The structural and functional characterization of human RecQ4 reveals insights into its helicase mechanism.

RecQ4 is a member of the RecQ helicase family, an evolutionarily conserved class of enzymes, dedicated to preserving genomic integrity by operating in telomere maintenance, DNA repair and replication. While reduced RecQ4 activity is associated with cancer predisposition and premature aging, RecQ4 upregulation is related to carcinogenesis and metastasis. Within the RecQ family, RecQ4 assumes an exceptional position, lacking several characteristic RecQ domains. Here we present the crystal structure of human RecQ4, encompassing the conserved ATPase core and a novel C-terminal domain that lacks resemblance to the RQC domain observed in other RecQ helicases. The new domain features a zinc-binding site and two distinct types of winged-helix domains, which are not involved in canonical DNA binding or helicase activity. Based on our structural and functional analysis, we propose that RecQ4 exerts a helicase mechanism, which may be more closely related to bacterial RecQ helicases than to its human family members.

Quantitative two-dimensional measurement of oil-film thickness by laser-induced fluorescence in a piston-ring model experiment.

This paper describes advances in using laser-induced fluorescence of dyes for imaging the thickness of oil films in a rotating ring tribometer with optical access, an experiment representing a sliding piston ring in an internal combustion engine. A method for quantitative imaging of the oil-film thickness is developed that overcomes the main challenge, the accurate calibration of the detected fluorescence signal for film thicknesses in the micrometer range. The influence of the background material and its surface roughness is examined, and a method for flat-field correction is introduced. Experiments in the tribometer show that the method yields quantitative, physically plausible results, visualizing features with submicrometer thickness.

Integrative Analysis of MicroRNA and mRNA Data Reveals an Orchestrated Function of MicroRNAs in Skeletal Myocyte Differentiation in Response to TNF-α or IGF1.

INTRODUCTION: Skeletal muscle cell differentiation is impaired by elevated levels of the inflammatory cytokine tumor necrosis factor-α (TNF-α) with pathological significance in chronic diseases or inherited muscle disorders. Insulin like growth factor-1 (IGF1) positively regulates muscle cell differentiation. Both, TNF-α and IGF1 affect gene and microRNA (miRNA) expression in this process. However, computational prediction of miRNA-mRNA relations is challenged by false positives and targets which might be irrelevant in the respective cellular transcriptome context. Thus, this study is focused on functional information about miRNA affected target transcripts by integrating miRNA and mRNA expression profiling data. METHODOLOGY/PRINCIPAL FINDINGS: Murine skeletal myocytes PMI28 were differentiated for 24 hours with concomitant TNF-α or IGF1 treatment. Both, mRNA and miRNA expression profiling was performed. The data-driven integration of target prediction and paired mRNA/miRNA expression profiling data revealed that i) the quantity of predicted miRNA-mRNA relations was reduced, ii) miRNA targets with a function in cell cycle and axon guidance were enriched, iii) differential regulation of anti-differentiation miR-155-5p and miR-29b-3p as well as pro-differentiation miR-335-3p, miR-335-5p, miR-322-3p, and miR-322-5p seemed to be of primary importance during skeletal myoblast differentiation compared to the other miRNAs, iv) the abundance of targets and affected biological processes was miRNA specific, and v) subsets of miRNAs may collectively regulate gene expression. CONCLUSIONS: Joint analysis of mRNA and miRNA profiling data increased the process-specificity and quality of predicted relations by statistically selecting miRNA-target interactions. Moreover, this study revealed miRNA-specific predominant biological implications in skeletal muscle cell differentiation and in response to TNF-α or IGF1 treatment. Furthermore, myoblast differentiation-associated miRNAs are suggested to collectively regulate gene clusters and targets associated with enriched specific gene ontology terms or pathways. Predicted miRNA functions of this study provide novel insights into defective regulation at the transcriptomic level during myocyte proliferation and differentiation due to inflammatory stimuli.

TNF-α and IGF1 modify the microRNA signature in skeletal muscle cell differentiation.

BACKGROUND: Elevated levels of the inflammatory cytokine TNF-α are common in chronic diseases or inherited or degenerative muscle disorders and can lead to muscle wasting. By contrast, IGF1 has a growth promoting effect on skeletal muscle. The molecular mechanisms mediating the effect of TNF-α and IGF1 on muscle cell differentiation are not completely understood. Muscle cell proliferation and differentiation are regulated by microRNAs (miRNAs) which play a dominant role in this process. This study aims at elucidating how TNF-α or IGF1 regulate microRNA expression to affect myoblast differentiation and myotube formation. RESULTS: In this study, we analyzed the impact of TNF-α or IGF1 treatment on miRNA expression in myogenic cells. Results reveal that i) TNF-α and IGF1 regulate miRNA expression during skeletal muscle cell differentiation in vitro, ii) microRNA targets can mediate the negative effect of TNF-α on fusion capacity of skeletal myoblasts by targeting genes associated with axon guidance, MAPK signalling, focal adhesion, and neurotrophin signalling pathway, iii) inhibition of miR-155 in combination with overexpression of miR-503 partially abrogates the inhibitory effect of TNF-α on myotube formation, and iv) MAPK/ERK inhibition might participate in modulating the effect of TNF-α and IGF1 on miRNA abundance. CONCLUSIONS: The inhibitory effects of TNF-α or the growth promoting effects of IGF1 on skeletal muscle differentiation include the deregulation of known muscle-regulatory miRNAs as well as miRNAs which have not yet been associated with skeletal muscle differentiation or response to TNF-α or IGF1. This study indicates that miRNAs are mediators of the inhibitory effect of TNF-α on myoblast differentiation. We show that intervention at the miRNA level can ameliorate the negative effect of TNF-α by promoting myoblast differentiation. Moreover, we cautiously suggest that TNF-α or IGF1 modulate the miRNA biogenesis of some miRNAs via MAPK/ERK signalling. Finally, this study identifies indicative biomarkers of myoblast differentiation and cytokine influence and points to novel RNA targets.

Inhibition of neogenin dampens hepatic ischemia-reperfusion injury.

OBJECTIVE: Liver ischemia and reperfusion injury is a common source of significant morbidity and mortality following liver transplantation, hemorrhagic shock, or major hepatic surgery. Based on studies showing a critical role for the neuronal guidance receptor neogenin (Neo1) outside the nervous system in mediating tissue adaption during acute inflammation, we hypothesized that Neo1 enhances hepatic ischemia and reperfusion injury. DESIGN: Animal study. SETTING: University-based experimental laboratory. SUBJECTS: Wid-type, neogenin deficient and chimeric mice. INTERVENTIONS: Neogenin expression was evaluated during inflammatory stimulation in vitro and during ischemia and reperfusion injury in vivo, intravital microscopy performed to study intravascular flow characteristics. The extent of liver injury was evaluated using histology, serum levels of lactate dehydrogenase, aspartate, and alanine aminotransferase. The functional role of Neo1 during liver IR was evaluated in mice with gene targeted repression of neogenin (Neo1-/-), bone marrow chimeric animals and controls. In addition, functional inhibition of neogenin was performed using antibody injection. MEASUREMENTS AND MAIN RESULTS: We observed an induction of Neo1 during inflammation in vitro and ischemia and reperfusion in vivo. Intravital microscopy demonstrated a decreased ability of Neo1 leukocytes to attach to endothelial vascular wall during inflammation. Subsequent studies in Neo1 mice showed attenuated serum levels of lactate dehydrogenase, aspartate, alanine, and proinflammatory cytokines during hepatic ischemia and reperfusion injury. This was associated with improved hepatic histology scores. Studies in chimeric animals demonstrated that the hematopoietic Neo1 expression to be crucial for the observed results. Treatment with an anti-Neo1 antibody resulted in a significant reduction of experimental hepatic ischemia and reperfusion injury, involving attenuated variable of lactate dehydrogenase, alanine, aspartate, and cytokine levels. CONCLUSIONS: These data provide a unique role for Neo1 in the development of hepatic ischemia and reperfusion injury and identified Neo1 as a potential target to prevent liver dysfunction in the future.

Profound effect of profiling platform and normalization strategy on detection of differentially expressed microRNAs--a comparative study.

BACKGROUND: Adequate normalization minimizes the effects of systematic technical variations and is a prerequisite for getting meaningful biological changes. However, there is inconsistency about miRNA normalization performances and recommendations. Thus, we investigated the impact of seven different normalization methods (reference gene index, global geometric mean, quantile, invariant selection, loess, loessM, and generalized procrustes analysis) on intra- and inter-platform performance of two distinct and commonly used miRNA profiling platforms. METHODOLOGY/PRINCIPAL FINDINGS: We included data from miRNA profiling analyses derived from a hybridization-based platform (Agilent Technologies) and an RT-qPCR platform (Applied Biosystems). Furthermore, we validated a subset of miRNAs by individual RT-qPCR assays. Our analyses incorporated data from the effect of differentiation and tumor necrosis factor alpha treatment on primary human skeletal muscle cells and a murine skeletal muscle cell line. Distinct normalization methods differed in their impact on (i) standard deviations, (ii) the area under the receiver operating characteristic (ROC) curve, (iii) the similarity of differential expression. Loess, loessM, and quantile analysis were most effective in minimizing standard deviations on the Agilent and TLDA platform. Moreover, loess, loessM, invariant selection and generalized procrustes analysis increased the area under the ROC curve, a measure for the statistical performance of a test. The Jaccard index revealed that inter-platform concordance of differential expression tended to be increased by loess, loessM, quantile, and GPA normalization of AGL and TLDA data as well as RGI normalization of TLDA data. CONCLUSIONS/SIGNIFICANCE: We recommend the application of loess, or loessM, and GPA normalization for miRNA Agilent arrays and qPCR cards as these normalization approaches showed to (i) effectively reduce standard deviations, (ii) increase sensitivity and accuracy of differential miRNA expression detection as well as (iii) increase inter-platform concordance. Results showed the successful adoption of loessM and generalized procrustes analysis to one-color miRNA profiling experiments.

Robust biclustering by sparse singular value decomposition incorporating stability selection.

MOTIVATION: Over the past decade, several biclustering approaches have been published in the field of gene expression data analysis. Despite of huge diversity regarding the mathematical concepts of the different biclustering methods, many of them can be related to the singular value decomposition (SVD). Recently, a sparse SVD approach (SSVD) has been proposed to reveal biclusters in gene expression data. In this article, we propose to incorporate stability selection to improve this method. Stability selection is a subsampling-based variable selection that allows to control Type I error rates. The here proposed S4VD algorithm incorporates this subsampling approach to find stable biclusters, and to estimate the selection probabilities of genes and samples to belong to the biclusters. RESULTS: So far, the S4VD method is the first biclustering approach that takes the cluster stability regarding perturbations of the data into account. Application of the S4VD algorithm to a lung cancer microarray dataset revealed biclusters that correspond to coregulated genes associated with cancer subtypes. Marker genes for different lung cancer subtypes showed high selection probabilities to belong to the corresponding biclusters. Moreover, the genes associated with the biclusters belong to significantly enriched cancer-related Gene Ontology categories. In a simulation study, the S4VD algorithm outperformed the SSVD algorithm and two other SVD-related biclustering methods in recovering artificial biclusters and in being robust to noisy data. AVAILABILITY: R-Code of the S4VD algorithm as well as a documentation can be found at http://s4vd.r-forge.r-project.org/.