Growth experiments
Growth conditions were identical to those previously described in more detail (Avramova et al, 2015a, 2016). Briefly, maize seedlings were grown in a growth chamber (16h day/8h night, 25°C/18°C day/night [d/n], 300-400µmol.m-2 s-1Photosynthetically Active Radiation, provided by high pressure sodium lamps). Control pots were re-watered daily to a Soil Water Content (SWC) of 54%. For drought treatments, water contents were allowed to drop after sowing to 43% SWC (mild stress, no wilting), and 34% SWC (severe stress, leaves are wilting during the day), respectively, where they were maintained (Figure S1). Three days after emergence of the fifth leaf, the plants were harvested at the middle of photoperiod (14:00 h, MD), end of the day (22:00 h, ED), two hours after beginning of the night (24:00 h, 2hN), end of the night (6:00 h, EN). The first 10 cm from the base of leaf five of each plant were cut in ten segments of 1 cm and the samples were immediately frozen in liquid nitrogen and kept at −80°C until used for measurements (protein and metabolite quantification, enzyme activities).

Proteome analysis

Protein extraction, digestion, and labeling
Total protein extracts were prepared following a modified protocol of trichloroacetic acid (TCA)-acetone extraction (Méchin et al., 2007). Protein concentrations were determined using a Pierce BCA Protein Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). After trypsin digestion at 37°C, peptides were labeled with isobaric tags for relative and absolute quantification (ITRAQ, Wiese et al., 2007). For the reconstitution of the tags, they were dissolved in 50 µl of isopropanol according to the manufacturer’s protocol (Applied biosystems, Foster City, CA, USA). Subsequently, peptides were incubated with the tags for 2 hours at ambient temperature. Pooled samples were prepared based on the labeled samples with a peptide concentration ratio of 1:1:1:1:1:1:1:1. Details about the labeling design of the 4 sample pools are shown in Table S1.
Nano reverse phase liquid chromatography and mass spectrometry
To reduce the overall complexity of the ITRAQ-labeled samples, a 2D-LC fractionation was performed. In a first dimension, performed offline, samples were separated on an Acquity UPLC system (Waters, Milford, MA, USA) with an X-bridge BEH C18 LC column (130 Å, 5 µm particles, 4.6 mm x 150 mm). The column was operated at 40°C and the following mobile phases were used: mobile phase A: 2% acetonitrile and 0.25% formic acid at pH 9 with H5NO and mobile phase B: 98% acetonitrile, 0.25% formic acid at pH 9 with H5NO. A linear gradient from 2% B to 60% B in 9.5 min followed by a steep increase to 90% B in 0.5 min at a flow rate of 1.5 ml/min was used to separate the samples in 10 fractions. Subsequently, these peptide fractions were vacuum dried.
The peptide mixture was further separated by reversed phase chromatography on a Waters nanoAqcuity-UPLC system using an ACQUITY UPLC Peptide BEH C18 nanoACQUITY Column, 130 Å, 1.7 µm, 100 µm X 100 mm (Waters, Milford, MA, USA). Before loading, the sample was dissolved in mobile phase A, containing 2% acetonitrile and 0.1% formic acid and spiked with 20 fmol Glu-1-fibrinopeptide B (Glu-fib, Protea biosciences, Morgantown, WV, USA). A linear gradient of mobile phase B (0.1% formic acid in 98% acetonitrile) in mobile phase A (0.1% formic acid in 2% acetonitrile) from 2 to 35% in 110 min followed by a steep increase to 95% mobile phase B in 2 min was used at a flow rate of 350 nl/min. The nano-LC was coupled online with the mass spectrometer using a PicoTip Emitter (New Objective, Woburn, MA, USA) coupled to a nanospray ion source (Thermo Scientific, San Jose, CA). The LTQ Orbitrap Velos (Thermo Scientific, San Jose, CA) was set up in a MS/MS mode where a full scan spectrum (350 - 5000 m/z, resolution 60 000) was followed by a maximum of five dual CID/HCD tandem mass spectra (100 - 2000 m/z). Peptide ions were selected for further interrogation by tandem MS as the five most intense peaks of a full scan mass spectrum. Collision Induced Dissociation (CID) scans were acquired in the linear ion trap of the mass spectrometer, High energy Collision activated Dissociation (HCD) scans in the Orbitrap, at a resolution of 7500. The normalized collision energy used was 35% in CID and 55% in HCD. We applied a dynamic exclusion list of 30 sec for data dependent acquisition. The entire wet lab and LC-MS procedures were controlled for confounding factors.
Proteome data analysis
Proteome discoverer software (version 1.3, Thermo Scientific, San Jose, CA) was used to perform database searching against the Uniprot Zea mays database using both Sequest and Mascot algorithms, and the following settings: precursor mass tolerance of 10 ppm, fragment mass tolerance of 0.5 Da. Trypsin was specified as digesting enzyme and 2 missed cleavages were allowed. Methylthio (C) and ITRAQ modifications (N-terminus and lysine residues) were defined as fixed modifications and methionine oxidation and phosphorylation (STY) were variable modifications. The results were filtered for confident peptide-to-spectrum matches (PSMs) based on a non-concatenated target-decoy approach. The decoy database is a reversed version of the target database. Only first ranked peptides with a global False Discovery Rate (FDR) smaller than 5% were included in the results. In the ITRAQ quantification workflow the most confident centroid method was used with an integration window of 20 ppm. The reporter ion intensities were corrected for isotope contamination by solving a system of linear equations and the known label purity values from the vendor’s data sheet. The 10 raw datasets from the offline fraction of each sample were analyzed simultaneously in Proteome Discoverer. All the sequences and reporter ion intensities of the peptide spectrum matches (PSMs) that match the confidence requirements were retained for further data-analysis. Data were normalized within each sample pool, but not between the pools and expression values of all the peptides matching to the same protein were averaged. All peptides listed with multiple accessions were removed and peptide sequences belonging to single protein identifications were kept for further statistical analysis, increasing the confidence of protein quantification (Bradshaw et al., 2006; Neilson et al., 2011). Hierarchical clustering was performed using MATLAB (version 9.0, MathWorks Inc., Natick, MA, USA). In each pool, proteins not identified in all biological replicate samples were excluded from the analysis (1 protein in the meristem, 5 proteins in the mature zone, and 5 proteins in the pool comparing the 3 zones). Data were then log2-transformed and a one-way ANOVA was performed within each sample using the software MeV (Multi Experiment Viewer, Saeed et al., 2003) and False Discovery Rate (FDR) was used as a multiple testing correction. Original and corrected P -values are listed in Table S2. A Quality Threshold clustering (QT, Heyer et al., 1999) was performed in MeV (Multi Experiment Viewer, Saeed et al., 2003) using Euclidian distance, cluster diameter 0.4 and minimum cluster population 4. Enrichment studies of the differential proteins levels across the developmental zones and in response to drought in each zone, based on 5% and 10% FDR, respectively, were carried out by PageMan (Usadel et al., 2006).