Introduction
One of the first responses of plants to drought is reduced leaf growth in order to limit transpiration and conserve water (Ahmad et al., 2016; Avramova et al., 2016). In crops, this contributes to a loss of up to 60% of the potential yield, even during mild drought conditions when visual signs of wilting are absent (Ribaut et al., 1997). Leaf growth responses are mediated by cell division and expansion (Rymen, 2010), regulated by molecular networks of integrated signals, including hormones (Nelissen et al., 2012; Pacifici et al., 2015), reactive oxygen species (ROS, Tsukagoshi et al., 2010) and sugar signals (Gibson et al., 2005). Drought stress affects physiological parameters such as stomatal aperture, water relations and photosynthesis and causes changes in carbon metabolism (Farooq et al., 2009). Starch plays a key role in balancing growth and carbon assimilation (Thalmann and Santelia, 2017). It accumulates during the photoperiod and is degraded during the night to support respiration and growth. Drought increases starch concentrations during the photoperiod (Foyer et al., 1998). In mutants unable to synthesize or degrade starch, growth is impaired (Stitt and Zeeman, 2012). Starch reserves are remobilized to release soluble sugars, which function as osmolites, support growth and serve as signal molecules (Thalmann and Santelia, 2017).
To obtain an integrated mechanistic understanding of the growth response to drought, we combined cellular, physiological and molecular analyses of the maize (Zea mays L.) leaf growth zone (Avramova et al., 2015a; Avramova et al., 2017). The large size of this growth zone (Avramova et al., 2015b) provides enough tissue for analyses at the transcriptome (Avramova et al., 2015a; Czedik-Eysenberg et al., 2016; Kravchik and Bernstein, 2013; Li et al., 2010; Wang et al., 2014), epigenome (Candaele et al., 2014), proteome (Bonhomme et al., 2012; Facette et al., 2013; Majeran et al., 2010; Riccardi et al., 1998) and metabolome levels (Avramova et al., 2015a, 2017; Czedik-Eysenberg et al., 2016; Nelissen et al., 2012, 2018; Pick et al., 2011; Wang et al., 2014) along the developmental gradient and allows to study responses to environmental stress (Avramova et al., 2015a, 2017; Kravchik and Bernstein, 2013; Nelissen et al., 2018; Rymen et al., 2007; Walter et al., 2009).
The effect of drought stress on the maize leaf proteome has been studied by gel-based approaches (Benešová et al., 2012; Riccardi et al., 1998; Xin et al., 2018), which are limited to detect only the most-abundant proteins in mature leaves. LC-MS/MS based techniques, which have a higher sensitivity, are increasingly used to study proteome and phosphoproteome changes, including responses to drought stress in mature leaves (Zhao et al., 2016) and growth zone of growing leaves (Dai Vu et al., 2016). Currently, the only large-scale studies comparing the effect of drought in dividing, expanding and mature tissues of maize leaves have been performed at the transcriptome (Avramova et al., 2015a), the phosphoproteome (Bonhomme et al., 2012) and the metabolome (Avramova et al., 2017; Nelissen et al., 2018) levels. In addition to transcriptional regulation, molecular adaptation could be regulated at the post-transcriptional, posttranslational and metabolite levels (Ghatak et al., 2017; Nägele and Weckwerth, 2014). Therefore, integrated studies combining data from different regulatory levels are needed to obtain a mechanistic understanding of the growth response to drought.
In this study, we investigated the drought response in the leaf growth zone at the proteome level, using a mass spectrometry-based protein quantification, complemented with high-resolution metabolite and biochemical measurements. We compared wild type and sh2 mutant plants, defective in starch biosynthesis under drought conditions and demonstrate the importance of increased starch synthesis in maintaining growth and facilitating recovery during and upon recovery from drought.

Materials and Methods

Plant material

The inbred line B73 (Iowa Stiff Stalk Synthetic) was used for proteomic, metabolite and biochemical measurements. The shrunken2 mutant and its wild type (W22), were obtained from MaizeGDB (http://www.maizegdb.org/stock_catalog).