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Microbial Identification, High-Resolution Microscopy and Spectrometry of the Rhizosphere in Its Native Spatial Context.

ABSTRACT: During the past decades, several stand-alone and combinatorial methods have been developed to investigate the chemistry (i.e., mapping of elemental, isotopic, and molecular composition) and the role of microbes in soil and rhizosphere. However, none of these approaches are currently applicable to characterize soil-root-microbe interactions simultaneously in their spatial arrangement. Here we present a novel approach that allows for simultaneous microbial identification and chemical analysis of the rhizosphere at micro- to nano-meter spatial resolution. Our approach includes (i) a resin embedding and sectioning method suitable for simultaneous correlative characterization of Zea mays rhizosphere, (ii) an analytical work flow that allows up to six instruments/techniques to be used correlatively, and (iii) data and image correlation. Hydrophilic, immunohistochemistry compatible, low viscosity LR white resin was used to embed the rhizosphere sample. We employed waterjet cutting and avoided polishing the surface to prevent smearing of the sample surface at nanoscale. The quality of embedding was analyzed by Helium Ion Microscopy (HIM). Bacteria in the embedded soil were identified by Catalyzed Reporter Deposition-Fluorescence in situ Hybridization (CARD-FISH) to avoid interferences from high levels of autofluorescence emitted by soil particles and organic matter. Chemical mapping of the rhizosphere was done by Scanning Electron Microscopy (SEM) with Energy-dispersive X-ray analysis (SEM-EDX), Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS), nano-focused Secondary Ion mass Spectrometry (nanoSIMS), and confocal Raman spectroscopy (μ-Raman). High-resolution correlative characterization by six different techniques followed by image registration shows that this method can meet the demanding requirements of multiple characterization techniques to identify spatial organization of bacteria and chemically map the rhizosphere. Finally, we presented individual and correlative workflows for imaging and image registration to analyze data. We hope this method will be a platform to combine various 2D analytics for an improved understanding of the rhizosphere processes and their ecological significance.

SUBMITTER: Bandara CD

PROVIDER: S-EPMC8293618 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Mass spectrometric sequencing of low abundance, integral membrane proteins, particularly the transmembrane domains, presents challenges that span the multiple phases of sample preparation including solubilization, purification, enzymatic digestion, peptide extraction, and chromatographic separation. We describe a method through which we have obtained high peptide coverage for 12 ?-aminobutyric acid type A receptor (GABAA receptor) subunits from 2 picomoles of affinity-purified GABAA receptors from rat brain neocortex. Focusing on the ?? subunit, we identified peptides covering 96% of the protein sequence from fragmentation spectra (MS2) using a database searching algorithm and deduced 80% of the amino acid residues in the protein from de novo sequencing of Orbitrap spectra. The workflow combined microscale membrane protein solubilization, protein delipidation, in-solution multi-enzyme digestion, multiple stationary phases for peptide extraction, and acquisition of high-resolution full scan and fragmentation spectra. For de novo sequencing of peptides containing the transmembrane domains, timed digestions with chymotrypsin were utilized to generate peptides with overlapping sequences that were then recovered by sequential solid phase extraction using a C4 followed by a porous graphitic carbon stationary phase. The specificity of peptide identifications and amino acid residue sequences was increased by high mass accuracy and charge state assignment to parent and fragment ions. Analysis of three separate brain samples demonstrated that 78% of the sequence of the ?? subunit was observed in all three replicates with an additional 13% covered in two of the three replicates, indicating a high degree of sequence coverage reproducibility. Label-free quantitative analysis was applied to the three replicates to determine the relative abundances of 11 ?-aminobutyric acid type A receptor subunits. The deep sequence MS data also revealed two N-glycosylation sites on the ?? subunit, confirmed two splice variants of the ?? subunit (??L and ??S) and resolved a database discrepancy in the sequence of the ?? subunit.

Dataset Information

Microbial Identification, High-Resolution Microscopy and Spectrometry of the Rhizosphere in Its Native Spatial Context.

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