LipiD-QuanT: a novel method to quantify lipid accumulation in live cells

Varinli, Hilal; Osmond, Megan; Molloy, Peter L.; Vallotton, Pascal

doi:10.1194/jlr.d059758

Cited by 21 publications

(17 citation statements)

References 70 publications

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“…We also quantified the lipid accumulation by creating and optimizing a CellProfiler pipeline to analyze ORO-stained fluorescence images. We analyzed both total lipid droplet area in the cultures ( Figure 5(b) ) and the area of lipid droplet clusters exceeding 10 μ m diameter limit ( Figure S1 ) to visualize the ongoing adipogenic differentiation and maturation of adipocytes which is distinguished by the increasing number of lipid droplets as well as the enlargement of the individual fat vacuoles [ 39 ]. Lipid droplet cluster areas over 10 μ m in diameter were further normalized with cell nuclei number to obtain results representative of the single-cell level ( Figure 5(b) ).…”

Section: Resultsmentioning

confidence: 99%

Focal Adhesion Kinase and ROCK Signaling Are Switch-Like Regulators of Human Adipose Stem Cell Differentiation towards Osteogenic and Adipogenic Lineages

Hyväri

Ojansivu

Juntunen

et al. 2018

Stem Cells International

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Adipose tissue is an attractive stem cell source for soft and bone tissue engineering applications and stem cell therapies. The adipose-derived stromal/stem cells (ASCs) have a multilineage differentiation capacity that is regulated through extracellular signals. The cellular events related to cell adhesion and cytoskeleton have been suggested as central regulators of differentiation fate decision. However, the detailed knowledge of these molecular mechanisms in human ASCs remains limited. This study examined the significance of focal adhesion kinase (FAK), Rho-Rho-associated protein kinase (Rho-ROCK), and their downstream target extracellular signal-regulated kinase 1/2 (ERK1/2) on hASCs differentiation towards osteoblasts and adipocytes. Analyses of osteogenic markers RUNX2A, alkaline phosphatase, and matrix mineralization revealed an essential role of active FAK, ROCK, and ERK1/2 signaling for the osteogenesis of hASCs. Inhibition of these kinases with specific small molecule inhibitors diminished osteogenesis, while inhibition of FAK and ROCK activity led to elevation of adipogenic marker genes AP2 and LEP and lipid accumulation implicating adipogenesis. This denotes to a switch-like function of FAK and ROCK signaling in the osteogenic and adipogenic fates of hASCs. On the contrary, inhibition of ERK1/2 kinase activity deceased adipogenic differentiation, indicating that activation of ERK signaling is required for both adipogenic and osteogenic potential. Our findings highlight the reciprocal role of cell adhesion mechanisms and actin dynamics in regulation of hASC lineage commitment. This study enhances the knowledge of molecular mechanisms dictating hASC differentiation and thus opens possibilities for more efficient control of hASC differentiation.

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Section: Resultsmentioning

confidence: 99%

Focal Adhesion Kinase and ROCK Signaling Are Switch-Like Regulators of Human Adipose Stem Cell Differentiation towards Osteogenic and Adipogenic Lineages

Hyväri

Ojansivu

Juntunen

et al. 2018

Stem Cells International

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“…Lipid droplet images were taken 2 days later. A total of 803 lipid droplets were used to assess lipid droplet size by the LipiD-QuanT method (19).…”

Section: Lipid-quant Analysismentioning

confidence: 99%

Melatonin reduces intramuscular fat deposition by promoting lipolysis and increasing mitochondrial function

Liu¹,

Yu²,

Wei

et al. 2019

Journal of Lipid Research

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“…101 They have therefore been applied, in a number of combinations and variations, for analysis of LD size and number distribution. 102,103 More recently, the field of computer vision has shifted focus to machine learning approaches for everything from automatic feature extraction to image classification. This has been driven in large part by the success of convolutional neural networks (CNN), and their rapid development in the past decade.…”

Section: Object Recognition Algorithmsmentioning

confidence: 99%