Toll-like receptor 4 (TLR4) expression in human and murine pancreatic beta-cells affects cell viability and insulin homeostasis

<p>Abstract</p> <p>Background</p> <p>Toll-like receptor 4 (TLR4) is widely recognized as an essential element in the triggering of innate immunity, binding pathogen-associated molecules such as Lipopolysaccharide (LPS), and in initiating a cascade of pro-inflammatory events. Evidence for TLR4 expression in non-immune cells, including pancreatic β-cells, has been shown, but, the functional role of TLR4 in the physiology of human pancreatic β-cells is still to be clearly established. We investigated whether TLR4 is present in β-cells purified from freshly isolated human islets and confirmed the results using MIN6 mouse insulinoma cells, by analyzing the effects of TLR4 expression on cell viability and insulin homeostasis.</p> <p>Results</p> <p>CD11b positive macrophages were practically absent from isolated human islets obtained from non-diabetic brain-dead donors, and TLR4 mRNA and cell surface expression were restricted to β-cells. A significant loss of cell viability was observed in these β-cells indicating a possible relationship with TLR4 expression. Monitoring gene expression in β-cells exposed for 48h to the prototypical TLR4 ligand LPS showed a concentration-dependent increase in TLR4 and CD14 transcripts and decreased insulin content and secretion. TLR4-positive MIN6 cells were also LPS-responsive, increasing TLR4 and CD14 mRNA levels and decreasing cell viability and insulin content.</p> <p>Conclusions</p> <p>Taken together, our data indicate a novel function for TLR4 as a molecule capable of altering homeostasis of pancreatic β-cells.</p

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Abstract\ud \ud \ud \ud Background\ud \ud Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills.\ud \ud \ud \ud Results\ud \ud Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al.\ud \ud \ud \ud Conclusion\ud \ud GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.This research was supported by FAPESP, CAPES, CNPq, FINEP and PRP-USP.This research was supported by FAPESP, CAPES, CNPq, FINEP and PRPUSP

Modeling gene expression regulatory networks with the sparse vector autoregressive model

<p>Abstract</p> <p>Background</p> <p>To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems.</p> <p>Results</p> <p>We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets.</p> <p>Conclusion</p> <p>The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any <it>a priori </it>information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.</p

Androgen responsive intronic non-coding RNAs

BACKGROUND: Transcription of large numbers of non-coding RNAs originating from intronic regions of human genes has been recently reported, but mechanisms governing their biosynthesis and biological functions are largely unknown. In this work, we evaluated the existence of a common mechanism of transcription regulation shared by protein-coding mRNAs and intronic RNAs by measuring the effect of androgen on the transcriptional profile of a prostate cancer cell line. RESULTS: Using a custom-built cDNA microarray enriched in intronic transcribed sequences, we found 39 intronic non-coding RNAs for which levels were significantly regulated by androgen exposure. Orientation-specific reverse transcription-PCR indicated that 10 of the 13 were transcribed in the antisense direction. These transcripts are long (0.5–5 kb), unspliced and apparently do not code for proteins. Interestingly, we found that the relative levels of androgen-regulated intronic transcripts could be correlated with the levels of the corresponding protein-coding gene (asGAS6 and asDNAJC3) or with the alternative usage of exons (asKDELR2 and asITGA6) in the corresponding protein-coding transcripts. Binding of the androgen receptor to a putative regulatory region upstream from asMYO5A, an androgen-regulated antisense intronic transcript, was confirmed by chromatin immunoprecipitation. CONCLUSION: Altogether, these results indicate that at least a fraction of naturally transcribed intronic non-coding RNAs may be regulated by common physiological signals such as hormones, and further corroborate the notion that the intronic complement of the transcriptome play functional roles in the human gene-expression program

Generation and characterization of human insulin-releasing cell lines

<p>Abstract</p> <p>Background</p> <p>The in vitro culture of insulinomas provides an attractive tool to study cell proliferation and insulin synthesis and secretion. However, only a few human beta cell lines have been described, with long-term passage resulting in loss of insulin secretion. Therefore, we set out to establish and characterize human insulin-releasing cell lines.</p> <p>Results</p> <p>We generated ex-vivo primary cultures from two independent human insulinomas and from a human nesidioblastosis, all of which were cultured up to passage number 20. All cell lines secreted human insulin and C-peptide. These cell lines expressed neuroendocrine and islets markers, confirming the expression profile found in the biopsies. Although all beta cell lineages survived an anchorage independent culture, none of them were able to invade an extracellular matrix substrate.</p> <p>Conclusion</p> <p>We have established three human insulin-releasing cell lines which maintain antigenic characteristics and insulin secretion profiles of the original tumors. These cell lines represent valuable tools for the study of molecular events underlying beta cell function and dysfunction.</p

RECK is not an independent prognostic marker for breast cancer

Abstract\ud \ud Background\ud The REversion-inducing Cysteine-rich protein with Kazal motif (RECK) is a well-known inhibitor of matrix metalloproteinases (MMPs) and cellular invasion. Although high expression levels of RECK have already been correlated with a better clinical outcome for several tumor types, its main function, as well as its potential prognostic value for breast cancer patients, remain unclear.\ud \ud \ud Methods\ud The RECK expression profile was investigated in a panel of human breast cell lines with distinct aggressiveness potential. RECK functional analysis was undertaken using RNA interference methodology. RECK protein levels were also analyzed in 1040 cases of breast cancer using immunohistochemistry and tissue microarrays (TMAs). The association between RECK expression and different clinico-pathological parameters, as well as the overall (OS) and disease-free (DFS) survival rates, were evaluated.\ud \ud \ud Results\ud Higher RECK protein expression levels were detected in more aggressive breast cancer cell lines (T4-2, MDA-MB-231 and Hs578T) than in non-invasive (MCF-7 and T47D) and non-tumorigenic (S1) cell lines. Indeed, silencing RECK in MDA-MB-231 cells resulted in elevated levels of pro-MMP-9 and increased invasion compared with scrambled (control) cells, without any effect on cell proliferation. Surprisingly, by RECK immunoreactivity analysis on TMAs, we found no association between RECK positivity and survival (OS and DFS) in breast cancer patients. Even considering the different tumor subtypes (luminal A, luminal B, Her2 type and basal-like) or lymph node status, RECK remained ineffective for predicting the disease outcome. Moreover, by multivariate Cox regression analysis, we found that RECK has no prognostic impact for OS and DFS, relative to standard clinical variables.\ud \ud \ud Conclusions\ud Although it continues to serve as an invasion and MMP inhibitor in breast cancer, RECK expression analysis is not useful for prognosis of these patients.Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Pesquisa (CNPq)Financiadora de Estudos e Projetos (FINEP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Banco Nacional de Desenvolvimento Social e Econômico (BNDES – FUNTEC)Departamento de Ciência e Tecnologia em Saúde - Ministério da Saúde (DECIT-MS) and Ministério da Ciência, Tecnologia e Inovação (MCTI)

Cloning and characterization of a novel alternatively spliced transcript of the human CHD7 putative helicase

<p>Abstract</p> <p>Background</p> <p>The <it>CHD7 </it>(Chromodomain Helicase DNA binding protein 7) gene encodes a member of the chromodomain family of ATP-dependent chromatin remodeling enzymes. Mutations in the <it>CHD7 </it>gene are found in individuals with CHARGE, a syndrome characterized by multiple birth malformations in several tissues. CHD7 was identified as a binding partner of PBAF complex (Polybromo and BRG Associated Factor containing complex) playing a central role in the transcriptional reprogramming process associated to the formation of multipotent migratory neural crest, a transient cell population associated with the genesis of various tissues. <it>CHD7 </it>is a large gene containing 38 annotated exons and spanning 200 kb of genomic sequence. Although genes containing such number of exons are expected to have several alternative transcripts, there are very few evidences of alternative transcripts associated to <it>CHD7 </it>to date indicating that alternative splicing associated to this gene is poorly characterized.</p> <p>Findings</p> <p>Here, we report the cloning and characterization by experimental and computational studies of a novel alternative transcript of the human <it>CHD7 </it>(named CHD7 CRA_e), which lacks most of its coding exons. We confirmed by overexpression of CHD7 CRA_e alternative transcript that it is translated into a protein isoform lacking most of the domains displayed by the canonical isoform. Expression of the CHD7 CRA_e transcript was detected in normal liver, in addition to the DU145 human prostate carcinoma cell line from which it was originally isolated.</p> <p>Conclusions</p> <p>Our findings indicate that the splicing event associated to the CHD7 CRA_e alternative transcript is functional. The characterization of the CHD7 CRA_e novel isoform presented here not only sets the basis for more detailed functional studies of this isoform, but, also, contributes to the alternative splicing annotation of the <it>CHD7 </it>gene and the design of future functional studies aimed at the elucidation of the molecular functions of its gene products.</p

Correlation between MMPs and their inhibitors in breast cancer tumor tissue specimens and in cell lines with different metastatic potential

Background: The metastatic disease rather than the primary tumor itself is responsible for death in most solid tumors, including breast cancer. The role of matrix metalloproteinases ( MMPs), tissue inhibitors of MMPs (TIMPs) and Reversion-inducing cysteine-rich protein with Kazal motifs ( RECK) in the metastatic process has previously been established. However, in all published studies only a limited number of MMPs/MMP inhibitors was analyzed in a limited number of cell lines. Here, we propose a more comprehensive approach by analyzing the expression levels of several MMPs (MMP-2, MMP-9 and MMP-14) and MMP inhibitors (TIMP-1, TIMP-2 and RECK) in different models ( five human breast cancer cell lines, 72 primary breast tumors and 30 adjacent normal tissues). Methods: We analyzed the expression levels of MMP-2, MMP-9 and MMP-14 and their inhibitors (TIMP-1, TIMP-2 and RECK) by quantitative RT-PCR (qRT-PCR) in five human breast cancer cell lines presenting increased invasiveness and metastatic potential, 72 primary breast tumors and 30 adjacent normal tissues. Moreover, the role of cell-extracellular matrix elements interactions in the regulation of expression and activity of MMPs and their inhibitors was analyzed by culturing these cell lines on plastic or on artificial ECM (Matrigel). Results: The results demonstrated that MMPs mRNA expression levels displayed a positive and statistically significant correlation with the transcriptional expression levels of their inhibitors both in the cell line models and in the tumor tissue samples. Furthermore, the expression of all MMP inhibitors was modulated by cell-Matrigel contact only in highly invasive and metastatic cell lines. The enzyme/inhibitor balance at the transcriptional level significantly favors the enzyme which is more evident in tumor than in adjacent non-tumor tissue samples. Conclusion: Our results suggest that the expression of MMPs and their inhibitors, at least at the transcriptional level, might be regulated by common factors and signaling pathways. Therefore, the multi-factorial analysis of these molecules could provide new and independent prognostic information contributing to the determination of more adequate therapy strategies for each patient.`Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Conselho Nacional de Pesquisa (CNPq)Financiadora de Estudos e Projetos (FINEP)Pro-Reitoria da Universidade de Sao Paulo (PRP-USP

TGF-β1 modulates the homeostasis between MMPs and MMP inhibitors through p38 MAPK and ERK1/2 in highly invasive breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Metastasis is the main factor responsible for death in breast cancer patients. Matrix metalloproteinases (MMPs) and their inhibitors, known as tissue inhibitors of MMPs (TIMPs), and the membrane-associated MMP inhibitor (RECK), are essential for the metastatic process. We have previously shown a positive correlation between MMPs and their inhibitors expression during breast cancer progression; however, the molecular mechanisms underlying this coordinate regulation remain unknown. In this report, we investigated whether TGF-β1 could be a common regulator for MMPs, TIMPs and RECK in human breast cancer cell models.</p> <p>Methods</p> <p>The mRNA expression levels of TGF-β isoforms and their receptors were analyzed by qRT-PCR in a panel of five human breast cancer cell lines displaying different degrees of invasiveness and metastatic potential. The highly invasive MDA-MB-231 cell line was treated with different concentrations of recombinant TGF-β1 and also with pharmacological inhibitors of p38 MAPK and ERK1/2. The migratory and invasive potential of these treated cells were examined in vitro by transwell assays.</p> <p>Results</p> <p>In general, TGF-β2, TβRI and TβRII are over-expressed in more aggressive cells, except for TβRI, which was also highly expressed in ZR-75-1 cells. In addition, TGF-β1-treated MDA-MB-231 cells presented significantly increased mRNA expression of MMP-2, MMP-9, MMP-14, TIMP-2 and RECK. TGF-β1 also increased TIMP-2, MMP-2 and MMP-9 protein levels but downregulated RECK expression. Furthermore, we analyzed the involvement of p38 MAPK and ERK1/2, representing two well established Smad-independent pathways, in the proposed mechanism. Inhibition of p38MAPK blocked TGF-β1-increased mRNA expression of all MMPs and MMP inhibitors analyzed, and prevented TGF-β1 upregulation of TIMP-2 and MMP-2 proteins. Moreover, ERK1/2 inhibition increased RECK and prevented the TGF-β1 induction of pro-MMP-9 and TIMP-2 proteins. TGF-β1-enhanced migration and invasion capacities were blocked by p38MAPK, ERK1/2 and MMP inhibitors.</p> <p>Conclusion</p> <p>Altogether, our results support that TGF-β1 modulates the mRNA and protein levels of MMPs (MMP-2 and MMP-9) as much as their inhibitors (TIMP-2 and RECK). Therefore, this cytokine plays a crucial role in breast cancer progression by modulating key elements of ECM homeostasis control. Thus, although the complexity of this signaling network, TGF-β1 still remains a promising target for breast cancer treatment.</p

Unveiling novel genes upregulated by both rhBMP2 and rhBMP7 during early osteoblastic transdifferentiation of C2C12 cells

<p>Abstract</p> <p>Findings</p> <p>We set out to analyse the gene expression profile of pre-osteoblastic C2C12 cells during osteodifferentiation induced by both rhBMP2 and rhBMP7 using DNA microarrays. Induced and repressed genes were intercepted, resulting in 1,318 induced genes and 704 repressed genes by both rhBMP2 and rhBMP7. We selected and validated, by RT-qPCR, 24 genes which were upregulated by rhBMP2 and rhBMP7; of these, 13 are related to transcription (<it>Runx2, Dlx1, Dlx2, Dlx5, Id1, Id2, Id3, Fkhr1, Osx, Hoxc8, Glis1, Glis3 </it>and <it>Cfdp1</it>), four are associated with cell signalling pathways (<it>Lrp6, Dvl1, Ecsit </it>and <it>PKCδ</it>) and seven are associated with the extracellular matrix (<it>Ltbp2, Grn, Postn, Plod1, BMP1, Htra1 </it>and <it>IGFBP-rP10</it>). The novel identified genes include: <it>Hoxc8, Glis1, Glis3, Ecsit, PKCδ, LrP6, Dvl1, Grn, BMP1, Ltbp2, Plod1, Htra1 </it>and <it>IGFBP-rP10</it>.</p> <p>Background</p> <p>BMPs (bone morphogenetic proteins) are members of the TGFβ (transforming growth factor-β) super-family of proteins, which regulate growth and differentiation of different cell types in various tissues, and play a critical role in the differentiation of mesenchymal cells into osteoblasts. In particular, rhBMP2 and rhBMP7 promote osteoinduction <it>in vitro </it>and <it>in vivo</it>, and both proteins are therapeutically applied in orthopaedics and dentistry.</p> <p>Conclusion</p> <p>Using DNA microarrays and RT-qPCR, we identified both previously known and novel genes which are upregulated by rhBMP2 and rhBMP7 during the onset of osteoblastic transdifferentiation of pre-myoblastic C2C12 cells. Subsequent studies of these genes in C2C12 and mesenchymal or pre-osteoblastic cells should reveal more details about their role during this type of cellular differentiation induced by BMP2 or BMP7. These studies are relevant to better understanding the molecular mechanisms underlying osteoblastic differentiation and bone repair.</p