NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm

BACKGROUND: Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. RESULTS: In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM), also have been employed and compared with NBA-Palm. CONCLUSION: Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from:

The lncRNA ADAMTS9-AS2 Regulates RPL22 to Modulate TNBC Progression via Controlling the TGF-β Signaling Pathway

BackgroundLong non-coding RNAs (lncRNAs) are key regulators of triple-negative breast cancer (TNBC) progression, but further work is needed to fully understand the functional relevance of these non-coding RNAs in this cancer type. Herein, we explored the functional role of the lncRNA ADAMTS9-AS2 in TNBC.MethodsNext-generation sequencing was conducted to compare the expression of different lncRNAs in TNBC tumor and paracancerous tissues, after which ADAMTS9-AS2differential expression in these tumor tissues was evaluated via qPCR. The functional role of this lncRNA was assessed by overexpressing it in vitro and in vivo. FISH and PCR were used to assess the localization of ADAMTS9-AS2within cells. Downstream targets of ADAMTS9-AS2 signaling were identified via RNA pulldown assays and transcriptomic sequencing.ResultsThe expression ofADAMTS9-AS2 was decreased in TNBC tumor samples (P < 0.05), with such downregulation being correlated with TNM stage, age, and tumor size. Overexpressing ADAMTS9-AS2 promoted the apoptotic death and cell cycle arrest of tumor cells in vitro and inhibited tumor growth in vivo. From a mechanistic perspective, ADAMTS9-AS2 was found to control the expression of RPL22 and to thereby modulate TGF-β signaling to control TNBC progression.ConclusionADAMTS9-AS2 controls the expression of RPL22 and thereby regulates TNBC malignancy via the TGF-β signaling pathway

Early life perfluorooctanesulphonic acid (PFOS) exposure impairs zebrafish organogenesis

Additional authors (Zengxin Gai and Xue Ma) appear and the author order is revised on the published version of this article.As a persistent organic contaminant, perfluorooctanesulphonic acid (PFOS) has been widely detected in the environment, wildlife, and humans. The present study revealed that zebrafish embryos exposed to 16 µM PFOS during a sensitive window of 48-96 hour post-fertilization (hpf) disrupted larval morphology at 120 hpf. Malformed zebrafish larvae were characterized by uninflated swim bladder, less developed gut, and curved spine. Histological and ultrastructural examination of PFOS-exposed larvae showed structural alterations in swim bladder and gut. Whole genome microarray was used to identify the early transcripts dysregulated following exposure to 16 µM PFOS at 96 hpf. In total, 1,278 transcripts were significantly misexpressed (p < 0.05) and 211 genes were changed at least two-fold upon PFOS exposure in comparison to the vehicle exposed control group. A PFOS-induced network of perturbed transcripts relating to swim bladder and gut development revealed that misexpression of genes were involved in organogenesis. Taken together, early life stage exposure to PFOS perturbs various molecular pathways potentially resulting in observed defects in swim bladder and gut development.This is an author's peer-reviewed manuscript. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/aquatic-toxicology/.Keywords: Perfluorooctanesulfonic acid, Zebrafish embryo, Developmental toxicity, Swim bladder, GutKeywords: Perfluorooctanesulfonic acid, Zebrafish embryo, Developmental toxicity, Swim bladder, Gu

MiCroKit 3.0: an integrated database of midbody, centrosome and kinetochore

During cell division/mitosis, a specific subset of proteins is spatially and temporally assembled into protein super complexes in three distinct regions, i.e. centrosome/spindle pole, kinetochore/centromere and midbody/cleavage furrow/phragmoplast/bud neck, and modulates cell division process faithfully. Although many experimental efforts have been carried out to investigate the characteristics of these proteins, no integrated database was available. Here, we present the MiCroKit database (http://microkit.biocuckoo.org) of proteins that localize in midbody, centrosome and/or kinetochore. We collected into the MiCroKit database experimentally verified microkit proteins from the scientific literature that have unambiguous supportive evidence for subcellular localization under fluorescent microscope. The current version of MiCroKit 3.0 provides detailed information for 1489 microkit proteins from seven model organisms, including Saccharomyces cerevisiae, Schizasaccharomyces pombe, Caenorhabditis elegans, Drosophila melanogaster, Xenopus laevis, Mus musculus and Homo sapiens. Moreover, the orthologous information was provided for these microkit proteins, and could be a useful resource for further experimental identification. The online service of MiCroKit database was implemented in PHP + MySQL + JavaScript, while the local packages were developed in JAVA 1.5 (J2SE 5.0)

Phase portraits and optical soliton solutions of coupled Sasa–Satsuma model in birefringent fibers

The main purpose of this paper is to discuss the optical soliton solutions and phase portraits of the coupled Sasa–Satsuma model in nonlinear optics. This model is usually used to describe the propagation of femtosecond pulses in optical fibers. By using traveling wave transformation, the coupled Sasa–Satsuma model is simplified into the coupled nonlinear ordinary differential equations. After that, the coupled nonlinear ordinary differential equations are transformed into two-dimensional planar dynamic system with the Hamiltonian system. According to the bifurcation theory of planar dynamical system, the phase portrait of two-dimensional dynamical system is drawn. What is more, some very important optical soliton solutions are also constructed. In order to explain the propagation of optical solitons, three-dimensional diagrams, two-dimensional diagrams and the contour plots of the obtained solutions are drawn by using Maple software

GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy *S⃞

Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been addressed. In this work, we adopted a well established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily, and single PK. In addition, we developed a simple approach to estimate the theoretically maximal false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large scale prediction of more than 13,000 mammalian phosphorylation sites by GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic prediction of Aurora-B-specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases and is freely available on line

GPS-SNO: computational prediction of protein S-nitrosylation sites with a modified GPS algorithm.

As one of the most important and ubiquitous post-translational modifications (PTMs) of proteins, S-nitrosylation plays important roles in a variety of biological processes, including the regulation of cellular dynamics and plasticity. Identification of S-nitrosylated substrates with their exact sites is crucial for understanding the molecular mechanisms of S-nitrosylation. In contrast with labor-intensive and time-consuming experimental approaches, prediction of S-nitrosylation sites using computational methods could provide convenience and increased speed. In this work, we developed a novel software of GPS-SNO 1.0 for the prediction of S-nitrosylation sites. We greatly improved our previously developed algorithm and released the GPS 3.0 algorithm for GPS-SNO. By comparison, the prediction performance of GPS 3.0 algorithm was better than other methods, with an accuracy of 75.80%, a sensitivity of 53.57% and a specificity of 80.14%. As an application of GPS-SNO 1.0, we predicted putative S-nitrosylation sites for hundreds of potentially S-nitrosylated substrates for which the exact S-nitrosylation sites had not been experimentally determined. In this regard, GPS-SNO 1.0 should prove to be a useful tool for experimentalists. The online service and local packages of GPS-SNO were implemented in JAVA and are freely available at: http://sno.biocuckoo.org/