Researchers have created an algorithm to identify similar cell types in species – including fish, mice, flatworms and sponges – that have diverged hundreds of millions of years and could help reduce gaps in understanding our evolution.
Cells are the basic elements of life and are present in every living thing. But how similar do you think your cells are to a mouse? Over? worm?
Comparing cell types in different types of life tree can help biologists understand how cell types have emerged and how they have adapted to the functional needs of different life forms. This has been the subject of growing interest in evolutionary biologists in recent years, as new technology now allows the sequencing and identification of all cells in all living things. “There is essentially a wave in the scientific community to classify all cell types into a variety of different organisms,” said Bo Wang, an assistant professor of bioengineering at Stanford University.
In response to this opportunity, Wang’s lab developed an algorithm to connect similar cell types over evolutionary distances. Their method, detailed in a paper published on May 4, 2021, at eLifeIt is designed to compare cell types of different types.
In their research, the team used seven types to compare 21 different pairs and was able to identify the cell types found in all species, along with their similarities and differences.
Compare cell types
According to Alexander Tarashansky, a graduate student in bioengineering who works in Wang’s lab, the idea to create the algorithm came when Wang entered the lab one day and asked him if he could analyze two-cell sets. different types of worms on which laboratory studies have been performed. Same time.
“I was amazed at how obvious the differences were between them,” said Tarashansky, who was the lead author of the paper and an interdisciplinary college at Stanford Bio-X. I thought they should have similar cell types, but when we try to analyze them using the technical standard, the method does not recognize them because they are the same. “
He wondered if there was a problem with the technology or if the cell types were too different to match between species. Then Tarashansky began working on the algorithm to better match the cell types between species.
“Suppose I want to compare a sponge to a man,” Tarashansky said. “It is not very clear which of the sponge genes corresponds to any human gene, because with the evolution of organisms, the genes multiply and change and repeat again. You now have a gene in the sponge that can be linked to many genes in humans. “
Instead of trying to find a one-to-one genetic match like previous methods of matching data, the method of mapping researchers matches a single gene in a sponge with all possible corresponding human genes. Then the algorithm continues to see which one is correct.
Tarashansky says trying to find only pairs of individual genes has limited scientists who have looked in the past for a map of cell types. “I think the main innovation here is that we take into account the characteristics that have changed over hundreds of millions of years of evolution for large-scale comparisons.”
“How can we use constantly evolving genes to recognize the same constantly changing cell type in different species?” Said Wang, the first author of the paper. “Evolution was understood using genes and organic traits, I think we are now at an interesting turning point for scale reduction, analyzing how cells evolve.”
Fill the tree of life
Using a cartographic approach, the team discovered a number of conserved genes and families of cell types between species.
Tarashansky said the highlight of the research was when they compared stem cells between two very different worms.
“The fact that we found a one-to-one match in the stem cell groups was really interesting,” he said. “I think basically this has opened up a lot of new and interesting information about how stem cells appear inside a flat parasitic worm that infects hundreds of millions of people around the world.”
The team’s mapping results also indicate that there is robust protection for the properties of neurons and muscle cells from very simple animal species, such as sponges, to more complex mammals, such as mice and humans.
Wang said, “This really indicates that these types of cells appeared very early in the evolution of animals.”
Now that the team has built the cell comparison tool, researchers can continue to collect data for a variety of species for analysis. As more data sets from several species are collected and compared, biologists will be able to track the cell types in different organisms and improve their ability to recognize new cell types.
“If you only had sponges and then worms and you lost everything between them,” Tarashansky said, “it’s hard to know how the types of spongy cells evolved or how their ancestors diversified into sponges and worms.” “We want to complete as many nodes as possible throughout the tree of life, so that we can facilitate this type of evolutionary analysis and transfer knowledge between species.”
Reference: “Mapping of single-cell atlases along Metazoa reveals cell type evolution” Posted by Alexander J. Tarashansky, Jacob M. Moser, Margarita Khariton, Penjiang Lee, Detlev Arendt, Stephen R. Kwake, Bo Wang, May 4, 2021, eLife.
DOI: 10.7554 / eLife.66747
Other Stanford co-authors include graduate students Margarita Khariton, Bingyang Lee and Stephen Kwik, professor of bioengineering Lee Otterson and professor of applied physics and co-chair of Chan Zuckerberg Biohub. The other co-authors come from the European Molecular Biology Laboratory and the University of Heidelberg. Wang is also a member of Stanford Bio-X and the Wu Cai Institute of Neuroscience. Kwik is a member of Bio-X, Stanford Cardiovascular Institute, Stanford Cancer Institute and Wu Tsai Institute of Neurosciences.
This research was funded by the Stanford Bio-X, the Beckman Young Investigator Award and the National Institutes of Health. Wang and Kwik will build on this work as part of the Neuro-Omic Initiative funded by the Wu Tsai Institute of Neuroscience.
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