Application of 2D-DIGE and iTRAQ Workflows to Analyze CSF in Gliomas.

Proteomics is an indispensable tool for disease biomarker discovery. It is widely used for the analysis of biological fluids such as cerebrospinal fluid (CSF), blood, and saliva, which further aids in our understanding of disease incidence and progression. CSF is often the biospecimen of choice in case of intracranial tumors, as rapid changes in the tumor microenvironment can be easily assessed due to its close proximity to the brain. On the contrary studies comprising of serum or plasma samples do not truly reflect the underlying molecular alterations due to the presence of protective blood-brain barrier. We have described in here the detailed workflows for two advanced proteomics techniques, namely, 2D-DIGE (two-dimensional difference in-gel electrophoresis) and iTRAQ (isobaric tag for relative and absolute quantitation), for CSF analysis. Both of these techniques are very sensitive and widely used for quantitative proteomics analysis.

Clinical biomarker discovery by SWATH-MS based label-free quantitative proteomics: impact of criteria for identification of differentiators and data normalization method.

BACKGROUND: SWATH-MS has emerged as the strategy of choice for biomarker discovery due to the proteome coverage achieved in acquisition and provision to re-interrogate the data. However, in quantitative analysis using SWATH, each sample from the comparison group is run individually in mass spectrometer and the resulting inter-run variation may influence relative quantification and identification of biomarkers. Normalization of data to diminish this variation thereby becomes an essential step in SWATH data processing. In most reported studies, data normalization methods used are those provided in instrument-based data analysis software or those used for microarray data. This study, for the first time provides an experimental evidence for selection of normalization method optimal for biomarker identification. METHODS: The efficiency of 12 normalization methods to normalize SWATH-MS data was evaluated based on statistical criteria in 'Normalyzer'-a tool which provides comparative evaluation of normalization by different methods. Further, the suitability of normalized data for biomarker discovery was assessed by evaluating the clustering efficiency of differentiators, identified from the normalized data based on p-value, fold change and both, by hierarchical clustering in Genesis software v.1.8.1. RESULTS: Conventional statistical criteria identified VSN-G as the optimal method for normalization of SWATH data. However, differentiators identified from VSN-G normalized data failed to segregate test and control groups. We thus assessed data normalized by eleven other methods for their ability to yield differentiators which segregate the study groups. Datasets in our study demonstrated that differentiators identified based on p-value from data normalized with Loess-R stratified the study groups optimally. CONCLUSION: This is the first report of experimentally tested strategy for SWATH-MS data processing with an emphasis on identification of clinically relevant biomarkers. Normalization of SWATH-MS data by Loess-R method and identification of differentiators based on p-value were found to be optimal for biomarker discovery in this study. The study also demonstrates the need to base the choice of normalization method on the application of the data.

Calibration Using a Single-Point External Reference Material Harmonizes Quantitative Mass Spectrometry Proteomics Data between Platforms and Laboratories.

Mass spectrometry (MS) measurements are not inherently calibrated. Researchers use various calibration methods to assign meaning to arbitrary signal intensities and improve precision. Internal calibration (IC) methods use internal standards (IS) such as synthesized or recombinant proteins or peptides to calibrate MS measurements by comparing endogenous analyte signal to the signal from known IS concentrations spiked into the same sample. However, recent work suggests that using IS as IC introduces quantitative biases that affect comparison across studies because of the inability of IS to capture all sources of variation present throughout an MS workflow. Here, we describe a single-point external calibration strategy to calibrate signal intensity measurements to a common reference material, placing MS measurements on the same scale and harmonizing signal intensities between instruments, acquisition methods, and sites. We demonstrate data harmonization between laboratories and methodologies using this generalizable approach.

Evaluation of NCI-7 Cell Line Panel as a Reference Material for Clinical Proteomics.

Reference materials are vital to benchmarking the reproducibility of clinical tests and essential for monitoring laboratory performance for clinical proteomics. The reference material utilized for mass spectrometric analysis of the human proteome would ideally contain enough proteins to be suitably representative of the human proteome, as well as exhibit a stable protein composition in different batches of sample regeneration. Previously, The Clinical Proteomic Tumor Analysis Consortium (CPTAC) utilized a PDX-derived comparative reference (CompRef) materials for the longitudinal assessment of proteomic performance; however, inherent drawbacks of PDX-derived material, including extended time needed to grow tumors and high level of expertise needed, have resulted in efforts to identify a new source of CompRef material. In this study, we examined the utility of using a panel of seven cancer cell lines, NCI-7 Cell Line Panel, as a reference material for mass spectrometric analysis of human proteome. Our results showed that not only is the NCI-7 material suitable for benchmarking laboratory sample preparation methods, but also NCI-7 sample generation is highly reproducible at both the global and phosphoprotein levels. In addition, the predicted genomic and experimental coverage of the NCI-7 proteome suggests the NCI-7 material may also have applications as a universal standard proteomic reference.

Standardization approaches in absolute quantitative proteomics with mass spectrometry.

Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and elemental) proteomics is provided in this review.

Human Prestin: A Candidate PE1 Protein Lacking Stringent Mass Spectrometric Evidence?

The evidence that any protein exists in the Human Proteome Project (HPP; protein evidence 1 or PE1) has revolved primarily (although not exclusively) around mass spectrometry (MS) (93% of PE1 proteins have MS evidence in the latest neXtProt release), with robust and stringent, well-curated metrics that have served the community well. This has led to a significant number of proteins still considered "missing" (i.e., PE2-4). Many PE2-4 proteins have MS evidence of unacceptable quality (small or not enough unitypic peptides and unacceptably high protein/peptide FDRs), transcriptomic, or antibody evidence. Here we use a Chromosome 7 PE2 example called Prestin to demonstrate that clear and robust criteria/metrics need to be developed for proteins that may not or cannot produce clear-cut MS evidence while possessing significant non-MS evidence, including disease-association data. Many of the PE2-4 proteins are inaccessible, spatiotemporally expressed in a limited way, or expressed at such a very low copy number as to be unable to be detected by current MS methodologies. We propose that the HPP community consider and lead a communal initiative to accelerate the discovery and characterization of these types of "missing" proteins.

Proof-of-Concept Workflow for Establishing Reference Intervals of Human Urine Proteome for Monitoring Physiological and Pathological Changes.

Urine as a true non-invasive sampling source holds great potential for biomarker discovery. While approximately 2000 proteins can be detected by mass spectrometry in urine from healthy people, the amount of these proteins vary considerably. A systematic evaluation of a large number of samples is needed to determine the range of the variations. Current biomarker studies often measure limited number of urine samples in the discovery phase, which makes it difficult to determine whether proteins differentially expressed between control and disease groups represent actual difference, or are just physiological variations among the individuals, leads to failures in the validation phase with the increased sample numbers. Here, we report a streamlined workflow with capacity of measuring 8 urine proteomes per day at the coverage of >1500 proteins. With this workflow, we evaluated variations in 497 urine proteomes from 167 healthy donors, establishing reference intervals (RIs) that covered urine protein variations. We demonstrated that RIs could be used to monitor physiological changes by detecting transient outlier proteins. Furthermore, we provided a RIs-based algorithm for biomarker discovery and validation to screen for diseases such as cancer. This study provided a proof-of-principle workflow for the use of urine proteome for health monitoring and disease screening.

DOSCATs: Double standards for protein quantification.

The two most common techniques for absolute protein quantification are based on either mass spectrometry (MS) or on immunochemical techniques, such as western blotting (WB). Western blotting is most often used for protein identification or relative quantification, but can also be deployed for absolute quantification if appropriate calibration standards are used. MS based techniques offer superior data quality and reproducibility, but WB offers greater sensitivity and accessibility to most researchers. It would be advantageous to apply both techniques for orthogonal quantification, but workflows rarely overlap. We describe DOSCATs (DOuble Standard conCATamers), novel calibration standards based on QconCAT technology, to unite these platforms. DOSCATs combine a series of epitope sequences concatenated with tryptic peptides in a single artificial protein to create internal tryptic peptide standards for MS as well as an intact protein bearing multiple linear epitopes. A DOSCAT protein was designed and constructed to quantify five proteins of the NF-κB pathway. For three target proteins, protein fold change and absolute copy per cell values measured by MS and WB were in excellent agreement. This demonstrates that DOSCATs can be used as multiplexed, dual purpose standards, readily deployed in a single workflow, supporting seamless quantitative transition from MS to WB.

Evaluating the Characteristics of Reporter Ion Signal Acquired in the Orbitrap Analyzer for Isobaric Mass Tag Proteome Quantification Experiments.

Multiplexed quantification with isobaric chemical tags (e.g., TMT, iTRAQ) provides a robust and efficient means to comparatively examine proteome dynamics between several biological states using a mass spectrometer (MS). The quantitative nature of isobaric tags necessitates strict validation of the observed ion signals in the chosen MS detector before differential patterns are extracted between biological states. We present an in-depth analysis of isobaric tag data acquired on current generation Orbitrap MS hardware to illustrate pitfalls in acquisition settings that can negatively impact results. We establish, for the first time, the presence of a notch, a region of no observed values, in the reporter ion distributions from isobaric-labeled peptide mixtures acquired on these instruments. We determine that this notch is present in published data across a wide range of instruments of the same or different type and is isolated to the Orbitrap mass analyzer. We demonstrate that the impact of the notch can be minimized using manipulations of Orbitrap scan parameters and on-column injection amounts. Lastly, using a mixture of synthetic standard peptides we investigated the impact on identification rates and quantification precision. Together, these data highlight an important phenomenon that negatively impacts peptide identification and quantification in the Orbitrap analyzer as well as outlining guidelines to follow to ensure minimization of MS-induced artifacts in isobaric tag experiments resulting from the notch.