Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published May 20, 2022 | Accepted
Journal Article Open

Single-cell deletion analyses show control of pro–T cell developmental speed and pathways by Tcf7, Spi1, Gata3, Bcl11a, Erg, and Bcl11b

Abstract

As early T cell precursors transition from multipotentiality to T lineage commitment, they change expression of multiple transcription factors. It is unclear whether individual transcription factors directly control choices between T cell identity and some alternative fate or whether these factors mostly affect proliferation or survival during the normal commitment process. Here, we unraveled the impacts of deleting individual transcription factors at two stages in early T cell development, using synchronized in vitro differentiation systems, single-cell RNA-seq with batch indexing, and controlled gene-disruption strategies. First, using a customized method for single-cell CRISPR disruption, we defined how the early-acting transcription factors Bcl11a, Erg, Spi1 (PU.1), Gata3, and Tcf7 (TCF1) function before commitment. The results revealed a kinetic tug of war within individual cells between T cell factors Tcf7 and Gata3 and progenitor factors Spi1 and Bcl11a, with an unexpected guidance role for Erg. Second, we tested how activation of transcription factor Bcl11b during commitment altered ongoing cellular programs. In knockout cells where Bcl11b expression was prevented, the cells did not undergo developmental arrest, instead following an alternative path as T lineage commitment was blocked. A stepwise, time-dependent regulatory cascade began with immediate-early transcription factor activation and E protein inhibition, finally leading Bcl11b knockout cells toward exit from the T cell pathway. Last, gene regulatory networks of transcription factor cross-regulation were extracted from the single-cell transcriptome results, characterizing the specification network operating before T lineage commitment and revealing its links to both the Bcl11b knockout alternative network and the network consolidating T cell identity during commitment.

Additional Information

© 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. his is an article distributed under the terms of the Science Journals Default License. Received: 2 September 2021. Accepted: 11 April 2022. We thank J. Park and S. Chen from the Caltech Single Cell Profiling and Engineering Center for providing support for processing 10X Chromium samples, B. Shin for discussions and additional data visualization, R. Diamond and members of the Caltech Flow Cytometry and Cell Sorting facility for sorting, I. Soto for mouse care, M. Quiloan for mouse genotyping and supervision, and I. Antoshechkin and V. Kumar of the Caltech Jacobs Genomics Facility for bulk RNA-seq. We also thank G. Crooks and A. Montel-Hagen (UCLA) for sharing the mATO system with us. Support for this project came from USPHS grants (R01AI135200, R01HL119102, and R01HD100039) to E.V.R., the Beckman Institute at Caltech for support of all the Caltech facilities, the Biology and Biological Engineering Division Bowes Leadership Chair Fund, the Louis A. Garfinkle Memorial Laboratory Fund, and the Al Sherman Foundation. E.V.R. acknowledges past support from the Albert Billings Ruddock Professorship. Author contributions: W.Z. and E.V.R. conceptualized the project, wrote the paper, and edited the paper. In addition, W.Z. designed the project, carried out the experiments, and analyzed the data. W.Z. and F.G. developed the methodology. F.G. wrote the in-house bioinformatic pipeline for Perturb-seq and hashtag alignment and assignment, provided further analysis, and edited the manuscript. M.R.-W. and S.J. performed preliminary experiments. E.V.R. supervised research, acquired funding, and provided additional data analysis. Competing interests: W.Z. is employed by BillionToOne Inc. and has been employed by 10x Genomics. E.V.R. is a member of the Scientific Advisory Board for Century Therapeutics and has advised Kite Pharma and A2 Biotherapeutics. Data and materials availability: Custom-made software for analysis of single-cell transcriptome perturbations using gRNA and batch hashtags has been released and is now available at https://github.com/gaofan83/single_cell_perturb_seq/releases/tag/v.1.0.0. All genomic sequencing data have been deposited in Gene Expression Omnibus under accession numbers GSE165835 and GSE183026. All other data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.

Attached Files

Accepted Version - nihms-1820192.pdf

Supplemental Material - sciimmunol.abm1920_sm.pdf

Supplemental Material - sciimmunol.abm1920_tables_s1_to_s12.zip

Files

nihms-1820192.pdf
Files (25.0 MB)
Name Size Download all
md5:7ceb3bee2d754668662f4d6fa536b1c6
4.0 MB Preview Download
md5:d33ffe738dc0e73ef9c30fcc6487356a
3.7 MB Preview Download
md5:d31e38290f5d7d65eb3293114e33410b
17.3 MB Download

Additional details

Created:
October 25, 2023
Modified:
January 9, 2024