Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry

BACKGROUND: Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms. FINDINGS: High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma. CONCLUSIONS: With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets

Functional Characteristics of an Endophyte Community Colonizing Rice Roots as Revealed by Metagenomic Analysis

Roots are the primary site of interaction between plants and microorganisms. To meet food demands in changing climates, improved yields and stress resistance are increasingly important, stimulating efforts to identify factors that affect plant productivity. The role of bacterial endophytes that reside inside plants remains largely unexplored, because analysis of their specific functions is impeded by difficulties in cultivating most prokaryotes. Here, we present the first metagenomic approach to analyze an endophytic bacterial community resident inside roots of rice, one of the most important staple foods. Metagenome sequences were obtained from endophyte cells extracted from roots of field-grown plants. Putative functions were deduced from protein domains or similarity analyses of protein-encoding gene fragments, and allowed insights into the capacities of endophyte cells. This allowed us to predict traits and metabolic processes important for the endophytic lifestyle, suggesting that the endorhizosphere is an exclusive microhabitat requiring numerous adaptations. Prominent features included flagella, plant-polymer-degrading enzymes, protein secretion systems, iron acquisition and storage, quorum sensing, and detoxification of reactive oxygen species. Surprisingly, endophytes might be involved in the entire nitrogen cycle, as protein domains involved in N2-fixation, denitrification, and nitrification were detected and selected genes expressed. Our data suggest a high potential of the endophyte community for plant-growth promotion, improvement of plant stress resistance, biocontrol against pathogens, and bioremediation, regardless of their culturability.</p

Cell–Cell Communication in Azospirillum and Related PGPR

International audienc