Towards a metabolic model of circadian clock control of metabolism in Neurospora crassa.
EMSL Project ID
49259
Abstract
Biofuel production using cellulases extracted from fungi has the potential to be a major resource to replace fossil fuels and regulating the synthesis of these and other enzymes is crucial for the economics of biofuel production from lignocellulose. Some of the best inducers of plant cell wall-degrading enzymes are filamentous fungi. However, environmental controls on cellular metabolism are known to modulate the amount of cellulases that can be produced in fungi. The filamentous fungus Neurospora is commonly used in the production of cellulases for biofuel manufacture and it is also the principal fungal model system for the study of the effects of light and circadian clocks. The circadian clock plays a large role in the regulation of the Neurospora genome: as many as 40% of Neurospora genes can be clock regulated, including many genes that regulate metabolism. Although the dominant general role of the clock in metabolic regulation is appreciated, the degree to which the clock controls specific aspects of metabolism is not currently understood.
This project seeks to identify the link between time of day and cellulase levels in an effort to better understand their regulation and improve the manufacture of these important components for energy production. Many proteins under clock regulation are transcription factors (TFs) and one of these, CSP-1, is predominantly involved in regulating metabolism. Another clock regulated TF, CLR-1, directly impacts cellulase production. Removal of TFs by targeted deletion provides an opportunity to eliminate circadian regulation of specific aspects of metabolism, potentially increasing and stabilizing cellulase production.
To understand the role that the circadian clock plays in regulating cellular metabolism, more specifically the regulation of cellulases, we will determine the metabolic profile of wildtype Neurospora, as well as strains in which TFs known to regulate metabolism are deleted. We will then track known cellulases specifically, and the proteome more generally, via comparative mass spectrometry (MS) to determine conditions under which optimal levels of cellulases are created, whether at a specific time of day or in a strain with no clock regulation on metabolism. Data on regulation of the proteome as a function of time of day will provide important context for interpreting the metabolome data. In both cases, we will rely on the technical abilities of EMSL to provide a cutting edge MS analysis of the Neurospora metabolome or proteome over a circadian cycle. Our labs will use commonly applied informatic and statistical analyses to determine which elements are rhythmic and the degree to which the loss of certain TFs affects circadian control of metabolic output. Lastly, the network of TFs governing the proteome and ultimately the metabolome has only been described in constant light when the clock does not run, whereas we know that in darkness the activities of many salient TFs are clock-regulated. Thus the network may be different at different times of day. To assess this, we will prepare ChIP samples and will rely on EMSL sequencing capabilities to carry out ChIP-seq to reveal how time sculpts the transcriptional network. In collaborative exploratory studies carried out at EMSL, all of these data (metabolome, proteome, transcriptome, and TF network) will be used for computational modeling of the metabolome and cellulose utilization. We hypothesize that these data will provide insights into whether and how to decouple metabolism from the clock with the goal of increasing the production of cellulases needed in biofuel manufacture.
Project Details
Project type
Large-Scale EMSL Research
Start Date
2016-10-01
End Date
2018-09-30
Status
Closed
Released Data Link
Team
Principal Investigator
Co-Investigator(s)
Team Members
Related Publications
Hurley J.M., M.S. Jankowski, H. De Los Santos, A.M. Crowell, S. Fordyce, J.D. Zucker, and N. Kumar, et al. 2018. "Circadian proteomic analysis uncovers mechanisms of post-transcriptional regulation in metabolic pathways." Cell Systems 7, no. 6:613-626. PNNL-SA-138421. doi:10.1016/j.cels.2018.10.014