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Abstract: Molecular mass spectrometry (MS) analysis of protein phosphorylation is partially limited by the molecular specie specificity of the analytical responses that might impair both qualitative and quantitative performances. Elemental MS, such as inductively coupled plasma mass spectrometry (ICP-MS) can overcome these drawbacks; in fact, analytical performance is theoretically independent of the molecular structure of a target analyte naturally containing the elements of interest. Nevertheless, isobaric interferences derived from sample matrix and laboratory environment can hinder the quantitative determination of both phosphorus (P) and sulfur (S) as 31P+ and 32S+ by inductively coupled plasma quadrupole mass spectrometry (ICP-QMS) under standard plasma conditions. These interferences may be overcome by quantifying P and S as oxide ions 31P16O+ and 32S16O+, respectively. In this study, we present a systematic investigation on the effect of plasma instrumental conditions on the oxide ion responses by a design of experiment approach for the simultaneous ICP-QMS determination of P and S (31P16O+ and 32S16O+, respectively) in protein samples without the use of dynamic reaction, collision reaction cells or pre-addition of oxygen as reactant gas in the torch. The proposed method was evaluated in terms of limit of detection, limit of quantification, linearity, repeatability, and trueness. Moreover, detection and quantification capabilities of the optimized method were compared to the standard plasma mode for determination of 31P+ and 34S+. Spectral and non-spectral interferences affecting the quantification of 31P+, 31P16O+ and 32S16O+ were also studied. The suitability of inorganic elemental standards for P and S quantification in proteins was assessed. The method was applied to quantify the phosphorylation stoichiometry of commercially available caseins (bovine β-casein, native and dephosphorylated α-casein) and results were confirmed by Matrix Assisted Laser Desorption Ionization Time of Flight MS analysis. We demonstrate that ICP-QMS, by quantifying P and S as oxide ions, was able to accurately calculate the degree of phosphorylation of β-casein and α-casein and to detect specific partial enzymatic dephosphorylation. The collected results might lead to further development of ICP-QMS interfaces optimized for protein phosphorylation studies and for proteomics investigations. [Copyright &y& Elsevier]

Abstract: Serum proteome investigations have raised an incredible interest in the research of novel molecular biomarker, nevertheless few of the proposed evidences have been translated to the clinical practice. One of the limiting factors has been the lack of generally accepted guidelines for clinical proteomics studies and the lack of a robust analytical and pre-analytical ground for the proposed classification models. Pre-analytical issues may results in a deep impact for biomarker discovery campaign. In this study we present a systematic evaluation of sample storage and sampling conditions for clinical proteomics investigations. We have developed and validated a linear MALDI-TOF-MS protein profiling method to explore the low protein molecular weight region (5–20kDa) of serum samples. Data normalization and processing was performed using optimise peak detection routine (LIMPIC) able to describe each group under investigation. Data were acquired either from healthy volunteers and from multiple sclerosis patients in order to highlight ex vivo protein profile alteration related to different physio-pathological conditions. Our data showed critical conditions for serum protein profiles depending on storage times and temperatures: 23°C, 4°C, −20°C and −80°C. We demonstrated that upon a −20°C short term storage, characteristic degradation profiles are associated with different clinical groups. Protein signals were further identified after preparative HPLC separation by peptide sequencing on a nanoLC-Q-TOF TANDEM mass spectrometer. Apolipoprotein A-IV and complement C3 protein fragments, transthyretin and the oxidized isoforms in different apolipoprotein species represent the major molecular features of such a degradation pattern. [Copyright &y& Elsevier]