Transcriptional program for nitrogen starvation-induced lipid accumulation in Chlamydomonas reinhardtii

Abstract

BackgroundAlgae accumulate lipids to endure different kinds of environmental stresses including macronutrient starvation. Although this response has been extensively studied, an in depth understanding of the transcriptional regulatory network (TRN) that controls the transition into lipid accumulation remains elusive. In this study, we used a systems biology approach to elucidate the transcriptional program that coordinates the nitrogen starvation-induced metabolic readjustments that drive lipid accumulation in Chlamydomonas reinhardtii.ResultsWe demonstrate that nitrogen starvation triggered differential regulation of 2147 transcripts, which were co-regulated in 215 distinct modules and temporally ordered as 31 transcriptional waves. An early-stage response was triggered within 12 min that initiated growth arrest through activation of key signaling pathways, while simultaneously preparing the intracellular environment for later stages by modulating transport processes and ubiquitin-mediated protein degradation. Subsequently, central metabolism and carbon fixation were remodeled to trigger the accumulation of triacylglycerols. Further analysis revealed that these waves of genome-wide transcriptional events were coordinated by a regulatory program orchestrated by at least 17 transcriptional regulators, many of which had not been previously implicated in this process. We demonstrate that the TRN coordinates transcriptional downregulation of 57 metabolic enzymes across a period of nearly 4 h to drive an increase in lipid content per unit biomass. Notably, this TRN appears to also drive lipid accumulation during sulfur starvation, while phosphorus starvation induces a different regulatory program. The TRN model described here is available as a community-wide web-resource at http://networks.systemsbiology.net/chlamy-portal.ConclusionsIn this work, we have uncovered a comprehensive mechanistic model of the TRN controlling the transition from N starvation to lipid accumulation. The program coordinates sequentially ordered transcriptional waves that simultaneously arrest growth and lead to lipid accumulation. This study has generated predictive tools that will aid in devising strategies for the rational manipulation of regulatory and metabolic networks for better biofuel and biomass production.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-015-0391-z) contains supplementary material, which is available to authorized users.

Nitrogen-induced metabolic changes and molecular determinants of carbon allocation in Dunaliella tertiolecta

“…stationary phase). Surprisingly, the transcriptome profile of D. tertiolecta – specifically the upregulation of CCM genes contributing to the supply of acetyl-CoA and NADPH – were vastly similar to oleaginous microalgae including N. oceanica 7 and C. reinhardtii 47. The increased transcript levels of TCA cycle genes and genes contributing to reducing power such as G6PDH and ME were correspondingly observed in heterotrophic fungi such as Mortierella alpina 48 and Mucor circinelloides 4950 to be critical determinants of lipid synthesis.…”

Systems biology approach identifies functional modules and regulatory hubs related to secondary metabolites accumulation after transition from autotrophic to heterotrophic growth condition in microalgae

“…Moreover, many TFs related to photosynthetic carbon fixation such as MYB-related TFs is up-regulated with the same pattern across developmental phases. It has been demonstrated that Myb-related transcription factor is involved in phytochrome signal transduction pathway leading to upregulation of lchb (light-harvesting chlorophyll b) gene in Arabidopsis [38,39] Transcriptional regulators (TRs) are at the interface between sensing and responding to environmental conditions [40]. Results indicated that GNAT (GCN5-related-N-acetyltransferase), SNF2 (sucrose non-fermenting 2), and SET families are top classes of TRs at three phases (S3 Table).…”

Systems biology approaches towards predictive microbial ecology

“…We advocate for integrated microbial community models that include gene regulation across time. Along with other successful efforts in gene regulatory network inference (Desai et al, 2017;Chan et al, 2017;von Dassow et al, 2000;Liu et al, 2016), environmental gene regulatory influence network (EGRIN) models have broadly been used to predict cellular phenotypic states from single species (Yoon et al, 2013;Ashworth et al, 2013;Bonneau et al, 2007;Peterson et al, 2014;López García de Lomana et al, 2015;Brooks et al, 2014). The goal of creating EGRIN models for denitrifying organisms is to highlight key regulatory pathways and environmental determinants affecting the production and consumption of N 2 O.…”