Recent Developments in Data Independent Acquisition (DIA) Mass Spectrometry: Application of Quantitative Analysis of the Brain Proteome

被引:65
作者
Li, Ka Wan [1 ]
Gonzalez-Lozano, Miguel A. [1 ]
Koopmans, Frank [1 ]
Smit, August B. [1 ]
机构
[1] Vrije Univ Amsterdam, Dept Mol & Cellular Neurobiol, Ctr Neurogen & Cognit Res, Fac Sci,Amsterdam Neurosci, Amsterdam, Netherlands
来源
FRONTIERS IN MOLECULAR NEUROSCIENCE | 2020年 / 13卷
关键词
proteomics; neuroscience; brain; synapse; LC-MS; quantitative analyses; SYNAPTIC PLASTICITY; QUANTIFICATION; REPRODUCIBILITY; ACCURACY; DEPTH;
D O I
10.3389/fnmol.2020.564446
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Mass spectrometry is the driving force behind current brain proteome analysis. In a typical proteomics approach, a protein isolate is digested into tryptic peptides and then analyzed by liquid chromatography-mass spectrometry. The recent advancements in data independent acquisition (DIA) mass spectrometry provide higher sensitivity and protein coverage than the classic data dependent acquisition. DIA cycles through a pre-defined set of peptide precursor isolation windows stepping through 400-1,200 m/z across the whole liquid chromatography gradient. All peptides within an isolation window are fragmented simultaneously and detected by tandem mass spectrometry. Peptides are identified by matching the ion peaks in a mass spectrum to a spectral library that contains information of the peptide fragment ions' pattern and its chromatography elution time. Currently, there are several reports on DIA in brain research, in particular the quantitative analysis of cellular and synaptic proteomes to reveal the spatial and/or temporal changes of proteins that underlie neuronal plasticity and disease mechanisms. Protocols in DIA are continuously improving in both acquisition and data analysis. The depth of analysis is currently approaching proteome-wide coverage, while maintaining high reproducibility in a stable and standardisable MS environment. DIA can be positioned as the method of choice for routine proteome analysis in basic brain research and clinical applications.
引用
收藏
页数:8
相关论文
共 67 条
[61]   Surfaceome dynamics reveal proteostasis-independent reorganization of neuronal surface proteins during development and synaptic plasticity [J].
van Oostrum, Marc ;
Campbell, Benjamin ;
Seng, Charlotte ;
Mueller, Maik ;
Dieck, Susanne tom ;
Hammer, Jacqueline ;
Pedrioli, Patrick G. A. ;
Foeldy, Csaba ;
Tyagarajan, Shiva K. ;
Wollscheid, Bernd .
NATURE COMMUNICATIONS, 2020, 11 (01)
[62]   Removing the Hidden Data Dependency of DIA with Predicted Spectral Libraries [J].
Van Puyvelde, Bart ;
Willems, Sander ;
Gabriels, Ralf ;
Daled, Simon ;
De Clerck, Laura ;
Vande Casteele, Sofie ;
Staes, An ;
Impens, Francis ;
Deforce, Dieter ;
Martens, Lennart ;
Degroeve, Sven ;
Dhaenens, Maarten .
PROTEOMICS, 2020, 20 (3-4)
[63]   CKAMP44: A Brain-Specific Protein Attenuating Short-Term Synaptic Plasticity in the Dentate Gyrus [J].
von Engelhardt, Jakob ;
Mack, Volker ;
Sprengel, Rolf ;
Kavenstock, Netta ;
Li, Ka Wan ;
Stern-Bach, Yael ;
Smit, August B. ;
Seeburg, Peter H. ;
Monyer, Hannah .
SCIENCE, 2010, 327 (5972) :1518-1522
[64]   MS/MS Spectrum Prediction for Modified Peptides Using pDeep2 Trained by Transfer Learning [J].
Zeng, Wen-Feng ;
Zhou, Xie-Xuan ;
Zhou, Wen-Jing ;
Chi, Hao ;
Zhan, Jianfeng ;
He, Si-Min .
ANALYTICAL CHEMISTRY, 2019, 91 (15) :9724-9731
[65]   Data-Independent Acquisition Mass Spectrometry-Based Proteomics and Software Tools: A Glimpse in 2020 [J].
Zhang, Fangfei ;
Ge, Weigang ;
Ruan, Guan ;
Cai, Xue ;
Guo, Tiannan .
PROTEOMICS, 2020, 20 (17-18)
[66]   Systematic Assessment of the Effect of Internal Library in Targeted Analysis of SWATH-MS [J].
Zhong, Chuan-Qi ;
Wu, Rui ;
Chen, Xi ;
Wu, Suqin ;
Shuai, Jianwei ;
Han, Jiahuai .
JOURNAL OF PROTEOME RESEARCH, 2020, 19 (01) :477-492
[67]   pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning [J].
Zhou, Xie-Xuan ;
Zeng, Wen-Feng ;
Chi, Hao ;
Luo, Chunjie ;
Liu, Chao ;
Zhan, Jianfeng ;
He, Si-Min ;
Zhang, Zhifei .
ANALYTICAL CHEMISTRY, 2017, 89 (23) :12690-12697