Using the mathematical analysis of models of behavior of human and animal cells, scientists say that they have developed a computer program that imitates the behavior of these cells in any part of the body. Led by investigators from the University of Indiana, Johns Hopkins Medicine, the University of Maryland School of Medicine and the Oregon Health University, the new work has been designed to advance the means to test and predict biological processes, drug responses and other cell dynamics before undertaking more expensive experiences with living cells.
With additional work on the program, researchers say that this could possibly serve as a “digital twin” to test the effect of any medication on cancer or other conditions, gene interactions during brain development or a number of dynamic cellular molecular processes in people where such studies are not possible.
Funded mainly by the Jayne Koskinas Ted Giovanis Foundation and the National Institutes of Health, and the print of previous knowledge and data funded by the Lustgarten Foundation and the National Foundation for Research on Cancer, the new study and the examples of cell simulations are described online on July 25 Cell.
According to Geneviève Stein-O’Brien, Ph.D., the professor of neuroscience and neurology of the family of the Terkowitz family at the Johns Hopkins University School of Medicine, the research project began during a workshop for a previous version of computer software, called Physicell, designed by the university engineering teacher of Indiana Paul Macklin, Ph.D.
Physicell is based on so-called agents, “essentially, mathematical robots which act on (a set of) rules which reflect the DNA and the RNA of the cells”, explains Stein-O’Brien. Each type of cell in the body is mapped to an agent, then digitally manipulated to do things, such as interacting with other cells and environmental factors such as therapy, oxygen and other molecules forming tissues, organs and sometimes cancer.
By following the cells that follow their assigned rules, scientists can virtually see things such as the way tumors emerge and interact with therapy and the immune system. They can follow cells that form layers of the brain’s cortex and see how brain cells are organized to lay the foundations they will need to create circuits. The Stein-O’Brien laboratory in collaboration with the co-family author Daniel Bergman, Ph.D., assistant professor at the Institute of Sciences of the Genome of the Medical School of Maryland University, leads the subsequent development of software to go from cells to brain circuits.
Macklin says that typical computer modeling programs exist but generally require sophisticated knowledge of mathematical models and computer coding to use and interpret. The new Physicell software, he says, has formulated a new “grammar” which makes the computer model based on agents more accessible to scientists who know a lot about biology but are not competent in programming.
“We needed months to write the code for these models, and now we can teach other scientists to create a basic immunology model in an hour or two,” explains Macklin. “We can also use this program to model the spatial transcriptomic, a long -standing objective for scientists, to visualize where each type of cell can be found and how they work in 3D replicas of tissues and tumors. »»
Stein-O’Brien describes the new coding grammar as “literally, an Excel spreadsheet which, on each line, corresponds to a type of cell with a rule in the human legible syntax. For example: this cell increases division as the concentration of oxygen increases. »»
Then, the program automatically translates the biological grammar of the calculation sheet in mathematical equations which produce a guide for cellular behavior. The program can also adjust the model to match the data established from transcriptome studies, the output of genetic equipment.
The author of the study David Zhou, a undergraduate student of neuroscience from Johns Hopkins University at the time, worked with Stein-O’Brien to provide many cellular behavior included in the new program. He and Zachary Nicholas, a doctorate of human genetics by Johns Hopkins. The candidate and the NIH / NIND D-SPAN scholarship holder built the brain development model as the first of his data for use of the Allen brain atlas.
This has been made possible by new progress in software that uses data spatially resolved to connect instantaneous cellular behavior to build a film that shows cellular and tissue interactions over time.
This is very important for human diseases. We want to test changes in the rules, models and paths of cells to see how cells change their behavior. »»
Genevieve Stein-O’Brien, Ph.D., The Terkowitz Family Rising Professor of Neuroscience and Neurology à la Johns Hopkins University School of Medicine
The models involving a behavior of cancer cells were initially based on data from a large collection of human pancreatic tumors in Johns Hopkins and on mouse laboratory experiences, explains Elana Fertig, PH.D., professor and director of the Institute for the Sciences of the Genome of the Medical School of the University of Maryland. Fertig co-directed the project, starting in its previous role at the Johns Hopkins Kimmel Cancer Center and continuing in its current role.
In an experience designed to validate the new program, Co-Prime Author, Jeanette Johnson, Ph.D., postdoctoral scholarship of the Institute of Sciences of the Genome and recent graduate of the Ph.D. of immunology. Program at Johns Hopkins, directed the model to simulate how macrophages, a type of breast tumors invaded by immune cells by increasing the expression of a genetic route called EGFR. The increase in this way generally promotes the growth of cancer. Simulation has shown that tumors have increased because cancer cells have increased their ability to move.
With cancer cells in the living breast cultivated in the laboratory, the researchers observed the same type of tumor growth linked to an increase in cellular movement.
“We still have a lot of work to do to add more cellular behavior data to the program,” explains Johnson, who continues this work as a postdoctoral scholarship holder with Fertig at the University of Maryland Medical School.
“We are thinking of this project in terms of virtual cell laboratory,” explains Stein-O’Brien. Instead of doing all the experiences from the start on the laboratory bench with living cells, the objective is to use these tools, which could possibly work as a “digital twin”, to prioritize hypotheses and therapeutic targets. “So,” she said, “we can focus our bench on what seems most promising. »»
In current work, the team uses artificial intelligence to write simulation models using the new grammar, opening new possibilities to connect models to new data and allowing medical research to improve digital twins models.
Funding was provided by the Jayne Koskinas Ted Giovanis Foundation for Health and Policy, the National Institutes of Health (P01CA247886, K08CA248624, U24CA284156, 1U01CA294548-01, P50CA062924, U01CA253403, U54CA274371, U01CA212007, U54CA268083, R00NS122085, U01CA284090, T32GM148383, T32CA153952, T32 AG058527, T32CA254888, R35 GM157099, U01CA23237, R35 GM157099, U01CA23237, R01CA169702, R01CA197296, P30CA006973, P30 CA069533, T32GM141938-03, CA054174, F99NS139554, P30CA134274), The National Science Foundation, The National Science Foundation, Foundation Kuni, Fondation National Science, Fondation Science, Fonds Fuller, Kuni Foundation, Fondation National Science, Fondation Science, Fond Foundation, la Leidos Biomedical Research Foundation, la Grant de Maryland Cancer Moonshot Research, A Luddy Faculty Fellowship, la Susan G Komen Foundation, le Brenden-Colson Center for Pancreatic Care, le Sol Goldman Pancreatic Cancer Research Center, le Maryland Cigarette Restution Fund Institut de technologie omniprésente universitaire.
En plus de stein-o’brien, Macklin, Zhou, Nicholas, Johnson et Fermig, Les Auteurs Incluence Daniel Bergman, Heber Rocha, Eric Cramer, Ian McLean, Yoseph Dance, Max Both, Tamara Lopez-Vidal, ATUL Deshpande, Mathew, Elmar Bucher, Fatheh Anré. Forjaz, Michael Getz, Inês Godet, Furkan Kurtoglu, Melissa Lyman, John Metzcar, Jacob Mitchell, Andrew Raddatz, Jacobo Solorzano, Aneequa Sundus, Yafei Wang, David Denardo, Andrew Ewal the Thompson, Denis Wirtz, Laura Wood, Pei-Hsun. Wu, Neeha Zaidi, she Zheng, Jacquelyn Zimmerman, Jude Phillip, Elizabeth Jaffee, Joe Gray, Lisa Coussens, Young Hwan Chang et Laura M. Heiser.