In glacier-fed streams, ecological windows of opportunity allow complex microbial biofilms to develop and transiently form the basis of the food web, thereby controlling key ecosystem processes. Using metagenome-assembled genomes, we unravel strategies that allow biofilms to seize this opportunity in an ecosystem otherwise characterized by harsh environmental conditions. We observe a diverse microbiome spanning the entire tree of life including a rich virome. Various co-existing energy acquisition pathways point to diverse niches and the exploitation of available resources, likely fostering the establishment of complex biofilms during windows of opportunity. The wide occurrence of rhodopsins, besides chlorophyll, highlights the role of solar energy capture in these biofilms while internal carbon and nutrient cycling between photoautotrophs and heterotrophs may help overcome constraints imposed by oligotrophy in these habitats. Mechanisms potentially protecting bacteria against low temperatures and high UV-radiation are also revealed and the selective pressure of this environment is further highlighted by a phylogenomic analysis differentiating important components of the glacier-fed stream microbiome from other ecosystems. Our findings reveal key genomic underpinnings of adaptive traits contributing to the success of complex biofilms to exploit environmental opportunities in glacier-fed streams, which are now rapidly changing owing to global warming.
KAUST Repository Item: Exported on 2022-04-26
Acknowledgements: Funded by The NOMIS Foundation to TJB. SBB was supported by the Synergia grant (CRSII5_180241: Swiss National Science Foundation) to TJB. LdN and PW are supported by the Luxembourg National Research Fund (FNR; PRIDE17/11823097). RM and DD are supported by King Abdullah University of Science and Technology through baseline research funds to DD. We are thankful for the assistance of Audrey Frachet Bour, Lea Grandmougin, Janine Habier, Laura Lebrun (LCSB) and Emmy Marie Oppliger (EPFL) for laboratory support. We are grateful to Alex Washburne for his feedback on the draft, and we also acknowledge the valuable input from Rashi Halder at the LCSB Sequencing Platform with respect to library preparation. We are equally grateful for the valuable insights into metagenomic processing from Patrick May, Anna Heintz-Buschart, and Cedric Christian Laczny, and especially Valentina Galata with the python scripts and Snakemake workflows. The computational analyses presented in this paper were carried out using the HPC facilities at the University of Luxembourg (https://hpc.uni.lu)142
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
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