Increasing the Throughput and Reproducibility of Activity-Based Proteome Profiling Studies with Hyperplexing and Intelligent Data Acquisition

Intelligent data
acquisition (IDA) strategies, such as a real-time
database search (RTS), have improved the depth of proteome coverage
for experiments that utilize isobaric labels and gas phase purification
techniques (i.e., SPS-MS3). In this work, we introduce inSeqAPI, an
instrument application programing interface (iAPI) program that enables
construction of novel data acquisition algorithms. First, we analyze
biotinylated cysteine peptides from ABPP experiments to demonstrate
that a real-time search method within inSeqAPI performs similarly
to an equivalent vendor method. Then, we describe PairQuant, a method
within inSeqAPI designed for the hyperplexing approach that utilizes
protein-level isotopic labeling and peptide-level TMT labeling. PairQuant
allows for TMT analysis of 36 conditions in a single sample and achieves
∼98% coverage of both peptide pair partners in a hyperplexed
experiment as well as a 40% improvement in the number of quantified
cysteine sites compared with non-RTS acquisition. We applied this
method in the ABPP study of ligandable cysteine sites in the nucleus
leading to an identification of additional druggable sites on protein-
and DNA-interaction domains of transcription regulators and on nuclear
ubiquitin ligases.