William M. Old

Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics

Measurements of mass spectral peak intensities and spectral counts are promising methods for quantifying protein abundance changes in shotgun proteomic analyses. We describe Serac, software developed to evaluate the ability of each method to quantify relative changes in protein abundance. Dynamic range and linearity using a three-dimensional ion trap were tested using standard proteins spiked into a complex sample. Linearity and good agreement between observed versus expected protein ratios were obtained after normalization and background subtraction of peak area intensity measurements and correction of spectral counts to eliminate discontinuity in ratio estimates. Peak intensity values useful for protein quantitation ranged from 107 to 1011 counts with no obvious saturation effect, and proteins in replicate samples showed variations of less than 2-fold within the 95% range (±2ς) when ≥3 peptides/protein were shared between samples. Protein ratios were determined with high confidence from spectral counts when maximum spectral counts were ≥4 spectra/protein, and replicates showed equivalent measurements well within 95% confidence limits. In further tests, complex samples were separated by gel exclusion chromatography, quantifying changes in protein abundance between different fractions. Linear behavior of peak area intensity measurements was obtained for peptides from proteins in different fractions. Protein ratios determined by spectral counting agreed well with those determined from peak area intensity measurements, and both agreed with independent measurements based on gel staining intensities. Overall spectral counting proved to be a more sensitive method for detecting proteins that undergo changes in abundance, whereas peak area intensity measurements yielded more accurate estimates of protein ratios. Finally these methods were used to analyze differential changes in protein expression in human erythroleukemia K562 cells stimulated under conditions that promote cell differentiation by mitogen-activated protein kinase pathway activation. Protein changes identified with p < 0.1 showed good correlations with parallel measurements of changes in mRNA expression.

Mapping protein post-translational modifications with mass spectrometry

Post-translational modifications of proteins control many biological processes, and examining their diversity is critical for understanding mechanisms of cell regulation. Mass spectrometry is a fundamental tool for detecting and mapping covalent modifications and quantifying their changes. Modern approaches have made large-scale experiments possible, screening complex mixtures of proteins for alterations in chemical modifications. By profiling protein chemistries, biologists can gain deeper insight into biological control. The aim of this review is introduce biologists to current strategies in mass spectrometry–based proteomics that are used to characterize protein post-translational modifications, noting strengths and shortcomings of various approaches.

Functional Proteomics Identifies Targets of Phosphorylation by B-Raf Signaling in Melanoma

Melanoma and other cancers harbor oncogenic mutations in the protein kinase B-Raf, which leads to constitutive activation and dysregulation of MAP kinase signaling. In order to elucidate molecular determinants responsible for B-Raf control of cancer phenotypes, we present a method for phosphoprotein profiling, using negative ionization mass spectrometry to detect phosphopeptides based on their fragment ion signature caused by release of PO(3)(-). The method provides an alternative strategy for phosphoproteomics, circumventing affinity enrichment of phosphopeptides and isotopic labeling of samples. Ninety phosphorylation events were regulated by oncogenic B-Raf signaling, based on their responses to treating melanoma cells with MKK1/2 inhibitor. Regulated phosphoproteins included known signaling effectors and cytoskeletal regulators. We investigated MINERVA/FAM129B, a target belonging to a protein family with unknown category and function, and established the importance of this protein and its MAP kinase-dependent phosphorylation in controlling melanoma cell invasion into three-dimensional collagen matrix.

Mps1 Activation Loop Autophosphorylation Enhances Kinase Activity

The Mps1 protein kinase is required for proper assembly of the mitotic spindle, checkpoint signaling, and several other aspects of cell growth and differentiation. Mps1 regulation is mediated by cell cycle-dependent changes in transcription and protein level. There is also a strong correlation between hyperphosphorylated mitotic forms of Mps1 and increased kinase activity. We investigated the role that autophosphorylation plays in regulating human Mps1 (hMps1) protein kinase activity. Here we report that hyperphosphorylated hMps1 forms are not the only active forms of the kinase. However, autophosphorylation of hMps1 within the activation loop is required for full activity in vitro. Mass spectrometry analysis of de novo synthesized enzyme in Escherichia coli identified autophosphorylation sites at residues Thr675, Thr676, and Thr686, but phosphatase-treated and reactivated enzyme was only phosphorylated on Thr676. Mutation of Thr676 in hMps1 or the corresponding Thr591 residue within yeast Mps1 reduces kinase activity in vitro. We find that overexpression of an hMps1-T676A mutation inhibits centrosome duplication in RPE1 cells. Likewise, yeast cells harboring mps1-T591A as the sole MPS1 allele are not viable. Our data strongly support the conclusion that site-specific Mps1 autophosphorylation within the activation loop is required for full activity in vitro and function in vivo.

Modulation of the G Protein Regulator Phosducin by Ca2+/Calmodulin-dependent Protein Kinase II Phosphorylation and 14-3-3 Protein Binding

Phototransduction is a canonical G protein-mediated cascade of retinal photoreceptor cells that transforms photons into neural responses. Phosducin (Pd) is a Gβγ-binding protein that is highly expressed in photoreceptors. Pd is phosphorylated in dark-adapted retina and is dephosphorylated in response to light. Dephosphorylated Pd binds Gβγ with high affinity and inhibits the interaction of Gβγ with Gα or other effectors, whereas phosphorylated Pd does not. These results have led to the hypothesis that Pd down-regulates the light response. Consequently, it is important to understand the mechanisms of regulation of Pd phosphorylation. We have previously shown that phosphorylation of Pd by cAMP-dependent protein kinase moderately inhibits its association with Gβγ. In this study, we report that Pd was rapidly phosphorylated by Ca2+/calmodulin-dependent kinase II, resulting in 100-fold greater inhibition of Gβγ binding than cAMP-dependent protein kinase phosphorylation. Furthermore, Pd phosphorylation by Ca2+/calmodulin-dependent kinase II at Ser-54 and Ser-73 led to binding of the phosphoserine-binding protein 14-3-3. Importantly, in vivodecreases in Ca2+ concentration blocked the interaction of Pd with 14-3-3, indicating that Ca2+ controls the phosphorylation state of Ser-54 and Ser-73 in vivo. These results are consistent with a role for Pd in Ca2+-dependent light adaptation processes in photoreceptor cells and also suggest other possible physiological functions.

Regulation of Kinetochore Recruitment of Two Essential Mitotic Spindle Checkpoint Proteins by Mps1 Phosphorylation

Mps1 is a protein kinase that plays essential roles in spindle checkpoint signaling. Unattached kinetochores or lack of tension triggers recruitment of several key spindle checkpoint proteins to the kinetochore, which delays anaphase onset until proper attachment or tension is reestablished. Mps1 acts upstream in the spindle checkpoint signaling cascade, and kinetochore targeting of Mps1 is required for subsequent recruitment of Mad1 and Mad2 to the kinetochore. The mechanisms that govern recruitment of Mps1 or other checkpoint proteins to the kinetochore upon spindle checkpoint activation are incompletely understood. Here, we demonstrate that phosphorylation of Mps1 at T12 and S15 is required for Mps1 recruitment to the kinetochore. Mps1 kinetochore recruitment requires its kinase activity and autophosphorylation at T12 and S15. Mutation of T12 and S15 severely impairs its kinetochore association and markedly reduces recruitment of Mad2 to the kinetochore. Our studies underscore the importance of Mps1 autophosphorylation in kinetochore targeting and spindle checkpoint signaling.

Improved Validation of Peptide MS/MS Assignments Using Spectral Intensity Prediction

A major limitation in identifying peptides from complex mixtures by shotgun proteomics is the ability of search programs to accurately assign peptide sequences using mass spectrometric fragmentation spectra (MS/MS spectra). Manual analysis is used to assess borderline identifications; however, it is error-prone and time-consuming, and criteria for acceptance or rejection are not well defined. Here we report a Manual Analysis Emulator (MAE) program that evaluates results from search programs by implementing two commonly used criteria: 1) consistency of fragment ion intensities with predicted gas phase chemistry and 2) whether a high proportion of the ion intensity (proportion of ion current (PIC)) in the MS/MS spectra can be derived from the peptide sequence. To evaluate chemical plausibility, MAE utilizes similarity (Sim) scoring against theoretical spectra simulated by MassAnalyzer software (Zhang, Z. (2004) Prediction of low-energy collision-induced dissociation spectra of peptides. Anal. Chem. 76, 3908–3922) using known gas phase chemical mechanisms. The results show that Sim scores provide significantly greater discrimination between correct and incorrect search results than achieved by Sequest XCorr scoring or Mascot Mowse scoring, allowing reliable automated validation of borderline cases. To evaluate PIC, MAE simplifies the DTA text files summarizing the MS/MS spectra and applies heuristic rules to classify the fragment ions. MAE output also provides data mining functions, which are illustrated by using PIC to identify spectral chimeras, where two or more peptide ions were sequenced together, as well as cases where fragmentation chemistry is not well predicted.

Identification of global ferredoxin interaction networks in Chlamydomonas reinhardtii

Background: Chlamydomonas contains six chloroplast ferredoxins (FDXs) whose function is still unclear. Results: A global FDX interactome was obtained where FDX1 has a predominant role and is the most relevant electron donor to FNR1 and HYDA1. Conclusion: FDXs have distinct but also overlapping function. Significance: We discovered new FDX interaction partners and specific roles for each FDX isoform. Ferredoxins (FDXs) can distribute electrons originating from photosynthetic water oxidation, fermentation, and other reductant-generating pathways to specific redox enzymes in different organisms. The six FDXs identified in Chlamydomonas reinhardtii are not fully characterized in terms of their biological function. In this report, we present data from the following: (a) yeast two-hybrid screens, identifying interaction partners for each Chlamydomonas FDX; (b) pairwise yeast two-hybrid assays measuring FDX interactions with proteins from selected biochemical pathways; (c) affinity pulldown assays that, in some cases, confirm and even expand the interaction network for FDX1 and FDX2; and (d) in vitro NADP+ reduction and H2 photo-production assays mediated by each FDX that verify their role in these two pathways. Our results demonstrate new potential roles for FDX1 in redox metabolism and carbohydrate and fatty acid biosynthesis, for FDX2 in anaerobic metabolism, and possibly in state transition. Our data also suggest that FDX3 is involved in nitrogen assimilation, FDX4 in glycolysis and response to reactive oxygen species, and FDX5 in hydrogenase maturation. Finally, we provide experimental evidence that FDX1 serves as the primary electron donor to two important biological pathways, NADPH and H2 photo-production, whereas FDX2 is capable of driving these reactions at less than half the rate observed for FDX1.

A Simulated MS/MS Library for Spectrum-to-spectrum Searching in Large Scale Identification of Proteins

Identifying peptides from mass spectrometric fragmentation data (MS/MS spectra) using search strategies that map protein sequences to spectra is computationally expensive. An alternative strategy uses direct spectrum-to-spectrum matching against a reference library of previously observed MS/MS that has the advantage of evaluating matches using fragment ion intensities and other ion types than the simple set normally used. However, this approach is limited by the small sizes of the available peptide MS/MS libraries and the inability to evaluate the rate of false assignments. In this study, we observed good performance of simulated spectra generated by the kinetic model implemented in MassAnalyzer (Zhang, Z. (2004) Prediction of low-energy collision-induced dissociation spectra of peptides. Anal. Chem. 76, 3908–3922; Zhang, Z. (2005) Prediction of low-energy collision-induced dissociation spectra of peptides with three or more charges. Anal. Chem. 77, 6364–6373) as a substitute for the reference libraries used by the spectrum-to-spectrum search programs X!Hunter and BiblioSpec and similar results in comparison with the spectrum-to-sequence program Mascot. We also demonstrate the use of simulated spectra for searching against decoy sequences to estimate false discovery rates. Although we found lower score discrimination with spectrum-to-spectrum searches than with Mascot, particularly for higher charge forms, comparable peptide assignments with low false discovery rate were achieved by examining consensus between X!Hunter and Mascot, filtering results by mass accuracy, and ignoring score thresholds. Protein identification results are comparable to those achieved when evaluating consensus between Sequest and Mascot. Run times with large scale data sets using X!Hunter with the simulated spectral library are 7 times faster than Mascot and 80 times faster than Sequest with the human International Protein Index (IPI) database. We conclude that simulated spectral libraries greatly expand the search space available for spectrum-to-spectrum searching while enabling principled analyses and that the approach can be used in consensus strategies for large scale studies while reducing search times.

Spectrum-to-spectrum searching using a proteome-wide spectral library

The unambiguous assignment of tandem mass spectra (MS/MS) to peptide sequences remains a key unsolved problem in proteomics. Spectral library search strategies have emerged as a promising alternative for peptide identification, in which MS/MS spectra are directly compared against a reference library of confidently assigned spectra. Two problems relate to library size. First, reference spectral libraries are limited to rediscovery of previously identified peptides and are not applicable to new peptides, because of their incomplete coverage of the human proteome. Second, problems arise when searching a spectral library the size of the entire human proteome. We observed that traditional dot product scoring methods do not scale well with spectral library size, showing reduction in sensitivity when library size is increased. We show that this problem can be addressed by optimizing scoring metrics for spectrum-to-spectrum searches with large spectral libraries. MS/MS spectra for the 1.3 million predicted tryptic peptides in the human proteome are simulated using a kinetic fragmentation model (MassAnalyzer version2.1) to create a proteome-wide simulated spectral library. Searches of the simulated library increase MS/MS assignments by 24% compared with Mascot, when using probabilistic and rank based scoring methods. The proteome-wide coverage of the simulated library leads to 11% increase in unique peptide assignments, compared with parallel searches of a reference spectral library. Further improvement is attained when reference spectra and simulated spectra are combined into a hybrid spectral library, yielding 52% increased MS/MS assignments compared with Mascot searches. Our study demonstrates the advantages of using probabilistic and rank based scores to improve performance of spectrum-to-spectrum search strategies.