Traditional methods for enumerating and identifying microbial populations within the rumen can be time consuming and cumbersome. Methods that involve culturing and microscopy can also be inconclusive, particularly when studying anaerobic rumen fungi. A real-time PCR SYBR Green assay, using PCR primers to target total rumen fungi and the cellulolytic bacteria Ruminococcus flavefaciens and Fibrobacter succinogenes, is described, including design and validation. The DNA and crude protein contents with respect to the fungal biomass of both polycentric and monocentric fungal isolates were investigated across the fungal growth stages to aid in standard curve generation. The primer sets used were found to be target specific with no detectable cross-reactivity. Subsequently, the real-time PCR assay was employed in a study to detect these populations within cattle rumen. The anaerobic fungal target was observed to increase 3.6-fold from 0 to 12 h after feeding. The results also indicated a 5.4-fold increase in F. succinogenes target between 0 and 12 h after feeding, whereas R. flavefaciens was observed to maintain more or less consistent levels. This is the first report of a real-time PCR assay to estimate the rumen anaerobic fungal population.

The degradation of plant cell walls by ruminants is of major economic importance in the developed as well as developing world. Rumen fermentation is unique in that efficient plant cell wall degradation relies on the cooperation between microorganisms that produce fibrolytic enzymes and the host animal that provides an anaerobic fermentation chamber. Increasing the efficiency with which the rumen microbiota degrades fiber has been the subject of extensive research for at least the last 100 years. Fiber digestion in the rumen is not optimal, as is supported by the fact that fiber recovered from feces is fermentable. This view is confirmed by the knowledge that mechanical and chemical pretreatments improve fiber degradation, as well as more recent research, which has demonstrated increased fiber digestion by rumen microorganisms when plant lignin composition is modified by genetic manipulation. Rumen microbiologists have sought to improve fiber digestion by genetic and ecological manipulation of rumen fermentation. This has been difficult and a number of constraints have limited progress, including: (a) a lack of reliable transformation systems for major fibrolytic rumen bacteria, (b) a poor understanding of ecological factors that govern persistence of fibrolytic bacteria and fungi in the rumen, (c) a poor understanding of which glycolyl hydrolases need to be manipulated, and (d) a lack of knowledge of the functional genomic framework within which fiber degradation operates. In this review the major fibrolytic organisms are briefly discussed. A more extensive discussion of the enzymes involved in fiber degradation is included. We also discuss the use of plant genetic manipulation, application of free-living lignolytic fungi and the use of exogenous enzymes. Lastly, we will discuss how newer technologies such as genomic and metagenomic approaches can be used to improve our knowledge of the functional genomic framework of plant cell wall degradation in the rumen.

Methyl coenzyme-M reductase A (mcrA) clone libraries were generated from microbial DNA extracted from the rumen of cattle fed a roughage diet with and without supplementation of the antimethanogenic compound bromochloromethane. Bromochloromethane reduced total methane emissions by c. 30%, with a resultant increase in propionate and branched chain fatty acids. The mcrA clone libraries revealed that Methanobrevibacter spp. were the dominant species identified. A decrease in the incidence of Methanobrevibacter spp. from the clone library generated from bromochloromethane treatment was observed. In addition, a more diverse methanogenic population with representatives from Methanococcales, Methanomicrobiales and Methanosacinales orders was observed for the bromochloromethane library. Sequence data generated from these libraries aided in the design of an mcrA-targeted quantitative PCR (qPCR) assay. The reduction in methane production by bromochloromethane was associated with an average decrease of 34% in the number of methanogenic Archaea when monitored with this qPCR assay. Dissociation curve analysis of mcrA amplicons showed a clear difference in melting temperatures for Methanobrevibacter spp. (80-82 degrees C) and all other methanongens (84-86 degrees C). A decrease in the intensity of the Methanobrevibacter spp. specific peak and an increase for the other peak in the bromochloromethane-treated animals corresponded with the changes within the clone libraries.

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.