An Improved Stable Isotope N‑Terminal Labeling Approach with Light/Heavy TMPP To Automate Proteogenomics Data Validation: dN-TOP

In silico gene prediction has proven to be prone
to errors, especially regarding precise localization of start codons
that spread in subsequent biological studies. Therefore, the high
throughput characterization of protein N-termini is becoming an emerging
challenge in the proteomics and especially proteogenomics fields.
The trimethoxyphenyl phosphonium (TMPP) labeling approach (N-TOP)
is an efficient N-terminomic approach that allows the characterization
of both N-terminal and internal peptides in a single experiment. Due
to its permanent positive charge, TMPP labeling strongly affects MS/MS
fragmentation resulting in unadapted scoring of TMPP-derivatized peptide
spectra by classical search engines. This behavior has led to difficulties
in validating TMPP-derivatized peptide identifications with usual
score filtering and thus to low/underestimated numbers of identified
N-termini. We present herein a new strategy (dN-TOP) that overwhelmed
the previous limitation allowing a confident and automated N-terminal
peptide validation thanks to a combined labeling with light and heavy
TMPP reagents. We show how this double labeling allows increasing
the number of validated N-terminal peptides. This strategy represents
a considerable improvement to the well-established N-TOP method with
an enhanced and accelerated data processing making it now fully compatible
with high-throughput proteogenomics studies.