Metabolic Exchanges Between Cyanobacteria and Snow Algae in Beartooth Mountains: A Focus on Nitrogen and Phosphorus Cycling

Abstract

Snow algae have been linked to accelerated glacier melt through climate-driven feedback loops. These findings, and their broader implications for global warming, have increased interest in understanding the microbial communities that support snow algae in extreme alpine environments like the Beartooth Mountains. Snow algae coexist with diverse prokaryotic and eukaryotic organisms, forming nutrient-exchange networks that help them survive harsh conditions. However, the mechanisms driving nutrient cycling within these communities remain under-researched. Our research focuses on the role of cyanobacteria in cycling nitrogen and phosphorus within snow algae ecosystems. Cyanobacteria are known to perform key nutrient transformations, including nitrogen fixation and phosphorus mobilization. From this, we seek to discover the difference in community composition in samples with and without snow algae and how cyanobacteria interact with the community through nutrient cycling. Studying nutrient flow directly in live cultures is time-consuming and costly, so predictive metabolic modeling offers an efficient alternative. Tools such as KBase can generate simulated metabolic pathways that allow researchers to trace nutrient movement. In this study, we isolated DNA, amplified and sequenced the 16S rRNA gene through PCR and Nanopore GridION sequencing, and identified cyanobacterial taxa present in snow algae samples from the Beartooth Mountains. Using this data, we constructed metabolic models under varying nitrogen and phosphorus availability and sources to determine how cyanobacteria may favor certain nutrient distribution patterns in their surrounding microbial community. Model outputs showed that reducing nitrogen or phosphorus availability increased their predicted fluxes, indicating a stronger metabolic dependence on these scarce nutrients. We hypothesize that microbial composition will differ significantly between samples with and without snow algae, along with cyanobacteria providing substantially more nitrogen than phosphorus to the microbial community. Furthermore, metabolic modeling will reveal a stronger dependence of nitrogen cycles on cyanobacterial growth than on extracellular phosphorus sources. The findings can aid in further research surrounding global warming concerns. Future direction in the study can be aimed at exploring different nutrient cycles within cyanobacteria.