Thanks to a groundbreaking technology called Moscot (“Multi-Omics Single-Cell Optimal Transport”), researchers can now observe millions of cells simultaneously as they form new organs, like the pancreas. This remarkable technique was developed by an international team of scientists led by Helmholtz Munich and was published in the prestigious journal Nature.
In the past, biologists had a limited grasp of how cells grow in their natural environments, especially during organ formation in embryos. “Existing methods only provide snapshots of a handful of cells or fail to bridge the dynamic processes that happen over time and space,” explains Dominik Klein, a primary author of the study, PhD candidate at the Helmholtz Munich Institute of Computational Biology, and researcher at the Technical University of Munich (TUM). “This severely limited our understanding of the complex interactions involved in organ development and various disease mechanisms.”
Moscot Maps Cell Development Across Organs and Organisms
Together with an interdisciplinary team including Giovanni Palla (Helmholtz Munich), Marius Lange (ETH Zurich), Michal Klein (Apple), and Zoe Piran (Hebrew University of Jerusalem), Dominik Klein created Moscot. This project builds on an 18th-century theory known as optimal transport, which explains how to move items most efficiently to conserve time, energy, or resources. Initially, applying this theory to two cell populations was complicated due to the constraints of biomedical data sizes. However, advancements in artificial intelligence, significantly helped by co-author Marco Cuturi (Apple), have addressed this challenge. “We’ve refined our mathematical models to accurately depict the molecular details and locations of cells during their development. The optimal transport theory enhances our understanding of how cells migrate, evolve, and change states,” Klein explains. This breakthrough enables researchers to observe millions of cells simultaneously with a level of precision never achieved before.
Moscot provides a detailed mapping of individual cells within tissues, crucial for grasping dynamic biological processes. It links millions of cells over time, connecting changes in gene expression to cellular decisions. The goal of Moscot is to analyze vast datasets using sophisticated algorithms while providing an accessible interface for biologists. Additionally, Moscot captures the molecular state of numerous cells at once, tracking their development through space and time. For the first time, this method allows deeper insights into complex cellular processes within entire living organs and organisms.
New Discoveries in Pancreas and Diabetes Research
The use of Moscot has yielded significant insights into pancreas research: the team effectively mapped the development of hormone-producing cells in the pancreas through various measurements. Based on these findings, scientists can now further investigate the mechanisms behind diabetes. “This new perspective on cellular processes opens pathways for targeted therapies that address the root causes of diseases instead of just their symptoms,” remarks Prof. Heiko Lickert, head of the Institute of Diabetes and Regeneration Research at Helmholtz Munich and co-lead author of the study alongside Prof. Fabian Theis.
A Milestone in Medical Research
Fabian Theis, Director of the Institute of Computational Biology at Helmholtz Munich and a professor at TUM, emphasizes Moscot’s significance for biomedical research: “Moscot is redefining how we interpret and leverage biological data. It enables us to not only capture the dynamics of cell development in great detail but also accurately forecast disease progression, aiming for personalized treatment strategies.”
For Theis, Moscot is a testament to the power of interdisciplinary collaboration: “The successful merging of mathematics and biology in this endeavor highlights the crucial role of teamwork across fields in achieving genuine scientific breakthroughs. Our close partnership with Heiko Lickert’s team at the Helmholtz Diabetes Center enabled us to validate Moscot’s predictions with laboratory experiments.”
Discover more: moscot-tools.org
