Analysis of Microbial Mixtures by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Karen L. Wahl,* Sharon C. Wunschel, Kristin H. Jarman, Nancy B. Valentine, Catherine E. Petersen, Mark T. Kingsley, Kimberly A. Zartolas, † and Adam J. Saenz † Pacific Northwest National Laboratory, Richland, Washington 99352 Many different laboratories are currently developing mass- spectrometric techniques to analyze and identify micro- organisms. However, minimal work has been done with mixtures of bacteria. To demonstrate that microbial mixtures could be analyzed by matrix-assisted laser de- sorption/ 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 5 0 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 -1 2 2 3 ). The samples were analyzed by MALDI- MS with automated data extraction and analysis algo- rithms 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 chal- lenging for the current algorithms, especially in dif- ferentiating 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. Matrix-assisted laser desorption/ ionization mass spectrometry (MALDI -MS) has been used to analyze intact, cultured micro- organisms with minimal sample handling. 2,3,4 Two recent review articles, which include the capabilities and current limitations that need to be addressed, 5,6 provide an excellent overview of this emerging research field. The MALDI-MS technique for identifying biomolecules provides rapid analysis time ( <1 min/ sample analysis), low sample-volume requirements ( <1 μL of fluid), and the highly selective nature of mass spectrometric analysis based on molecular weights. The m/ z values for mass spectral peaks and the patterns with which they are observed can provide very specific and unbiased analysis, because they indicate molecular weights of true components of the sample. Bacterial cells can be identified by comparing MALDI-MS spectra obtained from cul- tured bacterial cells and simple microbial mixtures against a library of known MALDI-MS spectral fingerprints obtained from intact bacterial cells 1 or from comparison with the proteomic database. 7 One main advantage of this MALDI-MS technique over many other bacterial analysis methods is the generic capability to classify and identify bacteria. A large number of targets can be analyzed simultaneously and do not require an a priori selection of specific antibody or primer for identification. It may be possible that genetically altered microorganisms can at least be classified with their nearest neighbors in the database and, therefore, direct further, more specific testing. We previously reported our initial blind study 1 designed to determine if MALDI-MS could be used to identify bacterial species from pure cultures or simple microbial mixtures with automated data-analysis algorithms. Data extraction and visualization algo- rithms developed in our laboratory were used to generate MALDI- MS fingerprints from replicate spectra. Further development of our algorithms and expansion of our bacterial fingerprint library warranted another blind study to further verify this approach for bacterial identification with more complex samples and an extended database. Nine different bacterial species currently in the MALDI-MS fingerprint library and one “unknown control” that was not in the library were chosen for this study. They were used to generate 50 simulated mixed bacterial cultures, similar to that done for the initial blind study presented previously. 1 Three of the two-component mixtures from the original study were repli- cated and reevaluated in the present work. Twenty-eight samples contained two bacterial species, and 18 samples contained three bacterial species. In addition, a four-component mixture was replicated four times to evaluate reproducibility in analyzing a “complex” sample. The data were evaluated at different bacterial classification levels to determine the limits of the current analysis algorithms. The original blind study was performed with a database containing only five organisms, each representing a different species, and thus, species level and strain level identifica- † Current address: Dartmouth College, MML Building, Hanover, NH. (1) 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. (2) Claydon, M. A.; Davey, S. N.; Edwards-Jones, V.; Gordon, D. B. Nature Biotechnol. 1996 , 14, 1584-1586. (3) Holland, R. D.; Wilkes, J. G.; Rafii, F.; Sutherland, J.; Persons, C.; Voorhees, K.; Lay, J. O., Jr. Rapid Commun. Mass Spectrom. 1996 , 10, 1227-1232. (4) Krishnamurthy, T.; Ross, P. L. Rapid Commun. Mass Spectrom. 1996 , 10, 1992-1996. (5) Fenselau, C.; Demirev, P. A. Mass Spectrom. Rev. 2001 , 20 (4), 157-171. (6) Lay, J. O., Jr. Mass Spectrom. Rev. 2001 , 20 (4), 172-194. (7) Demirev, P. A.; Ho. Y.; Ryzhov, V.; Fenselau, C. Anal. Chem. 1999 , 71 ( 14) , 2732-2738. Anal. Chem. 2002, 74, 6191-6199 10.1021/ac0203847 CCC: $22.00 © 2002 American Chemical Society Analytical Chemistry, Vol. 74, No. 24, December 15, 2002 6191 Published on Web 11/15/2002