Gene Regulatory Networks Respond to Day and Night Cues to Affect Phenotype in Cyanbacteria

The Science

Scientists have discovered how gene regulatory networks react to environmental changes and coordinate control of metabolism in cyanobacteria as they transition between day and night. Using advanced computational approaches, researchers analyzed the expression of thousands of genes to identify the cellular “command centers” that orchestrate metabolic changes. They found that different transcriptional control mechanisms operate during day versus night. Daytime influences “command centers” to activate photosynthesis, CO₂ fixation, and conversion of carbon into glycogen as energy storage. Conversely, at night when light is unavailable, regulators deactivate photosynthesis and CO₂ fixation while mobilizing stored glycogen as an internal energy reserve to maintain essential cellular processes. This discovery, part of Pacific Northwest National Laboratory's Predictive Phenomics Initiative, or PPI, provides fundamental insights into how living cells organize their genetic information to respond to environmental changes—a critical aspect of how all organisms adapt and survive.

The Impact

This research significantly advances scientists’ understanding of how biological systems process information and coordinate responses to enviromental changes. By analyzing the architecture of gene regulatory networks rather than focusing solely on individual connections, researchers revealed organizing principles that help explain how cells achieve complex behaviors with simple components. The findings demonstrate that biological systems use centrality—the position of regulators within networks—to amplify the influence of key control points. These network principles extend beyond cyanobacteria to illuminate universal mechanisms of biological information processing that apply across diverse organisms. By identifying the master switches that control metabolic states, this work creates new opportunities to understand cellular adaptation and response to stress, with potential applications in environmental monitoring, biotechnology, and fundamental research on how organisms maintain balance under changing conditions.

Summary

The study applied network analysis techniques to map how day and nighttime conditions drive the command structure governing metabolic transitions in cyanobacteria. The research team constructed comprehensive gene regulatory networks by integrating multiple computational approaches with gene expression data representing over 200 environmental conditions. The findings showed striking differences in how day versus night metabolism is controlled: daytime processes involve distributed regulation through multiple coordination points, while nighttime processes operate through more centralized control. Key transcriptional regulators were identified by their high network centrality, with three previously understudied regulators (HimA, TetR, and SrrB) emerging as particularly significant. HimA appears to function as a DNA architecture regulator that helps repress photosynthesis genes at night, while TetR and SrrB coordinate nighttime glycogen mobilization and redox balance—critical processes that allow cyanobacteria to maintain energy production when photosynthesis is unavailable. Their high centrality in the network indicates these regulators serve as critical hubs that orchestrate broad metabolic shifts rather than controlling individual pathways, highlighting how cellular networks amplify the influence of key control points. These discoveries provide fundamental insights into how cyanobacteria coordinate complex metabolic transitions between light and dark conditions, with potential applications for enhancing biofuel production and understanding stress adaptation in photosynthetic organisms.

Contact

• Pavlo Bohutskyi, pavlo.bohutskyi@pnnl.gov, PNNL

Funding

This research was supported by the Predictive Phenomics Initiative, a Laboratory Directed Research and Development program at Pacific Northwest National Laboratory (PNNL), and the Department of Energy (DOE), Office of Science program Biopreparedness Research Virtual Environment (BRaVE) Initiative award to PNNL (81832). David Anderson was supported in part by the DOE, Office of Science, Office of Workforce Development for Teachers and Scientists under the Science Undergraduate Laboratory Internships program. PNNL is operated by Battelle for the DOE under Contract DE-AC05-76RL01830.