Biology subjects

Amos, S. E.

Publications and source records attributed to Amos, S. E..

3 recordsLinked to original sources

bioRxiv2024

Tumor spheroid elasticity estimation using mechano-microscopy combined with a conditional generative adversarial network

Techniques for imaging the mechanical properties of cells are needed to study how cell mechanics influence cell function and disease progression. Mechano-microscopy (a high-resolution variant of compression optical coherence elastography) generates elasticity images of a sample undergoing compression from the phase difference between optical coherence microscopy (OCM) B-scans. However, the existing mechano-microscopy signal processing chain (referred to as the algebraic method) assumes the sample stress is uniaxial and axially uniform, such that violation of these assumptions reduces the accuracy and precision of elasticity images. Furthermore, it does not account for prior information regarding the sample geometry or mechanical property distribution. In this study, we investigate the feasibility of training a conditional generative adversarial network (cGAN) to generate elasticity images from phase difference images of samples containing a cell spheroid embedded in a hydrogel. To train and test the cGAN, we constructed 30,000 elasticity and phase difference image pairs, where elasticity images were generated using a parametric model to simulate artificial samples, and phase difference images were computed using finite element analysis to simulate compression applied to the artificial samples. By applying both the cGAN and algebraic methods to simulated phase difference images, our results indicate the cGAN elasticity images exhibit better spatial resolution and sensitivity. We also evaluated the cGAN on experimental phase difference images of real spheroids embedded in hydrogels and compared the cGAN elasticity with the algebraic elasticity, OCM, and confocal fluorescence microscopy, and found the cGAN elasticity is often more robust to noise, especially within stiff nuclei.

bioengineering↗

bioRxiv2024

Multimodal mechano-microscopy reveals mechanical phenotypes of breast cancer spheroids in three dimensions

Cancer cell invasion relies on an equilibrium between cell deformability and the biophysical constraints imposed by the extracellular matrix (ECM). However, there is little consensus on the nature of the local biomechanical alterations in cancer cell dissemination in the context of three-dimensional (3D) tumor microenvironments (TME). While the shortcomings of two-dimensional (2D) models in replicating in situ cell behavior are well known, 3D TME models remain underutilized because contemporary mechanical quantification tools are limited to surface measurements. Here, we overcome this major challenge by quantifying local mechanics of cancer cell spheroids in 3D TMEs. We achieve this using multimodal mechano-microscopy, integrating optical coherence microscopy-based elasticity imaging with confocal fluorescence microscopy. We observe that non-metastatic cancer spheroids show no invasion while showing increased peripheral cell elasticity in both stiff and soft environments. Metastatic cancer spheroids, however, show ECM-mediated softening in a stiff microenvironment and, in a soft environment, initiate cell invasion with peripheral softening associated with early metastatic dissemination. This exemplar of live-cell 3D mechanotyping supports that invasion increases cell deformability in a 3D context, illustrating the power of multimodal mechano-microscopy for quantitative mechanobiology in situ.

bioengineering↗

bioRxiv2023

Polymer-mediated oligonucleotide delivery enables construction of barcoded 3D cultures for spatial single-cell analysis

Spatial transcriptomics has been widely used to capture gene expression profiles, realised as a two-dimensional (2D) projection of RNA captured from tissue sections. Wree-dimensional (3D) cultures such as spheroids and organoids are highly promising alternatives to oversimplified and homogeneous 2D cell culture models, but existing spatial transcriptomic platforms do not currently have sufficient resolution for robust analysis of 3D cultures. We present a transfection-based method for fluorescent DNA barcoding of cell populations, and the subsequent construction of spheroidal cellular architectures using barcoded cells in a layer-by-layer approach. For the first time, changes in gene expression throughout this 3D culture architecture are interrogated using multiplex single-cell RNA sequencing in which DNA barcodes are used to encode the spatial positioning of cells. We show that transfection with fluorophore-conjugated barcode oligonucleotides enables both imaging and sequencing at single-cell resolution, providing spatial maps of gene expression and drug response. Additionally, we show that fluorophore-conjugated DNA barcodes support correlative imaging studies such as mechano-microscopy to capture information about spatially-varying mechanical heterogeneity in 3D cultures. We ability to create customised, encoded cellular assemblies is a general approach that can resolve spatial differences in gene expression in 3D cell culture models.

bioengineering↗