Multiplex Immuno-MALDI-TOF MS for Targeted Quantification of

Feb 8, 2018 - ... method comparison between immuno-MALDI MS and reference methods using Bland Altman tests; mass spectra of SAA proteoforms; relative ...
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Multiplex Immuno-MALDI-TOF MS for Targeted Quantification of Protein Biomarkers and Their Proteoforms Related to Inflammation and Renal Dysfunction Jie Gao, Klaus Meyer, Katrin Borucki, and Per Magne Ueland Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04975 • Publication Date (Web): 08 Feb 2018 Downloaded from http://pubs.acs.org on February 10, 2018

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Analytical Chemistry

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Multiplex Immuno-MALDI-TOF MS for Targeted

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Quantification of Protein Biomarkers and Their

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Proteoforms Related to Inflammation and Renal

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Dysfunction

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Jie Gao,† Klaus Meyer,‡ Katrin Borucki,§, and Per Magne Ueland†,∏

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Department of Clinical Science, University of Bergen, and ∏Laboratory of Clinical

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Biochemistry, Haukeland University Hospital, 5021 Bergen, Norway

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Bevital AS, Jonas Lies veg 87, Laboratory building, 9th floor, 5021 Bergen, Norway

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Institute for Clinical Chemistry and Pathobiochemistry, Leipziger Strasse 44

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Otto-von-Guericke University Magdeburg, 39120 Magdeburg, Germany

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ABSTRACT

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Circulating proteins are widely used as biomarkers in clinical applications for the diagnosis,

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prediction and treatment of numerous diseases. Immunoassays are the most common

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technologies for quantification of protein biomarkers and exist in various formats. Traditional

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immunoassays offer sensitive and fast analyses, but cannot differentiate between proteoforms.

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Protein micro-heterogeneity, mainly due to post-translational modification, has been recognized

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as fingerprint for different pathologies, and knowledge about proteoforms is an important step

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towards personalized medicine. Mass spectrometry (MS) has emerged to be a powerful technique

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for the characterization and quantification of proteoforms. We have established a novel four-plex

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immunoassay based on Matrix-assisted Laser Desorption/Ionization Time-Of-Flight (MALDI-

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TOF) MS for the targeted quantification of the inflammatory markers C-reactive protein (CRP),

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serum amyloid A (SAA) and calprotectin (S100A8/9), and the kidney function marker cystatin C

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(CysC). Antibodies were covalently bound to super-paramagnetic beads, which delivered robust

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and fast sample processing. Polyhistidine-tagged recombinant target proteins were used as

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internal standards for quantification. Our method identified a number of proteoforms for SAA

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(n=11), S100A8/9 (n=4) and CysC (n=4). The assay was characterized by low limits of detection

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(0.007 - 0.172 µg/mL) and low coefficients of variation (3.8 - 9.4%). Method validation

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demonstrated good between-assay agreement with immuno-turbidimetry (R2 = 0.963 for CRP),

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ELISA (R2 = 0.958 for SAA; R2 = 0.913 for S100A8/9), and nephelometry (R2 = 0.963 for CysC).

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The low sample consumption of 20 µl and the high sample throughput of 384 samples per day

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make this targeted immuno-MALDI approach suited for assessment of inflammatory and renal

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status in large cohort studies based on precious biobanks samples.

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Analytical Chemistry

INTRODUCTION

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Protein biomarkers have attracted increasing attention during the last years for the diagnosis,

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risk assessment, and therapy of diseases.1, 2 Micro-heterogeneity increases the diversity of protein

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biomarkers, as mutations, alternative splicing or post-translational modifications (PTMs) result in

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proteoforms, which can play different roles in biological processes and may vary between

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pathologies and individuals.3, 4 Knowledge about protein heterogeneity is a key to personalized

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diagnostics and treatment of disease. Thus, there is increasing demand for quantitative techniques

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for investigation of biomarker diversity. Discrimination of proteoforms by traditional

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immunological techniques such as enzyme-linked immunosorbent assay (ELISA) or

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radioimmunoassay (RIA) is difficult or impossible.5, 6 They either capture the wild type form

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only or the antibody cannot discriminate between the proteoforms.

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Mass spectrometry (MS) allows determination of the molecular mass, differentiation between

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proteoforms, and multiplexing of biomarkers, which are advantages when compared to traditional

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immunoassay. Quantification of peptides and proteins by MS is carried out as bottom-up or top-

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down approaches.7, 8 Bottom-up methods identify the proteins indirectly using their constituent

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peptide fragments, whereas top-down assays detect the intact protein and are superior methods

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for discrimination of structurally related proteoforms. Matrix-assisted Desorption/Ionization

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Time-of-Flight (MALDI-TOF) MS is known to be a sensitive and rapid method for the detection

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of large biomolecules.9, 10 When combined with immuno-affinity capture, MALDI-TOF MS has

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been proven as a powerful tool for the targeted quantification of intact proteins.6,

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Combination of immuno-affinity with MALDI MS has to overcome two challenges, i.e. design of

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a robust and compatible assay format for protein capture, and application of intact proteins as

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internal standards (ISs). During the last decade different formats have been evaluated, which are

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based on chips13, 14, pipetting tips12, 15 and magnetic beads (MBs)16-18. Especially, the so-called 3 ACS Paragon Plus Environment

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mass spectrometric immunoassay (MSIA) has been applied to various protein biomarkers and has

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recently become commercially available.19 Uniformly-isotope-labelled proteins, modified

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recombinant and endogenous proteins have been successfully used as ISs in quantitative

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analyses.11, 12, 20, 21

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Chronic low-grade inflammatory processes have been related to many common diseases

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including arthrosclerosis, diabetes, obesity, rheumatic disorders and cancer.22-26 Many biomarkers

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of inflammation have been identified. Due to the complexity of inflammatory and immune

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responses, a combination of multiple markers may perform better in terms of disease prediction,

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diagnosis or prognosis than a single marker.

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C-reactive protein (CRP) belongs to the pentraxin family of proteins, which is characterized by

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calcium-dependent assembly of five monomers forming a radial symmetric ring.27 While the

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pentameric ring represents the native form in serum and plasma, dissociation results in

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monomeric CRP (mCRP), which is mostly found in tissues28. CRP is produced in hepatocytes,

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mainly under the transcriptional control of cytokines, IL-6 and IL-1. CRP is a major acute-phase

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reactant and the most important marker for the diagnosis of systemic inflammation in clinical

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practice. During an acute immune response levels can increase more than 1000-fold and peak

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after about 48 hours. Low levels of the so-called high-sensitivity (hs-) CRP below 10 µg/mL are

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typically found in the general population. Chronically elevated levels within this range have been

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associated with higher risks of different pathologies, including cardiovascular diseases (CVD),

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stroke, metabolic syndrome, and cancer.29-31

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Serum amyloid A (SAA) is another key acute-phase protein and is coded by four different

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genes. SAA1 and SAA2 encode for the acute-phase proteins, while SAA3 is an apparent

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pseudogene, and SAA4 is constitutively expressed32, 33. Various single nucleotide polymorphisms

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have been described for SAA1 and SAA2, and their protein products undergo posttranslational 4 ACS Paragon Plus Environment

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Analytical Chemistry

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truncation, which generate a large number of proteoforms34. SAA production occurs in the liver,

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and is driven by IL-6, IL-1 and TNF-α. During acute inflammation SAA is secreted into the

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circulation where concentrations could increase more than 1000-fold compared to normal values

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of 0.997. Non-linear standard curves have been described earlier for a similar MALDI

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assay12 and may be related to differences in immuno-affinity enrichment or MALDI MS

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detection between the target protein and the IS. 13 ACS Paragon Plus Environment

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Assay Performance. Assay precisions for the markers were evaluated in terms of within- and

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between-day coefficients of variations (CVs, Table 1). Within-day precisions were high and

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comparable for all 4 markers, CV ranging from 3.8% to 7.5%. Between-day CVs for CRP, total

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SAA (tSAA) and total S100A8/9 (tS100A8/9) varied from 7.5% to 9.4%. Between-day CVs of

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total CysC (tCysC) were similar to within-day CVs and ranged from 3.9% to 5.1%.

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Measurement of the four protein biomarkers was sensitive with LODs and LOQs of 0.06

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µg/mL and 0.17 µg/mL for CRP, 0.04 µg/mL and 0.12 µg/mL for tSAA, 0.02 µg/mL and 0.07

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µg/mL for tS100A8/9, and 0.01 µg/mL and 0.02 µg/mL for tCysC, respectively.

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Compared to other MSIAs established for CRP, cystatin C and SAA, the precision of the

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present assay was similar or better. In general, assay precision of different MSIAs is not related

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to whether recombinant target proteins or exogenous proteins were used as ISs.

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precision compared to our assay has been reported for a method based on addition of IS to the

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sample after enrichment

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during sample treatment. Detection sensitivity of the method was in the low pmol range and

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similar to most MSIAs. Only an approach for quantification of B-type natriuretic peptide

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demonstrated lower LODs down to the fmol range.18

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11, 12, 73, 74

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, which underlines the importance of an IS to correct for variations

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Biomarker stability. Protein degradation or denaturation during sample storage and freeze-

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thaw cycles are crucial for immunoassays. While partial degradation may create artefacts

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including generation of proteoforms that do not exist in vivo, denaturation can alter antigen-

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antibody interaction by changing the three-dimensional integrity of the protein. The stabilities of

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CRP and cystatin C during sample handling and storage have been evaluated in several studies,

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demonstrating that both proteins in general tolerate several freeze-thaw cycles, and short and

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long-term storage between +20°C and -80°C76-79. Long-term stability data for SAA and

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S100A8/9 do not exist. While short-term stability data for SAA are not consistent, S100A8/9 has

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been proven to be stable at +8°C for one week and -20°C for 6 month80-83. As long as adequate

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details on stability are not available for these two proteins, sample storage at -80°C should be

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mandatory.

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Method Comparison. Comparison of our immuno-MALDI MS assay with established

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techniques showed good between-assay agreement (Figure 3). Signal saturation did not occur for

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any of the markers within the working ranges, indicating that about 50 µg of antibody per mg of

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beads84 provided sufficient binding capacity for this four-plex assay.

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Good between-assay agreement (R2 = 0.963) was achieved for CRP, covering a wide

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concentration range of from 0.1 to 100 µg/mL (Figure 3). The slope (95% CI) obtained by

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Passing-Bablok regression was not different from 1 (0.99, 1.12), while the intercept showed a

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small, but significant deviation (95% CI) of 0.48 µg/mL (-0.72, -0.26) from 0. Bland-Altman plot

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confirmed the good between-method agreement by a small average deviation of 2% (Supporting

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Information Figure S-2).

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Validation of SAA was limited to 25 reference samples of tSAA values below 12 µg/mL,

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because most samples exceeded the analytical range of ELISA. Passing-Bablok comparison

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demonstrated good linearity (R2 = 0.958), but significant deviations of slope and intercept from 1

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(95% CI: (0.75, 0.97)) and 0 (95% CI: (-1.46, -0.86)), respectively (Figure 3). The Bland-Altman

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plot illustrated the divergence showing higher levels by ELISA than MALDI MS at low tSAA

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concentrations (Supporting Information Figure S-2).

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Total S100A8/9 levels of the reference plasma covered a range from 0.6 to about 13 µg/mL

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(Figure 3). When comparing with results based on ELISA assay, we observed good between-

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assay agreement, but it dropped from R2 = 0.941 to 0.913 after correction for interference with

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des-S CysC-OH (data not shown). Slope of the regression line did not differ significantly from 1

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(95% CI: (0.99, 1.16)), but intercept showed a significant bias of 2.03 µg/mL (95% CI: (1.70,

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2.28)) from 0. Deviation between the methods decreased with increasing concentration

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(Supporting Information Figure S-2). Divergence of S100A8/9 levels between immunological

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assays has been reported earlier80, 85 and with increasing usage of serum/plasma calprotectin in

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clinical studies, introduction of certified reference material is crucial for assay harmonization.

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However, as long as there is no consensus about the exact stoichiometry of the S100A8/9 hetero-

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complex, immunoassays may differ by capturing uneven portions of different hetero-complexes.

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Validation of tCysC, covering plasma levels from 0.63 to 5.58 µg/mL, delivered good linearity

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(R2 = 0.963) and agreement between immuno-MALDI MS and nephelometry (Figure 3). While

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the slope did not differ significantly from 1 (95% CI: (0.94, 1.06)), the intercept showed a minor,

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but significant deviation from 0 (95% CI: (0.02, 0.15)). The average deviation (about 7%) and the

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limit of agreement (23%) between the two methods were low (Supporting Information Figure S-

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2).

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Quantification of Proteoforms. All proteoforms observed in this work have been described

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earlier by different MS approaches (Supporting Information Table S-1). CRP was detected as

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mCRP only, most probably derived from dissociation of the native pentameric form during

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sample preparation. The pro-inflammatory mCRP has been described exclusively in tissues28, and

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it is unlikely that mCRP generated in vivo contributed substantially to the levels measured in

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serum/plasma. Application of a monoclonal antibody against mCRP could clarify its site of

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origin.86

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SAA demonstrated large micro-heterogeneity depending on the expressed genes and

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truncations (Supporting Information Figure S-3). SAA1 and SAA2 exist as 5 and 2 allelic

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variants, respectively, which in combination with 2 N-terminal posttranslational truncations, des16 ACS Paragon Plus Environment

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Analytical Chemistry

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R and des-RS, can be expressed as 21 different proteoforms (Supporting Information Table S-1).

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However, several of the proteoforms had very low abundances and/or overlapped in the mass

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spectra, limiting the number of detectable proteoforms to 11. SAA1 represented the most

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prominent proteoforms in the 80 reference samples with a relative abundance of 71% (Supporting

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Information Figure S-4), while SAA2.1 accounted for 21 % only. SAA1.3 and 2.2 were difficult

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to disentangle by automated peak identification in many samples. Therefore, these proteoforms

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were analyzed together and contributed in average 8% to tSAA. Visual inspection of the mass

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signals revealed that SAA1.3 and 2.2 contributed equally to the combined ion signal.

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Furthermore, the des-R truncations of both isoforms overlapped with the des-RS SAA1.2. The

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relative proportion of SAA truncations varied strongly between individuals with CVs between 27%

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and 41% (Supporting Information Figure S-5). Shorter truncations as described by Trenchevska

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et al 74 were not detected in our analyses.

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The hetero-complexes of S100A8/9 were detectable by its S100A8 and S100A9 monomers

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with relative abundance of 74% and 26%, respectively, and consisted of four different

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proteoforms (Supporting Information Table S-1). Intact complexes of S100A8/9, as described by

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Vogl et al,49 were not detected by our method. We assume that the majority of the monomers

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originated from dissociated hetero-complexes, since the amount of circulating monomers has

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been reported to be minor.87 However, the three times higher fraction of S100A8 compared to

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S100A9 was not consistent with any described structure of S100A8/9 hetero-complexes. Between

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individuals the proportions of the proteoforms varied with CVs from 6% (S100A8) to 48% (des-

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M S100A9) (Supporting Information Figure S-5).

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CysC consisted of five proteoforms (Supporting Information Table S-1) and the obtained

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relative amounts were consistent with earlier findings12. Hydroxylated and native CysC

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represented the most abundant proteoforms contributing to tCysC with in average 40% and 35%, 17 ACS Paragon Plus Environment

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respectively (Supporting Information Figure S-5). Variation of the relative abundances of

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proteoform among individuals was very low for the non-truncated forms with a CV of 5%, while

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highest variation was observed for des-SSP CysC with a CV of 26%.

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Analytical Chemistry

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CONCLUSION

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This study has described a four-plex immuno-MALDI approach for the targeted quantification of

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three inflammatory markers, CRP, SAA, and S100A8/9, and the functional marker of kidney

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function, CysC. The method allowed sensitive and precise quantification of all four markers, and

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comparison with established immunoassays demonstrated high agreement for CRP, SAA, and

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CysC. Lack of certified materials for S100A8/9 allowed relative comparison only, and underlined

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the urgent demand for harmonization of calprotectin immunoassays. Our method delivered

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detailed insights into the biomarkers diversities by identifying up to 20 proteoforms per sample,

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and especially SAA demonstrated large heterogeneity between individuals. Various immuno-MS

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approaches have been established for targeted protein quantification. Most of these methods are

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bottom-up approaches and are based on the positive identification of selected peptides often by

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Multiple Reaction Monitoring (MRM) mass spectrometry. With the introduction of Stable

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Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) and immuno-MALDI

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(iMALDI) assays, sensitivities of bottom-up techniques improved dramatically with LODs down

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to the attomol range.

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covers modifications of the entire protein sequence and is less-labour intense, which allows fast

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investigation of structurally similar proteoforms of multiple biomarkers. Among diverse immuno-

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affinity formats applied in MS, functionalized super-paramagnetic beads have become very

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popular because of their high versatility and easy workflow17, 91, 92. However, the application of

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super-paramagnetic beads in top-down approaches is still rare. In this work we have evaluated

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commercially available beads, which delivered robust antibody immobilization, low unspecific

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binding, and high assay capacity. The high-throughput and the low sample consumption make

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this method well suited for assessment of inflammation and renal status in large cohort studies.

88-90

In contrast, direct protein detection by immuno-MALDI-TOF MS

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The assay is currently used for screening of different biobanks to obtain levels of biomarkers and

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with-subject reproducibility measures in various healthy and clinical cohorts.

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Analytical Chemistry

404 405 406 407 408 Table 1. Within- and Between-day Variation of Three Different Reference Samples CRP tSAA tS100A8/9 concn CV concn CV concn CV (µg/mL) (%) (µg/mL) (%) (µg/mL) (%) within-day variationa 5.6 4.9 12.6 4.9 1.7 3.8 2.2 4.4 5.3 4.8 1.0 5.0 0.7 4.0 1.7 4.5 0.6 7.5 between-day variationb 5.6 7.5 12.6 8.6 1.7 8.6 2.2 8.2 5.3 9.0 1.0 8.4 0.7 9.4 1.7 8.4 0.6 8.7

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a

N=16

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b

N=3 x 10d

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tCysC concn CV (µg/mL) (%) 1.2 1.0 0.9

3.9 5.0 4.3

1.2 1.0 0.9

5.1 3.9 4.1

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ASSOCIATED CONTENT

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Supporting information. The Supporting Information is available free of charge on the ACS

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Publications website.

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One table with sequences and molecular weights of investigated proteoforms and internal

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standards; five figures showing standard curves for quantification of CRP, tSAA, tS100A8/9 and

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tCysC, method comparison between immuno-MALDI MS and reference methods using Bland

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Altman tests, mass spectra of SAA proteoforms, relative abundances of SAA proteoforms in 80

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human plasma samples, and variability of SAA, S100A8/9 and CysC proteoforms among 80

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human plasma samples.

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AUTHOR INFORMATION

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Corresponding author

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*E-mail: [email protected]

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ORCID

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Jie Gao:

0000-0002-8477-5318

437

Klaus Meyer:

0000-0002-2145-7777

438

Katrin Borucki:

0000-0003-3648-2657

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Per Magne Ueland:

0000-0002-1903-0571

440

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Notes

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The authors declare no competing financial interest.

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Analytical Chemistry

References (1) Anderson, N. L. Clin Chem 2010, 56, 177-185. (2) Boschetti, E.; D'Amato, A.; Candiano, G.; Righetti, P. G. J Proteomics 2017, 17, 3028530293. (3) Nedelkov, D.; Kiernan, U. A.; Niederkofler, E. E.; Tubbs, K. A.; Nelson, R. W. Proc Natl Acad Sci U S A 2005, 102, 10852-10857. (4) Walsh, G.; Jefferis, R. Nat Biotechnol 2006, 24, 1241-1252. (5) Nelson, R. W.; Krone, J. R.; Bieber, A. L.; Williams, P. Anal Chem 1995, 67, 1153-1158. (6) Kiernan, U. A.; Phillips, D. A.; Trenchevska, O.; Nedelkov, D. PloS one 2011, 6, e17282. (7) Kelleher, N. L.; Lin, H. Y.; Valaskovic, G. A.; Aaserud, D. J.; Fridriksson, E. K.; McLafferty, F. W. J Am Chem Soc 1999, 121, 806-812. (8) Chait, B. T. Science 2006, 314, 65-66. (9) Kaufmann, R. J Biotechnol 1995, 41, 155-175. (10) Cho, Y. T.; Su, H.; Wu, W. J.; Wu, D. C.; Hou, M. F.; Kuo, C. H.; Shiea, J. Adv Clin Chem 2015, 69, 209-254. (11) Trenchevska, O.; Nedelkov, D. Proteome Sci 2011, 9, 19-26. (12) Meyer, K.; Ueland, P. M. Anal Chem 2014, 86, 5807-5814. (13) Patrie, S. M.; Mrksich, M. Anal Chem 2007, 79, 5878-5887. (14) Kim, Y. E.; Yi, S. Y.; Lee, C. S.; Jung, Y.; Chung, B. H. Analyst 2012, 137, 386-392. (15) Kiernan, U. A.; Tubbs, K. A.; Gruber, K.; Nedelkov, D.; Niederkofler, E. E.; Williams, P.; Nelson, R. W. Anal Biochem 2002, 301, 49-56. (16) Chou, P.-H.; Chen, S.-H.; Liao, H.-K.; Lin, P.-C.; Her, G.-R.; Lai, A. C.-Y.; Chen, J.-H.; Lin, C.-C.; Chen, Y.-J. Anal Chem 2005, 77, 5990-5997. (17) Sparbier, K.; Wenzel, T.; Dihazi, H.; Blaschke, S.; Muller, G. A.; Deelder, A.; Flad, T.; Kostrzewa, M. Proteomics 2009, 9, 1442-1450. (18) Suzuki, T.; Israr, M. Z.; Heaney, L. M.; Takaoka, M.; Squire, I. B.; Ng, L. L. Clin Chem 2017, 63, 880-886. (19) Krastins, B.; Prakash, A.; Sarracino, D. A.; Nedelkov, D.; Niederkofler, E. E.; Kiernan, U. A.; Nelson, R.; Vogelsang, M. S.; Vadali, G.; Garces, A.; Sutton, J. N.; Peterman, S.; Byram, G.; Darbouret, B.; Perusse, J. R.; Seidah, N. G.; Coulombe, B.; Gobom, J.; Portelius, E.; Pannee, J.; Blennow, K.; Kulasingam, V.; Couchman, L.; Moniz, C.; Lopez, M. F. Clin Biochem 2013, 46, 399-410. (20) Tubbs, K. A.; Nedelkov, D.; Nelson, R. W. Anal Biochem 2001, 289, 26-35. (21) Brun, V.; Dupuis, A.; Adrait, A.; Marcellin, M.; Thomas, D.; Court, M.; Vandenesch, F.; Garin, J. Mol Cell Proteomics 2007, 6, 2139-2149. (22) Wellen, K. E.; Hotamisligil, G. S. J Clin Invest 2005, 115, 1111-1119. (23) Grivennikov, S. I.; Greten, F. R.; Karin, M. Cell 2010, 140, 883-899. (24) Fernandez-Sanchez, A.; Madrigal-Santillan, E.; Bautista, M.; Esquivel-Soto, J.; MoralesGonzalez, A.; Esquivel-Chirino, C.; Durante-Montiel, I.; Sanchez-Rivera, G.; Valadez-Vega, C.; Morales-Gonzalez, J. A. Int J Mol Sci 2011, 12, 3117-3132. (25) Franks, A. L.; Slansky, J. E. Anticancer Res 2012, 32, 1119-1136. (26) Guarner, V.; Rubio-Ruiz, M. E. Interdiscip Top Gerontol 2015, 40, 99-106. (27) Pepys, M. B.; Hirschfield, G. M. J Clin Invest 2003, 111, 1805-1812. (28) Eisenhardt, S. U.; Thiele, J. R.; Bannasch, H.; Stark, G. B.; Peter, K. Cell Cycle 2009, 8, 3885-3892. (29) Ridker, P. M.; Buring, J. E.; Cook, N. R.; Rifai, N. Circulation 2003, 107, 391-397. 23 ACS Paragon Plus Environment

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(60) Koc, M.; Batur, M. K.; Karaarslan, O.; Abali, G. Cardiol J 2010, 17, 374-380. (61) Angelidis, C.; Deftereos, S.; Giannopoulos, G.; Anatoliotakis, N.; Bouras, G.; Hatzis, G.; Panagopoulou, V.; Pyrgakis, V.; Cleman, M. W. Curr Top Med Chem 2013, 13, 164-179. (62) Wilson, M. E.; Boumaza, I.; Lacomis, D.; Bowser, R. PLoS One 2010, 5, e15133. (63) Mathews, P. M.; Levy, E. Ageing Res Rev 2016, 32, 38-50. (64) Trenchevska, O.; Nedelkov, D. Proteome Sci 2011, 9, (65) Nedelkov, D.; Shainag, S.; Trenchevska, O.; Aleksovski, V.; Mitrevski, A.; Stojanoski, K. Open Proteomics J 2008, 1, 54-58. (66) Yassine, H. N.; Trenchevska, O.; Dong, Z.; Bashawri, Y.; Koska, J.; Reaven, P. D.; Nelson, R. W.; Nedelkov, D. Proteome Sci 2016, 14, 7-15. (67) Trenchevska, O.; Koska, J.; Sinari, S.; Yassine, H.; Reaven, P. D.; Billheimer, D. D.; Nelson, R. W.; Nedelkov, D. Clinical Mass Spectrometry 2016, 1, 27-31. (68) Wenzel T1, S. K., Mieruch T, Kostrzewa M. Rapid Commun Mass Spectrom 2006, 20, 785793. (69) International Conference on Harmonization (ICH) of Technical Requirements for the Registration of Pharmaceuticals for Human Use, Validation of analytical procedures: Text and Methodology 1996, Geneva, (70) Passing, H.; Bablok J Clin Chem Clin Biochem 1983, 21, 709-720. (71) Bland, J. M.; Altman, D. G. Lancet 1986, 1, 307-310. (72) http://www.acomed-statistik.de/, (73) Kiernan, U. A.; Addobbati, R.; Nedelkov, D.; Nelson, R. W. J Proteome Res 2006, 5, 16821687. (74) Trenchevska, O.; Yassine, H. N.; Borges, C. R.; Nelson, R. W.; Nedelkov, D. Biomarkers 2016, 1-9. (75) Wang, K.-Y.; Chuang, S.-A.; Lin, P.-C.; Huang, L.-S.; Chen, S.-H.; Ouarda, S.; Pan, W.-H.; Lee, P.-Y.; Lin, C.-C.; Chen, Y.-J. Anal Chem 2008, 80, 6159-6167. (76) Aziz, N.; Fahey, J. L.; Detels, R.; Butch, A. W. Clin Diagn Lab Immunol 2003, 10, 652-657. (77) Erlandsen, E. J.; Randers, E.; Kristensen, J. H. Scand J Clin Lab Invest 1999, 59, 1-8. (78) Gislefoss, R. E.; Grimsrud, T. K.; Morkrid, L. Clin Chem Lab Med 2009, 47, 596-603. (79) Doumatey, A. P.; Zhou, J.; Adeyemo, A.; Rotimi, C. Clin Biochem 2014, 47, 315-318. (80) Biovendor Biovendor Product Brochure 2014, (81) Hillstrom, A.; Tvedten, H.; Lilliehook, I. Acta Vet Scand 2010, 52, 8. (82) Ton, H.; Brandsnes; Dale, S.; Holtlund, J.; Skuibina, E.; Schjonsby, H.; Johne, B. Clin Chim Acta 2000, 292, 41-54. (83) Tothova, C.; Nagy, O.; Seidel, H.; Kovac, G. Vet Med Int 2012, 2012, 861458. (84) Thermoscientific User Guide: Pierce NHS-Activated Magnetic Beads 2013, (85) Nilsen, T.; Sunde, K.; Larsson, A. J. Inflamm. 2015, 12, 1-8. (86) Schwedler, S. B.; Amann, K.; Wernicke, K.; Krebs, A.; Nauck, M.; Wanner, C.; Potempa, L. A.; Galle, J. Circulation 2005, 112, 1016-1023. (87) Yasar, O.; Akcay, T.; Obek, C.; Turegun, F. A. Scand J Clin Lab Invest 2017, 77, 437-441. (88) Weiss, F.; van den Berg, B. H.; Planatscher, H.; Pynn, C. J.; Joos, T. O.; Poetz, O. Biochim Biophys Acta 2013, 927-932. (89) Anderson, N. L.; Anderson, N. G.; Haines, L. R.; Hardie, D. B.; Olafson, R. W.; Pearson, T. W. J Proteome Res 2004, 3, 235-244. (90) Jiang, J.; Parker, C. E.; Hoadley, K. A.; Perou, C. M.; Boysen, G.; Borchers, C. H. Proteomics Clin Appl 2007, 1, 1651-1659. 25 ACS Paragon Plus Environment

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Analytical Chemistry

589

Figure legends

590

Figure 1. Description of the immuno-MALDI-TOF MS assay. The method consists of four

591

steps starting with preparation of magnetic beads, followed by protein enrichment, protein elution

592

and finally quantification by MALDI MS. The fundamental reactions (A) and the work flow (B)

593

are illustrated for each step. First, antibodies were linked to superparamagnetic beads by covalent

594

conjugation of the antibody’s primary amines with N-hydroxysuccinimide (NHS)-esters of the

595

functionalized beads. Linking was performed separately for each antibody, which had been

596

diluted to equal concentrations of 0.5 µg/ml. Beads were mixed in equal amounts prior sample

597

purification. 20 µl of each serum/plasma sample was spiked with 20 µl internal standard (IS) and

598

was incubated with 10 µl of beads for 1h, processed in 96-microtiter plates. After protein

599

enrichment, beads were washed 2 times both with Tris-buffered saline (TBS) and ultrapure water

600

using a 96-well magnet plate for separation of the beads from the liquids. Proteins were released

601

from the antibodies adding 9 µl of 0.1 M glycine solution. Beads were collected by the magnet

602

plate and the supernatant was transferred into a new microtiter plate. Finally, samples were mixed

603

intensely with 5 µl of 2,5-dihydroxyacetophenone (DHAP) matrix and 2 µl of the sample/matrix

604

solution was spotted onto an anchor target plate for quantification of the proteoforms by MALDI-

605

TOF MS.

606 607

Figure 2. Four-plex immuno-MALDI-TOF MS spectrum of a human plasma sample. Mass

608

spectra of the enriched proteoforms and internal standards were acquired in reflector ion mode

609

and ranged from 5 - 24 kDa. Signals were assigned to three different patterns at 5 - 8 kDa, 10 - 15

610

kDa and 22 - 24 kDa. Mass signals between 5 and 8 kDa were doubly charged proteoforms, while

611

the other patterns mainly consisted of singly charged proteoforms with exception of (CRP+2H)2+.

612

The mass pattern at 10 - 15 kDa was shown in detail (inset) and included all investigated 27 ACS Paragon Plus Environment

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613

proteoforms and internal standards (not all SAA truncations were labelled). Due to the mass

614

interference of (CRP+2H)2+ with the truncation des-R SAA1.1, proteoforms of SAA were

615

analyzed by their doubly charged signals (5.6 - 5.8 kDa), while CRP was quantified by its singly

616

charged species (22 - 24 kDa). Since the signal-to-noise ratio of (CRP+H)+ was 4x higher in

617

linear mode (inset), samples were prepared twice and analyzed in both ion modes to achieve

618

optimal signal quality with respect to resolution and sensitivity.

619 620

Figure 3. Method comparison between immuno-MALDI-TOF MS and reference techniques

621

using Passing-Bablok regression. Comparison demonstrated linear relationships for all markers

622

with R2 ranging from 0.963 to 0.913. Best between-assay agreements were obtained for CRP and

623

CysC. Significant difference of the slope from one was obtained for SAA. Significant deviation

624

of the intercept from zero was observed for all markers and was highest for S100A8/9 and SAA.

625

Analyses of SAA were limited to 25 of the 80 reference samples due to saturation of ELISA for

626

values > 12 µg/mL.

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Analytical Chemistry

29 ACS Paragon Plus Environment

1. Beads preparation

2. Protein enrichment

Analytical Chemistry

4. Quantification

3. Protein elution

Protein Internal 1 standard + 2 3 4 B. Work flow 5 6 4-plex mixture 2 cycles 2 cycles 7 10µl 8 anti-CRP anti-SAA anti-S100A8/9 anti-CysC 9 10 11 ACS Paragon Plus Environment 12 Spiked Incubation Washing Washing Elution with Antibodies linked to NHS-activated magnetic beads sample (40µl) for 1h with TBS with water 9µl glycine 13 14

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Intensity

A. Reactions

+ +

O

O

N

H2N

H2N

O

O

NH2

NH2

NH

NH

O

O

NH

O

m/z

+ +

2µl

_++ 5µl matrix (2,5-DHAP) MALDI-TOF MS

1/2

t~m

S100A8/9-His

SAA1.1

Page 31 of 32 Analytical Chemistry CRP2+

des-R SAA1.1

CysC-OH

SAA2.1

CysC

CRP-His2+

S100A8

1 2 3 4 5 6 7 8 9 10 11

des-S CysC

des-R SAA2.1

CysC-His

des-M S100A9-O2

4

x10

des-MTCKM S100A9

SAA1.12+ /SAA2.12+

2.0

Relative intensity (a.u.)

des-S CysC-OH S100A9-O2

des-SSP CysC

SAA-His

1.5

11000

12000

13000

1.0

14000

CRP CRP-His

ACS Paragon Plus Environment

0.5

Linear mode

6000

8000

10000

12000

14000

16000

18000

20000

22000

m/z

15000 m/z

14

N = 80

80

1 60 2 40 3 20 4 0 0 5 6 20 7 18 16 8 14 9 12 10 10 8 11 64 12 2 13 0 0 14

Concentration immuno-MALDI MS (μg/ml)

Analytical Chemistry tSAA 12

CRP

Concentration immuno-MALDI MS (μg/ml)

100

R2 = 0.963 slope (95% CI): 1.052 (0.999, 1.119) intercept (95% CI): -0.4815 (-0.718, -0.256)

20

40

60

80

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R2 = 0.958 slope (95% CI): 0.887 (0.754, 0.967) intercept (95% CI): -1.259 (-1.458, -0.864)

10

N = 25

8 6 4 2 0

100

Concentration Turbidimetry (μg/ml)

0

2

4

6

8

10

Concentration ELISA (μg/ml)

12

7 tS100A8/9 N = 80

Concentration immuno-MALDI MS (μg/ml)

Concentration immuno-MALDI MS (μg/ml)

120

tCysC

6

N = 80

5 4 3 2

1 ACS Paragon Plus Environment

R2 = 0.913 slope (95% CI): 1.059 (0.991, 1.160) intercept (95% CI): 2.026 (1.703, 2.279)

2

4

6

8

10

Concentration ELISA (μg/ml)

12

0

R2 = 0.963 slope (95% CI): 0.996 (0.941, 1.059) intercept (95% CI): 0.078 (0.018, 0.154)

0

1

2

3

4

5

Concentration Nephelometry (μg/ml)