We compared and statistically evaluated the effectiveness of nine DNA extraction procedures by using frozen and dried samples of two silt loam soils and a silt loam wetland sediment with different organic matter contents. The effects of different chemical extractants (sodium dodecyl sulfate [SDS], chloroform, phenol, Chelex 100, and guanadinium isothiocyanate), different physical disruption methods (bead mill homogenization and freeze-thaw lysis), and lysozyme digestion were evaluated based on the yield and molecular size of the recovered DNA. Pairwise comparisons of the nine extraction procedures revealed that bead mill homogenization with SDS combined with either chloroform or phenol optimized both the amount of DNA extracted and the molecular size of the DNA (maximum size, 16 to 20 kb). Neither lysozyme digestion before SDS treatment nor guanidine isothiocyanate treatment nor addition of Chelex 100 resin improved the DNA yields. Bead mill homogenization in a lysis mixture containing chloroform, SDS, NaCl, and phosphate-Tris buffer (pH 8) was found to be the best physical lysis technique when DNA yield and cell lysis efficiency were used as criteria. The bead mill homogenization conditions were also optimized for speed and duration with two different homogenizers. Recovery of high-molecular-weight DNA was greatest when we used lower speeds and shorter times (30 to 120 s). We evaluated four different DNA purification methods (silica-based DNA binding, agarose gel electrophoresis, ammonium acetate precipitation, and Sephadex G-200 gel filtration) for DNA recovery and removal of PCR inhibitors from crude extracts. Sephadex G-200 spin column purification was found to be the best method for removing PCR-inhibiting substances while minimizing DNA loss during purification. Our results indicate that for these types of samples, optimum DNA recovery requires brief, low-speed bead mill homogenization in the presence of a phosphate-buffered SDS-chloroform mixture, followed by Sephadex G-200 column purification.

There is concern that antibiotic resistance can potentially be transferred from animals to humans through the food chain. The relationship between specific antibiotic resistant bacteria and the genes they carry remains to be described. Few details are known about the ecology of antibiotic resistant genes and bacteria in food production systems, or how antibiotic resistance genes in food animals compare to antibiotic resistance genes in other ecosystems. Here we report the distribution of antibiotic resistant genes in publicly available agricultural and non-agricultural metagenomic samples and identify which bacteria are likely to be carrying those genes. Antibiotic resistance, as coded for in the genes used in this study, is a process that was associated with all natural, agricultural, and human-impacted ecosystems examined, with between 0.7 to 4.4% of all classified genes in each habitat coding for resistance to antibiotic and toxic compounds (RATC). Agricultural, human, and coastal-marine metagenomes have characteristic distributions of antibiotic resistance genes, and different bacteria that carry the genes. There is a larger percentage of the total genome associated with antibiotic resistance in gastrointestinal-associated and agricultural metagenomes compared to marine and Antarctic samples. Since antibiotic resistance genes are a natural part of both human-impacted and pristine habitats, presence of these resistance genes in any specific habitat is therefore not sufficient to indicate or determine impact of anthropogenic antibiotic use. We recommend that baseline studies and control samples be taken in order to determine natural background levels of antibiotic resistant bacteria and/or antibiotic resistance genes when investigating the impacts of veterinary use of antibiotics on human health. We raise questions regarding whether the underlying biology of each type of bacteria contributes to the likelihood of transfer via the food chain.

Enteric methane (CH₄) emissions produced by microbial fermentation in the rumen resulting in the emission of greenhouse gases (GHG) into the atmosphere. The GHG emissions reduction from the livestock industry can be attained by increasing production efficiency and improving feed efficiency, by lowering the emission intensity of production, or by combining the two. In this work, information was compiled from peer-reviewed studies to analyze CH₄ emissions calculated per unit of milk production, energy-corrected milk (ECM), average daily gain (ADG), dry matter intake (DMI), and gross energy intake (GEI), and related emissions to rumen fermentation profiles (volatile fatty acids [VFA], hydrogen [H₂]) and microflora activities in the rumen of beef and dairy cattle. For dairy cattle, there was a positive correlation (p < 0.001) between CH₄ emissions and DMI (R² = 0.44), milk production (R² = 0.37; p < 0.001), ECM (R² = 0.46), GEI (R² = 0.50), and acetate/propionate (A/P) ratio (R² = 0.45). For beef cattle, CH₄ emissions were positively correlated (p < 0.05–0.001) with DMI (R² = 0.37) and GEI (R² = 0.74). Additionally, the ADG (R² = 0.19; p < 0.01) and A/P ratio (R² = 0.15; p < 0.05) were significantly associated with CH₄ emission in beef steers. This information may lead to cost-effective methods to reduce enteric CH₄ production from cattle. We conclude that enteric CH₄ emissions per unit of ECM, GEI, and ADG, as well as rumen fermentation profiles, show great potential for estimating enteric CH₄ emissions.