[show abstract][hide abstract] ABSTRACT: Dysfunction of ENaC, the epithelial sodium channel that regulates salt and water reabsorption in epithelia, causes several human diseases, including cystic fibrosis (CF). To develop a global understanding of molecular regulators of ENaC traffic/function and to identify of candidate CF drug targets, we performed a large-scale screen combining high-content live-cell microscopy and siRNAs in human airway epithelial cells. Screening over 6,000 genes identified over 1,500 candidates, evenly divided between channel inhibitors and activators. Genes in the phosphatidylinositol pathway were enriched on the primary candidate list, and these, along with other ENaC activators, were examined further with secondary siRNA validation. Subsequent detailed investigation revealed ciliary neurotrophic factor receptor (CNTFR) as an ENaC modulator and showed that inhibition of (diacylglycerol kinase, iota) DGKι, a protein involved in PiP2 metabolism, downgrades ENaC activity, leading to normalization of both Na(+) and fluid absorption in CF airways to non-CF levels in primary human lung cells from CF patients.
[show abstract][hide abstract] ABSTRACT: The genetic integrity of every organism depends on the faithful partitioning of its genome between two daughter cells in mitosis. In all eukaryotes, chromosome segregation requires the assembly of the mitotic spindle, a bipolar array of dynamic microtubules. Perturbations in microtubule dynamics affect spindle assembly and maintenance and ultimately result in aberrant cell divisions. To identify new regulators of microtubule dynamics within the hundreds of mitotic hits, reported in RNAi screens performed in C. elegans, Drosophila and mammalian tissue culture cells [Sonnichsen et al., 2005; Goshima et al., 2007; Neumann et al., 2010], we established a fast and quantitative assay to measure microtubule dynamics in living cells. Here we present a fully automated workflow from RNAi transfection, via image acquisition and data processing, to the quantitative characterization of microtubule behaviour. Candidate genes are knocked down by solid-phase reverse transfection with siRNA oligos in HeLa cells stably expressing EB3-EGFP, a microtubule plus end marker. Mitotic cells are selected using an automatic classifier [Conrad et al., 2011] and imaged on a spinning disk confocal microscope at high temporal and spatial resolution. The time-lapse movies are analysed using a multiple particle tracking software, developed in-house, that automatically detects microtubule plus ends, tracks microtubule growth events over consecutive frames and calculates growth speeds, lengths and lifetimes of the tracked microtubules. The entire assay provides a powerful tool to analyse the effect of essential mitotic genes on microtubule dynamics in living cells and to dissect their contribution in spindle assembly and maintenance.
[show abstract][hide abstract] ABSTRACT: As several genomes have been sequenced, post-genomic approaches like transcriptomics and proteomics, identifying gene products differentially expressed in association with a given pathology, have held promise both of understanding the pathways associated with the respective disease and as a fast track to therapy. Notwithstanding, these approaches cannot distinguish genes and proteins with mere secondary pathological association from those primarily involved in the basic defect(s). New global strategies and tools identifying gene products responsible for the basic cellular defect(s) in CF pathophysiology currently being performed are presented here. These include high-content screens to determine proteins affecting function and trafficking of CFTR and ENaC.
Methods in molecular biology (Clifton, N.J.) 01/2011; 742:249-64.
[show abstract][hide abstract] ABSTRACT: Quantitative microscopy relies on imaging of large cell numbers but is often hampered by time-consuming manual selection of specific cells. The 'Micropilot' software automatically detects cells of interest and launches complex imaging experiments including three-dimensional multicolor time-lapse or fluorescence recovery after photobleaching in live cells. In three independent experimental setups this allowed us to statistically analyze biological processes in detail and is thus a powerful tool for systems biology.
[show abstract][hide abstract] ABSTRACT: Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
[show abstract][hide abstract] ABSTRACT: Chromosome segregation and cell division are essential, highly ordered processes that depend on numerous protein complexes. Results from recent RNA interference screens indicate that the identity and composition of these protein complexes is incompletely understood. Using gene tagging on bacterial artificial chromosomes, protein localization, and tandem-affinity purification-mass spectrometry, the MitoCheck consortium has analyzed about 100 human protein complexes, many of which had not or had only incompletely been characterized. This work has led to the discovery of previously unknown, evolutionarily conserved subunits of the anaphase-promoting complex and the gamma-tubulin ring complex--large complexes that are essential for spindle assembly and chromosome segregation. The approaches we describe here are generally applicable to high-throughput follow-up analyses of phenotypic screens in mammalian cells.
[show abstract][hide abstract] ABSTRACT: Fluorescence microscopy is one of the most powerful tools to investigate complex cellular processes such as cell division, cell motility, or intracellular trafficking. The availability of RNA interference (RNAi) technology and automated microscopy has opened the possibility to perform cellular imaging in functional genomics and other large-scale applications. Although imaging often dramatically increases the content of a screening assay, it poses new challenges to achieve accurate quantitative annotation and therefore needs to be carefully adjusted to the specific needs of individual screening applications. In this review, we discuss principles of assay design, large-scale RNAi, microscope automation, and computational data analysis. We highlight strategies for imaging-based RNAi screening adapted to different library and assay designs.
The Journal of Cell Biology 02/2010; 188(4):453-61. · 10.82 Impact Factor
[show abstract][hide abstract] ABSTRACT: High-throughput time-lapse microscopy is an excellent way of studying gene function by collecting time-resolved image data of the cellular responses to gene perturbations. With the increase in both data amount and complexity, computational methods capable of dealing with large image data sets are required. While image processing methods have been successfully applied to endpoint assays in the past, the analysis of complex time-resolved read-outs was so far still too immature to be applied on a large-scale. Here, we present a complete computational processing pipeline for such screens. By automatic image processing and machine learning, a quantitative description of phenotypic dynamics is obtained from the raw bitmaps. In order to visualize the resulting phenotypes in their temporal context, we introduce Event Order Maps allowing a concise representation of the major tendencies of causes and consequences of phenotypic classes. In order to cluster the phenotypic kinetics, we propose a novel technique based on trajectory representation of multidimensional time series. We demonstrate the use of these methods applying them on a genome wide RNAi screen by time-lapse microscopy.
Journal of Structural Biology 10/2009; 170(1):1-9. · 3.36 Impact Factor
[show abstract][hide abstract] ABSTRACT: The MitoCheck project aims at identifying and characterizing the function of genes involved in mitosis in live human cells. The genome wide RNA interference screen developed for this purpose is based on automatic time-lapse microscopy to analyze the phenotypes after knocking down each human gene individually in cultured cells whose chromosomes are fluorescently labeled. Such a screen produces large amounts of digital image data (~ 200.000 video sequences, i.e. over 18 millions of images) which can no longer be handled and interpreted manually. We have developed an image processing method consisting of segmentation, feature extraction and automatic classification, which assigns to each nucleus in each image one out of several predefined morphological classes. Using the relative cell counts in each of these classes, measured over time for each experiment, we derive a phenotypic fingerprint for each gene that allows clustering of genes by functional similarity. This paper will give an overview over the computational aspects of this screen. The complete quality controlled data set and phenotypic measurements will be available after publication on http://www.mitocheck.org/.
Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on; 06/2008
[show abstract][hide abstract] ABSTRACT: Light microscopic analysis of cell morphology provides a high-content readout of cell function and protein localization. Cell arrays and microwell transfection assays on cultured cells have made cell phenotype analysis accessible to high-throughput experiments. Both the localization of each protein in the proteome and the effect of RNAi knock-down of individual genes on cell morphology can be assayed by manual inspection of microscopic images. However, the use of morphological readouts for functional genomics requires fast and automatic identification of complex cellular phenotypes. Here, we present a fully automated platform for high-throughput cell phenotype screening combining human live cell arrays, screening microscopy, and machine-learning-based classification methods. Efficiency of this platform is demonstrated by classification of eleven subcellular patterns marked by GFP-tagged proteins. Our classification method can be adapted to virtually any microscopic assay based on cell morphology, opening a wide range of applications including large-scale RNAi screening in human cells.
Genome Research 07/2004; 14(6):1130-6. · 14.40 Impact Factor