Dataset Information

Shifting Perspectives of Translational Research in Bio-Bactericides: Reviewing the Bacillus amyloliquefaciens Paradigm.

ABSTRACT: Bacterial biological control agents (BCAs) have been increasingly used against plant diseases. The traditional approach to manufacturing such commercial products was based on the selection of bacterial species able to produce secondary metabolites that inhibit mainly fungal growth in optimal media. Such species are required to be massively produced and sustain long-term self-storage. The endpoint of this pipeline is large-scale field tests in which BCAs are handled as any other pesticide. Despite recent knowledge of the importance of BCA-host-microbiome interactions to trigger plant defenses and allow colonization, holistic approaches to maximize their potential are still in their infancy. There is a gap in scientific knowledge between experiments in controlled conditions for optimal BCA and pathogen growth and the nutrient-limited field conditions in which they face niche microbiota competition. Moreover, BCAs are considered to be safe by competent authorities and the public, with no side effects to the environment; the OneHealth impact of their application is understudied. This review summarizes the state of the art in BCA research and how current knowledge and new biotechnological tools have impacted BCA development and application. Future challenges, such as their combinational use and ability to ameliorate plant stress are also discussed. Addressing such challenges would establish their long-term use as centerfold agricultural pesticides and plant growth promoters.

SUBMITTER: Dimopoulou A

PROVIDER: S-EPMC8614995 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Physiologically-based pharmacokinetics (PBPK) modeling is a robust tool that supports drug development and the pharmaceutical industry and regulatory authorities. Implementation of predictive systems in the clinics is more than ever a reality, resulting in a surge of interest for PBPK models by clinicians. We aimed to establish a repository of available PBPK models developed to date to predict drug-drug interactions (DDIs) in the different therapeutic areas by integrating intrinsic and extrinsic factors such as genetic polymorphisms of the cytochromes or environmental clues. This work includes peer-reviewed publications and models developed in the literature from October 2017 to January 2021. Information about the software, type of model, size, and population model was extracted for each article. In general, modeling was mainly done for DDI prediction via Simcyp® software and Full PBPK. Overall, the necessary physiological and physio-pathological parameters, such as weight, BMI, liver or kidney function, relative to the drug absorption, distribution, metabolism, and elimination and to the population studied for model construction was publicly available. Of the 46 articles, 32 sensibly predicted DDI potentials, but only 23% integrated the genetic aspect to the developed models. Marked differences in concentration time profiles and maximum plasma concentration could be explained by the significant precision of the input parameters such as Tissue: plasma partition coefficients, protein abundance, or Ki values. In conclusion, the models show a good correlation between the predicted and observed plasma concentration values. These correlations are all the more pronounced as the model is rich in data representative of the population and the molecule in question. PBPK for DDI prediction is a promising approach in clinical, and harmonization of clearance prediction may be helped by a consensus on selecting the best data to use for PBPK model development.

Dataset Information

Shifting Perspectives of Translational Research in Bio-Bactericides: Reviewing the Bacillus amyloliquefaciens Paradigm.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets