Understanding gene expression within the body has been a boon for 21st century biology and therapeutics, but most discoveries using these techniques have focused only on one small region of one organ or tissue.
At the University of Chicago’s Pritzker School of Molecular Engineering (UChicago PME), Assoc. Professor Nicolas Chevrier’s group has developed a new system for understanding how disease affects molecules, cells, tissues, and organs throughout the body. This is a major goal of both scientists and doctors. This interdisciplinary research was led by Maggie Clevenger, a staff scientist in the lab, and included several industry and academic collaborators.
By developing new techniques to prepare specimens for testing and combining them with computational tools, including machine learning models, Dr. Chevrier and his lab mapped gene expression across sections of the mouse’s entire body.
The system accurately mapped every organ, tissue region, and approximately 75% of known cell types in the mouse body, providing a toolkit that researchers could use to study molecular and cellular processes throughout the entire body of laboratory mice. The results were announced today. cellit has the potential to be used both in basic scientific research and in fields such as drug discovery.
We now have the tools to generate datasets at a scale previously unimaginable. This lays the foundation for generating the kind of data needed to build “virtual mice” that can be used to test treatments and understand biological processes throughout the body. That’s the ultimate goal. ”
Associate Professor Nicola Chebrier, University of Chicago Pritzker School of Molecular Engineering
Measuring systemic inflammation throughout the body
This new technology leverages spatial transcriptomics, which uses high-resolution microscopy and gene sequencing to measure gene expression across tissues. Optimized over the past decade, this technology gives researchers important insights into structures and diseases within organs or tissue samples, rather than just single cells.
However, researchers have been troubled by the small scale this technique allows. Chevrier wanted to use this to measure gene expression across mouse models.
In 2025, he and his team developed Array-seq, which uses DNA microarrays with custom-designed probes to analyze tissue samples.
But to use its Array-seq technology to analyze whole mice, researchers needed to develop a way to generate very thin slices of frozen mouse bodies and transfer them to Array-seq slides with the RNA intact and preserved. In collaboration with Professor Tadafumi Kawamoto of Tsurumi University in Yokohama, they did just that, obtaining whole-body cross-sections of laboratory mice with average cell thickness.
After performing spatial transcriptomics on the specimens, the team developed a new computational model to annotate cellular information throughout the mouse. The model was developed in collaboration with Ashwini Patil of Combinatics (Chiba, Japan), a long-time industrial partner of the lab.
The research team also worked with AI expert Professor Feng Bao from Fudan University in Shanghai, China, to create a new machine learning model that labels each organ, tissue, and cell type on tissue sections simply stained with hematoxylin and eosin, the most widely used stains in tissue research and clinical diagnosis.
“If we were to do this manually, we would have to label all these different cell types in the lab using staining reagents such as antibodies, which is currently not possible to do throughout the mouse body,” Chevrier said. “We trained an AI model to do this, so now we can do it virtually and very cheaply.”
To test the new techniques, they used them to measure inflammation in a mouse model of sepsis. Sepsis is a dysregulated immune response of the whole organism to infection and is a major public health challenge.
“For the first time, we have been able to quantify the effects of systemic inflammation on all cell types and all major organ tissues at a scale never before possible,” Professor Chevrier said. “This paves the way for molecular mapping of laboratory mice and many other model systems on an unprecedented scale.”
A big step towards a “virtual mouse”
The new system could be used to study how genes affect areas throughout the body and to study the effects of new drugs. “It can show how the drug is affecting the tissue in a way that was not predicted,” Chevrier said.
The next goal is to use this system to model the entire body of the mouse, rather than just one slice of the mouse. This is an important step in creating the kind of data that could one day help create “virtual mouse” models that could be used in place of real mice for research.
“We think this data could be one of the technologies to realize this vision of a virtual laboratory mouse model,” Chevrier said.
Other authors on the paper include Maggie Clevenger, Dennis Sypulko, Ashwini Patil, Bohan Li, Michihiro Takahama, Mei Linghan, Madison Plaster, Gabriela Ritchie, and Feng Bao.
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Reference magazines:
M.H., Clevenger; others. (2026). Whole body molecular and cellular mapping of laboratory mice. cell. DOI: 10.1016/j.cell.2026.03.006. https://www.cell.com/cell/abstract/S0092-8674(26)00273-4
