Machine learning enhances prediction of plants as potential sources of antimalarials

A new R package to parse plant species occurrence records into unique collection events efficiently reduces data redundancy

Biodiversity data aggregators, such as Global Biodiversity Information Facility (GBIF) suffer from inflation of the number of occurrence records when data from different databases are merged but not fully reconciled. The ParseGBIF workflow is designed to parse duplicate GBIF species occurrence records into unique collection events (gatherings) and to optimise the quality of the spatial data associated with them. ParseGBIF provides tools to verify and standardize species scientific names according to the World Checklist of Vascular Plants taxonomic backbone, and to parse duplicate records into unique 'collection events', in the process compiling the most informative spatial data, where more than one duplicate is available, and providing crude estimates of taxonomic and spatial data quality. When GBIF occurrence records for a medium-sized vascular plant family, the Myrtaceae, were processed by ParseGBIF, the average number of records useful for spatial analysis increased by 180%. ParseGBIF could therefore be valuable in the evaluation of species' occurrences at the national scale in support for national biodiversity plans, identification of plant areas important for biodiversity, sample bias estimation to inform future sampling efforts, and to forecast species range shifts in response to global climate change.

Revealing active constituents within traditional Chinese Medicine used for treating bacterial pneumonia, with emphasis on the mechanism of baicalein against multi-drug resistant Klebsiella pneumoniae

ETHNOPHARMACOLOGICAL RELEVANCE

The emergence of antibiotic-resistant bacteria has rendered it more challenging to treat bacterial pneumonia. Traditional Chinese medicine (TCM) has superior efficacy in the treatment of pneumonia, and it has the unique advantage of antibacterial resistance against multi-drug resistant (MDR) bacteria, but the medication rule and pharmacological mechanism of its antibacterial activity are not clear.

AIM OF THE STUDY

This study aims to reveal Chinese medication patterns in treating bacterial pneumonia to select bioactive constituents in core herbs, predict their pharmacological mechanisms and further explore their antibacterial ability against clinically isolated MDR Klebsiella pneumoniae (KP) and their antibacterial mechanisms.

MATERIALS AND METHODS

The high-frequency medicinal herbs to treat lung diseases were first screened from Pharmacopoeia of the People's Republic of China (ChP.), and then bioactive compounds in core herbs and targets for compounds and disease were collected. Potential targets, signaling pathways, and drugs' core components were determined by constructing protein-protein interaction network, enrichment analysis and "component-target-pathway-disease" network were mapped by Cytoscape 3.8.2, and the potential therapeutic value of selected core components was verified by comparing the disease targets in the GEO database with the herbal component targets in the ITCM database. The clinically isolated KP were screened by drug sensitivity tests with meropenem (MEM), polymyxin E (PE), and tigecycline and biofilm-forming assay; broth microdilution, chessboard methods and biofilm morphology and permeability experiments were employed to determine the antibacterial, bactericidal and biofilm inhibition ability of selected bioactive constituents alone and in combination with antibiotics; The mechanism of bioactive components on quorum sensing (QS) genes LuxS and LuxR was predicted by molecular docking and tested by RT-PCR.

RESULTS

The 13 core Chinese medicines were obtained by mining ChP., and 615 potential targets of core herbal medicine were screened, and the PI3K-Akt signaling pathway might play crucial roles in the therapeutic process. In-vitro experiments revealed that the selected core compounds, including forsythoside B, baicalin, baicalein, and forsythin, all have antibacterial activity, in which baicalein had the strongest ability and a synergistic effect in combination with MEM or PE. Their synergy exhibited a stronger effect on biofilms of MDR KP, inhibiting biofilm formation, disrupting formed biofilms, and removing the residual structures of dead bacteria. Baicalein was predicted to have stable binding capacity to LuxS and LuxR genes by molecular docking, and RT-PCR results verified that the combination of baicalein with MEM or PE was effective in inhibiting the expression of QS genes (LuxS and LuxR) and consequently suppressing biofilm formation.

CONCLUSION

The core Chinese herbal medicine in the ChP. to treat lung diseases has a multi-component, multi-target, and multi-pathway synergy to improve bacterial pneumonia. Experimental studies have confirmed that the bioactive compound baicalein was able to combat MDR KP alone and synergistic with MEM or PE, inhibited and disrupted biofilms via regulating LuxS and LuxR genes, and further disturbed quorum sensing system to promote the therapeutic efficacy, which provides a new pathway and rationale for treating MDR KP-induced bacterial pneumonia.