Lipid droplet quantification based on iterative image processing

Exner, Tarik; Beretta, Carlo A.; Gao, Qi; Afting, Cassian; Romero-Brey, Inés; Bartenschlager, Ralf; Fehring, Leonard; Poppelreuther, Margarete; Füllekrug, Joachim

doi:10.1194/jlr.d092841

Cited by 29 publications

(21 citation statements)

References 50 publications

(56 reference statements)

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“…Thus, it is interesting to explore if SG formation can indeed facilitate the PPAR response. It is not clear how PPAR target translation evades bulk translational inhibition, which results in SG formation during mTOR inhibition (Kedersha and Anderson, 2007;Takahara and Maeda, 2012;Exner et al, 2019). It is possible that a recently demonstrated model of SGs sequestering longer mRNA plays a role (Sheikh and Fornace, 1999).…”

Section: Discussionmentioning

confidence: 99%

Small Molecule Screen Reveals Joint Regulation of Stress Granule Formation and Lipid Droplet Biogenesis

Amen

Kaganovich

2021

Front. Cell Dev. Biol.

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Metabolic regulation is a necessary component of all stress response pathways, because all different mechanisms of stress-adaptation place high-energy demands on the cell. Mechanisms that integrate diverse stress response pathways with their metabolic components are therefore of great interest, but few are known. We show that stress granule (SG) formation, a common adaptive response to a variety of stresses, is reciprocally regulated by the pathways inducing lipid droplet accumulation. Inability to upregulate lipid droplets reduces stress granule formation. Stress granule formation in turn drives lipid droplet clustering and fatty acid accumulation. Our findings reveal a novel connection between stress response pathways and new modifiers of stress granule formation.

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Section: Discussionmentioning

confidence: 99%

Small Molecule Screen Reveals Joint Regulation of Stress Granule Formation and Lipid Droplet Biogenesis

Amen

Kaganovich

2021

Front. Cell Dev. Biol.

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“…For co-localization experiments, Z-stacks were acquired at 0.41 µm per slice by sequential scanning with a 60× objective lens. The co-localization analysis and LD quantification (ALDQ) was done using ImageJ software [57]. SIM images were acquired on the Deltavision OMX SR imaging system, Cytiva (formerly GE).…”

Section: Methodsmentioning

confidence: 99%

Japanese encephalitis virus capsid protein interacts with non-lipidated MAP1LC3 on replication membranes and lipid droplets

Sarkar

Sharma

Kumari

et al. 2021

Journal of General Virology

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Microtubule-associated protein 1 light chain 3 (MAP1LC3) is a protein with a well-defined function in autophagy, but still incompletely understood roles in several other autophagy-independent processess. Studies have shown MAP1LC3 is a host-dependency factor for the replication of several viruses. Japanese encephalitis virus (JEV), a neurotropic flavivirus, replicates on ER-derived membranes that are marked by autophagosome-negative non-lipidated MAP1LC3 (LC3-I). Depletion of LC3 exerts a profound inhibition on virus replication and egress. Here, we further characterize the role of LC3 in JEV replication, and through immunofluorescence and immunoprecipitation show that LC3-I interacts with the virus capsid protein in infected cells. This association was observed on capsid localized to both the replication complex and lipid droplets (LDs). JEV infection decreased the number of LDs per cell indicating a link between lipid metabolism and virus replication. This capsid-LC3 interaction was independent of the autophagy adaptor protein p62/Sequestosome 1 (SQSTM1). Further, no association of capsid was seen with the Gamma-aminobutyric acid receptor-associated protein family, suggesting that this interaction was specific for LC3. High-resolution protein-protein docking studies identified a putative LC3-interacting region in capsid, 56FTAL59, and other key residues that could mediate a direct interaction between the two proteins.

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“…Manual camera setting was optimal for almost all images except those for rain intensity I1 that had too small drops and the AutoISO setting captured better and sharper drops. Exner et al (2019) indicated that droplet identification is based on their circular edges and central fluorescence intensity maxima. Therefore, the next stage was to detect and measure the diameter of drops.…”

Section: Methodsmentioning

confidence: 99%

Detailed procedure for outdoor measurement of raindrop size distribution using photogrammetry

Abdollahi

Sadeghi

Darvishan

2021

Journal of Hydrology and Hydromechanics

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Kinetic energy and corresponding erosive force of rainfall are strongly influenced by raindrop. The present paper aims to explore the raindrop size variation during rainfall events with different intensities in northern Iran by applying the processes of camera-taken photographs. Five rainfall intensities of 1 to 10 mm h–1 that occur frequently in the study area were analyzed. A camera with a very short exposure time was used to record the distribution of raindrops size. The raindrops diameters of the rain events ranged from <0.2 to 5.1 mm while the majority of them were between 1 and 2 mm. The results also showed that the variation of rainfall intensity significantly influenced (P< 0.05) raindrops size. Image processing was proven as an accurate technique of translation between the human visual system and digital imaging devices. The findings of the study can be practically utilized by researchers who work in the field of soil erosion and meteorology.

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Lipid droplet quantification based on iterative image processing

Cited by 29 publications

References 50 publications

Small Molecule Screen Reveals Joint Regulation of Stress Granule Formation and Lipid Droplet Biogenesis

Small Molecule Screen Reveals Joint Regulation of Stress Granule Formation and Lipid Droplet Biogenesis

Japanese encephalitis virus capsid protein interacts with non-lipidated MAP1LC3 on replication membranes and lipid droplets

Detailed procedure for outdoor measurement of raindrop size distribution using photogrammetry

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