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iTRAQ 4plex method enables multiplexing of up to four samples for simultaneous quantitation to improve sensitivity and scope of proteomic analysis. Here, we describe iTRAQ 4plex labeling of human aqueous humor specimens followed by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and data analysis for peptide identification and quantitation using Proteome Discoverer software. The protocol can be applied for other animals as well; however, pooling of specimens may be required to obtain sufficient amount of protein for labeling.

Bottom-up glycoproteomics by liquid chromatography-mass spectrometry (LC-MS) is an established approach for assessing glycosylation in a protein- and site-specific manner. Consequently, tools are needed to automatically align, calibrate, and integrate LC-MS glycoproteomics data. We developed a modular software package designed to tackle the individual aspects of an LC-MS experiment, called LaCyTools. Targeted alignment is performed using user defined m/z and retention time (tr) combinations. Subsequently, sum spectra are created for each user defined analyte group. Quantitation is performed on the sum spectra, where each user defined analyte can have its own tr, minimum, and maximum charge states. Consequently, LaCyTools deals with multiple charge states, which gives an output per charge state if desired, and offers various analyte and spectra quality criteria. We compared throughput and performance of LaCyTools to combinations of available tools that deal with individual processing steps. LaCyTools yielded relative quantitation of equal precision (relative standard deviation <0.5%) and higher trueness due to the use of MS peak area instead of MS peak intensity. In conclusion, LaCyTools is an accurate automated data processing tool for high-throughput analysis of LC-MS glycoproteomics data. Released under the Apache 2.0 license, it is freely available on GitHub ( https://github.com/Tarskin/LaCyTools ).

The study of N-linked glycosylation has long been complicated by a lack of bioinformatics tools. In particular, there is still a lack of fast and robust data processing tools for targeted (relative) quantitation. We have developed modular, high-throughput data processing software, MassyTools, that is capable of calibrating spectra, extracting data, and performing quality control calculations based on a user-defined list of glycan or glycopeptide compositions. Typical examples of output include relative areas after background subtraction, isotopic pattern-based quality scores, spectral quality scores, and signal-to-noise ratios. We demonstrated MassyTools' performance on MALDI-TOF-MS glycan and glycopeptide data from different samples. MassyTools yielded better calibration than the commercial software flexAnalysis, generally showing 2-fold better ppm errors after internal calibration. Relative quantitation using MassyTools and flexAnalysis gave similar results, yielding a relative standard deviation (RSD) of the main glycan of ~6%. However, MassyTools yielded 2- to 5-fold lower RSD values for low-abundant analytes than flexAnalysis. Additionally, feature curation based on the computed quality criteria improved the data quality. In conclusion, we show that MassyTools is a robust automated data processing tool for high-throughput, high-performance glycosylation analysis. The package is released under the Apache 2.0 license and is freely available on GitHub ( https://github.com/Tarskin/MassyTools ).

The glycome of a diagnostic biological material such as blood, urine, saliva, tissue, or cell cultures comprises of a vast array of structurally distinct glycans attached to the protein complement. Aberrant glycan structures and distributions result from changes in specific glycosyltransferase activities and have different biological significance, making proper quantitation of glycans highly important. In this review, common HPLC/CE and LC-MS/MS-based methods for glycomics, their advantages and disadvantages, will be discussed with respect to the main quantitative strategies. With the increasing interest in absolute quantitation for glycomics, we discuss absolute and relative glycome quantitation and how it affects the resulting conclusions drawn from glycomics studies. We argue that while absolute quantitation of glycomes may be attractive for some areas of clinical glycomics, relative quantitation of glycans remains the most informative and time/cost-effective method to obtain biological insight into the regulation of the cellular glycosylation machinery and the synthesis of the resultant glycan structures in most research questions due to the enzymatic relatedness of the biosynthesized glycans. Recent developments in multiplexing of glycomes by the introduction of stable isotopic labeling of glycans show promise for providing another level of information to the existing benefits of relative quantitation., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

For analysis of nitration modification of α oxoglutarate dehydrogenase (α-OGDH) induced by diabetes, a targeted proteomics strategy was developed through the use of Skyline. All peptides containing Y and W of the target proteins were nitrated in silico and output to produce parallel reaction monitoring (PRM) or SRM method for nitration analysis. A nitrated casein mixture was used as standard protein to assess the feasibility of this method. The results demonstrated the availability of this strategy for nitration identification, and subsequently this method was used to analyze the nitration of α-OGDH from myocardial tissue extracts of diabetic mouse. The PRM method was primarily generated by Skyline for identification of the actual nitrated peptides from all possible nitrated peptides of α-OGDH due to the complexity of α-OGDH. The PRM-based data were analyzed by SEQUEST, and transitions of the identified nitrated peptides were used to develop an SRM method for relative quantitation of nitration degree. The nitration degree of α-OGDH for diabetic mouse is higher than that for control mouse, indicating that α-OGDH of the diabetic mouse suffered from more intense oxidative damage. We believe that this approach for obtaining information regarding nitration will facilitate the study of other PTMs in complex mixtures., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Retinoblastoma is the most common pediatric cancer of the eye. Currently, the chemotherapeutic treatments for retinoblastoma are broad-based drugs such as vincristine, carboplatin, or etoposide. However, therapies targeted directly to aberrant signaling pathways may provide more effective therapy for this disease. The purpose of our study is to illustrate the relationship between the expressions of miRs-449a and -449b to retinoblastoma proliferation and apoptosis. We are the first to confirm an inhibitory effect of miR-449a and -449b in retinoblastoma by demonstrating significantly impaired proliferation and increased apoptosis of tumor cells when these miRNAs are overexpressed. This study suggests that these miRNAs could serve as viable therapeutic targets for retinoblastoma treatment., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Introduction: A close association exists between oral health and cardiovascular disease. Periodontal disease induces early vascular changes while oral pathogens have been detected in sub gingival and atheromatous plaques. We examined the interrelationship between Periodontal disease, oral bacteria, surrogate sub-clinical markers and coronary artery disease (CAD) in a representative Asian Indian cohort., Materials and Methods: 532 Gingivitis cases and 282 Periodontitis cases were assessed for early peripheral vascular changes, namely pulse wave velocity (PWV), arterial stiffness index (ASI) and ankle brachial index (ABI) using computerized oscillometry method. Relative quantitation (RQ) of Porphyromonas gingivalis (Pg) was estimated in saliva samples of 54 Periodontitis, 25 Gingivitis and 51 CAD cases (38 also had oral disease) by Taqman assay by amplifying pathogen-specific gene targets, 16srRNA and IktA, respectively, and 16s universal bacterial rRNA as endogenous control., Results: PWV and ASI were elevated in Periodontitis compared to Gingivitis cases (p<0.0001) and in those with diabetes and hypertension. Cases with Periodontitis showed higher mean expression of Pg than Gingivitis (0.37±0.05 versus 0.15±0.04, p<0.0001), while CAD patients with oral disease (N=38) showed lower mean Pg expression than those without oral disease (N=13) (0.712±0.119 versus 1.526±0.257, p=0.008). Higher Pg expression was recorded in subjects with diabetes and hypertension., Conclusion: Oral disease induces early changes in the peripheral blood vessels. Further, common presence of Pg in subjects with oral disease, in those with established cardiovascular risk factors and in patients with symptomatic CAD reflects the importance of oral hygiene in the development of Coronary Artery Disease in Asian Indians., (Copyright © 2013 Elsevier Ltd. All rights reserved.)