Rapid and\nRobust Workflows Using Different Ionization,\nComputation, and Visualization Approaches for Spatial Metabolome Profiling\nof Microbial Natural Products in <i>Pseudoalteromonas</i>

Ambient mass spectrometry\n(MS) technologies have been applied to\nspatial metabolomic profiling of various samples in an attempt to\nboth increase analysis speed and reduce the length of sample preparation.\nRecent studies, however, have focused on improving the spatial resolution\nof ambient approaches. Finer resolution requires greater analysis\ntimes and commensurate computing power for more sophisticated data\nanalysis algorithms and larger data sets. Higher resolution provides\na more detailed molecular picture of the sample; however, for some\napplications, this is not required. A liquid microjunction surface\nsampling probe (LMJ-SSP) based MS platform combined with unsupervised\nmultivariant analysis based hyperspectral visualization is demonstrated\nfor the metabolomic analysis of marine bacteria from the genus <i>Pseudoalteromonas</i> to create a rapid and robust spatial profiling\nworkflow for microbial natural product screening. In our study, metabolomic\nprofiles of different <i>Pseudoalteromonas</i> species are\nquickly acquired without any sample preparation and distinguished\nby unsupervised multivariant analysis. Our robust platform is capable\nof automated direct sampling of microbes cultured on agar without\nclogging. Hyperspectral visualization-based rapid spatial profiling\nprovides adequate spatial metabolite information on microbial samples\nthrough red–green–blue (RGB) color annotation. Both\nstatic and temporal metabolome differences can be visualized by straightforward\ncolor differences and differentiating <i>m</i>/<i>z</i> values identified afterward. Through this approach, novel analogues\nand their potential biosynthetic pathways are discovered by applying\nresults from the spatial navigation to chromatography-based metabolome\nannotation. In this current research, LMJ-SSP is shown to be a robust\nand rapid spatial profiling method. Unsupervised multivariant analysis\nbased hyperspectral visualization is proven straightforward for facile/rapid\ndata interpretation. The combination of direct analysis and innovative\ndata visualization forms a powerful tool to aid the identification/interpretation\nof interesting compounds from conventional metabolomics analysis.