The expression of peptidoglycan recognition protein-S1 gene in the scallop Chlamys farreri was enhanced after a second challenge by Listonella anguillarum

A more rapid and powerful response against repeated exposure of same pathogen in vertebrates is usually considered as the reflection of immunological memory, but it is not well understood in invertebrates. In the present Study, the temporal expression profiles of Chlamys farreri peptidoglycan recognition protein-S1 (CfPGRP-S1) gene after two challenges of Listonella anguillarum were examined to evaluate priming response in scallops. The up-regulation of CFPGRP-S1 mRNA occurred 3 h earlier, and the expression level was significant higher (P < 0.05), after the second challenge than that after the first challenge. The preliminary results Provided new insights into invertebrate immunological memory, and they also would be helpful to develop strategies for disease control. (C) 2008 Elsevier Inc. All rights reserved.

Molecular cloning and characterisation of a pattern recognition protein, lipopolysaccharide and beta-1,3-glucan binding protein (LGBP) from Chinese shrimp Fenneropenaeus chinensis

A pattern recognition protein (PRP), lipopolysaccharide and beta-1,3-glucan binding protein (LGBP) cDNA was cloned from the haemocyte of Chinese shrimp Fenneropenaeus chinensis by the techniques of homology cloning and RACE. Analysis of nucleotide sequence revealed that the full-length cDNA of 1,275 bp has an open reading frame of 1,098 bp encoding a protein of 366 amino acids including a 17 amino acid signal peptide. Sequence comparison of the deduced amino acid sequence of F. chinensis LGBP showed a high identity of 94%, 90%, 87%, 72% and 63% with Penaeus monodon BGBP, Litopenaeus stylirostris LGBP, Marsupenaeu japonicus BGBP, Homarus gammarus BGBP and Pacifastacus leniusculus LGBP, respectively. The calculated molecular mass of the mature protein is 39,857 Da with a deduced pI of 4.39. Two putative integrin binding motifs, RGD (Arg-Gly-Asp) and a potential recognition motif for beta-1,3-linkage of polysaccharides were observed in LGBP sequence. RT-PCR analysis showed that LGBP gene expresses in haemocyte and hepatopancreas only, but not in other tissues. Capillary electrophoresis RT-PCR method was used to quantify the variation of mRNA transcription level during artificial infection with heat-killed Vibrio anguillarum and Staphylococcus aureusin. A significant enhancement of LGBP transcription was appeared at 6 h post-injection in response to bacterial infection. These results have provided useful information to understand the function of LGBP in shrimp.

Molecular cloning and mRNA expression of peptidoglycan recognition protein (PGRP) gene in bay scallop (Argopecten irradians, Lamarck 1819)

Peptidoglycan recognition proteins (PGRPs) are a type of pattern recognition molecules (PRM) that recognize the unique cell wall component peptidoglycan (PGN) of bacteria and are involved in innate immunity. The first bivalve PGRP cDNA sequence was cloned from bay scallop Argopecten irradians by expressed sequence tag (EST) and PCR technique. The full-length cDNA of bay scallop PGRP (designated AiPGRP) gene contained 10 18 bp with a 615-bp open reading frame that encoded a polypeptide of 205 amino acids. The predicted amino acid sequence of AiPGRP shared high identity with PGRP in other organisms, such as PGRP precursor in Trichoplusia ni and PGRP SC2 in Drosophila melanogaster. A quantitative reverse transcriptase Real-Time PCR (qRT-PCR) assay was developed to assess the mRNA expression of AiPGRP in different tissues and the temporal expression of AiPGRP in the mixed primary cultured hemocytes challenged by microbial components lipopolyssacharide (LPS) from Escherichia coli and PGN from Micrococcus luteus. Higher-level mRNA expression of AiPGRP was detected in the tissues of hemocytes, gonad and kidney. The expression of AiPGRP in the mixed primary cultured hemocytes was up regulated after stimulated by PGN, while LPS from E. coli did not induce AiPGRP expression. The results indicated that AiPGRP was a constitutive and inducible expressed protein that was mainly induced by PGN and could be involved in scallop immune response against Gram-positive bacteria infection. (c) 2006 Elsevier Ltd. All rights reserved.

Molecular cloning and characterization of a short type peptidoglycan recognition protein (CfPGRP-S1) cDNA from Zhikong scallop Chlamys farreri

Peptidoglycan recognition protein (PGRP) specifically binds to peptidoglycan and plays a crucial role in the innate immune responses as a pattern recognition receptor (PRR). The cDNA of a short type PGRP was cloned from scallop Chlamys farreri (named CfPGRP-SI) by homology cloning with degenerate primers, and confirmed by virtual Northern blots. The full length of CfPGRP-SI cDNA was 1073 bp in length, including a 5 ' untranslated region (UTR) of 59 bp, a 3 ' UTR of 255 bp, and an open reading frame (ORF) of 759 bp encoding a polypeptide of 252 amino acids with an estimated molecular mass of 27.88 kDa and a predicted isoelectric point of 8.69. BLAST analysis revealed that CfPGRP-S1 shared high identities with other known PGRPs. A conserved PGRP domain and three zinc-binding sites were present at its C-terminus. The temporal expression of QPGRP-S1 gene in healthy, Vibrio anguillarum-challenged and Micrococcus lysodeikticus-challenged scallops was measured by RT-PCR analysis. The expression of CfPGRP-S1 was upregulated initially in the first 12 h or 24 h either by M. lysodeikticus or V. anguillarum challenge and reached the maximum level at 24 h or 36 h, then dropped progressively, and recovered to the original level as the stimulation decreased at 72 h. There was no significant difference between V. anguillarum and M. lysodeikticus challenge. The results indicated that the CfPGRP-S1 was a constitutive and inducible acute-phase protein which was involved in the immune response against bacterial infection. (c) 2007 Elsevier Ltd. All rights reserved.

CfLGBP, a pattern recognition receptor in Chlamys farreri involved in the immune response against various bacteria

Lipopolysaccharide and beta-1, 3-glucan binding protein (LGBP) is a kind of pattern recognition receptor, which can recognize and bind LPS and beta-1, 3-glucan, and plays curial roles in the innate immune defense against Gram-negative bacteria and fungi. In this study, the functions of LGBP from Zhikong scallop Chlamys farreri performed in innate immunity were analyzed. Firstly, the mRNA expression of CfLGBP in hemocytes toward three typical PAMPS stimulation was examined by realtime PCR. It was up-regulated extremely (P < 0.01) post stimulation of LPS and beta-glucan, and also exhibited a moderate up-regulation (P < 0.01) after PGN injection. Further PAMPs binding assay with the polyclonal antibody specific for CfLGBP proved that the recombinant CfLGBP (designated as rCfLGBP) could bind not only LPS and beta-glucan, but also PGN in vitro. More importantly, rCfLGBP exhibited obvious agglutination activity towards Gram-negative bacteria Escherichia coil, Gram-positive bacteria Bacillus subtilis and fungi Pichia pastoris. Taking the results of immunofluorescence assay into account, which displayed CfLGBP was expressed specifically in the immune cells (hemocytes) and vulnerable organ (gill and mantle), we believed that LGBP in C farreri, serving as a multi-functional PRR, not only involved in the immune response against Gram-negative and fungi as LGBP in other invertebrates, but also played significant role in the event of anti-Gram-positive bacteria infection. As the first functional research of LGBP in mollusks, our study provided new implication into the innate immune defense mechanisms of C. farreri and mollusks. (C) 2010 Elsevier Ltd. All rights reserved.

Peptidoglycan recognition protein of Chlamys farreri (CfPGRP-S1) mediates immune defenses against bacterial infection

Peptidoglycan recognition protein (PGRP) is an essential molecule in innate immunity for both invertebrates and vertebrates, owing to its prominent ability in detecting and eliminating the invading bacteria. Several PGRPs have been identified from mollusk, but their functions and the underlined mechanism are still unclear. In the present study, the mRNA expression profiles, location, and possible functions of PGRP-S1 from Zhikong scallop Chlamys farreri (CfPG RP-St) were analyzed. The CfPGRP-S1 protein located in the mantle, gill, kidney and gonad of the scallops. Its mRNA expression in hemocytes was up-regulated extremely after PGN stimulation (P < 0.01), while moderately after the stimulations of LPS (P < 0.01) and beta-glucan (P < 0.05). The recombinant protein of CfPGRP-S1 (designated as rCfPGRP-S1) exhibited high affinity to PGN and moderate affinity to LPS, but it did not bind beta-glucan. Meanwhile, rCfPGRP-S1 also exhibited strong agglutination activity to Gram-positive bacteria Micrococcus luteus and Bacillus subtilis and weak activity to Gram-negative bacteria Escherichia coli. More importantly, rCfPGRP-S1 functioned as a bactericidal amidase to degrade PGN and strongly inhibit the growth of E. coli and Staphyloccocus aureus in the presence of Zn2+. These results indicated that CfPGRP-S1 could not only serve as a pattern recognition receptor recognizing bacterial PGN and LPS, but also function as a scavenger involved in eliminating response against the invaders. (C) 2010 Elsevier Ltd. All rights reserved.

Computer-assisted automatic peak recognition and result evaluation for analysis of chlorinated hydrocarbons in environmental samples

A data manipulation method has been developed for automatic peak recognition and result evaluation in the analysis of organic chlorinated hydrocarbons with dual-column gas chromatography. Based on the retention times of two internal standards, pentachlorotoluene and decachlorobiphenyl, the retention times of chlorinated hydrocarbons can be calibrated automatically and accurately. It is very convenient to identify the peaks by comparing the retention times of samples with the calibrated retention times calculated from the relative retention indices of standards. Meanwhile, with a suggested two-step evaluation method the evaluation coefficients and the suitable quantitative results of each component can be automatically achieved for practical samples in an analytical system using two columns with different polarities and two internal standards. (C) 2002 Elsevier Science B.V. All rights reserved.

Stimulus Familiarity Determines Recognition Strategy for Novel 3-D Objects

We describe a psychophysical investigation of the effects of object complexity and familiarity on the variation of recognition time and recognition accuracy over different views of novel 3D objects. Our findings indicate that with practice the response times for different views become more uniform and the initially orderly dependency of the response time on the distance to a "good" view disappears. One possible interpretation of our results is in terms of a tradeoff between memory needed for storing specific-view representations of objects and time spent in recognizing the objects.

Recognition by Linear Combinations of Models

Visual object recognition requires the matching of an image with a set of models stored in memory. In this paper we propose an approach to recognition in which a 3-D object is represented by the linear combination of 2-D images of the object. If M = {M1,...Mk} is the set of pictures representing a given object, and P is the 2-D image of an object to be recognized, then P is considered an instance of M if P = Eki=aiMi for some constants ai. We show that this approach handles correctly rigid 3-D transformations of objects with sharp as well as smooth boundaries, and can also handle non-rigid transformations. The paper is divided into two parts. In the first part we show that the variety of views depicting the same object under different transformations can often be expressed as the linear combinations of a small number of views. In the second part we suggest how this linear combinatino property may be used in the recognition process.

Grouping For Recognition

This paper presents a new method of grouping edges in order to recognize objects. This grouping method succeeds on images of both two- and three- dimensional objects. So that the recognition system can consider first the collections of edges most likely to lead to the correct recognition of objects, we order groups of edges based on the likelihood that a single object produced them. The grouping module estimates this likelihood using the distance that separates edges and their relative orientation. This ordering greatly reduces the amount of computation required to locate objects and improves the system's robustness to error.

Automatic Recognition of Tractability in Inference Relations

A procedure is given for recognizing sets of inference rules that generate polynomial time decidable inference relations. The procedure can automatically recognize the tractability of the inference rules underlying congruence closure. The recognition of tractability for that particular rule set constitutes mechanical verification of a theorem originally proved independently by Kozen and Shostak. The procedure is algorithmic, rather than heuristic, and the class of automatically recognizable tractable rule sets can be precisely characterized. A series of examples of rule sets whose tractability is non-trivial, yet machine recognizable, is also given. The technical framework developed here is viewed as a first step toward a general theory of tractable inference relations.

The Effect of Indexing on the Complexity of Object Recognition

Many current recognition systems use constrained search to locate objects in cluttered environments. Previous formal analysis has shown that the expected amount of search is quadratic in the number of model and data features, if all the data is known to come from a sinlge object, but is exponential when spurious data is included. If one can group the data into subsets likely to have come from a single object, then terminating the search once a "good enough" interpretation is found reduces the expected search to cubic. Without successful grouping, terminated search is still exponential. These results apply to finding instances of a known object in the data. In this paper, we turn to the problem of selecting models from a library, and examine the combinatorics of determining that a candidate object is not present in the data. We show that the expected search is again exponential, implying that naﶥ approaches to indexing are likely to carry an expensive overhead, since an exponential amount of work is needed to week out each of the incorrect models. The analytic results are shown to be in agreement with empirical data for cluttered object recognition.

Viewpoint-Specific Representations in Three-Dimensional Object Recognition

We report a series of psychophysical experiments that explore different aspects of the problem of object representation and recognition in human vision. Contrary to the paradigmatic view which holds that the representations are three-dimensional and object-centered, the results consistently support the notion of view-specific representations that include at most partial depth information. In simulated experiments that involved the same stimuli shown to the human subjects, computational models built around two-dimensional multiple-view representations replicated our main psychophysical results, including patterns of generalization errors and the time course of perceptual learning.

An Efficient Correspondence Based Algorithm for 2D and 3D Model Based Recognition

A polynomial time algorithm (pruned correspondence search, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image, is presented. Efficient verification algorithms, based on a linear representation of location constraints, are given for the case of affine transformations among vector spaces and for the case of rigid 2D and 3D transformations with scale. Some preliminary experiments suggest that PCS is a practical algorithm. Its similarity to existing correspondence based algorithms means that a number of existing techniques for speedup can be incorporated into PCS to improve its performance.