Robust Photosynthesis in Dynamic Environments
In contrast to growth inside a laboratory setting, plants in natural environments must contend with diverse, highly dynamic and unpredictable challenges and conditions. Optimizing the photosynthetic reactions that underpin plant and microalgal growth requires fine balancing of regulation that responds to these environmental conditions with other critical processes of development and must also interface with the current metabolic status of the organism. If the reactions of photosynthesis are not properly regulated and balanced with regard to these considerations, deleterious side products and photodamage can result. How the components of photosynthesis are integrated into a self-organizing molecular assembly that is capable of robustness in the face of these fluctuating conditions and is a grand challenge in basic plant biology and in basic engergy sciences.
Unlike the core processes of photosynthesis, which have been studied for decades and are relatively well-understood, the "ancillary" pathways and regulation that allow photosynthesis to proceed effectively under dynamic environmental conditions are essentially unexplored. For example, a number of scientific investigations have shown that many plant mutants behave essentially normally when analyzed in the lab, only to exhibit strong phenotypes under the fluctuating conditions found outdoors or in a greenhouse. Understanding how the biochemical reactions of photosynthesis are tuned in real-time under natural settings is not only of academic interest, it is a critical concern of biotechonological applications. A frequently encountered problem is that newly developed photosynthetic strains demonstrate promising behavior in the lab, but vastly underperform when placed in the variable conditions of field trials or scaled bioreactors.
Despite the importance of understanding photosynthetic robustness under natural conditions, this area has been largely overlooked in research due to lack of the appropriate A) incubation technologies for growing plants in dynamic, yet reproducible conditions; B) integrated, on-board spectroscopic probes and sensors for monitoring photosynthetic parameters of these organisms in real-time over long time periods; C) access to a wide array of relevant plant strains and mutants with both known photosynthetic phenotypes and mutants in pathways presumed to be unrelated to photosynthesis, and finally; D) the capacity to collect growth and photosynthetic data in a high-throughput platform and then analyze and interpret the resulting large datasets.
The PRL is tackling these challenges using a combination of novel instrumentation developed in-house (e.g. Dynamic Environmental Phenotyping Imagers, or DEPI), established experts in the field of photosynthesis, on-campus collections of plant libraries containing a vast array of ecotypes and mutants, and development of automated data processing streams and bioinformatic pipelines. Briefly, the newly invented growth chambers allow a researcher to program in fluctuating, yet reproducible conditions. For example, it is possible to gather actual environmental data from a natural site (e.g. collect light and temperature readings from an Autumn day in a Michigan park) and then to replay these conditions faithfully within the chamber. On-board detectors monitor the growth and health of the plant lines and can determine how efficiently their photosynthesis proceeds without destroying the plants by using spectroscopic and fluorescence sensors. In this way, many lines may be monitored and analyzed over time to uncover the functions of heretofore unknown genes that act to buffer photosynthesis against environmental fluctuations and stresses.
Figure 2: Example of a single time point collected for multiple Arabidopsis strains and mutants. Rows of young plants are imaged using advanced spectroscopic techniques throughout a simulated day/night cycle to determine plant growth, photosynthetic efficiency, and photodamage. A plant's dissipation of light in a nonproductive manner (NPQ) is measured across its surface area and pseudo-colored from low (blue) to high (red).
Primary Research Groups Involved:
Attaran, Elham, et al. "Temporal dynamics of growth and photosynthesis suppression in response to jasmonate signaling." Plant physiology 165.3 (2014): 1302-1314.
Xu, Lei, et al. "Plant Photosynthesis Phenomics Data Quality Control." Bioinformatics (2015): btu854.