Dependency on de novo protein synthesis and proteomic changes during metamorphosis of the marine bryozoan Bugula neritina
Article - Full Text
Supplemental File 1
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Bioscience Core Lab
Computational Bioscience Research Center (CBRC)
Integrative Systems Biology Lab
OCRF- Special Academic Partnership
Online Publication Date2010-05-25
Print Publication Date2010
Permanent link to this recordhttp://hdl.handle.net/10754/325256
MetadataShow full item record
AbstractBackground: Metamorphosis in the bryozoan Bugula neritina (Linne) includes an initial phase of rapid morphological rearrangement followed by a gradual phase of morphogenesis. We hypothesized that the first phase may be independent of de novo synthesis of proteins and, instead, involves post-translational modifications of existing proteins, providing a simple mechanism to quickly initiate metamorphosis. To test our hypothesis, we challenged B. neritina larvae with transcription and translation inhibitors. Furthermore, we employed 2D gel electrophoresis to characterize changes in the phosphoproteome and proteome during early metamorphosis. Differentially expressed proteins were identified by liquid chromatography tandem mass spectrometry and their gene expression patterns were profiled using semi-quantitative real time PCR.Results: When larvae were incubated with transcription and translation inhibitors, metamorphosis initiated through the first phase but did not complete. We found a significant down-regulation of 60 protein spots and the percentage of phosphoprotein spots decreased from 15% in the larval stage to12% during early metamorphosis. Two proteins--the mitochondrial processing peptidase beta subunit and severin--were abundantly expressed and phosphorylated in the larval stage, but down-regulated during metamorphosis. MPPbeta and severin were also down-regulated on the gene expression level.Conclusions: The initial morphogenetic changes that led to attachment of B. neritina did not depend on de novo protein synthesis, but the subsequent gradual morphogenesis did. This is the first time that the mitochondrial processing peptidase beta subunit or severin have been shown to be down-regulated on both gene and protein expression levels during the metamorphosis of B. neritina. Future studies employing immunohistochemistry to reveal the expression locality of these two proteins during metamorphosis should provide further evidence of the involvement of these two proteins in the morphogenetic rearrangement of B. neritina. 2010 Wong et al; licensee BioMed Central Ltd.
CitationWong Y, Arellano SM, Zhang H, Ravasi T, Qian P-Y (2010) Dependency on de novo protein synthesis and proteomic changes during metamorphosis of the marine bryozoan Bugula neritina. Proteome Science 8: 25. doi:10.1186/1477-5956-8-25.
PubMed Central IDPMC2890537
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Phosphoproteome analysis during larval development and metamorphosis in the spionid polychaete Pseudopolydora vexillosa.
- Authors: Chandramouli KH, Mok FS, Wang H, Qian PY
- Issue date: 2011 May 25
- 2D gel-based proteome and phosphoproteome analysis during larval metamorphosis in two major marine biofouling invertebrates.
- Authors: Thiyagarajan V, Wong T, Qian PY
- Issue date: 2009 Jun
- Changes in the proteome and phosphoproteome expression in the bryozoan Bugula neritina larvae in response to the antifouling agent butenolide.
- Authors: Qian PY, Wong YH, Zhang Y
- Issue date: 2010 Oct
- Quantitative proteomics identify molecular targets that are crucial in larval settlement and metamorphosis of Bugula neritina.
- Authors: Zhang H, Wong YH, Wang H, Chen Z, Arellano SM, Ravasi T, Qian PY
- Issue date: 2011 Jan 7
- In Silico Prediction of Neuropeptides/Peptide Hormone Transcripts in the Cheilostome Bryozoan Bugula neritina.
- Authors: Wong YH, Yu L, Zhang G, He LS, Qian PY
- Issue date: 2016
Showing items related by title, author, creator and subject.
ProDis-ContSHC: Learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrievalWang, Jim Jing-Yan; Gao, Xin; Wang, Quanquan; Li, Yongping (BMC Bioinformatics, Springer Nature, 2012-05-08) [Article]Background: The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database.Results: In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis-ContSHC regularizes an existing dissimilarity measure dij by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (i, j), if their context N (i) and N (j) is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing dij by a factor learned from the context N (i) and N (j). Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new Supervised learned Dissimilarity measure, we update the Protein Hierarchial Context Coherently in an iterative algorithm--ProDis-ContSHC.We test the performance of ProDis-ContSHC on two benchmark sets, i.e., the ASTRAL 1.73 database and the FSSP/DALI database. Experimental results demonstrate that plugging our supervised contextual dissimilarity measures into the retrieval systems significantly outperforms the context-free dissimilarity/similarity measures and other unsupervised contextual dissimilarity measures that do not use the class label information.Conclusions: Using the contextual proteins with their class labels in the database, we can improve the accuracy of the pairwise dissimilarity/similarity measures dramatically for the protein retrieval tasks. In this work, for the first time, we propose the idea of supervised contextual dissimilarity learning, resulting in the ProDis-ContSHC algorithm. Among different contextual dissimilarity learning approaches that can be used to compare a pair of proteins, ProDis-ContSHC provides the highest accuracy. Finally, ProDis-ContSHC compares favorably with other methods reported in the recent literature. 2012 Wang et al.; licensee BioMed Central Ltd.
CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure predictionCui, Xuefeng; Lu, Zhiwu; wang, sheng; Wang, Jim Jing-Yan; Gao, Xin (Bioinformatics, Oxford University Press (OUP), 2016-06-15) [Article]Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.
Auxin efflux by PIN-FORMED proteins is activated by two different protein kinases, D6 PROTEIN KINASE and PINOIDZourelidou, Melina; Absmanner, Birgit; Weller, Benjamin; Barbosa, Inês CR; Willige, Björn C; Fastner, Astrid; Streit, Verena; Port, Sarah A; Colcombet, Jean; de la Fuente van Bentem, Sergio; Hirt, Heribert; Kuster, Bernhard; Schulze, Waltraud X; Hammes, Ulrich Z; Schwechheimer, Claus (eLife, eLife Sciences Publications, Ltd, 2014-06-19) [Article]The development and morphology of vascular plants is critically determined by synthesis and proper distribution of the phytohormone auxin. The directed cell-to-cell distribution of auxin is achieved through a system of auxin influx and efflux transporters. PIN-FORMED (PIN) proteins are proposed auxin efflux transporters, and auxin fluxes can seemingly be predicted based on the-in many cells-asymmetric plasma membrane distribution of PINs. Here, we show in a heterologous Xenopus oocyte system as well as in Arabidopsis thaliana inflorescence stems that PIN-mediated auxin transport is directly activated by D6 PROTEIN KINASE (D6PK) and PINOID (PID)/WAG kinases of the Arabidopsis AGCVIII kinase family. At the same time, we reveal that D6PKs and PID have differential phosphosite preferences. Our study suggests that PIN activation by protein kinases is a crucial component of auxin transport control that must be taken into account to understand auxin distribution within the plant.