预期建模和估计在大型食品传播病原体基因组数据库中的流行病学信息匹配率
Lanlan Yin1, James B Pettengill2
1Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, U. S. Food and Drug Administration, College Park, MA, USA.
BMC research notes
|July 9, 2024
概括
基因组数据库通过匹配临床和非临床病原体分离物来帮助食品安全. 填充更多非临床数据的数据库可以改善病原体检测和公共卫生监测.
科学领域:
- 食品安全 食品安全
- 基因组流行病学基因组流行病学
- 公共卫生微生物学
背景情况:
- 基因组数据库对于公共卫生至关重要,特别是在食品安全方面.
- 这些数据库包含来自临床 (患者) 和非临床 (环境) 来源的病原体分离物.
- 临床和非临床分离物之间的遗传匹配表明潜在的食物传播疾病爆发.
研究的目的:
- 在主要的基因组数据库中调查临床和非临床分离物之间的匹配率.
- 在NCBI的病原体检测项目中分析影响这些匹配率的因素.
- 以基因组数据为基础,为公共卫生监测策略提供信息.
主要方法:
- 在Listeria monocytogenes,大肠杆菌和沙门氏菌数据库中的匹配率的分析.
- 在研究中包括较小的Cronobacter数据库.
- 逻辑回归建模以根据数据库特征预测匹配率.
主要成果:
- 目前的匹配率:单细胞菌 (33%),沙门氏菌 (46%),大肠杆菌 (7%).
- 匹配率受到生物多样性,数据库大小和非临床样本比例的影响.
- 后勤回归模型在预测匹配率方面表现良好.
结论:
- 用非临床分离物填充基因组数据库对于有效的临床样本匹配至关重要.
- 这一策略有助于公共卫生官员优先考虑监测.
- 迫切需要扩大较小的新兴病原体数据库,比如Cronobacter sakazakii.
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