Automated Cell Culture Systems and Their Applications to Human Pluripotent Stem Cell Studies

Automated human induced pluripotent stem cell culture and sample preparation for 3D live-cell microscopy

To produce abundant cell culture samples to generate large, standardized image datasets of human induced pluripotent stem (hiPS) cells, we developed an automated workflow on a Hamilton STAR liquid handler system. This was developed specifically for culturing hiPS cell lines expressing fluorescently tagged proteins, which we have used to study the principles by which cells establish and maintain robust dynamic localization of cellular structures. This protocol includes all details for the maintenance, passage and seeding of cells, as well as Matrigel coating of 6-well plastic plates and 96-well optical-grade, glass plates. We also developed an automated image-based hiPS cell colony segmentation and feature extraction pipeline to streamline the process of predicting cell count and selecting wells with consistent morphology for high-resolution three-dimensional (3D) microscopy. The imaging samples produced with this protocol have been used to study the integrated intracellular organization and cell-to-cell variability of hiPS cells to train and develop deep learning-based label-free predictions from transmitted-light microscopy images and to develop deep learning-based generative models of single-cell organization. This protocol requires some experience with robotic equipment. However, we provide details and source code to facilitate implementation by biologists less experienced with robotics. The protocol is completed in less than 10 h with minimal human interaction. Overall, automation of our cell culture procedures increased our imaging samples' standardization, reproducibility, scalability and consistency. It also reduced the need for stringent culturist training and eliminated culturist-to-culturist variability, both of which were previous pain points of our original manual pipeline workflow.

A clinically relevant large-scale biomanufacturing workflow to produce natural killer cells and natural killer cell-derived extracellular vesicles for cancer immunotherapy

Natural killer cell-derived extracellular vesicles (NK-EVs) have shown promising potential as biotherapeutics for cancer due to their unique attributes as cytotoxic nanovesicles against cancer cells and immune-modulatory activity towards immune cells. However, a biomanufacturing workflow is needed to produce clinical-grade NK-EVs for pre-clinical and clinical applications. This study established a novel biomanufacturing workflow using a closed-loop hollow-fibre bioreactor to continuously produce NK-EVs from the clinically relevant NK92-MI cell line under serum-free, Xeno-free and feeder-free conditions following GMP-compliant conditions. The NK92 cells grown in the bioreactor for three continuous production lots resulted in large quantities of both NK cell and NK-EV biotherapeutics at the end of each production lot (over 109 viable cells and 1013 EVs), while retaining their cytotoxic payload (granzyme B and perforin), pro-inflammatory cytokine (interferon-gamma) content and cytotoxicity against the human leukemic cell line K562 with limited off-target toxicity against healthy human fibroblast cells. This scalable biomanufacturing workflow has the potential to facilitate the clinical translation of adoptive NK cell-based and NK-EV-based immunotherapies for cancer with GMP considerations.

Automated cell culture system for the production of cell aggregates with growth plate-like structure from induced pluripotent stem cells

Programmable liquid handling devices for cell culture systems have dramatically enhanced scalability and reproducibility. We previously reported a protocol to produce cell aggregates demonstrating growth plate-like structures containing hypertrophic chondrocytes from human induced pluripotent stem cells (hiPSCs). To apply this protocol to large-scale drug screening for growth plate-related diseases, we adapted it to the automated cell culture system (ACCS) consisting of programmable liquid handling devices connected to CO2 incubators, a refrigerator, and labware feeders, designed for up to 4 batches with several cell culture plates culturing for several months. We developed a new program preparing culture media with growth factors at final concentration immediately before dispensing them to each well and precisely positioning the tip for the medium change without damaging cell aggregates. Using these programs on the ACCS, we successfully cultured cell aggregates for 56 days, only needing to replenish the labware, medium, and growth factors twice a week. The size of cell aggregates in each well increased over time, with low well-to-well variability. Cell aggregates on day 56 showed histochemical, immunohistochemical, and gene expression properties of growth plate-like structures containing hypertrophic chondrocytes, indicating proper quality as materials for basic research and drug discovery of growth plate related diseases. The established program will be a suitable reference for making programs of experiments requiring long term and complex culture procedures using ACCS.

Toward Transplantation of Liver Organoids: From Biology and Ethics to Cost-effective Therapy

Liver disease is a common cause of morbidity and mortality, and many patients would benefit from liver transplantation. However, because of a shortage of suitable donor livers, even of those patients who are placed on the donor liver waiting list, many do not survive the waiting time for transplantation. Therefore, alternative treatments for end-stage liver disease need to be explored. Recent advances in organoid technology might serve as a solution to overcome the donor liver shortage in the future. In this overview, we highlight the potential of organoid technology for cell therapy and tissue engineering approaches. Both organoid-based approaches could be used as treatment for end-stage liver disease patients. Additionally, organoid-based cell therapy can also be used to repair liver grafts ex vivo to increase the supply of transplantable liver tissue. The potential of both approaches to become clinically available is carefully assessed, including their clinical, ethical, and economic implications. We provide insight into what aspects should be considered further to allow alternatives to donor liver transplantation to be successfully clinically implemented.

Natural Killer Cell-Derived Extracellular Vesicles as a Promising Immunotherapeutic Strategy for Cancer: A Systematic Review

Cancer is the second leading contributor to global deaths caused by non-communicable diseases. The cancer cells are known to interact with the surrounding non-cancerous cells, including the immune cells and stromal cells, within the tumor microenvironment (TME) to modulate the tumor progression, metastasis and resistance. Currently, chemotherapy and radiotherapy are the standard treatments for cancers. However, these treatments cause a significant number of side effects, as they damage both the cancer cells and the actively dividing normal cells indiscriminately. Hence, a new generation of immunotherapy using natural killer (NK) cells, cytotoxic CD8⁺ T-lymphocytes or macrophages was developed to achieve tumor-specific targeting and circumvent the adverse effects. However, the progression of cell-based immunotherapy is hindered by the combined action of TME and TD-EVs, which render the cancer cells less immunogenic. Recently, there has been an increase in interest in using immune cell derivatives to treat cancers. One of the highly potential immune cell derivatives is the NK cell-derived EVs (NK-EVs). As an acellular product, NK-EVs are resistant to the influence of TME and TD-EVs, and can be designed for "off-the-shelf" use. In this systematic review, we examine the safety and efficacy of NK-EVs to treat various cancers in vitro and in vivo.

Organoid factory: The recent role of the human induced pluripotent stem cells (hiPSCs) in precision medicine

During the last decades, hiPSC-derived organoids have been extensively studied and used as in vitro models for several applications among which research studies. They can be considered as organ and tissue prototypes, especially for those difficult to obtain. Moreover, several diseases can be accurately modeled and studied. Hence, patient-derived organoids (PDOs) can be used to predict individual drug responses, thus paving the way toward personalized medicine. Lastly, by applying tissue engineering and 3D printing techniques, organoids could be used in the future to replace or regenerate damaged tissue. In this review, we will focus on hiPSC-derived 3D cultures and their ability to model human diseases with an in-depth analysis of gene editing applications, as well as tumor models. Furthermore, we will highlight the state-of-the-art of organoid facilities that around the world offer know-how and services. This is an increasing trend that shed the light on the need of bridging the publicand the private sector. Hence, in the context of drug discovery, Organoid Factories can offer biobanks of validated 3D organoid models that can be used in collaboration with pharmaceutical companies to speed up the drug screening process. Finally, we will discuss the limitations and the future development that will lead hiPSC-derived technology from bench to bedside, toward personalized medicine, such as maturity, organoid interconnections, costs, reproducibility and standardization, and ethics. hiPSC-derived organoid technology is now passing from a proof-of-principle to real applications in the clinic, also thanks to the applicability of techniques, such as CRISPR/Cas9 genome editing system, material engineering for the scaffolds, or microfluidic systems. The benefits will have a crucial role in the advance of both basic biological and translational research, particularly in the pharmacological field and drug development. In fact, in the near future, 3D organoids will guide the clinical decision-making process, having validated patient-specific drug screening platforms. This is particularly important in the context of rare genetic diseases or when testing cancer treatments that could in principle have severe side effects. Therefore, this technology has enabled the advancement of personalized medicine in a way never seen before.

Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks

Human pluripotent stem cells are promising for a wide range of research and therapeutic purposes. Their maintenance in culture requires the deep control of their pluripotent and clonal status. A non-invasive method for such control involves day-to-day observation of the morphological changes, along with imaging colonies, with the subsequent automatic assessment of colony phenotype using image analysis by machine learning methods. We developed a classifier using a convolutional neural network and applied it to discriminate between images of human embryonic stem cell (hESC) colonies with "good" and "bad" morphological phenotypes associated with a high and low potential for pluripotency and clonality maintenance, respectively. The training dataset included the phase-contrast images of hESC line H9, in which the morphological phenotype of each colony was assessed through visual analysis. The classifier showed a high level of accuracy (89%) in phenotype prediction. By training the classifier on cropped images of various sizes, we showed that the spatial scale of ~144 μm was the most informative in terms of classification quality, which was an intermediate size between the characteristic diameters of a single cell (~15 μm) and the entire colony (~540 μm). We additionally performed a proteomic analysis of several H9 cell samples used in the computational analysis and showed that cells of different phenotypes differentiated at the molecular level. Our results indicated that the proposed approach could be used as an effective method of non-invasive automated analysis to identify undesirable developmental anomalies during the propagation of pluripotent stem cells.

Induced Pluripotent Stem Cells, a Stepping Stone to In Vitro Human Models of Hearing Loss

Hearing loss is the most prevalent sensorineural impairment in humans. Yet despite very active research, no effective therapy other than the cochlear implant has reached the clinic. Main reasons for this failure are the multifactorial nature of the disorder, its heterogeneity, and a late onset that hinders the identification of etiological factors. Another problem is the lack of human samples such that practically all the work has been conducted on animals. Although highly valuable data have been obtained from such models, there is the risk that inter-species differences exist that may compromise the relevance of the gathered data. Human-based models are therefore direly needed. The irruption of human induced pluripotent stem cell technologies in the field of hearing research offers the possibility to generate an array of otic cell models of human origin; these may enable the identification of guiding signalling cues during inner ear development and of the mechanisms that lead from genetic alterations to pathology. These models will also be extremely valuable when conducting ototoxicity analyses and when exploring new avenues towards regeneration in the inner ear. This review summarises some of the work that has already been conducted with these cells and contemplates future possibilities.

Damage-free evaluation of cultured cells based on multivariate analysis with a single-polymer probe

We present a pattern-recognition-based sensor that targets cell-derived components in culture media and evaluates cultured cells without damaging them. An array sensor made of a single-polymer probe was employed to obtain fluorescence response patterns of the analyte media, allowing successful identification of the type and state of the cells via multivariate analysis.

Opportunities for pharmacoproteomics in biomarker discovery

Proteomic data are a uniquely valuable resource for drug response prediction and biomarker discovery because most drugs interact directly with proteins in target cells rather than with DNA or RNA. Recent advances in mass spectrometry and associated processing methods have enabled the generation of large-scale proteomic datasets. Here we review the significant opportunities that currently exist to combine large-scale proteomic data with drug-related research, a field termed pharmacoproteomics. We describe successful applications of drug response prediction using molecular data, with an emphasis on oncology. We focus on technical advances in data-independent acquisition mass spectrometry (DIA-MS) that can facilitate the discovery of protein biomarkers for drug responses, alongside the increased availability of big biomedical data. We spotlight new opportunities for machine learning in pharmacoproteomics, driven by the combination of these large datasets and improved high-performance computing. Finally, we explore the value of pre-clinical models for pharmacoproteomic studies and the accompanying challenges of clinical validation. We propose that pharmacoproteomics offers the potential for novel discovery and innovation within the cancer landscape. This article is protected by copyright. All rights reserved.

AAV2-mediated gene therapy for Bietti crystalline dystrophy provides functional CYP4V2 in multiple relevant cell models

Bietti crystalline dystrophy (BCD) is an inherited retinal disease (IRD) caused by mutations in the CYP4V2 gene. It is a relatively common cause of IRD in east Asia. A number of features of this disease make it highly amenable to gene supplementation therapy. This study aims to validate a series of essential precursor in vitro experiments prior to developing a clinical gene therapy for BCD. We demonstrated that HEK293, ARPE19, and patient induced pluripotent stem cell (iPSC)-derived RPE cells transduced with AAV2 vectors encoding codon optimization of CYP4V2 (AAV2.coCYP4V2) resulted in elevated protein expression levels of CYP4V2 compared to those transduced with AAV2 vectors encoding wild type CYP4V2 (AAV2.wtCYP4V2), as assessed by immunocytochemistry and western blot. Similarly, we observed significantly increased CYP4V2 enzyme activity in cells transduced with AAV2.coCYP4V2 compared to those transduced with AAV2.wtCYP4V2. We also showed CYP4V2 expression in human RPE/choroid explants transduced with AAV2.coCYP4V2 compared to those transduced with AAV2.wtCYP4V2. These preclinical data support the further development of a gene supplementation therapy for a currently untreatable blinding condition—BCD. Codon-optimized CYP4V2 transgene was superior to wild type in terms of protein expression and enzyme activity. Ex vivo culture of human RPE cells provided an effective approach to test AAV-mediated transgene delivery.

Cell Cluster Sorting in Automated Differentiation of Patient-specific Induced Pluripotent Stem Cells Towards Blood Cells

Induced pluripotent stem cells (iPS cells) represent a particularly versatile stem cell type for a large array of applications in biology and medicine. Taking full advantage of iPS cell technology requires high throughput and automated iPS cell culture and differentiation. We present an automated platform for efficient and robust iPS cell culture and differentiation into blood cells. We implemented cell cluster sorting for analysis and sorting of iPS cell clusters in order to establish clonal iPS cell lines with high reproducibility and efficacy. Patient-specific iPS cells were induced to differentiate towards hematopoietic cells via embryoid body (EB) formation. EB size impacts on iPS cell differentiation and we applied cell cluster sorting to obtain EB of defined size for efficient blood cell differentiation. In summary, implementing cell cluster sorting into the workflow of iPS cell cloning, growth and differentiation represent a valuable add-on for standard and automated iPS cell handling.

Robotic high-throughput biomanufacturing and functional differentiation of human pluripotent stem cells

Efficient translation of human induced pluripotent stem cells (hiPSCs) requires scalable cell manufacturing strategies for optimal self-renewal and functional differentiation. Traditional manual cell culture is variable and labor intensive, posing challenges for high-throughput applications. Here, we established a robotic platform and automated all essential steps of hiPSC culture and differentiation under chemically defined conditions. This approach allowed rapid and standardized manufacturing of billions of hiPSCs that can be produced in parallel from up to 90 different patient- and disease-specific cell lines. Moreover, we established automated multi-lineage differentiation and generated functional neurons, cardiomyocytes, and hepatocytes. To validate our approach, we compared robotic and manual cell culture operations and performed comprehensive molecular and cellular characterizations (e.g., single-cell transcriptomics, mass cytometry, metabolism, electrophysiology) to benchmark industrial-scale cell culture operations toward building an integrated platform for efficient cell manufacturing for disease modeling, drug screening, and cell therapy.

Transitioning into GMP-Compliance: Alternative Methods for Producing Retinal Organoids for Transplantation

Three-dimensional retinal organoids derived from human induced pluripotent stem cells (hiPSCs) are gaining much attention as a possible source for cell transplantation to treat retinal degenerative conditions. However, the protocol for producing retinal organoids is time and labor intensive, involving a sequence of precise steps, and thus has yet to be successfully translated into a Good Manufacturing Practice (GMP)-compliant procedure. This review seeks to define the progress that has already been made in the pursuit of designing a GMP-compliant, streamlined, and automated protocol for retinal organoid production for optimal clinical success. The reviewed literature compares various approaches for cell culture automation, appropriate xeno-free conditions, and cell sources for iPSC line generation; yet, there are still important gaps for these three key considerations that remain to be addressed. Thus, the authors also discuss further potential strategies to successfully achieve GMP-compliant production of retinal organoids for eventual safe and efficient use in clinical trials.

Automation of Organoid Cultures: Current Protocols and Applications

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Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking

Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop quality control methods to standardize stem cell manufacturing. Here, we report a deep learning-based automated cell tracking (DeepACT) technology for noninvasive quality control and identification of cultured human stem cells. The combination of deep learning-based cascading cell detection and Kalman filter algorithm-based tracking successfully tracked the individual cells within the densely packed human epidermal keratinocyte colonies in the phase-contrast images of the culture. DeepACT rapidly analyzed the motion of individual keratinocytes, which enabled the quantitative evaluation of keratinocyte dynamics in response to changes in culture conditions. Furthermore, DeepACT can distinguish keratinocyte stem cell colonies from non-stem cell-derived colonies by analyzing the spatial and velocity information of cells. This system can be widely applied to stem cell cultures used in regenerative medicine and provides a platform for developing reliable and noninvasive quality control technology.

Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery—A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation

Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.

Techno-Economic Analysis of Automated iPSC Production

Induced pluripotent stem cells (iPSC) open up the unique perspective of manufacturing cell products for drug development and regenerative medicine in tissue-, disease- and patient-specific forms. iPSC can be multiplied almost without restriction and differentiated into cell types of all organs. The basis for clinical use of iPSC is a high number of cells (approximately 7 × 107 cells per treatment), which must be produced cost-effectively while maintaining reproducible and high quality. Compared to manual cell production, the automation of cell production offers a unique chance of reliable reproducibility of cells in addition to cost reduction and increased throughput. StemCellFactory is a prototype for a fully automated production of iPSC. However, in addition to the already tested functionality of the system, it must be shown that this automation brings necessary economic advantages. This paper presents that fully automated stem cell production offers economic advantages in addition to increased throughput and better quality. First, biological and technological basics for a fully automated production of iPSC are presented. Second, the basics for profitability calculation are presented. Third, profitability of both manual and automated production are calculated. Finally, different scenarios effecting the profitability of manual and automated production are compared.

A Variable Scheduling Maintenance Culture Platform for Mammalian Cells

Cell culturing is a basic experimental technique in cell biology and medical science. However, culturing high-quality cells with a high degree of reproducibility relies heavily on expert skills and tacit knowledge, and it is not straightforward to scale the production process due to the education bottleneck. Although many automated culture systems have been developed and a few have succeeded in mass production environments, very few robots are permissive of frequent protocol changes, which are often required in basic research environments. LabDroid is a general-purpose humanoid robot with two arms that performs experiments using the same tools as humans. Combining our newly developed AI software with LabDroid, we developed a variable scheduling system that continuously produces subcultures of cell lines without human intervention. The system periodically observes the cells on plates with a microscope, predicts the cell growth curve by processing cell images, and decides the best times for passage. We have succeeded in developing a system that maintains the cultures of two HEK293A cell plates with no human intervention for 192 h.

Microfluidic Sensing System with a Multichannel Surface Plasmon Resonance Chip: Damage-Free Characterization of Cells by Pattern Recognition

The development of a versatile sensing strategy for the damage-free characterization of cultured cells is of great importance for both fundamental biological research and industrial applications. Here, we present a pattern-recognition-based cell-sensing approach using a multichannel surface plasmon resonance (SPR) chip. The chip, in which five cysteine derivatives with different structures are immobilized on Au films, is capable of generating five unique SPR sensorgrams for the cell-secreted molecules that are contained in cell culture media. An automatic statistical program was built to acquire kinetic parameters from the SPR sensorgrams and to select optimal parameters as "pattern information" for subsequent multivariate analysis. Our system rapidly (∼10 min) provides the complex information by merely depositing a small amount of cell culture media (∼25 μL) onto the chip, and the amount of information obtained is comparable to that furnished by a combination of conventional laborious biochemical assays. This noninvasive pattern-recognition-based cell-sensing approach could potentially be employed as a versatile tool for characterizing cells.

Automation in the Life Science Research Laboratory

Protocols in the academic life science laboratory are heavily reliant on the manual manipulation of tools, reagents and instruments by a host of research staff and students. In contrast to industrial and clinical laboratory environments, the usage of automation to augment or replace manual tasks is limited. Causes of this 'automation gap' are unique to academic research, with rigid short-term funding structures, high levels of protocol variability and a benevolent culture of investment in people over equipment. Automation, however, can bestow multiple benefits through improvements in reproducibility, researcher efficiency, clinical translation, and safety. Less immediately obvious are the accompanying limitations, including obsolescence and an inhibitory effect on the freedom to innovate. Growing the range of automation options suitable for research laboratories will require more flexible, modular and cheaper designs. Academic and commercial developers of automation will increasingly need to design with an environmental awareness and an understanding that large high-tech robotic solutions may not be appropriate for laboratories with constrained financial and spatial resources. To fully exploit the potential of laboratory automation, future generations of scientists will require both engineering and biology skills. Automation in the research laboratory is likely to be an increasingly critical component of future research programs and will continue the trend of combining engineering and science expertise together to answer novel research questions.

The StemCellFactory: A Modular System Integration for Automated Generation and Expansion of Human Induced Pluripotent Stem Cells

While human induced pluripotent stem cells (hiPSCs) provide novel prospects for disease-modeling, the high phenotypic variability seen across different lines demands usage of large hiPSC cohorts to decipher the impact of individual genetic variants. Thus, a much higher grade of parallelization, and throughput in the production of hiPSCs is needed, which can only be achieved by implementing automated solutions for cell reprogramming, and hiPSC expansion. Here, we describe the StemCellFactory, an automated, modular platform covering the entire process of hiPSC production, ranging from adult human fibroblast expansion, Sendai virus-based reprogramming to automated isolation, and parallel expansion of hiPSC clones. We have developed a feeder-free, Sendai virus-mediated reprogramming protocol suitable for cell culture processing via a robotic liquid handling unit that delivers footprint-free hiPSCs within 3 weeks with state-of-the-art efficiencies. Evolving hiPSC colonies are automatically detected, harvested, and clonally propagated in 24-well plates. In order to ensure high fidelity performance, we have implemented a high-speed microscope for in-process quality control, and image-based confluence measurements for automated dilution ratio calculation. This confluence-based splitting approach enables parallel, and individual expansion of hiPSCs in 24-well plates or scale-up in 6-well plates across at least 10 passages. Automatically expanded hiPSCs exhibit normal growth characteristics, and show sustained expression of the pluripotency associated stem cell marker TRA-1-60 over at least 5 weeks (10 passages). Our set-up enables automated, user-independent expansion of hiPSCs under fully defined conditions, and could be exploited to generate a large number of hiPSC lines for disease modeling, and drug screening at industrial scale, and quality.

Robotic High-Throughput Biomanufacturing and Functional Differentiation of Human Pluripotent Stem Cells

Efficient translation of human induced pluripotent stem cells (hiPSCs) depends on implementing scalable cell manufacturing strategies that ensure optimal self-renewal and functional differentiation. Currently, manual culture of hiPSCs is highly variable and labor-intensive posing significant challenges for high-throughput applications. Here, we established a robotic platform and automated all essential steps of hiPSC culture and differentiation under chemically defined conditions. This streamlined approach allowed rapid and standardized manufacturing of billions of hiPSCs that can be produced in parallel from up to 90 different patient-and disease-specific cell lines. Moreover, we established automated multi-lineage differentiation to generate primary embryonic germ layers and more mature phenotypes such as neurons, cardiomyocytes, and hepatocytes. To validate our approach, we carefully compared robotic and manual cell culture and performed molecular and functional cell characterizations (e.g. bulk culture and single-cell transcriptomics, mass cytometry, metabolism, electrophysiology, Zika virus experiments) in order to benchmark industrial-scale cell culture operations towards building an integrated platform for efficient cell manufacturing for disease modeling, drug screening, and cell therapy. Combining stem cell-based models and non-stop robotic cell culture may become a powerful strategy to increase scientific rigor and productivity, which are particularly important during public health emergencies (e.g. opioid crisis, COVID-19 pandemic).

Neuronal Reprogramming for Tissue Repair and Neuroregeneration

Stem cell and cell reprogramming technology represent a rapidly growing field in regenerative medicine. A number of novel neural reprogramming methods have been established, using pluripotent stem cells (PSCs) or direct reprogramming, to efficiently derive specific neuronal cell types for therapeutic applications. Both in vitro and in vivo cellular reprogramming provide diverse therapeutic pathways for modeling neurological diseases and injury repair. In particular, the retina has emerged as a promising target for clinical application of regenerative medicine. Herein, we review the potential of neuronal reprogramming to develop regenerative strategy, with a particular focus on treating retinal degenerative diseases and discuss future directions and challenges in the field.

Automated sensing and splitting of stem cell colonies on microraft arrays

Human induced pluripotent stem cells (hiPSCs) are widely used for disease modeling, tissue engineering, and clinical applications. Although the development of new disease-relevant or customized hiPSC lines is of high importance, current automated hiPSC isolation technologies rely largely on the fluorescent labeling of cells, thus limiting the cell line development from many applications. The objective of this research was to develop a platform for high-throughput hiPSC cytometry and splitting that utilized a label-free cell sensing approach. An image analysis pipeline utilizing background subtraction and standard deviation projections was implemented to detect hiPSC colonies from bright-field microscopy data. The pipeline was incorporated into an automated microscopy system coupling quad microraft cell-isolation arrays, computer-based vision, and algorithms for smart decision making and cell sorting. The pipeline exhibited a hiPSC detection specificity of 98% and a sensitivity of 88%, allowing for the successful tracking of growth for hundreds of microcolonies over 7 days. The automated platform split 170 mother colonies from a microarray within 80 min, and the harvested daughter biopsies were expanded into viable hiPSC colonies suitable for downstream assays, such as polymerase chain reaction (PCR) or continued culture. Transmitted light microscopy offers an alternative, label-free modality for isolating hiPSCs, yet its low contrast and specificity for adherent cells remain a challenge for automation. This novel approach to label-free sensing and microcolony subsampling with the preservation of the mother colony holds the potential for hiPSC colony screening based on a wide range of properties including those measurable only by a cell destructive assay.

Fabricating retinal pigment epithelial cell sheets derived from human induced pluripotent stem cells in an automated closed culture system for regenerative medicine

Regenerative medicine has received a lot of attention as a novel strategy for injuries and diseases that are difficult to cure using current techniques. Cell production, which is vital for regenerative medicine, has undergone remarkable progress via breakthroughs in developmental biology and tissue engineering; currently, cell production requires numerous experimental operators performing manual, small-scale cell cultures. Other major obstacles for cell production and regenerative medicine include the variable quality of products based on the experimental procedure, the skills of operators, the level of labor required for production, and costs. Technological developments are required to overcome this, including automation instead of manual culture. Age-related macular regeneration (AMD) is a refractory ocular disease that causes severe deterioration in central vision due to senescence in the retinal pigment epithelium (RPE). Recently, we performed an autologous transplantation of induced pluripotent stem (iPS) cell-derived RPE cell sheets and started clinical research on allografts from RPE cell suspensions differentiated from iPS cells. The use of regenerative therapies for AMD using iPS cell-derived RPE is expected to become more widespread. In the present study, human iPS cell-derived RPE cells were cultured to form RPE cell sheets using equipment with a closed culture module. The quality of the automated cultured RPE cell sheets was confirmed by comparing their morphological and biological properties with those of manually generated RPE cell sheets. As a result, machine-cultured RPE sheets displayed the same quality as manually cultured RPE sheets, showing that iPS cell-derived RPE cell sheets were successfully cultured by an automated process.

Physiological Microenvironmental Conditions in Different Scalable Culture Systems for Pluripotent Stem Cell Expansion and Differentiation

Human Pluripotent Stem Cells (PSCs) are a valuable cell type that has a wide range of biomedical applications because they can differentiate into many types of adult somatic cell. Numerous studies have examined the clinical applications of PSCs. However, several factors such as bioreactor design, mechanical stress, and the physiological environment have not been optimized. These factors can significantly alter the pluripotency and proliferation properties of the cells, which are important for the mass production of PSCs. Nutritional mass transfer and oxygen transfer must be effectively maintained to obtain a high yield. Various culture systems are currently available for optimum cell propagation by maintaining the physiological conditions necessary for cell cultivation. Each type of culture system using a different configuration with various advantages and disadvantages affecting the mechanical conditions in the bioreactor, such as shear stress. These factors make it difficult to preserve the cellular viability and pluripotency of PSCs. Additional limitations of the culture system for PSCs must also be identified and overcome to maintain the culture conditions and enable large-scale expansion and differentiation of PSCs. This review describes the different physiological conditions in the various culture systems and recent developments in culture technology for PSC expansion and differentiation.

Using stem cell-derived neurons in drug screening for neurological diseases

Induced pluripotent stem cells and their derivatives have become an important tool for researching disease mechanisms. It is hoped that they could be used to discover new therapies by providing the most reliable and relevant human in vitro disease models for drug discovery. This review will summarize recent efforts to use stem cell-derived neurons for drug screening. We also explain the current hurdles to using these cells for high-throughput pharmaceutical screening and developments that may help overcome these hurdles. Finally, we critically discuss whether induced pluripotent stem cell-derived neurons will come to fruition as a model that is regularly used to screen for drugs to treat neurological diseases.

Single-Cell Profiling Identifies Key Pathways Expressed by iPSCs Cultured in Different Commercial Media

We assessed the pluripotency of human induced pluripotent stem cells (iPSCs) maintained on an automated platform using StemFlex and TeSR-E8 media. Analysis of transcriptome of single cells revealed similar expression of core pluripotency genes, as well as genes associated with naive and primed states of pluripotency. Analysis of individual cells from four samples consisting of two different iPSC lines each grown in the two culture media revealed a shared subpopulation structure with three main subpopulations different in pluripotency states. By implementing a machine learning approach, we estimated that most cells within each subpopulation are very similar between all four samples. The single-cell RNA sequencing analysis of iPSC lines grown in both media reports the molecular signature in StemFlex medium and how it compares to that observed in the TeSR-E8 medium.

Optimizing the Use of a Liquid Handling Robot to Conduct a High Throughput Forward Chemical Genetics Screen of Arabidopsis thaliana

Chemical genetics is increasingly being employed to decode traits in plants that may be recalcitrant to traditional genetics due to gene redundancy or lethality. However, the probability of a synthetic small molecule being bioactive is low; therefore, thousands of molecules must be tested in order to find those of interest. Liquid handling robotics systems are designed to handle large numbers of samples, increasing the speed with which a chemical library can be screened in addition to minimizing/standardizing error. To achieve a high-throughput forward chemical genetics screen of a library of 50,000 small molecules on Arabidopsis thaliana (Arabidopsis), protocols using a bench-top multichannel liquid handling robot were developed that require minimal technician involvement. With these protocols, 3,271 small molecules were discovered that caused visible phenotypic alterations. 1,563 compounds induced short roots, 1,148 compounds altered coloration, 383 compounds caused root hair and other, non-categorized, alterations, and 177 compounds inhibited germination.