Fluorescence microscopy is a core method for visualizing and quantifying the spatial and temporal dynamics of complex biological processes. While many fluorescent microscopy techniques exist, due to its cost-effectiveness and accessibility, widefield fluorescent imaging remains one of the most widely used. To accomplish imaging of 3D samples, conventional widefield fluorescence imaging entails acquiring a sequence of 2D images spaced along the z-dimension, typically called a z-stack. Oftentimes, the first step in an analysis pipeline is to project that 3D volume into a single 2D image because 3D image data can be cumbersome to manage and challenging to analyze and interpret. Furthermore, z-stack acquisition is often time-consuming, which consequently may induce photodamage to the biological sample; these are major barriers for workflows that require high-throughput, such as drug screening. As an alternative to z-stacks, axial sweep acquisition schemes have been proposed to circumvent these drawbacks and offer potential of 100-fold faster image acquisition for 3D-samples compared to z-stack acquisition. Unfortunately, these acquisition techniques generate low-quality 2D z-projected images that require restoration with unwieldy, computationally heavy algorithms before the images can be interrogated. We propose a novel workflow to combine axial z-sweep acquisition with deep learning-based image restoration, ultimately enabling high-throughput and high-quality imaging of complex 3D-samples using 2D projection images. To demonstrate the capabilities of our proposed workflow, we apply it to live-cell imaging of large 3D tumor spheroid cultures and find we can produce high-fidelity images appropriate for quantitative analysis. Therefore, we conclude that combining axial z-sweep image acquisition with deep learning-based image restoration enables high-throughput and high-quality fluorescence imaging of complex 3D biological samples.
The tumor-associated extracellular matrix (ECM) provides critical biochemical micro-environment cues, as well as an essential structural scaffold, for solid tumors to survive and grow (see Pickup et al. 2014 for review). With a view to enabling more translational and turnkey 3D in vitro assays for cancer biology, we have developed and optimized techniques for seeding, growing and automatically quantifying the properties of multiple tumor spheroids in ECMs in 96-well format using real-time live-cell analysis. Matrigel (Corning) was dispensed across a range of volumes (20 - 50 μL) and concentrations (1 - 5 mg mL-1) into flat-bottomed 96-well TC micro-plates to form a solidified base layer. Tumor cells (A549, MCF-7, SKOV-3, MDA-MB-231) were seeded on top (1 - 2K cells per well), and in some experiments a full ECM sandwich was created by addition of a further volume of Matrigel (2 - 25%, 0.2 - 5 mg mL-1). Using a custom autofocusing method, phase contrast, bright-field and fluorescence images (10x) were captured every 6h for 7 days from within the cell incubator (IncuCyte S3 live-cell analysis system). Typically, 20 - 80 spheroids were analyzed in each well. All four cell types formed multiple cell aggregates within the first 3 days, ranging in diameter from 30 - 80 μM. A549, SKOV-3 and MCF-7 multi-spheroids grew as round aggregates while MDA-MB-231 spheroids displayed stellate branching characteristic of an invasive morphology. At Matrigel volumes less than 40 μL or concentrations less than 3 mg mL-1, cells penetrated to the base of the plate and grew as ‘flat 2D' cultures. Using a novel bright-field image analysis algorithm, the number, area and average size of the spheroids could be computed over time non-invasively and without the use of fluorescent labels. Once formed, A549, SKOV-3, MCF-7 and MDA-MB-231 multi-spheroids increased 3.0-, 1.6-, 3.8- and 3.3-fold in size over 4 days, respectively. Treatment of A549 multi-spheroids with the DNA enzyme topo-isomerase inhibitor camptothecin (1μM) inhibited growth with comparable spheroid size at day 0 and day 7 post treatment (average brightfield area 1.4 x104 μM2). Using fluorescent protein reporters for apoptosis (Annexin V) and cell viability (IncuCyte CytoTox Green) we could verify camptothecin-induced cell death (fluorescence values 149±16% of control (Annexin V) and 243±51% of control (CytoTox). A concomitant decrease of stably expressed RFP (to 3±1% of control) was observed. The combination of protocol developments, novel image acquisition/analysis algorithms and cell health reporters creates an integrated solution for measuring growth and vitality of multiple small spheroids in a relevant and 3D bio-matrix over time. This approach should be applicable to primary- and patient-derived organoid tumor samples as well as cancer cell lines. Pickup, MW, Muow, JK, Weaver, MW (2014), EMBO Rep. 15(12): 1243-1253 Citation Format: Kalpana Patel, Miniver Oliver, Nevine Holtz, Tim Jackson, Nicholas Dana, Gillian Lovell, Nicola J. Bevan, Tim J. Dale, Derek J. Trezise. Development and optimization of Matrigel-based multi-spheroid 3D tumor assays using real-time live-cell analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5030.
Organoid technologies are increasingly being used as in-vitro models of human development and disease as they exhibit structural, morphogenetic, and functional properties that recapitulate in vivo pathophysiology. To successfully use these models across a variety of research disciplines and applications, approaches that reduce variability and technology pipelines to image & quantify these complex cell models are required. Here, we demonstrate simple, robust workflows for monitoring and automatically quantifying features, such as morphology, growth and death of organoids using real time live cell analysis. To quantitatively optimize and characterize organoid cultures in-vitro, mouse hepatic, intestinal and pancreatic organoids were embedded in Matrigel® domes (50% or 100%) in 24-well plates and imaged over time in an Incucyte® Live Cell System. Organoid growth, differentiation, and maturation was measured using Incucyte’ s automated Organoid Software Analysis Module, which tracks changes in size and morphology. Integrated metrics enabled objective determination of cell-type specific growth conditions and passaging regimes. To illustrate the utility of the Incucyte® Organoid Analysis Software Module to track organoid growth and death in 96-well plates, intestinal and hepatic organoid fragments were embedded in Matrigel® (50%) for 3 days prior to treatment with protein kinase inhibitor staurosporine (1 µM, STP). Vehicle treated organoids increased in size (10-fold; intestinal or 3-fold; hepatic) over time while marked reduction was observed in the presence of STP. Using label-free size and morphology metrics we could distinguish between cytotoxic and cytostatic mechanisms of action (MoA) of known chemotherapeutic compounds. STP, cisplatin (CIS, DNA synthesis inhibitor) or fluorouracil (5-FU, thymidylate synthetase inhibitor) exhibited concentration dependent inhibition of hepatic organoid growth, yielding IC50 values of 3 nM for STP, 9.7 µM for CIS and 0.78 µM for 5-FU. Whilst attenuation of size was observed across all compounds, increases in eccentricity and darkness indictive of 3D structure disruption and cell death respectively were only observed in CIS and STP-treated organoids (cytotoxic MoA). Differences between the size and morphology readouts illustrated the cytostatic mechanism of 5-FU. Use of this approach was extended to visualize and quantify CFTR function. Following forskolin stimulation, a concentration-dependent increase in intestinal organoid size was observed. In the presence of CFTR inhibitor CFTRinh-172 the maximal response was reduced by >50% (~150% at 10 µM) illustrating that swelling was CFTR-dependent. These data demonstrate the capability to kinetically visualize and quantify distinct organoid morphologies, assess drug-induced cellular changes label-free and illustrates the amenability of this approach across a range of disease areas. Citation Format: Tim R. Jackson, Miniver Oliver, Daniel Appledorn, Tim Dale, Kalpana Barnes. Label-free, real-time live cell assays for 3D organoids embedded in Matrigel® [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3084.
To develop new therapeutics, researchers are exploring the role of the immune system in defending the body against tumors. Modelling induced malignant cell death in vitro is of paramount importance. Tumor and immune cell co-cultures were created in 96 well plates and using live-cell analysis, various parameters of tumor killing were quantified in real-time. Red nuclear labeled target cells and various densities of pre-activated PBMCs (α-CD3/IL2, 4 d) were seeded in combination with IncuCyte Annexin V green apoptosis detection reagent. Images were acquired every 2 h for 3 d using IncuCyte. Analysis of the fluorescence images provides measurement of target cell number and apoptosis. Enhancement of the phase contrast image analytics enabled single cell segmentation, permitting determination of effector cell parameters; cell number, shape and, using fluorescently labeled surface marker antibodies, protein expression levels. In addition, studies into spatial interactions of target and effector cells were conducted. To exemplify how these new analytical features can be used to investigate the biology of tumor cell killing, studies of a α-hCD3xCD19 bi-specific T-cell engager antibody induced cytotoxicity were performed. Further characterization of effects on cell cycle during target cell death and use of more advanced 3D models of immune cell killing were also assessed, demonstrating the flexibility of live-cell analysis as a powerful tool for analyzing immune cell killing. Advances in data analytics has enabled the multiplexing of target cell quantification alongside the interrogation of effector cell properties in live cells. The added insight gained from these approaches will hopefully lead to improved immuno-therapeutics.
Fluorescence microscopy has become a core tool for visualizing and quantifying the spatial and temporal dynamics of complex biological processes. Thanks to its low cost and ease-of-use, widefield fluorescent imaging remains one of the most widely used fluorescence microscopy imaging modalities. To accomplish imaging of 3D samples, conventional fluorescence imaging entails acquiring a sequence of 2D images spaced along the z-dimension, typically called a z-stack. Oftentimes, the next step is to project the 3D volume into a single 2D image, as 3D image data can be cumbersome to manage and challenging to analyze and interpret, effectively limiting the utlity of z-dimensional information. Furthermore, z-stack acquisition is often time-consuming and consequently may induce photodamage to the biological sample, which are both major hurdles for its application in experiments that require high-throughput, such as drug screening. As an alternative to z-stacks, axial sweep acquisition schemes have been proposed to circumvent these drawbacks and offers potential of 100-fold faster image acquisition for 3D-samples compared to z-stack acquisition but unfortunately results in blurry, low-quality raw 2D z-projected images. We propose a novel workflow to combine axial z-sweep acquisition with deep learning-based image restoration, ultimately enabling high-throughput and high-quality imaging of complex 3D-samples using 2D projection images. To demonstrate the capabilities of our proposed workflow, we apply it to live-cell imaging of 3D tumor spheroids and find we can produce high-fidelity images appropriate for quantitative analysis. Therefore, we conclude that combining axial z-sweep image acquisition with deep learning-based image restoration enables high-throughput and high-quality fluorescence imaging of complex 3D biological samples.
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