Researchers have created an algorithm to identify similar cell types in species – including fish, mice, worms and sponges – that have diverged for hundreds of millions of years, which could help fill gaps in our understanding of evolution.
Cells are the building blocks of life, present in every living organism. But how similar do you think your cells are to a mouse? A fish? A worm?
Comparing the cell types of different species in the tree of life can help biologists understand how cell types have emerged and how they have adapted to the functional needs of different life forms. This has aroused increasing interest among evolutionary biologists in recent years, as new technology now allows the sequencing and identification of all cells in whole organisms. “There is virtually a wave in the scientific community to classify all cell types into a wide 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 link similar distance cells over evolving distances. Their method, detailed in an article published on May 4, 2021 in eLife, is designed to compare cell types of different species.
For their research, the team used seven species to compare 21 different pairs and was able to identify the cell types present in all species, as well as their similarities and differences.
Comparison of 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 once entered the lab and asked if he could analyze cell-type data sets from two different worms. in which the laboratory studies. same time.
“I was struck by the seriousness of the differences between them,” said Tarashansky, lead author and interdisciplinary colleague at Stanford Bio-X. “We thought they should have similar cell types, but when we try to analyze them using standard techniques, the method doesn’t recognize them as similar.”
He wondered if this was a problem with the technique or if the cell types were simply too different to fit from species to species. Tarashansky then began working on the algorithm to better match cell types between species.
“Let’s say I want to compare a sponge to a man,” Tarashansky said. “You don’t really know which sponge gene corresponds to which human gene, because as organisms evolve, genes duplicate, change, duplicate again. And now you have a gene in the sponge that can be linked to many genes in humans. “
Instead of trying to find a one-to-one gene match, such as previous data matching methods, the method of mapping the researchers matches the sponge gene with all the potentially matching human genes. Then the algorithm determines which one is correct.
Tarashansky says trying to find only pairs of genes one-on-one has limited scientists who have sought to map cell types in the past. “I think the main innovation here is that we take into account the characteristics that have changed over the hundreds of millions of years of evolution for long-term comparisons.”
“How can we use ever-changing genes to recognize the same constantly changing cell type in different species?” Said Wang, who is the lead author of the article. “Evolution was understood using genes and features of the body, I think we are now in an interesting time to tie the scales, analyzing how cells evolve.
Fill the tree of life
Using their mapping approach, the team discovered a number of genes and families of conserved cell types between species.
Tarashansky said that a highlight of the research was the comparison of stem cells between two very different flatworms.
“The fact that we found individual matches in their stem cell populations was really interesting,” he said. “I think this has essentially unlocked a lot of new and interesting information about what stem cells look like inside a flat parasitic worm that infects hundreds of millions of people around the world.”
The results of the team’s mapping also suggest that there is a strong preservation of the characteristics of neurons and muscle cells, from very simple animal types such as sponges to more complex mammals such as mice and humans.
“It does suggest that these types of cells appeared very early in the evolution of animals,” Wang said.
Now that the team has built the cell comparison tool, researchers can continue to collect data for a wide variety of species for analysis. As more data sets from several species are collected and compared, biologists will be able to track the trajectory of cell types in different organisms and improve their ability to recognize new cell types.
“If you only have sponges and then worms and you miss everything in between, it’s hard to know how sponge cell types evolved or how their ancestors diversified into sponges and worms,” Tarashansky said. “We want to fill as many nodes as possible throughout the tree of life, in order to facilitate this type of evolutionary analysis and knowledge transfer between species.”
Reference: “Mapping of single-cell atlases along Metazoa reveals the evolution of cell type” by Alexander J Tarashansky, Jacob M Musser, Margarita Khariton, Pengyang Li, Detlev Arendt, Stephen R Quake and Bo Wang, May 4, 2021, eLife.
DOI: 10.7554 / eLife.66747
Other Stanford co-authors include graduate students Margarita Khariton and Pengyang Li and Stephen Quake, Lee Otterson professor of bioengineering and professor of applied physics and co-chair of Chan Zuckerberg Biohub. 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 Tsai Institute of Neuroscience. Quake is also a member of Bio-X, Stanford Cardiovascular Institute, Stanford Cancer Institute and Wu Tsai Neurosciences Institute.
This research was funded by Stanford Bio-X, a Beckman Young Investigator Award and the National Institutes of Health. Wang and Quake will build on this work as part of the Neuro-Omic Initiative funded by the Wu Tsai Institute of Neuroscience.
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