Research Focus: Systems Approaches for Discovery and Interaction of Guard Cell Signaling Mechanisms

Two pairs of Arabidopsis guard cells.

Pairs of guard cells found in the leaf epidermis circumscribe and define microscopic pores called stomata. In response to a myriad of environmental signals, guard cells regulate stomatal aperture size by osmotically-driven swelling or shrinking. Light-stimulated stomatal opening is imperative for uptake of carbon dioxide from the atmosphere, which is the starting point for carbon fixation during photosynthesis. Conversely, during drought, the plant hormone abscisic acid (ABA) inhibits stomatal opening and promotes stomatal closure, thereby promoting plant water conservation. In our laboratory, we assess guard cell responses by whole plant measurements of carbon dioxide uptake and water loss, assessed using gas exchange techniques, by direct visualization of stomatal apertures under the microscope, by omics approaches that determine how the transcriptome, proteome, and metabolome change in response to environmental signals, and by electrophysiological assays that measure the ionic currents responsible for changes in guard cell osmotica.

Light-Induced Stomatal Opening Network Model (Sun et. al. 2014)

Current projects are focused on the roles of heterotrimeric G proteins as regulators of ABA and CO2 signaling in guard cells, on the guard cell response to red light (including collaborations with Prof. Toshinori Kinoshita (Nagoya University) and Prof. Beronda Montgomery (Michigan State University), and on the metabolomics of the guard cell response to pathogens (in collaboration with Prof. Sixue Chen (U. Florida). We have described the guard cell transcriptome (Wang et al., 2011), proteome (Zhao et al., 2008; Zhao et. al., 2010; Zhu and Assmann, 2017; Zhu et. al., 2019), and metabolome (Jin et al., 2013), and with Prof. Reka Albert, Penn State Dept. of Physics, we are applying dynamic modeling and other systems biology tools to synthesize information on light- and ABA-regulated guard cell signaling from our group and from the literature into models that are both accurate and predictive (Li et al., 2006; Assmann and Albert, 2009; Assmann, 2010; Li et al., 2012; Sun et al., 2014; Albert et. al., 2017; Maheshwari et. al., 2019). It is worth noting that the network methods we develop are system-agnostic and can be applied to any biological system for which data on signaling components and interactions are available.