TY - JOUR
T1 - Dynamic Signatures of Lipid Droplets as New Markers to Quantify Cellular Metabolic Changes
AU - Zhang, Chi
AU - Boppart, Stephen A.
N1 - Funding Information:
The authors thank Aneesh Alex, Jang Hyuk Lee, and Jose Rico-Jimenez from the Center for Optical Molecular Imaging for the initial installation of the laser and data acquisition/PC systems and thank GlaxoSmithKline for the sponsored research support of the Center. This research was financially supported in part by grants from the NIH (R01CA241618, R01EB023232) and the NSF (CBET 18-41539).
Publisher Copyright:
©
PY - 2020/12/15
Y1 - 2020/12/15
N2 - The metabolic properties of live cells are very susceptible to intra- or extracellular perturbations, making their measurements challenging tasks. We show that the dynamics of lipid droplets (LDs) carry information to measure the lipid metabolism of live cells. Coherent anti-Stokes Raman scattering microscopy was used to statistically quantify LD dynamics in living cells in a label-free manner. We introduce dynamic signatures of cells derived from the LD displacement, speed, travel length, and directionality, which allows for the detection of cellular changes induced by stimuli such as fluorescent labeling, temperature change, starvation, and chemical treatment. Histogram fittings of the dynamic signatures using log-normal distribution functions provide quantification of changes in cellular metabolic states. The LD dynamics also enable separation of subpopulations of LDs correlated with different functions. We demonstrate that LD dynamics measured by chemical imaging are new markers to quantify the metabolic changes in live cells.
AB - The metabolic properties of live cells are very susceptible to intra- or extracellular perturbations, making their measurements challenging tasks. We show that the dynamics of lipid droplets (LDs) carry information to measure the lipid metabolism of live cells. Coherent anti-Stokes Raman scattering microscopy was used to statistically quantify LD dynamics in living cells in a label-free manner. We introduce dynamic signatures of cells derived from the LD displacement, speed, travel length, and directionality, which allows for the detection of cellular changes induced by stimuli such as fluorescent labeling, temperature change, starvation, and chemical treatment. Histogram fittings of the dynamic signatures using log-normal distribution functions provide quantification of changes in cellular metabolic states. The LD dynamics also enable separation of subpopulations of LDs correlated with different functions. We demonstrate that LD dynamics measured by chemical imaging are new markers to quantify the metabolic changes in live cells.
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U2 - 10.1021/acs.analchem.0c03366
DO - 10.1021/acs.analchem.0c03366
M3 - Article
C2 - 33232121
AN - SCOPUS:85097828678
VL - 92
SP - 15943
EP - 15952
JO - Analytical Chemistry
JF - Analytical Chemistry
SN - 0003-2700
IS - 24
ER -