The computational analysis described above identified putative microorganisms in mule deer tissue based on detection of proteinencoding transcriptional activity. Although the cDNA used in our analyses was derived from total RNA enriched for polyadenylated RNA, it retained a considerable amount of the abundant ribosomal RNA (rRNA). These sequences contribute to the 'no hits' category in Figure 1 and Table S2 . Bacterial rRNA derived from the same dataset can, therefore, be used to provide additional support for species identification. By classifying the rRNA-tags from each library using the RDP rRNA classifier tool [34, 35] (http://rdp.cme.msu.edu/) we increased the number of bacterial genera identified (see Fig. 2 for MD 257, Fig. S1 for MD 80228 and MD OCT-pool, and Table S4 ). Abiotrophia, which is a component of the normal oral and intestinal microbial commu-nity, was detected in six of the seven libraries; environmental bacteria such as Thermoanaerobacter, which is frequently found in hot springs, were detected in four of the seven samples. Other genera that were identified based on rRNA in at least two of the libraries were Actinomyces, Campylobacter and Mycoplasma. Of particular importance, rRNA-tags supported the presence of Helicobacter in the MD 257 library (Fig. 2) , of Acinetobacter, Escherichia, Pseudomonas, Salmonella, Shigella and Variovorax in the MD 80228 library, and of Shigella in the MD Bonner-pool library ( Fig. 1 and Fig. S1 , Tables S3 and S4).