Bacterial Community Structure and Physiological State within an Industrial Phenol Bioremediation System

Abstract

The structure of bacterial populations in specific compartments of an operational industrial phenol remediation system was assessed to examine bacterial community diversity, distribution, and physiological state with respect to the remediation of phenolic polluted wastewater. Rapid community fingerprinting by PCRbased denaturing gradient gel electrophoresis (DGGE) of 16S rDNA indicated highly structured bacterial communities residing in all nine compartments of the treatment plant and not exclusively within the Vitox biological reactor. Whole-cell targeting by fluorescent in situ hybridization with specific oligonucleotides (directed to the ␣, ␤ and ␥ subclasses of the class Proteobacteria [␣-, ␤-, and ␥-Proteobacteria, respectively], the Cytophaga-Flavobacterium group, and the Pseudomonas group) tended to mirror gross changes in bacterial community composition when compared with DGGE community fingerprinting. At the whole-cell level, the treatment compartments were numerically dominated by cells assigned to the Cytophaga-Flavobacterium group and to the ␥-Proteobacteria. The ␣ subclass Proteobacteria were of low relative abundance throughout the treatment system whilst the ␤ subclass of the Proteobacteria exhibited local dominance in several of the processing compartments. Quantitative image analyses of cellular fluorescence was used as an indicator of physiological state within the populations probed with rDNA. For cells hybridized with EUB338, the mean fluorescence per cell decreased with increasing phenolic concentration, indicating the strong influence of the primary pollutant upon cellular rRNA content. The ␥ subclass of the Proteobacteria had a ribosome content which correlated positively with total phenolics and thiocyanate. While members of the Cytophaga-Flavobacterium group were numerically dominant in the processing system, their abundance and ribosome content data for individual populations did not correlate with any of the measured chemical parameters. The potential importance of the ␥-Proteobacteria and the Cytophaga-Flavobacteria during this bioremediation process was highlighted.

Impact of Transgenic Tobacco on Trinitrotoluene (TNT) Contaminated Soil Community

“…Genomic DNA (gDNA) was extracted directly from soil using the Ultra Clean Soil DNA Isolation Kit (Mo Bio Laboratories, Inc., Solana Beach, CA) and used as the template in polymerase chain reaction (PCR) to amplify a fragment of the 16S rDNA as described by Whiteley and Bailey (26). The primers used for PCR (GC338F (5′ -CGC CCG CCG CGC CCC CGC CCC GGC CCG CCG CCC CCG CCC ACT CCT ACG GGA GGC AGC -3′) and 530R (5′ -GTA TTA CCG CGG CTG CTG -3′) yielded an amplicon corresponding to bases 338 to 530 (Escherichia coli numbering) of the bacterial 16S rDNA with a GC clamp.…”

“…DGGE analysis was performed as described by Whiteley and Bailey (26). Band profiling was performed using Scion Imaging for Windows Software (Scion Corporation, Frederick, MD) and dendograms were constructed for comparison of DGGE samples by the Pearson Correlation method.…”

Importance of rare and abundant populations for the structure and functional potential of freshwater bacterial communities

“…The first reaction of the meta pathway is started by catechol 2, 3-dioxygenases (coded by the xylE genes). Although microbial bioremediation is increasingly implemented, information on the diversity and functionality of the remediating communities is scarce (Whiteley & Bailey 2000), and little is known about the capacity of natural aquatic microbial communities to degrade aromatic compounds.…”

An Overview of Different Techniques on the Microbial Community Structure, and Functional Diversity of Plant Growth Promoting Bacteria

“…Theoretically, DGGE separates DNA with one base-pair difference (Miller et al, 1999) and TGGE uses the same principle as that of DGGE except that the gradient is temperature based rather than that of chemical denaturants. DGGE/TGGE has been used to assess the diversity of bacteria and fungi in the rhizosphere (Smalla et al, 2001), caused by changes of nutrient addition (Iwamoto et al, 2000) and addition of anthropogenic chemicals (Whiteley and Bailey, 2000). The partial community level fingerprints derived from DGGE/TGGE banding patterns have been applied for diversity studies based on intensity and number of the DNA bands between treatments.…”