Dataset Information

Differential urine proteome analysis of a ventilator-induced lung injury rat model by label-free quantitative and parallel reaction monitoring proteomics

ABSTRACT: Urine is a promising resource for biomarker research. Therefore, the purpose of this study was to investigate potential urinary biomarkers to monitor the disease activity of ventilator-induced lung injury (VILI). In the discovery phase, a label-free data-dependent acquisition (DDA) quantitative proteomics method was used to profile the urinary proteomes of VILI rats. For further validation, the differential proteins were verified by parallel reaction monitoring (PRM)-targeted quantitative proteomics. In total, 727 high-confidence proteins were identified with at least 1 unique peptide (FDR ≤ 1%). Compared to the control group, 110 proteins (65 upregulated, 45 downregulated) were significantly changed in the VILI group (1.5-fold change, P < 0.05). The canonical pathways and protein–protein interaction analyses revealed that the differentially expressed proteins were enriched in multiple functions, including oxidative stress and inflammatory responses. Finally, thirteen proteins were identified as candidate biomarkers for VILI by PRM validation. Among these PRM-validated proteins, AMPN, MEP1B, LYSC1, DPP4 and CYC were previously reported as lung-associated disease biomarkers. SLC31, MEP1A, S15A2, NHRF1, XPP2, GGT1, HEXA, and ATPB were newly discovered in this study. Our results suggest that the urinary proteome might reflect the pathophysiological changes associated with VILI. These differential proteins are potential urinary biomarkers for the activity of VILI.

SUBMITTER: Qin W

PROVIDER: S-EPMC8563714 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundEarly diagnosis and typing are crucial for improving the prognosis of patients with renal amyloidosis. Currently, Untargeted proteomics based precise diagnosis and typing of amyloid deposits are crucial for guiding patient management. Although untargeted proteomics achieve ultra-high-throughput by selecting the most abundant eluting cationic peptide precursors in series for tandem MS events, it lacks in sensitivity and reproducibility, which may not be suitable for early-stage renal amyloidosis with minor damages. Here, we aimed to develop parallel reaction monitoring (PRM)-based targeted proteomics to achieve high sensitivity and specificity by determining absolute abundances and codetecting all transitions of highly repeatable peptides of preselected amyloid signature and typing proteins in identifying early-stage renal immunoglobulin-derived amyloidosis.Methods and resultsIn 10 discovery cohort cases, Congo red-stained FFPE slices were micro-dissected and analyzed by data-dependent acquisition-based untargeted proteomics for preselection of typing specific proteins and peptides. Further, a list of proteolytic peptides from amyloidogenic proteins and internal standard proteins were quantified by PRM-based targeted proteomics to validate performance for diagnosis and typing in 26 validation cohort cases. The diagnosis and typing effectiveness of PRM-based targeted proteomics in 10 early-stage renal amyloid cases was assessed via a comparison with untargeted proteomics. A peptide panel of amyloid signature proteins, immunoglobulin light chain and heave chain in PRM-based targeted proteomics showed significantly distinguishing ability and amyloid typing performance in patients. The diagnostic algorithm of targeted proteomics with a low amount of amyloid deposits in early-stage renal immunoglobulin-derived amyloidosis showed better performance than untargeted proteomics in amyloidosis typing.ConclusionsThis study demonstrates that the utility of these prioritized peptides in PRM-based targeted proteomics ensure high sensitivity and reliability for identifying early-stage renal amyloidosis. Owing to the development and clinical application of this method, rapid acceleration of the early diagnosis, and typing of renal amyloidosis is expected.

Project description:Targeted high-resolution and accurate mass analyses performed on fast sequencing mass spectrometers have opened new avenues for quantitative proteomics. More specifically, parallel reaction monitoring (PRM) implemented on quadrupole-orbitrap instruments exhibits exquisite selectivity to discriminate interferences from analytes. Furthermore, the instrument trapping capability enhances the sensitivity of the measurements. The PRM technique, applied to the analysis of limited peptide sets (typically 50 peptides or less) in a complex matrix, resulted in an improved detection and quantification performance as compared with the reference method of selected reaction monitoring performed on triple quadrupole instruments. However, the implementation of PRM for the analysis of large peptide numbers requires the adjustment of mass spectrometry acquisition parameters, which affects dramatically the quality of the generated data, and thus the overall output of an experiment. A newly designed data acquisition scheme enabled the analysis of moderate-to-large peptide numbers while retaining a high performance level. This new method, called internal standard triggered-parallel reaction monitoring (IS-PRM), relies on added internal standards and the on-the-fly adjustment of acquisition parameters to drive in real-time measurement of endogenous peptides. The acquisition time management was designed to maximize the effective time devoted to measure the analytes in a time-scheduled targeted experiment. The data acquisition scheme alternates between two PRM modes: a fast low-resolution "watch mode" and a "quantitative mode" using optimized parameters ensuring data quality. The IS-PRM method exhibited a highly effective use of the instrument time. Applied to the analysis of large peptide sets (up to 600) in complex samples, the method showed an unprecedented combination of scale and analytical performance, with limits of quantification in the low amol range. The successful analysis of various types of biological samples augurs a broad applicability of the method, which is likely to benefit a wide range of proteomics experiments.

Project description:High-density lipoprotein (HDL), a lipid nanoparticle containing many different low abundance proteins, is an attractive target for clinical proteomics because its compositional heterogeneity is linked to its cardioprotective effects. Selected reaction monitoring (SRM) is currently the method of choice for targeted quantification of proteins in such a complex biological matrix. However, model system studies suggest that parallel reaction monitoring (PRM) is more specific than SRM because many product ions can be used to confirm the identity of a peptide. We therefore compared PRM and SRM for their abilities to quantify proteins in HDL, using (15)N-labeled apolipoprotein A-I (HDL's most abundant protein) as the internal standard. PRM and SRM exhibited comparable linearity, dynamic range, precision, and repeatability for protein quantification of HDL. Moreover, the single internal standard protein performed as well as protein-specific peptide internal standards when quantifying 3 different proteins. Importantly, PRM and SRM yielded virtually identical quantitative results for 26 proteins in HDL isolated from 44 subjects. Because PRM requires less method development than SRM and is potentially more specific, our observations indicate that PRM in concert with a single isotope-labeled protein is a promising new strategy for quantifying HDL proteins in translational studies.Biological significanceHDL, a complex matrix composed of lipids and proteins, is implicated in cardioprotection. Its cholesterol content correlates inversely with cardiovascular disease and it is the current metric to assess cardiovascular risk. However, the cholesterol content does not capture HDL's complexity and heterogeneity. Devising metrics that better capture HDL's cardioprotective effects, we developed an optimized method for quantification of HDL proteome, using PRM in concert with a single labeled protein as internal standard. The availability of a method that increases sample throughput without compromising the reproducibility, sensitivity, and accuracy could therefore point to better risk assessment for CVD or other diseases.

Dataset Information

Differential urine proteome analysis of a ventilator-induced lung injury rat model by label-free quantitative and parallel reaction monitoring proteomics

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets