Proteonano™: a nanobinder-based proteomics platform for robust and standardized deep plasma proteomics study

INTRODUCTION: Profiling the human plasma proteome is challenging due to the immense dynamic range of plasma protein concentration spanning ten orders of magnitudes between the most abundant protein and the least abundant proteins detected so far. Most of currently used workflows are labor-intensive and rely on abundant protein depletion and fractionation methods to improve detection depth. In addition, most of the pipelines involve manual sample processing, limiting throughput and assay consistency. We developed unique nanobinders that enriches low abundant proteins and semi-automatic workflow to increase plasma protein detection limit with increased throughput and decreased intersample variation.

METHODS: Superparamagnetic nanoparticles were synthesized at scale and conjugated with small molecules and peptides by using a proprietary deep learning pipeline. Abilities of these nanobinders to capture plasma proteins were determined by LC-MS/MS. Sample processing was performed by using a in-house designed liquid handling Nanomation™ G1 system optimized for parallel (up to 96 samples) nanobinder-based proteomic sample processing. Using Nanomation™ G1, nanobinders were incubated with plasma samples, washed, followed by denaturation, reduction, alkylation, digestion, and desalting. Digested samples were analyzed using high-resolution mass spectrometers, including ThermoFisher Exploris 480 and Orbitrap Astral, and Bruker timsTOF Pro2.

RESULTS: More than 500 nanobinders were synthesized and characterized. The ability of these nanobinders were determined by LC-MS/MS. The best nanobinder detected 4129 protein groups in a single run, compared to 810 without enrichment. Concentrations of detected proteins spanned nine orders of magnitude, with 70.2% of detected proteins had reported concentrations below 10 ng/mL. When human and porcine plasma were mixed at different proportions and subjected to LC-MS/MS, concentrations of detected human proteins at different mixing ratios displayed similar linearity between samples with or without Proteonano™ based pre-processing. For assay stability measurements, the same plasma sample were parallelly processed by Nanomation™ instrument using two batches of the same nanobinder. 4057±38, 4159±30 protein groups were identified for each batch of nanobinders, respectively, with protein concentration coefficient of variation (CV) at 9.87% and 9.62%, without data normalization. In a real-world test, 12 replicates of the same quality control (QC) tests were interspersed with 206 experimental plasma samples, which detected 4348 protein groups in QC samples with a protein number CV of 1.47%. For commonly detected protein groups, a median CV for protein centration was 16.88 % without data normalization demonstrating high reproducibility.

CONCLUSIONS: Proteonano™ platform allows deep, rapid, reproducible proteomic analysis of plasma samples.