Molecular cloning of an invertebrate goose-type lysozyme gene from Chlamys farreri, and lytic activity of the recombinant protein

Lysozyme is a widely distributed hydrolase possessing lytic activity against bacterial peptidoglycan, which enables it to protect the host against pathogenic infection. In the present study, the cDNA of an invertebrate goose-type lysozyme (designated CFLysG) was cloned from Zhikong scallop Chlamys farreri by expressed sequence tag (EST) and rapid amplification of cDNA ends (RACE) techniques. The full-length cDNA of CFLysG consisted of 829 nucleotides with a canonical polyadenylation signal sequence AATAAA and a poly(A) tail, and an open reading frame (ORF) of 603 bp encoding a polypeptide of 200 amino acid residues with a predicted molecular weight of 21.92 kDa and theoretical isoelectric point of 7.76. The high similarity of CFLysG with goose-type (g-type) lysozymes in vertebrate indicated that CFLysG should be an invertebrate counterpart of g-type lysozyme family, which suggested that the origin of g-type lysozyme preceded the emergence of urochordates and even preceded the emergence of deuterostomes. Similar to most g-type lysozymes, CFLysG possessed all conserved features critical for the fundamental structure and function of g-type lysozymes, such as three catalytic residues (Glu 82, Asp 97, Asp 108). By Northern blot analysis, mRNA transcript of CFLysG was found to be most abundantly expressed in the tissues of gills, hepatopancreas and gonad, weakly expressed in the tissues of haemocytes and mantle, while undetectable in the adductor muscle. These results suggested that CFLysG could possess combined features of both the immune and digestive adaptive lysozymes. To gain insight into the in vitro lytic activities of CFLysG, the mature peptide coding region was cloned into Pichia pastoris for heterogeneous expression. Recombinant CFLysG showed inhibitive effect on the growth of both Gram-positive and Gram-negative bacteria with more potent activities against Gram-positive bacteria, which indicated the involvement of CFLysG in the innate immunity of C. farreri. (c) 2006 Elsevier Ltd. All rights reserved.

SmC2P1, a C2 domain protein from Scophthalmus maximus that binds bacterial pathogen-infected lymphocytes and reduces bacterial survival

C2 domains are protein structural modules found in many eukaryotic proteins involved in signal transduction, membrane trafficking, and immune defense. Most of the studied C2 domain-containing proteins are multi-domained in structure, in which the C2 domain is an independently folded motif and plays an essential role in calcium-dependent membrane-targeting. Although C2 domains isolated from intact proteins have been studied for biological functions, no study on natural proteins containing C2 domain only has been documented. In this study, we identified a Scophthalmus maximus protein SmC2P1 that is comprised of a single C2 domain and lacks any other apparent domain structures. The deduced amino acid sequence of SmC2P1 contains 129 residues and shares 36-38% identities with the C2 domains of the perforins of several fish species. Like typical C2 domains, SmC2P1 is predicted to organize into eight beta-strands with a Ca2+-binding site located in inter-strand loops. SmC2P1 expression was detected, in deceasing order, in liver, spleen, blood, brain, muscle, kidney, gill, and heart. Experimental challenge of turbot with a bacterial pathogen significantly upregulated SmC2P1 expression in kidney in a time-dependent manner. Recombinant SmC2P1 purified from yeast exhibits no hemolytic activity but binds to pathogen-infected kidney lymphocytes in the presence of calcium. Furthermore, interaction of recombinant SmC2P1 with bacterium-infected lymphocytes reduced bacterial survival. These results indicate that SmC2P1 is a functional protein that is involved in host immune defense against bacterial infection. (C) 2010 Elsevier Ltd. All rights reserved.

Cloning and structure analysis of hydrogenase gene from Chlamydomonas reinhardtii SE

The cDNA of Chlamydomonas reinhardtii SE encoding hydrogenase (HydA2) was obtained from the total RNA of C reinhardtii SE by RT-PCR. The DNA of hydrogenase was amplified by PCR from the genomic DNA of C reinhardtii SE. The cDNA and DNA of hydrogenase were sequenced, respectively. The structure of hydrogenase gene was analyzed by biology software. The open reading frame predicts that the hydrogenase is composed of 3584 bp encoding 505 amino acids in length with a predicted M.W. of 53.69 kDa. Ten exons (including 1518 bp) and nine introns (including 2066 bp) have been found in the hydrogenase, and there were two potential N-glycosylate sites, eight protein kinase C phosphorylation site, eight casein kinase H phosphorylation site and one sulphorylation in the sequence. The theory pI was 6.15. Total number of negatively charged residues (Asp + Glu) and positively charged residues (Arg + Lys) were 55 and 61, respectively. (c) 2005 Elsevier Ltd. All rights reserved.

Confirmation of Data Mining Based Predictions of Protein Function

King, R. D. and Wise, P. H. and Clare, A. (2004) Confirmation of Data Mining Based Predictions of Protein Function. Bioinformatics 20(7), 1110-1118

Application of Inductive Logic Programming to Structure-Based Drug Design

Enot, D. and King, R. D. (2003) Application of Inductive Logic Programming to Structure-Based Drug Design. 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD '03). Springer LNAI 2838 p156-167

Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light

Chungui Lu, Olga A. Koroleva, John F. Farrar, Joe Gallagher, Chris J. Pollock, and A. Deri Tomos (2002). Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light. Plant Physiology, 130 (3) pp.1335-1348 Sponsorship: BBSRC RAE2008

Integration of relational and hierarchical network information for protein function prediction

BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.