Expression of bone morphogenetic protein 4 and its receptors in the remodeling heart

Aims

Heart failure is associated with activation of fetal gene programs. Bone morphogenetic proteins (BMPs) regulate embryonic development through interaction with BMP receptors (BMPRs) on the cell surface. We investigated if the expression of BMP4 and its receptors BMPR1a and BMPR2 were activated in post-infarction remodeling and heart failure.

Main methods

Left ventricular biopsies were taken from explanted hearts of patients with end-stage heart failure due to dilated cardiomyopathy (CMP; n = 15) or ischemic heart disease (CAD; n = 9), and compared with homograft control preparations from organ donors deceased due to non-cardiac causes (n = 7). Other samples were taken from patients undergoing coronary artery bypass grafting (CABG; n = 11). Mice were subjected to induced infarction by permanent coronary artery ligation or sham operation, and hearts were sampled serially thereafter (n = 7 at each time point).

Key findings

Human and mouse hearts expressed BMP4 and both receptor subtypes. CABG and CMP patients had increased expression of mRNA encoding for BMP4, but unchanged protein. Mouse hearts had increased BMP4 precursor protein 24 h after infarction. BMPR1a protein decreased in CAD patients and initially in postinfarcted mouse hearts, but increased again in the latter after two weeks. Human recombinant BMP4 promoted survival after H₂O₂ injury in HL-1 cells, and also protected adult mouse cardiomyocytes against hypoxia–reoxygenation injury.

Significance

Adult hearts express BMP4, the mRNA increasingly so in patients with coronary artery disease with good cardiac function. BMPRs are downregulated in cardiac remodeling and failure. Recombinant BMP4 has protective effects on cultured cardiomyocytes.     

Microarray analysis reveals a potential role of LncRNAs expression in cardiac cell proliferation

Background

Long non-coding RNAs (LncRNAs) have been identified to play important roles in epigenetic processes that underpin organogenesis. However, the role of LncRNAs in the regulation of transition from fetal to adult life of human heart has not been evaluated.

Methods

Immunofiuorescent staining was used to determine the extent of cardiac cell proliferation. Human LncRNA microarrays were applied to define gene expression signatures of the fetal (13–17 weeks of gestation, n?=?4) and adult hearts (30–40 years old, n?=?4). Pathway analysis was performed to predict the function of differentially expressed mRNAs (DEM). DEM related to cell proliferation were selected to construct a lncRNA-mRNA co-expression network. Eight lncRNAs were confirmed by quantificational real-time polymerase chain reaction (n?=?6).

Results

Cardiac cell proliferation was significant in the fetal heart. Two thousand six hundred six lncRNAs and 3079 mRNAs were found to be differentially expressed. Cell cycle was the most enriched pathway in down-regulated genes in the adult heart. Eight lncRNAs (RP11-119 F7.5, AX747860, HBBP1, LINC00304, TPTE2P6, AC034193.5, XLOC_006934 and AL833346) were predicted to play a central role in cardiac cell proliferation.

Conclusions

We discovered a profile of lncRNAs differentially expressed between the human fetal and adult heart. Several meaningful lncRNAs involved in cardiac cell proliferation were disclosed.

     

Microarray expression profiling in the denervated hippocampus identifies long noncoding RNAs functionally involved in neurogenesis

Background

The denervated hippocampus provides a proper microenvironment for the survival and neuronal differentiation of neural progenitors. While thousands of lncRNAs were identified, only a few lncRNAs that regulate neurogenesis in the hippocampus are reported. The present study aimed to perform microarray expression profiling to identify long noncoding RNAs (lncRNAs) that might participate in the hippocampal neurogenesis, and investigate the potential roles of identified lncRNAs in the hippocampal neurogenesis.

Results

In this study, the profiling suggested that 74 activated and 29 repressed (|log fold-change|>1.5) lncRNAs were differentially expressed between the denervated and the normal hippocampi. Furthermore, differentially expressed lncRNAs associated with neurogenesis were found. According to the tissue-specific expression profiles, and a novel lncRNA (lncRNA2393) was identified as a neural regulator in the hippocampus in this study. The expression of lncRNA2393 was activated in the denervated hippocampus. FISH showed lncRNA2393 specially existed in the subgranular zone of the dentate gyrus in the hippocampus and in the cytoplasm of neural stem cells (NSCs). The knockdown of lncRNA2393 depletes the EdU-positive NSCs. Besides, the increased expression of lncRNA2393 was found to be triggered by the change in the microenvironment.

Conclusion

We concluded that expression changes of lncRNAs exists in the microenvironment of denervated hippocampus, of which promotes hippocampal neurogenesis. The identified lncRNA lncRNA2393 expressed in neural stem cells, located in the subgranular zone of the dentate gyrus, which can promote NSCs proliferation in vitro. Therefore, the question is exactly which part of the denervated hippocampus induced the expression of lncRNA2393. Further studies should aim to explore the exact molecular mechanism behind the expression of lncRNA2393 in the hippocampus, to lay the foundation for the clinical application of NSCs in treating diseases of the central nervous system.

     

A Low-Dose β1-Blocker in Combination with Milrinone Improves Intracellular Ca2+ Handling in Failing Cardiomyocytes by Inhibition of Milrinone-Induced Diastolic Ca2+ Leakage from the Sarcoplasmic Reticulum

Objectives

The purpose of this study was to investigate whether adding a low-dose β1-blocker to milrinone improves cardiac function in failing cardiomyocytes and the underlying cardioprotective mechanism.

Background

The molecular mechanism underlying how the combination of low-dose β1-blocker and milrinone affects intracellular Ca²⁺ handling in heart failure remains unclear.

Methods

We investigated the effect of milrinone plus landiolol on intracellular Ca²⁺ transient (CaT), cell shortening (CS), the frequency of diastolic Ca²⁺ sparks (CaSF), and sarcoplasmic reticulum Ca²⁺ concentration ({Ca²⁺}_SR) in normal and failing canine cardiomyocytes and used immunoblotting to determine the phosphorylation level of ryanodine receptor (RyR2) and phospholamban (PLB).

Results

In failing cardiomyocytes, CaSF significantly increased, and peak CaT and CS markedly decreased compared with normal myocytes. Administration of milrinone alone slightly increased peak CaT and CS, while CaSF greatly increased with a slight increase in {Ca²⁺}_SR. Co-administration of β1-blocker landiolol to failing cardiomyocytes at a dose that does not inhibit cardiomyocyte function significantly decreased CaSF with a further increase in {Ca²⁺}_SR, and peak CaT and CS improved compared with milrinone alone. Landiolol suppressed the hyperphosphorylation of RyR2 (Ser2808) in failing cardiomyocytes but had no effect on levels of phosphorylated PLB (Ser16 and Thr17). Low-dose landiolol significantly inhibited the alternans of CaT and CS under a fixed pacing rate (0.5 Hz) in failing cardiomyocytes.

Conclusion

A low-dose β1-blocker in combination with milrinone improved cardiac function in failing cardiomyocytes, apparently by inhibiting the phosphorylation of RyR2, not PLB, and subsequent diastolic Ca²⁺ leak.     

Integration of Genome-wide Approaches Identifies lncRNAs of Adult Neural Stem Cells and Their Progeny In Vivo

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Highlights? RNA-seq, RNA Capture-Seq of SVZ-NSCs reveals unannotated lncRNAs and splice variants ? lncRNA loci have dynamic chromatin signatures, including bivalency in SVZ-NSCs ? Online resource facilitates discovery of lncRNAs involved in adult neurogenesis ? lncRNAs can regulate glial-neuronal lineage specification of SVZ-NSCs     

LncRNA OIP5-AS1 regulates radioresistance by targeting DYRK1A through miR-369-3p in colorectal cancer cells

Object

This study aimed to investigate the role of lncRNA OIP5-AS1 in regulating radioresistance of colorectal cancer (CRC) cells.

Sitagliptin Reduces Cardiac Apoptosis,Hypertrophy and Fibrosis Primarily by Insulin-Dependent Mechanisms in Experimental type-II Diabetes. Potential Roles of GLP-1 Isoforms

Background

Myocardial fibrosis is a key process in diabetic cardiomyopathy. However, their underlying mechanisms have not been elucidated, leading to a lack of therapy. The glucagon-like peptide-1 (GLP-1) enhancer, sitagliptin, reduces hyperglycemia but may also trigger direct effects on the heart.

Methods

Goto-Kakizaki (GK) rats developed type-II diabetes and received sitagliptin, an anti-hyperglycemic drug (metformin) or vehicle (n=10, each). After cardiac structure and function assessment, plasma and left ventricles were isolated for biochemical studies. Cultured cardiomyocytes and fibroblasts were used for in vitro assays.

Results

Untreated GK rats exhibited hyperglycemia, hyperlipidemia, plasma GLP-1 decrease, and cardiac cell-death, hypertrophy, fibrosis and prolonged deceleration time. Moreover, cardiac pro-apoptotic/necrotic, hypertrophic and fibrotic factors were up-regulated. Importantly, both sitagliptin and metformin lessened all these parameters. In cultured cardiomyocytes and cardiac fibroblasts, high-concentration of palmitate or glucose induced cell-death, hypertrophy and fibrosis. Interestingly, GLP-1 and its insulinotropic-inactive metabolite, GLP-1(9-36), alleviated these responses. In addition, despite a specific GLP-1 receptor was only detected in cardiomyocytes, GLP-1 isoforms attenuated the pro-fibrotic expression in cardiomyocytes and fibroblasts. In addition, GLP-1 receptor signalling may be linked to PPARδ activation, and metformin may also exhibit anti-apoptotic/necrotic and anti-fibrotic direct effects in cardiac cells.

Conclusions

Sitagliptin, via GLP-1 stabilization, promoted cardioprotection in type-II diabetic hearts primarily by limiting hyperglycemia e hyperlipidemia. However, GLP-1 and GLP-1(9-36) promoted survival and anti-hypertrophic/fibrotic effects on cultured cardiac cells, suggesting cell-autonomous cardioprotective actions.     

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

Background

With the development of sequencing technology, more and more long non-coding RNAs (lncRNAs) have been identified. Some lncRNAs have been confirmed that they play an important role in the process of development through the dosage compensation effect, epigenetic regulation, cell differentiation regulation and other aspects. However, the majority of the lncRNAs have not been functionally characterized. Explore the function of lncRNAs and the regulatory network has become a hot research topic currently.

Methods

In the work, a network-based model named BiRWLGO is developed. The ultimate goal is to predict the probable functions for lncRNAs at large scale. The new model starts with building a global network composed of three networks: lncRNA similarity network, lncRNA-protein association network and protein-protein interaction (PPI) network. After that, it utilizes bi-random walk algorithm to explore the similarities between lncRNAs and proteins. Finally, we can annotate an lncRNA with the Gene Ontology (GO) terms according to its neighboring proteins.

Results

We compare the performance of BiRWLGO with the state-of-the-art models on a manually annotated lncRNA benchmark with known GO terms. The experimental results assert that BiRWLGO outperforms other methods in terms of both maximum F-measure (F_max) and coverage.

Conclusions

BiRWLGO is a relatively efficient method to predict the functions of lncRNA. When protein interaction data is integrated, the predictive performance of BiRWLGO gains a great improvement.

     

CRlncRNA: a manually curated database of cancer-related long non-coding RNAs with experimental proof of functions on clinicopathological and molecular features

Background

Recent studies demonstrated that long non-coding RNAs (lncRNAs) could be intricately implicated in cancer-related molecular networks, and related to cancer occurrence, development and prognosis. However, clinicopathological and molecular features for these cancer-related lncRNAs, which are very important in bridging lncRNA basic research with clinical research, fail to well settle to integration.

Results

After manually reviewing more than 2500 published literature, we collected the cancer-related lncRNAs with the experimental proof of functions. By integrating from literature and public databases, we constructed CRlncRNA, a database of cancer-related lncRNAs. The current version of CRlncRNA embodied 355 entries of cancer-related lncRNAs, covering 1072 cancer-lncRNA associations regarding to 76 types of cancer, and 1238 interactions with different RNAs and proteins. We further annotated clinicopathological features of these lncRNAs, such as the clinical stages and the cancer hallmarks. We also provided tools for data browsing, searching and download, as well as online BLAST, genome browser and gene network visualization service.

Conclusions

CRlncRNA is a manually curated database for retrieving clinicopathological and molecular features of cancer-related lncRNAs supported by highly reliable evidences. CRlncRNA aims to provide a bridge from lncRNA basic research to clinical research. The lncRNA dataset collected by CRlncRNA can be used as a golden standard dataset for the prospective experimental and in-silico studies of cancer-related lncRNAs. CRlncRNA is freely available for all users at http://crlnc.xtbg.ac.cn.

     

Laplacian normalization and bi-random walks on heterogeneous networks for predicting lncRNA-disease associations

Background

Evidences have increasingly indicated that lncRNAs (long non-coding RNAs) are deeply involved in important biological regulation processes leading to various human complex diseases. Experimental investigations of these disease associated lncRNAs are slow with high costs. Computational methods to infer potential associations between lncRNAs and diseases have become an effective prior-pinpointing approach to the experimental verification.

Results

In this study, we develop a novel method for the prediction of lncRNA-disease associations using bi-random walks on a network merging the similarities of lncRNAs and diseases. Particularly, this method applies a Laplacian technique to normalize the lncRNA similarity matrix and the disease similarity matrix before the construction of the lncRNA similarity network and disease similarity network. The two networks are then connected via existing lncRNA-disease associations. After that, bi-random walks are applied on the heterogeneous network to predict the potential associations between the lncRNAs and the diseases. Experimental results demonstrate that the performance of our method is highly comparable to or better than the state-of-the-art methods for predicting lncRNA-disease associations. Our analyses on three cancer data sets (breast cancer, lung cancer, and liver cancer) also indicate the usefulness of our method in practical applications.

Conclusions

Our proposed method, including the construction of the lncRNA similarity network and disease similarity network and the bi-random walks algorithm on the heterogeneous network, could be used for prediction of potential associations between the lncRNAs and the diseases.