Identification of serum proteomic biomarkers for early porcine reproductive and respiratory syndrome (PRRS) infection

ABSTRACT: BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) is one of the most significant swine diseases worldwide. Despite its relevance, serum biomarkers associated with early-onset viral infection, when clinical signs are not detectable and the disease is characterized by a weak anti-viral response and persistent infection, have not yet been identified. Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) is a reproducible, accurate, and simple method for the identification of biomarker proteins related to disease in serum. This work describes the SELDI-TOF MS analyses of sera of 60 PRRSV-positive and 60 PRRSV-negative, as measured by PCR, asymptomatic Large White piglets at weaning. Sera with comparable and low content of hemoglobin (< 4.52 ug/mL) were fractionated in 6 different fractions by anion-exchange chromatography and protein profiles in the mass range 1-200 kDa were obtained with the CM10, IMAC30, and H50 surfaces. RESULTS: A total of 200 significant peaks (p < 0.05) were identified in the initial discovery phase of the study and 47 of them were confirmed in the validation phase. The majority of peaks (42) were up-regulated in PRRSV-positive piglets, while 5 were down-regulated. A panel of 14 discriminatory peaks identified in fraction 1 (pH=9), on the surface CM10, and acquired at low focus mass provided a serum protein profile diagnostic pattern that enabled to discriminate between PRRSV-positive and -negative piglets with a sensitivity and specificity of 77% and 73%, respectively. CONCLUSIONS: SELDI-TOF MS profiling of sera from PRRSV-positive and PRRSV-negative asymptomatic piglets provided a proteomic signature with large scale diagnostic potential for early identification of PRRSV infection in weaning piglets. Furthermore, SELDI-TOF protein markers represent a refined phenotype of PRRSV infection that might be useful for whole genome association studies.     

蛋白质芯片SELDI-TOFMS技术的研究进展及其在临床中的应用

蛋白质芯片为新一代的蛋白质组研究技术,由美国Ciphergen生物系统公司引进,表面增强激光解吸电离-飞行时间质谱(SELDI-TOFMS)提供一个高通量和高灵敏度的检测平台。投放至今虽短短10来年,但卓越的成果已广为医学科学界重视,尤其在恶性肿瘤的早期诊断、监控和预后研究上。蛋白质是细胞内执行生物功能的最终分子,蛋白质组学研究让人类更深入了解疾病和生命的本源,不断发现的特异性肿瘤标志物更为攻克癌症带来新希望。这里除对表面增强激光解吸电离_飞行时间质谱作较详尽的介绍外,更重点阐述其近年来蛋白质芯片近期的研究进展和在临床中的应用,并就其优劣和发展前景作出评估。     

The application of SELDI-TOF mass spectrometry to mammalian cell culture

Surface Enhanced Laser Desorption/Ionisation Time-of-Fight Mass Spectrometry (SELDI-TOF MS) is a technique by which protein profiles can be rapidly produced from a wide variety of biological samples. By employing chromatographic surfaces combined with the specificity and reproducibility of mass spectrometry it has allowed for profiles from complex biological samples to be analysed. Profiling and biomarker identification have been employed widely throughout the biological sciences. To date, however, the benefits of SELDI-TOF MS have not been realised in the area of mammalian cell culture. The advantages in identifying markers for cell stresses, apoptosis and other culture parameters mean that these tools could help greatly to enhance monitoring and control of bioreaction process and improve the production of therapeutics. Better characterisation of culture systems through proteome analysis will allow for improved productivity and better yields.     

Methods for on-chip protein analysis

The unambiguous identification of peptides/proteins is crucial for the definition of the proteome. Using ProteinChip Array technology also known as surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS), we developed experimental protocols and probed test conditions required for the protein identification on ProteinChip surfaces. We were able to directly digest peptides/proteins on-chip surfaces by specific proteases, such as trypsin, and to obtain the peptide mass fingerprint of the sample under investigation by its direct analysis on a simple laser desorption/ionization mass spectrometer. Furthermore, tandem mass spectrometry was performed on several of the resulting tryptic peptides by using collision quadrupole time of flight (Qq-TOF) MS/MS via the ProteinChip interface, thus allowing the unambiguous identification of the protein(s) within the sample. In addition, we were able to identify the C-terminal sequence of peptides by their digestion with carboxypeptidase Y directly on ProteinChip surfaces coupled with SELDI-TOF MS analysis of the resulting peptide mass ladders employing the instrument's protein ladder sequence software. Moreover, the removal of up to nine amino acid residues from the C-terminal end of a peptide extends the functional range of Qq-TOF MS/MS sequence determination to over 3000 m/z. The utility of these procedures for the proteome exploration are discussed.     

Biomarker discovery for arsenic exposure using functional data. Analysis and feature learning of mass spectrometry proteomic data

Plasma biomarkers of exposure to environmental contaminants play an important role in early detection of disease. The emerging field of proteomics presents an attractive opportunity for candidate biomarker discovery, as it simultaneously measures and analyzes a large number of proteins. This article presents a case study for measuring arsenic concentrations in a population residing in an As-endemic region of Bangladesh using plasma protein expressions measured by SELDI-TOF mass spectrometry. We analyze the data using a unified statistical method based on functional learning to preprocess mass spectra and extract mass spectrometry (MS) features and to associate the selected MS features with arsenic exposure measurements. The task is challenging due to several factors, the high dimensionality of mass spectrometry data, complicated error structures, and a multiple comparison problem. We use nonparametric functional regression techniques for MS modeling, peak detection based on the significant zero-downcrossing method, and peak alignment using a warping algorithm. Our results show significant associations of arsenic exposure to either under- or overexpressions of 20 proteins.     

From SELDI-TOF MS to protein identification by on-chip elution

SELDI-TOF MS has been demonstrated as a powerful tool for biomarker discovery. However, a major disadvantage of SELDI-TOF MS is the lack of direct identification of the discriminatory peaks discovered. We describe a novel experimental identification strategy where peptides/proteins captured to a weak cation exchange ProteinArray surface (CM10) are eluted, and thereafter identified by utilizing a sensitive LC-MS/MS (i.e. LTQ Orbitrap). A mixture of four known proteins was used to test the novel experimental approach described, and all four proteins were successfully identified. Additionally, a biomarker candidate previously discovered in plasma of Atlantic cod (Gadus morhua) by SELDI-TOF MS was identified. Thus, this study indicated that a combination of on-chip elution and a highly sensitive LC-MS/MS system can be an alternative approach to identify biomarker candidates discovered by use of SELDI-TOF MS.     

Limitations in quantitation of the biomarker CCL18 in Gaucher disease blood samples by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

SELDI-TOF MS assisted the discovery of the chemokine CCL18/PARC as plasma biomarker for pathological storage cells in Gaucher disease patients. Prognostic elevation of CCL18 in blood of Gaucher patients has been confirmed by ELISA. Given its low molecular mass, positive charge, and relatively high abundance, CCL18 seems a particular attractive protein for SELDI-TOF based quantitation. Therefore, we determined CCL18 levels in plasma using SELDI-TOF MS and ELISA, in parallel. CCL18 levels in some blood samples were significantly underestimated when determined by SELDI-TOF MS. Spiking of recombinant CCL18 indicated that its detection by SELDI-TOF MS is strongly determined by the nature of the sample, even markedly varying between samples obtained from one donor at different time points. Independent of the total CCL18 concentration in blood only 1-10% of the chemokine bound to the ProteinChip Array. Even when comparable amounts of CCL18 from distinct samples were bound to the ProteinChip Array, diverse peak intensities could be observed. Thus, limited binding capacity and sample-dependent suppression of CCL18 ionization contribute significantly to the final peak intensity. In conclusion, SELDI-TOF MS offers no reliable procedure to quantitatively monitor CCL18 levels in blood and thus cannot be applied in evaluation of disease status of Gaucher patients.     

A computational platform for MALDI-TOF mass spectrometry data: Application to serum and plasma samples

BackgroundMass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data.ResultsMASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population.ConclusionsThe analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf.     

In-source decay causes artifacts in SELDI-TOF MS spectra

SELDI-TOF MS is a mass spectrometric technique which has been extensively used for biomarker discovery. In this study, we show that in-source decay is an important source for the generation of additional spectral peaks with this technique, both for pure proteins and proteins in serum samples. Thus, SELDI-TOF MS could be used to gain sequence information from proteins, but the results also question the uncritical use of SELDI-TOF MS as a general method for the detection of biomarkers.     

SELDI-TOF MS Proteomics in Breast Cancer

Background

Proteomic profiling is a rapidly developing technology that may enable early disease screening and diagnosis. Surface-enhanced laser desorption ionization–time of flight mass spectrometry (SELDI-TOF MS) has demonstrated promising results in screening and early detection of many diseases. In particular, it has emerged as a high-throughput tool for detection and differentiation of several cancer types. This review aims to appraise published data on the impact of SELDI-TOF MS in breast cancer.

Methods

A systematic literature search between 1965 and 2009 was conducted using the PubMed, EMBASE, and Cochrane Library databases. Studies covering different aspects of breast cancer proteomic profiling using SELDI-TOF MS technology were critically reviewed by researchers and specialists in the field.

Results

Fourteen key studies involving breast cancer biomarker discovery using SELDI-TOF MS proteomic profiling were identified. The studies differed in their inclusion and exclusion criteria, biologic samples, preparation protocols, arrays used, and analytical settings. Taken together, the numerous studies suggest that SELDI-TOF MS methodology may be used as a fast and robust approach to study the breast cancer proteome and enable the analysis of the correlations between proteomic expression patterns and breast cancer.

Conclusion

SELDI-TOF MS is a promising high-throughput technology with potential applications in breast cancer screening, detection, and prognostication. Further studies are needed to resolve current limitations and facilitate clinical utility.     

Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS)

Background

Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis.

Results

The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra.

Conclusion

This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.

     

Identification of treatment efficacy-related host factors in chronic hepatitis C by ProteinChip serum analysis

Recent development of proteomic array technology, including protein profiling coupling ProteinChip array with surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF/MS), provides a potentially powerful tool for discovery of new biomarkers by comparison of its profiles according to patient phenotypes. We used this approach to identify the host factors associated with treatment response in patients with chronic hepatitis C (CHC) receiving a 48-wk course of pegylated interferon (PEG-IFN) alpha 2b plus ribavirin (RBV). Protein profiles of pretreatment serum samples from 32 patients with genotype 1b and high viral load were conducted by SELDI-TOF/MS by using the three different ProteinChip arrays (CM10, Q10, IMAC30). Proteins showed significantly different peak intensities between sustained virological responders (SVRs), and non-SVRs were identified by chromatography, SDS-PAGE, TOF/MS and tandem mass spectrometry (MS/MS) assay. Eleven peak intensities were significantly different between SVRs and non-SVRs. The three SVR-increased peaks could be identified as two apolipoprotein (Apo) fragments and albumin and, among the eight non-SVR-increased proteins, four peaks identified as two iron-related and two fibrogenesis-related protein fragments, respectively. Multivariate analysis showed that the serum ferritin and three peak intensity values (Apo A1, hemopexin and transferrin) were independent variables associated with SVRs, and the area under the receiver operating characteristic (ROC) curves for SVR prediction by using the Apo A1/hemopexin and hemopexin/transferrin were 0.964 and 0.936. In conclusion, pretreatment serum protein profiling by SELDI-TOF/MS is variable for identification of response-related host factors, which are useful for treatment efficacy prediction in CHC receiving PEG-IFN plus RBV. Our data also may help us understand the mechanism for treatment resistance and development of more effective antiviral therapy targeted toward the modulation of lipogenesis or iron homeostasis in CHC patients.     

Biomarker discovery from body fluids using mass spectrometry

Systems analysis of body fluids by mass spectrometry (MS) is an upcoming field of biomarker research. This approach is extremely attractive because it does not require biomarker candidates and the sample preparation is simple. However, during the development of the technique strong critical comments were made on the poor reproducibility, the special characteristics of blood as a source of peptides and on the frequent non-adequate statistical analysis of the data. Here we discuss the efforts made in the last few years to develop suitable protocols, which could lead to biomarker discovery from body fluids by mass spectrometry. Our review focuses on the systems analysis of non-digested blood serum or plasma samples by MALDI-TOF and SELDI-TOF.     

Laboratory methods to improve SELDI peak detection and quantitation

Background  

Protein profiling with surface-enhanced laser desorption-ionisation time-of-flight mass spectrometry (SELDI-TOF MS) is a promising approach for biomarker discovery. Some candidate biomarkers have been identified using SELDI-TOF, but validation of these can be challenging because of technical parameters that effect reproducibility. Here we describe steps to improve the reproducibility of peak detection.     

Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers

We report on a multicenter analysis of HUPO reference specimens using SELDI-TOF MS. Eight sites submitted data obtained from serum and plasma reference specimen analysis. Spectra from five sites passed preliminary quality assurance tests and were subjected to further analysis. Intralaboratory CVs varied from 15 to 43%. A correlation coefficient matrix generated using data from these five sites demonstrated high level of correlation, with values >0.7 on 37 of 42 spectra. More than 50 peaks were differentially present among the various sample types, as observed on three chip surfaces. Additionally, peaks at approximately 9200 and approximately 15,950 m/z were present only in select reference specimens. Chromatographic fractionation using anion-exchange, membrane cutoff, and reverse phase chromatography, was employed for protein purification of the approximately 9200 m/z peak. It was identified as the haptoglobin alpha subunit after peptide mass fingerprinting and high-resolution MS/MS analysis. The differential expression of this protein was confirmed by Western blot analysis. These pilot studies demonstrate the potential of the SELDI platform for reproducible and consistent analysis of serum/plasma across multiple sites and also for targeted biomarker discovery and protein identification. This approach could be exploited for population-based studies in all phases of the HUPO PPP.     

Modern Tumor Marker Discovery in Urology: Surface Enhanced Laser Desorption and Ionization (SELDI)

During the last two decades, biomarker research has benefited from the introduction of new proteomic analytical techniques. In this article, we review the application of surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectroscopy in urologic cancer research. After reviewing the literature from MEDLINE on proteomics and urologic oncology, we found that SELDI-TOF is an emerging proteomic technology in biomarker discovery that allows for rapid and sensitive analysis of complex protein mixtures. SELDI-TOF is a novel proteomic technology that has the potential to contribute further to the understanding and clinical exploitation of new, clinically relevant biomarkers.     

Proteomics-based identification of biomarkers for predicting sensitivity to a PI3-kinase inhibitor in cancer

To identify biomarkers for predicting sensitivity to phosphatidylinositol 3-kinase (PI3K) inhibitors, we have developed a proteomics-based approach. Using surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF MS), we measured the expression of 393 proteins in 39 human cancer cell lines (JFCR-39), and combined it with our previously established chemosensitivity database to select for proteins whose expressions show significant correlations to drug sensitivities. This integrated approach allowed us to identify peaks from two proteins, 11.6 and 11.8 kDa, that showed significant correlations with the sensitivity to a PI3K inhibitor, LY294002. We found that the 11.8 kDa protein was a phosphorylated form of the 11.6 kDa protein. While the 11.8 kDa protein showed a positive correlation with the sensitivity to LY294002, the 11.6 kDa protein showed a negative correlation with that of the LY294002. The 11.6 kDa protein was purified chromatographically, and was identified by SELDI-TOF MS as the ribosomal P2 protein, which possesses two prospective phosphorylation sites. These results suggested that the phosphorylation status of the ribosomal P2 was responsible for determining the sensitivity to LY294002, and that the ribosomal P2 could be a potential biomarker for predicting chemosensitivity.     

Beyond the Matrix-Assisted Laser Desorption Ionization (MALDI) Biotyping Workflow: in Search of Microorganism-Specific Tryptic Peptides Enabling Discrimination of Subspecies

A well-accepted method for identification of microorganisms uses matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) coupled to analysis software which identifies and classifies the organism according to its ribosomal protein spectral profile. The method, called MALDI biotyping, is widely used in clinical diagnostics and has partly replaced conventional microbiological techniques such as biochemical identification due to its shorter time to result (minutes for MALDI biotyping versus hours or days for classical phenotypic or genotypic identification). Besides its utility for identifying bacteria, MS-based identification has been shown to be applicable also to yeasts and molds. A limitation to this method, however, is that accurate identification is most reliably achieved on the species level on the basis of reference mass spectra, making further phylogenetic classification unreliable. Here, it is shown that combining tryptic digestion of the acid/organic solvent extracted (classical biotyping preparation) and resolubilized proteins, nano-liquid chromatography (nano-LC), and subsequent identification of the peptides by MALDI-tandem TOF (MALDI-TOF/TOF) mass spectrometry increases the discrimination power to the level of subspecies. As a proof of concept, using this targeted proteomics workflow, we have identified subspecies-specific biomarker peptides for three Salmonella subspecies, resulting in an extension of the mass range and type of proteins investigated compared to classical MALDI biotyping. This method therefore offers rapid and cost-effective identification and classification of microorganisms at a deeper taxonomic level.     

Protocol for the purification of proteins from biological extracts for identification by mass spectrometry

When a protein signal is selected by mass spectrometry as being a potential biomarker, it is necessary to formally identify it. This process involves separation of the protein in question and its identification by either peptide fingerprinting or tandem mass spectrometry sequencing. In the following pages, a simple and rapid protocol is described. Basically, the protocol consists of an initial rational selection of a few sorbents followed by alignment of these as a series of columns to obtain the purified target protein. This preparation is then submitted to electrophoresis, the band is excised and the trypsin digest is analyzed by either mass spectrometry (mass fingerprinting approach) or by LC-MS/MS (sequencing). The development of the process takes only a few days. Experimental data for the isolation and identification of proteins are discussed and two examples are shown.     

Rapid discrimination of Bacillus anthracis from other members of the B. cereus group by mass and sequence of "intact" small acid soluble proteins (SASPs) using mass spectrometry

The intentional contamination of buildings, e.g. anthrax in the bioterrorism attacks of 2001, demonstrated that the population can be affected rapidly and lethally if the appropriate treatment is not provided at the right time. Molecular approaches, primarily involving PCR, have proved useful in characterizing "white powders" used in these attacks as well as isolated organisms. However there is a need for a simpler approach, which does not involve temperamental reagents (e.g. enzymes and primers) which could potentially be used by first responders. It is demonstrated here that small acid-soluble proteins (SASPs), located in the core region of Bacillus spores, are reliable biomarkers for identification. The general strategy used in this study was to measure the molecular weight (MW) of an intact SASP by electrospray ionization mass spectrometry (ESI MS) followed by generation of sequence-specific information by ESI MS/MS (tandem mass spectrometry). A prominent SASP of mass 6679 was present in all B. anthracis strains. For B. cereus and B. thuringiensis strains the SASP had a mass of 6712. This represents a two amino acid substitution (serine to alanine; phenylalanine to tyrosine). The only SASP present in the B. anthracis genome consistent with this sequence is encoded by the gene ssB. This protein has a predicted mass of 6810, presumably post-translational processing leads to loss of methionine (mass 131) generating a SASP of mass 6679. This study showed that intact SASPs can be used as a biomarker for identification of B. anthracis; the protocol is simple and rapid. Extrapolation of this approach might prove important for real-time biodetection.