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Metabolites
Special Issues
Metabolic Profiling of Biofluids and Tissues Using Multiplatform Approaches
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Metabolic Profiling of Biofluids and Tissues Using Multiplatform Approaches

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Metabolomic Profiling Technology".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 3011

Special Issue Editor

Dr. Estelle Pujos-Guillot

E-Mail Website
Guest Editor
Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
Interests: metabolism and mass spectrometry; metabolomics; data mining; nutrition; non-communicable diseases

Special Issue Information

Dear Colleagues,

Over recent years, there have been extensive method developments to analyze the metabolomes of various biofluids and tissues. However, given the high diversity of metabolites present over a wide concentration range in biological samples, one of the analytical challenges is to ideally cover the entire metabolic space (metabolome) using complementary techniques and methods. However, this multiplatform strategy is time and cost consuming and therefore needs to be optimized to recover the largest possible amount of chemical information, relevant to the biological context, in a reasonable timeframe, to be compatible with large-scale studies. In addition, such a multiplatform strategy generates complex and massive data that will need dedicated management and workflows for data treatments.

This Special Issue of Metabolites, “Metabolic Profiling of Biofluids and Tissues Using Multiplatform Approaches”, will first be dedicated to cutting-edge methods and technology developments for multiplatform metabolomics/lipidomics approaches both from a fundamental as well as an applied point of view. Second, it will address the question of data treatment and fusion for such a strategy. The topics that will be more particularly covered by this Special Issue include (though not exclusively) sample preparation dedicated to multiplatform approaches, choice of technologies and methods for multiplatform profiling and annotation, high-throughput, standardization and quality control, data extraction and treatments, data management, data fusion and integration, and analytical redundancy management.

Manuscripts dealing with other challenging issues are also highly relevant.

Dr. Estelle Pujos-Guillot
Guest Editor

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

  • metabolomics
  • lipidomics
  • multiplatform approach
  • profiling
  • annotation
  • standardization
  • quality control
  • data management
  • data fusion
  • data integration

Published Papers (1 paper)

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Research

16 pages, 3240 KiB  
Article
Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories
by Shin Nishiumi, Yoshihiro Izumi, Akiyoshi Hirayama, Masatomo Takahashi, Motonao Nakao, Kosuke Hata, Daisuke Saigusa, Eiji Hishinuma, Naomi Matsukawa, Suzumi M. Tokuoka, Yoshihiro Kita, Fumie Hamano, Nobuyuki Okahashi, Kazutaka Ikeda, Hiroki Nakanishi, Kosuke Saito, Masami Yokota Hirai, Masaru Yoshida, Yoshiya Oda, Fumio Matsuda and Takeshi Bambaadd Show full author list remove Hide full author list
Metabolites 2022, 12(2), 135; https://doi.org/10.3390/metabo12020135 - 01 Feb 2022
Viewed by 2588
Abstract
In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand [...] Read more.
In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories. Full article
(This article belongs to the Special Issue Metabolic Profiling of Biofluids and Tissues Using Multiplatform Approaches)
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