Skip to content
#protein folding Open access

Analytical validation of a multiplexed peptide microarray for multi-antigen Epstein–Barr virus serological profiling across diverse clinical specimens

Sep 2026 · Frontiers in Immunology · 0 citations · 27 references
Advanced Biosensing Techniques and Applications

Abstract

Epstein–Barr virus (EBV) infects more than 95% of adults and is associated with outcomes ranging from asymptomatic latency to infectious mononucleosis (IM), malignancies, and multiple sclerosis (MS). Conventional ELISA-based EBV serology is often restricted to a small number of soluble, whole-protein antigens and does not preserve information regarding the specific linear regions of antigen recognition that contribute to the overall antibody response. Multiplexed peptide microarrays address this limitation, but their use in clinical practice requires characterization of their analytical performance and behavior across the diverse conditions encountered in practical use. Here we report the analytical validation of a 108-peptide microarray spanning nine EBV proteins, applied to 329 specimens collected as serum, EDTA plasma, and Streck cell-free DNA (cfDNA) blood collection tubes. Within-block and between-slide reproducibility, detection thresholds, and minimum detectable fold-change were consistent with established peptide-array benchmarks, and composite antigen scores correlated with ELISA assays for EBNA-1, VCA-p18, and EA-D. IgG signals were stable across collection matrices, whereas IgM was selectively attenuated in Streck plasma, indicating that fixative-containing tubes should be approached cautiously when IgM is the readout of interest. When applied to IM, MS, and non-MS donors, the peptide array consistently detected broad EBV humoral reactivity. In this proof-of-concept disease-cohort analysis, the array recapitulated biologically relevant EBNA-1 C-terminal reactivity patterns previously associated with MS-related molecular mimicry, but array-wide EBV reactivity did not yield a simple MS-discriminating signature. Although EBV reactivity has been reported to distinguish MS from non-MS cohorts, only a very small set of EBV epitopes was cohort-associated in our data, indicating that platform-level seropositivity reflects EBV exposure rather than an obvious MS-specific signal. These findings support the platform as an analytically characterized, peptide-level EBV serology tool for translational research.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Google DeepMind Blog Nov 25, 2025

AlphaFold: Five years of impact

Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.