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).