Software Lock Mass by Two-Dimensional Minimization of Peptide Mass Errors

Mass accuracy is a key parameter in proteomic experiments, improving specificity, and success rates of peptide identification. Advances in instrumentation now make it possible to routinely obtain high resolution data in proteomic experiments. To compensate for drifts in instrument calibration, a compound of known mass is often employed. This ‘lock mass’ provides an internal mass standard in every spectrum. Here we take advantage of the complexity of typical peptide mixtures in proteomics to eliminate the requirement for a physical lock mass. We find that mass scale drift is primarily a function of the m/z and the elution time dimensions. Using a subset of high confidence peptide identifications from a first pass database search, which effectively substitute for the lock mass, we set up a global mathematical minimization problem. We perform a simultaneous fit in two dimensions using a function whose parameterization is automatically adjusted to the complexity of the analyzed peptide mixture. Mass deviation of the high confidence peptides from their calculated values is then minimized globally as a function of both m/z value and elution time. The resulting recalibration function performs equal or better than adding a lock mass from laboratory air to LTQ-Orbitrap spectra. This ‘software lock mass’ drastically improves mass accuracy compared with mass measurement without lock mass (up to 10-fold), with none of the experimental cost of a physical lock mass, and it integrated into the freely available MaxQuant analysis pipeline (www.maxquant.org)

A high confidence, manually validated human blood plasma protein reference set

<p>Abstract</p> <p>Background</p> <p>The immense diagnostic potential of human plasma has prompted great interest and effort in cataloging its contents, exemplified by the Human Proteome Organization (HUPO) Plasma Proteome Project (PPP) pilot project. Due to challenges in obtaining a reliable blood plasma protein list, HUPO later re-analysed their own original dataset with a more stringent statistical treatment that resulted in a much reduced list of high confidence (at least 95%) proteins compared with their original findings. In order to facilitate the discovery of novel biomarkers in the future and to realize the full diagnostic potential of blood plasma, we feel that there is still a need for an ultra-high confidence reference list (at least 99% confidence) of blood plasma proteins.</p> <p>Methods</p> <p>To address the complexity and dynamic protein concentration range of the plasma proteome, we employed a linear ion-trap-Fourier transform (LTQ-FT) and a linear ion trap-Orbitrap (LTQ-Orbitrap) for mass spectrometry (MS) analysis. Both instruments allow the measurement of peptide masses in the low ppm range. Furthermore, we employed a statistical score that allows database peptide identification searching using the products of two consecutive stages of tandem mass spectrometry (MS3). The combination of MS3 with very high mass accuracy in the parent peptide allows peptide identification with orders of magnitude more confidence than that typically achieved.</p> <p>Results</p> <p>Herein we established a high confidence set of 697 blood plasma proteins and achieved a high 'average sequence coverage' of more than 14 peptides per protein and a median of 6 peptides per protein. All proteins annotated as belonging to the immunoglobulin family as well as all hypothetical proteins whose peptides completely matched immunoglobulin sequences were excluded from this protein list. We also compared the results of using two high-end MS instruments as well as the use of various peptide and protein separation approaches. Furthermore, we characterized the plasma proteins using cellular localization information, as well as comparing our list of proteins to data from other sources, including the HUPO PPP dataset.</p> <p>Conclusion</p> <p>Superior instrumentation combined with rigorous validation criteria gave rise to a set of 697 plasma proteins in which we have very high confidence, demonstrated by an exceptionally low false peptide identification rate of 0.29%.</p

Proteomic profile of KSR1-regulated signalling in response to genotoxic agents in breast cancer

Kinase suppressor of Ras 1 (KSR1) has been implicated in tumorigenesis in multiple cancers, including skin, pancreatic and lung carcinomas. However, our recent study revealed a role of KSR1 as a tumour suppressor in breast cancer, the expression of which is potentially correlated with chemotherapy response. Here, we aimed to further elucidate the KSR1-regulated signalling in response to genotoxic agents in breast cancer. Stable isotope labelling by amino acids in cell culture (SILAC) coupled to high-resolution mass spectrometry (MS) was implemented to globally characterise cellular protein levels induced by KSR1 in the presence of doxorubicin or etoposide. The acquired proteomic signature was compared and GO-STRING analysis was subsequently performed to illustrate the activated functional signalling networks. Furthermore, the clinical associations of KSR1 with identified targets and their relevance in chemotherapy response were examined in breast cancer patients. We reveal a comprehensive repertoire of thousands of proteins identified in each dataset and compare the unique proteomic profiles as well as functional connections modulated by KSR1 after doxorubicin (Doxo-KSR1) or etoposide (Etop-KSR1) stimulus. From the up-regulated top hits, several proteins, including STAT1, ISG15 and TAP1 are also found to be positively associated with KSR1 expression in patient samples. Moreover, high KSR1 expression, as well as high abundance of these proteins, is correlated with better survival in breast cancer patients who underwent chemotherapy. In aggregate, our data exemplify a broad functional network conferred by KSR1 with genotoxic agents and highlight its implication in predicting chemotherapy response in breast cancer

The Diagnostic Potential of Fe Lines Applied to Protostellar Jets

We investigate the diagnostic capabilities of iron lines for tracing the physical conditions of shock-excited gas in jets driven by pre-main sequence stars. We have analyzed the 3000-25000 \uc5, X-shooter spectra of two jets driven by the pre-main sequence stars ESO-H\u3b1 574 and Par-Lup 3-4. Both spectra are very rich in [Fe II] lines over the whole spectral range; in addition, lines from [Fe III] are detected in the ESO-H\u3b1 574 spectrum. Non-local thermal equilibrium codes solving the equations of the statistical equilibrium along with codes for the ionization equilibrium are used to derive the gas excitation conditions of electron temperature and density and fractional ionization. An estimate of the iron gas-phase abundance is provided by comparing the iron lines emissivity with that of neutral oxygen at 6300 \uc5. The [Fe II] line analysis indicates that the jet driven by ESO-H\u3b1 574 is, on average, colder (T e 3c 9000 K), less dense (n e 3c 2 7 104 cm-3), and more ionized (x e 3c 0.7) than the Par-Lup 3-4 jet (T e 3c 13,000 K, n e 3c 6 7 104 cm-3, x e < 0.4), even if the existence of a higher density component (n e 3c 2 7 105 cm-3) is probed by the [Fe III] and [Fe II] ultra-violet lines. The physical conditions derived from the iron lines are compared with shock models suggesting that the shock at work in ESO-H\u3b1 574 is faster and likely more energetic than the Par-Lup 3-4 shock. This latter feature is confirmed by the high percentage of gas-phase iron measured in ESO-H\u3b1 574 (50%-60% of its solar abundance in comparison with less than 30% in Par-Lup 3-4), which testifies that the ESO-H\u3b1 574 shock is powerful enough to partially destroy the dust present inside the jet. This work demonstrates that a multiline Fe analysis can be effectively used to probe the excitation and ionization conditions of the gas in a jet without any assumption on ionic abundances. The main limitation on the diagnostics resides in the large uncertainties of the atomic data, which, however, can be overcome through a statistical approach involving many line

A human MAP kinase interactome.

Mitogen-activated protein kinase (MAPK) pathways form the backbone of signal transduction in the mammalian cell. Here we applied a systematic experimental and computational approach to map 2,269 interactions between human MAPK-related proteins and other cellular machinery and to assemble these data into functional modules. Multiple lines of evidence including conservation with yeast supported a core network of 641 interactions. Using small interfering RNA knockdowns, we observed that approximately one-third of MAPK-interacting proteins modulated MAPK-mediated signaling. We uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2. This study makes available a large resource of MAPK interactions and clone libraries, and it illustrates a methodology for probing signaling networks based on functional refinement of experimentally derived protein-interaction maps

Coilin Phosphomutants Disrupt Cajal Body Formation, Reduce Cell Proliferation and Produce a Distinct Coilin Degradation Product

Coilin is a nuclear phosphoprotein that accumulates in Cajal bodies (CBs). CBs participate in ribonucleoprotein and telomerase biogenesis, and are often found in cells with high transcriptional demands such as neuronal and cancer cells, but can also be observed less frequently in other cell types such as fibroblasts. Many proteins enriched within the CB are phosphorylated, but it is not clear what role this modification has on the activity of these proteins in the CB. Coilin is considered to be the CB marker protein and is essential for proper CB formation and composition in mammalian cells. In order to characterize the role of coilin phosphorylation on CB formation, we evaluated various coilin phosphomutants using transient expression. Additionally, we generated inducible coilin phosphomutant cell lines that, when used in combination with endogenous coilin knockdown, allow for the expression of the phosphomutants at physiological levels. Transient expression of all coilin phosphomutants except the phosphonull mutant (OFF) significantly reduces proliferation. Interestingly, a stable cell line induced to express the coilin S489D phosphomutant displays nucleolar accumulation of the mutant and generates a N-terminal degradation product; neither of which is observed upon transient expression. A N-terminal degradation product and nucleolar localization are also observed in a stable cell line induced to express a coilin phosphonull mutant (OFF). The nucleolar localization of the S489D and OFF coilin mutants observed in the stable cell lines is decreased when endogenous coilin is reduced. Furthermore, all the phosphomutant cells lines show a significant reduction in CB formation when compared to wild-type after endogenous coilin knockdown. Cell proliferation studies on these lines reveal that only wild-type coilin and the OFF mutant are sufficient to rescue the reduction in proliferation associated with endogenous coilin depletion. These results emphasize the role of coilin phosphorylation in the formation and activity of CBs

Receptor Tyrosine Kinase (RTK) Mediated Tyrosine Phosphor-Proteome from Drosophila S2 (ErbB1) Cells Reveals Novel Signaling Networks

Protein phosphorylation mediates many critical cellular responses and is essential for many biological functions during development. About one-third of cellular proteins are phosphorylated, representing the phosphor-proteome, and phosphorylation can alter a protein's function, activity, localization and stability. Tyrosine phosphorylation events mediated by aberrant activation of Receptor Tyrosine Kinase (RTK) pathways have been proven to be involved in the development of several diseases including cancer. To understand the systems biology of RTK activation, we have developed a phosphor-proteome focused on tyrosine phosphorylation events under insulin and EGF signaling pathways using the PhosphoScan® technique coupled with high-throughput mass spectrometry analysis. Comparative proteomic analyses of all these tyrosine phosphorylation events revealed that around 70% of these pY events are conserved in human orthologs and paralogs. A careful analysis of published in vivo tyrosine phosphorylation events from literature and patents revealed that around 38% of pY events from Drosophila proteins conserved on 185 human proteins are confirmed in vivo tyrosine phosphorylation events. Hence the data are validated partially based on available reports, and the credibility of the remaining 62% of novel conserved sites that are unpublished so far is very high but requires further follow-up studies. The novel pY events found in this study that are conserved on human proteins could potentially lead to the discovery of drug targets and biomarkers for the detection of various cancers and neurodegenerative diseases

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance

Ultra-fast searching assists in evaluating sub-ppm mass accuracy enhancement in U-HPLC/Orbitrap MS data

A strategy, detailed methodology description and software are given with which the mass accuracy of U-HPLC-Orbitrap data (resolving power 50,000 FWHM) can be enhanced by an order of magnitude to sub-ppm levels. After mass accuracy enhancement all 211 reference masses have mass errors within 0.5 ppm; only 14 of these are outside the 0.2 ppm error margin. Further demonstration of mass accuracy enhancement is shown on a pre-concentrated urine sample in which evidence for 89 (342 ions) potential hydroxylated and glucuronated DHEA-metabolites is found. Although most DHEA metabolites have low-intensity mass signals, only 11 out of 342 are outside the ±1 ppm error envelop; 272 mass signals have errors below 0.5 ppm (142 below 0.2 ppm). The methodology consists of: (a) a multiple internal lock correction (here ten masses; no identity of internal lock masses is required) to avoid suppression problems of a single internal lock mass as well as to increase lock precision, (b) a multiple external mass correction (here 211 masses) to correct for calibration errors, (c) intensity dependant mass correction, (d) file averaging. The strategy is supported by ultra-fast file searching of baseline corrected, noise-reduced metAlign output. The output and efficiency of ultra-fast searching is essential in obtaining the required information to visualize the distribution of mass errors and isotope ratio deviations as a function of mass and intensity