Deep Ubiquitination Site Profiling by Data-Independent Acquisition Mass Spectrometry Reveals Usp7 Targets on a Proteome-Wide Scale

2020 ◽  
Author(s):  
Martin Steger ◽  
Phillip Ihmor ◽  
Mattias Backmann ◽  
Stefan Müller ◽  
Henrik Daub
Keyword(s):  
Mass Spectrometry ◽  
Data Independent Acquisition ◽  
Ubiquitination Site ◽  
Wide Scale

scholarly journals Time-resolved in vivo ubiquitinome profiling by DIA-MS reveals USP7 targets on a proteome-wide scale

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Martin Steger ◽  
Vadim Demichev ◽  
Mattias Backman ◽  
Uli Ohmayer ◽  
Phillip Ihmor ◽  
...  
Keyword(s):  
Neural Network ◽  
Mass Spectrometry ◽  
Sample Preparation ◽  
Mode Of Action ◽  
System Level ◽  
High Temporal Resolution ◽  
Time Resolved ◽  
Data Independent Acquisition ◽  
Wide Scale

AbstractMass spectrometry (MS)-based ubiquitinomics provides system-level understanding of ubiquitin signaling. Here we present a scalable workflow for deep and precise in vivo ubiquitinome profiling, coupling an improved sample preparation protocol with data-independent acquisition (DIA)-MS and neural network-based data processing specifically optimized for ubiquitinomics. Compared to data-dependent acquisition (DDA), our method more than triples identification numbers to 70,000 ubiquitinated peptides in single MS runs, while significantly improving robustness and quantification precision. Upon inhibition of the oncology target USP7, we simultaneously record ubiquitination and consequent changes in abundance of more than 8,000 proteins at high temporal resolution. While ubiquitination of hundreds of proteins increases within minutes of USP7 inhibition, we find that only a small fraction of those are ever degraded, thereby dissecting the scope of USP7 action. Our method enables rapid mode-of-action profiling of candidate drugs targeting DUBs or ubiquitin ligases at high precision and throughput.

scholarly journals Deep ubiquitination site profiling by single-shot data-independent acquisition mass spectrometry

2020 ◽  
Author(s):  
Martin Steger ◽  
Phillip Ihmor ◽  
Mattias Backman ◽  
Stefan Müller ◽  
Henrik Daub
Keyword(s):  
Mass Spectrometry ◽  
High Precision ◽  
Protein Extraction ◽  
Single Shot ◽  
Spectral Library ◽  
Sample Analysis ◽  
Precision Data ◽  
Data Independent Acquisition ◽  
Ubiquitination Site ◽  
High Precision Data

We report a highly optimized proteomics method for in-depth ubiquitination profiling, which combines efficient protein extraction and data-independent acquisition mass spectrometry (DIA-MS). Employing DIA for both spectral library generation and single-shot sample analysis, we quantify up to 70,000 ubiquitinated peptides per MS run with high precision, data completeness and throughput. Our approach resolves the dynamics of ubiquitination and protein degradation with an unprecedented analytical depth.

scholarly journals Proteomic insights into synaptic signaling in the brain: the past, present and future

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yalan Xu ◽  
Xiuyue Song ◽  
Dong Wang ◽  
Yin Wang ◽  
Peifeng Li ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Complexes ◽  
Synaptic Signaling ◽  
Brain Functions ◽  
The Past ◽  
Data Independent Acquisition ◽  
Technological Advances ◽  
Neural Communication ◽  
Chemical Synapses ◽  
The Brain

AbstractChemical synapses in the brain connect neurons to form neural circuits, providing the structural and functional bases for neural communication. Disrupted synaptic signaling is closely related to a variety of neurological and psychiatric disorders. In the past two decades, proteomics has blossomed as a versatile tool in biological and biomedical research, rendering a wealth of information toward decoding the molecular machinery of life. There is enormous interest in employing proteomic approaches for the study of synapses, and substantial progress has been made. Here, we review the findings of proteomic studies of chemical synapses in the brain, with special attention paid to the key players in synaptic signaling, i.e., the synaptic protein complexes and their post-translational modifications. Looking toward the future, we discuss the technological advances in proteomics such as data-independent acquisition mass spectrometry (DIA-MS), cross-linking in combination with mass spectrometry (CXMS), and proximity proteomics, along with their potential to untangle the mystery of how the brain functions at the molecular level. Last but not least, we introduce the newly developed synaptomic methods. These methods and their successful applications marked the beginnings of the synaptomics era.

Dipeptidyl peptidase 9 substrates and their discovery: current progress and the application of mass spectrometry-based approaches

2016 ◽  
Vol 397 (9) ◽  
pp. 837-856 ◽  
Author(s):  
Claire H. Wilson ◽  
Hui Emma Zhang ◽  
Mark D. Gorrell ◽  
Catherine A. Abbott
Keyword(s):  
Mass Spectrometry ◽  
Type Ii Diabetes ◽  
Dipeptidyl Peptidase ◽  
Dipeptidyl Peptidase 4 ◽  
Protein Substrates ◽  
Inflammatory Conditions ◽  
Protease Substrate ◽  
Wide Scale ◽  
Dipeptidyl Peptidases

Abstract The enzyme members of the dipeptidyl peptidase 4 (DPP4) gene family have the very unusual capacity to cleave the post-proline bond to release dipeptides from the N-terminus of peptide/protein substrates. DPP4 and related enzymes are current and potential therapeutic targets in the treatment of type II diabetes, inflammatory conditions and cancer. Despite this, the precise biological function of individual dipeptidyl peptidases (DPPs), other than DPP4, and knowledge of their in vivo substrates remains largely unknown. For many years, identification of physiological DPP substrates has been difficult due to limitations in the available tools. Now, with advances in mass spectrometry based approaches, we can discover DPP substrates on a system wide-scale. Application of these approaches has helped reveal some of the in vivo natural substrates of DPP8 and DPP9 and their unique biological roles. In this review, we provide a general overview of some tools and approaches available for protease substrate discovery and their applicability to the DPPs with a specific focus on DPP9 substrates. This review provides comment upon potential approaches for future substrate elucidation.

scholarly journals Novel circulating protein biomarkers for thyroid cancer determined through data-independent acquisition mass spectrometry

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9507
Author(s):  
Dandan Li ◽  
Jie Wu ◽  
Zhongjuan Liu ◽  
Ling Qiu ◽  
Yimin Zhang
Keyword(s):  
Mass Spectrometry ◽  
Area Under The Curve ◽  
High Sensitivity ◽  
Factor H ◽  
Complement Factor ◽  
Protein Biomarkers ◽  
Serum Samples ◽  
Data Independent Acquisition ◽  
Median Serum ◽  
And Control

Background Distinguishing between different types of thyroid cancers (TC) remains challenging in clinical laboratories. As different tumor types require different clinical interventions, it is necessary to establish new methods for accurate diagnosis of TC. Methods Proteomic analysis of the human serum was performed through data-independent acquisition mass spectrometry for 29 patients with TC (stages I–IV): 13 cases of papillary TC (PTC), 10 cases of medullary TC (MTC), and six cases follicular TC (FTC). In addition, 15 patients with benign thyroid nodules (TNs) and 10 healthy controls (HCs) were included in this study. Subsequently, 17 differentially expressed proteins were identified in 291 patients with TC, including 247 with PTC, 38 with MTC, and six with FTC, and 69 patients with benign TNs and 176 with HC, using enzyme-linked immunosorbent assays. Results In total, 517 proteins were detected in the serum samples using an Orbitrap Q-Exactive-plus mass spectrometer. The amyloid beta A4 protein, apolipoprotein A-IV, gelsolin, contactin-1, gamma-glutamyl hydrolase, and complement factor H-related protein 1 (CFHR1) were selected for further analysis. The median serum CFHR1 levels were significantly higher in the MTC and FTC groups than in the PTC and control groups (P < 0.001). CFHR1 exhibited higher diagnostic performance in distinguishing patients with MTC from those with PTC (P < 0.001), with a sensitivity of 100.0%, specificity of 85.08%, area under the curve of 0.93, and detection cut-off of 0.92 ng/mL. Conclusion CFHR1 may serve as a novel biomarker to distinguish PTC from MTC with high sensitivity and specificity.

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