A new computer model traces the origin of the cellular changes that drive development
Johns Hopkins Medicine scientists say they have developed a computer model – called quantitative fate mapping – that traces the developmental timeline to trace the origin of cells in a fully developed organism. The new model, they say, will help researchers determine more precisely which cells acquire changes during development that change an organism’s fate from a healthy state to a diseased one. states, including cancer and dementia. .
The achievement, described in the November 23 issue of Celluses mathematical algorithms that take into account the general rate of division and differentiation of cells, the rate of natural accumulation of mutations, and other known factors of organismal development.
“We can use this method to examine the development of organisms from cell samples, including those from non-model organisms like humpback whales that we don’t normally study,” says Reza Kalhor , Ph. D., assistant professor of biomedical engineering. , Genetic Medicine, Molecular Biology and Genetics, and Neuroscience at Johns Hopkins University and School of Medicine. “For example, with a sample of cells from the carcass of a humpback whale, we can understand how it developed as an embryo.”
The new computer model is based on the fact that every complex living organism comes from a single fertilized cell, or zygote. This cell divides and the daughter cells continue to divide, eventually differentiating into specialized tissue cells. Humans, for example, have about 70 trillion individual cells and several thousand cell types.
Every time a cell divides, a mutation can occur, and this change is passed on to daughter cells, which divide again, perhaps developing a second mutation, which is both passed on to their daughter cells, and so on. Mutations act as a kind of barcode that can be seen with genomic sequencing equipment. Scientists can follow these mutations in reverse order to develop a cell’s lineage, they say.
The quantitative fate mapping program has two parts. One is a computer program called Phylotime, which reads cell mutations as barcodes to indicate the time scale associated with cell divisions. The name Phylotime stands for Phylogeny Reconstruction Using Likelihood of Time. In biology, phylogeny outlines and describes lines of evolutionary development. The second part developed by the Johns Hopkins team is a computer algorithm called ICE-FASE, which creates a model of the hierarchy and cell lineages within an organism based on time measurements of cell divisions.
To test the computer model, the Johns Hopkins team induced mutations in human induced pluripotent cells (iPSCs) at certain locations in the genome and at random times. These iPSCs give rise to almost every cell in the human body. They cultured the cells and allowed them to divide, tracking the original mutation and the spontaneous ones that arose in subsequent daughter cells.
At the end of the experiment, the researchers performed genomic sequencing on the final group of daughter cells and entered any mutations they found into the computer model.
The result is a kind of family tree that extends from the original human iPSC.
Researchers can develop an ancestor of mature cells by comparing combinations of mutations and drawing a more accurate picture of how the organism developed. They tested the model using computer simulations of mouse cells and human iPSCs.
Kalhor said the new tool will help scientists compare normal and diseased states in organisms, including humans. “This tool could be useful in showing how and when cells deviate from the normal path, which could help in the development of disease prevention tools or therapeutic treatments,” added by Kalhor.
The cellular “fate maps” generated by the Quantitative Fate Mapping Tool provide a history of cell fate-determining events that occurred during an organism’s development, but unlike genomic sequencing studies alone, the new tool when fate engagement occurs and the relation of large numbers. of different cell types in the population, said Weixiang Fang, Ph.D., postdoctoral fellow in the Johns Hopkins Department of Biomedical Engineering and first author of the study.
While the computer model can generate how and when cells grow in an organism, it cannot determine whether spontaneous mutations occur due to external, internal or random factors.
Fang and Kalhor have made Phylotime free for other scientists, and it is available online.
The research was supported by the Simons Foundation, the National Institutes of Health and the David and Lucile Packard Foundation.
Other scientists who contributed to the research include Hongkai Ji, Ph.D., professor of biostatistics at the Johns Hopkins Bloomberg School of Public Health, who co-supervised the study, as well as Claire Bell, Abel Sapirstein, Soichiro Asami, Kathleen Leeper and Donald Zack of Johns Hopkins.
