Dataset Information

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF.

ABSTRACT: Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.

SUBMITTER: Theron L

PROVIDER: S-EPMC5260965 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF.

Théron Laëtitia L Centeno Delphine D Coudy-Gandilhon Cécile C Pujos-Guillot Estelle E Astruc Thierry T Rémond Didier D Barthelemy Jean-Claude JC Roche Frédéric F Feasson Léonard L Hébraud Michel M Béchet Daniel D Chambon Christophe C

Proteomes 20161026 4

Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the t ...[more]

PMID: 28248242

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Project description:BackgroundAlthough fold change is a commonly used criterion in quantitative proteomics for differentiating regulated proteins, it does not provide an estimation of false positive and false negative rates that is often desirable in a large-scale quantitative proteomic analysis. We explore the possibility of applying the Significance Analysis of Microarray (SAM) method (PNAS 98:5116-5121) to a differential proteomics problem of two samples with replicates. The quantitative proteomic analysis was carried out with nanoliquid chromatography/linear iron trap-Fourier transform mass spectrometry. The biological sample model included two Mycobacterium smegmatis unlabeled cell cultures grown at pH 5 and pH 7. The objective was to compare the protein relative abundance between the two unlabeled cell cultures, with an emphasis on significance analysis of protein differential expression using the SAM method. Results using the SAM method are compared with those obtained by fold change and the conventional t-test.ResultsWe have applied the SAM method to solve the two-sample significance analysis problem in liquid chromatography/mass spectrometry (LC/MS) based quantitative proteomics. We grew the pH5 and pH7 unlabelled cell cultures in triplicate resulting in 6 biological replicates. Each biological replicate was mixed with a common 15N-labeled reference culture cells for normalization prior to SDS/PAGE fractionation and LC/MS analysis. For each biological replicate, one center SDS/PAGE gel fraction was selected for triplicate LC/MS analysis. There were 121 proteins quantified in at least 5 of the 6 biological replicates. Of these 121 proteins, 106 were significant in differential expression by the t-test (p < 0.05) based on peptide-level replicates, 54 were significant in differential expression by SAM with Delta = 0.68 cutoff and false positive rate at 5%, and 29 were significant in differential expression by the t-test (p < 0.05) based on protein-level replicates. The results indicate that SAM appears to overcome the false positives one encounters using the peptide-based t-test while allowing for identification of a greater number of differentially expressed proteins than the protein-based t-test.ConclusionWe demonstrate that the SAM method can be adapted for effective significance analysis of proteomic data. It provides much richer information about the protein differential expression profiles and is particularly useful in the estimation of false discovery rates and miss rates.

Project description:Quantitation of wheat proteins is still a challenge, especially regarding amylase/trypsin-inhibitors (ATIs). A selection of ATIs was silenced in the common wheat cultivar Bobwhite and durum wheat cultivar Svevo by RNAi and gene editing, respectively, in order to reduce the amounts of ATIs. The controls and silenced lines were analyzed after digestion to peptides by LC-MS/MS with different approaches to evaluate changes in composition of ATIs. First, a targeted method with stable isotope dilution assay (SIDA) using labeled peptides as internal standards was applied. Additionally, four different approaches for relative quantitation were conducted, in detail, iTRAQ labeled and label free quantitation (LFQ) combined with data dependent acquisition (DDA) and data independent acquisition (DIA). Quantitation was performed manually (Skyline and MASCOT) and with different proteomics software tools (PLGS, MaxQuant, and PEAKS X Pro). To characterize the wheat proteins on protein level, complementary techniques as high-performance liquid chromatography (HPLC) and gel electrophoresis were performed. The targeted approach with SIDA was able to quantitate all ATIs, even at low levels, but an optimized extraction is necessary. The labeled iTRAQ approach revealed an indistinct performance. LFQ with low resolution equipment (IonTrap) showed similar results for major ATIs, but low abundance ATIs as CM1, were not detectable. DDA measurements with an Orbitrap system and evaluation using MaxQuant showed that the relative quantitation was dependent on the wheat species. The combination of manual curation of the MaxQuant search with Skyline revealed a very good performance. The DIA approach with analytical flow found similar results compared to absolute quantitation except for some minor ATIs, which were not detected. Comparison of applied methods revealed that peptide selection is a crucial step for protein quantitation. Wheat proteomics faces challenges due to the high genetic complexity, the close relationship to other cereals and the incomplete, redundant protein database requiring sensitive, precise and accurate LC-MS/MS methods.

Dataset Information

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF.

Publications

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF.

Similar Datasets

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