AUTHOR=Fan Yiling , Wang Shujuan , Song Minghui , Zhou Liangliang , Liu Chengzhi , Yang Yan , Yu Shuijing , Yang Meicheng 

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

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2023.1270760

DOI=10.3389/fmicb.2023.1270760

ISSN=1664-302X

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 5.6×10 2 CFU of BCC bacteria in pure culture or 1.2 pg of BCC bacteria genomic DNA within 30 minutes. 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.