Effects of substrate stiffness on changes in cell morphology and MMP-1 gene expression in isolated tenocytes responding to inflammatory cytokine

2019 ◽  
Vol 2019.31 (0) ◽  
pp. 2F21
Author(s):  
Eijiro MAEDA ◽  
Yoriko ANDO ◽  
Takeo MATSUMOTO
Keyword(s):  
Gene Expression ◽  
Cell Morphology ◽  
Inflammatory Cytokine ◽  
Substrate Stiffness

scholarly journals Modulation of Human Mesenchymal Stem Cells by Electrical Stimulation Using an Enzymatic Biofuel Cell

Catalysts ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 62
Author(s):  
Won-Yong Jeon ◽  
Seyoung Mun ◽  
Wei Beng Ng ◽  
Keunsoo Kang ◽  
Kyudong Han ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Electrical Stimulation ◽  
Regenerative Medicine ◽  
Cell Morphology ◽  
Electrical Current ◽  
Specific Gene ◽  
Next Generation ◽  
The Impact

Enzymatic biofuel cells (EBFCs) have excellent potential as components in bioelectronic devices, especially as active biointerfaces to regulate stem cell behavior for regenerative medicine applications. However, it remains unclear to what extent EBFC-generated electrical stimulation can regulate the functional behavior of human adipose-derived mesenchymal stem cells (hAD-MSCs) at the morphological and gene expression levels. Herein, we investigated the effect of EBFC-generated electrical stimulation on hAD-MSC cell morphology and gene expression using next-generation RNA sequencing. We tested three different electrical currents, 127 ± 9, 248 ± 15, and 598 ± 75 nA/cm2, in mesenchymal stem cells. We performed transcriptome profiling to analyze the impact of EBFC-derived electrical current on gene expression using next generation sequencing (NGS). We also observed changes in cytoskeleton arrangement and analyzed gene expression that depends on the electrical stimulation. The electrical stimulation of EBFC changes cell morphology through cytoskeleton re-arrangement. In particular, the results of whole transcriptome NGS showed that specific gene clusters were up- or down-regulated depending on the magnitude of applied electrical current of EBFC. In conclusion, this study demonstrates that EBFC-generated electrical stimulation can influence the morphological and gene expression properties of stem cells; such capabilities can be useful for regenerative medicine applications such as bioelectronic devices.

Endotoxin recognition in fish results in inflammatory cytokine secretion not gene expression

2010 ◽  
Vol 17 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Nerea Roher ◽  
Agnes Callol ◽  
Josep V. Planas ◽  
Frederick W. Goetz ◽  
Simon A. MacKenzie
Keyword(s):  
Gene Expression ◽  
Inflammatory Cytokine ◽  
Cytokine Secretion

scholarly journals Rice Bran Protein Hydrolysates Improve Insulin Resistance and Decrease Pro-inflammatory Cytokine Gene Expression in Rats Fed a High Carbohydrate-High Fat Diet

Nutrients ◽  
2015 ◽  
Vol 7 (8) ◽  
pp. 6313-6329 ◽  
Author(s):  
Kampeebhorn Boonloh ◽  
Veerapol Kukongviriyapan ◽  
Bunkerd Kongyingyoes ◽  
Upa Kukongviriyapan ◽  
Supawan Thawornchinsombut ◽  
...  
Keyword(s):  
Gene Expression ◽  
Insulin Resistance ◽  
Rice Bran ◽  
High Fat Diet ◽  
Inflammatory Cytokine ◽  
Cytokine Gene Expression ◽  
Cytokine Gene ◽  
High Fat ◽  
High Carbohydrate ◽  
Improve Insulin Resistance

scholarly journals Moderate and intensive mechanical loading differentially modulate the phenotype of tendon stem/progenitor cells in vivo

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242640
Author(s):  
Jianying Zhang ◽  
Daibang Nie ◽  
Kelly Williamson ◽  
Arthur McDowell ◽  
MaCalus V. Hogan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Progenitor Cells ◽  
Cell Morphology ◽  
Fluorescent Protein ◽  
Treadmill Running ◽  
Whole Body ◽  
Tendon Cells ◽  
Elevated Expression ◽  
Green Fluorescent

To examine the differential mechanobiological responses of specific resident tendon cells, we developed an in vivo model of whole-body irradiation followed by injection of either tendon stem/progenitor cells (TSCs) expressing green fluorescent protein (GFP-TSCs) or mature tenocytes expressing GFP (GFP-TNCs) into the patellar tendons of wild type C57 mice. Injected mice were subjected to short term (3 weeks) treadmill running, specifically moderate treadmill running (MTR) and intensive treadmill running (ITR). In MTR mice, both GFP-TSC and GFP-TNC injected tendons maintained normal cell morphology with elevated expression of tendon related markers collagen I and tenomodulin. In ITR mice injected with GFP-TNCs, cells also maintained an elongated shape similar to the shape found in normal/untreated control mice, as well as elevated expression of tendon related markers. However, ITR mice injected with GFP-TSCs showed abnormal changes, such as cell morphology transitioning to a round shape, elevated chondrogenic differentiation, and increased gene expression of non-tenocyte related genes LPL, Runx-2, and SOX-9. Increased gene expression data was supported by immunostaining showing elevated expression of SOX-9, Runx-2, and PPARγ. This study provides evidence that while MTR maintains tendon homeostasis by promoting the differentiation of TSCs into TNCs, ITR causes the onset of tendinopathy development by inducing non-tenocyte differentiation of TSCs, which may eventually lead to the formation of non-tendinous tissues in tendon tissue after long term mechanical overloading conditions on the tendon.

scholarly journals Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic

2021 ◽  
Author(s):  
Yuen Ler Chow ◽  
Shantanu Singh ◽  
Anne E Carpenter ◽  
Gregory P. Way
Keyword(s):  
Gene Expression ◽  
Cell Morphology ◽  
Learning Algorithm ◽  
Simulated Data ◽  
Biomedical Data ◽  
Data Types ◽  
Generative Capacity ◽  
Latent Space ◽  
Variational Autoencoder ◽  
Target Effects

A variational autoencoder (VAE) is a machine learning algorithm, useful for generating a compressed and interpretable latent space. These representations have been generated from various biomedical data types and can be used to produce realistic-looking simulated data. However, standard vanilla VAEs suffer from entangled and uninformative latent spaces, which can be mitigated using other types of VAEs such as β-VAE and MMD-VAE. In this project, we evaluated the ability of VAEs to learn cell morphology characteristics derived from cell images. We trained and evaluated these three VAE variants-Vanilla VAE, β-VAE, and MMD-VAE-on cell morphology readouts and explored the generative capacity of each model to predict compound polypharmacology (the interactions of a drug with more than one target) using an approach called latent space arithmetic (LSA). To test the generalizability of the strategy, we also trained these VAEs using gene expression data of the same compound perturbations and found that gene expression provides complementary information. We found that the β-VAE and MMD-VAE disentangle morphology signals and reveal a more interpretable latent space. We reliably simulated morphology and gene expression readouts from certain compounds thereby predicting cell states perturbed with compounds of known polypharmacology. Inferring cell state for specific drug mechanisms could aid researchers in developing and identifying targeted therapeutics and categorizing off-target effects in the future.

scholarly journals Substrate stiffness modulates integrin α5 expression and ECM-associated gene expression in fibroblasts

2021 ◽  
Author(s):  
Brijesh Kumar Verma ◽  
Aritra Chatterjee ◽  
Paturu Kondaiah ◽  
Namrata Gundiah
Keyword(s):  
Gene Expression ◽  
Gelatin Zymography ◽  
Confocal Imaging ◽  
Substrate Stiffness ◽  
Specific Substrate ◽  
Tgf Beta ◽  
Cell Nuclei ◽  
Compliant Substrates ◽  
Collagen Iii ◽  
Activated State

Biomaterials, like polydimethylsiloxane (PDMS), are soft, biocompatible, and tuneable, which makes them useful to delineate specific substrate factors that regulate the complex landscape of cell-substrate interactions. We used a commercial formulation of PDMS to fabricate substrates with moduli 40 kPa, 300 kPa, and 1.5 MPa, and cultured HMF3S fibroblasts on them. Gene expression analysis was performed by RT-PCR and Western blotting. Cellular and nuclear morphologies were analyzed using confocal imaging, and MMP-2 and MMP-9 activities were determined with gelatin zymography. Results, comparing mechanotransduction on PDMS substrates with control petridishes, show that substrate stiffness modulates cell morphologies and proliferations. Cell nuclei were rounded on compliant substrates and correlated with increased tubulin expression. Proliferations were higher on stiffer substrates with cell cycle arrest on softer substrates. Integrin alpha5 expression decreased on lower stiffness substrates, and correlated with inefficient TGF-beta; activation. Changes to the activated state of the fibroblast on higher stiffness substrates were linked to altered TGF-beta; secretion. Collagen I, collagen III, and MMP-2 expression levels were lower on compliant PDMS substrates as compared to stiffer ones; there was little MMP-9 activity on substrates. These results demonstrate critical feedback mechanisms between substrate stiffness and ECM regulation by fibroblasts which is highly relevant in diseases like tissue fibrosis.

scholarly journals Gene Expression Profiling of Human Hepatocytes Grown on Differing Substrate Stiffness

2019 ◽  
Vol 16 (S2) ◽  
pp. 131-131
Author(s):  
Fan Feng ◽  
Tingting Xia ◽  
Runze Zhao ◽  
Mengyue Wang ◽  
Li Yang
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Human Hepatocytes ◽  
Substrate Stiffness
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