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      Seeding Biochemistry on Other Worlds: Enceladus as a Case Study

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          Abstract

          The Solar System is becoming increasingly accessible to exploration by robotic missions to search for life. However, astrobiologists currently lack well-defined frameworks to quantitatively assess the chemical space accessible to life in these alien environments. Such frameworks will be critical for developing concrete predictions needed for future mission planning, both to determine the potential viability of life on other worlds and to anticipate the molecular biosignatures that life could produce. Here, we describe how uniting existing methods provides a framework to study the accessibility of biochemical space across diverse planetary environments. Our approach combines observational data from planetary missions with genomic data catalogued from across Earth and analyzed using computational methods from network theory. To demonstrate this, we use 307 biochemical networks generated from genomic data collected across Earth and “seed” these networks with molecules confirmed to be present on Saturn's moon Enceladus. By expanding through known biochemical reaction space starting from these seed compounds, we are able to determine which products of Earth's biochemistry are, in principle, reachable from compounds available in the environment on Enceladus, and how this varies across different examples of life from Earth (organisms, ecosystems, planetary-scale biochemistry). While we find that none of the 307 prokaryotes analyzed meet the threshold for viability, the reaction space covered by this process can provide a map of possible targets for detection of Earth-like life on Enceladus, as well as targets for synthetic biology approaches to seed life on Enceladus. In cases where biochemistry is not viable because key compounds are missing, we identify the environmental precursors required to make it viable, thus providing a set of compounds to prioritize for detection in future planetary exploration missions aimed at assessing the ability of Enceladus to sustain Earth-like life or directed panspermia.

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          Most cited references48

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          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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            KEGG: new perspectives on genomes, pathways, diseases and drugs

            KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an encyclopedia of genes and genomes. Assigning functional meanings to genes and genomes both at the molecular and higher levels is the primary objective of the KEGG database project. Molecular-level functions are stored in the KO (KEGG Orthology) database, where each KO is defined as a functional ortholog of genes and proteins. Higher-level functions are represented by networks of molecular interactions, reactions and relations in the forms of KEGG pathway maps, BRITE hierarchies and KEGG modules. In the past the KO database was developed for the purpose of defining nodes of molecular networks, but now the content has been expanded and the quality improved irrespective of whether or not the KOs appear in the three molecular network databases. The newly introduced addendum category of the GENES database is a collection of individual proteins whose functions are experimentally characterized and from which an increasing number of KOs are defined. Furthermore, the DISEASE and DRUG databases have been improved by systematic analysis of drug labels for better integration of diseases and drugs with the KEGG molecular networks. KEGG is moving towards becoming a comprehensive knowledge base for both functional interpretation and practical application of genomic information.
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              KEGG as a reference resource for gene and protein annotation

              KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an integrated database resource for biological interpretation of genome sequences and other high-throughput data. Molecular functions of genes and proteins are associated with ortholog groups and stored in the KEGG Orthology (KO) database. The KEGG pathway maps, BRITE hierarchies and KEGG modules are developed as networks of KO nodes, representing high-level functions of the cell and the organism. Currently, more than 4000 complete genomes are annotated with KOs in the KEGG GENES database, which can be used as a reference data set for KO assignment and subsequent reconstruction of KEGG pathways and other molecular networks. As an annotation resource, the following improvements have been made. First, each KO record is re-examined and associated with protein sequence data used in experiments of functional characterization. Second, the GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes. Third, new automatic annotation servers, BlastKOALA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from the GENES database. As a resource for translational bioinformatics, various data sets are created for antimicrobial resistance and drug interaction networks.
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                Author and article information

                Journal
                Astrobiology
                Astrobiology
                ast
                Astrobiology
                Mary Ann Liebert, Inc., publishers (140 Huguenot Street, 3rd FloorNew Rochelle, NY 10801USA )
                1531-1074
                1557-8070
                February 2021
                04 February 2021
                04 February 2021
                : 21
                : 2
                : 177-190
                Affiliations
                [ 1 ]School of Earth and Space Exploration, Arizona State University, Tempe, Arizona, USA.
                [ 2 ]ASU-SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, Arizona, USA.
                [ 3 ]Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, Arizona, USA.
                [ 4 ]Santa Fe Institute, Santa Fe, New Mexico, USA.
                Author notes
                [*]

                Current affiliation: Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan.

                [*]Address correspondence to: Harrison B. Smith, Earth-Life Science Institute, Tokyo Institute of Technology, 2-12-1 17E-315 Ookayama, Meguro-ku, Tokyo 152-8550, Japan hbs@ 123456elsi.jp
                [*]Address correspondence to: Sara Imari Walker, Beyond Center for Fundamental Concepts in Science, Arizona State University, PO Box 870506, Tempe, AZ 85287-0506, USA sara.i.walker@ 123456asu.edu
                Article
                10.1089/ast.2019.2197
                10.1089/ast.2019.2197
                7876360
                33064954
                7f68a373-12f7-4ae2-81d4-6c55b40e6903
                © Harrison B. Smith et al., 2021; Published by Mary Ann Liebert, Inc.

                This Open Access article is distributed under the terms of the Creative Commons License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

                History
                : Submitted 7 November 2019
                : Accepted 7 September 2020
                Page count
                Figures: 7, References: 49, Pages: 14
                Categories
                Research Articles

                biochemical networks,enceladus,habitability,life as a planetary process,metabolic networks,panspermia,planetary protection

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