Research Area: This proposal is for 06: Enabling Technologies and specific Challenge Topic HG-102 Technologies for obtaining genomic, proteomic, and metabolomic data from individual viable cells in complex tissues. Abstract Most existing technologies can only measure the properties of a population of cells and not the properties of individual cells. C. elegans is unique among model organisms in that the complete cell lineage is known, enabling one to identify each nucleus in an individual. We have developed an automated cell lineage analyzer capable of extracting digital, single-cell expression information from confocal images of worms expressing GFP reporters. This cell analyzer can be used to extract expression data in a semi-high throughput manner. As proof-of-principle, we generated expression profiles of 93 genes in 363 specific cells from L1 stage larvae, and were able to quantitatively analyze expression of each gene as well as the molecular expression signature for each cell. This proposal is to first develop a generalized method to automatically annotate nuclei from confocal images, by assigning them a specific name from the cell lineage. We will then use the automated cell lineage analyzer in a data pipeline to analyze images from 1000 genes at six different developmental stages in 8000 confocal images. By generating a single cell expression database over the next two years, we will create a rich, new source of data for many years to come. Currently, images of worms in confocal data stacks can only be browsed manually, one gene at a time. Our database will convert images to quantitative expression values in an expression table that is suitable for computational analysis. Single cell expression analysis is a conceptually new way to study development and aging in C. elegans, using quantitative molecular signatures rather than cellular morphology. For instance, we can use the molecular signatures to determine how many different cell types are formed out of the total 959 cells in the lineage, to determine when and where during development cells begin to express different sets of genes, and to look for the way in which molecular fates are repeated in the cell lineage in order to extract the underlying regulatory modules that guide developmental pattern. This digital, single-cell expression database will be unique because C. elegans is the only model organism in which we can map the identities of individual nuclei and to our knowledge, we are the only group with a cell lineage annotator capable of extracting single cell expression information from larvae and adults.

Public Health Relevance

Kim, Stuart K. Narrative Most existing technologies can only measure the properties of a population of cells and not the properties of individual cells. C. elegans is unique among model organisms in that the complete cell lineage is known, enabling one to identify each nucleus in an individual. We have developed an automated cell lineage analyzer capable of extracting digital, single-cell expression information from confocal images of worms expressing GFP reporters. This project is a conceptual breakthrough in understanding the molecular phenotype of nearly all cell types in the worm, and the role it plays in tissue function in wild-type and mutant animals. PHS 398/2590 (Rev. 11/07) Page Continuation Format Page

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
NIH Challenge Grants and Partnerships Program (RC1)
Project #
1RC1GM091342-01
Application #
7830334
Study Section
Special Emphasis Panel (ZRG1-BST-M (58))
Program Officer
Edmonds, Charles G
Project Start
2009-09-30
Project End
2011-08-31
Budget Start
2009-09-30
Budget End
2010-08-31
Support Year
1
Fiscal Year
2009
Total Cost
$500,000
Indirect Cost
Name
Stanford University
Department
Anatomy/Cell Biology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Aerni, Sarah J; Liu, Xiao; Do, Chuong B et al. (2013) Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans. Bioinformatics 29:i18-26