Cooperation and competition by RNA-binding proteins in cancer.

Post-transcriptional regulation of gene expression plays a major role in determining the cellular proteome in health and disease. Post-transcriptional control mechanisms are disrupted in many cancers, contributing to multiple processes of tumorigenesis. RNA-binding proteins (RBPs), the main post-transcriptional regulators, often show altered expression and activity in cancer cells. Dysregulation of RBPs contributes to many cancer phenotypes, functioning in complex regulatory networks with other cellular players such as non-coding RNAs, signaling mediators and transcription factors to alter the expression of oncogenes and tumor suppressor genes. RBPs often function combinatorially, based on their binding to target sequences/structures on shared mRNA targets, to regulate the expression of cancer-related genes. This gives rise to cooperativity and competition between RBPs in mRNA binding and resultant functional outcomes in post-transcriptional processes such as mRNA splicing, stability, export and translation. Cooperation and competition is also observed in the case of interaction of RBPs and microRNAs with mRNA targets. RNA structural change is a common mechanism mediating the cooperative/competitive interplay between RBPs and between RBPs and microRNAs. RNA modifications, leading to changes in RNA structure, add a new dimension to cooperative/competitive binding of RBPs to mRNAs, further expanding the RBP regulatory landscape. Therefore, cooperative/competitive interplay between RBPs is a major determinant of the RBP interactome and post-transcriptional regulation of gene expression in cancer cells.

Quorum Sensing by Gelsolin Regulates Programmed Cell Death 4 Expression and a Density-Dependent Phenotype in Macrophages.

Quorum-sensing mechanisms that sense the density of immune cells at the site of inflammation to initiate inflammation resolution have recently been demonstrated as a major determinant of the inflammatory response. We observed a density-dependent increase in expression of the inflammatory tumor suppressor protein programmed cell death 4 (PDCD4) in mouse macrophage cells. Conditioned medium from high-density cells upregulated PDCD4 expression, revealing the presence of a secreted factor(s) acting as a macrophage quorum sensor. Secreted gelsolin (GSN) was identified as the quorum-sensing autoinducer. Alteration of GSN levels changed PDCD4 expression and the density-dependent phenotype of cells. LPS induced the expression of microRNA miR-21, which downregulated both GSN and PDCD4 expression, and reversed the high-density phenotype. The high-density phenotype was correlated with an anti-inflammatory gene expression program, which was counteracted by inflammatory stimulus. Together, our observations establish the miR-21-GSN-PDCD4 regulatory network as a crucial mediator of a macrophage quorum-sensing mechanism for the control of inflammatory responses.

Transcriptome-wide analysis reveals spatial correlation between N6-methyladenosine and binding sites of microRNAs and RNA-binding proteins.

N6-methyladenosine (m6A), the most prevalent epitranscriptomic modification in eukaryotes, is enriched in 3'-untranslated regions (3'UTRs) of mRNAs. As 3'UTRs are major binding sites of RNA-binding proteins (RBPs) and microRNAs (miRNAs), m6A-dependent local RNA structure change may alter the accessibility of RBPs and miRNAs to their target sites and regulate mRNA function. Using a human transcriptome-wide computational analysis to investigate the relation between m6A, RBPs and miRNAs, we find a strong positive correlation between number of m6A sites, miRNAs and RBPs binding to mRNAs, suggesting m6A-modified mRNAs are more targeted by miRNAs and RBPs. Moreover, m6A sites are located proximally to miRNA target sites and binding sites of multiple RBPs. Further, miRNA target sites and RBP-binding sites located close to each other are also located proximally to m6A. This study indicates three-way interplay between m6A, microRNA and RBP binding, suggesting the influence of mRNA modifications on the miRNA and RBP interactomes.

RiboD: a comprehensive database for prokaryotic riboswitches.

SUMMARY: Riboswitches are cis-regulatory non-coding genomic segments that control the expression of downstream genes by undergoing conformational change upon ligand binding. We present a comprehensive database of prokaryotic riboswitches that allows the user to search for riboswitches using multiple criteria, extract information about riboswitch location and gene/operon it regulates. RiboD provides a very useful resource that can be utilized for the better understanding of riboswitch-based gene regulation in bacteria and archaea. AVAILABILITY AND IMPLEMENTATION: RiboD can be freely accessed on the web at http://ribod.iiserkol.ac.in/.

MYCbase: a database of functional sites and biochemical properties of Myc in both normal and cancer cells.

BACKGROUND: Myc is an essential gene having multiple functions such as in cell growth, differentiation, apoptosis, genomic stability, angiogenesis, and disease biology. A large number of researchers dedicated to Myc biology are generating a substantial amount of data in normal and cancer cells/tissues including Burkitt's lymphoma and ovarian cancer. RESULTS: MYCbase ( http://bicresources.jcbose.ac.in/ssaha4/mycbase ) is a collection of experimentally supported functional sites in Myc that can influence the biological cellular processes. The functional sites were compiled according to their role which includes mutation, methylation pattern, post-translational modifications, protein-protein interactions (PPIs), and DNA interactions. In addition, biochemical properties of Myc are also compiled, which includes metabolism/pathway, protein abundance, and modulators of protein-protein interactions. The OMICS data related to Myc- like gene expression, proteomics expression using mass-spectrometry and miRNAs targeting Myc were also compiled in MYCbase. The mutation and pathway data from the MYCbase were analyzed to look at the patterns and distributions across different diseases. There were few proteins/genes found common in Myc-protein interactions and Myc-DNA binding, and these can play a significant role in transcriptional feedback loops. CONCLUSION: In this report, we present a comprehensive integration of relevant information regarding Myc in the form of MYCbase. The data compiled in MYCbase provides a reliable data resource for functional sites at the residue level and biochemical properties of Myc in various cancers.

Integrated Regulation of HuR by Translation Repression and Protein Degradation Determines Pulsatile Expression of p53 Under DNA Damage.

Expression of tumor suppressor p53 is regulated at multiple levels, disruption of which often leads to cancer. We have adopted an approach combining computational systems modeling with experimental validation to elucidate the translation regulatory network that controls p53 expression post DNA damage. The RNA-binding protein HuR activates p53 mRNA translation in response to UVC-induced DNA damage in breast carcinoma cells. p53 and HuR levels show pulsatile change post UV irradiation. The computed model fitted with the observed pulse of p53 and HuR only when hypothetical regulators of synthesis and degradation of HuR were incorporated. miR-125b, a UV-responsive microRNA, was found to represses the translation of HuR mRNA. Furthermore, UV irradiation triggered proteasomal degradation of HuR mediated by an E3-ubiquitin ligase tripartite motif-containing 21 (TRIM21). The integrated action of miR-125b and TRIM21 constitutes an intricate control system that regulates pulsatile expression of HuR and p53 and determines cell viability in response to DNA damage.

PPIMpred: a web server for high-throughput screening of small molecules targeting protein-protein interaction.

PPIMpred is a web server that allows high-throughput screening of small molecules for targeting specific protein-protein interactions, namely Mdm2/P53, Bcl2/Bak and c-Myc/Max. Three different kernels of support vector machine (SVM), namely, linear, polynomial and radial basis function (RBF), and two other machine learning techniques including Naive Bayes and Random Forest were used to train the models. A fivefold cross-validation technique was used to measure the performance of these classifiers. The RBF kernel of SVM outperformed and/or was comparable with all other methods with accuracy values of 83%, 79% and 90% for Mdm2/P53, Bcl2/Bak and c-Myc/Max, respectively. About 80% of the predicted SVM scores of training/testing datasets from Mdm2/P53 and Bcl2/Bak have significant IC50 values and docking scores. The proposed models achieved an accuracy of 66-90% with blind sets. The three mentioned (Mdm2/P53, Bcl2/Bak and c-Myc/Max) proposed models were screened in a large dataset of 265 242 small chemicals from National Cancer Institute open database. To further realize the robustness of this approach, hits with high and random SVM scores were used for molecular docking in AutoDock Vina wherein the molecules with high and random predicted SVM scores yielded moderately significant docking scores (p-values < 0.1). In addition to the above-mentioned classification scheme, this web server also allows users to get the structural and chemical similarities with known chemical modulators or drug-like molecules based on Tanimoto coefficient similarity search algorithm. PPIMpred is freely available at http://bicresources.jcbose.ac.in/ssaha4/PPIMpred/.