Structural characteristics of the molecular species of tetraacylglycerols in lesquerella ( Physaria fendleri ) oil elucidated by mass spectrometry

2017 ◽  
Vol 10 ◽  
pp. 167-173 ◽  
Author(s):  
Jiann-Tsyh Lin ◽  
Grace Q. Chen
Keyword(s):  
Mass Spectrometry ◽  
Molecular Species ◽  
Structural Characteristics ◽  
Physaria Fendleri

scholarly journals Automated Biomarker Candidate Discovery in Imaging Mass Spectrometry Data Through Spatially Localized Shapley Additive Explanations

2020 ◽  
Author(s):  
Leonoor E.M. Tideman ◽  
Lukasz G. Migas ◽  
Katerina V. Djambazova ◽  
Nathan Heath Patterson ◽  
Richard M. Caprioli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Molecular Species ◽  
Imaging Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Decision Making Process ◽  
Spatial Specificity ◽  
The Relationship ◽  
Insight Into ◽  
Imaging Mass Spectrometry Data

AbstractThe search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impractical due to the large size and high-dimensionality of IMS datasets. Instead, we propose an interpretable machine learning workflow that automatically identifies biomarker candidates by their mass-to-charge ratios, and that quantitatively estimates their relevance to recognizing a given biological class using Shapley additive explanations (SHAP). The task of biomarker candidate discovery is translated into a feature ranking problem: given a classification model that assigns pixels to different biological classes on the basis of their mass spectra, the molecular species that the model uses as features are ranked in descending order of relative predictive importance such that the top-ranking features have a higher likelihood of being useful biomarkers. Besides providing the user with an experiment-wide measure of a molecular species’ biomarker potential, our workflow delivers spatially localized explanations of the classification model’s decision-making process in the form of a novel representation called SHAP maps. SHAP maps deliver insight into the spatial specificity of biomarker candidates by highlighting in which regions of the tissue sample each feature provides discriminative information and in which regions it does not. SHAP maps also enable one to determine whether the relationship between a biomarker candidate and a biological state of interest is correlative or anticorrelative. Our automated approach to estimating a molecular species’ potential for characterizing a user-provided biological class, combined with the untargeted and multiplexed nature of IMS, allows for the rapid screening of thousands of molecular species and the obtention of a broader biomarker candidate shortlist than would be possible through targeted manual assessment. Our biomarker candidate discovery workflow is demonstrated on mouse-pup and rat kidney case studies.HighlightsOur workflow automates the discovery of biomarker candidates in imaging mass spectrometry data by using state-of-the-art machine learning methodology to produce a shortlist of molecular species that are differentially expressed with regards to a user-provided biological class.A model interpretability method called Shapley additive explanations (SHAP), with observational Shapley values, enables us to quantify the local and global predictive importance of molecular species with respect to recognizing a user-provided biological class.By providing spatially localized explanations for a classification model’s decision-making process, SHAP maps deliver insight into the spatial specificity of biomarker candidates and enable one to determine whether (and where) the relationship between a biomarker candidate and the class of interest is correlative or anticorrelative.

scholarly journals Intact molecular characterization of cord factor (trehalose 6,6′-dimycolate) from nine species of mycobacteria by MALDI-TOF mass spectrometry

Microbiology ◽  
2005 ◽  
Vol 151 (10) ◽  
pp. 3403-3416 ◽  
Author(s):  
Yukiko Fujita ◽  
Takashi Naka ◽  
Michael R. McNeil ◽  
Ikuya Yano
Keyword(s):  
Molecular Structure ◽  
Mass Spectrometry ◽  
Molecular Species ◽  
Mycolic Acid ◽  
Molecular Ions ◽  
Ion Distribution ◽  
Mycolic Acids ◽  
Maldi Tof ◽  
Cord Factor

Cord factor (trehalose 6,6′-dimycolate, TDM) is an unique glycolipid with a trehalose and two molecules of mycolic acids in the mycobacterial cell envelope. Since TDM consists of two molecules of very long branched-chain 3-hydroxy fatty acids, the molecular mass ranges widely and in a complex manner. To characterize the molecular structure of TDM precisely and simply, an attempt was made to determine the mycolic acid subclasses of TDM and the molecular species composition of intact TDM by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry for the first time. The results showed that less than 1 μg mycolic acid methyl ester of TDM from nine representative species of mycobacteria and TDM from the same species was sufficient to obtain well-resolved mass spectra composed of pseudomolecular ions [M+Na]+. Although the mass ion distribution was extremely diverse, the molecular species of each TDM was identified clearly by constructing a molecular ion matrix consisting of the combination of two molecules of mycolic acids. The results showed a marked difference in the molecular structure of TDM among mycobacterial species and subspecies. TDM from Mycobacterium tuberculosis (H37Rv and Aoyama B) showed a distinctive mass pattern and consisted of over 60 molecular ions with α-, methoxy- and ketomycolate. TDM from Mycobacterium bovis BCG Tokyo 172 similarly showed over 35 molecular ions, but that from M. bovis BCG Connaught showed simpler molecular ion clusters consisting of less than 35 molecular species due to a complete lack of methoxymycolate. Mass ions due to TDM from M. bovis BCG Connaught and Mycobacterium kansasii showed a biphasic distribution, but the two major peaks of TDM from M. kansasii were shifted up two or three carbon units higher compared with M. bovis BCG Connaught. Within the rapid grower group, in TDM consisting of α-, keto- and wax ester mycolate from Mycobacterium phlei and Mycobacterium flavescens, the mass ion distribution due to polar mycolates was shifted lower than that from the Mycobacterium avium–intracellulare group. Since the physico-chemical properties and antigenic structure of mycolic acid of TDM affect the host immune responses profoundly, the molecular characterization of TDM by MALDI-TOF mass analysis may give very useful information on the relationship of glycolipid structure to its biological activity.

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