iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics

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 iTRAQ¹ (isobaric tags for relative and absolute quantification (1)) and TMT (tandem mass tags (2)) 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 (3)), and reductive dimethylation (4). 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 pairs 114/31, 115/30, 116/29, and 117/28 (1). Three nonisobaric mTRAQ labels were generated by adding or removing four neutrons to the mTRAQ-Δ4 label resulting in mTRAQ-Δ8 and mTRAQ-Δ0, respectively. Both iTRAQ and mTRAQ reagents are available as N-hydroxy-succinimide esters to facilitate primary amine labeling of peptides.Open in a separate windowFig. 1.A, Labeling strategy for comparative evaluation of iTRAQ and mTRAQ tags. Peptides were labeled with the indicated iTRAQ and mTRAQ reagents for combined phosphoproteome and proteome analysis. B, Selection of optimal instrument methods for analysis of iTRAQ- and mTRAQ-labeled peptides. Unfractionated proteome samples (1 ug) and phosphoproteome samples (enriched from 250 μg peptides) were analyzed for iTRAQ samples with a CID/HCD-Top8 method, whereas for mTRAQ we compared CID-Top16 acquisition to HCD-Top8. Note that duty cycle times were for all instrument methods ∼3.1 s.One potential advantage of an iTRAQ labeling strategy is its additive effect on precursor intensities when samples are multiplexed, resulting in increased sensitivity. However, iTRAQ ratios have been demonstrated to be prone to compression. This occurs when other nonregulated background peptides are co-isolated and cofragmented in the same isolation window of the peptide of interest and contribute fractional intensity to the reporter ions in MS2-scans (5–7). Because most peptides in an experiment are present at 1:1:1:1 ratios between multiplexed samples, all ratios in the experiment tend to be dampened toward unity when cofragmentation occurs. This inaccuracy led to the development of mTRAQ labels to facilitate accurate precursor-based quantification of proteins initially identified in iTRAQ discovery experiments with targeted assays, such as multiple reaction monitoring (MRM) (8). Although iTRAQ has been widely used in discovery-based proteomics studies, mTRAQ has only appeared in a small number of studies thus far (8).In this study we investigated the advantages and disadvantages of iTRAQ and mTRAQ labeling for proteome-wide analysis of protein phosphorylation and expression changes. We selected epidermal growth factor (EGF)-stimulated HeLa cells as a model system for our comparative evaluation of iTRAQ and mTRAQ labeling, as both changes in the phosphoproteome (9) as well as the proteome (10) are well described for EGF stimulation. We show that iTRAQ labeling yields superior results to mTRAQ in terms of numbers of quantified phosphopeptides, proteins and regulated components. By means of spike-in experiments with GluC generated peptides of known ratios we find that iTRAQ quantification is more precise but less accurate than mTRAQ due to ratio compression. We identify a linear relationship of observed versus expected logarithmic GluC generated peptide ratios as well as for logarithmic iTRAQ and mTRAQ ratios of the phosphoproteome and proteome analysis. This indicates a uniform degree of ratio compression over two orders of magnitude throughout iTRAQ data sets and explains why iTRAQ ratio compression does not compromise the ability to detect regulated elements in these experiments.     

A technically detailed and pragmatic protocol for quantitative serum proteomics using iTRAQ

Blood is recognised as a highly important source of disease-related biomarkers, and proteomic approaches for identifying novel blood-borne biomarkers are in demand. The complexity and dynamic protein concentration range of plasma/serum however complicates the analysis process. A number of strategies for simplification of blood prior to proteomic analysis have been developed. In addition, methods for quantifying the levels of proteins in samples, such as isobaric tags for relative and absolute quantification (iTRAQ) are emerging. However, the successful application of these procedures is not always straightforward and technical hurdles must be overcome. Here we provide a technically detailed working protocol for iTRAQ-based quantification of serum proteins following immunodepletion of high abundance proteins. To improve the number of proteins identified and quantified we have introduced several modifications to the standard iTRAQ protocol. We report identifications of 217 proteins (5773 peptides) with a false discovery rate of 1% or 254 proteins with 95% confidence, respectively. Relative quantification data were obtained for 234 (95% confidence) serum proteins, including species present in the concentration range of tissue leakage factors. The samples described here relate to pancreatic cancer; however the protocol can be applied to serum from other control or disease types.     

How proteomics reveals potential biomarkers in brain diseases

The brain is complex, and so are the proteomics studies of brain tissue and its diseases, including Alzheimer’s Disease, Parkinson’s Disease and schizophrenia. In this review, general considerations and strategies of proteomics technologies, the advantages and challenges as well as the special needs for brain tissue are described and summarized. In addition, the results of the first studies are presented including a quality evaluation of the candidate proteins for these diseases. A paragraph is dedicated to the efforts of standardization in this field.     

How proteomics reveals potential biomarkers in brain diseases

The brain is complex, and so are the proteomics studies of brain tissue and its diseases, including Alzheimer's Disease, Parkinson's Disease and schizophrenia. In this review, general considerations and strategies of proteomics technologies, the advantages and challenges as well as the special needs for brain tissue are described and summarized. In addition, the results of the first studies are presented including a quality evaluation of the candidate proteins for these diseases. A paragraph is dedicated to the efforts of standardization in this field.     

Protein profiling of human lung telocytes and microvascular endothelial cells using iTRAQ quantitative proteomics

Telocytes (TCs) are described as a particular type of cells of the interstitial space ( www.telocytes.com ). Their main characteristics are the very long telopodes with alternating podoms and podomers. Recently, we performed a comparative proteomic analysis of human lung TCs with fibroblasts, demonstrating that TCs are clearly a distinct cell type. Therefore, the present study aims to reinforce this idea by comparing lung TCs with endothelial cells (ECs), since TCs and ECs share immunopositivity for CD34. We applied isobaric tag for relative and absolute quantification (iTRAQ) combined with automated 2‐D nano‐ESI LC‐MS/MS to analyse proteins extracted from TCs and ECs in primary cell cultures. In total, 1609 proteins were identified in cell cultures. 98 proteins (the 5th day), and 82 proteins (10th day) were confidently quantified (screened by two‐sample t‐test, P < 0.05) as up‐ or down‐regulated (fold change >2). We found that in TCs there are 38 up‐regulated proteins at the 5th day and 26 up‐regulated proteins at the 10th day. Bioinformatics analysis using Panther revealed that the 38 proteins associated with TCs represented cellular functions such as intercellular communication (via vesicle mediated transport) and structure morphogenesis, being mainly cytoskeletal proteins and oxidoreductases. In addition, we found 60 up‐regulated proteins in ECs e.g.: cell surface glycoprotein MUC18 (15.54‐fold) and von Willebrand factor (5.74‐fold). The 26 up‐regulated proteins in TCs at 10th day, were also analysed and confirmed the same major cellular functions, while the 56 down‐regulated proteins confirmed again their specificity for ECs. In conclusion, we report here the first extensive comparison of proteins from TCs and ECs using a quantitative proteomics approach. Our data show that TCs are completely different from ECs. Protein expression profile showed that TCs play specific roles in intercellular communication and intercellular signalling. Moreover, they might inhibit the oxidative stress and cellular ageing and may have pro‐proliferative effects through the inhibition of apoptosis. The group of proteins identified in this study needs to be explored further for the role in pathogenesis of lung disease.     

Label-free quantitative proteomics reveals differentially regulated proteins influencing urolithiasis

Urinary proteins have been implicated as inhibitors of kidney stone formation (urolithiasis). As a proximal fluid, prefiltered by the kidneys, urine is an attractive biofluid for proteomic analysis in urologic conditions. However, it is necessary to correct for variations in urinary concentration. In our study, individual urine samples were normalized for this variation by using a total protein to creatinine ratio. Pooled urine samples were compared in two independent experiments. Differences between the urinary proteome of stone formers and nonstone-forming controls were characterized and quantified using label-free nano-ultraperformance liquid chromatography high/low collision energy switching analysis. There were 1063 proteins identified, of which 367 were unique to the stone former groups, 408 proteins were unique to the control pools, and 288 proteins were identified for comparative quantification. Proteins found to be unique in stone-formers were involved in carbohydrate metabolism pathways and associated with disease states. Thirty-four proteins demonstrated a consistent >twofold change between stone formers and controls. For ceruloplasmin, one of the proteins was shown to be more than twofold up-regulated in the stone-former pools, this observation was validated in individuals by enzyme-linked immunosorbent assay. Moreover, in vitro crystallization assays demonstrated ceruloplasmin had a dose-dependent increase on calcium oxalate crystal formation. Taken together, these results may suggest a functional role for ceruloplasmin in urolithiasis.     

IsobariQ: software for isobaric quantitative proteomics using IPTL, iTRAQ, and TMT

Isobaric peptide labeling plays an important role in relative quantitative comparisons of proteomes. Isobaric labeling techniques utilize MS/MS spectra for relative quantification, which can be either based on the relative intensities of reporter ions in the low mass region (iTRAQ and TMT) or on the relative intensities of quantification signatures throughout the spectrum due to isobaric peptide termini labeling (IPTL). Due to the increased quantitative information found in MS/MS fragment spectra generated by the recently developed IPTL approach, new software was required to extract the quantitative information. IsobariQ was specifically developed for this purpose; however, support for the reporter ion techniques iTRAQ and TMT is also included. In addition, to address recently emphasized issues about heterogeneity of variance in proteomics data sets, IsobariQ employs the statistical software package R and variance stabilizing normalization (VSN) algorithms available therein. Finally, the functionality of IsobariQ is validated with data sets of experiments using 6-plex TMT and IPTL. Notably, protein substrates resulting from cleavage by proteases can be identified as shown for caspase targets in apoptosis.     

Aberrant Mucin5B expression in lung adenocarcinomas detected by iTRAQ labeling quantitative proteomics and immunohistochemistry

Background

Lung cancer is the number one cause of cancer-related deaths in the United States and worldwide. The complex protein changes and/or signature of protein expression in lung cancer, particularly in non-small cell lung cancer (NSCLC) has not been well defined. Although several studies have investigated the protein profile in lung cancers, the knowledge is far from complete. Among early studies, mucin5B (MUC5B) has been suggested to play an important role in the tumor progression. MUC5B is the major gel-forming mucin in the airway. In this study, we investigated the overall protein profile and MUC5B expression in lung adenocarcinomas, the most common type of NSCLCs.

Methods

Lung adenocarcinoma tissue in formalin-fixed paraffin-embedded (FFPE) blocks was collected and microdissected. Peptides from 8 tumors and 8 tumor-matched normal lung tissue were extracted and labeled with 8-channel iTRAQ reagents. The labeled peptides were identified and quantified by LC-MS/MS using an LTQ Orbitrap Velos mass spectrometer. MUC5B expression identified by iTRAQ labeling was further validated using immunohistochemistry (IHC) on tumor tissue microarray (TMA).

Results

A total of 1288 peptides from 210 proteins were identified and quantified in tumor tissues. Twenty-two proteins showed a greater than 1.5-fold differences between tumor and tumor-matched normal lung tissues. Fifteen proteins, including MUC5B, showed significant changes in tumor tissues. The aberrant expression of MUC5B was further identified in 71.1% of lung adenocarcinomas in the TMA.

Discussions

A subset of tumor-associated proteins was differentially expressed in lung adenocarcinomas. The differential expression of MUC5B in lung adenocarcinomas suggests its role as a potential biomarker in the detection of adenocarcinomas.     

Investigation of plasma biomarkers in HIV-1/HCV mono- and coinfected individuals by multiplex iTRAQ quantitative proteomics

The analysis of plasma samples from HIV-1/HCV mono- and coinfected individuals by quantitative proteomics is an efficient strategy to investigate changes in protein abundances and to characterize the proteins that are the effectors of cellular functions involved in viral pathogenesis. In this study, the infected and healthy plasma samples (in triplicate) were treated with ProteoMiner beads to equalize protein concentrations and subjected to 4-plex iTRAQ labeling and liquid chromatography/mass spectrometry (LC-MS/MS) analysis. A total of 70 proteins were identified with high confidence in the triplicate analysis of plasma proteins and 65% of the proteins were found to be common among the three replicates. Apolipoproteins and complement proteins are the two major classes of proteins that exhibited differential regulation. The results of quantitative analysis revealed that APOA2, APOC2, APOE, C3, HRG proteins were upregulated in the plasma of all the three HIV-1 mono-, HCV mono-, and coinfected patient samples compared to healthy control samples. Ingenuity pathway analysis (IPA) of the upregulated proteins revealed that they are implicated in the hepatic lipid metabolism, inflammation, and acute-phase response signaling pathways. Thus, we identified several differentially regulated proteins in HIV-1/HCV mono and coinfected plasma samples that may be potential biomarkers for liver disease.     

A noise model for mass spectrometry based proteomics

Motivation: Mass spectrometry data are subjected to considerablenoise. Good noise models are required for proper detection andquantification of peptides. We have characterized noise in bothquadrupole time-of-flight (Q-TOF) and ion trap data, and haveconstructed models for the noise. Results: We find that the noise in Q-TOF data from Applied BiosystemsQSTAR fits well to a combination of multinomial and Poissonmodel with detector dead-time correction. In comparison, iontrap noise from Agilent MSD-Trap-SL is larger than the Q-TOFnoise and is proportional to Poisson noise. We then demonstratethat the noise model can be used to improve deisotoping forpeptide detection, by estimating appropriate cutoffs of thegoodness of fit parameter at prescribed error rates. The noisemodels also have implications in noise reduction, retentiontime alignment and significance testing for biomarker discovery. Contact: pdu{at}us.ibm.com Supplementary information: Supplementary data are availableat Bioinfomatics Online. Associate Editor: Olga Troyanskaya     

iTRAQ proteomics analysis reveals that PI3K is highly associated with bupivacaine‐induced neurotoxicity pathways

Bupivacaine, a commonly used local anesthetic, has potential neurotoxicity through diverse signaling pathways. However, the key mechanism of bupivacaine‐induced neurotoxicity remains unclear. Cultured human SH‐SY5Y neuroblastoma cells were treated (bupivacaine) or untreated (control) with bupivacaine for 24 h. Compared to the control group, bupivacaine significantly increased cyto‐inhibition, cellular reactive oxygen species, DNA damage, mitochondrial injury, apoptosis (increased TUNEL‐positive cells, cleaved caspase 3, and Bcl‐2/Bax), and activated autophagy (enhanced LC3II/LC3I ratio). To explore changes in protein expression and intercommunication among the pathways involved in bupivacaine‐induced neurotoxicity, an 8‐plex iTRAQ proteomic technique and bioinformatics analysis were performed. Compared to the control group, 241 differentially expressed proteins were identified, of which, 145 were up‐regulated and 96 were down‐regulated. Bioinformatics analysis of the cross‐talk between the significant proteins with altered expression in bupivacaine‐induced neurotoxicity indicated that phosphatidyl‐3‐kinase (PI3K) was the most frequently targeted protein in each of the interactions. We further confirmed these results by determining the downstream targets of the identified signaling pathways (PI3K, Akt, FoxO1, Erk, and JNK). In conclusion, our study demonstrated that PI3K may play a central role in contacting and regulating the signaling pathways that contribute to bupivacaine‐induced neurotoxicity.     

Advances in quantitative proteomics

Large-scale protein quantification has become a major proteomics application in many areas of biological and medical research. During the past years, different techniques have been developed, including gel-based such as differential in-gel electrophoresis (DIGE) and liquid chromatography-based such as isotope labeling and label-free quantification. These quantitative proteomics tools hold significant promise for biomarker discovery, diagnostic and therapeutic applications. They are also important for research in functional genomics and systems biology towards basic understanding of molecular networks and pathway interactions. In this review, we summarize current technologies in quantitative proteomics and discuss recent applications of the technologies.     

A comparison of the bovine uterine and plasma proteome using iTRAQ proteomics

Early embryo loss is a key factor affecting fertility in dairy and beef herds. Prior to implantation, the bovine embryo spends around 16 days free-floating in the uterine environment and is dependent on the composition of uterine fluid for normal growth and development. However, there is a lack of information regarding the protein composition of the bovine uterus and how it relates to plasma. In this study, uterine flushings (UF) (n = 6) and blood plasma (n = 4) were collected from beef heifers on day 7 of the oestrous cycle, albumin depleted and compared using iTRAQ proteomics. A total of 35 proteins were higher and 18 were lower in UF including metabolic enzymes, proteins with anti-oxidant activity and those involved in modulation of the immune response. This study confirms the dynamic nature of the bovine uterine proteome and that it differs from plasma. Factors affecting the uterine proteome and how it impacts on embryo survival warrant further study.     

Comparative iTRAQ proteomics revealed proteins associated with horn development in yak

Background

The practice of dehorning yak raises animal safety concerns, which have been addressed by selective breeding to obtain genetically hornless yak. The POLLED locus in yak has been studied extensively; however, little is known regarding the proteins that regulate horn bud development.

Methods

A differential proteomic analysis was performed to compare the skin from the horn bud region of polled yak fetuses and the horn bud tissue of horned yak fetuses using isobaric tags for relative and absolute quantitation (iTRAQ) technology coupled with 2D LC-MS/MS.

Results

One hundred differentially abundant proteins (DAPs) were identified. Of these, 29 were up-regulated and 71 were down-regulated in skin from the horn bud region of polled fetuses when compared to the horn bud tissue of horned fetuses. Bioinformatics analyses showed that the up-regulated DAPs were mainly associated with metabolic activities, while the down-regulated DAPs were significantly enriched in cell adhesion and cell movement activities.

Conclusions

We concluded that some important proteins were associated with cell adhesion, cell motility, keratinocyte differentiation, cytoskeleton organization, osteoblast differentiation, and fatty acid metabolism during horn bud development. These results advance our understanding of the molecular mechanisms underlying horn development.

     

Quantitative chemical proteomics reveals new potential drug targets in head and neck cancer

Tumors of the head and neck represent a molecularly diverse set of human cancers, but relatively few proteins have actually been shown to drive the disease at the molecular level. To identify new targets for individualized diagnosis or therapeutic intervention, we performed a kinase centric chemical proteomics screen and quantified 146 kinases across 34 head and neck squamous cell carcinoma (HNSCC) cell lines using intensity-based label-free mass spectrometry. Statistical analysis of the profiles revealed significant intercell line differences for 42 kinases (p < 0.05), and loss of function experiments using siRNA in high and low expressing cell lines identified kinases including EGFR, NEK9, LYN, JAK1, WEE1, and EPHA2 involved in cell survival and proliferation. EGFR inhibition by the small molecule inhibitors lapatinib, gefitinib, and erlotinib as well as siRNA led to strong reduction of viability in high but not low expressing lines, confirming EGFR as a drug target in 10-20% of HNSCC cell lines. Similarly, high, but not low EPHA2-expressing cells showed strongly reduced viability concomitant with down-regulation of AKT and ERK signaling following EPHA2 siRNA treatment or EPHA1-Fc ligand exposure, suggesting that EPHA2 is a novel drug target in HNSCC. This notion is underscored by immunohistochemical analyses showing that high EPHA2 expression is detected in a subset of HNSCC tissues and is associated with poor prognosis. Given that the approved pan-SRC family kinase inhibitor dasatinib is also a very potent inhibitor of EPHA2, our findings may lead to new therapeutic options for HNSCC patients. Importantly, the strategy employed in this study is generic and therefore also of more general utility for the identification of novel drug targets and molecular pathway markers in tumors. This may ultimately lead to a more rational approach to individualized cancer diagnosis and therapy.     

Study of nitrate stress in Desulfovibrio vulgaris Hildenborough using iTRAQ proteomics.

The response of Desulfovibrio vulgaris Hildenborough (DvH), a sulphate-reducing bacterium, to nitrate stress was examined using quantitative proteomic analysis. DvH was stressed with 105 mM sodium nitrate (NaNO(3)), a level that caused a 50% inhibition in growth. The protein profile of stressed cells was compared with that of cells grown in the absence of nitrate using the iTRAQ peptide labelling strategy and tandem liquid chromatography separation coupled with mass spectrometry (quadrupole time-of-flight) detection. A total of 737 unique proteins were identified by two or more peptides, representing 22% of the total DvH proteome and spanning every functional category. The results indicate that this was a mild stress, as proteins involved in central metabolism and the sulphate reduction pathway were unperturbed. Proteins involved in the nitrate reduction pathway increased. Increases seen in transport systems for proline, glycine-betaine and glutamate indicate that the NaNO(3) exposure led to both salt stress and nitrate stress. Up-regulation observed in oxidative stress response proteins (Rbr, RbO, etc.) and a large number of ABC transport systems as well as in iron-sulphur-cluster-containing proteins, however, appear to be specific to nitrate exposure. Finally, a number of hypothetical proteins were among the most significant changers, indicating that there may be unknown mechanisms initiated upon nitrate stress in DvH.     

Comprehensive comparison of iTRAQ and label-free LC-based quantitative proteomics approaches using two Chlamydomonas reinhardtii strains of interest for biofuels engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approaches--iTRAQ and label-free--were implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two Chlamydomonas reinhardtii strains in the context of alternative biofuels production. The strain comparison includes sta6 (a starch-less mutant of cw15) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain cw15 (a cell wall-deficient C. reinhardtii strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between cw15 and sta6 reveals already known but also new mechanisms likely responsible for the production of lipids in sta6 and sets the baseline for future studies aimed at engineering these strains for high oil production.     

Label-free quantitative proteomics reveals differentially regulated proteins in the latex of sticky diseased Carica papaya L. plants

Papaya meleira virus (PMeV) is so far the only described laticifer-infecting virus, the causal agent of papaya (Carica papaya L.) sticky disease. The effects of PMeV on the laticifers' regulatory network were addressed here through the proteomic analysis of papaya latex. Using both 1-DE- and 1D-LC-ESI-MS/MS, 160 unique papaya latex proteins were identified, representing 122 new proteins in the latex of this plant. Quantitative analysis by normalized spectral counting revealed 10 down-regulated proteins in the latex of diseased plants, 9 cysteine proteases (chymopapain) and 1 latex serine proteinase inhibitor. A repression of papaya latex proteolytic activity during PMeV infection was hypothesized. This was further confirmed by enzymatic assays that showed a reduction of cysteine-protease-associated proteolytic activity in the diseased papaya latex. These findings are discussed in the context of plant responses against pathogens and may greatly contribute to understand the roles of laticifers in plant stress responses.