A general aim of microbial ecology is to observe, understand, and predict the distribution and interactions of microorganisms in the context of environmental conditions. Taxonomic profiling of different microbial communities often reveals significant but unexplained variations across aquatic environments both in space and time. Functional differences among organisms are often invoked as an explanation; and variation in gene content (assessed by metagenomics) often reveals dynamic relationships between metabolic pathways and environmental conditions, the strength of which typically depends on the magnitude of the environmental change between communities. However, a major challenge in microbial ecology remains. Many taxa that appear functionally redundant at the metabolic pathway level show significant variation across environments with different ecological features. Possible explanations include dispersal limitation, biotic interactions, and rapid adaptation to environmental conditions that are not easily predictable based on gene content alone.
This special issue explores recent advances and current limitations about how large-scale meta-omics analyses can be integrated into biogeochemical and eco-evolutionary frameworks to better predict taxonomic and functional diversity patterns across aquatic ecosystems from lakes and rivers to oceans and from viruses and microbes to protists.
Special Issue Editors:
Hans-Peter Grossart, Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Ramon Massana, Institut de Ciències del Mar
Trina McMahon, University of Wisconsin-Madison
David Walsh, Concordia University
A conceptual framework for how to integrate the diversity of meta‐omics approaches into advanced studies of aquatic microbial ecology and biogeochemistry as exemplified by the contributions to this special issue. The red box represents an overview of the meta‐omics tool kit and the microbial genotype to phenotype information that can be provided by meta‐omics approaches. The orange box highlights the importance of environmental and biogeochemical metadata that are essential in linking community dynamics to biogeochemical processes. The green box depicts the importance of model systems, hypothesis testing, and modeling as detailed in Section 4 of this review article. The large double‐ended arrow indicates how linking microbiology tools and approaches can facilitate an integration of ecological and biogeochemical knowledge of aquatic microbiomes, and move microbial ecology from a descriptive to a more predictive discipline. (Grossart et al. 2019)