基于高通量测序的生物制品外源因子污染检测工具Kraken2与Sylph的性能比较

陈威廉; 李峰; 郑周沁; 沈泓; 陈欢

doi:10.13748/j.cnki.issn1007-7693.20251511

基于高通量测序的生物制品外源因子污染检测工具Kraken2与Sylph的性能比较

Performance Comparison of Kraken2 and Sylph Tools for Detecting Adventitious Agent Contamination in Biological Products Based on Next-Generation Sequencing

摘要

摘要:
目的评估高通量测序技术(next-generation sequencing，NGS)检测生物制品中病毒、细菌及真菌等外源因子污染的应用潜力，系统比较生物信息学工具Kraken2与Sylph的检测性能差异。
方法以市售人血白蛋白为基质，梯度浓度加标乙肝病毒(hepatitis B virus，HBV)、副铜绿假单胞菌(Pseudomonas paraeruginosa)、斯皮宰曾氏芽孢杆菌(Bacillus spizizenii)及巴西曲霉(Aspergillus brasiliensis)，构建不同浓度污染样本进行高通量测序，分别采用Kraken2和Sylph进行物种分类和丰度分析，评价2种工具的检测限和检测灵敏度，并比较其非目标物种检出情况。
结果在0.5M(500000条)序列的数据量下，Kraken2工具对HBV的检测限为1×10⁵ copies·mL⁻¹，对P. paraeruginosa、B. spizizenii和A. brasiliensis的检测限分别为1、100、100 CFU·mL⁻¹。Sylph工具对HBV的检测限为1×10⁷ copies·mL⁻¹，对P. paraeruginosa、B. spizizenii和A. brasiliensis的检测限分别为1×10⁴、1×10⁴、1×10⁵ CFU·mL⁻¹。阴性对照中检测到非目标物种。在多种数据量下，Kraken2工具对于HBV的检测限为1×10⁵ copies·mL⁻¹，对P. paraeruginosa、B. spizizenii和A. brasiliensis的检测限分别为1、10、10 CFU·mL⁻¹。Sylph工具对HBV的检测限为1×10⁵ copies·mL⁻¹，对P. paraeruginosa、B. spizizenii和A. brasiliensis的检测限分别为100、1×10³、1×10⁴ CFU·mL⁻¹。
结论 Kraken2的检测灵敏度高于Sylph，但其检出的非目标物种也更多。总体来说，NGS技术可同步检测生物制品中的多类别外源因子。通过优化测序流程及结合多工具交叉验证策略，显著提升检测可靠性，NGS技术有望成为生物制品质控的有效手段。

Abstract:
OBJECTIVE To evaluate the application potential of next-generation sequencing(NGS) for detecting adventitious agent contamination, including viruses, bacteria, and fungi, in biological products and to systematically compare the detection performance of Kraken2 and Sylph.
METHODS Human serum albumin was used as the matrix and spiked with different concentrations of Hepatitis B virus(HBV), Pseudomonas paraeruginosa, Bacillus spizizenii and Aspergillus brasiliensis. The samples were subjected to NGS, and Kraken2 and Sylph were used for taxonomic classification and relative abundance analysis. The limits of detection and detection sensitivities of the 2 tools were evaluated, and their detection profiles for non-target taxa were compared.
RESULTS With a data volume of 0.5M(500000) sequences, the detection limit of Kraken2 for HBV was 1×10⁵ copies·mL⁻¹, and the detection limits for P. paraeruginosa, B. spizizenii and A. brasiliensis were 1, 100, 100 CFU·mL⁻¹, respectively. The detection limit for HBV using Sylph was 1×10⁷ copies·mL⁻¹. The detection limits for P. paraeruginosa, B. spizizenii and A. brasiliensis were 1×10⁴, 1×10⁴, 1×10⁵ CFU·mL⁻¹, respectively. Non-target taxa were detected in the negative controls. In various sequencing data volumes, the detection limit of Kraken2 for HBV was 1×10⁵ copies·mL⁻¹, and the detection limits for P. paraeruginosa, B. spizizenii and A. brasiliensis were 1, 10, 10 CFU·mL⁻¹, respectively. The detection limit for HBV using Sylph was 1×10⁵ copies·mL⁻¹. The detection limits for P. paraeruginosa, B. spizizenii and A. brasiliensis were 100, 1×10³, 1×10⁴ CFU·mL⁻¹, respectively.
CONCLUSION Kraken2 showed higher detection sensitivity than Sylph but also detected more non-target taxa. Overall, NGS technology can simultaneously detect multiple categories of adventitious agents in biological products. By optimizing the sequencing process and combining the multi-tool cross-validation strategy, the detection reliability is significantly improved. NGS technology is expected to become an effective means of quality control of biological products.

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