Analyzing progenitor fate and dynamics long after embryonic development

According to Johns Hopkins Medicine researchers, they have devised a computer model called quantitative fate mapping that looks back in time to track the origin of cells in a fully grown organism. According to the scientists, the new model can help them more precisely identify which cells acquire modifications during development that change an organism's fate from healthy to disease states, such as cancer and dementia.

The breakthrough, published on November 23^rd, 2022, in the journal Cell, is based on mathematical algorithms that account for the general rate at which cells divide and differentiate, the rate at which mutations normally occur, and other known elements of organism development.

We can use this method to examine the development of organisms from cell samples, including those from non-model organisms such as humpback whales that we don’t ordinarily study. For example, with a cell sample from the carcass of a humpback whale, we can understand how it developed as an embryo.”

Reza Kalhor PhD, Assistant Professor, Biomedical Engineering, Johns Hopkins University and School of Medicine

Reza Kalhor is also associated with the Departments of Genetic Medicine, Molecular Biology, and Genetics and Neuroscience.

The new computer model is predicated on the idea that every complex living entity is derived from a single fertilized cell, or zygote. This cell divides, and the daughter cells divide further, eventually developing into tissue-specific cells. Humans, for instance, have over 70 trillion distinct cells and several thousand different cell types.

A mutation can arise each time a cell divides, and that change is passed on to the daughter cells, who divide again, possibly obtaining a second mutation, both of which are passed on to their daughter cells, and so on. The mutations function as a form of barcode that can be read by genetic sequencing equipment. Experts claim that they can trace these mutations in reverse order to reconstruct a cell's lineage.

The quantitative fate mapping program is split into two sections. One is a computer tool called Phylotime that interprets cell mutations as barcodes to determine the timeframe connected to cell divisions.

Phylotime is an acronym that stands for Phylogeny Reconstruction Using Likelihood of Time. Phylogeny defines and displays evolutionary development lines in biology. The second component produced by the Johns Hopkins group is a computer algorithm known as ICE-FASE, which generates a model of the hierarchy and lineages of cells inside an organism based on cell division timelines.

To put the computer model to the test, Johns Hopkins scientists produced mutations in human induced pluripotent cells (iPSCs) at random sites in the genome. These iPSCs can develop into practically any cell in the human body. They cultured the cells and allowed them to divide, observing the original mutation as well as spontaneous mutations in subsequent daughter cells.

The scientists completed the experiment by doing genome sequencing on the final group of daughter cells and entering any mutations discovered into the computer model.

As a result, a kind of family tree that started with the original human iPSC was created.

By comparing mutation combinations, scientists may build an ancestry of mature cells and generate a far more exact picture of how the organism evolved. They put the idea to the test using computer simulations of mouse cells and human iPSCs.

According to Kalhor, the new method can assist scientists in comparing normal vs diseased states in organisms including humans.

This tool may be helpful in showing how and when cells deviate from the normal path, which can aid the development of disease prevention tools or curative therapies.”

Reza Kalhor PhD, Assistant Professor, Biomedical Engineering, Johns Hopkins University and School of Medicine

The quantitative fate mapping tool’s so-called cell “fate maps” provide a history of cell fate determination events that took place during an organism’s development, however, unlike genomic sequencing research alone, the new tool reveals when the fate commitment took place and the relationship of a large number of various cell types in the population, according to Weixiang Fang PhD, a postdoctoral fellow in the department of biomedical engineering at Johns Hopkins and first author of the study.

While the computer model can predict how and when cells develop in an organism, it cannot tell whether spontaneous mutations are caused by external, internal, or random factors.

Fang and Kalhor have made Phylotime freely available to other researchers, and it is accessible online.