MPDB 2.0: a large scale and integrated medicinal plant database of Bangladesh

Objective

MPDB 2.0 is built to be the continuation of MPDB 1.0, to serve as a more comprehensive data repertoire for Bangladeshi medicinal plants, and to provide a user-friendly interface for researchers, health practitioners, drug developers, and students who wish to study the various medicinal & nutritive plants scattered around Bangladesh and the underlying phytochemicals contributing to their efficacy in Bangladeshi folk medicine.

Results

MPDB 2.0 database (https://www.medicinalplantbd.com/) comprises a collection of more than five hundred Bangladeshi medicinal plants, alongside a record of their corresponding scientific, family, and local names together with their utilized parts, information regarding ailments, active compounds, and PubMed ID of related publications. While medicinal plants are not limited to the borders of any country, Bangladesh and its Southeast Asian neighbors do boast a huge collection of potent medicinal plants with considerable folk-medicinal history compared to most other countries in the world. Development of MPDB 2.0 has been highly focused upon human diseases, albeit many of the plants indexed here can serve in developing biofuel (e.g.: Jatropha curcas used in biofuel) or bioremediation technologies (e.g.: Amaranthus cruentus helps to reduce cadmium level in soil) or nutritive diets (Terminalia chebula can be used in nutritive diets) or cosmetics (Aloe vera used in cosmetics), etc.

Insights Into the Resistome of Bovine Clinical Mastitis Microbiome, a Key Factor in Disease Complication

Bovine clinical mastitis (CM) is one of the most prevalent diseases caused by a wide range of resident microbes. The emergence of antimicrobial resistance in CM bacteria is well-known, however, the genomic resistance composition (the resistome) at the microbiome-level is not well characterized. In this study, we applied whole metagenome sequencing (WMS) to characterize the resistome of the CM microbiome, focusing on antibiotics and metals resistance, biofilm formation (BF), and quorum sensing (QS) along with in vitro resistance assays of six selected pathogens isolated from the same CM samples. The WMS generated an average of 21.13 million reads (post-processing) from 25 CM samples that mapped to 519 bacterial strains, of which 30.06% were previously unreported. We found a significant (P = 0.001) association between the resistomes and microbiome composition with no association with cattle breed, despite significant differences in microbiome diversity among breeds. The in vitro investigation determined that 76.2% of six selected pathogens considered "biofilm formers" actually formed biofilms and were also highly resistant to tetracycline, doxycycline, nalidixic acid, ampicillin, and chloramphenicol and remained sensitive to metals (Cr, Co, Ni, Cu, Zn) at varying concentrations. We also found bacterial flagellar movement and chemotaxis, regulation and cell signaling, and oxidative stress to be significantly associated with the pathophysiology of CM. Thus, identifying CM microbiomes, and analyzing their resistomes and genomic potentials will help improve the optimization of therapeutic schemes involving antibiotics and/or metals usage in the prevention and control of bovine CM.

Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

H7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, h ydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.