Disentangling Membrane Dynamics and Cell Migration; Differential Influences of F-actin and Cell-Matrix Adhesions

An introduction to representation learning for single-cell data analysis

Single-cell-resolved systems biology methods, including omics- and imaging-based measurement modalities, generate a wealth of high-dimensional data characterizing the heterogeneity of cell populations. Representation learning methods are routinely used to analyze these complex, high-dimensional data by projecting them into lower-dimensional embeddings. This facilitates the interpretation and interrogation of the structures, dynamics, and regulation of cell heterogeneity. Reflecting their central role in analyzing diverse single-cell data types, a myriad of representation learning methods exist, with new approaches continually emerging. Here, we contrast general features of representation learning methods spanning statistical, manifold learning, and neural network approaches. We consider key steps involved in representation learning with single-cell data, including data pre-processing, hyperparameter optimization, downstream analysis, and biological validation. Interdependencies and contingencies linking these steps are also highlighted. This overview is intended to guide researchers in the selection, application, and optimization of representation learning strategies for current and future single-cell research applications.

Morphomigrational description as a new approach connecting cell's migration with its morphology

The examination of morphology and migration of cells plays substantial role in understanding the cellular behaviour, being described by plethora of quantitative parameters and models. These descriptions, however, treat cell migration and morphology as independent properties of temporal cell state, while not taking into account their strong interdependence in adherent cells. Here we present the new and simple mathematical parameter called signed morphomigrational angle (sMM angle) that links cell geometry with translocation of cell centroid, considering them as one morphomigrational behaviour. The sMM angle combined with pre-existing quantitative parameters enabled us to build a new tool called morphomigrational description, used to assign the numerical values to several cellular behaviours. Thus, the cellular activities that until now were characterized using verbal description or by complex mathematical models, are described here by a set of numbers. Our tool can be further used in automatic analysis of cell populations as well as in studies focused on cellular response to environmental directional signals.

Multisite assessment of reproducibility in high-content cell migration imaging data

High-content image-based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high-quality open-access data sharing and meta-analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta-analysis of results from live-cell microscopy, have not been systematically investigated. Here, using high-content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta-analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image-based datasets of perturbation experiments. Thus, reproducible quantitative high-content cell image analysis of perturbation effects and meta-analysis depend on standardized procedures combined with batch correction.

Mapping Phenotypic Plasticity upon the Cancer Cell State Landscape Using Manifold Learning

ABSTRACT

Phenotypic plasticity describes the ability of cancer cells to undergo dynamic, nongenetic cell state changes that amplify cancer heterogeneity to promote metastasis and therapy evasion. Thus, cancer cells occupy a continuous spectrum of phenotypic states connected by trajectories defining dynamic transitions upon a cancer cell state landscape. With technologies proliferating to systematically record molecular mechanisms at single-cell resolution, we illuminate manifold learning techniques as emerging computational tools to effectively model cell state dynamics in a way that mimics our understanding of the cell state landscape. We anticipate that "state-gating" therapies targeting phenotypic plasticity will limit cancer heterogeneity, metastasis, and therapy resistance.

SIGNIFICANCE

Nongenetic mechanisms underlying phenotypic plasticity have emerged as significant drivers of tumor heterogeneity, metastasis, and therapy resistance. Herein, we discuss new experimental and computational techniques to define phenotypic plasticity as a scaffold to guide accelerated progress in uncovering new vulnerabilities for therapeutic exploitation.

Tracking Single Molecules in Biomembranes: Is Seeing Always Believing?

The spatial organization of molecules in cell membranes and their dynamic interactions play a central role in regulating cell functions. Single-particle tracking (SPT), a technique in which single molecules are imaged and tracked in real time, has led to breakthrough discoveries regarding these spatiotemporal complexities of cell membranes. There are, however, emerging concerns about factors that might produce misleading interpretations of SPT results. Here, we briefly review the application of SPT to understanding the nanoscale heterogeneities of plasma membranes, with a focus on the unique challenges, pitfalls, and limitations that confront the use of nanoparticles as imaging probes for tracking the dynamics of single molecules in cell membranes.

CIRP regulates BEV-induced cell migration in gliomas

Purpose

A better understanding of the underlying molecular mechanisms in treatment failure of bevacizumab (BEV) for malignant glioma would contribute to overcome therapeutic resistance.

Methods

Here, we used a quantitative proteomic method to identify molecular signatures of glioblastoma cell after BEV treatment by two-dimensional liquid chromatography-tandem mass spectrometry analysis and 6-plex iTRAQ quantification. Next, the function of cold-inducible RNA-binding protein (CIRP), one of the most significantly affected proteins by drug treatment, was evaluated in drug resistance of glioma cells by invasion assays and animal xenograft assays. Target molecules bound by CIRP were determined using RNA-binding protein immunoprecipitation and microarray analysis. Then, these mRNAs were identified by quantitative real-time PCR.

Results

Eighty-seven proteins were identified with significant fold changes. The biological functional analysis indicated that most of the proteins were involved in the process of cellular signal transduction, cell adhesion, and protein transport. The expression of CIRP greatly decreased after BEV treatment, and ectopic expression of CIRP abolished cell migration in BEV-treated glioma cells. In addition, CIRP could bind mRNA of CXCL12 and inhibit BEV-induced increase of CXCL12 in glioma cells.

Conclusion

These data suggested that CIRP may take part in BEV-induced migration of gliomas by binding of migration-relative RNAs.

Computational model of wound healing: EGF secreted by fibroblasts promotes delayed re-epithelialization of epithelial keratinocytes

It is widely agreed that keratinocyte migration plays a crucial role in wound re-epithelialization. Defects in this function contribute to wound reoccurrence causing significant clinical problems. Several in vitro studies have shown that the speed of migrating keratinocytes can be regulated by epidermal growth factor (EGF) which affects keratinocyte's integrin expression. The relationship between integrin expression (through cell-matrix adhesion) stimulated by EGF and keratinocyte migration speed is not linear since increased adhesion, due to increased integrin expression, has been experimentally shown to slow down cell migration due to the biphasic dependence of cell speed on adhesion. In our previous work we showed that keratinocytes that were co-cultured with EGF-enhanced fibroblasts formed an asymmetric migration pattern, where, the cumulative distances of keratinocytes migrating toward fibroblasts were smaller than those migrating away from fibroblasts. This asymmetric pattern is thought to be provoked by high EGF concentration secreted by fibroblasts. The EGF stimulates the expression of integrin receptors on the surface of keratinocytes migrating toward fibroblasts via paracrine signaling. In this paper, we present a computational model of keratinocyte migration that is controlled by EGF secreted by fibroblasts using the Cellular Potts Model (CPM). Our computational simulation results confirm the asymmetric pattern observed in experiments. These results provide a deeper insight into our understanding of the complexity of keratinocyte migration in the presence of growth factor gradients and may explain re-epithelialization failure in impaired wound healing.

Functional impairment triggered by altertoxin II (ATXII) in intestinal cells in vitro: cross-talk between cytotoxicity and mechanotransduction

Intestinal cells are able to continuously integrate response to multiple stimuli/stressors; these include the concomitant activation of “chemically driven” pathways, of paramount importance in the response to toxicants, as well as physical stimulation derived from motility. Altertoxin II (ATXII, 0.1, 1 and 10 µM), a mycotoxin produced by the food contaminant fungus Alternaria alternata was studied in HT-29 intestinal adenocarcinoma cells and in non-transformed intestinal epithelial cells, HCEC. One-hour incubation with ATXII was sufficient to trigger irreversible cytotoxicity in both cell types, as well as to modify cellular responses to concomitant pro-oxidant challenge (H₂O₂, 100–500 µM, DCF-DA assay) suggesting that even relatively short-time exposure of the intestinal cells could be sufficient to alter their functionality. Combination of ATXII (1 µM) with physical stimulation typical of the intestinal compartment (shear stress) revealed differential response of tumor-derived epithelial cells HT-29 in comparison to HCEC, in particular in the localization of the transcription factor Nrf2 (NF-E2-related factor 2). Moreover, ATXII reduced the migratory potential of HCEC as well as their membrane fluidity, but had no respective impact on HT-29 cells. Taken together, ATXII appeared to alter predominantly membrane functionality in HCEC thus hampering crucial functions for cellular motility/turnover, as well as barrier function of healthy intestinal cells and had very limited activity on the tumor counterparts.

Exploring the role of stromal osmoregulation in cancer and disease using executable modelling

Osmotic regulation is a vital homoeostatic process in all cells and tissues. Cells initially respond to osmotic stresses by activating transmembrane transport proteins to move osmotically active ions. Disruption of ion and water transport is frequently observed in cellular transformations such as cancer. We report that genes involved in membrane transport are significantly deregulated in many cancers, and that their expression can distinguish cancer cells from normal cells with a high degree of accuracy. We present an executable model of osmotic regulation and membrane transport in mammalian cells, providing a mechanistic explanation for phenotype change in varied disease states, and accurately predicting behaviour from single cell expression data. We also predict key proteins involved in cellular transformation, SLC4A3 (AE3), and SLC9A1 (NHE1). Furthermore, we predict and verify a synergistic drug combination in vitro, of sodium and chloride channel inhibitors, which target the osmoregulatory network to reduce cancer-associated phenotypes in fibroblasts.

Using Systems Microscopy to Understand the Emergence of Cell Migration from Cell Organization

Cell migration is a dynamic process that emerges from fine-tuned networks coordinated in three-dimensional space, spanning molecular, subcellular, and cellular scales, and over multiple temporal scales, from milliseconds to days. Understanding how cell migration arises from this complexity requires data collection and analyses that quantitatively integrate these spatial and temporal scales. To meet this need, we have combined quantitative live and fixed cell fluorescence microscopy, customized image analysis tools, multivariate statistical methods, and mathematical modeling. Collectively, this constitutes the systems microscopy strategy that we have applied to dissect how cells organize themselves to migrate. In this overview, we highlight key principles, concepts, and components of our systems microscopy methodology, and exemplify what we have learnt so far and where this approach may lead.

15-Deoxy-Δ12,14-prostaglandin J2 inhibits migration of human thyroid carcinoma cells by disrupting focal adhesion complex and adherens junction

Metastasis is frequently observed in human follicular thyroid carcinoma. The present study investigated the peroxisome proliferator-activated receptor γ agonist, 15-deoxy-Δ^12,14-prostaglandin J² (15d-PGJ₂), and its effect on the migration of CGTH W-2 human thyroid carcinoma cells. 15d-PGJ₂ decreased the survival rate of CGTH W-2 cells in a dose-dependent manner. The Transwell migration assay demonstrated that 15d-PGJ₂ reduced the migration rate of CGTH W-2 cells by 35% following treatment with 30 µM 15d-PGJ₂ compared with control cells. The cell adhesion assay indicated that, following 15d-PGJ₂ treatment for 24 h, cell adhesion decreased by 26% compared with the control group. The expression levels of focal adhesion proteins, including integrin β1, phospho-focal adhesion kinase and p-paxillin, were downregulated following treatment with 15d-PGJ₂. Immunostaining revealed that the puncta of vinculin were reduced and the actin stress fiber was disassembled following 15d-PGJ₂ treatment. By contrast, p120-catenin (p120-ctn) and β-catenin levels staining accumulated in the region of the lamellipodium following 15d-PGJ₂ treatment. Membrane fractionation revealed that p120-ctn and N-cadherin were decreased in the cell membrane, but increased in the cytoplasm of 15d-PGJ₂-treated cells. Therefore, 15d-PGJ₂ inhibited human thyroid carcinoma cell migration and this may be due to the impairment of focal adhesion complexes and the accumulation of p120-ctn in the cytoplasm in the region of the lamellipodium.

Pathway-related molecules of VEGFC/D-VEGFR3/NRP2 axis in tumor lymphangiogenesis and lymphatic metastasis

Precondition for tumor lymphatic metastasis is that tumor cells induce formation of original and newborn lymphatic vessels and invade surrounding lymphatic vessels in tumor stroma, while some pathway-related molecules play an important role in mechanisms associated with proliferation and migration of lymphatic endothelial cells (LECs) and tumor cells. In lymphangiogenesis and lymphatic metastasis, the pathway-related molecules of VEGFC/D-VEGFR3/NRP2 axis, such as Furin-like enzyme, CNTN1, Prox1, LYVE-1, Podoplanin, SOX18, SDF1 and CXCR4, are direct constitutors as a portion of VEGFC/D-VEGFR3/NRP2 axis, and their biological activities rely on this ligand-receptor system. These axis-related signal molecules could gradually produce waterfall-like cascading effects, mediate differentiation and maturation of LECs, remodel original and neonatal lymphatic vessels, as well as ultimately promote tumor cell chemotaxis, migration, invasion and metastasis to lymphoid tracts. This review summarizes the structure and function features of pathway-related molecules of VEGFC/D-VEGFR3/NRP2 axis, the expression changes of these molecules in different anatomic organs or histopathologic types or development stages of various tumors, the characteristics of transduction, implementation, integration of signal networks, the interactive effects on biological behaviors between tumor cells and lymphatic endothelial cells, and their molecular mechanisms and significances in tumor lymphangiogenesis and lymphatic metastasis.

Light-Emitting Diode Irradiation (640 nm) Regulates Keratinocyte Migration and Cytoskeletal Reorganization Via Hypoxia-Inducible Factor-1α

OBJECTIVE

The objective of this study was to determine the effect of light-emitting diode (LED) irradiation on the migration and proliferation of keratinocytes.

BACKGROUND DATA

Keratinocytes play a key role in re-epithelialization during wound healing; it is speculated that low-level LED therapy might improve keratinocyte migration and proliferation.

MATERIALS AND METHODS

Human keratinocyte cells (HKCs) were isolated from child or adult foreskins and irradiated with LED light with a wavelength of 640 nm and a dosage of 12 or 24 J/cm(2). Cell motility, migration, and proliferation were examined using live cell imaging, scratch assay, and a colorimetric cell counting assay, respectively. Hypoxia-inducible factor-1α (HIF-1α) protein levels were analyzed by using Western blotting. Filamentous actin (F-actin) was stained by phalloidin. YC-1 [3-(5-hydroxymethyl-2-furyl)-1-benzylindazole] was used as an HIF-1 inhibitor, and CoCl2 (cobalt chloride) and DMOG (dimethyloxaloyl glycine) are HIF-1α activators.

RESULTS

LED irradiation significantly promoted cell motility and migration, but did not significantly influence cell proliferation in HKCs. Furthermore, LED irradiation resulted in a reorganization of cellular F-actin and a dramatic upregulation of HIF-1α expression. Suppression of HIF-1α using the compound YC-1 prevented reorganization of the actin cytoskeleton following LED irradiation, suggesting that the effect of LED irradiation on the cytoskeleton is mediated through HIF-1α. Conversely, chemical activation of HIF-1α via DMOG or CoCl2 resulted in a reorganization of F-actin.

CONCLUSIONS

LED irradiation may increase keratinocyte migration via HIF-1α-dependent cytoskeletal reorganization.

An analysis toolbox to explore mesenchymal migration heterogeneity reveals adaptive switching between distinct modes

Mesenchymal (lamellipodial) migration is heterogeneous, although whether this reflects progressive variability or discrete, 'switchable' migration modalities, remains unclear. We present an analytical toolbox, based on quantitative single-cell imaging data, to interrogate this heterogeneity. Integrating supervised behavioral classification with multivariate analyses of cell motion, membrane dynamics, cell-matrix adhesion status and F-actin organization, this toolbox here enables the detection and characterization of two quantitatively distinct mesenchymal migration modes, termed 'Continuous' and 'Discontinuous'. Quantitative mode comparisons reveal differences in cell motion, spatiotemporal coordination of membrane protrusion/retraction, and how cells within each mode reorganize with changed cell speed. These modes thus represent distinctive migratory strategies. Additional analyses illuminate the macromolecular- and cellular-scale effects of molecular targeting (fibronectin, talin, ROCK), including 'adaptive switching' between Continuous (favored at high adhesion/full contraction) and Discontinuous (low adhesion/inhibited contraction) modes. Overall, this analytical toolbox now facilitates the exploration of both spontaneous and adaptive heterogeneity in mesenchymal migration.