Single cell analysis is becoming increasingly important as it is clear that ensemble measurements mask the diversity of the biology in cell populations. Single cell genotyping and phenotyping are necessary to define functional heterogeneity in varying cell types including diseased vs. normal cells. The overall goal of this project is to develop new bioanalytical tools for performing high resolution single cell analysis. This interdisciplinary project involves Chemistry, Molecular Biology, Biochemistry, Genetics, and Bioengineering and will be conducted by a team including a senior Principal Investigator, one postdoctoral associate, and two graduate students.
Specific Aim 1 -Develop a high fidelity single DNA molecule genotyping approach for analyzing thousands of molecules simultaneously and with the ability to interrogate multiple SNPs. We plan to employ fiber optic microwell arrays to develop a robust, efficient, fast, and affordable method of simultaneously genotyping single DNA molecules from thousands of individual cells.
Specific Aim 2 -Develop an approach to isolating single cells, capturing genomic DNA, and genotyping the captured DNA. In this Aim, we will apply the methods developed in Specific Aim 1 to whole cells. Thousands of single E. coli cells will be captured in individual wells, lysed, genomic DNA fragmented, the DNA captured on the surface of the individual wells, and then genotyped.
Specific Aim 3 -Develop a high resolution single molecule analysis method for analyzing the contents of single cells. We will develop methods for performing high resolution single molecule counting of the contents of individual cells. Single cells will be isolated, lysed, and their contents will be captured in microwell arrays such that individual mRNA and protein molecules are isolated. We will then use a variety of methods that enable us to count the individual molecules. Success of these aims will provide a powerful new technology broadly applicable to multiple areas of biological research. For biologists, it provides the ability to describe the complex genetics of cell populations, providing clinicians with improved opportunities for diagnostics, and relating population genetics with responses to therapy and clinical outcomes. For experimentalists, it provides new ways to study phenomena such as tumor progression and responses to experimental therapies. For researchers on aging, it provides the ability to monitor changes in somatic genetics with age and the factors influencing them. For geneticists, it provides a low cost ability to construct genetic maps, to identify trans-acting elements controlling recombination, and to monitor the molecular structure of recombination products with high resolution. Our long term goal is to apply the developed technology to a variety of cell types to study fundamental cell biology and to understand how cell-to-cell and cell population differences may lead to different cell fates and may define disease.

Public Health Relevance

Individual cells in a population, such as are present in bacterial infections, as well as diseased tissues such as cancer, exhibit random behaviors such that different cells may behave quite differently relative to the average behavior of the population and can lead to such conditions as bacterial antibiotic resistance and cancer metastasis. The goal of this project is to develop new tools for analyzing single cells to characterize and understand the differences between cells in a population.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG006021-02
Application #
8197062
Study Section
Enabling Bioanalytical and Biophysical Technologies Study Section (EBT)
Program Officer
Schloss, Jeffery
Project Start
2010-11-18
Project End
2013-10-31
Budget Start
2011-11-01
Budget End
2012-10-31
Support Year
2
Fiscal Year
2012
Total Cost
$338,933
Indirect Cost
$113,933
Name
Tufts University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
073134835
City
Medford
State
MA
Country
United States
Zip Code
02155
Walt, David R (2013) Optical methods for single molecule detection and analysis. Anal Chem 85:1258-63
Palacios, Manuel A; Lacy, Michael M; Schubert, Stephanie M et al. (2013) Assessing the stochastic intermittency of single quantum dot luminescence for robust quantification of biomolecules. Anal Chem 85:6639-45
Zhang, Huaibin; Nie, Shuai; Etson, Candice M et al. (2012) Oil-sealed femtoliter fiber-optic arrays for single molecule analysis. Lab Chip 12:2229-39