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Animal and Cellular Models in Metabolomics Research

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A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Animal Metabolism".

Deadline for manuscript submissions: closed (30 May 2020) | Viewed by 27017

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Special Issue Editors

Dr. Michal Ciborowski

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Guest Editor

Clinical Research Centre, Medical University of Bialystok, 15-089 Białystok, Poland
Interests: metrabolomics; mass spectrometry; diabetes and oncolody
Special Issues, Collections and Topics in MDPI journals

Dr. Joanna Godzien

E-Mail Website
Guest Editor

Clinical Research Centre, Medical University of Bialystok, 15-089 Białystok, Poland
Interests: LC-MS metabolomics; lipidomics; metabolites annotation and diabetes
Special Issues, Collections and Topics in MDPI journals

Dr. Stanislaw Deja

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Guest Editor

Center for Human Nutrition, The University of Texas Southwestern Medical Center, Dallas, TX 75390-8828, USA
Interests: metabolomics; stable isotope tracers; metabolic flux analysis; computational models of metabolism and liver metabolism
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics, an essential tool of modern biochemical research, is no longer solely a hypothesis-generating platform, but rather is extensively used in hypothesis testing studies. Progress in gene manipulation techniques allows the turning on and off of particular enzymatic functions in a cell- or tissue-specific manner. High-throughput cell culture and animal model studies are increasingly popular. While many metabolic questions can be answered under well-controlled cell culture conditions, the true test is the transition from the dish to the in vivo models.

We therefore invite research and review articles devoted to various aspects of cell and animal models used in metabolic studies. The focus of this Special Issue involves technical approaches and the translation from cell to animal metabolic models. The topics include but are not limited to the use of cell culture and animal models in the exploration of single cell metabolism, high-throughput metabolomics, and the use of stable isotope tracers for metabolic flux analysis. Studies using genetic manipulations or in vivo dietary and pharmacological interventions are particularly welcome. Studies applying in vitro/in vivo imaging of metabolites with the use of DNP-NMR and MRI are highly anticipated. Finally, protocols describing experimental guidelines are also welcome.

The Special Issue is open for submission now. A proper extension may be granted, please kindly let us know in advance. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the Special Issue website.

Dr. Michal Ciborowski
Dr. Joanna Godzien
Dr. Stanislaw Deja
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

cell culture models
animal models
animal microbiome
tumour xenografts
targeted and untargeted metabolomics
metabolic flux analysis (MFA)
metabolic imaging
DNP-NMR

Published Papers (7 papers)

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Research

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22 pages, 4067 KiB

Open AccessArticle

Metabolic Profiling of a Porcine Combat Trauma-Injury Model Using NMR and Multi-Mode LC-MS Metabolomics—A Preliminary Study

by Anna Karen Carrasco Laserna, Yiyang Lai, Guihua Fang, Rajaseger Ganapathy, Mohamed Shirhan Bin Mohamed Atan, Jia Lu, Jian Wu, Mahesh Uttamchandani, Shabbir M. Moochhala and Sam Fong Yau Li

Metabolites 2020, 10(9), 373; https://doi.org/10.3390/metabo10090373 - 16 Sep 2020

Cited by 4 | Viewed by 2702

Abstract

Profiles of combat injuries worldwide have shown that penetrating trauma is one of the most common injuries sustained during battle. This is usually accompanied by severe bleeding or hemorrhage. If the soldier does not bleed to death, he may eventually succumb to complications arising from trauma hemorrhagic shock (THS). THS occurs when there is a deficiency of oxygen reaching the organs due to excessive blood loss. It can trigger massive metabolic derangements and an overwhelming inflammatory response, which can subsequently lead to the failure of organs and possibly death. A better understanding of the acute metabolic changes occurring after THS can help in the development of interventional strategies, as well as lead to the identification of potential biomarkers for rapid diagnosis of hemorrhagic shock and organ failure. In this preliminary study, a metabolomic approach using the complementary platforms of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography coupled with mass spectrometry (LC-MS) was used to determine the metabolic changes occurring in a porcine model of combat trauma injury comprising of penetrating trauma to a limb with hemorrhagic shock. Several metabolites associated with the acute-phase reaction, inflammation, energy depletion, oxidative stress, and possible renal dysfunction were identified to be significantly changed after a thirty-minute shock period. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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23 pages, 2756 KiB

Open AccessFeature PaperArticle

Metabolic Signatures of Tumor Responses to Doxorubicin Elucidated by Metabolic Profiling in Ovo

by Iman W. Achkar, Sara Kader, Shaima S. Dib, Kulsoom Junejo, Salha Bujassoum Al-Bader, Shahina Hayat, Aditya M. Bhagwat, Xavier Rousset, Yan Wang, Jean Viallet, Karsten Suhre and Anna Halama

Metabolites 2020, 10(7), 268; https://doi.org/10.3390/metabo10070268 - 28 Jun 2020

Cited by 21 | Viewed by 3626

Abstract

Background: Dysregulated cancer metabolism is associated with acquired resistance to chemotherapeutic treatment and contributes to the activation of cancer survival mechanisms. However, which metabolic pathways are activated following treatment often remains elusive. The combination of chicken embryo tumor models (in ovo) with metabolomics phenotyping could offer a robust platform for drug testing. Here, we assess the potential of this approach in the treatment of an in ovo triple negative breast cancer with doxorubicin. Methods: MB-MDA-231 cells were grafted in ovo. The resulting tumors were then treated with doxorubicin or dimethyl sulfoxide (DMSO) for six days. Tumors were collected and analyzed using a global untargeted metabolomics and comprehensive lipidomics. Results: We observed a significant suppression of tumor growth in the doxorubicin treated group. The metabolic profiles of doxorubicin and DMSO-treated tumors were clearly separated in a principle component analysis. Inhibition of glycolysis, nucleotide synthesis, and glycerophospholipid metabolism appear to be triggered by doxorubicin treatment, which could explain the observed suppressed tumor growth. In addition, metabolic cancer survival mechanisms could be supported by an acceleration of antioxidative pathways. Conclusions: Metabolomics in combination with in ovo tumor models provide a robust platform for drug testing to reveal tumor specific treatment targets such as the antioxidative tumor capacity. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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15 pages, 2031 KiB

Open AccessArticle

Comparison of Metabolomic Profiles of Organs in Mice of Different Strains Based on SPME-LC-HRMS

by Katarzyna Burlikowska, Iga Stryjak, Joanna Bogusiewicz, Bogumiła Kupcewicz, Karol Jaroch and Barbara Bojko

Metabolites 2020, 10(6), 255; https://doi.org/10.3390/metabo10060255 - 17 Jun 2020

Cited by 10 | Viewed by 3736

Abstract

Given that the extent to which genetics alters the metabolomic profile of tissues is still poorly understood, the current study aimed to characterize and investigate the metabolite profiles of brain, liver, kidney and skeletal muscle of two common mouse inbred strains (BALB/c, C57BL/6) and one outbred stock (CD1) for strain-specific differences. Male mice (n = 15) at the age of 12 weeks were used: BALB/c (n = 5), C57BL/6 (n = 5) and CD1 (n = 5). Solid phase microextraction (SPME) was applied for the extraction of analytes from the tissues. SPME fibers (approximately 0.2 mm in diameter) coated with a biocompatible sorbent (4 mm length of hydrophilic-lipophilic balanced particles) were inserted into each organ immediately after euthanasia. Samples were analyzed using liquid chromatography coupled to a Q-Exactive Focus Orbitrap mass spectrometer. Distinct interstrain differences in the metabolomic patterns of brain and liver tissue were revealed. The metabolome of kidney and muscle tissue in BALB/c mice differed greatly from C57BL/6 and CD1 strains. The main compounds differentiating all the targeted organs were alpha-amino acids, purine nucleotides and fatty acid esters. The results of the study indicate that the baseline metabolome of organs, as well as different metabolic pathways, vary widely among general-purpose models of laboratory mice commonly used in biomedical research. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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15 pages, 3855 KiB

Open AccessArticle

Evaluation of MDA-MB-468 Cell Culture Media Analysis in Predicting Triple-Negative Breast Cancer Patient Sera Metabolic Profiles

by Wojciech Wojtowicz, Anna Wróbel, Karolina Pyziak, Radosław Tarkowski, Alicja Balcerzak, Marek Bębenek and Piotr Młynarz

Metabolites 2020, 10(5), 173; https://doi.org/10.3390/metabo10050173 - 27 Apr 2020

Cited by 10 | Viewed by 3322

Abstract

Triple-negative breast cancer (TNBC) is characterized by limited survival, poor prognosis, and high recurrence. Understanding the metabolic adaptations of TNBC could help reveal improved treatment regiments. Here we performed a comprehensive ¹H NMR metabolic characterization of the MDA-MB-468 cell line, a commonly used model of TNBC, followed by an analysis of serum samples obtained from TNBC patients and healthy controls. MDA-MB-468 cells were cultured, and changes in the metabolic composition of the medium were monitored for 72 h. Based on time courses, metabolites were categorized as being consumed, being produced, or showing a mixed behavior. When comparing TNBC and control samples (HC), and by using multivariate and univariate analyses, we identified nine metabolites with differing profiles). The serum of TNBC patients was characterized by higher levels of glucose, glutamine, citrate, and acetoacetate and by lower levels of lactate, alanine, tyrosine, glutamate, and acetone. A comparative analysis between MDA-MB-468 cell culture media and TNBC patients’ serum identified a potential systemic response to the carcinogenesis-associated processes, highlighting that MDA-MB-468 cells footprint does not reflect metabolic changes observed in studied TNBC serum fingerprint. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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7 pages, 526 KiB

Open AccessArticle

A Cross-Sectional Study of Obesity Effects on the Metabolomic Profile of a Leptin-Resistant Swine Model

by M. Victoria Sanz-Fernandez, Laura Torres-Rovira, Jose L. Pesantez-Pacheco, Marta Vazquez-Gomez, Consolacion Garcia-Contreras, Susana Astiz and Antonio Gonzalez-Bulnes

Metabolites 2020, 10(3), 89; https://doi.org/10.3390/metabo10030089 - 5 Mar 2020

Cited by 6 | Viewed by 2144

Abstract

Identifying metabolite signatures associated with obesity and related diseases might represent a valuable preventive and therapeutic tool to predict subjects at risk, establish an accurate prognosis, and monitor treatment success. The current cross-sectional study is aimed to evaluate the metabolite profile of diet-induced obesity in a porcine model of leptin resistance. Six Iberian female pigs prone to develop obesity (OB) were ad libitum fed a fat-enriched diet (HFD) for 82 days. Five lean Iberian sows (CON) in a maintenance diet served as controls. At the end of the dietary treatments, all animals were sacrificed, and plasma, liver, and muscle samples were immediately collected for nuclear magnetic resonance analysis. In plasma, signals corresponding to betaine, glycerophosphocholine/phosphocholine, glycine, and glutamate were decreased; and the valine signal was increased in OB sows compared to controls. Similarly, the betaine signal was decreased in the liver. No differences were detected in muscle. The observed metabolite changes suggest alterations in branched chain amino-acid metabolism and the methionine-homocysteine cycle, which have been previously associated with obesity-related diseases and type 2 diabetes in human observational studies. The current study supports the utilization of the leptin resistant Iberian pig for further interventional research in the field. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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Review

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27 pages, 1452 KiB

Open AccessReview

Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis

by Svetlana Volkova, Marta R. A. Matos, Matthias Mattanovich and Igor Marín de Mas

Metabolites 2020, 10(8), 303; https://doi.org/10.3390/metabo10080303 - 24 Jul 2020

Cited by 40 | Viewed by 6486

Abstract

Metabolic networks are regulated to ensure the dynamic adaptation of biochemical reaction fluxes to maintain cell homeostasis and optimal metabolic fitness in response to endogenous and exogenous perturbations. To this end, metabolism is tightly controlled by dynamic and intricate regulatory mechanisms involving allostery, enzyme abundance and post-translational modifications. The study of the molecular entities involved in these complex mechanisms has been boosted by the advent of high-throughput technologies. The so-called omics enable the quantification of the different molecular entities at different system layers, connecting the genotype with the phenotype. Therefore, the study of the overall behavior of a metabolic network and the omics data integration and analysis must be approached from a holistic perspective. Due to the close relationship between metabolism and cellular phenotype, metabolic modelling has emerged as a valuable tool to decipher the underlying mechanisms governing cell phenotype. Constraint-based modelling and kinetic modelling are among the most widely used methods to study cell metabolism at different scales, ranging from cells to tissues and organisms. These approaches enable integrating metabolomic data, among others, to enhance model predictive capabilities. In this review, we describe the current state of the art in metabolic modelling and discuss future perspectives and current challenges in the field. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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26 pages, 2976 KiB

Open AccessReview

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

by Teresa W. -M. Fan, Richard M. Higashi, Yelena Chernayavskaya and Andrew N. Lane

Metabolites 2020, 10(6), 249; https://doi.org/10.3390/metabo10060249 - 15 Jun 2020

Cited by 9 | Viewed by 4168

Abstract

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME. Full article

(This article belongs to the Special Issue Animal and Cellular Models in Metabolomics Research)

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