DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics
| Autor: | Brent R. Martin, Sarah E. Haynes, Jaimeen D. Majmudar |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Proteomics
0301 basic medicine Proteome Cell Culture Techniques Mass spectrometry 01 natural sciences Article Mass Spectrometry Analytical Chemistry 03 medical and health sciences Protein Annotation Stable isotope labeling by amino acids in cell culture Humans Data-independent acquisition Amino Acids Chemistry Stable isotope ratio 010401 analytical chemistry Filter (signal processing) 0104 chemical sciences HEK293 Cells 030104 developmental biology Isotope Labeling Deconvolution Biological system Software |
| Zdroj: | Analytical Chemistry. 90:8722-8726 |
| ISSN: | 1520-6882 0003-2700 |
| DOI: | 10.1021/acs.analchem.8b01618 |
| Popis: | Quantitative mass spectrometry-based protein profiling is widely used to measure protein levels across different treatments or disease states, yet current mass spectrometry acquisition methods present distinct limitations. While data-independent acquisition (DIA) bypasses the stochastic nature of data-dependent acquisition (DDA), fragment spectra derived from DIA are often complex and challenging to deconvolve. In-line ion mobility separation (IMS) adds an additional dimension to increase peak capacity for more efficient product ion assignment. As a similar strategy to sequential window acquisition methods (SWATH), IMS-enabled DIA methods rival DDA methods for protein annotation. Here we evaluate IMS-DIA quantitative accuracy using stable isotope labeling by amino acids in cell culture (SILAC). Since SILAC analysis doubles the sample complexity, we find that IMS-DIA analysis is not sufficiently accurate for sensitive quantitation. However, SILAC precursor pairs share common retention and drift times, and both species co-fragment to yield multiple quantifiable isotopic y-ion peak pairs. Since y-ion SILAC ratios are intrinsic for each quantified precursor, combined MS1 and y-ion ratio analysis significantly increases the total number of measurements. With increased sampling, we present DIA-SIFT (SILAC Intrinsic Filtering Tool), a simple statistical algorithm to identify and eliminate poorly quantified MS1 and/or MS2 events. DIA-SIFT combines both MS1 and y-ion ratios, removes outliers, and provides more accurate and precise quantitation ( |
| Databáze: | OpenAIRE |
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