Comparison of Methods for Image-Based Profiling of Cellular Morphological Responses to Small-Molecule Treatment

Ljosa, Vebjorn; Caie, Peter D.; Horst, Rob ter; Sokolnicki, Katherine L; Jenkins, Emma; Daya, Sandeep; Roberts, Mark; Jones, Thouis R.; Singh, Shantanu; Genovesio, Auguste; Clemons, Paul A.; Carragher, Neil O.; Carpenter, Anne E.

doi:10.1177/1087057113503553

Cited by 178 publications

(269 citation statements)

References 25 publications

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“…Hierarchical clustering of well-annotated BIO compounds based on their MC profiles grouped compounds with similar biological effects together (SI Appendix, Fig. S1), confirming results from earlier studies (19,24).…”

Section: Compound Sets With Diverse Cell Morphology Profiles Have DIVsupporting

confidence: 82%

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

Wawer¹,

Li²,

Gústafsdóttir³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cellbased and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.chemical diversity | biological performance diversity | biological activity | chemical similarity P rofiling small molecules based on multiple biological activity measurements can illuminate mechanisms of action by comparing profiles with compounds whose mechanisms of action are known (1-5). Here, we describe a previously unidentified use of small-molecule profiling-enabling the creation of activityenriched and performance-diverse compound libraries for smallmolecule probe and drug discovery.Biochemical and cell-based high-throughput screening (HTS) is routinely used to discover novel bioactive molecules through unbiased testing of up to several million compounds per screen (6). However, despite ongoing advances in throughput, compound libraries will always represent only a small fraction of all relevant compounds theoretically accessible through chemical synthesis (a concept often referred to as "chemical space") (7). Library composition therefore presents a strong source of bias and potential limitation for any screening endeavor.There is little dissent about the notion that a good screening collection should yield many high-quality hits for a wide range of biological targets or phenotypes. In other words, it should be enriched for bioactive compounds and have high biological performance diversity. A high percentage of compounds lacking any activity will contribute to high cost and low performance of a high-throughput screen. A practical example is a compound collection containing a high percentage of compounds that fail to penetrate cell membranes-such a library will be unlikely to perform effectively in a cell-based HTS exploring an intracellular process. Similarly, a screening collection of compounds with highly redundant biological activities will be less efficient than an equally sized library with diverse performance (Fig. 1). A systematic path to reach these goals, however, remains elusive. One common practice is analyzing structural features of compounds to maximize chemical structural diversity. Ho...

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Section: Compound Sets With Diverse Cell Morphology Profiles Have DIVsupporting

confidence: 82%

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

Wawer¹,

Li²,

Gústafsdóttir³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

195

177

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“…In fact, the accuracy of this model was calculated to be 83% compared to the abovementioned factor analysis model with 94% accuracy. 47 Caie et al 2010 correlated phenotypic drug response with several cancer cell types of different genetic background. 49 A library of well-characterized drugs was investigated and HCA was run in a four-wavelength assay with four different cancer cell lines.…”

Section: Application Examples For Cell-based Profilingmentioning

confidence: 99%

Target identification by image analysis

et al. 2016

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Each biologically active compound induces phenotypic changes in target cells that are characteristic for its mode of action. These phenotypic alterations can be directly observed under the microscope or made visible by labelling structural elements or selected proteins of the cells with dyes. A comparison of the cellular phenotype induced by a compound of interest with the phenotypes of reference compounds with known cellular targets allows predicting its mode of action. While this approach has been successfully applied to the characterization of natural products based on a visual inspection of images, recent studies used automated microscopy and analysis software to increase speed and to reduce subjective interpretation. In this review, we give a general outline of the workflow for manual and automated image analysis, and we highlight natural products whose bacterial and eucaryotic targets could be identified through such approaches.

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“…2: experimentation exemplified by the NCI-60 collection [5]. 3: the inclusion of gene-expression data in profiling experiments [72, 73]. 4: profiling of a small number of related compounds across many cell lines [21].…”

Section: Figurementioning

confidence: 99%

Integrating phenotypic small-molecule profiling and human genetics: the next phase in drug discovery

2015

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Over the past decade, tremendous progress in high-throughput small-molecule screening methods has facilitated the rapid expansion of phenotype-based data. Parallel advances in genomic characterization methods have complemented these efforts by providing a growing list of annotated cell line features. Together, these developments have paved the way for feature-based identification of novel, exploitable cellular dependencies, subsequently expanding our therapeutic toolkit in cancer and other diseases. Here, we provide an overview of the evolution of phenotypic small-molecule profiling and discuss the most significant and recent profiling and analytical efforts, their impact on the field, and their clinical ramifications. We additionally provide a perspective for future developments in phenotypic profiling efforts guided by genomic science.

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Comparison of Methods for Image-Based Profiling of Cellular Morphological Responses to Small-Molecule Treatment

Cited by 178 publications

References 25 publications

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

Target identification by image analysis

Integrating phenotypic small-molecule profiling and human genetics: the next phase in drug discovery

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