Label-free peptide profiling of Orbitrap™ full mass spectra

BACKGROUND

We developed a new version of the open source software package Peptrix that can yet compare large numbers of Orbitrap™ LC-MS data. The peptide profiling results for Peptrix on MS1 spectra were compared with those obtained from a small selection of open source and commercial software packages: msInspect, Sieve™ and Progenesis™. The properties compared in these packages were speed, total number of detected masses, redundancy of masses, reproducibility in numbers and CV of intensity, overlap of masses, and differences in peptide peak intensities. Reproducibility measurements were taken for the different MS1 software applications by measuring in triplicate a complex peptide mixture of immunoglobulin on the Orbitrap™ mass spectrometer. Values of peptide masses detected from the high intensity peaks of the MS1 spectra by peptide profiling were verified with values of the MS2 fragmented and sequenced masses that resulted in protein identifications with a significant score.

FINDINGS

Peptrix finds about the same number of peptide features as the other packages, but peptide masses are in some cases approximately 5 to 10 times less redundant present in the peptide profile matrix. The Peptrix profile matrix displays the largest overlap when comparing the number of masses in a pair between two software applications. The overlap of peptide masses between software packages of low intensity peaks in the spectra is remarkably low with about 50% of the detected masses in the individual packages. Peptrix does not differ from the other packages in detecting 96% of the masses that relate to highly abundant sequenced proteins. MS1 peak intensities vary between the applications in a non linear way as they are not processed using the same method.

CONCLUSIONS

Peptrix is capable of peptide profiling using Orbitrap™ files and finding differential expressed peptides in body fluid and tissue samples. The number of peptide masses detected in Orbitrap™ files can be increased by using more MS1 peptide profiling applications, including Peptrix, since it appears from the comparison of Peptrix with the other applications that all software packages have likely a high false negative rate of low intensity peptide peaks (missing peptides).

Proteomic analysis of human osteoblastic cells: relevant proteins and functional categories for differentiation

Osteoblasts are the bone forming cells, capable of secreting an extracellular matrix with mineralization potential. The exact mechanism by which osteoblasts differentiate and form a mineralized extracellular matrix is presently not fully understood. To increase our knowledge about this process, we conducted proteomics analysis in human immortalized preosteoblasts (SV-HFO) able to differentiate and mineralize. We identified 381 proteins expressed during the time course of osteoblast differentiation. Gene ontology analysis revealed an overrepresentation of protein categories established as important players for osteoblast differentiation, bone formation, and mineralization such as pyrophosphatases. Proteins involved in antigen presentation, energy metabolism and cytoskeleton rearrangement constitute other overrepresented processes, whose function, albeit interesting, is not fully understood in the context of osteoblast differentiation and bone formation. Correlation analysis, based on quantitative data, revealed a biphasic osteoblast differentiation, encompassing a premineralization and a mineralization period. Identified differentially expressed proteins between mineralized and nonmineralized cells include cytoskeleton (e.g., CCT2, PLEC1, and FLNA) and extracellular matrix constituents (FN1, ANXA2, and LGALS1) among others. FT-ICR-MS data obtained for FN1, ANXA2, and LMNA shows a specific regulation of these proteins during the different phases of osteoblast differentiation. Taken together, this study increases our understanding of the proteomics changes that accompany osteoblast differentiation and may permit the discovery of novel modulators of bone formation.

Proteomics comparison of cerebrospinal fluid of relapsing remitting and primary progressive multiple sclerosis

Background

Based on clinical representation of disease symptoms multiple sclerosis (MScl) patients can be divided into two major subtypes; relapsing remitting (RR) MScl (85–90%) and primary progressive (PP) MScl (10–15%). Proteomics analysis of cerebrospinal fluid (CSF) has detected a number of proteins that were elevated in MScl patients. Here we specifically aimed to differentiate between the PP and RR subtypes of MScl by comparing CSF proteins.

Methodology/Principal Findings

CSF samples (n = 31) were handled according to the same protocol for quantitative mass spectrometry measurements we reported previously. In the comparison of PP MScl versus RR MScl we observed a number of differentially abundant proteins, such as protein jagged-1 and vitamin D-binding protein. Protein jagged-1 was over three times less abundant in PP MScl compared to RR MScl. Vitamin D-binding protein was only detected in the RR MScl samples. These two proteins were validated by independent techniques (western blot and ELISA) as differentially abundant in the comparison between both MScl types.

Conclusions/Significance

The main finding of this comparative study is the observation that the proteome profiles of CSF in PP and RR MScl patients overlap to a large extent. Still, a number of differences could be observed. Protein jagged-1 is a ligand for multiple Notch receptors and involved in the mediation of Notch signaling. It is suggested in literature that the Notch pathway is involved in the remyelination of MScl lesions. Aberration of normal homeostasis of Vitamin D, of which approximately 90% is bound to vitamin D-binding protein, has been widely implicated in MScl for some years now. Vitamin D directly and indirectly regulates the differentiation, activation of CD4+ T-lymphocytes and can prevent the development of autoimmune processes, and so it may be involved in neuroprotective elements in MScl.

Quantitative matrix-assisted laser desorption ionization-fourier transform ion cyclotron resonance (MALDI-FT-ICR) peptide profiling and identification of multiple-sclerosis-related proteins

We introduce a matrix-assisted laser desorption ionization-Fourier transform ion cyclotron resonance (MALDI-FT-ICR) method for quantitative peptide profiling, using peak height as a measure for abundance. Relative standard deviations in peak height of peptides spiked over 3 orders of magnitude in concentration were below 10% and allowed for accurate comparisons between multiple sclerosis and controls. Application on a set of 163 cerebrospinal fluid (CSF) samples showed significantly differential abundant peptides, which were subsequently identified into proteins (e.g., chromogranin A, clusterin, and complement C3).

Multiple sclerosis-related proteins identified in cerebrospinal fluid by advanced mass spectrometry

A total of 164 cerebrospinal fluid (CSF) samples taken from neurological patients were classed into four groups according to the clinical diagnosis: multiple sclerosis (MScl, n = 44), clinically isolated syndrome of demyelination (CIS, n = 40), other inflammatory neurological disease (OIND, n = 26) and other neurological disease (OND, n = 54). After tryptic digestion, the samples were measured by MALDI-TOF MS. Spectra were analyzed using the R-project software package, in which a peak detection algorithm was developed. Subsequently, the peak lists were compared based on ranked data (non-parametric). Significant differences were observed in the comparisons of MScl vs. OND and CIS vs. OND. The comparisons of MScl vs. OIND, and CIS vs. OIND showed fewer significant differences. No significant differences were found in comparisons MScl vs. CIS and OIND vs. OND. MScl and CIS had strikingly similar profiles, probably a reflection of common pathological mechanisms. Three differentially expressed proteins in the comparison of MScl vs. OND were identified: chromogranin A, a potential marker for neurodegeneration; and two important factors in complement-mediated inflammatory reaction, clusterin and complement C3. CSF chromogranin A levels were confirmed to be significantly elevated in the MScl group using an ELISA.

A software application for comparing large numbers of high resolution MALDI-FTICR MS spectra demonstrated by searching candidate biomarkers for glioma blood vessel formation

BACKGROUND

A Java application is presented, which compares large numbers (n > 100) of raw FTICR mass spectra from patients and controls. Two peptide profile matrices can be produced simultaneously, one with occurrences of peptide masses in samples and another with the intensity of common peak masses in all the measured samples, using the peak- and background intensities of the raw data. In latter way, more significantly differentially expressed peptides are found between groups than just using the presence or absence in samples of common peak masses. The software application is tested by searching angiogenesis related proteins in glioma by comparing laser capture micro dissected- and enzymatic by trypsin digested tissue sections.

RESULTS

By hierarchical clustering of the presence-absence matrix, it appears that proteins, such as hemoglobin alpha and delta subunit, fibrinogen beta and gamma chain precursor, tubulin specific chaperone A, epidermal fatty acid binding protein, neutrophil gelatinase-associated lipocalin precursor, peptidyl tRNA hydrolase 2 mitochondrial precursor, placenta specific growth hormone, and zinc finger CCHC domain containing protein 13 are significantly different expressed in glioma vessels. The up-regulated proteins in the glioma vessels with respect to the normal vessels determined by the Wilcoxon-Mann-Whitney test on the intensity matrix are vimentin, glial fibrillary acidic protein, serum albumin precursor, annexin A5, alpha cardiac and beta actin, type I cytoskeletal 10 keratin, calcium binding protein p22, and desmin. Peptide masses of calcium binding protein p22, Cdc42 effector protein 3, fibronectin precursor, and myosin-9 are exclusively present in glioma vessels. Some peptide fragments of non-muscular myosin-9 at the C-terminus are strongly up-regulated in the glioma vessels with respect to the normal vessels.

CONCLUSION

The less rigorous than in general used commercial propriety software de-isotope algorithm results in more mono-isotopic peptide masses and consequently more proteins. Centroiding of peptide masses takes place by taking the average over more spectra in the profile matrix. Cytoskeleton proteins and proteins involved in the calcium signaling pathway seem to be most up-regulated in glioma vessels. The finding that peptides at the C-terminus of myosin-9 are up-regulated could be ascribed to splicing or fragmentation by proteases.

Identification of Glioma Neovascularization-related Proteins by Using MALDI-FTMS and Nano-LC Fractionation to Microdissected Tumor Vessels

The identification of angiogenesis-related proteins is important for the development of new antiangiogenic therapies, and such proteins are potential new biomarkers for gliomas. The aim of this study was to identify proteins that are exclusively present in glioma neovasculature and not in the vasculature of normal brain. We combined advanced proteomics techniques to compare the expression profiles of microdissected blood vessels from glioma with blood vessels of normal control brain samples. We measured the enzymatic generated peptide profiles from these microdissected samples by MALDI-FTMS. Subsequently, the samples were fractionated by nano-LC prior to MALDI-TOF/TOF. This combined approach enabled us to identify four proteins that appeared to be exclusively expressed in the glioma blood vessels. Two of these proteins, fibronectin and colligin 2, were validated on tissue sections using specific antibodies. We found that both proteins are present in active angiogenesis in glioma, other neoplasms, and reactive conditions in which neoangiogenesis takes place. This work proves that gel-free mass spectrometric techniques can be used on relatively small numbers of cells generated by microdissection procedures to successfully identify differentially expressed proteins.

A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls

Background

Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest.

Results

A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups.

Conclusion

The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles.