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Title: Soil Diversity Along a Forest Profile Using PCR-DGGE

Author
item THOMPSON, MEIKO - ALABAMA A&M UNIVERSITY
item MOSS, ELICA - ALABAMA A&M UNIVERSITY
item Ibekwe, Abasiofiok - Mark
item SENWO, ZACHARY - ALABAMA A&M UNIVERSITY
item TAYLOR, ROBERT - ALABAMA A&M UNIVERSITY

Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 10/20/2006
Publication Date: 11/12/2006
Citation: Thompson, M., Moss, E., Ibekwe, A.M., Senwo, Z., Taylor, R. 2006. Soil Diversity Along a Forest Profile Using PCR-DGGE. Soil Science Society of America Annual Meeting in Indianapolis, IN Nov 12-16, 2006. CD-ROM

Interpretive Summary:

Technical Abstract: Forest ecosystems are complex and involve diverse relationships between its biotic and abiotic components. As implementation of fire for restoration and conservation practices has increased, a vital need for quantitative metrics of the effects of fire on the ecosystem as a whole, including soil quality and function has also developed. Use of traditional molecular biological methods of soil microbial diversity is limited because of selective culture methods. These methods only account for a small fraction of soil microbial communities. Analysis of microbial nucleic acids extracted from soil samples is considered an emerging strategy for studying both the ecological fate and diversity of soils. For this study both traditional and non-traditional culture techniques were used to assess diversity. For nucleic determination, whole community DNA was extracted from soils in the William Bankhead National Forest using the UltraClean SOIL DNA Isolation Kit. Polymerase Chain Reaction (PCR) was performed using the DNA primers PRBA338f and PRUN518r located at the V3 region of the 16s rRNA genes of bacterioplankton, and denaturing gradient gel electrophoresis (DGGE) was used as a separation technique to qualify if there were difference along the horizon. Sequence analysis was completed with the Basic Local Alignment Search Tool database and PILEUP program. A complete random design (CRD) was used for statistical analysis. The soil samples were taken from each site in duplicate. Diversity was assessed using the Shannon Diversity Index. Results show that the majority of microbial diversity lay within the O, A, and upper B-horizons of the soil profile (top 0-15 cm).