Dataset Information

Library-free BoxCarDIA solves the missing value problem in label-free quantitative proteomics

ABSTRACT: The last decade has seen significant advances in the application of quantitative mass spectrometry-based proteomics technologies to tackle important questions in plant biology. The current standard for quantitative proteomics in plants is the use of data-dependent acquisition (DDA) analysis with or without the use of chemical labels. However, the DDA approach preferentially measures higher abundant proteins, and often requires data imputation due to quantification inconsistency between samples. In this study we systematically benchmarked a recently developed library-free data-independent acquisition (directDIA) method against a state-of-the-art DDA label-free quantitative proteomics workflow for plants. We next developed a novel acquisition approach combining MS1-level BoxCar acquisition with MS2-level directDIA analysis that we call BoxCarDIA. DirectDIA achieves a 33% increase in protein quantification over traditional DDA, and BoxCarDIA a further 8%, without any changes in instrumentation, offline fractionation, or increases in mass-spectrometer run time. BoxCarDIA, especially, offers wholly reproducible quantification of proteins between replicate injections, thereby addressing the long-standing missing-value problem in label-free quantitative proteomics. Further, we find that the gains in dynamic range sampling by directDIA and BoxCarDIA translate to deeper quantification of key, low abundant, functional protein classes (e.g., protein kinases and transcription factors) that are underrepresented in data acquired using DDA. We applied these methods to perform a quantitative proteomic comparison of dark and light grown Arabidopsis cell cultures, providing a critical resource for future plant interactome studies. Our results establish BoxCarDIA as the new method of choice in quantitative proteomics using Orbitrap-type mass-spectrometers, particularly for proteomes with large dynamic range such as that of plants.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Arabidopsis Thaliana (mouse-ear Cress)

TISSUE(S): Plant Cell, Cell Suspension Culture, Cell Culture

SUBMITTER: Richard Uhrig

LAB HEAD: R. Glen Uhrig

PROVIDER: PXD022448 | Pride | 2021-05-11

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:Clubroot of Brassicaceae, an economically important soil borne disease, is caused by Plasmodiophora brassicae Woronin, an obligate, biotrophic protist. This disease poses a serious threat to canola and related crops in Canada and around the globe causing significant loss to seed yield. The pathogen is continuously evolving and new pathotypes are emerging, this necessitates the development of novel resistant canola cultivars to manage the disease effectively. Given that proteins play a crucial role in majority of biological processes and molecular functions, the identification of differentially abundant proteins (DAP) using proteomics information is an attractive approach to understand the plant-pathogen interactions as well as in the future development of gene specific markers for developing clubroot resistant (CR) cultivars. In this study, P. brassicae pathotype 3 (P3H) was used to challenge CR and clubroot susceptible (CS) canola lines. Root samples were collected at three distinct stages of pathogenesis, 7-, 14-, and 21-days post inoculation (DPI), protein samples were isolated, digested with trypsin and subjected to LC-MS/MS analysis. A total of 937 proteins demonstrated a significant (q < 0.05) change in abundance in at least in one of the time points when compared between control and inoculated CR-parent, CR-progeny, CS-parent, CS-progeny and 784 proteins were significantly (q < 0.05) changed in abundance in at least in one of the time points when compared between the inoculated- CR and CS root proteomes of parent and progeny across the three time points tested. Functional annotation of the differentially abundant proteins (DAPs) revealed several proteins related to calcium dependent signaling pathways in response to the pathogen. In addition, proteins related to reactive oxygen species (ROS) biochemistry, dehydrins, lignin, thaumatin, and phytohormones were identified. Among the DAPs, 74 putative proteins orthologous to CR proteins and quantitative trait loci (QTL) associated with eight CR loci in four chromosomes including chromosomes A3 and A8 were identified. In conclusion, these results have contributed to an improved understanding of the mechanisms that are involved in mediating response to P. brassicae in canola at the protein level.

Dataset Information

Library-free BoxCarDIA solves the missing value problem in label-free quantitative proteomics

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure