LipidPioneer : A Comprehensive User-Generated Exact Mass Template for Lipidomics

Ulmer, Candice Z.; Koelmel, Jeremy P.; Ragland, Jared M.; Garrett, Timothy J.; Bowden, John A.

doi:10.1007/s13361-016-1579-6

Cited by 33 publications

(25 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When possible, identifications were made against the METLIN database within a mass accuracy of 15 ppm ( 59 , 60 ). For lipid species not found in common lipidomics databases, in-house databases were generated with ChemDraw (DGDGs and lysyl-PGs; PerkinElmer) or LipidPioneer (MGDGs and CLs) ( 61 ). CCS values for lipid standard extracts were obtained by using the DriftScope v2.8 (Waters Corp.) chromatographic peak detection algorithm with lock mass correction.…”

Section: Methodsmentioning

confidence: 99%

Characterization of the Mechanisms of Daptomycin Resistance among Gram-Positive Bacterial Pathogens by Multidimensional Lipidomics

Hines

Waalkes

Penewit

et al. 2017

mSphere

105

141

View full text Add to dashboard Cite

This work comprehensively characterizes lipidomic changes underlying daptomycin resistance in three Gram-positive bacterial species, E. faecalis, S. aureus, and C. striatum, by using a novel three-dimensional lipidomics methodology based on advanced mass spectrometry. We demonstrated a number of advantages of our method in comparison with other methods commonly used in the field, such as high molecular specificity, sensitivity, and throughput. Whole-genome sequencing of the S. aureus and C. striatum strains identified mutations in pgsA, which encodes phosphatidylglycerophosphate synthase, in both resistant strains. Lipidomics revealed significantly decreased levels of lipids downstream of PgsA, as well as accumulation of lipids upstream of PgsA in the resistant strains. Furthermore, we found that changes in individual molecular species of each lipid class depend on the their specific fatty acid compositions. The characteristic changes in individual lipid species could be used as biomarkers for identifying underlying resistance mechanisms and for evaluating potential therapies.

show abstract

Section: Methodsmentioning

confidence: 99%

Characterization of the Mechanisms of Daptomycin Resistance among Gram-Positive Bacterial Pathogens by Multidimensional Lipidomics

Hines

Waalkes

Penewit

et al. 2017

mSphere

105

141

View full text Add to dashboard Cite

show abstract

“…Currently, 58 lipid types are covered when considering all ether and oxidized lipids each as a single lipid type. Within Lipid Annotator, the user can view a table of all in silico lipid libraries by class, by precursor m/z match, or by text query similar to LipidPioneer [30].…”

Section: Lipid Annotator Librariesmentioning

confidence: 99%

Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software

Koelmel

Stow

et al. 2020

Metabolites

Self Cite

View full text Add to dashboard Cite

Lipidomics has great promise in various applications; however, a major bottleneck in lipidomics is the accurate and comprehensive annotation of high-resolution tandem mass spectral data. While the number of available lipidomics software has drastically increased over the past five years, the reduction of false positives and the realization of obtaining structurally accurate annotations remains a significant challenge. We introduce Lipid Annotator, which is a user-friendly software for lipidomic analysis of data collected by liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). We validate annotation accuracy against lipid standards and other lipidomics software. Lipid Annotator was integrated into a workflow applying an iterative exclusion MS/MS acquisition strategy to National Institute of Standards and Technology (NIST) SRM 1950 Metabolites in Frozen Human Plasma using reverse phase LC-HRMS/MS. Lipid Annotator, LipidMatch, and MS-DIAL produced consensus annotations at the level of lipid class for 98% and 96% of features detected in positive and negative mode, respectively. Lipid Annotator provides percentages of fatty acyl constituent species and employs scoring algorithms based on probability theory, which is less subjective than the tolerance and weighted match scores commonly used by available software. Lipid Annotator enables analysis of large sample cohorts and improves data-processing throughput as compared to previous lipidomics software.

show abstract

“…Only the lipid species with mean and standard deviation calculated were included in the final consensus estimation (unless otherwise indicated). Data was validated, with respect to proper annotation, m/z value, and adduct measured using LipidPioneer (7). Any corrections to the original laboratory submission were sent to each laboratory for approval.…”

Section: Handling Of Submitted Lipidomic Datamentioning

confidence: 99%

Lipid concentrations in standard reference material (SRM) 1950: results from an interlaboratory comparison exercise for lipidomics

Bowden¹,

Heckert²,

Ulmer³

et al. 2017

View full text Add to dashboard Cite

The continued growth of the lipidomics research community, combined with a concomitant increase in the number of lipidomic applications, has culminated in an emerging need for the harmonization and standardization of lipidomics measurement. Harmonization and standardization of lipidomic measurement is a considerable undertaking, owing to the vast structural diversity and complexity of lipids, which also subsequently coincides with the use of a broad range of qualitative and quantitative measurement strategies employed by the lipidomics community. The lipidomics community needs to address the variability present in current lipidomics measurement before harmonization and standardization can begin to occur. Accordingly, this work encompasses the first community-supported harmonization effort via an interlaboratory comparison exercise, focused on ascertaining sources of lipidomic measurement variability and/or agreement, while also highlighting measurement challenges in regards to lipid quantitation.The main objectives of the interlaboratory comparison exercise were to 1) generate consensus estimates in nmol/mL for those lipids routinely measured by participants, 2) determine the extent of agreement present within the community using current quantitation lipidomics workflows, 3) and identify those lipids or lipid classes that require more attention. The basic framework of the National Institute of Standards and Technology (NIST) interlaboratory comparison for lipidomics was to distribute one vial of Standard Reference Material (SRM) 1950 -Metabolites in Frozen Human Plasma to each participating laboratory, and to encourage each participant to employ the analytical methodologies that they typically use to quantify lipids in their laboratory. SRM 1950 was chosen as the vehicle for the comparison exercise as it has been previously recognized and promoted as an appropriate reference material for metabolomics (1)(2)(3)(4)(5). In addition, SRM 1950 was constructed to approximate "normal" blood plasma indicative of the United States population (see http://srm1950.nist.gov/). Invitations were sent to a cohort of laboratories that were representative of the diverse cross-section of lipid measurement methodologies present within the lipidomics community. Consensus estimates (at sum composition level), with corresponding uncertainties, were generated for those lipids measured by at least five laboratories. Additional analyses were performed to further assess the collective submitted data, including coefficient of dispersion (COD) for each consensus estimate and zetascores (ζ-scores). COD values were used to evaluate the quality or "usefulness" of the consensus estimates. ζ-scores were used to determine the relative measurement agreement amongst the consensus estimates by lipid species and lipid class.The final consensus estimates and associated uncertainties generated from this exercise hold considerable potential for the lipidomics community, both to serve as inter-and intralaboratory benchmarks but also to initiate follow-up...

show abstract

LipidPioneer : A Comprehensive User-Generated Exact Mass Template for Lipidomics

Cited by 33 publications

References 23 publications

Characterization of the Mechanisms of Daptomycin Resistance among Gram-Positive Bacterial Pathogens by Multidimensional Lipidomics

Characterization of the Mechanisms of Daptomycin Resistance among Gram-Positive Bacterial Pathogens by Multidimensional Lipidomics

Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software

Lipid concentrations in standard reference material (SRM) 1950: results from an interlaboratory comparison exercise for lipidomics

Contact Info

Product

Resources

About