Carbon use efficiency diagnostics in Nannochloropsis salina

Carbon dioxide (CO2) can be a significant resource input affecting the cost of algae biomass production on an industrial scale. Improvements in biofuel productivity therefore require characterization of CO2 use efficiency (CUE). RuBisCO saturation with CO2 is an important factor influencing biomass productivity. During CO2 fixation by RuBisCO, fractionation of carbon isotopes occurs, with preferential fixation of 12CO2, resulting in assimilation of the lighter isotope in algae. This photosynthetic discrimination (ΔDIC-algae), approximated by the difference between the δ13C of external medium and that of algae, is a function of the proportion of CO2 fixed relative to supply. ΔDIC-algae has been applied to the study of photosynthesis in algae over the past few decades and we have adopted the tool to characterize improvements in conditions optimized for biofuel productivity, such as controlled photobioreactors. We report the use of ΔDIC-algae as a tool for characterizing CO2 dynamics and RuBisCO saturation in Nannochloropsis salina CCMP 1776, a benchmark strain in algal biofuels research. We use ΔDIC-algae to describe the conditions under which RuBisCO saturation can be achieved to maximize biomass productivity. Our results suggest that determination of ΔDIC-algae can provide important feedback to support engineering and cultural improvements that can impact carbon use efficiency and biomass productivity. •RuBisCO prefers 12CO2 to 13CO2 during photosynthesis, leading to different isotopic signatures in photosynthetic organisms.•N salina δ13C in algae and media measured under different CO2 concentrations to determine C fractionation.•Photosynthetic discrimination (ΔDIC-algae) increased with [CO2], approaching theoretical maximum under saturating CO2.•High ΔDIC-algae was diagnostic of RuBisCO saturation and high overall biomass production.•CUE was negatively correlated to ΔDIC-algae suggesting a balance required for optimizing sustainable production.•We discuss these results in the context of characterization of CCMs and optimization of conditions for biofuel production.