Mass spectrometry (MS) has become the gold standard method for proteomics by allowing the simultaneous identification and/or quantification of thousands of proteins of a given sample. Over time, mass spectrometry has evolved into newer quantitative approaches with increased sensitivity and accuracy, such as the sequential windows acquisition of all theoretical fragment-ion spectra (SWATH)-MS approach. Moreover, in the past few years, some improvements were made in the SWATH-acquisition algorithm, allowing the design of sample-customized acquisition methods by adjusting the Q1 windows’ width in order to reduce it in the most populated m/z regions. This customization results in an increase in the specificity and a reduction in the interferences, ultimately leading to an improvement in the amount of quantitative data extracted to eventually increase the proteome coverage. These improvements are especially relevant for clinical neuroproteomics, which is mainly based on the analysis of circulatory biofluids, in particular the cerebrospinal fluid (CSF) due to its close connection with the brain.
In the present chapter, a detailed description of the methodologies necessary to perform a whole-proteome relative quantification of CSF samples by SWATH-MS is presented, starting with the isolation of the protein fraction, its preparation for MS analysis, with all the necessary information for the design of a SWATH-MS method specific for each sample batch, and finally providing different methodologies for the analysis of the quantitative data obtained.
CSF Untargeted proteomics SWATH-MS Variable Q1 windows
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This work was supported by Fundação para a Ciência e Tecnologia (FCT) [PTDC/SAU-NMC/112183/2009, PTDC/NEU-NMC/0205/2012, PTDC/NEU-SCC/7051/2014, UID/NEU/04539/2013, UID/BIM/04773/2013, PEst-C/SAU/LA0001/2013-2014, POCI-01-0145-FEDER-016428 (ref.: SAICTPAC/0010/2015), POCI-01-0145-FEDER-029311 (ref.: PTDC/BTM-TEC/29311/2017), POCI-01-0145-FEDER-30943 (ref.: PTDC/MEC-PSQ/30943/2017)] and cofinanced by “COMPETE Programa Operacional Factores de Competitividade”, QREN; the European Union (FEDER—Fundo Europeu de Desenvolvimento Regional) and by The National Mass Spectrometry Network (RNEM) (POCI-01-0145-FEDER-402-022125) (ref.: ROTEIRO/0028/2013). Cátia Santa is supported by FCT PhD fellowship SFRH/BD/88419/2012, cofinanced by the European Social Fund (ESF) through the POCH—Programa Operacional do Capital Humano and national funds via FCT.
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