Researchers at Columbia University Medical Center have created a brand new tool to describe the many possible ways in which a cell might develop. Rooted in the mathematical field of topology, the particular tool provides a roadmap that offers detailed insight into how originate cells give rise to specialized cells.
The study was published in Nature Biotechnology .
Every organism begins with one particular cell. As that cell divides, its copies department off to become specialized cells — such as heart, bone tissue, or brain cells — in a process known as difference. To understand the internal and external cues that move tissue along this path, scientists can sequence their RNA — the molecular messenger that translates DNA in to proteins and other products.
Sequencing RNA from the batch of cells is not ideal, however , because the tissues are usually in different states of development. To address this problem, researchers have developed single-cell RNA sequencing. “It’s like a new microscope, giving us the ability to study many biological phenomena at the same time, ” said Raul Rabadan, PhD, associate professor associated with systems biology and biomedical informatics at Columbia plus co-author of the paper. “However, researchers are still left using the problem of understanding the relationships between different cell declares, which drive the process of development. ”
To analyze cellular development, scientists use mathematical tools to analyze enormous amounts of sequencing data. But these tools rely on underlying presumptions that narrow the possible results. “Due to the difficulty involved in cellular development, models that make assumptions actually restrict your ability to make new discoveries, ” said Abbas Rizvi, PhD, a postdoctoral research scientist in Columbia’s Department of Biochemistry and Molecular Biophysics and the prospect author of the paper.
Dr . Rizvi, along with Pablo G. Camara, PhD, a postdoctoral fellow plus theoretical physicist in the Departments of Biomedical Informatics plus Systems Biology, looked to topology, an area of mathematics that studies the spatial relationships between surfaces plus shapes, to identify connections between different cellular states as well as the genes that are active while cells are in those declares. The collaboration developed an algorithm, called single-cell topological information analysis (scTDA). The algorithm analyzes the RNA sequences of individual cells, reconstructing the underlying developmental trajectories, plus capturing the progression of different transcriptional programs in time.
The researchers used scTDA to map the way of mouse stem cells, which they had coaxed straight into becoming motor neuron cells. The map correctly pointed out the possible developmental trajectory of these cells, starting because stem cells and finally becoming neurons. By looking at which genetics were active near particular forks in the map, the particular researchers were able to identify proteins that appear to guide mobile development at different points along the path. The method seemed to be applied to study the development paths of stem tissues from mouse lungs, human embryos, and mouse minds.
“We expect many more discoveries to come in order to light as scientists mine this data set, inch said co-author Tom Maniatis, PhD, the Isidore Ersus. Edelman Professor of Biochemistry, Chair of the Department associated with Biochemistry and Molecular Biophysics at Columbia. “It actually opens up possibilities for a very deep analysis of person cells at very specific stages of development, inch said Dr . Maniatis.
“This approach offers deep insights into the potential fate of a cell, providing us access to the pivotal regulators and molecular changes that govern a cell’s identity — and offering the opportunity to steer cells away from paths that have a negative impact on its development, ” said Dr . Rizvi.
The approach is currently being applied to uncover the characteristics and cell makeup of complex biological processes, which includes cancer.