Stoichiometric modelling of leaf metabolism reveals metabolic and morphological determinants for introducing Crassulacean acid metabolism and alternative watersaving flux modes into a C3 leaf in different environments.

11Crassulacean Acid Metabolism (CAM) evolved in arid environments as a water-saving 12 alternative to C3 photosynthesis. There is great interest in engineering more drought-resistant 13 crop species by introducing CAM into C3 plants. However, one of the open questions is 14 whether full CAM or alternative water-saving flux modes would be more productive in the 15 environments typically experienced by C3 crops. To study the effect of temperature and 16relative humidity on plant metabolism we coupled a time-resolved diel model of leaf 17 metabolism to an environment-dependent gas-exchange model. This model allowed us to 18 study the emergence of CAM or CAM-like behaviour as a result of a trade-off between leaf 19 productivity and water-saving. We show that vacuolar storage capacity in the leaf is a major 20 determinant of the extent of CAM and shapes the occurrence of phase II and IV of the CAM 21 cycle. Moreover, the model allows us to study alternative flux routes and we identify 22 mitochondrial isocitrate dehydrogenase (ICDH) and an isocitrate-citrate-proline-2OG cycle as 23 a potential contributor to initial carbon fixation at night. Simulations across a wide range of 24 environmental parameters show that the water-saving potential of CAM strongly depends on 25 the environment and that the additional water-saving effect of carbon fixation by ICDH can 26 reach up to 4% for the conditions tested. 27 28 An optimality study reveals trade-offs between productivity and WUE 131Computationally, the question of how a system's behaviour changes when operating between 132 competing objectives can be tackled by performing a Pareto analysis [16][17][18][19] . In our case phloem 133 output and water-saving represented two competing driving forces. We started the Pareto 134 analysis from the above described scenario of a mature leaf optimized for maximum phloem 135 output (i.e. 100% phloem output, here termed Pareto step 1). We then subsequently reduced 136 the required phloem output in 10%-steps and used minimization of water loss as the primary 137 optimization objective. Given this setup, we saw an almost linear decrease in water loss with 138 decreasing phloem output, hence we did not observe any significant water-saving mechanism 139