NSF Award
2424579
Viruses play a crucial role in ecosystem dynamics by infecting bacteria, with nearly half of all bacteria being infected at any given time. Despite the importance of viruses, most microbial ecology studies overlook their impact. A major challenge is disentangling the interaction of viruses and bacteria in the environment because most of these microbes cannot be grown in laboratory conditions. The project addresses this gap by introducing a new data science and mathematics approach to model the complex dynamics of virus and bacteria and testing it in lakes that resemble ancient oceans. These lakes are an ideal controlled environment because they have stable, oxygen-free layers that are dominated by photosynthetic bacteria and viruses but lack complex life forms. The research will identify the key viruses influencing the dynamics of the bacterial communities. Characterizing the dynamic role of these viruses will help reinterpret the geological records from these lakes, which provide insights into early microbial life on Earth. Additionally, the project will create a user-friendly software for others to apply the technology to investigate the impact of viruses in different ecosystems. This project will train new interdisciplinary scientists and share their findings to the public in international journals and museum exhibits to highlight the complex role that viruses play.<br/><br/>Viruses infecting bacteria display two main infection modes: lytic and lysogenic. In the lytic mode, the virus uses cell machinery to produce viral particles, imposing predation pressure on microbial communities. During lysogeny, the virus remains latent, often providing new cell functions, including protection against new infections. Currently, no technology can identify the dynamics of the most impactful (keystone) lytic and lysogenic viruses in complex microbiomes. This project will fill this gap integrating viral and microbial omics data with an innovative transient dynamics method, leveraging the long-term collaboration between PI Luque and co-PI Silveira in viral ecology. The research will model the dynamics of viruses and bacteria in the chemocline of meromictic lakes, which serve as analogs for ancient oceans. Their stability and lack of complex organisms are ideal to study the impact of viruses on microbial communities and biogeochemistry. The project will use bioinformatics to predict the life traits of bacteria and viruses from microbial abundances, infection networks, metagenomics, and transcriptomics. It will also develop and calibrate an adaptive Boolean transient dynamic method using mesocosm experiments. The calibrated model will simulate year-long natural microbiome dynamics to identify keystone viruses and their infection strategies. The impact of these viruses will be projected to reinterpret biogeochemical profiles in the lakes. The developed mathematical technology will be released as an accessible software package, available via GitHub, Colab, and Python repositories. The findings will be disseminated through peer-reviewed publications, international conferences, public exhibits, and online platforms.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
