Everyone knows that the development of a human being, from the first cell (the zygote) to the adult individual, is a complex process. However, how complicated is it? A study by researchers from the Federal University of Bahia (UFBA) provides a more precise measure of this complexity, as well as clues that might aid the treatment of certain diseases in the future.
The study was conducted by a team of physicists that decided to explore the biological applications of the tools more commonly used in their original field. Hence a highly uncommon approach: they decided to look upon human development as if it were a computer network such as the internet.
In the initial stage of the study, Viviane Galvão, who at the time was doing her doctorate at the State University of Feira de Santana and is now a researcher at the Physics Institute of UFBA, combed scientific literature in search of all the references about the types of cells of the human body, regardless of the latter?s development stage. An analysis was conducted of studies on spontaneously aborted embryos and fetuses in different stages of pregnancy. The physicist also consulted studies that identified the types of cells in fully formed individuals, from birth to death.
Overall, the team identified 873 different cell types. The number may seem strange to those who are conversant with human embryology; after all, it is generally acknowledged that in the body of an adult there are some 200 cell types. What explains this difference is that the work of the group from Bahia, conducted jointly with researchers from Ceará state and from the United States, takes into account the cells of tissues that only exist during certain development stages and that then disappear, as is the case of the placenta, only found during pregnancy.
After putting together a catalog of cells as complete as possible, the group used computer models to look for connections between the different cell types, in the hope of establishing the precursors of each type of tissue and creating a network of relationships among all the cells. This was when the so-called network of human cell differentiation (NHCD) arose. It was described in detail in an article published in March of this year in the journal PNAS.
During this stage of the work, they got a surprise: the results contradicted those of preceding studies. Instead of forming a pattern reminiscent of a tree, in which the trunk consists of the precursory cells and the branches, of their derivates, a rather different design emerged: the links were more complex, with paths that were not necessarily linear and that were rich in intermediary connections. At some points, the network was reminiscent of a spider’s web. “We found that cell A might turn not only into cell B, but also into cell C,” Viviane tells us. “There were several possible tracks for the formation of a given type of cell.”
The cell differentiation map has a pattern of connections that can be studied with the mathematical tools used to study networks such as the internet. However, more importantly, according to the researchers, this work provides us with a systemic overview of cell differentiation.
Physicians and biologists that investigate an organ such as the heart usually have in-depth understanding of heart cells and of their precursors, just like a pneumologist knows much more about respiratory cells than about the others. “With this network, one can now see: ‘Ah, this digestive cell also appears in the respiratory system,’ which a person from a specific area might not know,” Viviane explains.
The pattern of the network may also provide some guidance in the search for substances that can allow one to better control cell differentiation processes, this being one of the major challenges of research into steam cells, known for their vast potential to give rise to different body tissues provided they get the right stimulus. “One can see in the network that a given cell type A more commonly comes from a cell B, but that it can also arise from a C type cell; therefore, this encourages researchers to look for new pharmaceutical formulations capable of inducing this specific differentiation,” says the researcher from UFBA.
Studies on stem cells, incidentally, are the ones that might benefit the most from the more integrated view of cell differentiation. While she was developing the cell differentiation network, Viviana Galvão was also working on the modeling of several more specific networks tied to processes connected to diseases. One of the studies sought to depict what happens in cardiac regeneration terms when a heart damaged by the Chagas’ disease parasite gets an injection of adult stem cells. The treatment was developed by the group of the physician Ricardo Ribeiro dos Santos, from the Oswaldo Cruz Foundation (Fiocruz) of Bahia, and it has shown promising results so far, although the actual mechanism involved in the effect of the stem cells is still unclear.
One of Viviane’s studies, in which the Fiocruz researcher was also involved, attempted to cast some light on this issue, by theoretical means. The results suggest certain explanations of why the treatment works and may, in the future, help to indicate the ideal quantity of stem cells to be used, although several biological mechanisms involved in heart recovery are still far from clear.
Viviane also worked on similar models for other diseases, such as certain types of cancer, and she states that the results can be used, for instance, to forecast the potential metastatic pathways. “By identifying the kinship among different cell types, we can understand why a specific cancer will invade a given organ and not another,” she says.
She and her collaborators now plan to establish a network to characterize the immune response and cell interactions of other diseases caused by parasites, such as tuberculosis and malaria. However, at first, physicians and biologists may have their reservations about these findings. After all, it is not yet known for sure whether all types of human cells have been identified and an incomplete network might lead to wrong conclusions.
GALVÃO, V. et al. Modularity map of the network of human cell differentiation. PNAS. v. 107, n. 13, p. 5.750-55. 30 Mar. 2010.