Global quantification of intact proteins via chemical isotope labeling

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Global quantification of intact proteins via chemical isotope labeling and mass spectrometry Zheyi Liu, Ruimin Wang, Jing Liu, Ruixiang Sun, and Fangjun Wang J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.9b00071 • Publication Date (Web): 16 Apr 2019 Downloaded from http://pubs.acs.org on April 16, 2019

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Journal of Proteome Research

Global quantification of intact proteins via chemical isotope labeling and mass spectrometry Zheyi Liu1,#, Ruimin Wang2,#, Jing Liu3, Ruixiang Sun2,*, Fangjun Wang1,* 1 CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China

2 Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China 3 College of Pharmacy, Dalian Medical University, Dalian, 116044, China # Contributed equally to this work. * Corresponding Authors (Email: [email protected] and [email protected]) Dedicated to the 70th anniversary of Dalian Institute of Chemical Physics, CAS Abstract Although thousands of intact proteins can be feasibly identified in recent years, global quantification of intact proteins is still challenging. Herein, we develop a high-throughput strategy for global intact protein quantification based on chemical isotope labeling. The isotope incorporation efficiency is as high as 99.2% for complex intact protein samples extracted from HeLa cells. Further, the pTop 2.0 software is developed for automated quantification of intact proteoforms in a high-throughput manner. The high quantification accuracy and reproducibility of this strategy have been demonstrated for both standard and complex cellular protein samples. A total of 2,283 intact proteoforms originated from 660 protein accessions are successfully quantified under anaerobic and aerobic conditions and the differentially expressed proteins are observed to be involved into the important biological processes such as stress response.

Keywords: Mass spectrometry, Chemical isotope labeling, Intact protein quantification, pTOP, Highest isotopic peak

1. Introduction The bottom-up proteomics based on proteolytic peptide characterization by liquid chromatography coupled with mass spectrometry (LC-MS/MS) has been greatly developed in the past 20 years1. However, full sequence coverage is hardly achieved for most of the proteins due to the fact that only part of the proteolytic peptides could be detected by this strategy2. 1

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Furthermore, important information such as mutations, splice variants, endogenous proteolytic cleavage and the combinatorial patterns of different types of post-translational modifications (PTMs) is easily lost during proteolytic digestion. Direct characterization of intact proteins by top-down proteomics strategy could avoid these disadvantages and give an ideal alternative to the bottom-up strategy. However, proteome-wide analysis of intact proteins is still challenging due to the poor chromatographic separation efficiency3 and difficulties in mass spectrometry characterization4-7. Recently, Tran et al. combined a three-dimensional separation system with MS for intact protein analysis, and over 1000 proteins could be identified8. Compared with qualitative analysis, quantitative proteomics is more often utilized in elucidating the mechanisms of biological processes9-12. However, global quantification of cellular intact proteins is still a big challenge until now. Stable isotope labeling by amino acids in cell culture (SILAC) has been widely utilized in bottom-up proteomics13-16. Intact proteins with molecular weights (MWs) between 10 to 200 kDa could also be quantified by SILAC strategy17 including NeuCode isotopic tagging, which has been applied to

the quantification

of yeast proteome18-20. However, the incorporation efficiency of the isotopic amino acid is about 95% in a typical SILAC labeling, which would influence the accuracy of heavy and light ion pairs determination in MS spectra17, 21, 22. Label-free quantification (LFQ) is another popular strategy in proteomic quantification23. Davis et al applied this strategy for intact protein quantification and 131 proteins with MWs 25 KDa) were feasibly quantified with reproducible quantification results (Figure 4C and S9), but the detail protein sequences were not matched due to the insufficient resolution of MS and poor fragmentation efficiency in MS2 sequencing (Figure S10). Finally, a total of 2283 intact proteoforms originated from 660 protein accessions were successfully quantified (Table S3), in which 639 proteoforms were quantified in both Group A and Group B. Then, a strict filter (PrSM count ≥ 5) was applied to further screen out the most confident quantification results and finally 290 proteoforms corresponding to 110 protein accessions passed this filter. As the oxidation of methionine is a well-known artificial modification during protein sample preparation and has an adverse influence on the quantification (Figure S11), the proteoforms with this modification were not taken into further consideration. Comparison and correlation of the quantification ratios (log2) from Group A and Group B were performed (Figure 4D). At protein accession level, 13 up-regulated and 11 down-regulated proteins were significantly discovered under anaerobic condition (Table S2). Under anaerobic condition, the yeast cells rely on fermentation to produce ATP for survives. It has been reported that cytoplasmic ribosomal proteins exhibited a high degree of collective down-regulation during fermentation49. In this work, 8 of 11 down-regulated proteins are belong to cytoplasmic ribosomal proteins (RS20, RS22B, RS19B, RL22B, RS21B, RS7A, RLA4 and RLA3), which are typically highly positive charged and with relatively small molecular weights. In contrast, most of the upregulated protein in anaerobic condition is stress-responsive proteins (SIP18, GRE1, HSP12, IPA3 and IPB2). SIP18 and GRE1 are also characterized as hydrophilins, which are highly expressed in response to osmotic stress. In this work the expression levels of SIP18 and GRE1 were increased about 200 and 15 folds under the anaerobic condition (Figure 5 and Figure S12), 14


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which is also consistent with the precious reports49-51. HSP12 is one of heat shock proteins, which are important in regulating protein folding. The over expression of this protein has been reported under anaerobic conditions such as wine fermentation 49, 50, 52. The protein expression of HSP12 was increased about 3 times compared to the aerobic condition in this work (Figure S13). The up-regulation of IPA3 and IPB2 was also reported in previous work in response to hypoxic condition53. The up-regulation of all these stress-responsive proteins may relate to the accumulation of organic acids, gases or alcohol in the culture media, when the oxygen was exhausted, and the cell must rely on fermentation to produce ATP for proliferation. Obviously, our intact protein isotope labeling and pTop quantification strategy could be feasibly applied for real complex cellular samples to screen out the dysregulated proteins with high reliability.

Figure 4 The differential expression levels of intact proteoforms of yeast under aerobic and anaerobic conditions by isotope dimethyl labeling and pTop quantification strategy. (A) the base peak chromatograms of A group and B group; (B) the mass spectra at the identical LC retention time in each group; (C) the overlay of spectra for a 28 kDa protein observed in the A and B group; (D) the correlation of quantification ratios (Log2) for the proteoforms (without modification of oxidation) in groups A and B, the differential expressed proteins were colored in red and green. Group A: anaerobic culture (light labeled) and aerobic culture (heavy labeled); Group B: anaerobic culture (heavy labeled) and aerobic culture (light labeled).

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Figure 5 The differential expression of SIP8 protein in the under aerobic and anaerobic conditions: (A and C), the MS1 spectra of SIP8 protein in Group A and Group B; (B and D), annotated and deconvoluted spectra of SIP8 protein in Group A and Group B; Group A: anaerobic culture (light labeled) and aerobic culture (heavy labeled); Group B: anaerobic culture (heavy labeled) and aerobic culture (light labeled).

4. Discussion Proteome analysis in a top-down manner for intact proteins is a well-recognized important direction for proteomics development. Intact protein analysis could provide a lot of important information, such as mutations, splice variants, endogenous proteolytic cleavage and the combination patterns of different types of PTMs. Quantification of intact proteins would play an increasingly important role in elucidating the mechanisms of different biological processes. Recently, thousands of intact proteins could be identified from human cell lines. However, comprehensive intact protein quantification is still lagging behind the development of identification. Chemical isotope labeling strategies are widely utilized in peptide-based proteomic quantification due to their high quantification accuracy and wide applicability. Much higher requirements are needed for intact proteins chemical labeling because they have much more reactive groups. Any deficiency of a labeling reaction would be amplified in intact protein level. Isotopic dimethyl labeling is a popular strategy for mass differential isotopes incorporation due to its high reaction efficiency and specificity. In this study, the reducing reagent of dimethyl labeling was replaced with pyridine borane to eliminate the side-reaction caused by NaCNBH3 and the pH of the reaction system was reduced to about 7.0 to suppress the side-reactions of formaldehyde. Thus, full incorporation of mass differential isotopes was 16


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demonstrated for both standard intact proteins and complex protein samples extracted from cell lines. This highly efficient chemical labeling strategy for intact proteins provides assurance for the accurate quantification of intact proteins in MS1 level. In order to realize automated intact protein quantification in high throughput, an intact protein quantification mode was developed and added into pTop 2.0 31 for the identification and quantification of the isotope labeled intact proteins from model organisms with known databases. A total of 2,283 intact proteoforms originated from 660 protein accessions were successfully quantified by the pTop 2.0 in this work. Compared with the typical used monoisotopic peak based quantification mode in common bottom-up proteomic analyses, the highest isotopic peaks of each intact protein forms were utilized for quantification, which significantly increased the accuracy of quantification results (Figure 3). However, due to the function limitation of pTop 2.0, only the oxidation of methionine and acetylation of N-termini could be set as variable modifications during the data process at current stage. As the oxidation of methionine is mainly introduced during the sample preparation procedures, the oxidation levels are hard to predict for intact proteins. For example, 35 of the 37 proteoforms of SIP8 have oxidation modification and exhibit a wide distribution of quantification ratios in our results (Figure S11), which indicates that abundant oxidation on methionine residues are introduced in the sample preparation and the oxidation degree is hard to control among different experiments. Thus, the unpredicted oxidation of methionine residue might hinder the quantification accuracy of intact proteins and eliminating the influence of exogenous oxidation of methionine is important for improving the quantification accuracy of proteoforms. Moreover, a lot of isotopic ion pairs with highly positive charges were observed in MS detection but could not be assigned with protein sequences, which might be attributed to the low resolution of the MS and the poor fragmentation efficiency of the intact proteins by commonly utilized CID or HCD modes in MS/MS sequencing. As the MS instruments are rapidly developed in the recent years, the new generation of mass spectrometer can provide higher mass detection resolution and new dissociation strategy, such as the promising ultraviolet photodissociation (UVPD)54-57. Therefore, we think the isotopic labeled intact proteins with higher molecular weights will be accurately identified and quantified in the near future. 17



5. Conclusions In this study, we developed a high-throughput strategy for global intact protein quantification based on chemical isotope labeling. High quantification accuracy was feasibly demonstrated for both standard and complex intact proteins samples. The pTop 2.0 software was developed to further deal with the isotopic proteoform pairs and the quantification of intact proteins could be achieved in a high-throughput manner. This intact protein isotope labeling and pTop 2.0 quantification strategy was successfully applied to quantify the different proteome expression levels of yeast cells under anaerobic and aerobic conditions. Many important proteins related to the biological processes such as stress response were observed with significant dysregulation.

SUPPORTING INFORMATION: The following supporting information is available free of charge at ACS website http://pubs.acs.org: Supporting Information 1: supporting methods and figures. -

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Supportting exprimental Figure S1 The overlay spectra of unlabeled and labeled lysozyme (A) and RNase (B). Figure S2 The fragmentation patterns of myoglobin ions with different charge state. Figure S3 The fragmentation patterns of lysozyme ions with different charge state. Figure S4 The MS spectra of dimethyl isotope labeled proteins (heavy/light = 1), (A) RNase A; (B) lysozyme; (C) myoglobin and (D) β-casein. Figure S5 The MS spectra of dimethyl labeled β-casein. (A) the ion pairs with different charges in 1:1 pre-mixed sample; (B-E) the MS spectra of 1:1, 2:1, 5:1 and 10:1 with the charge state of 17+. Figure S6 The measured and calculated MS spectra of myoglobin with a charge state of 17+. The monoisotopic peak was indicated by red arrow. Figure S7 The linearity plot of quantitative ratio of each intact protein. Figure S8 The quantification ratios of the mixed intact proteins with different pre-mixing ratios based on the intensities of monoisotopic species after deconvolution. Figure S9 (A) MS1 spectra of an unknown protein with a mass of 28 kDa detected in both A and B group; (B) the enlarge figures of MS1 spectra and a consistent result is obtained for this protein, which indicates that high quantification accuracy could well be obtained for large proteins. Figure S10 the MS1 and MS2 spectra of an unknown protein with a mass of 28 kDa. Figure S11 The correlation of quantification ratios (Log2) for the proteoforms in groups A and B. Figure S12 The quantification of GRE1 protein in Group A: (A), the MS1 spectra of GRE1 protein; (B), annotated and deconvoluted spectra of GRE1 protein. 18


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Figure S13 The quantification of HSP12 protein in Group A: (A), the MS1 spectra of HSP12 protein; (B), annotated and deconvoluted spectra of HSP12 protein. Table S2 The up-regulated and down-regulated proteins (anaerobic vs aerobic). Table S1 The identified peptides from HeLa proteome after dimethyl labeling. (xlsx) Table S3 The quantified proteoforms from yeast proteome under anaerobic and aerobic conditions. (xlsx)

Notes: The authors declare no competing financial interest.

Acknowledgement The authors greatly appreciated Prof. Simin He and Dr. Chao Liu for the helpful discussion and constructive suggestion. Financial supports are gratefully acknowledged for the China State Key Research Grant (2016YFF0200504), the National Natural Science Foundation of China (21675152, 91853101 and 31670837) and grant from DICP (ZZBS201603).

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Global quantification of intact proteins via chemical isotope labeling

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