Abstract

Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combined omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. Evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism.

Highlights

  • Microalgae hold great potential as feed stocks for renewable biofuel production and have attracted attention for their ability to biosynthesize large amounts of high-value hydrocarbons while harnessing only sunlight, carbon dioxide and wastewater (Georgianna and Mayfield, 2012)

  • Using the pipeline and basic rules for identification and classification of transcription factors and transcriptional regulators adopted by PlnTFDB 3.0

  • Uni-potsdam.de/v3.0/), we identified in our Chlamydomonas transcriptional profiling data a total of 241 putative TFs that belong to 37 different protein families and 173 putative transcriptional regulators (TRs) that are members of 21 families based on the presence or absence of one or more characteristic domains

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Summary

Introduction

Microalgae hold great potential as feed stocks for renewable biofuel production and have attracted attention for their ability to biosynthesize large amounts of high-value hydrocarbons while harnessing only sunlight, carbon dioxide and wastewater (Georgianna and Mayfield, 2012). Successful rational metabolic engineering of microalgae requires a comprehensive understanding of the regulation of metabolic pathways in the context of the whole cell rather than at the single pathway level (Capell and Christou, 2004). This includes a full understanding of regulatory proteins such as transcription factors (TFs) and transcriptional regulators (TRs), as well as microRNAs, and how they respond to external stimuli and control downstream processes (Latchman, 1997). Some genes have been identified to be involved in this response, the underlying sensing and the downstream regulatory mechanisms have not been clearly defined

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