Jinal Patel

Recent evidence provides support for involvement of the microbiota-gut-brain axis in Parkinson's disease (PD) pathogenesis. We propose that a pro-inflammatory intestinal milieu, due to intestinal hyper-permeability and/or microbial dysbiosis, initiates or exacerbates PD pathogenesis. One factor that can cause intestinal hyper-permeability and dysbiosis is chronic stress which has been shown to accelerate neuronal degeneration and motor deficits in Parkinsonism rodent models. We hypothesized that stress-induced intestinal barrier dysfunction and microbial dysbiosis lead to a pro-inflammatory milieu that exacerbates the PD phenotype in the low-dose oral rotenone PD mice model. To test this hypothesis, mice received unpredictable restraint stress (RS) for 12 weeks, and during the last six weeks mice also received a daily administration of low-dose rotenone (10 mg/kg/day) orally. The initial six weeks of RS caused significantly higher urinary cortisol, intestinal hyperpermeability, and decreased abundance of putative "anti-inflammatory" bacteria (Lactobacillus) compared to non-stressed mice. Rotenone alone (i.e., without RS) disrupted the colonic expression of the tight junction protein ZO-1, increased oxidative stress (N-tyrosine), increased myenteric plexus enteric glial cell GFAP expression and increased α-synuclein (α-syn) protein levels in the colon compared to controls. Restraint stress exacerbated these rotenone-induced changes. Specifically, RS potentiated rotenone-induced effects in the colon including: 1) intestinal hyper-permeability, 2) disruption of tight junction proteins (ZO-1, Occludin, Claudin1), 3) oxidative stress (N-tyrosine), 4) inflammation in glial cells (GFAP + enteric glia cells), 5) α-syn, 6) increased relative abundance of fecal Akkermansia (mucin-degrading Gram-negative bacteria), and 7) endotoxemia. In addition, RS promoted a number of rotenone-induced effects in the brain including: 1) reduced number of resting microglia and a higher number of dystrophic/phagocytic microglia as well as (FJ-C+) dying cells in the substantia nigra (SN), 2) increased lipopolysaccharide (LPS) reactivity in the SN, and 3) reduced dopamine (DA) and DA metabolites (DOPAC, HVA) in the striatum compared to control mice. Our findings support a model in which chronic stress-induced, gut-derived, pro-inflammatory milieu exacerbates the PD phenotype via a dysfunctional microbiota-gut-brain axis.

Labeling of primary amines on peptides with reagents containing stable isotopes is a commonly used technique in quantitative mass spectrometry. Isobaric labeling techniques such as iTRAQ™ or TMT™ allow for relative quantification of peptides based on ratios of reporter ions in the low m/z region of spectra produced by precursor ion fragmentation. In contrast, nonisobaric labeling with mTRAQ™ yields precursors with different masses that can be directly quantified in MS1 spectra. In this study, we compare iTRAQ- and mTRAQ-based quantification of peptides and phosphopeptides derived from EGF-stimulated HeLa cells. Both labels have identical chemical structures, therefore precursor ion- and fragment ion-based quantification can be directly compared. Our results indicate that iTRAQ labeling has an additive effect on precursor intensities, whereas mTRAQ labeling leads to more redundant MS2 scanning events caused by triggering on the same peptide with different mTRAQ labels. We found that iTRAQ labeling quantified nearly threefold more phosphopeptides (12,129 versus 4,448) and nearly twofold more proteins (2,699 versus 1,597) than mTRAQ labeling. Although most key proteins in the EGFR signaling network were quantified with both techniques, iTRAQ labeling allowed quantification of twice as many kinases. Accuracy of reporter ion quantification by iTRAQ is adversely affected by peptides that are cofragmented in the same precursor isolation window, dampening observed ratios toward unity. However, because of tighter overall iTRAQ ratio distributions, the percentage of statistically significantly regulated phosphopeptides and proteins detected by iTRAQ and mTRAQ was similar. We observed a linear correlation of logarithmic iTRAQ to mTRAQ ratios over two orders of magnitude, indicating a possibility to correct iTRAQ ratios by an average compression factor. Spike-in experiments using peptides of defined ratios in a background of nonregulated peptides show that iTRAQ quantification is less accurate but not as variable as mTRAQ quantification. Labeling of primary amines on peptides with reagents containing stable isotopes is a commonly used technique in quantitative mass spectrometry. Isobaric labeling techniques such as iTRAQ™ or TMT™ allow for relative quantification of peptides based on ratios of reporter ions in the low m/z region of spectra produced by precursor ion fragmentation. In contrast, nonisobaric labeling with mTRAQ™ yields precursors with different masses that can be directly quantified in MS1 spectra. In this study, we compare iTRAQ- and mTRAQ-based quantification of peptides and phosphopeptides derived from EGF-stimulated HeLa cells. Both labels have identical chemical structures, therefore precursor ion- and fragment ion-based quantification can be directly compared. Our results indicate that iTRAQ labeling has an additive effect on precursor intensities, whereas mTRAQ labeling leads to more redundant MS2 scanning events caused by triggering on the same peptide with different mTRAQ labels. We found that iTRAQ labeling quantified nearly threefold more phosphopeptides (12,129 versus 4,448) and nearly twofold more proteins (2,699 versus 1,597) than mTRAQ labeling. Although most key proteins in the EGFR signaling network were quantified with both techniques, iTRAQ labeling allowed quantification of twice as many kinases. Accuracy of reporter ion quantification by iTRAQ is adversely affected by peptides that are cofragmented in the same precursor isolation window, dampening observed ratios toward unity. However, because of tighter overall iTRAQ ratio distributions, the percentage of statistically significantly regulated phosphopeptides and proteins detected by iTRAQ and mTRAQ was similar. We observed a linear correlation of logarithmic iTRAQ to mTRAQ ratios over two orders of magnitude, indicating a possibility to correct iTRAQ ratios by an average compression factor. Spike-in experiments using peptides of defined ratios in a background of nonregulated peptides show that iTRAQ quantification is less accurate but not as variable as mTRAQ quantification. Stable isotope labeling techniques have become very popular in recent years to perform quantitative mass spectrometry experiments with high precision and accuracy. In contrast to label-free approaches, multiplexed isotopically labeled samples can be simultaneously analyzed resulting in increased reproducibility and accuracy for quantification of peptides and proteins from different biological states. Isotopic labeling strategies can be grouped into two major categories: isobaric labels and nonisobaric labels. In the former category are iTRAQ 1The abbreviations used are:iTRAQisobaric tags for relative and absolute quantificationmTRAQmass differential tags for relative and absolute quantificationTMTtandem mass tagsSILACstable isotope labeling by amino acids in cell cultureCIDcollision-induced dissociationHCDhigher-energy collisional dissociationPIPprecursor isolation purityMRMmultiple reaction monitoringSCXstrong cation exchangeEGFepidermal growth factorEGFRepidermal growth factor receptor. 1The abbreviations used are:iTRAQisobaric tags for relative and absolute quantificationmTRAQmass differential tags for relative and absolute quantificationTMTtandem mass tagsSILACstable isotope labeling by amino acids in cell cultureCIDcollision-induced dissociationHCDhigher-energy collisional dissociationPIPprecursor isolation purityMRMmultiple reaction monitoringSCXstrong cation exchangeEGFepidermal growth factorEGFRepidermal growth factor receptor. (isobaric tags for relative and absolute quantification (1Ross P.L. Huang Y.N. Marchese J.N. Williamson B. Parker K. Hattan S. Khainovski N. Pillai S. Dey S. Daniels S. Purkayastha S. Juhasz P. Martin S. Bartlet-Jones M. He F. Jacobson A. Pappin D.J. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.Mol. Cell. Proteomics. 2004; 3: 1154-1169Abstract Full Text Full Text PDF PubMed Scopus (3680) Google Scholar)) and TMT (tandem mass tags (2Thompson A. Schäfer J. Kuhn K. Kienle S. Schwarz J. Schmidt G. Neumann T. Johnstone R. Mohammed A.K. Hamon C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.Anal. Chem. 2003; 75: 1895-1904Crossref PubMed Scopus (1709) Google Scholar)) mass tags. In the nonisobaric labeling category are methods such as mTRAQ (mass differential tags for relative and absolute quantification), stable isotope labeling by amino acids in cell culture (SILAC (3Ong S.E. Blagoev B. Kratchmarova I. Kristensen D.B. Steen H. Pandey A. Mann M. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.Mol. Cell. Proteomics. 2002; 1: 376-386Abstract Full Text Full Text PDF PubMed Scopus (4569) Google Scholar)), and reductive dimethylation (4Boersema P.J. Raijmakers R. Lemeer S. Mohammed S. Heck A.J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics.Nat. Protoc. 2009; 4: 484-494Crossref PubMed Scopus (1055) Google Scholar). Isobaric labeling techniques allow relative quantification of peptides based on ratios of low m/z reporter ions produced by fragmentation of the precursor ion, whereas nonisobaric labeling yields precursors with different masses that can be directly quantified from MS1 intensity. iTRAQ and mTRAQ reagents provide a great opportunity to directly compare capabilities of reporter and precursor ion quantification since both labels have identical chemical structures and differ only in their composition and number of 13C, 15N, and 18O atoms. In fact, iTRAQ-117 and mTRAQ-Δ4 are identical mass tags with a total mass of 145 Da (Fig. 1A). To achieve 4-plex quantification capabilities for iTRAQ labels, the composition of stable isotopes is arranged in a way to obtain the reporter ion/balancing group and (1Ross P.L. Huang Y.N. Marchese J.N. Williamson B. Parker K. Hattan S. Khainovski N. Pillai S. Dey S. Daniels S. Purkayastha S. Juhasz P. Martin S. Bartlet-Jones M. He F. Jacobson A. Pappin D.J. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.Mol. Cell. Proteomics. 2004; 3: 1154-1169Abstract Full Text Full Text PDF PubMed Scopus (3680) Google Scholar). nonisobaric mTRAQ labels were by or to the mTRAQ-Δ4 resulting in and Both iTRAQ and mTRAQ reagents are as to primary labeling of isobaric tags for relative and absolute quantification mass differential tags for relative and absolute quantification mass tags stable isotope labeling by amino acids in cell culture collisional precursor isolation reaction cation growth factor growth factor receptor. isobaric tags for relative and absolute quantification mass differential tags for relative and absolute quantification mass tags stable isotope labeling by amino acids in cell culture collisional precursor isolation reaction cation growth factor growth factor receptor. of an iTRAQ labeling strategy is additive effect on precursor samples are resulting in increased However, iTRAQ ratios have to be to nonregulated background peptides are and cofragmented in the same isolation of the peptide of and to the reporter ions in accuracy and precision in iTRAQ Cell. Proteomics. Full Text Full Text PDF PubMed Scopus Google M. J. C. I. iTRAQ in simple and complex the and the 2009; PubMed Scopus Google F. T. G. M. M. for reproducibility and of mass spectrometry PubMed Scopus Google Scholar). most peptides in an are ratios multiplexed ratios in the to be toward to the of mTRAQ labels to accurate quantification of proteins in iTRAQ experiments with such as reaction reaction of peptides absolute quantification of of a in and PubMed Scopus Google Scholar). Although iTRAQ has used in mTRAQ has only in a number of reaction of peptides absolute quantification of of a in and PubMed Scopus Google Scholar). In this we the and of iTRAQ and mTRAQ labeling for analysis of protein and expression We growth factor HeLa as a for comparative of iTRAQ and mTRAQ as both in the Blagoev B. F. B. C. P. Mann M. in and in signaling Full Text Full Text PDF PubMed Scopus Google as as the J. Mann M. high peptide mass and protein PubMed Scopus Google are for We show that iTRAQ labeling yields results to mTRAQ in of of quantified proteins and regulated of experiments with peptides of ratios we that iTRAQ quantification is more but less accurate than mTRAQ to ratio We a linear of observed versus logarithmic peptide ratios as as for logarithmic iTRAQ and mTRAQ ratios of the and a of ratio compression over two orders of iTRAQ and iTRAQ ratio compression not the to regulated in HeLa were used to signaling by in cells. were by for and with for or were for in and were by for and protein were by We total protein of cells. were with and were with were with and was in an ratio of of samples were with peptides were on and to in a peptides were labeled with iTRAQ and mTRAQ reagents to the peptide of labeling were were in of and labeling was in of the reaction was with labeled peptides were and on analysis of and peptides was as by and with J. approach for analysis by mass Protoc. 3: PubMed Scopus Google Scholar). were in cation and on a cation from using an We used a with a with a linear to a linear to in for and a with for was and the was the were with a the of was by the and were the peptide of was and were into samples that were using J. Mann M. for and of peptides for using Protoc. PubMed Scopus Google Scholar). analysis of was and the were into samples that were with and to in a peptides were to as J. approach for analysis by mass Protoc. 3: PubMed Scopus Google Scholar). peptides were in and for with of in samples were on J. Mann M. for and of peptides for using Protoc. PubMed Scopus Google twice with and with peptides were from the to the by of were with of to and with of were by and in peptide samples were on an and analyzed on an mass of and of peptide containing of were a with and with of was a ion to the mass peptides were an of with an linear from in to was for a and was using the in ion a of spectra were in the with a of and a mass from to a of was the was and ion were to collisional was to was and ion was iTRAQ the most ions were and to with and in ions were analyzed in the linear ion whereas ions were analyzed with the mTRAQ samples were analyzed with We used an isolation of for isolation of ions to and for were for fragmentation. mass spectra were using the by for iTRAQ and mTRAQ-based quantification and ion quantification was using ion for precursor for the ion of precursor ion to was by the in the MS1 of the using of the isotope in both the and m/z were based on precursor and to on the relative of the in the isotope versus spectra on the same precursor m/z in the same were the iTRAQ and spectra were on the same spectra were by the iTRAQ reporter region from a and into the reporter ion in the ion was for precursor ion for from MS1 as the of the precursor ion in the precursor isolation spectra with precursor and the by not a of masses by the mass of an amino were from peptide spectra were an protein containing to a of proteins was linear or with a of and or precursor mass Da or mass and of and iTRAQ or mTRAQ labeling of and peptide as variable were of of or with a precursor of to for spectra were as by and for precursor in a of the a overall the peptide of In the protein and the is in the the protein is the of the of peptide is the of a peptide detected an spectra for a peptide have as different precursor from by of but are as a a peptide is in protein in the the proteins are grouped and the and number are In the protein are grouped in this are peptides a of the group or of a and are and toward the total number of iTRAQ and mTRAQ ratios were from the protein in ratios of peptides were used to the ratios of ratios of phosphopeptides for biological were over of the same peptide different states. of peptide were in To obtain protein ratios the was over peptides to a protein in biological were from ratios a that was using and derived from the were used to that were for by the the a and approach to Scholar). of using was to peptide and protein ratios and a with a defined of regulated and proteins with a in biological were defined as significantly with were in with We defined the ratio of a to be was quantified in two biological and ratios have the was as the based on the linear for two with S. Google Scholar). was with to the of the absolute of the two spectra for peptides can be with a in results on are using the Our in this was to mTRAQ and iTRAQ labeling strategies in an of a quantitative To this we different biological to the different nonisobaric tags that are for (Fig. 1A). same biological samples were labeled in with isobaric iTRAQ labels labels were used to relative the biological and a was used a ratio to accuracy (Fig. We a for of precursor versus reporter ion quantification. HeLa were with for and to and of and peptides were labeled with iTRAQ and mTRAQ as in To caused by in of the labeling the labels were in the biological experiments We methods by samples by we and used the methods for and strategies have to and peptides on such as M. M. T. G. B. and iTRAQ quantification on an mass Cell. Proteomics. Full Text Full Text PDF PubMed Scopus Google and S. for quantitative analysis of 2009; PubMed Scopus Google T. P. M. C. A. N. G. K. precision quantitative using iTRAQ on an a mass the of 2009; PubMed Scopus Google Scholar). of fragment ions than of the precursor ion mass is in linear ion C. D.J. a to and low mass ions in a ion mass PubMed Scopus Google is iTRAQ reporter ions can be detected in linear ion from low mass and ions to fragmentation as we have B. M. K. of iTRAQ on for Scholar). and precision for of iTRAQ reporter ions in the cell fragmentation have significantly since an has in P. T. J. T. G. K. precision of iTRAQ and TMT quantification by an in an Chem. PubMed Scopus Google Scholar). We to samples with on the same precursor as both fragmentation can be in of we a of we found to iTRAQ reporter ions as as ions in the same derived from were not only used for but for as the reporter mass region of was with on the same precursor to quantitative from with their strategy is only reporter ions but are derived in from of the same are in the of MS2 fragmentation for precursor ion quantification methods such as fragmentation with in the cell has the of fragment ion spectra that can more than in the linear ion as as peptide are high to of the with in the linear ion is more and only of can be an for low precursors such as We the of and quantified peptides in and samples of EGF-stimulated HeLa that were labeled with iTRAQ or iTRAQ samples were with a in the most precursors were with and (Fig. mTRAQ samples were with a and results were with In this simple we observed that the iTRAQ strategy the mTRAQ strategy by to and more phosphopeptides and of quantified peptides is for samples with peptides than for not to the derived from in most quantitative In contrast, on low samples more in that not be with However, quantitative from the low mass region of was not for such of and fragmentation for samples that both fragmentation techniques are with more in for both and We as the of for samples in this because samples derived from to have and in the ion To both labeling strategies on we peptide samples derived from EGF-stimulated HeLa using We used of the total for analysis and the into whereas of the total was used for analysis and into (Fig. were with J. approach for analysis by mass Protoc. 3: PubMed Scopus Google Scholar). In we more than phosphopeptides of more than were quantified iTRAQ experiments more than phosphopeptides with an of biological resulting in phosphopeptides that were quantified mTRAQ in more than phosphopeptides with a of phosphopeptides biological and a total of quantified We observed more quantified phosphopeptides from the iTRAQ strategy with the mTRAQ was both the (Fig. and (Fig. We this in and quantified peptides to two the for peptide precursors were than for peptides to the additive effect of iTRAQ labeling on precursor samples are multiplexed using the different iTRAQ tags. using the strategy samples that are to more complex the to the of to precursor ions for labeled results in in MS2 scanning events of the We found that of MS2 in mTRAQ are on peptides that have in a different mTRAQ of phosphopeptides and proteins that were and quantified in both biological of EGF-stimulated using iTRAQ and mTRAQ are a based on linear derived for regulated peptides are are a based on linear derived for regulated peptides are and quantified are quantified of biological in of biological in of regulated in of regulated in of regulated in of regulated in quantified of biological in of biological in of regulated in of regulated in of regulated in of regulated in and quantified are quantified of biological in of biological in of regulated in of regulated in of regulated in of regulated in and quantified are are a based on linear derived for regulated peptides are of biological in of regulated in in a labeling yields more phosphopeptides that were quantified in two biological with iTRAQ and mTRAQ ratios for the and and for the of were derived by indicate for and linear is in and the in in the reproducibility of ratios that were quantified for phosphopeptides that in two biological ratios in correlation two on a the with a of We used linear analysis and peptide ratios a are in toward a ratio of for iTRAQ with the is most to the isolation M. J. C. I. iTRAQ in simple and complex the and the 2009; PubMed Scopus Google Scholar). We ratios in the mTRAQ in the of the and strategy in this of ratios as to in precursor quantification. of precursor quantification only on of the different precursor ions of a peptide and the labeling strategy in such of such the of a linear and for whereas for mTRAQ and However, very of regulated is to peptides ratios are statistically significantly different than using for iTRAQ and mTRAQ labeled In both and of phosphopeptides were and ratios are in two biological in iTRAQ with mTRAQ We proteins with phosphopeptides in the iTRAQ and mTRAQ to the and found that both labeling strategies to the of the most signaling events of the such as the and the However, regulated on were observed in the iTRAQ with only in the mTRAQ threefold more regulated containing peptides were detected in the iTRAQ of quantified peptides can into of quantified proteins and of the relative protein To in protein expression we a of quantified peptides for this proteins were quantified in the iTRAQ to more proteins with the mTRAQ of major in protein expression were detected whereas of proteins were observed to be regulated the with both labeling most proteins not their expression or of we by that most of the observed regulated events are not because of in protein the most regulated we observed a factor that was found to be regulated in an J. Mann M. high peptide mass and protein PubMed Scopus Google Scholar). of iTRAQ ratios to a the protein with the to the of the In the of a linear and for whereas and for We that be in the A. J. Mann M. than peptide in but the is to PubMed Scopus Google a of the precursor to the total ion in the isolation used to for fragmentation. to for the a of this precursor isolation in samples that precursor was more than in the the effect was of for peptides in samples was the in the samples was In contrast, the of mTRAQ labeled and is the by the nonisobaric mass tags. We observed a of with both labeling as of proteins and of phosphopeptides quantified with mTRAQ were quantified with iTRAQ of and protein in the iTRAQ and mTRAQ a correlation both labeling techniques (Fig. the in linear results in of for and for protein ratios with of and In we more complex samples to a of is by the of the in the of the the of with number indicating more complex is more than the less complex analysis of the on peptide in a of with a of the peptide a with correlation we have more in the analysis on protein very percentage of regulated phosphopeptides and proteins can be defined with for iTRAQ and mTRAQ is from the linear observed in and over two orders of in for iTRAQ and mTRAQ are versus for the and versus for the to for a such as ratio compression in iTRAQ regulated can be to a as in using quantification strategies mTRAQ and that from or To quantification and accuracy in iTRAQ- and we peptides with ratios into and of the peptides were derived from a of HeLa to from background peptides that derived from (Fig. peptides were labeled with iTRAQ or mTRAQ defined and into samples such that of peptides were and were We observed that ratios for the peptides were more accurate for but mTRAQ ratios by an average of only from the whereas iTRAQ ratios were by an average of from the of were for more than In contrast, the for the iTRAQ were To the of iTRAQ quantification accuracy on we the observed iTRAQ ratios of the peptides versus precursor isolation the accuracy of iTRAQ ratios has to caused by of peptide precursors M. J. C. I. iTRAQ in simple and complex the and the 2009; PubMed Scopus Google we observed correlation in the of precursor in the MS1 to the MS2 versus the iTRAQ reporter ion of that precursor ions of can reporter ions with variable over two orders of of correlation to precursor isolation as a for quantification accuracy. To precursor isolation of iTRAQ ratios we a of iTRAQ ratios affected by background ratios (Fig. a with logarithmic ratios that show of and of and a of is to the average for and we a nearly linear correlation of to ratios over two orders of analysis of that and that to and in linear a of that a of iTRAQ peptide ratios be for compression over two orders of linear of iTRAQ versus mTRAQ ratios (Fig. from the and analysis the possibility to an overall factor. To this we logarithmic iTRAQ ratios of peptides into background versus We observed a linear correlation of the ratios with versus background peptides (Fig. and derived from linear analysis were used to iTRAQ ratios and the average to we the same to the iTRAQ and using ratios as for iTRAQ were by a factor of for phosphopeptides and for proteins to the In this study, we two chemical labeling strategies for quantification. mTRAQ strategy quantitative from precursor ion whereas the iTRAQ strategy peptide fragmentation to reporter ions for quantitative We the of to relative on both the and protein To a biological we analyzed in the and total a very We found that quantification nearly threefold more quantified phosphopeptides (12,129 versus 4,448) and nearly twofold more quantified proteins (2,699 versus 1,597) with mTRAQ-based quantification. results that iTRAQ labeling is to mTRAQ for in complex can be by iTRAQ labeling an additive effect on precursor intensities, whereas mTRAQ labeling leads to a number of redundant MS2 scanning events caused by triggering on the same peptide different mTRAQ labels. Our results indicate that in of are to redundant of the same peptide in different isotopically labeled in or reductive dimethylation In to of MS2 be be into and for quantification key proteins in the EGFR signaling network were quantified with both techniques, indicating that of protein the of quantification for both iTRAQ- and However, the of protein found in the were detected and quantified only in iTRAQ indicating a to of of iTRAQ ratios because of nonregulated background peptides has in a number of accuracy and precision in iTRAQ Cell. Proteomics. Full Text Full Text PDF PubMed Scopus Google M. J. C. I. iTRAQ in simple and complex the and the 2009; PubMed Scopus Google F. T. G. M. M. for reproducibility and of mass spectrometry PubMed Scopus Google Scholar). and defined a for iTRAQ quantification and reproducibility of quantification results for protein high that to high fragmentation. is very to we have used in this in the We observed only correlation of high with quantification accuracy of peptides ratios into complex is because of the that the of reporter ions in iTRAQ are to the of the precursor ions from ions of can iTRAQ reporter ions that over two orders of in intensity. that very low background ions can significantly to reporter ion cofragmented with the precursor ion the MS2 is be used as an accurate to for quantified iTRAQ ratios in and has that iTRAQ ratio compression a an and results in a linear observed and ratios of proteins accuracy and precision in iTRAQ Cell. Proteomics. Full Text Full Text PDF PubMed Scopus Google Scholar). We the same in peptide as as iTRAQ and mTRAQ ratios for the and of regulated phosphopeptides and proteins can be in iTRAQ and mTRAQ as not only regulated iTRAQ ratios but ratio in the Our iTRAQ that this linear of logarithmic ratios the of a analysis therefore only be for iTRAQ ratios or because be is to that of iTRAQ ratio compression by an average compression factor can only be to very of ratios are and and ratios can be is on and the number of of peptides using methods can quantification accuracy M. J. C. iTRAQ ratio compression and PubMed Scopus Google K. S. of different for analysis of in to Scopus Google Scholar). We a effect of phosphopeptides as iTRAQ ratio compression is for samples with samples to their overall has that the of the isolation for from to has effect on TMT quantification accuracy multiplexed quantification with isobaric PubMed Scopus Google Scholar). However, in two recent peptide fragmentation have to iTRAQ reporter ion that of that are on precursors multiplexed quantification with isobaric PubMed Scopus Google or on high m/z ions R. ratio in isobaric multiplexed quantitative proteomics.Nat. PubMed Scopus Google Scholar). of be to iTRAQ quantification accuracy and to iTRAQ ratio compression In we show that iTRAQ reagents are to mTRAQ reagents to of novel regulated in and iTRAQ quantification less and reproducibility than quantification with accuracy to compression of iTRAQ ratios not the of regulated phosphopeptides and with

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). reduced-representation assay a platform for the of across a of for thousands of We the assay highly for of and and of Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). reduced-representation assay a platform for the of across a of for thousands of We the assay highly for of and and of of and is of in the the of in of gene expression data from samples to and gene expression and data for data an the of reaction profiles from with and of these profiles to develop the to small and a new for of parallel reaction represents a to and only of cellular and the post-translational modifications to the and for these and to changes treatment and are mediated by changes of post-translational modifications on in is to be a strong of cellular signaling of in and gene the to in the in disruptions in in on and of in protein in protein changes in cellular of of protein to the for and of the protein in and of of phosphosignaling is to be in A assay 1 a of in is a that in signaling of of to and to from to and and in that We that phosphosignaling responses to and cellular that to gene expression is of for these profiles of these post-translational of protein are and the of and are in are in the of in protein A to protein protein of the protein is of the of and in cell signaling analytical to for protein have been have been developed to signaling of of to and to and by peptide by for protein and have been to and from proteolytic of and for and of for phosphopeptide enrichment for by with highly sensitive these enrichment have studies in in and changes in pathways protein of and to for and and to and in gene expression be highly to have reproducible observations of phosphopeptide analytes across of samples generated under different with the and sensitive MS is possible to measure of the across experiments using across small of experiments are in processing and data of and for of of the an A for and of protein in in data in the of the is a is possible to and phosphosites in a of these we that is mediated by a protein and that of thousands of on protein We that the of to that is in the cellular by and that the of on coordinate could a set of highly phosphopeptide probes. This is with by phosphosignaling cell lines with different to were profiled to that were in parallel pathways of under and conditions of and of a was to develop the reduced-representation assay that is the for the assay of of the of expression to and gene expression a reduced-representation set of phosphopeptide probes using a targeted MS could be a and to changes in phosphosignaling in to and an assay could and cell cell using to in the A was by and developed a targeted assay to in in to by from data A protein assay for cellular targeted could and for across in to a and of three a discovery we a set of phosphopeptide probes from a we develop a phosphopeptide assay that data that observations for and a we the of the assay to and and demonstrate discovery we data samples that 26 chemical in three different cell lines using phosphopeptide enrichment and these data we selected phosphosites from of that regulation across discovery We a targeted parallel reaction monitoring assay these phosphopeptide probes using and in developed that proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment from 96 samples in of the assay to a of of the assay was to samples under conditions to in discovery experiments to we could the using only the reduced-representation a fraction of the for deeper in we conditions to the treatments, cell types, and measured with the of that the assay could profiles of the under which was developed and to demonstrate that the assay is to disruptions of signaling pathways of We assay phosphopeptide probes in a This assay is a phosphosignaling of Profiling assay the of by targeted in that to be of We that the assay highly for and of and of of chemical and to of is these the for to were in with and were in with and were in with and and and were of and for cell were in with and were in with and were in with and were to to and were from with the of which was the of ∼95% were treated with the in and for the were with and by were for 2 was and the cell was in cell and phosphopeptide and for discovery in a new discovery experiments, we to of these experiments, we the and the drugs in the and in and in each were were using of treatment for each of the discovery data a that for each of the 26 be in This data set been in with experiments, were in of the of the assay are to were from ∼95% were treated with the in for the were with in plate in 1 2 1 2 3 and by were for and to phosphopeptide cell were by for of were with by in cell cell of were in each of and and ∼95% were treated with the in for were by with and for 2 was and the cell were in cell and phosphopeptide cell were for in 1 2 1 2 3 were for and protein of the were measured protein assay of protein was for with and for with were to 2 with were with in a on a was by the samples to a of samples were a for were using and to of post-translational modifications by Phosphopeptide enrichment was using that were by with to were in were for with for each for Phosphopeptide enrichment was enrichment for by was on and for and of for using were with 2 of 2 of and 2 of were and with of and of were from with 3 of and with of from with were on a a of cell were for in 1 2 1 2 3 were for and protein of the were measured protein assay of protein was to a platform for in in to 2 in and with in was by the samples to a of samples were a in a plate for were using and to samples were in that for enrichment and to an were with with and with were with and samples were were a of 2 were with and were with were to and using to the A is were for in 1 2 1 2 3 were for and protein of the were measured protein assay of protein was to a platform for in in to 2 in and with in was by the samples to a of samples were a in a plate for were using and to samples were in that for enrichment and to an that we the enrichment from the were with with and with were with samples were and were were with and were with were to and using to the A is in Phosphopeptide using was to 3 with the data were using a data were using A of was using an for each to of the in these data were in the of and were we and that been in a of the samples in We that targeted for these to a data for we created for each to in the with the of a from discovery to targeted assay for data three the conditions were using a with a with a was under to with and were in and were with a from of and and for and were a A MS was a of from to was by a an were and the was set the was set of post-translational modifications by were and the was set the were the of were selected from to were using the conditions the with the were in of phosphopeptide probes. were using a from of and for were a A MS was a of from to was by fully targeted 2 peptide was to for on the on the of of a of phosphopeptide probes. the experiments, were a with the with the MS was from to and with data have been in the and are to the targeted be MS were with the was and and the modifications were of of of and of allowed were for MS and for and were using by and were for and be in that were in of experiments were a data was for a in a we by of a on the and of of that in conditions of were variance was measured for each and with the of variance across experiments were of for and was We clustering of using clustering samples and using a of of these data was using the data to phosphopeptides were selected from each using an that data each by to in and data of that were selected be in were a an for and targeted with for reduced-representation phosphopeptide probes and for the phosphopeptide probes were on the of for and and phosphopeptide was using the of with samples and the of with were on the of using for each were by the of samples was in using with the and possible were using A was for each set of for a in a cell was the in to an A the three of in and the 3 of in that the A and is the of the possible of these A for of was to and the were using using the the is directly to the We set to develop a and targeted assay that could on the of cellular of process is in 1 We small that were to in We treated cell with these and We a small of and a of phosphosites were to be the of are across a of We that a set of could for a we were to of phosphosites that from which we selected We a reduced-representation targeted MS assay for these phosphopeptide probes We the assay in new samples under treatment conditions in discovery experiments to that the assay was We the assay on samples from new cell and that were for assay to demonstrate the of the assay under we phosphosignaling profiles from treated with of in a to demonstrate that the assay is sensitive to disruptions in common signaling MAPK, PI3K/mTOR, and cell experiments allowed to the of of we a data platform that the of phosphosignaling that be to drugs and and to drugs to to small with on we gene expression data in the for that the expression of of and was a set of expression is the phosphosites that be We highly be to the on the the of the data set of data for samples across cell lines and and each is the gene expression from of a treatment in a cell We by probes to of We these data in the that treatment with gene expression profiles We each for the of of are by the in were selected from with an on of the by in the the in we selected of a to on we selected 26 1 and 1 that we to be strong for of and across a of cell we measured the cellular by these 26 different with across three cell lines and in for a of experiments in data set we that were in of only these we and variance phosphosites were the data we clustering of the conditions and the detected phosphosites We the discovery data set with an reproducible responses of by phosphosites for conditions and could be we could phosphopeptide and a of the from are in 2 to these We show a to treatment across three cell lines in with of phosphosites across a set of that of treatment in the of the cell We a and is these cell lines are of a that in phosphosites to these clustering these in are a of the We demonstrate and across a set of in and is a in the treatment of conditions in the of and are to have of these across the and cell lines and a common of a of phosphosites the protein with the is of we a of a of that only to in show that are in common of of to in cellular we that these are and are on the of from these data is We an of phosphosites in the data set that to be across a of conditions we that the of a in to different treatment and across cell We that the of the in to have a strong and was by a enrichment the which that the were for with an of with in the data We that of the in the are to in in a in the with and This the of regulation of the by phosphosignaling in a are to be from deeper of the discovery data was the the the of which was to develop an phosphosignaling for We a to the of phosphosites that could be a small of to the This of signaling a fraction of the with This from the assay developed for the of that the of for monitoring expression have in a gene expression assay that of of the of expression A been by in the of signaling in A protein assay for cellular We by clustering on data in and we that to of the variance in the data We and measured the of these a of the data for of We a in the and on to set on clustering data that the phosphosites different We that the of to of the gene expression assay to we selected 2 phosphopeptide probes from each of the for a of phosphopeptides probes were using to of on the we developed a targeted assay to and highly and phosphopeptides across cell treated with of probes peptide probes could be the targeted assay for peptide peptide MS in a of 96 phosphopeptide probes in of the that we selected a of possible with a of and 96 probes A of assay a we the processing in a cell the processing protein a protein digestion, phosphopeptide and using and the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of using This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptides in to for the of the are in and We were to phosphosignaling profiles in under 2 from the of cell to using assay by directly measuring the reduced-representation set of phosphopeptides across cell and signaling pathways from the of and by the phosphopeptides that were to the reduced-representation phosphopeptide set are in for each signaling are on a that is to the of in a that are in the set of A that a signaling is by a of of the signaling in that are different signaling and lines a of are We that these pathways be in the targeted assay by proxy the reduced-representation and demonstrate for of and of targeted data are using an for and targeted and data and are a of to reproducible are of data A the data is in that the assay could of to from we a of the conditions from discovery experiments and We the of these experiments in an of the data of the samples are by and of the probes are in each cell is the of the of the peptide to the and the is to the of from the a phosphopeptide is in a to are in data set data and we were to from of possible samples data from of the 96 probes. were of the probes were and probes were were in of be that a that we to the peptide that the was to the we could these to a We of from and to to samples treated with we that and in the phosphosignaling profiles that from and in the assay We that of the across cell in the for We an alternative of these in with in and We that alternative A of the of cell treated with with cell and treatment the across cell and the treatment each cell are in the the of is a of samples are and the phosphosignaling are in that of samples a strong the of of samples be and on we a of which that the assay is the the of the samples demonstrate strong treated with different on the observations from these strong members This that the profiles be in and and of the the from the treatment across cell types, characterizing the in the a treatment cell signaling pathways across cell types, the of a of the across different cell lines 1 that the on phosphosignaling across cell the of the and responses to the only a of the the of the the of the treatment each cell are of a the of the assay process across different strong 1 that are to be the and that is a strong to signaling responses in a the performance of the assay, we a with A the from a of probes is in is a we of phosphopeptide probes and that in with that we a in the responses of the demonstrate that we have selected analytes that have responses under a of cellular making for the signaling of the cell in clustering the in of in and with the and the making This that the of from be to and be for and that phosphosignaling. that the assay could in for we a using cell lines and that were assay We selected and derived from these of in We to the and with to of modifications regulation been to be for of and from in have been with and A of and in a an and phosphosignaling profiles generated from and are in we in of the we that profiles across cell We of responses to that the signaling of these in cell the and developed in the of phosphosignaling the we have that are the using assay the of by targeted data we show that these develop in the of to the that be the and signaling in by the observations in these observations were using the reduced-representation assay in a that was we were samples and demonstrate that the assay be to in cell types, a we an to demonstrate that the assay is to of We selected a of small that were to members of MAPK, PI3K/mTOR, and signaling of the the that with a from of and and to in is in was to measure the of and we samples and of We these experiments in the which the and and of and to and of of in the cell for profiles derived from these experiments are in are in profiles are to the and each of the each are in from to is from these profiles that the different generated a set of responses in the We that of the have only with of with the the the 3 This is of the with of and are and a and to have to profiles the only a strong of which the was developed a treatment for the of the cell for We the of of these for the different the profiles to a of the and signaling to be We derived from that were with to the to be we of the of samples each 3 samples with 3 samples, with and the for is in from the are on the which the of the we that were of that to be to the we to these of and we that to the that we from the This is to that of the the the in the the that in the pathways of the phosphosignaling with reduced-representation of the to of from the data was to develop a for a assay that could be to the of on cell signaling across generated under of cellular responses to drugs data and and of and for of of the an a from discovery to targeted assay for the of thousands of in samples, across conditions are and data discovery experiments that are and to data with we a targeted assay for a set phosphopeptide probes that a highly of the We these probes from discovery cell studies and the assay for under cell types, We that targeted for assay, data and the of phosphosignaling studies a fraction of the of discovery assay cellular phosphosignaling of profiles that be across small and of the the assay to on of we strong across cell using data are to of of each of the we profiles from of to and which small are of could a of the assay the of using profiles an of cellular to small and a new for with of the assay a the and of the assay were by processing We developed for protein digestion, phosphopeptide and using and We process monitoring enrichment to for peptide and that are to a effort. We demonstrated that we could simultaneous process 96 samples in only 3 with a plate enrichment of and ∼95% of the reduced-representation phosphopeptides in to samples using assay is a with a to data We the targeted assay and the of a reduced-representation by of set to deeper data under the conditions for discovery experiments these we were to in discovery experiments that a set of phosphopeptide probes be for a phosphopeptide are using a that and to the of and these we evaluated the performance of the assay We and cell lines and demonstrated that the is in with treatment be detected a cell and across cell We on to show that the of the profiles in the assay have and of is for of and in for in that is in the assay to and that cellular responses to are we could treatment the we of in the profiles the and that we observations changes in protein the assay We the of measuring the of the to be of the of the that we to the assay to a the of of a is a of the we the changes and the protein We that the assay represents of the experiments that are by 3 and that the the 3 and We that is the to measure phosphosignaling changes in have a to strong on the in the We the assay to to the in in in of we measured of in and we to with the of the possible in cell that we the we that of these data be treatment with the in the of cell we only data an of to phosphosignaling profiles in cell that and We that the assay be in of We demonstrated that the assay was in by data from new cell treated with the assay We were to measure phosphosignaling profiles in and in to different of a an and with cell experiments, of by across and to using data for treated and the for the assay to be in a of and We demonstrated that with of cell signaling that monitoring phosphosites is for the phosphosignaling profiles we generated from and and of reduced-representation phosphopeptide probes is to the of by of the and developed a targeted assay to responses to in a by from data A protein assay for cellular we selected probes that were highly in discovery data we selected probes to signaling the of protein selected a of probes for protein and experiments and to the we selected a set of phosphopeptide probes to with the assay, the of reduced-representation be to different of probes be detected and have varying responses to reduced-representation to probes to to the to measure across the the of the is to that the of the reduced-representation set was data of cellular pathways This is on of we that by that phosphosites with a of in the the of the cellular to that to responses to that the is to of and to of cellular the discovery data to the assay a of that to be that the assay these pathways by the the selected probes have to the discovery pathways by are in Many of these cell signaling pathways have been in and are of to and the signaling been in and of of signaling pathways in of in and been to and protein signaling cell and in and protein the process an signaling signaling is with and a of signaling and targeted we have demonstrated that the assay is sensitive to disruptions of the MAPK, PI3K/mTOR, and cell to these pathways these experiments, we in these signaling pathways and that allowed to the the of the from and with of of and which to of the data the assay samples and of to and the pathways by the that the assay is a proxy for monitoring cellular processes. to in these pathways is in with the pathways which we the assay on the is for phosphosignaling assay in the for possible be a assay that and of analytes the to data for phosphopeptide analytes of in assay is a on is to be in with gene expression to develop of cellular responses to be to data on in assay the of by targeted parallel reaction monitoring modifications on the with of that are directly targeted by the with of process that be of of signaling responses for these We to by with under the of the of to data from a set of and across a of cell A of these data been in of We that these of data of and phosphosignaling to we developed and a assay that be a to the of on cell signaling in cell assay we demonstrated that reduced-representation are by in discovery We cell signaling in a assay and demonstrated that is and We were to that are to the that have signaling we the assay a of data that be to phosphosignaling profiles by only phosphopeptide probes are we demonstrated the of studies by a MS assay that be a that the to thousands of with be an from the to of the of cellular and to We for to data We for with