title: Characterizing microbial communities through space and time.
abstract: Until recently, the study of microbial diversity has mainly been limited to descriptive approaches, rather than predictive model-based analyses. The development of advanced analytical tools and decreasing cost of high-throughput multi-omics technologies has made the later approach more feasible. However, consensus is lacking as to which spatial and temporal scales best facilitate understanding of the role of microbial diversity in determining both public and environmental health. Here, we review the potential for combining these new technologies with both traditional and nascent spatio-temporal analysis methods. The fusion of proper spatio-temporal sampling, combined with modern multi-omics and computational tools, will provide insight into the tracking, development and manipulation of microbial communities.
authors.affiliation: Department of Computer Science, University of Colorado at Boulder, Boulder, CO 80309, USA.
authors.forename: Antonio
authors.initials: A
authors.lastname: Gonzalez
authors.forename: Andrew
authors.initials: A
authors.lastname: King
authors.forename: Michael S
authors.initials: MS
authors.lastname: Robeson
authors.forename: Sejin
authors.initials: S
authors.lastname: Song
authors.forename: Ashley
authors.initials: A
authors.lastname: Shade
authors.forename: Jessica L
authors.initials: JL
authors.lastname: Metcalf
authors.forename: Rob
authors.initials: R
authors.lastname: Knight
mesh_terms: D001419:Bacteria / Q000145:classification* / Q000235:genetics; D044822:Biodiversity; D004783:Environmental Microbiology; D056186:Metagenomics / Q000379:methods; D008954:Models, Biological; D062211:Spatio-Temporal Analysis