Advancing Neurodegenerative Disease Research With iPSCs

The Progress and Promise of iPSCs in Disease Modeling Simplifying Progress The Burden of Gradual Decay Neurodegenerative diseases represent a group of conditions marked by the progressive decline of neuron structure and function. These diseases are particularly harrowing as they lead to a gradual deterioration of motor skills, memory, and cognitive abilities, profoundly affecting patient lives. Alzheimer’s and Parkinson’s diseases are the most common neurodegenerative disorders, each presenting unique challenges. Alzheimer’s disease gradually erodes memory and cognitive function, while Parkinson’s disease is known for its motor symptoms, such as tremors and stiffness. The burden of these neurodegenerative disorders is immense, not only in terms of the number of people affected, but also in the impact on families and the healthcare system. The Alzheimer’s Association estimates that 6.7 million Americans aged 65 and older live with Alzheimer’s dementia. In contrast, Parkinson’s disease affects nearly one million people in the United States, according to the Parkinson’s Foundation. Current treatment options for neurodegenerative diseases are limited. Medications approved for symptom management provide only temporary relief and do not address the underlying disease progression. For example, cholinesterase inhibitors in Alzheimer’s may temporarily improve memory and judgment, but they do not prevent neuronal death. Similarly, dopamine precursors can alleviate symptoms in Parkinson’s but do not stop motor loss and cellular deterioration. This underscores the urgent need for therapies that target the pathogenesis of these diseases. Barriers to Progress One of the major hurdles in developing such therapies is the restrictive nature of the blood-brain barrier (BBB). The BBB serves as a protective shield, preventing nearly 99% of substances from entering the brain. While this is crucial for brain health, it also poses a significant challenge for drug delivery, as most therapeutic agents cannot cross the BBB to reach their targets in the central nervous system. Moreover, the lack of accurate translational models that mimic human neurodegenerative diseases complicates research. Primary neuronal cultures, acquired postmortem, are restricted by availability, a short lifespan, and meticulous handling protocols. Immortalized cell lines, while easier to maintain, often lack the complex behaviors of true neurons, are prone to genetic changes, and do not replicate the brain’s three-dimensional structure. Alternatively, animal models can be poor predictors of treatment response in humans, leading to a high failure rate in clinical trials. Researchers are addressing these limitations by embracing advanced cell culture systems. Exploring New Dimensions in Neuroscience with Advanced Cell Models Table of Contents Application Note Solutions for the Culturing, Maintaining and Characterization of Induced Pluripotent Stem Cells Daryl Cole, PhD — Scientist - Sartorius Kirsty McBain — Scientist - Sartorius Nicola Bevan — Manager - Sartorius Introduction From drug discovery to organoid modeling of disease, stem cells are increasingly being used in research as a vital tool for scientific investigation. The current trend away from animal models and the push to more relevant systems for simulating the human body require flexible and specific tools to achieve this goal. Induced Pluripotent Stem Cells (iPSCs) are produced from normal tissue, through the forced expression of key transcription factors1, providing a limitless supply of these precious cells for research and development. Due to the very specialized nature of these cells, their maintenance and culture is more intensive than most cell lines. For this reason, it is important that solutions for the culture and maintenance of these cell types are readily and widely available. Characterization of stem cells can be difficult and unreliable, depending on the methodology used, which is why it is important to develop robust techniques for monitoring stem cells throughout culture and experimental testing. If conditions are not optimal during the maintenance of iPSCs, their pluripotency can be lost. Reproducibility is highly prized in research and automated solutions can provide high levels of consistency in method and data generation. The CellCelector Flex is an automated platform for targeted cell identification and picking that is not only highly accurate, but also very gentle on cells, providing an ideal solution when working with delicate iPSCs. The Incucyte® Live-Cell Analysis platform automates the imaging processes of iPSC workflows, allowing cells to be monitored over time to analyze changes in morphology and colony formation from within the incubator. This limits the disturbance to precious iPSC culture plates, but also enables real-time tracking of cell growth and health metrics. Key words or phrases: Induced Pluripotent Stem Cells, iPSCs, Pluripotency, Stem Cells, CellCelector Flex, Incucyte, iQue, Cell Culture, iPSC Characterization, iPSC R&D Find out more: www.sartorius.com/ipscs Further characterization of iPSCs can be performed on the iQue®3 High-Throughput Cytometry Platform, investigating changes in expression of pluripotency markers integral to maintaining stemness, providing an overview of the status of iPSCs. Many traditional methods for culturing, monitoring and characterizing iPSCs can: 1. Be inconsistent and unreliable, resulting in seeded populations with high levels of heterogeneity, cell death and differentiation 2. Require regular disturbance of culture plates to monitor growth and confluency, with no integrated options for analysis 3. Demand large volumes of precious sample for analysis, resulting in less material for downstream applications 4. Necessitate the use of a variety of techniques to measure multiple characteristics This application note discusses the novel solutions provided by Sartorius platforms for the culture, maintenance, and characterization of iPSCs, during research and development. Methods The following methods outline a flexible, in-depth workflow for growth and characterization of iPSCs using multiple Sartorius platforms. Cell Culture and Maintenance Picking and seeding iPSCs Individual cells and colonies were picked using the CellCelector Flex with the Adherent Colony Picking Module and seeded into tissue culture plates for further expansion and downstream processing. Images were taken prior to and post picking to monitor and record the effects of colony manipulation using the CellCelector Flex. Propidium Iodide (PI) staining was undertaken on iPSC colonies after seeding by adding PI at a concentration of 500 nM and incubating for 3 minutes, rinsing twice with PBS and resuspending in growth medium (mTESR Plus) for imaging. Figure 1. Schematic showcasing the use of Sartorius platforms in iPSC culture. Using the three Sartorius instruments, CellCelector Flex, Incucyte® and iQue®3, iPSCs can be picked and seeded, pluripotency tested, and growth and confluency monitored. Picking and Isolating cells CellCelector Flex Incucyte® Live-Cell Analysis Platform iQue®3 High-Throughput Screening Cytometer Monitoring, morphology, confluency and growth Characterization of marker expression Thawing and Culturing iPSCs Cells (ATCC-DYS0100 cells derived from human foreskin fibroblasts) were thawed and plated onto Vitronectin XF™ (1:25 dilution in CellAdhere™ Dilution Buffer) precoated 6-well plates at a seeding density of 1x106 cells/well in 1 mL growth medium (mTESR™ Plus) supplemented with Y-27632 (ROCK inhibitor, 10 μM) and incubated at 37°C. iPSCs were monitored using the Incucyte® system to assess confluency, colony formation, and general cell morphology and health. The confluence of colonies was analyzed using the integrated Incucyte® AI confluence Characterization and Monitoring of Pluripotency Pluripotency Characterization: iQue® iPSCs were dissociated to single cells during passage and at specified timepoints using Gentle Cell Dissociation Reagent. Single cell suspensions were stained with cell surface marker antibodies (in PBS + 2% FBS) for one non-pluripotent marker, SSEA-1, and two pluripotency markers, SSEA-4 and TRA-1- 60, in addition to the iQue® Membrane Integrity (B/Red) Dye, for viability analysis. Cells were seeded at 2x104 cells/well in a V-bottom 96-well plate and stained with the cocktail of Monitoring Pluripotency and Cell Health: Incucyte® During the experiments, iPSCs were monitored for changes in morphology and confluency using the Incucyte® Live-Cell Analysis platform. Cultured iPSCs lines were monitored by high definition (HD) phase contrast at 4-hour intervals using a repeating scan schedule at 10X. Nuclear to cytoplasmic ratios were Intracellular and Surface Marker Studies iPSC and control THP-1 cells were seeded at 2x104 cells/ well in a V-bottom 96-well plate and fixed, permeabilized and stained according to the protocol found in the following tech note: Intracellular Staining Assay for iQue® Platform. Pluripotency markers, SSEA-4, TRA-1-60, Oct Results Developing workflows for the culture and characterization of stem cells such as iPSCs is vital in producing consistent, reproducible and robust data. Using the Sartorius platforms showcased here (Figure 1), we can highlight the benefits of the approaches described for culturing iPSCs that are healthy and pluripotent while monitoring and characterizing these stem cells for key markers of health and stemness. software algorithm. Passages were performed every 3-4 days at approximately 60-70% confluence using Gentle Cell Dissociation Reagent and replated at 1x105 cells/well. Medium changes were performed daily during the week, while double volume medium changes were performed on Friday to account for no medium changes over the weekend. For the non-optimized iPSC culture, cells were grown as above except using RPMI 1640 medium supplemented with 10% FBS, L-glutamine 2 mM, Penicillin/Streptomycin 100 μg/mL. antibodies described (RT in the dark for 30 minutes). To wash plates, PBS + 2% FBS (100 μl) was added, prior to centrifugation (300 x g, 5 minutes), then aspirated. Plates were shaken (3000 rpm, 60 seconds) and the samples resuspended in PBS + 2% FBS (20 μL), prior to being analyzed on the iQue®3. Analysis of data was performed using the iQue Forecyt® software after compensation had been optimized for each of the antibodies. calculated by staining iPSC nuclei using the Incucyte® Nuclight Rapid Red Dye (1:1000) and measuring the cytoplasmic area (confluence mask) and the nuclear area (fluorescence mask) using basic masking to quantify pluripotency/normal iPSC morphology. 3/4 and Sox-2 were analyzed, while SSEA-1 expression was used as a marker for non-pluripotency. Analysis was performed on the iQue Forecyt® software after compensation had been optimized for each of the antibodies. Picking iPSCs Using the CellCelector Flex Is Fast, Gentle and Reliable It is important when working with any cell system, but notably stem cells such as iPSCs, to maintain good cell health. The data here highlights the delicate, gentle picking and seeding capability of the CellCelector Flex. When stained with Propidium Iodide (PI), a stain that indicates cell death, manual manipulation of iPSCs produces an Figure 2. Picking iPSCs using the CellCelector Flex is accurate, fast, gentle and reliable. Micrographs taken using the CellCelector platform highlighting iPSC colonies selected by the system. (A) Manually and (B) CellCelector picked and seeded iPSC colony stained with propidium iodide (PI) to identify cell death. (C) Micrograph depicting an area of differentiation in a stem cell colony prior to picking with the CellCelector. (D) The same area of the culture plate shown in (C) after removal. (E) Micrograph of a large iPSC colony grown on a feeder layer, prior to picking a section of pluripotent cells. The bottom right of the colony has indications of spontaneous differentiation. (F) The colony in (E) after picking using the CellCelector Flex, the area of pluripotent cells targeted by the machine has been collected for further culture. Scale bar equals 500 μm. increased number of PI positive cells when compared to the CellCelector Flex, indicative of fewer healthy cells (Figure 2A). The CellCelector Flex colony also has less debris and more tightly defined borders (Figure 2B). The flexibility and power of the CellCelector Flex is exemplified by its capabilities, it is able to pick single iPSCs or whole iPSC colonies from a tissue culture plate. This provides the opportunity to select ideal colonies from cultures on a standard plate for further propagation. Additionally, portions of colonies can be selected for further culture. This is useful if a portion of the colony spontaneously differentiates. Differentiated sections can be removed or pluripotent sections can be picked for passaging or analysis (Figure 2C-F). Propidium iodide Propidium iodide C. Differentiated Section E. Pluripotent Section A. Manual B. CellCelector Flex D. Removal of Section F. Removal of Section Figure 3. Monitoring morphology and pluripotent potential during iPSC culture. Incucyte® images of iPSCs grown under optimized (mTESR Plus) and non-optimized (RPMI) conditions. (A, D) Fluorescent images of iPSCs stained with Nuclight Rapid Red Dye comparing nuclear density between conditions. (B, E) Phase contrast images of the same iPSCs showing morphological differences between the two variables. (C, F) Analysis masking on the Incucyte® depicting confluency and nuclear masking that can be used to determine the nuclear/ cytoplasm ratio illustrated in (G). Scale bar equals 400 μm. total nuclei area =nuclear/cytoplasm ratio total cytoplasmic area Monitoring Morphology and Pluripotent Potential During iPSC Culture The CellCelector Flex can be used within the same workflow as another Sartorius platform, the Incucyte® Live- Cell Analysis platform. This system provides tools for monitoring cells during culture within the incubator, so changes in morphology can be recorded and analyzed without requiring removal of culture plates. In the following case, losses in morphological indicators of pluripotency can be observed, recorded, and subsequent analysis can be performed to quantify these changes. Incucyte® images of iPSCs after 2 days in culture, show a marked difference in morphology between the optimized and non-optimized culture conditions. iPSCs grown in optimized conditions form tightly packed colonies with clearly defined edges, that ‘glow’ under phase images (Figure 3B), by contrast, non-optimized iPSCs are much more spread out and no longer form tightly packed colonies, they are beginning to resemble fibroblast cells (Figure 3E). Nuclear staining using Incucyte® Nuclight Rapid Red Dye also highlights the separation of the cells when grown in non-optimized conditions (Figure 3D), nuclei are much more spread out and lose the tight distribution found in optimized conditions (Figure 3A). Quantification of these morphological differences was performed using the Incucyte® Adherent Cell-by-Cell scan at 10X magnification and nuclear and cytoplasm area measurements were made using the Basic Analyzer and AI Confluence analysis (micrographs in Figure 3C, F) using the following equation to provide a nuclear/ cytoplasm ratio, a standard measurement used when studying iPSCs. The graph in Figure 3G illustrates the reduction in this ratio in the non-optimized conditions, from 0.6 to 0.4. The more iPSC like, and thus pluripotent, a cell is, the higher the nuclear/cytoplasm ratio. A D B E C F Nuclear/Cytoplasm Ratio 1.0 0.2 0.4 0.6 0.8 0.0 Optimized Non-optimized G. 6 Figure 4. Changes in iPSC marker expression analyzed with the iQue®3. Bar graphs of data collected in iQue Forecyt® software of iPSCs grown for (A) 2 days and (B) 4 days in optimized (mTESR Plus) and nonoptimized (RPMI) media to induce ‘differentiation’. Marker expression of SSEA-1 (non-pluripotent marker), SSEA-4 (pluripotent marker), TRA-1-60 (pluripotent marker) and ‘Pluripotent’ (SSEA-1 negative, SSEA-4/ TRA-1-60 positive) shown (± SEM, n=4). (C) Dot plots showing SSEA-1 and ‘Pluripotent’ marker raw data as presented in the iQue Forecyt® software of iPSCs grown under optimized and non-optimized conditions for 2 days (n=4). NCCIT and THP-1 are control cell lines for pluripotent marker expression and nonpluripotent marker expression, respectively. profile over the time course of these studies was observed (95 ± 0.4% for pluripotent markers and less than 1.8 ± 0.5% for SSEA-1). (Figure 4A, B). In addition, the increase in nonpluripotent marker SSEA-1 expression (57.5 ± 0.7%) is clear as early as 2 days post treatment (Figure 4A) and remains high throughout culture. In Figure 4C, (dot plots taken directly from iQue Forecyt® software) there is a clear shift in SSEA-1 expression between the optimized (1.63% SSEA-1 positive) and non-optimized conditions (57.5 % SSEA-1 positive) (upper two dot plots). The lower plots further illustrate the shift away from pluripotent marker expression in the non-optimized conditions, where the optimized iPSCs present a compact population in the upper right quadrant of the plot (SSEA- 4+, TRA-1-60+) while the non-optimized iPSCs present a much more spread population shifting into the TRA-1-60 negative portion of the plot. Percentage Expression of Live Cells THP-1 NCCIT Changes in iPSC Marker Expression Analyzed with the iQue®3 High-Throughput Cytometry Platform To investigate further the losses in pluripotency in iPSCs when cultured in non-optimal conditions, surface marker expression of specific pluripotency markers can be analyzed with the iQue® 3, requiring as little as 10 μL per sample. iPSCs grown in non-optimized conditions show rapid loss of pluripotency marker expression compared to optimized conditions (Figure 4). This indicates a loss in pluripotency correlating with the data collected on the Incucyte® platform (Figure 3). After 2 days in culture (Figure 4A), analysis of non-optimized conditions shows a decrease in expression of pluripotency markers SSEA-4 (97.3 ± 0.8%), TRA-1-60 (89.8 ± 0.9%), and the pluripotent population (34.6 ± 0.3%), with a further decrease after 4 days of treatment (SSEA-4 63.4 ± 2.9%, TRA-1-60 58.9 ± 2.9%, pluripotent population 19.3 ± 3.0%) when compared with optimized conditions (Figure 4B). In contrast, for the optimized iPSCs, no marked differences in expression A. 100 50 0 iPSC Optimized iPSC Non-optimized Percentage Expression of Live Cells THP-1 NCCIT B. 100 50 0 iPSC Optimized iPSC Non-optimized SSC-H SSEA-4 (RL 1-H) SSEA-4 (RL 1-H) SSC-H 107 107 0.49% 0.11% 15.96% 2.55% 99.40% 0.00% 80.64% 0.85% Region Set 2 107 Region Set 3 107 105 105 105 104 103 105 106 106 106 106 SSEA-1 (BL1-H) Optimized SSEA-1 negative Optimized Non-optimized SSEA-1 negative Non-optimized TRA-1-60 (BL2-H) TRA-1-60 (BL2-H) SSEA-1 (BL1-H) 105 105 105 105 106 106 107 106 106 103 103 103 103 104 104 104 104 102 102 C. SSEA-1 SSEA-4 TRA-1-60 Pluripotent 7 Figure 5. Surface and intracellular marker staining provides solutions for high throughput cellular characterization. SSEA-1 was used as a marker of normal, non-pluripotent cells, while SSEA-4, TRA-1-60, Sox 2, and Oct 3/4 were all used to characterize pluripotent cells. (A) Histograms and dot plots created in the Forecyt software system for iQue®3, showing the expression of various surface and intracellular markers in iPSC and control cells (n=4). (B) Heatmap from iQue Forecyt ® illustrating the expression of the same markers, representing the plate map and expression profile per well. (C) Bar graph showing marker expression data in 3rd party software (± SEM, n=4). Surface and Intracellular Marker Staining Provides Solutions for High-Throughput Cellular Characterization Using the iQue®3 to monitor intracellular markers in addition to surface markers further characterizes the pluripotency of cells. Using THP-1 cells as a non-pluripotent control, iPSCs were fixed, permeabilized and stained for the surface markers SSEA-1, SSEA-4 and TRA-1-60, in addition to the intracellular markers Oct 3/4 and Sox 2 (Figure 5). Dot plot data taken directly from iQue Forecyt® software, clearly show the expression of pluripotency markers SSEA-4, TRA- 1-60, Oct 3/4 and Sox 2 in iPSC cells (black) and the nonpluripotent marker, SSEA-1, only expressed in the THP-1 control cell line (yellow) (Figure 5A). The heatmap in Figure 5B illustrates this expression pattern in a plate view configuration, where black is high expression and yellow is low expression, exemplifying the flexibility of data presentation in the iQue Forecyt® software. Analysis of this data as a bar graph in Figure 5C further highlights the contrasting expression profiles of the two cell types. The ability to characterize a range of marker expression in cell lines, including iPSCs, via a flexible multiplexed workflow, exemplifies the power and utility of Sartorius platforms such as the iQue®3 High-Throughput Cytometry Platform. SSEA-1 SSEA-4 TRA-1-60 Sox 2 Oct 3/4 100 0 B. THP-1 iPSC Events 100 90 80 70 60 50 40 30 20 10 0 100 90 80 70 60 50 40 30 20 10 0 SSEA-1 (BL1-H) 102 103 Live Live Live Live Live Live Live Live Live Live 104 105 106 SSEA-1 (BL1-H) 102 103 104 105 106 107 SSEA-4 (RL1-H) 102 103 104 105 106 107 TRA-1-60 (BL2-H) 102 103 104 105 106 107 Sox 2 (VL1-H) 102 103 104 105 106 107 Oct 3/4 (VL2-H) 102 103 104 105 106 107 SSEA-1 (RL1-H) 102 103 104 105 106 TRA-1-60 (BL2-H) 102 103 104 105 106 Sox 2 (VL1-H) 102 103 104 105 106 Oct 3/4 (VL2-H) 102 103 104 105 106 140 120 100 80 60 40 20 0 SSC-H Events 107 106 105 104 103 SSC-H 107 106 105 104 103 SSC-H 107 106 105 104 103 SSC-H 107 106 105 104 103 SSC-H 107 106 105 104 103 140 120 100 80 60 40 20 0 Events 140 120 100 80 60 40 20 0 Events Samples THP-1 Samples iPSC SSEA-1 pos SSEA-4 pos TRA-1-60 pos Sox 2* Oct 3/4* A. Percentage Expression of Live Cells SSEA-1 SSEA-4 100 50 0 Surface Markers Intracellular Markers TRA-1-60 Sox 2 Oct 3/4 THP-1 iPSC C. 8 Specifications subject to change without notice. ©2023 All rights reserved. All names of Sartorius products are registered trademarks and the property of Sartorius AG and/or one of its affiliated companies. Culture-Maintain-characterize-iPSCs-App-Note-2307-en-L-Sartorius Status: 07 | 2023 Conclusions iPSCs are increasingly used in many areas of research, requiring specific conditions for optimal growth, to maintain pluripotency, viability, and propagation potential. These requirements are often expensive and methods for monitoring iPSC status can be complex and time intensive, requiring multiple complicated techniques and solutions. Using various Sartorius platforms throughout an iPSC culture workflow, we have shown how we can successfully pick and seed iPSCs, monitor their morphological status and characterize their pluripotency using the CellCelector Flex, the Incucyte® Live-Cell Analysis platform and the iQue®3 High-Throughput Cytometry Platformr. The key advantages of using this combined workflow over conventional methods are: 1. Consistency and reliability, the CellCelector Flex can reproducibly pick specific iPSC colonies for further testing or culture, maintaining high levels of cell health 2. The ability to monitor delicate iPSC line culture morphology and growth characteristics without removing plates from the incubator 3. Minimal sample volumes required to characterize precious cell types, with minimal attrition for downstream requirements 4. Multiplexing experiments providing flexibility for the characterization of multiple metrics, such as surface and intracellular marker expression, using the same platform The data presented here showcases the advantages of using a streamlined workflow combining multiple Sartorius systems for the culture, monitoring and characterization of iPSCs for several applications from drug development, disease modeling and clinical therapy research. References 1. Takahashi K, Yamanaka S. (2022) Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006 Aug 25;126(4):663-76. doi: 10.1016/j.cell.2006.07.024. Epub 2006 Aug 10. PMID: 16904174. North America Phone +1 734 769 1600 Europe Phone +44 1763 227400 Email: Japan Phone +81 3 6478 5202 China Phone +86 21 6878 2300 Rest of Asia Pacific and other countries around the world: Email: lps.opm.na@sartorius.com Phone +65 6872 3966 orderhandling.lps.ne@sartorius.com Email: sartoriusap@sartorius.com For questions, email: AskAScientist@sartorius.com Find out more: www.sartorius.com/ique Find out more: www.sartorius.com/incucyte Neurodegenerative diseases, which include Alzheimer’s disease and related dementias, Parkinson’s disease, and motor neuron diseases such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy, significantly impact individuals and society. Developing effective treatments for these conditions hinges on access to translational models that help identify drug candidates with a high likelihood of success in clinical trials. This article offers an overview of the role of complex cell models in neurodegenerative disease research, as well as advanced live-cell techniques for obtaining essential real-time insights from these systems. The Necessity of Complex Cell Models for Disease Modeling Traditional disease modeling has relied heavily on the use of immortalized cell lines, such as HeLa and HEK293 cells, and primary cells derived from animal or human tissues. While these models have facilitated many scientific breakthroughs, they inherently lack the complexity of human disease states. Complex cell models, such as iPSCs and 3D cultures, represent a paradigm shift in disease modeling.1 iPSCs, with their capacity to differentiate into any cell type, offer a renewable source of patient-specific cells that retain the donor’s genetic information. This allows for the modeling of diseases with a genetic component in a patient-specific way, providing insights into the personalized nature of disease progression and response to treatment. iPSCs also enable the study of rare diseases for which patient samples are scarce, broadening the scope of research and potential therapeutic interventions. Three-dimensional (3D) cell models, including organoids and spheroids, further enhance the capabilities of iPSCs by providing a scaffold for the development of tissue-like structures. These models replicate the architecture and multicellular complexity of organs, including the formation of gradients for oxygen, nutrients, and signaling molecules, which are essential for understanding disease progression and the efficacy of therapeutics. Advancing Neurodegenerative Disease Research: The Critical Role of Complex Cell Models and Live-Cell Techniques Tina Shahian, PhD — Content Writer - Sartorius Predictive Cellular Models for Neurodegenerative Diseases The use of iPSCs in neurodegenerative disease modeling enables detailed exploration of disease mechanisms with unprecedented precision. iPSC-derived neurons can display key Alzheimer’s features, including amyloid-beta peptide aggregation and tau hyperphosphorylation, providing a dynamic system for studying disease progression. Additionally, iPSCs allow for the study of neuronal loss and synaptic dysfunction, crucial to understanding neurodegeneration. Beyond their role in modeling disease pathology, iPSCs are transforming drug discovery and development. iPSCderived neural cells enable high-throughput screening to pinpoint potential therapeutics and assess drug toxicity and efficacy, thus fast-tracking the journey from laboratory research to clinical application. Stem cell-derived 3D cell culture techniques have significantly improved our capacity to model neurodegenerative diseases.2,3 For Alzheimer’s disease, 3D brain organoids enable the observation of amyloid plaque formation and neurofibrillary tangles, providing a more accurate platform for investigating disease mechanisms and evaluating drug candidates. These 3D models also enhance the study of non-neuronal factors in neurodegeneration, including microglial involvement in inflammation and the influence of astrocytes on neuronal health.4 Pros and Cons of Traditional Techniques for Cell Analysis Traditional cell biology techniques like flow cytometry and high-content imaging (HCI) have been pivotal in studying cellular processes and disease states. Flow cytometry analyzes individual cells, yielding detailed data on cell health, size, and marker expression through fluorophores and labeled antibodies. HCI enables the visualization and analysis of static cell populations, capturing heterogeneity and allowing for single-cell level subset analysis. However, these methods have limitations, especially with complex cell models. The preparatory and labeling processes required for flow cytometry and HCI can alter the cellular environment, potentially introducing artifacts that affect experimental results. Moreover, these techniques usually provide snapshots at single time points, missing the dynamic cellular changes over time that are crucial for understanding disease progression. Real-Time Monitoring of Live Cellular Behavior Live-cell analysis overcomes many of these limitations by enabling continuous monitoring. This method is especially useful for complex models, providing real-time insights into living cells’ behavior and function without disrupting their natural state. For example, live-cell analysis can observe the growth and maturation of iPSC-derived neurons or the development of neural networks in 3D brain organoids, offering a glimpse into these processes. Technologies like the Incucyte® Live-Cell Analysis System (Sartorius) are tailored for live-cell analysis, allowing for automated imaging and analysis within a cell incubator’s controlled environment. Its non-invasive approach permits the detection of gradual cellular changes in morphology, function, and interactions, crucial for studying diseases with slow cellular progression. Additionally, the system’s capability to simultaneously monitor multiple parameters, such as cell morphology and marker expression, is invaluable for understanding complex cellular behaviors like phagocytosis. Numerous studies have illustrated the utility of live-cell analysis in neuroscience research, including one by Jessica Tilman’s group at Axol Bioscience Ltd. demonstrating disease-specific functional impairments in ALS cells.5 Their work revealed morphological and functional differences between healthy and iPSC-derived ALS cells, with ALS motor neurons showing disorganized structures and erratic firing patterns, and ALS microglia demonstrating reduced phagocytosis. They used the Incucyte® system to measure spontaneous neuronal activity and microglial phagocytosis, highlighting the value of real-time monitoring of cellular behavior. Conclusion The integration of advanced cell models with live-cell analysis is a critical development in neurodegenerative disease research. This non-destructive approach allows for the continuous collection of vital data, enhancing our References 1. Langhans SA. Three-dimensional in vitro cell culture models in drug discovery and drug repositioning. Front Pharmacol. 9, 6 (2018). https://doi.org/10.3389/fphar.2018.00006 2. Lee HK, Velazquez Sanchez C, Chen M, Morin PJ, Wells JM, Hanlon EB, Xia W. Three-dimensional human neuro-spheroid model of Alzheimer’s disease based on differentiated induced pluripotent stem cells. PLoS ONE. 11, e0163072 (2016). https:// doi.org/10.1371/journal.pone.0163072 3. Park J, Wetzel I, Marriott I, Dréau D, D’Avanzo C, Kim DY, Tanzi RE, Cho H. A 3D human triculture system modeling neurodegeneration and neuroinflammation in Alzheimer’s disease. Nat Neurosci. 21, 941–951 (2018). https://doi.org/10.1038/ s41593-018-0175-4 4. Park J, Wetzel I, Marriott I, Dréau D, D’Avanzo C, Kim DY, Tanzi RE, Cho H. A 3D human triculture system modeling neurodegeneration and neuroinflammation in Alzheimer’s disease. Nat Neurosci. 21, 941–951 (2018). https://doi.org/10.1038/ s41593-018-0175-4 5. Tilman J. iPSC-derived motor neurons and microglia from ALS background display disease phenotype. Axol Bioscience Ltd. (2023, August 31). Available from: https://www.sartorius.com/en/products/live-cell-imaging-analysis/live-cell-analysisresources/ ipsc-derived-motor-neurons-and-microglia-white-paper White Paper August 31, 2023 Keywords or phrases: ALS, Neurodegenerative, iPSC, Immunocytochemistry, Neuronal Activity, Phagocytosis, Motor Neurons, Microglia, Live-Cell Analysis iPSC-Derived Motor Neurons and Microglia From ALS Background Display Disease Phenotype Jessica Tilman Axol Bioscience Ltd, Roslin Innovation Centre, Charnock Bradley Building, Easter Bush Campus, Easter Bush EH25 9RG UK Correspondence Email: AskAScientist@sartorius.com Abstract Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder caused by the degeneration of motor neurons, and ultimately results in death. Despite the fatal nature of this disease, there is no current cure or effective treatment available. The clear overlap between ALS and Frontotemporal Dementia (FTD) has led to the belief that it is not only disruption in motor neurons which drives ALS symptoms, but other cell types such as microglia, the main immune cell found in the brain, may also play a role. To investigate this, fibroblasts taken from a healthy individual and an ALS patient carrying a C9orf72 hexanucleotide expansion (GGGGCC >145) were reprogrammed to Induced Pluripotent Stem Cells (iPSCs), and then differentiated to motor neurons and microglia alongside controls. The cells were then assessed for differences in morphology and functional activity, measured via electrophysiology, spontaneous neural activity, and microglial phagocytosis. Diseased iPSC-derived motor neurons exhibited less organized morphology compared to control, as well as less synchronized firing patterns and hyperexcitability. ALS patient-derived microglia demonstrated a decreased capability for phagocytosis, particularly when cryopreserved. Taken together, these results demonstrate clear morphological and functional differences in differentiated cells derived from a C9orf72-positive ALS patient, compared to healthy control cells which can therefore be used as a robust model for C9orf72 ALS research and drug discovery. For further information, visit www.sartorius.com 2 Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder caused by the degeneration of motor neurons, and ultimately results in death on average 2–3 years after onset of symptoms. 5–10% of ALS cases have a familial background with an autosomal dominant inheritance pattern. Of these, mutations in C9orf72 account for the highest number of cases1. Sporadic ALS accounts for the remaining cases, with a high degree of them containing identifiable genetic causes. There is a clear overlap between ALS and FTD with approximately 5% of ALS patients showing overt characteristics of FTD, and up to 50% showing more subtle similarities2. This observation has led to the belief that it is not only disruption in motor neurons which drives ALS symptoms, but other cell types play an important role too. Microglia are the main immune cell found in the brain, with key roles in maintaining neuronal homeostasis as well as driving inflammatory responses3. Changes in inflammatory response and phagocytosis have been heavily implicated in neurodegeneration and FTD, and more recently have been shown to be defective in ALS. C9orf72 mutation has been shown to drive an exaggerated immune response in microglia and lead to impaired phagocytosis and excitotoxicity in motor neurons3,4. ALS has an incidence rate of 2:100,000 per year, and despite the fatal nature of this disease, there is no current cure or effective treatment available1. There has been significant progress in the field with greater understanding of the genetics, pathology, and biomarkers of ALS, but development of novel and effective therapies has in part been hindered by a lack of relevant and translational pre-clinical models. Understanding how different cell types become impaired and drive the development and progression of ALS is crucial in developing novel and effective treatments. Use of relevant pre-clinical models is essential in not only understanding disease onset and progression, but also in gaining insight into the functionality of potential new treatments. ALS is a heterogeneous condition, and as such one treatment plan is unlikely to work for all patients. Mouse models are limited in this respect, as in most cases they rely on genetic modification or silencing of a key gene and would therefore only apply to patients with the same mutation. iPSC-derived models provide a relevant human platform which is reproducible and scalable. More importantly, the ability to reprogram samples directly from affected individuals allows for patient stratification based on not only genetic factors, but also on defined symptoms. This is invaluable in determining which treatments may work more effectively for subpopulations of patients with ALS and drive more effective clinical trials. An additional benefit of using iPSC-derived cells is the ability to differentiate these cells towards different lineages and generate several cell types which all contribute to development of ALS. Motor neurons harbouring a C9orf72 mutation are known to be hyperexcitable and to become dysfunctional in ALS. However, C9orf72 is most highly expressed in myeloid cells, implying an important contribution from these cells. Using iPSC-derived motor neurons and microglia from the same patient background enables for the study of these cells in isolation as well as in co-culture. Method and Assays axoLines™ iPSCs: Fibroblasts taken from a healthy individual and an ALS patient carrying a C9orf72 hexanucleotide expansion (GGGGCC >145) were reprogrammed to iPSCs using Sendai virus or episomal vector. axoCells™ iPSC-Derived Motor Neurons: To generate mature motor neurons, iPSCs were differentiated to axoCells motor neuron progenitor cells (ax0078 and ax0074). Progenitor cells were generated in monolayer using small molecule induction methods. Progenitors were then matured to motor neurons for up to 20 days using the Axol Bioscience methodology to include neural media with the addition of Axol Bioscience motor neuron accelerator (ax0072 and ax0179). Motor neurons were characterized by immunocytochemistry, showing expression of HB9, LIM3, OLIG2, and TUJ1 by day 104 of maturation. axoCells™ iPSC-Derived Microglia: iPSCs were differentiated to macrophage-precursors by mesoderm induction via the formation of embryoid bodies. Precursor cells were characterised by flow cytometry for key macrophage|monocyte markers (CD14, CD11b, and CD16) before maturing the cells to microglia for a further 7 days using a cocktail of growth factors. At day 7 cells were either used for assays or cryopreserved. Upon thaw, cryopreserved microglia were plated on cell culture plates coated with Surebond XF and Concanavalin A and matured for a further 7 days before performing assays. Fresh and cryopreserved microglia were characterized by immunocytochemistry for expression of key microglia markers TMEM119, P2RY12, CX3CR1, and Iba1. Immunocytochemistry: Cells were fixed using 4% PFA for 10 minutes and washed in phosphate buffered saline (PBS). Cells were permeabilised using 1% Triton X and blocked in buffer containing Tween 20 and Donkey serum. Cells were then stained with primary antibodies for 2 hours at room temperature (RT) and washed twice using PBS-Tween. Secondary antibodies conjugated to FITC or AF-594 were then added for a further 2 hour incubation at RT. All wells were treated with ProLong™ Gold Antifade reagent containing DAPI and imaged using a Leica microscope. Introduction 3 Multi-Electrode Array (MEA): Motor neuron progenitor cells were seeded at 150,000 cells/cm2 in 48 well Axion CytoView MEA plates coated with vitronectin. Neurons were matured for 10 days, and MEA recordings of spontaneous firing taken throughout this process using an Axion Maestro Pro system. Recordings were analyzed to provide information on neuronal activity, burst firing, and synchronicity. Spontaneous Neuronal Activity (SNA): On day two of maturation of motor neurons, cells were transfected with Incucyte® Neuroburst Orange Lentivirus (Sartorius, Cat. no. 4736), a lentiviral based live-cell neuronal labeling reagent driven by a synapsin promoter, leading to the long term expression of an orange fluorescent calcium indicator. Motor neurons were imaged daily up to day 21 of maturation. Images were acquired using an Incucyte® S3 Live-Cell Analysis System configured with an Orange/NIR optical module and integrated Incucyte® Neuronal Activity Analysis Software Module was used to determine metrics of spontaneous neuronal activity. Phagocytosis: Myelin basic protein (MBP) was labeled with pHrodo® Orange Cell Labeling Dye for Incucyte® (Sartorius, Cat. no.: 4766 ) following the manufacturer’s specifications. Labeled MBP was used as bait for microglia. Briefly, microglia were seeded in 384 well plates and matured for 7 days. On day 7, bait was added to each well and imaged using an Incucyte® S3 Live- Cell Analysis System for up to 24 hours. Cytochalasin D was added to control wells 30 minutes prior to addition of bait. iPSC-Derived Motor Neuron Morphology axoCells™ iPSC-derived motor neurons undergo quality control by staining for key markers such as CHAT, TUJ1, and HB9 (not shown) to ensure maturity (Figure 1). While these markers are present in both control and ALS motor neurons, the morphology of the neuronal networks shows differences between the two, indicating a disease driven phenotype. Control motor neurons form large clusters of cell bodies connected by strong cabling networks formed by neurites. In comparison, ALS motor neurons form many smaller clusters across the culture with a more disordered network formation. This could drive the hyperexcitability observed in ALS motor neuron cultures and explain in part the loss of synchronicity in this population. Phase contrast Blue: DAPI Figure 1: Mature axoCells™ iPSC-derived motor neurons (control and ALS) immunocytochemistry. Cells were matured for 20 days and stained for markers of motor neurons. DAPI was used as a nuclear dye. Ax0078 (control) Ax0074 (ALS C9orf72) Green: HB9 Red: TUJ1 Merge 4 Figure 2: MEA recordings of day 10 mature motor neurons from healthy and ALS patients. Traces of activity detected for each cell line (top) and raster plot (bottom) demonstrating the difference in firing frequency and synchronicity. axoCells™ Motor Neuron (control-derived) Motor Neuron MEA Sodium Spike Profile axoCells™ Motor Neuron (ALS-derived) Motor Neuron MEA Sodium Spike Profile Time (sec) Synchronized clustered firing 100 200 300 400 500 600 There are several methods that can be used to assess neuronal function in vitro, one of which is using a multi electrode array (MEA) system. The functional behavior of neuronal networks can be captured to investigate electrical activity by measuring spontaneous action potentials (field potentials). Using this system, electrical activity can be compared between healthy and disease motor neurons to identify patterns of firing which contribute to the disease phenotype. In this way, a ‘disease phenotype’ can be defined and used to test potential drug candidates that may lead to a return to normal firing in motor neurons from a disease background. Another method to assess neuronal function is to interrogate the function of the whole well, as opposed to MEA in which a certain number of electrodes provide the information for the cell networks directly on them. Spontaneous neuronal activity can be measured using the Incucyte® Neuronal Activity Assay, wherein cells are monitored daily over the maturation process. Cells are transfected with Incucyte® Neuroburst Orange Lentivirus, a genetically-encoded calcium sensor, resulting in long term non-perturbing expression in neuronal cell types. Using integrated software, calcium flux can then be kinetically measured as a readout for spontaneous neuronal activity and enabling assessment of burst rate, burst duration, and synchronicity (mean correlation) to investigate functional differences between cell lines. Data obtained from healthyand ALS-derived motor neurons shows that control neurons have a regular and synchronized firing pattern while ALS neurons fire more frequently and with reduced synchronicity (Figure 3 A). ALS motor neurons exhibited significantly higher burst rate compared to the control line, along with lower burst duration and lower mean correlation (hence less synchronized burst firing) (Figure 3 B). Synchronized clustered firing Time (sec) 100 150 200 250 300 350 400 450 500 550 Motor neurons from control and ALS patient backgrounds were assessed using an Axion MEA system and demonstrated a clear disease phenotype (Figure 2). Control neurons exhibited regular and synchronized firing while ALS neurons showed more random clustered firing. This can be observed in the field potential traces (top) and in the raster plot (bottom). This disease phenotype is in line with the physiological dysfunction observed in neurons from ALS patients, including hyperexcitability and a loss of synchronicity within the cell population. axoCells™ ALS Derived Motor Neurons Display Hyperexcitability Across Several Assay Platforms 5 Time (sec) Intensity (OCU) 18 0 10 20 30 40 50 60 70 80 90 16 14 12 10 8 6 4 2 0 Time (sec) Intensity (OCU) 0 10 20 30 40 50 60 70 80 90 2 10 3 4 5 6 7 8 9 10 A) axoCells™ Motor Neuron axoCells™ Motor Neuron B) Mean Burst Rate Burst rate (1/min) 6 ax0074 (ALS) ax0078 (cont) 4 2 0 * Mean correlation 1.2 ax0074 (ALS) ax0078 (cont) 0.8 0.4 0 ** 1.0 0.6 0.2 Burst duration (sec) 15 ax0074 (ALS) ax0078 (cont) 10 05 0 ** Mean Correlation Mean Burst Duration Figure 3: Spontaneous neuronal activity assay on day 18 motor neurons. Calcium signalling was monitored and analysed using the Incucyte® Neuronal Activity Software Module. A) Burst patterns for control and ALS motor neurons. B) Neuronal activity analysis for calcium signalling. Statistical significance was assessed using a non-parametric T-test, *p<0.05, **p<0.01. iPSC-derived microglia provide a platform to investigate how the immune response contributes to neurodegeneration and thus can be used for disease modeling and drug discovery. axoCells™ iPSC-derived microglia show expression of key markers by immunocytochemistry, including TMEM119, Iba1, P2RY12, and CX3CR1. Using iPSC-derived microglia, a clear difference could be observed in the capability of these cells to uptake myelin basic protein (MBP) with significantly higher phagocytosis in healthy cells compared to those from an ALS patient (Figure 4). In addition, ALS microglia were more sensitive to the cryopreservation process, with the difference between healthy and disease cells exacerbated in thawed cells. Together this data indicate that ALS microglia are affected by the C9orf72 expansion in ALS with decreased phagocytosis and potentially becoming more sensitive to stresses such as cryopreservation. ALS Disease Phenotype is Observed in Microglia Phagocytosis North America Sartorius Corporation 565 Johnson Avenue Bohemia, NY 11716 USA Phone +1 734 769 1600 Email: orders.US07@sartorius.com Europe Sartorius UK Ltd. Longmead Business Centre Blenheim Road Epsom Surrey, KT19 9QQ United Kingdom Phone +44 1763 227400 Email: eurordersUK03@sartorius.com For further information, visit www.sartorius.com Axol Bioscience Ltd Roslin Innovation Centre, Charnock Bradley Building, Easter Bush Campus, Easter Bush EH25 9RG UK Asia Pacific Sartorius Japan K.K 4th Floor, Daiwa Shinagawa North Bldg. 1-8-11, Kita-Shinagawa 1-chome Shinagawa-Ku Tokyo 140-0001 Japan Phone +813 6478 5202 Email: eurordersUS07@sartorius.com Specifications subject to change without notice. ©2023. All rights reserved. All names of Sartorius products are registered trademarks and the property of Sartorius AG and | or one of its affiliated companies. IPSC-Derived-Motor-Neurons-Whitepaper-en-Sartorius. Status: 10 | 2023 Figure 4: axoCells™ iPSC-derived microglia characterized by A) immunocytochemistry for key markers (representative images); B) phagocytosis of pHrodo® for Incucyte® labeled Myelin Basic Protein (MBP) was assessed on an Incucyte® Live-Cell Analysis System up to 24h using fresh and cryopreserved microglia. Cytochalasin D (10 μM) was used as a control. Statistical significance was assessed using a one-way ANOVA, **p<0.01, ***p<0.001, ****p<0.001. Summary & Outlook iPSC-derived cells provide a valuable tool for disease modelling, with the ability to use cells directly from affected patients, as well as the potential to drive these cells towards multiple lineages. In this study, axoCells™ motor neurons and microglia from the same healthy and ALS axoLines™ iPSCs were shown to exhibit disease phenotypes which can be quantified and used for future drug discovery purposes. Further characterization of both cell types could elucidate additional functional dysregulation compared to healthy cells which may provide valuable insight into future potential treatments. In addition to understanding disease phenotype for each cell type, the potential to develop a co-culture system would add value in determining how these cells interact and whether both microglia and motor neurons from ALS patients could drive a more pronounced disease phenotype. References 1. Mead, R.J., Shan, N., Reiser, H.J. et al. Amyotrophic lateral sclerosis: a neurodegenerative disorder poised for successful therapeutic translation. Nat Rev Drug Discov 22, 185–212 (2023). https://doi.org/10.1038/s41573-022-00612-2 2. Poulomi Banerjee et al. Cell-autonomous immune dysfunction driven by disrupted autophagy in C9orf72-ALS iPSC-derived microglia contributes to neurodegeneration. Sci. Adv.9,eabq0651(2023).DOI:10.1126/sciadv.abq0651 3. J. Brettschneider, J. B. Toledo, V. M. van Deerlin, L. Elman, L. McCluskey, V. M.-Y. Lee, J. Q. Trojanowski, Microglial activation correlates with disease progression and upper motor neuron clinical symptoms in amyotrophic lateral sclerosis. PLOS ONE 7, e39216 (2012). 4. O. Dols-Icardo, V. Montal, S. Sirisi, G. López-Pernas, L. Cervera-Carles, M. Querol-Vilaseca, L. Muñoz, O. Belbin, D. Alcolea, L. Molina-Porcel, J. Pegueroles, J. Turón-Sans, R. Blesa, A. Lleó, J. Fortea, R. Rojas-García, J. Clarimón, Motor cortex transcriptome reveals microglial key events in amyotrophic lateral sclerosis. A) Red: TMEM119 Blue: DAPI Red: P2RY12 Blue: DAPI Green: Iba1 Blue: DAPII Red: CX3CR1 Blue: DAPI Integrated total intensity 0.8 Healthy ALS (C9orf72) 0.4 0.0 ** Cyto D 10μM **** 0.6 0.2 B) MBP 24h (fresh) Relative Phagocytosis 0.5 Healthy ALS (C9orf72) 0.3 0.0 *** Cyto D *** 0.4 0.2 0.1 MBP 24h (Cryopreserved) Note: axoCells™ and axoLines™ are registered trademarks of Axol Bioscience iPSCs in Focus: Translational Strategies for Reproducible Organoid Research Effective analysis of 3D cell models can be challenging. The Incucyte® Live-cell Analysis System is a turnkey solution that automatically monitors and quantifies cell formation, growth, and health in real time directly inside the incubator. Multiple assays are available for real-time visualization and label-free objective quantification to optimize organoid and spheroid culture conditions. Simplifying Progress Specifications subject to change without notice. © 2024. All rights reserved. Incucyte and all names of Sartorius products are registered trademarks and the property of Sartorius AG. Application Note December 01, 2022 Keywords or phrases: Neuroscience, Neuronal activity, Neuronal Function, GECI, Calcium flux, iPSC, Cell Analysis Systems Find out more: www.sartorius.com/incucyte Long-Term Live-Cell Visualization and Quantification of Neuronal Activity S. L. Alcantara¹, J. Trigg¹, J. Rauch², L. Oupicka², N. Holtz², E. Endsley², T. Dale¹* ¹ Sartorius UK Ltd., Royston, Hertfordshire, UK ² Sartorius Corporation, 300 West Morgan Road, Ann Arbor, MI 48108 USA * With thanks to T. Campbell**, T. Jackson, A. Overland, J. Brown, T. G. Garay ** Talisman-therapeutics.com Introduction A major impediment to studying diseases affecting the human nervous system is the ability to monitor, analyze, and quantify the activity of neuronal cell populations that accurately represent human phenotypes. These limitations are the consequence of minimal access to cells from human patient tissue, as well as a lack of purposebuilt instrumentation enabling functional measurements from neuronal cells at sufficient throughput to permit full phenotypic characterizations. With the advent of cellular reprogramming technologies, there has been abundant research toward protocol development to differentiate human induced pluripotent stem cells (hiPSCs) into multiple cell populations found in the brain (e.g. neuronal, glial, immunological, etc.). This has resulted in the generation of many different neuronal cell models (e.g. dopaminergic, GABAergic, glutamatergic, peripheral, etc.), most of which remain poorly characterized. This imparts a requirement to better understand in vitro cellular models and identify means by which they could be refined. The Incucyte® Live-Cell Analysis System technology, methodology, and applications described within this application note were designed with these issues in mind. That is, to provide researchers with a set of automated tools in order to facilitate the evaluation, characterization, and validation of complex neuronal models. Susana Lopez Alcantara — Scientist – Sartorius Jasmine Trigg — Scientist – Sartorius John Rauch — Manager of Cell Assays – Sartorius Libby Oupicka — Scientist – Sartorius Nevine Holtz, PhD — Manager of Advanced Algorithm Development – Sartorius Eric Endsley — Head of Technology Translation – Sartorius Tim Dale — Head of LPS Applications – Sartorius With thanks to: T. Campbell — Talisman-therapeutics.com T. Jackson, A. Overland, J. Brown, T. G. Garay Burst Rate Correlation Mean Correlation Mean Burst Rate Time (days) 1.00 0.75 0.50 0.25 0.00 9/min 6 3 0 0 5 10 15 20 Figure 1: Incucyte® Neuronal Activity Assay Workflow The Incucyte® Neuronal Activity Assay allows for measurements of long-term synaptic activity from neuronal cell models in physiologically relevant conditions. The assay provides an end-to-end solution consisting of reagents, protocols, instrumentation, and software for a user-friendly workflow. 2 Assay Principle While measuring morphological features of neurons (e.g. neurite outgrowth) can provide insight into their structure, neuronal activity assays provide a more exquisite and sophisticated understanding of how neurons function, form synaptic connections with other neurons, and how they respond to their environment. In this application note, we describe an integrated solution for long-term neuronal activity measurements based on Incucyte® Neuroburst Orange Lentivirus, a neuronal specific, live-cell genetically-encoded calcium indicator (GECI) and the Incucyte® Live-Cell Analysis Systems configured with either an Orange/NIR or a Green/Orange/NIR Optical Module. Along with integrated analysis tools provided by the Incucyte® Neuronal Activity Analysis Software Module, this enables automated quantification of calcium oscillations and morphological monitoring of thousands of functional neurons within a culture over long periods of time—days, weeks, and months (Figure 1). This approach provides researchers the opportunity to better understand how and when network connections are made between cells in culture, and how the environmental context (e.g. drug treatments, stromal cells, media formulations, etc.) can alter their behavior. The Incucyte® Live-Cell Analysis System user interface is designed to visualize neuronal activity within each well of a 96-well plate. Each scan consists of a 30–180 second “Stare Mode” capture of cellular activity at a rate of three frames per second. Each “Stare Mode”-acquired movie is distilled into a single range image to allow for simple viewing (Figure 2B). This image represents the range of intensities that are detected from each cell within the culture over the specified scan time. Using this image, automated image segmentation tools are used to identify active objects (cells) within each well (Figure 2C). Based on the changing fluorescent intensity of each individual cell, intensity traces are displayed for every active cell in the culture (Figure 2D). Scanning is typically completed once every 24 hours. As shown in these sample traces of iPSC-derived iCell® GlutaNeurons (Cellular Dynamics), the activity within these cultures can significantly change from day-to-day as the network matures, in this case with minimal activity at Day 4, a gradual increase at Day 7, and highly synchronous activity visualized at Day 12 and Day 17. Once these data are collected, several automated metrics are calculated for each well and at each scan time, allowing for simple visualization of changing metrics over the full time-course of the experiment (Table 1). 1. Prepare assay plate Infect neurons in mono- or co-culture with Incucyte® Neuroburst Orange Lentivirus. 2. Acquire movies Capture short-term, calcium-flux kinetics using Incucyte® Stare Mode acquisition. 3. Analyze active cells Quantify burst rate of active neurons in every movie and visually assess morphology with phase-contrast images. 4. Conduct chronic studies Continuously interrogate dynamic changes in the same population of cells in individual wells over weeks or months. Active Objects=1363 Mean Correlation=0.493 Active Objects=118 Mean Correlation=0.0161 Active Objects=2003 Mean Correlation=0.864 Active Objects=2028 Mean Correlation=0.828 Intensity (OCU) Intensity (OCU) Intensity (OCU) Intensity (OCU) 0 0 0 0 60 60 60 60 120 120 120 120 180 180 180 180 Time (sec) Time (sec) Time (sec) Time (sec) 4.8 4.8 4.8 4.8 3.6 3.6 3.6 3.6 2.4 2.4 2.4 2.4 1.2 1.2 1.2 1.2 0 0 0 0 Figure 2: Incucyte® Neuronal Activity Assay Protocol and Purpose-built Software Quick guide workflow of Incucyte® Neuroburst Orange Lentivirus infection protocol (A). The Incucyte® Neuronal Activity Analysis Software Module user interface is capable of displaying object traces, viewing movies, and longitudinal data of neuronal activity from each well (B). Fluorescent range image and automated segmentation mask of each active object represents a snapshot of activity over the complete scan (C). An example of iCell® GlutaNeuron calcium traces from each 3 minute scan indicate changing neuronal activity (fluorescence intensity) over 17 days in culture (D). B. C. D. Fluorescent Range Day 4 Day 12 Active Object Mask Day 7 Day 19 3 Coat plate with matrix of choice and incubate at ambient temperature overnight. Plate Incucyte® rCortical Neurons. Plate Incucyte® rAstrocytes. 1. Remove Incucyte® Neuroburst Orange Lentivirus. 2. Add Uridine + 5- Fluoro-2’- deoxyuridine. 3. Start Neuronal Activity scanning. Add Incucyte® Neuroburst Orange Lentivirus. 1. DIV: -1 2. DIV: 0 3. DIV: 0 + 2 hr 4. DIV: 2 5. DIV: 3 A. Quick Guide: Incucyte® Neuroburst Orange Lentivirus Neurons per well Table 1: Neuronal Activity Analysis Metrics Figure 3: Functional Activity of Primary Neurons. Primary rat forebrain neurons were seeded at 40K (rows A and B), 20K (rows C and D), 10K (rows E and F), and 5K (rows G and H) cells/well. All densities of neurons were plated in a co-culture with primary rat astrocytes seeded at 15K cells/well and transduced with the Incucyte® Neuroburst Orange Lentivirus. 96-well vessel view of the range image over the course of the scan provides a snapshot of active wells at each time point (A). Summary traces of fluorescence intensity across all active objects for the 96-well plate at Day 12 provide an overview of activity and display metrics of bursting intensity, active object number and mean correlation (B). 96-well throughput with high kinetic reproducibility over 12 days in culture (C). A. B. Summary Trace Activity at Day 12 C. Number of Active Objects over 12 Days 1 A B C D E F G H 2 3 4 5 6 7 8 9 10 11 12 4 Metric Description Active Object Count (1/image) The number of objects (cells/cell clusters) that burst at least once above the Minimum Burst threshold over the total scan time. Mean Intensity (OCU) The mean intensity of an object over the total scan time. All objects within the image are calculated individually, then values are averaged. Mean Correlation Every object is compared to every other object in the image to generate a value between -1 and 1, with 0 being completely random and 1 being highly synchronized. This is a measure of network connectivity. Mean Burst Duration (sec) The duration of each calcium burst over the total scan time is calculated individually, then values are averaged. Mean Burst Rate (1/min) The number of calcium bursts over the total scan time divided by the scan time in min. Mean Burst Strength (OCU) The area under each calcium burst divided by the duration of that burst is calculated individually, then values are averaged. Results Optimization of Incucyte® Neuroburst Orange Lentivirus Primary rat neurons (E18) in co-culture with primary rat astrocytes represent a well-tested model for studying neuronal activity. In this experiment, E18 rat forebrain neurons were plated at decreasing cell densities (5–40K/well) in co-culture with a fixed number of rat astrocytes (15K per well). As visualized in Figure 3A, fluorescence intensity within the range image strongly correlates with cell density, with the highest amount of activity observed at 40K neurons/well. The range image also provides the researcher with a qualitative assessment of morphology, toxicity, and transduction efficiency. Summary Ca2+ traces of neuronal activity provide a quantitative assessment of activity within each well, and density of neurons tested was optimal for visualization of neuronal activity within each scan (Figure 3B) and detection of active objects over the full 12-day time course (Figure 3C). 5 Functional Profiling of Different iPSC-derived Neurons Using the Incucyte® Live-Cell Analysis System and the Incucyte® Neuroburst Orange Lentivirus, we evaluated four different types of iPSC-derived neurons over 30–50 days in culture. These included iCell® GlutaNeurons (Figure 4A), iCell® GABANeurons (Figure 4B), iCell® DopaNeurons (Figure 4C) co-cultured with primary rat astrocytes, as well as CNS.4U neurons (Figure 4D). iCell® GlutaNeurons, described as human glutamatergicenriched cortical neurons derived from iPSCs, displayed a rapid induction of calcium burst activity in >1500 cells that became highly correlated within 10 days of co-culture. iCell® GABANeurons, characterized as a culture of >95% pure population of GABAergic (inhibitory) neurons, also displayed a rapid increase in the number of cells with calcium burst activity within the first week of co-culture. However, iCell® GABANeurons did not display significant correlation at any time-point tested, in line with their inhibitory phenotype. A closer examination of cellular activity at Day 14, displayed as object traces over the full 3 minute scan (Figure 4A and 4B), supports the observation of a significant number of active cells in both the iCell® Gluta- and GABANeurons; the former displaying higher calcium burst intensity and synchronicity when compared to the latter. Interestingly, the kinetics of iCell® DopaNeuron activity was strikingly similar to iCell® GlutaNeurons, illustrating a very rapid induction of highly active, highly correlated networks within the first 10 days of culture. Ncardia® CNS.4U cells represent an in vitro coculture model of hiPSC-derived neurons and astrocytes. These cells showed significant activity from nearly 1200 cells within the first week of culture and an increase in correlated activity (network connectivity) at approximately Day 34 in culture, reaching a correlation of 0.7 at Day 45 when the experiment was terminated. 0 0 0 0 0 0 Active Object # Correlation Active Object # Correlation Active Object # Correlation Active Object # Correlation 30 100 120 140 160 180 100 120 140 160 180 30 30 10 30 40 40 10 10 5 10 20 20 5 5 15 5 60 80 60 80 15 15 20 15 20 20 25 20 25 25 25 Days Time (sec) Time (sec) Days Days Days 1.0 0.8 0.6 0.4 0.2 0.0 2.8 2 1 0 2.8 2 1 0 1.0 0.8 0.6 0.4 0.2 0.0 1.0 0.8 0.6 0.4 0.2 0.0 1.0 0.8 0.6 0.4 0.2 0.0 2000 1500 1000 500 0 3000 2000 1000 0 1500 1000 500 0 1000 800 600 400 200 0 Figure 4: Functional Activity of Different iPSC-derived Neurons iCell® GlutaNeurons, iCell® GABANeurons, iCell® DopaNeurons (Cellular Dynamics International) and CNS.4U neurons (Ncardia®) were all seeded at 20K cells/well. iCell® GlutaNeurons, iCell® GABANeurons and iCell® DopaNeurons were also plated with a co-culture of rat astrocytes seeded at 15K cells/well. Neurons were infected with Incucyte® Neuroburst Orange Lentivirus, and Active Object Number and Mean Correlation were quantified for up to 45 days. Example calcium oscillation traces and kinetic graphs of activity metrics over time for iCell® GlutaNeurons (A) and iCell® GABANeurons (B). Mean Correlation and Active Object Count were quantified for iCell® DopaNeurons (25 days) (C) and CNS.4U neurons (45 days) (D). Data points represent Mean ± SEM. A. iCell® GlutaNeurons C. iCell® DopaNeurons Mean Correlation Intensity (OCU) Intensity (OCU) Mean Correlation Mean Correlation Mean Correlation Active Objects Active Objects Active Objects Active Objects B. iCell® GABANeurons D. CNS.4U Figure 5: Quantifying Pharmacological Neurotoxic Effects of Chemotherapeutic Taxol ® Rat cortical neurons seeded at 30K cells/well were co-cultured with rat astrocytes seeded at 15K cells/well and transduced with Incucyte® Neuroburst Orange or Neurolight Orange Lentivirus at Day 3 in culture. Live-cell analysis measurements were made each day using the Incucyte® Live-Cell Analysis System. After 11 days, neural networks had fully formed and stabilized. Taxol® or vehicle control was then added and cultures were monitored for an additional 11 days. Time courses of neurite development (A) and neuronal activity (B) prior to, and after the addition of, control or increasing concentrations of Taxol® are shown. Potency (IC50 values) plotted against time post-treatment for neuronal activity (grey) and neurite length (orange) (C). Data is expressed as % neurite length or active object count, normalized to the pre-treatment value. Data points represent Mean ± SEM. Neuronal activity summary traces at pre-treatment and at 5, 10, and 15 days post-treatment display decreased activity levels over the course of the experiment (D). D. Pre-treatment Drug: Day 5 Drug: Day 10 Drug: Day 15 10-6 M 10-7 M 10-8 M 10-9 M 10-10 M 10-11 M 10-12 M Vehicle 0 7 14 21 0 7 14 21 2 4 6 8 10 Days Days Days 120 80 40 0 120 80 40 0 Neurite Length Neuronal Activity 1000 100 10 A. B. C. Normalized Neurite Length Normalized Active Objects IC50 (pM) 6 Insights Into Structure-Function Quantification Peripheral neuropathies are a common side effect of chemotherapeutic drugs such as paclitaxel (Taxol®) and are associated with numbness and loss of sensory function. To study potential neurotoxic effects, primary rat cortical neurons were first co-cultured with primary rat astrocytes for 11 days, allowing the cultures to mature and stabilize. Baseline measurements of activity and morphology were made each day using Incucyte® Neuroburst Orange and Incucyte® Neurolight Orange Lentivirus respectively (Figure 5). At Day 11, cultures were treated with a range of concentrations of Taxol®. Activity and morphology were monitored for a further 11 days in culture. Figure 5 illustrates that by Day 21, at sub-nanomolar (<10-⁹ M) concentrations of Taxol® only small changes in neurite length were observed, while a reduction in neuronal activity occurred (Figure 5C). Individual well traces indicated both concentrationand time-dependent responses of neuronal activity following Taxol® treatment as shown in Figure 5D. Stem Cell Development Workflow The development of advanced human cell-based models, such as human iPSC-derived neurons and glia in monoculture and co-culture, that are species- and -disease relevant, have increased in recent years. Live-cell analysis provides insights into these translational models and enables the opportunity to identify novel pharmacological treatments for neurodegenerative diseases. Robust methods are needed when developing human iPSC-derived models. This includes the characterization of the cells and quality control (QC) of the final model. Differentiation from Human iPSCs – Phase Images Neural Maintenance Media 16-Day Neural Differentiation of iPSCs Using Proprietary Methods (Based on Shi et al., 2012 Nature Protocols 7:1836-46) Monitor Neural Differentiation with Phase Microscope Day 30 Day 60 Transcriptomic Profiling Transcriptomic Profiling Proteomic Profiling by ICC Functional QC Talisman Workflow Transcriptomic Profiling Neurite Outgrowth Late Born Upper ICC Layer Neurons and Ostrocytes Day 60+ Early Born Deep Layer Neurons Day 25 Cortical Rosettes Day 18 iPSCs Day 0 Day 12 Figure 6: Differentiation of Human iPSC-Derived Neurons Workflow Neuronal Activity Intensity (OCU) Time (sec) 0 30 60 90 120 6 5 43 2 1 0 7 Figure 6 illustrates the differentiation and characterisation workflow developed at Talisman Therapeutics for use with human iPSC-derived neurons. This workflow describes where the use of both neurite outgrowth and neuronal activity, as quantified on the Incucyte® Live-Cell Analysis System can be integrated into the workflow alongside other techniques. Once matured, these neurons are shown to form active networks suitable to test novel treatments for disease. Glia Modulation As opposed to the traditional view that brain function results exclusively from neuronal activity, it is now widely accepted as a more coordinated perspective involving both neurons and glia. Astrocytes are regarded as active partners in brain activity via bidirectional communication, orchestrated at the tripartite synapse, composed of the neuronal pre- and post-synapses and their close interaction with the surrounded astroglia. To investigate the effect of astrocytes in the signalling response of neurons via measurements of calcium oscillations, a humanized live-cell model of neuronal activity was developed in collaboration with Talisman Therapeutics. Recent advances in hiPSC offer a powerful in vitro model strategy for the study of both healthy and disease stages of the human nervous system. Non-perturbing neurite outgrowth measurements can be performed in monoor co-culture (post-infection with Incucyte® Neurolight Orange Lentivirus) via automatic segmentation of timelapse imaging using the Incucyte® Neurotrack Analysis Software Module. Cell bodies and neurites are discriminated and kinetically quantified. Co-cultures include interactions observed in more complex systems that monocultures are unable to capture. When co-cultured with astrocytes, neurons developed greater and more branched neurites compared to monocultures (Figure 7). The functional profile of co-cultures also differed of that of monocultures, the former showing greater active objects (1/image), burst duration (sec), and lower burst rate (1/min), at a similar correlation, indicating greater network stability in the presence of glial cells. The presence of astrocytes impacts neuronal architecture and network activity. Network activity in neuron-astrocyte co-cultures differs from that seen in neuronal monocultures, displaying a reduced frequency of longer-lasting calcium events, characteristic of a more mature neuronal network through the development of a network’s ability to fire trains of action potentials. Neurite Development Time (h) 160 120 80 40 0 MC CC 0 48 96 144 192 240 Neurite length (mm/mm²) Time (h) 4 3 2 1 0 0 48 96 144 192 240 Branch Points (x10³/mm²) Neural Activity 1000 750 500 250 0 Active Objects (1/Image) MC CC 10 8 6 4 2 0 Burst Rate (1/image) 1.0 0.8 0.6 0.4 0.2 0 ActiveMean Correlation 8 6 4 2 0 Burst Duration (sec) Intensity (OCU) Time (sec) 0 30 60 90 120 5 4 3 2 1 0 Mono-Culture Intensity (OCU) Time (sec) 0 30 60 90 120 5 4 3 2 1 0 Co-Culture Figure 7: iPSC Neurons Co-cultured With Mature Astrocytes Yield Greater Outgrowth and Branching and Neuronal Network Activity Is Modified. Network activity in neuron-astrocyte co-culture differs from monocultures, displaying a reduced frequency of longer-lasting burst rates (characteristic of a more mature neuronal network through the development of a network’s ability to fire trains of APs). n = 12. Traces and bar charts are 23 days post-infection. 8 9 Conclusions In this application note, we present data to support the use of the Incucyte® Live-Cell Analysis System configured with an Orange/NIR or Green/Orange/NIR Optical Module to characterize and refine different neuronal phenotypes and their maturation for modeling their function in vitro. This single live-cell imaging platform, in combination with the Incucyte® Neuroburst Orange Lentivirus, allows users to assess calcium flux kinetics and continuously monitor morphology of neuronal populations long-term using non-perturbing reagents, validated protocols that are cell-sparing, and a built-in, guided interface for non-experts provided by the Incucyte® Neuronal Activity Analysis Software Module. The system can be used within the operator’s own incubator under physiological conditions and may be used with a variety of neuronal cell types (such as primary neurons and iPSC-derived models). As described above, this system and reagents can provide valuable, “real world” kinetic insights into neuronal network activity and connectivity in neurological models that might be missed by traditional end-point analysis. Knowing when iPSC-derived neurons become functionally active, how to optimize their activity, and gaining insight into the synaptic connectivity of cultured neurons has eluded neuroscience researchers. Using predominantly GABA and Gluta iPSC-derived neuronal models, we have shown how the Incucyte® Live-Cell Analysis System provides a means to study a variety of cell models using relevant quantitative metrics (e.g. neurite length and cellular activity). Additionally, these disease-relevant humanized models allow us to investigate pharmacological modulation. Lastly, the robustness and throughput provided by the Incucyte® Live- Cell Analysis System enables researchers to focus on isolating variables in order to improve iPSC-derived neuronal model development. The Incucyte® Live-Cell Analysis System provides a complete end-to-end solution for the characterization of neuronal phenotypes and their maturation, not only for neuronal cell function, but also provides important information for a wide variety of neurological questions that may be missed by other methods. Application Note Optimization of iPSC Culture Protocol Using High Quality Growth Factors and Cytokines Daryl Cole, Amber Ward, Jasmine Trigg, Nicola Bevan Sartorius UK Ltd, Royston, Hertfordshire, UK Correspondence Email: AskAScientist@sartorius.com Abstract Cytokines and growth factors constitute a diverse group of proteins essential for intercellular communication. Two cytokines that are a key focus for in vitro cell culture are fibroblast growth factor 2 (FGF-2) and transforming growth factor β1 (TGF-β1). These cytokines are used in precise concentrations for maintaining induced pluripotent stem cells (iPSCs) in their pluripotent state. However, achieving the desired efficacy of these cytokines and growth factors in an in vitro setting has been challenging due to issues like thermostability, leading to a short half-life and necessitating frequent media changes, which are resource intensive. In this application note, we present data on the utilization and optimization of Sartorius Research Use Only (RUO) Cytokines and Growth Factors for iPSC culture. Our goal is to sustain pluripotency and proliferative potential while reducing the need for daily media replenishment. We assess this by analyzing crucial cell surface markers, morphological indicators, and growth patterns using advanced tools like the iQue®3 High-Throughput Screening Cytometer and the Incucyte® Live-Cell Analysis System, showcasing the practicality of Sartorius RUO Growth Factors and Cytokines in iPSC culture maintenance. November 1, 2023 Keywords or phrases: Research Use Only (RUO), Cytokines, Growth Factors, iPSC, Cell Culture, Pluripotency, Live-Cell Analysis, Advanced Flow Cytometry, Immunocytochemistry Daryle Cole, PhD — Scientist – Sartorius Daryle Cole, PhD — Field Application Specialist – Sartorius Jasmine Trigg — Scientist – Sartorius Nicola Bevan — Scientist – Sartorius 2 Introduction Cytokines are a large and diverse family of proteins secreted by cells for intercellular communication. By binding to extracellular receptors, they can induce an intracellular cascade of signaling to initiate a biological response. The induction and co-ordination of a range of processes are attributed to the correct signal intensity and timing of cytokine release, from embryonic development to growth and wound healing. One group of cytokines, classified as growth factors, are responsible for the growth of a specific tissue by stimulating proliferation and differentiation. The importance of these growth factors can be seen in diseases where their strict regulation is lost, such as rheumatoid arthritis, multiple sclerosis, and COVID-19.¹,²,³ There is often a specific growth factor that drives the growth and differentiation of a defined tissue, for example epidermal growth factor (EGF) enhances osteogenesis, whilst fibroblast growth factor (FGF) and vascular endothelial growth factor (VEGF) stimulate angiogenesis.⁴,⁵ Since these growth factors are required for maintaining cell health in vivo, it is essential that cells cultured in vitro also have access to physiological levels of growth factors. Two cytokines that are a key focus for in vitro cell culture are fibroblast growth factor 2 (FGF-2) and transforming growth factor β1 (TGF-β1 PLUS). FGF-2 is mitogenic, playing a significant role in physiological processes such as embryonic development, tissue repair, and cell growth, as well as pathological processes such as tumor growth, perfusion, and invasion.⁶ Similarly, TGF-β1 PLUS plays a key role in differentiation and oncogenesis and is associated with Alzheimer’s disease, but is also secreted by leukocytes as a key component of coordinating the immune response.⁷ Induced pluripotent stem cells (iPSCs) are an in vitro cell model that require precise concentrations of these growth factors to maintain their pluripotent properties. iPSCs start as somatic cells that undergo a reprogramming process, using cytokines to alter their cell fate and enable the cell to gain pluripotent properties.⁸ Through further exposure to growth factors that mimic the in vivo differentiation process, theoretically these iPSCs can then differentiate into any somatic cell type. iPSCs are valuable for studying the differentiation process as they do not face the same ethical concerns of protocols using embryonic stem cells. The pluripotent qualities of a cell can be determined by investigating cell surface markers, such as stage-specific embryonic antigen (SSEA)-1, SSEA-4, TRA-1-60, and intracellular markers such as SOX2 and OCT-4.⁹ Despite their importance in cell culture maintenance, translating the efficacy of growth factors into an in vitro environment has been challenging. Sensitive cell types, such as iPSCs, require highly pure growth factors and cytokines as even trace amounts of endotoxins and other impurities can impact their genetic stability and differentiation potential. While recombinant growth factors and cytokines are free of contaminating animal proteins, thermostability can be an issue, resulting in a short half-life. This means growth factors in the cell culture media degrade faster, necessitating regular media changing; both a time and resource-intensive process.¹⁰ Furthermore, many growth factors become compromised after three freeze-thaw cycles, complicating their use in culture.¹¹ Sartorius Research Use Only (RUO) Growth Factors and Cytokines are produced using recombinant human DNA technology and do not contain any animal-derived contaminants. They are also manufactured to the highest quality standards to ensure purity and low endotoxicity. In this application note, we demonstrate optimization of culture conditions to maintain a pluripotent phenotype and the proliferative capability of iPSCs using Sartorius RUO Growth Factors and Cytokines, including thermostable varieties. We also demonstrate the utility of the iQue®3 High-Throughput Cytometry Platform and Incucyte® Live- Cell Analysis System for analyzing cell surface markers, cell growth, and cell morphology. Methods and Materials Cell Culture iPSCs were passaged using Accutase® to lift cells twice per week in vitronectin (10 μg/mL) coated 6-well plates at a density of 100 K/well. NutriStem® hPSC XF (Cat. No. 05-100-1A) pre-conditioned iPSCs (ATCC 1019) were cultured in NutriStem® hPSC XF media, whereas iPSC 1019 cells were cultured in commercial media. After passaging, cells were reseeded in media containing 10 μM ROCK inhibitor (Y-27632), which was removed after 24 hours. Growth Factors for Standard iPSC Culture To optimize the concentration of RUO Recombinant Human TGF-β1 PLUS Protein (Cat. No. CYK-0050-0010) and Recombinant Human FGF-2 Protein 154 aa (Cat. No. CYK-0100-0023) to be added to the growth factor-free media, several concentrations of each growth factor were tested. iPSCs were seeded in vitronectin (10 μg/mL) coated 24-well plates (100 K/well). Pluripotency was determined at 3 and 6 days post-seeding. A concentration range of FGF-2 was tested (3.13 – 200 ng/mL) in combination with 2 ng/mL TGF-β1 PLUS in all conditions. Similarly, a concentration range of TGF-β1 PLUS was tested (0.13 – 8 ng/mL) with 100 ng/mL FGF-2 in all conditions. NutriStem® hPSC XF GF-free (Cat. No. 06-5100-01-1A), commercial media, and RPMI 1640 were used as control media formulations. THP-1 cells were used as a non-pluripotent biological control. The cells were analyzed for marker expression using the iQue® Advanced Flow Cytometry Platform. Generating Concentration Response Curves iPSCs were seeded at 20 K/well in vitronectin coated 24-well plates and monitored over 6 days in the Incucyte® Live- Cell Analysis System. The cells were fed daily with 500 μL media containing a concentration range of TGF-β1 PLUS and FGF-2. NutriStem® hPSC XF GF-free, NutriStem® hPSC XF, commercial media, and RPMI 1640 were used as controls. The cells were then lifted using Accutase® and reseeded in a 96-well V-bottom plate, centrifuged at 300 g for 5 minutes and washed twice with PBS + 5% FBS before being treated with SSEA-1-FITC (1:50), SSEA-4-APC (1:800), TRA-1-60-PE (1:25), and iQue® B/Red Viability Dye (1:50) and incubated at room temperature in the dark for 30 minutes. The plate was then spun at 300 g for 5 minutes before analyzing on the iQue®3 High-Throughput Cytometry Platform. FGF-2-G3 Long Term Comparison Recombinant FGF2-G3 protein (Cat. No. CYK-0100-0002) is an enhanced, thermostable version of FGF-2 designed to enable longer duration between feeds. Cells were seeded at a density of 20 K/well in vitronectin (10 μg/mL) coated 24-well plates. These cells were treated with a concentration range of FGF2-G3 in combination with 2 ng/mL of TGF-β1 PLUS, without subsequent refeeds. NutriStem® hPSC XF GF-free, stabilized commercial media (enabling longer duration between feeds), and RPMI 1640 were used as control media formulations. THP-1 cells were used as a non-pluripotent biological control. After 6 days, the cells were analyzed on the iQue®3 platform. Cells were monitored using the Incucyte® Live-Cell Analysis System for the duration of the experiment to investigate growth dynamics and morphological changes. Immunocytochemistry (ICC) iPSCs were seeded at 2 K/well in a 96-well plate in ROCK inhibitor (1:1000). After 24 hours, ROCK inhibitor was removed and 100 μL NutriStem® XF was added to each well. After a further 24 hours, a concentration range of TGF-β1 PLUS was added alongside controls of NutriStem® hPSC XF, NutriStem® hPSC XF GF-free, commercial media, commercial media plus, and RPMI 1640. After 5 days, cells were washed, fixed, permeabilized, and blocked. Cells were then immunostained for markers of pluripotency (SSEA-4 Alexa Fluor™ 647, OCT-4 Alexa Fluor™ 555, and SOX2 Alexa Fluor™ 488; ThermoFisher A24881) and imaged in PBS. Phase and fluorescence images were acquired using the Incucyte® system and analyzed using integrated software. Results Ensuring iPSCs are cultured optimally is essential for successfully maintaining the pluripotency, health, and longevity of these highly valuable cells. The advantage of using iPSCs in research is in their differentiation capability, where disparate tissue types can be derived from a single cell. Due to their complex nature, the requirement for specific culture conditions necessitates the use of a variety of supplements in culture media to grow highly pluripotent iPSCs. The following data highlights the efficacy of Sartorius RUO Growth Factors and Cytokines as supplements in media for the successful culture of iPSCs. Note: iPSCs were cultured in NutriStem® hPSC XF GF-free (NutriStem®-GF) supplemented with concentration ranges of Sartorius RUO FGF-2 and TGF-β1 PLUS. Cells were harvested after 3 and 6 days and analyzed on the iQue®3 High-Throughput Screening Cytometer. (A) Pluripotent (SSEA-1 -, SSEA-4 +, TRA-1-60 +) and (B) Non-pluripotent (SSEA-1 +) expression profile analysis of iPSCs supplemented with FGF-2. (C) Pluripotent and (D) Nonpluripotent expression profile analysis of iPSCs supplemented with TGF-β1 PLUS. Data presented as mean ± SEM, n = 3. Figure 1: Quantification of iPSC Marker Expression During Stem Cell Maintenance. NutriStem®-GF FGF-2 50 ng/mL FGF-2 100 ng/mL FGF-2 200 ng/mL Commercial media RPMI THP-1 0 50 100 Pluripotent % positive of live cells A FGF-2 and TGF-β1 PLUS Supplementation Maintains Pluripotency in iPSCs We grew iPSCs in NutriStem® hPSC XF GF-free with or without supplementation with FGF-2 and TGF-β1 PLUS over 3 and 6 days with daily feeds. Using the iQue®3 High- Throughput Screening Cytometer, we analyzed changes in cell surface pluripotency marker expression associated with optimized growth conditions. The capabilities of the iQue®3 allow for multiple markers to be analyzed in the same sample well, greatly increasing the speed of data collection and saving precious sample. Comparisons of pluripotency (SSEA-1 −, SSEA-4 +, TRA-1-60 +) and non-pluripotency (SSEA-1 +) marker expression profiles (Figure 1) highlight a decrease in pluripotency marker expression when iPSCs are cultured in NutriStem® XF GF-free for 6 days. NutriStem®-GF TGF-ß1 PLUS 2 ng/mL TGF-ß1 PLUS 4 ng/mL TGF-ß1 PLUS 8 ng/mL Commercial media RPMI THP-1 0 50 100 Pluripotent % positive of live cells C NutriStem®-GF FGF-2 50 ng/mL FGF-2 100 ng/mL FGF-2 200 ng/mL Commercial media RPMI THP-1 0 50 100 Non-pluripotent % positive of live cells B NutriStem®-GF TGF-ß1 PLUS 2 ng /mL TGF-ß1 PLUS 4 ng/mL TGF-ß1 PLUS 8 ng/mL Commercial media RPMI THP-1 0 50 100 Non-pluripotent % positive of live cells D 3 days 6 days 3 days 6 days 3 days 6 days 3 days 6 days 4 Results Ensuring iPSCs are cultured optimally is essential for successfully maintaining the pluripotency, health, and longevity of these highly valuable cells. The advantage of using iPSCs in research is in their differentiation capability, where disparate tissue types can be derived from a single cell. Due to their complex nature, the requirement for specific culture conditions necessitates the use of a variety of supplements in culture media to grow highly pluripotent iPSCs. The following data highlights the efficacy of Sartorius RUO Growth Factors and Cytokines as supplements in media for the successful culture of iPSCs. Note: iPSCs were cultured in NutriStem® hPSC XF GF-free (NutriStem®-GF) supplemented with concentration ranges of Sartorius RUO FGF-2 and TGF-β1 PLUS. Cells were harvested after 3 and 6 days and analyzed on the iQue®3 High-Throughput Screening Cytometer. (A) Pluripotent (SSEA-1 -, SSEA-4 +, TRA-1-60 +) and (B) Non-pluripotent (SSEA-1 +) expression profile analysis of iPSCs supplemented with FGF-2. (C) Pluripotent and (D) Nonpluripotent expression profile analysis of iPSCs supplemented with TGF-β1 PLUS. Data presented as mean ± SEM, n = 3. Figure 1: Quantification of iPSC Marker Expression During Stem Cell Maintenance. NutriStem®-GF FGF-2 50 ng/mL FGF-2 100 ng/mL FGF-2 200 ng/mL Commercial media RPMI THP-1 0 50 100 Pluripotent % positive of live cells A FGF-2 and TGF-β1 PLUS Supplementation Maintains Pluripotency in iPSCs We grew iPSCs in NutriStem® hPSC XF GF-free with or without supplementation with FGF-2 and TGF-β1 PLUS over 3 and 6 days with daily feeds. Using the iQue®3 High- Throughput Screening Cytometer, we analyzed changes in cell surface pluripotency marker expression associated with optimized growth conditions. The capabilities of the iQue®3 allow for multiple markers to be analyzed in the same sample well, greatly increasing the speed of data collection and saving precious sample. Comparisons of pluripotency (SSEA-1 −, SSEA-4 +, TRA-1-60 +) and non-pluripotency (SSEA-1 +) marker expression profiles (Figure 1) highlight a decrease in pluripotency marker expression when iPSCs are cultured in NutriStem® XF GF-free for 6 days. NutriStem®-GF TGF-ß1 PLUS 2 ng/mL TGF-ß1 PLUS 4 ng/mL TGF-ß1 PLUS 8 ng/mL Commercial media RPMI THP-1 0 50 100 Pluripotent % positive of live cells C NutriStem®-GF FGF-2 50 ng/mL FGF-2 100 ng/mL FGF-2 200 ng/mL Commercial media RPMI THP-1 0 50 100 Non-pluripotent % positive of live cells B NutriStem®-GF TGF-ß1 PLUS 2 ng /mL TGF-ß1 PLUS 4 ng/mL TGF-ß1 PLUS 8 ng/mL Commercial media RPMI THP-1 0 50 100 Non-pluripotent % positive of live cells D 3 days 6 days 3 days 6 days 3 days 6 days 3 days 6 days 5 In previous experiments, iPSCs cultured in RPMI presented a loss in pluripotency marker expression and a gain in SSEA-1 expression, so this condition was used as a non-optimized control. High expression of SSEA-1 combined with low levels of pluripotency marker expression were seen in non-pluripotent iPSC controls; grown in RPMI, or the THP-1 non-pluripotent immortalized cell line. Supplementation with FGF-2 (50 - 200 ng/mL) showed a marked, concentration-dependent increase in pluripotency marker expression (Figure 1A), while SSEA-1 expression remained constant (Figure 1B). We observed a similar trend when supplementing with TGF-β1 PLUS; pluripotency marker expression maintained at 6 days in cells supplemented with concentrations as low as 2 ng/mL (Figure 1C). SSEA-1 expression also remains low throughout the study timeline (Figure 1D). iPSCs Supplemented with FGF-2 and TGF-β1 PLUS Display Pluripotent Morphological Phenotypes In addition to phenotypic marker analysis using the iQue®3 High-Throughput Screening Cytometer, it is also important to assess the morphological characteristics of iPSCs to provide more insight into the condition and growth of cultures. Using the Incucyte® Live-Cell Analysis System, we were able to compare different media for their impact on the growth and morphology of the live iPSCs directly from the incubator, without perturbing the cells (Figure 2). Highdefinition phase contrast images of iPSCs grown in NutriStem® XF–GF show low confluency in the plate, with visible spontaneous differentiation. Following addition of FGF-2 or TGF-β1 PLUS, iPSC morphology changed, with higher confluency, increased colony density, and no spontaneous differentiation. The morphology was comparable to cells grown in NutriStem® XF. The RPMI control illustrated that the morphological presentation associated with a loss of pluripotency; the colony density and compactness was reduced, and the cellular cytoplasmic area was increased. Figure 2: Morphological Analysis of iPSCs During Stem Cell Maintenance. Note: iPSCs were cultured in NutriStem® XF–GF supplemented with a range of concentrations of Sartorius RUO Recombinant Human FGF-2 and TGF-β1 PLUS. Cells were monitored over 6 days and images acquired using the Incucyte® Live-Cell Analysis System. Representative 10X phase contrast images taken at 2 days and 10 hours post-treatment. 200 ng/mL FGF-2 NutriStem® XF-GF Commercial Media 2 ng/mL TGF-ß1 PLUS NutriStem® XF RPMI Growth Rate and Confluency of iPSCs Supplemented With FGF-2 and TGF-β1 PLUS is Concentration-Dependent The acquisition of kinetic data on the Incucyte® Live-Cell Analysis System enabled easy quantification of iPSC growth via confluency and phase object area analysis (Figure 3). Here we showed the difference in iPSC growth when cultured with varying concentrations of FGF-2 and TGF-β1 PLUS (Figure 3). The data shows that in higher concentrations of FGF-2 (50 – 200 ng/mL), iPSC growth is similar with a plateau at 3 days, which remains stable (Figure 3A). In contrast, data for lower FGF-2 concentrations (3.13 – 25 ng/mL), show a dramatic drop in confluency post three days, indicating a lack of growth and potential cell death. Analysis of average phase object area (size of iPSC colonies) over time provided more granular indication of iPSC growth patterns. Note: iPSCs were cultured in NutriStem® XF–GF supplemented with a range of concentrations of Sartorius RUO Recombinant Human FGF-2 and TGF-β1 PLUS. Cells were monitored over 6 days and analyzed using the Incucyte® Live-Cell Analysis System. Confluency analysis of iPSCs supplemented with (A) FGF-2 at decreasing concentrations and (C) TGF-β1 PLUS at decreasing concentrations. Phase Area Object Average analysis at 5 days for (B) FGF-2 and (D) TGF-β1 PLUS. Figure 3: Growth Analysis of iPSCs During Stem Cell Maintenance. 0 40 100 Phase Object Confluence (%) 80 60 20 1 A 2 3 4 5 Days NutriStem® XF FGF-2 200 ng/mL FGF-2 100 ng/mL FGF-2 50 ng/mL FGF-2 25 ng/mL FGF-2 12.5 ng/mL FGF-2 6.25 ng/mL FGF-2 3.13 ng/mL NutriStem® XF-GF For example, lower concentrations of FGF-2 (3.13–25 ng/mL) produced iPSCs that form smaller colonies after 5 days, compared to higher concentrations of supplemented FGF-2 (25–200 ng/mL) (Figure 3B). TGF-β1 PLUS supplementation at a range of concentrations (Figure 3C), had minimal impact on the growth of iPSCs, indicating this protein is not as critical as FGF-2 for iPSC growth at this concentration range. Analysis of average phase object area, however, revealed that with decreasing concentrations of TGF-β1 PLUS, iPSCs form smaller colonies over time. Although growth is minimally affected, colony size varies depending on TGF-β1 PLUS concentration (Figure 3D). Based on this data, we recommend the concentrations of 100 ng/mL FGF-2 and 2 ng/mL TGF-β1 PLUS for optimal growth and maintenance of iPSCs. 0 40 100 Phase Object Confluence (%) 80 60 20 1 C 2 3 4 5 Days NutriStem® XF TGF-1 PLUS 8 ng/mL TGF-1 PLUS 4 ng/mL TGF-1 PLUS 2 ng/mL TGF-1 PLUS 1 ng/mL TGF-1 PLUS 0.5 ng/mL TGF-1 PLUS 0.25 ng/mL TGF-1 PLUS 0.13 ng/mL NutriStem® XF-GF NutriStem® XF-GF FGF-2 3.13 ng/mL Phase Area Object Average (m²) NutriStem® XF B FGF-2 6.25 ng/mL FGF-2 12.5 ng/mL FGF-2 25 ng/mL FGF-2 50 ng/mL FGF-2 100 ng/mL FGF-2 200 ng/mL 0 5×106 1×106 1.5×106 2×106 2.5×106 NutriStem® XF-GF TGF-ß1 PLUS 0.13 ng/mL Phase Area Object Average (m²) NutriStem® XF D TGF-ß1 PLUS 0.25 ng/mL TGF-ß1 PLUS 0.5ng/mL TGF-ß1 PLUS 1ng/mL TGF-ß1 PLUS 2 ng/mL TGF-ß1 PLUS 4 ng/mL TGF-ß1 PLUS 8ng/mL 0 5×106 1×106 1.5×106 2×106 2.5×106 6 Growth Rate and Confluency of iPSCs Supplemented With FGF-2 and TGF-β1 PLUS is Concentration-Dependent The acquisition of kinetic data on the Incucyte® Live-Cell Analysis System enabled easy quantification of iPSC growth via confluency and phase object area analysis (Figure 3). Here we showed the difference in iPSC growth when cultured with varying concentrations of FGF-2 and TGF-β1 PLUS (Figure 3). The data shows that in higher concentrations of FGF-2 (50 – 200 ng/mL), iPSC growth is similar with a plateau at 3 days, which remains stable (Figure 3A). In contrast, data for lower FGF-2 concentrations (3.13 – 25 ng/mL), show a dramatic drop in confluency post three days, indicating a lack of growth and potential cell death. Analysis of average phase object area (size of iPSC colonies) over time provided more granular indication of iPSC growth patterns. Note: iPSCs were cultured in NutriStem® XF–GF supplemented with a range of concentrations of Sartorius RUO Recombinant Human FGF-2 and TGF-β1 PLUS. Cells were monitored over 6 days and analyzed using the Incucyte® Live-Cell Analysis System. Confluency analysis of iPSCs supplemented with (A) FGF-2 at decreasing concentrations and (C) TGF-β1 PLUS at decreasing concentrations. Phase Area Object Average analysis at 5 days for (B) FGF-2 and (D) TGF-β1 PLUS. Figure 3: Growth Analysis of iPSCs During Stem Cell Maintenance. 0 40 100 Phase Object Confluence (%) 80 60 20 1 A 2 3 4 5 Days NutriStem® XF FGF-2 200 ng/mL FGF-2 100 ng/mL FGF-2 50 ng/mL FGF-2 25 ng/mL FGF-2 12.5 ng/mL FGF-2 6.25 ng/mL FGF-2 3.13 ng/mL NutriStem® XF-GF For example, lower concentrations of FGF-2 (3.13–25 ng/mL) produced iPSCs that form smaller colonies after 5 days, compared to higher concentrations of supplemented FGF-2 (25–200 ng/mL) (Figure 3B). TGF-β1 PLUS supplementation at a range of concentrations (Figure 3C), had minimal impact on the growth of iPSCs, indicating this protein is not as critical as FGF-2 for iPSC growth at this concentration range. Analysis of average phase object area, however, revealed that with decreasing concentrations of TGF-β1 PLUS, iPSCs form smaller colonies over time. Although growth is minimally affected, colony size varies depending on TGF-β1 PLUS concentration (Figure 3D). Based on this data, we recommend the concentrations of 100 ng/mL FGF-2 and 2 ng/mL TGF-β1 PLUS for optimal growth and maintenance of iPSCs. 0 40 100 Phase Object Confluence (%) 80 60 20 1 C 2 3 4 5 Days NutriStem® XF TGF-1 PLUS 8 ng/mL TGF-1 PLUS 4 ng/mL TGF-1 PLUS 2 ng/mL TGF-1 PLUS 1 ng/mL TGF-1 PLUS 0.5 ng/mL TGF-1 PLUS 0.25 ng/mL TGF-1 PLUS 0.13 ng/mL NutriStem® XF-GF NutriStem® XF-GF FGF-2 3.13 ng/mL Phase Area Object Average (m²) NutriStem® XF B FGF-2 6.25 ng/mL FGF-2 12.5 ng/mL FGF-2 25 ng/mL FGF-2 50 ng/mL FGF-2 100 ng/mL FGF-2 200 ng/mL 0 5×106 1×106 1.5×106 2×106 2.5×106 NutriStem® XF-GF TGF-ß1 PLUS 0.13ng/mL Phase Area Object Average (m²) NutriStem® XF D TGF-ß1 PLUS 0.25 ng/mL TGF-ß1 PLUS 0.5 ng/mL TGF-ß1 PLUS 1ng/mL TGF-ß1 PLUS 2 ng/mL TGF-ß1 PLUS 4 ng/mL TGF-ß1 PLUS 8ng/mL 0 5×106 1×106 1.5×106 2×106 2.5×106 Pluripotency marker expression was higher in all cells treated with FGF2-G3 compared to all other treatment types, with a consistent level across the concentration range (~70%) outperforming an alternative commercial media (Figure 4A). Comparisons of SSEA-1 expression show very low levels in iPSCs cultured with FGF2-G3 from 50–200 ng/mL, lower than NutriStem® hPSC XF GF-free and NutriStem hPSC XF (Figure 4B). Control cells grown in RPMI, or THP-1 cell controls, presented high expression of SSEA-1 and low levels of pluripotency marker expression as seen previously. This data indicates that thermostable Sartorius RUO FGF2-G3 maintains function in culture for longer periods, mitigating the need for daily media changes. Note: iPSCs were cultured in NutriStem® XF–GF supplemented with thermostable FGF2-G3 at a range of concentrations for 5 days without media changes and pluripotency markers were analyzed on the iQue®3 High-Throughput Screening Cytometer on day 6. (A) Pluripotent (SSEA-1, SSEA-4 +, TRA-1-60 +) and (B) Non-pluripotent (SSEA-1 +) marker expression profile. Stabilized CM (Stabilized Commercial Media enabling extended duration between feeds). Representative data from one of 3 experiments. Data presented as mean ± SEM, n = 3. NutriStem® XF-GF FGF2-G3 50 ng/mL FGF2-G3 100 ng/mL FGF2-G3 200 ng/mL Stabilized CM RPMI THP-1 0 20 40 60 80 100 Use of Thermostable FGF2-G3 Facilitates iPSC Culture Without Daily Feeding iPSCs are high maintenance and require daily media refreshing to maintain a pluripotent phenotype. Thermostable growth factors enable reduced media change frequency due to increased compound stability, which eliminates the need for inconvenient weekend media changes. To test this, we grew iPSCs in NutriStem® hPSC XF GF-free with supplementation (2 ng/mL TGF-β1 PLUS, varying concentrations of FGF2-G3) for 5 days without media changes and analyzed marker expression on the iQue®3 platform at day 6. The Sartorius RUO FGF2-G3 is an enhanced, thermostable version of FGF-2 designed to enable longer duration between feeds. Figure 4: Long Term iPSC Culture Without Media Change. A Pluripotent % positive of live cells NutriStem® XF-GF FGF2-G3 50 ng/mL FGF2-G3 100 ng/mL FGF2-G3 200 ng/mL Stabilized CM RPMI THP-1 0 20 40 60 80 100 B Non-pluripotent % positive of live cells Morphological Analysis of iPSCs Supplemented With FGF2-G3 We monitored the iPSCs supplemented with thermostable FGF2-G3 on the Incucyte® Live-Cell Analysis System over the 5-day study to investigate morphological effects. Representative images of cells cultured in FGF2-G3 PLUS supplemented NutriStem® hPSC XF GF-free showed formation of very tightly condensed colonies with defined edges and minimal cell death (Figure 5A). While iPSCs grown in NutriStem® hPSC XF GF-free without supplementation presented reduced growth with more cell death (Figure 5B). Cells grown in commercial media produced very tight colonies with defined edges, but with some spontaneous differentiation (data not shown). Analysis of the Incucyte® images for iPSCs grown in FGF2-G3 supplemented media for 5 days without daily media refeeds highlighted changes in growth compared to alternative media types. Note: iPSCs were cultured in NutriStem® hPSC XF GF-free and supplemented with FGF2-G3. Cells were monitored over 5 days and imaged and analyzed on the Incucyte® Live-Cell Analysis System. Representative 10X phase contrast images taken at 2 days and 10 hours post treatment of iPSCs treated with (A) NutriStem® hPSC XF GF-free supplemented with 200 ng/mL FGF2-G3 and (B) NutriStem® hPSC XF GF-free. (C) Confluency analysis of iPSCs supplemented with FGF2-G3 at decreasing concentrations. Figure 5: Morphological Visualization and Long-Term Growth Analysis of iPSCs Supplemented With FGF2-G3 Without Media Changes. For example, iPSCs grown in NutriStem® hPSC XF GF-free supplemented with FGF2-G3 exhibited increased growth over NutriStem® hPSC XF and NutriStem® hPSC XF GF-free cultured iPSCs (Figure 5C). NutriStem® hPSC XF outperformed NutriStem® hPSC XF GF-free, but the differences were less marked at the end of the time course, suggesting degradation of key growth factors, such as FGF-2. Culturing iPSCs in alternative commercial media designed for weekend feeding provided similar growth to FGF2-G3 supplementation, however, these cells plateaued sooner, suggesting exhaustion of growth factors required for continued growth (data not shown). Interestingly, lower concentrations of FGF2-G3 supplementation (50 and 100 ng/mL) achieved the same effect as the highest concentration (200 ng/mL) in analyses on both the iQue®3 and Incucyte® platforms, suggesting that the potency of this growth factor allows for lower dosing, thus saving reagent. 0 8 Phase Object Confluence Normalized to pre-treatment 6 4 2 1 C 2 3 4 5 Days FGF2-G3 200 ng/mL FGF2-G3 100 ng/mL FGF2-G3 50 ng/mL NutriStem® XF-GF NutriStem® XF A 200 ng/mL FGF2-G3 B NutriStem® XF-GF 0 8 Phase Object Confluence Normalized to pre-treatment 6 4 2 1 C 2 3 4 5 Days FGF2-G3 200 ng/mL FGF2-G3 100 ng/mL FGF2-G3 50 ng/mL NutriStem® XF-GF NutriStem® XF Determining Pluripotency Marker Expression in iPSCs Using Immunocytochemistry To gain further insight about the efficacy of Sartorius RUO Growth Factors and Cytokines, we cultured iPSCs in RPMI and NutriStem® hPSC XF GF-free supplemented with 100 ng/mL FGF-2 and 2 ng/mL TGF-β1 PLUS followed by staining to observe expression of key markers for pluripotency in different culture conditions. Our data showed that when supplemented with Sartorius RUO Growth Factors and Cytokines, iPSCs expressed high levels of pluripotency markers: the cell surface marker SSEA-4, and sub-cellular markers SOX2 and OCT-4. However, cells grown in RPMI displayed much lower levels of expression, as expected (Figure 6A). The Incucyte® Live-Cell Analysis System facilitated our investigation of the marker expression pattern in iPSCs grown under different conditions. SSEA-4 expression, for example, highlights the differences in distribution in pluripotent iPSCs grown with FGF-2 and TGF-β1 PLUS compared to RPMI. Low levels of expression were evident in RPMI cultured iPSCs, while a high level of expression throughout the surface of the cell was clearly visible in growth factor supplemented iPSCs. Quantification of fluorescence area normalized to phase area to account for differences in cell area revealed global differences in marker expression across each condition (Figure 6B). SSEA-4 expression was approximately 30% higher in supplemented iPSCs compared to RPMI, while OCT-4 and SOX2 expression was approximately 10% higher in supplemented iPSCs. These data support previous analysis of marker expression on the iQue®3 High-Throughput Cytometry Platform, indicating an increased level of pluripotency in iPSCs supplemented with Sartorius RUO Growth Factors and Cytokines compared to other media conditions. Figure 6: Immunocytochemistry Analysis of Pluripotency Marker Expression in iPSCs Supplemented With FGF-2 and TGF-β1 PLUS. Note: iPSCs were cultured in NutriStem® hPSC XF GF-free and supplemented with 100 ng/mL FGF-2 and 2 ng/mL TGF-β1 PLUS or RPMI for 2 days. Cells were fixed then stained for SSEA-4, OCT-4 and SOX2 and imaged and analyzed on the Incucyte® Live-Cell Analysis System. (A) Representative 20X fluorescence images taken of iPSCs in the indicated conditions. (B) Analysis of Incucyte® images comparing the percentage of fluorescence area normalized to phase area for each marker under each condition. Representative data from one of 3 experiments. Data presented as mean ± SEM, n = 3. A SSEA-4 OCT-4 100 ng/mL FGF-2 + 2 ng/mL TGF-ß1 PLUS SOX2 Merged SSEA-4 OCT-4 RPMI SOX2 Merged SSEA-4 OCT-4 SOX2 0 10 20 30 40 50 60 B Fluorescence Area/Phase Area (%) NutriStem® XF + Supplements RPMI Specifications subject to change without notice. ©2023. All rights reserved. All names of Sartorius products are registered trademarks and the property of Sartorius AG and/or one of its affiliated companies. Filename: Optimization-of-iPSC-Culture-Protocol-RUO-Cytokines-Application-Note-en-Sartorius Status: 10 | 2023 North America Sartorius Corporation 300 West Morgan Road Ann Arbor, Michigan 48108 USA Phone +1 734 769 1600 Email: orders.US07@sartorius.com Europe Sartorius UK Ltd. Longmead Business Centre Blenheim Road Epsom Surrey, KT19 9QQ United Kingdom Phone +44 1763 227400 Email: euorders.UK03@sartorius.com For further information, visit www.sartorius.com Asia Pacific Sartorius Japan K.K. 4th Floor, Daiwa Shinagawa North Bldg. 1-8-11, Kita-Shinagawa 1-chome Shinagawa-Ku Tokyo 140-0001 Japan Phone +81 3 6478 5202 Email: orders.US07@sartorius.com Conclusion iPSCs are rapidly becoming the cell type of choice for a multitude of research and clinical fields; they are highly proliferative and can be differentiated into all somatic tissues in the human body. However, the requirements for successful culture of these cells are both resource and time-intensive. It is also of paramount importance to maintain pluripotency during culture and finding the correct media formulation is essential to achieving this goal. The data shown here demonstrate the efficacy of Sartorius RUO Growth Factors and Cytokines as supplements in iPSC media formulations to preserve pluripotency, support growth, and increase the interval between feeding, helping to remove the requirement of daily media exchanges. Sartorius RUO Growth Factors and Cytokines are free from animal-derived contaminants, are manufactured to the highest quality standards ensuring purity and low endotoxicity, providing excellent solutions to challenging cell culture conditions. In addition, using the iQue®3 High-Throughput Cytometry Platform in conjunction with the Incucyte® Live-Cell Analysis System, allows simple monitoring and quantification of growth and pluripotent phenotype of iPSC cells during cell culture and media formulation development. References 1. Rosengren, S., Corr, M. and Boyle, D.L. (2010) ‘Plateletderived growth factor and transforming growth factor beta synergistically potentiate inflammatory mediator synthesis by fibroblast-like synoviocytes’, Arthritis Research &amp; Therapy, 12(2). doi:10.1186/ar2981. 2. Lu, H. et al. (2021) ‘Growth factors and their roles in multiple sclerosis risk’, Frontiers in Immunology, 12. doi:10.3389/fimmu.2021.768682. 3. Ilias, I. et al. (2021) ‘Covid-19 and growth hormone/ insulin-like growth factor 1: Study in critically and noncritically ill patients’, Frontiers in Endocrinology, 12. doi:10.3389/fendo.2021.644055. 4. Platt, M.O. et al. (2009) ‘Sustained epidermal growth factor receptor levels and activation by tethered ligand binding enhances osteogenic differentiation of multi-potent marrow stromal cells’, Journal of Cellular Physiology, 221(2), pp. 306–317. doi:10.1002/jcp.21854. 5. Kovacevic, I., Hoffmeister, M. and Oess, S. (2015) ‘Fibroblast growth factor signaling in vascular development’, Endothelial Signaling in Development and Disease, pp. 93–114. doi:10.1007/978-1-4939-2907-8_4. 6. Itoh, N. et al. (2016) ‘Roles of FGF signals in heart development, health, and disease’, Frontiers in Cell and Developmental Biology, 4. doi:10.3389/ fcell.2016.00110. 7. Zhang, X., Huang, W.-J. and Chen, W.-W. (2016) ‘TGF-β1 factor in the cerebrovascular diseases of Alzheimer’s disease’, European Review for Medical and Pharmacological Sciences, 20(24), pp. 5178–5185. 8. Kogut, I. et al. (2018) ‘High-efficiency RNA-based reprogramming of human primary fibroblasts’, Nature Communications, 9(1). doi:10.1038/ s41467-018-03190-3. 9. Song, Y. et al. (2021) ‘Generation and characterization of a human IPSC line HECI001-A from a healthy adult donor pancreata’, Stem Cell Research, 56, p. 102541. 10. Liu, C. et al. (2021) ‘Cytokines: From clinical significance to quantification’, Advanced Science, 8(15), p. 2004433. doi:10.1002/advs.202004433. 11. Zhou, X. et al. (2010) ‘Conceptual and methodological issues relevant to cytokine and inflammatory marker measurements in clinical research’, Current Opinion in Clinical Nutrition and Metabolic Care, 13(5), pp. 541– 547. doi:10.1097/mco.0b013e32833cf3bc. Elevate Your Research With High-Performance Media and Reagents for Stem Cell Growth and Cultivation Achieve consistent, scalable results in both 2D and 3D stem cell cultures using Sartorius’ range of high-quality growth factors, cytokines, transfection reagents, and animal-free cell culture media. Our products meet stringent quality benchmarks, enhancing cell health and easing upkeep, paving the way for a transition toward manufacturing. Simplifying Progress Specifications subject to change without notice. © 2024. All rights reserved. Incucyte and all names of Sartorius products are registered trademarks and the property of Sartorius AG. Specifications subject to change without notice. ©2024 All rights reserved. All names of Sartorius products are registered trademarks and the property of Sartorius AG and/or one of its affiliated companies. Stem-cells-in-disease-modeling+research-ebook-2403-en-Sartorius Status: 03 | 2024 North America Phone +1 734 769 1600 Europe Phone +44 1763 227400 Email: Japan Phone +81 3 6478 5202 China Phone +86 21 6878 2300 Rest of Asia Pacific and other countries around the world: Phone +65 6872 3966