Cells are the building blocks of life, present in every living organism. But how similar does one think your cells are to a mouse? A fish? A worm?
Comparing cell types in several species across the tree of life can help biologists understand how cell types arose and the way they need adapted to the functional needs of various life forms. This has been of accelerating interest to evolutionary biologists in recent years because new technology now allows sequencing and identifying all cells throughout whole organisms. “There’s essentially a wave within the scientific community to classify all kinds of cells in a big variety of various organisms,” explained Bo Wang, an professor of bioengineering at Stanford University .
In response to the present opportunity, Wang’s lab developed an algorithm to link similar cell types across evolutionary distances. Their method, detailed in a paper published May 4 in eLife, is meant to match cell types in several species.
For their research, the team used seven species to match 21 different pairings and were ready to identify cell types present altogether species along side their similarities and differences.
Comparing cell types
According to Alexander Tarashansky, a grad student in bioengineering who works in Wang’s laboratory, the thought to make the algorithm came when Wang walked into the lab 1 day and asked him if he could analyze cell-type datasets from two different worms the lab studies at an equivalent time.
“I was struck by how stark the differences are between them,” said Tarashansky, who was lead author of the paper and may be a Stanford Bio-X Interdisciplinary Fellow. “We thought that they ought to have similar cell types, but once we try analyzing them using standard techniques, the tactic doesn’t recognize them as being similar.”
He wondered if it had been a drag with the technique or if the cell types were just too different to match across species. Tarashansky then began performing on the algorithm to better match cell types across species.
“Let’s say i would like to match a sponge to a human ,” said Tarashansky. “It’s really not clear which sponge gene corresponds to which human gene because as organisms evolve, genes duplicate, they modify , they duplicate again. then now you’ve got one gene within the sponge that maybe related with many genes in humans.”
Instead of trying to seek out a one-to-one gene match like previous methods for data matching, the researchers’ mapping method matches the one gene within the sponge to all or any potentially corresponding human genes. Then the algorithm proceeds to work out which is that the right one.
Tarashansky says trying to seek out only one-to-one gene pairs has limited scientists looking to map cell types within the past. “I think the most innovation here is that we account for features that have changed over the course of many many years of evolution for long-range comparisons.”
“How can we use the ever-evolving genes to acknowledge an equivalent cell type that also are constantly changing in several species?” said Wang, who is senior author of the paper. “Evolution has been understood using genes and organismal traits, i feel we are now at an exciting turning point to bridge the scales by watching how cells evolve.”
Filling within the tree of life
Using their mapping approach, the team discovered variety of conserved genes and cell type families across species.
Tarashansky said a highlight of the research was once they were comparing stem cells between two very different flatworms.
“The incontrovertible fact that we did find one-to-one matches in their somatic cell populations was really exciting,” he said. “I think that basically unlocked tons of latest and exciting information about how stem cells look inside a parasitic flatworm that infects many many people everywhere the planet .”
The results of the team’s mapping also suggest there is a strong conservation of characteristics of neurons and muscle cells from very simple animal types, like sponges, to more complex mammals like mice and humans.
“That really suggests those cell types arose very early in animal evolution,” Wang said.
Now that the team has built the tool for cell comparison, researchers can still collect data on a good sort of species for analysis. As more datasets from more species are collected and compared, biologists are going to be ready to trace the trajectory of cell types in several organisms and therefore the ability to acknowledge novel cell types will improve.
“If you simply have sponges then worms and you’re missing everything in between, it’s hard to understand how the sponge cell types evolved or how their ancestors have diversified into sponges and worms,” said Tarashansky. “We want to fill in as many nodes along the tree of life as possible to be ready to facilitate this sort of evolutionary analysis and transfer of knowledge across species.”
The research reported on eLife.
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