Urinary levels of the acrolein conjugates of carnosine are associated with inhaled toxicants.

OBJECTIVE: The inhalation of air-borne toxicants is associated with adverse health outcomes which can be somewhat mitigated by enhancing endogenous anti-oxidant capacity. Carnosine is a naturally occurring dipeptide (ß-alanine-L-histidine), present in high abundance in skeletal and cardiac muscle. This multi-functional dipeptide has anti-oxidant properties, can buffer intracellular pH, chelate metals, and sequester aldehydes such as acrolein. Due to these chemical properties, carnosine may be protective against inhaled pollutants which can contain metals and aldehydes and can stimulate the generation of electrophiles in exposed tissues. Thus, assessment of carnosine levels, or levels of its acrolein conjugates (carnosine-propanal and carnosine-propanol) may inform on level of exposure and risk assessment. METHODS: We used established mass spectroscopy methods to measure levels of urinary carnosine (n = 605) and its conjugates with acrolein (n = 561) in a subset of participants in the Louisville Healthy Heart Study (mean age = 51 ± 10; 52% male). We then determined associations between these measures and air pollution exposure and smoking behavior using statistical modeling approaches. RESULTS: We found that higher levels of non-conjugated carnosine, carnosine-propanal, and carnosine-propanol were significantly associated with males (p < 0.02) and those of Caucasian ethnicity (p < 0.02). Levels of carnosine-propanol were significantly higher in never-smokers (p = 0.001) but lower in current smokers (p = 0.037). This conjugate also demonstrated a negative association with mean-daily particulate air pollution (PM2.5) levels (p = 0.01). CONCLUSIONS: These findings suggest that urinary levels of carnosine-propanol may inform as to risk from inhaled pollutants.

seekCRIT: Detecting and characterizing differentially expressed circular RNAs using high-throughput sequencing data.

Over the past two decades, researchers have discovered a special form of alternative splicing that produces a circular form of RNA. Although these circular RNAs (circRNAs) have garnered considerable attention in the scientific community for their biogenesis and functions, the focus of current studies has been on the tissue-specific circRNAs that exist only in one tissue but not in other tissues or on the disease-specific circRNAs that exist in certain disease conditions, such as cancer, but not under normal conditions. This approach was conducted in the relative absence of methods that analyze a group of common circRNAs that exist in both conditions, but are more abundant in one condition relative to another (differentially expressed). Studies of differentially expressed circRNAs (DECs) between two conditions would serve as a significant first step in filling this void. Here, we introduce a novel computational tool, seekCRIT (seek for differentially expressed CircRNAs In Transcriptome), that identifies the DECs between two conditions from high-throughput sequencing data. Using rat retina RNA-seq data from ischemic and normal conditions, we show that over 74% of identifiable circRNAs are expressed in both conditions and over 40 circRNAs are differentially expressed between two conditions. We also obtain a high qPCR validation rate of 90% for DECs with a FDR of < 5%. Our results demonstrate that seekCRIT is a novel and efficient approach to detect DECs using rRNA depleted RNA-seq data. seekCRIT is freely downloadable at https://github.com/UofLBioinformatics/seekCRIT. The source code is licensed under the MIT License. seekCRIT is developed and tested on Linux CentOS-7.

Choice of library size normalization and statistical methods for differential gene expression analysis in balanced two-group comparisons for RNA-seq studies.

BACKGROUND: High-throughput RNA sequencing (RNA-seq) has evolved as an important analytical tool in molecular biology. Although the utility and importance of this technique have grown, uncertainties regarding the proper analysis of RNA-seq data remain. Of primary concern, there is no consensus regarding which normalization and statistical methods are the most appropriate for analyzing this data. The lack of standardized analytical methods leads to uncertainties in data interpretation and study reproducibility, especially with studies reporting high false discovery rates. In this study, we compared a recently developed normalization method, UQ-pgQ2, with three of the most frequently used alternatives including RLE (relative log estimate), TMM (Trimmed-mean M values) and UQ (upper quartile normalization) in the analysis of RNA-seq data. We evaluated the performance of these methods for gene-level differential expression analysis by considering the factors, including: 1) normalization combined with the choice of a Wald test from DESeq2 and an exact test/QL (Quasi-likelihood) F-Test from edgeR; 2) sample sizes in two balanced two-group comparisons; and 3) sequencing read depths. RESULTS: Using the MAQC RNA-seq datasets with small sample replicates, we found that UQ-pgQ2 normalization combined with an exact test can achieve better performance in term of power and specificity in differential gene expression analysis. However, using an intra-group analysis of false positives from real and simulated data, we found that a Wald test performs better than an exact test when the number of sample replicates is large and that a QL F-test performs the best given sample sizes of 5, 10 and 15 for any normalization. The RLE, TMM and UQ methods performed similarly given a desired sample size. CONCLUSION: We found the UQ-pgQ2 method combined with an exact test/QL F-test is the best choice in order to control false positives when the sample size is small. When the sample size is large, UQ-pgQ2 with a QL F-test is a better choice for the type I error control in an intra-group analysis. We observed read depths have a minimal impact for differential gene expression analysis based on the simulated data.

Sample size calculations for the differential expression analysis of RNA-seq data using a negative binomial regression model.

High throughput RNA sequencing (RNA-seq) technology is increasingly used in disease-related biomarker studies. A negative binomial distribution has become the popular choice for modeling read counts of genes in RNA-seq data due to over-dispersed read counts. In this study, we propose two explicit sample size calculation methods for RNA-seq data using a negative binomial regression model. To derive these new sample size formulas, the common dispersion parameter and the size factor as an offset via a natural logarithm link function are incorporated. A two-sided Wald test statistic derived from the coefficient parameter is used for testing a single gene at a nominal significance level 0.05 and multiple genes at a false discovery rate 0.05. The variance for the Wald test is computed from the variance-covariance matrix with the parameters estimated from the maximum likelihood estimates under the unrestricted and constrained scenarios. The performance and a side-by-side comparison of our new formulas with three existing methods with a Wald test, a likelihood ratio test or an exact test are evaluated via simulation studies. Since other methods are much computationally extensive, we recommend our M1 method for quick and direct estimation of sample sizes in an experimental design. Finally, we illustrate sample sizes estimation using an existing breast cancer RNA-seq data.

A combined approach with gene-wise normalization improves the analysis of RNA-seq data in human breast cancer subtypes.

Breast cancer (BC) is increasing in incidence and resistance to treatment worldwide. The challenges in limited therapeutic options and poor survival outcomes in BC subtypes persist because of its molecular heterogeneity and resistance to standard endocrine therapy. Recently, high throughput RNA sequencing (RNA-seq) has been used to identify biomarkers of disease progression and signaling pathways that could be amenable to specific therapies according to the BC subtype. However, there is no single generally accepted pipeline for the analysis of RNA-seq data in biomarker discovery due, in part, to the needs of simultaneously satisfying constraints of sensitivity and specificity. We proposed a combined approach using gene-wise normalization, UQ-pgQ2, followed by a Wald test from DESeq2. Our approach improved the analysis based on within-group comparisons in terms of the specificity when applied to publicly available RNA-seq BC datasets. In terms of identifying differentially expressed genes (DEGs), we combined an optimized log2 fold change cutoff with a nominal false discovery rate of 0.05 to further minimize false positives. Using this method in the analysis of two GEO BC datasets, we identified 797 DEGs uniquely expressed in triple negative BC (TNBC) and significantly associated with T cell and immune-related signaling, contributing to the immunotherapeutic efficacy in TNBC patients. In contrast, we identified 1403 DEGs uniquely expressed in estrogen positive and HER2 negative BC (ER+HER2-BC) and significantly associated with eicosanoid, notching and FAK signaling while a common set of genes was associated with cellular growth and proliferation. Thus, our approach to control for false positives identified two distinct gene expression profiles associated with these two subtypes of BC which are distinguishable by their molecular and functional attributes.

A causal mediation model of ischemia reperfusion injury in the retina.

The goal of this study is to develop a model that explains the relationship between microRNAs, transcription factors, and their co-target genes. This relationship was previously reported in gene regulatory loops associated with 24 hour (24h) and 7 day (7d) time periods following ischemia-reperfusion injury in a rat's retina. Using a model system of retinal ischemia-reperfusion injury, we propose that microRNAs first influence transcription factors, which in turn act as mediators to influence transcription of genes via triadic regulatory loops. Analysis of the relative contributions of direct and indirect regulatory influences on genes revealed that a substantial fraction of the regulatory loops (69% for 24 hours and 77% for 7 days) could be explained by causal mediation. Over 40% of the mediated loops in both time points were regulated by transcription factors only, while about 20% of the loops were regulated entirely by microRNAs. The remaining fractions of the mediated regulatory loops were cooperatively mediated by both microRNAs and transcription factors. The results from these analyses were supported by the patterns of expression of the genes, transcription factors, and microRNAs involved in the mediated loops in both post-ischemic time points. Additionally, network motif detection for the mediated loops showed a handful of time specific motifs related to ischemia-reperfusion injury in a rat's retina. In summary, the effects of microRNAs on genes are mediated, in large part, via transcription factors.

A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data.

Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read count variability that affects the overall sensitivity and specificity. In order to properly determine the most appropriate normalization methods, it is critical to compare the performance and shortcomings of a representative set of normalization routines based on different dataset characteristics. Therefore, we set out to evaluate the performance of the commonly used methods (DESeq, TMM-edgeR, FPKM-CuffDiff, TC, Med UQ and FQ) and two new methods we propose: Med-pgQ2 and UQ-pgQ2 (per-gene normalization after per-sample median or upper-quartile global scaling). Our per-gene normalization approach allows for comparisons between conditions based on similar count levels. Using the benchmark Microarray Quality Control Project (MAQC) and simulated datasets, we performed differential gene expression analysis to evaluate these methods. When evaluating MAQC2 with two replicates, we observed that Med-pgQ2 and UQ-pgQ2 achieved a slightly higher area under the Receiver Operating Characteristic Curve (AUC), a specificity rate > 85%, the detection power > 92% and an actual false discovery rate (FDR) under 0.06 given the nominal FDR (≤0.05). Although the top commonly used methods (DESeq and TMM-edgeR) yield a higher power (>93%) for MAQC2 data, they trade off with a reduced specificity (<70%) and a slightly higher actual FDR than our proposed methods. In addition, the results from an analysis based on the qualitative characteristics of sample distribution for MAQC2 and human breast cancer datasets show that only our gene-wise normalization methods corrected data skewed towards lower read counts. However, when we evaluated MAQC3 with less variation in five replicates, all methods performed similarly. Thus, our proposed Med-pgQ2 and UQ-pgQ2 methods perform slightly better for differential gene analysis of RNA-seq data skewed towards lowly expressed read counts with high variation by improving specificity while maintaining a good detection power with a control of the nominal FDR level.

Building a glaucoma interaction network using a text mining approach.

BACKGROUND: The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. RESULTS: A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. CONCLUSIONS: This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of relations that could not be found in existing interaction databases and that were found to be new, in addition to a smaller subnetwork consisting of interconnected clusters of seven glaucoma genes. Future improvements can be applied towards obtaining a better version of this network.

Regulatory networks in retinal ischemia-reperfusion injury.

BACKGROUND: Retinal function is ordered by interactions between transcriptional and posttranscriptional regulators at the molecular level. These regulators include transcription factors (TFs) and posttranscriptional factors such as microRNAs (miRs). Some studies propose that miRs predominantly target the TFs rather than other types of protein coding genes and such studies suggest a possible interconnection of these two regulators in co-regulatory networks. RESULTS: Our lab has generated mRNA and miRNA microarray expression data to investigate time-dependent changes in gene expression, following induction of ischemia-reperfusion (IR) injury in the rat retina. Data from different reperfusion time points following retinal IR-injury were analyzed. Paired expression data for miRNA-target gene (TG), TF-TG, miRNA-TF were used to identify regulatory loop motifs whose expressions were altered by the IR injury paradigm. These loops were subsequently integrated into larger regulatory networks and biological functions were assayed. Systematic analyses of the networks have provided new insights into retinal gene regulation in the early and late periods of IR. We found both overlapping and unique patterns of molecular expression at the two time points. These patterns can be defined by their characteristic molecular motifs as well as their associated biological processes. We highlighted the regulatory elements of miRs and TFs associated with biological processes in the early and late phases of ischemia-reperfusion injury. CONCLUSIONS: The etiology of retinal ischemia-reperfusion injury is orchestrated by complex and still not well understood gene networks. This work represents the first large network analysis to integrate miRNA and mRNA expression profiles in context of retinal ischemia. It is likely that an appreciation of such regulatory networks will have prognostic potential. In addition, the computational framework described in this study can be used to construct miRNA-TF interactive systems networks for various diseases/disorders of the retina and other tissues.

Ischemia-reperfusion injury of the retina is linked to necroptosis via the ERK1/2-RIP3 pathway.

PURPOSE: Ischemia-reperfusion (IR) injury is involved in the pathology of many retinal disorders since it contributes to the death of retinal neurons and the subsequent decline in vision. We determined the molecular patterns of some of the principal molecules involved in necroptosis and investigated whether IR retinal injury is associated with the extracellular signal-regulated kinase-1/2- receptor-interacting protein kinase 3 (ERK1/2-RIP3) pathway. METHODS: The cellular and subcellular localization of molecules involved in the cell death pathway, including RAGE, ERK1/2, FLIP, and RIP3, was determined with immunohistochemistry of cryosections of IR-injured retina from 2-month-old Long Evans rats. The total and phosphorylated protein levels were analyzed with quantitative western blots. ERK1/2 activity was inhibited by intravitreal injection of U0126, a highly selective inhibitor of mitogen-activated protein kinase 1/2 (MEK1/2). RESULTS: The IR-injured rat retinas expressed two RAGE isoforms with different intracellular localizations at early time points after injury. At that time point, frame inhibition of ERK activation decreased RIP3 accumulation and cell death. FLIP was detected in the IR-injured rat retinas at early time points after ischemia reperfusion. CONCLUSIONS: We report that the necroptotic cell death mechanism is executed by an ERK1/2-RIP3 pathway in the retinal ganglion cells in early stages after IR injury. Inhibition of ERK1/2 activity increased retinal ganglion cell (RGC) survival indicating that targeting of this pathway within the initial 12 h after IR injury can be used to inhibit the necroptosis pathway. We also provide evidence that a novel RAGE isoform is expressed in the early stages in rat retinal RGCs.

Time-dependent Gene Profiling Indicates the Presence of Different Phases for Ischemia/Reperfusion Injury in Retina.

Ischemia/reperfusion (IR) injury has been associated with several retinal pathologies, and a few genes/gene products have been linked to IR injury. However, the big picture of temporal changes, regarding the affected gene networks, pathways, and processes remains to be determined. The purpose of the present study was to investigate initial, intermediate, and later stages to characterize the etiology of IR injury in terms of the pathways affected over time. Analyses indicated that at the initial stage, 0-hour reperfusion following the ischemic period, the ischemia-associated genes were related to changes in metabolism. In contrast, at the 24-hour time point, the signature events in reperfusion injury include enhanced inflammatory and immune responses as well as cell death indicating that this would be a critical period for the development of any interventional therapeutic strategies. Genes in the signal transduction pathways, particularly transmitter receptors, are downregulated at this time. Activation of the complement system pathway clearly plays an important role in the later stages of reperfusion injury. Together, these results demonstrate that the etiology of injury related to IR is characterized by the appearance of specific patterns of gene expression at any given time point during retinal IR injury. These results indicate that evaluation of treatment strategies with respect to time is very critical.

MicroRNAs in the Neural Retina.

The health and function of the visual system rely on a collaborative interaction between diverse classes of molecular regulators. One of these classes consists of transcription factors, which are known to bind to DNA and control the transcription activities of their target genes. For a long time, it was thought that the transcription factors were the only regulators of gene expression. More recently, however, a novel class of regulators emerged. This class consists of a large number of small noncoding endogenous RNAs, namely, miRNAs. The miRNAs compose an essential component of posttranscriptional gene regulation, since they ultimately control the fate of gene transcripts. The retina, as a part of the central nervous system, is a well-established model for unraveling the molecular mechanisms underlying neuronal and glial functions. Numerous recent efforts have been made towards identification of miRNAs and their inferred roles in the visual pathway. In this review, we summarize the current state of our knowledge regarding the expression and function of miRNA in the neural retina and we discuss their potential uses as biomarkers for some retinal disorders.

Cross-kingdom sequence similarities between human micro-RNAs and plant viruses.

Micro-RNAs regulate the expression of cellular and tissue phenotypes at a post-transcriptional level through a complex process involving complementary interactions between micro-RNAs and messenger-RNAs. Similar nucleotide interactions have been shown to occur as cross-kingdom events; for example, between plant viruses and plant micro-RNAs and also between animal viruses and animal micro-RNAs. In this study, this view is expanded to look for cross-kingdom similarities between plant virus and human micro-RNA sequences. A method to identify significant nucleotoide sequence similarities between plant viruses and hsa micro-RNAs was created. Initial analyses demonstrate that plant viruses contain nucleotide sequences which exactly match the seed sequences of human micro-RNAs in both parallel and anti-parallel directions. For example, the bean common mosaic virus strain NL4 from Colombia contains sequences that match exactly the seed sequence for micro-RNA of the hsa-mir-1226 in the parallel direction, which suggests a cross-kingdom conservation. Similarly, the rice yellow stunt viral cRNA contains a sequence that is an exact match in the anti-parallel direction to the seed sequence of hsa-micro-RNA let-7b. The functional implications of these results need to be explored. The finding of these cross-kingdom sequence similarities is a useful starting point in support of bench level investigations.

Transcriptomic analysis of the zebrafish inner ear points to growth hormone mediated regeneration following acoustic trauma.

BACKGROUND: Unlike mammals, teleost fishes are capable of regenerating sensory inner ear hair cells that have been lost following acoustic or ototoxic trauma. Previous work indicated that immediately following sound exposure, zebrafish saccules exhibit significant hair cell loss that recovers to pre-treatment levels within 14 days. Following acoustic trauma in the zebrafish inner ear, we used microarray analysis to identify genes involved in inner ear repair following acoustic exposure. Additionally, we investigated the effect of growth hormone (GH) on cell proliferation in control zebrafish utricles and saccules, since GH was significantly up-regulated following acoustic trauma. RESULTS: Microarray analysis, validated with the aid of quantitative real-time PCR, revealed several genes that were highly regulated during the process of regeneration in the zebrafish inner ear. Genes that had fold changes of ≥ 1.4 and P -values ≤ 0.05 were considered significantly regulated and were used for subsequent analysis. Categories of biological function that were significantly regulated included cancer, cellular growth and proliferation, and inflammation. Of particular significance, a greater than 64-fold increase in growth hormone (gh1) transcripts occurred, peaking at 2 days post-sound exposure (dpse) and decreasing to approximately 5.5-fold by 4 dpse. Pathway Analysis software was used to reveal networks of regulated genes and showed how GH affected these networks. Subsequent experiments showed that intraperitoneal injection of salmon growth hormone significantly increased cell proliferation in the zebrafish inner ear. Many other gene transcripts were also differentially regulated, including heavy and light chain myosin transcripts, both of which were down-regulated following sound exposure, and major histocompatability class I and II genes, several of which were significantly regulated on 2 dpse. CONCLUSIONS: Transcripts for GH, MHC Class I and II genes, and heavy- and light-chain myosins, as well as many others genes, were differentially regulated in the zebrafish inner ear following overexposure to sound. GH injection increased cell proliferation in the inner ear of non-sound-exposed zebrafish, suggesting that GH could play an important role in sensory hair cell regeneration in the teleost ear.

Modeling microRNA-mRNA interactions using PLS regression in human colon cancer.

BACKGROUND: Changes in microRNA (miRNA) expression patterns have been extensively characterized in several cancers, including human colon cancer. However, how these miRNAs and their putative mRNA targets contribute to the etiology of cancer is poorly understood. In this work, a bioinformatics computational approach with miRNA and mRNA expression data was used to identify the putative targets of miRNAs and to construct association networks between miRNAs and mRNAs to gain some insights into the underlined molecular mechanisms of human colon cancer. METHOD: The miRNA and mRNA microarray expression profiles from the same tissues including 7 human colon tumor tissues and 4 normal tissues, collected by the Broad Institute, were used to identify significant associations between miRNA and mRNA. We applied the partial least square (PLS) regression method and bootstrap based statistical tests to the joint expression profiles of differentially expressed miRNAs and mRNAs. From this analysis, we predicted putative miRNA targets and association networks between miRNAs and mRNAs. Pathway analysis was employed to identify biological processes related to these miRNAs and their associated predicted mRNA targets. RESULTS: Most significantly associated up-regulated mRNAs with a down-regulated miRNA identified by the proposed methodology were considered to be the miRNA targets. On average, approximately 16.5% and 11.0% of targets predicted by this approach were also predicted as targets by the common prediction algorithms TargetScan and miRanda, respectively. We demonstrated that our method detects more targets than a simple correlation based association. Integrative mRNA:miRNA predictive networks from our analysis were constructed with the aid of Cytoscape software. Pathway analysis validated the miRNAs through their predicted targets that may be involved in cancer-associated biological networks. CONCLUSION: We have identified an alternative bioinformatics approach for predicting miRNA targets in human colon cancer and for reverse engineering the miRNA:mRNA network using inversely related mRNA and miRNA joint expression profiles. We demonstrated the superiority of our predictive method compared to the correlation based target prediction algorithm through a simulation study. We anticipate that the unique miRNA targets predicted by the proposed method will advance the understanding of the molecular mechanism of colon cancer and will suggest novel therapeutic targets after further experimental validations.

Comparative in silico analyses of cpeb1-4 with functional predictions.

BACKGROUND: Cytoplasmic polyadenylation element binding proteins (Cpebs) are a family of proteins that bind to defined groups of mRNAs and regulate their translation. While Cpebs were originally identified as important features of oocyte maturation, recent interest is due to their prospective roles in neural system plasticity. RESULTS: In this study we made use of bioinformatic tools and methods including NCBI Blast, UCSC Blat, and Invitrogen Vector NTI to comprehensively analyze all known isoforms of four mouse Cpeb paralogs extracted from the national UniGene, UniProt, and NCBI protein databases. We identified multiple alternative splicing variants for each Cpeb. Regions of commonality and distinctiveness were evident when comparing Cpeb2, 3, and 4. In addition, we performed cross-ortholog comparisons among multiple species. The exon patterns were generally conserved across vertebrates. Mouse and human isoforms were compared in greater detail as they are the most represented in the current databases. The homologous and distinct regions are strictly conserved in mouse Cpeb and human CPEB proteins. Novel variants were proposed based on cross-ortholog comparisons and validated using biological methods. The functions of the alternatively spliced regions were predicted using the Eukaryotic Linear Motif resource. CONCLUSIONS: Together, the large number of transcripts and proteins indicate the presence of a hitherto unappreciated complexity in the regulation and functions of Cpebs. The evolutionary retention of variable regions as described here is most likely an indication of their functional significance.

Genomic profiling of messenger RNAs and microRNAs reveals potential mechanisms of TWEAK-induced skeletal muscle wasting in mice.

BACKGROUND: Skeletal muscle wasting is a devastating complication of several physiological and pathophysiological conditions. Inflammatory cytokines play an important role in the loss of skeletal muscle mass in various chronic diseases. We have recently reported that proinflammatory cytokine TWEAK is a major muscle-wasting cytokine. Emerging evidence suggests that gene expression is regulated not only at transcriptional level but also at post-transcriptional level through the expression of specific non-coding microRNAs (miRs) which can affect the stability and/or translation of target mRNA. However, the role of miRs in skeletal muscle wasting is unknown. METHODOLOGY/PRINCIPAL FINDINGS: To understand the mechanism of action of TWEAK in skeletal muscle, we performed mRNA and miRs expression profile of control and TWEAK-treated myotubes. TWEAK increased the expression of a number of genes involved in inflammatory response and fibrosis and reduced the expression of few cytoskeletal gene (e.g. Myh4, Ankrd2, and TCap) and metabolic enzymes (e.g. Pgam2). Low density miR array demonstrated that TWEAK inhibits the expression of several miRs including muscle-specific miR-1-1, miR-1-2, miR-133a, miR-133b and miR-206. The expression of a few miRs including miR-146a and miR-455 was found to be significantly increased in response to TWEAK treatment. Ingenuity pathway analysis showed that several genes affected by TWEAK are known/putative targets of miRs. Our cDNA microarray data are consistent with miRs profiling. The levels of specific mRNAs and miRs were also found to be similarly regulated in atrophying skeletal muscle of transgenic mice (Tg) mice expressing TWEAK. CONCLUSIONS/SIGNIFICANCE: Our results suggest that TWEAK affects the expression of several genes and microRNAs involved in inflammatory response, fibrosis, extracellular matrix remodeling, and proteolytic degradation which might be responsible for TWEAK-induced skeletal muscle loss.

Characterization of the transcripts and protein isoforms for cytoplasmic polyadenylation element binding protein-3 (CPEB3) in the mouse retina.

BACKGROUND: Cytoplasmic polyadenylation element binding proteins (CPEBs) regulate translation by binding to regulatory motifs of defined mRNA targets. This translational mechanism has been shown to play a critical role in oocyte maturation, early development, and memory formation in the hippocampus. Little is known about the presence or functions of CPEBs in the retina. The purpose of the current study is to investigate the alternative splicing isoforms of a particular CPEB, CPEB3, based on current databases, and to characterize the expression of CPEB3 in the retina. RESULTS: In this study, we have characterized CPEB3, whose putative role is to regulate the translation of GluR2 mRNA. We identify the presence of multiple alternative splicing isoforms of CPEB3 transcripts and proteins in the current databases. We report the presence of eight alternative splicing patterns of CPEB3, including a novel one, in the mouse retina. All but one of the patterns appear to be ubiquitous in 13 types of tissue examined. The relative abundance of the patterns in the retina is demonstrated. Experimentally, we show that CPEB3 expression is increased in a time-dependent manner during the course of postnatal development, and CPEB3 is localized mostly in the inner retina, including retinal ganglion cells. CONCLUSION: The level of CPEB3 was up-regulated in the retina during development. The presence of multiple CPEB3 isoforms indicates remarkable complexity in the regulation and function of CPEB3.

Glutamate-induced NFkappaB activation in the retina.

PURPOSE: To determine the distribution and glutamate-mediated activation of nuclear factor (NF) kappaB members in the retina and pan-purified retinal ganglion cells (RGCs) and to characterize steps in the signal transduction events that lead to NFkappaB activation. METHODS: Retinal expression patterns and RGCs were evaluated for five NFkappaB proteins with the aid of immunohistochemistry. Retinal explants or RGCs were treated with glutamate with or without the presence of the NDMA receptor antagonist memantine, the calcium chelator EGTA, or a specific inhibitor for calcium/calmodulin-dependent protein kinase-II (CaMKII). Characterizations of NFkappaB activation were performed with the aid of electrophoretic mobility shift assays and supershift assays. RESULTS: All five NFkappaB proteins were present in the retina and in the pan-purified RGCs. In response to a glutamate stimulus, all NFkappaB proteins except c-Rel were activated. P65 was unique in that it was not constitutively active but showed a glutamate-inducible activation in the retina and in the cultured RGCs. Memantine, EGTA, or autocamtide-2-related inhibitory peptide (AIP) inhibited NFkappaB activation in the retina. Furthermore, AIP significantly reduced the level of glutamate-induced degradation of IkappaBs. CONCLUSIONS: These data indicate that glutamate activates distinct NFkappaB proteins in the retina. P65 activation may be especially important with regard to RGC responses to glutamate given that its activity is induced by conditions known to lead to the death of these cells. The NMDA receptor-Ca(2+)-CaMKII signaling pathway is involved in glutamate-induced NFkappaB activation. Because AIP blocks the degradation of IkappaB, its regulation is clearly downstream of CaMKII.

Increased chondroitin sulfate proteoglycan expression in denervated brainstem targets following spinal cord injury creates a barrier to axonal regeneration overcome by chondroitinase ABC and neurotrophin-3.

Increased chondroitin sulfate proteoglycan (CSPG) expression in the vicinity of a spinal cord injury (SCI) is a primary participant in axonal regeneration failure. However, the presence of similar increases of CSPG expression in denervated synaptic targets well away from the primary lesion and the subsequent impact on regenerating axons attempting to approach deafferented neurons have not been studied. Constitutively expressed CSPGs within the extracellular matrix and perineuronal nets of the adult rat dorsal column nuclei (DCN) were characterized using real-time PCR, Western blot analysis and immunohistochemistry. We show for the first time that by 2 days and through 3 weeks following SCI, the levels of NG2, neurocan and brevican associated with reactive glia throughout the DCN were dramatically increased throughout the DCN despite being well beyond areas of trauma-induced blood brain barrier breakdown. Importantly, regenerating axons from adult sensory neurons microtransplanted 2 weeks following SCI between the injury site and the DCN were able to regenerate rapidly within white matter (as shown previously by Davies et al. [Davies, S.J., Goucher, D.R., Doller, C., Silver, J., 1999. Robust regeneration of adult sensory axons in degenerating white matter of the adult rat spinal cord. J. Neurosci. 19, 5810-5822]) but were unable to enter the denervated DCN. Application of chondroitinase ABC or neurotrophin-3-expressing lentivirus in the DCN partially overcame this inhibition. When the treatments were combined, entrance by regenerating axons into the DCN was significantly augmented. These results demonstrate both an additional challenge and potential treatment strategy for successful functional pathway reconstruction after SCI.