Cellular Phenotyping

Cellular Phenotyping for High Throughput Screening

HL1

The BHF Centre for Cardiovascular Target Discovery currently has two high-throughput phenotyping approaches - high content imaging using a Perkin Elmer Operetta System, and a multimodal plate reader (Perkin Elmer Envision, provided through the Target Discovery Institute).

Perkin Elmer Envision Multimodal Plate Reader

The Perkin Elmer Envision multimodal plate reader allows reporter assays (luciferase, renilla, GFP), calcium measurements, FRET and BRET assays, among others.

Perkin Elmer Operetta High Content Screening Microscope

The Perkin Elmer Operetta is a 96-384 well spinning disk confocal microscopy system, that has live cell imaging capacity, automated quantitative image analysis (Harmony) and machine learning (PhenoLOGIC) software. It can perform many types of assay followed by automated image analysis -including cell cycle, apoptosis, cell shape, G-proteins, cytoskeletal reorganisation, texture, membrane texture, nuclear foci - nucleoli, neurite outgrowth, angiogenic tube formation, mitochondria mass, cytoplasmic foci – e.g. autophagosomes, colony formation, cell migration, 3D cell invasion, and protein localisation and quantification.

If you have an assay that you can perform using ordinary or confocal microscopy, we should be able to port it to the Operetta system.

Multiparametric Imaging

The image (provided by Dr Ayman Zen, Bhattacharya Group) shows HL1 cardiomyocytes stained using DAPI (nuclei), phalloidin (actin, red), and anti-tubulin antibody (green). A major goal is to develop multiparametric imaging to maximise phenotype information retrieval from high-content images such as this.

Key references for multiparametric imaging

1. Caie, P.D., Walls, R.E., Ingleston-Orme, A., Daya, S., Houslay, T., Eagle, R., Roberts, M.E. & Carragher, N.O. High-content phenotypic profiling of drug response signatures across distinct cancer cells. Mol Cancer Ther 9, 1913-26 (2010).

2. Fuchs, F., Pau, G., Kranz, D., Sklyar, O., Budjan, C., Steinbrink, S., Horn, T., Pedal, A., Huber, W. & Boutros, M. Clustering phenotype populations by genome-wide RNAi and multiparametric imaging. Mol Syst Biol 6, 370 (2010).

3. Jones, T.R., Carpenter, A.E., Lamprecht, M.R., Moffat, J., Silver, S.J., Grenier, J.K., Castoreno, A.B., Eggert, U.S., Root, D.E., Golland, P. & Sabatini, D.M. Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning. Proceedings of the National Academy of Sciences of the United States of America 106, 1826-31 (2009).

4. Collinet, C., Stoter, M., Bradshaw, C.R., Samusik, N., Rink, J.C., Kenski, D., Habermann, B., Buchholz, F., Henschel, R., Mueller, M.S., Nagel, W.E., Fava, E., Kalaidzidis, Y. & Zerial, M. Systems survey of endocytosis by multiparametric image analysis. Nature 464, 243-9 (2010).

5. Shamir, L., Delaney, J.D., Orlov, N., Eckley, D.M. & Goldberg, I.G. Pattern recognition software and techniques for biological image analysis. PLoS computational biology 6, e1000974 (2010).

Contact Details

Professor Shoumo Bhattacharya MD MSc (Biochem) FRCP FESC FMedSci

BHF Chair of Cardiovascular Medicine
Department of Cardiovascular Medicine & Wellcome Trust Centre for Human Genetics
Roosevelt Drive
Oxford
OX3 7BN

Email: shoumo.bhattacharya@well.ox.ac.uk
PA: Mrs Jan Duff
Email: jan.duff@well.ox.ac.uk

British Heart Foundation

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