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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: closed (31 July 2016) | Viewed by 107504

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Prof. Dr. Philip Newton Baker

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Guest Editor

1. Director – Gravida: National Centre for Growth and Development, Professor of Maternal and Fetal Health, Consultant Obstetrician and Senior Scientist, The University of Auckland, Level 2, Building 505, 85 Park Rd, Grafton, Private Bag 92019, Auckland 1142, New Zealand
2. Research Professor, Institute of Science and Technology & Medicine, Keele University, Keele, UK
3. Distinguished Professor, Chongqing Medical University, Chongqing, China
Interests: preeclampsia; fetal growth restriction; pregnancy; placenta; metabolomics
Special Issues, Collections and Topics in MDPI journals

Dr. Ting-Li (Morgan) Han

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Guest Editor

Consulting scientist- Gravida: National Centre for Growth and Development The University of Auckland; Post-doctoral fellow- Canada-China-New Zealand Joint Laboratory of Maternal and Fetal Medicine, The First Affiliated Hospital of Chongqing Medical University
Interests: metabolomics; GC-MS; LC-MS; pregancy complications; biomarker discovery; bioinformatic tools

Dr. Elizabeth McKenzie

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Guest Editor

Research Fellow – Gravida: National Centre for Growth and Development, Liggins Institute, Faculty of Medical and Health Sciences, University of Auckland, Level 2, Bldg 505 85 Park Rd, Grafton, Auckland 1142, New Zealand
Interests: Sample preparation methods for metabolite profiling; instrument techniques for metabolomics; data analysis pipelines for metabolomic data; user-friendly interfaces for data analysis

Special Issue Information

Dear Colleagues,

The advent of laboratory robotics and multi-core computing has led to the development of high-throughput laboratory analysis and rapid data processing, driving a transformation in the way in which samples are analysed. We now have the ability to identify and measure hundreds, or thousands, of compounds in every sample, for hundreds or thousands of samples, simultaneously. In medicine, the increase in analytical power has rapidly advanced metabolic profiling of disease, enabling studies of large population cohorts. Low mass compounds produced by cellular processes can provide clues to early or hidden disease states, and the identification of such biomarkers can lead to the development of more reliable diagnostic tests. However, comprehensive profiling of all metabolites in a sample is challenging because the chemical and physical properties of each metabolite are different, and the presence of interfering compounds in the sample extract can affect analysis. While techniques exist that will analyse many metabolites adequately, it is currently not possible to analyse all metabolites optimally using a single technique.

Since its conception in the mid-late 20th century, metabolomic analysis has been dominated by mass spectrometry and nuclear magnetic resonance spectroscopy, and many emerging metabolomics technologies use hyphenated instrumentation with different sample introduction and separation techniques, such as gas chromatography, liquid chromatography, or capillary electrophoresis. While we now have the ability to acquire large amounts of high-resolution data, the software available to process and analyse this type of data has lagged somewhat, with the fastest progress being made in open source applications developed by individual researchers, rather than by commercial scientific companies. This has created a data analysis bottleneck in many metabolomic studies, especially when datasets run into thousands of samples.

This Special Issue will cover novel emerging technologies, techniques, and software in metabolomics analysis, with emphasis on the following topics:

Discovery metabolomics.
Translational metabolomics.
Robotics and automation
High-throughput technologies
Biosample extraction techniques
New sample introduction technologies
Modelling of metabolite pathways in disease
Quality control techniques
Bioinformatics tools
Design and optimisation of data processing software.
Metabolomics for personalised medicine

Prof. Philip N. Baker
Dr. Elizabeth McKenzie
Dr. Morgan Han
Guest Editors

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Keywords

metabolomics
mass spectrometry
nuclear magnetic resonance
translational metabolomics
high-throughput analysis
metabolite profiling
biomarker discovery
bioinformatics

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Published Papers (12 papers)

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Research

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935 KiB

Open AccessArticle

A Systematic Evaluation of Blood Serum and Plasma Pre-Analytics for Metabolomics Cohort Studies

by Elodie Jobard, Olivier Trédan, Déborah Postoly, Fabrice André, Anne-Laure Martin, Bénédicte Elena-Herrmann and Sandrine Boyault

Int. J. Mol. Sci. 2016, 17(12), 2035; https://doi.org/10.3390/ijms17122035 - 5 Dec 2016

Cited by 59 | Viewed by 8222

Abstract

The recent thriving development of biobanks and associated high-throughput phenotyping studies requires the elaboration of large-scale approaches for monitoring biological sample quality and compliance with standard protocols. We present a metabolomic investigation of human blood samples that delineates pitfalls and guidelines for the collection, storage and handling procedures for serum and plasma. A series of eight pre-processing technical parameters is systematically investigated along variable ranges commonly encountered across clinical studies. While metabolic fingerprints, as assessed by nuclear magnetic resonance, are not significantly affected by altered centrifugation parameters or delays between sample pre-processing (blood centrifugation) and storage, our metabolomic investigation highlights that both the delay and storage temperature between blood draw and centrifugation are the primary parameters impacting serum and plasma metabolic profiles. Storing the blood drawn at 4 °C is shown to be a reliable routine to confine variability associated with idle time prior to sample pre-processing. Based on their fine sensitivity to pre-analytical parameters and protocol variations, metabolic fingerprints could be exploited as valuable ways to determine compliance with standard procedures and quality assessment of blood samples within large multi-omic clinical and translational cohort studies. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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Open AccessArticle

Effect of High-Carbohydrate Diet on Plasma Metabolome in Mice with Mitochondrial Respiratory Chain Complex III Deficiency

by Jayasimman Rajendran, Nikica Tomašić, Heike Kotarsky, Eva Hansson, Vidya Velagapudi, Jukka Kallijärvi and Vineta Fellman

Int. J. Mol. Sci. 2016, 17(11), 1824; https://doi.org/10.3390/ijms17111824 - 1 Nov 2016

Cited by 12 | Viewed by 6236

Abstract

Mitochondrial disorders cause energy failure and metabolic derangements. Metabolome profiling in patients and animal models may identify affected metabolic pathways and reveal new biomarkers of disease progression. Using liver metabolomics we have shown a starvation-like condition in a knock-in (Bcs1l^c.232A>G) mouse model of GRACILE syndrome, a neonatal lethal respiratory chain complex III dysfunction with hepatopathy. Here, we hypothesized that a high-carbohydrate diet (HCD, 60% dextrose) will alleviate the hypoglycemia and promote survival of the sick mice. However, when fed HCD the homozygotes had shorter survival (mean ± SD, 29 ± 2.5 days, n = 21) than those on standard diet (33 ± 3.8 days, n = 30), and no improvement in hypoglycemia or liver glycogen depletion. We investigated the plasma metabolome of the HCD- and control diet-fed mice and found that several amino acids and urea cycle intermediates were increased, and arginine, carnitines, succinate, and purine catabolites decreased in the homozygotes. Despite reduced survival the increase in aromatic amino acids, an indicator of liver mitochondrial dysfunction, was normalized on HCD. Quantitative enrichment analysis revealed that glycine, serine and threonine metabolism, phenylalanine and tyrosine metabolism, and urea cycle were also partly normalized on HCD. This dietary intervention revealed an unexpected adverse effect of high-glucose diet in complex III deficiency, and suggests that plasma metabolomics is a valuable tool in evaluation of therapies in mitochondrial disorders. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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5595 KiB

Open AccessArticle

Metabolic Response to XD14 Treatment in Human Breast Cancer Cell Line MCF-7

by Daqiang Pan, Michel Kather, Lucas Willmann, Manuel Schlimpert, Christoph Bauer, Simon Lagies, Karin Schmidtkunz, Steffen U. Eisenhardt, Manfred Jung, Stefan Günther and Bernd Kammerer

Int. J. Mol. Sci. 2016, 17(10), 1772; https://doi.org/10.3390/ijms17101772 - 24 Oct 2016

Cited by 9 | Viewed by 6981

Abstract

XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment. XD14 inhibits bromodomain and extra-terminal domain (BET) proteins (BRD2, BRD3, BRD4 and BRDT) and consequently suppresses cell proliferation. In this study, metabolic profiling reveals the molecular effects in the human breast cancer cell line MCF-7 (Michigan Cancer Foundation-7) treated by XD14. A three-day time series experiment with two concentrations of XD14 was performed. Gas chromatography-mass spectrometry (GC-MS) was applied for untargeted profiling of treated and non-treated MCF-7 cells. The gained data sets were evaluated by several statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Cell proliferation was strongly inhibited by treatment with 50 µM XD14. Samples could be discriminated by time and XD14 concentration using PLS-DA. From the 117 identified metabolites, 67 were significantly altered after XD14 treatment. These metabolites include amino acids, fatty acids, Krebs cycle and glycolysis intermediates, as well as compounds of purine and pyrimidine metabolism. This massive intervention in energy metabolism and the lack of available nucleotides could explain the decreased proliferation rate of the cancer cells. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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2162 KiB

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New Potential Biomarker for Methasterone Misuse in Human Urine by Liquid Chromatography Quadrupole Time of Flight Mass Spectrometry

by Jianli Zhang, Jianghai Lu, Yun Wu, Xiaobing Wang, Youxuan Xu, Yinong Zhang and Yan Wang

Int. J. Mol. Sci. 2016, 17(10), 1628; https://doi.org/10.3390/ijms17101628 - 24 Sep 2016

Cited by 5 | Viewed by 5481

Abstract

In this study, methasterone urinary metabolic profiles were investigated by liquid chromatography quadrupole time of flight mass spectrometry (LC-QTOF-MS) in full scan and targeted MS/MS modes with accurate mass measurement. A healthy male volunteer was asked to take the drug and liquid–liquid extraction was employed to process urine samples. Chromatographic peaks for potential metabolites were hunted out with the theoretical [M − H]⁻ as a target ion in a full scan experiment and actual deprotonated ions were studied in targeted MS/MS experiment. Fifteen metabolites including two new sulfates (S1 and S2), three glucuronide conjugates (G2, G6 and G7), and three free metabolites (M2, M4 and M6) were detected for methasterone. Three metabolites involving G4, G5 and M5 were obtained for the first time in human urine samples. Owing to the absence of helpful fragments to elucidate the steroid ring structure of methasterone phase II metabolites, gas chromatography mass spectrometry (GC-MS) was employed to obtain structural information of the trimethylsilylated phase I metabolite released after enzymatic hydrolysis and the potential structure was inferred using a combined MS method. Metabolite detection times were also analyzed and G2 (18-nor-17β-hydroxymethyl-2α, 17α-dimethyl-androst-13-en-3α-ol-ξ-O-glucuronide) was thought to be new potential biomarker for methasterone misuse which can be detected up to 10 days. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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845 KiB

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Urinary Metabolic Phenotyping Reveals Differences in the Metabolic Status of Healthy and Inflammatory Bowel Disease (IBD) Children in Relation to Growth and Disease Activity

by Francois-Pierre Martin, Jessica Ezri, Ornella Cominetti, Laeticia Da Silva, Martin Kussmann, Jean-Philippe Godin and Andreas Nydegger

Int. J. Mol. Sci. 2016, 17(8), 1310; https://doi.org/10.3390/ijms17081310 - 11 Aug 2016

Cited by 27 | Viewed by 5715

Abstract

Background: Growth failure and delayed puberty are well known features of children and adolescents with inflammatory bowel disease (IBD), in addition to the chronic course of the disease. Urinary metabonomics was applied in order to better understand metabolic changes between healthy and IBD children. Methods: 21 Pediatric patients with IBD (mean age 14.8 years, 8 males) were enrolled from the Pediatric Gastroenterology Outpatient Clinic over two years. Clinical and biological data were collected at baseline, 6, and 12 months. 27 healthy children (mean age 12.9 years, 16 males) were assessed at baseline. Urine samples were collected at each visit and subjected to ¹H Nuclear Magnetic Resonance (NMR) spectroscopy. Results: Using ¹H NMR metabonomics, we determined that urine metabolic profiles of IBD children differ significantly from healthy controls. Metabolic differences include central energy metabolism, amino acid, and gut microbial metabolic pathways. The analysis described that combined urinary urea and phenylacetylglutamine—two readouts of nitrogen metabolism—may be relevant to monitor metabolic status in the course of disease. Conclusion: Non-invasive sampling of urine followed by metabonomic profiling can elucidate and monitor the metabolic status of children in relation to disease status. Further developments of omic-approaches in pediatric research might deliver novel nutritional and metabolic hypotheses. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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Review

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1511 KiB

Open AccessReview

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research

by David J. Beale, Oliver A. H. Jones, Avinash V. Karpe, Saravanan Dayalan, Ding Yuan Oh, Konstantinos A. Kouremenos, Warish Ahmed and Enzo A. Palombo

Int. J. Mol. Sci. 2017, 18(1), 24; https://doi.org/10.3390/ijms18010024 - 23 Dec 2016

Cited by 71 | Viewed by 10363

Abstract

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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2034 KiB

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Advances in Lipidomics for Cancer Biomarkers Discovery

by Francesca Perrotti, Consuelo Rosa, Ilaria Cicalini, Paolo Sacchetta, Piero Del Boccio, Domenico Genovesi and Damiana Pieragostino

Int. J. Mol. Sci. 2016, 17(12), 1992; https://doi.org/10.3390/ijms17121992 - 28 Nov 2016

Cited by 151 | Viewed by 10514

Abstract

Lipids play critical functions in cellular survival, proliferation, interaction and death, since they are involved in chemical-energy storage, cellular signaling, cell membranes, and cell–cell interactions. These cellular processes are strongly related to carcinogenesis pathways, particularly to transformation, progression, and metastasis, suggesting the bioactive lipids are mediators of a number of oncogenic processes. The current review gives a synopsis of a lipidomic approach in tumor characterization; we provide an overview on potential lipid biomarkers in the oncology field and on the principal lipidomic methodologies applied. The novel lipidomic biomarkers are reviewed in an effort to underline their role in diagnosis, in prognostic characterization and in prediction of therapeutic outcomes. A lipidomic investigation through mass spectrometry highlights new insights on molecular mechanisms underlying cancer disease. This new understanding will promote clinical applications in drug discovery and personalized therapy. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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1659 KiB

Open AccessReview

Why Are Omics Technologies Important to Understanding the Role of Nutrition in Inflammatory Bowel Diseases?

by Lynnette R. Ferguson and Matthew P. G. Barnett

Int. J. Mol. Sci. 2016, 17(10), 1763; https://doi.org/10.3390/ijms17101763 - 21 Oct 2016

Cited by 8 | Viewed by 6672

Abstract

For many years, there has been confusion about the role that nutrition plays in inflammatory bowel diseases (IBD). It is apparent that good dietary advice for one individual may prove inappropriate for another. As with many diseases, genome-wide association studies across large collaborative groups have been important in revealing the role of genetics in IBD, with more than 200 genes associated with susceptibility to the disease. These associations provide clues to explain the differences in nutrient requirements among individuals. In addition to genes directly involved in the control of inflammation, a number of the associated genes play roles in modulating the gut microbiota. Cell line models enable the generation of hypotheses as to how various bioactive dietary components might be especially beneficial for certain genetic groups. Animal models are necessary to mimic aspects of the complex aetiology of IBD, and provide an important link between tissue culture studies and human trials. Once we are sufficiently confident of our hypotheses, we can then take modified diets to an IBD population that is stratified according to genotype. Studies in IBD patients fed a Mediterranean-style diet have been important in validating our hypotheses and as a proof-of-principle for the application of these sensitive omics technologies to aiding in the control of IBD symptoms. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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1893 KiB

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Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era

by Abdellah Tebani, Lenaig Abily-Donval, Carlos Afonso, Stéphane Marret and Soumeya Bekri

Int. J. Mol. Sci. 2016, 17(7), 1167; https://doi.org/10.3390/ijms17071167 - 20 Jul 2016

Cited by 96 | Viewed by 12834

Abstract

Inborn errors of metabolism (IEM) represent a group of about 500 rare genetic diseases with an overall estimated incidence of 1/2500. The diversity of metabolic pathways involved explains the difficulties in establishing their diagnosis. However, early diagnosis is usually mandatory for successful treatment. Given the considerable clinical overlap between some inborn errors, biochemical and molecular tests are crucial in making a diagnosis. Conventional biological diagnosis procedures are based on a time-consuming series of sequential and segmented biochemical tests. The rise of “omic” technologies offers holistic views of the basic molecules that build a biological system at different levels. Metabolomics is the most recent “omic” technology based on biochemical characterization of metabolites and their changes related to genetic and environmental factors. This review addresses the principles underlying metabolomics technologies that allow them to comprehensively assess an individual biochemical profile and their reported applications for IEM investigations in the precision medicine era. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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946 KiB

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Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

by Jumpei Washio and Nobuhiro Takahashi

Int. J. Mol. Sci. 2016, 17(6), 870; https://doi.org/10.3390/ijms17060870 - 2 Jun 2016

Cited by 43 | Viewed by 8231

Abstract

Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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230 KiB

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Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

by Ina Aretz and David Meierhofer

Int. J. Mol. Sci. 2016, 17(5), 632; https://doi.org/10.3390/ijms17050632 - 27 Apr 2016

Cited by 130 | Viewed by 9803

Abstract

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

509 KiB

Open AccessReview

Gut Microbiota and Nonalcoholic Fatty Liver Disease: Insights on Mechanism and Application of Metabolomics

by Xuyun He, Guang Ji, Wei Jia and Houkai Li

Int. J. Mol. Sci. 2016, 17(3), 300; https://doi.org/10.3390/ijms17030300 - 15 Mar 2016

Cited by 70 | Viewed by 15352

Abstract

Gut microbiota are intricately involved in the development of obesity-related metabolic diseases such as nonalcoholic fatty liver disease (NAFLD), type 2 diabetes, and insulin resistance. In the current review, we discuss the role of gut microbiota in the development of NAFLD by focusing on the mechanisms of gut microbiota-mediated host energy metabolism, insulin resistance, regulation of bile acids and choline metabolism, as well as gut microbiota-targeted therapy. We also discuss the application of a metabolomic approach to characterize gut microbial metabotypes in NAFLD. Full article

(This article belongs to the Special Issue Metabolomic Technologies in Medicine)

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