Identification of fish species through tRNA-based primer design.

BACKGROUND: The correct establishment of the barcode classification system for fish can facilitate biotaxonomists to distinguish fish species, and it can help the government to verify the authenticity of the ingredients of fish products or identify unknown fish related samples. The Cytochrome c oxidation I (COI) gene sequence in the mitochondria of each species possesses unique characteristics, which has been widely used as barcodes in identifying species in recent years. Instead of using COI gene sequences for primer design, flanking tRNA segments of COI genes from 2618 complete fish mitochondrial genomes were analyzed to discover suitable primers for fish classification at taxonomic family level. The minimal number of primer sets is designed to effectively distinguish various clustered groups of fish species for identification applications. Sequence alignment analysis and cross tRNA segment comparisons were applied to check and ensure the primers for each cluster group are exclusive. RESULTS: Two approaches were applied to improve primer design and re-cluster fish species. The results have shown that exclusive primers for 2618 fish species were successfully discovered through in silico analysis. In addition, we applied sequence alignment analysis to confirm that each pair of primers can successfully identify all collected fish species at the taxonomic family levels. CONCLUSIONS: This study provided a practical strategy to discover unique primers for each fishery species and a comprehensive list of exclusive primers for extracting COI barcode sequences of all known fishery species. Various applications of verification of fish products or identification of unknown fish species could be effectively achieved.

Comprehensive Linear Epitope Prediction System for Host Specificity in Nodaviridae.

BACKGROUND: Nodaviridae infection is one of the leading causes of death in commercial fish. Although many vaccines against this virus family have been developed, their efficacies are relatively low. Nodaviridae are categorized into three subfamilies: alphanodavirus (infects insects), betanodavirus (infects fish), and gammanodavirus (infects prawns). These three subfamilies possess host-specific characteristics that could be used to identify effective linear epitopes (LEs). METHODOLOGY: A multi-expert system using five existing LE prediction servers was established to obtain initial LE candidates. Based on the different clustered pathogen groups, both conserved and exclusive LEs among the Nodaviridae family could be identified. The advantages of undocumented cross infection among the different host species for the Nodaviridae family were applied to re-evaluate the impact of LE prediction. The surface structural characteristics of the identified conserved and unique LEs were confirmed through 3D structural analysis, and concepts of surface patches to analyze the spatial characteristics and physicochemical propensities of the predicted segments were proposed. In addition, an intelligent classifier based on the Immune Epitope Database (IEDB) dataset was utilized to review the predicted segments, and enzyme-linked immunosorbent assays (ELISAs) were performed to identify host-specific LEs. PRINCIPAL FINDINGS: We predicted 29 LEs for Nodaviridae. The analysis of the surface patches showed common tendencies regarding shape, curvedness, and PH features for the predicted LEs. Among them, five predicted exclusive LEs for fish species were selected and synthesized, and the corresponding ELISAs for antigenic feature analysis were examined. CONCLUSION: Five identified LEs possessed antigenicity and host specificity for grouper fish. We demonstrate that the proposed method provides an effective approach for in silico LE prediction prior to vaccine development and is especially powerful for analyzing antigen sequences with exclusive features among clustered antigen groups.

Conformational epitope matching and prediction based on protein surface spiral features.

BACKGROUND: A conformational epitope (CE) is composed of neighboring amino acid residues located on an antigenic protein surface structure. CEs bind their complementary paratopes in B-cell receptors and/or antibodies. An effective and efficient prediction tool for CE analysis is critical for the development of immunology-related applications, such as vaccine design and disease diagnosis. RESULTS: We propose a novel method consisting of two sequential modules: matching and prediction. The matching module includes two main approaches. The first approach is a complete sequence search (CSS) that applies BLAST to align the sequence with all known antigen sequences. Fragments with high epitope sequence identities are identified and the predicted residues are annotated on the query structure. The second approach is a spiral vector search (SVS) that adopts a novel surface spiral feature vector for large-scale surface patch detection when queried against a comprehensive epitope database. The prediction module also contains two proposed subsystems. The first system is based on knowledge-based energy and geometrical neighboring residue contents, and the second system adopts combinatorial features, including amino acid contents and physicochemical characteristics, to formulate corresponding geometric spiral vectors and compare them with all spiral vectors from known CEs. An integrated testing dataset was generated for method evaluation, and our two searching methods effectively identified all epitope regions. The prediction results show that our proposed method outperforms previously published systems in terms of sensitivity, specificity, positive predictive value, and accuracy. CONCLUSIONS: The proposed method significantly improves the performance of traditional epitope prediction. Matching followed by prediction is an efficient and effective approach compared to predicting directly on specific surfaces containing antigenic characteristics.

A voting mechanism-based linear epitope prediction system for the host-specific Iridoviridae family.

BACKGROUND: The Iridoviridae family is categorized into five genera and clustered into two subfamilies: Alphairidovirinae includes Lymphocystivirus, Ranavirus (GIV), and Megalocystivirus (TGIV), which infect vertebrate hosts and Betairidovirinae includes Iridovirus and Chloriridovirus, which infect invertebrate hosts. Clustered Iridoviridae subfamilies possess host-specific characteristics, which can be considered as exclusive features for in-silico prediction of effective epitopes for vaccine development. A voting mechanism-based linear epitope (LE) prediction system was applied to identify and endorse LE candidates with a minimum length requirement for each clustered subfamily RESULTS: The experimental results showed that four conserved epitopes among the Iridovirideae family, one exclusive epitope for invertebrate subfamily and two exclusive epitopes for vertebrate family were predicted. These predicted LE candidates were further validated by ELISA assays for evaluating the strength of antigenicity and cross antigenicity. The conserved LEs for Iridoviridae family reflected high antigenicity responses for the two subfamilies, while exclusive LEs reflected high antigenicity responses only for the host-specific subfamily CONCLUSIONS: Host-specific characteristics are important features and constraints for effective epitope prediction. Our proposed voting mechanism based system provides a novel approach for in silico LE prediction prior to vaccine development, and it is especially powerful for analyzing antigen sequences with exclusive features between two clustered groups.

Comparison of grouper infection with two different iridoviruses using transcriptome sequencing and multiple reference species selection.

Due to high-density aquafarming in Taiwan, groupers are commonly infected with two different iridoviruses: Megalocytivirus (grouper iridovirus of Taiwan, TGIV) and Ranavirus (grouper iridovirus, GIV). Iridoviral diseases cause mass mortality, and surviving fish retain these pathogens, which can then be horizontally transferred. These viruses have therefore become a major challenge for grouper aquaculture. In this study, comparisons of the biological responses of groupers to infection with these two different iridoviruses were performed. A novel approach for transcriptomic analysis was proposed to enhance the discovery of differentially expressed genes and associated biological pathways. In this method, suitable and available reference species are selected from the NCBI taxonomy tree and the Ensembl and KEGG databases instead of either choosing only one model species or adopting the NCBI non-redundant dataset as references. Our results show that selection of multiple appropriate model species as references increases the efficiency and performance of analyses compared to those of traditional approaches. Using this method, 17 shared pathways and 5 specific pathways were found to be significantly differentially expressed following infection with the two iridoviruses, among which 11 pathways were additionally identified based on the proposed method of multiple reference species selection. Among the pathways responsive to infection with a specific iridovirus, the spliceosomal pathway (ko03040; p-value = 0.0011) was exclusively associated with TGIV infection, while the glycolysis/gluconeogenesis pathway (ko00010; p-value = 0.0032) was associated with GIV infection. These findings and designed corresponding biological experiments may facilitate a deeper understanding of the mechanisms by which both TGIV and GIV cause fatal infections, as well as the ways in which they induce different pathologies and symptoms. We believe that the proposed novel mechanism for de novo transcriptomic analysis provides superior and comprehensive functional annotations and that the resulting shared and specific pathways identified may help immunologists develop specific vaccines against various types of iridovirus in the near future.

Development of a growth-hormone-conjugated nanodiamond complex for cancer therapy.

It is highly desirable to develop a therapeutic, observable nanoparticle complex for specific targeting in cancer therapy. Growth hormone (GH) and its antagonists have been explored as cancer cell-targeting molecules for both imaging and therapeutic applications. In this study, a low toxicity, biocompatible, therapeutic, and observable GH-nanoparticle complex for specifically targeting growth hormone receptor (GHR) in cancer cells was synthesized by conjugating GH with green fluorescence protein and carboxylated nanodiamond. Moreover, we have shown that this complex can be triggered by laser irradiation to create a "nanoblast" and induce cell death in the A549 non-small-cell lung cancer cell line via the apoptotic pathway. This laser-mediated, cancer-targeting platform can be widely used in cancer therapy.

Synthesis of apolipoprotein B lipoparticles to deliver hydrophobic/amphiphilic materials.

To develop a drug delivery system (DDS), it is critical to address challenging tasks such as the delivery of hydrophobic and amphiphilic compounds, cell uptake, and the metabolic fate of the drug delivery carrier. Low-density lipoprotein (LDL) has been acknowledged as the human serum transporter of natively abundant lipoparticles such as cholesterol, triacylglycerides, and lipids. Apolipoprotein B (apo B) is the only protein contained in LDL, and possesses a binding moiety for the LDL receptor that can be internalized and degraded naturally by the cell. Therefore, synthetic/reconstituting apoB lipoparticle (rABL) could be an excellent delivery carrier for hydrophobic or amphiphilic materials. Here, we synthesized rABL in vitro, using full-length apoB through a five-step solvent exchange method, and addressed its potential as a DDS. Our rABL exhibited good biocompatibility when evaluated with cytotoxicity and cell metabolic response assays, and was stable during storage in phosphate-buffered saline at 4 °C for several months. Furthermore, hydrophobic superparamagnetic iron oxide nanoparticles (SPIONPs) and the anticancer drug M4N (tetra-O-methyl nordihydroguaiaretic acid), used as an imaging enhancer and lipophilic drug model, respectively, were incorporated into the rABL, leading to the formation of SPIONPs- and M4N- containing rABL (SPIO@rABL and M4N@rABL, respectively). Fourier transform infrared spectroscopy suggested that rABL has a similar composition to that of LDL, and successfully incorporated SPIONPs or M4N. SPIO@rABL presented significant hepatic contrast enhancement in T2-weighted magnetic resonance imaging in BALB/c mice, suggesting its potential application as a medical imaging contrast agent. M4N@rABL could reduce the viability of the cancer cell line A549. Interestingly, we developed solution-phase high-resolution transmission electron microscopy to observe both LDL and SPIO@rABL in the liquid state. In summary, our LDL-based DDS, rABL, has significant potential as a novel DDS for hydrophobic and amphiphilic materials, with good cell internalization properties and metabolicity.

Inhibitory effects of chloroform extracts derived from Corbicula fluminea on the release of pro-inflammatory cytokines.

Corbicula fluminea, the primary freshwater bivalve cultivated in Taiwan, was formerly used as a remedy for hepatitis. Recent reports indicate that C. fluminea has many bioactivities, but it remains unknown whether C. fluminea affects inflammation. This study explored the anti-inflammatory activity of C. fluminea. C. fluminea was first treated with chloroform to obtain clam chloroform extracts (CCEs). On the basis of the assay for the release of pro-inflammatory cytokines in vitro and in vivo, the results show that the CCEs significantly lowered the release of lipopolysaccharide (LPS)-induced pro-inflammatory cytokines. Additionally, the CCEs reduced LPS-induced organ damage. Real-time polymerase chain reaction analysis suggested that CCEs inhibit the LPS-induced mRNA expression of interleukin-1ß and tumor necrosis factor-α. Western blot analysis indicated that the CCEs increased expression of IκB and attenuated the phosphorylation of IκB. Gas chromatography-mass spectrometry suggests that phytosterols and fatty acids are responsible for the anti-inflammatory properties of CCEs. Taken together, CCEs have the potential to be developed as an anti-inflammatory functional food.

Identification of antigens for the development of a subunit vaccine against Photobacterium damselae ssp. piscicida.

Photobacterium damselae ssp. piscicida (Ph.d.p.), the causative agent of photobacteriosis, is among the most important pathogens affecting finfish aquaculture globally. With the emergence of recombinant technology, subunit vaccines have been actively pursued, but mostly for viral diseases. Bacterial subunit vaccines are more difficult to develop since the bacterial genome is more complex, with numerous candidate antigens, leading to a lengthy and laborious screening process. Immunoproteomics, using western blotting on protein analyzed with 2DE and LC-MS/MS to isolate immune-reactive proteins and acquire amino acid sequences, followed by recombinant technology to clone the candidate gene, identified eight candidate antigens from Ph.d.p., which have been cloned and expressed in Escherichia coli BL21(DE3). These proteins were purified and used as antigens in an efficacy trial. Three, rHSP60, rENOLASE, and rGAPDH proteins, elicited higher specific antibody titers and stronger protective immunity than the other five and an inactivated Ph.d.p. whole bacterial vaccine. These three antigens may be candidates for the development of a subunit vaccine against Ph.d.p.

A new amide alkaloid from the leaves of Piper sarmentosum.

A new amide alkaloid, N-(3',4',5'-trimethoxy-cis-cinnamoyl)pyrrolidine (1), named sarmentomicine was isolated from the ethanol extract of the leaves of Malayan Piper sarmentosum, together with two known phenylpropanoids. Their structures were elucidated on the basis of spectroscopic analysis.