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Dive into the research topics where Anoop Mayampurath is active.

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Featured researches published by Anoop Mayampurath.


BMC Bioinformatics | 2009

Decon2LS: An open-source software package for automated processing and visualization of high resolution mass spectrometry data

Navdeep Jaitly; Anoop Mayampurath; Kyle A. Littlefield; Joshua N. Adkins; Gordon A. Anderson; Richard D. Smith

BackgroundData generated from liquid chromatography coupled to high-resolution mass spectrometry (LC-MS)-based studies of a biological sample can contain large amounts of biologically significant information in the form of proteins, peptides, and metabolites. Interpreting this data involves inferring the masses and abundances of biomolecules injected into the instrument. Because of the inherent complexity of mass spectral patterns produced by these biomolecules, the analysis is significantly enhanced by using visualization capabilities to inspect and confirm results. In this paper we describe Decon2LS, an open-source software package for automated processing and visualization of high-resolution MS data. Drawing extensively on algorithms developed over the last ten years for ICR2LS, Decon2LS packages the algorithms as a rich set of modular, reusable processing classes for performing diverse functions such as reading raw data, routine peak finding, theoretical isotope distribution modelling, and deisotoping. Because the source code is openly available, these functionalities can now be used to build derivative applications in relatively fast manner. In addition, Decon2LS provides an extensive set of visualization tools, such as high performance chart controls.ResultsWith a variety of options that include peak processing, deisotoping, isotope composition, etc, Decon2LS supports processing of multiple raw data formats. Deisotoping can be performed on an individual scan, an individual dataset, or on multiple datasets using batch processing. Other processing options include creating a two dimensional view of mass and liquid chromatography (LC) elution time features, generating spectrum files for tandem MS data, creating total intensity chromatograms, and visualizing theoretical peptide profiles. Application of Decon2LS to deisotope different datasets obtained across different instruments yielded a high number of features that can be used to identify and quantify peptides in the biological sample.ConclusionDecon2LS is an efficient software package for discovering and visualizing features in proteomics studies that require automated interpretation of mass spectra. Besides being easy to use, fast, and reliable, Decon2LS is also open-source, which allows developers in the proteomics and bioinformatics communities to reuse and refine the algorithms to meet individual needs.Decon2LS source code, installer, and tutorials may be downloaded free of charge at http://http:/ncrr.pnl.gov/software/.


Bioinformatics | 2008

DeconMSn: A Software Tool for accurate parent ion monoisotopic mass determination for tandem mass spectra

Anoop Mayampurath; Navdeep Jaitly; Samuel O. Purvine; Matthew E. Monroe; Kenneth J. Auberry; Joshua N. Adkins; Richard D. Smith

UNLABELLED DeconMSn accurately determines the monoisotopic mass and charge state of parent ions from high-resolution tandem mass spectrometry data, offering significant improvement for LTQ_FT and LTQ_Orbitrap instruments over the commercially delivered Thermo Fisher Scientifics extract_msn tool. Optimal parent ion mass tolerance values can be determined using accurate mass information, thus improving peptide identifications for high-mass measurement accuracy experiments. For low-resolution data from LCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-based charge detection algorithm that identifies the most likely charge of a parent species through peak characteristics of its fragmentation pattern. AVAILABILITY http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/.


Genes & Development | 2012

Spatial and functional relationships among Pol V-associated loci, Pol IV-dependent siRNAs, and cytosine methylation in the Arabidopsis epigenome

Andrzej T. Wierzbicki; Ross Cocklin; Anoop Mayampurath; Ryan Lister; M. Jordan Rowley; Brian D. Gregory; Joseph R. Ecker; Haixu Tang

Multisubunit RNA polymerases IV and V (Pols IV and V) mediate RNA-directed DNA methylation and transcriptional silencing of retrotransposons and heterochromatic repeats in plants. We identified genomic sites of Pol V occupancy in parallel with siRNA deep sequencing and methylcytosine mapping, comparing wild-type plants with mutants defective for Pol IV, Pol V, or both Pols IV and V. Approximately 60% of Pol V-associated regions encompass regions of 24-nucleotide (nt) siRNA complementarity and cytosine methylation, consistent with cytosine methylation being guided by base-pairing of Pol IV-dependent siRNAs with Pol V transcripts. However, 27% of Pol V peaks do not overlap sites of 24-nt siRNA biogenesis or cytosine methylation, indicating that Pol V alone does not specify sites of cytosine methylation. Surprisingly, the number of methylated CHH motifs, a hallmark of RNA-directed de novo methylation, is similar in wild-type plants and Pol IV or Pol V mutants. In the mutants, methylation is lost at 50%-60% of the CHH sites that are methylated in the wild type but is gained at new CHH positions, primarily in pericentromeric regions. These results indicate that Pol IV and Pol V are not required for cytosine methyltransferase activity but shape the epigenome by guiding CHH methylation to specific genomic sites.


Journal of Proteome Research | 2010

An LC-IMS-MS Platform Providing Increased Dynamic Range for High-Throughput Proteomic Studies

Erin S. Baker; Eric A. Livesay; Daniel J. Orton; Ronald J. Moore; William F. Danielson; David C. Prior; Yehia M. Ibrahim; Brian L. Lamarche; Anoop Mayampurath; Athena A. Schepmoes; Derek F. Hopkins; Keqi Tang; Richard D. Smith; Mikhail E. Belov

A high-throughput approach and platform using 15 min reversed-phase capillary liquid chromatography (RPLC) separations in conjunction with ion mobility spectrometry-mass spectrometry (IMS-MS) measurements was evaluated for the rapid analysis of complex proteomics samples. To test the separation quality of the short LC gradient, a sample was prepared by spiking 20 reference peptides at varying concentrations from 1 ng/mL to 10 microg/mL into a tryptic digest of mouse blood plasma and analyzed with both a LC-Linear Ion Trap Fourier Transform (FT) MS and LC-IMS-TOF MS. The LC-FT MS detected 13 out of the 20 spiked peptides that had concentrations >or=100 ng/mL. In contrast, the drift time selected mass spectra from the LC-IMS-TOF MS analyses yielded identifications for 19 of the 20 peptides with all spiking levels present. The greater dynamic range of the LC-IMS-TOF MS system could be attributed to two factors. First, the LC-IMS-TOF MS system enabled drift time separation of the low concentration spiked peptides from the high concentration mouse peptide matrix components, reducing signal interference and background, and allowing species to be resolved that would otherwise be obscured by other components. Second, the automatic gain control (AGC) in the linear ion trap of the hybrid FT MS instrument limits the number of ions that are accumulated to reduce space charge effects and achieve high measurement accuracy, but in turn limits the achievable dynamic range compared to the IMS-TOF instrument.


Rapid Communications in Mass Spectrometry | 2011

Improving confidence in detection and characterization of protein N‐glycosylation sites and microheterogeneity

Anoop Mayampurath; Yin Wu; Zaneer M. Segu; Yehia Mechref; Haixu Tang

Protein glycosylation is one of the most common post-translational modifications, estimated to occur in over 50% of human proteins. Mass spectrometry (MS)-based approaches involving different fragmentation mechanisms have been frequently used to detect and characterize protein N-linked glycosylations. In addition to the popular Collision-Induced Dissociation (CID), high-energy C-trap dissociation (HCD) fragmentation, which is a feature of a linear ion trap orbitrap hybrid mass spectrometer (LTQ Orbitrap), has been recently used for the fragmentation of tryptic N-linked glycopeptides in glycoprotein analysis. The oxonium ions observed with high mass accuracy in the HCD spectrum of glycopeptides can be combined with characteristic fragmentation patterns in the CID spectrum resulting from consecutive glycosidic bond cleavages, to improve the detection and characterization of N-linked glycopeptides. As a means of automating this process, we describe here GlypID 2.0, a software tool that implements several algorithmic approaches to utilize MS information including accurate precursor mass and spectral patterns from both HCD and CID spectra, thus allowing for an unequivocal and accurate characterization of N-linked glycosylation sites of proteins.


Analytical Chemistry | 2014

Computational Framework for Identification of Intact Glycopeptides in Complex Samples

Anoop Mayampurath; Chuan-Yih Yu; Ehwang Song; Jagadheshwar Balan; Yehia Mechref; Haixu Tang

Glycosylation is an important protein modification that involves enzymatic attachment of sugars to amino acid residues. Understanding the structure of these sugars and the effects of glycosylation are vital for developing indicators of disease development and progression. Although computational methods based on mass spectrometric data have proven to be effective in monitoring changes in the glycome, developing such methods for the glycoproteome are challenging, largely due to the inherent complexity in simultaneously studying glycan structures with their corresponding glycosylation sites. This paper introduces a computational framework for identifying intact N-linked glycopeptides, i.e. glycopeptides with N-linked glycans attached to their glycosylation sites, in complex proteome samples. Scoring algorithms are presented for tandem mass spectra of glycopeptides resulting from collision-induced dissociation (CID), higher-energy C-trap dissociation (HCD), and electron transfer dissociation (ETD) fragmentation modes. An empirical false-discovery rate estimation method, based on a target-decoy search approach, is derived for assigning confidence. The power of our method is further enhanced when multiple data sets are pooled together to increase identification confidence. Using this framework, 103 highly confident N-linked glycopeptides from 53 sites across 33 glycoproteins were identified in complex human serum proteome samples using conventional proteomic platforms with standard depletion of the 7-most abundant proteins. These results indicate that our method is ready to be used for characterizing site-specific protein glycosylation in complex samples.


Molecular & Cellular Proteomics | 2010

DtaRefinery, a Software Tool for Elimination of Systematic Errors from Parent Ion Mass Measurements in Tandem Mass Spectra Data Sets

Vladislav A. Petyuk; Anoop Mayampurath; Matthew E. Monroe; Ashoka D. Polpitiya; Samuel O. Purvine; Gordon A. Anderson; David G. Camp; Richard D. Smith

Hybrid two-stage mass spectrometers capable of both highly accurate mass measurement and high throughput MS/MS fragmentation have become widely available in recent years, allowing for significantly better discrimination between true and false MS/MS peptide identifications by the application of a relatively narrow window for maximum allowable deviations of measured parent ion masses. To fully gain the advantage of highly accurate parent ion mass measurements, it is important to limit systematic mass measurement errors. Based on our previous studies of systematic biases in mass measurement errors, here, we have designed an algorithm and software tool that eliminates the systematic errors from the peptide ion masses in MS/MS data. We demonstrate that the elimination of the systematic mass measurement errors allows for the use of tighter criteria on the deviation of measured mass from theoretical monoisotopic peptide mass, resulting in a reduction of both false discovery and false negative rates of peptide identification. A software implementation of this algorithm called DtaRefinery reads a set of fragmentation spectra, searches for MS/MS peptide identifications using a FASTA file containing expected protein sequences, fits a regression model that can estimate systematic errors, and then corrects the parent ion mass entries by removing the estimated systematic error components. The output is a new file with fragmentation spectra with updated parent ion masses. The software is freely available.


Journal of Proteome Research | 2008

Rapid sample processing for LC-MS-based quantitative proteomics using high intensity focused ultrasound.

Daniel Lopez-Ferrer; Tyler H. Heibeck; Konstantinos Petritis; Kim K. Hixson; Wei Jun Qian; Matthew E. Monroe; Anoop Mayampurath; Ronald J. Moore; Mikhail E. Belov; David G. Camp; Richard D. Smith

A new sample processing workflow that uses high intensity focused ultrasound to rapidly reduce and alkylate cysteines, digest proteins and then label peptides with (18)O was developed for quantitative proteomics applications. Each step was individually refined to minimize reaction times, peptide loses and undesired byproducts or modifications. When this novel workflow was used, mouse plasma proteins were successfully denatured, alkylated, in-solution digested, and (18)O-labeled in <10 min for subsequent analysis by liquid chromatography-electrospray ionization high resolution mass spectrometry. Performance was evaluated in terms of the number of mouse plasma peptides and proteins identified in a shotgun approach and the quantitative dynamic range. The results were compared with previously published results obtained using conventional sample preparation methods and were found to be similar. Advantages of the new method include greatly simplified and accelerated sample processing, as well as being readily amenable to automation.


Rapid Communications in Mass Spectrometry | 2010

Mapping site-specific protein N-glycosylations through liquid chromatography/mass spectrometry and targeted tandem mass spectrometry

Yin Wu; Yehia Mechref; Iveta Klouckova; Anoop Mayampurath; Milos V. Novotny; Haixu Tang

Glycosylation is one of the most common posttranslational modifications (PTMs) of proteins, the characterization of which is commonly achieved through proteomic protocol, involving trypsin digestion followed by liquid chromatography/tandem mass spectrometry (LC/MS/MS). However, it is often not possible to characterize all glycopeptides in a complex sample because of the high complexity of glycoproteomic samples, and the relative lower abundances of glycopeptides in comparison to the unmodified peptides. We present here a targeted MS/MS analysis approach, which utilizes a previously developed computational tool, GlyPID, to guide multiple experiments, thus permitting a complete characterization of all N-glycosylation sites of glycoproteins present in a complex sample. We have tested our approach using model glycoproteins analyzed by high-resolution LTQ-FT MS. The results demonstrate a potential use of our method for a high-throughput characterization of complex mixtures of glycosylated proteins.


Bioinformatics | 2013

Automated annotation and quantification of glycans using liquid chromatography–mass spectrometry

Chuan-Yih Yu; Anoop Mayampurath; Yunli Hu; Shiyue Zhou; Yehia Mechref; Haixu Tang

UNLABELLED As a common post-translational modification, protein glycosylation plays an important role in many biological processes, and it is known to be associated with human diseases. Mass spectrometry (MS)-based glycomic profiling techniques have been developed to measure the abundances of glycans in complex biological samples and applied to the discovery of putative glycan biomarkers. To automate the annotation of glycomic profiles in the liquid chromatography-MS (LC-MS) data, we present here a user-friendly software tool, MultiGlycan, implemented in C# on Windows systems. We tested MultiGlycan by using several glycomic profiling datasets acquired using LC-MS under different preparations and show that MultiGlycan executes fast and generates robust and reliable results. AVAILABILITY MultiGlycan can be freely downloaded at http://darwin.informatics.indiana.edu/MultiGlycan/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

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Haixu Tang

Indiana University Bloomington

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Richard D. Smith

Pacific Northwest National Laboratory

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Chuan-Yih Yu

Indiana University Bloomington

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Matthew E. Monroe

Pacific Northwest National Laboratory

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Gordon A. Anderson

Pacific Northwest National Laboratory

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Mikhail E. Belov

Pacific Northwest National Laboratory

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