Robust High Throughput DIA Plasma Proteomics Pipeline Finds Body Mass Index-associated Increases in Inflammatory Pathways

Bennike, T. B. (Lecturer), Yue Xuan (Other), Vibeke Andersen (Lecturer), Frederik Trier Møller (Lecturer), Stensballe, A. (Lecturer), Hanno Steen (Lecturer)

Activity: Talks and presentationsConference presentations

Description

Background: Plasma is the most widely-used body fluid for the discovery of biomarkers. Despite its well defined composition, large numbers of samples have to be analyzed to identify meaningful biomarker candidates. To address this need, we developed a high-throughput plasma proteomics pipeline using 96-well plates, DIA and capillary-flow LC that allows for the complete processing and analysis of 96 samples within one work week using one mass spectrometer. Methods: Plasma samples from 62 patients were individually trypsinized and desalted using 96-well PVDF membrane and C18 plates. For the spectral library generation, plasma from 62 participants was pooled and trypsinized with and without i) prior depletion of the Top14 abundant proteins and ii) subsequent high-pH fractionation. The different digests were analyzed on a Q Exactive MS using either DDA or DIA with a capillary-flow LC. The data was analyzed with MaxQuant and Spectronaut. Results: For evaluating the performance of our DIA plasma proteomics pipeline, we analyzed a pooled plasma sample in triplicates, identifying on average 467±2 proteins with 82.5% overlap, i.e. twice the number of proteins identified using comparable DDA workflows. Using <1 µl of plasma, and <1 hour of instrument time, our high-throughput plasma proteome maps cover >5 orders of magnitude dynamic range. We next analyzed 62 plasma samples identifying in total 664 proteins, and on average 433±36.5 plasma proteins/sample. Detecting the expected sex-dependent changes in the plasma proteomes validated our pipeline. Correlating BMIs of the patients with changes in the plasma proteomes identified 18 (23) (anti )correlating proteins. Intriguingly, the list of positively correlating proteins was enriched in inflammatory proteins, demonstrating an association between inflammatory processes and obesity. Conclusion: Our plasma proteomics pipeline is robust, easily automatable, and applicable to small (e.g. fingerstick) plasma sample volumes. Using the pipeline, we demonstrate an association between increased BMI and inflammatory proteins.
Period19 Sep 2017
Held atHuman Proteome Organisation World Congress (HUPO) 2017
Event typeConference
LocationDublin, Ireland
Degree of RecognitionInternational