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Mechanical stimulation of induced pluripotent stem derived cardiac fibroblasts | Scientific Reports – Nature.com

CFs are the main contributors of cardiac fibrosis development3. The availability of human CFs is limited hampering the field to move forward. To date, CFs can be generated from iPSCs, which could provide an unlimited source of human CFs13,14,15. However, the behaviour of iPSC-CFs in relation to mechanical stimulation had not been investigated yet.

In this study we demonstrated that iPSC-CFs are comparable to primary CFs with regard to the expression of key CF markers at gene and protein levels. Expression of the cardiac markers GATA4 and TCF21 indicate the cardiac lineage of the cells. Furthermore, expression of the mesenchymal markers VIM and PDGFRA as well as the ECM component COL1A1 and the collagen binding receptor DDR2 support their fibroblast phenotype. In addition, we showed that iPSC-CFs respond to pro-fibrotic and mechanical stimulation. TGF- induces CFs transdifferentiation into myofibroblasts and promotes ECM remodelling. Mechanical stimulation in the form of cyclic stretch at physiological levels reduces collagen expression in iPSC-CFs. Interestingly, cyclic stretch also protects against TGF- stimulation, preventing the cells from transdifferentiating into myofibroblasts.

One can only use iPSC-derived cells when they accurately represent their primary counterparts. Key characteristics of CFs are a defined mRNA profile, responsiveness to pro-fibrotic cytokines, interaction with the ECM and mechanical sensitivity. iPSC-CFs generated using the protocol developed by Zhang et al. showed a comparable RNA sequencing profile in iPSC-CFs and primary CFs13. Using our iPSCs lines, following the same protocol we generated iPSC-CFs with an mRNA profile comparable to primary CFs. Furthermore, at a functional level we demonstrated that iPSC-CFs interact with their environment in a similar way as primary CFs, and respond to pro-fibrotic stimulation. These results indicate that iPSC-CFs possess several key characteristics of primary CFs and may be suitable to investigate the behaviour of CFs and develop disease models of cardiac fibrosis.

In order to investigate the behaviour of CFs in their native environment, we next investigated the behaviour of iPSC-CFs under physiologically relevant conditions. In an effort to mimic the dynamic environment of the continuously beating heart, we investigated the effects of cyclic mechanical stretch on iPSC-CFs. The importance of mechanical stimulation has been acknowledged, but the effects of mechanical stimulation on CFs remain controversial in in vitro studies23. On one hand, it has been reported that cyclic stretch may induce transdifferentiation of CFs into myofibroblasts. On the other hand, it has been shown that cyclic stretch may have a protective effect instead. One of the main factors influencing this controversy is the usage of cell sources from different species.

As primary human CFs are limited in availability, iPSC-CFs could provide a representative and stable source of cells to move forward. In order to study how iPSC-CFs and primary CFs behave in a mechanically dynamic environment similar to the heart, cells were exposed to 10% cyclic stretch at 1Hz for 72h19. With this approach, we demonstrated that: Cyclic stretch alone inhibits expression of collagen 1 but does not affect iPSC-CFs transdifferentiation or expression of matrix remodelling genes. In addition, cyclic stretch is protective against TGF- mediated myofibroblast transdifferentiation in iPSC-CFs, resulting in normalised expression of collagen 1, -SMA and matrix remodelling genes such as TIMP1 and MMP1.

The cause of the aforementioned controversy in literature regarding either the pro-fibrotic or anti-fibrotic response of CFs to mechanical stimulation is hard to pin-point; experimental conditions vary widely between studies, such as cell origin, the duration of the experiment, the surface coating and the presence of serum. A common trend in all those studies is that there may be a time-dependent response of stretch. It was shown in primary mouse CFs that the response starts with an initial increase in phosphorylation of AKT, a downstream kinase involved in the transduction of mechanical stimuli24,25. At the gene level, it was shown in primary rat CFs that there is an initial increase in fibrotic markers (i.e. ACTA2, TGFB1, CTGF) after 4 h followed by a reduced increase after 24h26. Roche et al. observed a similar effect in primary rat CFs with an apparent reduced increase of COL1A1 gene expression after 48h compared to 24h27. 72h of cyclic stretch was instead shown to inhibit TGF- induced fibroblast activation in primary human CFs16,18. Furthermore, it has been demonstrated that 96h of cyclic stretch can promote or inhibit the response of primary mouse CFs to a broad spectrum of biochemical stimuli, including TGF-, angiotensin II, interleukin-1 and others17. Overall, it appears that longer stimulation results in a gradual decrease of an initial pro-fibrotic response with eventually cells balancing the fibrotic response to the mechanically active environment in order to reach homeostasis. We may hypothesize that the duration of this response curve is dependent on different factors, including the origin and age of the cells, their culture conditions (surface coating, substrate stiffness, or medium supplementation with serum) and the presence of other cell types23. A clear association between mechanosensing and a response of CFs is apparent, but there is a need for a reproducible cell type to better understand this phenomenon.

TGF- signalling is one of the main pathways involved in the activation of CFs and development of cardiac fibrosis28. Exposure of iPSC-CFs to TGF- promotes the expression of fibrotic and myofibroblast markers, such as -SMA. When stretched however, this effect is diminished. How mechanical changes communicate with the TGF- pathway is not well understood. On one hand, mechanical strain has been shown in tissue to release active TGF- from the ECM, which would promote fibroblast activation29. On the other hand, in this in vitro study mechanical strain appears to inhibit fibroblast activation, indicating that there may be other mechanisms at play in this model. It is unknown whether this anti-fibrotic effect is directly caused by interplay between mechanosensitive complexes and the TGF- pathway. Mechanosensitive receptors such as integrins or mechanoresponsive factors such as YAP/TAZ may communicate with the TGF- pathway30,31. Alternatively, cyclic stretch may have an indirect effect, for example through internalization of extracellular receptors, altering the response to ligand stimulation. Regardless, the field of mechanotransduction in CFs remains requires further investigation.

While iPSCs have started a new era of research, the usage of these cells comes with limitations. iPSC-CFs showed many similarities with primary CFs, but the maturity of iPSC-derived cell lineages remains an important topic of contention. Although maturation is clearly defined for some cell types, such as cardiac myocytes, a clear definition lacks for CFs. The heterogeneity and plasticity of this cellular population under physiological conditions makes it difficult to set well defined standards of mature CFs32. iPSC-CFs present with various characteristics of primary cells, but they differ in several aspects as well. For example, Zhang et al. noted an increased proliferation capacity in iPSC-CFs and foetal CFs compared to adult CFs, indicating the iPSC-CFs may be more foetal-like13. This increased proliferation capacity and ability to stay in an inactivated state while in culture increases the applicability of the iPSC-CFs in research, as it has been demonstrated that CFs which have transdifferentiated into myofibroblast will have an altered response to mechanical stimulation33. In addition, little is known about the electrophysiological characteristics of iPSC-CFs and their interaction with other conducting cells such as cardiomyocytes34. Further electrophysiological characterisation should be performed to better understand the behaviour of these cell in the electrical circuit of the heart.

To conclude, in this study we demonstrated that iPSC-derived CFs show similar gene and protein expression as primary CFs. In addition, pro-fibrotic stimulation promoted transdifferentiation of iPSC-CFs into a myofibroblast phenotype. When stimulated with cyclic stretch, this transdifferentiation is inhibited. Together, the mechano- and TGF--responsive characteristics support the use of iPSC-CFs for physiological relevant disease modelling. Future studies could further dive into the mechanisms driving cardiac fibroblast behaviour and cardiac fibrosis.

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Cell culture

Eight human iPSC lines were employed in this study (Supplementary TableS1). The cells were cultured using Corning Matrigel hESC-Qualified Matrix (Corning, Cat. No. 354277) coated plates with the use of StemMACS iPS Brew XF Medium (Miltenyi Biotec, Cat. No. 130-104-368) or Essential 8 medium (ThermoFisher Scientific, Cat. No. A157001), in antibiotic-free conditions, and maintained at 37C, 5% CO2. iPSCs were passaged every 35 days using either Accutase or 0.5mM phosphate-buffered saline (PBS)/EDTA. Briefly, when passaging the cells with Accutase, cells were firstly washed with DMEM, 1ml of Accutase was added per 6-well and the cells were incubated at 37C for 34min, to ensure proper cell detachment. After the incubation an equal volume of DMEM was added to the well and the cells were collected and centrifuged at 1200rpm for 3min at 4C. For splitting with PBS/EDTA (ThermoFisher Scientific, Cat. No. 15575020), cells were briefly washed with DMEM, 1ml PBS/EDTA was added per 6-well and the cells were incubated until they started to roughly dissociate. The EDTA was aspirated and the cells or the cell pellet (when splitting using Accutase), were resuspended in fresh medium supplemented with 10M ROCK inhibitor, Y-27632, (Miltenyi Biotec, Cat. No. 130-106-538). The next day the medium was changed back to iPSC medium without ROCK inhibitor. All cell lines were thoroughly characterized for their pluripotency (Supplementary Fig.1A, B) and were tested frequently for mycoplasma contamination.

The generation of cortical progenitors and neurons was performed as described before [27, 28] with minor modifications. Briefly, iPSCs from five 6-wells were collected with Accutase and seeded onto an ES-Matrigel coated 12-well. When 100% confluency was reached, StemMACS iPS Brew XF Medium was replaced by neural induction medium (NIM; DMEM/F12 Glutamax, Neurobasal, 100 mM L-Glutamine, 0.5N-2, 0.5B-27+Vitamin A, 50M Non-Essential Amino Acids, 50M 2-mercaptoethanol, 2.5g/ml insulin, 1M dorsomorphine, 10M SB431542). The medium was changed every day until the appearance of a tightly packed neuroepithelial sheet (NES). NES was passaged with 0.5mM EDTA in a ratio of 1:2 or 1:3 to Corning Matrigel Growth Factor Reduced (GFR) Basement Membrane Matrix (GFR-Matrigel; Corning, Cat. No. 354230) coated plates. The next day, the medium was switched to neural maintenance medium (NMM; DMEM/F12 Glutamax, Neurobasal, 100mM L-Glutamine, 0.5N-2, 0.5B-27+Vitamin A, 50M Non-Essential Amino Acids, 50M 2-mercaptoethanol, 2.5g/ml insulin) and was changed every other day. Upon the appearance of rosettes, 20ng/ml FGF2 (Peprotech, Cat. No. 100-18C) were added to the medium for four days. On the fourth day of FGF2 treatment, the cells were split again with 0.5mM EDTA in a ratio of 1:2 to 1:3 onto GFR-Matrigel coated plates. The medium was switched back to NMM and the cortical progenitors were maintained for about 510 days until neurons accumulated outside of the rosettes. At this point, cells were passaged with Accutase, and 50,000 cells/cm were seeded on poly-L-ornithin/Laminin coated plates for further neuronal differentiation. Alternatively, 24million cells/ml were frozen with neural freezing medium. Neurons differentiated further with half medium changes every two to three days. Samples were harvested at day (d) 0, 7, 16, 27, 50, and 100.

For the DFMO treatment, adherent cell cultures were treated daily with 10M DFMO (difluoromethylornithine hydrochloride hydrate; Merck, Cat. No. D193) starting from the first day of differentiation until the collection of cellular pellet and supernatant for mass spectrometry analysis or fixation for subsequent immunocytochemistry (ICC).

Cells were fixed in 4% paraformaldehyde (PFA; Sigma, Cat. No. 158127-500G) in PBS solution for 20min at room temperature (RT). The non-specific binding was blocked with incubation with blocking buffer (3% bovine serum albumin (BSA), 0.2% Triton 100 in PBS) for 1h at RT. The primary antibody (Ab) was diluted in the blocking buffer in the recommended concentration and the Ab solution was applied overnight at 4C. The following primary Abs were used in the following concentrations: AFP 1:400 (Dako, Cat. No. A000829-2), GAD65/67 1:100 (Abcam, Cat. No. AB183999), GFAP 1:400 (Sigma, Cat. No. G3893-.2ML), Ki67-VioR667 1:200 (Miltenyi, Cat. No.130-120-422), MAP2 1:1,000 (SynapticSystems, Cat. No.188006), NEUN 1:500 (Sigma, Cat. No. ABN78), OCT3/4 1:200 (Szabo-Scandic, Cat. No. GTX101497-100), PAX6 1:500 (Invitrogen, Cat. No. 42-6600), S100b 1:750 (Abcam, Cat. No. ab52642), SMA 1:500 (Abcam, Cat. No. ab7817), SOX1 1:200 (R&D Systems, Cat. No. AF3369), SOX2 1:500 (R&D Systems, Cat. No. MAB2018), TAU 1:200 (Cell Signaling Technology, Cat. No. 4019), TUBB3 1:1,000 (BioLegend, Cat. No. 801202 and Abcam, Cat.No. ab52623), vGLUT 1:100 (SynapticSystems, Cat. No. 135311). The secondary Ab was diluted 1:500 in 1.5% BSA, 0,2% Triton 100 in PBS, and the solution was applied for 2h at RT. The secondary Abs used in this study were: donkey anti-rabbit Alexa FluorTM 488 (ThermoFisher Scientific, Cat. No. A-21206), donkey anti-rabbit Alexa FluorTM 546 (ThermoFisher Scientific, Cat. No. A-10040), donkey anti-mouse Alexa FluorTM 594 (ThermoFisher Scientific, Cat. No. A-21203), donkey anti-mouse Alexa FluorTM 647 (ThermoFisher Scientific, Cat. No. A-31571), donkey anti-goat Alexa FluorTM 594 (ThermoFisher Scientific, Cat. No. A-11058), goat anti-chicken Alexa FluorTM 594 (ThermoFisher Scientific, Cat. No. A32759). Finally, the nuclei were counterstained using 4,6-diamidino-2-phenylindole (DAPI; ThermoFisher Scientific, Cat. No. D21490) in PBS in 1:5000 dilution for 5min at RT. The coverslips were mounted using Aqua-Poly/Mount mounting medium (PolySciences, Cat. No. 18606-20).

Fluorescent pictures were acquired with the Zeiss Axio Observer Z1 inverted fluorescent microscope and the Leica DMi8 inverted microscope. The image acquisition was performed under the same exposure and laser intensity settings for each set of analyses. For each sample, ten random fields of view were acquired, with a minimum of 20 z-stacks collected per field to ensure proper signal coverage. Further image processing was carried out using the ImageJ software. For quantitative fluorescence intensity analysis, maximum intensity projection was applied and the mean fluorescence intensity values were calculated after background noise subtraction. These values were then normalized to the DAPI+ nuclear area to account for variations in cell density in the different fields of view.

Total RNA was extracted from cells using TRI Reagent (Merck, Cat. No. T9424), according to the manufacturers instructions. Genomic DNA was removed through treatment with DNase I (Sigma-Aldrich, Cat. No. AMPD1). Subsequently, 1g of purified RNA was reverse transcribed into cDNA using the RevertAid RT Reverse Transcription Kit (ThermoFisher Scientific, Cat. No. K1691), following the manufacturers guidelines. The expression levels of specific target genes at the mRNA level were quantified via reverse transcription quantitative PCR (RT-qPCR) using the 5 HOT FIREPol EvaGreen qPCR Mix Plus (no ROX) (Solis BioDyne, Cat. No. 08-25-00001-10). Samples were analyzed in technical triplicates to ensure data reliability. Non-template controls (NTCs) were included for each primer pair in every assay to monitor for reagent contamination and primer-dimer formation. To confirm the absence of genomic DNA contamination, random RNA samples were evaluated through gel electrophoresis. The RT-qPCR assays were conducted on the CFX Connect Real-Time PCR Detection System (Bio-Rad). Gene expression levels were normalized to the housekeeping gene ACTB. Relative expression changes were calculated employing the Ct method [29]. The list of the primers used for RT-qPCR assays is shown in Table1.

Total RNA was isolated from cells at six time points during the cortical differentiation and was prepared for paired-end mRNA sequencing. RNA extraction was performed using the TRI Reagent (Merck, Cat. No. T9424) according to the manufacturers guidelines. Genomic DNA digest was performed with the use of the TURBO DNA-free Kit (ThermoFisher Scientific, Cat. No. AM2238). For the library preparation, the Illumina TruSeq RNA Library Prep Kit v2 was used (Illumina, Cat. No. RS-122-2001, RS-122-2002). Quality, as well as concentration of RNA were assessed employing the Agilent RNA 6000 Pico kit (Agilent, cat. no. 5067-1513), Nanodrop, the NEBNext Library Quant Kit for Illumina (New England Biolabs, Cat. No. E7630S) and the Qubit RNA Integrity and Quality (IQ) Assay Kit (ThermoFisher Scientific, Cat. No. Q33222). All the kits were used according to the manufacturers guidelines. Paired-end sequencing was performed with the NextSeq 500/550 v2 Kit (150 cycles) (Illumina).

Low-quality ends and adapter sequences were trimmed using the wrapper Trim Galore!. Reads were mapped to the human reference genome (GRCh38) using the open-source software STAR [30]. The raw counts were generated with the Hypergeometric Optimization of Motif EnRichment (HOMER) suite [31]. All the subsequent analysis was performed using R [32]. Differential gene expression analysis was performed using the DESeq2 package [33]. Raw counts were normalized using the median of ratios (variance stabilization transformation; vst) [34]. Heatmaps were generated with the ClustVis [35] tool, using the z-score of the vst transcriptomic data for every gene. Gene ontology (GO) enrichment analysis was performed using the ShinyGO 0.76 online tool [36].

A likelihood ratio test (LRT) was used to identify the differentially expressed genes (DEGs) of SCZ and control (CTRL) across the multiple time points of neuronal differentiation [32]. The LRT compared the full model containing the covariates sex, batch, time point, and disease with a model reducing the covariates sex, batch, and time point. Statistical values were corrected for FDR using the Benjamini-Hochberg method.

Weighted Gene Correlation Network Analysis (WGCNA) allows the generation of modules that include genes that are co-expressed in the same manner. The vst counts were used to build a co-expression network using the WGCNA [37] package in R [32]. The data were corrected for sex and batch effects using the ComBat function that is implemented in the sva package [38]. The topological overlap measure was calculated using the adjacency matrix. The DynamicTree Cut algorithm, implemented in the WGCNA package, was used to identify the different modules. The gray module contains all the genes that were not assigned to any of the other modules. The module eigengene were calculated. Pearsons correlation was used to compare modules to each other and to the traits SCZ and the differentiation time points in the adjacency matrix. The top 25% of genes with the highest module membership (MM) were identified as hub genes.

Functional enrichment analysis was performed with an input gene ID list using the tool g:GOSt from the g:Profiler [39] R package. Statistical significance was computed and the g:SCS-threshold was corrected at p<0.05.

The cells were washed with 1ml sterile 1x PBS for 60s. After the wash, the cells were scraped using 1ml PBS and the suspension was collected and centrifuged at 4000rpm for 5min, at RT. The cell pellets were kept constantly on dry ice and stored at 80C until further processing. The cell supernatant was collected after a 24-h incubation, centrifuged at 4000rpm for 10min, immediately placed on dry ice and stored at 80C. Samples were analyzed using the biocrates MxP Quant 500 (biocrates life sciences AG, Cat. No. 21094.12). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to analyze small molecules, including analyte classes such as amino acids, biogenic amines, carboxylic acids, and amino acid-related molecules [40]. Lipid species were measured using flow injection analysis tandem mass spectrometry (FIAMS/MS). Small molecules were quantified with external 7-point calibrations and internal standards and lipids were quantified by internal standards [41]. The raw data were processed by applying a modified 80% rule to reduce the false positive measurements [42]. The actual missing values, i.e., the values over the level of detection (LOD) for one time point but not for another time point, were uniformly at random imputed with a non-zero value between LOD/2 and LOD. Missing values within one class(i.e., timepoints and metabolites) were imputed using the arithmetic mean of the class. Batch effects were corrected by centering the data within the groups(i.e., time points) and batches. The performance of the normalization was assessed by plotting the row standard deviations versus the row means and the principal component analysis (PCA). In addition, variancePartition analysis was performed to evaluate the contribution of each individual component of the study design (i.e., time point, batch, and condition), to the measured variation of each metabolite [43].

For metabolite extraction, cell pellets were resuspended in 500L ice-cold methanol. Metabolites from supernatants (50L) were extracted using 450L 8:1 methanol:water. Fully 13C, 15N labeled amino acid standard (Cambridge Isotope Laboratories, Cat. No. MSK-CAA-1) and 6D-gamma hydroxybutyrate (Sigma-Aldrich, Cat. No. 615587) were spiked into samples at the first step of the extraction. After simultaneous proteo-metabolome liquid-liquid extraction [44], protein content was determined from extracted cellular interphases using a Pierce Micro BCA Protein Assay Kit (Thermo Fisher Scientific, Cat. No. 23235). Dried metabolite samples from cell pellets were dissolved in 20L 0.1% formic acid (FA) or 50L 0.1% FA for the analysis from the supernatant samples. The sample (1L) was injected on an Atlantis Premier BEH C18 AX column (1.7m, 2.1150mm, Waters, 186009361) equilibrated at 40C using an Acquity Premier UPLC system (Waters). A gradient was run at a flowrate of 0.4mL/min with mobile phase A (0.1% FA in water) and mobile phase B (0.1% FA in acetonitrile) as follows: 1min at 1% B, to 40% B in 1min, 40% B to 99% B in 0.5min, hold at 99% B for 1.1min, 99% B to 1% B in 0.1min followed by 1.8min of re-equilibration at 1% B. GABA and Glutamate (Glu) were detected using a Xevo-TQ XS Mass spectrometer (Waters) equipped with an electrospray ionization source running in positive mode. The transitions 104>69 (endogenous GABA), 110>73 (labeled GABA), 148>102 (endogenous Glu) and 154>107 (labeled Glu) were used for quantification. The raw files were processed using MS Quan in waters connect (Waters, V1.7.0.7). The data was further analyzed in R and normalized to the protein content.

To analyze time-related cluster dynamics, the non-parametric clustering algorithm of Short Time-series Expression Miner (STEM) was used [45]. STEM is an online tool that assigns genes or metabolites to significant temporal expression profiles. The Maximum Number of Model Profiles and the Maximum Unit Change in Model Profiles between time points were set to 50 and 2, respectively. Data were normalized to d0. Integrated into the STEM tool is a GO enrichment analysis. All annotations (Biological Process (BP), Molecular Function (MF), and Cellular Component (CC)) were selected and applied. Statistical significance was computed and FDR-corrected at p<0.05.

The network establishment was based on the gene expression and metabolite level changes across the five successive time point comparisons, along the cortical differentiation. The connectivity information for the initial network was acquired from the publicly available recon3D stoichiometric model data set (available at https://www.vmh.life/#downloadview, retrieved in September 2020) [46]. Ultimately, 51 metabolites and 1135 genes were matched with their corresponding IDs.

Briefly, the construction of the network was performed based on the following steps. Initially, all the reactions associated with any of the target genes were extracted. The metabolites associated with these reactions were identified and the educt-product stoichiometry was applied for every metabolite involved in the network. Subsequently, the reaction data were filtered to extract and proceed only with the genes and metabolites measured in our dataset. The network was further enriched with protein-protein interaction information, derived using the signor database (available at https://signor.uniroma2.it/downloads.php, retrieved in September 2020) [47]. Finally, the network vertices were constructed after examining the unique metabolites and genes, existing in the edge dataset and were further enriched with vertex attributes, such as the vertex type (i.e., gene/metabolite). Log2 fold changes (log2FC) were converted to a color gradient scale, ranging from blue (indicating a downregulation compared to the previous time point) to red (indicating upregulation).

Extraction of subnetworks from the parental network, was based on assigning membership to the pathways, as defined by the KEGG pathway database, and selecting the subnetwork that included the highest number of differentially expressed genes and metabolites, with the closest degree distribution of the vertices. Pie charts with five equal fractions were used in order to visualize the fold changes occurring across a single metabolite or gene, corresponding to the transitions between two succeeding time points. Additionally, ellipses were used for visualizing the metabolites, while the genes were visualized with circles.

Metabolites that were needed as substantial interconnections between measured metabolites, but were not measured in our dataset, were visualized as small dots. The position for every node was provided as coordinates on a 2D plane. Network visualizations were performed using the R igraph package [48].

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Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia ... - Nature.com

Using stem cell-derived heart muscle cells to advance heart regenerative therapy – EurekAlert

image:

Study shows that cardiac spheroids, derived from human induced pluripotent stem cells, can be easily transported and injected into damaged areas of the heart to promote its regeneration and recovery of function.

Credit: Hideki Kobayashi from Shinshu University

Regenerative heart therapies involve transplanting cardiac muscle cells into damaged areas of the heart to recover lost function. However, the risk of arrhythmias following this procedure is reportedly high. In a recent study, researchers from Japan tested a novel approach that involves injecting cardiac spheroids, cultured from human stem cells, directly into damaged ventricles. The highly positive outcomes observed in primate models highlight the potential of this strategy.

Cardiovascular diseases are still among the top causes of death worldwide, and especially prevalent in developed countries. Myocardial infarctions, commonly known as heart attacks, are on the rise, resulting in a significant number of deaths each year.

Heart attacks typically kill millions of cardiac muscle cells, leaving the heart in a weakened state. Since mammals cannot regenerate cardiac muscle cells on their own, heart transplants are currently the only clinically viable option for patients suffering (or likely to suffer) heart failure. Given that full heart transplants are expensive and donors difficult to come by, it is no surprise that alternative therapies are highly sought after by the medical community.

One promising strategy that has been steadily gaining traction is using human induced pluripotent stem cells (HiPSCs) for regenerative heart therapy. Simply put, HiPSCs are cells derived from mature cells that can be effectively reprogrammed into a completely different cell type, such as cardiac muscle cells (cardiomyocytes). By transplanting or injecting cardiomyocytes derived from HiPSCs into damaged areas of the heart, it is possible to recover some lost functionality. Unfortunately, studies have reported that this approach can increase the risk of arrythmias, posing a major hurdle to clinical trials.

In a recent study, a Japanese research team from Shinshu University and Keio University School of Medicine, tested a new strategy for regenerative heart therapy that involves injecting cardiac spheroids derived from HiPSCs into monkeys with myocardial infarction. This study, published on April 26, 2024, in the journal Circulation, was led by Professor Yuji Shiba from the Department of Regenerative Science and Medicine, Shinshu University.

The team included Hideki Kobayashi, the first author, and Koichiro Kuwahara from the Department of Cardiovascular Medicine, Shinshu University School of Medicine, as well as Shugo Tohyama, and Keiichi Fukuda from the Department of Cardiology, Keio University School of Medicine, among others.

In their novel approach, the researchers cultivated HiPSCs in a medium that led to their differentiation into cardiomyocytes. After carefully extracting and purifying cardiac spheroids (three-dimensional clusters of cardiac cells) from the cultures, they injected approximately 6 107 cells into the damaged hearts of crab-eating macaques (Macaca fascicularis). They monitored the condition of the animals for twelve weeks, taking regular measurements of cardiac function. Following this, they analyzed the monkeys hearts at the tissue level to assess whether cardiac spheroids could regenerate the damaged heart muscles.

First, the team verified the correct reprogramming of HiPSCs into cardiomyocytes. They observed, via cellular-level electrical measurements, that the cultured cells exhibited potential patterns typical of ventricular cells. The cells also responded as expected to various known drugs. Most importantly, they found that the cells abundantly expressed adhesive proteins such as connexin 43 and N-cadherin, which would promote their vascular integration into an existing heart.

Afterwards, the cells were transported from the production facility at Keio University to Shinshu University, located 230 km away. The cardiac spheroids, which were preserved at 4 C in standard containers, withstood the four-hour journey without problem. This means that no extreme cryogenic measures would be needed when transporting the cells to clinics, which would make the proposed approach less expensive and easier to adopt.

Finally, the monkeys received injections of either cardiac spheroids or a placebo directly into the damaged heart ventricle. During the observation period, the researchers noted that arrythmias were very uncommon, with only two individuals experiencing transient tachycardia (fast pulse) in the first two weeks among the treatment group. Through echocardiography and computed tomography exams, the team confirmed that the hearts of monkeys that received treatment had better left ventricular ejection after four weeks compared to the control group, indicating a superior blood pumping capability.

Histological analysis ultimately revealed that the cardiac grafts were mature and properly connected to pre-existing existing tissue, cementing the results of previous observations. HiPSC-derived cardiac spheroids could potentially serve as an optimal form of cardiomyocyte products for heart regeneration, given their straightforward generation process and effectiveness, remarks Assistant Professor Kobayashi. We believe that the results of this research will help solve the major issue of ventricular arrhythmia that occurs after cell transplantation and will greatly accelerate the realization of cardiac regenerative therapy, he further adds.

Although tested in monkeys, it is worth noting that the cardiac spheroid production protocol used in this study was designed for clinical application in humans. The favorable results obtained thus far are sufficient to provide a green light for our clinical trial, called the LAPiS trial. We are already employing the same cardiac spheroids on patients with ischemic cardiomyopathy, comments Asst. Prof. Kobayashi.

Let us all hope for a resounding success in the LAPiS trial, paving the way for expanded and effective treatment avenues for people suffering from heart problems.

###

About Shinshu University

Shinshu Universityis a national university founded in 1949 and located nestling under the Japanese Alps in Nagano known for its stunning natural landscapes. Our motto, "Powered by Nature - strengthening our network with society and applying nature to create innovative solutions for a better tomorrow" reflects the mission of fostering promising creative professionals and deepening the collaborative relationship with local communities, which leads to our contribution to regional development by innovation in various fields. Were working on providing solutions for building a sustainable society through interdisciplinary research fields: material science (carbon, fiber and composites), biomedical science (for intractable diseases and preventive medicine) and mountain science, and aiming to boost research and innovation capability through collaborative projects with distinguished researchers from the world. For more information visit https://www.shinshu-u.ac.jp/english/ or follow us on X (Twitter) @ShinshuUni for our latest news.

About Assistant Professor Hideki Kobayashi

Prof. Hideki Kobayashi became a faculty member at Shinshu University Graduate School of Medicine in 2017, focusing his expertise in cardiology and cardiac electrophysiology. With a prolific publication record, he has contributed to over 25 papers in these fields. His professional affiliations include membership in esteemed organizations such as the Japan Society of Internal Medicine, the Japan Circulation Society, the Japanese Heart Rhythm Society and the International Society of Cardiology Research.

About Professor Yuji Shiba

Prof. Yuji Shiba obtained MD and PhD degrees from Shinshu University in 1998 and 2007, respectively, and has remained closely affiliated with the institution throughout his career. Since 2017, he has been a full Professor at the Institute for Biomedical Sciences, Interdisciplinary Cluster for Cutting Edge Research at Shinshu University. His research endeavours primarily focus on cardiac regeneration using stem cells, an emerging biotechnological field. He has published over 45 papers on these topics, as well as over 10 books and book chapters. He is a member of the Japan Society of Internal Medicine and the Japan Circulation Society.

Experimental study

Animals

Regeneration of non-human primate hearts with human induced pluripotent stem cell-derived cardiac spheroids

26-Apr-2024

The authors have no competing interests to declare.

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Using stem cell-derived heart muscle cells to advance heart regenerative therapy - EurekAlert

Accelerating cardiac regenerative therapy with HiPSC spheroids – Drug Target Review

Injections of cardiac spheroids into primate ventricles improved left ventricular ejection after four weeks.

Researchers from Shinshu University and Keio University School of Medicine have tested a novel strategy for regenerative heart therapy. They transplanted cardiac spheroids derived from human induced pluripotent stem cells (HiPSCs) into damaged ventricles and observed very positive outcomes in primate models. These results could expand treatment options for people suffering from heart problems.

The prevalence of myocardial infarction is rising. These destroy millions of cardiac muscle cells, leaving the heart in a weakened state. Currently, as mammals cannot regenerate cardiac muscle cells on their own, heart transplants are the only clinically viable option for patients suffering heart failure. However, full heart transplants are expensive and donors are rare, so alternative therapies are highly sought after.

The team cultivated HiPSCs in a medium that led to their differentiation into cardiomyocytes. Following the extraction and purification of cardiac spheroids, they injected approximately 6 107cells into the damaged hearts of crab-eating macaques and monitored the condition of the animals for twelve weeks, taking regular measurements of cardiac function.

Analysis of the monkeys hearts at the tissue level was then conducted to assess whether cardiac spheroids could regenerate the damaged heart muscles. The researchers verified the correct reprogramming of HiPSCs into cardiomyocytes first, observing at cellular-level electrical measurements that the cultured cells showed patterns typical of ventricular cells. Also, the cells responded as expected to numerous known drugs. Significantly, they discovered that the cells abundantly expressed adhesive proteins like connexin 43 and N-cadherin, which would promote their vascular integration into an existing heart.

Furthermore, this approach is less expensive and easier to adopt because the cells were transported from the production facility at Keio University to Shinshu University, located 230km away. The cardiac spheroids were preserved at 4C in standard containers and withstood the four-hour journey, meaning extreme cryogenic measures would not be required when transporting the cells to clinics.

The monkeys received injections of either cardiac spheroids or a placebo directly into the damaged heart ventricle. The team noted that arrhythmias were very uncommon, with only two individuals experiencing transient tachycardia in the first two weeks among the treatment group. Echocardiography and computed tomography exams confirmed that, compared to the control group, the hearts of monkeys that received treatment had better left ventricular ejection after four weeks, demonstrating a superior blood pumping capability.

Ultimately, it was revealed through the histological analysis that the cardiac grafts were mature and properly connected to pre-existing existing tissue, confirming the results of previous observations. HiPSC-derived cardiac spheroids could potentially serve as an optimal form of cardiomyocyte products for heart regeneration, given their straightforward generation process and effectiveness, explained first author Dr Hideki Kobayashi. We believe that the results of this research will help solve the major issue of ventricular arrhythmia that occurs after cell transplantation and will greatly accelerate the realisation of cardiac regenerative therapy.

Despite this cardiac spheroid production protocol being tested in monkeys, it was designed for clinical application in humans. The favourable results obtained thus far are sufficient to provide a green light for our clinical trial, called the LAPiS trial. We are already employing the same cardiac spheroids on patients with ischemic cardiomyopathy, concluded Dr Kobayashi.

This study was published in Circulation.

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Accelerating cardiac regenerative therapy with HiPSC spheroids - Drug Target Review

Investigating the promising future of organoids – Drug Target Review

In this podcast episode, titled Investigating the promising future of organoids, we will be discussing the ways in which organoids are being used to study diseases and improve drug development. We explore the specific preclinical models organoids are replacing, the current limitations of organoids and how to overcome these, as well as where the field is heading.

This conversation features Dr Radhika Menon, Senior Scientist of Neurobiology at Ncardia,Dr Etienne De Braekeleer, Senior Research Scientist at AstraZeneca, and Dr Paige Vinson, Director of High Throughput Screening at Southern Research.

This podcast is in association with Molecular Devices. With its innovative life science technology, Molecular Devices makes scientific breakthroughs possible for academic, pharmaceutical, government and biotech customers. Head to moleculardevices.comto find out more.

About the speakers

Dr Radhika Menon, Senior Scientist of Neurobiology at Ncardia

Radhika Menon, PhD is a Senior Scientist at Ncardia, Leiden. In her current position, she leads projects involving human induced pluripotent stem cells (iPSCs) and various iPSC-derived cell types. She started her scientific career as a Junior Researcher in India where she worked on human iPSCs and (embryonic stem cells) ESCs and a cellular model for Alzheimers Disease. She received her PhD in Translational Neuroscience from the Johannes Gutenberg University, Mainz, Germany, working under the supervision of Professor Marisa Karow and Professor Benedikt Berninger. Her PhD project involved the establishment and characterization of an iPSC-derived brain organoid model to study a neurodevelopmental disorder (Opitz Syndrome). Her motivation to do impactful work in the fields of disease modelling, drug development and patient care guided her move to industry to pursue translational research. She moved to the Netherlands to join Mimetas, an organ-on-a-chip company, where she worked with human neuronal, cancer and intestinal biology systems. Dr Menons expertise in cellular differentiation (2D & 3D) and disease modelling in various therapeutic areas is leveraged at Ncardia for cell manufacture and model development services.

Dr Paige Vinson, Director of High Throughput Screening at Southern Research

Paige Vinson, PhD leads a team of scientists in the Southern Research High-Throughput Screening Center in Birmingham, Alabama, where she serves as Director. She earned her PhD in Analytical Chemistry with a focus in Neuroscience from Emory University in Atlanta, Georgia followed by postdoctoral training in Biochemistry at Emory.

Early in her professional career, she gained experience in providing high-throughput drug discovery solutions to researchers in both academia and industry as part of the laboratory automation business unit at Thermo Fisher Scientific. Following this role, Vinson held a research faculty position at Vanderbilt University where she spent twelve years participating in team science, including drug discovery efforts, both as director of HTS and in the molecular pharmacology group of the Warren Center for Neuroscience Drug Discovery.

An ongoing theme in Vinsons career is the bridging of basic research into a drug discovery space through novel approaches in assay development, implementation, and automation including more challenging translational in vitro models. In her current role at Southern Research, Vinson enjoys combining her passions for data-driven approaches and team science to advance projects toward the clinic.

Dr Etienne De Braekeleer, Senior Research Scientist at AstraZeneca

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Investigating the promising future of organoids - Drug Target Review