Scientists develop Twitter for communication between living cells

Tariq Kabil

Computational biologists led by Professor Evan Sais of the Vip-Yogent Infection Research Center have developed a new method of bioinformatics to improve the study of intercellular communication.

This method, called "NicheNet" or "nest network," helps researchers gain an in-depth view of how cells genetics are organized by interacting cells with each other.

On December 9, researchers published the Nature Methods detailed description of a website for modeling intercellular communication similar to Twitter's method of exchanging short text messages.

Twitter cells
The ability of cells to exchange signals and properly respond to their microenvironment is the basis for growth, tissue restoration, and immunity, as well as internal tissue balance. Any error in cellular information is responsible for serious diseases such as cancer, autoimmune diseases, and diabetes. Therefore, understanding the processes of exchanging cellular signals is particularly important for an effective treatment of these diseases.

Cellular and Molecular Biology has focused on studying single parts of cellular signal production networks and their pathways. But systems biology researchers are currently helping to understand the infrastructure of cellular signal networks and how the change in these networks affects the transmission of information between different cells and tissues.

Scientists have succeeded in interpreting cellular messages similar to "tweets" on "Twitter" to exchange and translate short messages. Nietzsche.net currently has a wide range of potential applications in areas such as immunology and oncology biology, and it has already been successfully used by the group collaborating with Professor Martin Gilliams from the Vip-Eugent Center.

One click
In multicellular organisms, cells do not function by themselves, but rather produce signaling (marking) molecules that affect gene expression in interacting cells. The signal represents an electrical quantity (electric current) caused by the chemical reactions of the charged ions (ions). It is also used to denote the transfer of information between vital cells in the bodies of living organisms.

This intercellular communication plays an important role in many biological processes. An example of a process in which intercellular communication is necessary is the differentiation of macrophages (macrophages or macrophages), a type of immune cell that engulfs and shatteres the foreign intruder from the body, in a process called phagocytosis. This process is affected by other cell types in the environment, or the "stature, specialty" of macrophages.

Student Robin Perways - who works under the supervision of Dr. Water Silence, and Evan Saiss, from Professor Gilliams' group - a study of this process of Kupffer cells, which are specialized phagocytic cells found in the liver and which form part of the entire endothelial retina.

"The idea of ​​the study was to take advantage of the vast amount of knowledge available about the signaling of cells obtained over the years, and to use this knowledge to know the processes of communication between cells that take place in the data that we have," Perways explains the idea of ​​the study.

"To do this, we had to implement several methods of machine and statistical learning, including network algorithms that are also used to analyze social networks, for example," he says.

Silence summarizes the new method by saying, "In essence, you can compare our newly developed method (Niche Net) with a hypothetical biologist who not only knows everything that has already been published about intercellular communication, but can also apply all of this knowledge to complex and large data sets."

"Predictions for intercellular communication were something that would have required weeks of study of scientific research in the past, but this can now be done with the press of a button."

Exam Niche Net
The first test case for NietzscheNet was the specialized data for the Kupffer cell created by Gilliams Laboratory. The researchers in this lab were able to verify the authenticity of some of the signals that were predicted by "Nietzsche Net"

"With (Nietzsche) we studied the factors that we could not think of ourselves. For us, (Nietzsche) was an essential tool to help uncover the status of the Kupffer cell," Williams said.

"In addition to the Kupffer cell story, we have also implemented Nietzsche to investigate cellular cellular connections in the micro-environment of a tumor," Sais says.

"We used (Nichy Net) on single cell data previously published, but we are now working on new data sets created by collaborative research groups. How do different types of treatment affect cellular interactions within the micro-tumor environment, and how does this affect the tumor, they are both The questions we are trying to address with (Nietzsche Net). "

These applications demonstrate the value of NietzscheNet to generate new hypotheses about how cells communicate in biological processes and underlying diseases.