Decoding molecular markers and transcriptional circuitry of naive and primed states of human pluripotency

Inference of Dynamic Growth Regulatory Network in Cancer Using High-Throughput Transcriptomic Data

Growth is regulated by gene expression variation at different developmental stages of biological processes such as cell differentiation, disease progression, or drug response. In cancer, a stage-specific regulatory model constructed to infer the dynamic expression changes in genes contributing to tissue growth or proliferation is referred as a dynamic growth regulatory network (dGRN). Over the past decade, gene expression data has been widely used for reconstructing dGRN by computing correlations between the differentially expressed genes (DEGs). A wide variety of pipelines are available to construct the GRNs using DEGs and the choice of a particular method or tool depends on the nature of the study. In this protocol, we have outlined a step-by-step guide for the analysis of DEGs using RNA-Seq data, beginning from data acquisition, pre-processing, mapping to reference genome, and construction of a correlation-based co-expression network to further downstream analysis. We have also outlined the steps for the inclusion of publicly available interaction/regulation information into the dGRN followed by relevant topological inferences. This tutorial has been designed in a way that early researchers can refer to for an easy and comprehensive glimpse of methodologies used in the inference of dGRN using transcriptomics data.

Network analysis of transcriptomic data uncovers molecular signatures and the interplay of mRNAs, lncRNAs, and miRNAs in human embryonic stem cells

Growing evidence has shown that besides the protein coding genes, the non-coding elements of the genome are indispensable for maintaining the property of self-renewal in human embryonic stem cells and in cell fate determination. However, the regulatory mechanisms and the landscape of interactions between the coding and non-coding elements is poorly understood. In this work, we used weighted gene co-expression network analysis (WGCNA) on transcriptomic data retrieved from RNA-seq and small RNA-seq experiments and reconstructed the core human pluripotency network (called PluriMLMiNet) consisting of 375 mRNA, 57 lncRNA and 207 miRNAs. Furthermore, we derived networks specific to the naïve and primed states of human pluripotency (called NaiveMLMiNet and PrimedMLMiNet respectively) that revealed a set of molecular markers (RPS6KA1, ZYG11A, ZNF695, ZNF273, and NLRP2 for naive state, and RAB34, TMEM178B, PTPRZ1, USP44, KIF1A and LRRN1 for primed state) which can be used to distinguish the pluripotent state from the non-pluripotent state and also to identify the intra-pluripotency states (i.e., naïve and primed state). The lncRNA DANT1 was found to be a crucial as it formed a bridge between the naive and primed state-specific networks. Analysis of the genes neighbouring DANT1 suggested its possible role as a competing endogenous RNA (ceRNA) for the induction and maintenance of human pluripotency. This was computationally validated by predicting the missing DANT1-miRNA interactions to complete the ceRNA circuit. Here we first report that DANT1 might harbour binding sites for miRNAs hsa-miR-30c-2-3p, hsa-miR-210-3p and hsa-let-7b-5p which may influence pluripotency.

The Role of ZNF275/AKT Pathway in Carcinogenesis and Cisplatin Chemosensitivity of Cervical Cancer Using Patient-Derived Xenograft Models

Zinc finger protein 275 (ZNF275) is a C2H2-type transcription factor that is localized on chromosome Xq28. Whether ZNF275 participates in modulating the biological behaviors of cervical cancer has not been determined to our knowledge. The present study employed CCK-8, BrdU, flow cytometry, and a transwell assay to investigate the cell viability, proliferation, apoptosis, migration, and invasion of cervical cancer cells. The application of Western blotting and immunohistochemistry (IHC) aims to assess ZNF275 protein expression and identify the signaling pathway relevant to ZNF275-mediated effects on cervical cancer. The therapeutic impact of the combined therapy of the AKT inhibitor triciribine and cisplatin was evaluated on cervical cancer patient-derived xenograft (PDX) models expressing high ZNF275. The current research illustrated that cervical cancer tissue exhibited a higher expression of ZNF275 in contrast to the surrounding normal cervical tissue. The downregulation of ZNF275 suppressed cell viability, migration, and invasion, and facilitated the apoptosis of SiHa and HeLa cells via weakening AKT/Bcl-2 signaling pathway. Moreover, triciribine synergized with cisplatin to reduce cell proliferation, migration, and invasion, and enhanced the apoptosis of SiHa cells expressing high ZNF275. In addition, the combination treatment of triciribine and cisplatin was more effective in inducing tumor regression than single agents in cervical cancer PDX models expressing high ZNF275. Collectively, the current findings demonstrated that ZNF275 serves as a sufficiently predictive indicator of the therapeutic effectiveness of the combined treatment of triciribine and cisplatin on cervical cancer. Combining triciribine with cisplatin greatly broadens the therapeutic options for cervical cancer expressing high ZNF275, but further research is needed to confirm these results.

Suspension culture improves iPSC expansion and pluripotency phenotype

BACKGROUND

Induced pluripotent stem cells (iPSCs) offer potential to revolutionize regenerative medicine as a renewable source for islets, dopaminergic neurons, retinal cells, and cardiomyocytes. However, translation of these regenerative cell therapies requires cost-efficient mass manufacturing of high-quality human iPSCs. This study presents an improved three-dimensional Vertical-Wheel® bioreactor (3D suspension) cell expansion protocol with comparison to a two-dimensional (2D planar) protocol.

METHODS

Sendai virus transfection of human peripheral blood mononuclear cells was used to establish mycoplasma and virus free iPSC lines without common genetic duplications or deletions. iPSCs were then expanded under 2D planar and 3D suspension culture conditions. We comparatively evaluated cell expansion capacity, genetic integrity, pluripotency phenotype, and in vitro and in vivo pluripotency potential of iPSCs.

RESULTS

Expansion of iPSCs using Vertical-Wheel® bioreactors achieved 93.8-fold (IQR 30.2) growth compared to 19.1 (IQR 4.0) in 2D (p < 0.0022), the largest expansion potential reported to date over 5 days. 0.5 L Vertical-Wheel® bioreactors achieved similar expansion and further reduced iPSC production cost. 3D suspension expanded cells had increased proliferation, measured as Ki67⁺ expression using flow cytometry (3D: 69.4% [IQR 5.5%] vs. 2D: 57.4% [IQR 10.9%], p = 0.0022), and had a higher frequency of pluripotency marker (Oct4⁺Nanog⁺Sox2⁺) expression (3D: 94.3 [IQR 1.4] vs. 2D: 52.5% [IQR 5.6], p = 0.0079). q-PCR genetic analysis demonstrated a lack of duplications or deletions at the 8 most commonly mutated regions within iPSC lines after long-term passaging (> 25). 2D-cultured cells displayed a primed pluripotency phenotype, which transitioned to naïve after 3D-culture. Both 2D and 3D cells were capable of trilineage differentiation and following teratoma, 2D-expanded cells generated predominantly solid teratomas, while 3D-expanded cells produced more mature and predominantly cystic teratomas with lower Ki67⁺ expression within teratomas (3D: 16.7% [IQR 3.2%] vs.. 2D: 45.3% [IQR 3.0%], p = 0.002) in keeping with a naïve phenotype.

CONCLUSION

This study demonstrates nearly 100-fold iPSC expansion over 5-days using our 3D suspension culture protocol in Vertical-Wheel® bioreactors, the largest cell growth reported to date. 3D expanded cells showed enhanced in vitro and in vivo pluripotency phenotype that may support more efficient scale-up strategies and safer clinical implementation.

Single-Cell and Spatial Transcriptomics Decodes Wharton's Jelly-Derived Mesenchymal Stem Cells Heterogeneity and a Subpopulation with Wound Repair Signatures

The highly heterogeneous characteristics of Wharton's jelly mesenchymal stem cells (WJ-MSCs) may be responsible for the poor clinical outcomes and poor reproducibility of treatments based on WJ-MSCs. Exploration of WJ-MSC heterogeneity with multimodal single-cell technologies will aid in establishing accurate MSC subtyping and developing screening protocols for dominant functional subpopulations. Here, the characteristics of WJ-MSCs are systematically analyzed by single cell and spatial transcriptome sequencing. Single-cell transcriptomics analysis identifies four WJ-MSC subpopulations, namely proliferative_MSCs, niche-supporting_MSCs, metabolism-related_MSCs and biofunctional-type_MSCs. Furthermore, the transcriptome, cellular heterogeneity, and cell-state trajectories of these subpopulations are characterized. Intriguingly, the biofunctional-type MSCs (marked by S100A9, CD29, and CD142) selected in this study exhibit promising wound repair properties in vitro and in vivo. Finally, by integrating omics data, it has been found that the S100A9⁺ CD29⁺ CD142⁺ subpopulation is more enriched in the fetal segment of the umbilical cord, suggesting that this subpopulation deriving from the fetal segment may have potential for developing into an ideal therapeutic agent for wound healing. Overall, the presented study comprehensively maps the heterogeneity of WJ-MSCs and provides an essential resource for future development of WJ-MSC-based drugs.

Nisin Mutant Prevention Concentration and the Role of Subinhibitory Concentrations on Resistance Development by Diabetic Foot Staphylococci

The most prevalent microorganism in diabetic foot infections (DFI) is Staphylococcus aureus, an important multidrug-resistant pathogen. The antimicrobial peptide nisin is a promising compound for DFI treatment, being effective against S. aureus. However, to avoid the selection of resistant mutants, correct drug therapeutic doses must be established, being also important to understand if nisin subinhibitory concentrations (subMIC) can potentiate resistant genes transfer between clinical isolates or mutations in genes associated with nisin resistance. The mutant selection window (MSW) of nisin was determined for 23 DFI S. aureus isolates; a protocol aiming to prompt vanA horizontal transfer between enterococci to clinical S. aureus was performed; and nisin subMIC effect on resistance evolution was assessed through whole-genome sequencing (WGS) applied to isolates subjected to a MEGA-plate assay. MSW ranged from 5–360 μg/mL for two isolates, from 5–540 μg/mL for three isolates, and from 5–720 μg/mL for one isolate. In the presence of nisin subMIC values, no transconjugants were obtained, indicating that nisin does not seem to promote vanA transfer. Finally, WGS analysis showed that incubation in the presence of nisin subMIC did not promote the occurrence of significant mutations in genes related to nisin resistance, supporting nisin application to DFI treatment.

Epigenetics as "conductor" in "orchestra" of pluripotent states

Pluripotent character is described as the potency of cells to differentiate into all three germ layers. The best example to reinstate the term lies in the context of embryonic stem cells (ESCs). Pluripotent ESC describes the in vitro status of those cells that originate during the complex process of embryogenesis. Pre-implantation to post-implantation development of embryo embrace cells with different levels of stemness. Currently, four states of pluripotency have been recognized, in the progressing order of "naïve," "poised," "formative," and "primed." Epigenetics act as the "conductor" in this "orchestra" of transition in pluripotent states. With a distinguishable gene expression profile, these four states associate with different epigenetic signatures, sometimes distinct while otherwise overlapping. The present review focuses on how epigenetic factors, including DNA methylation, bivalent chromatin, chromatin remodelers, chromatin/nuclear architecture, and microRNA, could dictate pluripotent states and their transition among themselves.

Transcriptomic Analysis of Human Naïve and Primed Pluripotent Stem Cells

Over the last decade, RNA-Sequencing (RNA-Seq) has revolutionized the field of transcriptomics due to its sheer advantage over previous technologies for studying gene expression. Even the domain of stem cell bioinformatics has benefited from these advancements. It has helped look deeper into how the process of pluripotency is maintained by stem cells and how it may be exploited for application in regenerative medicine. However, as it is still an evolving technology, there is no single accepted protocol for RNA-Seq data analysis. From a wide array of tools and/or algorithms available for the purpose, researchers tend to develop a pipeline that is best suited for their sample, experimental design, and computational power. In this tutorial, we describe a pipeline based on open-source tools to analyze RNA-Seq data from naïve and primed state human pluripotent stem cell samples. Precisely, we show how RNA-Seq data can be downloaded from databases, processed, and used to identify differentially expressed genes and construct a co-expression network. Further, we also show how the list of interesting genes obtained from differential expression testing or co-expression network be analyzed to gain biological insights.