Abstract
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.
Highlights
The brain is the most complex organ in the human body
Many synaptic proteins were present on the surface at the time when synapse counts began to increase, and they reached peak abundance 2 days before the peak of synapse counts at 18 days in vitro. This suggests that many synaptic proteins are produced and trafficked to the membrane surface before synapses are formed and only later are these proteins organized into synaptic micro-domains by surface diffusion
A recent study demonstrated that using a spectral library search in dependent acquisition (DDA), in a manner similar to a data independent acquisition (DIA) data analysis strategy, led to substantial improvement of reproducibility in protein identification and quantitation with lower coefficient of variation and reduced missing values (Fernandez-Costa et al, 2020)
Summary
The brain is the most complex organ in the human body. It consists of about 85 billion neurons of different types, and an equal number of non-neuronal cells (Herculano-Houzel, 2009). As MS/MS fragments, all the peptide precursors within a mass range of interest are used, and a highly complex fragment ion mass spectrum is generated This is challenging for data analysis using a conventional genome-wide species-specific database. A project-specific spectral library is typically acquired from multiple fractionated DDA analysis of the same type of sample on the same instrument, and searched against a protein sequence database to identify peptides. The fragment ion intensities of the lower abundant peptides may be suppressed For this reason, current DIA protocols often use isolation windows
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