Literature DB >> 23739482

Chemical markers for rumen methanogens and methanogenesis.

C A McCartney1, I D Bull, R J Dewhurst.   

Abstract

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.

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Year:  2013        PMID: 23739482     DOI: 10.1017/S1751731113000694

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  4 in total

Review 1.  Microbial trophic interactions and mcrA gene expression in monitoring of anaerobic digesters.

Authors:  Alejandra Alvarado; Lilia E Montañez-Hernández; Sandra L Palacio-Molina; Ricardo Oropeza-Navarro; Miriam P Luévanos-Escareño; Nagamani Balagurusamy
Journal:  Front Microbiol       Date:  2014-11-12       Impact factor: 5.640

2.  Oral Samples as Non-Invasive Proxies for Assessing the Composition of the Rumen Microbial Community.

Authors:  Ilma Tapio; Kevin J Shingfield; Nest McKain; Aurélie Bonin; Daniel Fischer; Ali R Bayat; Johanna Vilkki; Pierre Taberlet; Timothy J Snelling; R John Wallace
Journal:  PLoS One       Date:  2016-03-17       Impact factor: 3.240

Review 3.  Application of meta-omics techniques to understand greenhouse gas emissions originating from ruminal metabolism.

Authors:  Robert J Wallace; Timothy J Snelling; Christine A McCartney; Ilma Tapio; Francesco Strozzi
Journal:  Genet Sel Evol       Date:  2017-01-16       Impact factor: 4.297

Review 4.  Detection of Species-Specific Lipids by Routine MALDI TOF Mass Spectrometry to Unlock the Challenges of Microbial Identification and Antimicrobial Susceptibility Testing.

Authors:  Vera Solntceva; Markus Kostrzewa; Gerald Larrouy-Maumus
Journal:  Front Cell Infect Microbiol       Date:  2021-02-04       Impact factor: 5.293

  4 in total

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