In insects, the glutathione S-transferase is initiated in both the detoxification process and the protection of cellular membranes against oxidative damage. In this study, we identified the open reading frame (ORF) sequence of GST-iso1 and 2 from Tenebrio molitor (TmGST-iso1 and 2). To investigate the expression patterrns of TmGST-iso1 and 2 in response to herbicide, 0.06, 0.6, and 6 ㎍/㎕ of butachlor (FarmHannong, Seoul, South Korea) was challenged into T. molitor larvae, resulting that the TmGST-iso1 were highly induced at 3 and 24 h-post injection. Whereas, the highest expression of TmGST-iso2 was detected at 24 h after treatment. This study may contribute to basic information about the detoxifying activities of T. molitor.

Selecting an appropriate antigen with optimal immunogenicity and physicochemical properties is a pivotal factor to develop a protein based subunit vaccine. Despite rapid progress in modern molecular cloning and recombinant protein technology, there remains a huge challenge for purifying and using protein antigens rich in hydrophobic domains, such as membrane associated proteins. To overcome current limitations using hydrophobic proteins as vaccine antigens, we adopted in silico analyses which included bioinformatic prediction and sequence-based protein 3D structure modeling, to develop a novel periodontitis subunit vaccine against the outer membrane protein FomA of Fusobacterium nucleatum. To generate an optimal antigen candidate, we predicted hydrophilicity and B cell epitope parameter by querying to web-based databases, and designed a truncated FomA (tFomA) candidate with better solubility and preserved B cell epitopes. The truncated recombinant protein was engineered to expose epitopes on the surface through simulating amino acid sequence-based 3D folding in aqueous environment. The recombinant tFomA was further expressed and purified, and its immunological properties were evaluated. In the mice intranasal vaccination study, tFomA significantly induced antigen-specific IgG and sIgA responses in both systemic and oral-mucosal compartments, respectively. Our results testify that intelligent in silico designing of antigens provide amenable vaccine epitopes from hard-to-manufacture hydrophobic domain rich microbial antigens.

Most gene functions of biochemical pathways were still unexplored, especially interactions of constituent genes. We attempted to uncover interaction network of biochemical pathways via a survey of co-expression clusters, which we have constructed from the NCBI GEO database, and then to define key genes of networks with expression correlations between members. Top 20 pathways with high numbers of individual genes were retrieved from 178 pathways. One pathway, ‘removal of superoxide radicals’ was excluded for further study, evidencing somewhat low degree (16%, 13 out of 79 genes) of mapped probes. We employed expression correlations of random pairs of 1,000 randomly selected genes for determining a cut off r-value for gene networks. Numbers of interactions with a significant expression correlation values between members might evidence that “hub genes” play key roles among a given pathway genes. For example most interactive pathway, ‘tRNA charging pathway’, that is composed of 60 probes corresponding to genes showed 264 positive significant interactions between members of 47 genes while 5 negative interactions between members of 7 genes., evidencing ‘Os10g26050’ (methionyl-tRNA synthetase) gene with highest interactions is suggestive of a hub gene. These findings might provide some clues on evolutionary fate of co-expression genes including each of biochemical pathways, e.g. convergent evolution

In order to uncover gene regulatory networks clustering of co-expressing genes was performed using a rice micorarray dataset of 155 gene expression omnibus sample (GSM) plates in NCBI, generating a total of 1660 clusters. One cluster with 85 co-expressing genes was measured with the correlation coefficient between pairs, resulting in an average r value of 0.66 with a range of -0.08 to 0.98. This result might support the notion that genes included in each cluster play common functional role(s). We also retrieved 23 Affymetrix GeneChip spots IDs corresponding to each of candidate genes related to abiotic stresses obtained from the P1antQTL-GE database and subsequently detected 23 clusters including co-expressing genes with each of the genes. Expression profiles of co-expressing genes revealed some degree of tissue-specific expression patterns, probably reflecting the existence of, at least partial, parallel versions of stress-related networks with evolutionary process, such as subfuntionalization. The finding that several cis-elements related to abiotic stresses was detected by differences in frequency between co-expressing genes and randomly selected genes. Clustering, expression profiles, and putative cis-acting regulatory elements of co-expressing genes related to abiotic stresses may provide clues to shed further light on the gene regulatory network of stress-responsive pathway.