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Massachusetts Institute of Technology

Cell-based sensors for quantifying cell health and disease progression in engineered systems

Abstract

dc:description.abstract

Healthy cells create healthy beings, while dysfunctional cells cause disease. Studying disease requires an understanding of how cells become dysfunctional from physiological states. Gaining this insight in vitro involves subjecting cells to relevant microenvironments and utilizing methodologies for assaying cells. Critically, to obtain accurate and unbiased insight, it is important to ensure that the cellular microenvironment remains representative, and that the assay methodology itself does not adversely perturb cell state. This thesis presents an approach where cells 'report' upon their healthy or stressed states, which could be assessed to either learn disease mechanisms, or quantified to design 'cell-friendly' methodologies. We engineered cell-based sensors that emit stress-regulated fluorescence, and applied them to characterize how distinct microenvironments regulate cell health. Here, we describe two endeavors that highlight the utility of this approach. We first developed cell stress sensors for a diverse bioinstrumentation community to quantify the impact of engineered systems and methodologies upon cell health. Using NIH3T3 cells, we engineered sensors that report on stresses induced by DNA damage, heat shock, or fluid shear stresses. Each sensor provides sensitive and specific responses to stress-induced pathways (relevant to several cell types), and can be used for a multiplexed stress-readout. The sensors do not require additional reagents and can be conveniently quantified with flow cytometry and real-time imaging. Successful distribution and adoption of the sensors by external users enabled quantitative characterization of flow sorting systems in the context of cell health, which was not explored before. Hence, the cell-sensor methodology designed as an 'open source' tool, could potentially serve as a novel standard for quantifying cell stress, and broadly for designing 'cell-friendly' methodologies. We further utilized cell-based sensors to gain biological insight into stress-regulated diseases. We focused on atherosclerosis, a flow-regulated cardiovascular disease that remains a major cause of morbidity and mortality worldwide. We engineered a novel microfluidic platform to study atherogenesis in vitro that overcomes several limitations of existing models. This device emulates in vivo microenvironments by applying programmable spatiotemporal flow profiles observed from human patients directly upon cultured human cells. Utilizing an endothelial cell-based sensor (that reports on vascular health), device flows were validated with known biomarkers and endothelial signatures. Subsequently, these sensors were used to gain novel insight upon atherogenesis through the impact of hemodynamic flows upon endothelial function. Overall, this thesis presents a facile and quantitative approach to investigate complex cell-stress emergent from diverse bioinstrumentation or within a disease microenvironment, which can be utilized to discover how environmental conditions regulate cell physiology, and human health.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Varma, Sarvesh
Advisor dc:contributor.advisor
  • Joel Voldman.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/112031
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/112031

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Varma, Sarvesh. Cell-based sensors for quantifying cell health and disease progression in engineered systems. Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112031