Oral Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Mass spectrometry workflow for characterization of plasma proteome changes related to ageing (#111)

Valentina Siino 1 , Giulia Accardi 2 , Sonya Vasto 3 , Fredrik Levander 1
  1. Department of Immunotechnology, Lund University, Lund, SKANE LAN, Sweden
  2. Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.) , University of Palermo, Palermo, Italy
  3. Department of Biological Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo, Palermo, PA, Italy


With simultaneous increase in life expectancy and age-related disorders, it becomes important to understand the ageing´s process to find early signs of disorders. Blood samples constitute an ideal source for molecular characterization, but the presence of highly abundant proteins and the lack of reproducibility represent challenges in plasma proteomics. However, in the past few years, fast developments of MS-based technologies and sample preparation protocols have revived the interest in plasma proteomics. The study presented here, aims to establish a robust and reproducible workflow for the quantification of plasma proteins. The method was used for the identification of blood biomarkers related to age in a cohort of 150 donors (30 to 100 years old).



Plasma proteins were retrieved from healthy donors. Technical replicates were used for running two different workflows: HILIC (ReSynBiosciences) and S-trap (Protifi). Sample preparation, including digestion, was performed in 2 hours. S-trap and HILIC peptides were separated on a nano LC-system coupled with a QExactive HF-X Orbitrap (Thermo Fisher Scientific). Data were acquired in DDA and DIA mode.



Without any fractionation or depletion, we were able to identify over 400 plasma proteins/sample. Comparing the two sample preparation methods, the most comprehensive results were achieved by using S-trap. Furthermore, by acquiring in DDA and DIA mode over 600 plasma proteins were identified.



From the present study, we concluded that the use of S-trap, coupled with DDA and DIA mode is ideal for the identification of plasma proteins. These results are encouraging, suggesting that a quick and high-throughput methodology can be employed to quantify a wide range of plasma proteins. This method may enable the classification and stratification of patients by their age as well as the identification of specific biomarkers that could predict the development of certain age-related disorders.