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1.
Front Immunol ; 13: 964901, 2022.
Article in English | MEDLINE | ID: mdl-36275708

ABSTRACT

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with multi-organ inflammation and defect, which is linked to many molecule mediators. Oxylipins as a class of lipid mediator have not been broadly investigated in SLE. Here, we applied targeted mass spectrometry analysis to screen the alteration of oxylipins in serum of 98 SLE patients and 106 healthy controls. The correlation of oxylipins to lupus nephritis (LN) and SLE disease activity, and the biomarkers for SLE classification, were analyzed. Among 128 oxylipins analyzed, 92 were absolutely quantified and 26 were significantly changed. They were mainly generated from the metabolism of several polyunsaturated fatty acids, including arachidonic acid (AA), linoleic acid (LA), docosahexanoic acid (DHA), eicosapentanoic acid (EPA) and dihomo-γ-linolenic acid (DGLA). Several oxylipins, especially those produced from AA, showed different abundance between patients with and without lupus nephritis (LN). The DGLA metabolic activity and DGLA generated PGE1, were significantly associated with SLE disease activity. Random forest-based machine learning identified a 5-oxylipin combination as potential biomarker for SLE classification with high accuracy. Seven individual oxylipin biomarkers were also identified with good performance in distinguishing SLE patients from healthy controls (individual AUC > 0.7). Interestingly, the biomarkers for differentiating SLE patients from healthy controls are distinct from the oxylipins differentially expressed in LN patients vs. non-LN patients. This study provides possibilities for the understanding of SLE characteristics and the development of new tools for SLE classification.


Subject(s)
Lupus Erythematosus, Systemic , Lupus Nephritis , Humans , Lupus Nephritis/diagnosis , Oxylipins , 8,11,14-Eicosatrienoic Acid , Eicosapentaenoic Acid , Alprostadil , Biomarkers , Arachidonic Acids , Linoleic Acids
2.
Anal Chem ; 89(11): 5784-5792, 2017 06 06.
Article in English | MEDLINE | ID: mdl-28530406

ABSTRACT

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.


Subject(s)
Proteomics/methods , Specimen Handling/methods , Buffers , Chromatography, Liquid , Detergents/isolation & purification , Peptides/analysis , Proteins/analysis , Salts/isolation & purification , Tandem Mass Spectrometry
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