DGGE with genomic DNA: Suitable for detection of numerically important organisms but not for identification of the most abundant organisms

Identification of all important community members as well as of the numerically dominant members of a community are key aspects of microbial community analysis of bioreactor samples. A systematic study was conducted with artificial consortia to test whether denaturing gradient gel electrophoresis (DGCE) is a reliable technique to obtain such community data under conditions where results would not be affected by differences in DNA extraction efficiency from cells. A total of 27 consortia were established by mixing DNA extracted from Escherichia coli K12, Burkholderia cepacia and Stenotrophomonas maltophilia in different proportions. Concentrations of DNA of single organisms in the consortia were either 0.04, 0.4 or 4 ng/mu l. DGGE-PCR of genomic DNA with primer sets targeted at the V3 and V6-V8 regions of the 16S rDNA failed to detect the three community members in only 7% of consortia, but provided incorrect information about dominance or co-dominance for 85% and 89% of consortia with the primer sets for the V6-V8 and V3 regions, respectively. The high failure rate in detection of dominant B. cepacia with the primers for the V6-V8 region was attributable to a single nucleoticle primer mismatch in the target sequences of both, the forward and reverse primer. Amplification bias in PCR of E. coli and S. maltophilia for the V6-V8 region and for all three organisms for the V3 region occurred due to interference of genomic DNA in PCR-DGGE, since a nested PCR approach, where PCR-DGGE was started from mixtures of 16S rRNA genes of the organisms, provided correct information about the relative abundance of original DNA in the sample. Multiple bands were not observed in pure culture amplicons produced with the V6-V8 primer pair, but pure culture V3 DGGE profiles of E. coli, S. maltophilia and B. cepacia contained 5, 3 and 3 bands, respectively. These results demonstrate DGGE was suitable for identification of all important community members in the three-membered artificial consortium, but not for identification of the dominant organisms in this small community. Multiple DGGE bands obtained for single organisms with the V3 primer pair could greatly confound interpretation of DGGE profiles. (C) 2008 Elsevier Ltd. All rights reserved.

Early Changes in Gene Expression Induced by Tobacco Smoke: Evidence for the Importance of Estrogen within Lung Tissue

Lung cancer is the leading cause of cancer deaths in the United States, surpassing breast cancer as the primary cause of cancer-related mortality in women. The goal of the present study was to identify early molecular changes in the lung induced by exposure to tobacco smoke and thus identify potential targets for chemoprevention. Female A/J mice were exposed to either tobacco smoke or HEPA-filtered air via a whole-body exposure chamber (6 h/d, 5 d/wk for 3, 8, and 20 weeks). Gene expression profiles of lung tissue from control and smoke-exposed animals were established using a 15K cDNA microarray. Cytochrome P450 1b1, a phase I enzyme involved in both the metabolism of xenobiotics and the 4-hydroxylation of 17 beta-estradiol (E(2)), was modulated to the greatest extent following smoke exposure. A panel of 10 genes were found to be differentially expressed in control and smoke-exposed lung tissues at 3, 8, and 20 weeks (P < 0.001). The interaction network of these differentially expressed genes revealed new pathways modulated by short-term smoke exposure, including estrogen metabolism. In addition, E(2) was detected within murine lung tissue by gas chromatography-coupled mass spectrometry and immunohistochemistry. Identification of the early molecular events that contribute to lung tumor formation is anticipated to lead to the development of promising targeted chemopreventive therapies. In conclusion, the presence of E2 within lung tissue when combined with the modulation of cytochrome P450 1b1 and other estrogen metabolism genes by tobacco smoke provides novel insight into a possible role for estrogens in lung cancer. Cancer Prev Res; 3(6); 707-17. (C) 2010 AACR.