In-Source Decay Causes Artifacts in SELDI-TOF MS Spectra

Investigation of serum protein profiles in scrapie infected sheep by means of SELDI-TOF-MS and multivariate data analysis

Background

Classical scrapie in sheep is a fatal neurodegenerative disease associated with the conversion PrP^C to PrP^Sc. Much is known about genetic susceptibility, uptake and dissemination of PrP^Sc in the body, but many aspects of prion diseases are still unknown. Different proteomic techniques have been used during the last decade to investigate differences in protein profiles between affected animals and healthy controls. We have investigated the protein profiles in serum of sheep with scrapie and healthy controls by SELDI-TOF-MS and LC-MS/MS. Latent Variable methods such as Principal Component Analysis, Partial Least Squares-Discriminant Analysis and Target Projection methods were used to describe the MS data.

Results

The serum proteomic profiles showed variable differences between the groups both throughout the incubation period and at the clinical end stage of scrapie. At the end stage, the target projection model separated the two groups with a sensitivity of 97.8%, and serum amyloid A was identified as one of the protein peaks that differed significantly between the groups.

Conclusions

At the clinical end stage of classical scrapie, ten SELDI peaks significantly discriminated the scrapie group from the healthy controls. During the non-clinical incubation period, individual SELDI peaks were differently expressed between the groups at different time points. Investigations of differences in -omic profiles can contribute to new insights into the underlying disease processes and pathways, and advance our understanding of prion diseases, but comparison and validation across laboratories is difficult and challenging.

Association between protein signals and type 2 diabetes incidence

Understanding early determinants of type 2 diabetes is essential for refining disease prevention strategies. Proteomic technology may provide a useful approach to identify novel protein patterns potentially related to pathophysiological changes that lead up to diabetes. In this study, we sought to identify protein signals that are associated with diabetes incidence in a middle-aged population. Serum samples from 519 participants in a nested case-control selection (167 cases and 352 age-, sex- and BMI-matched normoglycemic control subjects, median follow-up 14.0 years) within the Whitehall-II cohort were analyzed by linear matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Nine protein peaks were found to be associated with incident diabetes. Rate ratios for high peak intensity ranged between 0.4 (95% CI, 0.2-0.8) and 4.0 (95% CI, 1.7-9.2) and were robust to adjustment for main potential confounders, including obesity, lipids and C-reactive protein. The proteins associated with these peaks may reflect diabetes pathogenesis. Our study exemplifies the utility of an approach that combines proteomic and epidemiological data.

MALDI mass spectrometry in prostate cancer biomarker discovery

Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

The effect of preanalytical factors on stability of the proteome and selected metabolites in cerebrospinal fluid (CSF)

To standardize the use of cerebrospinal fluid (CSF) for biomarker research, a set of stability studies have been performed on porcine samples to investigate the influence of common sample handling procedures on proteins, peptides, metabolites and free amino acids. This study focuses at the effect on proteins and peptides, analyzed by applying label-free quantitation using microfluidics nanoscale liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (chipLC-MS) as well as matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FT-ICR-MS) and Orbitrap LC-MS/MS to trypsin-digested CSF samples. The factors assessed were a 30 or 120 min time delay at room temperature before storage at -80 degrees C after the collection of CSF in order to mimic potential delays in the clinic (delayed storage), storage at 4 degrees C after trypsin digestion to mimic the time that samples remain in the cooled autosampler of the analyzer, and repeated freeze-thaw cycles to mimic storage and handling procedures in the laboratory. The delayed storage factor was also analyzed by gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) for changes of metabolites and free amino acids, respectively. Our results show that repeated freeze/thawing introduced changes in transthyretin peptide levels. The trypsin digested samples left at 4 degrees C in the autosampler showed a time-dependent decrease of peak areas for peptides from prostaglandin D-synthase and serotransferrin. Delayed storage of CSF led to changes in prostaglandin D-synthase derived peptides as well as to increased levels of certain amino acids and metabolites. The changes of metabolites, amino acids and proteins in the delayed storage study appear to be related to remaining white blood cells. Our recommendations are to centrifuge CSF samples immediately after collection to remove white blood cells, aliquot, and then snap-freeze the supernatant in liquid nitrogen for storage at -80 degrees C. Preferably samples should not be left in the autosampler for more than 24 h and freeze/thaw cycles should be avoided if at all possible.

Challenges for biomarker discovery in body fluids using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.

Serum biomarker profiling by solid-phase extraction with particle-embedded micro tips and matrix-assisted laser desorption/ionization mass spectrometry

One of the main challenges in high-throughput serum profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is the development of proteome fractionation approaches that allow the acquisition of reproducible profiles with a maximum number of spectral features and minimum interferences from biological matrices. This study evaluates a new class of solid-phase extraction (SPE) pipette tips embedded with different chromatographic media for fractionation of model protein digests and serum samples. The materials embedded include strong anion exchange (SAX), weak cation exchange (WCX), C18, C8, C4, immobilized metal affinity chromatography (IMAC) and zirconium dioxide particles. Simple and rapid serum proteome profiling protocols based on these SPE micro tips are described and tested using a variety of MALDI matrices. We show that different types of particle-embedded SPE micro tips provide complementary information in terms of the spectral features detected for beta-casein digests and control human serum samples. The effect of different sample pretreatments, such as serum dilution and ultrafiltration using molecular weight cut-off membranes, and the reproducibility observed for replicate experiments, are also evaluated. The results demonstrate the usefulness of these simple SPE tips combined with offline MALDI-TOF MS for obtaining information-rich serum profiles, resulting in a robust, versatile and reproducible open-source platform for serum biomarker discovery.