2019 Advanced 3D Human Models and High-Content Analysis Symposium

The SLAS 2019 Advanced 3D Human Models and High-Content Analysis Symposium course package contains 16 presentations on:

-Enabling Technologies

-Lightning Session: Lost in Translation

-High Throughput 3D Cellular Models

-Advances in Imaging and Analysis

-Complex Translational Models

-Keynote speaker presentation

Based on presenter permission, 16 of the 23 total SLAS 2019 Advanced 3D Human Models and High-Content Analysis Symposium presentations are available on-demand. The SLAS Advanced 3D Human Models and High-Content Analysis Program Committee selects conference speakers based on the innovation, relevance and applicability of research as well as those that best address the interests and priorities of today’s life sciences discovery and technology community. All presentations are published with the permission of the presenters.

Jason Swedlow, Ph.D., FRSE

Professor of Quantitative Cell Biology

Centre for Gene Regulation and Expression

Jason Swedlow earned a BA in Chemistry from Brandeis University in 1982 and PhD in Biophysics from UCSF in 1994. After a postdoctoral fellowship with Dr T. J. Mitchison at UCSF and then Harvard Medical School, Dr Swedlow established his own laboratory in 1998 at the Wellcome Trust Biocentre, University of Dundee, as a Wellcome Trust Career Development Fellow. He was awarded a Wellcome Trust Senior Research Fellowship in 2002 and named Professor of Quantitative Cell Biology in 2007. His lab focuses on studies of mitotic chromosome structure and dynamics and has published numerous leading papers in the field. He is co-founder of the Open Microscopy Environment (OME), a community-led open source software project that develops specifications and tools for biological imaging. In 2005, he founded Glencoe Software, Inc., a commercial start-up that provides commercial licenses and customization for OME software. In 2011, Prof Swedlow and the OME Consortium were named BBSRC's Social Innovator of the Year and Overall Innovator of the Year. In 2012, he was named Fellow of the Royal Society of Edinburgh. Prof Swedlow has organized or directed several courses in quantitative microscopy at the Marine Biological Laboratory, Woods Hole, USA,
Cold Spring Harbor Laboratory, USA and the National Centre for Biological Science, Bangalore. India.

Lucas Dent

Postdoctoral Fellow

Institute of Cancer Research

My research aims to understand the signalling networks controlling cell shape and adhesion during normal development, and how these are altered in disease. To do this, my approach is to combine Drosophila (fruit fly) genetics and mammalian (human) systems to reveal the broad principles and mechanistic details of adhesion signalling, respectively.

I completed doctoral studies in 2015 at the Peter MacCallum Cancer Centre in Melbourne, Australia, where I described control of tissue growth, cell shape, and organ development by integrin adhesion signalling proteins in Drosophila. In 2018 I was awarded a Commonwealth Rutherford Fellowship to study cell shape and adhesion with Professor Chris Bakal, at the Institute of Cancer Research in London. In my work with Professor Bakal, we are combining high-throughput and high-content imaging to uncover adhesion signalling networks and use this information to improve targeted therapies in cancer.

Martin Jones, DPhil

Deputy Head of Microscopy Prototyping

The Francis Crick Institute

Martin Jones works in the Electron Microscopy Science Technology Platform at the Francis Crick Institute in London, developing new hardware and software for extracting meaning from ever more complex datasets.

Martin's DPhil from Sussex University was in experimental atomic and quantum physics, followed by a postdoc in experimental quantum information processing. After this he moved to biology, joining the vascular biology lab at Cancer Research UK's London Research Institute, subsequently joining the EM team there.

William Stebbeds, Ph.D.

Senior Scientist

GSK

Senior scientist at GSK specializing in developing novel assays for drug discovery and development using complex in vitro models and multi-parametric analysis.

Donna Davies, Ph.D.

Professor of Respiratory Cell and Molecular Biology, Clinical and Experimental Sciences

University of Southampton

Donna Davies has a PhD in Biochemistry and holds a Personal Chair at the University of Southampton, UK. She has pioneered the use of tissue engineering using airway tissue derived from volunteers with asthma or COPD as alternatives to using animal models of pulmonary disease. More recently, she has also developed novel in vitro models of lung fibrosis for development of novel anti-fibrotic agents. Notable discoveries include demonstration of epithelial dysfunction in asthma and COPD, dissection of the function of the asthma susceptibility gene, ADAM33, and involvement of the epithelial mesenchymal tropic unit in asthma pathogenesis. She co-founded the University spin-out company, Synairgen, which has developed inhaled interferon-beta (SNG001) as a novel treatment for asthma and COPD exacerbations.

Krisztián Koós, Ph.D.

Biological Research Centre

Hungarian Academy of Sciences

Krisztian Koos is currently a Ph.D. candidate in the laboratory of Peter Horvath, Biological Research Centre of the Hungarian Academy of Sciences. He graduated as a computer scientist at the University of Szeged where he worked on computer tomography algorithms. His research interests lie in image processing and machine learning, and he is interested in developing algorithms to solve interesting problems from the life sciences. His main topic is label-free image processing using DIC microscopy. He developed an automatic electrophysiological measurement system that performs whole-cell patch-clamp recording in human brain tissues.

Arne Hansen, M.D.

Associate Professor, Department for Experimental Pharmacology and Toxicology

UKE/Hamburg

Arne Hansen received his MD at the University of Hamburg. After clinical training and a 3-year PostDoc at NIH he joined the Department for Experimental Pharmacology and Toxicology at UKE/Hamburg in 2007 and was appointed as Assistant Professor in 2012 and Associate Professor in 2018. His research focus is the development of 3D cell culture models to study cardiomyocyte biology and disease. In this context, he has developed techniques to generate heart tissues from human CRISPR/Cas9 engineered iPSCs -and optimized test systems to analyze contractile force and calcium transients with high levels of automation.

Niklas Rindtorff

MD/Ph.D. Student

German Cancer Research Center (DKFZ)

Thierry Dorval, Ph.D.

Head of Data Science Lab

Servier

Thierry Dorval received a B.S. degree in physic and graduated in image processing and artificial intelligence at Pierre & Marie Curie University, Paris, France. He received a Ph.D.d then joined the Institut Pasteur Korea in 2005 first as researcher in biological image analysis then as a group leader specialized in High Content Screening applied to cellular differentiation as well as toxicity prediction.

In 2012 he joined AstraZeneca, UK. His activities were about developing and advising on quantitative image and data analysis solutions in support of high content phenotypic screens in addition to cellular and tissue imaging.

In 2015 he joined Servier, France, as leader of the High Content Screening group within CPCB CentEX. He is currently still working on phenotypic approaches to improve drug discovery pipeline using high content strategies and currently lead the Data Science Lab.

Gregory Vladimer, Ph.D.

CSO

Allcyte

Gregory Vladimer is the CSO of Allcyte, a startup in Vienna, Austria. He received his PhD from UMass Medical School where he studied inflammation, and was a Senior Postdoctoral Fellow at CeMM in Vienna. Together with the Department of Hematology of the MedUniWien, spearheaded the use of single-cell image-based screening for the personalized identification of treatments for hematological cancers through a prospective clinical trial, and several retrospective studies. His work is published in journals including Nature, Lancet-Hematology, NEJM, and Cell, and he is on the steering-committee for the precision haematology working group of EHA advocating for standards around functional testing.

Mario Saporta, MD, Ph.D., MBA

Assistant Professor of Neurology and Human Genetics

University of Miami Miller School of Medicine

Mario Saporta, MD, Ph.D., MBA is an assistant professor of Neurology and Human Genetics at the University of Miami. He is a clinical neurologist and translational scientist specialized in neuromuscular genetic diseases. His lab focuses on the use of patient-derived cell lines to model genetic neuropathies for mechanistic studies. He is particularly interested in the identification of axon phenotypes using novel tridimensional culture strategies to develop new, disease-relevant, drug screening platforms.

Hazel Screen, Ph.D., MRes, BEng

Professor of Biomedical Engineering

Queen Mary University of London

Hazel Screen is Professor of Biomedical Engineering and Chair of Bioengineering at Queen Mary University of London.

Her research group focuses on multi-scale structure-function behaviour and mechanobiology in tissues. She has particular interest in in vitro models to explore health and drivers of disease in musculoskeletal and cardiovascular tissues, using her mechanobiology expertise to develop models with more physiologically relevant physical environmental cues. She has authored ~100 peer-reviewed publications and several book chapters.

Prof Screen also directs the UK RI funded Organ on a Chip Technologies network, which aims to drive forward and support UK-wide research activity in the field.

Gary Allenby, Ph.D.

Chief Scientific Officer

Aurelia Bioscience

PhD in reproductive tox, worked in pre-clinical pharma for 25 years in Hit ID, Hits to Lead, Target Biology sections developing cell based assays for compound screening. Founding entrepreneur of Aurelia Bioscience in 2012, delivering tailored assay development for compounds pharmacological profiling for screening purposes

Glauco Souza, Ph.D.

Director of Global Business Development & Innovation

Greiner Bio-One North America, Inc.

"Dr. Souza is the Director of Global Business Development and Innovation, 3D Culture at Greiner Bio-One and former Adjunct Assistant Professor at the University of Texas Health Science Center at Houston. He is one of the creators of magnetic 3D cell culture, including magnetic 3D bioprinting. Results using these groundbreaking technologies have been reported in various high-impact scientific journals, including Nature Nanotechnology, Proceedings of the National Academy of Sciences, Nature Protocols, Biomaterials, and Nature Reviews Cancer. Recently, his work was selected for the Short List of The Lush Prize for outstanding research producing an effective non-animal safety test. Dr. Souza’s research has been funded by grants from National Science Foundation (NSF), National Institute of Health (NIH), Department of Defense (DOD), Center for Advancement of Science in Space (CASIS), and Texas Emerging Technology Fund (ETF)."

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Keynote
Keynote Address-OME’s Bio-Formats, OMERO & IDR: Open Tools for Accessing, Integrating, Mining and Publishing Image Data at Scale
Open to view video.
Open to view video. Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. The Open Microscopy Environment (OME; http://openmicroscopy.org) is an open-source software framework developed to address these challenges. OME releases specifications and software for managing image datasets and integrating them with other scientific data. OME’s Bio-Formats and OMERO are used in thousands of labs worldwide to enable discovery with imaging. We have used Bio-Formats and OMERO to build solutions for sharing and publishing imaging data. The Image Data Resource (IDR; https://idr.openmicroscopy.org) includes image data linked to >70 independent studies from genetic, RNAi, chemical, localisation and geographic high content screens, super-resolution microscopy, and digital pathology. Datasets range from several GBs to tens of TBs. Wherever possible, we have integrated image data with all relevant experimental, imaging and analytic metadata. With this metadata integration, we have identified gene networks that link to cellular phenotypes. We have also built cloud-based analysis tool portals to catalyse the re-use and re-analysis of published imaging data. Through OME’s commercial arm, Glencoe Software, we have built PathViewer (http://www.glencoesoftware.com/products/pathviewer/), a web-based WSI visualisation and annotation tool that is used in academic medical centres and 10 pharmaceutical companies and for digital pathology data sharing, atlases, analysis, and also for e-learning in medical education. I’ll present our latest work on linking genotypes and phenotypes in IDR, and our proposals for next generation data formats and public resources for imaging.
Advances in Imaging and Analysis
Imaging Rapid Cell Shape Transitions and Volume Control in 3D
Open to view video.
Open to view video. Imaging rapid cell shape transitions and volume control in 3D Regulation of cell shape in 3D space is essential during human development, and misregulation of cell shape is central to human disease states such as metastatic cancer. We are using 3D high content imaging to understand how healthy and diseased cells regulate their 3D shape and volume. Approach: Oblique plane microscopy for 3D imaging To make measurements in 3D we are taking advantage of recently developed Oblique Plane Microscopy (OPM). OPM imaging combines the benefits of light sheet microscopy - high speed 3D imaging, and low phototoxicity - with the advantages of conventional microscopy such as simple mounting techniques and high throughput sampling. i) Cell shape transitions To understand the molecular networks controlling 3D shape transitions in melanoma, we are live imaging cells embedded in collagen matrices. We are using this system to establish baseline shape dynamics, as well as shape transitions when cytoskeletal regulators are inhibited or when cells are in the presence of clinical drugs. ii) Control of cell volume Volume control is key to cell function because the volume of a cell influences the scale, duration and dynamics of all biochemical processes within. We have been using volumetric imaging by OPM in immortalised epithelial cells to understand how cell geometry is maintained throughout each stage of the cell cycle, and across cell generations. We anticipate these discoveries can form the basis of new strategies to target size control checkpoints in the treatment of cancers.
Extracting Meaning From Big Data in Volume Electron Microscopy
Open to view video.
Open to view video. Many different imaging modalities now routinely produce huge amounts of data thanks to increased acquisition speeds and extensive automation. Volume electron microscopy techniques, such as serial block face SEM (SBF SEM), focused ion beam SEM (FIB SEM) and array tomography (AT), produce datasets in the terabyte regime. Multimodal imaging methods such as correlative light and electron microscopy (CLEM) can be used to navigate the sample more efficiently, reducing the amount of data that must be analysed. We have developed a set of tools that allow us to "find the needle in the haystack" using these CLEM techniques. Electron microscopy image data has remained stubbornly resistant to automatic computational analysis, with painstaking manual segmentation (finding and delineating a structure or object of interest) still being the gold standard. However, recent generations of microscope produce data far more quickly than a small team of experts can thoroughly analyse. Whilst new deep learning techniques offer significant promise in automating this analysis, the collection of sufficient annotations to provide training data is a major bottleneck. In collaboration with the Zooniverse (zooniverse.org) we have developed a citizen science project called “Etch a Cell” (etchacell.org) in which we ask volunteers to contribute segmentations. By collecting multiple segmentations per image, we are able to aggregate the volunteers’ annotations into accurate and robust data that can be used to train our machine learning system. Beyond the research applications, we have also found the project to be an effective outreach and education tool, letting students and non-experts gain an insight into the scientific process at the raw data level.
Development of a Multiparametric Structural Cardiovascular Toxicity Imaging Assay Using iPSc Derived Cardiomyocytes
Open to view video.
Open to view video. According to Laverty and co-workers (2011), 27% of drugs fail to reach phase I due to cardiovascular liability and up to 45% of drug withdrawals post approval are due to cardiovascular toxicity. The majority of these withdrawals were due to the induction of arrythmia in patients which led to various initiatives by regulatory agencies such as the comprehensive in vitro proarrhythmia assay (CiPA) initiative by the FDA which utilise functional assessments of human iPSc derived cardiomyocytes to predict potential acute cardiovascular liabilities. However, these approaches cannot capture the effects of compounds with a chronic dosage regimen that are capable of causing structural changes in cardiac cells. The aim of this project is to develop an in vitro assay capable of flagging compounds with potential cardiovascular liabilities when applied chronically using iPSc derived cardiomyocytes. In order to capture the multivariate potential mechanisms of toxicity, cells were measured to assess a number of different functional and structural parameters, such as calcium flux, contraction, viability, mitochondrial membrane potential as well as actin organisation. The use of 3D co-culture models was also assessed as these are postulated in the literature to increase the maturity and, therefore, the physiological relevance of the model. The approach generated data from numerous parameters describing both kinetic and imaging readouts, requiring customised data analysis solutions. This brought the challenge to balance the need to test compounds rapidly in high throughput (384-well) at early lead identification and lead optimisation stages of drug development, with the desire to generate rich datasets informative of underlying mechanisms of structural cardiotoxicity. Assay predictivity was assessed using annotated diverse compound sets including both proprietary and public domain compounds known to induce structural cardiotoxicity in vivo. Authors: Ellie Handford, GSK Peter Clements, GSK Andrew Brown, GSK Jo Francis, GSK
Complex Translational Models
Modelling the Human Airway Mucosa for Preclinical Drug Development and Testing
Open to view video.
Open to view video. In the UK, lung diseases account for 20% of deaths, >700,000 hospital admissions and >6 million inpatient bed-days/year. Admissions often result from acute exacerbations for which there are no effective treatments, despite large investment by pharma. Over 85% of promising new drug candidates fail in clinical trials leading to high rates of attrition. Likely explanations include the poor correlation between current animal models with the human pathology and the lack of representative, validated and qualified 3D human cell models. In our clinical translational studies, we use human lung tissue samples to study disease mechanisms and are developing the ‘4D Airway Biochip’ platform to help improve our understanding of lung diseases. This microfluidic platform models interstitial flow, providing a cellular environment that is closer to the in vivo situation, and allows kinetic sampling of cellular secretions. Furthermore, it provides an air interface for challenge with environmental agents, whilst frequency-dependent electrical impedance measurements allow epithelial barrier properties to be monitored in real time. Data from this platform suggest that it is predictive of in vivo tissue responses and offers a practical solution for new drug discovery not only in airway diseases but for other diseases where epithelial barrier defects contribute to disease pathogenesis. It may also offer a useful in vitro platform for pharmacological and toxicological studies.
Metastatic Colorectal Cancer Organoids as a Novel Model System for Personalized Medicine and Reverse Translation
Open to view video.
Open to view video. Regorafenib has shown anti-cancer activity in metastatic colorectal cancer (mCRC) patients by inhibiting tumor vasculature. A mCRC PDO model can mimic tumor-stroma interaction for improving patient selection and measure drug resistance. In this work, we recapitulated clinical response in vivo, and compared to the ex vivo tumor-stroma model. A translational phase II trial of regorafenib in chemo-refractory mCRC patients with biopsiable metastases was conducted. For the in vivo models, PDOs were implanted in livers of NSG mice and treated with regorafenib. The Ex vivo model was generated by co-culturing PDOs with CAFs and EC. PDOs retained genomic and transcriptomic features of parental biopsies. The results showed vascular density reduction after regorafenib treatment in mice from responders’ patients, and no significant changes in non-responders. The developed PDO co-cultures resembled the metastatic niche predicting response to anti-cancer treatments to inform clinical decisions. Co-Authors: 1 Georgios Vlachogiannis 2 Andrea Lampis 3 Khurum Khan 4 David Cunningham 5 Matteo Fassan 6 Ruwaida Begum 7 Leo Chan 8 Ning Lai 9 Reem Eldawud 10 Nicola Valeri
Enabling Technologies
Deep Learning Techniques for 3D Tissue and Organoid Manipulation and Segmentation
Open to view video.
Open to view video. In this talk I will give an overview of the techniques developed to convert our high content screening pipeline from 2D to organoids. First, I will present classical image processing algorithms and novel deep learning approaches for single cell-based analysis. I will discuss the challenges, opportunities and difficulties in converting these methods to 3 dimensions. A tool will be presented for annotating volumetric data to generate training image database. Our goal is to develop a deep learning architecture for 3D instance segmentation which will be used for processing image stacks of spheroids acquired on light sheet microscopy. Furthermore, I will present our 3D pipeline from spheroid generation to imaging. We are developing the Spheroid Picker robot that is capable of automatically selecting spheroids based on their morphological properties and transfer them from growing plates to high content plates. This low-cost device is a stereo microscope equipped with a pipette manipulator and a pressure controller system. The clearing method applied on the sample to allow high resolution deep imaging with light sheet fluorescence microscopy will be introduced. Finally, I will describe our label free automatic patch clamp system that performs electrophysiological measurements on living neurons in 3D brain tissue slices. The system is validated on hundreds of rodent and human cells.
Human Engineered Heart Tissue – An Innovative Model for Preclinical Cardiac Assessment
Open to view video.
Open to view video. The presentation will focus on Engineered Heart Tissue technology (EHT). EHTs are three-dimensional, force-generating cardiac tissues in 24 well-format which are generated from single cell suspensions of human induced pluripotent stem cell-derived cardiomyocytes. EHTs are developed between flexible silicone posts under auxotonic stretch. Automated test platforms will be introduced to analyze physiological parameter like contractile force and calcium transients under standardized conditions based on video-optical recording. Specific aspects related to cardiomyocyte maturation and application for in vitro cardiac assessment of compounds will be addressed.
Multiparametric Phenotyping of Compound Effects on Patient Derived Organoids
Open to view video.
Open to view video. Patient derived organoids (PDOs) closely resemble individual tumor biology and allow testing of small molecules ex vivo. To systematically dissect compound effects on 3D organoids, we developed a high-throughput imaging and quantitative analysis approach. We generated PDOs from colorectal cancer patients, treated them with >500 small molecules and captured >3 million images by confocal microscopy. We developed the software framework SCOPE to measure compound induced re-organization of PDOs. We found diverse, but re-occurring phenotypes that clustered by compound mode-of-action. Complex phenotypes were not congruent with PDO viability and many were specific to subsets of PDO lines or were influenced by recurrent mutations. We further analyzed specific phenotypes induced by compound classes and found GSK3 inhibitors to disassemble PDOs via focal adhesion signaling or that MEK inhibition led to bloating of PDOs by enhancing of stemness. Finally, by viability classification, we show heterogeneous susceptibilities of PDOs to clinical anticancer drugs. Authors: Johannes Betge, Niklas Rindtorff, Jan Sauer, Benedikt Rauscher, Clara Dingert, Haristi Gaitantzi, Frank Herweck, Thilo Miersch, Erica Valentini, Veronika Hauber, Tobias Gutting, Larissa Frank, Sebastian Belle, Timo Gaiser, Inga Buchholz, Ralf Jesenofsky, Nicolai Härtel, Tianzuo Zhan, Bernd Fischer, Katja Breitkopf-Heinlein, Elke Burgermeister, Matthias P. Ebert, Michael Boutros
High Throughput 3D Cellular Models
Medium-scale Comparative Study of 2D vs. 3D Models Using High Content Imaging Approaches
Open to view video.
Open to view video. 3D cellular models represent a fantastic opportunity for pharmaceutical industries to improve their discovery pipeline efficacy by bringing potentially much more relevant models within the early stages of the workflow. Moreover, it has been shown that in specific cases 2D and 3D models response to drug treatment can strongly vary and thus impact the in vitro relevance of the physiopathological model associated readouts. This approach is particularly well suited for complex or partially characterized targets in oncology. In this context, we have performed a systematic comparison of the 2D vs. 3D high content imaging readouts using a single cancer cell line. We will discuss about the challenges associated to such large scale screening in term of cellular processing but also in term of image and data analysis. Ultimately, we will discuss about the results generated from such a comparative study.
Single-Cell Imaging and Advanced Image Analysis of Primary Tumors for Anticancer Therapy Development
Open to view video.
Open to view video. The ability to perform high-content screening in a high-throughput fashion is routinely limited to cell lines and other explant model systems, however, there is a risk that these may not be fully representative of the in vivo environment due to culture adaptation or the lack of multi-lineage cell types. The ability to gather high-content data directly from primary samples however, both direct from blood and bone marrow or from metastasized cancers, without cell outgrowth or selection in a method amenable to laboratory automation can be a more direct system. Further, by combining imaging of these primary sample with an analysis pipelines robust to micro-aggregates, vastly different cell shapes and sizes, and that can ultimately harness the features from each cell can become a powerful means to study drug response in a variety of indications using model systems directly derived from the patient. This methodology has been used to prioritize therapy for late-state patients with hematological cancers in a basket trial (Snijder & Vladimer et al 2017,Lancet Hematology), has been integrated with genetic data to further uncover biological understanding and clinical synergy options (Schmidl & Vladimer et al 2019, Nat Chem Bio), and is now robustly being tested in technical validation studies for some indications to understand its potential use as an in vitro diagnostic.
Human 3D Neuronal Cultures for Pheontypic Drug Screening In Neurodegenerative Diseases
Open to view video.
Open to view video. Several neurodegenerative diseases are characterized by axon degeneration. This is especially true for the peripheral neuropathies, a heterogeneous group of human diseases characterized by progressive degeneration of peripheral axons. Charcot-Marie-Tooth disease (CMT) is a group of peripheral neuropathies caused by a variety of genetic mutations leading to length-dependent axon loss. CMT is the most common neurogenetic disease, affecting 3 million people worldwide. It is a devastating, untreatable disorder. It limits patients’ ability to walk, balance themselves and use their hands and is associated with significant functional disability. It can also cause marked sensory impairment and neuropathic pain. Despite significant advances in our understanding of the pathophysiology of CMT, disease-modifying therapies are entirely lacking, partially due to lack of translational models suitable for drug discovery. One of the major challenges in creating such models is the need to specifically analyze axons in vitro. Two-dimensional neuronal cultures often exhibit overlap of cell bodies and neurites, making it difficult to analyze axonal morphology and potential screenable phenotypes in a high throughput manner. To overcome this limitation, we created a three-dimensional culture system based on induced pluripotent stem cell (iPSC)-derived motor neurons (spinal spheroids), one of the main cellular types affected by CMT. Spinal spheroids can be formed by culturing sorted iPSC-derived motor neurons in ultra-low-attachment 384-well plates. When transferred to laminin-coated plates, spinal spheroids attach to the bottom of the well, allowing for the robust growth of axons in a centrifugal fashion, optimal for high content imaging. Using this system, we identified a robust and reproducible axonal phenotype in spinal spheroids from patients with CMT2E, a particular type of CMT caused by missense mutations in NEFL (neurofilament light chain gene). This phenotype is characterized by the abnormal accumulation of neurofilaments in discrete areas of the motor axons and nicely recapitulates findings from a mouse model of this same disease. This phenotype is also easily quantifiable using automated image analysis. A focused, proof-of-concept experiment investigating the effect of kinase inhibitors on the CMT2E axonal phenotype identified two compounds capable of improving neurofilament distribution in motor axons, demonstrating the potential of this platform as a useful tool for drug discovery in CMT. High throughput drug screening of several compound libraries is expected to start soon. Co-Authors: Renata, Maciel, PhD, MBA Banupriya, Sridharan, PhD Louis, Scampavia, PhD Timothy, Spicer, PhD
Lightning Session: Lost in Translation
The Organ on a Chip Technologies Network
Open to view video.
Open to view video. The Organ-on-a-Chip Technologies Network is a UKRI funded Technology Touching Life initiative, designed to capture, inspire and grow UK research activity in the Organ-on-a-Chip research field. Our global aims are to: •Develop a vibrant multidisciplinary research community, bringing focus to the varied Organ-on-a-Chip and in vitro model research activity in the UK; •Facilitate inter-disciplinary and inter-sectoral research collaborations, to develop the next generation of organ-on-a-chip research solutions; •Train, support and inspire the next generation of outstanding leaders in organ-on-a-chip research. Our flagship sabbatical funding programme is designed to pump prime new collaborations and research activity in the field. Researchers can spend time in a different (cross-discipline) laboratory. Funding includes salary for the sabbatical period plus up to £5k consumables and a travel/subsistence grant. We run 6 monthly network events, which aim at sharing members latest research, facilitating new collaborations and identifying routes to support our community. We are currently establishing a range of special interest groups within the network, providing financial support for groups to run more focused organ-on-a-chip workshops and events. We also provide funding for network members to travel between each other’s laboratories to initiate new collaborations. We have a strong focus on early career researcher support and training, running activities specifically for this group. Currently, our early career researchers are spearheading new public engagement activities for the organ-on-a-chip community with support (financial, training and delivery) from our team. The network is free and simple to join: https://www.organonachip.org.uk/ Members of our leadership team can provide further information: Hazel Screen (QMUL) Martin Knight (QMUL) Anthony Bull (Imperial Col) Alicia El Haj (Birmingham) Andy Carr (Oxford) Matt Dalby (Glasgow) Katia Karalis (Emulate) Paul Workman (ICR)
Magnetic Electrospun Microfibre Scaffold Assemblies: Examples of Their Use for Cell-Based Screening Applications
Open to view video.
Open to view video. In an effort to create a more physiological three-dimensional (3-D) environment for cell growth while maintaining the logistics of well plate screening for drug discovery purposes, we have develop a 3-D micro-scaffold platform from electrospun material used in conjunction with well plates for higher throughput screening. We have engineered electrospun material to form micro-scaffold islands of cells. Cells grow on, around and into the material, forming a micro-island of adherent cells that are effectively 3-D in solution. The incorporation of iron nano-particles into the fibres during manufacture results in micro-scaffold islands that can be physically manipulated using electro-magnetism. We can culture cells on micro-scaffolds in culture vessels in media within the incubator in addition to moving them within wells using arrays of neodymium magnets, attracting scaffolds to the edges of wells to prevent damage during media replacement or align scaffolds in the centre of wells for imaging purposes. Using sheathed electromagnetic tips we can move micro-scaffolds from well to well with no adverse effects to cells. In addition we have developed a liquid handling device capable of identifying the location of scaffolds in a petri dish then performing a ˜pick and place™ procedure putting them into user defined wells of a plates. Furthermore, we have incorporated fluorescent dyes or quantum dots into the fibres such that fibres can be visualised using fluorescence microscopy, while quantum dots can be used as a barcode to distinguish between two cell populations on different scaffolds within the same well. Cells can be transfected while cultured on micro-scaffolds using either lipofection or electroporation. Recombinant cells can be cryo-preserved on micro-scaffolds. We will show data of exemplar assays using recombinant, primary and differentiated stem cell assays on micro-scaffolds. We have used this approach to examine a number of luminescence and fluorescence readouts in recombinant cell lines and have differentiated iPSC™s to cortical neurones in 3-D on micro-scaffolds to characterise then use imaging as a readout. Our data suggests that this micro-scaffold approach may open up new opportunities for both recombinant cell based screening and differentiated stem cell assays using single and co-cultures in a well plate-based format more amenable to higher throughputs with very little manual intervention.
Magnetic 3D Bioprinting, from Spheroids to Fingerprinting Cells in 3D Using a 2D Workflow
Open to view video.
Open to view video. The growing push for 3D cell culture models is limited by technical challenges in handling, processing, and scalability to high-throughput applications. To meet these challenges, we use our platform, magnetic 3D bioprinting, in which cells are individually magnetized and assembled with magnetic forces. In magnetizing cells, not only do we make routine cell culture and experiments feasible and scalable, but we also gain fine spatial control in the formation of spheroids and more complex structures. This presentation will focus on recent developments using this platform, particularly in cancer biology and immunology. Specifically, we will present a method for phenotypic profiling of cell types within spheroids using real-time high-throughput imaging. This label-free method allows for multiplexing with other assay endpoints for high-content screening. Overall, we use magnetic 3D bioprinting to create functionally and structurally representative spheroids for high-throughput screening.