Research Article: An automated quantitative analysis of cell, nucleus and focal adhesion morphology

Date Published: March 30, 2018

Publisher: Public Library of Science

Author(s): Antonetta B. C. Buskermolen, Nicholas A. Kurniawan, Carlijn V. C. Bouten, Thomas Abraham.

http://doi.org/10.1371/journal.pone.0195201

Abstract

Adherent cells sense the physical properties of their environment via focal adhesions. Improved understanding of how cells sense and response to their physical surroundings is aided by quantitative evaluation of focal adhesion size, number, orientation, and distribution in conjunction with the morphology of single cells and the corresponding nuclei. We developed a fast, user-friendly and automated image analysis algorithm capable of capturing and characterizing these individual components with a high level of accuracy. We demonstrate the robustness and applicability of the algorithm by quantifying morphological changes in response to a variety of environmental changes as well as manipulations of cellular components of mechanotransductions. Finally, as a proof-of-concept we use our algorithm to quantify the effect of Rho-associated kinase inhibitor Y-27632 on focal adhesion maturation. We show that a decrease in cell contractility leads to a decrease in focal adhesion size and aspect ratio.

Partial Text

In the last decades studies have shown the essential role of cell adhesion in processes like cell migration [1], survival, proliferation, and differentiation [2], as well as tissue morphogenesis [3]. These types of cell behavior are affected by the physical properties from the cell micro-environment as adherent cells have the ability to sense and respond to these properties by adapting their shape and orientation. More specifically, signals from the micro-environment are transmitted to the interior of the cell through a structural pathway, i.e. focal adhesions (FAs) physically linking the environment via the actin cytoskeleton to the nucleus. Although intense efforts have been devoted to understand how cells sense and respond to the properties of the micro-environment via FAs, the functional underlying mechanisms are not yet fully understood [4].

Algorithms to quantify cellular, nuclear and focal adhesion morphology were developed and optimized using a primary cell source, Human Vena Saphena Cells (HVSCs). To test the robustness and applicability of the method, the algorithms were subsequently applied and evaluated using a second cell type, under pharmacological manipulation, and substrate manipulation. All cell culture and manipulations were performed at 37°C in 5% CO2.

To demonstrate that the algorithm could automatically and accurately detect morphological changes in cells, nuclei and focal adhesions (FAs) rapidly, we first cultured Human Vena Saphena Cells (HVSCs) on homogeneously coated substrates with fibronectin and determined the morphological features of the cell, nucleus and focal adhesions (FAs). Accordingly, the robustness and applicability of the algorithm was tested by comparing three well-known factors affecting cellular, nuclear, and focal adhesion morphology to see whether the algorithm was able to detect changes in morphological features. Then as a proof-of-concept, the new algorithm was applied to quantify the morphological features of the FAs in response to a pharmacological drug which is known to inhibit a modulator of contractility.

Our work presents a straightforward segmentation strategy to automatically and accurately process raw images of the actin cytoskeleton, nucleus, and focal adhesions to detect individual (sub)cellular components. The automated algorithm is particularly useful for obtaining high-throughput quantitative (sub)cellular data relevant to identify important morphological changes between different cell types and in response to different environmental or pharmacological manipulations. A full, open-source software implementation of this pipeline is provided to contribute to further research on the mechanisms of how cells sense and respond to different environmental properties.

 

Source:

http://doi.org/10.1371/journal.pone.0195201