A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids.

Vito Rt Zanotelli,Xiao-Kang Lun,Fanny Georgi,Natalie De Souza,Bernd Bodenmiller,Matthias Leutenegger

doi:10.15252/msb.20209798

Abstract

Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell‐intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems‐level studies of single‐cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell‐intrinsic and cell‐extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies.

Highlights

The ability of a cell to sense and adapt to its local environment depends on an intracellular signaling network that integrates paracrine, juxtacrine, nutritional, and mechanical cues to drive phenotypic decisions (Fig 1A)
We evaluated spheroids formed by four cell lines, each grown in six different growth conditions, quantified single-cell marker levels, and analyzed how cell state, local neighborhood, and global environment interact to contribute to cell-to-cell variability in marker expression
Spheroid culture coupled with multiplexed imaging enables quantification of phenotypic variability

Summary

Introduction

The ability of a cell to sense and adapt to its local environment depends on an intracellular signaling network that integrates paracrine, juxtacrine, nutritional, and mechanical cues to drive phenotypic decisions (Fig 1A). Genomic alterations that deregulate environment sensing and signaling can enable cells to grow outside their physiologically permissive tissue context, leading to diseases such as cancer. Since even strongly deregulated cells depend on and react to microenvironmental cues (Snijder & Pelkmans, 2011; Battich et al, 2015), microenvironment-induced cellular plasticity may contribute to the clinically relevant tumor cell heterogeneity observed in cancer tissues (Marusyk et al, 2012; Bodenmiller, 2016). Existing atlases of cancer tissues are based on static measurements of cellular markers that cannot reliably discriminate environment-dependent phenotypic plasticity from phenotypic variation due to genomic or lineage differences (Wagner et al, 2016; Regev et al, 2017). To quantify variability caused by the environment, it is necessary to identify comparable cells that vary phenotypically only because their environments differ

Methods

Results

Conclusion