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

Abstract

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. 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. 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). 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.