Fengycin and the amyloid TasA of Bacillus subtilis stimulates the growth and immunization of plants by targeting the seed storages

Beneficial microbes are known to stimulate the germination of the seeds; however, the exact mechanisms mediating these interactions are only beginning. Bacillus subtilis is a commonly detected member of the plant holobiont and provides multifaceted traits to the plant health. In this work, we demonstrated that B. subtilis triggered genetic and physiological responses in seeds that resulted in changes in the metabolic and developmental status of adult plants. A multidisciplinary approach based on microscopy, transcriptomics and metabolomics demonstrated that the chemically diverse extracellular matrix of Bacillus structurally cooperate in bacterial colonization of the seed storage tissues. The amyloid protein TasA and fengycin, two components of the extracellular matrix differentially stimulated levels of ROS inside seeds after imbibition and targeted the oil bodies of the seed endosperm, provoking specific changes in lipid metabolism or accumulation of glutathione-related molecules that resulted in two different plant growth programs: the development of seed radicles or major growth and immunization of adult plants. Our findings prove the versatility of the bacterial ECM in establishing a mutualistic interaction with plants.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

From bacterial antagonism to co-existence: the chemical interplay and adaptative strategies between Pseudomonas and Bacillus

Bacterial communities are continuously adapting and evolving for survival. They produce and secrete a broad range of molecules that kill, defend, or mediate communication between cells of different lineages, thus shaping the final structure of the microbial community. In this work, with the combination of -omics approaches, molecular biology and microscopic techniques, we expand our knowledge on the chemical interplay and specific mutations that modulate the transition from antagonism to co-existence between two plant-beneficial bacteria, Pseudomonas chlororaphis and Bacillus amyloliquefaciens. We demonstrate that bacillaene, a secondary metabolite with bacteriostatic activity produced by Bacillus, interacts with the protein elongation factor FusA of P. chlororaphis to arrest its growth and population advancement. Point mutations in this protein lead to tolerance to bacillaene and other inhibitors of protein translation. Additionally, we describe the key role of the glycerol kinase GlpK from B. amyloliquefaciens in its unspecific tolerance against P. chlororaphis. Mutations in GlpK provoked by a decrease of Bacillus cell membrane permeability among other pleiotropic responses. We conclude that nutrient specialization and mutations in basic biological functions are bacterial adaptive dynamics that lead to the coexistence of two primary competitive bacterial species rather than their mutual eradication.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

microbeMASST: A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms’ role in ecology and human health

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms’ role in ecology and human health

Heterologous Expression in Anabaena of the Columbamide Pathway from the Cyanobacterium Moorena bouillonii and Production of New Analogs

Columbamides are chlorinated acyl amide natural products, several of which exhibit cannabinomimetic activity. These compounds were originally discovered from a culture of the filamentous marine cyanobacterium Moorena bouillonii PNG5-198 collected from the coastal waters of Papua New Guinea. The columbamide biosynthetic gene cluster (BGC) had been identified using bioinformatics, but not confirmed by experimental evidence. Here, we report the heterologous expression in Anabaena (Nostoc) PCC 7120 of the 28.5 kb BGC that encodes for columbamide biosynthesis. The production of columbamides in Anabaena is investigated under several different culture conditions, and several new columbamide analogs are identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and nuclear magnetic resonance (NMR). In addition to previously characterized columbamides A, B, and C, new columbamides I-M are produced in these experiments, and the structure of the most abundant monochlorinated analog, columbamide K (11), is fully characterized. The other new columbamide analogs are produced in only small quantities, and structures are proposed based on high-resolution-MS, MS/MS, and 1H NMR data. Overexpression of the pathway's predicted halogenases resulted in increased productions of di- and trichlorinated compounds. The most significant change in production of columbamides in Anabaena is correlated with the concentration of NaCl in the medium

Enabling pan-repository reanalysis for big data science of public metabolomics data

Public untargeted metabolomics data is a growing resource for metabolite and phenotype discovery; however, accessing and utilizing these data across repositories pose significant challenges. Therefore, we\u27ve developed pan-repository universal identifiers and harmonized cross-repository metadata. This novel ecosystem facilitates discovery by integrating diverse data sources from public repositories including MetaboLights, Metabolomics Workbench, and GNPS/MassIVE. Our approach simplifies data handling and unlocks previously inaccessible reanalysis workflows, fostering unmatched research opportunities

A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products

This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural products. The concept was applied to the extract of a filamentous marine cyanobacterium known to be a prolific producer of cytotoxic natural products. This environmental Symploca extract was roughly fractionated, and then prioritized and guided by cancer cell cytotoxicity, NMR-based SMART 2.0, and MS2-based molecular networking. This led to the isolation and rapid identification of a new chimeric swinholide-like macrolide, symplocolide A, as well as the annotation of swinholide A, samholides A-I, and several new derivatives. The planar structure of symplocolide A was confirmed to be a structural hybrid between swinholide A and luminaolide B by 1D/2D NMR and LC-MS2 analysis. A second example applies SMART 2.0 to the characterization of structurally novel cyclic peptides, and compares this approach to the recently appearing "atomic sort" method. This study exemplifies the revolutionary potential of combined traditional and deep learning-assisted analytical approaches to overcome longstanding challenges in natural products drug discovery

Feature-based molecular networking in the GNPS analysis environment

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry

Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry