An algorithm for bacterial identification using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry is being developed. This mass spectral fingerprint comparison algorithm is fully automated and statistically based, providing objective analysis of samples to be identified. Based on extraction of reference fingerprint ions from test spectra, this approach should lend itself well to real-world applications where samples are likely to be impure. This algorithm is illustrated using a blind study. In the study, MALDI-MS fingerprints for Bacillus atrophaeus ATCC 49337, Bacillus cereus ATCC 14579T, Escherichia coli ATCC 33694, Pantoea agglomerans ATCC 33243, and Pseudomonas putida F1 are collected and form a reference library. The identification of test samples containing one or more reference bacteria, potentially mixed with one species not in the library (Shewanella alga BrY), is performed by comparison to the reference library with a calculated degree of association. Out of 60 samples, no false positives are present, and the correct identification rate is 75%. Missed identifications are largely due to a weak B. cereus signal in the bacterial mixtures. Potential modifications to the algorithm are presented and result in a higher than 90% correct identification rate for the blind study data, suggesting that this approach has the potential for reliable and accurate automated data analysis of MALDI-MS.

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Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) was used to demonstrate the reproducibility of bacterial spectra collected on different days. The reproducibility of analysis by MALDI-MS of intact Escherichia coli and Bacillus atrophaeus is presented as a replicate culture study in which spectra were collected on ten different occasions over a three-month period and by two different operators. The analysis resulted in the detection of specific biomarkers in the m/z 2000-20 000 range. Some of the peaks in the Escherichia coli spectra are identified by comparison with other published work. All of the spectra obtained are reproducible over the course of the experiment, but operator variability does exist. The Escherichia coli spectra show operator variability while the Bacillus atrophaeus spectra do not. This work demonstrates the utility of MALDI in obtaining consistent spectra from bacteria over a period of time.

Many different laboratories are currently developing mass-spectrometric techniques to analyze and identify microorganisms. However, minimal work has been done with mixtures of bacteria. To demonstrate that microbial mixtures could be analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), mixed bacterial cultures were analyzed in a double-blind fashion. Nine different bacterial species currently in our MALDI-MS fingerprint library were used to generate 50 different simulated mixed bacterial cultures similar to that done for an initial blind study previously reported (Jarman, K. H.; Cebula, S. T.; Saenz, A. J.; Petersen, C. E.; Valentine, N. B.; Kingsley, M. T.; Wahl, K. L. Anal. Chem. 2000, 72, 1217-1223). The samples were analyzed by MALDI-MS with automated data extraction and analysis algorithms developed in our laboratory. The components present in the sample were identified correctly to the species level in all but one of the samples. However, correctly eliminating closely related organisms was challenging for the current algorithms, especially in differentiating Serratia marcescens, Escherichia coli, and Yersinia enterocolitica, which have some similarities in their MALDI-MS fingerprints. Efforts to improve the specificity of the algorithms are in progress.