Literature DB >> 33094747

Structural-based connectivity and omic phenotype evaluations (SCOPE): a cheminformatics toolbox for investigating lipidomic changes in complex systems.

Melanie T Odenkirk1, Phyo Phyo K Zin, Jeremy R Ash, David M Reif, Denis Fourches, Erin S Baker.   

Abstract

Since its inception, the main goal of the lipidomics field has been to characterize lipid species and their respective biological roles. However, difficulties in both full speciation and biological interpretation have rendered these objectives extremely challenging and as a result, limited our understanding of lipid mechanisms and dysregulation. While mass spectrometry-based advancements have significantly increased the ability to identify lipid species, less progress has been made surrounding biological interpretations. We have therefore developed a Structural-based Connectivity and Omic Phenotype Evaluations (SCOPE) cheminformatics toolbox to aid in these evaluations. SCOPE enables the assessment and visualization of two main lipidomic associations: structure/biological connections and metadata linkages either separately or in tandem. To assess structure and biological relationships, SCOPE utilizes key lipid structural moieties such as head group and fatty acyl composition and links them to their respective biological relationships through hierarchical clustering and grouped heatmaps. Metadata arising from phenotypic and environmental factors such as age and diet is then correlated with the lipid structures and/or biological relationships, utilizing Toxicological Prioritization Index (ToxPi) software. Here, SCOPE is demonstrated for various applications from environmental studies to clinical assessments to showcase new biological connections not previously observed with other techniques.

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Year:  2020        PMID: 33094747      PMCID: PMC7695036          DOI: 10.1039/d0an01638a

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  50 in total

1.  Corrigendum to "Common cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation" [Biochim. Biophys. Acta 1862(8) (2017) 766-770].

Authors:  Jeremy P Koelmel; Candice Z Ulmer; Christina M Jones; Richard A Yost; John A Bowden
Journal:  Biochim Biophys Acta Mol Cell Biol Lipids       Date:  2017-06-27       Impact factor: 4.698

2.  Online Ozonolysis Combined with Ion Mobility-Mass Spectrometry Provides a New Platform for Lipid Isomer Analyses.

Authors:  Berwyck L J Poad; Xueyun Zheng; Todd W Mitchell; Richard D Smith; Erin S Baker; Stephen J Blanksby
Journal:  Anal Chem       Date:  2017-12-21       Impact factor: 6.986

3.  Structural Characterization of Phosphatidylcholines Using 193 nm Ultraviolet Photodissociation Mass Spectrometry.

Authors:  Dustin R Klein; Jennifer S Brodbelt
Journal:  Anal Chem       Date:  2017-01-23       Impact factor: 6.986

4.  Hydrophilic interaction liquid chromatography-mass spectrometry of (lyso)phosphatidic acids, (lyso)phosphatidylserines and other lipid classes.

Authors:  Eva Cífková; Roman Hájek; Miroslav Lísa; Michal HolĿapek
Journal:  J Chromatogr A       Date:  2016-01-29       Impact factor: 4.759

5.  The direct determination of double bond positions in lipid mixtures by liquid chromatography/in-line ozonolysis/mass spectrometry.

Authors:  Chenxing Sun; Yuan-Yuan Zhao; Jonathan M Curtis
Journal:  Anal Chim Acta       Date:  2012-12-19       Impact factor: 6.558

6.  Fatty acid composition of plasma lipids in patients with pancreatic, lung and oesophageal cancer in comparison with healthy subjects.

Authors:  Sonja D Zuijdgeest-van Leeuwen; Michiel S van der Heijden; Trinet Rietveld; J Willem O van den Berg; Hugo W Tilanus; Jacobus A Burgers; J H Paul Wilson; Pieter C Dagnelie
Journal:  Clin Nutr       Date:  2002-06       Impact factor: 7.324

7.  Unveiling molecular signatures of preeclampsia and gestational diabetes mellitus with multi-omics and innovative cheminformatics visualization tools.

Authors:  Melanie T Odenkirk; Kelly G Stratton; Marina A Gritsenko; Lisa M Bramer; Bobbie-Jo M Webb-Robertson; Kent J Bloodsworth; Karl K Weitz; Anna K Lipton; Matthew E Monroe; Jeremy R Ash; Denis Fourches; Brandie D Taylor; Kristin E Burnum-Johnson; Erin S Baker
Journal:  Mol Omics       Date:  2020-09-23

8.  ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models.

Authors:  Skylar W Marvel; Kimberly To; Fabian A Grimm; Fred A Wright; Ivan Rusyn; David M Reif
Journal:  BMC Bioinformatics       Date:  2018-03-05       Impact factor: 3.169

9.  Discovering and validating between-subject variations in plasma lipids in healthy subjects.

Authors:  Husna Begum; Bowen Li; Guanghou Shui; Amaury Cazenave-Gassiot; Richie Soong; Rick Twee-Hee Ong; Peter Little; Yik-Ying Teo; Markus R Wenk
Journal:  Sci Rep       Date:  2016-01-08       Impact factor: 4.379

Review 10.  Reshaping Lipid Biochemistry by Pushing Barriers in Structural Lipidomics.

Authors:  Tiffany Porta Siegel; Kim Ekroos; Shane R Ellis
Journal:  Angew Chem Int Ed Engl       Date:  2019-02-18       Impact factor: 15.336

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  4 in total

1.  Combining Micropunch Histology and Multidimensional Lipidomic Measurements for In-Depth Tissue Mapping.

Authors:  Melanie T Odenkirk; Brian M Horman; James N Dodds; Heather B Patisaul; Erin S Baker
Journal:  ACS Meas Sci Au       Date:  2021-10-28

2.  From Prevention to Disease Perturbations: A Multi-Omic Assessment of Exercise and Myocardial Infarctions.

Authors:  Melanie T Odenkirk; Kelly G Stratton; Lisa M Bramer; Bobbie-Jo M Webb-Robertson; Kent J Bloodsworth; Matthew E Monroe; Kristin E Burnum-Johnson; Erin S Baker
Journal:  Biomolecules       Date:  2020-12-30

3.  ToxPi*GIS Toolkit: creating, viewing, and sharing integrative visualizations for geospatial data using ArcGIS.

Authors:  Jonathon Fleming; Skylar W Marvel; Stacy Supak; Alison A Motsinger-Reif; David M Reif
Journal:  J Expo Sci Environ Epidemiol       Date:  2022-04-26       Impact factor: 6.371

4.  Lipidomic comparison of 2D and 3D colon cancer cell culture models.

Authors:  Fernando Tobias; Amanda B Hummon
Journal:  J Mass Spectrom       Date:  2022-08       Impact factor: 2.394

  4 in total

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