plexDIA: sensitive proteomics with simultaneous deep coverage, high throughput, low missing data.

Although current mass-spectrometry (MS) methods can separately achieve deep proteome coverage, low missing data, high throughput, or high sensitivity, simultaneous combination of these has remained challenging.

Here Derks et al. present plexDIA, an experimental and computational method that, by a combination of chemical labelling and multiplexing both peptide and sample analysis, simultaneously accomplishes all four.

Involving 3-plex non-isobaric mass tag labelling with a Thermo Fisher Q Exactive Orbitrap coupled to IonOpticks Aurora Series UHPLC columns, plexDIA quantifies about 8,000 proteins per sample – a 3-fold increase in protein quantification across limited sample amounts. Throughput increases as a multiple of the number of labels without reducing proteomic coverage, quantitative accuracy, precision, or reproducibility.

The framework is expected to scale to n labels, increasing throughput n-fold, reducing costs nearly n-fold, and increasing the fraction of proteins quantified across all samples. The development of higher plex labels will thus facilitate even greater throughput.

Furthermore, plexDIA increases the consistency of protein quantification both across and within runs, by buffering sample-to-sample variability in protein composition. This results in a >2-fold reduction in missing data, in samples with variable protein composition or abundance.

plexDIA is particularly attractive for the analysis of nanogram samples where it may afford accurate and deep proteome quantification without using offline fractionation. The potential extends to significant gains in sensitivity for single-cell proteomics, or to large-scale experiments where batch effects pose a significant challenge. plexDIA may arguably become the predominant DIA workflow, preferable over label-free approaches for most applications.

Read the full paper
Increasing the throughput of sensitive proteomics by plexDIA.
bioRxiv preprint, November 4, 2021. doi: 10.1101/2021.11.03.467007

Jason Derks, Andrew Leduc, R. Gray Huffman, Harrison Specht, Markus Ralser, Vadim Demichev & Nikolai Slavov

Commentary by Jarrod Sandow, PhD.

About the author
Jarrod has a background in biotechnology and completed his PhD at the Institute of Medical and Veterinary Science in Adelaide. He is a co-inventor of IonOpticks’ core technology and is driven towards developing innovative solutions for the global proteomics research community that will enable scientists and clinicians to discover more from their samples to accelerate advances in biological and medical research.