Jair J. Pineda-Pineda, Jesús Muñoz-Rojas, Yolanda E. Morales-García, Esperanza Trenado-Sánchez, José M. Sigarreta
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引用次数: 0
Abstract
The sustainable use of terrestrial ecosystems is crucial to ensure food security for future generations, and the formulation of plant growth–promoting bacterial consortia has proven useful not only in sustainable agriculture but also in applications such as phytopathogen biocontrol, bioremediation of contaminated soils and waters, biofertilization, organic waste degradation, and the production of industrially relevant enzymes. In this work, we developed a mathematical model to quantify and identify antagonism-free consortia based on double-agar-layer assays with 20 and 33 bacterial strains from independent studies. Simultaneously, we implemented a graph-based geometric model to analyse their topological properties and defined an index to quantify feasible consortia. The proposed methods were experimentally validated, identifying 36,851 and 376,126 subsets of compatible strains, for 20 and 33 strains, respectively. These subsets have the potential to promote plant growth and other biotechnological functions, thus providing a scalable tool for the management of agricultural resources, environmental restoration, and the design of sustainable biotechnological practices.
期刊介绍:
Microbial Biotechnology publishes papers of original research reporting significant advances in any aspect of microbial applications, including, but not limited to biotechnologies related to: Green chemistry; Primary metabolites; Food, beverages and supplements; Secondary metabolites and natural products; Pharmaceuticals; Diagnostics; Agriculture; Bioenergy; Biomining, including oil recovery and processing; Bioremediation; Biopolymers, biomaterials; Bionanotechnology; Biosurfactants and bioemulsifiers; Compatible solutes and bioprotectants; Biosensors, monitoring systems, quantitative microbial risk assessment; Technology development; Protein engineering; Functional genomics; Metabolic engineering; Metabolic design; Systems analysis, modelling; Process engineering; Biologically-based analytical methods; Microbially-based strategies in public health; Microbially-based strategies to influence global processes