Extraction and activity of chemical constituents from Houttuynia cordata Thunb by ultrasonic method.

Polyphenols and flavonoids are phytochemicals that have essential roles in human nutrition. In this regard, the contents of polyphenols and flavonoids in Houttuynia cordata Thunb and their antioxidant activities were evaluated in the current study. Two Houttuynia cordata materials with the same chromosome number and chemical type were used to comprehensively assess the contents of total phenols and flavonoids in different parts of H. cordata. These chemical components were extracted by the ultrasonic method. The results showed that the total phenols and antioxidant capacity of different parts of H. cordata were significantly different. The content of polyphenols in roots and stems was low, the antioxidant capacity was weak, the total phenols in flowers and leaves were high, and the antioxidant capacity was strong. Therefore, different parts of H. cordata had different pharmacological and food effects. The whole herb can be used as Chinese herbal medicine, and its young leaves and roots can be used as vegetables. Flavonoids are the main phenolic components, and total phenols are the main components of antioxidant activity. It can explain a very significant positive correlation between total phenols and flavonoids. Therefore, in the further breeding work of H. cordata, the procedure can be simplified by determining one of the above indexes to predict the varieties with high total phenolic and antioxidant activity.

Morphological and Developmental Features of Stone Cells in Eriobotrya Fruits.

Some members of the Rosaceae family, particularly pear, contain stone cells in their fruits. Although stone cells in pear fruits are well studied, relatively little attention has been given to loquat stone cells. Only a few reports have suggested a relationship between stone cell traits and storage and transport tolerance of loquat fruits. Previously, we generated the variety JT8 from the interspecific hybrid of the loquat cultivar Jiefangzhong (JFZ; Eriobotrya japonica Lindl. cv. Jiefangzhong, female parent) and wild Taiwanese loquat (TL; E. deflexa Nakai, male parent). The JT8 fruits had a granular feel, similar to that of pear fruits, due to the presence of stone cells. In this study, the shape, size, development, and distribution dynamics of stone cells of Eriobotrya plants were thoroughly investigated. The results showed that loquat stone cells are brachysclereids and often contain typical branching pits. Loquat stone cells were distributed as both single stone cells and in stone cell clusters (SCCs), and the density of the stone cells near the core was higher than that near the peel. Stone cell density first increased and then decreased during fruit development. These traits noted in Eriobotrya were very similar to those observed in pear, indicating a close relationship between loquat and pear. Moreover, the contents, density dynamics, and aggregation traits of stone cells of the interspecific hybrid JT8 were derived from the male parent (TL). Transgressive segregation was likely exhibited in the content of stone cells and the size of the SCCs. More specifically, the content of stone cells reached 1.61% (w/w). In extreme cases, SCCs of JT8 exceeded 1,000 µm in length and 500 µm in width. This demonstrated that stone cell traits could be transmitted from parent to progeny through interspecific hybridization. The density dynamics of stone cells in two loquat cultivars with different storage and transport tolerances were also investigated, which indicated that the cultivar with more stone cells was more tolerant to storage and transport. We suggest that wild loquat genetic resources containing stone cells in Eriobotrya plants can be used to gradually improve the storage and transport tolerance of loquat fruits.

Polyploidy underlies co-option and diversification of biosynthetic triterpene pathways in the apple tribe.

Whole-genome duplication (WGD) plays important roles in plant evolution and function, yet little is known about how WGD underlies metabolic diversification of natural products that bear significant medicinal properties, especially in nonmodel trees. Here, we reveal how WGD laid the foundation for co-option and differentiation of medicinally important ursane triterpene pathway duplicates, generating distinct chemotypes between species and between developmental stages in the apple tribe. After generating chromosome-level assemblies of a widely cultivated loquat variety and Gillenia trifoliata, we define differentially evolved, duplicated gene pathways and date the WGD in the apple tribe at 13.5 to 27.1 Mya, much more recent than previously thought. We then functionally characterize contrasting metabolic pathways responsible for major triterpene biosynthesis in G. trifoliata and loquat, which pre- and postdate the Maleae WGD, respectively. Our work mechanistically details the metabolic diversity that arose post-WGD and provides insights into the genomic basis of medicinal properties of loquat, which has been used in both traditional and modern medicines.

The Role of EjSVPs in Flower Initiation in Eriobotrya japonica.

Flowering plants have evolved different flowering habits to sustain long-term reproduction. Most woody trees experience dormancy and then bloom in the warm spring, but loquat blooms in the cold autumn and winter. To explore its mechanism of flowering regulation, we cloned two SHORT VEGETATIVE PHASE (SVP) homologous genes from 'Jiefanzhong' loquat (Eriobotrya japonica Lindl.), namely, EjSVP1 and EjSVP2. Sequence analysis revealed that the EjSVPs were typical MADS-box transcription factors and exhibited a close genetic relationship with other plant SVP/DORMANCY-ASSOCIATED MADS-BOX (DAM) proteins. The temporal and spatial expression patterns showed that EjSVP1 and EjSVP2 were mainly expressed in the shoot apical meristem (SAM) after the initiation of flowering; after reaching their highest level, they gradually decreased with the development of the flower until they could not be detected. EjSVP1 expression levels were relatively high in young tissues, and EjSVP2 expression levels were relatively high in young to mature transformed tissues. Interestingly, EjSVP2 showed relatively high expression levels in various flower tissues. We analyzed the EjSVP promoter regions and found that they did not contain the C-repeat/dehydration-responsive element. Finally, we overexpressed the EjSVPs in wild-type Arabidopsis thaliana Col-0 and found no significant changes in the number of rosette leaves of Arabidopsis thaliana; however, overexpression of EjSVP2 affected the formation of Arabidopsis thaliana flower organs. In conclusion, EjSVPs were found to play an active role in the development of loquat flowering. These findings may provide a reference for exploring the regulation mechanisms of loquat flowering and the dormancy mechanisms of other plants.

Silver Nanoparticle-Induced Phosphorylation of Histone H3 at Serine 10 Involves MAPK Pathways.

The phosphorylation of histone H3 at serine 10 (p-H3S10) has been shown to be closely correlated with mitotic chromosome condensation. We previously reported that intracellular silver nanoparticles (AgNPs) release Ag ions that alter actin filament dynamics, leading to the activation of Aurora kinases and the formation of p-H3S10 through a mechanism clearly different from that occurring during mitosis. In the present study, we examined other mechanisms underlying the induction of p-H3S10 formation by AgNPs. We observed that the early formation of p-H3S10 induced by AgNPs occurred via the activation of mitogen-activated protein kinase (MAPK) pathways, specifically the Jun N-terminal protein kinase (JNK) and extracellular signal-regulated kinase (ERK) pathways. The late AgNP-induced p-H3S10 formation occurred via the activation of the entire MAPK cascade. On the other hand, p-H3S10 formation was not due to DNA damage induced by AgNPs, or the activation of the kinases ataxia telangiectasia-mutated (ATM) and ATM-Rad3-related (ATR). Several studies have compared the mechanism of AgNP toxicity to a Trojan horse-type molecular pathway. We observed different effects of AgNO3 (Ag⁺) and AgNPs on cells, and only the JNK inhibitor suppressed the temporary AgNO3-induced formation of p-H3S10. These results strongly indicate that AgNP-induced p-H3S10 formation does not rely solely on one signaling pathway, but rather may involve two or more pathways.

Differential Expression Proteins Contribute to Race-Specific Resistant Ability in Rice (Oryza sativa L.).

Rice blast, caused by the fungus, Magnaporthe grisea (M. grisea), lead to the decrease of rice yields widely and destructively, threatening global food security. Although many resistant genes had been isolated and identified in various rice varieties, it is still not enough to clearly understand the mechanism of race-specific resistant ability in rice, especially on the protein level. In this research, proteomic methods were employed to analyze the differentially expressed proteins (DEPs) in susceptible rice variety CO39 and its two near isogenic lines (NILs), CN-4a and CN-4b, in response to the infection of two isolates with different pathogenicity, GUY11 and 81278ZB15. A total of 50 DEPs with more than 1.5-fold reproducible change were identified. At 24 and 48 hpi of GUY11, 32 and 16 proteins in CN-4b were up-regulated, among which 16 and five were paralleled with the expression of their corresponding RNAs. Moreover, 13 of 50 DEPs were reported to be induced by M. grisea in previous publications. Considering the phenotypes of the three tested rice varieties, we found that 21 and 23 up-regulated proteins were responsible for the rice resistant ability to the two different blast isolates, 81278ZB15 and GUY11, respectively. Two distinct branches corresponding to GUY11 and 81278ZB15 were observed in the expression and function of the module cluster of DEPs, illuminating that the DEPs could be responsible for race-specific resistant ability in rice. In other words, DEPs in rice are involved in different patterns and functional modules' response to different pathogenic race infection, inducing race-specific resistant ability in rice.

Prediction of protein-protein interactions between fungus (Magnaporthe grisea) and rice (Oryza sativa L.).

Rice blast disease caused by the fungus Magnaporthe grisea (M. grisea) is one of the most serious diseases for the cultivated rice Oryza sativa (O. sativa). A key factor causing rice blast disease and defense might be protein-protein interactions (PPIs) between rice and fungus. In this research, we have developed a computational pipeline to predict PPIs between blast fungus and rice. After cross-prediction by interolog-based and domain-based method, we achieved 532 potential PPIs between 27 fungus proteins and 236 rice proteins. Accuracy of jackknife test, 10-fold cross-validation test and independent test for these PPIs were 90.43, 93.85 and 84.67%, respectively, by using support vector machine classification method. Meanwhile, the pathogenic genes of blast fungus were enriched in the predicted PPIs network when compared with 1000 random interaction networks. The rice regulatory network was downloaded and divided into 228 subnetworks with over six nodes, and the top seven subnetworks affected by blast fungus through PPIs were investigated. The results indicated that 34 upregulated and 12 downregulated master regulators in rice interacting with the fungus proteins in response to the infection of blast fungus. The common master regulators in rice in response to the infection of M. grisea, Xanthomonas oryzae pv.oryzae and rice stripe virus were analyzed. The ubiquitin proteasome pathway was the common pathway in rice regulated by these three pathogens, while apoptosis signaling pathway was induced by fungus and bacteria. In summary, the results in this article provide insight into the process of blast fungus infection.

De Novo Analysis Reveals Transcriptomic Responses in Eriobotrya japonica Fruits during Postharvest Cold Storage.

Cold storage is the primary preservation method of postharvest loquat fruits. However, cold storage also results in many chilling injury physiological disorders called lignification, which decreases the quality and economic value of the fruits. Few studies to date have focused on the transcriptomic responses associated with lignification except lignin synthesis pathways. This study aimed to explore the changes of loquat transcriptome during long-term cold storage. Our results showed that the gene expression patterns were differed among the five stages. The differentially expressed genes (DEGs) in response to cold storage were more intense and complex in earlier stage. The membrane-related genes preferentially responded to low temperature and were followed by intracellular-located genes. The cold-induced pathways were mainly concerned with signal transduction and secondary metabolism (i.e., lignin, pectin, cellulose, terpenoid, carotenoid, steroid) in the first three stages and were chiefly related to primary metabolism in the later two stages, especially energy metabolism. Further investigation suggested that 503 protein kinases, 106 protein phosphatases, and 40 Ca2+ signal components were involved in the cold signal transduction of postharvest loquat fruits. We predicted a pathway including 649 encoding genes of 49 enzymes, which displayed the metabolisms of major sugars and polysaccharides in cold-stored loquat fruits. The coordinated expression patterns of these genes might contribute to the changes of saccharides in the pathway. These results provide new insight into the transcriptomic changes of postharvest loquat fruits in response to cold storage environment, which may be helpful for improving the postharvest life of loquat in the future.

Construction and Analysis of Gene Co-Expression Networks in Escherichia coli.

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Escherichia coli (E. coli) has long been a popular model organism for basic biological research. In this paper, weighted gene co-expression network analysis (WGCNA) algorithm was applied to construct gene co-expression networks in E. coli. Thirty-one gene co-expression modules were detected from 1391 microarrays of E. coli data. Further characterization of these modules with the database for annotation, visualization, and integrated discovery (DAVID) tool showed that these modules are associated with several kinds of biological processes, such as carbohydrate catabolism, fatty acid metabolism, amino acid metabolism, transportation, translation, and ncRNA metabolism. Hub genes were also screened by intra-modular connectivity. Genes with unknown functions were annotated by guilt-by-association. Comparison with a previous prediction tool, EcoliNet, suggests that our dataset can expand gene predictions. In summary, 31 functional modules were identified in E. coli, 24 of which were functionally annotated. The analysis provides a resource for future gene discovery.

Prediction and identification of the effectors of heterotrimeric G proteins in rice (Oryza sativa L.).

Heterotrimeric G protein signaling cascades are one of the primary metazoan sensing mechanisms linking a cell to environment. However, the number of experimentally identified effectors of G protein in plant is limited. We have therefore studied which tools are best suited for predicting G protein effectors in rice. Here, we compared the predicting performance of four classifiers with eight different encoding schemes on the effectors of G proteins by using 10-fold cross-validation. Four methods were evaluated: random forest, naive Bayes, K-nearest neighbors and support vector machine. We applied these methods to experimentally identified effectors of G proteins and randomly selected non-effector proteins, and tested their sensitivity and specificity. The result showed that random forest classifier with composition of K-spaced amino acid pairs and composition of motif or domain (CKSAAP_PROSITE_200) combination method yielded the best performance, with accuracy and the Mathew's correlation coefficient reaching 74.62% and 0.49, respectively. We have developed G-Effector, an online predictor, which outperforms BLAST, PSI-BLAST and HMMER on predicting the effectors of G proteins. This provided valuable guidance for the researchers to select classifiers combined with different feature selection encoding schemes. We used G-Effector to screen the effectors of G protein in rice, and confirmed the candidate effectors by gene co-expression data. Interestingly, one of the top 15 candidates, which did not appear in the training data set, was validated in a previous research work. Therefore, the candidate effectors list in this article provides both a clue for researchers as to their function and a framework of validation for future experimental work. It is accessible at http://bioinformatics.fafu.edu.cn/geffector.

Impact of SNPs on Protein Phosphorylation Status in Rice (Oryza sativa L.).

Single nucleotide polymorphisms (SNPs) are widely used in functional genomics and genetics research work. The high-quality sequence of rice genome has provided a genome-wide SNP and proteome resource. However, the impact of SNPs on protein phosphorylation status in rice is not fully understood. In this paper, we firstly updated rice SNP resource based on the new rice genome Ver. 7.0, then systematically analyzed the potential impact of Non-synonymous SNPs (nsSNPs) on the protein phosphorylation status. There were 3,897,312 SNPs in Ver. 7.0 rice genome, among which 9.9% was nsSNPs. Whilst, a total 2,508,261 phosphorylated sites were predicted in rice proteome. Interestingly, we observed that 150,197 (39.1%) nsSNPs could influence protein phosphorylation status, among which 52.2% might induce changes of protein kinase (PK) types for adjacent phosphorylation sites. We constructed a database, SNP_rice, to deposit the updated rice SNP resource and phosSNPs information. It was freely available to academic researchers at http://bioinformatics.fafu.edu.cn. As a case study, we detected five nsSNPs that potentially influenced heterotrimeric G proteins phosphorylation status in rice, indicating that genetic polymorphisms showed impact on the signal transduction by influencing the phosphorylation status of heterotrimeric G proteins. The results in this work could be a useful resource for future experimental identification and provide interesting information for better rice breeding.

Rice_Phospho 1.0: a new rice-specific SVM predictor for protein phosphorylation sites.

Experimentally-determined or computationally-predicted protein phosphorylation sites for distinctive species are becoming increasingly common. In this paper, we compare the predictive performance of a novel classification algorithm with different encoding schemes to develop a rice-specific protein phosphorylation site predictor. Our results imply that the combination of Amino acid occurrence Frequency with Composition of K-Spaced Amino Acid Pairs (AF-CKSAAP) provides the best description of relevant sequence features that surround a phosphorylation site. A support vector machine (SVM) using AF-CKSAAP achieves the best performance in classifying rice protein phophorylation sites when compared to the other algorithms. We have used SVM with AF-CKSAAP to construct a rice-specific protein phosphorylation sites predictor, Rice_Phospho 1.0 (http://bioinformatics.fafu.edu.cn/rice_phospho1.0). We measure the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) of Rice_Phospho 1.0 to be 82.0% and 0.64, significantly higher than those measures for other predictors such as Scansite, Musite, PlantPhos and PhosphoRice. Rice_Phospho 1.0 also successfully predicted the experimentally identified phosphorylation sites in LOC_Os03g51600.1, a protein sequence which did not appear in the training dataset. In summary, Rice_phospho 1.0 outputs reliable predictions of protein phosphorylation sites in rice, and will serve as a useful tool to the community.

Genome-wide identification of heat shock proteins (Hsps) and Hsp interactors in rice: Hsp70s as a case study.

BACKGROUND: Heat shock proteins (Hsps) perform a fundamental role in protecting plants against abiotic stresses. Although researchers have made great efforts on the functional analysis of individual family members, Hsps have not been fully characterized in rice (Oryza sativa L.) and little is known about their interactors. RESULTS: In this study, we combined orthology-based approach with expression association data to screen rice Hsps for the expression patterns of which strongly correlated with that of heat responsive probe-sets. Twenty-seven Hsp candidates were identified, including 12 small Hsps, six Hsp70s, three Hsp60s, three Hsp90s, and three clpB/Hsp100s. Then, using a combination of interolog and expression profile-based methods, we inferred 430 interactors of Hsp70s in rice, and validated the interactions by co-localization and function-based methods. Subsequent analysis showed 13 interacting domains and 28 target motifs were over-represented in Hsp70s interactors. Twenty-four GO terms of biological processes and five GO terms of molecular functions were enriched in the positive interactors, whose expression levels were positively associated with Hsp70s. Hsp70s interaction network implied that Hsp70s were involved in macromolecular translocation, carbohydrate metabolism, innate immunity, photosystem II repair and regulation of kinase activities. CONCLUSIONS: Twenty-seven Hsps in rice were identified and 430 interactors of Hsp70s were inferred and validated, then the interacting network of Hsp70s was induced and the function of Hsp70s was analyzed. Furthermore, two databases named Rice Heat Shock Proteins (RiceHsps) and Rice Gene Expression Profile (RGEP), and one online tool named Protein-Protein Interaction Predictor (PPIP), were constructed and could be accessed at http://bioinformatics.fafu.edu.cn/.

Expression and interaction of small heat shock proteins (sHsps) in rice in response to heat stress.

The inherent immobility of rice (Oryza sativa L.) limited their abilities to avoid heat stress and required them to contend with heat stress through innate defense abilities in which heat shock proteins played important roles. In this study, Hsp26.7, Hsp23.2, Hsp17.9A, Hsp17.4 and Hsp16.9A were up-regulated in Nipponbare during seedling and anthesis stages in response to heat stress. Subsequently, the expressing levels of these five sHsps in the heat-tolerant rice cultivar, Co39, were all significantly higher than that in the heat-susceptible rice cultivar, Azucena. This indicated that the expressive level of these five sHsps was positively related to the ability of rice plants to avoid heat stress. Thus, the expression level of these five sHsps can be regarded as bio-markers for screening rice cultivars with different abilities to avoid heat stress. Hsp18.1, Hsp17.9A, Hsp17.7 and Hsp16.9A, in the three rice cultivars under heat stress were found to be involved in one protein complex by Native-PAGE, and the interactions of Hsp18.1 and Hsp 17.7, Hsp18.1 and Hsp 17.9A, and Hsp17.7 and Hsp16.9A were further validated by yeast 2-hybridization. Pull down assay also confirmed the interaction between Hsp17.7 and Hsp16.9A in rice under heat stress. In conclusion, the up-regulation of the 5 sHsps is a key step for rice to tolerate heat stress, after that some sHsps assembled into a large hetero-oligomeric complex. In addition, through protein-protein interaction, Hsp101 regulated thiamine biosynthesis, and Hsp82 homology affected nitrogen metabolism, while Hsp81-1 were involved in the maintenance of sugar or starch synthesis in rice plants under heat stress. These results provide new insight into the regulatory mechanism of sHsps in rice.