Application of next-generation sequencing for detectingcontamination in veterinary vaccines.

Abstract

Ensuring the safety and efficacy of veterinary vaccines requires reliable methods for detecting microbial contamination, particularly fromspecies, which pose a significant risk in cell-culture-derived vaccines. In the Republic of Korea, polymerase chain reaction (PCR) is predominantly used fortesting due to its faster turnaround compared to culture-based methods. However, in combination with vaccines containingand classical swine fever virus, PCR is rendered ineffective because of cross-reactivity betweenuniversal primers and, resulting in non-specific amplification. This limitation necessitates reliance on the labor-intensive culture method, underscoring the need for more accurate and efficient alternatives. This study aimed to develop and validate next-generation sequencing (NGS)-based methods for detectingcontamination in veterinary vaccines and to compare their performance with that of PCR. Five species, including(genus) and fourspecies-,,, and-were spiked into samples containing, a common vaccine component. Two NGS-based approaches were evaluated: (1) a reference-mapping method incorporating two-step alignment andassembly, and (2) a 16S rRNA-based metabarcoding analysis using DADA2 and Qiime2. The reference-mapping method effectively filtered non-specific reads and accurately reconstructed-derived contigs, whereas the metabarcoding approach enabled taxonomic profiling with quantitative resolution. The detection limits of NGS-based methods were substantially lower than those of PCR, demonstrating improvements of up to 100-fold depending on the species. Notably, omission of the initial mapping step resulted in excessive non-specific contig formation, highlighting the importance of the dual-step reference-mapping strategy. Although metabarcoding provided valuable abundance data, it was more prone to non-specific hits due to limited read overlap. In conclusion, the reference-mapping method demonstrated superior sensitivity, specificity, and quantification compared to both conventional PCR and metabarcoding, supporting its use as a robust tool for vaccine quality control. Implementing NGS-based detection methods could significantly enhance the safety and effectiveness of veterinary vaccines, ultimately enhancing vaccine quality control.