Isolation and characterization of novel lipases/esterases from a bovine rumen metagenome

Privé, Florence; Newbold, C. J.; Kaderbhai, Naheed; Girdwood, Susan Elizabeth; Golyshina, Olga V.; Golyshin, Peter N.; Scollan, Nigel D.; Huws, Sharon

doi:10.1007/s00253-014-6355-6

Cited by 65 publications

(43 citation statements)

References 46 publications

(61 reference statements)

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“…This approach proved successful in the discovery and characterisation of many key microbial enzymes such as glycosyl hydrolases [29–33], polyphenol oxidases [34], and lipases [35, 36]. During annotation of whole metagenomes in rumen studies, it was apparent that the majority of the open reading frames (ORF) encoded genes that were unknown or not yet included in reference databases.…”

Section: Reviewmentioning

confidence: 99%

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

et al. 2017

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Methane emissions from ruminal fermentation contribute significantly to total anthropological greenhouse gas (GHG) emissions. New meta-omics technologies are beginning to revolutionise our understanding of the rumen microbial community structure, metabolic potential and metabolic activity. Here we explore these developments in relation to GHG emissions. Microbial rumen community analyses based on small subunit ribosomal RNA sequence analysis are not yet predictive of methane emissions from individual animals or treatments. Few metagenomics studies have been directly related to GHG emissions. In these studies, the main genes that differed in abundance between high and low methane emitters included archaeal genes involved in methanogenesis, with others that were not apparently related to methane metabolism. Unlike the taxonomic analysis up to now, the gene sets from metagenomes may have predictive value. Furthermore, metagenomic analysis predicts metabolic function better than only a taxonomic description, because different taxa share genes with the same function. Metatranscriptomics, the study of mRNA transcript abundance, should help to understand the dynamic of microbial activity rather than the gene abundance; to date, only one study has related the expression levels of methanogenic genes to methane emissions, where gene abundance failed to do so. Metaproteomics describes the proteins present in the ecosystem, and is therefore arguably a better indication of microbial metabolism. Both two-dimensional polyacrylamide gel electrophoresis and shotgun peptide sequencing methods have been used for ruminal analysis. In our unpublished studies, both methods showed an abundance of archaeal methanogenic enzymes, but neither was able to discriminate high and low emitters. Metabolomics can take several forms that appear to have predictive value for methane emissions; ruminal metabolites, milk fatty acid profiles, faecal long-chain alcohols and urinary metabolites have all shown promising results. Rumen microbial amino acid metabolism lies at the root of excessive nitrogen emissions from ruminants, yet only indirect inferences for nitrogen emissions can be drawn from meta-omics studies published so far. Annotation of meta-omics data depends on databases that are generally weak in rumen microbial entries. The Hungate 1000 project and Global Rumen Census initiatives are therefore essential to improve the interpretation of sequence/metabolic information.

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Section: Reviewmentioning

confidence: 99%

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

et al. 2017

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“…In the same way, Privé et al . () isolated 14 novel lipases from a bovine rumen metagenome, mainly active on short‐ and medium‐chain FA esters. Such studies cannot indicate which bacteria produce these lipases that could originate from unknown or uncultured bacteria.…”

Section: Rumen Bh: a Microbiota Response To Dietary Ufasmentioning

confidence: 99%

Rumen microbiota and dietary fat: a mutual shaping

et al. 2017

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Summary Although fat content in usual ruminant diets is very low, fat supplements can be given to farm ruminants to modulate rumen activity or the fatty acid (FA) profile of meat and milk. Unsaturated FAs, which are dominant in common fat sources for ruminants, have negative effects on microbial growth, especially protozoa and fibrolytic bacteria. In turn, the rumen microbiota detoxifies unsaturated FAs (UFAs) through a biohydrogenation (BH) process, transforming dietary UFAs with cis geometrical double‐bonds into mainly trans UFAs and, finally, into saturated FAs. Culture studies have provided a large amount of data regarding bacterial species and strains that are affected by UFAs or involved in lipolysis or BH, with a major focus on the Butyrivibrio genus. More recent data using molecular approaches to rumen microbiota extend and challenge these data, but further research will be necessary to improve our understanding of fat and rumen microbiota interactions.

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“…Rumen microbes attempt to detoxify PUFA by biohydrogenation (Maia et al, 2010). Biohydrogenation pathways require an initial hydrolysis of ingested dietary glyceride by microbial lipases/esterases causing the release of FA (Prive et al, 2015) at this stage; Anaerovibrio lipolytica is recognized as one of the major species involved in lipid hydrolysis in ruminants (Prive et al, 2013). Wallace et al (2006) proposed that Butyrivibrio genus contained the main bacterial species involved in the biohydrogenation process.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of ruminal bacterial populations involved in lipid metabolism in dairy cows fed different vegetable oils

Vargas‐Bello‐Pérez

Cancino‐Padilla

Romero

et al. 2016

Animal

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Vegetable oils are used to increase energy density of dairy cow diets, although they can provoke changes in rumen bacteria populations and have repercussions on the biohydrogenation process. The aim of this study was to evaluate the effect of two sources of dietary lipids: soybean oil (SO, an unsaturated source) and hydrogenated palm oil (HPO, a saturated source) on bacterial populations and the fatty acid profile of ruminal digesta. Three non-lactating Holstein cows fitted with ruminal cannulae were used in a 3 × 3 Latin square design with three periods consisting of 21 days. Dietary treatments consisted of a basal diet (Control, no fat supplement) and the basal diet supplemented with SO (2.7% of dry matter (DM)) or HPO (2.7% of DM). Ruminal digesta pH, NH 3 -N and volatile fatty acids were not affected by dietary treatments. Compared with control and HPO, total bacteria measured as copies of 16S ribosomal DNA/ml by quantitative PCR was decreased ( P < 0.05) by SO. Fibrobacter succinogenes, Butyrivibrio proteoclasticus and Anaerovibrio lipolytica loads were not affected by dietary treatments. In contrast, compared with control, load of Prevotella bryantii was increased ( P < 0.05) with HPO diet. Compared with control and SO, HPO decreased ( P < 0.05) C18:2 cis n-6 in ruminal digesta. Contents of C15:0 iso, C18:11 trans-11 and C18:2 cis-9, trans-11 were increased ( P < 0.05) in ruminal digesta by SO compared with control and HPO. In conclusion, supplementation of SO or HPO do not affect ruminal fermentation parameters, whereas HPO can increase load of ruminal P. bryantii. Also, results observed in our targeted bacteria may have depended on the saturation degree of dietary oils.

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Isolation and characterization of novel lipases/esterases from a bovine rumen metagenome

Cited by 65 publications

References 46 publications

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

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

Rumen microbiota and dietary fat: a mutual shaping

Quantitative analysis of ruminal bacterial populations involved in lipid metabolism in dairy cows fed different vegetable oils

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