Single-Cell Heterogeneity Unveiled: Noise-Induced Volumetric Compression

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Summary

Diverse biological system heterogeneities stem from mechanisms as varied as intracellular chromosomal divisions to nuanced biochemical cues in time and space. Notwithstanding, scant attention has been accorded to how physical microclimates foster singular cell heterogeneity. This discourse illuminates that when subjected to uniform physical pressure, a consistent populace of non–small-cell lung carcinoma bifurcates into varied subsets, corroborated through meticulous cellular transcriptomic analyses. Such partitions sporadically accrue characteristic genes emblematic of epithelial–mesenchymal transition and oncogenic stem cells. The trajectory examination delineates dual divergent evolutionary cellular courses under said pressure, intensifying specific genetic markers sequentially. The compression-induced gene expression oscillations, congruous with regulatory schema, eventuate in contrasting cellular destinies. This nexus between mechanical perturbations and cell-fate elucidation, harmonized with empirical and computational data, underscores the nuanced interrelation of cancer's evolution and its physio-ecological milieu, enriching our understanding of singular cell variability.

Research Criteria

The study explores how mechanical factors, such as compression typically arising from tumor progression, can impact gene-expression noise and subsequently lead to varied cell-fate transitions. The researchers aim to understand the mechanoregulation of tumor heterogeneity and propose that the mechanical microenvironment, as sensed by the cell's cytoplasmic volume, might be a significant contributor to tumor heterogeneity. This is in contrast to the traditional understanding that attributes tumor heterogeneity mainly to genetic factors. The article emphasizes the interplay between mechanical stimulations and cell-fate determination, shedding light on the origin of single-cell heterogeneity.

Sample Type

H1975 cells

Result - In a Homogeneous Cell Population, Physical Compression Causes Single-Cell Heterogeneity

In an intricate exploration of the effects of physical compression on cellular heterogeneity, researchers utilized advanced single-cell sequencing technology to monitor transcriptomic evolution within a uniform population of non–small-cell lung carcinoma. This carcinoma, a malignant lung tumor, has its growth dynamics intricately tied to dysregulated osmotic pressures, which are implicated in various lung diseases. By subjecting these cells to a hypertonic medium enriched with PEG 300, a neutral polymer, and subsequently analyzing them at distinct intervals, the study discerned the emergence of diverse cell subpopulations post osmotic compression. Notably, these subpopulations bore signature genes linked to both the epithelial-mesenchymal transition (EMT) and cancer stem cells. Correlation analyses further underscored the pronounced gene expression shifts post-compression. Complementing these findings, fluorescent immunostaining assays revealed that, upon osmotic stress, cells predominantly expressed either the epithelial marker E-cadherin or the mesenchymal marker Vimentin, aligning with the single-cell transcriptomic data and suggesting enduring phenotypic alterations at the protein expression level.

Fig. 1 Mechanical compression induces the emergence of distinct subgroups within an initially uniform non-small-cell lung carcinoma population, displaying characteristics akin to both epithelial and mesenchymal gene expressions¹.

Result - Hierarchy of Compression-Induced Heterogeneity Reconstruction

In an intricate exploration of cellular heterogeneity induced by compression, researchers employed trajectory analysis, particularly the PAGA algorithm, to computationally reconstruct transitions between cell subpopulations post-osmotic compression. This methodological approach yielded an abstracted graph, confidently illustrating branching events that culminate in a singular differentiation tree. This tree, rooted in the cluster of uncompressed cells, bifurcates into distinct mesenchymal and epithelial paths. As time progresses, cells exhibit a spatial divergence based on compression duration, aligning with gene-expression continuity along these paths. Notably, mesenchymal genes incrementally rise in the mesenchymal trajectory, while inversely behaving in the epithelial trajectory. Complementary algorithms, such as UMAP and t-SNE, corroborate the conclusions drawn from PAGA. Furthermore, the study identifies a minimal gene set - VIM, CDH1, and CLDN7 - capable of distinguishing EMT subgroups, resonating with prior EMT scoring methodologies.

Fig. 2 The hierarchy of compression-induced heterogeneity is reconstructed using trajectory analysis¹.

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Reference

1. Zhao, Xing, et al. "Volumetric compression develops noise-driven single-cell heterogeneity." Proceedings of the National Academy of Sciences 118.51 (2021): e2110550118.