Differential sensitivity to longitudinal and transverse stretch mediates transcriptional responses in mouse neonatal ventricular myocytes.

To identify how cardiomyocyte mechanosensitive signaling pathways are regulated by anisotropic stretch, micropatterned mouse neonatal cardiomyocytes were stretched primarily longitudinally or transversely to the myofiber axis. Four hours of static, longitudinal stretch induced differential expression of 557 genes, compared with 30 induced by transverse stretch, measured using RNA-seq. A logic-based ordinary differential equation model of the cardiac myocyte mechanosignaling network, extended to include the transcriptional regulation and expression of 784 genes, correctly predicted measured expression changes due to anisotropic stretch with 69% accuracy. The model also predicted published transcriptional responses to mechanical load in vitro or in vivo with 63-91% accuracy. The observed differences between transverse and longitudinal stretch responses were not explained by differential activation of specific pathways but rather by an approximately twofold greater sensitivity to longitudinal stretch than transverse stretch. In vitro experiments confirmed model predictions that stretch-induced gene expression is more sensitive to angiotensin II and endothelin-1, via RhoA and MAP kinases, than to the three membrane ion channels upstream of calcium signaling in the network. Quantitative cardiomyocyte gene expression differs substantially with the axis of maximum principal stretch relative to the myofilament axis, but this difference is due primarily to differences in stretch sensitivity rather than to selective activation of mechanosignaling pathways.NEW & NOTEWORTHY Anisotropic stretch applied to micropatterned neonatal mouse ventricular myocytes induced markedly greater acute transcriptional responses when the major axis of stretch was parallel to the myofilament axis than when it was transverse. Analysis with a novel quantitative network model of mechanoregulated cardiomyocyte gene expression suggests that this difference is explained by higher cell sensitivity to longitudinal loading than transverse loading than by the activation of differential signaling pathways.

Substrate Stiffness and Stretch Regulate Profibrotic Mechanosignaling in Pulmonary Arterial Adventitial Fibroblasts.

Pulmonary arterial adventitial fibroblasts (PAAFs) are important regulators of fibrotic vascular remodeling during the progression of pulmonary arterial hypertension (PAH), a disease that currently has no effective anti-fibrotic treatments. We conducted in-vitro experiments in PAAFs cultured on hydrogels attached to custom-made equibiaxial stretchers at 10% stretch and substrate stiffnesses representing the mechanical conditions of mild and severe stages of PAH. The expression of collagens α(1)I and α(1)III and elastin messenger RNAs (Col1a1, Col3a1, Eln) were upregulated by increased stretch and substrate stiffness, while lysyl oxidase-like 1 and α-smooth muscle actin messenger RNAs (Loxl1, Acta2) were only significantly upregulated when the cells were grown on matrices with an elevated stiffness representative of mild PAH but not on a stiffness representative of severe PAH. Fibronectin messenger RNA (Fn1) levels were significantly induced by increased substrate stiffness and transiently upregulated by stretch at 4 h, but was not significantly altered by stretch at 24 h. We modified our published computational network model of the signaling pathways that regulate profibrotic gene expression in PAAFs to allow for differential regulation of mechanically-sensitive nodes by stretch and stiffness. When the model was modified so that stiffness activated integrin ß3, the Macrophage Stimulating 1 or 2 (MST1\2) kinases, angiotensin II (Ang II), transforming growth factor-ß (TGF-ß), and syndecan-4, and stretch-regulated integrin ß3, MST1\2, Ang II, and the transient receptor potential (TRP) channel, the model correctly predicted the upregulation of all six genes by increased stiffness and the observed responses to stretch in five out of six genes, although it could not replicate the non-monotonic effects of stiffness on Loxl1 and Acta2 expression. Blocking Ang II Receptor Type 1 (AT1R) with losartan in-vitro uncovered an interaction between the effects of stretch and stiffness and angiotensin-independent activation of Fn1 expression by stretch in PAAFs grown on 3-kPa matrices. This novel combination of in-vitro and in-silico models of PAAF profibrotic cell signaling in response to altered mechanical conditions may help identify regulators of vascular adventitial remodeling due to changes in stretch and matrix stiffness that occur during the progression of PAH in-vivo.

Transcriptomic analysis identifies a role of PI3K-Akt signalling in the responses of skeletal muscle to acute hypoxia in vivo.

KEY POINTS: Changes in gene expression that occur within hours of exposure to hypoxia in in vivo skeletal muscles remain unexplored. Two hours of hypoxia caused significant down-regulation of extracellular matrix genes followed by a shift at 6 h to altered expression of genes associated with the nuclear lumen while respiratory and blood gases were stabilized. Enrichment analysis of mRNAs classified by stability rates suggests an attenuation of post-transcriptional regulation within hours of hypoxic exposure, where PI3K-Akt signalling was suggested to have a nodal role by pathway analysis. Experimental measurements and bioinformatic analyses suggested that the dephosphorylation of Akt after 2 h of hypoxic exposure might deactivate RNA-binding protein BRF1, hence resulting in the selective degradation of mRNAs. ABSTRACT: The effects of acute hypoxia have been widely studied, but there are few studies of transcriptional responses to hours of hypoxia in vivo, especially in hypoxia-tolerant tissues like skeletal muscles. We used RNA-seq to analyse gene expression in plantaris muscles while monitoring respiration, arterial blood gases, and blood glucose in mice exposed to 8% O2 for 2 or 6 h. Rapid decreases in blood gases and a slower reduction in blood glucose suggest stress, which was accompanied by widespread changes in gene expression. Early down-regulation of genes associated with the extracellular matrix was followed by a shift to genes associated with the nuclear lumen. Most of the early down-regulated genes had mRNA half-lives longer than 2 h, suggesting a role for post-transcriptional regulation. These transcriptional changes were enriched in signalling pathways in which the PI3K-Akt signalling pathway was identified as a hub. Our analyses indicated that gene targets of PI3K-Akt but not HIF were enriched in early transcriptional responses to hypoxia. Among the PI3K-Akt targets, 75% could be explained by a deactivation of adenylate-uridylate-rich element (ARE)-binding protein BRF1, a target of PI3K-Akt. Consistent decreases in the phosphorylation of Akt and BRF1 were experimentally confirmed following 2 h of hypoxia. These results suggest that the PI3K-Akt signalling pathway might play a role in responses induced by acute hypoxia in skeletal muscles, partially through the dephosphorylation of ARE-binding protein BRF1.

A Protocol to Collect Specific Mouse Skeletal Muscles for Metabolomics Studies.

Due to the highly sensitive nature of metabolic states, the quality of metabolomics data depends on the suitability of the experimental procedure. Metabolism could be affected by factors such as the method of euthanasia of the animals and the sample collection procedures. The effects of these factors on metabolites are tissue-specific. Thus, it is important to select proper methods to sacrifice the animal and appropriate procedures for collecting samples specific to the tissue of interest. Here, we present our protocol to collect specific mouse skeletal muscles with different fiber types for metabolomics studies. We also provide a protocol to measure lactate levels in tissue samples as a way to estimate the metabolic state in collected samples.

MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data.

BACKGROUND: Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. RESULTS: We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila.MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. CONCLUSIONS: MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons.

Using Kepler for Tool Integration in Microarray Analysis Workflows.

Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines.