A Novel Approach to Measure Crop Plant Protein Expression
Crop development to improve yield or disease resistance has been explored for
centuries and the technologies to measure these improvements have subsequently become
complex. The use of transgenes in crop plants is a more technically advanced approach than
traditional breeding and the success of this approach is best assessed using modern
techniques that accurately quantify the desired traits. Here, we applied targeted liquid
chromatography–mass spectrometry (LC–MS) using synthetic stable
isotope–labeled peptides to identify and quantify the relative levels of transgenic to
native protein. The methodology was developed using rice plants in which mRNA expression and
phenotypic effect of the transgene had been validated. Relative quantification of transgenic
barley alanine aminotransferase (AlaAT) used targeted LC–MS of tryptic protein
fragments. We chose the LC–MS method as a superior technique to directly measure
protein levels because other methods such as western blot analysis and RNA were unable to
distinguish the minor amino acid differences between the transgenic and native proteins.
Establishment of this methodology is a first step toward using LC–MS as a predictive
tool to quantify the value of genetically engineered plants before the high investment of a
full field trial.
The improvement of crop plants for yield, insect resistance,
and abiotic stress tolerance is a continuous process in agriculture.
In addition to traditional breeding, genetic engineering
offers an approach to introduce changes with a targeted
adjustment in a plant’s ability to grow. While the ultimate goal in
crop improvement is often focused on increasing yield, the tools to
measure the biological changes in the plant vary. Selecting the right
tool to quantify the improvement hinges on many factors but all
other things being equal, the most important consideration is the
balance of time and cost.
Here we describe the use of liquid chromatography–mass spectrometry
(LC–MS) to quantify the expression levels of a transgenic
protein, barley alanine aminotransferase (AlaAT) across multiple
rice lines. LC–MS is an increasingly popular tool in proteomic
analyses because it bypasses the difficulties and time often needed
for generating antibodies to detect specific proteins (1–5). LC–MS
would be particularly useful when specific antibodies are not available,
as is the case for barley AlaAT. The AlaAT protein superfamily
is highly conserved, and currently available antibodies detect both
the native and transgenic protein, thus confounding our ability to
quantify the presence of the specific transgene. Therefore, LC–MS
technology was selected based on its ability to accurately differentiate
transgenic from native proteins.
We detected and quantified transgenic proteotypic peptides
using stable isotope–labeled peptides as internal standards and
spiked them into rice leaf samples to accurately quantify the endogenous
levels of transgenic protein. This workflow is similar to other
targeted proteomic workflows for the identification of biomarkers
and low-level endogenous proteins in complex matrices (6,7).
Our goal was to measure the amount of transgenic barley AlaAT
protein against the amount of native AlaAT across multiple rice
lines. If the technique proves to be a robust and accurate means
to measure protein levels, in the future we could apply LC–MS to
evaluate the potential performance of a rice line before the investment
in space, time, and resources for a field trial. By correlating
yield improvements to transgenic protein levels in the greenhouse
or growth chamber, we could significantly reduce the number of
transformation lines that require field testing. The first step in this
process is to establish the methodology with plant lines that have
been evaluated in the field and determine whether LC–MS is a suitable
tool for measuring protein levels. The work we describe here
established the necessary resources to differentiate transgenic from
native protein using LC–MS as a primary tool.
Experimental Methods
Tissue Collection
 Table I: Targeted peptides of barley alanine aminotransferase.
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Flag leaves were collected at the booting stage from field-grown
rice plants in which mRNA expression level and phenotypic effect
of the transgene had been validated. The plant leaves were
immediately frozen in liquid nitrogen and stored until manually ground to homogenization
using a chilled mortar and pestle.
Total Protein
Quantification and Normalization
Protein samples were prepared using the
NucleoSpin RNA/Protein kit and quantified
using the Protein Quantification
Assay (both from Macherey-Nagel) according
to manufacturer instruction. All
protein samples were analyzed by 4–12%
Bis-Tris sodium dodecyl sulfate–polyacrylamide
gel electrophoresis (SDS-PAGE) in
MES buffer (Invitrogen).
Protein Gel Electrophoresis
A 5-μL volume of Kaleidoscope Prestained Standard (Bio-Rad) and 70 μg of each total protein sample were loaded onto a NuPAGE
Novex 4–12% Bis-Tris Gel 1.5 mm, 10-well precast polyacrylamide gel (Invitrogen). The protein bands were visualized using
the Colloidal Blue Staining Kit
(Invitrogen).
Excision of Barley AlaAT Protein Bands
The gel was cut into approximately 1-mm
pieces for each sample between the BSA
band (<78 kDa) and the carbonic anhydrase
band (>45.7 kDa), a section that
contains the target barley AlaAT protein.
Blank lanes were used as controls. Gel
pieces were stored separately at -20 °C in
1.5-mL siliconized Eppendorf tubes.
Peptides and Digest
The bands corresponding to AlaAT were
excised, destained, reduced with tris
(2-carboxyethyl)phosphine (TCEP), and
alkylated with iodoacetamide before digestion
using an in-gel tryptic digestion
kit (Thermo Fisher Scientific). Quantification
of AlaAT in transgenic rice used
targeted LC–MS of four peptides. We previously
discovered which peptides could
be readily detected in the transgenic rice
lines. Peptides were selected based on results
from transgenic rice samples and are
described in Table I. Liquid chromatography–
multiple reaction monitoring-mass
spectrometry (LC–MRM-MS) was used
to determine which of the specific proteotypic
peptides generated clear MRM
signals in the endogenous matrix of background
peptides. The peptides were also
selected based on unique sequence identity
for barley over the rice native AlaAT.
Four synthetic heavy peptides (Table I,
Thermo Fisher Scientific) were mixed
with sequencing-grade porcine trypsin
(Promega) just before its addition to
excised gel pieces. Protein was digested
using a protein-to-enzyme ratio of approximately
50:1 and incubated at 37 °C
for 16 h. The amount of each stable isotope
(13C/15N)–labeled peptide added to
each gel sample was 1500 fmol. For each
analysis, one-half of the recovered tryptic
digest was analyzed.
 Figure 1: Protein sequence alignment of the barley and rice AlaATs.
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Chromatography and Mass Spectrometry
Chromatography of peptides used a Paradigm
MDLC MS4 LC pump and a 150
mm × 0.2 mm, 3-μm dp, 200-Å C18AQ
column (Michrom Bioresources). Peptides
were eluted using a 2-μL/min flow rate and
a gradient of acetonitrile (solvent B) in 0.1%
formic acid (solvent A) as follows: 5–40% B
over 50 min, 40–80% B over 1 min, hold at
80% B for 1 min, 80–5% B over 1 min, and
hold at 5% B for 14 min.
An LCQ Deca XP-plus ion-trap mass
spectrometer (Thermo Scientific) equipped
with a Michrom Advance Spray Source
was used for MS-MS analysis in positiveion
electrospray mode. The source spray
voltage was 1200 kV and the capillary
temperature was 200 °C. The MS-MS filters,
instrument conditions, and voltages
were optimized for each targeted peptide
by direct infusion and LC–MS analyses of
the heavy synthetic peptides. LC–MS data
were integrated and processed using Xcalibur
software (Thermo Scientific).