Bayesian-integrated microbial forensics

Abstract

In the aftermath of the 2001 anthrax letters, researchers have been exploring ways to predict the production environment of unknown-source microorganisms. Culture medium, presence of agar, culturing temperature, and drying method are just some of the broad spectrum of characteristics an investigator might like to infer. The effects of many of these factors on microorganisms are not well understood, but the complex way in which microbes interact with their environments suggests that numerous analytical techniques measuring different properties will eventually be needed for complete characterization. In this work, we present a Bayesian statistical framework for integrating disparate analytical measurements. We illustrate its application to the problem of characterizing the culture medium of Bacillus spores using three different mass spectral techniques. The results of our study suggest that integrating data in this way significantly improves the accuracy and robustness of the analyses.

FIG. 1.

SIMS metal profiles of B. subtilis 49760 in different growth media.

FIG. 2.

Carbon and nitrogen stable iosotope ratios of Bacillus spores (multiple species) in common media. Col A, Columbia agar; Fox A and B, modified SSMA and SSMB.

FIG. 3.

ESI MS agar profiles of B. subtilis 49760 in agar-based medium. Ions marked by an asterisk are due to digested agar. The arrows indicate the progression of agar ions through three tandem mass spectral analyses. Only the MS3 329 ion is used as an indicator of the presence of agar in this study.

FIG. 4.

DAG for integrated characterization of culture media. The nodes indicate different steps in the process, while the arrows indicate causal relationships between the nodes. IR, isotope ratio.

FIG. 5.

Box plots of SIMS Zn and Cu intensities (Int.) for B. subtilis spores in multiple media. The center lines through the boxes indicate the median values. The heights of the boxes indicate the spread of 75% of the measurements. The dotted lines spanning the plots show the critical threshold (thresh) used in the Bayesian network.

FIG. 6.

Box plots of the ESI-MS MS3 329 m/z ion intensities (Int.) for multiple Bacillus species in multiple culture media. The center lines through the boxes indicate the median values. The heights of the boxes indicate the spread of 75% of the measurements. The dotted lines spanning the plots show the critical threshold used in the Bayesian network.

FIG. 7.

Nitrogen and carbon isotope ratios of B. subtilis spores produced in different media identified by C/N source. Agar- and broth-grown samples are included in the plot without being explicitly indicated.

FIG. 8.

Screenshot of Bayesian network applied to data on B. subtilis spores grown in GA.

FIG. 9.

Illustration of Bayesian network on data from B. subtilis spores grown in LDB.

FIG. 10.

Illustration of Bayesian network on data from B. subtilis spores grown in TSB with ESI MS data omitted.