Making the Impossible Possible: Uniting TMT and DIA for Scalable Low-Input-Proteomics

Abstract

Isobaric multiplexing using tandem mass tags (TMT) and data-independent acquisition (DIA) are two powerful techniques in quantitative proteomics, each offering distinct advantages. Combining these strategies provides synergistic benefits for low-input applications such as single-cell proteomics (SCP). However, integrating these strategies has remained challenging due to co-isolation interference and increased data complexity. Here, we present a systematic, identification-linked evaluation of a hybrid DIA-TMTpro 18-plex workflow on the Orbitrap Astral mass spectrometer (MS). Using a two-proteome interference model of human and yeast digests, we benchmarked quantitative accuracy and precision of TMT based DDA and DIA acquisition strategies across a range of isolation windows, injection times and input amounts. We provide READ (Reporter Ion Extractor and Annotation Director), an in-house developed Python-based tool which enables streamlined reporter ion (RI) quantification and co-isolation purity assessment. Using READ, TMT-based quantification becomes possible from DIA-focused search engines like Spectronaut or DIA-NN, which do not natively support TMT. We show that co-isolation interference drives both ratio compression and ratio inflation in TMT RI-based quantification regardless of acquisition mode. As an interference-resistant alternative, we further evaluated quantification via TMT complementary ions, which achieved near-label free quantitative accuracy at the cost of reduced plexing capacity and proteome depth. Together, these results establish practical guidelines for combining DIA and TMTpro on the Orbitrap Astral mass spectrometer and provide a foundation for extending DIA-TMT workflows to low-input applications such as SCP, where sensitivity, accuracy and throughput are critical.