Stages Of Cell Cycle Research Articles

Differentiation signals induce APOBEC3A expression via GRHL3 in squamous epithelia and squamous cell carcinoma.

Two APOBEC DNA cytosine deaminase enzymes, APOBEC3A and APOBEC3B, generate somatic mutations in cancer, thereby driving tumour development and drug resistance. Here, we used single-cell RNA sequencing to study APOBEC3A and APOBEC3B expression in healthy and malignant mucosal epithelia, validating key observations with immunohistochemistry, spatial transcriptomics and functional experiments. Whereas APOBEC3B is expressed in keratinocytes entering mitosis, we show that APOBEC3A expression is confined largely to terminally differentiating cells and requires grainyhead-like transcription factor 3 (GRHL3). Thus, in normal tissue, neither deaminase appears to be expressed at high levels during DNA replication, the cell-cycle stage associated with APOBEC-mediated mutagenesis. In contrast, in squamous cell carcinoma we find that, there is expansion of GRHL3expression and activity to a subset of cells undergoing DNA replication and concomitant extension of APOBEC3A expression to proliferating cells. These findings suggest that APOBEC3A may play a functional role during keratinocyte differentiation, and offer a mechanism for acquisition of APOBEC3A mutagenic activity in tumours.

CCRG-03. DETECTION OF HETEROGENEOUS CELL CYCLE ALTERATIONS UPON TMZ CHEMOTHERAPY TREATMENT THROUGH ADVANCED MACHINE LEARNING

Abstract Glioblastoma (GB), the most aggressive central nervous system tumor, is hallmarked by its frequent relapse under alkylating chemotherapy. GB cells frequently exhibit changes in cell cycle phases during TMZ treatment, with a reduction in the G0-G1 phase and an increase in the S and G2 phases. This indicate both tumor cell re-entry into the cell cycle and a TMZ-induced arrest, contributing to resistance and progression. In this study, we leverage dynamic protein abundance of Ki-67, a proliferation marker peaking during S, G2, and M phases, to analyse cellular responses to TMZ in various cell lines and tissue samples. We designed an image-based machine learning approach for pattern recognition to reconstruct and analyse the cell cycle at the single-cell level. Six primary cell lines were characterized through whole-genome DNA, methylation and RNA sequencing. Functional read-outs were performed with large-scale, time- and concentration-dependent TMZ treatments in cell culture and GB-tissue slice models. Our model successfully reconstructed detailed cell cycle stages, showing that untreated cells were predominantly in the G0-G1 phase. TMZ treatment significantly shifted cells toward the S/G2 phase (p < 0.02) in 3 of 6 cell lines and the pseudo-time reconstruction highlighted dose-dependent cell cycle changes. Cell lines with enhanced stem-like features, defined based on epigenetic and transcriptional data signature, showed no cell cycle changes at high TMZ doses (>150µM), regardless the MGMT promoter methylation status. This heterogeneity in cell cycle response emphasizes the complexity of GB and the need for personalized treatments. Our study provides insights into GB MGMT cell cycle alterations and resistance mechanisms that are independent of MGMT methylation status, a known TMZ response biomarker. Therefore, the observed TMZ-induced cell cycle changes may serve as novel biomarkers for assessing treatment response, paving the way for personalized therapeutic approaches.

GLO1 regulates hepatocellular carcinoma proliferation and migration through the cell cycle pathway

BackgroundHepatocellular carcinoma (HCC) is a malignant tumor characterized by a high mortality rate. The occurrence and progression of HCC are linked to oxidative stress. Glyoxalase-1 (GLO1) plays an important role in regulating oxidative stress, yet the underlying mechanism remains unclear. GLO1 may serve as a prognostic biomarker and therapeutic target for HCC.MethodsBased on TCGA database hepatocellular carcinoma samples, we conducted a bioinformatics analysis to explore the correlation between GLO1 expression and HCC cell proliferation and viability. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that differentially expressed genes (DEGs) were mainly enriched in the cell cycle pathway. We analyzed the relationships between GLO1 and 24 genes enriched in the cell cycle pathway using a protein-protein interaction (PPI) network. Finally, experimental validation was performed to assess GLO1’s impact on the distribution of cells at different cell cycle stages and on the proliferation and migration of HCC cells.ResultsOur study demonstrated that GLO1 was overexpressed in HCC tissues and was associated with a poor prognosis. Data analysis indicated that overexpression of GLO1 activated the cell cycle pathway and positively correlated with expression of the majority of key cell cycle genes. Experimental validation showed that GLO1 expression affects the number of HCC cells in G2 and S phases and regulates HCC cell proliferation and migration.ConclusionsGLO1 represents a promising therapeutic target for HCC, providing valuable insights into its role in the viability and proliferation of HCC cells.

Heterogeneity in oligodendrocyte precursor cell proliferation is dynamic and driven by passive bioelectrical properties

Oligodendrocyte precursor cells (OPCs) generate myelinating oligodendrocytes and are the main proliferative cells in the adult central nervous system. OPCs are a heterogeneous population, with proliferation and differentiation capacity varying with brain region and age. We demonstrate that during early postnatal maturation, cortical, but not callosal, OPCs begin to show altered passive bioelectrical properties, particularly increased inward potassium (K+) conductance, which correlates with G1 cell cycle stage and affects their proliferation potential. Neuronal activity-evoked transient K+ currents in OPCs with high inward K+ conductance potentially release OPCs from cell cycle arrest. Eventually, OPCs in all regions acquire high inward K+ conductance, the magnitude of which may underlie differences in OPC proliferation between regions, with cells being pushed into a dormant state as they acquire high inward K+ conductance and released from dormancy by synchronous neuronal activity. Age-related accumulation of OPCs with high inward K+ conductance might contribute to differentiation failure.

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction.

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1 , which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

8672 Disrupted Glucocorticoid Receptor Mediated Signalling Causes a Primary Cilia Defect in the Fetal Mouse Renal Tubule

Abstract Disclosure: J. Lao: None. K.L. Short: None. J. Ng: None. D.L. Cottle: None. T.J. Cole: None. Primary cilia are microtubule-based organelles that protrude from cell membranes to mediate diverse developmental signalling pathways and senses extracellular stimuli to maintain tissue homeostasis. We show that glucocorticoid (GC) signalling via the glucocorticoid receptor (GR) is a regulator of normal primary cilia formation in kidney renal tubules. RNA sequencing of whole E18.5 fetal kidney from mice with global deletion of the GR (GR-null) compared to littermate wild-type controls identified significantly reduced mRNA levels of key ciliogenesis-related genes. Further analysis of whole fetal kidney RNA by real-time-qPCR confirmed reduced mRNA levels for the cilia-associated proteins Ccp110 (fold -2.18), Cep97 (fold -1.78), Cep290 (fold -2.91), Kif3a (fold -1.82) and Rpgr (fold -1.90). Confocal microscopy revealed abnormal, stunted primary cilia in renal proximal tubules, collecting ducts and podocytes in GR-null or in renal tubule conditional GR-deleted mice, created using the HoxB7 Cre-driver allele. Primary cilia length was significantly decreased in kidney proximal tubule cells in GR-null mice (5.01 ± 0.11μm) compared with wildtype controls (6.20 ± 0.15μm). Furthermore, scanning electron microscopy of E18.5 GR-null kidney further confirmed aberrant primary cilia morphology in the proximal renal tubules and the absence of an apical brush border. Activation of GR signalling with the synthetic GC dexamethasone in cultured mouse IMCD3 kidney tubule cells significantly increased primary cilia length (2.89 ± 0.04μm) compared to vehicle controls (2.46 ± 0.28μm), an effect blocked by the GR antagonist RU486 (vehicle + RU486: 2.06 ± 0.02μm, dexamethasone + RU486: 2.00 ± 0.02μm). Aurora kinase A (AURKA) is a known regulator of primary cilia formation via the AKT cell signalling pathway and distinct proteins at different stages of the mitotic cell cycle. AURKA protein levels were downregulated in GR-null kidney and in IMCD3 cells which suggest GR regulates AURKA to control the assembly and disassembly of primary cilia. Together, these results demonstrate that GC signalling via the GR is required for normal primary ciliogenesis in the developing renal tubule and suggests that synthetic GR agonists may provide a novel therapeutic option for human ciliopathies such as those observed in forms of polycystic kidney disease. Presentation: 6/2/2024

Coupling of cell growth modulation to asymmetric division and cell cycle regulation in Caulobacter crescentus

In proliferating bacteria, growth rate is often assumed to be similar between daughter cells. However, most of our knowledge of cell growth derives from studies on symmetrically dividing bacteria. In many α-proteobacteria, asymmetric division is a normal part of the life cycle, with each division producing daughter cells with different sizes and fates. Here, we demonstrate that the functionally distinct swarmer and stalked daughter cells produced by the model α-proteobacterium Caulobacter crescentus can have different average growth rates under nutrient-replete conditions despite sharing an identical genome and environment. The discrepancy in growth rate is due to a growth slowdown associated with the cell cycle stage preceding DNA replication (the G1 phase), which initiates in the late predivisional mother cell before daughter cell separation. Both progenies experience a G1-associated growth slowdown, but the effect is more severe in swarmer cells because they have a longer G1 phase. Activity of SpoT, which produces the (p)ppGpp alarmone and extends the G1 phase, accentuates the cell cycle-dependent growth slowdown. Collectively, our data identify a coupling between cell growth, the G1 phase, and asymmetric division that C. crescentus may exploit for environmental adaptation through SpoT activity. This coupling differentially modulates the growth rate of functionally distinct daughter cells, thereby altering the relative abundance of ecologically important G1-specific traits within the population.

Aurora A Kinase Begins to Localize to the Centrosome in the S-phase of the Cell Cycle in the XL2 Cell Line

Background: The centrosome is one of the principal cell hubs, where numerous proteins important for intracellular regulatory processes are concentrated. One of them, serine-threonine kinase 6, alias Aurora A, is involved in centrosome duplication and mitotic spindle formation and maintenance. Methods: Long-term vital observations of cells, immunofluorescence analysis of protein localization, synchronization of cells at different phases of the cell cycle, Western blot analysis of protein content were used in the work. Results: In this study, we investigated the dynamics of Aurora A protein accumulation and degradation in the XL2 Xenopus cell line during its 28-hour cell cycle. Using Western blot and immunofluorescence analyses, we demonstrated that Aurora A disappeared from the centrosome within one hour following mitosis and was not redistributed to other cell compartments. Using double Aurora A/Bromodeoxyuridine immunofluorescence labeling of the cells with precisely determined cell cycle stages, we observed that Aurora A reappeared in the centrosome during the S-phase, which was earlier than reported for all other known proteins with mitosis-specific centrosomal localization. Moreover, Aurora A accumulation in the centrosomal region and centrosome separation were asynchronous in the sister cells. Conclusions: The reported data allowed us to hypothesize that Aurora A is one of the primary links in coordinating centrosome separation and constructing the mitotic spindle.

Reversible and effective cell cycle synchronization method for studying stage-specific investigations.

The cell cycle is a crucial process for cell proliferation, differentiation, and development. Numerous genes and proteins play pivotal roles at specific cell cycle stages to regulate these events precisely. Studying the stage-specific functions of the cell cycle requires accumulating cell populations at the desired cell cycle stage. Cell synchronization, achieved through the use of cell cycle kinase and protein inhibitors, is often employed for this purpose. However, suboptimal concentrations of these inhibitors can result in reduced efficiency, irreversibility, and undesirable cell cycle defects. In this study, we have optimized effective and reversible techniques to synchronize the cell cycle at each stage in human RPE1 cells, utilizing both fixed high-precision cell cycle identification methods and high-temporal live-cell imaging. These reproducible synchronization methods are invaluable for investigating the regulatory mechanisms specific to each cell cycle stage.

Analysis of cell cycle stage, replicated DNA, and chromatin-associated proteins using high-throughput flow cytometry

Abstract Flow cytometry is a versatile tool used for cell sorting, DNA content imaging, and determining various cellular characteristics. With the possibility of high-throughput analyses, it combines convenient labelling techniques to serve rapid, quantitative, and qualitative workflows. The ease of sample preparation and the broad range of applications render flow cytometry a preferred approach for many scientific questions. Yet, we lack practical adaptations to fully harness the quantitative and high-throughput capabilities of most cytometers for many organisms. Here, we present simple and advanced protocols for the analysis of total DNA content, de novo DNA synthesis, and protein association to chromatin in budding yeast and human cells. Upon optimization of experimental conditions and choice of fluorescent dyes, up to four parameters can be measured simultaneously and quantitatively for each cell of a population in a multi-well plate format. Reducing sample numbers, plastic waste, costs per well, and hands-on time without compromising signal quality or single-cell accuracy are the main advantages of the presented protocols. In proof-of-principle experiments, we show that DNA content increase in S-phase correlates with de novo DNA synthesis and can be predicted by the presence of the replicative helicase MCM2-7 on genomic DNA.

Predicting cell cycle stage from 3D single-cell nuclear-stained images.

The cell cycle governs the proliferation, differentiation, and regeneration of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research spanning development, health, aging, and disease. However, current approaches to cell cycle profiling involve complex interventions that may confound experimental interpretation. To facilitate more efficient cell cycle annotation of microscopy data, we developed CellCycleNet, a machine learning (ML) workflow designed to simplify cell cycle staging with minimal experimenter intervention and cost. CellCycleNet accurately predicts cell cycle phase using only a fluorescent nuclear stain (DAPI) in fixed interphase cells. Using the Fucci2a cell cycle reporter system as ground truth, we collected two benchmarking image datasets and trained two ML models-a support vector machine (SVM) and a deep neural network-to classify nuclei as being in either the G1 or S/G2 phases of the cell cycle. Our results suggest that CellCycleNet outperforms state-of-the-art SVM models on each dataset individually. When trained on two image datasets simultaneously, CellCycleNet achieves the highest classification accuracy, with an improvement in AUROC of 0.08-0.09. The model also demonstrates excellent generalization across different microscopes, achieving an AUROC of 0.95. Overall, using features derived from 3D images, rather than 2D projections of those same images, significantly improves classification performance. We have released our image data, trained models, and software as a community resource.

Cell sorting based on pulse shapes from angle resolved detection of scattered light

Flow cytometry is a key technology for the analysis and sorting of cells or particles at high throughput. Conventional and current flow cytometry is primarily based on fluorescent stains to detect the cells of interest. However, such stains also have disadvantages, as their effect on cells must be carefully tested to avoid effects on the results of the experiments. Alternative approaches using imaging or other label-free techniques often require highly sophisticated setups, are commonly limited in resolution, and produce challenging amounts of data. Our technology exploits scattered light instead. The custom-built flow cytometry setup comprises a fiber array in forward scatter detection for angular resolution and captures the whole pulse shape with advanced signal processing. Thereby this setup enables cell analysis and sorting purely based on scattered light signals without the need for fluorescent labels. We demonstrate the feasibility of this cell sorting technology by sorting cell lines for their cell cycle stages based on scattered light. Furthermore, we demonstrate the ability to classify human peripheral blood T- and B-cell subsets.

YY1-controlled regulatory connectivity and transcription are influenced by the cell cycle.

Few transcription factors have been examined for their direct roles in physically connecting enhancers and promoters. Here acute degradation of Yin Yang 1 (YY1) in erythroid cells revealed its requirement for the maintenance of numerous enhancer-promoter loops, but not compartments or domains. Despite its reported ability to interact with cohesin, the formation of YY1-dependent enhancer-promoter loops does not involve stalling of cohesin-mediated loop extrusion. Integrating mitosis-to-G1-phase dynamics, we observed partial retention of YY1 on mitotic chromatin, predominantly at gene promoters, followed by rapid rebinding during mitotic exit, coinciding with enhancer-promoter loop establishment. YY1 degradation during the mitosis-to-G1-phase interval revealed a set of enhancer-promoter loops that require YY1 for establishment during G1-phase entry but not for maintenance in interphase, suggesting that cell cycle stage influences YY1's architectural function. Thus, as revealed here for YY1, chromatin architectural functions of transcription factors can vary in their interplay with CTCF and cohesin as well as by cell cycle stage.

Single cell expression and chromatin accessibility of the Toxoplasma gondii lytic cycle identifies AP2XII-8 as an essential ribosome regulon driver

Sequential lytic cycles driven by cascading transcriptional waves underlie pathogenesis in the apicomplexan parasite Toxoplasma gondii. This parasite’s unique division by internal budding, short cell cycle, and jumbled up classically defined cell cycle stages have restrained in-depth transcriptional program analysis. Here, unbiased transcriptome and chromatin accessibility maps throughout the lytic cell cycle are established at the single-cell level. Correlated pseudo-timeline assemblies of expression and chromatin profiles maps transcriptional versus chromatin level transition points promoting the cell division cycle. Sequential clustering analysis identifies functionally related gene groups promoting cell cycle progression. Promoter DNA motif mapping reveals patterns of combinatorial regulation. Pseudo-time trajectory analysis reveals transcriptional bursts at different cell cycle points. The dominant burst in G1 is driven largely by transcription factor AP2XII-8, which engages a conserved DNA motif, and promotes the expression of 44 ribosomal proteins encoding regulon. Overall, the study provides integrated, multi-level insights into apicomplexan transcriptional regulation.

Cell Proliferation and Cytotoxicity Assays, The Fundamentals for Drug Discovery

Review Cell Proliferation and Cytotoxicity Assays, The Fundamentals for Drug Discovery Jingyi Niu†, Minai Li† and Ying Wang* State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, Macao 999078, China * Correspondence: emilyywang@um.edu.mo † These authors contributed equally to this work Received: 6 May 2024; Revised: 19 June 2024; Accepted: 21 June 2024; Published: 20 August 2024 Abstract: Cell proliferation and cytotoxicity assays are fundamental to drug discovery. This review summarizes prevalent methodologies for assessing cell proliferation and cytotoxicity, including direct cell count, metabolic activity, luminescent labeling, and tri-color viability imaging. The critical determinants that can significantly impact these assay outcomes, such as cellular doubling time, transitional states like quiescence and autophagy, cell cycle stages, metabolic enzyme functions, and genetic variability, are also explored. It is necessary to integrate the commonly used assays with additional analytical techniques to achieve precision in drug discovery. A multi-tiered approach that combines cellular assays with molecular analyses can improve screening processes, reduce false negatives, and increase confidence in the therapeutic potential of lead compounds.

ImmunoCellCycle-ID: A high-precision immunofluorescence-based method for cell cycle identification.

The cell cycle is a fundamental process essential for cell proliferation, differentiation, and development. It consists of four major phases: G1, S, G2, and M. These phases collectively drive the reproductive cycle and are meticulously regulated by various proteins that play critical roles in both the prevention and progression of cancer. Traditional methods for studying these functions, such as flow cytometry, require a substantial number of cells to ensure accuracy. In this study, we have developed a user-friendly, immunofluorescence-based method for identifying cell cycle stages, providing single-cell resolution and precise identification of G1, early S, late S, early G2, late G2, and each sub-stage of the M phase using fluorescence microscopy. This method provides high-precision cell cycle identification and can serve as an alternative to, or in combination with, traditional flow cytometry to dissect detailed substages of the cell cycle in a variety of cell lines.

COMSE: analysis of single-cell RNA-seq data using community detection-based feature selection

BackgroundSingle-cell RNA sequencing enables studying cells individually, yet high gene dimensions and low cell numbers challenge analysis. And only a subset of the genes detected are involved in the biological processes underlying cell-type specific functions.ResultIn this study, we present COMSE, an unsupervised feature selection framework using community detection to capture informative genes from scRNA-seq data. COMSE identified homogenous cell substates with high resolution, as demonstrated by distinguishing different cell cycle stages. Evaluations based on real and simulated scRNA-seq datasets showed COMSE outperformed methods even with high dropout rates in cell clustering assignment. We also demonstrate that by identifying communities of genes associated with batch effects, COMSE parses signals reflecting biological difference from noise arising due to differences in sequencing protocols, thereby enabling integrated analysis of scRNA-seq datasets of different sources.ConclusionsCOMSE provides an efficient unsupervised framework that selects highly informative genes in scRNA-seq data improving cell sub-states identification and cell clustering. It identifies gene subsets that reveal biological and technical heterogeneity, supporting applications like batch effect correction and pathway analysis. It also provides robust results for bulk RNA-seq data analysis.

Methods of karyoplast cell cycle synchronization for increasing the efficiency of somatic cloning of farm animals

This article is aimed to the analysis of methods for synchronizing the cell cycle of the somatic cells (karyoplasts) upon somatic cloning of farm animals. To obtain cloned animals, the oocytes at the metaphase of the second meiotic division without prior activation are applied as recipient cells in most experiments. In most experiments to obtain cloned offspring, oocytes are used as recipient cells at metaphase of the second meiotic division without prior activation, which determines the choice of somatic cells as karyoplasts at the G0/G1 stage, the most optimal for subsequent nuclear reprogramming by oocyte cytoplasmic factors. The most commonly used methods for arresting cells in this phase are serum starvation and/or contact inhibition, which allows up to 90% of cells to be stopped at the G0/G1 stage. However, despite the effectiveness of these methods, they have a number of significant limitations, and therefore the addition of components to the culture medium of somatic cells that prevent the progression of cells through the cell cycle stages is becoming widespread. The advantage of using chemical inhibitors is the ability of a number of them to have a protective effect on somatic cells, preventing the induction of apoptotic changes. The efficacy of butyrolactone-I, mimosine and aphidicolin application is controversial but a number of studies attests the possible using of these drugs to synchronize the karyoplasts. Thus, there is a wide range of methods for effective synchronization of the cell cycle of karyoplasts, and when choosing the optimal method, one should pay attention to the type of cells, the species of animals from which they were obtained, the permissible duration of cultivation under given conditions in order to minimize the negative impact of conditions on karyoplast viability.

Mesangial cell-derived CircRNAs in chronic glomerulonephritis: RNA sequencing and bioinformatics analysis

Background Circular RNAs (circRNAs) have been shown to play critical roles in the initiation and progression of chronic glomerulonephritis (CGN), while their role from mesangial cells in contributing to the pathogenesis of CGN is rarely understood. Our study aims to explore the potential functions of mesangial cell-derived circRNAs using RNA sequencing (RNA-seq) and bioinformatics analysis. Methods Mouse mesangial cells (MMCs) were stimulated by lipopolysaccharide (LPS) to establish an in vitro model of CGN. Pro-inflammatory cytokines and cell cycle stages were detected by Enzyme-linked immunosorbent assay (ELISA) and Flow Cytometry experiment, respectively. Subsequently, differentially expressed circRNAs (DE-circRNAs) were identified by RNA-seq. GEO microarrays were used to identify differentially expressed mRNAs (DE-mRNAs) between CGN and healthy populations. Weighted co-expression network analysis (WGCNA) was utilized to explore clinically significant modules of CGN. CircRNA-associated CeRNA networks were constructed by bioinformatics analysis. The hub mRNAs from CeRNA network were identified using LASSO algorithms. Furthermore, utilizing protein–protein interaction (PPI), gene ontology (GO), pathway enrichment (KEGG), and GSEA analyses to explore the potential biological function of target genes from CeRNA network. In addition, we investigated the relationships between immune cells and hub mRNAs from CeRNA network using CIBERSORT. Results The expression of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α was drastically increased in LPS-induced MMCs. The number of cells decreased significantly in the G1 phase but increased significantly in the S/G2 phase. A total of 6 DE-mRNAs were determined by RNA-seq, including 4 up-regulated circRNAs and 2 down-regulated circRNAs. WGCNA analysis identified 1747 DE-mRNAs of the turquoise module from CGN people in the GEO database. Then, the CeRNA networks, including 6 circRNAs, 38 miRNAs, and 80 mRNAs, were successfully constructed. The results of GO and KEGG analyses revealed that the target mRNAs were mainly enriched in immune, infection, and inflammation-related pathways. Furthermore, three hub mRNAs (BOC, MLST8, and HMGCS2) from the CeRNA network were screened using LASSO algorithms. GSEA analysis revealed that hub mRNAs were implicated in a great deal of immune system responses and inflammatory pathways, including IL-5 production, MAPK signaling pathway, and JAK-STAT signaling pathway. Moreover, according to an evaluation of immune infiltration, hub mRNAs have statistical correlations with neutrophils, plasma cells, monocytes, and follicular helper T cells. Conclusions Our findings provide fundamental and novel insights for further investigations into the role of mesangial cell-derived circRNAs in CGN pathogenesis.

The Low Tumorigenic Risk and Subtypes of Cardiomyocytes Derived from Human-induced Pluripotent Stem Cells

Background: Clinical application of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) is a promising approach for the treatment of heart diseases. However, the tumorigenicity of hiPSC-CMs remains a concern for their clinical applications and the composition of the hiPSC-CM subtypes need to be clearly identified. Methods: In the present study, hiPSC-CMs were induced from hiPSCs via modulation of Wnt signaling followed by glucose deprivation purification. The structure, function, subpopulation composition, and tumorigenic risk of hiPSC-CMs were evaluated by single-cell RNA sequencing (scRNAseq), whole exome sequencing (WES), and integrated molecular biology, cell biology, electrophysiology, and/or animal experiments. Results: The high purity of hiPSC-CMs, determined by flow cytometry analysis, was generated. ScRNAseq analysis of differentiation day (D) 25 hiPSC-CMs did not identify the transcripts representative of undifferentiated hiPSCs. WES analysis showed a few newly acquired confidently identified mutations and no mutations in tumor susceptibility genes. Further, no tumor formation was observed after transplanting hiPSC-CMs into NOD-SCID mice for 3 months. Moreover, D25 hiPSC-CMs were composed of subtypes of ventricular-like cells (23.19%) and atrial-like cells (66.45%) in different cell cycle stages or mature levels, based on the scRNAseq analysis. Furthermore, a subpopulation of more mature ventricular cells (3.21%) was identified, which displayed significantly up-regulated signaling pathways related to myocardial contraction and action potentials. Additionally, a subpopulation of cardiomyocytes in an early differentiation stage (3.44%) experiencing nutrient stress-induced injury and heading toward apoptosis was observed. Conclusions: This study confirmed the biological safety of hiPSC-CMs and described the composition and expression profile of cardiac subtypes in hiPSC-CMs which provide standards for quality control and theoretical supports for the translational applications of hiPSC-CMs.