High-throughput peptide array analysis and computational techniques for serological profiling of flavivirus infections: Implications for diagnostics and vaccine development

IF 6.8 3区 医学 Q1 VIROLOGY Journal of Medical Virology Pub Date : 2024-09-18 DOI:10.1002/jmv.29923
Mauro Bombaci, Enrico Mario Alessandro Fassi, Andrea Gobbini, Davide Mileto, Irene Cassaniti, Elisa Pesce, Emanuele Casali, Alessandro Mancon, Jose’ Sammartino, Alessandro Ferrari, Elena Percivalle, Romualdo Grande, Edoardo Marchisio, Maria Rita Gismondo, Sergio Abrignani, Fausto Baldanti, Giorgio Colombo, Renata Grifantini
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Abstract

Arthropod-borne viruses, such as dengue virus (DENV), pose significant global health threats, with DENV alone infecting around 400 million people annually and causing outbreaks beyond endemic regions. This study aimed to enhance serological diagnosis and discover new drugs by identifying immunogenic protein regions of DENV. Utilizing a comprehensive approach, the study focused on peptides capable of distinguishing DENV from other flavivirus infections through serological analyses. Over 200 patients with confirmed arbovirus infection were profiled using high-density pan flavivirus peptide arrays comprising 6253 peptides and the computational method matrix of local coupling energy (MLCE). Twenty-four peptides from nonstructural and structural viral proteins were identified as specifically recognized by individuals with DENV infection. Six peptides were confirmed to distinguish DENV from Zika virus (ZIKV), West Nile virus (WNV), Yellow Fever virus (YFV), Usutu virus (USUV), and Chikungunya virus (CHIKV) infections, as well as healthy controls. Moreover, the combination of two immunogenic peptides emerged as a potential serum biomarker for DENV infection. These peptides, mapping to highly accessible regions on protein structures, show promise for diagnostic and prophylactic strategies against flavivirus infections. The described methodology holds broader applicability in the serodiagnosis of infectious diseases.

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用于黄病毒感染血清学分析的高通量肽阵列分析和计算技术:对诊断和疫苗开发的影响
登革热病毒(DENV)等节肢动物传播的病毒对全球健康构成重大威胁,仅登革热病毒每年就感染约 4 亿人,并在流行地区以外引起疫情爆发。这项研究旨在通过鉴定登革热病毒的免疫原性蛋白区,加强血清学诊断并发现新药。这项研究采用了一种综合方法,重点研究能够通过血清学分析将 DENV 与其他黄病毒感染区分开来的多肽。利用由6253个肽段组成的高密度泛黄病毒肽段阵列和局部耦合能矩阵(MLCE)计算方法,对200多名确诊虫媒病毒感染的患者进行了分析。从非结构性和结构性病毒蛋白中鉴定出了 24 个肽段,这些肽段被 DENV 感染者特异性识别。有六种肽被证实能将 DENV 与寨卡病毒 (ZIKV)、西尼罗河病毒 (WNV)、黄热病毒 (YFV)、乌苏图病毒 (USUV) 和基孔肯雅病毒 (CHIKV) 感染者以及健康对照组区分开来。此外,两种免疫原性肽的组合成为了 DENV 感染的潜在血清生物标记物。这些肽映射到蛋白质结构上的高易接近区域,有望用于黄病毒感染的诊断和预防策略。所述方法在传染病的血清诊断中具有更广泛的适用性。
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来源期刊
Journal of Medical Virology
Journal of Medical Virology 医学-病毒学
CiteScore
23.20
自引率
2.40%
发文量
777
审稿时长
1 months
期刊介绍: The Journal of Medical Virology focuses on publishing original scientific papers on both basic and applied research related to viruses that affect humans. The journal publishes reports covering a wide range of topics, including the characterization, diagnosis, epidemiology, immunology, and pathogenesis of human virus infections. It also includes studies on virus morphology, genetics, replication, and interactions with host cells. The intended readership of the journal includes virologists, microbiologists, immunologists, infectious disease specialists, diagnostic laboratory technologists, epidemiologists, hematologists, and cell biologists. The Journal of Medical Virology is indexed and abstracted in various databases, including Abstracts in Anthropology (Sage), CABI, AgBiotech News & Information, National Agricultural Library, Biological Abstracts, Embase, Global Health, Web of Science, Veterinary Bulletin, and others.
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