IMR Press / FBE / Volume 14 / Issue 3 / DOI: 10.31083/j.fbe1403022
Open Access Original Research
Characterisation of the Faecal Microbiome of Foals from 0–5 Months of Age and Their Respective Mares across Five Geographic Locations
Show Less
1 School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Camperdown, NSW 2050, Australia
2 Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB 403, Canada
3 School of Agriculture and Food Sciences, Faculty of Science, University of Queensland, Gatton, QLD 4343, Australia
*Correspondence: (Alex V. Chaves)
Academic Editor: Yasuhito Shimada
Front. Biosci. (Elite Ed) 2022, 14(3), 22;
Submitted: 7 May 2022 | Revised: 20 May 2022 | Accepted: 23 May 2022 | Published: 18 August 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

Background: A foal undergoes considerable growth and development from birth to weaning, progressing from a milk-based diet to complete herbivory. The symbiotic relationships between bacteria, archaea and fungi substantiate this energy demand by colonising the hindgut and remaining flexible throughout the diet transitions. Methods: A total of 70 faecal samples were collected from 14 mares and their foals across five studs in NSW as they aged from 0 to 5 months old. DNA was extracted from faecal samples and underwent amplification and sequencing of the 16S rRNA gene V4 hypervariable region of archaea and bacteria, and the fungal internal transcribed spacer-1 (ITS1) region. The fungal and bacterial community structure was assessed using Bray-Curtis dissimilarities, and the effect of age at sampling and location was determined using PERMANOVA. Results: Age at sampling had a substantial effect on the foal’s archaeal and bacterial faecal microbiota (PERMANOVA: R2 = 0.16; p < 0.01), while the effect of geographical location was smaller but still significant (PERMANOVA: R2 = 0.07; p < 0.01). The overall abundance, diversity and richness of bacterial and archaeal populations increased (p < 0.01) as foals aged, most noticeably rising between foals 1 to 2 and 2 to 3 months of age. The 15 most relatively abundant fungal species were all environmental saprophytes, most strongly affected by geographical location (p < 0.01) rather than age at sampling. There was an effect of location on Preussia Africana (p = 0.02) and a location × age interaction for fungal species Preussia persica (p < 0.01), Acremonium furcatum (p = 0.04), and Podospora pseudocomata (p = 0.01). There was no effect of age, location, or location × age interaction on the relative abundance of the remaining fungal species. Conclusions: The faecal microbiome appeared to stabilise for most bacterial and archaeal genera by 2 to 3 months of age, resembling an adult mare. Bacterial genera isolated from faecal samples belonged mainly to the Firmicutes phylum. Age at sampling more strongly affected the archaeal and bacterial faecal microbiota than the effect of the geographical location where the horse was sampled. The lack of effect of location on microbe populations suggests that although environmental factors may influence population structure, there are distinct differences at each stage of foal maturation.

16S rRNA gene sequencing
fungal ITS sequences
1. Introduction

The gastrointestinal tract (GIT) microbiome represents one of the most complex and rapidly evolving biotic networks responsible for the inner workings of an animal and its functional health. Heavily involved in immune function, gut-brain connectivity and behaviour, disturbance of the equine microbiome has been linked to metabolic diseases such as laminitis, colic, equine metabolic syndrome, equine grass sickness and colitis [1, 2, 3]. The developmental period from birth to weaning represents an interval of considerable growth for horses, where foals progress from 10% of their mature body weight at birth to 50% at weaning [4]. The energy demand to substantiate this growth is met by dietary transitions from changing milk compositions to complete herbivory, supported by the microbial colonisation of the GIT. The symbiosis between bacterial, archaeal, and fungal populations maximises hindgut feed digestion, producing by-products such as volatile fatty acids and metabolites to maintain host health [5, 6, 7, 8].

Studies of the equine GIT microbiome have identified a ‘core’ bacterial population consisting primarily of the phyla Firmicutes, Bacteroidetes, Verrucomicrobia, Actinobacteria, Proteobacteria and Spirochaetes [9, 10, 11, 12, 13]. However, the functional characteristics of many bacterial and fungal taxa and their importance to the host are yet to be proven in horses [9, 11, 13]. Rather, the bulk of the current literature addresses only ruminant fermentation [14, 15]. This is significantly misleading the industry’s current understanding of the equine microbiome, causing a lag in disease treatment strategies, perception of microbial resistance, and general appreciation of the microbiome’s role in equine health. Further, comparing the findings of previous investigations of the equine microbiome is compromised by the considerable influence of diet, climate, and management practices on the intestinal microbiota [16, 17]. This study is both a continued exploration of the equine microbiome and a novel investigation into the establishment of the mycobiome in neonate foals utilising high-throughput sequencing technology.

While bacterial populations in the foal hindgut have received considerable attention [16, 18, 19, 20], fungal colonisation remains relatively overlooked. Of the few studies reporting on the mycobiome, most only describe populations in adult horses or pathogenic overgrowth in compromised hosts [21, 22, 23, 24]. Fungi are instrumental in substantiating diet transitions by increasing the digestibility of foliage through the production of cellulolytic and hemicellulolytic enzymes [25, 26]. A better understanding of the symbiotic relationships between bacteria and fungi and the metabolites they produce is needed to more effectively manage GIT conditions and the effects that any perturbation, such as antibiotics, may have on the hosts’ internal microbiome [27, 28, 29].

The authors believe this is the first study to simultaneously characterise the colonisation of bacterial and fungal species during a principal developmental period. It is hypothesised that stages of gut maturation will be classifiable based on the analyses of the faecal microbiota of foals from birth to weaning. It is expected the bacterial colonisation of the hindgut will follow ‘core microbiome’ patterns, like those previously described, despite the effect of geographical location [16, 18, 19, 20].

A more inclusive exploration of the temporal evolution of microbial diversity in foals and the interactions between bacteria and fungi will aid in bridging the knowledge gap between hindgut fermenters and current ruminant and monogastric-based research. This study will also contribute to a better understanding of the progressive colonisation of the equine microbiome, irrespective of environmental factors [11, 30] and propose a similar notion for fungal populations that are overlooked in current literature.

2. Materials and Methods
2.1 Faecal Sample Collection

Faecal samples were collected from mares and foals at five Thoroughbred breeding farms across New South Wales, Australia, throughout one foaling season from late 2017 to early 2018. Farms were located in the Central West, Hunter Valley and Southern Highlands regions. A total of 70 samples were collected. Fourteen foals were sampled consecutively from their first month of life across a period of 3–5 months. Each corresponding mare was also sampled at the final foal sampling. Samples were collected from three mares and three foals at Stud 1, Stud 2, Stud 3, and Stud 4, with samples collected from two mare and foal pairs at Stud 5. The number of samples per foal ranged from 3 to 6, sampling age ranging from 7–30 days for the 0–1 m old category (n = 15), 36–58 days old for 1–2 m (n = 14), 66–83 days old for 2–3 m (n = 18), 92–121 days old for 3–4 m (n = 14), and 123–148 days old for the 4–5 m category (n = 9).

Faeces were collected with as little disturbance to the animal as possible, consistent with procedures approved by the University of Sydney Animal Ethics Committee (Project Number 1319). Targeted individuals were observed in holding yards during morning musters or later in the day within their allocated yards or paddocks until the time of defecation. Faeces were collected from the ground immediately after excretion, with the exception of 5 samples that were collected after 1–2 hours from smaller yards only containing the one mare and foal pair. A minimum of 10 g of faeces was collected with a gloved hand or a clean plastic spoon sterilised with 70% (w/v) ethanol. The exterior faecal layer was removed to ensure the samples were collected from where the specimen was least likely to have had contact with environmental contaminants. Samples were placed in sterile polypropylene falcon tubes or containers (Sarstedt, Australia) and stored on ice temporarily (approximately 1–3 hours) before transfer to a –20 °C freezer, as commonly practised [18, 31]. Details noted for each sample included age, farm, pen or field location and the clinical state of the animal.

2.2 Microbial Analysis and DNA Extraction

Samples were stored at –20 °C until placed in a freeze dryer (72 h). Samples were then finely ground using a coffee grinder and placed back into the freezer until extraction. Genomic DNA was extracted from faecal samples through repetitive bead beating, as described by Yu and Morrison [32]. Briefly, the sample (300 mg) was weighed into a sterile 2 mL microcentrifuge tube, inclusive of 300 mg of 0.5 mm and 0.1 mm silica beads. 1.1 mL InhibitEx buffer was then added, and samples were subjected to bead beating (10 min), incubation (2–8 ℃ for 5 min) and centrifugation (1 min at 10,000 ×g). The supernatant (600 μL) was then transferred into a sterile 2 mL microcentrifuge tube, along with 25 μL Proteinase-K. Samples were loaded into a QIAcube (Qiagen, Hilden, Germany) and DNA was extracted using the DNeasy PowerSoil Pro Kit (Qiagen, Hilden, Germany) and analysed for DNA yield through the use of a NanoDrop (Thermo Scientific NanoDrop Products) as described by Desjardins and Conklin [33]. The purity and integrity of DNA were quantified through methods described by Henderson et al. [34].

2.3 Sequencing of the Archaeal and Bacterial 16S rRNA Gene and Fungal ITS1 Region

The V4 hypervariable region of the archaeal and bacterial 16S rRNA gene and the internal transcribed spacer 1 (ITS1) (ITS1-5’-CTTGGTCATTTAGAGGAAGTAA; ITS2-5’-GCTGCGTTCTTCATCGATGC-3’) region for fungi were amplified and sequenced as previously described [35] using an Illumina MiSeq instrument and v2 Reagent Kit with 500 cycles (Illumina, Inc., San Diego, CA, USA). DADA2 v. 1.16.0 ( [36] in R v. 4.0.3 was used to process and quality-filter all sequences. Primer sequences were removed from all reads using cutadapt v. 2.10 [37]. The forward and reverse 16S rRNA gene sequences were trimmed to 200 and 210 bp, respectively, merged with a minimum overlap of 100 bp, and chimeras removed. Taxonomy was assigned to these remaining sequences, referred to here as operational taxonomic units (OTUs) at 100% similarity, using the RDP naïve Bayesian classifier and the SILVA SSU database release 138 [38]. OTUs classified as chloroplasts and mitochondria were removed prior to analyses. For the ITS1 sequences, reads were not trimmed, and the UNITE database release 8.2 [39] was used for assigning taxonomy.

The number of OTUs per sample, Shannon diversity index, and the inverse Simpson’s diversity index were calculated in R using vegan 2.5-7 and Phyloseq 1.34.0 [40]. The fungal and bacterial community structure was assessed using Bray-Curtis dissimilarities, which were calculated with vegan, and the effect of age at sampling and location was determined using PERMANOVA (adonis2 function). The pairwise.adonis function in the pairwiseAdonis package v. 0.4 [41] was used to compare each sampling time. To account for unequal sequencing depth, the 16S rRNA gene sequence samples were randomly subsampled to 10,500 sequences per sample and the ITS1 sequence samples to 7500, prior to calculation of the diversity measures and Bray-Curtis dissimilarities.

All 16S rRNA gene and ITS1 sequences were submitted to the Sequence Read Archive under BioProject accession PRJNA699302.

3. Results
3.1 Sequencing Summary

A total of 70 faecal samples collected from 14 mares and their foals across five NSW Thoroughbred breeding farms (i.e., studs) in 2017 were analysed. The average number of 16S rRNA gene sequences per sample were 30,579 ± 3655 SEM with a total of 7751 OTUs. For the fungal taxa, the average number of ITS1 region sequences per sample was 35,837 ± 1972 SEM, within 1831 OTUs in total. The relative abundances of the top 15 bacteria, archaea genera, and top 15 fungal species within each age category are presented in Figs. 1,2, respectively.

Fig. 1.

The 15 most relatively abundant archaeal and bacterial genera in the equine faecal microbiota by age at sampling and geographic location.

Fig. 2.

The 15 most relatively abundant fungal species in the equine faecal microbiota by age at sampling and geographic location.

3.2 Effect of Age and Geographic Location on the Equine Faecal Archaeal and Bacterial Microbiota

The archaeal and bacterial faecal microbiota was most strongly affected by age at sampling (PERMANOVA: R2 = 0.16; p < 0.01), and there was a smaller but significant effect of the geographical location where the horse was sampled (PERMANOVA: R2 = 0.07; p < 0.01) (Fig. 3). Not surprisingly, the faecal microbiota of the mares differed the most from that of the 0 to 1 month old foals (PERMANOVA: R2 = 0.19; p < 0.01), then 1 to 2 m (PERMANOVA: R2 = 0.14; p < 0.01) and 2 to 3 m (PERMANOVA: R2 = 0.09; p < 0.01). However, once the foals had reached 3 to 4 months of age, their faecal microbiota was no longer different from the mares (p > 0.05). Table 1 presents the foal faecal archaeal and bacterial diversity (inverse Simpson’s and Shannon diversity indices) and richness (number of OTUs) over the duration of the study. The overall archaeal and bacterial richness notably increased as the foals aged, becoming similar to the mares by 2 to 3 months of age (Table 1). The percentage relative abundance (PRA) and diversity, in terms of richness and uniformity, of certain archaeal and bacterial genera also increased as the foals aged, stabilising by 2 to 3 months post-partum.

Fig. 3.

Non-metric multidimensional scaling (NMDS) of the Bray-Curtis dissimilarities for the equine archaeal and bacteria faecal microbiota by age at sampling and geographic location.

Table 1.Faecal archaeal and bacterial diversity (inverse Simpson’s and Shannon diversity indices) and richness (Operational Taxonomic Units, number of OTUs) at different ages.
Age p-value
0 to 1 1 to 2 2 to 3 3 to 4 4 to 5 Mare SEM Location Age Location × Age
OTUs 300.4c 394.5bc 503.5ab 575.7a . 619.3a 50.03 0.17 <0.01 0.88
Shannon 4.0c 4.7b 5.2ab 5.4a . 5.6a 0.23 0.66 <0.01 0.99
Inverse Simpson’s 46.3c 44.3c 94.1b 123.3ab . 143.1a 17.40 0.26 <0.01 0.35

The PRA of 15 of the most relatively abundant archaeal and bacterial genera are presented in Fig. 1. Age had a significant effect on the PRA of the genera Akkermansia (p = 0.04), Blautia (p < 0.01), Christensenellaceae R-7 group (p < 0.01), Lachnospiraceae AC2044 and Lachnospiraceae XPB1014 groups (p < 0.01), Oscillospiraceae NK4A214, Oscillospiraceae UCG-002 and Oscillospiraceae UCG-005 groups (p < 0.01), Phascolarctobacterium (p = 0.01), and Rikenellaceae RC9 gut group (p = 0.03). The PRA of Akkermansia and Blautia was higher in foals at 0 to 1 m than all other sampling ages, including the mares. The PRA of Christensenellaceae R-7 group in foals at 1 to 2 m and 2 to 3 m was significantly higher than the mares and foals at 0 to 1 m, respectively. The PRA of Lachnospiraceae AC2044 and XPB1014 groups was greatest in mares, while these genera were enriched in 2- to 3-month-old foals compared to animals at 1 to 2 m, which was also greater than at 0 to 1 m. Oscillospiraceae NK4A214 group, Oscillospiraceae UCG-002 and Oscillospiraceae UCG-005 were more pronounced in 1 to 2 m foals than mares and foals at all other ages. Foals at 0 to 1 m and mares had a higher PRA of Phascolarctobacterium than those at 1 to 2 and 2 to 3 m. The PRA of Rikenellaceae RC9 gut group was greater in 3- to 4-month-old animals compared to foals at 0 to 1 and 1 to 2 m.

Escherichia-Shigella had a tendency (p = 0.07) to have a greater PRA in 0 to 1 month-old foals, while the PRA of Mogibacterium (p = 0.05) tended to be higher in foals at 2 to 3 m compared to mares and animals at 0 to 1 and 1 to 2 m. Location was a significant factor on the PRA of Lachnospiraceae XPB1014 group and Lachnospiraceae AC2044 group (p < 0.01), where the PRA was higher in animals at Stud 1 than those at Stud 2. At the same time, Phascolarctobacterium had a tendency (p = 0.06) to be higher in foals at Stud 3 than the other studs.

3.3 Effect of Age and Geographic Location on the Equine Faecal Fungal Microbiota

Although significant, age at sampling had a smaller effect on the faecal fungal microbiota (PERMANOVA: R2 = 0.08 p = 0.04) and there was a larger effect of geographic location (PERMANOVA: R2 = 0.11; p < 0.01) (Fig. 4). Surprisingly, all of the 15 most relatively abundant fungal species were environmental microfungi (Fig. 2). There were no effects of location, age or location × age interaction on the PRA of the species Ascochyta medicaginicola var. macrospora (p = 0.67; p = 0.73; p = 0.86), Corynascella inquinata (p = 0.91; p = 0.66; p = 0.99), Humicola olivacea (p = 0.42; p = 0.34; p = 0.83), Naganishia adeliensis (p = 0.88; p = 0.15; p = 0.73), Naganishia albida (p = 0.88; p = 0.39; p = 0.85), Nigrospora oryzae (p = 0.71; p = 0.30; p = 0.92), Parastagonospora phoenicicola (p = 0.57; p = 077; p = 0.83), Podospora decipiens (p = 0.93; p = 0.36; p = 0.95) Saitozyma flava (p = 0.94; p = 0.71; p = 0.99) and Trichobolus zukalii (p = 0.38; p = 0.31; p = 0.67). There was an effect of location on Preussia africana (p = 0.02), where the PRA was lower in foals at Stud 3 compared to Stud 5 and Stud 2. The PRA of Gibberella intricans tended to be greater in animals at Stud 2 than those at Stud 1 (p = 0.07). There was a location × age interaction for fungal species Preussia persica (p < 0.01), Acremonium furcatum (p = 0.04), and Podospora pseudocomata (p = 0.01). The relative abundance of P. persica in foals on Stud 2 increased to become like the adult mares by 3 to 4 m. A similar pattern was seen in foals at Stud 3, where the PRA was greater (p < 0.01) in 4 to 5 m foals and the mares, compared to all other ages. There was no clear effect of foal age on the PRA of P. persica at Stud 1, with the species spiking in 0 to 1 m and 2 to 3 m old foals and the mares. Stud 5 saw a peak in the relative abundance of P. persica in 3 to 4 m foals only. The relative abundance of A. furcatum remained higher in the mares of Stud 4 and Stud 5 compared to their respective foals. There were no differences in the PRA of A. furcatum at the remaining locations. The relative abundance of P. pseudocomata was greater in Stud 2 and Stud 3 animals than Stud 1 and Stud 5. Foals sampled at 4 to 5 m at Stud 3 had a greater relative abundance of P. pseudocomata than at Stud 2 and Stud 1, respectively, while the fungal species was also more prevalent in mares at Stud 4 than at Stud 1, Stud 5 and Stud 3. The relative abundance of P. pseudocomata remained similar across foals at all locations until the 4 to 5 m sampling point, at which foals at Stud 2 had a higher relative abundance of P. pseudocomata than at 0 to 1 and 1 to 2 m. Mares at Stud 4 had a greater PRA of P. pseudocomata than the foals at all sampling ages, and Stud 3 saw a spike in the fungal species in 4 to 5 m foals.

Fig. 4.

Non-metric multidimensional scaling (NMDS) of the Bray-Curtis dissimilarities for the equine fungal faecal microbiota by age at sampling and geographic location.

4. Discussion

This study has reported the identity and PRA of both fungal and bacterial microbial taxa present at each stage of foal maturation (0 to 5 months). The increase in bacterial diversity as foals aged most likely coincides with increased environmental exposure through changing diets and interaction with other animals. Costa et al. [16] reported that there are often statistically higher abundances of bacterial genera in young foals than in adult mares, with many belonging to the Firmicutes phylum, as seen in the current study. Dramatic and dynamic shifts in the bacterial microbiota have also been observed in newborn humans, puppies, and calves [42, 43, 44]. Perinatal exposure to microbial ecosystems of the meconium, amniotic fluid, and faeces aid in establishing the foal’s internal colonisation prior to birth [45]. The sudden post-partum exposure to environmental organisms, the mother’s own microbiota, and colostrum are all reflected in the increasing bacterial diversity and richness seen in young foals. Previous studies characterising the equine microbiome identified similar predominant phyla to those seen in the current investigation, including Firmicutes, Bacteroidetes, Verrucomicrobia and Proteobacteria [16, 19, 20, 46].

The identified fluctuations in the most relatively abundant bacterial and archaeal genera as the foal aged likely correlates with their metabolic function. Trends were seen in fibrolytic taxa such as Lachnospriaceae spp., where their PRA increased once foals surpassed 0 to 1 months old. Species within this family are drivers of key metabolic transformations such as reductive acetogenesis and lactate conversion. In addition, many members of the Lachnospriaceae are major butyrate-producers [47]. This would aid in substantiating the large energy demand for the growth foals experience during birth to weaning as they begin to graze and ingest carbohydrates. The Phascolarctobacterium genus also showed a positive relationship with age. Species within this genus are known to generate short-chain fatty acids such as acetate and propionate [48], likely contributing to energy utilisation and storage. In humans, the abundance of bacteria in the Christensenellaceae and Rikenellaceae families has been associated with reduced adipose tissue [49]. Their increase in PRA seen in 4 to 5 m old foals may contribute to the diversion of energy for fat and growth as foals prepare for weaning.

With few exceptions, samples from adult mares tended to cluster together, as did samples from foals in each age category, regardless of geographical location. A similar trend was identified by Costa et al. [16]. Although there was minor variation between individuals, the current study saw a general tendency for most bacterial and archaeal populations to stabilise in foals by 3 to 4 months of age. However, there are discrepancies in published observations where stabilisation timelines range from just 30 days [17] to six weeks [50] and 50 to 60 days post-partum [16, 51]. Variances in analytical methods and study design complicate the comparison of research groups. However, despite differences in findings, all studies agree that microbial reconfiguration occurs prior to weaning, corresponding with the introduction of plant fibre and solid feeds [18].

Limited studies have investigated microbial colonisation of foals from birth to weaning. Fewer still have considered fungal populations despite their critical role in digestive maturation and dietary transitions [52]. Although a study has been done to determine the effect of colostrum replacer on the foal microbiome, the small sample size and limited analysis provided little explanation [53]. Studies of the murine mycobiome have shown fungal populations display radical episodic variation over an animal’s lifetime while bacterial communities remain relatively stable [54]. Despite its superior fibrolytic activity, fungi account for only 8% of the rumen microbial biomass, which is thought to be due to their slower generation time than bacteria [55]. It is likely that a similar circumstance occurs in the hindgut of horses and may explain why such low PRAs were recorded in the current study.

Interestingly, age at sampling had a greater effect on the PRA of certain archaeal and bacterial genera than geographical location, yet the reverse was found for fungal species. As the 15 most relatively abundant fungal species isolated from faecal samples were environmental microfungi, it is not surprising that there were multiple age × location interactions. Namely, Preussia persica, Acremonium furcatum and Podospora pseudocomata. As a known dung-inhabitant, the increase of P. persica as foals aged at Stud 2, Stud 3 and Stud 4 likely corresponds with a gradual rise in grazing and exposure to faecal debris [56]. A similar trend was seen with A. furcatum where its PRA increased in older foals at Stud 4 and Stud 5, likely explained by the species’ familiar presence in soil and on plant material [57]. The spike in P. pseudocomata seen in 4 to 5 m foals at Stud 3 may have been due to the intake of a contaminated feed source as it is a known inhabitant of soil and herbivore dung [58].

The primary DNA barcode for eukaryotes like fungi is the ITS1 region between the 18S rRNA and 5.8S rRNA genes [59]. The authors chose to use ITS1 primers like those used in McGorum et al. [60], who collected post-mortem samples from the gastrointestinal tract of 54 horses with equine grass sickness and faecal samples from control horses. Results seen in McGorum et al. [60] are somewhat comparable to the current study, finding Acremonium, Preussia and Naganishia fungal species to be among the most dominant. However, it is unknown why Neocallimastigomycota species or other anaerobic fungal phyla known to colonise the alimentary tract of mammalian herbivores and hindgut fermenters were not detected in faecal samples analysed in the current study [24, 52, 61, 62, 63, 64, 65, 66]. As this is a preliminary study of the foal mycobiome, it may be that anaerobic fungi, such as Neocallimastigomycota, were present but at less abundant or undetectable levels.

Previous studies of the equine mycobiome have taken place in various geographical locations worldwide. Edwards et al. [23] collected faecal samples from mature ponies in the Netherlands fed haylage and straw, while Edwards et al. [22] sampled ponies from Concord, MA USA, across September and October that were provided predominantly pasture. Additionally, Mura et al. [15] sampled hindgut segments of a 24-year old Anglo-Arabian gelded male fed a mixed diet. Differences in pasture grass species, the area of forage being grazed, and the season during which the horses were sampled (summer vs winter pasture species) may influence the extent of a horse’s exposure to certain fungal organisms. It may be possible that the Australian Thoroughbreds sampled for this study may not have been exposed to high abundances of Neocallimastigomycota.

Multiple publications investigating the equine mycobiome have used at least one primer specific for the anaerobic phylum Neocallimastigomycota [15, 22, 23, 67] or employed anaerobic cultures [24]. This likely explains their reportedly high abundances compared to this study. It is possible that the type of samples collected in the current study did not offer the most accurate representation of the internal microbiome. However, a previous publication found cultured Neocallimastix spp. in high proportions in the left ventral colon (81%) and the rectum (75.5%), indicating that faecal samples are still viable as a qualitative reference sample [15]. Although, it is important to note that the same study used a Neocallimastigomycota specific 5.8S rRNA gene reverse primer.

Although there are discrepancies between this study’s results and previous literature, the authors are confident that the observations made here are accurate. The primary limitation of this study is the surprising abundance of aerobic species found, as the authors expected predominantly anaerobic organisms given the low-oxygen environment of the caecum. Potentially, the fungal PRA results may not truly reflect the faecal mycobiome but, in this case, may represent the highly abundant food-source species that survive the hindgut digestive processes, or environmental contamination. Similarly, a 2016 study sequenced the ITS1 region to identify over 90 fungal taxa within the human GIT and detected sequences belonging to edible fungi [68]. This suggests dietary fungal intake may be a confounding effect in mycobiota investigations [68]. Further, there is no exhaustive reference base for annotated fungal sequences as there is for bacteria [69, 70], making the establishment of definitions for ‘normal’ fungal diversity much more difficult. Future studies may need to undertake culture-based analysis to discern mycobiome phenotypes not resolved by sequencing, particularly as current databases overestimate the abundance of culturable sequences.

5. Conclusions

This study found that the microbial community within the foal hindgut stabilises by three to four months of age. As hypothesised, bacterial and archaeal genera identified in faecal samples belonged mainly to the Firmicutes phylum with several genera unique to 0–1-month-old animals. The colonisation of the equine hindgut and microbial composition corresponds to the introduction of plant fibre and solid feeds. This relates to the increase in the PRA of fibrolytic taxa, such as Lachnospriaceae, observed as foals surpassed 0 to 1 months old. Similarly there was a simultaneous steady increase in members of the Phascolarctobacterium genus, which are known for their role in feed conversion and VFA production. The age at sampling had significantly more influence over the archaeal and bacterial faecal microbiota than the effect of geographical location. However, the opposite was found for fungal species, more strongly affected by where the horse was sampled. Although, it is of note that the 15 most relatively abundant fungal species were environmental saprophytes. Therefore, it was more difficult to establish the relevance of these fungi as hindgut colonizers. Instead, authors conclude that environmental and dietary fungi can survive the digestive process and maintain relatively high abundances that may have outcompeted recognised ‘core’ anaerobic phyla such as Neocallimastigomycota.

Author Contributions

GM and KM designed the research study. GO, DH, KM, GM, MP, SM and AC performed the research. DH and AC analysed the data. GO wrote the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.

Ethics Approval and Consent to Participate

Faeces were collected with as little disturbance to the animal as possible, consistent with procedures approved by the University of Sydney Animal Ethics Committee (Project Number 1319).


The authors would like to thank the participating Thoroughbred studs located in the Central West, Hunter Valley and Southern Highlands regions for providing access to the samples required to complete this investigation.


This research received no external funding.

Conflict of Interest

The authors declare no conflict of interest.

Publisher’s Note: IMR Press stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Al Jassim RA, Andrews FM. The bacterial community of the horse gastrointestinal tract and its relation to fermentative acidosis, laminitis, colic, and stomach ulcers. Veterinary Clinics: Equine Practice. 2009; 25: 199–215.
Fouhse J, Zijlstra R, Willing B. The role of gut microbiota in the health and disease of pigs. Animal Frontiers. 2016; 6: 30–36.
Racklyeft D, Raidal S, Love D. Towards an understanding of equine pleuropneumonia: factors relevant for control. Australian Veterinary Journal. 2000; 78: 334–338.
Becvarova I, Buechner‐Maxwell V. Feeding the foal for immediate and long‐term health. Equine Veterinary Journal. 2012; 44: 149–156.
Bergman E. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiological Reviews. 1990; 70: 567–590.
Costa MC, Arroyo LG, Allen-Vercoe E, Stämpfli HR, Kim PT, Sturgeon A, et al. Comparison of the fecal microbiota of healthy horses and horses with colitis by high throughput sequencing of the V3-V5 region of the 16S rRNA gene. PLoS ONE. 2012; 7: e41484.
Marchesi JR, Ravel J. The vocabulary of microbiome research: a proposal. Microbiome. 2015; 3: 31.
Venable EB, Fenton KA, Braner VM, Reddington CE, Halpin MJ, Heitz SA, et al. Effects of feeding management on the equine cecal microbiota. Journal of Equine Veterinary Science. 2017; 49: 113–121.
Dougal K, de la Fuente G, Harris PA, Girdwood SE, Pinloche E, Geor RJ, et al. Characterisation of the faecal bacterial community in adult and elderly horses fed a high fibre, high oil or high starch diet using 454 pyrosequencing. PLoS ONE. 2014; 9: e87424.
O’Donnell M, Harris H, Jeffery I, Claesson M, Younge B, O’Toole P, et al. The core faecal bacterial microbiome of I rish T horoughbred racehorses. Letters in Applied Microbiology. 2013; 57: 492–501.
Salem SE, Maddox TW, Berg A, Antczak P, Ketley JM, Williams NJ, et al. Variation in faecal microbiota in a group of horses managed at pasture over a 12-month period. Scientific Reports. 2018; 8: 1–10.
Shepherd ML, Swecker Jr WS, Jensen RV, Ponder MA. Characterisation of the fecal bacteria communities of forage-fed horses by pyrosequencing of 16S rRNA V4 gene amplicons. FEMS Microbiology Letters. 2012; 326: 62–68.
Zhao Y, Li B, Bai D, Huang J, Shiraigo W, Yang L, et al. Comparison of fecal microbiota of Mongolian and Thoroughbred Horses by high-throughput sequencing of the V4 Region of the 16S rRNA gene. Asian-Australasian Journal of Animal Sciences. 2016; 29: 1345.
Mullen K, Yasuda K, Divers T, Weese J. Equine faecal microbiota transplant: current knowledge, proposed guidelines and future directions. Equine Veterinary Education. 2018; 30: 151–160.
Mura E, Edwards J, Kittelmann S, Kaerger K, Voigt K, Mrázek J, et al. Anaerobic fungal communities differ along the horse digestive tract. Fungal Biology. 2019; 123: 240–246.
Costa M, Stämpfli H, Allen‐Vercoe E, Weese JS. Development of the faecal microbiota in foals. Equine Veterinary Journal. 2016; 48: 681–688.
Faubladier C, Sadet-Bourgeteau S, Philippeau C, Jacotot E, Julliand V. Molecular monitoring of the bacterial community structure in foal feces pre-and post-weaning. Anaerobe. 2014; 25: 61–66.
De La Torre U, Henderson JD, Furtado KL, Pedroja M, Elenamarie OM, Mora A, et al. Utilising the fecal microbiota to understand foal gut transitions from birth to weaning. PLoS ONE. 2019; 14: e0216211.
Schoster A, Mosing M, Jalali M, Staempfli H, Weese J. Effects of transport, fasting and anaesthesia on the faecal microbiota of healthy adult horses. Equine Veterinary Journal. 2016; 48: 595–602.
Schoster A, Staempfli H, Guardabassi L, Jalali M, Weese J. Comparison of the fecal bacterial microbiota of healthy and diarrheic foals at two and four weeks of life. BMC Veterinary Research. 2017; 13: 1–10.
Dougal K, Harris PA, Edwards A, Pachebat JA, Blackmore TM, Worgan HJ, et al. A comparison of the microbiome and the metabolome of different regions of the equine hindgut. FEMS Microbiology Ecology. 2012; 82: 642–652.
Edwards J, Schennink A, Burden F, Long S, van Doorn D, Pellikaan W, et al. Domesticated equine species and their derived hybrids differ in their fecal microbiota. Animal Microbiome. 2020; 2: 1–13.
Edwards J, Shetty S, Van Den Berg P, Burden F, Van Doorn D, Pellikaan W, et al. Multi-kingdom characterisation of the core equine fecal microbiota based on multiple equine (sub) species. Animal Microbiome. 2020; 2: 1–16.
Solomon KV, Haitjema CH, Henske JK, Gilmore SP, Borges-Rivera D, Lipzen A, et al. Early-branching gut fungi possess a large, comprehensive array of biomass-degrading enzymes. Science. 2016; 351: 1192–1195.
Akin D. Histological and physical factors affecting digestibility of forages. Agronomy Journal. 1989; 81: 17–25.
Cheng Y, Shi Q, Sun R, Liang D, Li Y, Li Y, et al. The biotechnological potential of anaerobic fungi on fiber degradation and methane production. World Journal of Microbiology and Biotechnology. 2018; 34: 1–8.
Costa MC, Stämpfli HR, Arroyo LG, Allen-Vercoe E, Gomes RG, Weese JS. Changes in the equine fecal microbiota associated with the use of systemic antimicrobial drugs. BMC Veterinary Research. 2015; 11: 1–12.
Garber A, Hastie P, Murray J-A. Factors influencing equine gut microbiota: Current knowledge. Journal of Equine Veterinary Science. 2020; 88: 102943.
Geor RJ, Coenen M, Harris P. Equine applied and clinical nutrition E-book: Health, welfare and performance. Elsevier Health Sciences: Amsterdam. 2013.
Henderson G, Cox F, Ganesh S, Jonker A, Young W, Janssen PH. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Scientific Reports. 2015; 5: 1–15.
Liggenstoffer AS, Youssef NH, Couger M, Elshahed MS. Phylogenetic diversity and community structure of anaerobic gut fungi (phylum Neocallimastigomycota) in ruminant and non-ruminant herbivores. The ISME Journal. 2010; 4: 1225–1235.
Yu Z, Morrison M. Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques. 2004; 36: 808-812.
Desjardins P, Conklin D. NanoDrop microvolume quantitation of nucleic acids. Journal of Visualized Experiments. 2010; e2565.
Henderson G, Cox F, Kittelmann S, Miri VH, Zethof M, Noel SJ, et al. Effect of DNA extraction methods and sampling techniques on the apparent structure of cow and sheep rumen microbial communities. PLoS ONE. 2013; 8: e74787.
Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, et al. Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. Msystems. 2016; 1: e00009–00015.
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nature Methods. 2016; 13: 581–583.
Kechin A, Boyarskikh U, Kel A, Filipenko M. cutPrimers: a new tool for accurate cutting of primers from reads of targeted next generation sequencing. Journal of Computational Biology. 2017; 24: 1138–1143.
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic acids research. 2012; 41: D590–D596.
Nilsson RH, Larsson K-H, Taylor AFS, Bengtsson-Palme J, Jeppesen TS, Schigel D, et al. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research. 2019; 47: D259–D264.
McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS one. 2013; 8: e61217.
Martinez Arbizu P. pairwiseAdonis: Pairwise multilevel comparison using adonis. R package version (R package version 0.4.0, 2020). Available at: (Accessed: 31 May 2022).
Favier CF, Vaughan EE, De Vos WM, Akkermans AD. Molecular monitoring of succession of bacterial communities in human neonates. Applied and environmental microbiology. 2002; 68: 219–226.
Guard BC, Mila H, Steiner JM, Mariani C, Suchodolski JS, Chastant-Maillard S. Characterization of the fecal microbiome during neonatal and early pediatric development in puppies. PLoS ONE. 2017; 12: e0175718.
Mayer M, Abenthum A, Matthes J, Kleeberger D, Ege M, Hölzel C, et al. Development and genetic influence of the rectal bacterial flora of newborn calves. Veterinary Microbiology. 2012; 161: 179–185.
Quercia S, Freccero F, Castagnetti C, Soverini M, Turroni S, Biagi E, et al. Early colonisation and temporal dynamics of the gut microbial ecosystem in Standardbred foals. Equine Veterinary Journal. 2019; 51: 231–237.
Weese JS, Holcombe S, Embertson R, Kurtz K, Roessner H, Jalali M, et al. Changes in the faecal microbiota of mares precede the development of post partum colic. Equine Veterinary Journal. 2015; 47: 641–649.
Meehan CJ, Beiko RG. A phylogenomic view of ecological specialisation in the Lachnospiraceae, a family of digestive tract-associated bacteria. Genome Biology and Evolution. 2014; 6: 703–713.
Wu F, Guo X, Zhang J, Zhang M, Ou Z, Peng Y. Phascolarctobacterium faecium abundant colonisation in human gastrointestinal tract. Experimental and Therapeutic Medicine. 2017; 14: 3122–3126.
Tavella T, Rampelli S, Guidarelli G, Bazzocchi A, Gasperini C, Pujos-Guillot E, et al. Elevated gut microbiome abundance of Christensenellaceae, Porphyromonadaceae and Rikenellaceae is associated with reduced visceral adipose tissue and healthier metabolic profile in Italian elderly. Gut Microbes. 2021; 13: 1–19.
Earing JE, Durig AC, Gellin GL, Lawrence LM, Flythe MD. Bacterial colonisation of the equine gut; comparison of mare and foal pairs by PCR-DGGE. Advances in Microbiology. 2012; 2: 19667.
Lindenberg F, Krych L, Kot W, Fielden J, Frøkiær H, Van Galen G, et al. Development of the equine gut microbiota. Scientific Reports. 2019; 9: 1–9.
Harhangi HR, Freelove AC, Ubhayasekera W, van Dinther M, Steenbakkers PJ, Akhmanova A, et al. Cel6A, a major exoglucanase from the cellulosome of the anaerobic fungi Piromyces sp. E2 and Piromyces equi. Biochimica et Biophysica Acta (BBA)-Gene Structure and Expression. 2003; 1628: 30–39.
Julliand V, deVaux A, Villaro L, Richard Y. Preliminary studies on the bacterial flora of faeces taken from foals, from birth to twelve weeks. Effect of the oral administration of a commercial colostrum replacer. Pferdeheilkunde. 1996; 12: 209–212.
Dollive S, Chen Y-Y, Grunberg S, Bittinger K, Hoffmann C, Vandivier L, et al. Fungi of the murine gut: episodic variation and proliferation during antibiotic treatment. PLoS ONE. 2013; 8: e71806.
Hobson PN, Stewart CS. The rumen microbial ecosystem. Springer Science & Business Media: Secaucus. 2012.
Gonzalez-Menendez V, Martin J, Siles JA, Gonzalez-Tejero MR, Reyes F, Platas G, et al. Biodiversity and chemotaxonomy of Preussia isolates from the Iberian Peninsula. Mycological Progress. 2017; 16: 713–728.
Summerbell RC, Gueidan C, Schroers HJ, de Hoog GS, Starink M, Rosete YA, et al. Acremonium phylogenetic overview and revision of Gliomastix, Sarocladium, and Trichothecium. Studies in Mycology. 2011; 68: 139–162.
Boucher C, Nguyen T-S, Silar P. Species delimitation in the Podospora anserina/P. pauciseta/P. comata species complex (Sordariales). Cryptogamie, Mycologie. 2017; 38: 485–506.
Schoch CL, Seifert KA, Huhndorf S, Robert V, Spouge JL, Levesque CA, et al. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proceedings of the National Academy of Sciences. 2012; 109: 6241–6246.
McGorum B, Chen Z, Glendinning L, Gweon H, Hunt L, Ivens A, et al. Equine Grass Sickness (A Multiple Systems Neuropathy) is Associated with Alterations in the Gastrointestinal Mycobiome. Animal Microbiome. 2021; 3: 70.
Gruninger RJ, Puniya AK, Callaghan TM, Edwards JE, Youssef N, Dagar SS, et al. Anaerobic fungi (phylum Neocallimastigomycota): advances in understanding their taxonomy, life cycle, ecology, role and biotechnological potential. FEMS Microbiology Ecology. 2014; 90: 1–17.
Milne A, Theodorou MK, Jordan MG, King-Spooner C, Trinci AP. Survival of anaerobic fungi in feces, in saliva, and in pure culture. Experimental Mycology. 1989; 13: 27–37.
Nagpal R, Puniya AK, Sehgal JP, Singh K. In vitro fibrolytic potential of anaerobic rumen fungi from ruminants and non-ruminant herbivores. Mycoscience. 2011; 52: 31–38.
Teunissen MJ, den Camp HJO, Orpin CG, Huis JH, Vogels GD. Comparison of growth characteristics of anaerobic fungi isolated from ruminant and non-ruminant herbivores during cultivation in a defined medium. Microbiology. 1991; 137: 1401–1408.
Tuckwell DS, Nicholson MJ, McSweeney CS, Theodorou MK, Brookman JL. The rapid assignment of ruminal fungi to presumptive genera using ITS1 and ITS2 RNA secondary structures to produce group-specific fingerprints. Microbiology. 2005; 151: 1557–1567.
Li J, Heath IB. The phylogenetic relationships of the anaerobic chytridiomycetous gut fungi (Neocallimasticaceae) and the Chytridiomycota. I. Cladistic analysis of rRNA sequences. Canadian Journal of Botany. 1992; 70: 1738–1746.
Edwards JE, Kingston-Smith AH, Jimenez HR, Huws SA, Skøt KP, Griffith GW, et al. Dynamics of initial colonisation of nonconserved perennial ryegrass by anaerobic fungi in the bovine rumen. FEMS Microbiology Ecology. 2008; 66: 537–545.
Strati F, Di Paola M, Stefanini I, Albanese D, Rizzetto L, Lionetti P, et al. Age and gender affect the composition of fungal population of the human gastrointestinal tract. Frontiers in Microbiology. 2016; 7: 1227.
Jovel J, Patterson J, Wang W, Hotte N, O’Keefe S, Mitchel T, et al. Characterisation of the gut microbiome using 16S or shotgun metagenomics. Frontiers in Microbiology. 2016; 7: 459.
Stefanini I, Cavalieri D. Metagenomic approaches to investigate the contribution of the vineyard environment to the quality of wine fermentation: potentials and difficulties. Frontiers in Microbiology. 2018; 9: 991.
Publisher’s Note: IMR Press stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Back to top