Automated high-throughput characterization of microbial metabolites and species using array ballpoint electrospray ionization technique.

ABSTRACT

RATIONALE Microbial metabolites are widely used in agriculture, food, environment, and medicine. However, there is a lack of high-throughput, nonclogging, and simple methods for the identification of microbial metabolites and their subspecies using ambient mass spectrometry (MS). Here, we proposed a method for analyzing the microbial metabolites and identifying their species using the array ballpoint electrospray ionization (aBPESI) technique. METHODS: The previously developed BPESI was combined with the array analysis technique to form a high-throughput analysis technique called aBPESI. The bacteria cultured on the plate medium were directly analyzed using MS with aBPESI. Principal component analysis-linear discriminant analysis (PCA-LDA) algorithm was used to analyze the different subspecies groups. RESULTS: The results showed that aBPESI was capable of completing a sample analysis within 30 s, and the level of metabolite detection was comparable to existing techniques. The accuracy of bacterial subspecies identification was 90% (Pseudomonas aeruginosa) and 100% (Serratia marcescens). CONCLUSIONS: A new high-throughput and robust MS technique aBPESI was proposed. It does not require sample pretreatment and greatly reduces the sample analysis time. aBPESI shows a strong ability in microbial analysis and is expected to be further applied in other research fields.