Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona

Abstract

Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids. Varying the physicochemical properties of engineered NPs translates to distinct protein corona patterns enabling differential and reproducible interrogation of biological samples, including deep sampling of the plasma proteome. Spike experiments confirm a linear signal response. The median coefficient of variation was 22%. We screened 43 NPs and selected a panel of 5, which detect more than 2,000 proteins from 141 plasma samples using a 96-well automated workflow in a pilot non-small cell lung cancer classification study. Our streamlined workflow combines depth of coverage and throughput with precise quantification based on unique interactions between proteins and NPs engineered for deep and scalable quantitative proteomic studies.

Affinity Capture Enrichment versus Affinity Depletion: A Comparison of Strategies for Increasing Coverage of Low-Abundant Human Plasma Proteins

“…Therefore, a great effort is made to reduce sample complexity in biomarker discovery research employing a variety of methods. These include depletion of high-abundant proteins using immune affinity approaches, selective capturing of sub-proteomes [3][4][5], protein corona formation on nanoparticles [6] or enrichment techniques alone [7,8] and/or in combinations with extensive fractionation techniques such as sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) [9], strong cation exchange (SCX) [10], isoelectric focusing (IEF) [11], hydrophilic interaction chromatrography (HILIC), and high-pH separation [9]. Despite these efforts to reduce sample complexity, plasma biomarker studies generally identify a significantly lower number of proteins compared to proteomic analysis of protein extracts from tissue biopsies or isolated from cell cultures, despite the fact that more than 10,000 proteins to date have been identified in plasma, according to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org, last access day: 2 February 2015) [12,13].…”

Machine Learning Guided Postnatal Gestational Age Assessment Using Newborn Screening Metabolomic Data in South Asia and Sub-Saharan Africa

“…While rethinking and investigating lowtech variations suitable to LMIC settings, also to consider are, newer high throughput trans proteome/metabolome platforms which are now becoming affordable (i.e. Seers Nano peptide technology 46 ). An untargeted metabolomic approach may improve our ability to estimate GA postnatally while also identifying infants at risk of a variety of conditions.…”

Shotgun proteomics coupled to nanoparticle-based biomarker enrichment reveals a novel panel of extracellular matrix proteins as candidate serum protein biomarkers for early-stage breast cancer detection

“…Although our candidates were independently verified using an LC-MRM method, we recognize that use of semi-quantitative label-free data employed in the discovery phase may be a limitation of the study. Other alternative nanoparticle-based sample processing techniques provide broad proteomic coverage of blood proteins [ 47 ]. Unlike our HN sample enrichment method, these approaches do not specifically enrich the extra-vascular content contained in the LMW low abundant blood proteome.…”