Dataset Information

A novel phenotypic dissimilarity method for image-based high-throughput screens.

ABSTRACT: BACKGROUND: Discovering functional relationships of genes through cell-based phenotyping has become an important approach in functional genomics. High-throughput imaging offers the ability to quantitatively assess complex phenotypes after perturbation by RNA interference (RNAi). Such image-based high-throughput RNAi screening studies have facilitated the discovery of novel components of gene networks and their interactions. Images generated by automated microscopy are typically analyzed by extracting quantitative features of individual cells, resulting in large multidimensional data sets. Robust and sensitive methods to interpret these data sets and to derive biologically relevant information in a high-throughput and unbiased manner remain to be developed. RESULTS: Here we propose a new analysis method, PhenoDissim, which computes the phenotypic dissimilarity between cell populations via Support Vector Machine classification and cross validation. Applying this method to a kinome RNAi screening data set, we demonstrate that the proposed method shows a good replicate reproducibility, separation of controls and clustering quality, and we are able to identify siRNA phenotypes and discover potential functional links between genes. CONCLUSIONS: PhenoDissim is a novel analysis method for image-based high-throughput screen, relying on two parameters which can be automatically optimized without a priori knowledge. PhenoDissim is freely available as an R package.

SUBMITTER: Zhang X

PROVIDER: S-EPMC4225524 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A novel phenotypic dissimilarity method for image-based high-throughput screens.

Zhang Xian X Boutros Michael M

BMC bioinformatics 20131121

<h4>Background</h4>Discovering functional relationships of genes through cell-based phenotyping has become an important approach in functional genomics. High-throughput imaging offers the ability to quantitatively assess complex phenotypes after perturbation by RNA interference (RNAi). Such image-based high-throughput RNAi screening studies have facilitated the discovery of novel components of gene networks and their interactions. Images generated by automated microscopy are typically analyzed b ...[more]

PMID: 24256072

Similar Datasets

Project description:Despite advances toward understanding the prevention and treatment of many cancers, patients who suffer from oral squamous cell carcinoma (OSCC) confront a survival rate that has remained unimproved for more than 2 decades, indicating our ability to treat them pharmacologically has reached a plateau. In an ongoing effort to improve the clinical outlook for this disease, we previously reported that an essential component of the mechanism by which the proteasome inhibitor bortezomib (PS-341, Velcade) induced apoptosis in OSCC required the activation of a terminal unfolded protein response (UPR). Predicated on these studies, the authors hypothesized that high-throughput screening (HTS) of large diverse chemical libraries might identify more potent or selective small-molecule activators of the apoptotic arm of the UPR to control or kill OSCC. They have developed complementary cell-based assays using stably transfected CHO-K1 cell lines that individually assess the PERK/eIF2?/CHOP (apoptotic) or the IRE1/XBP1 (adaptive) UPR subpathways. An 66 K compound collection was screened at the University of Michigan Center for Chemical Genomics that included a unique library of prefractionated natural product extracts. The mycotoxin methoxycitrinin was isolated from a natural extract and found to selectively activate the CHOP-luciferase reporter at 80 µM. A series of citrinin derivatives was isolated from these extracts, including a unique congener that has not been previously described. In an effort to identify more potent compounds, the authors examined the ability of citrinin and the structurally related mycotoxins ochratoxin A and patulin to activate the UPR. Strikingly, it was found that patulin at 2.5 to 10 µM induced a terminal UPR in a panel of OSCC cells that was characterized by an increase in CHOP, GADD34, and ATF3 gene expression and XBP1 splicing. A luminescent caspase assay and the induction of several BH3-only genes indicated that patulin could induce apoptosis in OSCC cells. These data support the use of this complementary HTS strategy to identify novel modulators of UPR signaling and tumor cell death.

Project description:BACKGROUND:Lymphatic filariasis is caused by the parasitic worms Wuchereria bancrofti, Brugia malayi or B. timori, which are transmitted via the bites from infected mosquitoes. Once in the human body, the parasites develop into adult worms in the lymphatic vessels, causing severe damage and swelling of the affected tissues. According to the World Health Organization, over 1.2 billion people in 58 countries are at risk of contracting lymphatic filariasis. Very few drugs are available to treat patients infected with these parasites, and these have low efficacy against the adult stages of the worms, which can live for 7-15 years in the human body. The requirement for annual treatment increases the risk of drug-resistant worms emerging, making it imperative to develop new drugs against these devastating diseases. METHODOLOGY/PRINCIPAL FINDINGS:We have developed a yeast-based, high-throughput screening system whereby essential yeast genes are replaced with their filarial or human counterparts. These strains are labeled with different fluorescent proteins to allow the simultaneous monitoring of strains with parasite or human genes in competition, and hence the identification of compounds that inhibit the parasite target without affecting its human ortholog. We constructed yeast strains expressing eight different Brugia malayi drug targets (as well as seven of their human counterparts), and performed medium-throughput drug screens for compounds that specifically inhibit the parasite enzymes. Using the Malaria Box collection (400 compounds), we identified nine filarial specific inhibitors and confirmed the antifilarial activity of five of these using in vitro assays against Brugia pahangi. CONCLUSIONS/SIGNIFICANCE:We were able to functionally complement yeast deletions with eight different Brugia malayi enzymes that represent potential drug targets. We demonstrated that our yeast-based screening platform is efficient in identifying compounds that can discriminate between human and filarial enzymes. Hence, we are confident that we can extend our efforts to the construction of strains with further filarial targets (in particular for those species that cannot be cultivated in the laboratory), and perform high-throughput drug screens to identify specific inhibitors of the parasite enzymes. By establishing synergistic collaborations with researchers working directly on different parasitic worms, we aim to aid antihelmintic drug development for both human and veterinary infections.

Dataset Information

A novel phenotypic dissimilarity method for image-based high-throughput screens.

Publications

A novel phenotypic dissimilarity method for image-based high-throughput screens.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure