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(Seminar) Reconstruct cellular dynamics from single cell data
2020-08-06  【 】【打印】【关闭

CAS Key Laboratory of Theoretical Physics

Institute of Theoretical Physics

Chinese Academy of Sciences

Seminar

Title

题目

Reconstruct cellular dynamics from single cell data

Speaker

报告人

王维康  博士

Affiliation

所在单位

 美国匹兹堡大学医学院

Date

日期

 2020年8月6日(星期四)10:30 - 11:30

Venue

地点

 ITP South Building 6620

Contact Person

所内联系人

周海军

Abstract

摘要

Recent advances of single cell techniques catalyzed quantitative studies on the dynamics of cell phenotypic transitions (CPT) emerging as a new field. Two grand technical challenges, however, impede further development of the field. Fixed cell-based approaches can provide snapshots of high-dimensional expression profiles but have fundamental limits on revealing temporal information, and fluorescence-based live cell imaging approaches provide temporal information but are technically challenging for multiplex long- term imaging. To tackle the challenges we developed an integrated experimental/computational platform for reconstructing single cell phenotypic transition dynamics. We first developed a live-cell imaging platform that tracks cellular status change through combining endogenous fluorescent labeling that minimizes perturbation to cell physiology, and/or live cell imaging of high-dimensional cell morphological and texture features. With our platform and an A549 VIM-RFP EMT reporter cell line, recorded live cell trajectories reveal parallel paths of epithelial-to-mesenchymal transition missing from snapshot data due to cell-cell dynamic heterogeneity. Recognizing that CPTs are examples of rate processes, we introduced transition path analyses and the concept of reaction coordinate from the well-established rate theories into CPT studies, and applied on this EMT process. We modified a finite temperature string method to reconstruct the reaction coordinate from the trajectories, and reconstruct a corresponding quasi-potential. The potential reveals that the EMT process under study resembles a barrier-less relaxation process. Thus our work demonstrates the necessity of extracting dynamical information of phenotypic transitions and the existence of a unified theoretical framework describing transition and relaxation dynamics in systems with and without detailed balance.
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