Single Shot DIA Profiling of >1500 Plasma Proteomes of the Weight Loss and Maintenance Study DiOGenes Roland M. Bruderer1, Jan Muntel1, Sebastian Müller1, Oliver M. Bernhardt1, Tejas Gandhi1, Polina Mironova2, Ondine Walter2, Jérôme Carayol2, Arne Astrup3, Wim H.M. Saris4, Jörg Hager2, Armand Valsesia2, Loïc Dayon2, and Lukas Reiter1 1) Biognosys, Zurich-Schlieren, Switzerland 2) Nestlé Institute of Health Sciences, Lausanne, Switzerland 3) Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark 4) NUTRIM, School for Nutrition, Toxicology and Metabolism, Department of Human Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
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Results
INTRODUCTION
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Glycaton sites
Global proteins
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setup, we carried out a large-scale plasma sample study
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of the diet, obesity and genes (DiOGenes) project of the
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(A) A Waters M-Class UPLC was connected to a Thermo Scientific LUMOS mass spectrometer. For chromatography a 300um*15cm CSH C18 column 1.7um (Waters) was selected. (B) The identifications at different gradient lengths were calculated. A 40 min gradient at 5ul/min with 5ug sample was found to be an optimal balance between identifications (96% of the maximum identifications and an overhead of 13%). This method results in 32 DIA per day.
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optimized in-solution digestion protocol. Biognosys’ iRT kit and PlasmaDeepDive kit were spiked into the samples C
with Biognosys’ Spectronaut Pulsar.
resulting in a 45 min injection-to-injection cycle. Analysis of DIA runs was performed using Spectronaut Pulsar. The FDR was set to 1% on pepetide precursor and protein level.
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Study: 477 samples CID1 477 samples CID2 477 samples CID3 115 samples CID4 1,508 samples from the DiOGenes study were prepared in 17*96 well plates, using the optimized plasma sample preparation from Biognosys. This sample perparation included no depletion step. The samples were stemming from 4 clinical investigation days. (CID1 = base line, CID2 = 8-week weight loss, CID3 = after 6 months weight maintenance, CID4 = after 1 year weight maintenance). The identifications were at on average of 486 proteins.
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identification and quantification of over a thousand
during the weight maintenance period. The heavy
plasma samples. The high quantitative precision
isotope labeled reference peptides were detected
and reproducibility made the acquisition of technical
with hightreproducibility and enabled extrapolated
replicates unnecessary.
absolute quantification of almost 500 proteins
The setup was successfully used to analyze 1,576
Figure 6: Comparison to other large scale weight loss and maintenance studies x
proteins maintained an alternate expression pattern
spanning almost 6 orders of magnitude.
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The capillary flow LC-MS setup enabled robust
(A) Moreno and colleagues investigated the proteomic differences between between the CID1 and CID3 of the DiOGenes study using depletion and TMT isobaric labelling. A comparison of the significantly regulated proteins between the two studies revealed an overlap of 21 proteins (out of 32 dentified by Moreno and 64 from this study. The direction of fold change is conserved and correlated. (B) Geyer and colleagues analyzed samples from a different weight loss study of similar layout (8 weeks of weight- loss and monitored weight maintenance). They performed a label-free DDA approach using nanoflow LC-MS. Comparison of the differential abundant proteins (baseline to weigh-tloss) resulted in an overlap of 53 proteins. The direction of regulation was highly conserved, the fold change detected in the DiOGenes study was on average 80% higher for this study.
samples of the DiOGenes study. A single column was
Importantly, robust, reproducible detection of small
used to perform all the acquisitions. Cumulatively
changes of plasma proteins can be achieved in
590 proteins were identified.
large cohorts across different sample preparation
The strongest changes in the DiOGenes study
strategies (whole vs. depleted plasma), mass
were observed after the weight-loss period. The
spectrometric acquisition modes (label-free DIA vs
most effected pathways were lipid metabolism/
label-free DDA vs TMT labeling) and independent
transport and inflammation. Interestingly, multiple
weight loss and maintenance studies (Geyer et al.).
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REFERENCES
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Anderson, The Clinical Plasma Proteome: A Survey of Clinical Assays for Proteins in Plasma and Serum, 2010, Analytical chemistry Geyer et al., Proteomics reveals the effects of sustained weight loss on the human plasma proteome, 2016, Molecular Systems Biology Moreno et al. The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention, 2018, Proteomics Clin. Appl.
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CONTACT INFORMATION:
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Roland Bruderer, PhD Principal Scientist RnD
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Figure 7: Absolute quantification based on heavy labelled reference peptides anchors Using regression analysis for the label-free quantities of respective proteins and the known concentration of the reference peptides. The equation from the regression was used to extrapolate to the whole data set. The distribution of the absolute quantities for the whole data set was calculated. A box-plot visualization for the distributions of the extrapolated and the 63 directly determined quantities was performed. The absolute quantities span almost 6 orders of magnitude.
Biognosys AG Wagistrasse 21 8952 Schlieren Switzerland Phone +41 (0) 44 738 20 44
[email protected] www.biognosys.com
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(A) The identifications were monitored over time. At acquisition 402, cooling problems lead to unstable temperatures until acquisition 964. (B) The chromatographic retention time was monitored, highest fluctionation are visible during the period of unstable temperatures. 200 (C) Transformation of the retention time in dimension less space greatly reduced the chromatographic fluctuations. (D) Analysis of the 150 of identification of proteins in the curated data set (only reproducibiliy runs were included that contain more than 350 protein identifications). 100 were detected in 90% of all runs. The data set completeness 323 proteins was 74% on protein level. (E) Analysis of the variance of the of the whole 50 within the conditions. (F) Analysis of the variance within data set and individuals, that donated blood on all 4 CIDs. (G) Analysis of variance 0 inter individual was performed. (H) Partial least squares discriminant analysis was performed for the whole dataset. The weight loss timepoint was deviating most. The control pools (P1 and P2) showed reduced spread compared to the rest of the data set.
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CONCLUSIONS
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Figure 4: Exploratory view
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Sponaneous, non-enzymatic addition of suger (glucose) to proteins plays and important role in muliple processes in plasma, including the immune system. We generated a spectral library containing glycated peptides (dM +162Da) for 254 proteins from HPRP DDA plasma data, to our knowledge the largest data base for glycated proteins by proteomics. Targeted analysis of the DiOGenes data set resulted in the profiling of glycation sites of 180 proteins. (A) The global clustering of the conditions changed in the glycation analysis, as compared to the analysis of the whole proteins. (B) The last CID4 differs the most in the data set based on glycation analysis, whereas the weight-loss shows the strongest changes on global protein level.
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Figure 8: Glycation analysis
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(A) The weight loss timepoint (CID2) was compared to the baseline (CID1) using a paired two-sample Welch t-test and visualized using a Volcano plot. 117 proteins were detected to be significantly differential abundand. (B) Pathway enrichment analysis for the proteins which are significantly differential abundant between CID2 and CID1. Activated pathways are involved in the regulation of lipid and cholesterol metabolism, inflammation, coagulation and the immune system. (C) 28 proteins keep a consistently altered expression over the whole wight maintenance periode (CID3 and CID4). The expression profiles of six relevant plasma proteins are shown.
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Figure 5: Biological analysis
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Figure 2: DiOGenes study
DIA methods were acquired with a gradient of 40 min
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searched with MaxQuant. Spectral libraries were generated
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generation using UHPLC-HPRP factionated samples and
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setup was used consisting of a Waters M-class UPLC and
Scientific). DDA runs were performed for spectral library
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The samples were acquired on a Thermo Scientific Orbitrap Fusion Lumos mass spectrometer. A capillary-flow LC
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an EASY transfer line and an EASY spray source (Thermo
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METHODS
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Plasma deep dive Stable isotopes
Figure 1: Establishment of a capillary flow setup
before injection.
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a 300µm*150m Waters CSH 1.7µm column connected to
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months (CID4) (Fig 2).
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measuring 32 plasma proteomes per day (Fig. 1). Using this
and after weight maintenance of 6 months (CID3) and 12
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(A) A plasma pool sample was acquired in 10 reinjections on the finalized capillary flow DIA setup. The total identifications and the identifications 40 60 with coefficients of variation below 10% or 20% were calculated. (B) The reproducibility of protein identification was analyzed by counting the30 30 50 10 repeated identification of the individual proteins. (C) The identification and quantification of FDA approved biomarkers was analyzed. Of 52 identified 20 20 90 40 biomarkers (of totally 109, Anderson et al.), 48 were quantified with coefficients of variation below 20%. 10
a robust capillary-flow LC-MS-DIA setup capable of
(CIDs) at baseline (CID1), after 8-week weight loss (CID2)
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Figure 3: Capillary flow data-independent acquisition plasma proteomics
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To significantly reduce this limitation, we established
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requiring long gradient overheads.
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requirements. Up to now, in-depth analysis of the plasma
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plasma lacked the required statistical power to fulfill those
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confunding variables. Most previous proteomic studies of
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cohorts have to be measured. This enables to adjust for
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reproducible findings in plasma proteomics, large sample
European Union FP6. This measurement series contained
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analysis of the health state. To achieve robust and
proteome was achieved using delicate nano-flow setups
Density
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Comprehensive, robust, high-throughput analysis of the A plasma proteome has the potential to enable holistic
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