Sunday, May 26, 2024
HomeTop NewsBioengineers are developing an algorithm to compare cells between species

Bioengineers are developing an algorithm to compare cells between species

Published on


Researchers have developed an algorithm that identifies similar cell types from living things, including fish, rats, tapeworms, and sponges, which have been around for millions of years, helping to fill the gaps in our understanding of evolution.

Cells are the basic building blocks of life and are found in all living things. Do you think your cells are like a mouse? Fish? The worm?

By comparing different types of cells throughout the life cycle, biologists can be helped to understand how cell types originated and how they adapted to the functional needs of different organisms. In recent years, there has been a growing interest in evolutionary biologists because new technology now allows the order and identification of all cells in every living thing. “There is a wave in the scientific community to classify all types 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 an algorithm to link similar cell types at an evolutionary distance. Their method is described in a document published on May 4, 2021 eLifeIt is intended 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 in all organisms and their similarities and differences.

Compare cell types

According to Alexander Tarsansky, a bioengineering master working in Wang’s laboratory, Wang came to the laboratory one day and asked if he could analyze the two types of worm cell-type datasets he had studied in the laboratory. . At the same time.

See also  How Will 5G Impact the Online Gaming Community?

Tarasanskis, lead author and interdisciplinary colleague at Stanford Bio-Ex, said: “I was amazed at how clear the differences were between them. We thought they should be similar to cell types, but when we try to analyze them using standard methods, they are similar because the method does not recognize them. “

He wondered if this was a problem of technology or if cell types could not be matched in different species. Tarasanskis began to run an algorithm to better match cell types across different species.

“I want to compare a sponge to a human,” Tarazansky said. “It’s not clear which sponge genes are compatible with any human gene, because genes multiply and change and reproduce according to the evolution of organisms. Now you have a gene at the pump that may be linked to several human genes.”

Instead of trying to find one-to-one genetic compatibility like previous data matching methods, the researchers’ mapping method matches a sponge pump gene with a relevant human gene. The algorithm continues to see which ones are correct.

Attempts to find only individual gene pairs have limited the number of scientists searching for maps of cell types, Tarasanskis says. “The key finding here is that we take into account far – reaching comparisons of features that have evolved over millions of years.”

“How can we use the ever-evolving genes to identify the same type of cells that are constantly changing in different species?” Wang, the first author of the article, said. “Evolution can be understood through the use of genes and biological traits, and we are now at an exciting juncture in creating scale by looking at how cells develop.”

See also  "I assume we are in a good location. I disagree with him."

Fill in the outlook on life

Using a mapping approach, the team identified several genes and cell types that are preserved in families of different species.

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

“It’s really exciting to find each of us in stem cell groups,” he said. “I think it opens up a lot of new and exciting information about how stem cells appear inside a parasitic flatworm that basically affects millions of people around the world.”

The results of the team mapping also indicate that the characteristics of neurons and muscle cells are strictly protected from very simple animals such as sponges to complex mammals such as mice and humans.

“This really suggests that such cells originated at the very beginning of animal evolution,” Wang said.

Now that the team has developed a cell comparison tool, researchers can continue to gather information about different species for analysis. By collecting and comparing more data sets from different species, biologists can improve the ability of cell types in different organisms to identify and identify new cell types.

“If you only had sponges and then worms, and you lost everything in between,” it’s hard to know how sponge cell types evolved or how their ancestors diversified into sponges and worms. “We want to fill as many nodes as possible with the outlook on life so that this kind of analysis of evolution is possible and knowledge can be passed on between species.”

Reference: “Maping of unicellular atlases across metazoles reveals cell-type evolution.” Alexander J. Tarasanskis, Jacobs m. Mosers, Margarita Harriton, Pennijan Lee, Detlev Arents, Stephen R. Quake, Bo Wang, May 4, 2021 eLife.
DOI: 10.7554 / eLife.66747

See also  The father agrees to leave the position of teacher

Other Stanford co-authors include Masters Margarita Chariton, Binjiang Lee, Professor of Bioengineering Stephen Quick, Professor of Applied Physics, and co-chair of Chan Zuckerberg Biohub. 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 Kai Institute of Neuroscience. Kevick is a member of BioX, the Stanford Cardiovascular Institute, the Stanford Cancer Institute, and the Wu Sai Institute of Neuroscience.

The study was funded by the Stanford Bio-X, the Beckman Young Research Award, and the National Institutes of Health. Buy and Quick is producing this work as part of a Nero-Omics project funded by the Wu Sai Institute of Neuroscience.

Latest articles

More like this