iTop-Q: an Intelligent Tool for Top-down Proteomics Quantitation Using DYAMOND Algorithm.

Top-down proteomics using liquid chromatogram coupled with mass spectrometry has been increasingly applied for analyzing intact proteins to study genetic variation, alternative splicing, and post-translational modifications (PTMs) of the proteins (proteoforms). However, only a few tools have been developed for charge state deconvolution, monoisotopic/average molecular weight determination and quantitation of proteoforms from LC-MS1 spectra. Though Decon2LS and MASH Suite Pro have been available to provide intraspectrum charge state deconvolution and quantitation, manual processing is still required to quantify proteoforms across multiple MS1 spectra. An automated tool for interspectrum quantitation is a pressing need. Thus, in this paper, we present a user-friendly tool, called iTop-Q (intelligent Top-down Proteomics Quantitation), that automatically performs large-scale proteoform quantitation based on interspectrum abundance in top-down proteomics. Instead of utilizing single spectrum for proteoform quantitation, iTop-Q constructs extracted ion chromatograms (XICs) of possible proteoform peaks across adjacent MS1 spectra to calculate abundances for accurate quantitation. Notably, iTop-Q is implemented with a newly proposed algorithm, called DYAMOND, using dynamic programming for charge state deconvolution. In addition, iTop-Q performs proteoform alignment to support quantitation analysis across replicates/samples. The performance evaluations on an in-house standard data set and a public large-scale yeast lysate data set show that iTop-Q achieves highly accurate quantitation, more consistent quantitation than using intraspectrum quantitation. Furthermore, the DYAMOND algorithm is suitable for high charge state deconvolution and can distinguish shared peaks in coeluting proteoforms. iTop-Q is publicly available for download at http://ms.iis.sinica.edu.tw/COmics/Software_iTop-Q .

Metabolite marker discovery for the detection of bladder cancer by comparative metabolomics.

Bladder cancer is one of the most common urinary tract carcinomas in the world. Urine metabolomics is a promising approach for bladder cancer detection and marker discovery since urine is in direct contact with bladder epithelia cells; metabolites released from bladder cancer cells may be enriched in urine samples. In this study, we applied ultra-performance liquid chromatography time-of-flight mass spectrometry to profile metabolite profiles of 87 samples from bladder cancer patients and 65 samples from hernia patients. An OPLS-DA classification revealed that bladder cancer samples can be discriminated from hernia samples based on the profiles. A marker discovery pipeline selected six putative markers from the metabolomic profiles. An LLE clustering demonstrated the discriminative power of the chosen marker candidates. Two of the six markers were identified as imidazoleacetic acid whose relation to bladder cancer has certain degree of supporting evidence. A machine learning model, decision trees, was built based on the metabolomic profiles and the six marker candidates. The decision tree obtained an accuracy of 76.60%, a sensitivity of 71.88%, and a specificity of 86.67% from an independent test.

iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination.

Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤ 0.19) when quantifying the two internal standards and had higher abundance correlation (≥ 0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html.

Insights into the poor prognosis of allopurinol-induced severe cutaneous adverse reactions: the impact of renal insufficiency, high plasma levels of oxypurinol and granulysin.

OBJECTIVE: Allopurinol, an antihyperuricaemic agent, is one of the common causes of life-threatening severe cutaneous adverse reactions (SCAR), including drug rash with eosinophilia and systemic symptoms (DRESS), Stevens-Johnson syndrome (SJS) and toxic epidermal necrosis (TEN). The prognostic factors for allopurinol-related SCAR remain unclear. This study aimed to investigate the relationship of dosing, renal function, plasma levels of oxypurinol and granulysin (a cytotoxic protein of SJS/TEN), the disease severity and mortality in allopurinol-SCAR. METHODS: We prospectively enrolled 48 patients with allopurinol-SCAR (26 SJS/TEN and 22 DRESS) and 138 allopurinol-tolerant controls from 2007 to 2012. The human leucocyte antigen (HLA)-B*58:01 status, plasma concentrations of oxypurinol and granulysin were determined. RESULTS: In this cohort, HLA-B*58:01 was strongly associated with allopurinol-SCAR (p<0.001, OR (95% CI) 109 (25 to 481)); however, the initial/maintenance dosages showed no relationship with the disease. Poor renal function was significantly associated with the delayed clearance of plasma oxypurinol, and increased the risk of allopurinol-SCAR (p<0.001, OR (95% CI) 8.0 (3.9 to 17)). Sustained high levels of oxypurinol after allopurinol withdrawal correlated with the poor prognosis of allopurinol-SCAR. In particular, the increased plasma levels of oxypurinol and granulysin linked to the high mortality of allopurinol-SJS/TEN (p<0.01), and strongly associated with prolonged cutaneous reactions in allopurinol-DRESS (p<0.05). CONCLUSIONS: Impaired renal function and increased plasma levels of oxypurinol and granulysin correlated with the poor prognosis of allopurinol-SCAR. Allopurinol prescription is suggested to be avoided in subjects with renal insufficiency and HLA-B*58:01 carriers. An early intervention to increase the clearance of plasma oxypurinol may improve the prognosis of allopurinol-SCAR.

Mass accuracy improvement of reversed-phase liquid chromatography/electrospray ionization mass spectrometry based urinary metabolomic analysis by post-run calibration using sodium formate cluster ions.

RATIONALE: Typically, a batch metabolomics analysis using liquid chromatography/electrospray ionization time-of-flight mass spectrometry (LC/ESI-TOF MS) takes 2 to 3 days. However, the mass accuracy - which has an important influence on metabolite identification - can drift by as much as about 17 ppm in such a time period. In an untargeted urinary metabolomics analysis by reversed-phase liquid chromatography (RPLC)/ESI-MS, the signals of sodium formate cluster ions were detected at the column-washing step. The cluster ions were used to calibrate the mass spectrometer for more accurate detection. METHODS: The spectra were calibrated post-run by the sodium formate cluster ions, which were used as the internal standard, in order to improve the mass accuracy. RESULTS: In the analysis of urine samples, we calibrated the spectra acquired by the micrOTOF with the sodium cluster ions. In positive mode ESI, the average errors of these cluster ions were improved to ±0.48 ppm and in negative mode ESI, to ±0.94 ppm after calibration. The mass accuracy remained within ±0.01 ppm over the duration of 6.25 days. An error window of 4 ppm appears to be suitable for metabolite identification when using post-calibration. CONCLUSIONS: The results showed that sodium formate cluster ions could be utilized for the calibration of LC/ESI-TOF MS and the average instrumental errors could be maintained at low levels for long-term analyses. This method could be applied not only to urine sample, but also to low sodium samples, such as saliva, by dissolving the sample in 1 µM sodium formate solution. This method provides a good solution for accurate mass detection of metabolomic analysis.

The dysfunction of hepatic transcriptional factors in mice with Huntington's Disease.

Huntington's Disease (HD) is an autosomal dominant neurodegenerative disease caused by a CAG trinucleotide expansion in the Huntingtin (Htt) gene. The resultant mutant Htt protein (mHtt) forms aggregates in the brain and several peripheral tissues (e.g., the liver), and causes devastating widespread pathology. Since aggregates of mHtt have been found in the liver, defects in liver function might contribute to peripheral abnormalities in HD mice. We previously reported that two crucial transcription factors PPARγ (peroxisome proliferator-activated receptor-γ) and C/EBPα (CCAAT/enhancer-binding protein α) are potential therapeutic targets of HD. We herein demonstrate that the transcript level of PPARγ was markedly downregulated in the livers of a transgenic mouse model of HD (R6/2). Treatment of R6/2 mice with an agonist of PPARγ (thiazolidinedione, TZD) normalized the reduced PPARγ transcript. By reducing Htt aggregates and thereby ameliorating the recruitment of PPARγ into Htt aggregates, TZD treatment also elevated the availability of the PPARγ level and subsequently normalized the expression of its downstream genes [including PGC-1α (PPAR coactivator-1α) and several mitochondrial genes] and C/EBPα in the liver. The aforementioned protective effects appeared to be exerted by a direct activation of the PPARγ agonist (rosiglitazone) because rosiglitazone reduced mHtt aggregates and rescued energy deficiency in a hepatoma cell line (HepG2). These findings show that the impairment of PPARγ contributes to the liver dysfunction observed in HD. Treatment with PPARγ agents (TZD and rosiglitazone) enhanced the function of PPARγ, and might lead to therapeutic benefits.

Design and structural analysis of novel pharmacophores for potent and selective peroxisome proliferator-activated receptor gamma agonists.

Utilizing medicinal chemistry design strategies such as benzo splitting and ring expansion, we converted PPARalpha/gamma dual agonist 1 to selective PPARgamma agonists 19 and 20. Compounds 19 and 20 were 2- to 4-fold better than rosiglitazone at PPARgamma receptor, with 80- to 100-fold PPARgamma selectivity over PPARalpha receptor. X-ray cocrystal studies in PPARgamma and modeling studies in PPARalpha give molecular insights for the improved PPARgamma potency and selectivity for 19 when compared to 1.

Liquid chromatography-mass spectrometry in metabolite profiling.

Recent advances in the use of liquid chromatography-mass spectrometry for the study of metabolomics are reviewed. Sample preparations of biofluids and practical aspects of ultra-high pressure liquid chromatography are discussed. Applicability of different kinds of mass spectrometers for metabolite profiling is described. New tools-ion mobility spectroscopy and automated chip-based nanoelectrospray system with potentials to be applied in the metabolomics analysis are described.

Targeted protein quantitation and profiling using PVDF affinity probe and MALDI-TOF MS.

Development of a rapid, effective, and highly specific platform for target identification in complex biofluids is one of the most important tasks in proteomic research. Taking advantage of the natural hydrophobic interaction of PVDF with probe protein, a simple and effective method was developed for protein quantitation and profiling. Using antibody-antigen interactions as a proof-of-concept system, the targeted plasma proteins, serum amyloid P (SAP), serum amyloid A (SAA), and C-reactive protein (CRP), could be selectively isolated and enriched from human plasma by antibody-immobilized PVDF membrane and directly identified by MALDI-TOF MS without additional elution step. The approach was successfully applied to human plasma for rapid quantitation and variant screening of SAP, SAA, and CRP in healthy individuals and patients with gastric cancer. The triplexed on-probe quantitative analysis revealed significant overexpression of CRP and SAA in gastric cancer group, consistent with parallel ELISA measurements and pathological progression and prognostic significance reported in previous literatures. Furthermore, the variant mass profiling of the post-translationally modified forms revealed a high occurrence of de-sialic acid SAP in patients with gastric cancer. Due to the versatile assay design, ease of probe preparation without chemical synthesis, and compatibility with MALDI-TOF MS analysis, the methodology may be useful for target protein characterization, functional proteomics, and screening in clinical proteomics.

HLA-B*1502-bound peptides: implications for the pathogenesis of carbamazepine-induced Stevens-Johnson syndrome.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) can involve MHC-restricted presentation of a drug or its metabolites for T-cell activation. HLA-B(*)1502 tightly associated with carbamazepine (CBZ) induced these conditions in a Han Chinese population. OBJECTIVE: We sought to identify HLA-B(*)1502-bound peptides that might be involved in CBZ-induced SJS/TEN. METHODS: Soluble HLA-B(*)1502 was used to identify bound peptides in the presence and absence of CBZ by using liquid chromatography-tandem mass spectrometry. Peptide-binding assays were performed to detect the specific interaction between the HLA molecule and the identified peptides. Mass spectra were compared to detect CBZ-modified peptides. RESULTS: We identified more than 145 peptides bound to HLA-B(*)1502. In 13 of 15 peptides examined, we functionally confirmed their specificity with binding assays. Preferable uses of these peptides at the anchoring residues P2 and P9 were similar to those observed in other HLA-B alleles in the Han Chinese population. However, the preferable use of serine residues at the nonanchoring position (P) 5, P6, P7, and P8 appeared to be unique for the B(*)1502 peptides. No specific CBZ-modified peptides were detected when we compared the mass spectra of peptides detected in the presence or absence of the drug. CONCLUSION: Noncovalent interaction between a drug and an HLA complex might contribute to cytotoxic T cell-mediated cell death in patients with SJS/TEN. CLINICAL IMPLICATIONS: An understanding of pharmacologic interaction of drugs with an HLA complex might lead to safer drugs that avoid SJS/TEN.

Systematic uncovering of multiple pathways underlying the pathology of Huntington disease by an acid-cleavable isotope-coded affinity tag approach.

Huntington disease (HD) is an autosomal dominant neurodegenerative disease that results from a CAG (glutamine) trinucleotide expansion in exon 1 of huntingtin (Htt). The aggregation of mutant Htt has been implicated in the progression of HD. The earliest degeneration occurs in the striatum. To identify proteins critical for the progression of HD, we applied acid-cleavable ICAT technology to quantitatively determine changes in protein expressions in the striatum of a transgenic HD mouse model (R6/2). The cysteine residues of striatal proteins from HD and wild-type mice were labeled, respectively, with the heavy and light forms of the ICAT reagents. Samples were trypsinized, uncovered by avidin affinity chromatography, and analyzed by nano-LC-MS/MS. Western blot analyses were used to confirm and to calibrate the ICAT ratios. Linear regression was used to uncover a group of proteins that exhibited consistent changes. In two independent ICAT experiments, we identified 427 cysteine-containing striatal proteins among which approximately 66% (203 proteins) were detected in both ICAT experiments. Approximately two-thirds of proteins identified in each ICAT experiment were detected in both ICAT experiments. In total, 68 proteins with altered expressions in HD mice were identified. Elevated expressions of two down-regulated proteins (14-3-3sigma and FKBP12) effectively reduced Htt aggregates in a striatal cell line, supporting the functional relevance of the above findings. Collectively by using a well defined protocol for data analysis, large scale comparisons of protein expressions by ICAT can be reliable and can provide valuable clues for identifying proteins critical for pathophysiological functions.

Improved analysis of membrane protein by PVDF-aided, matrix-assisted laser desorption/ionization mass spectrometry.

Characterization of membrane proteins remains an analytical challenge because of difficulties associated with tedious isolation and purification. This study presents the utility of the polyvinylidene difluoride (PVDF) membrane for direct sub-proteome profiling and membrane protein characterization by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The hydrophobic adsorption of protein, particularly membrane proteins, on the PVDF surface enables efficient on-PVDF washing to remove high concentrations of detergents and salts, such as up to 5% sodium dodecyl sulfate (SDS). The enhanced spectrum quality for MALDI detection is particularly notable for high molecular weight proteins. By using on-PVDF washing prior to MALDI detection, we obtained protein profiles of the detergent-containing and detergent-insoluble membrane fractions from Methylococcus capsulatus (Bath). Similar improvements of signal-to-noise ratios were shown on the MALDI spectra for proteins electroblotted from SDS-polyacrylamide gel electrophoresis (SDS-PAGE) onto the PVDF membrane. We have applied this strategy to obtain intact molecular weights of the particulate methane monooxygenase (pMMO) composed of three intrinsic membrane-bound proteins, PmoA, PmoB, and PmoC. Together with peptide sequencing by tandem mass spectrometry, post-translational modifications including N-terminal acetylation of PmoA and PmoC and alternative C-terminal truncation of PmoB were identified. The above results show that PVDF-aided MALDI-MS can be an effective approach for profiling and characterization of membrane proteins.

Papain-like protease 2 (PLP2) from severe acute respiratory syndrome coronavirus (SARS-CoV): expression, purification, characterization, and inhibition.

Viral proteases are essential for pathogenesis and virulence of severe acute respiratory syndrome coronavirus (SARS-CoV). Little information is available on SARS-CoV papain-like protease 2 (PLP2), and development of inhibitors against PLP2 is attractive for antiviral therapy. Here, we report the characterization of SARS-CoV PLP2 (from residues 1414 to 1858) purified from baculovirus-infected insect cells. We demonstrate that SARS-CoV PLP2 by itself differentially cleaves between the amino acids Gly180 and Ala181, Gly818 and Ala819, and Gly2740 and Lys2741 of the viral polypeptide pp1a, as determined by reversed-phase high-performance liquid chromatography analysis coupled with mass spectrometry. This protease is especially selective for the P1, P4, and P6 sites of the substrate. The study demonstrates, for the first time among coronaviral PLPs, that the reaction mechanism of SARS-CoV PLP2 is characteristic of papain and compatible with the involvement of the catalytic dyad (Cys)-S(-)/(His)-Im(+)H ion pair. With a fluorogenic inhibitor-screening platform, we show that zinc ion and its conjugates potently inhibit the enzymatic activity of SARS-CoV PLP2. In addition, we provided evidence for evolutionary reclassification of SARS-CoV. The results provide important insights into the biochemical properties of the coronaviral PLP family and a promising therapeutic way to fight SARS-CoV.

MAPK-mediated phosphorylation of GATA-1 promotes Bcl-XL expression and cell survival.

In the interleukin 3-dependent hematopoietic cell line Ba/F3, inhibition of mitogen-activated protein kinase, a member of the MAPK/c-Jun N-terminal kinase/stress-activated protein kinase kinase family that plays an important role in cell growth and death control, rapidly leads to severe apoptosis. However, most of the antiapoptotic substrates of MAPK remain to be identified. Here we report that, upon interleukin-3 stimulation of Ba/F3 cells, the transcription factor GATA-1 is strongly phosphorylated at residue serine 26 by a MAPK-dependent pathway. Phosphorylation of GATA-1 increases GATA-1-mediated transcription of the E4bp4 survival gene without significantly changing the DNA-binding affinity of GATA-1. Further characterization of GATA-1 phosphorylation site mutants revealed that the antiapoptotic function of GATA-1 is strongly dependent upon its phosphorylation at the Ser-26 position and is probably mediated through its up-regulation of Bcl-X(L) expression. Taken together, our data demonstrate that MAPK-dependent GATA-1 phosphorylation is important for its transactivation of the E4bp4 gene, Bcl-X(L) expression and cell survival. Therefore, GATA-1 may represent a novel MAPK substrate that plays an essential role in a cytokine-mediated antiapoptotic response.