pFind Studio: a computational solution for mass spectrometry-based proteomics
2019
Nature Biotechnology2019. Devabhaktuni, A et al.
Stanford Univ, Stanford Sch Med, Dept Chem & Syst Biol, Stanford, CA 94305 USA.
ABSTRACT:Although mass spectrometry is well suited to identifying thousands of potential protein post-translational modifications (PTMs), it has historically been biased towards just a few. To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of covering enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model that we optimized for PTM assignments. We applied TagGraph to a published human proteomic dataset of 25 million mass spectra and tripled confident spectrum identifications compared to its original analysis. We identified thousands of modification types on almost 1 million sites in the proteome. We show alternative contexts for highly abundant yet understudied PTMs such as proline hydroxylation, and its unexpected association with cancer mutations. By enabling broad characterization of PTMs, TagGraph informs as to how their functions and regulation intersect.
Use: pNovo
EuPA Open Proteomics2019. Eggers, Britta et al.
Ruhr University Bochum, Faculty of Medicine, Medizinisches Proteom-Center, Gesundheitscampus 4, D-44801, Bochum, Germany
ABSTRACT:In a common proteomics analysis today, the origins of our sample in the vial are known and therefore a database dependent approach to identify the containing peptides can be used. The first YPIC challenge though provided us with 19 synthetic peptides, which together formed an English sentence. For the identification of these peptides, a de-novo approach was used, which brought us together with an internet search engine to the hidden sentence. But only having the sentence was not sufficient for us, we also wanted to identify as many as possible of the spectra in our data. Therefore, we created and refined a database approach from the de-novo method and finally could identify the peptide-sentence with a good overlap. 2019 Published by Elsevier B.V. on behalf of European Proteomics Association (EuPA).
Use: pNovo
International Journal of Molecular Sciences2019. Lundstrom, SL et al.
Karolinska Inst, Dept Med Biochem & Biophys, Div Physiol Chem 1, S-17177 Stockholm, Sweden.
ABSTRACT:Sarcoidosis is a systemic interstitial lung disease of unknown aetiology. Less invasive diagnostics are needed to decipher disease pathology and to distinguish sub-phenotypes. Here we test if SpotLight proteomics, which combines de novo MS/MS sequencing of enriched IgG and co-extracted proteins with subsequent label-free quantification of new and known peptides, can differentiate controls and sarcoidosis phenotypes (Lofgrens and non-Lofgrens syndrome, LS and nonLS). Intra-individually matched IgG enriched from serum and bronchial lavage fluid (BALF) from controls (n = 12), LS (n = 11) and nonLS (n = 12) were investigated. High-resolution mass-spectrometry SpotLight proteomics and uni- and multivariate-statistical analyses were used for data processing. Major differences were particularly observed in control-BALF versus sarcoidosis-BALF. However, interestingly, information obtained from BALF profiles was still present (but less prominent) in matched serum profiles. By using information from orthogonal partial least squares discriminant analysis (OPLS-DA) differentiating 1) sarcoidosis-BALF and control-BALF and 2) LS-BALF vs. nonLS-BALF, control-serum and sarcoidosis-serum (p = 0.0007) as well as LS-serum and nonLS-serum (p = 0.006) could be distinguished. Noteworthy, many factors prominent in identifying controls and patients were those associated with Fc-regulation, but also features from the IgG-Fab region and novel peptide variants. Differences between phenotypes were mostly IgG-specificity related. The results support the analytical utility of SpotLight proteomics which prospectively have potential to differentiate closely related phenotypes from a simple blood test.
Use: pNovo
JOURNAL OF CHROMATOGRAPHY A2019. Gao, WN et al.
Southern Univ Sci & Technol, Dept Chem, Shenzhen 518055, Peoples R China.
ABSTRACT:Glycosylation, as a biologically important protein post-translational modification, often alters on both glycosites and glycans, simultaneously. However, most of current approaches focused on biased profiling of either glycosites or glycans, and limited by time-consuming process and milligrams of starting protein material. We describe here a simple and integrated spintip-based glycoproteomics technology (termed Glyco-SISPROT) for achieving a comprehensive view of glycoproteome with shorter sample processing time and low microgram starting material. By carefully integrating and optimizing SCX, C18 and Concanavalin A (Con A) packing material and their combination in spintip format, both predigested peptides and protein lysates could be processed by Glyco-SISPROT with high efficiency. More importantly, deglycopeptide, intact glycopeptide and glycans released by multiple glycosidases could be readily collected from the same Glyco-SISPROT workflow for LC-MS analysis. In total, above 1850 glycosites in (1) over tilde 770 unique deglycopeptides were characterized from mouse liver by using either 100 mu g of predigested peptides or directly using 100 mu g of protein lysates, in which about 30% of glycosites were released by both PNGase F and Endos. To the best of our knowledge, this approach should be one of the most comprehensive glycoproteomic approaches by using limited protein starting material. One significant benefit of Glyco-SISPROT is that whole processing time is dramatically reduced from a few days to less than 6 h with good reproducibility when protein lysates were directly processed by Glyco-SISPROT. We expect that this method will be suitable for multi-level glycoproteome analysis of rare biological samples with high sensitivity. (C) 2019 Elsevier B.V. All rights reserved.
Use: pParse; pGlyco
Journal of proteome research2019. Zhang, Y et al.
Sichuan Univ, Key Lab Transplant Engn & Immunol, West China Washington Mitochondria & Metab Res Ct, West China Hosp,MOH, Chengdu 610041, Peoples R China.
ABSTRACT:Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer among women worldwide. It is confirmed mainly by fine-needle aspiration biopsy (FNAB), an invasive diagnostic method. The key proteins responsible for thyroid hormone biosynthesis are glycosylated. Hence, changes in site-specific glycosylation are associated with thyroid cancer. Integrated quantitative proteomic and glycoproteomic analyses of body fluids from patients with PTC may identify potential noninvasive biomarkers, improve diagnostic accuracy, and elucidate the basic mechanisms of tumor development. In the present study, we demonstrate an integrated, highly reproducible, rapid method involving body fluid proteome and glycoproteome analysis. Moreover, this method may quantitatively profile protein glycosylation. Intact N-glycopeptides from the urine and plasma of healthy controls (HC), PTC, and PTC with Hashimoto's thyroiditis (PHT) were enriched by hydrophilic interaction liquid chromatography. Sialic acid was removed from the N-glycopeptides with trifluoroacetic acid and heat. The desialo-N-glycopeptides were analyzed by HCD-MS/MS using stepped collision energies and several search engines for quantitative profiling. Ninety-two altered proteins and 134 intact N-glycopeptides were isolated from the plasma and urine samples of the three groups (90 samples from 15 subjects). To the best of our knowledge, this study is the first to compare the plasma and urinary proteomes and glycoproteomes of HC, PTC, and PHT. Moreover, we reveal a novel indicator (ratio of fucosylated to nonfucosylated N-glycopeptide or F/NF) through desialo-N-glycopeptide analysis. These differently expressed glycoproteins and F/NF may serve as biomarkers contributing to clinical cancer diagnostics and could be used to improve diagnostic accuracy noninvasively.
Use: pGlyco
Journal of proteome research2019. Zhang, Y et al.
Sichuan Univ, Chengdu, Peoples R China.
ABSTRACT:N-glycoproteins are involved in various biological processes. Certain distinctive glycoforms on specific glycoproteins enhance the specificity and/or sensitivity of cancer diagnosis. Therefore, the characterization of plasma N-glycoproteome is essential for a new biomarker discovery. The absence of suitable analytical methods for in-depth and large-scale analyses of low-abundance plasma glycoproteins makes it challenging to investigate the role of glycosylation. In this study, we developed an integrated method termed Glyco-CPLL, which integrates combinatorial peptide ligand libraries, high-pH reversed-phase prefractionation, hydrophilic interaction chromatography, trypsin and PNGase F digestion, shotgun proteomics, and various analysis software (MaxQuant and pGlyco2.0) for the low-abundance plasma glycoproteomic profiling. Then, we utilized the method to perform a comparative study and to explore papillary thyroid carcinoma-related proteins and glycosylations with reference to healthy controls. Finally, a large and comprehensive human plasma N-glycoproteomic database was established, containing 786 proteins, 369 N-glycoproteins, 862 glycosites, 171 glycan compositions, and 1644 unique intact N-glycopeptides. Additionally, several low-abundance plasma glycoproteins were identified, including SVEP1 (similar to 0.54 ng/mL), F8 similar to 0.83 ng/mL), and ADAMTS13 (similar to 1.2 ng/mL). These results suggest that this method will be useful for analyzing plasma intact glycopeptides in future studies. Besides, the Glyco-CPLL method has a great potential to be translated to clinical applications. Data are available via ProteomeXchange with identifier PXD016428.
Use: pGlyco
Molecular & Cellular Proteomics2019. Zhang, Shu et al.
Fudan Univ, Inst Biomed Sci, Shanghai 200032, Peoples R China; Fudan Univ, Key Lab Carcinogenesis & Canc Invas, Minist Educ, Shanghai 200032, Peoples R China; Fudan Univ, Dept Chem, Shanghai 200032, Peoples R China; Fudan Univ, NHC Key Lab Glycoconjugates Res, Shanghai 200032, Peoples R China; Fudan Univ, Zhongshan Hosp, Liver Canc Inst, Shanghai 200032, Peoples R China
ABSTRACT:N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on O-18/O-16 C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN(205)ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA(2) were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA(2) fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.
Use: pGlyco; pQuant
Analytica Chimica Acta2019. Qin, HQ et al.
Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China.
ABSTRACT:Determination of site-specific glycoforms is the key to reveal the micro-heterogeneity of protein glycosylation at proteome level. Herein, we presented an integrated virtual multistage MS strategy to identify intact glycopeptides, which allowed the determination of site-specific glycoforms. In this strategy, the enzymatically de-glycosylated peptides and intact glycopeptides were mixed and analyzed in the same LC-MS/MS run. The acquired MS2 spectra of intact glycopeptides allowed determination of the glycans, and the MS2 spectra of the de-glycosylated peptides enabled the identification of peptide backbone sequences. Compared with the conventional multistage strategy, the peptide backbones could be directly identified by the MS2 of the de-glycopeptides with higher sensitivity. This strategy was first validated by analyzing the glycosites and site-specific glycoforms of mouse liver tissues. Then, it was applied to differential analysis of the glycoproteomes of hepatocellular carcinoma (HCC) and adjacent liver tissues. Compared with the identification scheme using only MS2 spectra of intact glycopeptides or glycosites, this approach enabled quantitative analysis on two levels, i.e. glycosites and site-specific glycoforms, simultaneously. Thus, it could be a powerful tool to characterize the subtle differences in the macro- and micro-heterogeneity of protein glycosylation for different samples. (C) 2019 Elsevier B.V. All rights reserved.
Use: pGlyco
Journal of proteome research2019. Qin, HQ et al.
Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China.
ABSTRACT:Aberrant sialylation of glycoproteins is closely related to many malignant diseases, and analysis of sialylation has great potential to reveal the status of these diseases. However, in-depth analysis of sialylation is still challenging because of the high microheterogeneity of protein glycosylation, as well as the low abundance of sialylated glycopeptides (SGPs). Herein, an integrated strategy was fabricated for the detailed characterization of glycoprotein sialylation on the levels of glycosites and site-specific glycoforms by employing the SGP enrichment method. This strategy enabled the identification of up to 380 glycosites, as well as 414 intact glycopeptides corresponding to 383 site-specific glycoforms from only initial 6 mu L serum samples, indicating the high sensitivity of the method for the detailed analysis of glycoprotein sialylation. This strategy was further employed to the differential analysis of glycoprotein sialylation between hepatocellular carcinoma patients and control samples, leading to the quantification of 344 glycosites and 405 site-specific glycoforms, simultaneously. Among these, 43 glycosites and 55 site-specific glycoforms were found to have significant change on the glycosite and site-specific glycoform levels, respectively. Interestingly, several glycoforms attached onto the same glycosite were found with different change tendencies. This strategy was demonstrated to be a powerful tool to reveal subtle differences of the macro- and microheterogeneity of glycoprotein sialylation.
Use: pGlyco; pQuant
Analytica Chimica Acta2019. Zhao, T et al.
Fudan Univ, Shanghai Canc Ctr, Shanghai 200032, Peoples R China.
ABSTRACT:Increasing researches proved that abnormal glycosylation is strongly correlated with many diseases. Specially, site-specific glycosylation and its associated heterogeneity are closely related to the function and activity of the glycoprotein. However, intact N-glycopeptide analysis still faces great challenges because the presence of highly abundant non-glycosylated peptides would suppress the ionization of lowly abundant glycopeptides. In the present study, we developed a practical intact tryptic N-glycopeptide enrichment method using acrylamide-agarose composite gel that combined the size exclusion chromatography and hydrophilic (named SELIC) effects, aimed to remove the detergent rapidly and effectively, as well as enrich intact N-glycopeptides while extracting peptides. This is a useful tool to facilitate the intact N-glycopeptides analysis of complex protein mixtures, particularly for samples that extracted from formalin-fixed and paraffin-embedded (FFPE) tissues by SDS. Using this method, we successfully identified 700 site-specific intact tryptic N-glycopeptides corresponding to 261 glycosylation sites on 191 glycoproteins from FFPE thymoma tissues. (C) 2019 Elsevier B.V. All rights reserved.
Use: pGlyco