scholarly journals Relative Mass Defect Filtering of Mass Spectra: A Path to Discovery of Plant Specialized Metabolites

2015 ◽  
Vol 167 (4) ◽  
pp. 1221-1232 ◽  
Author(s):  
E.A. Prabodha Ekanayaka ◽  
Mary Dawn Celiz ◽  
A. Daniel Jones
Keyword(s):  
Mass Spectra ◽  
Relative Mass ◽  
Mass Defect ◽  
Specialized Metabolites

scholarly journals Understanding the Characteristics of Mass Spectrometry Data through the use of Simulation

2005 ◽  
Vol 1 ◽  
pp. 117693510500100 ◽  
Author(s):  
Kevin R. Coombes ◽  
John M. Koomen ◽  
Keith A. Baggerly ◽  
Jeffrey S. Morris ◽  
Ryuji Kobayashi
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectra ◽  
Biological Fluids ◽  
Time Lag ◽  
Time Discretization ◽  
Statistical Simulation ◽  
Mass Spectrometry Data ◽  
Relative Mass ◽  
Operating Characteristics ◽  
Tissue Samples

Background Mass spectrometry is actively being used to discover disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids. The potential importance of these clinical applications has made the development of better methods for processing and analyzing the data an active area of research. It is, however, difficult to determine which methods are better without knowing the true biochemical composition of the samples used in the experiments. Methods We developed a mathematical model based on the physics of a simple MALDI-TOF mass spectrometer with time-lag focusing. Using this model, we implemented a statistical simulation of mass spectra. We used the simulation to explore some of the basic operating characteristics of MALDI or SELDI instruments. Results The simulation reproduced several characteristics of actual instruments. We found that the relative mass error is affected by the time discretization of the detector (about 0.01%) and the spread of initial velocities (about 0.1%). The accuracy of calibration based on external standards decays rapidly outside the range spanned by the calibrants. Natural isotope distributions play a major role in broadening peaks associated with individual proteins. The area of a peak is a more accurate measure of its size than the height. Conclusions The model described here is capable of simulating realistic mass spectra. The simulation should become a useful tool for generating spectra where the true inputs are known, allowing researchers to evaluate the performance of new methods for processing and analyzing mass spectra. Availability http://bioinformatics.mdanderson.org/cromwell.html

Kendrick Mass Defect Spectrum:  A Compact Visual Analysis for Ultrahigh-Resolution Broadband Mass Spectra

2001 ◽  
Vol 73 (19) ◽  
pp. 4676-4681 ◽  
Author(s):  
Christine A. Hughey ◽  
Christopher L. Hendrickson ◽  
Ryan P. Rodgers ◽  
Alan G. Marshall ◽  
Kuangnan Qian
Keyword(s):  
Mass Spectra ◽  
Visual Analysis ◽  
Mass Defect ◽  
Ultrahigh Resolution ◽  
Kendrick Mass Defect

scholarly journals A robust clustering algorithm for analysis of composition-dependent organic aerosol thermal desorption measurements

2020 ◽  
Vol 20 (4) ◽  
pp. 2489-2512 ◽  
Author(s):  
Ziyue Li ◽  
Emma L. D'Ambro ◽  
Siegfried Schobesberger ◽  
Cassandra J. Gaston ◽  
Felipe D. Lopez-Hilfiker ◽  
...  
Keyword(s):  
Thermal Properties ◽  
Thermal Desorption ◽  
Mass Spectra ◽  
Clustering Algorithm ◽  
Organic Aerosol ◽  
Relative Mass ◽  
Ionization Mass ◽  
Molecular Formula ◽  
Mass Spectral ◽  
Compositional Variability

Abstract. One of the challenges of understanding atmospheric organic aerosol (OA) particles stems from its complex composition. Mass spectrometry is commonly used to characterize the compositional variability of OA. Clustering of a mass spectral dataset helps identify components that exhibit similar behavior or have similar properties, facilitating understanding of sources and processes that govern compositional variability. Here, we developed an algorithm for clustering mass spectra, the noise-sorted scanning clustering (NSSC), appropriate for application to thermal desorption measurements of collected OA particles from the Filter Inlet for Gases and AEROsols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). NSSC, which extends the common density-based special clustering of applications with noise (DBSCAN) algorithm, provides a robust, reproducible analysis of the FIGAERO temperature-dependent mass spectral data. The NSSC allows for the determination of thermal profiles for compositionally distinct clusters of mass spectra, increasing the accessibility and enhancing the interpretation of FIGAERO data. Applications of NSSC to several laboratory biogenic secondary organic aerosol (BSOA) systems demonstrate the ability of NSSC to distinguish different types of thermal behaviors for the components comprising the particles along with the relative mass contributions and chemical properties (e.g., average molecular formula) of each mass spectral cluster. For each of the systems examined, more than 80 % of the total mass is clustered into 9–13 mass spectral clusters. Comparison of the average thermograms of the mass spectral clusters between systems indicates some commonality in terms of the thermal properties of different BSOA, although with some system-specific behavior. Application of NSSC to sets of experiments in which one experimental parameter, such as the concentration of NO, is varied demonstrates the potential for mass spectral clustering to elucidate the chemical factors that drive changes in the thermal properties of OA particles. Further quantitative interpretation of the thermograms of the mass spectral clusters will allow for a more comprehensive understanding of the thermochemical properties of OA particles.

Higher-Order Mass Defect Analysis for Mass Spectra of Complex Organic Mixtures

2011 ◽  
Vol 83 (12) ◽  
pp. 4924-4929 ◽  
Author(s):  
Patrick J. Roach ◽  
Julia Laskin ◽  
Alexander Laskin
Keyword(s):  
Mass Spectra ◽  
Higher Order ◽  
Defect Analysis ◽  
Mass Defect ◽  
Organic Mixtures ◽  
Complex Organic

scholarly journals Exploring the Phytochemical Landscape of the Early-Diverging Flowering Plant Amborella trichopoda Baill.

Molecules ◽  
2019 ◽  
Vol 24 (21) ◽  
pp. 3814 ◽  
Author(s):  
Sheng Wu ◽  
Alexander E. Wilson ◽  
Lijing Chang ◽  
Li Tian
Keyword(s):  
Mass Spectra ◽  
Flowering Plant ◽  
Evolutionary Significance ◽  
Ionization Mass ◽  
Phylogenetic Groups ◽  
Phenolic Metabolism ◽  
Specialized Metabolites ◽  
Metabolic Genes ◽  
Starting Point ◽  
Interpro Database

Although the evolutionary significance of the early-diverging flowering plant Amborella (Amborella trichopoda Baill.) is widely recognized, its metabolic landscape, particularly specialized metabolites, is currently underexplored. In this work, we analyzed the metabolomes of Amborella tissues using liquid chromatography high-resolution electrospray ionization mass spectrometry (LC-HR-ESI-MS). By matching the mass spectra of Amborella metabolites with those of authentic phytochemical standards in the publicly accessible libraries, 63, 39, and 21 compounds were tentatively identified in leaves, stems, and roots, respectively. Free amino acids, organic acids, simple sugars, cofactors, as well as abundant glycosylated and/or methylated phenolic specialized metabolites were observed in Amborella leaves. Diverse metabolites were also detected in stems and roots, including those that were not identified in leaves. To understand the biosynthesis of specialized metabolites with glycosyl and methyl modifications, families of small molecule UDP-dependent glycosyltransferases (UGTs) and O-methyltransferases (OMTs) were identified in the Amborella genome and the InterPro database based on conserved functional domains. Of the 17 phylogenetic groups of plant UGTs (A–Q) defined to date, Amborella UGTs are absent from groups B, N, and P, but they are highly abundant in group L. Among the 25 Amborella OMTs, 7 cluster with caffeoyl-coenzyme A (CCoA) OMTs involved in lignin and phenolic metabolism, whereas 18 form a clade with plant OMTs that methylate hydroxycinnamic acids, flavonoids, or alkaloids. Overall, this first report of metabolomes and candidate metabolic genes in Amborella provides a starting point to a better understanding of specialized metabolites and biosynthetic enzymes in this basal lineage of flowering plants.

Resolution-enhanced Kendrick mass defect plots for the data processing of mass spectra from wood and coal hydrothermal extracts

Fuel ◽  
2019 ◽  
Vol 235 ◽  
pp. 944-953 ◽  
Author(s):  
Qingxin Zheng ◽  
Masato Morimoto ◽  
Hiroaki Sato ◽  
Thierry Fouquet
Keyword(s):  
Data Processing ◽  
Mass Spectra ◽  
Mass Defect ◽  
Kendrick Mass Defect

Fast Evaluation of Herbal Substance Class Composition by Relative Mass Defect Plots

2020 ◽  
Vol 92 (19) ◽  
pp. 12909-12916
Author(s):  
Birgit J. Waldner ◽  
Ramona Machalett ◽  
Stefan Schönbichler ◽  
Martin Dittmer ◽  
Moritz M. Rubner ◽  
...  
Keyword(s):  
Relative Mass ◽  
Mass Defect ◽  
Fast Evaluation ◽  
Class Composition
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