Significance of Research
Molecular biology is a huge subject with 30000 genes in mammalian genomes with 2 to the power of 30000 combinations of gene expressions (Soneji et al, 2007, p. 38). However, the possible gene expressions in real life are much less. Deep knowledge of architecture and the dynamic behavior of the transcription networks could reveal generation or reprogramming of cell fate for purposes of therapeutic or commercial benefit (Soneji et al, 2007, p. 38).
Development occurs when the ordered division of cells forms a whole organism. Signals and transcription factors that interact with one another to regulate the fate of individual cells control the process. These interactions, when viewed as a whole, form a genetic regulatory network. The regulation of development of cell behaviors like renewal, proliferation, differentiation, and death is not yet fully understood (Soneji et al, 2007, p. 31).
Cell-specific gene expression programs which are regulated by transcription factor interactions would help us to understand cell behaviors including development. Understanding the dynamics of genetic regulatory networks is an immense challenge to the future for the treatment of cancers, identifying congenital abnormalities, and the possibility of genetic engineering to cure or prevent them as required. The dynamics of these networks also throw light on the mechanisms of diseases that occur when the cellular processes are dysregulated. Accurate predictions can be made of the possibility of illnesses when these regulatory networks are affected (Karlebach and Shamir, 2008).
This research intends to explore ways to identify, model, test, and represent such networks to understand how transcription factors and signals work together to control development, and how cells are programmed to different phenotypes by using a variety of approaches, including in vivo, in vitro and in silico methods.
Review of Background of the Research
The School of Biology, Nottingham, is studying developmental genetics and gene control. Eukaryotic gene expression is focused upon in the research at this school. The embryonic development of vertebrates and the genetics involved is another focus. Mechanisms that regulate stem cell fate are mainly investigated in developmental studies (Loose, 2004). Stem cells from the nervous system, germ cells, and bone marrow-derived ones are being studied. Models are being developed by Dr. Matthew Loose for investigating how cell fate is controlled by the interplay of transcription factors and signals. The studies also include the control of transcription and the mechanisms of RNA maturation (Loose, 2004).
The modeling of genetic regulatory networks has evolved as the latest development in molecular biology. Global gene expression data sets and information of genome sequence from many species have made this possible through reverse genetic engineering (Soneji et al, 2007, p. 30). The hemopoietic stem cells are the most important of cells in the present era as they have unique biological properties which are of great interest to science, commercial purposes, and public interest. The molecular pathways are to be fully revealed.
The present information that has been accepted by researchers is that transcription factors are key regulators of cell activities (Enver and Greaves, 1998). It has been found that each cell has a different gene expression and cell fate is decided or changed by a change in a single transcription factor. However, cell combinations have varying gene expression patterns. The manners in which genes interact with each other provide a genetic regulatory network (Soneji et al, 2007, p.31). The decisions for the fate of the hemopoietic stem cell would be predicted by these networks.
Transcription factors and signals together have a functional relationship in the genetic regulatory network. The key determinants of cell fate are the transcription factors (Loose and Patient, 2004, p.467). Extracellular signals would trigger their binding with the DNA and gene transcription is regulated. Target genes would be other transcription factors and signals. This cross-regulation produces a relationship that would be stable when signals are not forthcoming. The molecular programming of cells during development would be provided by the extracellular signals, intracellular transcription factor responses, and the relationships between them (Loose and Patient, 2004, p. 467).
During embryonic development of the primary germ layers of ectoderm, mesoderm, and endoderm, part of the mesoderm and endoderm respond to inducing signals together and develop in a close relationship. This has been demonstrated in the amphibian Xenopus Laevis (Loose and Patient, 2004, p.467). Cardiac or other congenital abnormalities have also been attributed to defective development. The molecular pathways could be defective leading to this consequence. The highest abnormality seen at birth is a cardiac abnormality (McFadden, 2002).
A gene regulatory network has been developed for the specification of erythroid cells through the hemopoietic stem cell (Swiers, Patient and Loose, 2006). This network has a series of bipotential switches arranged in a cascade. It is believed that one pair of cross-antagonistic transcription factors could control two lineages in a mathematical model. This could be the pattern or motif seen throughout development (Loose and Patient, 2006). The transcription factors of GATA-1 and PU.1 mutually inhibit each other and model the process of lineage specification in hematopoietic cells (Roeder and Glauche, 2006). They create a situation that allows the progenitor cell to select between the erythroid megakaryocytic lineage and the myeloid-monocytic one. The transcription factors also promote the expression of genes that implement these lineages (Soneji et al, 2007, p. 37).
Computational methods have been developed with the help of microarray data sets to study the structure of the transcriptional networks from their dynamics. Several techniques have been adopted. The Probabilistic Boolean network has been found to be useful. High-quality data were obtained first from yeast. Mammalian stem cells are more difficult to handle for quality data as hematopoiesis is a complex system (Soneji et al, 2007, p. 35). The main issue would be to resolve cellular heterogeneity.
Specific Aims for Research
Genetic regulatory networks are being investigated to identify the networks by finding the transcription factors and the lineages. The model of linked networks is to be determined and the choice of fate made. The model would be tested for transcription –target gene relationship. The networks would be represented to understand how transcription factors and signals work together to regulate development. The promoters of the target would be having binding sites for the transcription factor which can either repress or activate (Loose and Patient, 2004, p. 468). The relationships would be classed directly if responding to the upstream factor when protein synthesis inhibitors are present. If there is no binding site, the relationship is indirect. Transcription factors that bind to the DNA through another transcription factor are also believed to be having a direct relationship. The intercellular signaling molecules are included in the research ((Loose and Patient, 2004, p. 468). The signaling molecules and transcription factors are to be labeled separately. The data obtained would be compared to the available statistics on the World Wide Web. The network is divided into time zones depending on the morphological and gene expression criteria. The various stages of development from fertilization onwards are followed carefully. The first stage could be up to the stage of mid-blastula and has the effects of the mother and the zygotic expression. Mid blastula transition has a surge of zygotic gene expression. Such a surge is again seen at a later stage or the late blastula stage (Loose and Patient, 2004, p. 468). The mesoderm and the endoderm are both well defined by the last stage.
Research approaches
A variety of approaches is employed. The in vivo approach would involve doing the study in live conditions. The in vitro approach would involve performing the research in laboratory conditions. The in silico approach is more effective for tracing the protein-protein interactions in the cells. Independent assessment procedures are possible using this approach. More data could be gathered too.
Researches on the development of cells have been done in the amphibian Xenopus Laevis. In vitro studies have been done on mouse haemangioblasts of the Mix+Brachyury+Flk-1+ (Swiers, 2007). Studies on the amphibian Ambystoma mexicanum (axolotl) show better results for germ cell specification than Xenopus. A cloned variety of axolotl homolog has shown only slight differences from the original variety (Swiers, 2007). Developmental studies have also been done on the sea-urchin. (Loose and Patient, 2004).
References
Enver, T. & M. Greaves. 1998. Loops, lineage, and leukemia. Cell 94: 9–12.
Karlebach, G. and Shamir, R. (2008). “Modelling and analysis of gene regulatory networks”. Nat. Rev. Mol Cell Biology, Vol. 9, No.10. Pg.770-780ю
Loose, M. and Patient, R. (2004). “A genetic regulatory network for Xenopus mesendoderm formation” Developmental Biology, Vol. 271, Pgs 467-478
McFadden DG, Olson EN. (2002). “Heart development: learning from mistakes”. Current Opinion Genetic Development 2002; 12:328–35.
Roeder, I. & I. Glauche. (2006). “Towards an understanding of lineage specification in hematopoietic stem cells: a mathematical model for the interaction of transcription factors GATA-1 and PU.1”. J. Theor. Biol.4: 852–865.
Soneji, S. et al. (2007). “Inference, Validation, and Dynamic Modeling of Transcription Networks in Multipotent Hematopoietic Cells”. Annals of New York Academic Science, Vol 1106, Pg 30-40, New York Academy of Sciences.
Swiers, G., Patient, R. and Loose, M. (2006). “Genetic regulatory networks programming haematopoietic stem cells and erythroid lineage specification”. Developmental Biology, Vol. 294, Pg 525-540, ScienceDirect, Elsevier.
Swiers, G. et al. (2007). “Exploring the role of Mix in mesoendoderm and blood specification in amphibians”, Program abstract 205, Institute of Genetics, University of Nottingham, Nottingham, UK.