Single-cell morphological data reveals signaling network architecture

Metastasis, the migration of cancer cells from the primary site of tumorigenesis and the subsequent invasion of secondary tissues, causes the vast majority of cancer deaths. To spread, metastatic cells dramatically rearrange their shape in complex, dynamic fashions. Genes encoding signaling proteins that regulate cell shape in normal cells are often mutated in cancer, especially in highly metastatic disease. To study these key signaling proteins in locomotion and metastasis, we develop and validate statistical methods to extract information from highthroughput morphological data from genetic screens. Our contributions fall into three major categories. 1) To define and apply robust statistical measures to identify genes regulating morphological variability. We develop and thoroughly test methods for measuring morphological variability of single-cells populations, and apply these metrics to genetic screens in yeast and fly. We further apply these techniques to subsets of genes involved in cellular processes to study genetic contributions to variability in these processes. We propose new roles for genes as suppressors or enhancers of morphological noise. We validate our findings on the basis of known gene function and network architecture. 2) To perform inference of protein signaling relationships by utilizing high-throughput morphological data. We apply machine-learning techniques to systematically identify genetic interactions between proteins on the basis of image-based data from double-knockout screens.

Department dc:contributor.department

Harvard University--MIT Division of Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Nir, Oaz

Advisor dc:contributor.advisor

• Bonnie Berger.

• Harvard University--MIT Division of Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/58457

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/58457