Bacterial diversity as a biomarker of soil health

Identification and quantification of phylogenetically defined bacterial populations in the environment are often performed using molecular tools targeting 16S rRNA. Fluorescence in situ hybridization has been used to monitor the expression and processing of pre16S rRNA. To expand this approach, reverse transcription of total RNA using primer S-D-Bact-0338-a-A-18 was optimized and detected by denaturing high performance liquid chromatography (DHPLC). The relative abundance of the precursor (pre) compared to the abundance of mature 16S rRNA was shown to be a sensitive indicator of the physiologic state of pure cultures. The assay was also used to differentiate among pre 16S rRNA levels with mixed pure cultures, as well as to examine the response of a mixed activated sludge culture exposed to fresh growth medium and the antibiotic chloramphenicol. It was further optimized to study soil bacterial population. Several soil enrichment media and incubation times were tested to increase the pre16S rRNA levels.

The results demonstrated that this was a sensitive and reliable method with a detection limit of 10 ng of single-stranded DNA or 0.75 grams of soil samples. Signature bacterial population including Actinobacteria and Bacillus by pre16S rRNA libraries was identified while Proteobatceria was absent under pyrene and Cr (VI) contamination. Comparison of pre16S rRNA and mature 16S rRNA clone libraries showed ribosome genesis was a sensitive indicator for pyrene and chromium contamination. Pre16S rRNA levels were significantly decreased compared with mature 16S rRNA levels in LTU soil samples with varying degrees of contaminate.

These results demonstrated that active bacterial species can be assessed by pre16S rRNA levels. A negative correlation between active bacterial diversity and contamination levels has also been found.

This method was the first demonstration of monitor the diversity of the metabolically – active fraction of the soil bacterial community in soil systems. It provides a better understanding of active bacterial structure in soil systems. We envision that this method could be applied to remediation efforts in the field.