Search tips
Search criteria

Results 1-4 (4)

Clipboard (0)

Select a Filter Below

Year of Publication
Document Types
1.  Image-based feedback control for real-time sorting of microspheres in a microfluidic device 
Lab on a chip  2010;10(18):2402-2410.
We describe a control system to automatically distribute antibody-functionalized beads to addressable assay chambers within a PDMS microfluidic device. The system used real-time image acquisition and processing to manage the valve states required to sort beads with unit precision. The image processing component of the control system correctly counted the number of beads in 99.81% of images (2 689 of 2 694), with only four instances of an incorrect number of beads being sorted to an assay chamber, and one instance of inaccurately counted beads being improperly delivered to waste. Post-experimental refinement of the counting script resulted in one counting error in 2,694 images of beads (99.96% accuracy). We analyzed a range of operational variables (flow pressure, bead concentration, etc.) using a statistical model to characterize those that yielded optimal sorting speed and efficiency. The integrated device was able to capture, count, and deliver beads at a rate of approximately four per minute so that bead arrays could be assembled in 32 individually addressable assay chambers for eight analytical measurements in duplicate (512 beads total) within 2.5 hours. This functionality demonstrates the successful integration of a robust control system with precision bead handling that is the enabling technology for future development of a highly multiplexed bead-based analytical device.
PMCID: PMC2928395  PMID: 20593069
2.  Genome-Wide Analysis of Effectors of Peroxisome Biogenesis 
PLoS ONE  2010;5(8):e11953.
Peroxisomes are intracellular organelles that house a number of diverse metabolic processes, notably those required for β-oxidation of fatty acids. Peroxisomes biogenesis can be induced by the presence of peroxisome proliferators, including fatty acids, which activate complex cellular programs that underlie the induction process. Here, we used multi-parameter quantitative phenotype analyses of an arrayed mutant collection of yeast cells induced to proliferate peroxisomes, to establish a comprehensive inventory of genes required for peroxisome induction and function. The assays employed include growth in the presence of fatty acids, and confocal imaging and flow cytometry through the induction process. In addition to the classical phenotypes associated with loss of peroxisomal functions, these studies identified 169 genes required for robust signaling, transcription, normal peroxisomal development and morphologies, and transmission of peroxisomes to daughter cells. These gene products are localized throughout the cell, and many have indirect connections to peroxisome function. By integration with extant data sets, we present a total of 211 genes linked to peroxisome biogenesis and highlight the complex networks through which information flows during peroxisome biogenesis and function.
PMCID: PMC2915925  PMID: 20694151
3.  Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells 
Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is measured with a fluorescence-activated cell sorter (FACS). The second method is based on budding index analysis. An automated image analysis method is presented for the task of detecting the cells and buds. The proposed methods can be used to obtain quantitative information on the cell cycle phase distribution of a budding yeast S. cerevisiae population. They therefore provide a solid basis for obtaining the complementary information needed in deconvolution of gene expression data. As a case study, both methods are tested with data that were obtained in a time series experiment with S. cerevisiae. The details of the time series experiment as well as the image and FACS data obtained in the experiment can be found in the online additional material at
PMCID: PMC3171340  PMID: 18354733
4.  Insulin-like growth factor binding protein 2 promotes ovarian cancer cell invasion 
Molecular Cancer  2005;4:7.
Insulin-like growth factor binding protein 2 (IGFBP2) is overexpressed in ovarian malignant tissues and in the serum and cystic fluid of ovarian cancer patients, suggesting an important role of IGFBP2 in the biology of ovarian cancer. The purpose of this study was to assess the role of increased IGFBP2 in ovarian cancer cells.
Using western blotting and tissue microarray analyses, we showed that IGFBP2 was frequently overexpressed in ovarian carcinomas compared with normal ovarian tissues. Furthermore, IGFBP2 was significantly overexpressed in invasive serous ovarian carcinomas compared with borderline serous ovarian tumors. To test whether increased IGFBP2 contributes to the highly invasive nature of ovarian cancer cells, we generated IGFBP2-overexpressing cells from an SKOV3 ovarian cancer cell line, which has a very low level of endogenous IGFBP2. A Matrigel invasion assay showed that these IGFBP2-overexpressing cells were more invasive than the control cells. We then designed small interference RNA (siRNA) molecules that attenuated IGFBP2 expression in PA-1 ovarian cancer cells, which have a high level of endogenous IGFBP2. The Matrigel invasion assay showed that the attenuation of IGFBP2 expression indeed decreased the invasiveness of PA-1 cells.
We therefore showed that IGFBP2 enhances the invasion capacity of ovarian cancer cells. Blockage of IGFBP2 may thus constitute a viable strategy for targeted cancer therapy.
PMCID: PMC549074  PMID: 15686601

Results 1-4 (4)