FOXO1 mitigates the SMAD3/FOXL2C134W transcriptomic effect in a model of human adult granulosa cell tumor.

BACKGROUND: Adult granulosa cell tumor (aGCT) is a rare type of stromal cell malignant cancer of the ovary characterized by elevated estrogen levels. aGCTs ubiquitously harbor a somatic mutation in FOXL2 gene, Cys134Trp (c.402C < G); however, the general molecular effect of this mutation and its putative pathogenic role in aGCT tumorigenesis is not completely understood. We previously studied the role of FOXL2C134W, its partner SMAD3 and its antagonist FOXO1 in cellular models of aGCT. METHODS: In this work, seeking more comprehensive profiling of FOXL2C134W transcriptomic effects, we performed an RNA-seq analysis comparing the effect of FOXL2WT/SMAD3 and FOXL2C134W/SMAD3 overexpression in an established human GC line (HGrC1), which is not luteinized, and bears normal alleles of FOXL2. RESULTS: Our data shows that FOXL2C134W/SMAD3 overexpression alters the expression of 717 genes. These genes include known and novel FOXL2 targets (TGFB2, SMARCA4, HSPG2, MKI67, NFKBIA) and are enriched for neoplastic pathways (Proteoglycans in Cancer, Chromatin remodeling, Apoptosis, Tissue Morphogenesis, Tyrosine Kinase Receptors). We additionally expressed the FOXL2 antagonistic Forkhead protein, FOXO1. Surprisingly, overexpression of FOXO1 mitigated 40% of the altered genome-wide effects specifically related to FOXL2C134W, suggesting it can be a new target for aGCT treatment. CONCLUSIONS: Our transcriptomic data provide novel insights into potential genes (FOXO1 regulated) that could be used as biomarkers of efficacy in aGCT patients.

Towards Resolving the Pro- and Anti-Tumor Effects of the Aryl Hydrocarbon Receptor.

We have postulated that the aryl hydrocarbon receptor (AHR) drives the later, more lethal stages of some cancers when chronically activated by endogenous ligands. However, other studies have suggested that, under some circumstances, the AHR can oppose tumor aggression. Resolving this apparent contradiction is critical to the design of AHR-targeted cancer therapeutics. Molecular (siRNA, shRNA, AHR repressor, CRISPR-Cas9) and pharmacological (AHR inhibitors) approaches were used to confirm the hypothesis that AHR inhibition reduces human cancer cell invasion (irregular colony growth in 3D Matrigel cultures and Boyden chambers), migration (scratch wound assay) and metastasis (human cancer cell xenografts in zebrafish). Furthermore, these assays were used for a head-to-head comparison between AHR antagonists and agonists. AHR inhibition or knockdown/knockout consistently reduced human ER−/PR−/Her2− and inflammatory breast cancer cell invasion, migration, and metastasis. This was associated with a decrease in invasion-associated genes (e.g., Fibronectin, VCAM1, Thrombospondin, MMP1) and an increase in CDH1/E-cadherin, previously associated with decreased tumor aggression. Paradoxically, AHR agonists (2,3,7,8-tetrachlorodibenzo-p-dioxin and/or 3,3′-diindolylmethane) similarly inhibited irregular colony formation in Matrigel and blocked metastasis in vivo but accelerated migration. These data demonstrate the complexity of modulating AHR activity in cancer while suggesting that AHR inhibitors, and, under some circumstances, AHR agonists, may be useful as cancer therapeutics.

Network-based analysis of transcriptional profiles from chemical perturbations experiments.

BACKGROUND: Methods for inference and comparison of biological networks are emerging as powerful tools for the identification of groups of tightly connected genes whose activity may be altered during disease progression or due to chemical perturbations. Connectivity-based comparisons help identify aggregate changes that would be difficult to detect with differential analysis methods comparing individual genes. METHODS: In this study, we describe a pipeline for network comparison and its application to the analysis of gene expression datasets from chemical perturbation experiments, with the goal of elucidating the modes of actions of the profiled perturbations. We apply our pipeline to the analysis of the DrugMatrix and the TG-GATEs, two of the largest toxicogenomics resources available, containing gene expression measurements for model organisms exposed to hundreds of chemical compounds with varying carcinogenicity and genotoxicity. RESULTS: Starting from chemical-specific transcriptional networks inferred from these data, we show that the proposed comparative analysis of their associated networks identifies groups of chemicals with similar functions and similar carcinogenicity/genotoxicity profiles. We also show that the in-silico annotation by pathway enrichment analysis of the gene modules with a significant gain or loss of connectivity for specific groups of compounds can reveal molecular pathways significantly associated with the chemical perturbations and their likely modes of action. CONCLUSIONS: The proposed pipeline for transcriptional network inference and comparison is highly reproducible and allows grouping chemicals with similar functions and carcinogenicity/genotoxicity profiles. In the context of drug discovery or drug repositioning, the methods presented here could help assign new functions to novel or existing drugs, based on the similarity of their associated network with those built for other known compounds. Additionally, the method has broad applicability beyond the uses here described and could be used as an alternative or as a complement to standard approaches of differential gene expression analysis.

Genetic Analysis Reveals a Longevity-Associated Protein Modulating Endothelial Function and Angiogenesis.

RATIONALE: Long living individuals show delay of aging, which is characterized by the progressive loss of cardiovascular homeostasis, along with reduced endothelial nitric oxide synthase activity, endothelial dysfunction, and impairment of tissue repair after ischemic injury. OBJECTIVE: Exploit genetic analysis of long living individuals to reveal master molecular regulators of physiological aging and new targets for treatment of cardiovascular disease. METHODS AND RESULTS: We show that the polymorphic variant rs2070325 (Ile229Val) in bactericidal/permeability-increasing fold-containing-family-B-member-4 (BPIFB4) associates with exceptional longevity, under a recessive genetic model, in 3 independent populations. Moreover, the expression of BPIFB4 is instrumental to maintenance of cellular and vascular homeostasis through regulation of protein synthesis. BPIFB4 phosphorylation/activation by protein-kinase-R-like endoplasmic reticulum kinase induces its complexing with 14-3-3 and heat shock protein 90, which is facilitated by the longevity-associated variant. In isolated vessels, BPIFB4 is upregulated by mechanical stress, and its knock-down inhibits endothelium-dependent vasorelaxation. In hypertensive rats and old mice, gene transfer of longevity-associated variant-BPIFB4 restores endothelial nitric oxide synthase signaling, rescues endothelial dysfunction, and reduces blood pressure levels. Furthermore, BPIFB4 is implicated in vascular repair. BPIFB4 is abundantly expressed in circulating CD34(+) cells of long living individuals, and its knock-down in endothelial progenitor cells precludes their capacity to migrate toward the chemoattractant SDF-1. In a murine model of peripheral ischemia, systemic gene therapy with longevity-associated variant-BPIFB4 promotes the recruitment of hematopoietic stem cells, reparative vascularization, and reperfusion of the ischemic muscle. CONCLUSIONS: Longevity-associated variant-BPIFB4 may represent a novel therapeutic tool to fight endothelial dysfunction and promote vascular reparative processes.

The role of the aryl hydrocarbon receptor in the development of cells with the molecular and functional characteristics of cancer stem-like cells.

BACKGROUND: Self-renewing, chemoresistant breast cancer stem cells are believed to contribute significantly to cancer invasion, migration and patient relapse. Therefore, the identification of signaling pathways that regulate the acquisition of stem-like qualities is an important step towards understanding why patients relapse and towards development of novel therapeutics that specifically target cancer stem cell vulnerabilities. Recent studies identified a role for the aryl hydrocarbon receptor (AHR), an environmental carcinogen receptor implicated in cancer initiation, in normal tissue-specific stem cell self-renewal. These studies inspired the hypothesis that the AHR plays a role in the acquisition of cancer stem cell-like qualities. RESULTS: To test this hypothesis, AHR activity in Hs578T triple negative and SUM149 inflammatory breast cancer cells were modulated with AHR ligands, shRNA or AHR-specific inhibitors, and phenotypic, genomic and functional stem cell-associated characteristics were evaluated. The data demonstrate that (1) ALDH(high) cells express elevated levels of Ahr and Cyp1b1 and Cyp1a1, AHR-driven genes, (2) AHR knockdown reduces ALDH activity by 80%, (3) AHR hyper-activation with several ligands, including environmental ligands, significantly increases ALDH1 activity, expression of stem cell- and invasion/migration-associated genes, and accelerates cell migration, (4) a significant correlation between Ahr or Cyp1b1 expression (as a surrogate marker for AHR activity) and expression of stem cell- and invasion/migration-associated gene sets is seen with genomic data obtained from 79 human breast cancer cell lines and over 1,850 primary human breast cancers, (5) the AHR interacts directly with Sox2, a master regulator of self-renewal; AHR ligands increase this interaction and nuclear SOX2 translocation, (6) AHR knockdown inhibits tumorsphere formation in low adherence conditions, (7) AHR inhibition blocks the rapid migration of ALDH(high) cells and reduces ALDH(high) cell chemoresistance, (8) ALDH(high) cells are highly efficient at initiating tumors in orthotopic xenografts, and (9) AHR knockdown inhibits tumor initiation and reduces tumor Aldh1a1, Sox2, and Cyp1b1 expression in vivo. CONCLUSIONS: These data suggest that the AHR plays an important role in development of cells with cancer stem cell-like qualities and that environmental AHR ligands may exacerbate breast cancer by enhancing expression of these properties.

Confirmation and pathogenicity of small copy number variations incidentally detected via a targeted next-generation sequencing-based PGT-A platform.

OBJECTIVE: To evaluate the technical accuracy, inheritance, and pathogenicity of small copy number variants (CNVs) detected by a targeted next-generation sequencing (NGS)-based PGT-A platform. DESIGN: Retrospective observational study performed between 2020-2022. SUBJECTS: 12,157 patients who underwent clinical PGT-A performed by targeted NGS for whole chromosome and large segmental aneuploidies. EXPOSURE: An incidental finding was reported when a CNV gain/loss of at least three consecutive amplicons appeared in at least two embryos from the same IVF cycle. MAIN OUTCOME MEASURES: The primary outcome measures were the specificity, incidence, inheritance, and pathogenicity of small CNVs detected by the PGT-A platform. Accuracy of the PGT-A platform CNV calls was assessed via concordance with the CNV calls (size and genomic location) on chromosomal microarray of the gamete provider(s). Parental origin of the CNV and pathogenicity classifications were also reported. RESULTS: In 75 of 12,157 unique PGT-A patients (0.62%;95%CI:0.5-0.8%), an incidental finding that met reporting criteria was identified. Chromosomal microarray follow-up was requested for all cases and results were received for one or both members of 65 reproductive couples. In all cases, one of the gamete providers was confirmed to have the CNV identified in the embryos (100.0%: N=65/65 95%CI:94.5-100). The identified CNV was of maternal origin in 34 cases (52.3%) and of paternal origin in 31 cases (47.7%). A significant correlation was identified between PGT-A-predicted CNV sizes and chromosomal microarray detected sizes (r=0.81) and genomic coordinates on parental DNA. Twenty-six (40%) of the CNVs were classified as benign/likely benign, 30 (46.2%) as a variant of uncertain significance (VUS), and 9 (13.8%) as pathogenic/likely pathogenic. CONCLUSION: Certain PGT-A platforms may enable the detection of inherited, small CNVs with extremely high specificity without prior knowledge of parental status. The majority of CNVs in this data set were confirmed to be benign/likely benign or a VUS; however, pathogenic/likely pathogenic CNVs associated with a broad range of phenotypic features may also be detected, although a reliable negative predictive value for small CNVs with current PGT-A technologies is unknown due to the many technical challenges.

Transcriptome based identification of mouse cumulus cell markers that predict the developmental competence of their enclosed antral oocytes.

BACKGROUND: The cumulus cells (CCs) enveloping antral and ovulated oocytes have been regarded as putative source of non-invasive markers of the oocyte developmental competence. A number of studies have indeed observed a correlation between CCs gene expression, embryo quality, and final pregnancy outcome. Here, we isolated CCs from antral mouse oocytes of known developmental incompetence (NSN-CCs) or competence (SN-CCs) and compared their transcriptomes with the aim of identifying distinct marker transcripts. RESULTS: Global gene expression analysis highlighted that both types of CCs share similar transcriptomes, with the exception of 422 genes, 97.6% of which were down-regulated in NSN-CCs vs. SN-CCs. This transcriptional down-regulation in NSN-CCs was confirmed by qRT-PCR analysis of CC-related genes (Has2, Ptx3, Tnfaip6 and Ptgs2). Only ten of the 422 genes were up-regulated with Amh being the most up-regulated in NSN-CCs, with an average 4-fold higher expression when analysed by qRT-PCR. CONCLUSIONS: The developmental incompetence (NSN) or competence (SN) of antral oocytes can be predicted using transcript markers expressed by their surrounding CCs (i.e., Has2, Ptx3, Tnfaip6, Ptgs2 and Amh). Overall, the regulated nature of the group of genes brought out by whole transcriptome analysis constitutes the molecular signature of CCs associated either with developmentally incompetent or competent oocytes and may represent a valuable resource for developing new molecular tools for the assessment of oocyte quality and to further investigate the complex bi-directional interaction occurring between CCs and oocyte.

Network-based target ranking for polypharmacological therapies.

With the growing understanding of complex diseases, the focus of drug discovery has shifted from the well-accepted "one target, one drug" model, to a new "multi-target, multi-drug" model, aimed at systemically modulating multiple targets. In this context, polypharmacology has emerged as a new paradigm to overcome the recent decline in productivity of pharmaceutical research. However, finding methods to evaluate multicomponent therapeutics and ranking synergistic agent combinations is still a demanding task. At the same time, the data gathered on complex diseases has been progressively collected in public data and knowledge repositories, such as protein-protein interaction (PPI) databases. The PPI networks are increasingly used as universal platforms for data integration and analysis. A novel computational network-based approach for feasible and efficient identification of multicomponent synergistic agents is proposed in this paper. Given a complex disease, the method exploits the topological features of the related PPI network to identify possible combinations of hit targets. The best ranked combinations are subsequently computed on the basis of a synergistic score. We illustrate the potential of the method through a study on Type 2 Diabetes Mellitus. The results highlight its ability to retrieve novel target candidates, which role is also confirmed by the analysis of the related literature.

Mouse embryonic stem cells irradiated with γ-rays differentiate into cardiomyocytes but with altered contractile properties.

Embryonic stem cells (ESCs) for their derivation from the inner cell mass of a blastocyst represent a valuable in vitro model to investigate the effects of ionizing radiation on early embryonic cellular response. Following irradiation, both human and mouse ESCs (mESCs) maintain their pluripotent status and the capacity to differentiate into embryoid bodies and to form teratomas. Although informative of the maintenance of a pluripotent status, these studies never investigated the capability of irradiated ESCs to form specific differentiated phenotypes. Here, for the first time, 5Gy-irradiated mESCs were differentiated into cardiomyocytes, thus allowing the analysis of the long-term effects of ionizing radiations on the differentiation potential of a pluripotent stem cell population. On treated mESCs, 96h after irradiation, a genome-wide expression analysis was first performed in order to determine whether the treatment influenced gene expression of the surviving mESCs. Microarrays analysis showed that only 186 genes were differentially expressed in treated mESCs compared to control cells; a quarter of these genes were involved in cellular differentiation, with three main gene networks emerging, including cardiogenesis. Based on these results, we differentiated irradiated mESCs into cardiomyocytes. On day 5, 8 and 12 of differentiation, treated cells showed a significant alteration (qRT-PCR) of the expression of marker genes (Gata-4, Nkx-2.5, Tnnc1 and Alpk3) when compared to control cells. At day 15 of differentiation, although the organization of sarcomeric α-actinin and troponin T proteins appeared similar in cardiomyocytes differentiated from either mock or treated cells, the video evaluation of the kinematics and dynamics of the beating cardiac syncytium evidenced altered contractile properties of cardiomyocytes derived from irradiated mESCs. This alteration correlated with significant reduction of Connexin 43 foci. Our results indicate that mESCs populations that survive an ionizing irradiation treatment are capable to differentiate into cardiomyocytes, but they have altered contractile properties.

Interest propagation for knowledge extraction and representation.

Due to the increasing number of available biomedical data repositories, providing a comprehensive and intuitive access to information is still a demanding task for Information Retrieval systems. In this work we present an interactive data exploration system that retrieves relevant information by propagating the user's interest within a network. The developed techniques have been applied to two different retrieval tasks useful for biomedical research: the prioritization of proteins related to a disease of interest and the search of publications in the literature. The method relies on a network of biomedical entities, scoring of entities of interest by the user, and score propagation. The assessment of the relevance of the retrieved information confirmed a high accuracy of the presented algorithms for both the domains considered.

Nutrient regulation of the islet epigenome controls adaptive insulin secretion.

Adaptation of the islet ß cell insulin-secretory response to changing insulin demand is critical for blood glucose homeostasis, yet the mechanisms underlying this adaptation are unknown. Here, we have shown that nutrient-stimulated histone acetylation plays a key role in adapting insulin secretion through regulation of genes involved in ß cell nutrient sensing and metabolism. Nutrient regulation of the epigenome occurred at sites occupied by the chromatin-modifying enzyme lysine-specific demethylase 1 (Lsd1) in islets. ß Cell-specific deletion of Lsd1 led to insulin hypersecretion, aberrant expression of nutrient-response genes, and histone hyperacetylation. Islets from mice adapted to chronically increased insulin demand exhibited shared epigenetic and transcriptional changes. Moreover, we found that genetic variants associated with type 2 diabetes were enriched at LSD1-bound sites in human islets, suggesting that interpretation of nutrient signals is genetically determined and clinically relevant. Overall, these studies revealed that adaptive insulin secretion involves Lsd1-mediated coupling of nutrient state to regulation of the islet epigenome.

Stage prediction of embryonic stem cell differentiation from genome-wide expression data.

MOTIVATION: The developmental stage of a cell can be determined by cellular morphology or various other observable indicators. Such classical markers could be complemented with modern surrogates, like whole-genome transcription profiles, that can encode the state of the entire organism and provide increased quantitative resolution. Recent findings suggest that such profiles provide sufficient information to reliably predict the cell's developmental stage. RESULTS: We use whole-genome transcription data and several data projection methods to infer differentiation stage prediction models for embryonic cells. Given a transcription profile of an uncharacterized cell, these models can then predict its developmental stage. In a series of experiments comprising 14 datasets from the Gene Expression Omnibus, we demonstrate that the approach is robust and has excellent prediction ability both within a specific cell line and across different cell lines. AVAILABILITY: Model inference and computational evaluation procedures in the form of Python scripts and accompanying datasets are available at http://www.biolab.si/supp/stagerank. CONTACT: blaz.zupan@fri.uni-lj.si SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gatekeeper of pluripotency: a common Oct4 transcriptional network operates in mouse eggs and embryonic stem cells.

BACKGROUND: Oct4 is a key factor of an expanded transcriptional network (Oct4-TN) that governs pluripotency and self-renewal in embryonic stem cells (ESCs) and in the inner cell mass from which ESCs are derived. A pending question is whether the establishment of the Oct4-TN initiates during oogenesis or after fertilisation. To this regard, recent evidence has shown that Oct4 controls a poorly known Oct4-TN central to the acquisition of the mouse egg developmental competence. The aim of this study was to investigate the identity and extension of this maternal Oct4-TN, as much as whether its presence is circumscribed to the egg or maintained beyond fertilisation. RESULTS: By comparing the genome-wide transcriptional profile of developmentally competent eggs that express the OCT4 protein to that of developmentally incompetent eggs in which OCT4 is down-regulated, we unveiled a maternal Oct4-TN of 182 genes. Eighty of these transcripts escape post-fertilisation degradation and represent the maternal Oct4-TN inheritance that is passed on to the 2-cell embryo. Most of these 80 genes are expressed in cancer cells and 37 are notable companions of the Oct4 transcriptome in ESCs. CONCLUSIONS: These results provide, for the first time, a developmental link between eggs, early preimplantation embryos and ESCs, indicating that the molecular signature that characterises the ESCs identity is rooted in oogenesis. Also, they contribute a useful resource to further study the mechanisms of Oct4 function and regulation during the maternal-to-embryo transition and to explore the link between the regulation of pluripotency and the acquisition of de-differentiation in cancer cells.

Information technology solutions to support translational research on inherited cardiomyopathies.

The INHERITANCE project, funded by the European Commission, is aimed at studying genetic or inherited Dilated cardiomyopathies (DCM) and at understanding the impact and management of the condition within families that suffer from heart conditions that are caused by DCMs. The project is supported by a number of advanced biomedical informatics tools, including data warehousing, automated literature search and decision support. The paper describes the design of these tools and the current status of implementation.

Text Mining approaches for automated literature knowledge extraction and representation.

Due to the overwhelming volume of published scientific papers, information tools for automated literature analysis are essential to support current biomedical research. We have developed a knowledge extraction tool to help researcher in discovering useful information which can support their reasoning process. The tool is composed of a search engine based on Text Mining and Natural Language Processing techniques, and an analysis module which process the search results in order to build annotation similarity networks. We tested our approach on the available knowledge about the genetic mechanism of cardiac diseases, where the target is to find both known and possible hypothetical relations between specific candidate genes and the trait of interest. We show that the system i) is able to effectively retrieve medical concepts and genes and ii) plays a relevant role assisting researchers in the formulation and evaluation of novel literature-based hypotheses.

A Network of microRNAs Acts to Promote Cell Cycle Exit and Differentiation of Human Pancreatic Endocrine Cells.

Pancreatic endocrine cell differentiation is orchestrated by the action of transcription factors that operate in a gene regulatory network to activate endocrine lineage genes and repress lineage-inappropriate genes. MicroRNAs (miRNAs) are important modulators of gene expression, yet their role in endocrine cell differentiation has not been systematically explored. Here we characterize miRNA-regulatory networks active in human endocrine cell differentiation by combining small RNA sequencing, miRNA over-expression, and network modeling approaches. Our analysis identified Let-7g, Let-7a, miR-200a, miR-127, and miR-375 as endocrine-enriched miRNAs that drive endocrine cell differentiation-associated gene expression changes. These miRNAs are predicted to target different transcription factors, which converge on genes involved in cell cycle regulation. When expressed in human embryonic stem cell-derived pancreatic progenitors, these miRNAs induce cell cycle exit and promote endocrine cell differentiation. Our study delineates the role of miRNAs in human endocrine cell differentiation and identifies miRNAs that could facilitate endocrine cell reprogramming.

Integrated In Vivo Quantitative Proteomics and Nutrient Tracing Reveals Age-Related Metabolic Rewiring of Pancreatic ß Cell Function.

Pancreatic ß cell physiology changes substantially throughout life, yet the mechanisms that drive these changes are poorly understood. Here, we performed comprehensive in vivo quantitative proteomic profiling of pancreatic islets from juvenile and 1-year-old mice. The analysis revealed striking differences in abundance of enzymes controlling glucose metabolism. We show that these changes in protein abundance are associated with higher activities of glucose metabolic enzymes involved in coupling factor generation as well as increased activity of the coupling factor-dependent amplifying pathway of insulin secretion. Nutrient tracing and targeted metabolomics demonstrated accelerated accumulation of glucose-derived metabolites and coupling factors in islets from 1-year-old mice, indicating that age-related changes in glucose metabolism contribute to improved glucose-stimulated insulin secretion with age. Together, our study provides an in-depth characterization of age-related changes in the islet proteome and establishes metabolic rewiring as an important mechanism for age-associated changes in ß cell function.

Interrogating islets in health and disease with single-cell technologies.

BACKGROUND: Blood glucose levels are tightly controlled by the coordinated actions of hormone-producing endocrine cells that reside in pancreatic islets. Islet cell malfunction underlies diabetes development and progression. Due to the cellular heterogeneity within islets, it has been challenging to uncover how specific islet cells contribute to glucose homeostasis and diabetes pathogenesis. Recent advances in single-cell technologies and computational methods have opened up new avenues to resolve islet heterogeneity and study islet cell states in health and disease. SCOPE OF REVIEW: In the past year, a multitude of studies have been published that used single-cell approaches to interrogate the transcriptome and proteome of the different islet cell types. Here, we summarize the conclusions of these studies, as well as discuss the technologies used and the challenges faced with computational analysis of single-cell data from islet studies. MAJOR CONCLUSIONS: By analyzing single islet cells from rodents and humans at different ages and disease states, the studies reviewed here have provided new insight into endocrine cell function and facilitated a high resolution molecular characterization of poorly understood processes, including regeneration, maturation, and diabetes pathogenesis. Gene expression programs and pathways identified in these studies pave the way for the discovery of new targets and approaches to prevent, monitor, and treat diabetes.

Met-Activating Genetically Improved Chimeric Factor-1 Promotes Angiogenesis and Hypertrophy in Adult Myogenesis.

BACKGROUND: Myogenic progenitor cells (activated satellite cells) are able to express both HGF and its receptor cMet. After muscle injury, HGF-Met stimulation promotes activation and primary division of satellite cells. MAGIC-F1 (Met-Activating Genetically Improved Chimeric Factor-1) is an engineered protein that contains two human Met-binding domains that promotes muscle hypertrophy. MAGIC-F1 protects myogenic precursors against apoptosis and increases their fusion ability enhancing muscle differentiation. Hemizygous and homozygous Magic-F1 transgenic mice displayed constitutive muscle hypertrophy. METHODS: Here we describe microarray analysis on Magic-F1 myogenic progenitor cells showing an altered gene signatures on muscular hypertrophy and angiogenesis compared to wild-type cells. In addition, we performed a functional analysis on Magic-F1+/+ transgenic mice versus controls using treadmill test. RESULTS: We demonstrated that Magic-F1+/+ mice display an increase in muscle mass and cross-sectional area leading to an improvement in running performance. Moreover, the presence of MAGIC-F1 affected positively the vascular network, increasing the vessel number in fast twitch fibers. Finally, the gene expression profile analysis of Magic-F1+/+ satellite cells evidenced transcriptomic changes in genes involved in the control of muscle growth, development and vascularisation. CONCLUSION: We showed that MAGIC-F1-induced muscle hypertrophy affects positively vascular network, increasing vessel number in fast twitch fibers. This was due to unique features of mammalian skeletal muscle and its remarkable ability to adapt promptly to different physiological demands by modulating the gene expression profile in myogenic progenitors.

Pseudotemporal Ordering of Single Cells Reveals Metabolic Control of Postnatal ß Cell Proliferation.

Pancreatic ß cell mass for appropriate blood glucose control is established during early postnatal life. ß cell proliferative capacity declines postnatally, but the extrinsic cues and intracellular signals that cause this decline remain unknown. To obtain a high-resolution map of ß cell transcriptome dynamics after birth, we generated single-cell RNA-seq data of ß cells from multiple postnatal time points and ordered cells based on transcriptional similarity using a new analytical tool. This analysis captured signatures of immature, proliferative ß cells and established high expression of amino acid metabolic, mitochondrial, and Srf/Jun/Fos transcription factor genes as their hallmark feature. Experimental validation revealed high metabolic activity in immature ß cells and a role for reactive oxygen species and Srf/Jun/Fos transcription factors in driving postnatal ß cell proliferation and mass expansion. Our work provides the first high-resolution molecular characterization of state changes in postnatal ß cells and paves the way for the identification of novel therapeutic targets to stimulate ß cell regeneration.