profiling-surface-protein-epitopes-on-viral-particles-multiplex-dual

Profiling of Surface Protein Epitopes on Viral Particles by Multiplex Dual-Reporter Strategy

Membrane proteins on enveloped viruses play an important role in many biological functions involving virus attachment to target cell receptors, fusion of ...

KTH Royal Institute of Technology

The plasma proteome offers a clinically useful window into human health. Recent advances from highly multiplexed assays now call for appropriate pipelines to validate individual candidates. Here, a workflow is developed to build dual binder sandwich immunoassays (SIA) and for proteins predicted to be secreted into plasma. Utilizing suspension bead arrays, ≈1800 unique antibody pairs are first screened against 209 proteins with recombinant proteins as well as EDTA plasma. Employing 624 unique antibodies, dilution-dependent curves in plasma and concentration-dependent curves of full-length proteins for 102 (49%) of the targets are obtained. For 22 protein assays, the longitudinal, interindividual, and technical performance is determined in a set of plasma samples collected from 18 healthy subjects every third month over 1 year. Finally, 14 of these assays are compared with with SIAs composed of other binders, proximity extension assays, and affinity-free targeted mass spectrometry. The workflow provides a multiplexed approach to screen for SIA pairs that suggests using at least three antibodies per target. This design is applicable for a wider range of targets of the plasma proteome, and the assays can be applied for discovery but also to validate emerging candidates derived from other platforms.

Systematic Development of Sandwich Immunoassays for the Plasma Secretome.

Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

Precision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular phenotypes, the descriptions of human health on an individual level have been far less elaborate.

Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling.

Protein biomarkers in biological fluids represent an important resource for improving the clinical management of diseases. Current proteomics technologies are capable of performing high-throughput and multiplex profiling in different types of fluids, often leading to the shortlisting of tens of candidate biomarkers per study. However, before reaching any clinical setting, these discoveries require thorough validation and an assay that would be suitable for routine analyses. In the path from biomarker discovery to validation, the performance of the assay implemented for the intended protein quantification is extremely critical toward achieving reliable and reproducible results. Development of robust sandwich immunoassays for individual candidates is challenging and labor and resource intensive, and multiplies when evaluating a panel of interesting candidates at the same time. Here we describe a versatile pipeline that facilitates the systematic and parallel development of multiple sandwich immunoassays using a bead-based technology.

Bead-Based Assays for Validating Proteomic Profiles in Body Fluids.

Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%-14.7%). This includes 5.4% of the samples being IgGIgM against several SARS-CoV-2 proteins, as well as 2.1% being IgGIgM and 5.0% being IgGIgM for the virus' S protein. Subjects classified as IgG for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG for only the S protein (OR = 6.1; p < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.

Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2.

Patient-centric sampling strategies, where the patient performs self-sampling and ships the sample to a centralized laboratory for readout, are on the verge of widespread adaptation. However, the key to a successful patient-centric workflow is user-friendliness, with few noncritical user interactions, and simple, ideally biohazard-free shipment. Here, we present a capillary-driven microfluidic device designed to perform the critical biomarker capturing step of a multiplexed immunoassay at the time of sample collection. On-chip sample drying enables biohazard-free shipment and allows us to make use of advanced analytics of specialized laboratories that offer the needed analytical sensitivity, reliability, and affordability. Using C-Reactive Protein, MCP1, S100B, IGFBP1, and IL6 as model blood biomarkers, we demonstrate the multiplexing capability and applicability of the device to a patient-centric workflow. The presented quantification of a biomarker panel opens up new possibilities for e-doctor and e-health applications.

Microfluidic Device for Patient-Centric Multiplexed Assays with Readout in Centralized Laboratories.

Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk.

Article	Year
Systematic Development of Sandwich Immunoassays for the Plasma Secretome. Proteomics\| PubMed ID: 31278833	2019
Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts. PLoS medicine\| PubMed ID: 32559194	2020
Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling. EBioMedicine\| PubMed ID: 32629387	2020
Bead-Based Assays for Validating Proteomic Profiles in Body Fluids. Methods in molecular biology (Clifton, N.J.)\| PubMed ID: 34115352	2021
Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2. Nature communications\| PubMed ID: 34140485	2021
Microfluidic Device for Patient-Centric Multiplexed Assays with Readout in Centralized Laboratories. Analytical chemistry\| PubMed ID: 36548393	2023
The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk. British journal of cancer\| PubMed ID: 38135714	2023

Matilda Dale

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