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Sample Preparation for Endopeptidomic Analysis in Human Cerebrospinal Fluid

Artikel i vetenskaplig tidskrift
Författare Karl Hansson
Tobias Skillbäck
Elin Pernevik
Jessica Holmén Larsson
Gunnar Brinkmalm
Kaj Blennow
Henrik Zetterberg
Johan Gobom
Publicerad i Jove-Journal of Visualized Experiments
Nummer/häfte 130
ISSN 1940-087X
Publiceringsår 2017
Publicerad vid Institutionen för neurovetenskap och fysiologi, sektionen för psykiatri och neurokemi
Språk en
Länkar doi.org/10.3791/56244
Ämnesord Neuroscience, Issue 130, Cerebrospinal fluid, peptidomics, endogenous peptides, biomarkers, neurodegeneration, Alzheimer's disease, LC-MS/MS, pre-fractionation, multiplexed isobaric labelling, alzheimers-disease, diagnostic-criteria, biomarkers, proteome, csf, chromatography, fractionation, peptidomics, Science & Technology - Other Topics
Ämneskategorier Neurokemi

Sammanfattning

This protocol describes a method developed to identify endogenous peptides in human cerebrospinal fluid (CSF). For this purpose, a previously developed method based on molecular weight cut-off (MWCO) filtration and mass spectrometric analysis was combined with an offline high-pH reverse phase HPLC pre-fractionation step. Secretion into CSF is the main pathway for removal of molecules shed by cells of the central nervous system. Thus, many processes in the central nervous system are reflected in the CSF, rendering it a valuable diagnostic fluid. CSF has a complex composition, containing proteins that span a concentration range of 8-9 orders of magnitude. Besides proteins, previous studies have also demonstrated the presence of a large number of endogenous peptides. While less extensively studied than proteins, these may also hold potential interest as biomarkers. Endogenous peptides were separated from the CSF protein content through MWCO filtration. By removing a majority of the protein content from the sample, it is possible to increase the sample volume studied and thereby also the total amount of the endogenous peptides. The complexity of the filtrated peptide mixture was addressed by including a reverse phase (RP) HPLC pre-fractionation step at alkaline pH prior to LC-MS analysis. The fractionation was combined with a simple concatenation scheme where 60 fractions were pooled into 12, analysis time consumption could thereby be reduced while still largely avoiding co-elution. Automated peptide identification was performed by using three different peptide/protein identification software programs and subsequently combining the results. The different programs were complementary rather than comparable with less than 15% of the identifications overlapped between the three.

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