Dealing with the unknown: Metabolomics and Metabolite Atlases

Bowen, Benjamin P.; Northen, Trent

doi:10.1016/j.jasms.2010.04.003

Cited by 182 publications

(165 citation statements)

References 53 publications

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“…Notably, the potential of mass spectrometry (MS)-based metabolomics and of the large-scale acquisition of tandem MS (MS/MS) spectra for as many metabolites as possible within a metabolic profile is severely constrained by the absence of straightforward classification and visualization pipelines that enable facile pathway interpretations. Metabolite annotation and identification are the obvious bottlenecks that thwart the metabolomics analysis of secondary metabolism (13,14). Ideally, we need approaches that combine the strengths of state-of-the-art statistical methods currently emerging from the genomics field with the recent advances in metabolomics data mining, such as the method of MS/MS molecular networking, which allow unknown metabolites to be readily classified based solely on their fragmentation patterns.…”

Section: Significancementioning

confidence: 99%

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Heiling

Baldwin

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Secondary metabolite diversity is considered an important fitness determinant for plants' biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissuemetabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function.secondary metabolism | mass spectrometry | metabolomics | information theory | Nicotiana attenuata P lants are elegant synthetic chemists making use of their metabolic prowess to produce complex blends of structurally diverse chemicals. Commonly quoted estimates state that plants produce somewhere on the order of 200,000 chemical structures. Secondary metabolites, also referred to as specialized metabolites or natural products, contribute to the largest fraction of this structural diversity. Compared with their counterparts in central metabolism (primary metabolites), secondary metabolite groups have diversified to the extreme in plant lineages, likely as a result of the multiple ecological roles they fulfill (1). The high degree of plasticity of secondary metabolism pathways is consistent with the existence of large families of metabolism-related genes such as cytochrome P450s and UDP-glycosyltransferases in plant genomes that can create structural and chemical modifications almost without limits. The majority of metabolic gene functions remain unknown, however, either because the metabolites that they produce are unknown or signi...

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Section: Significancementioning

confidence: 99%

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Heiling

Baldwin

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…The challenge of annotating mass spectrometry data also applies to proteomics, metabolomics, and lipidomics. These advanced "omics" tools, even when combined with the power of genome mining, peptidogenomics, and search algorithms, annotate only a small percentage of what are presumably some of the most abundant ions, as observed in an imaged sample (32), indicating that there are still many opportunities in mass spectrometry to develop novel approaches to identify (ID) molecules (8,24,42,46). We encourage the scientific community to develop systematic, integrated workflows for handling unknowns in IMS data that may capture more than 50% of the IMS signals.…”

Section: Final Remarksmentioning

confidence: 99%

Primer on Agar-Based Microbial Imaging Mass Spectrometry

et al. 2012

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Matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) imaging mass spectrometry (IMS) applied directly to microbes on agar-based medium captures global information about microbial molecules, allowing for direct correlation of chemotypes to phenotypes. This tool was developed to investigate metabolic exchange factors of intraspecies, interspecies, and polymicrobial interactions. Based on our experience of the thousands of images we have generated in the laboratory, we present five steps of microbial IMS: culturing, matrix application, dehydration of the sample, data acquisition, and data analysis/interpretation. We also address the common challenges encountered during sample preparation, matrix selection and application, and sample adherence to the MALDI target plate. With the practical guidelines described herein, microbial IMS use can be extended to bio-based agricultural, biofuel, diagnostic, and therapeutic discovery applications.

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“…Liquid chromatography mass spectrometry (LC/MS) is a sensitive technique that can detect many metabolites in a metabolome sample [1]. However, metabolite identification from the mass spectral data alone is often difficult [2][3][4][5][6]. There are only a limited number of metabolite standards available for spectral comparison to identify unknowns.…”

mentioning

confidence: 99%

A method for comprehensive analysis of urinary acylglycines by using ultra-performance liquid chromatography quadrupole linear ion trap mass spectrometry

Lewis-Stanislaus

Liang

2010

J. Am. Soc. Mass Spectrom.

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Acylglycines are an important class of metabolites that have been used in the diagnosis of several inborn errors of metabolism (IEM). However, current analytical methods detect only a few acylglycines. There is a need to profile these metabolites in a comprehensive manner for studying their functions and improving their diagnostic values for different IEM and potentially other diseases. We describe a sensitive method that combines the chromatographic resolving power of ultra-performance liquid chromatography (UPLC) to separate closely related metabolites including isomers with tandem mass spectrometry (MS/MS). Acylglycines were extracted from urine using an anion exchange solid-phase extraction (SPE) cartridge. After UPLC separation, the acylglycines were detected on a hybrid triple quadrupole linear ion trap mass spectrometer. A set of standards were used for the development of an optimal MS acquisition method. Several acquisition modes using information derived from collisioninduced dissociation breakdown curves were used to detect acylglycines. Using this method, 18 acylglycines were detected in the urine of healthy individuals and confirmed using standards, while 47 additional acylglycines were detected and tentatively identified, based on their retention and fragmentation pattern. Among the 65 acylglycines detected, only 18 of them have been previously reported in biofluids of healthy individuals. These results will be deposited in a public human metabolome database. This example illustrates that by developing a method tailored to the analysis of a class of metabolites sharing similar structural moieties, we can potentially identify many more new metabolites, thereby expanding the overall metabolome coverage. (J Am Soc Mass Spectrom 2010, 21, 2105-2116) © 2010 American Society for Mass Spectrometry M etabolomics is an emerging field that is poised to play a significant role in many disciplines of biosciences. One of the current challenges in metabolomics is to profile the metabolome in a very comprehensive manner, ideally covering the entire set of metabolites present in a biological system. However, due to technical limitations, only a small portion of the metabolome is analyzed. There is a great need to expand the metabolome coverage to reveal subtle changes of the metabolome in biological studies or disease biomarker discovery. Liquid chromatography mass spectrometry (LC/MS) is a sensitive technique that can detect many metabolites in a metabolome sample [1]. However, metabolite identification from the mass spectral data alone is often difficult [2][3][4][5][6]. There are only a limited number of metabolite standards available for spectral comparison to identify unknowns. For example, in the Human Metabolome Database (HMDB), product ion spectra of about 900 known standards obtained by tandem mass spectrometry (MS/MS) are included. To create this MS/MS spectral library, we went through almost all the possible commercial sources to acquire the available metabolite standards [7]. This number is still quite ...

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Dealing with the unknown: Metabolomics and Metabolite Atlases

Cited by 182 publications

References 53 publications

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Primer on Agar-Based Microbial Imaging Mass Spectrometry

A method for comprehensive analysis of urinary acylglycines by using ultra-performance liquid chromatography quadrupole linear ion trap mass spectrometry

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