Framework for in vivo T cell screens

Lauren E Milling; Samuel C Markson; Qin Tjokrosurjo; Nicole M Derosia; Ivy S L Streeter; Grant H Hickok; Ashlyn M Lemmen; Thao H Nguyen; Priyamvada Prathima; William Fithian; Marc A Schwartz; Nir Hacohen; John G Doench; Martin W LaFleur; Arlene H Sharpe

doi:10.1084/jem.20230699

Framework for in vivo T cell screens

J Exp Med. 2024 Apr 1;221(4):e20230699. doi: 10.1084/jem.20230699. Epub 2024 Feb 27.

Authors

Lauren E Milling^#^{1

2}, Samuel C Markson^#^{1

2

3}, Qin Tjokrosurjo^{1

2}, Nicole M Derosia^{1

2}, Ivy S L Streeter^{1

2}, Grant H Hickok^{1

2}, Ashlyn M Lemmen^{1

2}, Thao H Nguyen^{1

2}, Priyamvada Prathima^{1

2}, William Fithian⁴, Marc A Schwartz^{3

5}, Nir Hacohen^{3

5}, John G Doench³, Martin W LaFleur^#^{1

2

3}, Arlene H Sharpe^#^{1

2

3}

Affiliations

¹ Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
² Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital, Massachusetts General Hospital and Harvard Medical School , Boston, MA, USA.
³ Broad Institute of Harvard and Massachusetts Institute of Technology , Cambridge, MA, USA.
⁴ Department of Statistics, University of California, Berkeley, Berkeley, CA, USA.
⁵ Department of Medicine, Massachusetts General Hospital Cancer Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

^# Contributed equally.

PMID: 38411617
PMCID: PMC10899089 (available on 2024-08-27)
DOI: 10.1084/jem.20230699

Abstract

In vivo T cell screens are a powerful tool for elucidating complex mechanisms of immunity, yet there is a lack of consensus on the screen design parameters required for robust in vivo screens: gene library size, cell transfer quantity, and number of mice. Here, we describe the Framework for In vivo T cell Screens (FITS) to provide experimental and analytical guidelines to determine optimal parameters for diverse in vivo contexts. As a proof-of-concept, we used FITS to optimize the parameters for a CD8+ T cell screen in the B16-OVA tumor model. We also included unique molecular identifiers (UMIs) in our screens to (1) improve statistical power and (2) track T cell clonal dynamics for distinct gene knockouts (KOs) across multiple tissues. These findings provide an experimental and analytical framework for performing in vivo screens in immune cells and illustrate a case study for in vivo T cell screens with UMIs.

MeSH terms

Animals
CD8-Positive T-Lymphocytes*
Gene Knockout Techniques
Mice

Grants and funding

U19 AI133524/AI/NIAID NIH HHS/United States