The Impact of Pre-Analytical Conditions on Human Serum Peptidome Profiling

In the last few decades, studies on the human proteome aiming to discover new, clinically relevant biomarkers, have provided a unique opportunity for improving upon the identification of early stage diseases of several disorders, particularly in the detection of tumors. Different studies have been conducted to explore whole and/or low molecular weight proteome (peptidome), which may include many peptides originating from high molecular weight protein degradation. Initially, hopes were raised in the scientific community by insights obtained into new peptides/proteins, observed to have significantly deviated from the normal physiology in pathological conditions. However, no translation into routine clinical practice of these molecules was achieved, and criticism was raised, especially regarding the reproducibility of the studies performed.1 The most widely criticized items in proteomics-based biomarker discovery studies were: a) adoption of standardized operating procedures (SOP) for pre-analytical and analytical items, b) poor study design, c) lack of multi-centric studies, and d) unreliable data evaluation and statistical analyses.

Sample collection, handling, and storage have been found to have a marked impact on the reliability of clinical proteomics analyses, and poor standardization has been cited as an important factor compromising the comparability of results of both inter-laboratory and multi-center studies.2 For proteomics studies, it is important to choose the most appropriate available sample matrix, and to ensure that several types of samples can be analyzed, including almost all body fluid (e.g., blood, urine, cerebrospinal fluids, saliva, and tissues).3, 4 However, the vast majority of studies have focused on plasma or serum, two different matrix types originating from full blood, that is commonly collected from patients using vacuum drawn tubes containing plasma or serum anticoagulants. In plasma samples, pre-analytical variability can be due to the type of anticoagulants used. Jambunathan et al. reported that the plasma citrate matrix (together with serum) was more proteolytically active than plasma heparin and EDTA.5 Differently, when serum is obtained from coagulated blood, a network of serine proteases were activated, generating the so-called coagulation “degradome,” which was not found in plasma samples.6 Thus the different types of anticoagulants present in vacuum tubes, and the fact that some features are found in sera, but not in plasma, explain the differences in proteomic profiles, particularly those in the peptidome range.7 A further aspect that should be considered before sample collection is the presence of the separator gel in the blood collection tubes, as any residue after centrifugation may cause interference in the analytical phase, especially if samples are not centrifuged twice at high speed.7

As demonstrated by Umemura et al. on investigating sample handling, serum peptidome is affected by the time interval between venepuncture and samples preparation.2 In 2009, on analyzing serum peptidome using MALDI-TOF/MS, the authors recommended that a maximum time interval between venepuncture and serum separation of 60 min should be set in order to identify the most efficient possible marker in serum analyses; this was supported by findings made by De Girolamo et al.2, 8 Furthermore, to minimize any possible degradation of proteins in serum, known to be the most proteolytically active available matrix, serum samples should be frozen to the lowest possible temperature, better with liquid nitrogen.2

The aim of the latest study by Tsuchida et al. appearing in the current issue of Proteomics Clinical Application was to investigate relevant pre-analytical aspects of serum peptidome profiling, including long-term storage temperature (≤12 mos) and thawing methods in samples from eight healthy young donors.9 Serum samples, processed 30 min after collection to allow blood coagulation and stored at −20 °C, −80 °C, or in liquid nitrogen until analysis, were pre-treated and deposited using an automated cation exchange magnetic beads method, followed by the MALDI-TOF/MS technique. The strength of the study lies in the methodological workflow used, as automated samples preparation and deposition has been demonstrated to improve inter-assay reproducibility, thus minimizing sample-to-sample variability, and to maximize the number of peptides identified.8 In MALDI-TOF/MS peptidome profiling, for a given feature and in a feature-specific range of intensity, there is a linear correlation between the instrumental and the peptide abundance, for example, the linear tract of the signal-abundances sigmoid curve.10 However, when MALDI is used, several effects, such as ion suppression and nonhomogeneous sample-matrix crystallization, massively limit raw signals between-spectra comparability. Consequently, alternative approaches are used to improve feature comparability, including signal normalization and the adoption of internal standards.10, 11 Interestingly, Tsuchida et al. used two different internal standard peptides (instead of a single internal standard), parathyroid hormone (MW 3718) and muscarine toxin 1 (MW 7509), mixed into each sample, to calculate the ratio of the peaks intensity of serum peptidome, thus normalizing data across samples. Another important strength of the authors’ methodological approach is that it involved the evaluation of all the identified MS peaks, instead of a single or a small bunch of features, thus enhancing the reliability of results. On evaluating a total of 34 identified MS features in a mass ranging from m/z 600 to 10 000, the authors obtained that, at 3 months of storage at −20 °C, a series of features presented statistically significant differences with respect to the MS pattern on day 0, while at −80 °C and under liquid nitrogen no such differences were found even at 6 and 12 months storage. At −20 °C, the majority of differences were found for fibrinogen α chain, apolipoprotein C-I, apolipoprotein C-II, connective tissue activating peptide II, and complement C3f fragment. As yet, few studies have focused on the pre-analytical variables affecting serum peptidome profiling. Di Girolamo et al. used the same methodology and a similar m/z range (500–12 000) and found similar nonsignificant differences on storing serum samples at −80 °C for up to 1 month. Pieragostino et al. also reported that the serum proteome (5–20 kDa) of samples presented a significant alteration phenomenon even after 10 d storage at −20 °C, whereas sample storage at −80 °C, showing no significant modifications in the protein pattern acquired by linear MALDI-TOF-MS for at least 5 months, guarantee better conditions for long-term storage of biological samples.

Finally, Tsuchida et al. also found that no peptidome/proteome difference is present in samples stored at −80 °C or in liquid nitrogen for 3, 6, or 12 months and subsequently thawed using three conditions, namely kept on ice, at room temperature (around 25 °C), or in a 37 °C water bath.

Careful sample collection and handling are two aspects of utmost importance in mass spectrometry–based peptidomic profiling. In addition to biological variation (e.g., effect of age and circadian rhythm on peptides/proteins levels), another series of relevant pre-analytical conditions have been demonstrated to impact on the comparability of results. The definition of a SOP that takes all the above aspects into account is therefore mandatory, and should be used for proteomic analysis, especially when specimens are collected and handled by several laboratories for multi-centric studies.

Conflict of Interest

The author declared no conflict of interest.