Lemnaceae or duckweed is an aquatic plant that can be used to recover nutrients from wastewaters. The grown duckweed can be a good resource of proteins and starch, and utilized for the production of value-added products such as animal feed and fuel ethanol. In the last eleven years we have been working on growing duckweed on anaerobically treated swine wastewater and utilizing the duckweed for fuel ethanol production. Duckweed strains that grew well on the swine wastewater were screened in laboratory and greenhouse experiments. The selected duckweed strains were then tested for nutrient recovery under laboratory and field conditions. The rates of nitrogen and phosphorus uptake by the duckweed growing in the laboratory and field systems were determined in the study. The mechanisms of nutrient uptake by the duckweed and the growth of duckweed in a nutrient-limited environment have been studied. When there are nutrients (N and P) available in the wastewater, duckweed takes the nutrients from the wastewater to support its growth and to store the nutrients in its tissue. When the N and P are completely removed from the wastewater, duckweed can use its internally stored nutrients to keep its growth for a significant period of time. A modified Monod model has been developed to describe nitrogen transport in a duckweed-covered pond for nutrient recovery from anaerobically treated swine wastewater. Nutrient reserve in the duckweed biomass has been found the key to the kinetics of duckweed growth. Utilization of duckweed for value-added products has a good potential. Using duckweed to feed animals, poultry, and fish has been extensively studied with promising results. Duckweed is also an alternative starch source for fuel ethanol production. Spirodela polyrrhiza grown on anaerobically treated swine wastewater was found to have a starch content of 45.8% (dry weight). Enzymatic hydrolysis of the duckweed biomass with amylases yielded a hydrolysate with a reducing sugar content corresponding to 50.9% of the original dry duckweed biomass. Fermentation of the hydrolysate using yeast gave an ethanol yield of 25.8% of the original dry duckweed biomass. These results indicate that the duckweed biomass can produce significant quantities of starch that can be readily converted into ethanol.

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In prokaryotes, Shine–Dalgarno (SD) sequences, nucleotides upstream from start codons on messenger RNAs (mRNAs) that are complementary to ribosomal RNA (rRNA), facilitate the initiation of protein synthesis. The location of SD sequences relative to start codons and the stability of the hybridization between the mRNA and the rRNA correlate with the rate of synthesis. Thus, accurate characterization of SD sequences enhances our understanding of how an organism's transcriptome relates to its cellular proteome. We implemented the Individual Nearest Neighbor Hydrogen Bond model for oligo–oligo hybridization and created a new metric, relative spacing (RS), to identify both the location and the hybridization potential of SD sequences by simulating the binding between mRNAs and single-stranded 16S rRNA 3′ tails. In 18 prokaryote genomes, we identified 2,420 genes out of 58,550 where the strongest binding in the translation initiation region included the start codon, deviating from the expected location for the SD sequence of five to ten bases upstream. We designated these as RS+1 genes. Additional analysis uncovered an unusual bias of the start codon in that the majority of the RS+1 genes used GUG, not AUG. Furthermore, of the 624 RS+1 genes whose SD sequence was associated with a free energy release of less than −8.4 kcal/mol (strong RS+1 genes), 384 were within 12 nucleotides upstream of in-frame initiation codons. The most likely explanation for the unexpected location of the SD sequence for these 384 genes is mis-annotation of the start codon. In this way, the new RS metric provides an improved method for gene sequence annotation. The remaining strong RS+1 genes appear to have their SD sequences in an unexpected location that includes the start codon. Thus, our RS metric provides a new way to explore the role of rRNA–mRNA nucleotide hybridization in translation initiation.

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