Intracellular lipid droplets are associated with a myriad of afflictions including obesity, fatty liver disease, coronary artery disease and infectious diseases (e.g., HCV and tuberculosis). To develop high content assay (HCA) techniques to analyze lipid droplets and associated proteins, primary human pre-adipocytes, were plated in 96-well dishes in the presence of rosiglitazone (rosi), a PPARγ agonist which promotes adipogenesis. The cells were then labeled for nuclei, lipid droplets, and proteins such as perilipin, protein kinase C (PKC), and hormone sensitive lipase (HSL). The cells were imaged via automated digital microscopy and algorithms were developed to quantify lipid droplet (Lipid Droplet algorithm) and protein expression and colocalization (Colocalization algorithm). The algorithms, which were incorporated into Vala Science Inc’s CyteSeer® image cytometry program, quantified the rosi-induced increases in lipid droplet number, size, and intensity, and the expression of perilipin with exceptional consistency (Z’ values of 0.54 to 0.71). Regarding colocalization with lipid droplets, Pearson’s Correlation coefficients of 0.38 (highly colocalized), 0.16 (moderate), and − 0.0010 (random) were found for perilipin, PKC, and HSL, respectively. For hepatocytes (AML12, Huh7, and primary cells), the algorithms also quantified the stimulatory and inhibitory effect of oleic acid and triacsin c on lipid droplets (Z’s > 0.50) and ADFP expression/colocalization. Oleic-acid induced lipid droplets in HeLa cells and macrophages (THP-1) were also well quantified. The results suggest that HCA techniques can be utilized to quantify lipid droplets and associated proteins in many cell models relevant to a variety of diseases.

Hepatic lipid droplets (LDs) are associated with metabolic syndrome, type 2 diabetes, hepatitis C, and both alcoholic and nonalcoholic fatty liver disease. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the level of translation. Approximately 1000 different miRNA species are encoded within the human genome, and many are differentially expressed by healthy and diseased liver. However, few studies have investigated the role of miRNAs in regulating LD expression. Accordingly, a high-content assay (HCA) was performed in which human hepatocytes (Huh-7 cells) were transiently transfected with 327 unique human miRNAs; the cells were then fixed, labeled for nuclei and lipid droplets, and imaged with an automated digital microscopy workstation. LD expression was analyzed on a cell-by-cell basis, using automated image analysis. Eleven miRNAs were identified that altered LDs. MiR-181d was the most efficacious inhibitor, decreasing LDs by about 60%. miRNA-181d was also confirmed to reduce cellular triglycerides and cholesterol ester via biochemical assays. Furthermore, a series of proteins was identified via miRNA target analysis, and siRNAs directed against many of these proteins also modified LDs. Thus, HCA-based screening identified novel miRNA and protein regulators of LDs and cholesterol metabolism that may be relevant to hepatic diseases arising from obesity and alcohol abuse. (Journal of Biomolecular Screening 2010:798-805)

Lipolysis in adipocytes is associated with phosphorylation of hormone sensitive lipase (HSL) and translocation of HSL to lipid droplets. In this study, adipocytes were cultured in a high-throughput format (96-well dishes), exposed to lipolytic agents, and then fixed and labeled for nuclei, lipid droplets, and HSL (or HSL phosphorylated on serine 660 [pHSLser660]). The cells were imaged via automated digital fluorescence microscopy, and high-content analysis (HCA) methods were used to quantify HSL phosphorylation and the degree to which HSL (or pHSLser660) colocalizes with the lipid droplets. HSL:lipid droplet colocalization was quantified through use of Pearson's correlation, Mander's M1 Colocalization, and the Tanimoto coefficient. For murine 3T3L1 adipocytes, isoproterenol, Lys-γ3-melanocyte stimulating hormone, and forskolin elicited the appearance and colocalization of pHSLser660, whereas atrial natriuretic peptide (ANP) did not. For human subcutaneous adipocytes, isoproterenol, forskolin, and ANP activated HSL phosphorylation/colocalization, but Lys-γ3-melanocyte stimulating hormone had little or no effect. Since ANP activates guanosine 3',5'-cyclic monophosphate (cGMP)-dependent protein kinase, HSL serine 660 is likely a substrate for cGMP-dependent protein kinase in human adipocytes. For both adipocyte model systems, adipocytes with the greatest lipid content displayed the greatest lipolytic responses. The results for pHSLser660 were consistent with release of glycerol by the cells, a well-established assay of lipolysis, and the HCA methods yielded Z' values >0.50. The results illustrate several key differences between human and murine adipocytes and demonstrate advantages of utilizing HCA techniques to study lipolysis in cultured adipocytes.

The accurate quantification of skeletal muscle fiber cross‐sectional areas is desired in diverse areas of biomedical research. Majority of current studies employ time consuming analysis techniques with manual outlining of muscle fibers using Image J software. The goal of our study was to adapt CyteSeer, a recently developed automated image analysis program, for the quantification of skeletal muscle fiber cross‐sectional areas. Initial CyteSeer algorithm created masks located in the middle of the endomysium between adjacent muscle fibers. This caused the values of the CyteSeer analyzed muscle fiber cross‐sectional areas to be much larger (~25%) when compared with manual analysis of the same fibers. Subsequent modification of the CyteSeer algorithm allowed accurate quantification of skeletal muscle fiber cross‐sectional area. Automated analysis required only 5 seconds/image versus several hours/image needed for the manual analysis. Manual and automated analysis of muscle fiber cross‐sectional areas was performed side‐by‐side for samples from rats, mice, pigs, and monkeys. It showed very high degree of correlation with an average error of 3.2%. The results demonstrate that CyteSeer can be used for accurate automated quantification of skeletal muscle fiber cross‐sectional areas while greatly reducing time required for the analysis. Support: NIH R41AR55604 (PM).