Molecular analysis of microbial community structure in open ponds for algal biodiesel production
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Abstract
Algal farming in open ponds can be done with simple technology and low capital expenditures. However, in relatively uncontrolled ponds the likelihood that microbial contamination that could affect algal yield is high. We are interested in understanding natural contamination as an ecological process to better control the trajectory of microbial community assembly. Nannochloropsis salina was grown in small outdoor open ponds (100 L; 10 cm deep) through three cycles of batch culture using a simplified brackish growth medium. Time-course samples were monitored via pigment analyses, and direct microscopic counts. Extracted metagenomic DNA was subjected to touchdown PCR for amplification of 16S rRNA genes with universal bacterial primers and 18S rRNA genes with algae-specific primers, both using GC-clamps. PCR products of similar lengths were separated by melting characteristics using denaturing gradient gel electrophoresis (DGGE). Contamination of the open ponds by algae was not observed over three two-week batch culture cycles, however, contamination by bacteria was observed. Salinity and pH were likely major factors behind limited algal contamination. DGGE bands from bacterial 16S rRNA gene amplifications were excised, eluted, reamplified, and sequenced, revealing a diverse consortium of bacteria including Aeromonas, Loktanella, Marinobacter, and Pseudomonas. Most of the bands were seen on third and fourth day of the batch culture. As the culture progressed, the number of bands seen with DGGE decreased. Band migration was measured and relative front values were calculated. A 2% overall window was used to analyze how closely one band is associated with another. Overall there were 22 individual bands designated as novel based on relative front values. A dendrogram of relatedness was created to compare time-course samples from triplicate ponds, supporting the conclusion that community assembly was more of stochastic than deterministic in nature.