A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world.
Yang X., Cushman JC., Borland AM., Edwards EJ., Wullschleger SD., Tuskan GA., Owen NA., Griffiths H., Smith JAC., De Paoli HC., Weston DJ., Cottingham R., Hartwell J., Davis SC., Silvera K., Ming R., Schlauch K., Abraham P., Stewart JR., Guo H-B., Albion R., Ha J., Lim SD., Wone BWM., Yim WC., Garcia T., Mayer JA., Petereit J., Nair SS., Casey E., Hettich RL., Ceusters J., Ranjan P., Palla KJ., Yin H., Reyes-García C., Andrade JL., Freschi L., Beltrán JD., Dever LV., Boxall SF., Waller J., Davies J., Bupphada P., Kadu N., Winter K., Sage RF., Aguilar CN., Schmutz J., Jenkins J., Holtum JAM.
Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.