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 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.

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.

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.

Retinal ganglion cell death and neuroprotection: Involvement of the CaMKIIalpha gene.

The purpose of this study is to determine if calcium/calmodulin-dependent protein kinase-II (CaMKII) plays a role in neuronal cell death and if inhibition of this kinase affords some neuroprotection in the RGC-5 retinal ganglion cell line. The RGC-5 cells were treated with glutamate at various concentrations for increasing increments of time. Cytotoxicity was assayed by measuring the lactate dehydrogenase (LDH) leakage from non-viable cells and TUNEL assays. The involvement of caspase-3, Bcl-2 and caspase-8 in glutamate-induced cytotoxicity was determined by immunoblots and/or real time RT-PCR. In addition, the autocamtide-2-related inhibitory peptide (AIP), a specific inhibitor of CaMKII, was used to determine the involvement of CaMKII in glutamate-induced RGC-5 cell death. Application of increasing concentrations of glutamate to RGC-5 cells caused a dose-dependent increase in the level of cell death after 24 h. There was a glutamate-stimulated increase in the expression of caspase-8 and caspase-3 and a corresponding decrease in Bcl-2. The active fragment of caspase-3 increased in glutamate-treated cells. An early transient increase in the expression of CaMKIIalpha(B) gene and a corresponding CaMKIIalpha nuclear translocation was found in glutamate-treated cells. Treatment with AIP blocked the activation of caspase-3 and protected RGC from glutamate-mediated cell death but did not alter the glutamate-enhanced expression levels of caspase-8 or caspase-3. This report shows the likely involvement of a transcript of the CaMKIIalpha gene in the cytotoxicity response of RGC-5 cells similar to previous reports in the neural retina. AIP is shown to be a neuroprotectant for RGC-5 cells as was reported for the neural retina.

Human adult olfactory neuroepithelial derived progenitors retain telomerase activity and lack apoptotic activity.

Olfactory epithelium (OE) contains a population of progenitors responsible for its life-long regenerative capacity. Procedures for the isolation of these progenitors have been established [F.J. Roisen, K.M. Klueber, C.L. Lu, L.M. Hatcher, A. Dozier, C.B. Shields, Adult human olfactory stem cells, Brain Res., 890 (2001) 11-12.] and over 40 patient-specific cell lines from adult postmortem OE and endoscopic biopsy from patients undergoing nasal sinus surgery have been obtained. As these cells emerged in primary cultures, they formed neurospheres (NSFCs). The purpose of the present study was to further characterize these adult human olfactory-derived progenitors. Subcultures of the NSFCs have been passaged nearly 200 times, with a mitotic cycle of 18-20 h. Telomerase activity remains in stem cells; therefore, ELISA was employed to determine the telomerase activity of different lines and passages. Since progenitors undergo low levels of apoptosis, the levels of apoptosis were also examined in these populations. The levels of telomerase and apoptotic activity in 12 NSFC lines remained relatively constant irrespective of donor age, culture duration, or sex. To further study the apoptotic characteristics of the NSFCs, nine different caspases (cysteine proteases) known to be critical in apoptosis were evaluated using gene-microarrays comparing cells from a single line at passages 14, 88, and 183. No increases were found in caspase activity in all passages studied. ELISA confirmed the absence of caspase activity over the entire range of passages. This study further suggests that NSFCs can be obtained and used from patients, irrespective of age, sex, or time in culture without altered viability expanding the potential utility of these cells for autologous transplantation and possible diagnostic testing.

Enhanced expression of TNF-R1 protein in NMDA-mediated cell death in the retina.

Multiple apoptosis-related genes are expressed in the retina after exposure to N-methyl-D-aspartic acid (NMDA). For example, the mRNAs for TNF-R1, FasL, and Nur77 are up-regulated between 2.8 and 7-fold [Mol. Brain Res. 91 (2001) 34-42]. The purpose of the present study is to examine prospective changes in protein expression for these genes and to determine their cellular localizations subsequent to NMDA stimulation. Following anesthesia, a single intravitreal injection of 4 mM NMDA was administered into the right eye of anesthetized rats. The left eye was injected with phosphate-buffered saline. Retinae were harvested at 2 and 24 h postinjection. Western-blot and immunocytochemical techniques were used to detect changes in protein expression levels, and to localize their distributions within the retina. Analyses of Western blots demonstrated a significant increase in TNF-R1 (100 and 80%) compared to the sham-controls at 2 and 24 h postinjection with NMDA. Immunolabeling of TNF-R1 was observed in the inner nuclear layer (INL) at 2 h postinjection with NMDA. TNF-R1 was also clearly evident in cells within the INL and ganglion cell layers (GCL) at 24 h post-injection with NMDA. In contrast to these changes in TNF-R1 there were no significant changes in the levels or distributions of FasL or Nur77 in NMDA-stimulated animals at either 2 or 24 h when compared to the sham-controls. These results implicate the TNF-R1 signal transduction pathway in NMDA-induced cell death in the INL and GCL of the retina.