In-depth human plasma proteome analysis captures tissue proteins and transfer of protein variants across the placenta.

Maria Pernemalm,Yafeng Zhu,Marie Wahren-Herlenius,Jorrit Boekel,Janne Lehtiö,Claes-Göran Östenson,Albin Björk,Hanna Åmark,Annsofi Sandberg,Davide Tamburro,Magnus Westgren,Jochen M Schwenk

doi:10.7554/elife.41608

Maria Pernemalm, Yafeng Zhu + Show 10 more

Open Access

https://doi.org/10.7554/elife.41608

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Abstract

Here, we present a method for in-depth human plasma proteome analysis based on high-resolution isoelectric focusing HiRIEF LC-MS/MS, demonstrating high proteome coverage, reproducibility and the potential for liquid biopsy protein profiling. By integrating genomic sequence information to the MS-based plasma proteome analysis, we enable detection of single amino acid variants and for the first time demonstrate transfer of multiple protein variants between mother and fetus across the placenta. We further show that our method has the ability to detect both low abundance tissue-annotated proteins and phosphorylated proteins in plasma, as well as quantitate differences in plasma proteomes between the mother and the newborn as well as changes related to pregnancy.

Highlights

Several studies have presented draft maps of the human tissue proteome using mass spectrometry (MS)-based methods (Kim et al, 2014; Wilhelm et al, 2014; Bekker-Jensen et al, 2017)
The effect of MS analysis time alone on plasma proteome coverage was evaluated by an MS runtime control composed of 72 LC-MS/MS cycles of a depleted sample using identical settings and total MS time as for the HiRIEF fractions (Figure 1a)
This was done to make sure that the number of identifications post fractionation was not purely an inflation caused by MS analysis time alone or an effect of spurious and possibly false identifications caused in the search pipeline when searching a large number of MS-injections in parallel

Summary

Introduction

Several studies have presented draft maps of the human tissue proteome using mass spectrometry (MS)-based methods (Kim et al, 2014; Wilhelm et al, 2014; Bekker-Jensen et al, 2017). Due to major analytical challenges in plasma, extensive MS-based plasma proteome studies have largely focused on meta-analysis of publicly available datasets. Examples include the Plasma Proteome Database (PPD) (Nanjappa et al, 2014) and the PeptideAtlas plasma proteome repository (Schwenk et al, 2017). One major challenge in plasma proteomics is the ability to analyze larger sample cohorts while retaining proteome coverage. In the Plasma Proteome Database 10 546 proteins have been reported from 509 publications; only 3784 of the identified proteins are present in two or more studies (Nanjappa et al, 2014)

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Conclusion