Nonspecific adsorption evaluation and general minimization strategy in peptide analysis based on ultra-performance liquid chromatography-mass spectrometry

doi:10.3724/SP.J.1123.2021.12012

Abstract

Abstract:

Proteomics technology is being increasingly used in the development of novel therapeutic peptides and protein drugs, and also in the intensive search for clinical biomacromolecule diagnostic biomarkers. Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) is a rapid method to analyze peptides and proteins in low abundance. However, the nonspecific adsorption properties of peptides may lead to the loss or interference of the analytes throughout the analytical process. This unique nonspecific adsorption property is the main reason for the false negative and false positive results obtained through quantification, as well as for the poor precision, accuracy, linear range, and sensitivity, all of which impose significant challenges in the development of analytical methods.
Accordingly, a general strategy was established to evaluate and reduce the negative impact of the nonspecific adsorption of peptides on UPLC-MS analysis. In this study, bovine serum albumin (BSA) was used as a model protein to explore the correlation between the physicochemical properties of 50 peptides obtained by the enzymatic digestion of BSA, as well as the degree of nonspecific adsorption. First, these peptides were classified into four categories according to their response and the degree of adsorption in the pretreatment containers and LC system. Next, the factors influencing the adsorption of 12 Class Ⅱ peptides, which were highly responsive and susceptible to adsorption, were systematically studied in terms of several aspects, including: (1) time-dependent adsorption on centrifuge tubes of three kinds (Protein-LoBind polypropylene tube and two types of polypropylene tubes); (2) time-dependent adsorption on sample vials of three kinds (Protein-LoBind polypropylene vial, polypropylene vial, and glass vial); (3) carryovers on chromatographic columns with six different stationary phases (Polar C₁₈, Cortecs C₁₈⁺, PFP, BEH C₁₈, CSH C₁₈, and BEH C₈); (4) carryovers at different chromatographic gradients (2%B-30%B, 2%B-40%B, 2%B-50%B, and 2%B-60%B within 3 min), flow rates (0.2, 0.3, and 0.4 mL/min), and column temperatures (30, 40, 50, and 60 ℃); and (5) carryovers using different washing needle solutions (0.2% formic acid in 10% acetonitrile and 0.2% formic acid in 90% acetonitrile).
The results showed that parameters such as the HPLC index and amino acid length of peptides were significantly correlated with their degree of adsorption (p<0.05), However, the above parameters can only explain the adsorption degree of 30% of the peptides. The use of the modified polypropylene material resulted in higher recovery (recovery rate>80% within 24 h) of the peptide solution during storage or pretreatment. During protein/peptide pretreatment and storage, good overall recoveries (recovery rate>80% within 24 h) were obtained using centrifuge tubes and sample vials made of the modified polypropylene material. Analysis and optimization of the LC conditions revealed that the use of the C₈ chromatographic column, a high flow rate (0.4 mL/min), slow gradient (2%B-50%B within 3 min), and strong needle solution (0.2% formic acid in 90% acetonitrile) could minimize the carryover. However, the effect of the column temperature on the carryover varied considerably from peptide to peptide, and hence, requires further analysis for specific peptides. The combined optimization of the above experimental conditions resulted in minimal (approximately 1/150) or no adsorption of the Class Ⅱ peptides that were susceptible to adsorption in the analytical process.
In this study, a workflow was designed to standardize the procedures for evaluating and reducing peptide adsorption. Detailed data were collected to elucidate the key risk factors and corresponding general mechanism of nonspecific adsorption throughout the analysis. Thus, this study serves as a reference for the development of analytical methods for peptides and proteins with different physicochemical properties. In future work, the risk factors should be assessed during the development and validation of protein-based macromolecular analysis methods. In conclusion, it is important to implement adequate and appropriate measures to ensure risk elimination or minimization.

Key words: ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), proteomics, nonspecific adsorption, quantification, carryover, peptides

CLC Number:

O658

ZHANG Ying, YANG Jing, MA Yuexin, CAO Ling, HUANG Qing. Nonspecific adsorption evaluation and general minimization strategy in peptide analysis based on ultra-performance liquid chromatography-mass spectrometry[J]. Chinese Journal of Chromatography, 2022, 40(7): 616-624.

Figures/Tables 8

Table 1 Ion pair information and MRM parameters for Class Ⅱ peptides after enzymatic digestion of bovine serum albumin (BSA) hydrolysis

Number	Peptide	[M+H]⁺	Q1 (m/z)	Q3 (m/z)	Declustering potential/V	Collision energy/eV
P1	DAFLGSFLYEYSR	1567.743	784.38	1121.53	49.9	35.4
P2	GLVLIAFSQYLQQCPFDEHVK	2492.264	831.43	383.24	47.8	35.9
P3	ECCHGDLLECADDR	1749.662	583.89	765.28	58.7	28.0
P4	TVMENFVAFVDK	1399.693	700.35	1199.58	53.6	29.3
P5	LFTFHADICTLPDTEK	1907.921	636.65	589.28	56.4	30.6
P6	DDPHACYSTVFDK	1554.653	518.89	609.32	61.6	24.9
P7	MPCTEDYLSLILNR	1724.835	862.92	715.45	46.5	47.3
P8	LVNELTEFAK	1163.631	582.32	951.48	58.8	27.5
P9	SLHTLFGDELCK	1419.694	473.90	721.32	63.6	22.7
P10	VPQVSTPTLVEVSR	1511.843	756.43	900.52	51.1	42.1
P11	HLVDEPQNLIK	1305.716	653.36	1055.57	55.7	35.0
P12	LGEYGFQNALIVR	1479.795	740.40	1017.58	51.8	43.3

Fig. 1 (a)Grading strategy of peptides (b) nonspecific adsorption factor examination and optimization process

Fig. 2 Peptides recoveries after 24 h storage in different sample containers Recoveries of Class Ⅱ peptide solutions at three levels (50, 500, 5000 ng/mL) stored in different centrifuge tubes (Fig. 2a) and sample vials (Fig. 2b) after 24 h. PP-LB(LB): lowbind polypropylene tubes or vials; PP-A(A) and PP-B(B): polypropylene tubes from company A and B; PP: polypropylene vials; Glass/G: glass vials; Average: average recovery, %; SD: standard deviation; Min: minimum; Count: the number of peptides solutions with recoveries less than 80%.

Fig. 3 Trends of the recovery of low concentrations of peptide P7 solutions in different sample containers (n=3)

Fig. 4 (a) Gradient program for column carryover evaluation and (b) typical chromatogram for the carryover peptides

Table 2 Column characteristics

Stationary phase	Pore size/nm	Particle size/μm	Diameter/ mm	Length/ mm
Polar C₁₈	10	2.6	2.1	100
Cortecs C₁₈⁺	9	1.6	2.1	100
PFP	10	1.7	2.1	100
BEH C₁₈	30	1.7	2.1	100
CSH C₁₈	13	1.7	2.1	100
BEH C₈	13	1.7	2.1	100

Fig. 5 Effect of stationary phase types on peptide carryover on the chromatographic columns BEH-C8-opti is the carryover percentage obtained after optimization.

Fig. 6 Effect of different chromatographic conditions on the carryover of peptides on the columns (n=3) a. flow rate; b. gradient; c. percentage of formic acid (FA) in mobile phase; d. column temperature. G1-G4 were the gradients of 2-6 min: 2%B-30%B, 2%B-40%B, 2%B-50%B, and 2%B-60%B.

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