caa a22 4500 606175741 CHVBK 20210128100744.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00018-015-2004-1 doi (NATIONALLICENCE)springer-10.1007/s00018-015-2004-1 From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems [Elektronische Daten] [Daniel Garza, Bas Dutilh] Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment. The Author(s), 2015 Biological dark matter nationallicence Pan-genomics, data recycling nationallicence Eco-systems biology nationallicence Metagenome-wide modeling nationallicence Virus-host association nationallicence Garza Daniel Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 28, 6525 GA, Nijmegen, The Netherlands aut Dutilh Bas Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 28, 6525 GA, Nijmegen, The Netherlands aut Cellular and Molecular Life Sciences Springer Basel 72/22(2015-11-01), 4287-4308 1420-682X 72:22<4287 2015 72 18 https://doi.org/10.1007/s00018-015-2004-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 review-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00018-015-2004-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Garza Daniel Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 28, 6525 GA, Nijmegen, The Netherlands aut NATIONALLICENCE 700 1- Dutilh Bas Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 28, 6525 GA, Nijmegen, The Netherlands aut NATIONALLICENCE 773 0- Cellular and Molecular Life Sciences Springer Basel 72/22(2015-11-01), 4287-4308 1420-682X 72:22<4287 2015 72 18