Multidimensional analysis of Gammaherpesvirus RNA expression reveals unexpected heterogeneity of gene expression.

Virus-host interactions are frequently studied in bulk cell populations, obscuring cell-to-cell variation. Here we investigate endogenous herpesvirus gene expression at the single-cell level, combining a sensitive and robust fluorescent in situ hybridization platform with multiparameter flow cytometry, to study the expression of gammaherpesvirus non-coding RNAs (ncRNAs) during lytic replication, latent infection and reactivation in vitro. This method allowed robust detection of viral ncRNAs of murine gammaherpesvirus 68 (γHV68), Kaposi's sarcoma associated herpesvirus and Epstein-Barr virus, revealing variable expression at the single-cell level.

Differential Effects of Lipid-lowering Drugs in Modulating Morphology of Cholesterol Particles.

Treatment of dyslipidemia patients with lipid-lowering drugs leads to a significant reduction in low-density lipoproteins (LDL) level and a low to moderate level of increase in high-density lipoprotein (HDL) cholesterol in plasma. However, a possible role of these drugs in altering morphology and distribution of cholesterol particles is poorly understood. Here, we describe the in vitro evaluation of lipid-lowering drug effects in modulating morphological features of cholesterol particles using the plaque array method in combination with imaging flow cytometry.

Applications of Imaging Flow Cytometry for Microalgae.

The ability to image large numbers of cells at high resolution enhances flow cytometric analysis of cells and cell populations. In particular, the ability to image intracellular features adds a unique aspect to analyses, and can enable correlation between molecular phenomena resulting in alterations in cellular phenotype. Unicellular microalgae are amenable to high-throughput analysis to capture the diversity of cell types in natural samples, or diverse cellular responses in clonal populations, especially using imaging cytometry.

Plaque array method and proteomics-based identification of biomarkers from Alzheimer's disease serum.

Background: Progressive accumulation of amyloid plaques in the regions of brain, carotid and cerebral arteries is the leading cause of Alzheimer's disease (AD) and related dementia in affected patients. The early identification of individuals with AD remains a challenging task relying on symptomatic events and thus the development of a biomarker-based approach will significantly aid in the diagnosis of AD.

Methods: Here we describe a flow cytometer-based serum biomarker identification method using plaque particles, and applying mass spectrometry based proteomic analysis of the isolated plaque particles for the identification of serum proteins present in the plaque particles.