Frank Suits

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.

Blue Matter, an application framework for molecular simulation on blue gene

In this paper we describe the context, architecture, and challenges of Blue Matter, the application framework being developed in conjunction with the science effort within IBMs Blue Gene project. The study of the mechanisms behind protein folding and related topics can require long time simulations on systems with a wide range of sizes and the application supporting these studies must map efficiently onto a large range of parallel partition sizes to optimize scientific throughput for a particular study. The design goals for the Blue Matter architecture include separating the complexities of the parallel implementation on a particular machine from those of the scientific simulation as well as minimizing system environmental dependencies so that running an application within a low overhead kernel with minimal services is possible. We describe some of the parallel decompositions currently being explored that target the first member of the Blue Gene family, BG/L, and present simple performance models for these decompositions that we are using to prioritize our development work. Preliminary results indicate that the high-performance networks on BG/L will allow us to use FFT-based techniques for periodic electrostatics with reasonable speedups on 512-1024 node count partitions even for systems with as few as 5000 atoms.

A Critical Assessment of Feature Selection Methods for Biomarker Discovery in Clinical Proteomics

In this paper, we compare the performance of six different feature selection methods for LC-MS-based proteomics and metabolomics biomarker discovery—t test, the Mann–Whitney–Wilcoxon test (mww test), nearest shrunken centroid (NSC), linear support vector machine–recursive features elimination (SVM-RFE), principal component discriminant analysis (PCDA), and partial least squares discriminant analysis (PLSDA)—using human urine and porcine cerebrospinal fluid samples that were spiked with a range of peptides at different concentration levels. The ideal feature selection method should select the complete list of discriminating features that are related to the spiked peptides without selecting unrelated features. Whereas many studies have to rely on classification error to judge the reliability of the selected biomarker candidates, we assessed the accuracy of selection directly from the list of spiked peptides. The feature selection methods were applied to data sets with different sample sizes and extents of sample class separation determined by the concentration level of spiked compounds. For each feature selection method and data set, the performance for selecting a set of features related to spiked compounds was assessed using the harmonic mean of the recall and the precision (f-score) and the geometric mean of the recall and the true negative rate (g-score). We conclude that the univariate t test and the mww test with multiple testing corrections are not applicable to data sets with small sample sizes (n = 6), but their performance improves markedly with increasing sample size up to a point (n > 12) at which they outperform the other methods. PCDA and PLSDA select small feature sets with high precision but miss many true positive features related to the spiked peptides. NSC strikes a reasonable compromise between recall and precision for all data sets independent of spiking level and number of samples. Linear SVM-RFE performs poorly for selecting features related to the spiked compounds, even though the classification error is relatively low.

The Impact of Delayed Storage on the Measured Proteome and Metabolome of Human Cerebrospinal Fluid

BACKGROUND Because cerebrospinal fluid (CSF) is in close contact with diseased areas in neurological disorders, it is an important source of material in the search for molecular biomarkers. However, sample handling for CSF collected from patients in a clinical setting might not always be adequate for use in proteomics and metabolomics studies. METHODS We left CSF for 0, 30, and 120 min at room temperature immediately after sample collection and centrifugation/removal of cells. At 2 laboratories CSF proteomes were subjected to tryptic digestion and analyzed by use of nano-liquid chromatography (LC) Orbitrap mass spectrometry (MS) and chipLC quadrupole TOF-MS. Metabolome analysis was performed at 3 laboratories by NMR, GC-MS, and LC-MS. Targeted analyses of cystatin C and albumin were performed by LC-tandem MS in the selected reaction monitoring mode. RESULTS We did not find significant changes in the measured proteome and metabolome of CSF stored at room temperature after centrifugation, except for 2 peptides and 1 metabolite, 2,3,4-trihydroxybutanoic (threonic) acid, of 5780 identified peptides and 93 identified metabolites. A sensitive protein stability marker, cystatin C, was not affected. CONCLUSIONS The measured proteome and metabolome of centrifuged human CSF is stable at room temperature for up to 2 hours. We cannot exclude, however, that changes undetectable with our current methodology, such as denaturation or proteolysis, might occur because of sample handling conditions. The stability we observed gives laboratory personnel at the collection site sufficient time to aliquot samples before freezing and storage at -80 °C.

Two-dimensional method for time aligning liquid chromatography-mass spectrometry data.

We describe a new time alignment method that takes advantage of both dimensions of LC-MS data to resolve ambiguities in peak matching while remaining computationally efficient. This approach, Warp2D, combines peak extraction with a two-dimensional correlation function to provide a reliable alignment scoring function that is insensitive to spurious peaks and background noise. One-dimensional alignment methods are often based on the total-ion-current elution profile of the spectrum and are unable to distinguish peaks of different masses. Our approach uses one-dimensional alignment in time, but with a scoring function derived from the overlap of peaks in two dimensions, thereby combining the specificity of two-dimensional methods with the computational performance of one-dimensional methods. The peaks are approximated as two-dimensional Gaussians of varying width. This approximation allows peak overlap (the measure of alignment quality) to be calculated analytically, without computationally intensive numerical integration in two dimensions. To demonstrate the general applicability of Warp2D, we chose a variety of complex samples that have substantial biological and analytical variability, including human serum and urine. We show that Warp2D works well with these diverse sample sets and with minimal tuning of parameters, based on the reduced standard deviation of peak elution times after warping. The combination of high computational speed, robustness with complex samples, and lack of need for detailed tuning makes this alignment method well suited to high-throughput LC-MS studies.

Blue matter: strong scaling of molecular dynamics on blue gene/l

This paper presents strong scaling performance data for the Blue Matter molecular dynamics framework using a novel n-body spatial decomposition and a collective communications technique implemented on both MPI and low level hardware interfaces. Using Blue Matter on Blue Gene/L, we have measured scalability through 16,384 nodes with measured time per time-step of under 2.3 milliseconds for a 43,222 atom protein/lipid system. This is equivalent to a simulation rate of over 76 nanoseconds per day and represents an unprecedented time-to-solution for biomolecular simulation as well as continued speed-up to fewer than three atoms per node. On a smaller, solvated lipid system with 13,758 atoms, we have achieved continued speedups through fewer than one atom per node and less than 2 milliseconds/time-step. On a 92,224 atom system, we have achieved floating point performance of over 1.8 TeraFlops/second on 16,384 nodes. Strong scaling of fixed-size classical molecular dynamics of biological systems to large numbers of nodes is necessary to extend the simulation time to the scale required to make contact with experimental data and derive biologically relevant insights.

Molecular dynamics investigation of the structural properties of phosphatidylethanolamine lipid bilayers

We report a 14 ns microcanonical (NVE) molecular dynamics simulation of a fully hydrated bilayer of 1-stearoyl-2-oleoyl-phosphatidyethanolamine. This study describes the structure of the bilayer in terms of NMR order parameters and radial distribution functions, and compares them to experimental results and simulations of other lipids. A focus of this work is the characterization of the lipid-water interface, particularly the hydrogen bonding network of the phosphatidylethanolamine (PE) headgroups. We find that hydrogen bonding between the primary amine and phosphate groups has a pronounced effect on the structure of PE relative to phosphatidylcholine, and is evident in, for example, the P-N radial distribution functions.

Profiling and Identification of Cerebrospinal Fluid Proteins in a Rat EAE Model of Multiple Sclerosis.

The experimental autoimmune encephalomyelitis (EAE) model resembles certain aspects of multiple sclerosis (MScl), with common features such as motor dysfunction, axonal degradation, and infiltration of T-cells. We studied the cerebrospinal fluid (CSF) proteome in the EAE rat model to identify proteomic changes relevant for MScl disease pathology. EAE was induced in male Lewis rats by injection of myelin basic protein (MBP) together with complete Freunds adjuvant (CFA). An inflammatory control group was injected with CFA alone, and a nontreated group served as healthy control. CSF was collected at day 10 and 14 after immunization and analyzed by bottom-up proteomics on Orbitrap LC-MS and QTOF LC-MS platforms in two independent laboratories. By combining results, 44 proteins were discovered to be significantly increased in EAE animals compared to both control groups, 25 of which have not been mentioned in relation to the EAE model before. Lysozyme C1, fetuin B, T-kininogen, serum paraoxonase/arylesterase 1, glutathione peroxidase 3, complement C3, and afamin are among the proteins significantly elevated in this rat EAE model. Two proteins, afamin and complement C3, were validated in an independent sample set using quantitative selected reaction monitoring mass spectrometry. The molecular weights of the identified differentially abundant proteins indicated an increased transport across the blood-brain barrier (BBB) at the peak of the disease, caused by an increase in BBB permeability.

msCompare: A Framework for Quantitative Analysis of Label-free LC-MS Data for Comparative Candidate Biomarker Studies

Data processing forms an integral part of biomarker discovery and contributes significantly to the ultimate result. To compare and evaluate various publicly available open source label-free data processing workflows, we developed msCompare, a modular framework that allows the arbitrary combination of different feature detection/quantification and alignment/matching algorithms in conjunction with a novel scoring method to evaluate their overall performance. We used msCompare to assess the performance of workflows built from modules of publicly available data processing packages such as SuperHirn, OpenMS, and MZmine and our in-house developed modules on peptide-spiked urine and trypsin-digested cerebrospinal fluid (CSF) samples. We found that the quality of results varied greatly among workflows, and interestingly, heterogeneous combinations of algorithms often performed better than the homogenous workflows. Our scoring method showed that the union of feature matrices of different workflows outperformed the original homogenous workflows in some cases. msCompare is open source software (https://trac.nbic.nl/mscompare), and we provide a web-based data processing service for our framework by integration into the Galaxy server of the Netherlands Bioinformatics Center (http://galaxy.nbic.nl/galaxy) to allow scientists to determine which combination of modules provides the most accurate processing for their particular LC-MS data sets.

Molecular dynamics investigation of dynamical properties of phosphatidylethanolamine lipid bilayers.

We describe the dynamic behavior of a 1-stearoyl-2-oleoyl-phosphatidylethanolamine (SOPE) bilayer from a 20 ns molecular dynamics simulation. The dynamics of individual molecules are characterized in terms of (2)H spin-lattice relaxation rates, nuclear overhauser enhancement spectroscopy (NOESY) cross-relaxation rates, and lateral diffusion coefficients. Additionally, we describe the dynamics of hydrogen bonding through an analysis of hydrogen bond lifetimes and the time evolution of clusters of hydrogen bonded lipids. The simulated trajectory is shown to be consistent with experimental measures of internal, intermolecular, and diffusive motion. Consistent with our analysis of SOPE structure in the companion paper, we see hydrogen bonding dominating the dynamics of the interface region. Comparison of (2)H T(1) relaxation rates for chain methylene segments in phosphatidylcholine and phosphatidylethanolamine bilayers indicates that slower motion resulting from hydrogen bonding extends at least three carbons into the hydrophobic core. NOESY cross-relaxation rates compare well with experimental values, indicating the observed hydrogen bonding dynamics are realistic. Calculated lateral diffusion rates (4 +/ -1 x 10(-8) cm(2)s) are comparable, though somewhat lower than, those determined by pulsed field gradient NMR methods.