Combining the latest methods in gene splicing and computer modeling, Rice University researchers are trying to develop a predictive framework for one of the most basic and complex biological phenomena — cellular heterogeneity, or the ability of genetic clones to act and behave differently when exposed to the same set of environmental stimuli.
The five-year, $1.5 million project is funded by the National Institute of General Medical Sciences, one of the National Institutes of Health. It involves fundamental modeling studies in conjunction with a series of experiments on genetically modified strains of E. coli bacteria. The researchers hope the research will provide a clearer understanding not only of bacterial pathogenesis but also of other diseases like cancer.
“We are trying to understand the relationship between genotype — the inheritable information, or DNA, that each cell receives at birth — and phenotype — the outward, physical manifestation of the cell,” said principal investigator Nikos Mantzaris, assistant professor of chemical engineering and bioengineering.
In all cell cultures, be they colonies of single-celled bacteria or plant or animal tissues, a population of genetically identical clones — cells of the same genotype —will contain a number of different phenotypes.
“The basic reasons for heterogeneity in bacterial cell populations are conceptually understood, but scientists lack the means to predict the type and proportion of phenotypes that will develop from a specific genetic architecture under a precise set of circumstances, and that is what we hope to accomplish,” said Mantzaris.
Cells that share the same genes — and the same external environment — can develop differently for two basic reasons. Both have to do with the way genetic information is used and interpreted by the cellular machinery inside the cell.
In the first case, cells are given unequal resources at birth. In E. coli bacteria, for example, cells reproduce by splitting into daughter cells. Even though the daughters are given identical copies of DNA, they often get an unequal share of proteins, enzymes, transcription factors and other biochemical compounds from the original cell. This unequal start — referred to as unequal partitioning — can be enough to set the daughters on completely different developmental paths.
The second way genetically identical cells develop into different phenotypes is due purely to the chance action of specific, regulatory molecules inside each cell. Called stochastic heterogeneity, this derives from the fact that regulatory molecules, which strongly influence the phenotype of each individual cell, exist in very small numbers and hence, their action is purely random.
“To develop our predictive method of determining how heterogeneous phenotypes are distributed within a cell population, our group will create a series of E. coli strains that contain very precise and targeted mutations affecting gene-regulatory networks,” said George Bennett, professor and chair of the Department of Biochemistry and Cell Biology. “We're focusing on two well-characterized gene-regulatory networks, one that governs how well E. coli can stick to surfaces and another that governs adaptation to temperature change.”
Gene-regulatory networks are interconnected sets of genes that control the expression of particular genes in a cell. In E. coli, for example, the rise in temperature that occurs inside the human body activates a particular set of genes that make the bacteria much more virulent.
Via experiments on the tailored strains of E. coli, the project team will first focus on understanding how specific gene-regulatory structures, which are common among all cells of a population, give rise to different phenotypes within a cell population. Once a link is established between gene-regulatory architecture and cell population heterogeneity, the team will shift focus and concentrate on the interplay between cell population heterogeneity and adaptation dynamics. For example, how does the proportion of phenotypes within a population change when temperature rises or falls?
Two other Rice research groups — that of Kyriacos Zygourakis, the A.J. Hartsook Professor and chair of the Department of Chemical Engineering, and Ka-Yiu San, the E.D. Butcher Professor of Bioengineering — will characterize the temporal changes in cell population phenotype using a combination of flow cytometry and fluorescence microscopy.
All of the experimental evidence will feed back into the modeling efforts of Mantzaris' group, which will attempt to develop a predictive scheme that bioengineers and medical researchers can use to design test populations of cells that have tailored and predictable distributions of phenotypes. Designing cell populations with such specificity could be a real boon to scientists testing the effects of new drugs and experimental therapies on bacterial pathogens.
“By unveiling the relationship between gene-regulatory architecture and cell-to-cell phenotypic variability we hope to gain insight into fundamental biological and medical issues, such as developmental processes and cancer, where cell population heterogeneity is bound to be important,” said Mantzaris.