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Ayala-Ortiz C, Graf-Grachet N, Freire-Zapata V, Fudyma J, Hildebrand G, AminiTabrizi R, Howard-Varona C, Corilo YE, Hess N, Duhaime MB, Sullivan MB, Tfaily MM. MetaboDirect: an analytical pipeline for the processing of FT-ICR MS-based metabolomic data. MICROBIOME 2023; 11:28. [PMID: 36803638 PMCID: PMC9936664 DOI: 10.1186/s40168-023-01476-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 01/24/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Microbiomes are now recognized as the main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e., metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. RESULTS Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line-based pipeline for the analysis (e.g., chemodiversity analysis, multivariate statistics), visualization (e.g., Van Krevelen diagrams, elemental and molecular class composition plots), and presentation of direct injection high-resolution FT-ICR MS data sets after molecular formula assignment has been performed. When compared to other available FT-ICR MS software, MetaboDirect is superior in that it requires a single line of code to launch a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences (mass difference network-based approach) that provide an experimental assessment of metabolite connections within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. CONCLUSION Application of MetaboDirect to FT-ICR MS-based metabolomic data sets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. The source code and User's guide of MetaboDirect are freely available through ( https://github.com/Coayala/MetaboDirect ) and ( https://metabodirect.readthedocs.io/en/latest/ ), respectively. Video Abstract.
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Affiliation(s)
| | - Nathalia Graf-Grachet
- Department of Environmental, Science, University of Arizona, Tucson, AZ 85721 USA
- Present address: Roche, Pleasanton, CA 94588 USA
| | | | - Jane Fudyma
- Department of Environmental, Science, University of Arizona, Tucson, AZ 85721 USA
- Present address: University of California, Davis|Department of Plant Pathology, Davis, CA 95616-8751 USA
| | - Gina Hildebrand
- Department of Environmental, Science, University of Arizona, Tucson, AZ 85721 USA
| | - Roya AminiTabrizi
- Department of Environmental, Science, University of Arizona, Tucson, AZ 85721 USA
- Present address: University of Chicago Biological Sciences Division, Metabolomics Platform, Chicago, IL 60637 USA
| | - Cristina Howard-Varona
- Department of Microbiology, Ohio State University, Columbus, OH 43210 USA
- Center of Microbiome Science, Ohio State University, Columbus, OH 43210 USA
| | - Yuri E. Corilo
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354 USA
| | - Nancy Hess
- Present address: University of California, Davis|Department of Plant Pathology, Davis, CA 95616-8751 USA
| | - Melissa B. Duhaime
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109 USA
| | - Matthew B. Sullivan
- Department of Microbiology, Ohio State University, Columbus, OH 43210 USA
- Center of Microbiome Science, Ohio State University, Columbus, OH 43210 USA
- Department of Civil, Environmental, and Geodetic Engineering, Ohio State University, Columbus, OH 43210 USA
| | - Malak M. Tfaily
- Department of Environmental, Science, University of Arizona, Tucson, AZ 85721 USA
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354 USA
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Vistoli G, Pedretti A, Mazzolari A, Testa B. Approaching Pharmacological Space: Events and Components. Methods Mol Biol 2018; 1800:245-274. [PMID: 29934897 DOI: 10.1007/978-1-4939-7899-1_12] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
With a view to introducing the concept of pharmacological space and its potential applications in investigating and predicting the toxic mechanisms of xenobiotics, this opening chapter describes the logical relations between conformational behavior, physicochemical properties and binding spaces, which are seen as the three key elements composing the pharmacological space. While the concept of conformational space is routinely used to encode molecular flexibility, the concepts of property spaces and, particularly, of binding spaces are more innovative. Indeed, their descriptors can find fruitful applications (a) in describing the dynamic adaptability a given ligand experiences when inserted into a specific environment, and (b) in parameterizing the flexibility a ligand retains when bound to a biological target. Overall, these descriptors can conveniently account for the often disregarded entropic factors and as such they prove successful when inserted in ligand- or structure-based predictive models. Notably, and although binding space parameters can clearly be derived from MD simulations, the chapter will illustrate how docking calculations, despite their static nature, are able to evaluate ligand's flexibility by analyzing several poses for each ligand. Such an approach, which represents the founding core of the binding space concept, can find various applications in which the related descriptors show an impressive enhancing effect on the statistical performances of the resulting predictive models.
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Affiliation(s)
- Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche Università degli Studi di Milano, Milan, Italy.
| | - Alessandro Pedretti
- Dipartimento di Scienze Farmaceutiche Università degli Studi di Milano, Milan, Italy
| | - Angelica Mazzolari
- Dipartimento di Scienze Farmaceutiche Università degli Studi di Milano, Milan, Italy
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Chemodiversity and molecular plasticity: recognition processes as explored by property spaces. Future Med Chem 2011; 3:995-1010. [PMID: 21707401 DOI: 10.4155/fmc.11.54] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.
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