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 ,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.To target the ,21,000 protein-coding genes in the human genome, we used a chemically synthesized short interfering RNA (siRNA) library designed to uniquely target each gene with 2-3 independent sequences (Supplementary Methods). The siRNAs in this library were tested individually and reduced the messenger RNAs of targeted genes to below 30% of original levels (to an average of 13%) for 97% of more than 1,000 genes tested (Supplementary Table 1). To allow high-throughput phenotyping of each individual siRNA in triplicates by live-cell imaging, we used a previously established workflow for solid-phase transfection using siRNA microarrays coupled to automatic time-lapse microscopy 1 . As a high-content phenotypic assay we chose to monitor fluorescent chromosomes in a human cell line stably expressing core histone 2B tagged with green fluorescent protein (GFP) 1 . After seeding on the siRNA microarrays, on average 67 (630) cells for each siRNA of the library were imaged in triplicates for 2 days, thus documenting many of their basic functions such as cell division, proliferation, survival and migration. Image processing reveals mitotic hitsThis resulted in a large data set of ,190,000 time-lapse movies providing time-resolved records of over 19 million cell divisions. To automatically score and annotate phenotypes in this large data set, we developed a computational pipeline 2 ( Fig. 1) extending previously established methods of morphology recognition by supervised machine learning [3][4][5][6] . In brief, after segmentation, about 200 quantitative features were extracted from each nucleus and used for classification into one of 16 morphological classes ( Fig. 1 and Supplementary Movies 1-30) by a support vector machine classifier previously trained on a set of ,3,000 manually annotated nuclei (Supplementary Methods). This classifier automatically recognizes changes in nuclear morphology due to the cell cycle, cell death or other phenotypic changes with an overall accuracy of 87% (Supplementary Fig. 1) and allows us to convert each time-lapse movie into a phenotypic profile that quantifies the response to each siRNA ...

SUMMARY Hepatitis C virus (HCV) is a major causative agent of chronic liver disease in humans. To gain insight into host factor requirements for HCV replication we performed a siRNA screen of the human kinome and identified 13 different kinases, including phosphatidylinositol-4 kinase III alpha (PI4KIIIα) as required for HCV replication. Consistent with elevated levels of the PI4KIIIα product phosphatidylinositol-4-phosphate (PI4P) detected in HCV infected cultured hepatocytes and liver tissue from chronic hepatitis C patients, the enzymatic activity of PI4KIIIα was critical for HCV replication. Viral nonstructural protein 5A (NS5A) was found to interact with PI4KIIIα and stimulate its kinase activity. The absence of PI4KIIIα activity induced a dramatic change in the ultrastructural morphology of the membranous HCV replication complex. Our analysis suggests that the direct activation of a lipid kinase by HCV NS5A contributes critically to the integrity of the membranous viral replication complex.

RNA interference (RNAi) is a powerful tool to study gene function in cultured cells. Transfected cell microarrays in principle allow high-throughput phenotypic analysis after gene knockdown by microscopy. But bottlenecks in imaging and data analysis have limited such high-content screens to endpoint assays in fixed cells and determination of global parameters such as viability. Here we have overcome these limitations and developed an automated platform for high-content RNAi screening by time-lapse fluorescence microscopy of live HeLa cells expressing histone-GFP to report on chromosome segregation and structure. We automated all steps, including printing transfection-ready small interfering RNA (siRNA) microarrays, fluorescence imaging and computational phenotyping of digital images, in a high-throughput workflow. We validated this method in a pilot screen assaying cell division and delivered a sensitive, time-resolved phenoprint for each of the 49 endogenous genes we suppressed. This modular platform is scalable and makes the power of time-lapse microscopy available for genome-wide RNAi screens.

Elevated plasma cholesterol levels are considered responsible for excess cardiovascular morbidity and mortality. Cholesterol in plasma is tightly controlled by cholesterol within cells. Here, we developed and applied an integrative functional genomics strategy that allows systematic identification of regulators of cellular cholesterol levels. Candidate genes were identified by genome-wide gene-expression profiling of sterol-depleted cells and systematic literature queries. The role of these genes in cholesterol regulation was then tested by targeted siRNA knockdown experiments quantifying cellular cholesterol levels and the efficiency of low-density lipoprotein (LDL) uptake. With this strategy, 20 genes were identified as functional regulators of cellular cholesterol homeostasis. Of these, we describe TMEM97 as SREBP target gene that under sterol-depleted conditions localizes to endo-/lysosomal compartments and binds to LDL cholesterol transport-regulating protein Niemann-Pick C1 (NPC1). Taken together, TMEM97 and other factors described here are promising to yield further insights into how cells control cholesterol levels.

The secretory pathway in mammalian cells has evolved to facilitate the transfer of cargo molecules to internal and cell surface membranes. Use of automated microscopy-based genome-wide RNA interference screens in cultured human cells allowed us to identify 554 proteins influencing secretion. Cloning, fluorescent-tagging and subcellular localization analysis of 179 of these proteins revealed that more than two-thirds localize to either the cytoplasm or membranes of the secretory and endocytic pathways. The depletion of 143 of them resulted in perturbations in the organization of the COPII and/or COPI vesicular coat complexes of the early secretory pathway, or the morphology of the Golgi complex. Network analyses revealed a so far unappreciated link between early secretory pathway function, small GTP-binding protein regulation, actin cytoskeleton organization and EGF-receptor-mediated signalling. This work provides an important resource for an integrative understanding of global cellular organization and regulation of the secretory pathway in mammalian cells.

The complete DNA sequence of the yeast Saccharomyces cerevisiae chromosome XI has been determined. In addition to a compact arrangement of potential protein coding sequences, the 666,448-base-pair sequence has revealed general chromosome patterns; in particular, alternating regional variations in average base composition correlate with variations in local gene density along the chromosome. Significant discrepancies with the previously published genetic map demonstrate the need for using independent physical mapping criteria.

Here, we describe a robust protocol for the reverse transfection of cells on small interfering (siRNA) arrays, which, in combination with multi-channel immunofluorescence or time-lapse microscopy, is suitable for genome-wide RNA interference (RNAi) screens in intact human cells. The automatic production of 48 'transfection ready' siRNA arrays, each containing 384 samples, takes in total 7 h. Pre-fabricated siRNA arrays can be used without loss of transfection efficiency at least up to 15 months after printing. Different human cell lines that have been successfully transfected using the protocol are presented here. The present protocol has been applied to two genome-wide siRNA screens addressing mitosis and constitutive protein secretion.

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.