Animal modeling of disease states and bioreporters for in situ analysis of cellular dynamics are an essential aspect of biomedical research;however, most studies focus on genetic manipulation within the whole organism or tissue of interest, which does not accurately reflect disease states that are often associated with defects in individual cells or groups of cells. This discrepancy is largely due to the technical challenges of single cell manipulation and analysis within an intact organism. While ongoing SCAP studies are characterizing the transcriptome, proteome, and chromatin alterations within single cells, a biological system to test the impact of these single cell alterations is necessary. Therefore, consistent with this FOA, we believe that a system for con- trolled genetic manipulation (resulting in loss of function alleles or expression of exogenous cDNAs/bioreporters) within a single cell of a viable organism is required. This system should not alter or perturb the surrounding environment and should allow for potential systems based analysis and biomarker incorporation. Therefore we hypothesize that: 1) through the use of optogenetic (light inducible) Cre transgenic animals, single cell Cre recombination can be achieved allowing for single cell inducible gene alterations (i.e. conditional knockout or bioreporter/gene of interest expression);and 2) through the use of a Cre inducible Cas9 system, single and multiple gene ablations can be rapidly achieved within an individual cell of an intact organism. These two systems will be established within the zebrafish embryo but can be applied to all model organisms. Upon completion of this proposal we will have established versatile and efficient single cell tools for selective genetic alterations that will facilitate single cell analysis in a multitude of research fields. We anticipate that this research will have a broad positive impact on a number of other human diseases including (but not limited to) neurobiology, immunology, cancer biology, and developmental biology. This proposal is in alignment with the SCAP and this FOA objectives: 1) to develop tools that """"""""minimize cell perturbation and permit viability of cells for repeated measures over time"""""""";2) """"""""Systems-level single cell dataset analysis or modeling... in the context of tissues or whole organisms;and 3) """"""""the discovery of new, innovative tools for spati- otemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation"""""""".

Public Health Relevance

Most diseases are derived from genetic alterations or accumulation of biochemical alterations in a single or a cluster of cells within specific tissues. We are proposing to generate genetic tools to allow for single cell genetic alterations with spatia and temporal control. Understanding/modeling this disease progression is essential for disease prevention.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21NS092105-01
Application #
8831293
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lavaute, Timothy M
Project Start
2014-09-30
Project End
2016-08-31
Budget Start
2014-09-30
Budget End
2015-08-31
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Alabama Birmingham
Department
Pharmacology
Type
Schools of Medicine
DUNS #
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Parant, John M; Yeh, Jing-Ruey Joanna (2016) Approaches to Inactivate Genes in Zebrafish. Adv Exp Med Biol 916:61-86
Percival, Stefanie M; Parant, John M (2016) Observing Mitotic Division and Dynamics in a Live Zebrafish Embryo. J Vis Exp :
Percival, Stefanie M; Thomas, Holly R; Amsterdam, Adam et al. (2015) Variations in dysfunction of sister chromatid cohesion in esco2 mutant zebrafish reflect the phenotypic diversity of Roberts syndrome. Dis Model Mech 8:941-55
Thomas, Holly R; Percival, Stefanie M; Yoder, Bradley K et al. (2014) High-throughput genome editing and phenotyping facilitated by high resolution melting curve analysis. PLoS One 9:e114632