Environmental triggers for photosynthetic protein turnover determine the optimal nitrogen distribution and partitioning in the canopy

Abstract

Plants acclimatize their photosynthetic functions in leaves constantly to the fluctuating light, thereby optimizing the use of photosynthetic nitrogen (Nph) at the canopy level. To investigate the complex interplay between external signals during the acclimation processes, a mechanistic model based on the concept of protein turnover (synthesis and degradation) was proposed and parameterized using cucumber grown under nine combinations of nitrogen and light in growth chambers. Integrating this dynamic model into a multi-layer canopy model provided accurate predictions of photosynthetic acclimation of greenhouse cucumber canopies grown under high (HN) and low (LN) nitrogen supply in combination with day-to-day fluctuations in light at two different levels. This allowed us to quantify the degree of optimality in canopy nitrogen use for maximizing canopy carbon assimilation, which was influenced by Nph distribution along canopy depth or Nph partitioning between functional pools. Our analyses suggest that Nph distribution is close to optimum and Nph reallocation is more important under LN. Nph partitioning is only optimal under the light level similar to the average light intensity during acclimation, meaning that day-to-day light fluctuations inevitably result in sub-optimal Nph partitioning. Our study provides insights into photoacclimation and can be applied for crop model improvement.

Photosynthetic Acclimation to Fluctuating Irradiance in Plants

“…Nevertheless, these data are in contrast to a modeling study by Retkute et al (2015) which indicated that the optimal plant response to fluctuating irradiance was to increase A max . These results may also be in disagreement with a recent commentary by Pao et al (2019b), who suggested that photosynthetic capacity (expressed as maximum electron transport and carboxylation rates, J max and V cmax , respectively) is reduced in leaves under fluctuating irradiance; this analysis was based on a non-linear relationship between irradiance and protein synthesis rate, using data from a previous modeling study validated with measurements on Cucumis sativa (grown under constant irradiance) as reference (Pao et al, 2019a). The reasoning by Pao et al (2019b) is that leaves under fluctuating irradiance experience a relatively longer time close to the saturating end of this relationship compared to leaves under lower, uniform light.…”

“…This equilibrium state would depend on the speed of dynamic acclimation and the degree of linearity in the response of plant traits to changes in irradiance. These dynamics have been captured in simulation models either (i) by implementing a goalseeking behavior that calculates steady-state acclimation from optimization theory (Yin et al, 2019) or (ii) by simulating protein turnover dynamically (Thornley, 1998;Kull and Kruijt, 1999;Barillot et al, 2016;Pao et al, 2019a). Experimental evidence exists that coordination across leaves may be achieved through cytokinins carried by the transpiration stream (Pons et al, 2001), as transpiration will vary according to the irradiance profile.…”

Determining Ion Toxicity in Cucumber under Salinity Stress

“…to control plants in order to normalize for the effects of leaf age [18]. Cucumber has a high leaf turnover rate (the biochemical capacity for photosynthesis drops by 50% after 15 days past full expansion of the leaf [11,34,35]) and the accumulation of salt to a toxic level takes 15-20 days [11]. Without this normalization the ionic effects would be overestimated.…”

A mechanistic view of the reduction in photosynthetic protein abundance under diurnal light fluctuation

“…Protein abundance is regulated by the orchestration of multiple mechanisms and is the outcome of protein turnover: the continuous dynamics of protein synthesis and degradation (Kristensen et al , 2013; Nelson and Millar, 2015). Based on the concept of protein turnover, we have recently presented a mechanistic model describing photosynthetic acclimation (Pao et al , 2019) in which the experimental data suggested a non-linear relationship between the PPSR and PAR (see Supplementary Fig. S1 at JXB online).…”

“…1A), it is possible to assess the differences in photosynthetic protein abundance between plants grown under FL and SQ. To simulate the effect of the diurnal light fluctuation, we first converted the parameters in the model of Pao et al (2019) to an hourly basis by assuming a 12 h photoperiod and zero protein synthesis in the dark. Then, three FL patterns (Fig.…”