Prediction of carbohydrate-binding proteins from sequences using support vector machines

Transcriptome analysis of rice response to blast fungus identified core genes involved in immunity

Rice blast disease caused by the filamentous Ascomycetous fungus Magnaporthe oryzae is a major threat to rice production worldwide. The mechanisms underlying rice resistance to M. oryzae, such as transcriptional reprogramming and signalling networks, remain elusive. In this study, we carried out an in-depth comparative transcriptome study on the susceptible and resistant rice cultivars in response to M. oryzae. Our analysis highlighted that rapid, high-amplitude transcriptional reprogramming was important for rice defence against blast fungus. Ribosome- and protein translation-related genes were significantly enriched among differentially expressed genes (DEGs) at 12 hpi in both cultivars, indicating that the protein translation machinery is regulated in the activation of immunity in rice. Furthermore, we identified a core set of genes that are involved in the rice response to both biotic and abiotic stress. More importantly, among the core genes, we demonstrated that the metallothionein OsMT1a and OsMT1b genes positively regulated rice resistance while a peroxidase gene Perox4 negatively regulated rice resistance to M. oryzae. Our study provides novel insight into transcriptional reprogramming and serves as a valuable resource for functional studies on rice immune signalling components in resistance to blast disease.

Simple and Efficient Purification of Recombinant Proteins Using the Heparin-Binding Affinity Tag

Heparin, a member of the glycosaminoglycan family, is known to interact with more than 400 different types of proteins. For the past few decades, significant progress has been made to understand the molecular details involved in heparin-protein interactions. Based on the structural knowledge available from the FGF1-heparin interaction studies, we have designed a novel heparin-binding peptide (HBP) affinity tag that can be used for the simple, efficient, and cost-effective purification of recombinant proteins of interest. HBP-tagged fusion proteins can be purified by heparin Sepharose affinity chromatography using a simple sodium chloride gradient to elute the bound fusion protein. In addition, owing to the high density of positive charges on the HBP tag, recombinant target proteins are preferably expressed in their soluble forms. The purification of HBP-fusion proteins can also be achieved in the presence of chemical denaturants, including urea. Additionally, polyclonal antibodies raised against the affinity tag can be used to detect HBP-fused target proteins with high sensitivity. © 2017 by John Wiley & Sons, Inc.

Protein-RNA and protein-glycan recognitions in light of amino acid codes

BACKGROUND

RNA-binding proteins, in cooperation with non-coding RNAs, play important roles in post-transcriptional regulation. Non-coding micro-RNAs control information flow from the genome to the glycome by interacting with glycan-synthesis enzymes. Glycan-binding proteins read the cell surface and cytoplasmic glycome and transfer signals back to the nucleus. The profiling of the protein-RNA and protein-glycan interactomes is of significant medicinal importance.

SCOPE OF REVIEW

This review discusses the state-of-the-art research in the protein-RNA and protein-glycan recognition fields and proposes the application of amino acid codes in profiling and programming the interactomes.

MAJOR CONCLUSIONS

The deciphered PUF-RNA and PPR-RNA amino acid recognition codes can be explained by the protein-RNA amino acid recognition hypothesis based on the genetic code. The tripartite amino acid code is also involved in protein-glycan interactions. At present, the results indicate that a system of four codons ("gnc", where n=g - guanine, c - cytosine, u - uracil or a - adenine) and four amino acids (G - glycine, A - alanine, V - valine, D - aspartic acid) could be the original genetic code that imprinted "rules" into both recognition processes.

GENERAL SIGNIFICANCE

Amino acid recognition codes have provocative potential in the profiling and programming of the protein-RNA and protein-glycan interactomes. The profiling and even programming of the interactomes will play significant roles in diagnostics and the development of therapeutic procedures against cancer and neurodegenerative, developmental and other diseases.

De novo prediction of the genomic components and capabilities for microbial plant biomass degradation from (meta-)genomes

BACKGROUND

Understanding the biological mechanisms used by microorganisms for plant biomass degradation is of considerable biotechnological interest. Despite of the growing number of sequenced (meta)genomes of plant biomass-degrading microbes, there is currently no technique for the systematic determination of the genomic components of this process from these data.

RESULTS

We describe a computational method for the discovery of the protein domains and CAZy families involved in microbial plant biomass degradation. Our method furthermore accurately predicts the capability to degrade plant biomass for microbial species from their genome sequences. Application to a large, manually curated data set of microbial degraders and non-degraders identified gene families of enzymes known by physiological and biochemical tests to be implicated in cellulose degradation, such as GH5 and GH6. Additionally, genes of enzymes that degrade other plant polysaccharides, such as hemicellulose, pectins and oligosaccharides, were found, as well as gene families which have not previously been related to the process. For draft genomes reconstructed from a cow rumen metagenome our method predicted Bacteroidetes-affiliated species and a relative to a known plant biomass degrader to be plant biomass degraders. This was supported by the presence of genes encoding enzymatically active glycoside hydrolases in these genomes.

CONCLUSIONS

Our results show the potential of the method for generating novel insights into microbial plant biomass degradation from (meta-)genome data, where there is an increasing production of genome assemblages for uncultured microbes.

Bactericidal activity against meticillin-resistant Staphylococcus aureus of a novel eukaryotic therapeutic recombinant antimicrobial peptide

Antimicrobial peptides (AMPs) are one of several potential antibacterial agents in the current era of antibiotics facing severe challenges. In this study, the bactericidal activity and stability of two eukaryotic AMPs were determined. Both AMPs showed specific antibacterial activity in a HEK293T cell model infected with meticillin-resistant Staphylococcus aureus. The recombinant eukaryotic AMP pVAX1/hBD3-CBD showed better bactericidal activity and stability than the eukaryotic AMP pVAX1/hBD3. These results illustrate that this peptide, designed and used with eukaryotic expression and recombinant methods, should be studied and applied in further AMP research and trials.