23-Jul-2021 - Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt GmbH

Revealing the secrets of cell competition

Which features distinguish “winner” from “loser” cells

Cellular competition is a crucial quality control process that ensures that the development of an organism relies on healthy cells. Researchers revealed the secrets underlying cell competition and what features can pre-determine whether a cell will survive or not. Defects in energy production are critical in making cells vulnerable to elimination. The study was led by researchers from Helmholtz Zentrum München and Imperial College London.

As multicellular life relies on cell-cell interactions, it is not surprising that this is not always peaceful: cells with higher fitness eliminate cells with lower fitness through cell competition. Cell competition has emerged as a quality control mechanism and occurs when cells differ, genetically or otherwise, from each other. In mammals, the process of cell competition has been observed e.g., in cancer, during organ homeostasis, and during development as a process to select the fittest cells in the embryo and the adult. However, the features that distinguish “winner” from “loser” cells and whether there are key determinants for cell competition in various biological contexts remain elusive. 

The recipe for elimination of “loser” cells

The research team found out that the cells losing the competition are characterized by defective mitochondria and, in mouse embryos, they are marked by sequence changes in their mitochondrial genome. Their work was published in the journal Nature Metabolism. “Our work suggests that differences in mitochondrial activity are key determinants of competitive cell fitness in a wide range of systems. In particular, we discovered that genetic defects in the mitochondria characterize ‘loser’ cells in mouse embryos,” says Antonio Scialdone, co-corresponding author of the article.

In more detail: The mouse embryo uses cellular competition to get rid of unfit epiblast cells before the basic body plan is laid down during gastrulation. Using single-cell RNAseq (a specific sequencing technique), the researchers compared cells in embryos treated with a cell death inhibitor versus those in untreated mouse embryos. By applying machine learning algorithms, they could identify the gene expression signature of “loser” cells and discovered that these cells have defective mitochondria and are marked by sequence changes in their mitochondrial genome. “It was nice to see how with our computational pipeline we were able to extract such important information from the single-cell RNAseq datasets,” says Gabriele Lubatti co-first author of the article.

The information on how “loser” cells look like in the mouse embryo allowed them to determine a ”loser” cell identity. By analyzing the mitochondrial activity in other cell competition models, they could identify that mitochondrial dysfunction is a common characteristic in different “loser” cells and that small changes in the mitochondrial DNA are enough to drive cell competition.

Future work

This study suggests that mitochondrial activity may be a key determinant of cellular fitness in a variety of contexts where competition between cells occurs. Environmental changes can strongly influence metabolism and mitochondria play a central role in this process. Therefore, it is possible that cellular competition and associated defects in the mitochondrial genome in response to certain environmental factors leads to the emergence of a particular genotype (“winner” cells). This implies that cellular competition could be a direct link between environment and genotype, which will be interesting to explore further.

Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt GmbH

Recommend news PDF version / Print Add news to watchlist

Share on

Facts, background information, dossiers

  • cells
  • single-cell RNA sequencing
  • machine-learning
  • mitochondria
  • gene expression

More about Helmholtz Zentrum München

  • News

    Fighting blood diseases with artificial intelligence

    How can we better diagnose blood diseases? A research group led by Helmholtz Munich aims to answer this question with artificial intelligence (AI). Their goal is to facilitate the time-consuming analysis of bone marrow cells under the microscope. The researchers developed the largest open-s ... more

    AI helps to spot single diseased cells

    Researchers developed a novel artificial intelligence algorithm for clinical applications called “scArches”. It efficiently compares patients’ cells with a reference atlas of cells of healthy individuals. This enables physicians to pinpoint cells in disease and prioritize them for personali ... more

    Pancreatic organoids on newly developed chip platform

    A new organoid-on-chip platform robustly mimics the key features of human pancreas development. This is a milestone on the way to being able to diagnose pancreatic cancer at an early stage in the future. The study was conducted by an interdisciplinary team of researchers from Helmholtz Zent ... more

  • q&more articles

    Using deep learning to better understand blood disorders

    For a long time, doctors have been diagnosing disorders of the body’s hematopoietic system using a light microscope. The analysis of individual blood cells is largely performed manually. Now, artificial intelligence can lend them a digital hand. more

  • Authors

    Dr. Carsten Marr

    Carsten Marr, born in 1977, received his diploma in general physics from the Technische Universität München in 2002. He wrote his diploma thesis at the Max-Planck-Institute for Quantum Optics, Garching, Germany, and in 2003 visited the Quantum Information and Quantum Optics Theory Group at ... more

    Dr. Christian Matek

    Christian Matek, born in 1986, received undergraduate degrees in both Physics and Medicine in Munich. He then moved to the UK and finished his DPhil in Theoretical Physics at Oxford University in 2014. Since 2017, his main research interest has been applying artificial intelligence and mach ... more

More about Imperial College of London

  • News

    New type of photosynthesis discovered

    The discovery changes our understanding of the basic mechanism of photosynthesis and should rewrite the textbooks. It will also tailor the way we hunt for alien life and provide insights into how we could engineer more efficient crops that take advantage of longer wavelengths of light. The ... more

    Research from poor countries deserves a fairer hearing

    Academia could be overlooking new ideas from low income nations without realising it, suggests an Imperial College London researcher. Dr Matthew Harris, from Imperial’s School of Public Health and Institute of Global Health Innovation, discusses how unconscious bias could be keeping develop ... more

    Quantum computers may be able to come out of the cold

    A materials expert says quantum computers may be able to come out of the cold, thanks to his research breakthrough. Dr Jonathan Breeze is from the Department of Materials at Imperial College London. He says his research breakthrough may help scientists overcome a major obstacle with quantum ... more

q&more – the networking platform for quality excellence in lab and process

The q&more concept is to increase the visibility of recent research and innovative solutions, and support the exchange of knowledge. In the broad spectrum of subjects covered, the focus is on achieving maximum quality in highly innovative sectors. As a modern knowledge platform, q&more offers market participants one-of-a-kind networking opportunities. Cutting-edge research is presented by authors of international repute. Attractively presented in a high-quality context, and published in German and English, the original articles introduce new concepts and highlight unconventional solution strategies.

> more about q&more

q&more is supported by: