A Model of Cyclic Transcriptomic Behavior in Cyanobacterium Cyanothece sp. ATCC 51142
Systems biology attempts to reconcile large amounts of disparate data with existing knowledge to provide models of functioning biological systems. Useful and predictive models aim to summarize complex and dynamic processes and represent the relationships between these processes. The cyanobacterial Cyanothece species Strain sp. ATCC 51142 is an excellent candidate for such systems studies because: (i) it displays tight functional regulation as it must separate the opposing processes of oxygen-generating photosynthesis and oxygen-sensitive nitrogen fixation temporally in the same cell, ; (ii) it has robust cyclic patterns at the genetic, protein and metabolomic levels, ; and (iii) and it has potential applications for bioenergy and carbon sequestration, and thus a predictive model of its function is of practical use. We have represented the transcriptomic data from Cyanothece 51142 under diurnal light/dark cycles as a high-level functional abstraction and describe development of a predictive in silico model of diurnal and circadian behavior in terms of regulatory and metabolic processes in Cyanothece 51142. Our model provides a way to integrate disparate data types into a framework that can be used to explain behavior, generate high-quality predictions for validation, and to suggest future experiments. We show that incorporating network topology into the model improves performance in terms of our ability to explain the behavior of the system under new conditions. The model presented robustly describes transcriptomic behavior of Cyanothece 51142 under different cyclic and non-cyclic growth conditions robustly, and represents a significant advance in the understanding of gene regulation in this important organism.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1021826
- Report Number(s):
- PNNL-SA-74409; 15490; KP1704020; TRN: US201117%%399
- Journal Information:
- Molecular Biosystems, 7(8):2407-2418, Vol. 7, Issue 8
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
BIOLOGY
CARBON SEQUESTRATION
FUNCTIONALS
GENE REGULATION
NITROGEN FIXATION
PERFORMANCE
PHOTOSYNTHESIS
PROTEINS
REGULATIONS
STRAINS
TOPOLOGY
VALIDATION
systems biology
predictive modeling
cyanobacteria
Environmental Molecular Sciences Laboratory