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Cited by 504Ruminant Nutrition and Digestive PhysiologyAnaerobic Digestion and Biogas ProductionAnimal Nutrition and Physiology

Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future

Open access
Huws, Sharon A., Creevey, Christopher J., Oyama, Linda B., Mizrahi, Itzhak, Denman, Stuart E., Popova, Milka, Muñoz-Tamayo, Rafael, Forano, Evelyne +29 more·2018·Frontiers in Microbiology
DOI 10.3389/fmicb.2018.02161PMC PMC6167468
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Abstract

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.

AI snapshot

Written from the paper’s full text.

TL;DR

This review argues that understanding and manipulating the rumen microbiome is central to meeting global livestock challenges, including increasing ruminant production while reducing environmental impact. It surveys past, present, and future approaches across rumen microbes, diet, host genetics, early-life interventions, biomarkers, modeling, and omics technologies.

Key findings

  • Global demand pressures are large: the world population is predicted to reach approximately 9.7 billion by 2050, total agricultural production may need to be 60% higher than in 2005, and global meat and milk production may need to increase by 76% and 63%, respectively.
  • Ruminant livestock production is estimated to account for approximately 14% of anthropogenic methane, and around 2–8% of dietary energy can be lost to methane production, with values as high as 12% for low-quality feeds; 3-nitrooxypropanol has been shown to reduce methane emissions by up to 30%, but animal production benefits are modest.
  • A global comparison of 742 rumen samples across 32 species found 30 of the most abundant bacterial groups in over 90% of samples, with *Methanobrevibacter gottschalkii* and *Methanobrevibacter ruminantium* in nearly all samples and accounting for 74% of archaea; diet was concluded to be the main driver of rumen microbiome composition.
  • Host genetics also influences the rumen microbiome: 22 bacterial OTUs showed heritability estimates of 0.7 or greater in dairy cattle and were correlated with traits such as dry matter intake and residual feed intake; early-life dietary interventions and microbiome gene biomarkers are highlighted as promising but not yet fully validated.

Methods

  • Narrative review/synthesis of published literature on the rumen microbiome, global agricultural challenges, dietary interventions, host genomics, lower gastrointestinal tract microbiomes, biomarkers, mathematical modeling, and omics technologies.
  • The paper draws on cited studies, comparative datasets, and summary tables, including examples of dietary interventions and potential gene biomarkers for feed efficiency and methane production.
  • No systematic review protocol, search strategy, or primary experimental dataset is reported in the paper.

Limitations

  • The paper states that the rumen microbiome remains poorly understood, most rumen microbes are difficult to culture outside the rumen, and high-throughput phenotyping of ruminants has been limited.
  • It notes that metataxonomic data are highly variable across studies due to differences in DNA extraction, primers, sequencing, and computational analysis, and that consensus gene biomarkers for residual feed intake and methane output are lacking across datasets.
  • As evident from the text, this is a narrative review rather than a primary study, so its conclusions depend on synthesis of cited literature and do not provide new experimental validation.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3389/fmicb.2018.02161

Cites

298 of 298 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

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  • Findingown data

    No consensus of other genes across the three published datasets was found.

    “Consensus of other genes across the three published datasets were not found (Table 3).”
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  • Findingcitation

    Genes involved in amino acid metabolism were less abundant in feed efficient animals.

    “Microbial gene correlations with RFI, data from Shabat et al. (2016) and Li and Guan (2017) showed some consensus as both showed that genes involved in amino acid metabolism were less abundant in feed efficient animals (Table 2).”
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  • Findingnone given

    Genes correlating to methane emissions show very little consensus amongst the five papers investigated.

    “Likewise, genes correlating to methane emissions show very little consensus amongst the five papers investigated.”
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  • Findingnone given

    In four datasets, the methyl coenzyme reductase enzyme showed the most correlation to methane.

    “Nevertheless, in four datasets the methyl coenzyme reductase enzyme, which is involved in the last step of the hydrogenotrophic methane pathway (Figure 1), showed the most correlation to methane.”
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  • Interpretationcitation

    A better understanding of the roles played by the constituent microbes is central to the development of advanced methods to manipulate the rumen microbiome in a manner that improves ruminant production whilst reducing environmental impact.

    “A better understanding of the roles played by the constituent microbes is central to the development of advanced methods to manipulate the rumen microbiome in a manner that improves ruminant production whilst reducing environmental impact (Yáñez-Ruiz et al., 2015).”
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    Premisecitation

    Global meat and milk production will have to increase by 76 and 63%, respectively.

    “estimates suggest that global meat and milk production will have to increase by 76 and 63%, respectively (Alexandratos and Bruinsma, 2012).”
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    L. leucocephala contains the toxin mimosine which is converted in the rumen to DHP, an effective goitrogen.

    “L. leucocephala contains the toxin mimosine which is converted in the rumen to 4-hydroxy-4(H)-pyridone (DHP), an effective goitrogen (Wallace, 2008)”
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    These microbes interact with each other and have a symbiotic relationship with the host, providing energy from the breakdown of plant cell wall carbohydrates that are largely inedible by humans.

    “These microbes interact with each other and have a symbiotic relationship with the host, providing energy from the breakdown of plant cell wall carbohydrates that are largely inedible by humans (Mizrahi, 2013).”
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    Ruminants commonly harbor distinct protozoal populations from birth, with only minor changes in diversity throughout life, although the abundances of species fluctuate with changes in diet.

    “Ruminants commonly harbor distinct protozoal populations from birth, with only minor changes in diversity throughout life, although the abundances of species fluctuate with changes in diet (Williams and Coleman, 1997).”
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    Premisecitation

    Methane is produced primarily via the hydrogenotrophic pathway as a result of the reduction of CO2, and less so through methylotrophic or acetoclastic pathways.

    “Methane is produced primarily via the hydrogenotrophic pathway (Figure 1) as a result of the reduction of CO2, and less so through the utilization of methyl groups (methylotrophic pathway), or even less commonly from acetate (acetoclastic pathway; Morgavi et al., 2010; Tapio et al., 2017).”
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    Premisecitation

    Around 2-8% of the dietary energy can be lost to methane production, with values as high as 12% reported for low quality feeds.

    “around 2–8% of the dietary energy can be lost to methane (CH4) production (IPCC, 2006); values as high as 12% have been reported for low quality feeds (Johnson and Johnson, 1995).”
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    Ruminant livestock production is responsible for approximately 14% of anthropogenic methane released annually into the atmosphere due to the activity of rumen methanogens.

    “Ruminant livestock production has been estimated to be responsible for approximately 14% of anthropogenic methane, a potent greenhouse gas (GHG), released annually into the atmosphere due to the activity of rumen methanogens (Gerber et al., 2013).”
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    N2O has a 298-fold greater global warming potential than CO2.

    “N2O, a GHG with a 298-fold greater global warming potential than CO2 (Hristov et al., 2013).”
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    The world population is predicted to reach approximately 9.7 billion by 2050.

    “Whilst some models predict the world population to peak at 9.7 billion in 2050, others estimate a population of 11.2 billion in 2100 (United Nations, 2015).”
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    Methanomassiliicoccaceae can represent approximately 50-70% of the rumen archaea.

    “some published data show that Methanomassiliicoccaceae can represent approximately 50–70% of the rumen archaea (Huang et al., 2016; Wang P. et al., 2016).”
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    Ruminants provide human-edible nutritious foods derived from marginal land, without competing with food crop production.

    “As a consequence of their highly evolved rumen microbiome, ruminants provide human-edible nutritious foods derived from marginal land, without competing with food crop production (Kingston-Smith et al., 2010).”
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    Premisecitation

    Tannins protect dietary protein from degradation in the rumen without significantly affecting the efficiency of carbohydrate digestion.

    “it is well established that tannins protect dietary protein from degradation in the rumen without significantly affecting the efficiency of carbohydrate digestion (Mcsweeney et al., 2001).”
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    Anaerobic fungi represent 10-20% of the rumen microbiome.

    “Chitin measurements (Rezaeian et al., 2004) and rRNA transcript abundance (Elekwachi et al., 2017) indicate that anaerobic fungi represent 10–20% of the rumen microbiome.”
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    Members of the methanogen clades Methanobrevibacter gottschalkii and Methanobrevibacter ruminantium were found in nearly all samples and accounted for 74% of the archaea.

    “Members of the methanogen clades Methanobrevibacter gottschalkii and Methanobrevibacter ruminantium were found in nearly all samples and accounted for 74% of the archaea.”
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    S. cerevisiae can increase the density of fibrolytic bacteria and hence feed efficiency due to its oxygen scavenging activity in the rumen.

    “Due to its oxygen scavenging activity in the rumen (Newbold et al., 1996), S. cerevisiae can increase the density of fibrolytic bacteria and hence feed efficiency (Desnoyers et al., 2009).”
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    Animals fed high-grain diets tend to have lower bacterial diversity and lower concentrations of fibrolytic microbes (protozoa and anaerobic fungi), which are generally associated with lower rumen proteolysis and ultimately higher feed efficiency.

    “animals fed high-grain diets tend to have lower bacterial diversity and lower concentrations of fibrolytic microbes (i.e., protozoa and anaerobic fungi), which are generally associated with lower rumen proteolysis and ultimately higher feed efficiency (Belanche et al., 2012).”
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    Premisecitation

    Sodium bicarbonate and yeast (Saccharomyces cerevisiae) supplementation both have shown some success in preventing sub-acute acidosis (SARA).

    “Sodium bicarbonate and yeast (Saccharomyces cerevisiae) supplementation both have shown some success in preventing sub-acute acidosis (SARA; Keunen et al., 2003; González et al., 2012; Ishaq et al., 2017).”
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    Anaerobic fungi have been shown to improve feed intake, feed digestibility, feed efficiency, daily weight gain and milk production.

    “Anaerobic fungi are clearly beneficial, and have been shown to improve feed intake, feed digestibility, feed efficiency, daily weight gain and milk production (Lee et al., 2000; Dey et al., 2004; Paul et al., 2004; Tripathi et al., 2007; Saxena et al., 2010; Puniya et al., 2015).”
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    Essential oils slow down starch and protein degradation, decreasing the risk of acidosis while causing minor reductions in rumen methanogenesis.

    “Essential oils have been proven to slow down starch and protein degradation, decreasing the risk of acidosis while causing minor reductions in rumen methanogenesis (Calsamiglia et al., 2007).”
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    Application of bromochloromethane (BCM) to young goat kids modified archaeal colonization of the rumen, and was linked to a reduction in methane emission of around 50%, with the effects persisting for 3 months after weaning.

    “It has been shown that application of bromochloromethane (BCM) to young goat kids modified archaeal colonization of the rumen, and was linked to a reduction in methane emission of around 50%, with the effects persisting for 3 months after weaning (Abecia et al., 2013, 2014).”
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    In another near-total rumen content exchange between high- and low-efficiency Holstein cows, the hosts returned the rumen bacterial community to the original status, linking the rumen microbiome to milk production efficiency.

    “Furthermore, in another near-total rumen content exchange between high- and low-efficiency Holstein cows, Weimer et al. (2017) demonstrated the hosts ability to return the rumen bacterial community to the original status, whilst linking the rumen microbiome to milk production efficiency.”
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    Diet is the main driver for rumen microbiome composition.

    “Whilst Henderson et al. (2015) postulated that diet was the main driver for rumen microbiome composition, they also identified some differences in the relative abundance of certain bacterial populations across ruminant species.”
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    Feeding live microorganisms to ruminants is not a novel concept and extensive work has been published on the use of direct-fed microbials (DFM).

    “Feeding live microorganisms to ruminants is not a novel concept and extensive work has been published on the use of “direct-fed microbials” (DFM; Martin and Nisbet, 1992; Jeyanathan et al., 2014).”
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    Feeding concentrate in early life stimulates the development of the epithelium, while feeding high fiber diets can stimulate development of rumen muscularization and volume.

    “It is also known that feeding concentrate in early life stimulates the development of the epithelium, while feeding high fiber diets can stimulate development of rumen muscularization and volume (Zitnan et al., 1998).”
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    Although the rumen microbiome establishes before intake of solid feeds, the type of feed consumed plays a significant role in shaping the established rumen microbiome.

    “It is important to note that although the rumen microbiome establishes before intake of solid feeds, the type of feed consumed plays a significant role in shaping the established rumen microbiome.”
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    Premisenone given

    Despite some promising results from early-life dietary interventions, the ecological dynamics underpinning the microbial colonization, the most effective window of time for intervention and the long-term implications have yet to be identified.

    “Despite some promising results from early-life dietary interventions, the ecological dynamics underpinning the microbial colonization, the most effective window of time for intervention and the long-term implications have yet to be identified.”
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    Premisereasoning

    Naturally reared calves have a greater number of Operational Taxonomic Units (OTUs) and bacterial diversity than artificially reared calves.

    “This explains the greater number of Operational Taxonomic Units (OTUs) and bacterial diversity observed in naturally reared calves.”
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    Artificially reared calves have a near absence of protozoa in the rumen, as protozoa can only be inoculated in the rumen by direct contact with the dam or other mature animals through saliva.

    “Another distinctive feature between natural and artificial rearing systems is the near absence of protozoa in the rumen of artificially reared calves, as protozoa can only be inoculated in the rumen by direct contact with the dam or other mature animals through saliva (Abecia et al., 2014).”
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    Supplementation of phloroglucinol together with 3-NOP promotes capture of excess hydrogen from methanogenesis and generates valuable metabolites for the host.

    “Supplementation of phloroglucinol together with 3-NOP promotes capture of excess hydrogen from methanogenesis and generates valuable metabolites for the host (Martinez-Fernandez et al., 2017).”
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    After near total exchange of the rumen contents between cows, individuals restored their bacterial composition back to pre-exchange conditions, which also returned rumen pH and volatile fatty acid (VFA) concentration to pre-exchange values.

    “Evidence of the influence of the host on the rumen microbiome was first postulated by Weimer et al. (2010) who found that after near total exchange of the rumen contents between cows, individuals restored their bacterial composition back to pre-exchange conditions, which also returned rumen pH and volatile fatty acid (VFA) concentration to pre-exchange values.”
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    The maturation stage of rumen microbial establishment is characterized by progressively increasing solid feed intake and a distribution of main bacterial phyla and other microbial groups comparable to that in adult animals.

    “iii) maturation stage in which solid feed intake progressively increases and the distribution of main bacterial phyla and other microbial groups is comparable to that in adult animals.”
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    The post-ruminal microbial community is composed predominantly of bacteria, but methanogenic archaea and anaerobic fungi have been described.

    “The post-ruminal microbial community is composed predominantly of bacteria, but methanogenic archaea and anaerobic fungi have been described (Davies et al., 1993), although the later phylogentic group has not been targeted intensively with high-throughput sequencing techniques.”
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    Prevotella, Bacteroides, Ruminococcus, Faecalibacterium, Roseburia and Clostridium are consistently identified in fecal samples from ruminants and are considered part of the core microbiota.

    “Prevotella, Bacteroides, Ruminococcus, Faecalibacterium, Roseburia and Clostridium are consistently identified in fecal samples from ruminants and are considered part of the core microbiota (Dowd et al., 2008; Durso et al., 2012).”
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    Differences in rumen and camelid foregut volume, physiology as well as feeding frequencies were suggested as a reason for the proportionally higher abundance of unclassified Veillonellaceae in camelids, deer and sheep compared to cattle.

    “For example, differences in rumen and camelid foregut volume, physiology as well as feeding frequencies, was suggested as a reason for the proportionally higher abundance of unclassified Veillonellaceae in camelids, deer and sheep compared to cattle (Henderson et al., 2015).”
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    Methane yield is associated with retention time in the rumen; increased passage rate in the rumen correlates with reduced methane yield.

    “In addition, methane yield is associated with retention time in the rumen (Pinares-Patiño et al., 2003) correlating increased passage rate in the rumen with reduced methane yield.”
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    Both a shorter rumen retention time and a smaller rumen result in reduced methane yield.

    “It has also been demonstrated that both a shorter rumen retention time and a smaller rumen result in reduced methane yield (Goopy et al., 2014).”
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    Prevotella, Bacteroides, Ruminococcus, Treponema, and Desulfovibrio genera were detected in all segments of the GI tract of ruminant animals, while Fibrobacter was only present in the foregut.

    “Prevotella, Bacteroides, Ruminococcus, Treponema, and Desulfovibrio genera were detected in all segments of the GI tract of ruminant animals, while Fibrobacter was only present in the foregut (Zeng et al., 2017).”
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    From the ileum onwards, including caecum, colon and feces, favorable fermentation conditions are present again and microbial density and phylogenetic diversity increase to a level comparable to that of the rumen.

    “From the ileum onwards, including caecum, colon and feces, favorable fermentation conditions are present again and microbial density and phylogenetic diversity increase to a level comparable to that of the rumen (Frey et al., 2010; De Oliveira et al., 2013; Popova et al., 2017; He et al., 2018; Yeoman et al., 2018).”
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    The rectal microbiota shows important inter-individual variation and is affected by diet.

    “As for the rumen, the rectal microbiota shows important inter-individual variation (Durso et al., 2010) and are affected by diet (Shanks et al., 2011).”
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    Most studies involve a small number of animals, making it difficult to clearly confirm the link between methanogen diversity and methane emissions.

    “However, most studies involve a small number of animals, making it difficult to clearly confirm the link between methanogen diversity and methane emissions (Morgavi et al., 2010).”
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    Purine bases were used as biomarkers for microbial (protein) synthesis in studies with intestinally cannulated animals.

    “while purine bases (Zinn and Owens, 1986) were also used as biomarkers for microbial (protein) synthesis in studies with intestinally cannulated animals.”
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    The main function of the intestinal microbiota has been suggested to be related to animal health and cross-talk interaction with the animal host.

    “Its main function has been suggested to be related to animal health and cross-talk interaction with the animal host (Lyte et al., 2018), although work in this area is only in its nascent phase and these aspects need further investigation.”
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    Nucleic acids have long been used as biomarkers for rumen microbial processes.

    “Nucleic acids have long been used as biomarkers for rumen microbial processes.”
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    Interpretationnone given

    Genes identified consistently across experiments represent the most promising marker genes.

    “Genes identified consistently across experiments and therefore representing the most promising marker genes are highlighted in gray.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationnone given

    The genes listed in Table 3 are potential gene biomarkers indicative of methane production from ruminants.

    “Table 3 Potential gene biomarkers indicative of methane production from ruminants.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Methanogen diversity, and not density, is critically important to methane output, with more diversity being associated with higher emissions.

    “Recent studies suggest that methanogen diversity, and not density, is critically important to methane output, with more diversity being associated with higher emissions (Janssen and Kirs, 2008; Carberry et al., 2014).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Janssen and Kirs, 2008

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    • cites Carberry et al., 2014 source

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  • May combine two claims.

    Premisecitation

    Mucosa-associated communities differ from those associated with luminal contents and vary among intestinal regions.

    “Mucosa-associated communities differ from those associated with luminal contents; and also vary among intestinal regions (Malmuthuge et al., 2014; Mao et al., 2015; Yeoman et al., 2018).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Malmuthuge et al., 2014 source

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    • cites Mao et al., 2015 source

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    • cites Yeoman et al., 2018 source

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Early work focussed on rumen microbial protein synthesis and RNA.

    “Early work focussed on rumen microbial protein synthesis and RNA (Mcallan and Smith, 1969),”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Mcallan and Smith, 1969

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  • May combine two claims.

    Premisecitation

    Feed efficient animals excrete less urinary ammonia, suggesting better rumen nitrogen use efficiency.

    “These data corresponds with observations that feed efficient animals excrete less urinary ammonia suggesting better rumen nitrogen use efficiency (Bach et al., 2005; Broderick and Reynal, 2009).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Bach et al., 2005 source

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    • cites Broderick and Reynal, 2009

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    An increase in the acrylate pathway coded by Megasphaera elsdenii and Coprococcus catus in the rumen may increase feed efficiency and reduce methane.

    “whereas Shabat et al. (2016), suggested that an increase in the acrylate pathway coded by Megasphaera elsdenii and Coprococcus catus in the rumen may increase feed efficiency and reduce methane.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Shabat et al., 2016 source

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  • May combine two claims.

    Premisecitation

    The ratio of bacteria:archaea reflects methane output from the animal, with positive correlations reported in a few studies, but results are not consistent.

    “It has been suggested also that the ratio of bacteria:archaea reflects methane output from the animal with positive correlations reported in a few studies (Wallace et al., 2014; Auffret et al., 2017b), but results are not consistent (Tapio et al., 2017).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Wallace et al., 2014 source

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    • cites Auffret et al., 2017b

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    • cites Tapio et al., 2017 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    Buccal swabbing may be used as a proxy for rumen samples.

    “raising the possibility that buccal swabbing may be used as a proxy for rumen samples.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    The oral microbiome of ruminants reflects the microbial diversity seen in the rumen.

    “Recently it was suggested that the oral microbiome of ruminants reflects the microbial diversity seen in the rumen (Tapio et al., 2016), raising the possibility that buccal swabbing may be used as a proxy for rumen samples.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Tapio et al., 2016 source

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  • Classified as probably not a substantial claim.

    Interpretationreasoning

    COBRA approaches provide rational tools for metabolic engineering.

    “Overall, COBRA approaches provide rational tools for metabolic engineering.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    A great challenge is to deploy different model structures, capitalizing on omics data, and responding to different goals varying from supporting livestock management within a precision farming context to guiding microbial programming strategies.

    “A great challenge is to deploy different model structures, capitalizing on “omics” data, and responding to different goals varying from supporting livestock management within a precision farming context to guiding microbial programming strategies.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    The construction of a rumen microbiome GEM will need to address central questions that remain to be elucidated due to the early stage of microbial community modeling.

    “The construction of a rumen microbiome GEM will need to address central questions that remain to be elucidated due to the early stage of microbial community modeling (Zengler and Palsson, 2012).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Zengler and Palsson, 2012

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  • May combine two claims.

    Premisecitation

    The Hungate1000 project sequenced 420 representatives of rumen microbes, mainly bacteria, providing a major tool for the community.

    “The Hungate1000 project recently finished having sequenced 420 representatives of rumen microbes (mainly bacteria), and thus providing a major tool for the community (Seshadri et al., 2018).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Seshadri et al., 2018 source

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  • Classified as probably not a substantial claim.

    Interpretationcitation

    Since COBRA approaches mainly operate at steady-state, dynamic frameworks will need to be adapted to account for dynamic fluctuations within the rumen environment.

    “Moreover, since COBRA approaches mainly operates at steady-state, dynamic frameworks (Mahadevan et al., 2002; Baroukh et al., 2014) will need to be adapted to account for the dynamic fluctuations within the rumen environment.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Mahadevan et al., 2002 source

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    • cites Baroukh et al., 2014 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    These rumen models represent relevant aspects that determine nutritional and emission responses for a given diet but do not attempt to provide a detailed description of the microbiota or its function.

    “These models represent relevant aspects that determine the nutritional and emission responses for a given diet but do not attempt to provide a detailed description of the microbiota or its function (Ellis et al., 2008).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Ellis et al., 2008 source

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    For specific bacterial 16S rRNA, V6-V8 primers were more appropriate than V3 primers.

    “However, Huws et al. (2007) concluded that for specific bacterial 16S rRNA V6-V8 primers were more appropriate.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Huws et al., 2007 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    The most popular COBRA method is flux balance analysis (FBA), which finds network reaction fluxes that optimize a regulatory condition such as microbial growth.

    “The most popular COBRA method is flux balance analysis (FBA; Varma et al., 1993; Varma and Palsson, 1994), which looks at finding the network reaction fluxes that optimize a regulatory condition (e.g., microbial growth).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Varma et al., 1993 source

      Not checked in the free run.

    • cites Varma and Palsson, 1994

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  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationnone given

    Rumen GEMs must be further integrated into whole rumen digestion models to provide a system-level picture of dynamic interplay between diet, host, and microbiota.

    “Clearly rumen GEMs must be further integrated into whole rumen digestion models to provide a system-level picture of the dynamic interplay between the diet, the animal host and the rumen microbiota.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Reducing agents were not required to culture all rumen bacteria and their removal resulted in higher microbial diversity.

    “A recent study by Poelaert et al. (2018) showed that reducing agents were not required to culture all rumen bacteria and that when removed they resulted in higher microbial diversity.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Poelaert et al., 2018 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    V3 primers were non-specific to bacteria and could amplify plant chloroplastic DNA as well as archaeal 16S rDNA and protozoal 18S rDNA sequences.

    “Huws et al. (2007) and Edwards et al. (2007), however showed that the V3 primers were non-specific to bacteria and could amplify plant chloroplastic DNA as well as archaeal 16S rDNA and protozoal 18S rDNA sequences.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Huws et al., 2007 source

      Not checked in the free run.

    • cites Edwards et al., 2007 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The amplicon size from Edwards et al. (2017) primers is often too large for effective sequencing, so the reverse primer was changed to avoid chloroplast identification and produce a smaller amplicon for NGS.

    “Nonetheless, the amplicon size obtained using the Edwards et al. (2017) primers are often too large for effective sequencing, therefore the reverse primer has been changed to enable avoidance of chloroplast identification and production of a smaller amplicon for NGS sequencing (Belanche et al., 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Belanche et al., 2017 source

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  • Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing).

    Premisecitation

    One key question is how microbial species, their metabolic networks, and interspecies interactions should be represented.

    “One of these key questions is how microbial species, their metabolic networks, and interspecies interactions should be represented (Biggs et al., 2015).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Biggs et al., 2015 source

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    Once this question is elucidated, a plethora of COBRA methods can be deployed to investigate genotype-phenotype relationships.

    “Once this question is elucidated, a plethora of constraint-based reconstruction and analysis (COBRA) methods can be deployed to investigate genotype–phenotype relationships (Lewis et al., 2012).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Lewis et al., 2012 source

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Each DNA extraction method has advantages and disadvantages that need to be considered based on sample type, but bead beating is critical.

    “They conclude that each method has advantages and disadvantages which need to be considered based on sample type, but bead beating is critical.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Vaidya et al., 2018 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Inferring metabolic function from phylogenetic data allows the scientific community to obtain retrospective value from these datasets in order to understand the rumen microbiome in light of global agricultural challenges.

    “Regardless, inferring metabolic function from phylogenetic data allows the scientific community to obtain retrospective value from these datasets in order to understand the rumen microbiome in light of global agricultural challenges.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Ensuring data accuracy by using internal standards represents one approach to ensure comparisons among datasets are valid.

    “Nonetheless, using a basic set of standardized protocols may not be possible, due to the differing hypotheses and the complex nature of the ecosystem (i.e., host animal), however ensuring data accuracy by using internal standards represents one approach to ensure that comparisons among datasets are valid.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    Metataxonomic rDNA data have provided insights into rumen microbiome composition under differing parameters, but these techniques are limited in providing insight into microbial function.

    “Irrespective, metataxonomic rDNA data have provided insights into the composition of the rumen microbiome under differing parameters, but these techniques are limited in terms of providing insight into microbial function.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    Central to this task and for development of novel strategies to enhance ruminant production and reduce environmental impact is the need for data sharing and collaboration.

    “Central to this task and for the development of novel strategies to enhance ruminant production and reduce environmental impact is the need for data sharing and collaboration.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Microdroplet encapsulation technique has had success for culturing marine bacteria.

    “Another method, which has had success for culturing marine bacteria, is the microdroplet encapsulation technique (Zengler et al., 2002).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Zengler et al., 2002 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    The RBB+C DNA extraction method yielded more DNA than other tested methods, and bead beating was crucial.

    “They concluded that the RBC + C method yielded more DNA and that bead beating was crucial.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Yu and Morrisson, 2004a

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Shotgun metagenomics was first applied to the rumen to discover novel biomass degrading enzymes from switchgrass-associated microbes.

    “Shotgun metagenomics was first applied to the rumen in order to discover novel biomass degrading enzymes from switchgrass-associated microbes (Hess et al., 2011).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Hess et al., 2011 source

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    During translation, the ribosome protects around 30 nucleotides of the mRNA from nuclease activity.

    “Riboseq takes advantage of the fact that during translation, the ribosome protects around 30 nucleotides of the mRNA from nuclease activity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Metagenomics has been used to study methane emissions in cattle and sheep, biomarkers to predict ruminal methanogenesis, effects of feed-conversion-ratio, breed and host genetics on rumen microbiome composition, nutrient acquisition, diet effects, and feed additives on antimicrobial-resistance gene abundance.

    “Subsequently, metagenomics has been used to study many aspects of rumen microbiology, including methane emissions in cattle (Wallace et al., 2015) and sheep (Shi et al., 2014), biomarkers to predict ruminal methanogenesis (Auffret et al., 2017b), the effect of feed-conversion-ratio, and breed and host genetics on the composition of the rumen microbiome (Roehe et al., 2016), nutrient acquisition (M”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Wallace et al., 2015 source

      Not checked in the free run.

    • cites Shi et al., 2014 source

      Not checked in the free run.

    • cites Auffret et al., 2017b

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Assembly binning was first achieved by Tyson et al. (2004) from an acidophilic biofilm.

    “Assembly binning refers to the construction of complete or near complete microbial genomes directly from metagenomic sequencing data, and was first achieved by Tyson et al. (2004) from an acidophilic biofilm.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Tyson et al., 2004 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Despite limitations, Snelling and Wallace (2017) identified proteins directly associated with the functional activity of the rumen microbial community from 2D PAGE spots, including abundant structural proteins (actin, alpha and beta tubulin, axonemal dynein light chain) involved in ciliate locomotion, and prokaryotic enzymes from Firmicutes and Bacteroidetes involved in central metabolism.

    “Despite these limitations, Snelling and Wallace (2017) did identify proteins directly associated with the functional activity of the rumen microbial community from 2D PAGE spots. Abundant structural proteins were identified including actin, alpha and beta tubulin, and axonemal isoforms dynein light chain, which are all involved in the locomotion of ciliates. Among prokaryotic proteins were enzymes”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Snelling and Wallace, 2017

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Hess et al. (2011) were the first to apply assembly binning to ruminants, assembling 15 draft microbial genomes from the switchgrass associated microbiome of cattle.

    “Hess et al. (2011) were the first to apply this to ruminants, assembling 15 draft microbial genomes from the switchgrass associated microbiome of cattle.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Hess et al., 2011 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Within metagenome sequences from 14 silage-fed cows, Prevotella possessed higher levels of glycosyl hydrolase isoforms relating to hemicellulose degradation, while Clostridium contained higher levels of GH isoforms for cellulose degradation.

    “Rubino et al. (2017) showed that, within metagenome sequences from 14 silage-fed cows, that the genus Prevotella possessed higher levels of glycosyl hydrolase (GH) isoforms relating specifically to the degradation of hemicellulose, whilst Clostridium contained higher levels of GH isoforms for enzymes specifically involved in cellulose degradation.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Rubino et al., 2017 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Metaproteomics has theoretical advantages over RNA sequencing because protein half-life can be significantly longer than RNA transcripts, so protein identification may provide a more accurate picture of microbial activity at a single time point than mRNA sequencing.

    “As a concept, it has some theoretical advantages over RNA sequencing methods in that the half-life of proteins can be significantly longer than RNA transcripts. Therefore, if the data represent a “snapshot” of microbial activity at a single time point, then identification of the proteins arguably will provide a more accurate picture than sequencing mRNA.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Using a combination of several metabolomics platforms, Saleem et al. (2013) demonstrated that the rumen metabolome is not as simple as previously anticipated, reporting 246 compounds including phospholipids, inorganic ions, gases, amino acids, dicarboxylic acids, fatty acids, volatile fatty acids, glycerides, carbohydrate and cholesterol esters.

    “Using a combination of several metabolomics platforms, the pioneer study by Saleem et al. (2013) demonstrated that the rumen metabolome is not as simple as previously anticipated. Indeed, 246 compounds were reported as part of the rumen metabolome, including: phospholipids, inorganic ions, gases, amino acids, dicarboxylic acids, fatty acids, volatile fatty acids, glycerides, carbohydrate and ch”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Saleem et al., 2013 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    Metatranscriptomes provide insight into the actual function of microbiomes via gene expression, whereas metagenomics allows evaluation of diversity and potential functional capacity.

    “Whilst metagenomics allows us to evaluate diversity and the potential functional capacity of a microbiome, metatranscriptomes provide insight into the actual function of microbiomes via gene expression.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Hi-C binning has been used effectively on human feces and in ruminants.

    “Hi-C binning has been used effectively on human feces (Press et al., 2017) as well as in ruminants (Stewart et al., 2018).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Press et al., 2017 source

      Not checked in the free run.

    • cites Stewart et al., 2018 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Integration of different omics data types has provided novel insights missed by either approach alone, such as Shi et al. (2014) demonstrating that differences in methane production were not due to differences in abundances of genes responsible, but rather a result of their differential expression.

    “This level of data integration has provided some novel insights missed by either approach alone, such as by Shi et al. (2014) who demonstrated that differences in methane production were not due to differences in the abundances of the genes responsible, but rather a result of their differential expression.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Shi et al., 2014 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Ribosome profiling (riboseq) has been developed as a direct method to quantify and characterize translation.

    “Ribosome profiling (riboseq) has been developed as a direct method to quantify and characterize translation (Ingolia et al., 2009).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Ingolia et al., 2009 source

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The success of metagenomic binning procedures is validated by investigating the number of single-copy core-genome genes within each bin, as implemented by CheckM.

    “The success of such binning procedures is validated by investigating the number of single-copy core-genome genes within each bin, as implemented by software such as CheckM (Parks et al., 2015).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Parks et al., 2015 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Artegoitia et al. (2017) reported 33 metabolites differing in cattle having high or low average daily gain.

    “Recently, Artegoitia et al. (2017) reported 33 metabolites differing in cattle having high or low average daily gain.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Artegoitia et al., 2017 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The majority of rumen metabolome studies have used LC-MS, GC-MS, and NMR, with NMR the most used due to reliability and absolute quantification.

    “To date, the majority of rumen metabolome studies have used liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR), with the latter the most used due to reliability and absolute quantification (Goldansaz et al., 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Goldansaz et al., 2017 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationnone given

    The development of MetaRibo-Seq at a metatranscriptomic level is in its infancy and still requires validation for the rumen microbiome.

    “Nonetheless, whilst the use of this technique on pure cultures has been effective, the development of the technique (MetaRibo-Seq) at a metatranscriptomic level is in its infancy and still requires validation for the rumen micobiome.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The rumen remains a source of valuable bioactives for the biotechnology industry, and metagenomics is a key tool for such bioprospecting.

    “The rumen also remains a source of valuable bioactives for the biotechnology industry, and metagenomics is a key tool for such bioprospecting (Oyama et al., 2017; Roumpeka et al., 2017).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Oyama et al., 2017 source

      Not checked in the free run.

    • cites Roumpeka et al., 2017 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Svartstrom et al. (2017) assembled 99 microbial genomes from the moose rumen, Stewart et al. (2018) assembled 913 microbial genomes from the rumen of cattle, and Parks et al. (2017) assembled over 8,000 novel microbial genomes from 1,500 public datasets, some of which originated from the rumen.

    “Subsequently, Svartstrom et al. (2017) assembled 99 microbial genomes from the moose rumen, Stewart et al. (2018) assembled 913 microbial genomes from the rumen of cattle, and Parks et al. (2017) assembled over 8,000 novel microbial genomes from 1,500 public datasets, some of which originated from the rumen.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Svartstrom et al., 2017 source

      Not checked in the free run.

    • cites Stewart et al., 2018 source

      Not checked in the free run.

    • cites Parks et al., 2017 source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationreasoning

    The terminology of microbiome is often misused within the rumen context because there is a tendency to focus on rumen bacteria alone without consideration of eukaryotes, which limits our ability to understand the rumen microbiome as these groups interact and affect production and environmental impact.

    “The terminology of microbiome is often misused within the rumen context as there is a tendency to focus on the study of the rumen bacteria alone, without consideration of the eukaryotes. This undoubtedly limits our ability to understand the rumen microbiome, as these groups of microbes interact with each other, consequently affecting production and the environmental impact of ruminants (Table 4).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Improving our ability to measure phenotype using rumen microbiome gene-based biomarkers may allow high-throughput phenotype predictions.

    “Improving our ability to measure phenotype using rumen microbiome gene based biomarkers may also allow high throughput phenotype predictions (Table 4).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationnone given

    Much emphasis has been given to using plant/additive/supplement strategies to manipulate the rumen microbiome to improve efficiency of animal production, but these have had limited success when applied to the mature animal.

    “Irrespective, much emphasis has been given to using plant/additive/supplement strategies to manipulate the rumen microbiome in a manner that improves efficiency of animal production. Although, these have had limited success when applied to the mature animal, recent data show that ruminant breeding programs coupled with a defined dietary management protocols from birth may be the best ways to”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Recent data show that ruminant breeding programs coupled with defined dietary management protocols from birth may be the best ways to achieve lifelong animal phenotype benefits with limited financial and labor input.

    “Although, these have had limited success when applied to the mature animal, recent data show that ruminant breeding programs coupled with a defined dietary management protocols from birth may be the best ways to achieve lifelong animal phenotype benefits with limited financial and labor input.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    The ruminant sector has made major strides to improving animal phenotype through understanding the rumen microbiome, and further advances will no doubt be accomplished given exponential advances in omic technologies.

    “Irrespective, the ruminant sector has made major strides to improving animal phenotype, through understanding the rumen microbiome, and further advances will no doubt be accomplished, especially given the exponential advances in “omic” technologies.”
    Quote in the paperNot a substantial claim
98 of 98

  • The paper relies on this without support.

    The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages.

    “The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages.”

  • The paper relies on this without support.

    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.

    “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.”

  • The paper relies on this without support.

    Ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security.

    “Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security.”

  • The paper relies on this without support.

    Total agricultural production (including crops and animals) will need to be 60% higher than in 2005.

    “the Food and Agriculture Organization of the United Nations (FAO) predicts that total agricultural production (including crops and animals) will need to be 60% higher than in 2005.”

  • The paper relies on this without support.

    The rumen epithelium plays an important role in both nutrient uptake and immunity.

    “In addition, the rumen epithelium plays an important role in both nutrient uptake and immunity.”

  • The paper relies on this without support.

    The microbial composition of the post-ruminal gastrointestinal tract is shaped by pH, gut motility, redox potential, and host secretions present in different compartments of the digestive tract.

    “The microbial composition of the post-ruminal gastrointestinal tract is shaped by pH, gut motility, redox potential, and host secretions present in different compartments of the digestive tract.”

  • The paper relies on this without support.

    Compared to the rumen, the proportion of Bacteroidetes decreases and that of Firmicutes and Proteobacteria increases in the post-rumen.

    “In general terms, compared to the rumen, the proportion of Bacteroidetes decrease and that of Firmicutes and Proteobacteria increase.”

  • The paper relies on this without support.

    The microbial diversity within the rumen offers the animal resilience from dietary related perturbations, such as acidosis.

    “The microbial diversity within the rumen offers the animal resilience from dietary related perturbations, such as acidosis.”

  • The paper relies on this without support.

    The sheer size of the rumen and its connectedness with the vascular, respiratory and immune systems mean that it is well-placed to both affect, and be affected by, animal function.

    “The sheer size of the rumen (12–15% of body mass) and connectedness with the vascular, respiratory and immune systems mean that it is well-placed to both affect, and be affected by, animal function.”

  • The paper relies on this without support.

    There is a growing number of examples where the interaction between host and intestinal microbial metabolism can be used to explain, or act as a biomarker for, complex traits such as nutrient efficiency, responses to stressors such as disease and adverse environments, as well as to predict animal behavior.

    “There is a growing number of examples where the interaction between host and intestinal microbial metabolism can be used to explain, or act as a biomarker for, complex traits such as nutrient efficiency, responses to stressors such as disease and adverse environments, as well as to predict animal behavior.”

  • The paper relies on this without support.

    Recent advances in analytical technologies and bioinformatics have greatly expanded capacity to investigate the role of the rumen and its microbiome in complex traits by studying the composition of microbial DNA and RNA, as well as microbial metabolites in blood or urine.

    “Recent advances in analytical technologies and bioinformatics have now greatly expanded our capacity to investigate the role of the rumen and its microbiome in complex traits by studying the composition of microbial DNA and RNA (metataxonomics, metagenomics and metatranscriptomics), as well as microbial metabolites in blood or urine (metabolomics).”

  • The paper relies on this without support.

    Due to the vastness of these datasets it is difficult to compare and investigate whether studies commonly find consensus genes that would serve as good global biomarkers in their correlation studies.

    “Due to the vastness of these datasets it is difficult to compare and investigate whether studies commonly find consensus genes that would serve as good global biomarkers in their correlation studies.”

  • The paper relies on this without support.

    Many rumen bacteria remain uncultured and uncharacterized, and genomic information on rumen eukaryotes is especially sparse in the Hungate1000 genomes due to challenges of sequencing A-T rich genomes.

    “However, many of the rumen bacteria remain uncultured and uncharacterized, with genomic information on the rumen eukaroytes being especially sparse in the Hungate1000 genomes as a result of the challenges of sequencing the A-T rich genomes of these microbes.”

  • The paper relies on this without support.

    Microbial metabolism is bound by constraints including thermodynamics, substrate and enzyme availability.

    “The COBRA methods rely on the principle that microbial metabolism is bound by constraints that include thermodynamics, substrate and enzyme availability.”

  • The paper relies on this without support.

    COBRA methods mainly operate under steady-state.

    “These methods mainly operate under steady-state.”

  • The paper relies on this without support.

    Annealing temperatures and number of PCR cycles bias results.

    “The annealing temperatures and number of cycles used for PCR are also clearly going to bias results somewhat.”

  • The paper relies on this without support.

    Large culture collections may be limited to or biased toward strains that are easy to culture, highly abundant organisms, and organisms of specific research interest.

    “However, they may also be limited to, or biased toward, strains that are easy to culture, highly abundant organisms and organisms which are of specific interest to research.”
17 of 17

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Highly efficient animals produce less CH4 and produce more milk, consuming less feed owing to their unique set of rumen microbiome.

    “Highly efficient animals produce less CH4 and produce more milk, consuming less feed owing to their unique set of rumen microbiome (13).”

    From Phytogenic Additives Can Modulate Rumen Microbiome to Mediate Fermentation Kinetics and Methanogenesis Through Exploiting Diet–Microbe Interaction (2020) · cites this paper as [13]

    In “Global agricultural challenges” (page not provided), the review says more feed-efficient steers require less feed to achieve the same production parameters—not that they produce more milk. In “Developing microbiome biomarkers for prediction of ruminant phenotype” (page not provided), it links rumen microbial differences to feed efficiency and suggests some may also reduce methane, but presents that connection cautiously rather than as a general trait of highly efficient animals. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Sharpea association conflicts with the cited study title

    Minor

    The text says Sharpea is less dense in low-methane animals, whereas the cited study describes low-methane sheep as having a Sharpea-enriched microbiome.

  • Yu and Morrisson 2004a is cited for the wrong study

    Minor

    The text attributes a comparison of DNA extraction methods to Yu and Morrisson (2004a), but the listed 2004a reference concerns comparisons of gene regions for microbial fingerprinting. The bibliography lists DNA extraction under 2004b.

2 of 2

Cites

Flagged first, then by citations

1 of the 299 references couldn’t be matched to a known paper.

Research works printed but not linked: 6

  1. Gruby, 1843, Recherches ser des animalcules se de veloppant en grand nombre dans l'estomac et dans les intestins, pedant la digestion des animaux herbivores et carnivores, Compt. Rend. Acad. Sci., 17, 1304
  2. Hristov, 2013, Mitigation of greenhouse gas emissions in livestock production. A review of options for non-CO2 emissions, 226
  3. Hungate, 1966, The Rumen and its Microbes
  4. 2006, Guidelines for National Greenhouse Inventories
  5. Russell, 1993, Microbial energetics
  6. 2015, World Food Programme Hunger Map

Cited by

Sorted by citations

Related

Authors
Huws, S. A., Creevey, C. J., Oyama, L. B., Mizrahi, I., Denman, S. E., Popova, M., Muñoz-Tamayo, R., Forano, E., Waters, S. M., Hess, M., Tapio, I., Smidt, H., Krizsan, S. J., Yáñez-Ruiz, D. R., Belanche, A., Guan, L., Gruninger, R. J., McAllister, T. A., Newbold, C. J., Roehe, R., Dewhurst, R. J., Snelling, T. J., Watson, M., Suen, G., Hart, E. H., Kingston-Smith, A. H., Scollan, N. D., do Prado, R. M., Pilau, E. J., Mantovani, H. C., Attwood, G. T., Edwards, J. E., McEwan, N. R., Morrisson, S., Mayorga, O. L., Elliott, C., & Morgavi, D. P.
Affiliations
  • Queen's University Belfast (GB)
  • Ben-Gurion University of the Negev (IL)
  • Commonwealth Scientific and Industrial Research Organisation (AU)
  • VetAgro Sup (FR)
  • University of California, Davis (US)
  • Natural Resources Institute Finland (FI)
  • Wageningen University & Research (NL)
  • Swedish University of Agricultural Sciences (SE)
  • Consejo Superior de Investigaciones Científicas (ES)
  • University of Alberta (CA)
  • Agriculture and Agri-Food Canada (CA)
  • Scotland's Rural College (GB)
  • Roslin Institute (GB)
  • University of Wisconsin–Madison (US)
  • Aberystwyth University (GB)
  • Universidade Estadual de Maringá (BR)
  • Robert Gordon University (GB)
  • Corporación Colombiana de Investigación Agropecuaria – AGROSAVIA (CO)
Corresponding author
Huws, Sharon A.
ORCID
Venue
Frontiers in Microbiology
Publisher
Frontiers Media SA
Published
2018-09-25
Volume
9
Pages
2161-2161
ISSN
1664-302X (ISSN-L)
DOI
10.3389/fmicb.2018.02161
PMC
PMC6167468
OpenAlex
W2889449548
Cited by
487
References
299
Citations by year
2026: 63 · 2025: 54 · 2024: 94 · 2023: 63 · 2022: 62 · 2021: 50 · 2020: 57 · 2019: 41 · 2018: 2 · 2017: 1
FWCI
5.73
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Microbiology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
  • Research Portal (Queen's University Belfast) (publishedVersion, cc-by)
  • Open Access Institutional Repository at Robert Gordon University (Robert Gordon University) (publishedVersion, cc-by)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
  • Socio-Environmental Systems Modeling (submittedVersion, cc-by)
  • HAL (submittedVersion, cc-by)
  • Americanae (AECID Library) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • Jukuri (Natural Resources Institute Finland (Luke)) (submittedVersion)
  • Open Access Institutional Repository at Robert Gordon University (Robert Gordon University) (submittedVersion, cc-by)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
Funders
  • U.S. Department of Agriculture (67015-23246)
  • Rural and Environment Science and Analytical Services Division
  • Scottish Government
  • European Commission (EU-H2020, 706899, HORIZON2020, H2020)
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (ALW.GAS.5)
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico
  • Scotland’s Rural College
  • Directorate for Biological Sciences
  • National Institute of Food and Agriculture (2015-67015-23246, 67015-23246)
  • Horizon 2020 Framework Programme (EU‐H2020, 640384)
  • Biotechnology and Biological Sciences Research Council (BBS/E/D/30002276, BBS/E/W/10964A01B, BBS/OS/GC/000011B, 172629373, BBS/E/W/0012843D, BB/N016742/1, BB/N01720X/1, BB/L026716/1, BB/L026716/2, BBS/E/D/20310000, BBSRC BB/N01720X/1)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Ruminant Nutrition and Digestive Physiology
  • Physical Sciences › Engineering › Building and Construction › Anaerobic Digestion and Biogas Production
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
Keywords
rumen microbiome, ruminants, animal husbandry, methane mitigation, methanogenic archaea, microbial interactions, dietary intervention, animal breeding, high-throughput phenotyping, omics, food security, environmental impact of livestock

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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