Bioengineers are developing a method of comparing cells between species

Bioengineers are developing a method of comparing cells between species

Researchers have developed a method to identify similar cell types from organisms, including fish, rats, tapeworms and sponges, which are hundreds of millions of years apart, and will help fill in the gaps in our understanding of evolution.

Cells are the basic elements of life, they are present in every living thing. But how often do you think your cells are like a mouse? Fish? Worm?

By comparing different types of cells across the tree of life, biologists can be helped to understand how species are formed and how they adapt to the functional needs of different life forms. In recent years, there has been a growing interest among evolutionary biologists as new technology now allows for the sorting and identification of all cells in all species. “There is a wave in the scientific community to classify all kinds of cells in different organisms,” explained Bo Wang, an assistant professor of bioengineering at Stanford University.

In response to this possibility, Wang’s laboratory developed a method to combine similar cell types over an evolutionary distance. Their method is detailed in a document published on 4 May 2021 eLifeIt is designed to compare different cell types.

In the study, the team used seven methods to compare 21 different pairs and was able to identify cell types and their similarities and differences in all organisms.

Compare cell types

According to Alexander Dorsansky, a bioengineering master working in Wang’s laboratory, when Wang came to the lab one day and asked if he could analyze the two types of worm cell data collected in the laboratory, he came up with the idea. . At the same time.

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“I was amazed at how clear the differences were between them,” said Tarasanskis, a leading writer and intermediate colleague at Stanford Bio-X. We thought they should be similar to cell types, but when we try to analyze them using standard methods we cannot identify them because the pattern is the same. “

He wondered if this was a complication in the technology or whether the cell types were different enough to fit in different species. Then Tarasanskis began to work on a way to better match cell types in different species.

“I can say that I like to compare a sponge to a man,” Tarasansky said. “It’s not clear which sponge genes are compatible with which human genome, because with the evolution of organisms, genes multiply and change over and over again. Now you have a gene that is linked to many human genes.”

Instead of trying to find one-on-one genetic compatibility like previous data matching methods, the researchers’ mapping method applies to all human genes associated with a sponge pump gene. The algorithm continues to see what is correct.

Tarasanskis argues that the attempt to find only individual genetic pairs has limited the number of scientists who can be used to search for maps of cell types. “The key finding here is that in visionary comparisons, we take into account aspects that have changed hundreds of millions of years of evolution.”

“How can we use the ever-evolving genes to identify the same type of cells that are constantly changing in different species?” Said Wang, the first author of the article. “Evolution is understood through the use of genes and organic properties. I think we are now at an exciting turning point in creating scale by looking at how cells are formed.”

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Fill the tree of life

Using the mapping approach, the team identified several preserved genes and cell types in families of different organisms.

Tarasanskis said the study focused on comparing stem cells between two different worms.

“It was very exciting that we found each other in the stem cell groups,” he said. “I think it basically opens up new and exciting information about how stem cells appear within a parasitic platform that affects hundreds of millions of people around the world.”

The results of the group map also indicate that the properties of neurons and muscle cells are tightly protected from the most simple animal species such as sponges to the most complex mammals such as mice and humans.

Wang said, “This really indicates that these types of cells appeared at the beginning of animal evolution.”

Now the team has developed a cell comparison tool that allows researchers to constantly collect data from different organisms for analysis. By collecting and comparing more data sets from multiple organisms, biologists can improve the ability to find the path of cell types in different organisms and recognize new cell types.

“If you had sponges, then only worms, and lost everything in between,” Tarasansky said, “it’s hard to know how sponge cell types evolved or how their ancestors diversified into sponges and worms.” , We also help transfer knowledge between organisms. “

Note: “Mapping of the Unicellular Atlas across the Metaso reveals cell type evolution.” Posted by Alexander J. Tarasanskis, Jacobs M. Mosers, Margarita Haridon, Pennigen Lee, Deadlew Arends, Stephen R. Quake, Bo Wang, May 4, 2021 eLife.
DOI: 10.7554 / eLife.66747

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Other Stanford co-authors include Masters Margarita Gardin, Pingyang Lee and Stephen Quick, Lee Otterson, Professor of Bioengineering and Professor of Applied Physics and co-chair of San Zuckerberg BioHob. Other co-authors are from the European Molecular Biology Laboratory and the University of Heidelberg. Wang is also a member of the Stanford Bio-X and Wu Cai Institute of Neuroscience. He is a member of Quick Bio-X, Stanford Heart Institute, Stanford Cancer Institute and Wu Chai Institute of Neuroscience.

The study was funded by the Stanford Bio-X, the Beckman Young Researcher Award and the National Institutes of Health. Wang and Quick will create this work as part of a Nero-Omics initiative funded by the Wu Chai Institute of Neuroscience.

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Cary Douglas

About the Author: Cary Douglas

Cary Douglas is a reporter who covers everything from oil trading to China's biggest conglomerates and technology companies. Originally from Chicago, he is a graduate of New York University's business and economic reporting program.

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