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Optimization of SWATH-MS workflow for human blood serum proteome analysis using a Design of Experiments approach

ABSTRACT: Accurate identification and quantification of the human serum proteome can help identify biomarkers of disease. SWATH (Sequential Window Acquisition of all Theoretical Spectra) is a type of Data Independent Acquisition (DIA) method which allows proteome-wide coverage and high quantification reproducibility. Optimization of the liquid chromatography (LC) and mass spectrometry (MS) parameters is essential for acquiring high quality raw data that results in precise and consistent protein quantification. We used Design of Experiments (DoE) to first identify the most important LC-MS parameters and subsequently refine them at the same time to increase the number of proteins quantified in human serum. The number of SWATH windows and the MS/MS accumulation time have the most significant impact over SWATH outcome, affecting the results in an interdependent manner. Our approach can efficiently optimize multiple parameters simultaneously and it is adaptable to different samples and equipment.

INSTRUMENT(S): TripleTOF 6600

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: John Isaacs

PROVIDER: MSV000085570 | MassIVE | Wed Jun 10 06:42:00 BST 2020

REPOSITORIES: MassIVE

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Project description:Use of Information Dependent Acquisition mass spectra and Sequential Window Acquisition of all Theoretical fragment-ion mass spectra for fruit juices metabolomics and authentication. LC-MS based untargeted metabolomics are the main untargeted methods used for juice metabolomics to solve the authentication problem faced in fruit juice industry. Objectives To evaluate the performances of different untargeted metabolomics methods on fruit juices metabolomics and authentication, orange and apple fruit juices were selected for this study. Methods IDA-MS and SWATH-MS based on UHPLC-QTOF were used for the metabolomics and authenticity determination of apple and orange juices, including the lab-made samples of oranges (Citrus sinensis Osb.) from Jiangxi Province, apples (Malus domestica Borkh) from Shandong Province, and different brands of commercial orange and apple juice samples from markets. Results IDA-MS and SWATH-MS could both acquire numerous MS1 features and MS2 information of juice components, while SWATH-MS excels at the acquisition rate of MS2. Distinctive separation between authentic orange juice and not authentic orange juice could be seen from principal component analysis and hierarchical clustering analysis based on both IDA-MS and SWATH-MS. After analysis of variance, fold change analysis and orthogonal projection to latent structures discriminant mode, 53 and 46 potential markers were defined by IDA-MS and SWATH-MS (with 77.4% and 100% MS2 acquisition rate) separately. Subsequently, these potential markers were putatively annotated using general chemical databases with 6 more annotated by SWATH-MS. Furthermore, 7 of the potential markers, l-asparagine, umbelliferone, glucosamine, phlorin, epicatechin, phytosphingosine and chlorogenic acid, were identified with standards. For the consideration of model simplicity, two determined makers (umbelliferone and chlorogenic acid) were selected to construct the DD-SIMCA model in commercial samples because of their good correlation with apple adulteration proportion, and the sensitivity and specificity of the model were 100% and 95%. Conclusion SWATH-MS excels at the MS2 acquisition of juice components and potential markers. This study provides an overall performance comparison between IDA-MS and SWATH-MS, and guidance for the method selection on fruit juice metabolomics and juice authenticity determination. Two of the potential markers determined, umbelliferone and chlorogenic acid, could be used as apple juice indicators in orange juice.

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Optimization of SWATH-MS workflow for human blood serum proteome analysis using a Design of Experiments approach

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