Literature DB >> 32307636

Environmental lipidomics: understanding the response of organisms and ecosystems to a changing world.

Jeremy P Koelmel1,2, Michael P Napolitano3, Candice Z Ulmer4, Vasilis Vasiliou2, Timothy J Garrett1,5, Richard A Yost1,5, M N V Prasad6, Krystal J Godri Pollitt2, John A Bowden7.   

Abstract

BACKGROUND: Understanding the interaction between organisms and the environment is important for predicting and mitigating the effects of global phenomena such as climate change, and the fate, transport, and health effects of anthropogenic pollutants. By understanding organism and ecosystem responses to environmental stressors at the molecular level, mechanisms of toxicity and adaptation can be determined. This information has important implications in human and environmental health, engineering biotechnologies, and understanding the interaction between anthropogenic induced changes and the biosphere. One class of molecules with unique promise for environmental science are lipids; lipids are highly abundant and ubiquitous across nearly all organisms, and lipid profiles often change drastically in response to external stimuli. These changes allow organisms to maintain essential biological functions, for example, membrane fluidity, as they adapt to a changing climate and chemical environment. Lipidomics can help scientists understand the historical and present biofeedback processes in climate change and the biogeochemical processes affecting nutrient cycles. Lipids can also be used to understand how ecosystems respond to historical environmental changes with lipid signatures dating back to hundreds of millions of years, which can help predict similar changes in the future. In addition, lipids are direct targets of environmental stressors, for example, lipids are easily prone to oxidative damage, which occurs during exposure to most toxins. AIM OF REVIEW: This is the first review to summarize the current efforts to comprehensively measure lipids to better understand the interaction between organisms and their environment. This review focuses on lipidomic applications in the arenas of environmental toxicology and exposure assessment, xenobiotic exposures and health (e.g., obesity), global climate change, and nutrient cycles. Moreover, this review summarizes the use of and the potential for lipidomics in engineering biotechnologies for the remediation of persistent compounds and biofuel production. KEY SCIENTIFIC CONCEPT: With the preservation of certain lipids across millions of years and our ever-increasing understanding of their diverse biological roles, lipidomic-based approaches provide a unique utility to increase our understanding of the contemporary and historical interactions between organisms, ecosystems, and anthropogenically-induced environmental changes.

Entities:  

Keywords:  Climate change; Exposure; Lipidomics; Lipids; Mass spectrometry; Metabolomics

Mesh:

Substances:

Year:  2020        PMID: 32307636     DOI: 10.1007/s11306-020-01665-3

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  165 in total

1.  Metabolite Spectral Accuracy on Orbitraps.

Authors:  Xiaoyang Su; Wenyun Lu; Joshua D Rabinowitz
Journal:  Anal Chem       Date:  2017-05-18       Impact factor: 6.986

2.  Algal lipid bodies: stress induction, purification, and biochemical characterization in wild-type and starchless Chlamydomonas reinhardtii.

Authors:  Zi Teng Wang; Nico Ullrich; Sunjoo Joo; Sabine Waffenschmidt; Ursula Goodenough
Journal:  Eukaryot Cell       Date:  2009-10-30

3.  Forensic identification of seal oils using lipid profiles and statistical models.

Authors:  Margaret H Broadwater; Gloria T Seaborn; John H Schwacke
Journal:  J Forensic Sci       Date:  2012-11-05       Impact factor: 1.832

4.  Obesogens: an environmental link to obesity.

Authors:  Wendee Holtcamp
Journal:  Environ Health Perspect       Date:  2012-02       Impact factor: 9.031

5.  Distinguishing between the metabolome and xenobiotic exposome in environmental field samples analysed by direct-infusion mass spectrometry based metabolomics and lipidomics.

Authors:  Andrew D Southam; Anke Lange; Raghad Al-Salhi; Elizabeth M Hill; Charles R Tyler; Mark R Viant
Journal:  Metabolomics       Date:  2014-07-15       Impact factor: 4.290

6.  Algal Oxylipins Mediate the Resistance of Diatoms against Algicidal Bacteria.

Authors:  Nils Meyer; Johanna Rettner; Markus Werner; Oliver Werz; Georg Pohnert
Journal:  Mar Drugs       Date:  2018-12-04       Impact factor: 5.118

7.  Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression.

Authors:  Netta Vidavsky; Jennie A M R Kunitake; Maria Elena Diaz-Rubio; Aaron E Chiou; Hyun-Chae Loh; Sheng Zhang; Admir Masic; Claudia Fischbach; Lara A Estroff
Journal:  ACS Cent Sci       Date:  2019-04-19       Impact factor: 14.553

8.  Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma.

Authors:  John A Bowden; Alan Heckert; Candice Z Ulmer; Christina M Jones; Jeremy P Koelmel; Laila Abdullah; Linda Ahonen; Yazen Alnouti; Aaron M Armando; John M Asara; Takeshi Bamba; John R Barr; Jonas Bergquist; Christoph H Borchers; Joost Brandsma; Susanne B Breitkopf; Tomas Cajka; Amaury Cazenave-Gassiot; Antonio Checa; Michelle A Cinel; Romain A Colas; Serge Cremers; Edward A Dennis; James E Evans; Alexander Fauland; Oliver Fiehn; Michael S Gardner; Timothy J Garrett; Katherine H Gotlinger; Jun Han; Yingying Huang; Aveline Huipeng Neo; Tuulia Hyötyläinen; Yoshihiro Izumi; Hongfeng Jiang; Houli Jiang; Jiang Jiang; Maureen Kachman; Reiko Kiyonami; Kristaps Klavins; Christian Klose; Harald C Köfeler; Johan Kolmert; Therese Koal; Grielof Koster; Zsuzsanna Kuklenyik; Irwin J Kurland; Michael Leadley; Karen Lin; Krishna Rao Maddipati; Danielle McDougall; Peter J Meikle; Natalie A Mellett; Cian Monnin; M Arthur Moseley; Renu Nandakumar; Matej Oresic; Rainey Patterson; David Peake; Jason S Pierce; Martin Post; Anthony D Postle; Rebecca Pugh; Yunping Qiu; Oswald Quehenberger; Parsram Ramrup; Jon Rees; Barbara Rembiesa; Denis Reynaud; Mary R Roth; Susanne Sales; Kai Schuhmann; Michal Laniado Schwartzman; Charles N Serhan; Andrej Shevchenko; Stephen E Somerville; Lisa St John-Williams; Michal A Surma; Hiroaki Takeda; Rhishikesh Thakare; J Will Thompson; Federico Torta; Alexander Triebl; Martin Trötzmüller; S J Kumari Ubhayasekera; Dajana Vuckovic; Jacquelyn M Weir; Ruth Welti; Markus R Wenk; Craig E Wheelock; Libin Yao; Min Yuan; Xueqing Heather Zhao; Senlin Zhou
Journal:  J Lipid Res       Date:  2017-10-06       Impact factor: 5.922

9.  Perfluoroalkyl and polyfluoroalkyl substances and indicators of immune function in children aged 12-19 y: National Health and Nutrition Examination Survey.

Authors:  Cheryl R Stein; Kathleen J McGovern; Ashley M Pajak; Paul J Maglione; Mary S Wolff
Journal:  Pediatr Res       Date:  2015-10-22       Impact factor: 3.756

10.  Identification of a dioxin-responsive oxylipin signature in roots of date palm: involvement of a 9-hydroperoxide fatty acid reductase, caleosin/peroxygenase PdPXG2.

Authors:  Abdulsamie Hanano; Mouhnad Shaban; Ibrahem Almousally; Denis J Murphy
Journal:  Sci Rep       Date:  2018-09-04       Impact factor: 4.379

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  5 in total

1.  A set of gene knockouts as a resource for global lipidomic changes.

Authors:  Aleksandra Spiegel; Chris Lauber; Mandy Bachmann; Anne-Kristin Heninger; Christian Klose; Kai Simons; Mihail Sarov; Mathias J Gerl
Journal:  Sci Rep       Date:  2022-06-22       Impact factor: 4.996

Review 2.  Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales.

Authors:  Jayan D M Senevirathna; Shuichi Asakawa
Journal:  Life (Basel)       Date:  2021-04-20

3.  Selection of a reference gene for studies on lipid-related aquatic adaptations of toothed whales (Grampus griseus).

Authors:  Jayan D M Senevirathna; Ryo Yonezawa; Taiki Saka; Yoji Igarashi; Noriko Funasaka; Kazutoshi Yoshitake; Shigeharu Kinoshita; Shuichi Asakawa
Journal:  Ecol Evol       Date:  2021-11-26       Impact factor: 2.912

4.  The Use of Non-targeted Lipidomics and Histopathology to Characterize the Neurotoxicity of Bifenthrin to Juvenile Rainbow Trout (Oncorhynchus mykiss).

Authors:  Jason T Magnuson; Leslie Caceres; Nathan Sy; Chenyang Ji; Philip Tanabe; Jay Gan; Michael J Lydy; Daniel Schlenk
Journal:  Environ Sci Technol       Date:  2022-07-25       Impact factor: 11.357

5.  An overview of lipidomics utilizing cadaver derived biological samples.

Authors:  Luheng Lyu; Neel Sonik; Sanjoy Bhattacharya
Journal:  Expert Rev Proteomics       Date:  2021-06-23       Impact factor: 4.250

  5 in total

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