Researchers from Gladstone Institutes, UC San Francisco, and Stanford University, working alongside Biohub, have revealed a full, high-resolution functional map of human immune cells aimed at transforming insights into how genetics influence health and disease. The study, published in Cell, marks a significant milestone in immunology and genomics. Through systematic stress-testing of genes across the genome in 22 million human immune cells, researchers moved past simple DNA sequencing to unravel the dynamic circuits governing gene activity in health and disease contexts. This advancement from observation to intervention provides a robust new framework for developing cancer immunotherapies and addressing autoimmune disorders, among other applications.
From Blueprint to Operating System
This new study builds on decades of biological research, according to Alex Marson, MD, PhD, who leads the Gladstone-UCSF Institute of Genomic Immunology and co-authored the findings. He notes that earlier efforts, like the Human Genome Project, provided the genetic code, while later projects such as the Human Cell Atlas revealed how cells interpret it. Now, scientists are exploring the consequences of altering genes directly, offering a clearer path to understanding how genetic changes influence cell behavior and function.
The findings also represent the largest single addition to the Billion Cells Project, a Biohub initiative aimed at assembling an open-access database of one billion individual cells. This resource will help train artificial intelligence systems to forecast cellular responses, accelerate research progress, and identify innovative disease treatments. It is part of Biohub’s broader Virtual Biology Initiative, which seeks to establish an open-data infrastructure for AI-driven biological research.
Unlike past studies that relied on standardized lab cell lines, this research focused on real human immune cells—specifically T cells—from blood donors. Using Perturb-seq, the team systematically deactivated nearly 12,800 genes in these cells. Emma Dann, PhD, a postdoctoral researcher at Gladstone and co-first author, explains that the results highlight how gene disruptions affect real immune cells differently than lab-grown ones. These cells still react to immune signals, and because they come from actual people, the findings directly reflect the immune variations seen in patients.
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Previously, researchers were just cataloging individual genes. Now, they can begin to connect them into a circuit, much like the circuits that control a computer. “This is fundamental to understanding how a cell actually ‘thinks’ and responds to its environment,” explains Ronghui (Ron) Zhu, PhD, a postdoctoral scholar at Gladstone and the study’s co-first author. This context-specific data is also essential for the future of “virtual biology,” where AI models are used to predict cell behavior. Notably, it serves as proof that such models must be trained on a diverse set of cell states and health scenarios to make accurate, reliable predictions.
The massive scale of the research was enabled by partnerships with industry leaders 10x Genomics and Ultima Genomics. 10x Genomics provided high-resolution single-cell analysis, while Ultima Genomics offered high-throughput sequencing capabilities. Together, these platforms allowed the scientists to screen a staggering 33.4 million cells, ultimately yielding 22 million high-quality cells used for the final analysis and map. The scientists are already pivoting to the next phase of their work, which will focus specifically on cancer. They plan to apply their genome-scale Perturb-seq approach to track how genetic changes alter human T cells as they infiltrate and interact with complex tumor environments.
The Next Frontier: Cancer Research
“We now have a fundamental rulebook of how genes control T cell responses,” Marson says. “Our hope is that this becomes a standard lookup table for the entire field, allowing any scientist to instantly see how a specific gene affects cells of the human immune system.”
