A systematic evaluation of normalization methods in quantitative label-free proteomics

To date, mass spectrometry (MS) data remain inherently biased as a result of reasons ranging from sample handling to differences caused by the instrumentation. Normalization is the process that aims to account for the bias and make samples more comparable. The selection of a proper normalization method is a pivotal task for the reliability of the downstream analysis and results. Many normalization methods commonly used in proteomics have been adapted from the DNA microarray techniques. Previous studies comparing normalization methods in proteomics have focused mainly on intragroup variation. In this study, several popular and widely used normalization methods representing different strategies in normalization are evaluated using three spike-in and one experimental mouse label-free proteomic data sets. The normalization methods are evaluated in terms of their ability to reduce variation between technical replicates, their effect on differential expression analysis and their effect on the estimation of logarithmic fold changes. Additionally, we examined whether normalizing the whole data globally or in segments for the differential expression analysis has an effect on the performance of the normalization methods. We found that variance stabilization normalization (Vsn) reduced variation the most between technical replicates in all examined data sets. Vsn also performed consistently well in the differential expression analysis. Linear regression normalization and local regression normalization performed also systematically well. Finally, we discuss the choice of a normalization method and some qualities of a suitable normalization method in the light of the results of our evaluation.

Development of an LC-MS/MS peptide mapping protocol for the NISTmAb

Peptide mapping is a component of the analytical toolbox used within the biopharmaceutical industry to aid in the identity confirmation of a protein therapeutic and to monitor degradative events such as oxidation or deamidation. These methods offer the advantage of providing site-specific information regarding post-translational and chemical modifications that may arise during production, processing or storage. A number of such variations may also be induced by the sample preparation methods themselves which may confound the ability to accurately evaluate the true modification levels. One important focus when developing a peptide mapping method should therefore be the use of sample preparation conditions that will minimize the degree of artificial modifications induced. Unfortunately, the conditions that are amenable to effective reduction, alkylation and digestion are often the same conditions that promote unwanted modifications. Here we describe the optimization of a tryptic digestion protocol used for peptide mapping of the NISTmAb IgG1κ which addresses the challenge of balancing maximum digestion efficiency with minimum artificial modifications. The parameters on which we focused include buffer concentration, digestion time and temperature, as well as the source and type of trypsin (recombinant vs. pancreatic; bovine vs porcine) used. Using the optimized protocol we generated a peptide map of the NISTmAb which allowed us to confirm its identity at the level of primary structure. Graphical abstract Peptide map of the NISTmAb RM 8671 monoclonal antibody. Tryptic digestion was performed using an optimized protocol and followed by LC-UV-MS analysis. The trace represents the total ion chromatogram. Each peak was mapped to peptides identified using mass spectrometry data.

The NISTmAb Reference Material 8671 value assignment, homogeneity, and stability

The NISTmAb Reference Material (RM) 8671 is intended to be an industry standard monoclonal antibody for pre-competitive harmonization of best practices and designing next generation characterization technologies for identity, quality, and stability testing. It must therefore embody the quality and characteristics of a typical biopharmaceutical product and be available long-term in a stable format with consistent product quality attributes. A stratified sampling and analysis plan using a series of qualified analytical and biophysical methods is described that assures RM 8671 meets these criteria. Results for the first three lots of RM 8671 highlight the consistency of material attributes with respect to size, charge, and identity. RM 8671 was verified to be homogeneous both within and between vialing lots, demonstrating the robustness of the lifecycle management plan. It was analyzed in concert with the in-house primary sample 8670 (PS 8670) to provide a historical link to this seminal material. RM 8671 was verified to be fit for its intended purpose as a technology innovation tool, external system suitability control, and cross-industry harmonization platform. Graphical abstract The NISTmAb Reference Material (RM) 8671 is intended to be an industry standard monoclonal antibody for pre-competitive harmonization of best practices and designing next generation characterization technologies for identity, quality, and stability testing.

Determination of ¹⁵N-incorporation into plant proteins and their absolute quantitation: a new tool to study nitrogen flux dynamics and protein pool sizes elicited by plant-herbivore interactions

Herbivory leads to changes in the allocation of nitrogen among different pools and tissues; however, a detailed quantitative analysis of these changes has been lacking. Here, we demonstrate that a mass spectrometric data-independent acquisition approach known as LC-MS(E), combined with a novel algorithm to quantify heavy atom enrichment in peptides, is able to quantify elicited changes in protein amounts and (15)N flux in a high throughput manner. The reliable identification/quantitation of rabbit phosphorylase b protein spiked into leaf protein extract was achieved. The linear dynamic range, reproducibility of technical and biological replicates, and differences between measured and expected (15)N-incorporation into the small (SSU) and large (LSU) subunits of ribulose-1,5-bisphosphate-carboxylase/oxygenase (RuBisCO) and RuBisCO activase 2 (RCA2) of Nicotiana attenuata plants grown in hydroponic culture at different known concentrations of (15)N-labeled nitrate were used to further evaluate the procedure. The utility of the method for whole-plant studies in ecologically realistic contexts was demonstrated by using (15)N-pulse protocols on plants growing in soil under unknown (15)N-incorporation levels. Additionally, we quantified the amounts of lipoxygenase 2 (LOX2) protein, an enzyme important in antiherbivore defense responses, demonstrating that the approach allows for in-depth quantitative proteomics and (15)N flux analyses of the metabolic dynamics elicited during plant-herbivore interactions.

Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.

Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.

Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.

High efficiency and quantitatively reproducible protein digestion by trypsin-immobilized magnetic microspheres

Aldehyde- and NHS-activated magnetic microspheres were used to immobilize trypsin (CHO-trypsin and NHS-trypsin), and their performance for protein digestion was evaluated by reversed phase liquid chromatography-electrospray ionization-tandem mass spectrometry using an LTQ Orbitrap Velos instrument. NHS-trypsin provided greater sequence coverage and identified more peptides for the digestion of bovine serum albumin. A 1-min digestion at room temperature using the immobilized trypsin also identified more peptides (96±6 vs. 48±1) and produced higher sequence coverage (90±2% vs. 75±2%) than traditional free trypsin digestion for 12h at 37 °C. Analysis of 15 nM (0.001 mg/mL) BSA digested by NHS-trypsin in 1 min at room temperature consistently yielded one detected peptide; 150 nM BSA generated 22 peptides. Peptide intensity and protein spectral count were used to evaluate the run-to-run digestion reproducibility of NHS-trypsin with a three-protein-mixture. Three high intensity peptides for each protein generated intensity ratios from 0.70 to 1.09 and spectral count ratios from 0.78 to 1.18. Finally, RAW 264.7 cell lysates were digested by NHS-trypsin for 10 min and 30 min at room temperature, 604 and 697 protein groups, respectively, were identified by RPLC-ESI-MS/MS, with a peptide false discovery rate of less than 1%. Digestion by solution phase trypsin for 12h at 37 °C resulted in identification of 878 protein groups.

Integration of high accuracy N-terminus identification in peptide sequencing and comparative protein analysis via isothiocyanate-based isotope labeling reagent with ESI ion-trap TOF MS

A multifunctional isothiocyanate-based isotope labeling reagent, [d (0)]-/[d (6)]-4,6-dimethoxy pyrimidine-2-isothiocyanate (DMPITC), has been developed for accurate N-terminus identification in peptide sequencing and comparative protein analysis by ESI Ion-trap TOF mass spectrometry. In contrast with the conventional labeling reagent phenyl isothiocyanate (PITC), DMPITC showed more desirable properties such as rapid labeling, sensitivity enhancement, and facilitating peptide sequencing. More significantly, DMPITC-based labeling strategy possessed the capacity of higher reliable N-terminus identification owning to the high-yield b(1) ion combined with the isotope validation of 6 Da. Meanwhile, it also showed potential in differentiating isomeric residues of leucine and isoleucine at N-terminus on the basis of the relative abundance ratios between the fragment ions of their respective b(1) ions. The strategy not only allows accurate interpretation for peptide but also ensures rapid and sensitive comparative analysis for protein by direct MS analysis. Using trypsin-digested bovine serum albumin (BSA), both peptide N-terminus identification and quantitative analysis were accomplished with high accuracy, efficiency, and reproducibility. The application of DMPITC-based labeling strategy is expected to serve as a promising tool for proteome research.

High-throughput proteomics processing of proteins in polyacrylamide in a multiwell format

Processing multiple protein samples from polyacrylamide at significant sensitivity represents a major chokepoint for raising the success rate in high-volume protein identification projects. A multiwell filterplate method for processing proteins in polyacrylamide was optimized for sensitivity using a protein standard. The results demonstrate this process to be a reliable and reproducible method over a range of gel loadings and suitable for the identification of proteins near the threshold of silver stain. This high-throughput manual method requires a minimum of specialized equipment, and can be performed disconnected from a proteomics infrastructure for the preparation of mass spectrometry-ready samples.

Optimization and Use of Peptide Mass Measurement Accuracy in Shotgun Proteomics

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.

[Establishment of diagnostic model of cerebrospinal protein fingerprint pattern for glioma and its clinical application]

OBJECTIVE

To establish the diagnostic model of cerebrospinal protein profile for gliomas by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and bioinformatics.

METHODS

Seventy-five samples of cerebrospinal fluid from patients with gliomas, benign brain tumors and mild brain traumas were collected. A total of 50 samples from gliomas and non-brain-tumors were divided into training sets (33 cases including 17 gliomas and 16 non-brain-tumors) and testing sets (17 cases including 5 gliomas and 12 non-brain-tumors). The cerebrospinal proteins bound to H4 chip were detected by SELDI-TOF MS, the profiles of cerebrospinal protein were gained and then analyzed with artificial neural network algorithm (ANN); and the diagnostic model of cerebrospinal protein profiles for differentiating gliomas from non-brain-tumors was established. Forty-seven of cerebrospinal samples of gliomas and benign brain tumors were divided into training sets (31 cases including 13 gliomas and 18 benign brain tumors) and testing sets (16 cases including 9 gliomas and 7 benign brain tumors), the diagnostic model of cerebrospinal protein profiles for differentiating gliomas from benign brain tumors was established based on the same method. The support vector machine (SVM) algorithm was also used for evaluation, both results were very similar, but the result derived from ANN was more stable than that from SVM.

RESULT

The diagnostic model of cerebrospinal protein profiles for differentiating gliomas from non-brain-tumors was established and was challenged with the test set randomly, the sensitivity and specificity were 100% and 91.7%, respectively. The cerebrospinal protein profiling model for differentiating gliomas from benign brain tumors was also developed and was challenged with the test set randomly, the sensitivity and specificity were 88.9%, and 100%, respectively.

CONCLUSION

The technology of SELDI-TOF MS which combined with analysis tools of bioinformatics is a novel effective method for screening and identifying tumor biomarkers of gliomas and it may provide a new approach for the clinical diagnosis of glioma.

Normalization of relative peptide ratios derived from in-gel digests: applications to protein variant analysis at the peptide level

The ability to detect protein variants and post-translational modifications by mass spectrometry has become increasingly important. Unfortunately, the ability to detect variants in large intact proteins (>80,000 Da) is limited. Even in the analysis of smaller proteins, algorithms are required to determine the presence of a 2 Da mass shift in an intact 13 kDa protein because the isotopic distribution of the multiply charged ions of the variant overlaps the wild-type distribution. Fortunately, most modern instruments are capable of detecting variants in tryptic peptides derived from intact proteins. If a single common variant protein is known, the presence of a variant tryptic peptide can be easily demonstrated. A more difficult issue is the case where a multiplicity of peptides with multiple amino acid substitutions can be associated with pathology. In these cases a decrease in the relative amount of a variant peptide relative to other internal tryptic fragments would be diagnostic. However, the variability associated with the analysis of in-gel or solution digests of proteins, related to efficiencies in digestion, extraction and ionization, confounds variant analysis at the peptide level. A strategy was developed to normalize for this variability by utilizing multiple isotopically labeled internal standards for multiple peptides derived from the same protein. Erythrocyte spectrin from 36 normal and 25 abnormal osmotic fragility samples was analyzed as a test case. Three isotopically labeled target peptides comprising the alpha/beta-spectrin self-association sites were added to purified digested alpha-spectrin. The utilization of multiple internal standards demonstrates the capability to normalize for sample variability due to ionization efficiency, solvent effects, digestion and extraction efficiency.

4SCOPmap: automated assignment of protein structures to evolutionary superfamilies

Background

Inference of remote homology between proteins is very challenging and remains a prerogative of an expert. Thus a significant drawback to the use of evolutionary-based protein structure classifications is the difficulty in assigning new proteins to unique positions in the classification scheme with automatic methods. To address this issue, we have developed an algorithm to map protein domains to an existing structural classification scheme and have applied it to the SCOP database.

Results

The general strategy employed by this algorithm is to combine the results of several existing sequence and structure comparison tools applied to a query protein of known structure in order to find the homologs already classified in SCOP database and thus determine classification assignments. The algorithm is able to map domains within newly solved structures to the appropriate SCOP superfamily level with ~95% accuracy. Examples of correctly mapped remote homologs are discussed. The algorithm is also capable of identifying potential evolutionary relationships not specified in the SCOP database, thus helping to make it better. The strategy of the mapping algorithm is not limited to SCOP and can be applied to any other evolutionary-based classification scheme as well. SCOPmap is available for download.

Conclusion

The SCOPmap program is useful for assigning domains in newly solved structures to appropriate superfamilies and for identifying evolutionary links between different superfamilies.

Identification of cross-linked peptides for protein interaction studies using mass spectrometry and 18O labeling

A new method is presented to screen proteolytic mass maps of cross-linked protein complexes for the presence of cross-linked peptides and for the verification of proposed structures. On the basis of the incorporation of 18O from isotopically enriched water into the C-termini of proteolytic peptides, cross-linked peptides are readily distinguished in mass spectra by a characteristic 8 amu shift. This is due to the incorporation of two 18O atoms in each C-terminus, so that normal and surface-labeled peptides shift 4 amu and cross-linked peptides containing two C-termini will shift 8 amu compared with their unlabeled counterparts. The method is fast, sensitive, and reliable and can be combined with any available cross-linking reagent and a wide range of proteolytic agents. As proof of principle, we successfully applied the method to a complex of two DNA repair proteins (Rad18-Rad6) and identified the interaction domain.

Statistical validation of reproducibility of HPLC peptide mapping for the identity of an investigational drug compound based on principal component analysis

Peptide mapping is a key analytical method for studying the primary structure of proteins. The sensitivity of the peptide map to even the smallest change in the covalent structure of the protein makes it a valuable "fingerprint" for identity testing and process monitoring. We recently conducted a full method validation study of an optimized reverse-phase high-performance liquid chromatography (RP-HPLC) tryptic map of a therapeutic anti-CD4 monoclonal antibody. We have used this method routinely for over a year to test production lots for clinical trials and to support bioprocess development. One of the difficulties in the validation of the peptide mapping method is the lack of proper quantitative measures of its reproducibility. A reproducibility study may include method and system precision study, ruggedness study, and robustness study. In this paper, we discuss the use of principal component analysis (PCA) to quantitate peptide maps properly using its projected scores on the reduced dimensions. This approach allowed us not only to summarize the reproducibility study properly, but also to use the method as a diagnostic tool to investigate any troubles in the reproducibility validation process.

Sample preparation for peptide mapping--A pharmaceutical quality-control perspective

In quality control of therapeutic proteins peptide mapping is used for confirmation of primary structure and detection of posttranslational modifications. The demands put on the experimental procedure are therefore different than in the case of determination of an unknown protein structure. It is here recognized that a peptide-mapping method for quality control of proteins should be inert (not induce or revert modifications), general, robust, and allow a high sample throughput. The steps prior to the separation of the generated peptides are identified as crucial for meeting these demands. This includes denaturation, reduction, alkylation, buffer exchange, solubilization, and digestion. A critical review of the literature regarding these steps is presented. Relevant options in all steps are experimentally evaluated. Novel approaches are developed for many of the steps. The result is a sample preparation procedure that essentially meets the stated demands.

Improved peptide mapping using phytic acid as ion-pairing buffer additive in capillary electrophoresis

By digestion of the highly basic polypeptide aprotinin or bovine pancreatic trypsin inhibitor (BPTI) with endoproteinase Lys-C after unfolding, reduction and pyridylethylation, five fragments are obtained. These fragments are separated by free solution capillary electrophoresis using a phosphate buffer at neutral pH. The effect of the ion-pairing buffer additive phytic acid on the separation was investigated. It is shown that phytic acid through ion-pair formation influences the mobility of only those peptide fragments having a net positive charge at the pH of the separation buffer. The affinity of phytic acid to the peptides correlates with their isoelectric point and the charge to mass ratios. Hence, by changing the concentration of phytic acid, it is possible to manipulate the migration order and the separation of the peptides.