Set of Novel Automated Quantitative Microproteomics Protocols for Small Sample Amounts and Its Application to Kidney Tissue Substructures

Here we assessed the ability of an automated sample preparation device equipped with disposable microcolumns to prepare mass-limited samples for high-sensitivity quantitative proteomics, using both label-free and isobaric labeling approaches. First, we compared peptide label-free quantification reproducibility for 1.5–150 μg of cell lysates and found that labware preconditioning was essential for reproducible quantification of <7.5 μg digest. Second, in-solution and on-column tandem mass tag (TMT) labeling protocols were compared and optimized for 1 μg of sample. Surprisingly, standard methods for in-solution and on-column labeling showed poor TMT labeling (50–85%); however, novel optimized and automated protocols restored efficient labeling to >98%. Third, compared with a single long gradient experiment, a simple robotized high-pH fractionation protocol using only 6 μg of starting material doubled the number of unique peptides and increased proteome coverage 1.43-fold. To facilitate the analysis of heterogeneous tissue samples, such as those obtained from laser capture microdissection, a modified BCA protein assay was developed that consumes and detects down to 15 ng of protein. As a proof-of-principle, the modular automated workflow was applied to 0.5 and 1 mm² mouse kidney cortex and medulla microdissections to show the method’s potential for real-life small sample sources and to create kidney substructure-specific proteomes

Set of Novel Automated Quantitative Microproteomics Protocols for Small Sample Amounts and Its Application to Kidney Tissue Substructures

Here we assessed the ability of an automated sample preparation device equipped with disposable microcolumns to prepare mass-limited samples for high-sensitivity quantitative proteomics, using both label-free and isobaric labeling approaches. First, we compared peptide label-free quantification reproducibility for 1.5–150 μg of cell lysates and found that labware preconditioning was essential for reproducible quantification of <7.5 μg digest. Second, in-solution and on-column tandem mass tag (TMT) labeling protocols were compared and optimized for 1 μg of sample. Surprisingly, standard methods for in-solution and on-column labeling showed poor TMT labeling (50–85%); however, novel optimized and automated protocols restored efficient labeling to >98%. Third, compared with a single long gradient experiment, a simple robotized high-pH fractionation protocol using only 6 μg of starting material doubled the number of unique peptides and increased proteome coverage 1.43-fold. To facilitate the analysis of heterogeneous tissue samples, such as those obtained from laser capture microdissection, a modified BCA protein assay was developed that consumes and detects down to 15 ng of protein. As a proof-of-principle, the modular automated workflow was applied to 0.5 and 1 mm² mouse kidney cortex and medulla microdissections to show the method’s potential for real-life small sample sources and to create kidney substructure-specific proteomes

Mass Spectrometry Imaging, Laser Capture Microdissection, and LC-MS/MS of the Same Tissue Section

Mass spectrometry imaging (MSI) is able to simultaneously record the distributions of hundreds of molecules directly from tissue. Rapid direct tissue analysis is essential for MSI in order to maintain spatial localization and acceptable measurement times. The absence of an explicit analyte separation/purification step means MSI lacks the depth of coverage of LC-MS/MS. In this work, we demonstrate how atmospheric pressure MALDI-MSI enables the same tissue section to be first analyzed by MSI, to identify regions of interest that exhibit distinct molecular signatures, followed by localized proteomics analysis using laser capture microdissection isolation and LC-MS/MS