Search bioRxiv⌕ Search

Biology subjects

Kirk, M. R.

Publications and source records attributed to Kirk, M. R..

2 recordsLinked to original sources

Diversity and community structure of anaerobic gut fungi in the rumen of wild and domesticated herbivores

The rumen houses a diverse community that plays a major role in the digestion process in ruminants. Anaerobic gut fungi (AGF) are key contributors to plant digestion in the rumen. Here, we present a global amplicon-based survey of the rumen mycobiome by examining 206 samples from 15 animal species, 15 countries and six continents. The rumen mycobiome was highly diverse, with 81 out of 88 currently recognized AGF genera or candidate genera identified. However, only six genera (Neocallimastix, Orpinomyces, Caecomyces, Cyllamyces, NY9, and Piromyces) were present at > 4% relative abundance. AGF diversity was higher in members of the families Antilocapridae and Cervidae compared to Bovidae. Community structure analysis identified a pattern of phylosymbiosis, where host family (10% of total variance) and species (13.5%) partially explained the rumen mycobiome composition. Domestication (11.14%) and biogeography (14.1%) also partially explained AGF community structure, although sampling limitation, geographic range restrictions, and direct association between domestication status and host species hindered accurate elucidation of the relative contribution of each factor. Pairwise comparison of rumen versus fecal samples obtained from the same subject (n=13) demonstrated greater diversity and inter-sample variability in rumen over fecal samples. The genera Neocallimastix and Orpinomyces were present in higher abundance in rumen samples, while Cyllamyces and Caecomyces were enriched in fecal samples. Comparative analysis of global rumen and feces datasets revealed a similar pattern. Our results provide a global view of AGF community in the rumen and identify patterns of AGF variability between rumen and feces in herbivores tract. ImportanceRuminants are highly successful and economically important mammalian suborder. Ruminants are herbivores that digest plant material with the aid of microorganisms residing in their GI tract. The rumen compartment represents the most important location where microbially-mediated plant digestion occurs in ruminants, and is known to house a bewildering array of microbial diversity. An important component of the rumen microbiome is the anaerobic gut fungi, members of the phylum Neocallimastigomycota. So far, studies examining AGF diversity have mostly employed fecal samples, and little is currently known regarding the identity of AGF residing in the rumen compartment, factors that impact the observed patterns of diversity and community structure of AGF in the rumen, and how AGF communities in the rumen compare to AGF communities in feces. Here, we examined the rumen AGF diversity using amplicon-based surveys targeting a wide range of wild and domesticated ruminants (n=206, 15 different animal species) obtained from 15 different countries. Our results demonstrate that while highly diverse, no new AGF genera were identified in the rumen mycobiome samples examined. Our analysis also indicate that animal host phylogeny plays a more important role in shaping AGF diversity in the rumen, compared to biogeography and domestication status. Finally, we demonstrate that a greater level of diversity and higher inter-sample variability was observed in rumen compared to fecal samples, with two genera (Neocallimastix and Orpinomyces) present in higher abundance in rumen samples, and two others (Cyllamyces and Caecomyces) enriched in fecal samples. Our results provide a global view of the identity, diversity, and community structure of AGF in ruminants, elucidate factors impacting diversity and community structure of the rumen mycobiome, and identify patterns of AGF community variability between the rumen and feces in the herbivorous GIT tract.

microbiology↗

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62{+/-}0.06, heritability 0.31{+/-}0.29, and genetic and phenotypic correlation with methane emissions of 0.88{+/-}0.25 and 0.64{+/-}0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0{+/-}5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8{+/-}1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

microbiology↗