The principal goal of this application is to accelerate the development of a whole brain imaging method that can link complex gene expression dynamics in single cells, to the function of populations of neurons known to be responsible for cognition. For the first time, whole brain imaging, analogous to PET or fMRI methods, can be conducted at the multiple single cell and multiple gene levels. The new method described in this proposal provides a bridge between what we know about the activity characteristics of cell ensembles recorded during behavior, and what we know about multiple genes that are activated by these behaviors. This method uses fluorescent in situ hybridization (FISH) to monitor the subcellular distribution of RNA of immediate-early genes such as Arc. In a recent report (Guzowski et.al., Nature Neuroscience), we demonstrate that Arc RNA first appears in the nucleus at discrete foci that appear to be sites of transcription. The processed mRNA then accumulates in the cytoplasm. Because the time course of FISH signal in nuclear and cytoplasmic compartments is distinct, we are able to infer the activity history of individual neurons at two different times. This method, termed cellular compartment analysis of temporal activity by FISH (catfish), allows visualization of gene expression, activated by discrete behaviors or experiences, in the populations of the single cells responsible for encoding these events. Because of its temporal and cellular resolution properties, catfish offers a unique insight into the cellular basis of information processing for a large number of cells across distal brain structures. Currently, the application of the catfish approach is limited by the time-consuming manual counting methods that are used. Recent advances in computer-assisted cell counting algorithms promise to increase objectivity and accelerate the data analysis so that large numbers of samples or braod regions of the brain can be examined. The co-P.I.'s of this application represent the laboratories from which the molecular imaging and parallel electrophysiological recording methods were developed. Additionally, Dr. B.Roysam and S.J.Lockett, who are experts in computer-assisted analyses of cell counts, will join the research program. The goal of Aim 1 is to develop an automated system to rapidly convert data acquitted from the confocal fluorescence microscope into quantitative counts of cells with intracellular IEG FISH signal.
Aim 2 will develop methods to assess the presence of cytoplasmic IEG FISH signal, and associate this staining to defined nuclei.
Aim 3 will use methods from Aims 1 and 2 to compare the pattern of gene activation in multiple brain regions (hippocampus and neocortex) of young rats, and hippocampal regions in young and memory-impaired old animals. These studies will provide an assessment of the general utility of the catfish method for imaging gene activation induced by behavior when explicit hypotheses for cellular activation can be made from electrophysiological experiments. Our long-term goal is to create a novel image analysis tool that links behavioral systems, and molecular neuroscience approaches to a variety of behaviors and brain regions.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG018230-02
Application #
6372499
Study Section
Special Emphasis Panel (ZRG1-MDCN-1 (02))
Program Officer
Wise, Bradley C
Project Start
2000-09-30
Project End
2003-08-31
Budget Start
2001-09-01
Budget End
2002-08-31
Support Year
2
Fiscal Year
2001
Total Cost
$236,656
Indirect Cost
Name
University of Arizona
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
City
Tucson
State
AZ
Country
United States
Zip Code
85721
Sutherland, Vicki L; Timlin, Jerilyn A; Nieman, Linda T et al. (2007) Advanced imaging of multiple mRNAs in brain tissue using a custom hyperspectral imager and multivariate curve resolution. J Neurosci Methods 160:144-8
Lin, Gang; Bjornsson, Chris S; Smith, Karen L et al. (2005) Automated image analysis methods for 3-D quantification of the neurovascular unit from multichannel confocal microscope images. Cytometry A 66:9-23
Burke, Sara N; Chawla, Monica K; Penner, Marsha R et al. (2005) Differential encoding of behavior and spatial context in deep and superficial layers of the neocortex. Neuron 45:667-74
Lin, Gang; Chawla, Monica K; Olson, Kathy et al. (2005) Hierarchical, model-based merging of multiple fragments for improved three-dimensional segmentation of nuclei. Cytometry A 63:20-33
Chawla, Monica K; Lin, Gang; Olson, Kathy et al. (2004) 3D-catFISH: a system for automated quantitative three-dimensional compartmental analysis of temporal gene transcription activity imaged by fluorescence in situ hybridization. J Neurosci Methods 139:13-24
Lin, Gang; Adiga, Umesh; Olson, Kathy et al. (2003) A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry A 56:23-36
Vazdarjanova, Almira; McNaughton, Bruce L; Barnes, Carol A et al. (2002) Experience-dependent coincident expression of the effector immediate-early genes arc and Homer 1a in hippocampal and neocortical neuronal networks. J Neurosci 22:10067-71