Dynamic modulation of phosphoprotein expression in ovarian cancer xenograft models.

BACKGROUND: The dynamic changes that occur in protein expression after treatment of a cancer in vivo are poorly described. In this study we measure the effect of chemotherapy over time on the expression of a panel of proteins in ovarian cancer xenograft models. The objective was to identify phosphoprotein and other protein changes indicative of pathway activation that might link with drug response. METHODS: Two xenograft models, platinum-responsive OV1002 and platinum-unresponsive HOX424, were used. Treatments were carboplatin and carboplatin-paclitaxel. Expression of 49 proteins over 14 days post treatment was measured by quantitative immunofluorescence and analysed by AQUA. RESULTS: Carboplatin treatment in the platinum-sensitive OV1002 model triggered up-regulation of cell cycle, mTOR and DDR pathways, while at late time points WNT, invasion, EMT and MAPK pathways were modulated. Estrogen receptor-alpha (ESR1) and ERBB pathways were down-regulated early, within 24 h from treatment administration. Combined carboplatin-paclitaxel treatment triggered a more extensive response in the OV1002 model modulating expression of 23 of 49 proteins. Therefore the cell cycle and DDR pathways showed similar or more pronounced changes than with carboplatin alone. In addition to expression of pS6 and pERK increasing, components of the AKT pathway were modulated with pAKT increasing while its regulator PTEN was down-regulated early. WNT signaling, EMT and invasion markers were modulated at later time points. Additional pathways were also observed with the NFκB and JAK/STAT pathways being up-regulated. ESR1 was down-regulated as was HER4, while further protein members of the ERBB pathway were upregulated late. By contrast, in the carboplatin-unresponsive HOX 424 xenograft, carboplatin only modulated expression of MLH1 while carboplatin-paclitaxel treatment modulated ESR1 and pMET. CONCLUSIONS: Thirteen proteins were modulated by carboplatin and a more robust set of changes by carboplatin-paclitaxel. Early changes included DDR and cell cycle regulatory proteins associating with tumor volume changes, as expected. Changes in ESR1 and ERBB signaling were also observed. Late changes included components of MAPK signaling, EMT and invasion markers and coincided in time with reversal in tumor volume reduction. These results suggest potential therapeutic roles for inhibitors of such pathways that may prolong chemotherapeutic effects.

Identification of a novel IL-1 cytokine family member in teleost fish.

A novel IL-1 family member (nIL-1F) has been discovered in fish, adding a further member to this cytokine family. The unique gene organization of nIL-1F, together with its location in the genome and low homology to known family members, suggests that this molecule is not homologous to known IL-1F. Nevertheless, it contains a predicted C-terminal beta-trefoil structure, an IL-1F signature region within the final exon, a potential IL-1 converting enzyme cut site, and its expression level is clearly increased following infection, or stimulation of macrophages with LPS or IL-1beta. A thrombin cut site is also present and may have functional relevance. The C-terminal recombinant protein antagonized the effects of rainbow trout rIL-1beta on inflammatory gene expression in a trout macrophage cell line, suggesting it is an IL-1beta antagonist. Modeling studies confirmed that nIL-1F has the potential to bind to the trout IL-1RI receptor protein, and may be a novel IL-1 receptor antagonist.

DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification.

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

Improving classification in protein structure databases using text mining.

BACKGROUND: The classification of protein domains in the CATH resource is primarily based on structural comparisons, sequence similarity and manual analysis. One of the main bottlenecks in the processing of new entries is the evaluation of 'borderline' cases by human curators with reference to the literature, and better tools for helping both expert and non-expert users quickly identify relevant functional information from text are urgently needed. A text based method for protein classification is presented, which complements the existing sequence and structure-based approaches, especially in cases exhibiting low similarity to existing members and requiring manual intervention. The method is based on the assumption that textual similarity between sets of documents relating to proteins reflects biological function similarities and can be exploited to make classification decisions. RESULTS: An optimal strategy for the text comparisons was identified by using an established gold standard enzyme dataset. Filtering of the abstracts using a machine learning approach to discriminate sentences containing functional, structural and classification information that are relevant to the protein classification task improved performance. Testing this classification scheme on a dataset of 'borderline' protein domains that lack significant sequence or structure similarity to classified proteins showed that although, as expected, the structural similarity classifiers perform better on average, there is a significant benefit in incorporating text similarity in logistic regression models, indicating significant orthogonality in this additional information. Coverage was significantly increased especially at low error rates, which is important for routine classification tasks: 15.3% for the combined structure and text classifier compared to 10% for the structural classifier alone, at 10-3 error rate. Finally when only the highest scoring predictions were used to infer classification, an extra 4.2% of correct decisions were made by the combined classifier. CONCLUSION: We have described a simple text based method to classify protein domains that demonstrates an improvement over existing methods. The method is unique in incorporating structural and text based classifiers directly and is particularly useful in cases where inconclusive evidence from sequence or structure similarity requires laborious manual classification.

Discovery of multiple beta-defensin like homologues in teleost fish.

Using a database mining approach, multiple defensin like genes have been discovered for the first time in fish, in species including zebrafish Danio rerio and the pufferfish, Takifugu rubripes and Tetraodon nigroviridis. They share the common features of vertebrate defensins, including small size, net cationic charge, and six conserved cysteines in the mature region. Based on their cysteine arrangement, the identified fish defensin like peptides resemble beta-defensin family members in birds and mammals. Computing modelling detected three beta-strands in all three zebrafish defensins and an extra N-terminal alpha-helix in one of the peptides. The coding regions of the fish genes contain three exons and two introns, the same as avian defensin genes. In zebrafish and tetraodon, two defensin genes identified are located in the same chromosome. An additional locus containing a third defensin gene has also been found in a different chromosome in zebrafish, demonstrating that multiple defensin loci may be present in fish. Comparative studies suggest that beta-defensins may represent the primitive form of the defensin family, which expanded during evolution by gene or genome duplication. In healthy zebrafish, constitutive expression of defensins was detected by RT-PCR in gill, gonad, gut, kidney, muscle, skin and spleen but the levels and patterns varied for individual defensin genes.

Relationship between differentially expressed mRNA and mRNA-protein correlations in a xenograft model system.

Differential mRNA expression studies implicitly assume that changes in mRNA expression have biological meaning, most likely mediated by corresponding changes in protein levels. Yet studies into mRNA-protein correspondence have shown notoriously poor correlation between mRNA and protein expression levels, creating concern for inferences from only mRNA expression data. However, none of these studies have examined in particular differentially expressed mRNA. Here, we examined this question in an ovarian cancer xenograft model. We measured protein and mRNA expression for twenty-nine genes in four drug-treatment conditions and in untreated controls. We identified mRNAs differentially expressed between drug-treated xenografts and controls, then analysed mRNA-protein expression correlation across a five-point time-course within each of the four experimental conditions. We evaluated correlations between mRNAs and their protein products for mRNAs differentially expressed within an experimental condition compared to those that are not. We found that differentially expressed mRNAs correlate significantly better with their protein product than non-differentially expressed mRNAs. This result increases confidence for the use of differential mRNA expression for biological discovery in this system, as well as providing optimism for the usefulness of inferences from mRNA expression in general.

Analysis of fish IL-1beta and derived peptide sequences indicates conserved structures with species-specific IL-1 receptor binding: implications for pharmacological design.

A large number of IL-1 protein sequences have become available recently from a range of vertebrate species and especially from bony fish. However, 3D structures are still only known for mammalian IL-1. In this review, we use a multiple sequence alignment of all published non-mammalian vertebrate IL-1beta proteins to locate the structurally important residues critical for maintaining the beta-trefoil fold and we investigate the degree to which functionally important residues involved in receptor binding are conserved across vertebrate species. We find that although there is a high level of variability of positions involved in receptor binding, the mode of binding and overall shape of the ligand-receptor complex is probably maintained. This implies that each species has evolved its own unique interleukin-1 signalling system through ligand-receptor co-evolution. Nonetheless, the IL-1beta processing mechanism in non-mammalian vertebrates remains unclear because, with the exception of three bony fish, all non-mammalian IL-1beta sequences discovered so far lack an ICE (Interleukin Converting Enzyme) cut site. The IL-1 system has become an important drug target because of its significance in inflammatory diseases. Research on peptides derived from IL-1beta has identified peptides that possess agonist activity in humans and in trout, and peptides with antagonist activity. The agonist peptides map to two distinct loop regions of IL-1beta that are known to interact with the flexible domain III of the corresponding receptor. Further analysis of the IL-1 system may prove useful in engineering IL-1 with improved features and in suggesting new avenues for therapeutic intervention.