Measurement of phagocytosis using fluorescent latex beads

Fluorescent monodisperse latex beads and a computer-centered spectrofluorimeter were used to devise a sensitive new assay for phagocytosis. LM fibroblasts, a transformed cell line with a high endocytic rate, were exposed to fluoresbrite beads and the following parameters were investigated: incubation time, incubation temperature and bead/cell ratio. The bead uptake was linear for 60 min over a wide range of bead/cell ratios up to 130 beads/cell. Phagocytosis was inhibited at 4 degrees C, by incubation in the presence of colchicine, and by glucose deprivation. Scanning and transmission electron microscopy were used to confirm that at 37 degrees C both bead adsorption and internalization occurred while at 4 degrees C only bead adsorption but not endocytosis occurred. Large bead sizes (0.86 and 1.72 micrometer diameter) were most useful due to higher fluorescence and higher signal to noise ratios than smaller beads (0.25 and 0.57 micrometer diameter). Beads (0.86 micrometer diameter) were taken up at a rate of 4.4 beads/cell/h at 37 degrees C when a bead/cell ratio of 70 was used. The uptake was zero when assayed at zero time. These criteria establish that fluoresbrite beads provide a useful new fluorimetric assay for phagocytosis.     

Effect of fatty acids on physical properties of microsomes from isolated perfused rat liver

A computer-centered spectrofluorimeter was used to examine the physicochemical properties of hepatic microsomes and microsomal lipids obtained from isolated rat livers perfused with medium containing palmitate or oleate. The fatty acid composition and degree of unsaturation of the liver microsomal lipids reflected that the fatty acid present in the perfusate. The absorption corrected fluorescence, relative fluorescence efficiency, polarization, and fluorescence anisotropy of several fluorescent probe molecules were measured to determine if their different microenvironments may be altered by the type of fatty acid infused. The probe molecules β-parinaric acid and 1.6-diphenyl-1,3,5-hexatriene had higher values for each of these parameters when incorporated into microsomes obtained from livers perfused with a medium containing palmitate than with oleate. The same parameters measured for cholesta-5,7,9(11)-trien-3β-ol and N-phenyl-1-naphthylamine were not altered. These differences appeared to be primarily due to alterations in microviscosity of the probe microenvironments since the rotational correlation time of 1,6-diphenyl-1,3,5-hexatriene was 25% lower in the microsomes from livers perfused with oleate as compared to livers perfused with palmitate. Thermal discontinuities in Arrhenius plots were noted in the intact microsomes but not in the isolated microsomal lipids with the fluorescence probe molecule β-parinaric acid. Break points occurred at 10°C and 26°C for microsomes from livers perfused with palmitate and at 12°C and 17°C for microsomes from livers perfused with oleate containing medium. These results suggest that the physicochemical properties of liver microsomes were determined in part by the fatty acid in the perfusate.     

Extracting a few functionally reproducible biomarkers to build robust subnetwork-based classifiers for the diagnosis of cancer

In microarray-based case–control studies of a disease, people often attempt to identify a few diagnostic or prognostic markers amongst the most significant differentially expressed (DE) genes. However, the reproducibility of DE genes identified in different studies for a disease is typically very low. To tackle the problem, we could evaluate the reproducibility of DE genes across studies and define robust markers for disease diagnosis using disease-associated protein–protein interaction (PPI) subnetwork. Using datasets for four cancer types, we found that the most significant DE genes in cancer exhibit consistent up- or down-regulation in different datasets. For each cancer type, the 5 (or 10) most significant DE genes separately extracted from different datasets tend to be significantly coexpressed and closely connected in the PPI subnetwork, thereby indicating that they are highly reproducible at the PPI level. Consequently, we were able to build robust subnetwork-based classifiers for cancer diagnosis.