Dataset Information

Enhanced protein identification using graphite-modified MALDI plates for offline LC-MALDI-MS/MS bottom-up proteomics.

ABSTRACT: The use of offline liquid chromatography-matrix assisted laser desorption/ionization (LC-MALDI) tandem mass spectrometry (MS/MS) for bottom-up proteomics offers advantages in terms of cost, ease of use, and the time-decoupled nature of the separation step and the mass analysis. A method was developed to improve the capabilities of LC-MALDI-MS/MS in terms of protein identification in a bottom-up proteomic workflow. Enhanced protein identification is achieved by an increase in the MALDI signal intensity of the precursor peptides brought about by coating the MALDI plate with a thin film of graphite powder. Using the Escherichia coli proteome, it is demonstrated that the graphite-modified MALDI plates used in an offline LC-MALDI-MS/MS bottom-up protocol led to a 50-135% increase in the number of peptide identifications, and a concomitant 21%-105% increase in the number of proteins inferred. We identify factors that lead to improvements in peptide sequence identifications and in the number of unique proteins identified when compared to using an unmodified MALDI plate. These improvements are achieved using a low cost approach that it is easy to implement, requires no hardware/protocol modification, it is compatible with LC and adds no additional analysis time.

SUBMITTER: Maus A

PROVIDER: S-EPMC6026324 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Enhanced protein identification using graphite-modified MALDI plates for offline LC-MALDI-MS/MS bottom-up proteomics.

Maus Anthony A Mignon Rudolph R Basile Franco F

Analytical biochemistry 20180108

The use of offline liquid chromatography-matrix assisted laser desorption/ionization (LC-MALDI) tandem mass spectrometry (MS/MS) for bottom-up proteomics offers advantages in terms of cost, ease of use, and the time-decoupled nature of the separation step and the mass analysis. A method was developed to improve the capabilities of LC-MALDI-MS/MS in terms of protein identification in a bottom-up proteomic workflow. Enhanced protein identification is achieved by an increase in the MALDI signal int ...[more]

PMID: 29326070

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Project description:Highly specialized cells are fundamental for proper functioning of complex organs. Variations in cell-type specific gene expression and protein composition have been linked to a variety of diseases. Although single cell technologies have emerged as valuable tools to address this cellular heterogeneity, a majority of these workflows lack sufficient in situ resolution for functional classification of cells and are associated with extremely long analysis time, especially when it comes to in situ proteomics. In addition, lack of understanding of single cell dynamics within their native environment limits our ability to explore the altered physiology in disease development. This limitation is particularly relevant in the mammalian brain, where different cell types perform unique functions and exhibit varying sensitivities to insults. The hippocampus, a brain region crucial for learning and memory, is of particular interest due to its obvious involvement in various neurological disorders. Here, we present a combination of experimental and data integration approaches for investigation of cellular heterogeneity and functional disposition within the mouse brain hippocampus using MALDI Imaging mass spectrometry (MALDI-IMS) and shotgun proteomics (LC-MS/MS) coupled with laser-capture microdissection (LCM) along with spatial transcriptomics. Within the dentate gyrus granule cells we identified two proteomically distinct cellular subpopulations that are characterized by a substantial number of discriminative proteins. These cellular clusters contribute to the overall functionality of the dentate gyrus by regulating redox homeostasis, mitochondrial organization, RNA processing, and microtubule organization. Importantly, most of the identified proteins matched their transcripts, verifying the in situ protein identification and supporting their functional analyses. By combining high-throughput spatial proteomics with transcriptomics, our approach enables reliable near-single-cell scale identification of proteins and profiling of inter-cellular heterogeneity within similar cell-types in tissues. This methodology has the potential to be applied to different biological conditions and tissues, providing a deeper understanding of cellular subpopulations in situ.

Project description:Highly specialized cells are fundamental for the proper functioning of complex organs. Variations in cell-type-specific gene expression and protein composition have been linked to a variety of diseases. Investigation of the distinctive molecular makeup of these cells within tissues is therefore critical in biomedical research. Although several technologies have emerged as valuable tools to address this cellular heterogeneity, most workflows lack sufficient in situ resolution and are associated with high costs and extremely long analysis times. Here, we present a combination of experimental and computational approaches that allows a more comprehensive investigation of molecular heterogeneity within tissues than by either shotgun LC-MS/MS or MALDI imaging alone. We applied our pipeline to the mouse brain, which contains a wide variety of cell types that not only perform unique functions but also exhibit varying sensitivities to insults. We explored the distinct neuronal populations within the hippocampus, a brain region crucial for learning and memory that is involved in various neurological disorders. As an example, we identified the groups of proteins distinguishing the neuronal populations of the dentate gyrus (DG) and the cornu ammonis (CA) in the same brain section. Most of the annotated proteins matched the regional enrichment of their transcripts, thereby validating the method. As the method is highly reproducible, the identification of individual masses through the combination of MALDI-IMS and LC-MS/MS methods can be used for the much faster and more precise interpretation of MALDI-IMS measurements only. This greatly speeds up spatial proteomic analyses and allows the detection of local protein variations within the same population of cells. The method's general applicability has the potential to be used to investigate different biological conditions and tissues and a much higher throughput than other techniques making it a promising approach for clinical routine applications.

Dataset Information

Enhanced protein identification using graphite-modified MALDI plates for offline LC-MALDI-MS/MS bottom-up proteomics.

Publications

Enhanced protein identification using graphite-modified MALDI plates for offline LC-MALDI-MS/MS bottom-up proteomics.

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