Quantitative Label-Free Live Cell Imaging
Phasefocus Livecyte: high content live-cell assays from 96 wells to single cells
LiveCyte 2 - Let Every Cell Tell its Story
Stop manually tracking your cells; let Livecyte do it for you automatically.
Now you can follow every individual cell, measuring how they move and change in response to changing culture conditions.
Livecyte™ identifies up to 19 different morphological characteristics for each cell, generating a unique phenotypic fingerprint by which thousands of individual cells can be automatically tracked, even within heterogeneous cell populations.
The result is a phenomenal new depth of information, compared to HCA or standard time-lapse instruments.
Cell Growth and Proliferation
- Livecyte measures individual cell growth independently from proliferation.
- Cell growth is more complex than just cells multiplying
- They can increase in size without dividing, they can divide asymmetrically, they can grow to a certain size then stop. All these aspects of cell growth are lost with most live cell assays. Not with Livecyte.
Measure true cell growth at the single cell level
- Directly measure cell motility with individual cells
- Separate out migration from proliferation in a single experiment
- Observe differences between leading edge and following cells
- Correlate motility to morphological differences
Go beyond traditional wound healing assays
- Livecyte automatically tracks cells, even in a 96-well plate.
- Just seed your cells, monitor with Livecyte and a full range of cell migration parameters will be generated.
- Compare the speed, directionality, confinement and heterogeneity of different populations.
Automatically measure cell motility without a scratch wound assay
- Directly measure mitotic time with individual cells
- Measure random and chemotactic migration
- Identify and characterise differences in subpopulations in heterogenous primary cultures
- Correlate motility to morphological differences
- Generate statistically valid results from multiple repeats in 96-wells.
Automatically measure the morphology and motion of every cell
- True label-free cell count, not just confluence
- Monitor dry mass to automatically determine viability and cell death
- Statistically robust results from multiple repeats in 96-well plates
- Generate label-free dose-response curves
Identify dynamic toxic responses missed by other methods
Go beyond confluence-based toxicity assays
- Label-free timelapse tube formation assays
- High-resolution large fields-of-view with no stitching
- Perform assays on Matrigel and standard plates
- Automated post-acquisition focus ensures consistent image quality for every well
- Simple, yet powerful analysis of tube formation metrics with Application Dashboard outputs
Automated analysis to determine tube length, formation, diameter etc
- Identify morphological phenotypes
- Watch and quantify cell differentiation
- Monitor stem cell populations, for many days, without perturbing cell behaviour
- Image through plastic and coated plates
- Image on extracellular matrices
- Cells are still viable after imaging
Obtain quantitative measurements without perturbing your cells
- Mitotic Time
- Mitotic Exit
- Mitotic Exit Half Life
- Total Mitotic Cells
- Normalised Cell Count
- Cumulative Mitotic Exit Failure Index
- Cumulative Mitotic Exit Failure Index End
- Mitotis Cell Tracks
- Multi-panel Video
- Median Cell Dry Mass
- Median Cell Area
- Median Cell Perimeter
- Median Length Width Ratio
- Median Cell Sphericity
- Multi-panel Video
- Start Cell Count
- Start Dry Mass
- Start Confluency
- Normalised Cell Count
- Normalised Dry Mass
- Cell Doubling Time
- Dry Mass Doubling Time
- Multi-panel Video
- Start Cell Count
- Start Confluency
- Meandering Index
- Speed Distribution
- Mean Velocity
- Multi-panel Video
- Scratch Area (Start and End of Time-lapse)
- Relative Scratch Area
- Half Life
- Collective Migration
- Multi-panel Video
- Fully automated Brightfield, Ptychographic QPI and Fluorescence modalities.
- 6 position objective turret — range of objectives available.
- Lateral Resolution — 0.4 µm.
- Axial Resolution — Typically 40 nm.
- Illumination Power QPI — 0.4uWmm2.
- Detector — sCMOS air cooled (2000X2000). Pix Size—6.5 µm.
- Temperature controlled macro-environment (adjustable from 28 oC—40 oC).
- Micro-environment controlling CO2, humidity and evaporation.
- Design Module.
- Acquire Module.
- Analyse Module.
- Application Specific Dashboards.
- Acquisition PC.
- PiBOX (reconstruct QPI data).
- CatBOX (analysis of data).
- NAS (Storage solution offering 12 TB of data—optional upgrades available).
- Bench space required: 1600 mm X 800 mm.
- Height above bench: 750 mm.
- Under bench space for rack: 700 mm X 600 mm X 800 mm.
No specialised optical table (anti-vibration) is required.
Automatically separate the effects of cell proliferation, experimental setup and types of cellular motion on the outcome of a scratch wound assay. The Livecyte Kinetic Cytometer produces single-cell motility parameters for all cells surrounding the wound, giving additional insights as to why a wound has closed faster.
Effects of far-red fluorescent labelling and LED irradiation on cell behaviour during long-term time-lapse microscopy using a Livecyte Kinetic Cytometer.
Automatically measure single-cell random motility parameters from live cell populations in formats up to 96-well plates with the Livecyte Kinetic Cytometer.
Use non-invasive time-lapse imaging to quantify cell death without labels, dyes or phytotoxic damage.
Go beyond traditional wound healing assays with the Phasefocus Livecyte.
Monitor continuously the mitotic index of a cell population in a non-invasive manner.
Produce a Staurosporine dose response curve without use of fluorescent labels.
Delve deeper into the dynamics of cell proliferation through non-invasive time-lapse imaging with the Livecyte system.
Measurement of mitotic time is important to numerous fields of cell biology and has uses in the development of anti-mitotic cancer drugs. Typically, manual methods are employed to identify mitotic events, track through cell division and record mitotic time.
Analyse and extract morphological and dynamic phenotypes to identify heterogeneity within mixed cancer cell populations.
A case study to demonstrate how analysis of a population to an individual cell level can reveal subtle differences in cell behaviour that would be unresolved by a population averaged approach.
Determine the lateral and axial resolution of a quantitative phase imaging (QPI) system.
Reveal morphological and dynamic phenotypic behaviour of your cells automatically and quickly by employing a robust seed point detection approach.
How the optical volume measured by Livcyte is related to the actual volume of a cell.
Utilise an adaptive algorithm to correct for the dynamic evolution of the fluid meniscus.
"Nanoparticles carrying fingolimod and methotrexate enables targeted induction of apoptosis and immobilization of invasive thyroid cancer". Niemela, E. et al. ELSEVIER, (2020). doi: 10.1016/j.ejpb.2019.12.015
"The clock gene Bmal1 inhibits macrophage motility, phagocytosis, and impairs defense against pneumonia". Kitchen, G. B. et al. PNAS, (2020). doi: 10.1073/pnas.1915932117
"Melanoma mutations modify melanocyte dynamics in coculture with keratinocytes or fibroblasts". Škalamera, D., Stevenson, A. J., Ehmann, A., Ainger, S.A., Lanagan, C., Sturm, R.A., Gabrielli, B., Journal of Cell Science (2019). doi:10.1242/jcs.234716
"Phospholipase D2 in prostate cancer: protein expression changes with Gleason score". Noble, A.R., Hogg, K., Suman, R. et al. Br J Cancer (2019) doi:10.1038/s41416-019-0610-7
"Assessing the Advantages, Limitations and Potential of Human Primary Prostate Epithelial Cells as a Pre-Clinical Model for Prostate Cancer Research". Frame FM, Noble AR, O'Toole P, Marrison J, Godden T, O'Brien A, Maitland NJ. Advances in Experimental Medicine and Biology; Vol 1164, 109-118. (2019). doi: 10.1007/978-3-030-22254-3_9
"Airway remodeling disease: primary human structural cells and phenotypic and pathway assays to identify targets with potential to prevent or reverse remodeling". Rosethorne EM, Charlton SJ. J Exp Pharmacol. 2018;10:75–85. (2018). doi:10.2147/JEP.S159124
"Rho Kinase Inhibition by AT13148 Blocks Pancreatic Ductal Adenocarcinoma Invasion and Tumor Growth". Nicola Rath, June Munro, Marie Francene Cutiongco, Alicja Jagiello, Nikolaj Gadegaard, Lynn McGarry, Mathieu Unbekandt, Evdokia Michalopoulou, Jurre J. Kamphorst, David Sumpton, Gillian Mackay, Claire Vennin, Marina Pajic, Paul Timpson and Michael F. Olson. Cancer Res (2018) (78) (12) 3321-3336; DOI: 10.1158/0008-5472.CAN-17-1339
“Tumor heterogeneity and therapy resistance - implications for future treatments of prostate cancer”, Fiona M. Frame, Amanda R. Noble, Sandra Klein, Hannah F. Walker, Rakesh Suman, Richard Kasprowicz, Vin M. Mann, Matt S. Simms, Norman J. Maitland. J Cancer Metastasis Treat (2017);3:302-14 http://jcmtjournal.com/article/view/2312
"Characterising live cell behaviour: Traditional label-free and quantitative phase imaging approaches", Richard Kasprowicz, Rakesh Suman and Peter O’Toole. https://doi.org/10.1016/j.biocel.2017.01.004
“Label free imaging to study phenotypic behavioural traits of cells in complex co-cultures,” Rakesh Suman, Gabrielle Smith, Katryn E.A. Hazel, Richard Kasprowicz, Mark Coles, Peter O’Toole, and Sangeeta Chawla. Rep. 6, 22032; doi: 10.1038/srep22032 (2016)
“Ptychography – a label free, high-contrast imaging technique for live cells using quantitative phase information,” Joanne Marrison, Lotta Räty, Poppy Marriott, and Peter O’Toole, Nature Scientific Reports 3, 2369 (2013) http://dx.doi.org/10.1038/srep02369
“Quantitative phase contrast optimised cancerous cell differentiation via ptychography,” Daniel Claus, Andrew M. Maiden, Fucai Zhang, Francis G. R. Sweeney, Martin J. Humphry, Hermann Schluesener, and John M. Rodenburg , Optics Express 20, 9911-9918 (2012). http://dx.doi.org/10.1364/OE.20.009911
“A Novel Method For Measuring Contraction Of Primary Human Airway Smooth Muscle Cells,” Eric Dubuis , Maria G. Belvisi, Sepideh Poushpas , Pauline Flajolet , Kevin Langley , and Mark A. Birrell,” American Thoracic Society International Conference Abstracts A28, (2015). http://www.atsjournals.org/doi/abs/10.1164/ajrccm-conference.2015.191.1_MeetingAbstracts.A1224
“Aberrant Phenotype in Human Endothelial Cells of Diabetic Origin: Implications for Saphenous Vein Graft Failure?” Anna C. Roberts, Jai Gohil, Laura Hudson, Kyle Connolly, Philip Warburton , Rakesh Suman , Peter O’Toole, David J. O’Regan, Neil A. Turner , Kirsten Riches, and Karen E. Porter, Journal of Diabetes Research Volume 2015 (2015), Article ID 409432, http://dx.doi.org/10.1155/2015/409432
“Ptychography: use of quantitative phase information for high-contrast label free time-lapse imaging of living cells,” Rakesh Suman, and Peter
O'Toole, Proc. SPIE 8947, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XII, 89471Z (2014) http://dx.doi.org/10.1117/12.2037670
“Ptychography: A powerful phase retrieval technique for biomedical imaging,” Daniel Claus, Hermann Schluesener, Andy Maiden, Fucai Zhang, Francis Sweeney, Martin Humphry, and John Rodenburg, SPIE 8947, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XII, 89471Z (2014)
“Phase calibration target for quantitative phase imaging and ptychography”, T. M. Godden, A. Muniz-Piniella, J. D. Claverley, A. Yacoot, and M. J Humphry. Optics Express 24, (2016).
“Reciprocal-space up-sampling from real-space oversampling in x-ray ptychography,” D. J. Batey, T. B. Edo, C. Rau, U. Wagner, Z. D. Pešić, T. A. Waigh, and J.M.Rodenburg, Rev. A 89, 043812 (2014). http://dx.doi.org/10.1103/PhysRevA.89.043812
“Ptychographic transmission microscopy in three dimensions using a multi-slice approach,” A. M. Maiden, M. Humphry, and J. Rodenburg, JOSA A 29, 1606-1614 (2012). http://dx.doi.org/10.1364/JOSAA.29.001606
“Ptychographic microscope for three-dimensional imaging,” T. M. Godden, R. Suman, M. J. Humphry, J. M. Rodenburg, and A. M. Maiden, Optics Express 22, 12513-12523 (2014). http://dx.doi.org/10.1364/OE.22.012513
“Superresolution imaging via ptychography,”A. M. Maiden, M. J. Humphry, F, Zhang, and J. M. Rodenburg, Opt. Soc. Am. A. 28, 604-612 (2011). http://dx.doi.org/10.1364/JOSAA.28.000604
“A new method of high resolution, quantitative phase scanning microscopy,” A. M. Maiden, J. M. Rodenburg, and M. J. Humphry, Proc. of SPIE 7729, 77291I-77291I-8 (2010). http://dx.doi.org/10.1117/12.853339
“Optical ptychography: A practical implementation with useful resolution,” A. M. Maiden, J. M. Rodenburg, and M. J. Humphry, Optics Letters 35, 2585-2587 (2010). http://dx.doi.org/10.1364/OL.35.002585
“Influence of thick crystal effects on ptychographic image reconstruction with moveable illumination,” C. Liu, T. Walther, and J. M. Rodenburg, Ultramicroscopy 109, 1263-1275 (2009). http://dx.doi.org/10.1016/j.ultramic.2009.05.017
“An improved ptychographical phase retrieval algorithm for diffractive imaging,” A. M. Maiden, and J. M. Rodenburg, Ultramicroscopy 109, 1256-1262 (2009). http://dx.doi.org/10.1016/j.ultramic.2009.05.012
“Information multiplexing in ptychography,” Darren J. Batey, Daniel Claus, and John M. Rodenburg, Ultramicroscopy 138, 13–21 (2014). http://dx.doi.org/10.1016/j.ultramic.2013.12.003
“Separation of three-dimensional scattering effects in tilt-series Fourier ptychography,” Peng Li, Darren J. Batey, Tega B. Edo, and John M. Rodenburg, Ultramicroscopy 158, 1–7 (2015). http://dx.doi.org/10.1016/j.ultramic.2015.06.010
“A phase retrieval algorithm for shifting illumination,” J. M. Rodenburg and H. M. L. Faulkner, Appl. Physics Lttrs 85, 4795-4797 (2004). http://dx.doi.org/10.1063/1.1823034
“An annealing algorithm to correct positioning errors in ptychography,” A. M. Maiden, M. J. Humphry, M. C. Sarahan, B Kraus, and J. M. Rodenburg, Ultramicroscopy 120, 64-72 (2012). http://dx.doi.org/10.1016/j.ultramic.2012.06.001
“Transmission Diffractive Microscopy Without Lenses at Visible, X-ray and Electron Wavelengths,” J. Rodenburg, A. Maiden, D. Batey, F. Sweeney, T. Edo, A. Hurst, F Hüe, P. Midgley, P. Wang, A. Kirkland, and M. Humphry, Microscopy and Microanalysis 17(S2), 1058 – 1059 (2011). http://dx.doi.org/10.1017/S1431927611006167
“Ptychography: A novel phase retrieval technique, advantages and its application,” D. Claus, M. Maiden, F. Zhang, A. Hurst, T. Edo, F. Sweeney, J. M. Rodenburg, H. Schluesener, and M. J. Humphry, Proceedings of SPIE 8001, The International Society for Optical Engineering 800109 (2011). http://dx.doi.org/10.1117/12.893512
The Livecyte™ system calculates the phase delay induced in the illumination light to extract a suite of information about your cells’ behaviour over time. The phase delay is represented as high contrast label free, quantitative images, which enables the behaviour of your cell population to be analysed right down to a single cell level. Combined with the time course ability, Livecyte enables a vast array of metrics to be calculated and combined to perform a number of applications such as true proliferation, advanced scratch wound, cell motility, chemotaxis and many more. Livecyte can also perform correlative fluorescence and brightfield imaging.
The Livecyte system utilises the technique of Ptychography to solve the phase problem in optics. Images representative of the phase delay (differences in relative optical path differences) can be constructed to produce high contrast quantitative images. The phase data is extracted from the reconstructed wavefront. The reconstructed wavefront can be propagated mathematically to focus your cells post acquisition, therefore the technique is not sensitive to focal drift, or any differences in focal positions across a well plate.
The continuous single cell segmentation can be utilised to categorise heterogeneous cell populations at every time point. Population scatter graphs (similar to those produced by flow cytometers) can be produced for every time point on the exact same population of cells. Livecyte allows a far more efficient (cost, time) and refined representation of the cell population. Livecyte also produces a time-lapse video to compliment the data, which allows the user to interpret, mine and validate their data.
Traditional imaging is dependent on light scatter and/or absorption from the sample in order to produce contrast in the image. Cells are essentially transparent, so contrast is enhanced either by optical considerations (phase contrast, DIC), or by the addition of fluorescent labels. These techniques have inherent disadvantages when applied to live cells such as optical artefacts (individual cells are difficult to segment and track), risk of phototoxic damage and introduction of additional parameters into the experimental setup. These disadvantages will introduce a level of uncertainty into the final outcome of your experiment.
Livecyte measurement is non-invasive (no labels required nor photo toxic effects on cells) and as such can be carried out over a long period of time on live sensitive cells. The ability to examine your data on the single cell level gives more refinement to your data. The non-invasive measurement makes Livecyte ideal for work on primary cells, neural cells and stem cells.
The nature of the technique also allows the areas of investigation larger than the field of view of the objective lens. Further to this it also allows for rectangular shaped regions to be measured (ideal for scratch wound assays), without the need for any image stitching and subsequently any image processing artefacts that may deteriorate the quality of your data.
In addition, due to the nature of the data collected, it is possible to automatically focus your sample post acquisition. This ensures that the microscope is not sensitive to focal drifts during a long term time lapse, or differing focus positions across an entire well plate.
Phase contrast induces an additional phase delay to scattered light in order to increase the contrast between your cells and the background. Livecyte produces images, which due to their nature are inherently high contrast. In phase contrast, the contrast is far lower than the Livecyte images. In addition, phase contrast images are not optically quantitative (thickness measurements cannot be extracted). Phase contrast images also contain well known diffraction effects (such as halos around scattering objects), which limit the downstream analysis that can be applied to the data.
The high contrast Livecyte images enables single cell segmentation to be robustly applied and as such you are not limited to an estimate of cell behaviour based on assumptions from some form of population analysis. In combination with the quantitative nature, Livecyte can build a fingerprint for each individual cell and subsequently each individual cell can be tracked throughout a time course.
Livecyte is a complete imaging and analysis time lapse system. Cells are supported in the custom designed Phasefocus™ POD (which ensures uniform CO2 delivery to the entire plate) within an incubation environment, which maintains a constant temperature of 37 oC. The nature of the illumination required for phase imaging (very low power red laser (650 nm, with power output of 0.1 mW) ensures that the risk of the measurement technique perturbing the natural behaviour of the cells is at an absolute minimum, even during a long term time lapse. Since the cells are not perturbed during the experiment they can be reused after measurement.
Cells can be imaged for a number of weeks if a media change can be incorporated.
Without incorporating a media change, we have been able to image Hippocampal cells for 7 days, capturing an image every 6 minutes, with the cells remaining viable at the end of this period.
The quantitative nature of the images refers to the fact that the intensity values in the image contain information relating the phase delay experienced by the light passing through the sample. This allows information representative of the thickness of your cell to be extracted. This enables relative changes in volume of cells to be investigated over time and/or compared across your experiment. It also provides Livecyte with an additional parameter to ‘finger print’ each individual cell, which aids in the robust tracking of individual cells throughout an entire time-lapse.
Biological context: What cell parameters does dry mass measure?
Dry mass is the summed mass of all cellular components (e.g. biomolecules such as proteins, lipids, carbohydrates, DNA, etc.), excluding water. As such, the dry mass measurement is an accurate measure of cell size; accounting for the extent of biosynthetic and degradative processes in addition to uptake and expulsion material by the cell. Thus, the growth of an individual cell, defined as a change in cell size over time, can be monitored by measuring changes in a cell’s dry mass over time. For a population of cells, the sum of the dry mass is a useful measure to enumerate the combined growth and proliferation rate of the population.
How dry mass is measured by quantitative phase imaging:
The pixel intensity of the quantitative phase image relates to the extent of phase delay. The phase delay information captured within our images can be directly converted to dry mass using the equation below. This equation makes use of a constant refractive increment (α= 1.8 × 10–4 m3/kg), which is a mean of the tight range of specific refractive increments measured for biomolecules that predominate cell composition. Typically, however, the specific value of α is not critical as normalisation is performed to compare the rate of change of dry mass between treatments.
The standard measure is percentage closure; comparing the initial area of the wound at time T=0 and measuring the time taken to fully close.
As Livecyte is continuously tracking the cells, additional metrics can also be captured including the half-life of the wound, i.e. the time taken to close the wound by 50%.
Also, by looking at individual cells, we can assess their speed and directionality to establish how the wound is closing, the rate of closure and why the wound may be closing more quickly.
There are a number of factors to consider when making a scratch. Uniform cell confluence and making the scratch perpendicular to the well will improve consistency. Some scientists also use the edge of the plate as a guide when making the scratch.
Livecyte automatically detects the leading edge, allowing the size and shape of the wound at T=0 to be determined. This means that the wound is being continuously monitored as it closes, so the evolution of the wound can be tracked over time.
Traditionally, when looking at scratch migration, the focus tends to be on how fast the front of the cells are moving to close the scratch, but that’s only one aspect of the biology of how cells move to close the wound.
When the epithelial front is injured, you get a wave travelling away from the front of the edge of the scratch that alerts the cells further back to become activated and start migrating in order to close the scratch. These cells need to change their cell phenotype and adhesion properties. Therefore, breaking down the front based on where the cells are located relative to the leading edge, we can start to understand how the cells are changing their phenotype in a collective manner.
Livecyte is an automated easy-to-use system. Therefore, minimum training is required. The system is also cell friendly so minimum perturbation is experienced by the cells. The nature of the data also ensures that an entire suite of information can be extracted at every time point. Therefore, it is highly suitable for limited cell lines and /or sensitive cell lines, as the information rich data produced ensures that a vast suite of metrics can be extracted to accurately describe the behaviour of your cells over time. Therefore, Livecyte is efficient in terms of cost and time.
Livecyte has the ability to acquire fluorescent images of your sample and automatically overlay these on your phase images. Livecyte comes equipped with 3 filter cubes as standard (optimised for DAPI, FitC and TxRED), but also has the scope for an additional four to be added.
Fluorescence is envisaged as a validation step, to verify specific features/processes visualised during the phase imaging. All precautions are in place to minimise the risk of phototoxic damage while utilising the fluorescence modality. For example, phase imaging can be used to extract the kinetic behaviour of the individual cell, while less frequent fluorescence data can be acquired to validate any specific process.
The spatial resolution of the images produced is ultimately limited by the resolution of the objective used in the measurement. Due to the increased contrast in the images produced by Livecyte, smaller sample features are more discernible than in the intensity/bright-field image. For a 40X measurement the spatial resolution is in the order is approximately 0.6 µm.
The depth resolution (z resolution) of the measurement is ultimately limited by the difference in refractive index between the cell and media. This can range from tens of nanometres to 1 µm (typically 40 nm).
Livecyte has default settings for a small, medium and large FOV, with the largest measuring 2 mm x 2 mm. However, users can define their own area of interest, up to the size of the whole well, if required. The size of the FOV will impact on the speed and amount of data that can be captured.
The shape of the FOV can be adjusted to a rectangular format, allowing the users to follow more of the area of interest. This is particularly useful in scratch wound analysis, permitting the user to image the whole of the wound.
The data produced from the Livecyte system is a native format to the CAT Analysis software (containing both intensity and phase images and a database file). However, a variety of export workflows are readily supported include exporting to ImageJ and Microsoft Excel compatible formats, as well as a variety of other common image and video formats.
The Livecyte system is a complete automated imaging and analysis system. It includes all you need to support your cells long term (incubation, C02 POD and all inserts to support various plate types, objectives [4X, 10X, 20X, 40X]), and produce information rich images. The system also includes CAT (Cell Analysis Toolbox™) to provide the necessary tools for you to perform the required analysis in an easy to use and highly intuitive suite of software. The system also supports fluorescent imaging and you will be provided with 3 fluorescent cubes (RGB), as well as LED illumination, to perform fluorescence imaging. The system comes with 12TB of storage as standard (sufficient for 3 months of support). There are no hidden or additional costs. Full training and support is included.
The following plates have been routinely tested on the Livecyte system:
- 35 mm dishes (WPI, glass-bottomed Fluorodish [Item#: FD35-100]; ibidi 35 mm dishes (glass or ibiTreat))
- Ibidi µ-slides and flow chambers (e.g. ibidi µ-slide I; ibidi 4 well µ-slide Ph+; ibidi µ-slide VI 0.4)
- 6 well plates (Corning Costar plastic 6 well, individually wrapped [Item#: 3516]; or [Item#: 3506];
- Cellvis 6 well glass bottomed plates [Item#: P06-1.5H-N])
- 12 well plates (Corning Costar plastic 12 well, individually wrapped [Item#: 3513])
- 24 well plates (Cellvis 24 well glass bottomed plates [Item#: P24-1.5H-N])
- 96 well plates (Corning Costar plastic 96 well, individually wrapped [Item#: 3603]; Greiner Screenstar
- 96 well plate [Item#: 655 866]; Cellvis 96 well glass bottomed plates [Item#: P96-1.5H-N])
- Corning Costar 96 Well Cell Culture Cluster. Flat bottom with low evaporation lid. Individually wrapped. Cat# 3595
However, you can also use other suppliers for glass-bottom plates and most individually wrapped
HCS (optical quality) plastic types.
Measurements can be performed on a number of coatings included matrigel, agarose, cell derived matrix and fibronectin.
- Timelapse scratch wound assays (recent example: 12 well plastic plate containing breast cancer cells (wt and point mutation) scratched with P200 tip, media added containing one of two different drugs).
- Label-free cytotoxicity assays (recent example: 96 well HCS plate containing prostate cancer cells treated with a range of concentrations of an inhibitor–cytostatic effects of drug and cell death measured over 24 h).
- Random motility assays (recent example: renal cell carcinoma line plated in a 6 well plate and treated with a positive control and test candidate drug, individual cells tracked, speed measured, positive control gave change in cell speed whilst test candidate did not – assay only needed 5 h imaging duration).
- Phenotyping heterogeneous responses in primary cells (recent example: primary prostate cancer cells examined in random motility assay, able to discriminate between different cell sub-populations using unique QPI metrics (e.g. dry mass), morphometrics and dynamic behaviour).
- Assays measuring effects on mitosis (recent example: effect of a drug on mitotic time in a cervical carcinoma cell line; effect of a drug upon the percentage of cervical carcinoma cells that stall in mitosis and those that fail during cytokinesis).
- Phagocytosis assays (recent example: correlating the uptake of fluorescent bacteria by individual cells to their speed and roaming).
- Angiogenesis assays (recent example: measuring the extent of tube formation for HUVEC cells plated on Matrigel in response to different ligands).
- Lineage determination (recent example: measuring the differences in motility, cell cycle time and lineage of wt and cripsr stem cells).
Chemotaxis assays (currently using ibidi chemotaxis slides to address chemotactic response of macrophages towards novel chemoattarctants).
For any inquiries, please contact us, we are happy to help! Email: firstname.lastname@example.org
A label-free high-content system
Livecyte changes what's possible to measure using live cell assays
- Livecyte produces exceptionally high contrast time-lapse videos using Phasefocus’s patented Ptychographic quantitive phase imaging (QPI) technology for a range of label-free assays with or without up to seven channels of complementary fluorescence.
- Automated single-cell tracking of even the most sensitive cells quickly reveals subtle phenotypic differences in unperturbed cell populations.
- Easy-to-use dashboards present coherent and concise results from up to 96 wells at a time whilst retaining the ability to investigate individual cell behaviour and outlying characteristics.
High Contrast Without Compromise
Fluorescence-like images without the compromise.
Livecyte's label-free imaging eliminates the constraints of phototoxicity and population averaged analysis, providing a more accurate and realistic account of treatment driven changes in cell behaviour.
Avoid the fluorescence paradox of added cost and perturbed cells. Livecyte easily produces high resolution, high contrast images from which individual cells can be readily defined and tracked for prolonged periods.
Powerful Integrated Analysis
- Integrated analysis suite enables cell behaviour to be monitored as a function of treatment
- Easily export results in Excel and Graphpad formats
- Monitor many different types of behaviour, from morphological to motile, in every experiment
- No need for multiple separate experiments
From assay level....
Down to single cell level...
Livecyte is a True Assay-Driven Tool
No Calibration, No Dedicated Consumables, No Hidden Costs.
Good science requires multiple repeats and comparisons across several treaments.
Using multi-well plates is the only way to do this efficiently and cost-effectively.
Livecyte's unique meniscus compensation and perfect focus technologies make it simple to automatically perform robust label-free assays within any standard plate, up to 96 wells.
Livecyte's patented technology uses a quantitative phase imaging (QPI) technique known as Ptychography. Phasefocus was awarded a Microscope Today Innovation Award in 2013 for the technology, and won a second award in 2017 for Livecyte itself.
In 2018, researchers from Cornell University set the Guinness World Record for the highest resolution microscope using Ptychography on an Electron Microscope.