Search

Machine learning is commonly employed to extract meaningful information from large and complex data. In situations where only scant data is available, algorithms can leverage abundant data from a separate (unrelated) context to address the learning problem. Here, we present two recently developed biomedical applications that take advantage of transfer learning to bridge the gap from model systems to human: single-cell label transfer and drug response prediction in patients. [ABSTRACT FROM AUTHOR]

The small non‐coding microRNAs (miRNAs) are post‐transcription regulators that modulate diverse cellular process in bone cells. Because optimal miRNA targeting is essential for their function, single‐nucleotide polymorphisms (SNPs) within or proximal to the loci of miRNA (miR‐SNPs) or mRNA (PolymiRTS) could potentially disrupt the miRNA‐mRNA interaction, leading to changes in bone metabolism and osteoporosis. Recent human studies of skeletal traits using miRNA profiling, genomewide association studies, and functional studies started to decipher the complex miRNA regulatory network. These studies have indicated that miRNAs may be a promising bone marker. This review focuses on human miRNA studies on bone traits and discusses how genetic variants affect bone metabolic pathways. Major ex vivo investigations using human samples supported with animal and in vitro models have shed light on the mechanistic role of miRNAs. Furthermore, studying the miRNAs' signatures in secondary osteoporosis and osteoporotic medications such as teriparatide (TPTD) and denosumab (DMab) have provided valuable insight into clinical management of the disease. © 2018 The Authors. JBMR Plus Published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research [ABSTRACT FROM AUTHOR]

Trauma and age‐related cartilage disorders represent a major global cause of morbidity, resulting in chronic pain and disability in patients. A lack of effective therapies, together with a rapidly aging population, creates an impressive clinical and economic burden on healthcare systems. In this scenario, experimental therapies based on transplantation or in situ stimulation of skeletal Mesenchymal Stem/progenitor Cells (MSCs) have raised great interest for cartilage repair. Nevertheless, the challenge of guiding MSC differentiation and preventing cartilage hypertrophy and calcification still needs to be overcome. While research has mostly focused on the stimulation of cartilage anabolism using growth factors, several issues remain unresolved prompting the field to search for novel solutions. Recently, inhibition of anti‐chondrogenic regulators has emerged as an intriguing opportunity. Anti‐chondrogenic regulators include extracellular proteins as well as intracellular transcription factors and microRNAs that act as potent inhibitors of pro‐chondrogenic signals. Suppression of these inhibitors can enhance MSC chondrogenesis and production of cartilage matrix. We here review the current knowledge concerning different types of anti‐chondrogenic regulators. We aim to highlight novel therapeutic targets for cartilage repair and discuss suitable tools for suppressing their anti‐chondrogenic functions. Further effort is needed to unveil the therapeutic perspectives of this approach and pave the way for effective treatment of cartilage injuries in patients. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res [ABSTRACT FROM AUTHOR]

Renal fibrosis is a common pathological feature in chronic kidney disease (CKD), including diabetic kidney disease (DKD) and obstructive nephropathy. Multiple microRNAs have been implicated in the pathogenesis of both DKD and obstructive nephropathy, although the overall role of microRNAs in tubular injury and renal fibrosis in CKD is unclear. Dicer (a key RNase III enzyme for microRNA biogenesis) was specifically ablated from kidney proximal tubules in mice via the Cre-lox system to deplete micoRNAs. Proximal tubular Dicer knockout (PT- Dicer KO) mice and wild-type (WT) littermates were subjected to streptozotocin (STZ) treatment to induce DKD or unilateral ureteral obstruction (UUO) to induce obstructive nephropathy. Renal hypertrophy, renal tubular apoptosis, kidney inflammation, and tubulointerstitial fibrosis were examined. Compared with WT mice, PT- Dicer KO mice showed more severe tubular injury and renal inflammation following STZ treatment. These mice also developed higher levels of tubolointerstitial fibrosis. Meanwhile, PT- Dicer KO mice had a significantly higher Smad2/3 expression in kidneys than WT mice (at 6 mo of age) in both control and STZ-treated mice. Similarly, UUO induced more severe renal injury, inflammation, and interstitial fibrosis in PT- Dicer KO mice than WT. Although we did not detect obvious Smad2/3 expression in sham-operated mice (2-3 mo old), significantly more Smad2/3 was induced in obstructed PT- Dicer KO kidneys. These results supported a protective role of Dicer-dependent microRNA synthesis in renal injury and fibrosis development in CKD, specifically in DKD and obstructive nephropathy. Depletion of Dicer and microRNAs may upregulate Smad2/3-related signaling pathway to enhance the progression of CKD. [ABSTRACT FROM AUTHOR]

The advent of high-throughput sequencing (HTS) technologies has revolutionized the way we understand the transformation of genetic information into morphological traits. Elucidating the network of interactions between genes that govern cell differentiation through development is one of the core challenges in genome research. These networks are known as developmental gene regulatory networks (dGRNs) and consist largely of the functional linkage between developmental control genes, cis- regulatory modules, and differentiation genes, which generate spatially and temporally refined patterns of gene expression. Over the last 20 years, great advances have been made in determining these gene interactions mainly in classical model systems, including human, mouse, sea urchin, fruit fly, and worm. This has brought about a radical transformation in the fields of developmental biology and evolutionary biology, allowing the generation of high-resolution gene regulatory maps to analyze cell differentiation during animal development. Such maps have enabled the identification of gene regulatory circuits and have led to the development of network inference methods that can recapitulate the differentiation of specific cell-types or developmental stages. In contrast, dGRN research in non-classical model systems has been limited to the identification of developmental control genes via the candidate gene approach and the characterization of their spatiotemporal expression patterns, as well as to the discovery of cis- regulatory modules via patterns of sequence conservation and/or predicted transcription-factor binding sites. However, thanks to the continuous advances in HTS technologies, this scenario is rapidly changing. Here, we give a historical overview on the architecture and elucidation of the dGRNs. Subsequently, we summarize the approaches available to unravel these regulatory networks, highlighting the vast range of possibilities of integrating multiple technical advances and theoretical approaches to expand our understanding on the global gene regulation during animal development in non-classical model systems. Such new knowledge will not only lead to greater insights into the evolution of molecular mechanisms underlying cell identity and animal body plans, but also into the evolution of morphological key innovations in animals. [ABSTRACT FROM AUTHOR]

Models describing the process of stem-cell differentiation are plentiful, and may offer insights into the underlying mechanisms and experimentally observed behaviour. Waddington’s epigenetic landscape has been providing a conceptual framework for differentiation processes since its inception. It also allows, however, for detailed mathematical and quantitative analyses, as the landscape can, at least in principle, be related to mathematical models of dynamical systems. Here we focus on a set of dynamical systems features that are intimately linked to cell differentiation, by considering exemplar dynamical models that capture important aspects of stem cell differentiation dynamics. These models allow us to map the paths that cells take through gene expression space as they move from one fate to another, e.g. from a stem-cell to a more specialized cell type. Our analysis highlights the role of the transition state (TS) that separates distinct cell fates, and how the nature of the TS changes as the underlying landscape changes—change that can be induced by e.g. cellular signaling. We demonstrate that models for stem cell differentiation may be interpreted in terms of either a static or transitory landscape. For the static case the TS represents a particular transcriptional profile that all cells approach during differentiation. Alternatively, the TS may refer to the commonly observed period of heterogeneity as cells undergo stochastic transitions. [ABSTRACT FROM AUTHOR]

Hematopoietic stem cell (HSC) fate is tightly controlled by various regulators, whereas the underlying mechanism has not been fully uncovered due to the high heterogeneity of these populations. In this study, we identify tetraspanin CD63 as a novel functional marker of HSCs in mice. We show that CD63 is unevenly expressed on the cell surface in HSC populations. Importantly, HSCs with high CD63 expression (CD63 hi ) are more quiescent and have more robust self-renewal and myeloid differentiation abilities than those with negative/low CD63 expression (CD63 -/lo ). On the other hand, using CD63 knockout mice, we find that loss of CD63 leads to reduced HSC numbers in the bone marrow. In addition, CD63-deficient HSCs exhibit impaired quiescence and long-term repopulating capacity, accompanied by increased sensitivity to irradiation and 5-fluorouracil treatment. Further investigations demonstrate that CD63 is required to sustain TGFβ signaling activity through its interaction with TGFβ receptors I and II, thereby playing an important role in regulating the quiescence of HSCs. Collectively, our data not only reveal a previously unrecognized role of CD63 but also provide us with new insights into HSC heterogeneity., (© 2021. The Author(s), under exclusive licence to ADMC Associazione Differenziamento e Morte Cellulare.)

Abstract: Pluripotent stem cells (PSCs) exist in multiple stable states, each with specific cellular properties and molecular signatures. The mechanisms that maintain pluripotency, or that cause its destabilization to initiate development, are complex and incompletely understood. We have developed a model to predict stabilized PSC gene regulatory network (GRN) states in response to input signals. Our strategy used random asynchronous Boolean simulations (R‐ABS) to simulate single‐cell fate transitions and strongly connected components (SCCs) strategy to represent population heterogeneity. This framework was applied to a reverse‐engineered and curated core GRN for mouse embryonic stem cells (mESCs) and used to simulate cellular responses to combinations of five signaling pathways. Our simulations predicted experimentally verified cell population compositions and input signal combinations controlling specific cell fate transitions. Extending the model to PSC differentiation, we predicted a combination of signaling activators and inhibitors that efficiently and robustly generated a Cdx2+Oct4− cells from naïve mESCs. Overall, this platform provides new strategies to simulate cell fate transitions and the heterogeneity that typically occurs during development and differentiation. [ABSTRACT FROM AUTHOR]

ABSTRACT: Genetic factors have been shown to be a small but significant predictor for osteoporosis and osteoporotic fracture risk. We performed a case–control association study to determine the association between miR‐146a, miR‐149, miR‐196a2, and miR‐499 polymorphisms and osteoporotic vertebral compression fracture (OVCF) susceptibility. In total, 286 unrelated postmenopausal Korean women (57 with OVCFs, 55 with non‐OVCFs, and 174 healthy controls) were recruited. All subjects underwent dual energy X‐ray absorptiometry to determine BMD at the lumbar spine and femoral neck. We focused on four single nucleotide polymorphisms (SNPs) of pre‐miRNA sequences including miR‐146aC>G (rs2910164), miR‐149T>C (rs2292832), miR‐196a2T>C (rs11614913), and miR‐499A>G (rs3746444). Genotype frequencies of these four SNPs were determined using polymerase chain reaction‐restriction fragment length polymorphism analysis. The TT genotype of miR‐149aT>C was less frequent in subjects with OVCFs, suggesting a protective effect against OVCF risk (Odds ratio [OR], 0.435; 95% confidence interval [CI], 0.22–0.85, p = 0.014), whereas the miR‐146aCG/ miR‐196a2TC combined genotype was more frequent in OVCF patients (OR, 5.163; 95%CI, 1.057–25.21, p = 0.043), suggesting an increase in OVCF risk. Additionally, combinations of miR‐146a, ‐149, ‐196a2, and ‐449 showed a significant association with increased prevalence of OVCFs in postmenopausal women. In particular, the miR‐146aG/‐149T/‐196a2C/‐449G allele combination was significantly associated with an increased risk of OVCF (OR, 35.01; 95% CI, 1.919–638.6, p = 0.001). Our findings suggest that the TT genotype of miR‐149aT>C may contribute to decreased susceptibility to OVCF in Korean postmenopausal women. Conversely, the miR‐146aCG/ miR‐196a2TC combined genotype and the miR‐146aG/‐149T/‐196a2C/‐449G allele combination may contribute to increased susceptibility to OVCF. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:244–253, 2018. [ABSTRACT FROM AUTHOR]

There are many lines of evidence indicating that mechanical stress regulates bone metabolism and promotes bone growth. BMP, Wnt, ERK1/2, and OPG/RANKL are the main molecules thought to regulate the effects of mechanical loading on bone formation. Recently, microRNAs were found to be involved in bone cell proliferation and differentiation, regulating the balance of bone formation and bone resorption. Emerging evidence indicates that microRNAs also participate in mechanical stress-mediated bone metabolism, and is associated with disuse induced osteoporosis or osteopenia. Mechanical stress is able to induce expression of microRNAs that modulate the expression of osteogenic and bone resorption factors, leading to the positive impact of mechanical stress on bone. This review discusses the emerging evidence implicating an important role for microRNAs in the mechanical stress response in bone cells, as well as the challenges of translating microRNA research into potential treatment. J. Cell. Physiol. 232: 1239-1245, 2017. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Synthetic cannabinoids are one of the many substances of abuse widely spreading in modern society. Medical practitioners and law enforcement alike highly seek portable, efficient, and reliable tools for on-site detection and diagnostics. Here, we propose a colorimetric lateral flow assay (LFA) combined with dye-loaded polymersome to detect the synthetic cannabinoid JWH-073 efficiently. Rhodamine B-loaded polymersome was conjugated to antibodies and fully characterized. Two LFA were proposed (sandwich and competitive), showing a high level of sensitivity with a limit of detection (LOD) reaching 0.53 and 0.31 ng/mL, respectively. The competitive assay was further analyzed by fluorescence, where the LOD reached 0.16 ng/mL. The application of the LFA over spiked synthetic saliva or real human saliva demonstrated an overall response of 94% for the sandwich assay and 97% for the competitive LFA. The selectivity of the system was assessed in the presence of various interferents. The analytical performance of the LFA system showed a coefficient of variation below 6%. The current LFA system appears as a plausible system for non-invasive detection of substance abuse and shows promise for synthetic cannabinoid on-site sensing., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Hematopoietic stem cell transplantation (HSCT) is the therapeutic concept to cure the blood/immune system of patients suffering from malignancies, immunodeficiencies, red blood cell disorders, and inherited bone marrow failure syndromes. Yet, allogeneic HSCT bear considerable risks for the patient such as non-engraftment, or graft-versus host disease. Transplanting gene modified autologous HSCs is a promising approach not only for inherited blood/immune cell diseases, but also for the acquired immunodeficiency syndrome. However, there is emerging evidence for substantial heterogeneity of HSCs in situ as well as ex vivo that is also observed after HSCT. Thus, HSC gene modification concepts are suggested to consider that different blood disorders affect specific hematopoietic cell types. We will discuss the relevance of HSC heterogeneity for the development and manufacture of gene therapies and in exemplary diseases with a specific emphasis on the key target HSC types myeloid-biased, lymphoid-biased, and balanced HSCs., (© 2021. The Author(s).)

Background: Ossification of the posterior longitudinal ligament (OPLL) of the spine is considered a multifactorial and polygenic disease. We aimed to investigate the association between four single nucleotide polymorphisms (SNPs) of pre-miRNAs [miR-146aC>G (rs2910164), miR-149T>C (rs2292832), miR-196a2T>C (rs11614913), and miR-499A>G (rs3746444)] and the risk of cervical OPLL in the Korean population. Methods: The genotypic frequencies of these four SNPs were analyzed in 207 OPLL patients and 200 controls by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. Findings: For four SNPs in pre-miRNAs, no significant differences were found between OPLL patients and controls. However, subgroup analysis based on OPLL subgroup (continuous: continuous type plus mixed type, segmental: segmental and localized type) showed that miR-499GG genotype was associated with an increased risk of segmental type OPLL (adjusted odds ratio = 4.314 with 95% confidence interval: 1.109–16.78). In addition, some allele combinations (C-T-T-G, G-T-T-A, and G-T-C-G of miR-146a/-149/-196a2/-499) and combined genotypes (miR-149TC/miR-196a2TT) were associated with increased OPLL risk, whereas the G-T-T-G and G-C-C-G allele combinations were associated with decreased OPLL risk. Conclusion: The results indicate that GG genotype of miR-499 is associated with significantly higher risks of OPLL in the segmental OPLL group. The miR-146a/-149/-196a2/-499 allele combinations may be a genetic risk factor for cervical OPLL in the Korean population. [ABSTRACT FROM AUTHOR]

Background/Aims: Embryonic stem (ES) cells have got a broad range differentiation potential. The differentiation is initiated via aggregation of non-differentiated ES cells into embryoid body (EB) capable of multi-lineage development. However experimental variables present in standard differentiation techniques lead to high EB heterogeneity, affecting development into the cells of desired lineage, and do not support the process automatization and scalability. Methods: Here we present a novel pipe based microbioreactor (PBM) setup based on segmented flow, designed for spatial maintenance of temperature, nutrition supply, gas supply and sterility. Results: We verified PBM feasibility for continuous process generating cardiac cells starting from single ES cell suspension followed by EB formation for up to 10 days. The ES cells used in the study were genetically modified for cardiac-specific EGFP expression allowing optical monitoring of cardiomyocytes while EBs remained within PBM for up to 10 days. Efficiency of cardiac cells formation within PBM was similar compared to a standard hanging drop based protocol. Conclusion: Our findings ensure further development of microfluidic bioreactor technology to enable robust cardiomyocytes production for needs of drug screening, tissue engineering and other applications. [ABSTRACT FROM AUTHOR]

Background: A dynamic vasculature is a prerequisite for bone formation where the interaction of bone cells and endothelial cells is essential for both the development and the healing process of bone. Enhanced understanding of the specific mediators involved in bone cell and endothelial cell interactions offers new avenues for skeletal regenerative applications. This study has investigated the osteogenic and angiogenic potential of co-cultures of human foetal diaphyseal or epiphyseal cells with human umbilical vein endothelial cells (HUVEC) in the presence and absence of vascular endothelial growth factor (VEGF) supplementation. Methods: Early osteogenic activities of the co-cultures (±VEGF) were assessed by alkaline phosphatase (ALP) activity. Osteogenic and angiogenic gene expression was measured using quantitative polymerase chain reaction. An ex vivo organotypic embryonic chick (E11) femur culture model was used to determine the osteogenic effects of VEGF as determined using micro-computed tomography (μCT) and Alcian blue/Sirius red histochemistry and immunocytochemistry for expression of CD31. Results: ALP activity and gene expression of ALP and Type-1 collagen was enhanced in foetal skeletal/HUVECs co-cultures. In foetal diaphyseal/HUVECs co-cultures, VEGF reduced the levels of ALP activity and displayed a negligible effect on von Willebrand factor (vWF) and VEGF gene expression. In contrast, VEGF supplementation was observed to significantly increase FLT-1 and KDR gene expression in co-cultures with modulation of expression enhanced, compared to VEGF skeletal monocultures. In the organotypic chick model, addition of VEGF significantly enhanced bone formation, which coincided with elevated levels of CD31-positive cells in the mid-diaphyseal region of the femurs. Conclusion: These studies demonstrate a differential skeletal response of early foetal skeletal cells, when co-cultured with endothelial cells and the potential of co-culture models for bone repair. The differential effect of VEGF supplementation on markers of angiogenesis and osteogenesis in co-cultures and organ cultures, demonstrate the importance of the intricate temporal coordination of osteogenic and angiogenic processes during bone formation and implications therein for effective approaches to bone regenerative therapies. [ABSTRACT FROM AUTHOR]

Osteoporosis is a disease marked by reduced bone mass, leading to an increased risk of fractures or broken bones. Bone formation is mediated by recruiting mesenchymal stem cells (MSCs). Elucidation of the molecular mechanisms that regulate MSC differentiation into osteoblasts is of great importance for the development of anabolic therapies for osteoporosis and other bone metabolism-related diseases. microRNAs (miRNAs) have been reported to have crucial roles in bone development, osteogenic differentiation and osteoporosis pathophysiology. However, to date, only a few miRNAs have been reported to enhance osteogenesis and regulate the suppressive effect of glucocorticoids on osteogenic differentiation. In this study, we discovered that miR-216a, a pancreatic-specific miRNA, was significantly upregulated during osteogenic differentiation in human adipose-derived MSCs (hAMSCs). The expression of miR-216a was positively correlated with the expression of bone formation marker genes in clinical osteoporosis samples. Functional analysis demonstrated that miR-216a can markedly promote osteogenic differentiation of hAMSCs, rescue the suppressive effect of dexamethasone (DEX) on osteogenic differentiation in vitro and enhance bone formation in vivo. c-Cbl, a gene that encodes a RING finger E3 ubiquitin ligase, was identified as a direct target of miR-216a. Downregulation of c-Cbl by short hairpin RNAs can mimic the promotion effects of miR-216a and significantly rescue the suppressive effects of DEX on osteogenesis. Pathway analysis indicated that miR-216a regulation of osteogenic differentiation occurs via the c-Cbl-mediated phosphatidylinositol 3 kinase (PI3K)/AKT pathway. The recovery effects of miR-216a on the inhibition of osteogenesis by DEX were attenuated after blocking the PI3K pathway. Thus, our findings suggest that miR-216a may serve as a novel therapeutic agent for the prevention and treatment of osteoporosis and other bone metabolism-related diseases. [ABSTRACT FROM AUTHOR]

ABSTRACT [ABSTRACT FROM AUTHOR]

The groundbreaking discovery that pluripotency can be induced in somatic cells opened new fields in sciences. Generation of patient- and disease-specific cell lines for drug screening and medical research is in reach. However, the numerous possibilities are limited by the amount of cells needed, that cannot be supplied by state-of-the-art cultivation techniques. New approaches for cell culture automation are wanted, mapping the requirements for this interesting, yet sophisticated cell type. [ABSTRACT FROM AUTHOR]

The study of cell differentiation, embryonic development, and personalized regenerative medicine are all possible through the use of human stem cells. The propensity for these cells to differentiate into all three germ layers of the body with the potential to generate any cell type opens a number of promising avenues for studying human development and disease. One major hurdle to the development of high-throughput production of human stem cells for use in regenerative medicine has been standardization of pluripotency assays. In this review we discuss technologies currently being deployed to produce standardized, high-quality stem cells that can be scaled for high-throughput derivation and screening in regenerative medicine applications. We focus on assays for pluripotency using bioinformatics and gene expression profiling. We review a number of approaches that promise to improve unbiased prediction of utility of both human induced pluripotent stem cells and embryonic stem cells. [ABSTRACT FROM AUTHOR]

NANOG, OCT4 and SOX2 form the core network of transcription factors supporting embryonic stem (ES) cell self-renewal. While OCT4 and SOX2 expression is relatively uniform, ES cells fluctuate between states of high NANOG expression possessing high self-renewal efficiency, and low NANOG expression exhibiting increased differentiation propensity. NANOG, OCT4 and SOX2 are currently considered to activate transcription of each of the three genes, an architecture that cannot readily account for NANOG heterogeneity. Here, we examine the architecture of the Nanog-centred network using inducible NANOG gain- and loss-of-function approaches. Rather than activating itself, Nanog activity is autorepressive and OCT4/SOX2-independent. Moreover, the influence of Nanog on Oct4 and Sox2 expression is minimal. Using Nanog:GFP reporters, we show that Nanog autorepression is a major regulator of Nanog transcription switching. We conclude that the architecture of the pluripotency gene regulatory network encodes the capacity to generate reversible states of Nanog transcription via a Nanog-centred autorepressive loop. Therefore, cellular variability in self-renewal efficiency is an emergent property of the pluripotency gene regulatory network. [ABSTRACT FROM AUTHOR]

GATA binding protein 1 (GATA-1) is one of the most important hematopoietic transcription factors in the production of blood cells, such as platelets, eosinophils, mast cells and erythrocytes. GATA-1 regulates the participation of microRNA (miRNAs/miRs) in erythroid differentiation under normoxia. However, GATA-1 expression and the regulation of miR-210-3p in the context of erythroid differentiation under hypoxia remain unknown. The present study examined the expression levels of GATA-1 and miR-210-3p in the model of erythroid differentiation in K562 cells under hypoxia, and determined the effects of GATA-1, miR-210-3p and SMAD2 on erythroid differentiation through lentivirus transfection experiments. The present study detected increased GATA-1 expression under hypoxia. Moreover, miR-210-3p was identified as a positive regulator of erythroid differentiation, which was upregulated both during erythroid differentiation and in GATA-1 overexpression experiments under hypoxia. Importantly, in the K562 cell model of erythroid differentiation under hypoxia, miR-210-3p was upregulated in a GATA-1-dependent manner. Using a double luciferase reporter assay, miR-210-3p was identified as a downstream target of GATA-1-mediated regulation of erythropoiesis. Gain- or loss-of-function analysis of miR-210-3p identified its importance in erythroid differentiation. Furthermore, it was found that SMAD2 may be a downstream target gene for miR-210-3p. Bioinformatics predictions suggested that SMAD2 mediated miR-210-3p-induced regulation of erythroid differentiation. Collectively, the present study provides novel insights into the miRNA regulation of erythroid differentiation. [ABSTRACT FROM AUTHOR]

Platelets are small pieces of cytoplasm that have become detached from the cytoplasm of mature megakaryocytes (MKs) in the bone marrow. Platelets modulate vascular system integrity and serve important role, particularly in hemostasis. With the rapid development of clinical medicine, the demand for platelet transfusion as a life-saving intervention increases continuously. Stem cell technology appears to be highly promising for transfusion medicine, and the generation of platelets from stem cells would be of great value in the clinical setting. Furthermore, several studies have been undertaken to investigate the potential of producing platelets from stem cells. Initial success has been achieved in terms of the yields and function of platelets generated from stem cells. However, the requirements of clinical practice remain unmet. The aim of the present review was to focus on several sources of stem cells and factors that induce MK differentiation. Updated information on current research into the genetic regulation of megakaryocytopoiesis and platelet generation was summarized. Additionally, advanced strategies of platelet generation were reviewed and the progress made in this field was discussed. [ABSTRACT FROM AUTHOR]

Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage. In this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios. Cross-validation, holdout validation and independent test experiments show that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirm that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification. Author summary: Identification of induced pluripotent stem (iPS) progenitor cells could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only after about 6 days of induction, iPS cells can be experimentally determined via fluorescent probes. What is more, the percentage of the progenitor cells during the early induction period is below 5%, too low to capture experimentally in early stage. In this work, we proposed an approach for the identification of iPS progenitor cells, the iPS forming cells, based on machine learning and microscopic image analysis. The aim is to help biologists to enrich iPS progenitor cells during the early stage of induction, which allows experimentalists to select iPS progenitor cells with much higher probability, and furthermore to study the biomarkers which trigger the reprogramming process. [ABSTRACT FROM AUTHOR]

There are an increasing number of reports that characterize the temporal behavior of gene expression at the single-cell level during cell differentiation. Despite accumulation of data describing the heterogeneity of biological responses, the dynamics of gene expression heterogeneity and its regulation during the differentiation process have not been studied systematically. To understand transcriptional heterogeneity during astrocyte differentiation, we analyzed single-cell transcriptional data from cells representing the different stages of astrocyte differentiation. When we compared the transcriptional variability of co-expressed genes between the undifferentiated and differentiated states, we found that there was significant increase in transcriptional variability in the undifferentiated state. The genes showing large changes in both "variability" and "correlation" between neural stem cells (NSCs) and astrocytes were found to be functionally involved in astrocyte differentiation. We determined that these genes are potentially regulated by Ascl1, a previously known oscillatory gene in NSCs. Pharmacological blockade of Ntsr2, which is transcriptionally co-regulated with Ascl1, showed that Ntsr2 may play an important role in the differentiation from NSCs to astrocytes. This study shows the importance of characterizing transcriptional heterogeneity and rearrangement of the co-regulation network between different cell states. It also highlights the potential for identifying novel regulators of cell differentiation that will further increase our understanding of the molecular mechanisms underlying the differentiation process. Computational neuroscience: transcriptional heterogeneity spotlights the key players in astrogenesis In addition to average gene expression levels across stem cell populations, the variation in gene expression between single cells triggered by biological oscillations can provide new insights. A team led by Hiroyuki Honda at Nagoya University in Japan introduced the concept of analyzing gene expression heterogeneity within a cell population to elucidate the mechanism of astrocyte differentiation. By scoring the variability and correlation within single-cell gene expression data, the expression heterogeneity in a cell population was found to increase before differentiation. The analysis highlighted key differentiation regulators like Ascl1, Sox9, and Ntsr2. This work underscores the importance of understanding transcriptional heterogeneity to identify key genes in stem cell differentiation that could not be found through conventional "level-focused" expression analysis. [ABSTRACT FROM AUTHOR]

The cell cycle is canonically described as a series of four consecutive phases: G1, S, G2, and M. In single cells, the duration of each phase varies, but the quantitative laws that govern phase durations are not well understood. Using time‐lapse microscopy, we found that each phase duration follows an Erlang distribution and is statistically independent from other phases. We challenged this observation by perturbing phase durations through oncogene activation, inhibition of DNA synthesis, reduced temperature, and DNA damage. Despite large changes in durations in cell populations, phase durations remained uncoupled in individual cells. These results suggested that the independence of phase durations may arise from a large number of molecular factors that each exerts a minor influence on the rate of cell cycle progression. We tested this model by experimentally forcing phase coupling through inhibition of cyclin‐dependent kinase 2 (CDK2) or overexpression of cyclin D. Our work provides an explanation for the historical observation that phase durations are both inherited and independent and suggests how cell cycle progression may be altered in disease states. Synopsis: Time‐lapse imaging of cell‐cycle phase transitions reveals that phase durations are uncoupled and can be modeled as an Erlang process. Phase coupling can be forced by perturbing a strong cell‐cycle regulator acting on multiple phases. Cell‐cycle phase durations are uncoupled in three human cell lines.Each cell‐cycle phase proceeds like a sequence of memoryless steps that can be modeled as an Erlang process.A "many‐for‐all model", in which large number of factors each exerting minor influence on phase duration, explains the stochastic but heritable nature of cell cycle progression.Coupling between cell‐cycle phases can be introduced by perturbing a cell‐cycle regulator of multiple phases. Time‐lapse imaging of cell‐cycle phase transitions reveals that phase durations are uncoupled and can be modeled as an Erlang process. Phase coupling can be forced by perturbing a strong cell‐cycle regulator acting on multiple phases. [ABSTRACT FROM AUTHOR]

During differentiation and reprogramming, new cell identities are generated by reconfiguration of gene regulatory networks. Here, we combined automated formal reasoning with experimentation to expose the logic of network activation during induction of naïve pluripotency. We find that a Boolean network architecture defined for maintenance of naïve state embryonic stem cells (ESC) also explains transcription factor behaviour and potency during resetting from primed pluripotency. Computationally identified gene activation trajectories were experimentally substantiated at single‐cell resolution by RT–qPCR. Contingency of factor availability explains the counterintuitive observation that Klf2, which is dispensable for ESC maintenance, is required during resetting. We tested 124 predictions formulated by the dynamic network, finding a predictive accuracy of 77.4%. Finally, we show that this network explains and predicts experimental observations of somatic cell reprogramming. We conclude that a common deterministic program of gene regulation is sufficient to govern maintenance and induction of naïve pluripotency. The tools exemplified here could be broadly applied to delineate dynamic networks underlying cell fate transitions. Synopsis: While a minimal interaction network of transcription factors recapitulates naïve state maintenance of embryonic stem cells, our understanding of the logic controlling acquisition of pluripotency remains fragmentary. In this study, an iterative, computational‐experimental approach reveals that a common network governs both maintenance and installation of naïve pluripotency. Formal verification of Boolean network dynamics uncovers the network logic governing induction of naïve pluripotency from murine primed epiblast stem cells (EpiSC) and somatic cells.Model predictions identify factors to enhance or be required for reprogramming.Dual combinations of factors act synergistically and sequentially to enhance EpiSC resetting.Network architecture and update rules predict gene activation dynamics substantiated by single‐cell gene expression analysis.Individual cells follow a deterministic trajectory in the final stage of productive reprogramming. A single transcription factor program governs maintenance and induction of naïve pluripotency. [ABSTRACT FROM AUTHOR]

The initiation of heterogeneity within a population of phenotypically identical progenitors is a critical event for the onset of morphogenesis and differentiation patterning. Gap junction communication within multicellular systems produces complex networks of intercellular connectivity that result in heterogeneous distributions of intracellular signaling molecules. In this study, we investigate emergent systems-level behavior of the intercellular network within embryonic stem cell (ESC) populations and corresponding spatial organization during early neural differentiation. An agent-based model incorporates experimentally-determined parameters to yield complex transport networks for delivery of pro-differentiation cues between neighboring cells, reproducing the morphogenic trajectories during retinoic acid-accelerated mouse ESC differentiation. Furthermore, the model correctly predicts the delayed differentiation and preserved spatial features of the morphogenic trajectory that occurs in response to intercellular perturbation. These findings suggest an integral role of gap junction communication in the temporal coordination of emergent patterning during early differentiation and neural commitment of pluripotent stem cells. [ABSTRACT FROM AUTHOR]

Background: Heterogeneous gene expressions of cells are widely observed in self-renewing pluripotent stem cells, suggesting possible coexistence of multiple cellular states with distinct characteristics. Though the elements regulating cellular states have been identified, the underlying dynamic mechanisms and the significance of such cellular heterogeneity remain elusive. Results: We present a gene regulatory network model to investigate the bimodal Nanog distribution in stem cells. Our model reveals a novel role of dynamic conversion between the cellular states of high and low Nanog levels. Model simulations demonstrate that the low-Nanog state benefits cell differentiation through serving as an intermediate state to reduce the barrier of transition. Interestingly, the existence of low-Nanog state dynamically slows down the reprogramming process, and additional Nanog activation is found to be essential to quickly attaining the fully reprogrammed cell state. Conclusions: Nanog has been recognized as a critical pluripotency gene in stem cell regulation. Our modeling results quantitatively show a dual role of Nanog during stem cell differentiation and reprogramming, and the importance of the intermediate state during cell state transitions. Our approach offers a general method for analyzing key regulatory factors controlling cell differentiation and reprogramming. [ABSTRACT FROM AUTHOR]

Background: Single-cell studies have demonstrated the presence of significant cell-to-cell heterogeneity in gene expression. Whether such heterogeneity is only a bystander or has a functional role in the cell differentiation process is still hotly debated. Methods: In this study, we quantified and followed single-cell transcriptional uncertainty – a measure of gene transcriptional stochasticity in single cells – in 10 cell differentiation systems of varying cell lineage progressions, from single to multi-branching trajectories, using the stochastic two-state gene transcription model. Results: By visualizing the transcriptional uncertainty as a landscape over a two-dimensional representation of the single-cell gene expression data, we observed universal features in the cell differentiation trajectories that include: (i) a peak in single-cell uncertainty during transition states, and in systems with bifurcating differentiation trajectories, each branching point represents a state of high transcriptional uncertainty; (ii) a positive correlation of transcriptional uncertainty with transcriptional burst size and frequency; (iii) an increase in RNA velocity preceding the increase in the cell transcriptional uncertainty. Conclusions: Our findings suggest a possible universal mechanism during the cell differentiation process, in which stem cells engage stochastic exploratory dynamics of gene expression at the start of the cell differentiation by increasing gene transcriptional bursts, and disengage such dynamics once cells have decided on a particular terminal cell identity. Notably, the peak of single-cell transcriptional uncertainty signifies the decision-making point in the cell differentiation process.

Background: Single-cell studies have demonstrated the presence of significant cell-to-cell heterogeneity in gene expression. Whether such heterogeneity is only a bystander or has a functional role in the cell differentiation process is still hotly debated. Methods: In this study, we quantified and followed single-cell transcriptional uncertainty – a measure of gene transcriptional stochasticity in single cells – in 10 cell differentiation systems of varying cell lineage progressions, from single to multi-branching trajectories, using the stochastic two-state gene transcription model. Results: By visualizing the transcriptional uncertainty as a landscape over a two-dimensional representation of the single-cell gene expression data, we observed universal features in the cell differentiation trajectories that include: (i) a peak in single-cell uncertainty during transition states, and in systems with bifurcating differentiation trajectories, each branching point represents a state of high transcriptional uncertainty; (ii) a positive correlation of transcriptional uncertainty with transcriptional burst size and frequency; (iii) an increase in RNA velocity preceding the increase in the cell transcriptional uncertainty. Conclusions: Our findings suggest a possible universal mechanism during the cell differentiation process, in which stem cells engage stochastic exploratory dynamics of gene expression at the start of the cell differentiation by increasing gene transcriptional bursts, and disengage such dynamics once cells have decided on a particular terminal cell identity. Notably, the peak of single-cell transcriptional uncertainty signifies the decision-making point in the cell differentiation process.