Large-scale image-based morphological profiling : from instrumentation to high-dimensional single-cell analysis

Abstract

The overarching challenge in biology today is how to dissect the cellular heterogeneity within and between cell types at single-cell level. To study cell-to-cell variations, the current gold-standard technology is single-cell RNA sequencing. It enables in-depth characterization of single cells by providing measurements of gene expression profiles of thousands of genes, but its applicability to studies of large cell populations (on the order of 106 cells) remains limited because of its prohibitively high cost per sample.

On the other hand, morphological profiling, which is a novel technique to characterize single cells by deriving a large set of morphological features from the microscopy images of cells, is more feasible for large-scale analysis in terms of cost and complexity. Notably, morphological profiling by using cell-painting assay has been successfully applied in various biological applications, such as screening for drug candidates and studying genetic perturbations. However, as a set of fluorescent dyes which are generally not live-cell-compatible are required to stain a variety of organelles in cell-painting assay, it is challenging to extend the assay for live-cell analysis.

To this end, there is a pressing need for a transformative technology that could offer not only large-scale, but also live-cell-compatible analysis of single cells in a cost-effective way. Here, an imaging flow cytometry (IFC) system which combines free-space angular-chirp-enhanced delay (FACED) and quantitative phase imaging (QPI) was developed to accomplish this goal – ultimately provide a routine solution for large-scale single-cell morphological profiling in a non-invasive manner. FACED was incorporated into the system to offer ultrafast line-scan rate (beyond 10’s MHz), so that high-throughput single-cell imaging could be achieved, while QPI allows quantification of a series of biophysical phenotypes (e.g., cell size and mass density) based on the cell images, so that individual cells could be profiled in a label-free manner.

Recently, there has been a growing number of studies showing that the biophysical phenotypes of cells are as effective as conventional molecular markers in revealing cellular heterogeneity with single-cell precision. However, biophysical phenotyping has not yet become a widely used technique in single-cell analysis because of the lack of molecular interpretability. To understand how the biophysical phenotypes derived from the label-free images could be linked to the biomolecular information of cells, fluorescence imaging was incorporated into the IFC system to provide the foundation knowledge. As a result, the multimodal FACED IFC system allows simultaneous capture of quantitative phase and fluorescence images of single cells at high throughput. Based on the dual-contrast images that are co-registered to the same cells, the correlation between biophysical and biomolecular information of cells could be systematically investigated at single-cell level. Correlative, compartment-specific analysis of the spatially resolved biophysical profiles during cell cycle progression has been demonstrated.

In the future, the FACED IFC system could be further advanced in imaging techniques and deep learning. Moreover, by integrating the system with microfluidic cell sorter to enable downstream analysis of gene expression profiling, the biophysical phenotypes could potentially be linked to the transcriptomic profiles of cells and thus equipped with genetic interpretability.