Identification of reactive Borrelia burgdorferi peptides associated with Lyme disease

Borrelia burgdorferi, the agent of Lyme disease, is estimated to cause >400,000 annual infections in the United States. Serology is the primary laboratory method to support the diagnosis of Lyme disease, but current methods have intrinsic limitations that require alternative approaches or targets. We used a high-density peptide array that contains >90,000 short overlapping peptides to catalogue immunoreactive linear epitopes from >60 primary antigens of B. burgdorferi. We then pursued a machine learning approach to identify immunoreactive peptide panels that provide optimal Lyme disease serodiagnosis and can differentiate antibody responses at various stages of disease. We examined 226 serum samples from the Lyme Biobank and the National Institutes of Health that included sera from 110 individuals diagnosed with Lyme disease, 31 probable cases from symptomatic individuals, and 85 healthy controls. Cases were grouped based on disease stage and presentation and included individua..., , , # Identification of reactive Borrelia burgdorferi peptides associated with Lyme disease

[https://doi.org/10.5061/dryad.8cz8w9h0c](https://doi.org/10.5061/dryad.8cz8w9h0c)

## Description of the data and file structure

The Tick-Borne Disease Serochip (TBD-Serochip) is a slide-based peptide array used to catalog antibody responses to tick-borne pathogens. For each antigen selected for inclusion on the array, all protein sequences available as of October 2016 were downloaded from the NCBI protein database, aligned, and used to design 12-mer peptides that tile each protein with an 11-aa overlap to the preceding peptide in a sliding window pattern. Our prototype version of the TBD-Serochip included approximately 170,000 12-mer peptides per subarray and contained 12-mer peptides designed from antigenic sequences of eight tick-borne pathogens present in North America. For B. burgdorferi, this included 62 different antigens (including all paralogs) that are known to elicit an antibody respons...,

伯氏疏螺旋体（Borrelia burgdorferi）是莱姆病的致病病原体，据估算每年在美国引发超过40万例感染。血清学检测是当前支持莱姆病诊断的主流实验室方法，但现有检测手段存在固有局限性，亟需开发替代检测策略或靶点。本研究采用包含超9万个短重叠肽段的高密度肽芯片（peptide array），对伯氏疏螺旋体60余种主要抗原的免疫反应性线性表位进行系统性编目与鉴定。随后我们采用机器学习（machine learning）方法，筛选出可实现最优莱姆病血清学诊断、并能区分疾病不同阶段抗体应答特征的反应性肽段组合。我们共检测了来自莱姆生物样本库（Lyme Biobank）与美国国立卫生研究院（National Institutes of Health, NIH）的226份血清样本，其中包含110例确诊莱姆病患者血清、31例有症状疑似病例血清以及85例健康对照血清。研究对象按疾病分期与临床表现进行分组，涵盖……
# 《与莱姆病相关的伯氏疏螺旋体反应性肽段的鉴定》
[https://doi.org/10.5061/dryad.8cz8w9h0c](https://doi.org/10.5061/dryad.8cz8w9h0c)

## 数据与文件结构说明
蜱传疾病血清芯片（Tick-Borne Disease Serochip, TBD-Serochip）是一种基于玻片的肽芯片，用于系统性编目蜱传病原体的抗体应答特征。针对芯片上纳入的每种抗原，我们于2016年10月从NCBI蛋白质数据库（NCBI Protein Database）下载其全部可用蛋白序列，经多序列比对后，设计以11个氨基酸为重叠步长、以滑动窗口方式覆盖整条蛋白序列的12聚体肽段。本研究使用的TBD-Serochip原型每个子阵列包含约17万个12聚体肽段，其序列源自北美地区8种蜱传病原体的抗原编码序列。针对伯氏疏螺旋体，该芯片涵盖了62种已知可诱导抗体应答的抗原（包含所有旁系同源蛋白）……