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

Manuscript Submission Information

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

Title: The potential of metabolomics analysis to offer new insights into neonatal hypoxic ischaemic encephalopathy
Author: Deirdre Murray
Abstract: In this paper we will summarise research in this field to date, with an emphasis on reported metabolomic profiles, and new pathway alterations seen in newborn infants with hypoxic-ischaemic encephalopathy. We will also examine the evidence for a link between these alterations and long term outcome. We will discuss the potential for metabolomic biomarkers to guide intervention in HIE.

Title: Metabolomic studies of oral biofilm, oral cancer and beyond
Authors: Jumpei Washio and Nobuhiro Takahashi
Abstract: 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 researches. New techniques for metabolomics developed in this decade, and helped to solve these difficulties. Metabolomic analyses of the oral biofilm and oral cancer have produced various new findings. In addition, metabolomic 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.

Title: Metabolic Response to the Treatment of XD14 in Human Breast Cancer Cell Line MCF-7
Authors: Daqiang Pan ¹; Lucas Willmann ^1,2; Manuel Schlimpert ¹; Christoph Bauer ¹; Michel Kather ¹, Simon Lagies ¹, Karin Schmidtkunz ³; Manfred Jung ³; Stephan Flemming ³, Stefan Günther ³; Bernd Kammerer ¹,*
Affiliation: ¹ Center for Biological Systems Analysis ZBSA, Albert-Ludwigs-University Freiburg, 79104 Freiburg, Germany; ² Institute of Biology II, Albert-Ludwigs-University Freiburg, 79104 Freiburg, Germany; ³ Institute of Pharmaceutical Sciences, Albert-Ludwigs-University Freiburg, 79104 Freiburg, Germany
Abstract: XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment within a small molecule library containing more than 7 million molecules. XD14 inhibits bromodomain of the bromodomain extra-terminal domain family and consequently restricts cell proliferation. In this study, metabolic profiling reveals responses in human breast cancer cell line MCF-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 statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA) and partial least square discriminant analysis (PLS-DA). Cell proliferation was obviously inhibited by treatment of 50 μM XD14. Further, the samples could be discriminated by time and XD14 concentration using PLS-DA. 117 metabolites were identified, in which 68 were significant 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 cancer cells and therefore makes XD14 a promising candidate for therapy against bromodomain-related tumors.

Title: NMR metabolomic assessment and liver diseases: a review
Authors: Roland Amathieu; Philippe Savarin; Laurence Le Moyec
Abstract: During the last decade, metabolomics have been widely used in the field of liver diseases. Many results have demonstrated that this is a powerful technique to improve the comprehension and the diagnostic of various liver diseases. In the present work we will try to explore the main publications on this subject by focusing on NMR metabolomics studies.