Nitrogen metabolism in cyanobacteria: metabolic and molecular control, growth consequences and biotechnological applications

Abstract

Cyanobacteria are one of the earliest branching groups of organisms on the planet, and during their evolutionary history were submitted to varying selective pressures. Nowadays, cyanobacteria can grow in a variety of conditions, using a large number of nitrogen sources. The control of the nitrogen metabolism in cyanobacteria depends on a fine-tuning regulatory network involving 2-oxoglutarate (2-OG), PII, PipX, and NtcA. This network answers to the cellular 2-OG levels, which reflects the cellular carbon/nitrogen balance, and as an output regulates gene expression, translation, protein activities and thus metabolic pathways. Hence, the diurnal regulation of growth may be directly dependent of this network, as it coordinates the use of photoassimilates towards either growth or the accumulation of reserves, based on the environmental conditions. Therefore, analysis of the nitrogen control network is not only important to comprehend the metabolic control of growth in cyanobacteria, but is also a target to improve cyanobacterial biotechnological potential. In this review, we discuss the mechanisms involved in the control of nitrogen metabolism and its potential role in the diurnal regulation of growth. Then, we highlight why a better understanding of the mechanisms involved in the partitioning of carbon and nitrogen towards growth or storage would increase the biotechnological potential of these organisms.

Keywords:

• Cyanobacteria
• biotechnological applications
• growth regulation
• nitrogen metabolism

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

A.A.E-F is recipient of Scholarships granted by the Agency for the Support and Evaluation of Graduate Education (CAPES-Brazil) [grant # BEX 8904/13-8] and the Thomas Crawford Hayes (NUI Galway). R.S. is recipient of a Visiting Professor grant from CNPq-Brazil PVPE [grant # 401090/2014-0 – Brazil] and the Millennium fund (NUI Galway). A.F. and R.S. acknowledge the H2020 GenialG project (ID: 727892); R.S. and M.I. are grateful for financial support by DAFM via the project VICCI (Research Stimulus Fund Project 14/S/819). Financial support from the Foundation for Research Assistance of the Minas Gerais State (FAPEMIG-Brazil) [Grant APQ-01357-14] to W.L.A. is also acknowledged.