Live-cell imaging of subcellular structures for quantitative evaluation of pluripotent stem cells

Noninvasive, label-free image approaches to predict multimodal molecular markers in pluripotency assessment

Manufacturing regenerative medicine requires continuous monitoring of pluripotent cell culture and quality assessment while eliminating cell destruction and contaminants. In this study, we employed a novel method to monitor the pluripotency of stem cells through image analysis, avoiding the traditionally used invasive procedures. This approach employs machine learning algorithms to analyze stem cell images to predict the expression of pluripotency markers, such as OCT4 and NANOG, without physically interacting with or harming cells. We cultured induced pluripotent stem cells under various conditions to induce different pluripotent states and imaged the cells using bright-field microscopy. Pluripotency states of induced pluripotent stem cells were assessed using invasive methods, including qPCR, immunostaining, flow cytometry, and RNA sequencing. Unsupervised and semi-supervised learning models were applied to evaluate the results and accurately predict the pluripotency of the cells using only image analysis. Our approach directly links images to invasive assessment results, making the analysis of cell labeling and annotation of cells in images by experts dispensable. This core achievement not only contributes for safer and more reliable stem cell research but also opens new avenues for real-time monitoring and quality control in regenerative medicine manufacturing. Our research fills an important gap in the field by providing a viable, noninvasive alternative to traditional invasive methods for assessing pluripotency. This innovation is expected to make a significant contribution to improving regenerative medicine manufacturing because it will enable a more detailed and feasible understanding of cellular status during the manufacturing process.

CP-Net: Instance-aware part segmentation network for biological cell parsing

Instance segmentation of biological cells is important in medical image analysis for identifying and segmenting individual cells, and quantitative measurement of subcellular structures requires further cell-level subcellular part segmentation. Subcellular structure measurements are critical for cell phenotyping and quality analysis. For these purposes, instance-aware part segmentation network is first introduced to distinguish individual cells and segment subcellular structures for each detected cell. This approach is demonstrated on human sperm cells since the World Health Organization has established quantitative standards for sperm quality assessment. Specifically, a novel Cell Parsing Net (CP-Net) is proposed for accurate instance-level cell parsing. An attention-based feature fusion module is designed to alleviate contour misalignments for cells with an irregular shape by using instance masks as spatial cues instead of as strict constraints to differentiate various instances. A coarse-to-fine segmentation module is developed to effectively segment tiny subcellular structures within a cell through hierarchical segmentation from whole to part instead of directly segmenting each cell part. Moreover, a sperm parsing dataset is built including 320 annotated sperm images with five semantic subcellular part labels. Extensive experiments on the collected dataset demonstrate that the proposed CP-Net outperforms state-of-the-art instance-aware part segmentation networks.

Viewing early life without labels: optical approaches for imaging the early embryo†

Embryo quality is an important determinant of successful implantation and a resultant live birth. Current clinical approaches for evaluating embryo quality rely on subjective morphology assessments or an invasive biopsy for genetic testing. However, both approaches can be inherently inaccurate and crucially, fail to improve the live birth rate following the transfer of in vitro produced embryos. Optical imaging offers a potential non-invasive and accurate avenue for assessing embryo viability. Recent advances in various label-free optical imaging approaches have garnered increased interest in the field of reproductive biology due to their ability to rapidly capture images at high resolution, delivering both morphological and molecular information. This burgeoning field holds immense potential for further development, with profound implications for clinical translation. Here, our review aims to: (1) describe the principles of various imaging systems, distinguishing between approaches that capture morphological and molecular information, (2) highlight the recent application of these technologies in the field of reproductive biology, and (3) assess their respective merits and limitations concerning the capacity to evaluate embryo quality. Additionally, the review summarizes challenges in the translation of optical imaging systems into routine clinical practice, providing recommendations for their future development. Finally, we identify suitable imaging approaches for interrogating the mechanisms underpinning successful embryo development.

Neutral rhenium(I) tricarbonyl complexes with sulfur-donor ligands: anti-proliferative activity and cellular localization

Rhenium(I) tricarbonyl complexes are widely studied for their cell imaging properties and anti-cancer and anti-microbial activities, but the complexes with S-donor ligands remain relatively unexplored. A series of six fac-[Re(NN)(CO)3(SR)] complexes, where (NN) is 2,2'-bipyridyl (bipy) or 1,10-phenanthroline (phen), and RSH is a series of thiocarboxylic acid methyl esters, have been synthesized and characterized. Cellular uptake and anti-proliferative activities of these complexes in human breast cancer cell lines (MDA-MB-231 and MCF-7) were generally lower than those of the previously described fac-[Re(NN)(CO)3(OH2)]+ complexes; however, one of the complexes, fac-[Re(CO)3(phen)(SC(Ph)CH2C(O)OMe)] (3b), was active (IC50 ∼ 10 μM at 72 h treatment) in thiol-depleted MDA-MB-231 cells. Moreover, unlike fac-[Re(CO)3(phen)(OH2)]+, this complex did not lose activity in the presence of extracellular glutathione. Taken together these properties show promise for further development of 3b and its analogues as potential anti-cancer drugs for co-treatment with thiol-depleting agents. Conversely, the stable and non-toxic complex, fac-[Re(bipy)(CO)3(SC(Me)C(O)OMe)] (1a), predominantly localized in the lysosomes of MDA-MB-231 cells, as shown by live cell confocal microscopy (λex = 405 nm, λem = 470-570 nm). It is strongly localized in a subset of lysosomes (25 μM Re, 4 h treatment), as shown by co-localization with a Lysotracker dye. Longer treatment times with 1a (25 μM Re for 48 h) resulted in partial migration of the probe into the mitochondria, as shown by co-localization with a Mitotracker dye. These properties make complex 1a an attractive target for further development as an organelle probe for multimodal imaging, including phosphorescence, carbonyl tag for vibrational spectroscopy, and Re tag for X-ray fluorescence microscopy.

Optical redox imaging to screen synthetic hydrogels for stem cell-derived cardiomyocyte differentiation and maturation

Significance

Heart disease is the leading cause of death in the United States, yet research is limited by the inability to culture primary cardiac cells. Cardiomyocytes (CMs) derived from human induced pluripotent stem cells (iPSCs) are a promising solution for drug screening and disease modeling.

Aim

Induced pluripotent stem cell-derived CM (iPSC-CM) differentiation and maturation studies typically use heterogeneous substrates for growth and destructive verification methods. Reproducible, tunable substrates and touch-free monitoring are needed to identify ideal conditions to produce homogenous, functional CMs.

Approach

We generated synthetic polyethylene glycol-based hydrogels for iPSC-CM differentiation and maturation. Peptide concentrations, combinations, and gel stiffness were tuned independently. Label-free optical redox imaging (ORI) was performed on a widefield microscope in a 96-well screen of gel formulations. We performed live-cell imaging throughout differentiation and early to late maturation to identify key metabolic shifts.

Results

Label-free ORI confirmed the expected metabolic shifts toward oxidative phosphorylation throughout the differentiation and maturation processes of iPSC-CMs on synthetic hydrogels. Furthermore, ORI distinguished high and low differentiation efficiency cell batches in the cardiac progenitor stage.

Conclusions

We established a workflow for medium throughput screening of synthetic hydrogel conditions with the ability to perform repeated live-cell measurements and confirm expected metabolic shifts. These methods have implications for reproducible iPSC-CM generation in biomanufacturing.

Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods

Human pluripotent stem cells have the potential for unlimited proliferation and controlled differentiation into various somatic cells, making them a unique tool for regenerative and personalized medicine. Determining the best clone selection is a challenging problem in this field and requires new sensing instruments and methods able to automatically assess the state of a growing colony ('phenotype') and make decisions about its destiny. One possible solution for such label-free, non-invasive assessment is to make phase-contrast images and/or videos of growing stem cell colonies, process the morphological parameters ('morphological portrait', or signal), link this information to the colony phenotype, and initiate an automated protocol for the colony selection. As a step in implementing this strategy, we used machine learning methods to find an effective model for classifying the human pluripotent stem cell colonies of three lines according to their morphological phenotype ('good' or 'bad'), using morphological parameters from the previously published data as predictors. We found that the model using cellular morphological parameters as predictors and artificial neural networks as the classification method produced the best average accuracy of phenotype prediction (67%). When morphological parameters of colonies were used as predictors, logistic regression was the most effective classification method (75% average accuracy). Combining the morphological parameters of cells and colonies resulted in the most effective model, with a 99% average accuracy of phenotype prediction. Random forest was the most efficient classification method for the combined data. We applied feature selection methods and showed that different morphological parameters were important for phenotype recognition via either cellular or colonial parameters. Our results indicate a necessity for retaining both cellular and colonial morphological information for predicting the phenotype and provide an optimal choice for the machine learning method. The classification models reported in this study could be used as a basis for developing and/or improving automated solutions to control the quality of human pluripotent stem cells for medical purposes.

Time-dependent cell-state selection identifies transiently expressed genes regulating ILC2 activation

The decision of whether cells are activated or not is controlled through dynamic intracellular molecular networks. However, the low population of cells during the transition state of activation renders the analysis of the transcriptome of this state technically challenging. To address this issue, we have developed the Time-Dependent Cell-State Selection (TDCSS) technique, which employs live-cell imaging of secretion activity to detect an index of the transition state, followed by the simultaneous recovery of indexed cells for subsequent transcriptome analysis. In this study, we used the TDCSS technique to investigate the transition state of group 2 innate lymphoid cells (ILC2s) activation, which is indexed by the onset of interleukin (IL)-13 secretion. The TDCSS approach allowed us to identify time-dependent genes, including transiently induced genes (TIGs). Our findings of IL4 and MIR155HG as TIGs have shown a regulatory function in ILC2s activation.

Label-free optical imaging and sensing for quality control of stem cell manufacturing

Human stem cells provide emerging methods for drug screening, disease modeling, and personalized patient therapies. To meet this growing demand for scale-up, stem cell manufacturing methods must be streamlined with continuous monitoring technologies and automated feedback to optimize growth conditions for high production and consistency. Label-free optical imaging and sensing, including multiphoton microscopy, Raman spectroscopy, and low-cost methods such as phase and transmitted light microscopy, can provide rapid, repeatable, and non-invasive monitoring of stem cells throughout cell differentiation and maturation. Machine learning algorithms trained on label-free optical imaging and sensing features could identify viable cells and predict optimal manufacturing conditions. These techniques have the potential to streamline stem cell manufacturing and accelerate their use in regenerative medicine.

Locus-Specific Isolation of the Nanog Chromatin Identifies Regulators Relevant to Pluripotency of Mouse Embryonic Stem Cells and Reprogramming of Somatic Cells

Pluripotency is a crucial feature of pluripotent stem cells, which are regulated by the core pluripotency network consisting of key transcription factors and signaling molecules. However, relatively less is known about the molecular mechanisms that modify the core pluripotency network. Here we used the CAPTURE (CRISPR Affinity Purification in situ of Regulatory Elements) to unbiasedly isolate proteins assembled on the Nanog promoter in mouse embryonic stem cells (mESCs), and then tested their functional relevance to the maintenance of mESCs and reprogramming of somatic cells. Gene ontology analysis revealed that the identified proteins, including many RNA-binding proteins (RBPs), are enriched in RNA-related functions and gene expression. ChIP-qPCR experiments confirmed that BCLAF1, FUBP1, MSH6, PARK7, PSIP1, and THRAP3 occupy the Nanog promoter region in mESCs. Knockdown experiments of these factors show that they play varying roles in self-renewal, pluripotency gene expression, and differentiation of mESCs as well as in the reprogramming of somatic cells. Our results show the utility of unbiased identification of chromatin-associated proteins on a pluripotency gene in mESCs and reveal the functional relevance of RBPs in ESC differentiation and somatic cell reprogramming.

Differential phase measurement based on synchronous phase shift determination

Based on synchronous phase shift determination, we propose a differential phase measurement method for differential interference contrast (DIC) microscopy. An on-line phase shift measurement device is used to generate carrier interferograms and determine the phase shift of DIC images. Then the differential phase can be extracted with the least-squares phase-shifting algorithm. In addition to realizing on-line, dynamic, real-time, synchronous and high precision phase shift measurement, the proposed method also can reconstruct the phase of the specimen by using the phase-integral algorithm. The differential phase measurement method reveals obvious advantages in error compensation, anti-interference, and noise suppression. Both simulation analysis and experimental result demonstrate that using the proposed method, the accuracy of phase shift measurement is higher than 0.007 rad. Very accurate phase reconstructions were obtained with both polystyrene microspheres and human vascular endothelial.

Downregulation of Odd-Skipped Related 2, a Novel Regulator of Epithelial-Mesenchymal Transition, Enables Efficient Somatic Cell Reprogramming

Somatic cell reprogramming proceeds through a series of events to generate induced pluripotent stem cells (iPSCs). The early stage of reprogramming of mouse embryonic fibroblasts (MEFs) is characterized by rapid cell proliferation and morphological changes, which are accompanied by downregulation of mesenchyme-associated genes. However, the functional relevance of their downregulation to reprogramming remains poorly defined. In this study, we have screened transcriptional regulators that are downregulated immediately upon reprogramming, presumably through direct targeting by reprogramming factors. To test if these transcriptional regulators impact reprogramming when expressed continuously, we generated an expression vector that harbors human cytomegalovirus upstream open reading frame 2 (uORF2), which reduces translation to minimize the detrimental effect of an expressed protein. Screening of transcriptional regulators with this expression vector revealed that downregulation of odd-skipped related 2 (Osr2) is crucial for efficient reprogramming. Using a cell-based model for epithelial-mesenchymal transition (EMT), we show that Osr2 is a novel EMT regulator that acts through induction of TGF-β signaling. During reprogramming, Osr2 downregulation not only diminishes TGF-β signaling but also allows activation of Wnt signaling, thus promoting mesenchymal-epithelial transition (MET) toward acquisition of pluripotency. Our results illuminate the functional significance of Osr2 downregulation in erasing the mesenchymal phenotype at an early stage of somatic cell reprogramming.

Microtubule-dependent subcellular organisation of pluripotent cells

With the advancement of cutting-edge live imaging technologies, microtubule remodelling has evolved as an integral regulator for the establishment of distinct differentiated cells. However, despite their fundamental role in cell structure and function, microtubules have received less attention when unravelling the regulatory circuitry of pluripotency. Here, we summarise the role of microtubule organisation and microtubule-dependent events required for the formation of pluripotent cells in vivo by deciphering the process of early embryogenesis: from fertilisation to blastocyst. Furthermore, we highlight current advances in elucidating the significance of specific microtubule arrays in in vitro culture systems of pluripotent stem cells and how the microtubule cytoskeleton serves as a highway for the precise intracellular movement of organelles. This Review provides an informed understanding of the intrinsic role of subcellular architecture of pluripotent cells and accentuates their regenerative potential in combination with innovative light-inducible microtubule techniques.

Single-shot quantitative phase imaging as an extension of differential interference contrast microscopy

Various studies have been conducted to obtain quantitative phase information based on differential interference contrast (DIC) microscopy. As one such attempt, we propose in this study a single-shot quantitative phase imaging (QPI) method by combining two developments. First, an add-on optical system to a commercialized DIC microscope was developed to perform quantitative phase gradient imaging (QPGI) with single image acquisition using a polarization camera. Second, an algorithm was formulated to reconstitute QPI from the obtained QPGI by reducing linear artifacts, which arise in simply integrated QPGI images. To demonstrate the applicability of the developed system in cell biology, the system was used to measure various cell lines and compared with fluorescence microscopy images of the same field of view. Consistent with previous studies, nucleoli and lipid droplets can be imaged by the system with greater optical path lengths (OPL). The results also implied that combining fluorescence microscopy and the developed system might be more informative for cell biology research than using these methods individually. Exploiting the single-shot performance of the developed system, time-lapse imaging was also conducted to visualize the dynamics of intracellular granules in monocyte-/macrophage-like cells. Our proposed approach may accelerate the implementation of QPI in standard biomedical laboratories.

Video bioinformatics analysis of human pluripotent stem cell morphology, quality, and cellular dynamics

StemCellQC is a video bioinformatics software tool for the quantitative analysis of human pluripotent stem cell (hPSC) colonies. Our objective was to use StemCellQC to evaluate and compare various experimental culture conditions, cell lines, and treatments and to demonstrate its applicability to PSC problems. Seven key features were identified that provided useful information on PSC morphology, dynamic behavior, and viability. Colony attachment was better on laminin‐521 than on Matrigel and Geltrex. Growth rates were similar on each matrix when data were normalized. The brightness/area ratio feature showed greater cell death in colonies grown on Matrigel and Geltrex than on laminin‐521 further contributing to an overall greater yield of cells on laminin‐521. Four different PSC culture media performed similarly; however, one medium produced batch‐to‐batch variation in colony morphology and dynamic features. Two embryonic and one induced pluripotent stem cell line showed significant differences in morphology, growth rates, motility, and death rates. Cells from the same vial that became phenotypically different in culture showed measurable differences in morphology, brightness, and motility. Likewise, differentiating and undifferentiated colonies varied in growth rate, intensity, and motility. Three pluripotent cell lines treated with a low concentration of cinnamaldehyde, a chemical used in consumer products, showed adverse effects and differed in their sensitivity to treatment. Our data demonstrate various applications of StemCellQC which could be used in basic and translational research, toxicological and drug testing, and clinical facilities engaged in stem cell therapy.

Cells/colony motion of oral keratinocytes determined by non-invasive and quantitative measurement using optical flow predicts epithelial regenerative capacity

Cells/colony motion determined by non-invasive, quantitative measurements using the optical flow (OF) algorithm can indicate the oral keratinocyte proliferative capacity in early-phase primary cultures. This study aimed to determine a threshold for the cells/colony motion index to detect substandard cell populations in a subsequent subculture before manufacturing a tissue-engineered oral mucosa graft and to investigate the correlation with the epithelial regenerative capacity. The distinctive proliferating pattern of first-passage [passage 1 (p1)] cells reveals the motion of p1 cells/colonies, which can be measured in a non-invasive, quantitative manner using OF with fewer full-screen imaging analyses and cell segmentations. Our results demonstrate that the motion index lower than 40 μm/h reflects cellular damages by experimental metabolic challenges although this value shall only apply in case of our culture system. Nonetheless, the motion index can be used as the threshold to determine the quality of cultured cells while it may be affected by any different culture conditions. Because the p1 cells/colony motion index is correlated with epithelial regenerative capacity, it is a reliable index for quality control of oral keratinocytes.

The frontier of live tissue imaging across space and time

What you see is what you get-imaging techniques have long been essential for visualization and understanding of tissue development, homeostasis, and regeneration, which are driven by stem cell self-renewal and differentiation. Advances in molecular and tissue modeling techniques in the last decade are providing new imaging modalities to explore tissue heterogeneity and plasticity. Here we describe current state-of-the-art imaging modalities for tissue research at multiple scales, with a focus on explaining key tradeoffs such as spatial resolution, penetration depth, capture time/frequency, and moieties. We explore emerging tissue modeling and molecular tools that improve resolution, specificity, and throughput.

Transcriptomic and Morphological Analysis of Cells Derived from Porcine Buccal Mucosa-Studies on an In Vitro Model

Simple Summary

Domestic pigs express high phylogenetic similarity to humans and are often used as a compatible model in biomedical research. Porcine tissues are used as an accessible biomaterial in human skin transplants and tissue architecture reconstruction. We used transcriptional analysis to investigate the dynamics of complex biological system of the mucosa. Additionally, we performed computer analysis of microscopic images of cultured cells in vitro. Computer analysis of images identified epithelial cells and connective tissue cells in in vitro culture.

Abstract

Transcriptional analysis and live-cell imaging are a powerful tool to investigate the dynamics of complex biological systems. In vitro expanded porcine oral mucosal cells, consisting of populations of epithelial and connective lineages, are interesting and complex systems for study via microarray transcriptomic assays to analyze gene expression profile. The transcriptomic analysis included 56 ontological groups with particular focus on 7 gene ontology groups that are related to the processes of differentiation and development. Most analyzed genes were upregulated after 7 days and downregulated after 15 and 30 days of in vitro culture. The performed transcriptomic analysis was then extended to include automated analysis of differential interference contrast microscopy (DIC) images obtained during in vitro culture. The analysis of DIC imaging allowed to identify the different populations of keratinocytes and fibroblasts during seven days of in vitro culture, and it was possible to evaluate the proportion of these two populations of cells. Porcine mucosa may be a suitable model for reference research on human tissues. In addition, it can provide a reference point for research on the use of cells, scaffolds, or tissues derived from transgenic animals for applications in human tissues reconstruction.

Mechanisms of the Metabolic Shift during Somatic Cell Reprogramming

Pluripotent stem cells (PSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), hold a huge promise for regenerative medicine, drug development, and disease modeling. PSCs have unique metabolic features that are akin to those of cancer cells, in which glycolysis predominates to produce energy as well as building blocks for cellular components. Recent studies indicate that the unique metabolism in PSCs is not a mere consequence of their preference for a low oxygen environment, but is an active process for maintaining self-renewal and pluripotency, possibly in preparation for rapid response to the metabolic demands of differentiation. Understanding the regulatory mechanisms of this unique metabolism in PSCs is essential for proper derivation, generation, and maintenance of PSCs. In this review, we discuss the metabolic features of PSCs and describe the current understanding of the mechanisms of the metabolic shift during reprogramming from somatic cells to iPSCs, in which the metabolism switches from oxidative phosphorylation (OxPhos) to glycolysis.