The high demand for ethanol in the U.S. has generated large stocks of wet distillers grains (DG) derived as a byproduct from the manufacture of ethanol from corn and sorghum grains. Ethanol production is expected to increase several fold due to the high demand and cost of foreign oil [1
]. Energy and protein dense DGs are attractive for use as a feed for beef cattle finishing diets; however little is known about the potential influence of dietary DG on fecal microbial community structure. A better understanding of the microbial population in beef cattle feces could be important in improving nutrient management, increasing animal growth performance, and decreasing odors and/or shedding of pathogens. A variety of emissions such as ammonia, volatile fatty acids, and hundreds of volatile organic compounds [2
] have been tied to beef cattle manure (reviewed by [3
]). Volatilization of ammonia has been linked to crude protein content in the diet fed and increased amounts of excreted urinary N [6
]. Previous studies suggested an association between dried distillers grains (DDGS) feeding and an increased prevalence and fecal shedding of the foodborne pathogen Escherichia coli
O157:H7 in cattle [7
A small number of studies have used culture-independent 16S rRNA-based [10
] and culture-dependent 16S rRNA-based methods with dairy cattle feces [11
spp were identified as the most dominant taxa across all lactating dairy cows (19% average abundance, range 13.9-25.4%) followed by Bacteroides
spp (9.26%, 5.2-13.7% respectively) using the culture-independent approach [10
]. In this study of Holstein dairy cows (n = 20), 274 different bacterial species were detected corresponding to 142 separate genera [10
]. Several thousand sequences were obtained per sample enabling the detection of populations below 0.1% abundance. Using culture-dependent methods, a total of 284 16S rRNA clones were obtained from three Holstein steers and classified at the 98% sequence similarity level [12
]. The dominant phyla observed were: Firmicutes (81.3%), Bacteroidetes (14.4%), Actinobacteria (2.5%), and Proteobacteria (1.4%). A comparison of dairy cattle fed a control diet or fed a diet supplemented with monensin using the culture-dependent 16S rRNA method returned 6,912 16S rRNA genes [11
]. Nearly equivalent abundance levels of Firmicutes (36.4-46.5%) and Bacteroidetes (40.5-54.9%) were observed across the six lactating Holstein cows with Proteobacteria comprising the next most abundant group (1.9-3.5%).
Culture-dependent and culture-independent 16S rRNA methods were also applied with studies involving beef cattle [13
]. Utilizing classical full length 16S rRNA gene sequence analysis a total of 1,906 OTUs (97% OTU designation) were identified from six cattle [14
]. A core set of phyla were observed based on 24 OTUs comprised of 1,253 sequences (1.2% of OTUs obtained) with 1,348 OTUs found only in individual libraries. Seven phyla were found within six animals with three dominant taxonomic groups; Firmicutes, (62.8% of the OTUs), Bacteroidetes (29.5% of the OTUs) and Proteobacteria (4.4% of the OTUs). In another small study of beef cattle (n = 6) the DNA pyrosequencing method was applied to the comparison of the effects of three diets on ruminal (fistulated Jersey cows, n = 3) and fecal (Angus steers) bacterial assemblages [13
]. Three diets (n = two cattle per diet, blocked by breed) in which of 0, 25, or 50% of the concentrate portion of the diet was replaced with dried distillers grains (DDGS) plus solubles were compared. Over 400 different bacterial species were detected that belonged to 56 separate genera from ruminal samples across all three diets. In all fecal samples, more than 540 different bacterial species were detected corresponding to 94 separate genera. The 25 most common genera that accounted for over 85% of the ruminal and fecal bacterial populations were identified. The Firmicutes: Bacteroidetes ratio tended to decrease as the proportion of DDGs increased.
In a much larger study involving 30 cattle distributed across geographically different locations and six different feeding operations (n = 5 cattle per operation) the DNA pyrosequencing method (633,877 high-quality reads) was used to assess fecal microbial community assemblages [15
]. The majority of sequences were distributed across four phyla: Firmicutes (55.2%), Bacteroidetes (25.4%), Tenericutes (2.9%), and Proteobacteria (2.5%). Core taxa were observed across 5 different phyla: Actinobacteria (0.11% of all pyrotags; 0.67% of shared taxa), Bacteroidetes (5.7% of all; 13.3% of shared taxa), Cyanobacteria (0.08% of all; 3.33% of shared taxa), Firmicutes (17.5% of all; 73.3% of shared taxa), and Tenericutes (0.96% of all; 3.33% of shared taxa). Using sequence-based clustering and taxonomic analyses, less variability was observed within a particular management practice/location than among different management practices. Animal feeding operations seemed to influence bovine fecal bacterial communities at the phylum and family taxonomic levels much more so than geographic location of the feedlot. Lastly, overall bacterial community composition seemed to be strongly influenced by fecal starch concentrations. The most responsive phyla to diet were Bacteroidetes, Firmicutes and Proteobacteria. The relative abundance of Bacteroidetes increased with increasing fecal starch concentration, whereas, the abundance of Firmicutes decreased with increasing fecal starch concentrations.
In the present study, we used the barcode DNA pyrosequencing technique to evaluate the influence of five beef cattle diets on fecal microbial assemblages. The diets consisted of a traditional diet feed beef cattle in the Southern High Plains of Texas-Con (steam-flaked corn or 0% DG), and four diets containing different percentages of DGs in the dietary dry matter; 10 C (10% corn DG), 5S (5% sorghum DG), 10S (10% sorghum DG), and 15S (15% sorghum DG). The barcoded DNA pyrosequencing method was used to generate 16S OTUs dataset. The 16S OTUs dataset was assigned to various taxonomic classes and each phylogenetic level was analyzed using a variety of statistical tests including UniFrac procedures, hierarchal cluster analysis, distance based redundancy analysis (dbRDA), and One-way ANOVA to test the influence of dietary treatments on microbial populations. We describe significant changes in microbial community structure and diversity that is influenced by these different DGs diets.