Author: Elizabeth A McDaniel,  Graduate Student (University of Wisconsin-Madison)

Description:
Microbial communities mediate essential biogeochemical cycles and nutrient transformations in freshwater lakes. However, due to the complexity of these communities and lack of pure cultures, the microbial component of most freshwater lakes remains a “black box.” Advances in high-throughput sequencing technologies and bioinformatic algorithms have allowed us to reconstruct individual microbial genomes from a mixed sample. These genomes can be leveraged to place their phylogenetic identities and metabolic potentials in the context of ecosystem-level functions. Here, we describe open-source workflows and software applications we have either developed or used for performing genome-resolved metagenomic and metatranscriptomic analyses. We have applied these approaches in three model freshwater lake systems in Wisconsin as part of the North Temperate Lakes Long Term Ecological Research (NTL-LTER) network. To date, we have produced a set of reference freshwater microbial genomes and connected their predicted physiologies to biogeochemical cycles and specific metabolisms, investigated within-population heterogeneity over time, and inferred their gene expression dynamics. Our work highlights how multi-omics data can be integrated to illuminate the microbial component of freshwater lakes.

Category: Scientific Program Abstract > Special Session > SS48 Data science for aquatic discovery and prediction: building a community of practice