Specific biomarker mining and rapid detection of Burkholderia cepacia complex by recombinase polymerase amplification

Yiling Fan; Shujuan Wang; Minghui Song; Liangliang Zhou; Chengzhi Liu; Yan Yang; Shuijing Yu; Meicheng Yang

doi:10.3389/fmicb.2023.1270760

Specific biomarker mining and rapid detection of Burkholderia cepacia complex by recombinase polymerase amplification

Front Microbiol. 2023 Sep 14:14:1270760. doi: 10.3389/fmicb.2023.1270760. eCollection 2023.

Authors

Yiling Fan^{1

2}, Shujuan Wang², Minghui Song², Liangliang Zhou³, Chengzhi Liu^{4

5}, Yan Yang², Shuijing Yu³, Meicheng Yang^{1

6}

Affiliations

¹ China State Institute of Pharmaceutical Industry, Shanghai, China.
² National Medical Products Administration Key Laboratory for Testing Technology of Pharmaceutical Microbiology, Shanghai Quality Inspection and Testing Center for Innovative Biological Products, Shanghai Institute for Food and Drug Control, Shanghai, China.
³ College of Resource and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, China.
⁴ Department of Infectious Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
⁵ Hangzhou Digital-Micro Biotech Co., Ltd., Hangzhou, China.
⁶ Shanghai Food and Drug Packaging Material Control Center, Shanghai, China.

Abstract

Objective: To mine specific proteins and their protein-coding genes as suitable molecular biomarkers for the Burkholderia cepacia Complex (BCC) bacteria detection based on mega analysis of microbial proteomic and genomic data comparisons and to develop a real-time recombinase polymerase amplification (rt-RPA) assay for rapid isothermal screening for pharmaceutical and personal care products.

Methods: We constructed an automatic screening framework based on Python to compare the microbial proteomes of 78 BCC strains and 263 non-BCC strains to identify BCC-specific protein sequences. In addition, the specific protein-coding gene and its core DNA sequence were validated in silico with a self-built genome database containing 158 thousand bacteria. The appropriate methodology for BCC detection using rt-RPA was evaluated by 58 strains in pure culture and 33 batches of artificially contaminated pharmaceutical and personal care products.

Results: We identified the protein SecY and its protein-coding gene secY through the automatic comparison framework. The virtual evaluation of the conserved region of the secY gene showed more than 99.8% specificity from the genome database, and it can distinguish all known BCC species from other bacteria by phylogenetic analysis. Furthermore, the detection limit of the rt-RPA assay targeting the secY gene was 5.6 × 10² CFU of BCC bacteria in pure culture or 1.2 pg of BCC bacteria genomic DNA within 30 min. It was validated to detect <1 CFU/portion of BCC bacteria from artificially contaminated samples after a pre-enrichment process. The relative trueness and sensitivity of the rt-RPA assay were 100% in practice compared to the reference methods.

Conclusion: The automatic comparison framework for molecular biomarker mining is straightforward, universal, applicable, and efficient. Based on recognizing the BCC-specific protein SecY and its gene, we successfully established the rt-RPA assay for rapid detection in pharmaceutical and personal care products.

Keywords: Burkholderia cepacia complex; mining; molecular marker; rapid detection; recombinase polymerase amplification; secY gene.