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Anaerobic fungi (AF) play an essential role in feed conversion due to their potent fiber degrading enzymes and invasive growth. Much has been learned about this unusual fungal phylum since the paradigm shifting work of Colin Orpin in the 1970s, when he characterized the first AF. Molecular approaches targeting specific phylogenetic marker genes have facilitated taxonomic classification of AF, which had been previously been complicated by the complex life cycles and associated morphologies. Although we now have a much better understanding of their diversity, it is believed that there are still numerous genera of AF that remain to be described in gut ecosystems. Recent marker-gene based studies have shown that fungal diversity in the herbivore gut is much like the bacterial population, driven by host phylogeny, host genetics and diet. Since AF are major contributors to the degradation of plant material ingested by the host animal, it is understandable that there has been great interest in exploring the enzymatic repertoire of these microorganisms in order to establish a better understanding of how AF, and their enzymes, can be used to improve host health and performance, while simultaneously reducing the ecological footprint of the livestock industry. A detailed understanding of AF and their interaction with other gut microbes as well as the host animal is essential, especially when production of affordable high-quality protein and other animal-based products needs to meet the demands of an increasing human population. Such a mechanistic understanding, leading to more sustainable livestock practices, will be possible with recently developed -omics technologies that have already provided first insights into the different contributions of the fungal and bacterial population in the rumen during plant cell wall hydrolysis.

Anaerobic fungi (Neocallimastigomycota) are common inhabitants of the digestive tract of large mammalian herbivores, where they make an important contribution to plant biomass degradation. The internal transcribed spacer 1 (ITS1) region is currently the molecular marker of choice for anaerobic fungal community analysis, despite its known size polymorphism and heterogeneity. The aim of this study was to assess the accuracy of high-throughput sequencing of the ITS1 region of anaerobic fungi for community composition analysis. To this end, full-length ITS1 clone libraries from five pure cultures, representing the ITS1 region size range, were Sanger sequenced to generate a reference dataset. Barcoded amplicons of the same five pure cultures, and four different mock communities derived from them, were then sequenced using Illumina HiSeq. The resulting sequences were then assessed in relation to either the reference dataset (for the pure cultures) or the corresponding theoretical mock communities. Annotation of sequences obtained from individual pure cultures was not always consistent at the clade or genus level, irrespective of whether data from clone libraries or high-throughput sequencing were analyzed. The detection limit of the high-throughput sequencing method appeared to be influenced by factors other than the parameters used during data processing, as some taxa with theoretical values >0.6% were not detected in the mock communities. The high number of PCR cycles used was considered to be a potential explanation for this observation. Accuracy of two of the four mock communities was limited, and this was speculated to be due to preferential amplification of smaller sized ITS1 regions. If this is true, then this is predicted to be an issue with only six of the 32 named anaerobic fungal clades. Whilst high-throughput sequencing of the ITS1 region from anaerobic fungi can be used for environmental sample analysis, we conclude that the accuracy of the method is influenc

Alfalfa (Medicago sativa L.) silage (AS) is an important feedstuff in ruminant nutrition. However, its high non-protein nitrogen content often leads to poor ruminal nitrogen retention. Various pre-ensiling treatments differing with respect to dry matter concentrations, wilting intensities and sucrose addition have been previously shown to improve the quality and true protein preservation of AS, and have substantial effects on in vitro ruminal fermentation of the resulting silages. However, it is unknown how these pre-ensiling treatments affect the ruminal microbiota composition, and whether alterations in the microbiota explain previously observed differences in ruminal fermentation. Therefore, during AS incubation in a rumen simulation system, liquid and solid phases were sampled 2 and 7 days after first incubating AS, representing an early (ET) and late (LT) time point, respectively. Subsequently, DNA was extracted and qPCR (bacteria, archaea, and anaerobic fungi) and prokaryotic 16S rRNA gene amplicon sequence analyses were performed. At the ET, high dry matter concentration and sucrose addition increased concentrations of archaea in the liquid phase (P = 0.001) and anaerobic fungi in the solid phase (P < 0.001). At the LT, only sucrose addition increased archaeal concentration in the liquid phase (P = 0.014) and anaerobic fungal concentration in the solid phase (P < 0.001). Bacterial concentrations were not affected by pre-ensiling treatments. The prokaryotic phylogenetic diversity index decreased in the liquid phase from ET to LT (P = 0.034), whereas the solid phase was not affected (P = 0.060). This is suggestive of a general adaption of the microbiota to the soluble metabolites released from the incubated AS, particularly regarding the sucrose-treated AS. Redundancy analysis of the sequence data at the genus level indicated that sucrose addition (P = 0.001), time point (P = 0.001), and their interaction (P = 0.001) affected microbial community composition in

Understanding rumen plant-microbe interactions is central for development of novel methodologies allowing improvements in ruminant nutrient use efficiency. This study investigated rumen bacterial colonization of fresh plant material and changes in plant chemistry over a period of 24 h period using three different fresh forages: Lolium perenne (perennial ryegrass; PRG), Lotus corniculatus (bird's foot trefoil; BFT) and Trifolium pratense (red clover; RC). We show using 16S rRNA gene ion torrent sequencing that plant epiphytic populations present pre-incubation (0 h) were substantially different to those attached post incubations in the presence of rumen fluid on all forages. Thereafter primary and secondary colonization events were evident as defined by changes in relative abundances of attached bacteria and changes in plant chemistry, as assessed using Fourier transform infrared (FTIR) spectroscopy. For PRG colonization, primary colonization occurred for up to 4 h and secondary colonization from 4 h onward. The changes from primary to secondary colonization occurred significantly later with BFT and RC, with primary colonization being up to 6 h and secondary colonization post 6 h of incubation. Across all 3 forages the main colonizing bacteria present at all time points post-incubation were Prevotella, Pseudobutyrivibrio, Ruminococcus, Olsenella, Butyrivibrio, and Anaeroplasma (14.2, 5.4, 1.9, 2.7, 1.8, and 2.0% on average respectively), with Pseudobutyrivibrio and Anaeroplasma having a higher relative abundance during secondary colonization. Using CowPI, we predict differences between bacterial metabolic function during primary and secondary colonization. Specifically, our results infer an increase in carbohydrate metabolism in the bacteria attached during secondary colonization, irrespective of forage type. The CowPI data coupled with the FTIR plant chemistry data suggest that attached bacterial function is similar irrespective of forage type, with the main chan

Understanding rumen plant-microbe interactions is central for development of novel methodologies allowing improvements in ruminant nutrient use efficiency. This study investigated rumen bacterial colonization of fresh plant material and changes in plant chemistry over a period of 24 h period using three different fresh forages: Lolium perenne (perennial ryegrass; PRG), Lotus corniculatus (bird's foot trefoil; BFT) and Trifolium pratense (red clover; RC). We show using 16S rRNA gene ion torrent sequencing that plant epiphytic populations present pre-incubation (0 h) were substantially different to those attached post incubations in the presence of rumen fluid on all forages. Thereafter primary and secondary colonization events were evident as defined by changes in relative abundances of attached bacteria and changes in plant chemistry, as assessed using Fourier transform infrared (FTIR) spectroscopy. For PRG colonization, primary colonization occurred for up to 4 h and secondary colonization from 4 h onward. The changes from primary to secondary colonization occurred significantly later with BFT and RC, with primary colonization being up to 6 h and secondary colonization post 6 h of incubation. Across all 3 forages the main colonizing bacteria present at all time points post-incubation were Prevotella, Pseudobutyrivibrio, Ruminococcus, Olsenella, Butyrivibrio, and Anaeroplasma (14.2, 5.4, 1.9, 2.7, 1.8, and 2.0% on average respectively), with Pseudobutyrivibrio and Anaeroplasma having a higher relative abundance during secondary colonization. Using CowPI, we predict differences between bacterial metabolic function during primary and secondary colonization. Specifically, our results infer an increase in carbohydrate metabolism in the bacteria attached during secondary colonization, irrespective of forage type. The CowPI data coupled with the FTIR plant chemistry data suggest that attached bacterial function is similar irrespective of forage type, with the main changes

Metataxonomic 16S rDNA based studies are a commonplace and useful tool in the research of the microbiome, but they do not provide the full investigative power of metagenomics and metatranscriptomics for revealing the functional potential of microbial communities. However, the use of metagenomic and metatranscriptomic technologies is hindered by high costs and skills barrier necessary to generate and interpret the data. To address this, a tool for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was developed for inferring the functional potential of an observed microbiome profile, based on 16S data. This allows functional inferences to be made from metataxonomic 16S rDNA studies with little extra work or cost, but its accuracy relies on the availability of completely sequenced genomes of representative organisms from the community being investigated. The rumen microbiome is an example of a community traditionally underrepresented in genome and sequence databases, but recent efforts by projects such as the Global Rumen Census and Hungate 1000 have resulted in a wide sampling of 16S rDNA profiles and almost 500 fully sequenced microbial genomes from this environment. Using this information, we have developed "CowPI," a focused version of the PICRUSt tool provided for use by the wider scientific community in the study of the rumen microbiome. We evaluated the accuracy of CowPI and PICRUSt using two 16S datasets from the rumen microbiome: one generated from rDNA and the other from rRNA where corresponding metagenomic and metatranscriptomic data was also available. We show that the functional profiles predicted by CowPI better match estimates for both the meta-genomic and transcriptomic datasets than PICRUSt, and capture the higher degree of genetic variation and larger pangenomes of rumen organisms. Nonetheless, whilst being closer in terms of predictive power for the rumen microbiome, there were differences when compared to bot

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.

Diurnal patterns of ruminal fermentation metabolites and microbial communities are not commonly assessed when investigating variation in ruminal CH4 production. The aims of this study were to monitor diurnal patterns of: (i) gaseous and dissolved metabolite concentrations in the bovine rumen, (ii) H2 and CH4 emitted, and (iii) the rumen microbiota. Furthermore, the effect of dietary inclusion of linseed oil on these patterns was assessed. Four rumen cannulated multiparous cows were used in a cross-over design with two 17 days periods and two dietary treatments: a control diet and a linseed oil supplemented diet [40% maize silage, 30% grass silage, 30% concentrate on dry matter (DM) basis for both diets; fat contents of 33 vs. 56 g/kg of DM]. On day 11, rumen contents were sampled for 10 h after morning feeding to profile gaseous and dissolved metabolite concentrations and microbiota composition. H2 and CH4 emission (mass per unit of time) was measured in respiration chambers from day 13 to 17. A 100-fold increase in ruminal H2 partial pressure (contribution to the total pressure of rumen headspace gases) was observed at 0.5 h after feeding. This peak was followed by a decline to basal level. Qualitatively similar patterns after feeding were also observed for H2 and CH4 emission, ethanol and lactate concentrations, and propionate molar proportion, although the opposite pattern was seen for acetate molar proportion. Associated with these patterns, a temporal biphasic change in the microbial composition was observed as based on 16S ribosomal RNA with certain taxa specifically associated with each phase. Bacterial concentrations (log10 16S ribosomal RNA gene copies based) were affected by time, and were increased by linseed oil supplementation. Archaeal concentrations (log10 16S ribosomal RNA gene copies based) tended to be affected by time and were not affected by diet, despite linseed oil supplementation decreasing CH4 emission, tending to decrease the partial pressur

Anaerobic fungi (phylum Neocallimastigomycota) are common inhabitants of the digestive tract of mammalian herbivores, and in the rumen, can account for up to 20% of the microbial biomass. Anaerobic fungi play a primary role in the degradation of lignocellulosic plant material. They also have a syntrophic interaction with methanogenic archaea, which increases their fiber degradation activity. To date, nine anaerobic fungal genera have been described, with further novel taxonomic groupings known to exist based on culture-independent molecular surveys. However, the true extent of their diversity may be even more extensively underestimated as anaerobic fungi continue being discovered in yet unexplored gut and non-gut environments. Additionally many studies are now known to have used primers that provide incomplete coverage of the Neocallimastigomycota. For ecological studies the internal transcribed spacer 1 region (ITS1) has been the taxonomic marker of choice, but due to various limitations the large subunit rRNA (LSU) is now being increasingly used. How the continued expansion of our knowledge regarding anaerobic fungal diversity will impact on our understanding of their biology and ecological role remains unclear; particularly as it is becoming apparent that anaerobic fungi display niche differentiation. As a consequence, there is a need to move beyond the broad generalization of anaerobic fungi as fiber-degraders, and explore the fundamental differences that underpin their ability to exist in distinct ecological niches. Application of genomics, transcriptomics, proteomics and metabolomics to their study in pure/mixed cultures and environmental samples will be invaluable in this process. To date the genomes and transcriptomes of several characterized anaerobic fungal isolates have been successfully generated. In contrast, the application of proteomics and metabolomics to anaerobic fungal analysis is still in its infancy. A central problem for all analyses, however