Increasing selectivity and coverage in LC-MS based metabolome analysis

Ortmayr, Karin; Causon, Tim J.; Hann, Stephan; Koellensperger, Gunda

doi:10.1016/j.trac.2016.06.011

Cited by 69 publications

(51 citation statements)

References 93 publications

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“…LC‐MS‐based metabolomics have revolutionized the study of small molecules, and has been applied to the study of acute and chronic diseases, nutrition, biomarker discovery, microbiology, metabolic/endocrine disorders, and precision medicine, which is a concept to tailor medical treatment based on an individual patient disease molecular characteristics. Due to its high sensitivity, versatility, and no need for chemical derivatization, and with the introduction of new ionization techniques, LC‐MS/MS‐based metabolomics has gained popularity in recent years . LC‐MS‐based metabolomics can be categorized into (i) targeted analysis which is a pre‐established quantitative analytical approach for a list of known metabolites and (ii) untargeted metabolomics which is characterized by the simultaneous measurement of a large number of metabolites from each sample, commonly without a priori knowledge of the constituents and changes to them.…”

Section: Introductionmentioning

confidence: 99%

“…Due to its high sensitivity, versatility, and no need for chemical derivatization, and with the introduction of new ionization techniques, 21,22 LC-MS/MS-based metabolomics has gained popularity in recent years. 23,24 LC-MS-based metabolomics can be categorized into (i) targeted analysis which is a pre-established quantitative analytical approach for a list of known metabolites and (ii) untargeted metabolomics which is characterized by the simultaneous measurement of a large number of metabolites from each sample, commonly without a priori knowledge of the constituents and changes to them. Here, we focus on untargeted LC-MS-based metabolomics.…”

Section: Introductionmentioning

confidence: 99%

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Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

Liang

Lee

2018

Mass Spectrometry Reviews

247

169

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In the past decade, advances in liquid chromatography-mass spectrometry (LC-MS) have revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply, researchers are now primed to uncover key metabolites and their associations with diseases. The employment of untargeted metabolomics has led to new biomarker discoveries and a better mechanistic understanding of diseases with applications in precision medicine. However, many major pertinent challenges remain. First, compound identification has been poor, and left an overwhelming number of unidentified peaks. Second, partial, incomplete metabolomes persist due to factors such as limitations in mass spectrometry data acquisition speeds, wide-range of metabolites concentrations, and cellular/tissue/temporal-specific expression changes that confound our understanding of metabolite perturbations. Third, to contextualize metabolites in pathways and biology is difficult because many metabolites partake in multiple pathways, have yet to be described species specificity, or possess unannotated or more-complex functions that are not easily characterized through metabolomics analyses. From a translational perspective, information related to novel metabolite biomarkers, metabolic pathways, and drug targets might be sparser than they should be. Thankfully, significant progress has been made and novel solutions are emerging, achieved through sustained academic and industrial community efforts in terms of hardware, computational, and experimental approaches. Given the rapidly growing utility of metabolomics, this review will offer new perspectives, increase awareness of the major challenges in LC-MS metabolomics that will significantly benefit the metabolomics community and also the broader the biomedical community metabolomics aspire to serve.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

Liang

Lee

2018

Mass Spectrometry Reviews

247

169

View full text Add to dashboard Cite

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“…With the same goal of providing a complementary and chemically informative descriptor for metabolites, the combination of gas phase ion mobility separation with HRMS (i.e. IM‐HRMS) is now of emerging interest for non‐targeted metabolomics studies . Of particular importance in this area is the use of mobility‐derived collision cross section (CCS) to support metabolite annotation, and also the possibility of harnessing the IM separation to support HR MS/MS workflows.…”

Section: Introductionmentioning

confidence: 99%

“…Fragment ions were then checked for consistency according to their isotope pattern as well as accurate mass. For glycine, C13 H 14 N 2 O 4 S, m/z 294.0669 was employed, whereas for histidine, C 5 H 9 N 3 , m/z 110.0712 was used. The concentration range depicted refers to the concentration of the analytical standard solution that was employed for reconstituting a defined amount of yeast cell extract (3.0 μg) and ranges from 0.1 μM up to 50 μM.…”

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confidence: 99%

Rapid screening methods for yeast sub‐metabolome analysis with a high‐resolution ion mobility quadrupole time‐of‐flight mass spectrometer

Mairinger

Kurulugama

Causon

et al. 2019

Rapid Comm Mass Spectrometry

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Rationale The wide chemical diversity and complex matrices inherent to metabolomics still pose a challenge to current analytical approaches for metabolite screening. Although dedicated front‐end separation techniques combined with high‐resolution mass spectrometry set the benchmark from an analytical point of view, the increasing number of samples and sample complexity demand for a compromise in terms of selectivity, sensitivity and high‐throughput analyses. Methods Prior to low‐field drift tube ion mobility (IM) separation and quadrupole time‐of‐flight mass spectrometry (QTOFMS) detection, rapid ultrahigh‐performance liquid chromatography separation was used for analysis of different concentration levels of dansylated metabolites present in a yeast cell extract. For identity confirmation of metabolites at the MS2 level, an alternating frame approach was chosen and two different strategies were tested: a data‐independent all‐ions acquisition and a quadrupole broad band isolation (Q‐BBI) directed by IM drift separation. Results For Q‐BBI analysis, the broad mass range isolation was successfully optimized in accordance with the distinctive drift time to m / z correlation of the dansyl derivatives. To guarantee comprehensive sampling, a broad mass isolation window of 70 Da was employed. Fragmentation was performed via collision‐induced dissociation, applying a collision energy ramp optimized for the dansyl derivatives. Both approaches were studied in terms of linear dynamic range and repeatability employing ethanolic extracts of Pichia pastoris spiked with 1 μM metabolite mixture. Example data obtained for histidine and glycine showed that drift time precision (<0.01 to 0.3% RSD, n = 5) compared very well with the data reported in an earlier IM‐TOFMS‐based study. Conclusions Chimeric mass spectra, inherent to data‐independent analysis approaches, are reduced when using a drift time directed Q‐BBI approach. Additionally, an improved linear dynamic working range was observed, representing, together with a rapid front‐end separation, a powerful approach for metabolite screening.

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“…RPLC remains the most popular mode of HPLC for practical broad scale metabolome coverage as the retention characteristics of these materials are well‐suited to a range of moderately polar and nonpolar metabolites. Moreover, advances in column chemistry leading to the development of fully wettable phases that can be routinely used with 100% aqueous mobile‐phase conditions without risk of phase collapse , have further extended the effective polarity range available in a single analysis . There are several ways to make silica‐based columns fully wettable such as having more available space between the alkyl chains that allows the chains to bend without forming a matted surface , or using polar‐embedded groups .…”

Section: Introductionmentioning

confidence: 99%

Comparison of fully wettable RPLC stationary phases for LC‐MS‐based cellular metabolomics

Si-Hung

Causon

2017

Electrophoresis

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Reversed-phase LC combined with high-resolution mass spectrometry (HRMS) is one of the most popular methods for cellular metabolomics studies. Due to the difficulties in analyzing a wide range of polarities encountered in the metabolome, 100%-wettable reversed-phase materials are frequently used to maximize metabolome coverage within a single analysis. Packed with silica-based sub-3 μm diameter particles, these columns allow high separation efficiency and offer a reasonable compromise for metabolome coverage within a single analysis. While direct performance comparison can be made using classical chromatographic characterization approaches, a comprehensive assessment of the column's performance for cellular metabolomics requires use of a full LC-HRMS workflow in order to reflect realistic study conditions used for cellular metabolomics. In this study, a comparison of several reversed-phase LC columns for metabolome analysis using such a dedicated workflow is presented. All columns were tested under the same analytical conditions on an LC-TOF-MS platform using a variety of authentic metabolite standards and biotechnologically relevant yeast cell extracts. Data on total workflow performance including retention behavior, peak capacity, coverage, and molecular feature extraction repeatability from these columns are presented with consideration for both nontargeted screening and differential metabolomics workflows using authentic standards and Pichia pastoris cell extract samples.

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Increasing selectivity and coverage in LC-MS based metabolome analysis

Cited by 69 publications

References 93 publications

Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

Rapid screening methods for yeast sub‐metabolome analysis with a high‐resolution ion mobility quadrupole time‐of‐flight mass spectrometer

Comparison of fully wettable RPLC stationary phases for LC‐MS‐based cellular metabolomics

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