HL / NHLBI NIH HHS / United States
2U19AI089992 / NH / NIH HHS / United States
RM1 HG006193 / HG / NHGRI NIH HHS / United States
P01 AI039671 / AI / NIAID NIH HHS / United States
2R01HL095791 / NH / NIH HHS / United States
K08 AI130392 / AI / NIAID NIH HHS / United States
R01 HL095791 / HL / NHLBI NIH HHS / United States
1R01AI138546 / NH / NIH HHS / United States
R56 HL126554 / HL / NHLBI NIH HHS / United States
2RM1HG006193 / HG / NHGRI NIH HHS / United States
1R01HL126554 / NH / NIH HHS / United States
1U54CA217377 / NH / NIH HHS / United States
P30 DK034854 / DK / NIDDK NIH HHS / United States
R33 CA202820 / CA / NCI NIH HHS / United States
P30 CA014051 / CA / NCI NIH HHS / United States
R01 DE013023 / DE / NIDCR NIH HHS / United States
R01 AI138546 / AI / NIAID NIH HHS / United States
U24 AI118672 / AI / NIAID NIH HHS / United States
1R01DA046277 / NH / NIH HHS / United States
U54 CA217377 / CA / NCI NIH HHS / United States
1DP2OD020839 / GM / NIGMS NIH HHS / United States
5U24AI118672 / National Institute of Allergy and Infectious Diseases / International
U19 AI089992 / AI / NIAID NIH HHS / United States
R01 DA046277 / DA / NIDA NIH HHS / United States
|