Analytical Chemistry Chemical Cytometry Quantitates Superoxide

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Figure 5. Behavior of primary scoring metrics for high-resolution correlation analysis. (a) Histogram depicting the sensitivity of an LC-Orbitrap- MS/MS analysis as a function of fragment ion bin widths at FDR < 1%. (b) High-resolution correlation analysis rescues false negatives that are inaccessible by high-mass accuracy precursor ion searching alone. (c) ROC plot using XCorr filtering during 1.0, 0.25, and 0.025 m/z-wide bin searches. Insets show histograms of the behavior of Xcorr during 1.0 and 0.025 m/z-wide bin searches. The 1.0 m/z TP distribution is blue, while the 1.0 m/z FP distribution is red. The 0.025 m/z TP distribution is green, while the 0.025 m/z FP distribution is orange. Note that while the primary score for TPs remains largely unchanged, FP scores are significantly reduced. (d) ROC plot using dCn filtering during 1.0, 0.25, and 0.025 m/z-wide bin searches. Insets show histograms of the behavior of dCn during 1.0 and 0.025 m/z-wide bin searches; the distributions are colored the same as in part c. DISCUSSION Soon, proteomics researchers will be swimming in a sea of mass spectra. During the later stages of development of Macro, we were asked to search a5hLTQVelos run with Macro and were surprised to find that it consisted of ∼170 000 tandem mass spectra. Clearly, the relative processing speed of computer-assisted spectral matching algorithms will be a critical feature for these algorithms in the coming years. Our intent with developing Macro was to refresh a scoring metric (Xcorr) that adds significant value to proteomics research by reorganizing the way it conducted searches. The fact that Macro is also very competitive with other search engines reinforces our view that candidate-centric searching represents a practical approach to search algorithm design in general. The core Macro process is also scalable: the MS/MS spectral array may be accessed in main CPU memory by multiple independent processing cores, each of which could digest a different portion of the FASTA database or perform scoring functions, or both; design modifications such as this are planned for future versions of Macro. Although the SEQUEST-specific version of Macro contains proprietary information that precludes its pubic release, we offer the source code for MacroParser to the proteomics community as a general framework for candidate-centric database parsing into which any peptide scorer could be inserted. Details regarding the Macro project can be found on our lab Web server at http:// proteomics.dartmouth.edu. We feel that the performance gains associated with Macro can allow for a host of features and functions to be added to the classical scoring function Xcorr, including post-translational modi- 6828 Analytical Chemistry, Vol. 82, No. 16, August 15, 2010 fication scanning and, as we show here, high-resolution correlation analysis. Although a parameter does exist in legacy SEQUEST that appears to allow users to scale fragment ion tolerances, closer inspection of the SEQUEST source code and search output when using this parameter reveals that it is not performing these searches as the user likely intends. Our inclusion of a variable fragment ion bin width parameter that accurately bins fragment ions into a scalable sparse array enables users with a mass spectrometer capable of better than unit resolution MS/MS spectra to search their data with the corresponding fragment ion mass tolerance. This has the added benefit of improved overall search accuracy relative to unit resolution searching. Although this does come as a speed penalty, we note that even when running at 0.025 m/z bin width, Macro is still 20× faster than SEQUEST on our platform. We anticipate that these highresolution correlation searches will result in a significant decrease in the minimum Xcorr threshold required to achieve a desired FDR: we observed the median Xcorr value of rescued PSMs, across all charge states, to be 1.52, with the lowest rescued PSM yielding an Xcorr of 0.67, albeit with a dCn of 0.08. Legacy SEQUEST users will likely need some adjusting to these unusually low score results, but with careful application of strategies to estimate data set false discovery rates 21 and calculate PSM posterior probability assignments, 26 we hope they will also ultimately appreciate the benefit of high mass precision to the improved accuracy of their data sets. (26) Kall, L.; Storey, J. D.; MacCoss, M. J.; Noble, W. S. J. Proteome Res. 2008, 7, 29–34.
Figure 6. Characterization of PSMs “rescued” by high-resolution correlation analysis. (a) Top-ranked PSMs and scores for a given MS/MS search result using 1.0 and 0.025 m/z-wide bins. Note that these sequences are identical, except for a K/Q substitution in the middle of the peptide, marked by a red box. While the 1.0 m/z-wide bin search rank 1 PSM satisfies a precursor ion tolerance and Xcorr cutoff, the dCn (0.005) precludes unambiguous TP assignment. The top-ranked PSMs and scores from the 0.025 m/z-wide bin search are shown below. The resolving power of much narrower fragment ion bins clearly allows for discrimination of the K-containing ion fragments, resulting in a dCn of 0.36 and an unambiguous TP PSM assignment. (b) Graphical representation of the distribution of candidate PSMs by Xcorr for the 1.0 (blue) and 0.025 (red) m/z-wide bin searches of the PSM from part a. (c) Histogram depicting the relative ranks of rescued PSMs in the lower resolution search. The lowest ranked PSM was rescued from the 4 715th position. (d) Reciprocal MS/MS plots, sequence, and matched fragment ions for the PSM rescued from the 4 715th rank position. The upper MS/MS spectrum is from the endogenous peptide from the HeLa cell lysate, and the lower MS/MS spectrum is from the synthetic peptide “AASVHTVGEDTEETPHR”. ACKNOWLEDGMENT We thank Mike Senko, Justin Blethrow, and colleagues at ThermoFisher Scientific for facilitating transfer of the SEQUST source code, additional platform testing, and general discussions. We thank Arminja Kettenbach for preparing the HeLa cell lysate digest and phosphopeptide-enriched sample and also thank Jason Gilmore for critical reading of the manuscript. This work was supported by the National Institutes of Health Grant P20-RR018787 from the IDeA Program of the National Center for Research Resources (to S.A.G.) and a predoctoral fellowship from the National Institute of General Medical Sciences Grant T32- GM008704 (to B.K.F.). SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. Received for review March 26, 2010. Accepted July 8, 2010. AC100783X Analytical Chemistry, Vol. 82, No. 16, August 15, 2010 6829
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Anal. Chem. 2010, 82, 6745-6750 Let
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purchased from Invitrogen-Molecular
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Figure 3. Electropherograms of TPP-
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Anal. Chem. 2010, 82, 6751-6755 Res
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(pH 8.0) with cysteine and cystamin
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Figure 4. Ion mobility mass spectra
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GOx glucose + O298 gluconic acid +
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coater at 2000 rpm for 20 s, and th
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Figure 5. Comparison of cyclic volt
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in channels with either no grooves
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indicators of atmospheric processin
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Figure 1. GC/MS total ion chromatog
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Table 2. Concentrations and Stable
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on a substrate are preferred. 20-24
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Figure 4. SERS analysis of NAADP co
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Anal. Chem. 2010, 82, 6775-6781 Hig
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NaCl, phosphate buffer saline (PBS)
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Figure 2. Product ion mass spectra
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-70 °C resolved the problem, givin
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Table 1. Intraday Precision and Acc
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Anal. Chem. 2010, 82, 6887-6894 Fer
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Figure 1. Infrared spectra of (A) u
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Figure 3. Cyclic voltammograms obta
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Figure 6. Calculated charge from ch
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Anal. Chem. 2010, 82, 6895-6903 Ele
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Table 1. Chemical Structure, pKa Va
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pH with a tilted baseline (Figure 1
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Table 2. Linearity and Detection Li
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ascorbic acid (AA), uric acid (UA),
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the multielement capabilities, the
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RESULTS AND DISCUSSION Sulfur Detec
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Table 2. Molecular Properties and C
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Anal. Chem. 2010, 82, 6911-6918 Dir
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dilution and hybridization buffer.
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solution under appropriate incubati
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Figure 4. Standardization curve for
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the ×10 objective, to have a large
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Figure 2. With a suitable removal o
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the NB signal in a much better foot
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Scheme 1. Reactions of Selenium Rea
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Figure 2. (a) ESI-MS spectrum showi
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Figure 4. (a) ESI-MS spectrum showi
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Anal. Chem. 2010, 82, 6933-6939 Dif
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trode 28 by a finite element using
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Figure 4. Comparison between simula
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Figure 6. Comparison between simula
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educed in the vicinity of double bo
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Figure 2. Normalized product ion ab
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Figure 4. EID (a) and IRMPD (b) of
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Anal. Chem. 2010, 82, 6947-6957 Ide
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Figure 1. Schematic flowchart showi
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difference, ppm compound Table 1. I
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isoforms, its successful use, in th
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Figure 5. Extracted ion current ESI
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m/z 1172.935 was observed for Ser14
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linked products via affinity tags.
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Scheme 2. Fragmentation Mechanism o
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Figure 1. (A) ESI-LTQ-CID-MS 2 prod
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Figure 3. (A) ESI-LTQ-CID-MS 2 prod
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Figure 5. (A) MALDI-TOF/TOF product
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Anal. Chem. 2010, 82, 6969-6975 Ana
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Figure 3. Equilibrium response as a
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Figure 6. The average measured resp
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for the fill time, and we find that
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nucleotide tails. 3-5 Thus, the amo
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allow the use of higher aptamer con
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quent ligation of the aptamers afte
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Anal. Chem. 2010, 82, 6983-6990 Imp
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Figure 2. Configuration editor wind
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Figure 4. Dependencies between volu
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Since the time for liquid expulsion
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Anal. Chem. 2010, 82, 6991-6999 Int
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Figure 1. Representation of the Car
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Table 2. Capillary Electrophoresis
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Figure 4. (A) Typical raw electroph
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field. DNA profiles were delivered
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Another approach to handle this lim
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(principal components, PCs) in whic
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Figure 5. Relevant score plots and
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CONCLUSIONS In this paper we have i
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electroactive-species loaded liposo
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Figure 2. Qdot-based FLFTS response
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Figure 6. Fluorescence imaging of Q
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Anal. Chem. 2010, 82, 7015-7020 Sel
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Table 1. Effect of 1 D-LC Condition
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Figure 3. Peak-production rate vers
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Anal. Chem. 2010, 82, 7021-7026 Cel
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luciferase (T7 control vector) was
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Figure 3. Inhibitory effects of luc
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Anal. Chem. 2010, 82, 7027-7034 Pat
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Electrochemistry. Electrochemical m
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Figure 2. SEM images of Au substrat
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Table 3. Film Thickness Measurement
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Anal. Chem. 2010, 82, 7035-7043 Qua
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Figure 1. (A) FL spectra of BSPOTPE
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Figure 4. (A) Variation in the FL i
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Figure 6. (A) FL spectra of BSPOTPE
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Scheme 1. Proposed Mechanism for Fl
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one or more drawbacks including poo
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Figure 2. Free fluorophores do not
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Anal. Chem. 2010, 82, 7049-7052 Dev
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Figure 2. Comparative analysis of d
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Analytical Chemistry Chemical Cytometry Quantitates Superoxide

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