De novo identification of universal cell mechanics regulators

Mechanical proprieties determine many cellular functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors governing cell mechanical phenotype is therefore a subject of great interest. Here we present a mechanomics approach for establishing links between mechanical phenotype changes and the genes involved in driving them. We employ a machine learning-based discriminative network analysis method termed PC-corr to associate cell mechanical states, measured by real-time deformability cytometry (RT-DC), with large-scale transcriptome datasets ranging from stem cell development to cancer progression, and originating from different murine and human tissues. By intersecting the discriminative networks inferred from two selected datasets, we identify a conserved module of five genes with putative roles in the regulation of cell mechanics. We validate the power of the individual genes to discriminate between soft and stiff cell states in silico, and demonstrate experimentally that the top scoring gene, CAV1, changes the mechanical phenotype of cells when silenced or overexpressed. The data-driven approach presented here has the power of de novo identification of genes involved in cell mechanics regulation and paves the way towards engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions

Another Brick in the Wall: RNAi Screens Identify New Barriers in iPSC Reprogramming.

Somatic cells can be reprogrammed to induced pluripotent stem cells via exogenous expression of a small set of transcription factors, but the regulatory mechanisms controlling this cell transition are poorly understood. Two recent reports demonstrate the value of RNAi screens as a tool to uncover roadblocks in this inefficient process

Another Brick in the Wall: RNAi Screens Identify New Barriers in iPSC Reprogramming.

Somatic cells can be reprogrammed to induced pluripotent stem cells via exogenous expression of a small set of transcription factors, but the regulatory mechanisms controlling this cell transition are poorly understood. Two recent reports demonstrate the value of RNAi screens as a tool to uncover roadblocks in this inefficient process

Single-cell mechanical phenotype is an intrinsic marker of reprogramming and differentiation along the mouse neural lineage

Cellular reprogramming is a dedifferentiation process during which cells continuously undergo phenotypical remodeling. Although the genetic and biochemical details of this remodeling are fairly well understood, little is known about the change in cell mechanical properties during the process. In this study, we investigated changes in the mechanical phenotype of murine fetal neural progenitor cells (fNPCs) during reprogramming to induced pluripotent stem cells (iPSCs). We find that fNPCs become progressively stiffer en route to pluripotency, and that this stiffening is mirrored by iPSCs becoming more compliant during differentiation towards the neural lineage. Furthermore, we show that the mechanical phenotype of iPSCs is comparable with that of embryonic stem cells. These results suggest that mechanical properties of cells are inherent to their developmental stage. They also reveal that pluripotent cells can differentiate towards a more compliant phenotype, which challenges the view that pluripotent stem cells are less stiff than any cells more advanced developmentally. Finally, our study indicates that the cell mechanical phenotype might be utilized as an inherent biophysical marker of pluripotent stem cells

V-ATPase inhibition increases cancer cell stiffness and blocks membrane related Ras signaling - a new option for HCC therapy.

Hepatocellular carcinoma (HCC) is the fifth most frequent cancer worldwide and the third leading cause of cancer-related death. However, therapy options are limited leaving an urgent need to develop new strategies. Currently, targeting cancer cell lipid and cholesterol metabolism is gaining interest especially regarding HCC. High cholesterol levels support proliferation, membrane-related mitogenic signaling and increase cell softness, leading to tumor progression, malignancy and invasive potential. However, effective ways to target cholesterol metabolism for cancer therapy are still missing. The V-ATPase inhibitor archazolid was recently shown to interfere with cholesterol metabolism. In our study, we report a novel therapeutic potential of V-ATPase inhibition in HCC by altering the mechanical phenotype of cancer cells leading to reduced proliferative signaling. Archazolid causes cellular depletion of free cholesterol leading to an increase in cell stiffness and membrane polarity of cancer cells, while hepatocytes remain unaffected. The altered membrane composition decreases membrane fluidity and leads to an inhibition of membrane-related Ras signaling resulting decreased proliferation in vitro and in vivo. V-ATPase inhibition represents a novel link between cell biophysical properties and proliferative signaling selectively in malignant HCC cells, providing the basis for an attractive and innovative strategy against HCC

Microarray and real time PCR analysis of fruit transcriptome in strawberry elite genotypes and correlation with PTR-MS spectra of volatile compounds

The throughput of cell mechanical characterization has recently approached that of conventional flow cytometers. However, this very sensitive, label-free approach still lacks the specificity of molecular markers. Here we developed an approach that combines real-time 1D-imaging fluorescence and deformability cytometry in one instrument (RT-FDC), thus opening many new research avenues. We demonstrated its utility by using subcellular fluorescence localization to identify mitotic cells and test for mechanical changes in those cells in an RNA interference screen

Systems Analyses Reveal Shared and Diverse Attributes of Oct4 Regulation in Pluripotent Cells.

SummaryWe combine a genome-scale RNAi screen in mouse epiblast stem cells (EpiSCs) with genetic interaction, protein localization, and “protein-level dependency” studies—a systematic technique that uncovers post-transcriptional regulation—to delineate the network of factors that control the expression of Oct4, a key regulator of pluripotency. Our data signify that there are similarities, but also fundamental differences in Oct4 regulation in EpiSCs versus embryonic stem cells (ESCs). Through multiparametric data analyses, we predict that Tox4 is associating with the Paf1C complex, which maintains cell identity in both cell types, and validate that this protein-protein interaction exists in ESCs and EpiSCs. We also identify numerous knockdowns that increase Oct4 expression in EpiSCs, indicating that, in stark contrast to ESCs, Oct4 is under active repressive control in EpiSCs. These studies provide a framework for better understanding pluripotency and for dissecting the molecular events that govern the transition from the pre-implantation to the post-implantation state