Filling the drug discovery gap: is high-content screening the missing link?

Chanrion, Benjamin; Cattin, Marie-Elodie

doi:10.1016/j.coph.2018.07.002

Cited by 23 publications

(16 citation statements)

References 41 publications

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“…HCS has the potential to combine cell viability, cell signaling and transcription, and/or phenotypic readouts in a single well across a large number of conditions in a target-based, phenotypic or combined targetphenotypic drug discovery mode. Therefore, in a single assay, HCS technology has the potential to predict and integrate key biological activities of compounds during the early stages of the drug discovery process [10,15].…”

Section: Advantages Of Hcs In Comparison To Current Assay Methodsmentioning

confidence: 99%

“…This list of descriptors is usually called phenotypic signature or fingerprint and represents the keystone of HCS but also its weakness, as it could lead to "highly precise" false positives. A set of principles has been established to facilitate the definition and development of disease-relevant assays, taking advantage of the latest advances in cell-based assay technologies [10,19]. To select the model of interest, an understanding of the biology at the molecular level, including the cause of the disease of interest, is required.…”

Section: Advantages Of Hcs In Comparison To Current Assay Methodsmentioning

confidence: 99%

“…In recent years, technological developments in various fields such as HCS analysis software, in vitro cellular models, genome engineering, chemoinformatic tools and phenotypic compound libraries provided the investigators significant capabilities to measure various biological out-puts in the most physiopathologically relevant in vitro models. According to Dorval et al [10], however, to fully benefit from the of HCS's capabilities for either target or drug discovery, it is critical to select the appropriate projects, taking into account (i) the level of understanding of the molecular processes involved in the biology of interest, (ii) the availability of a physiopathologically relevant in vitro models adapted to medium and large scale screening campaigns, (iii) the ability to select and measure the most appropriate and diversified phenotypic and functional features to provide a sufficient level of agnosticism and finally, (iv) the selection of multiple and appropriate controls to fully enable HCS capabilities and adequate hit selection. Furthermore, the current artificial intelligence (AI) revolution will catalyze further major evolutions in the way HCS is used.…”

Section: Essentials and Perspectives Of Hcsmentioning

confidence: 99%

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Application of Image-Based High Content Analysis for the Screening of Bioactive Natural Products

Nghị

Hương

2018

JST

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Each bioactive compound induces phenotypic changes in target cells that can be made visible by labelling selected molecules of the cells with fluorescent dyes and/or directly observed under the high-throughput microscope. A comparison of the cellular phenotype induced by a compound of interest with known cellular targets allows predicting its mode of action. Over the past 15 years, high-throughput microscopy has been one of the fastest growing fields in cell biology. When combined with automated multiparametric image and data analysis, it is referred to as high-content screening (HCS). Whilst HCS has been successfully applied to the bioactivity characterization of natural products, recent studies used automated microscopy and software to increase speed and to reduce subjective interpretation. In 2017, Institute of Natural Products Chemistry (INPC-VAST) has been equipped with a HCS platform (Olympus Scan^R) that designed for fully automated image acquisition and analysis of biological samples to visually inspect the cellular morphology induced by hit compounds as well as to discriminate from false positives. Accordingly, this short review covers the concepts of HCS and its application in screening of biologically active natural products whose molecular targets could be identified through such approaches.

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Section: Advantages Of Hcs In Comparison To Current Assay Methodsmentioning

confidence: 99%

Section: Advantages Of Hcs In Comparison To Current Assay Methodsmentioning

confidence: 99%

Section: Essentials and Perspectives Of Hcsmentioning

confidence: 99%

See 1 more Smart Citation

Application of Image-Based High Content Analysis for the Screening of Bioactive Natural Products

Nghị

Hương

2018

JST

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“…Exploiting image-based profiling assays for assessing single-cell phenotypes has also been explored, including by machine learning (Scheeder et al 2018 ). Powerful cell-based assay technologies that permit tighter linkage between in vitro and physio-pathological conditions and environments, including induced pluripotent stem cells, three-dimensional models, co-culture, and organ-on-a-chip systems, as well as advances in gene-editing technologies (Dorval et al 2018 ), were put forward as the reasons for this renaissance and its promising future. Methods have also been developed to capture it (Joslin et al 2018 ).…”

Section: Phenotypic Drug Discoverymentioning

confidence: 99%

Precision medicine review: rare driver mutations and their biophysical classification

et al. 2019

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How can biophysical principles help precision medicine identify rare driver mutations? A major tenet of pragmatic approaches to precision oncology and pharmacology is that driver mutations are very frequent. However, frequency is a statistical attribute, not a mechanistic one. Rare mutations can also act through the same mechanism, and as we discuss below, Blatent driver^mutations may also follow the same route, with Bhelper^mutations. Here, we review how biophysics provides mechanistic guidelines that extend precision medicine. We outline principles and strategies, especially focusing on mutations that drive cancer. Biophysics has contributed profoundly to deciphering biological processes. However, driven by data science, precision medicine has skirted some of its major tenets. Data science embodies genomics, tissue-and cell-specific expression levels, making it capable of defining genome-and systems-wide molecular disease signatures. It classifies cancer driver genes/mutations and affected pathways, and its associated protein structural data guide drug discovery. Biophysics complements data science. It considers structures and their heterogeneous ensembles, explains how mutational variants can signal through distinct pathways, and how allo-network drugs can be harnessed. Biophysics clarifies how one mutation-frequent or rare-can affect multiple phenotypic traits by populating conformations that favor interactions with other network modules. It also suggests how to identify such mutations and their signaling consequences. Biophysics offers principles and strategies that can help precision medicine push the boundaries to transform our insight into biological processes and the practice of personalized medicine. By contrast, Bphenotypic drug discovery,^which capitalizes on physiological cellular conditions and first-in-class drug discovery, may not capture the proper molecular variant. This is because variants of the same protein can express more than one phenotype, and a phenotype can be encoded by several variants.

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“…In the current era of big data analysis, instrumentation to generate massive amounts of image data is in high demand. For high throughput screening in biology, or for novel computer aided medical diagnoses in the field of digital pathology, there is a need for fluorescence imaging of tissues over large fields of view (∼few cm), in 3D (up to hundred layers of µm thickness), and at cellular resolution (∼1 µm) [1][2][3]. This can be used, for example, in immunofluorescence or fluorescence in situ hybridization (FISH) studies.…”

Section: Introductionmentioning

confidence: 99%

Multi-line fluorescence scanning microscope for multi-focal imaging with unlimited field of view

Graaff¹,

Leenders²,

Boyaval³

et al. 2019

Biomed. Opt. Express

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Confocal scanning microscopy is the de facto standard modality for fluorescence imaging. Point scanning, however, leads to a limited throughput and makes the technique unsuitable for fast multi-focal scanning over large areas. We propose an architecture for multifocal fluorescence imaging that is scalable to large area imaging. The design is based on the concept of line scanning with continuous 'push broom' scanning. Instead of a line sensor, we use an area sensor that is tilted with respect to the optical axis to acquire image data from multiple depths inside the sample simultaneously. A multi-line illumination where the lines span a plane conjugate to the tilted sensor is created by means of a diffractive optics design, implemented on a spatial light modulator. In particular, we describe a design that uses higher order astigmatism to generate focal lines of substantially constant peak intensity along the lines. The proposed method is suitable for fast 3D image acquisition with unlimited field of view, it requires no moving components except for the sample scanning stage, and provides intrinsic alignment of the simultaneously scanned focal slices. As proof of concept, we have scanned 9 focal slices simultaneously over an area of 36 mm 2 at 0.29 µm pixel size in object space. The projected ultimate throughput that can be realized with the proposed architecture is in excess of 100 Mpixel/s.

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Filling the drug discovery gap: is high-content screening the missing link?

Cited by 23 publications

References 41 publications

Application of Image-Based High Content Analysis for the Screening of Bioactive Natural Products

Application of Image-Based High Content Analysis for the Screening of Bioactive Natural Products

Precision medicine review: rare driver mutations and their biophysical classification

Multi-line fluorescence scanning microscope for multi-focal imaging with unlimited field of view

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