Phenotypic assays

    Cell Viability

    Viability assays are important methods in neuroscience, oncology and other fields, and are among our most requested services. The effects of compound libraries, newly developed modulator compounds, drug combinations or RNAi knockdown on specific cell-based disease models can be determined.

    A wide range of viability assays are available. Some assays measure ATP levels (figure A, a single synergy analysis graph extracted from a multiple cell line multi-drug combination screen), others measure the reducing capacity of cells (e.g. WST-type assays) or the release of cytoplasmic markers such as LDH (B) in cell culture wells with a plate reader. Yet others evaluate cell and tissue membrane permeability (C, organohippocampal slice culture shown, see ref 2) and/or nuclear morphology with imagers and/or plate readers. Examples of dual PI/LDH analyses can be found in reference 1. Figure D below zooms in on sub-field from a single well in a multiplate 384 well assay for caspase activation in primary neuronal culture (red indicates activated caspase is present, yellow/green shows it is not).

    Contact: Michael Courtney (michael.courtney [at] utu.fi)

    References

    1. Li LL, Ginet V, Liu X, Vergun O, Tuittila M, Mathieu M, Bonny C, Puyal J, Truttmann AC, Courtney MJ (2013) The nNOS-p38MAPK pathway is mediated by NOS1AP during neuronal death. J Neurosci. 33, 8185-8201. doi: 10.1523/JNEUROSCI.4578-12.2013 PMID: 23658158
    2. Li LL, Melero-Fernandez de Mera RM, Chen J, Ba W, Nadif Kasri N, Zhang M, Courtney MJ (2015) Unexpected Heterodivalent Recruitment of NOS1AP to nNOS Reveals Multiple Sites for Pharmacological Intervention in Neuronal Disease Models. J Neurosci. 35, 7349-7364. doi: 10.1523/JNEUROSCI.0037-15.2015 PMID: 25972165
    3. Li LL, Cisek K, Courtney MJ (2017) Efficient Binding of the NOS1AP C-Terminus to the nNOS PDZ Pocket Requires the Concerted Action of the PDZ Ligand Motif, the Internal ExF Site and Structural Integrity of an Independent Element. Front. Mol. Neurosci. 10:58. doi: 10.3389/fnmol.2017.00058. PMID: 28360833.
    4. Melero-Fernandez de Mera RM*, Li LL*, Popinigis A, Cisek K, Tuittila M, Yadav L, Serva A, Courtney MJ (2017) A simple optogenetic MAPK inhibitor design reveals resonance between transcription-regulating circuitry and temporally-encoded inputs. (*equal contribution) Nat. Commun. 8, 15017. doi: 10.1038/ncomms15017. PMID: 28497795.

    Organotypic 3D Cell Culture Models

    We offer a unique screening pipeline (Figure below), specifically tailored for the needs in early stage drug discovery. Our organotypic 3D cell culture models specifically address the complex biology of human tissues, and recapitulate histology and morphologic features. We offer expert services in cancer invasion, but address many phenotypic features of normal & disease tissues. Apart from 200+ cell lines, we work with primary, patient-derived cells.

    The organotypic 3D models includes important elements found in real tissues, e.g. tumor microenvironment (e.g. stromal or connective tissue cells), and matrix, both needed for the formation of tissue architecture. Microtissues form spontaneously from a small number of cells, seeded between two layers of biologically relevant extracellular matrix. Relevant tissue structures can be generated from small numbers of cells. Heterogeneous cell populations, typical for human cancers, can be quantitatively addressed. Despite considerable complexity, our platform is miniaturized and standardized. This allows rapid chemo-sensitivity tests and screening campaigns; and enables significant experimental throughput without simultaneously sacrificing the high level of biological significance that can be offered.

    Contact: Malin Åkerfelt (malin.akerfelt [at] utu.fi)
    For more information visit the HCSLab website

    References

    1. Ahonen I, Åkerfelt M, Toriseva M, Oswald E, Schuler J, Nees M. A high-content image analysis approach for quantitative measurements of chemosensitivity in patient-derived tumor microtissues. Sci Rep 2017; 7:6600.
    2. Björk JK, Åkerfelt M, Joutsen J, Puustinen MC, Cheng F, Sistonen L# and Nees, M#. Heat-shock factor 2 is a suppressor of prostate cancer invasion. Oncogene 2016; 35: 1770-84.
    3. Åkerfelt M, Bayramoglu N, Robinson S, Toriseva M, Schukov H-P, Virtanen J, Härmä V, Kaakinen M, Kannala J, Eklund L, Heikkilä J, and Nees M. Automated tracking of tumor-stroma morphology in microtissues identifies targets within the tumor microenvironment for therapeutic intervention. Oncotarget 2015; 6: 30035-56.
    4. Robinson S, Guyon L, Nevalainen J, Toriseva M, Åkerfelt M and Nees M. Segmentation of image data from complex organotypic 3D models of cancer tissues using Markov random fields. Plos One 2015; 10: e0143798.
    5. Härmä V, Schukov H-P, Happonen A, Ahonen I, Virtanen J, Siitari H, Åkerfelt M, Lötjönen J and Nees M. Quantification of dynamic morphological drug responses in 3D organotypic cell cultures by automated image analysis. Plos One 2014; 9: e96426.

    Small Animal Models

    We also offer opportunities to record changes to cells with small animal models such as C.elegans as shown (see Lehtonen et al., 2016).

    We are currently establishing high-throughput imaging assays for monitoring behaviour of zebrafish larvae (<5 dpf) in collaboration with the zebrafish core facility at the Turku Centre for Biotechnology. Our long-term capacity is being increased from 3 x 96 well plates imaged simultaneously. Time-projection data from sample 6 wells (only single larvae in each well, movement is visualised by the appearance of larvae in multiple positions) are shown below as an example. Larvae can be exposed to reagents and libraries and/or physiological stimulus such as a flash of light, and behaviour is analysed by automated image analysis.

    Contact: Michael Courtney (michael.courtney [at] utu.fi)

    References

    Lehtonen Š, Jaronen M, Vehviläinen P, Lakso M, Rudgalvyte M, Keksa-Goldsteine V, Wong G, Courtney MJ, Koistinaho J, Goldsteins G. Inhibition of Excessive Oxidative Protein Folding Is Protective in MPP(+) Toxicity-Induced Parkinson‘s Disease Models. Antioxid Redox Signal. 2016 Sep 10;25(8):485-97. doi:10.1089/ars.2015.6402. Epub 2016 Jun 15. PubMed PMID: 27139804.

    Image Analysis and Quantification

    Our phenotypic screening pipeline is based on live cell imaging, where we use live cell dyes to stain cells and organoids. Confocal microscopy is used for imaging of different structures and morphologies. The Automated Morphometric Image Data Analysis software AMIDA, allows segmentation and quantitative measurements of large numbers of images and structures, with a multitude of different cell or organoid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization.

    Contact: Malin Åkerfelt (malin.akerfelt [at] utu.fi)
    For more information visit the HCSLab website

    References

    1. Ahonen I, Åkerfelt M, Toriseva M, Oswald E, Schuler J, Nees M. A high-content image analysis approach for quantitative measurements of chemosensitivity in patient-derived tumor microtissues. Sci Rep 2017; 7:6600.
    2. Åkerfelt M, Bayramoglu N, Robinson S, Toriseva M, Schukov H-P, Virtanen J, Härmä V, Kaakinen M, Kannala J, Eklund L, Heikkilä J, and Nees M. Automated tracking of tumor-stroma morphology in microtissues identifies targets within the tumor microenvironment for therapeutic intervention. Oncotarget 2015; 6: 30035-56.
    3. Robinson S, Guyon L, Nevalainen J, Toriseva M, Åkerfelt M and Nees M. Segmentation of image data from complex organotypic 3D models of cancer tissues using Markov random fields. Plos One 2015; 10: e0143798.
    4. Härmä V, Schukov H-P, Happonen A, Ahonen I, Virtanen J, Siitari H, Åkerfelt M, Lötjönen J and Nees M. Quantification of dynamic morphological drug responses in 3D organotypic cell cultures by automated image analysis. Plos One 2014; 9: e96426.