Published online by Cambridge University Press: 06 June 2013
The targeting of mcrA or 16S rRNA genes by quantitative PCR (qPCR) has become the dominant method for quantifying methanogens in rumen. There are considerable discrepancies between estimates based on different primer sets, and the literature is equivocal about the relationship with methane production. There are a number of problems with qPCR, including low primer specificity, multiple copies of genes and multiple genomes per cell. Accordingly, we have investigated alternative markers for methanogens, on the basis of the distinctive ether lipids of archaeal cell membranes. The membranes of Archaea contain dialkyl glycerol ethers such as 2,3-diphytanayl-O-sn-glycerol (archaeol), and glycerol dialkyl glycerol tetraethers (GDGTs) such as caldarchaeol (GDGT-0) in different proportions. The relationships between estimates of methanogen abundance using qPCR and archaeol measurements varied across primers. Studies in other ecosystems have identified environmental effects on the profile of ether lipids in Archaea. There is a long history of analysing easily accessible samples, such as faeces, urine and milk, to provide information about digestion and metabolism in livestock without the need for intrusive procedures. Purine derivatives in urine and odd-chain fatty acids in milk have been used to study rumen function. The association between volatile fatty acid proportions and methane production is probably the basis for empirical relationships between milk fatty acid profiles and methane production. However, these studies have not yet identified consistent predictors. We have evaluated the relationship between faecal archaeol concentration and methane production across a range of diets in studies on beef and dairy cattle. Faecal archaeol is diagnostic for ruminant faeces being below the limit of detection in faeces from non-ruminant herbivores. The relationship between faecal archaeol and methane production was significant when comparing treatment means across diets, but appears to be subject to considerable between-animal variation. This variation was also evident in the weak relationship between archaeol concentrations in rumen digesta and faeces. We speculate that variation in the distribution and kinetics of methanogens in the rumen may affect the survival and functioning of Archaea in the rumen and therefore contribute to genetic variation in methane production. Indeed, variation in the relationship between the numbers of micro-organisms present in the rumen and those leaving the rumen may explain variation in relationships between methane production and both milk fatty acid profiles and faecal archaeol. As a result, microbial markers in the faeces and milk are unlikely to relate well back to methanogenesis in the rumen. This work has also highlighted the need to describe methanogen abundance in all rumen fractions and this may explain the difficulty interpreting results on the basis of samples taken using stomach tubes or rumenocentesis.