Transcriptomic analysis to reveal the differentially expressed miRNA targets and their miRNAs in response to Ralstonia solanacearum in ginger species

BACKGROUND

Bacterial wilt is the most devastating disease in ginger caused by Ralstonia solanacearum. Even though ginger (Zingiber officinale) and mango ginger (Curcuma amada) are from the same family Zingiberaceae, the latter is resistant to R. solanacearum infection. MicroRNAs have been identified in many crops which regulates plant-pathogen interaction, either through silencing genes or by blocking mRNA translation. However, miRNA's vital role and its targets in mango ginger in protecting bacterial wilt is not yet studied extensively. In the present study, using the "psRNATarget" server, we analyzed available ginger (susceptible) and mango ginger (resistant) transcriptome to delineate and compare the microRNAs (miRNA) and their target genes (miRTGs).

RESULTS

A total of 4736 and 4485 differential expressed miRTGs (DEmiRTGs) were identified in ginger and mango ginger, respectively, in response to R. solanacearum. Functional annotation results showed that mango ginger had higher enrichment than ginger in top enriched GO terms. Among the DEmiRTGs, 2105 were common in ginger and mango ginger. However, 2337 miRTGs were expressed only in mango ginger which includes 62 defence related and upregulated miRTGs. We also identified 213 miRTGs upregulated in mango ginger but downregulated in ginger, out of which 23 DEmiRTGS were defence response related. We selected nine miRNA/miRTGs pairs from the data set of common miRTGs of ginger and mango ginger and validated using qPCR.

CONCLUSIONS

Our data covered the expression information of 9221 miRTGs. We identified nine miRNA/miRTGs key candidate pairs in response to R. solanacearum infection in ginger. This is the first report of the integrated analysis of miRTGs and miRNAs in response to R. solanacearum infection among ginger species. This study is expected to deliver several insights in understanding the miRNA regulatory network in ginger and mango ginger response to bacterial wilt.

Mango ginger (curcuma amada) inhibits collagen-induced arthritis by modulating inflammatory cytokine levels in rats

Background/aim

Mango ginger (MG: curcuma amada) has antioxidant and antiinflammatory activities. The aim was to evaluate the antiarthritic potential efficacy of MG on collagen-induced arthritis.

Materials and methods

Twenty-one female Wistar-albino rats were divided into three groups. Arthritis was induced by intradermal injections of type II collagen and Freund’s adjuvant. MG extract was orally administered starting from the first collagen injection. TNF-α, IL-6, IL-17, obestatin, sclerostin, and DKK-1 serum levels were determined, and perisynovial inflammation and cartilage-bone destruction in the paws were histologically evaluated. Moreover, joint tissue TNF-α, IL-17, NF-κB, and COX-2 levels were analyzed.

Results

TNF-α, IL-17, IL-6, and DKK-1 serum levels were increased, and obestatin and sclerostin serum levels were decreased in the arthritis group compared to the control group. However, MG supplements decreased TNF-α, IL-17, IL-6, and DKK-1 serum levels and increased obestatin and sclerostin serum levels. Similarly, while collagen injection increased tissue TNF-α, IL-17, NF-κB, and COX-2 levels, MG decreased TNF-α, IL-17, and NF-κB levels. Moreover, MG ameliorated perisynovial inflammation and cartilage-bone destruction in the paws.

Conclusion

MG ameliorates arthritis via actions on inflammatory ways and wingless (Wnt) signaling pathway. These results suggest that MG may have a considerable potential efficacy for the treatment of rheumatoid arthritis.

In silico approach towards the identification of potential inhibitors from Curcuma amada Roxb against H. pylori: ADMET screening and molecular docking studies

Introduction: The present study attempts to identify potential targets of H. pylori for novel inhibitors from therapeutic herb, mango ginger (Curcuma amada Roxb.).

Methods: Crystal structure of all the selected drug targets obtained from Protein Data Bank (PDB) were subjected to molecular docking against a total of 130 compounds (found to have biological activity against H. pylori ) were retrieved from public databases. Compounds with good binding affinity were selected for Prime MM-GBSA rescoring and molecular dynamics (MD) simulation. Final list of compounds were taken for ADMET predictions.

Results: Based on binding affinity denoted by glide score and ligand efficiency, mango ginger compounds were found selective to shikimate kinase and type II dehydroquinase through hydrogen bonding and salt bridge interactions. Stability of the interactions and free energy calculations by Prime MM-GBSA results confirmed the affinity of mango ginger compounds towards both shikimate kinase and type II dehydroquinase. From the above results, 15 compounds were calculated for ADMET parameters, Lipinski’s rule of five, and the results were found promising without any limitations. MD simulations identified gentisic acid as hit compound for shikimate kinase of H. pylori.

Conclusion: Current study could identify the in silico potential of mango ginger compounds against shikimate kinase and type II dehydroquinase targets for H. pylori infections and are suitable for in vitro and in vivo evaluation.

Evaluation of rheological, bioactives and baking characteristics of mango ginger (curcuma amada) enriched soup sticks

Wheat flour was replaced with mango ginger powder (MGP) at 0, 5, 10 and 15 %. Influence of MGP on rheological and baking characteristics was studied. Farinograph was used to study the mixing profile of wheat flour-MGP blend. Pasting profile of the blends namely gelatinization and retrogradation were carried out using micro-visco-amylograph. Test baking was done to obtain the optimum level of replacement and processing conditions. Sensory attributes consisting texture, taste, overall quality and breaking strength were assessed. Nutritional characterization of the soup sticks in terms of protein and starch in vitro digestibility, dietary fiber, minerals, polyphenols and antioxidant activity were determined using standard methods. With the increasing levels of MGP from 0 to 15 %, the farinograph water absorption increased from 60 to 66.7 %. A marginal increase in the gelatinization temperature from 65.4 to 66.2 °C was observed. Retrogradation of gelatinized starch granules decreased with the addition of MGP. The results indicated that the soup stick with 10 % MG had acceptable sensory attributes. The soup stick showed further improvement in terms of texture and breaking strength with the addition of gluten powder, potassium bromate and glycerol monostearate. The total dietary fiber and antioxidant activity of the soup sticks having 10 % MGP increased from 3.31 to 8.64 % and 26.83 to 48.06 % respectively as compared to the control soup sticks. MGP in soup sticks improved the nutritional profile.

Modelling solubility of phenolics of mango ginger extract in supercritical carbon dioxide using equation of state and empirical models

Solubility of phenolics of mango ginger extract in supercritical carbon dioxide was studied at 40-60 °C and 100-350 bar. Critical temperature, critical pressure and critical volume of caffeic acid, the principal component of the extract were calculated using group contribution methods and compared with the values obtained by CHEMDRAW®. Vapor pressure of caffeic acid was predicted by Reidel method. Solubility prediction in supercritical carbon dioxide was studied using two different equation of states (EOS) models and eight empirical models. Peng-Robinson EOS predicted the solubility very well with average deviation of 0.68 % from the experimental solubility. Empirical equations based on the simple error minimization using non-linear regression method which do not require complex physiochemical properties was also found suitable to predict the solubility at different extraction conditions. Jouyban et al. model showed very less deviation (2.25 %) for predicted solubility values from the experiment.

Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network

Mango ginger (Curcuma amada) was dried in a through-flow dryer system at different temperatures (40-70 °C) and air velocities (0.84 - 2.25 m/s) to determine the effect of drying on drying rate and effective diffusivity. As the temperature and air velocity increased, drying time significantly decreased. Among the ten different thin layer drying models considered to determine the kinetic drying parameters, semi empirical Midilli et al., model gave the best fit for all drying conditions. Effective moisture diffusivity varied from 3.7 × 10(-10) m(2)/s to 12.5 × 10(-10) m(2)/s over the temperature and air velocity range of study. Effective moisture diffusivity regressed well with Arrhenius model and activation energy of the model was found to be 32.6 kJ/mol. Artificial neural network modeling was also employed to predict the drying behaviour and found suitable to describe the drying kinetics with very high correlation coefficient of 0.998.