title: Novel calibration model maintenance strategy for solving the signal instability in quantitative liquid chromatography-mass spectrometry.
abstract: In this contribution, a multiplicative effects model with a parameter accounting for the variations in overall sensitivity over time was proposed to reduce the effects of signal instability on quantitative results of LC-MS/MS. This method allows the use of calibration models constructed from large standard sets without having to repeat their measurement even though variations occur in sensitivity and baseline signal intensity. The performance of the proposed method was tested on two proof-of-concept model systems: the determination of the target peptide in two sets of peptide digests mixtures and the quantification of melamine and metronidazole in two sets of milk powder samples. Experimental results confirmed that multiplicative effects model could provide quite satisfactory concentration predictions for both systems with average relative predictive error values far lower than the corresponding values of various models investigated in this paper. Considering its capability in solving the problem of signal instability across samples and over time in LC-MS/MS assays and its implementation simplicity, it is expected that the multiplicative effects model can be developed and extended in many application areas such as the quantification of specific protein in cells and human plasma and other complex systems.
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.
authors.forename: Hai-Li
authors.initials: HL
authors.lastname: Du
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China. Electronic address: zpchen2002@hotmail.com.
authors.forename: Zeng-Ping
authors.initials: ZP
authors.lastname: Chen
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.
authors.forename: Mi
authors.initials: M
authors.lastname: Song
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.
authors.forename: Yao
authors.initials: Y
authors.lastname: Chen
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.
authors.forename: Ru-Qin
authors.initials: RQ
authors.lastname: Yu
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D002138:Calibration; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D008892:Milk / Q000737:chemistry; D008956:Models, Chemical; D008969:Molecular Sequence Data; D010455:Peptides / Q000032:analysis / Q000737:chemistry; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D010455:Peptides
keywords: Calibration model maintenance; Ion suppression; LC–MS/MS; Multiplicative effects model; Signal instability