The body’s organs are constantly communicating. Adipose tissue tells the liver when to store or release energy, the immune system sends signals for local inflammation, and thousands of proteins relay these messages to organs throughout the body. But while scientists have long known that such conversations exist, they have struggled to pinpoint exactly which cells are sending which messages.
Now researchers have discovered a way to listen. By refining an existing protein tagging technique called “proximity labeling” and applying it to genetically engineered mice, the team developed a platform to trace proteins back to their cells of origin and track their manufacture and folding in the endoplasmic reticulum (ER). This allowed us to create the most detailed map to date of how fat cells and liver cells communicate and how these networks are rewired during inflammation, fasting, and obesity. The researchers cross-referenced their findings with UK Biobank data and linked 65 of these signals to human conditions such as type 2 diabetes and cardiovascular disease.
However, the researchers point out that the most important contribution of this work is not the discovery of a single protein messenger, but rather the construction of a powerful new framework for studying how organs communicate, opening the door to the discovery of new biological pathways, and identifying signals that may serve as future biomarkers and therapeutic targets for any disease.
This platform is very broadly applicable. It can be applied to different tissues and different genetic factors, and biologists in all fields can use it to study communication between cells. ”
Ekaterina V. Vinogradova, Head of the Chemical Immunology and Proteomics Laboratory
combine expertise
A major hurdle in eavesdropping on communication between organs is that scientists have been unable to meaningfully listen to only one side of the conversation. The bloodstream is full of protein messengers that carry instructions between tissues, and researchers can often detect the signals. However, determining exactly which cell sent each message has proven difficult.
Some researchers have tried measuring RNA in cells as a proxy for the proteins they produce. Some researchers study isolated cells in the lab or use chemical tagging methods to label proteins before they enter the circulation. However, the RNA level often does not predict which proteins a cell will ultimately secrete, labeling techniques often cannot detect low abundance signaling molecules, and cultured cells cannot fully reproduce an organism’s physiology. “A major limitation in this field has been how to discover these proteins in vivo,” says Paul Cohen, director of the Wesley R. Janeway and William H. Janeway Institute for Molecular Metabolism.
The collaboration that would eventually overcome that limitation began with a shared frustration. Ken H. Loh, then a Rockefeller postdoctoral fellow in Jeffrey M. Friedman’s laboratory and now an assistant professor at Yale University, was interested in studying the communication between fat cells and the nerves present within adipose tissue. He genetically engineered a mouse model that indiscriminately tags proteins as they pass through the endoplasmic reticulum. By tagging proteins as they pass through the endoplasmic reticulum, researchers could potentially trace secreted proteins found in the bloodstream to the specific cells that produced them, which Lo and Friedman shared with Cohen and Vinogradova, sparking their collaboration. But when each lab started treating mice separately, they found they were running into exactly the same technical hurdles. We were struggling to successfully enrich tagged proteins and avoid losing rare signals in our mass spectrometry data. The mice were doing their job, but the challenge was to extract and detect the tagged proteins with enough sensitivity to be useful. “We realized that by joining forces, we could create more impactful stories together,” Cohen says.
Platform optimization
Lo and Cohen’s groups combined their expertise to contribute to physiological models of fasting, inflammation, and obesity, while Vinogradova’s lab refined the tissue processing workflows, proteomics, and computational pipelines needed to isolate and identify tagged proteins. The team worked together to improve how the platform recovers proteins from tissue and blood, reducing missing values in mass spectrometry data. The result is a much more sensitive platform that can detect trace signaling molecules in the circulation that previous studies could not detect, such as the fat-derived hormone leptin.
“Without optimization, the platform identified only the most abundant proteins, and these are generally the ones that people already know about,” Cohen says. “It is only by refining our techniques that we have been able to go deeper into uncharted territory in biology. What makes discoveries like this possible is not just having the technology, but executing it with great rigor and well.”
The team then put their optimized platform to work on fat cells and liver cells and tracked how these tissues responded to fasting, inflammation, and obesity. To understand the progression of metabolic diseases, the researchers compared protein communication networks in visceral fat around internal organs and subcutaneous fat under the skin in both early and advanced obesity, and also demonstrated the broad applicability of this platform to immunology by successfully mapping B lymphocyte protein production at baseline. They chose to study adipocytes, liver cells, and immune cells because they needed a well-understood testing ground to validate their newly optimized platform. Furthermore, these choices reflect the interests of both laboratories. Cohen studies how organs, particularly adipose tissue, communicate information to regulate metabolism throughout the body. Vinogradova uses chemical proteomics techniques to study the function of immune proteins.
“Adipose tissue is a humoral center of metabolic regulation, and its secretory repertoire clearly exceeds known circulating factors such as leptin and adipsin,” says Kaya Pruczynska, a postdoc in Cohen’s lab. “We are very excited that the tools we have developed allow us to precisely track and quantify novel, low-abundance, potentially disease-modifying blood-borne adipokines, allowing us to characterize the secretome of less-studied endocrine adipocytes, such as brown adipocytes.”
In addition to cataloging the proteins released into the bloodstream, the researchers also mapped proteins within the endoplasmic reticulum, where proteins are manufactured and folded, providing an unprecedented view of both the messages being sent and the machinery that generates them.
“People don’t pay attention to this, but it’s important for both health and disease,” Vinogradova says. “That’s because it tells us not only what messages cells are sending, but also how the machinery that generates those messages changes under stress.”The data revealed that the ER’s protein-folding machinery actively adapts to changing physiological conditions. Fasting suppressed the production of many immune-related proteins, while severe inflammation triggered stress response pathways that help cells cope with increased protein folding demands.
The resulting atlas revealed distinct communication programs for each metabolic state studied and revealed previously unknown factors. These include gamma-synuclein, a protein previously associated with the nervous system as a fat-derived messenger that decreases during fasting and inflammation, but increases sharply in advanced obesity, and MTR1L, an orphan receptor whose production spikes 30-fold in visceral fat during advanced obesity. They also discovered a number of proteins that change with obesity that had not previously been studied in relation to obesity. When the researchers compared their findings with data from more than 53,000 individuals in the UK Biobank, they found that 65 of the proteins shown to be altered by metabolic stress were associated with human diseases such as type 2 diabetes, obesity, hypertension, coronary artery disease, heart attack, stroke, atrial fibrillation, and sepsis.
“We worked with a protein made by fat cells and regulated by obesity, and we confirmed that this technique worked,” Cohen says. “But we also observed over 150 other proteins, many of which have never been studied in this context. We think that understanding how these proteins regulate metabolism throughout the body will be a really productive area going forward.”
“These TurboID experiments required a different data analysis approach than other mass spectrometry projects,” says Charlotte Wayne, a postdoctoral fellow in the Vinogradova lab. “However, now that our pipeline is established, we are excited to be able to apply this strategy to additional cell types and disease settings.”
Cohen plans to use this to investigate what proteins brown fat secretes to determine exactly how exercise improves overall health, while Vinogradova plans to extend the approach to other systems, particularly immunology, where tracking cell-to-cell communication has proven particularly difficult. In his new lab, Professor Low, like Rockefeller, has discovered that mouse models are fostering new collaborations to study issues at the interface of aging, obesity and reproductive physiology.
“What excites me most are the applications to study immune signaling and dysfunction,” Vinogradova says. “But we expect this to open the door to building organ interactomes across the entire spectrum of health and disease.”
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Reference magazines:
Pluchinska, K. Others. (2026). Cell type-specific proximity labeling of organ secretomes reveals energy balance-dependent proteomic remodeling. cell report. DOI: 10.1016/j.celrep.2026.117507. https://www.cell.com/cell-reports/fulltext/S2211-1247(26)00585-1
