1
|
Anderson BJ, Brademan DR, He Y, Overmyer KA, Coon JJ. LipiDex 2 Integrates MS n Tree-Based Fragmentation Methods and Quality Control Modules to Improve Discovery Lipidomics. Anal Chem 2024. [PMID: 38640432 DOI: 10.1021/acs.analchem.4c00359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
As lipidomics experiments increase in scale and complexity, data processing tools must support workflows for new liquid chromatography-mass spectrometry (LC-MS) methods while simultaneously supporting quality controls to maximize the confidence in lipid identifications. LipiDex 2 improves lipidomics data processing algorithms from LipiDex 1 and introduces new tools for spectral matching and peak annotation functions, with improvements in speed and user-friendliness. In silico spectral library generation now supports tandem mass spectral (MSn) tree-based fragmentation methods, and the LipiDex 2 workflow fully integrates the fragmentation logic into the data processing steps to enable lipid identification at the appropriate level of structural resolution. Finally, LipiDex 2 features new modules for automated quality control checks that also allow users to visualize data quality in a data dashboard user interface.
Collapse
Affiliation(s)
- Benton J Anderson
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Dain R Brademan
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Yuchen He
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Katherine A Overmyer
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Joshua J Coon
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| |
Collapse
|
2
|
Schenck EJ, Plataki M, Wheelock CE. A Lipid Map for Community-acquired Pneumonia with Sepsis: Observation Is the First Step in Scientific Progress. Am J Respir Crit Care Med 2024; 209:903-904. [PMID: 38412325 DOI: 10.1164/rccm.202401-0213ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 02/27/2024] [Indexed: 02/29/2024] Open
Affiliation(s)
- Edward J Schenck
- NewYork-Presbyterian Hospital and Joan and Sanford I. Weill Department of Medicine Weill Cornell Medicine New York, New York
| | - Maria Plataki
- NewYork-Presbyterian Hospital and Joan and Sanford I. Weill Department of Medicine Weill Cornell Medicine New York, New York
| | - Craig E Wheelock
- Unit of Integrative Metabolomics Institute of Environmental Medicine Karolinska Institute Stockholm, Sweden
- Department of Respiratory Medicine and Allergy Karolinska University Hospital Stockholm, Sweden
| |
Collapse
|
3
|
Chappel JR, Kirkwood-Donelson KI, Reif DM, Baker ES. From big data to big insights: statistical and bioinformatic approaches for exploring the lipidome. Anal Bioanal Chem 2024; 416:2189-2202. [PMID: 37875675 PMCID: PMC10954412 DOI: 10.1007/s00216-023-04991-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/01/2023] [Accepted: 10/05/2023] [Indexed: 10/26/2023]
Abstract
The goal of lipidomic studies is to provide a broad characterization of cellular lipids present and changing in a sample of interest. Recent lipidomic research has significantly contributed to revealing the multifaceted roles that lipids play in fundamental cellular processes, including signaling, energy storage, and structural support. Furthermore, these findings have shed light on how lipids dynamically respond to various perturbations. Continued advancement in analytical techniques has also led to improved abilities to detect and identify novel lipid species, resulting in increasingly large datasets. Statistical analysis of these datasets can be challenging not only because of their vast size, but also because of the highly correlated data structure that exists due to many lipids belonging to the same metabolic or regulatory pathways. Interpretation of these lipidomic datasets is also hindered by a lack of current biological knowledge for the individual lipids. These limitations can therefore make lipidomic data analysis a daunting task. To address these difficulties and shed light on opportunities and also weaknesses in current tools, we have assembled this review. Here, we illustrate common statistical approaches for finding patterns in lipidomic datasets, including univariate hypothesis testing, unsupervised clustering, supervised classification modeling, and deep learning approaches. We then describe various bioinformatic tools often used to biologically contextualize results of interest. Overall, this review provides a framework for guiding lipidomic data analysis to promote a greater assessment of lipidomic results, while understanding potential advantages and weaknesses along the way.
Collapse
Affiliation(s)
- Jessie R Chappel
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, 27606, USA
| | - Kaylie I Kirkwood-Donelson
- Immunity, Inflammation, and Disease Laboratory, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, 27709, USA
| | - David M Reif
- Predictive Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, 27709, USA.
| | - Erin S Baker
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA.
| |
Collapse
|
4
|
Abrahams T, Nicholls SJ. Perspectives on the success of plasma lipidomics in cardiovascular drug discovery and future challenges. Expert Opin Drug Discov 2024; 19:281-290. [PMID: 38402906 DOI: 10.1080/17460441.2023.2292039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 12/04/2023] [Indexed: 02/27/2024]
Abstract
INTRODUCTION Plasma lipidomics has emerged as a powerful tool in cardiovascular drug discovery by providing insights into disease mechanisms, identifying potential biomarkers for diagnosis and prognosis, and discovering novel targets for drug development. Widespread application of plasma lipidomics is hampered by technological limitations and standardization and requires a collaborative approach to maximize its use in cardiovascular drug discovery. AREAS COVERED This review provides an overview of the utility of plasma lipidomics in cardiovascular drug discovery and discusses the challenges and future perspectives of this rapidly evolving field. The authors discuss the role of lipidomics in understanding the molecular mechanisms of CVD, identifying novel biomarkers for diagnosis and prognosis, and discovering new therapeutic targets for drug development. Furthermore, they highlight the challenges faced in data analysis, standardization, and integration with other omics approaches and propose future directions for the field. EXPERT OPINION Plasma lipidomics holds great promise for improving the diagnosis, treatment, and prevention of CVD. While challenges remain in standardization and technology, ongoing research and collaboration among scientists and clinicians will undoubtedly help overcome these obstacles. As lipidomics evolves, its impact on cardiovascular drug discovery and clinical practice is expected to grow, ultimately benefiting patients and healthcare systems worldwide.
Collapse
Affiliation(s)
- Timothy Abrahams
- From the Victorian Heart Institute, Monash University, Melbourne, Australia
| | - Stephen J Nicholls
- From the Victorian Heart Institute, Monash University, Melbourne, Australia
| |
Collapse
|
5
|
Tian CY, Yang QH, Lv HZ, Yue F, Zhou FF. Combined untargeted and targeted lipidomics approaches reveal potential biomarkers in type 2 diabetes mellitus cynomolgus monkeys. J Med Primatol 2024; 53:e12688. [PMID: 38083989 DOI: 10.1111/jmp.12688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 11/14/2023] [Accepted: 12/01/2023] [Indexed: 02/13/2024]
Abstract
BACKGROUND The significantly increasing incidence of type 2 diabetes mellitus (T2DM) over the last few decades triggers the demands of T2DM animal models to explore the pathogenesis, prevention, and therapy of the disease. The altered lipid metabolism may play an important role in the pathogenesis and progression of T2DM. However, the characterization of molecular lipid species in fasting serum related to T2DM cynomolgus monkeys is still underrecognized. METHODS Untargeted and targeted LC-mass spectrometry (MS)/MS-based lipidomics approaches were applied to characterize and compare the fasting serum lipidomic profiles of T2DM cynomolgus monkeys and the healthy controls. RESULTS Multivariate analysis revealed that 196 and 64 lipid molecules differentially expressed in serum samples using untargeted and targeted lipidomics as the comparison between the disease group and healthy group, respectively. Furthermore, the comparative analysis of differential serum lipid metabolites obtained by untargeted and targeted lipidomics approaches, four common serum lipid species (phosphatidylcholine [18:0_22:4], lysophosphatidylcholine [14:0], phosphatidylethanolamine [PE] [16:1_18:2], and PE [18:0_22:4]) were identified as potential biomarkers and all of which were found to be downregulated. By analyzing the metabolic pathway, glycerophospholipid metabolism was associated with the pathogenesis of T2DM cynomolgus monkeys. CONCLUSION The study found that four downregulated serum lipid species could serve as novel potential biomarkers of T2DM cynomolgus monkeys. Glycerophospholipid metabolism was filtered out as the potential therapeutic target pathway of T2DM progression. Our results showed that the identified biomarkers may offer a novel tool for tracking disease progression and response to therapeutic interventions.
Collapse
Affiliation(s)
- Chao-Yang Tian
- Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
| | | | - Hai-Zhou Lv
- Hainan Jingang Biotech Co., Ltd, Haikou, China
| | - Feng Yue
- Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
| | - Fei-Fan Zhou
- Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
| |
Collapse
|
6
|
Conroy MJ, Andrews RM, Andrews S, Cockayne L, Dennis E, Fahy E, Gaud C, Griffiths W, Jukes G, Kolchin M, Mendivelso K, Lopez-Clavijo A, Ready C, Subramaniam S, O’Donnell V. LIPID MAPS: update to databases and tools for the lipidomics community. Nucleic Acids Res 2024; 52:D1677-D1682. [PMID: 37855672 PMCID: PMC10767878 DOI: 10.1093/nar/gkad896] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/03/2023] [Accepted: 10/04/2023] [Indexed: 10/20/2023] Open
Abstract
LIPID MAPS (LIPID Metabolites and Pathways Strategy), www.lipidmaps.org, provides a systematic and standardized approach to organizing lipid structural and biochemical data. Founded 20 years ago, the LIPID MAPS nomenclature and classification has become the accepted community standard. LIPID MAPS provides databases for cataloging and identifying lipids at varying levels of characterization in addition to numerous software tools and educational resources, and became an ELIXIR-UK data resource in 2020. This paper describes the expansion of existing databases in LIPID MAPS, including richer metadata with literature provenance, taxonomic data and improved interoperability to facilitate FAIR compliance. A joint project funded by ELIXIR-UK, in collaboration with WikiPathways, curates and hosts pathway data, and annotates lipids in the context of their biochemical pathways. Updated features of the search infrastructure are described along with implementation of programmatic access via API and SPARQL. New lipid-specific databases have been developed and provision of lipidomics tools to the community has been updated. Training and engagement have been expanded with webinars, podcasts and an online training school.
Collapse
Affiliation(s)
- Matthew J Conroy
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Robert M Andrews
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Simon Andrews
- Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT, UK
| | - Lauren Cockayne
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Edward A Dennis
- Department of Pharmacology, Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093-0601, USA
| | - Eoin Fahy
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92037, USA
| | - Caroline Gaud
- Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT, UK
| | - William J Griffiths
- Swansea University Medical School, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - Geoff Jukes
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Maksim Kolchin
- Boehringer Ingelheim Espana SA, Carrer de Prat de la Riba, 50, 08174 Sant Cugat del Vallès, Barcelona, Spain
| | - Karla Mendivelso
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | | | - Caroline Ready
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Shankar Subramaniam
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92037, USA
| | - Valerie B O’Donnell
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| |
Collapse
|
7
|
Nguyen NH. Genetics and Genomics of Infectious Diseases in Key Aquaculture Species. Biology (Basel) 2024; 13:29. [PMID: 38248460 PMCID: PMC10813283 DOI: 10.3390/biology13010029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/02/2024] [Accepted: 01/02/2024] [Indexed: 01/23/2024]
Abstract
Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease and species specific and contingent upon a multitude of factors. The fields of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus (WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish, and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease-resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favorable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate-to-high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems and AI algorithms and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.
Collapse
Affiliation(s)
- Nguyen Hong Nguyen
- School of Science, Technology and Engineering, University of the Sunshine Coast, Maroochydore, QLD 4558, Australia
| |
Collapse
|
8
|
Jia W, Guo A, Bian W, Zhang R, Wang X, Shi L. Integrative deep learning framework predicts lipidomics-based investigation of preservatives on meat nutritional biomarkers and metabolic pathways. Crit Rev Food Sci Nutr 2023:1-15. [PMID: 38127336 DOI: 10.1080/10408398.2023.2295016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Preservatives are added as antimicrobial agents to extend the shelf life of meat. Adding preservatives to meat products can affect their flavor and nutrition. This review clarifies the effects of preservatives on metabolic pathways and network molecular transformations in meat products based on lipidomics, metabolomics and proteomics analyses. Preservatives change the nutrient content of meat products via altering ionic strength and pH to influence enzyme activity. Ionic strength in salt triggers muscle triglyceride hydrolysis by causing phosphorylation and lipid droplet splitting in adipose tissue hormone-sensitive lipase and triglyceride lipase. DisoLipPred exploiting deep recurrent networks and transfer learning can predict the lipid binding trend of each amino acid in the disordered region of input protein sequences, which could provide omics analyses of biomarkers metabolic pathways in meat products. While conventional meat quality assessment tools are unable to elucidate the intrinsic mechanisms and pathways of variables in the influences of preservatives on the quality of meat products, the promising application of omics techniques in food analysis and discovery through multimodal learning prediction algorithms of neural networks (e.g., deep neural network, convolutional neural network, artificial neural network) will drive the meat industry to develop new strategies for food spoilage prevention and control.
Collapse
Affiliation(s)
- Wei Jia
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an, China
- Agricultural Product Processing and Inspection Center, Shaanxi Testing Institute of Product Quality Supervision, Xi'an, Shaanxi, China
- Agricultural Product Quality Research Center, Shaanxi Research Institute of Agricultural Products Processing Technology, Xi'an, China
- Food Safety Testing Center, Shaanxi Sky Pet Biotechnology Co., Ltd, Xi'an, China
| | - Aiai Guo
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an, China
| | - Wenwen Bian
- Agricultural Product Processing and Inspection Center, Shaanxi Testing Institute of Product Quality Supervision, Xi'an, Shaanxi, China
| | - Rong Zhang
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an, China
| | - Xin Wang
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an, China
| | - Lin Shi
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an, China
| |
Collapse
|
9
|
Teixeira FS, Pimentel LL, Pintado ME, Rodríguez-Alcalá LM. Impaired hepatic lipid metabolism and biomarkers in fatty liver disease. Biochimie 2023; 215:69-74. [PMID: 37769937 DOI: 10.1016/j.biochi.2023.09.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 09/13/2023] [Accepted: 09/17/2023] [Indexed: 10/03/2023]
Abstract
The liver plays a crucial role in lipid metabolism and metabolic homeostasis. Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common chronic liver disease worldwide and currently has no specific treatments. Lifestyle modifications such as weight loss, exercise, and dietary changes are recommended to reduce the risk factors associated with the disease. Oxidized cholesterol products, some phospholipids and diacylglycerols can activate inflammatory pathways and contribute to the progression to Non-Alcoholic Steatohepatitis. Monitoring the whole plasma and liver lipidome may provide insights into the onset, development, and prevention of inflammatory-related diseases. As Lipid Droplets (LDs) represent augmented lipid reservoirs in NAFLD, new developments are being made on different therapies focused on LD associated proteins modulation (seipin, PLIN-2), as well as LD lipophagy mechanisms. The information covered in this publication provides an overview of the available research on lipid biomarkers linked to NAFLD and can be used to guide the development of future pharmacological therapies.
Collapse
Affiliation(s)
- Francisca S Teixeira
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Rua Diogo Botelho 1327, 4169-005, Porto, Portugal.
| | - Lígia L Pimentel
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Rua Diogo Botelho 1327, 4169-005, Porto, Portugal.
| | - Manuela E Pintado
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Rua Diogo Botelho 1327, 4169-005, Porto, Portugal.
| | - Luís M Rodríguez-Alcalá
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Rua Diogo Botelho 1327, 4169-005, Porto, Portugal.
| |
Collapse
|
10
|
Kortesniemi M, Noerman S, Kårlund A, Raita J, Meuronen T, Koistinen V, Landberg R, Hanhineva K. Nutritional metabolomics: Recent developments and future needs. Curr Opin Chem Biol 2023; 77:102400. [PMID: 37804582 DOI: 10.1016/j.cbpa.2023.102400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/21/2023] [Accepted: 09/07/2023] [Indexed: 10/09/2023]
Abstract
Metabolomics has rapidly been adopted as one of the key methods in nutrition research. This review focuses on the recent developments and updates in the field, including the analytical methodologies that encompass improved instrument sensitivity, sampling techniques and data integration (multiomics). Metabolomics has advanced the discovery and validation of dietary biomarkers and their implementation in health research. Metabolomics has come to play an important role in the understanding of the role of small molecules resulting from the diet-microbiota interactions when gut microbiota research has shifted towards improving the understanding of the activity and functionality of gut microbiota rather than composition alone. Currently, metabolomics plays an emerging role in precision nutrition and the recent developments therein are discussed.
Collapse
Affiliation(s)
- Maaria Kortesniemi
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland.
| | - Stefania Noerman
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
| | - Anna Kårlund
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Jasmin Raita
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Topi Meuronen
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Ville Koistinen
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland; Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, FI-70211 Kuopio, Finland
| | - Rikard Landberg
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
| | - Kati Hanhineva
- Food Sciences Unit, Department of Life Technologies, University of Turku, FI-20014 Turun yliopisto, Finland; Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, FI-70211 Kuopio, Finland
| |
Collapse
|
11
|
Tietel Z, Hammann S, Meckelmann SW, Ziv C, Pauling JK, Wölk M, Würf V, Alves E, Neves B, Domingues MR. An overview of food lipids toward food lipidomics. Compr Rev Food Sci Food Saf 2023; 22:4302-4354. [PMID: 37616018 DOI: 10.1111/1541-4337.13225] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 06/20/2023] [Accepted: 07/27/2023] [Indexed: 08/25/2023]
Abstract
Increasing evidence regarding lipids' beneficial effects on human health has changed the common perception of consumers and dietary officials about the role(s) of food lipids in a healthy diet. However, lipids are a wide group of molecules with specific nutritional and bioactive properties. To understand their true nutritional and functional value, robust methods are needed for accurate identification and quantification. Specific analytical strategies are crucial to target specific classes, especially the ones present in trace amounts. Finding a unique and comprehensive methodology to cover the full lipidome of each foodstuff is still a challenge. This review presents an overview of the lipids nutritionally relevant in foods and new trends in food lipid analysis for each type/class of lipids. Food lipid classes are described following the LipidMaps classification, fatty acids, endocannabinoids, waxes, C8 compounds, glycerophospholipids, glycerolipids (i.e., glycolipids, betaine lipids, and triglycerides), sphingolipids, sterols, sercosterols (vitamin D), isoprenoids (i.e., carotenoids and retinoids (vitamin A)), quinones (i.e., coenzyme Q, vitamin K, and vitamin E), terpenes, oxidized lipids, and oxylipin are highlighted. The uniqueness of each food group: oil-, protein-, and starch-rich, as well as marine foods, fruits, and vegetables (water-rich) regarding its lipid composition, is included. The effect of cooking, food processing, and storage, in addition to the importance of lipidomics in food quality and authenticity, are also discussed. A critical review of challenges and future trends of the analytical approaches and computational methods in global food lipidomics as the basis to increase consumer awareness of the significant role of lipids in food quality and food security worldwide is presented.
Collapse
Affiliation(s)
- Zipora Tietel
- Department of Food Science, Gilat Research Center, Agricultural Research Organization, Volcani Institute, M.P. Negev, Israel
| | - Simon Hammann
- Department of Chemistry and Pharmacy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Sven W Meckelmann
- Applied Analytical Chemistry, University of Duisburg-Essen, Essen, Germany
| | - Carmit Ziv
- Department of Postharvest Science, Agricultural Research Organization, Volcani Center, Rishon LeZion, Israel
| | - Josch K Pauling
- LipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich (TUM), Freising, Germany
| | - Michele Wölk
- Lipid Metabolism: Analysis and Integration; Center of Membrane Biochemistry and Lipid Research; Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Vivian Würf
- LipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich (TUM), Freising, Germany
| | - Eliana Alves
- Mass Spectrometry Centre, LAQV-REQUIMTE, Department of Chemistry, Santiago University Campus, University of Aveiro, Aveiro, Portugal
| | - Bruna Neves
- Mass Spectrometry Centre, LAQV-REQUIMTE, Department of Chemistry, Santiago University Campus, University of Aveiro, Aveiro, Portugal
- Centre for Environmental and Marine Studies, CESAM, Department of Chemistry, Santiago University Campus, University of Aveiro, Aveiro, Portugal
| | - M Rosário Domingues
- Mass Spectrometry Centre, LAQV-REQUIMTE, Department of Chemistry, Santiago University Campus, University of Aveiro, Aveiro, Portugal
- Centre for Environmental and Marine Studies, CESAM, Department of Chemistry, Santiago University Campus, University of Aveiro, Aveiro, Portugal
| |
Collapse
|
12
|
Baker JL. Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research. FEMS Microbiol Rev 2023; 47:fuad051. [PMID: 37667515 PMCID: PMC10503653 DOI: 10.1093/femsre/fuad051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 08/02/2023] [Accepted: 09/01/2023] [Indexed: 09/06/2023] Open
Abstract
The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.
Collapse
Affiliation(s)
- Jonathon L Baker
- Department of Oral Rehabilitation & Biosciences, School of Dentistry, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR 97202, United States
- Genomic Medicine Group, J. Craig Venter Institute, La Jolla, CA 92037, United States
- Department of Pediatrics, UC San Diego School of Medicine, La Jolla, CA 92093, United States
| |
Collapse
|
13
|
van de Lavoir M, da Silva KM, Iturrospe E, Robeyns R, van Nuijs ALN, Covaci A. Untargeted hair lipidomics: comprehensive evaluation of the hair-specific lipid signature and considerations for retrospective analysis. Anal Bioanal Chem 2023; 415:5589-5604. [PMID: 37468753 DOI: 10.1007/s00216-023-04851-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/21/2023]
Abstract
Lipidomics investigates the composition and function of lipids, typically employing blood or tissue samples as the primary study matrices. Hair has recently emerged as a potential complementary sample type to identify biomarkers in early disease stages and retrospectively document an individual's metabolic status due to its long detection window of up to several months prior to the time of sampling. However, the limited coverage of lipid profiling presented in previous studies has hindered its exploitation. This study aimed to evaluate the lipid coverage of hair using an untargeted liquid chromatography-high-resolution mass spectrometry lipidomics platform. Two distinct three-step exhaustive extraction experiments were performed using a hair metabolomics one-phase extraction technique that has been recently optimized, and the two-phase Folch extraction method which is recognized as the gold standard for lipid extraction in biological matrices. The applied lipidomics workflow improved hair lipid coverage, as only 99 species could be annotated using the one-phase extraction method, while 297 lipid species across six categories were annotated with the Folch method. Several lipids in hair were reported for the first time, including N-acyl amino acids, diradylglycerols, and coenzyme Q10. The study suggests that hair lipids are not solely derived from de novo synthesis in hair, but are also incorporated from sebum and blood, making hair a valuable matrix for clinical, forensic, and dermatological research. The improved understanding of the lipid composition and analytical considerations for retrospective analysis offers valuable insights to contextualize untargeted hair lipidomic analysis and facilitate the use of hair in translational studies.
Collapse
Affiliation(s)
- Maria van de Lavoir
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium.
| | - Katyeny Manuela da Silva
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium
| | - Elias Iturrospe
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium
- Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel, Brussels, Belgium
| | - Rani Robeyns
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium
| | - Alexander L N van Nuijs
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium
| | - Adrian Covaci
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium.
| |
Collapse
|
14
|
Cajka T, Hricko J, Rudl Kulhava L, Paucova M, Novakova M, Fiehn O, Kuda O. Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling. Metabolites 2023; 13:966. [PMID: 37755246 PMCID: PMC10536874 DOI: 10.3390/metabo13090966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 08/19/2023] [Accepted: 08/21/2023] [Indexed: 09/28/2023] Open
Abstract
Liquid chromatography-mass spectrometry (LC-MS) is the key technique for analyzing complex lipids in biological samples. Various LC-MS modes are used for lipid separation, including different stationary phases, mobile-phase solvents, and modifiers. Quality control in lipidomics analysis is crucial to ensuring the generated data's reliability, reproducibility, and accuracy. While several quality control measures are commonly discussed, the impact of organic solvent quality during LC-MS analysis is often overlooked. Additionally, the annotation of complex lipids remains prone to biases, leading to potential misidentifications and incomplete characterization of lipid species. In this study, we investigate how LC-MS-grade isopropanol from different vendors may influence the quality of the mobile phase used in LC-MS-based untargeted lipidomic profiling of biological samples. Furthermore, we report the occurrence of an unusual, yet highly abundant, ethylamine adduct [M+46.0651]+ that may form for specific lipid subclasses during LC-MS analysis in positive electrospray ionization mode when acetonitrile is part of the mobile phase, potentially leading to lipid misidentification. These findings emphasize the importance of considering solvent quality in LC-MS analysis and highlight challenges in lipid annotation.
Collapse
Affiliation(s)
- Tomas Cajka
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Jiri Hricko
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Lucie Rudl Kulhava
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Michaela Paucova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Michaela Novakova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, 451 Health Sciences Drive, Davis, CA 95616, USA;
| | - Ondrej Kuda
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| |
Collapse
|
15
|
B O'Donnell V. Lipidomics Moves to Center Stage of Biomedicine. Function (Oxf) 2023; 4:zqac071. [PMID: 36632473 PMCID: PMC9830535 DOI: 10.1093/function/zqac071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 12/23/2022] [Indexed: 01/05/2023]
|
16
|
Abstract
Ferroptosis is a form of regulated cell death that occurs due to abnormal lipid metabolism. Lipids, which have been identified in over 45,000 different molecular species, play essential roles in modulating basic life processes. The process of ferroptosis is highly reliant on various lipid species, with polyunsaturated fatty acids (PUFAs) playing a central role in driving this process. Recent advances in mass spectrometry-based lipidomics have led to a surge in studies on ferroptosis. To explore the mechanism of lipid homeostasis in ferroptosis, the development of lipidomics techniques is critical. Currently, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) are the most widely used analytical techniques in lipidomics. These techniques offer deeper insights into the complex lipid mechanisms that underlie ferroptosis.
Collapse
Affiliation(s)
- Zhi Lin
- Department of Pediatrics, The Third Xiangya Hospital Central South University, Changsha, Hunan, China
| | - Minghua Yang
- Department of Pediatrics, The Third Xiangya Hospital Central South University, Changsha, Hunan, China.
| |
Collapse
|