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).