TY - JOUR
T1 - New Interface for Faster Proteoform Analysis
T2 - Immunoprecipitation Coupled with SampleStream-Mass Spectrometry
AU - Santos Seckler, Henrique Dos
AU - Park, Hae Min
AU - Lloyd-Jones, Cameron M.
AU - Melani, Rafael D.
AU - Camarillo, Jeannie M.
AU - Wilkins, John T.
AU - Compton, Philip D.
AU - Kelleher, Neil L.
N1 - Funding Information:
Work performed for this study was funded by the National Institutes of Health under grant UH3 CA246635-02 (N.L.K.), K23 HL133601-03 (J.T.W.), the American Heart Association, under grant SDG 27250022 (J.T.W.), and the National Institute of General Medical Sciences, under grant P41 GM108569 (N.L.K.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (HHSN268201800005I & HHSN268201800007I), Northwestern University (HHSN268201800003I), University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I). This manuscript has been reviewed by CARDIA for scientific content. The authors would like to thank Dr. Allan Sniderman and Dr. Donald Lloyd-Jones for reviews and comments that helped to further this article.
Publisher Copyright:
© 2021 American Chemical Society.
PY - 2021/7/7
Y1 - 2021/7/7
N2 - Different proteoform products of the same gene can exhibit differing associations with health and disease, and their patterns of modifications may offer more precise markers of phenotypic differences between individuals. However, currently employed protein-biomarker discovery and quantification tools, such as bottom-up proteomics and ELISAs, are mostly proteoform-unaware. Moreover, the current throughput for proteoform-level analyses by liquid chromatography mass spectrometry (LCMS) for quantitative top-down proteomics is incompatible with population-level biomarker surveys requiring robust, faster proteoform analysis. To this end, we developed immunoprecipitation coupled to SampleStream mass spectrometry (IP-SampleStream-MS) as a high-Throughput, automated technique for the targeted quantification of proteoforms. We applied IP-SampleStream-MS to serum samples of 25 individuals to assess the proteoform abundances of apolipoproteins A-I (ApoA-I) and C-III (ApoC-III). The results for ApoA-I were compared to those of LCMS for these individuals, with IP-SampleStream-MS showing a >7-fold higher throughput with >50% better analytical variation. Proteoform abundances measured by IP-SampleStream-MS correlated strongly to LCMS-based values (R2 = 0.6-0.9) and produced convergent proteoform-To-phenotype associations, namely, the abundance of canonical ApoA-I was associated with lower HDL-C (R = 0.5) and glycated ApoA-I with higher fasting glucose (R = 0.6). We also observed proteoform-To-phenotype associations for ApoC-III, 22 glycoproteoforms of which were characterized in this study. The abundance of ApoC-III modified by a single N-Acetyl hexosamine (HexNAc) was associated with indices of obesity, such as BMI, weight, and waist circumference (R ∼0.7). These data show IP-SampleStream-MS to be a robust, scalable workflow for high-Throughput associations of proteoforms to phenotypes.
AB - Different proteoform products of the same gene can exhibit differing associations with health and disease, and their patterns of modifications may offer more precise markers of phenotypic differences between individuals. However, currently employed protein-biomarker discovery and quantification tools, such as bottom-up proteomics and ELISAs, are mostly proteoform-unaware. Moreover, the current throughput for proteoform-level analyses by liquid chromatography mass spectrometry (LCMS) for quantitative top-down proteomics is incompatible with population-level biomarker surveys requiring robust, faster proteoform analysis. To this end, we developed immunoprecipitation coupled to SampleStream mass spectrometry (IP-SampleStream-MS) as a high-Throughput, automated technique for the targeted quantification of proteoforms. We applied IP-SampleStream-MS to serum samples of 25 individuals to assess the proteoform abundances of apolipoproteins A-I (ApoA-I) and C-III (ApoC-III). The results for ApoA-I were compared to those of LCMS for these individuals, with IP-SampleStream-MS showing a >7-fold higher throughput with >50% better analytical variation. Proteoform abundances measured by IP-SampleStream-MS correlated strongly to LCMS-based values (R2 = 0.6-0.9) and produced convergent proteoform-To-phenotype associations, namely, the abundance of canonical ApoA-I was associated with lower HDL-C (R = 0.5) and glycated ApoA-I with higher fasting glucose (R = 0.6). We also observed proteoform-To-phenotype associations for ApoC-III, 22 glycoproteoforms of which were characterized in this study. The abundance of ApoC-III modified by a single N-Acetyl hexosamine (HexNAc) was associated with indices of obesity, such as BMI, weight, and waist circumference (R ∼0.7). These data show IP-SampleStream-MS to be a robust, scalable workflow for high-Throughput associations of proteoforms to phenotypes.
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U2 - 10.1021/jasms.1c00026
DO - 10.1021/jasms.1c00026
M3 - Article
C2 - 34043341
AN - SCOPUS:85108414123
VL - 32
SP - 1659
EP - 1670
JO - Journal of the American Society for Mass Spectrometry
JF - Journal of the American Society for Mass Spectrometry
SN - 1044-0305
IS - 7
ER -
