Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA)

Recently,
we have developed a quantitative shotgun proteomics strategy
called mass accuracy precursor alignment (MAPA). The MAPA algorithm
uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC–MS analyses,
determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a
multitude of samples. Here, we introduce a novel feature of this algorithm
that allows the extraction and alignment of proteotypic peptide precursor
ions or any other target peptide from complex shotgun proteomics data
for accurate quantification of unique proteins. This strategy circumvents
the problem of confusing the quantification of proteins due to indistinguishable
protein isoforms by a typical shotgun proteomics approach. We applied
this strategy to a comparison of control and heat-treated tomato pollen
grains at two developmental stages, post-meiotic and mature. Pollen
is a temperature-sensitive tissue involved in the reproductive cycle
of plants and plays a major role in fruit setting and yield. By LC–MS-based
shotgun proteomics, we identified more than 2000 proteins in total
for all different tissues. By applying the targeted MAPA data-processing
strategy, 51 unique proteins were identified as heat-treatment-responsive
protein candidates. The potential function of the identified candidates
in a specific developmental stage is discussed.