Predicting phenotype using morphological cell responses to nanotopography

Abstract

<jats:title>Abstract</jats:title><jats:p>Cells respond in complex ways to topographies, making it challenging to identify a direct relationship between surface topography and cell response. A key problem is the lack of informative representations of topographical parameters that translate directly into biological properties. Here, we present a platform to relate the effects of nanotopography on morphology to function. This platform utilizes the ‘morphome’, a multivariate dataset containing single cell measures of focal adhesions, the cytoskeleton, and chromatin. We demonstrate that nanotopography-induced changes in cell phenotype are uniquely encoded by the morphome. The morphome was used to create a Bayesian linear regression model that robustly predicted changes in bone, cartilage, muscle and fibrous tissue gene expression induced by nanotopography. Furthermore, the morphome effectively predicted nanotopography-induced phenotype within a complex co-culture microenvironment. Thus, the morphome enables the cell function-oriented exploration of new topographies, with potential applications in the development of novel surface-patterned biomaterials for tissue implants.</jats:p>

High‐Aspect‐Ratio Nanostructured Surfaces as Biological Metamaterials

“…Incorporating a range of parameters, e.g., systematically changing geometry or testing multiple cell lines, into the experimental design can help. Approaches such as image‐based cell profiling can help to quantitatively analyze large numbers of cells, adding statistical weight to conclusions, as well as in identifying subpopulations and other effects driven by cell heterogeneity . For example, Reynolds et al illustrated the potential of these approaches for exploring the impact of topography in endothelial/fibroblast cell cocultures, in this case with low aspect ratio nanodot arrays ( Figure ) .…”

“…Approaches such as image-based cell profiling can help to quantitatively analyze large numbers of cells, adding statistical weight to conclusions, as well as in identifying subpopulations and other effects driven by cell heterogeneity. [137,173,263,459,460] For example, Reynolds et al illustrated the potential of these approaches for exploring the impact of topography in endothelial/fibroblast cell cocultures, in this case with low aspect ratio nanodot arrays (Figure 29). [263] Likewise, super-resolution microscopy techniques are likely to continue to offer better visualization of transmembrane proteins and interaction sites.…”

Free-energy-based framework for early forecasting of stem cell differentiation

“…While it is well-established that changes to gene expressions over a period of about 1-2 weeks dictate the lineage commitment and differentiation fate of hMSCs, more recent studies have indicated that a combination of a large number of cell, nuclear and cytoskeletal morphometrics also provides excellent forecasting of the lineage of hMSCs [22,23]. These morphometrics develop over a period of 1 to 2 days when the gene expression of cells has not been affected irreversibly by the environment.…”

“…A combination of a large number of cell, nuclear and cytoskeletal morphometrics that develop over a period of 1-2 days have been shown to forecast the lineage of hMSCs as measured via gene expressions over a period of about 1 week [22,23]. While such a morphometric analysis is undoubtedly useful it has two drawbacks: (i) it requires the measurement and analysis of a large number of morphological metrics, and (ii) it provides little insight into the physical phenomena that set the lineage of the cell.…”

“…The experimental observations can be related to the expression of transcription factors (such as CBF 1 for osteoblasts and PPAR for adipocytes) [20,21], or various measures of cell shape (such as cell area, aspect ratio, stress-fibre intensity, etc.) [22,23]. However, a frequent output from these models is a complex combination of input variables that seems to correlate strongly with cell fate, but physical significance of such measures remain poorly understood.…”