Predicting gene expression using morphological cell responses to nanotopography

Cutiongco, M. F.A. , Jensen, B. S. , Reynolds, P. M. and Gadegaard, N. (2020) Predicting gene expression using morphological cell responses to nanotopography. Nature Communications, 11, 1384. (doi: 10.1038/s41467-020-15114-1) (PMID:32170111) (PMCID:PMC7070086)

207386.pdf - Published Version
Available under License Creative Commons Attribution.



Cells respond in complex ways to their environment, making it challenging to predict a direct relationship between the two. A key problem is the lack of informative representations of parameters that translate directly into biological function. Here we present a platform to relate the effects of cell morphology to gene expression induced by nanotopography. This platform utilizes the ‘morphome’, a multivariate dataset of cell morphology parameters. We create a Bayesian linear regression model that uses the morphome to robustly predict changes in bone, cartilage, muscle and fibrous gene expression induced by nanotopography. Furthermore, through this model we effectively predict nanotopography-induced gene expression from a complex co-culture microenvironment. The information from the morphome uncovers previously unknown effects of nanotopography on altering cell–cell interaction and osteogenic gene expression at the single cell level. The predictive relationship between morphology and gene expression arising from cell-material interaction shows promise for exploration of new topographies.

Item Type:Articles
Additional Information:We acknowledge ERC funding through FAKIR 648892 Consolidator Award. MFAC is financially supported by the University of Glasgow MG Dunlop Bequest, College of Science and Engineering Scholarship, and FAKIR consolidator award. NG acknowledges support by the Research Council of Norway through its Centres of Excellence funding scheme, project number 262613.
Glasgow Author(s) Enlighten ID:Cutiongco, Ms Marie and Gadegaard, Professor Nikolaj and Jensen, Dr Bjorn and Reynolds, Dr Paul
Authors: Cutiongco, M. F.A., Jensen, B. S., Reynolds, P. M., and Gadegaard, N.
College/School:College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Engineering > Biomedical Engineering
College of Science and Engineering > School of Engineering > James Watt Nanofabrication Centre
Journal Name:Nature Communications
Publisher:Nature Research
ISSN (Online):2041-1723
Copyright Holders:Copyright © The Author(s) 2020
First Published:First published in Nature Communications 11:1384
Publisher Policy:Reproduced under a Creative Commons license
Related URLs:
Data DOI:10.5281/zenodo.3608197

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172025FAKIR: Focal Adhesion Kinetics In nanosurface RecognitionNikolaj GadegaardEuropean Research Council (ERC)648892ENG - Biomedical Engineering