Dear Colleagues,

Increasingly, metabolomics and next generation sequencing are being used in concert to extract data from experimental systems in order to understand the biological activity occurring in these systems. Analysis of microbiome-based systems in particular require this combined approach, as sequencing or metabolomics alone are typically insufficient to fully characterize these systems. This is driving an growing need for computational techniques to analyze such data in a synergistic way, such that metabolomics data can be used to reinforce conclusions derived from sequencing data, and vice versa. It is also important that these techniques support microbiome analysis, as this is the application area where a combined use of sequencing and metabolomics is currently most essential. Genome-scale metabolic models (GEMs) have emerged as important tools to address this novel challenge: (i) GEMs serve as a bridge between genomics and chemistry containing interconnected representation of both data types; (ii) GEMs have a distinct capacity to integrate numerous individual data points together into a broader representation of biological activity; and (iii) GEMs may be extended into broader models of entire microbial communities. However, numerous challenges continue to hinder efforts to apply GEMs to seamlessly integrate metabolomics and genomic data in microbiome systems. First and foremost, we have a significant dark-matter problem hindering both metabolomics data annotation and genomic data annotation. Numerous peaks observed in metabolomics data cannot be identified, and numerous proteins observed in genomic data cannot be annotated. GEM modeling must be augmented by new approaches that facilitate peak identification and rapidly propose new pathways to fill gaps in our biochemical knowledgebase. Second, we need new simulation and analysis techniques for applying GEM modeling to integrate metabolomic and genomic data in microbiome systems. Finally, we need improved and extensible biochemistry databases to provide a more complete set of candidates for metabolomics peak identification and also to facilitate GEM interoperability in community modeling.

Such databases must facilitate rapid extension to accommodate newly discovered compounds, reactions, pathways, and protein functions. This Special Issue of Metabolomics is focused on genome-scale metabolic modeling, and how genome-scale metabolic models are used to integrate metabolomics and next generation sequencing data for analysis of isolate and microbiome-based systems. We are particularly interested in articles about: (i) improved annotation of metabolomic and genomic data by removing knowledge gaps in microbiome system chemistry; (ii) new metabolomics and genomic data integration techniques using GEMs in microbiome systems; and (iii) improved databases that support improved annotation of metabolomic data, model reconstruction, and model interoperability.

Prof. Bas Teusink
Dr. Christopher Henry
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.

• Genome-scale metabolic model
• Metabolomics
• Data integration
• Metabolic interactions