Class C2 records a proxy response. The proxy holds for the conditions under which it was measured, and durable phenotypic change is a separate question. Boundary conditions.
Briggs combinatorial TF landscape
Briggs JA, Cho J, Strebinger D, Joung J, Braun TW, Macrae RK, Li H, Zhang F
2026 · Cell systems
Mammalian cells can be directed toward specific fates by overexpression of transcription factors (TFs).
Abstract
From the original paper, Cell systems · PubMed
Mammalian cells can be directed toward specific fates by overexpression of transcription factors (TFs). However, discovering and optimizing which TFs in combination produce a state of interest remains challenging. Here, we develop a scalable screening platform that addresses this challenge by combining high multiplicity of infection (MOI), pooled delivery of barcoded TF open reading frames (ORFs), data augmentation, targeted cell enrichments, and single-cell transcriptomic readouts. As proof of principle, we apply the platform to optimize the generation of hematopoietic stem and progenitor-like cells (HSPCs) from human embryonic stem cells. Our data demonstrate technical performance across a range of key metrics and reveal a richly structured reprogramming fitness landscape over millions of TF combinations. In silico optimization of HSPC-similarity metrics over this landscape revealed two TF combinations that demonstrate superior potency in generating naive multipotent hematopoietic progenitors relative to gold-standard controls. This study demonstrates a powerful approach for data-driven cell fate engineering using complex combinatorial perturbations.
Summary
Editorial summary pending review by the maintainer. The paper's own abstract appears above; the Atlas summary in the maintainer's voice will explain how Briggs combinatorial TF landscape relates to the inverse-design framework of the review.
Why this class
Level 2 because the method instantiates the inverse-design objective through an empirical or learned proxy response map rather than a mechanistic intervention-dependent model. Representation family is signature / state-matching. Cited in §3.3 of the review. Editorial rationale pending review by the maintainer.