3.1 Culture-dependent methods

Traditionally, culture-dependent methods have commonly been used to isolate gut fungi from fecal samples. The process of culturing gut fungi primarily includes isolation, cultivation, and identification, which is similar to bacterial culture (Figure 1). However, because of the low abundance of intestinal fungi, antibiotics have always been added to the culture medium to inhibit bacterial growth in fungal isolation to improve the fungal strain isolation. For example, vancomycin is used to remove Gram-positive bacteria, while gentamicin is employed to eliminate Gram-negative bacteria. Fungal isolation highly depends on the culture medium. Different media have selectively been used to culture various fungal species. For example, Sabouraud dextrose agar is a generally used medium for fungi (Das et al., 2010; Odds, 1991; Wiwanitkit, 2010), while CHROMagarTM Candida medium has always been used for Candida isolation (Malcok et al., 2009; Tang et al., 2019). Other media commonly used for fungal isolation include malt agar, potato dextrose agar, Czapek-Dox agar, Colombia agar, Dixon agar, modified Leeming Notman agar, Banana agar, glycine-vancomycinpolymyxin B agar and yeast peptone dextrose medium, and so on (Khelaifia et al., 2023; Tidjani Alou et al., 2020) (Table 1). Additionally, temperature, culture time, pH, and oxygen content are also important environmental factors influencing the isolation and culture of fungi. Most fungi are mesophilic and the cultivation temperature varies from 25°C for filamentous fungi to 37°C for yeast (Barzee et al., 2021; Tidjani Alou et al., 2020). The culture time depends on the kinds of fungi. Fungi can grow within a relatively wide pH range, but different pH may cause different morphologies of cultured fungi (Barzee et al., 2021). As for the effect of oxygen on the culture of gut fungi, most intestinal fungi can be cultured in anaerobic or strictly anaerobic environments due to low oxygen levels in the gut. Generally, different fungi can promote or antagonise each other under specific culture conditions. Consequently, the culturability of uncultured fungi can be enhanced by improving the nutrient components of the medium, optimising the culture conditions, and manipulating the temperature, time, and pH. Classical identification methods for gut fungi primarily rely on the observation of their morphological characteristics including macroscopic and microscopic morphology, colony colour, texture, shape, and cellular morphology. With the development of technologies, MALDI-TOF MS, ITS sequencing, and 18S rRNA gene sequencing have become the main technologies used for fungal identification in fungal culture (Becker et al., 2014; Hoggard et al., 2018; Robert et al., 2020).

In previous studies, the assessments of fungal diversity have mainly relied on culture-based methods. Through culture, we can discover some strains that cannot be identified by high-throughput sequencing, exam the morphological characteristics, and determine their culture conditions directly. The fungal strains isolated and identified by cultural methods can enrich the resource library of fungal strains. Simultaneously, we can also perform various in vivo and in vitro experiments on isolated strains to further explore their metabolites and physiological function properties. Furthermore, some strains that have been shown to be beneficial to the host also provide an excellent source of strains for disease prevention as well as for the development of probiotics. Thus, the cultivated fungal strains show great significance for the studies of gut fungi. A recent study isolated 12,453 fungal strains from fresh fecal samples of 135 healthy volunteers using multiple fungus-specific media. And then, A cultivated gut fungi catalog was established, including 760 fungal genomes. The catalog covered 206 species in 48 families, 69 of which were not found in existing databases and defined as unknown species. This catalog has significantly increased the genomic resources of gut fungal species (Yan et al., 2024). Nevertheless, the gut microbiota is a complex and dynamic microecosystem. Many fungi cannot be cultured due to low abundance and limited culture conditions (O'Brien et al., 2005). Previous studies have shown that the number of culturable fungal species in feces range from 10² to 10⁷ cfu/g (Krawczyk et al., 2021). External culture is not only time-consuming and labour-intensive, but also unable to truly reflect the dynamics of intestinal microbiota. In the studies of human gut fungi, the number of fungal species cultivated was far less than that of sequenced species. For example, amplicon-based ITS1 sequencing identified over 90 fungal taxa, whereas only 34 fungal species were isolated using the culture-based approach (Gouba et al., 2014). Up to now, there are few studies on the culture of human intestinal fungi, and even fewer in other mammals (Borges et al., 2018; Huseyin et al., 2017b; Yan et al., 2024). In pigs, a previous study investigated the dynamics of the gut mycobiome in piglets at pre- and post-weaning using culture-based method, and found a significant increase in fungal burden following weaning that does not differ from adult levels (Summers et al., 2019). However, to our knowledge, there are few studies about the comparison of fungal identification between sequencing- and culture-based approaches.

3.1.1 Culture-independent methods

Due to the low efficiency and unculturability for large numbers of microbes using traditional culture methods, researchers require more efficient and rapid methods to detect the composition of gut microbes. With the rapid development of biotechnology, high-throughput sequencing has become the most commonly used method for gut microbiota analysis including bacteria and fungi. Amplicon sequencing breaks through the shortcomings of unculturable microbes. Meanwhile, this method can obtain the information, such as the evolutionary relationship of microbial community structure and the correlation between microorganisms and environments. For fungal analysis, amplicon sequencing has always been performed using fungal-specific primers to amplify the ITS or 18S region of the rRNA gene (Berbee & Taylor, 1992; Schoch et al., 2012; Tang et al., 2015). Due to the longer length and higher resolution of the ITS2 region compared to ITS1, most studies have amplified and sequenced the ITS2 region, while 18S rRNA gene sequencing is commonly used for eukaryotic analysis. The process for data analysis of amplicon sequencing is shown in Figure 2a. Of note, in order to facilitate the analysis, a series of amplicon analysis pipelines have been developed, such as AMPtk (Palmer et al., 2018), Lotus2 (Özkurt et al., 2022), PipeCraft (Anslan et al., 2017), Pipits (Gweon et al., 2015), etc. However, the amplified and sequenced regions of marker genes show significant influence in the results of gut fungal compositions. For example, Arfken et al. (2023) compared the effects of amplicon sequencing of ITS1, ITS2, and 18S rRNA gene on the taxonomic annotation and the abundance of swine gut mycobiome, and found that ITS markers were slightly superior to 18S in the identification of species, but Lichtheimia corymbifera was not amplified by ITS1 and ITS2 primers. 18S marker-based abundance estimates of taxa were more accurate than ITS-based approach. At the species level, Kazachstania slooffiae showed the most stable copy numbers, while L. corymbifera displayed significant variability across gene regions. Amplicon analysis can quickly obtain fungal taxonomy information (D'Andreano et al., 2021), but this method has been criticised for having a low phylogenetic resolution that cannot achieve the species level (Ranjan et al., 2016). Some studies have demonstrated that the copy numbers of the ribosomal DNA in fungi vary greatly at both the species and strain level, ranging from tens to thousands (Lofgren et al., 2019; Sharma et al., 2022). The variable copy numbers of ITS region were also observed by another study, which reported that the copy numbers of the ITS region in 32 S. cerevisiae strains varied from 15 to 137, and ranged from 11 to 74 in 182 C. albicans strains (Xie et al., 2023). This variation presents a challenge for the quantitative taxonomic profiling of fungal communities, so more studies would need to address the limitations of this method.

Metagenomic sequencing has opened a new door for gut fungal analysis, which perfectly compensates for the shortcomings of amplicon sequencing and can obtain the genomic information of various microorganisms in a sample without amplification. With the continuous enrichment of fungal genomes and the development of various algorithms, multifarious software tools for characterising fungi from metagenomic data have emerged. The development of these software tools has promoted the studies on fungi and enabled the mining of metagenomic sequencing data (Table 2). The current methods for determining the fungal composition from metagenomic sequencing data mainly consist of three types: (i) reference genome-based approach; (ii) marker genes-based approach; (iii) database independent approach (Figure 2b).

• i.

  Reference genome-based approach

  The reference genome-based approach shows high accuracy for fungal identification. At present, the NCBI database contains a large number of 16,258 fungal genomes at various assembly levels (before 7 September 2023). Representative software tools for this analysis mainly included Kraken2 (Wood et al., 2019), bowtie2 (Langmead & Salzberg, 2012), and CCMetagen (Marcelino et al., 2020). In this approach, clean reads of metagenomic sequencing are mapped directly to the fungal genome to obtain taxonomic information. And then, various subsequent analyses, such as functional capacity analysis, are performed. However, this method has been limited by the incomplete and scattered data of fungal genome databases. Specifically, it can only describe the fungal community with genome information, and the fungal species without genome information cannot be analysed. At the same time, fungal genomes are easy to be contaminated by bacterial genomes, resulting in a high false discovery rate.

• ii.

  Marker genes-based approach

  Genome and protein sequences of fungi are prone to be contaminated by bacterial sequences, leading to incorrect identification. Fungal genomes take up a lot of memory and require a lot of time and resources to operate. However, these problemes can be effectively avoided by using marker genes. As an alternative to ribosomal DNAs, a set of single-copy marker genes can be candidates for microbiome classification annotation such as bacteria (Lind & Pollard, 2021). Currently, many software tools have been developed for marker gene analysis, such as EukDetect (Lind & Pollard, 2021), TaxaTarget (Commichaux et al., 2022), and CORRAL (Bazant et al., 2023). Identification of fungi based on marker genes shows a high specificity to eukaryotes with a strong phylogenetic signal (Simão et al., 2015). The disadvantage is that some marker genes are universal, but vary across species. Furthermore, the fungi unknown at present cannot be identified, and the marker genes only occupy a small fraction of fungal genomes, which may result in low sensitivity in identifying fungi from metagenomic sequencing data.

• iii.

  Database independent approach

  At present, only a limited number of fungal genomes are available in the database. For many undiscovered fungi, applications of various machine learning approaches independently from databases are a practical method. This method has always used K-Mer to recognise fungal contigs or bins from assembly. And then, the identified contigs or bins are used for further analyses (Kayani et al., 2021). Currently, the pipelines or software used in this kind of analyses mainly include Tiara (Karlicki et al., 2022), EukRep (West et al., 2018), and Whokaryote (Pronk & Medema, 2022). These tools used K-Mer frequencies and linear vectors for DNA sequence classification, which do not require a database and can provide access to a larger library of genetic resources. To assess the quality of eukaryotic Metagenome-Assembled Genomes (MAGs), EUKCC is frequently used to evaluate the quality of eukaryotic MAGs (Saary et al., 2020). EukRep identifies assembled contigs from different environments, and can accurately predict 97.5% of eukaryotic sequences (West et al., 2018). In fact, EukRep has been utilised as a tool for fungal metagenomic analysis in the construction of the first pan-cancer fungal atlas (Narunsky-Haziza et al., 2022) and for investigating the diversity and functional capacity of skin fungi (Saheb Kashaf et al., 2022). Nevertheless, to most researchers, the process of this approach is relatively complex.

Table 2. Software/pipelines for metagenomic analysis of fungi.

Sofware/pipelines	Description	Advantages	Link
Kraken2	Bases on k-mer approach provides a fast taxonomic classification of metagenomic sequence data, allowing greater amounts of reference genomic data to be used	High accuracy and fast	https://github.com/DerrickWood/kraken2
Bowtie2	Uses the FM index to index the reference genome	High speed, sensitivity and accuracy	https://github.com/BenLangmead/bowtie2
CCMetagen	Uses the entire NCBI nucleotide collection as a reference to detect species with incomplete genome data from all biological kingdoms	Efficiently, user-friendly, and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies	https://github.com/vrmarcelino/CCMetagen
EukDetect	Aligns metagenomic sequencing reads to a database of universally conserved eukaryotic marker genes	Avoids the bacterial contamination in eukaryotic genomes	https://github.com/allind/EukDetect
TaxaTarget	Uses a database of eukaryotic marker genes and a supervised learning approach for training	Efficient, with higher sensitivity, and often higher precision than similar tools using marker sequence databases	https://github.com/SethCommichaux/taxaTarget
CORRAL	Bases on alignments to eukaryote-specific marker genes and Markov clustering	Sensitive and accurate, capable of inferring the presence of eukaryotes not included in the marker gene reference, such as novel strains	https://github.com/wbazant/CORRAL
Tiara	Uses k-mer counts as features for deep learning models	Performs similarly to EukRep for prokaryotes classification and outperformed it for eukaryotes classification with lower calculation time	https://ibe-uw.github.io/tiara
EukRep	k-mer-based strategy for eukaryotic sequence identification	Assignment to draft genomes and improvement of the quality of gene predictions	https://github.com/patrickwest/EukRep
Whokaryote	A random forest classifier that uses intergenic distance, gene density and gene length as the most important features	Use k-mer frequencies as features, perform almost as well as the classifiers EukRep and Tiara	https://github.com/LottePronk/whokaryote
Mciop	Uses fast-mapping of reads to build a comprehensive reference database of full genomes from viruses and eukaryotes to achieve maximum read usage and enable the analysis of the virome and eukaryome in each sample	Proves more effective than existing methods at abundance profiling of viruses and eukaryotes in metagenomic samples	https://github.com/smangul1/MiCoP
HumanMycobiome	A bioinformatics tool for the taxonomic profiling of the mycobiome directly from raw data of next-generation sequencing	Characterisation of the fungal component of microbiomes, customising the database	https://sourceforge.net/projects/hmscan/
FunOmic	Two built-in fungal databases, FunOMIC-T and FunOMIC-P, integrated into an automated pipeline for taxonomic and functional profiling	Can effectively detect fungal species from shotgun metagenomic sequencing data	https://manichanh.vhir.org/funomic/
FindFungi	Identifies fungal sequences in public metagenome datasets	Can be applied to any shotgun metagenomics dataset	https://github.com/GiantSpaceRobot/FindFungi

There are several pipelines integrating multiple approaches and optimising the process of fungus identification, such as Mciop (LaPierre et al., 2019), HumanMycobiome (Soverini et al., 2019), FunOmic (Xie & Manichanh, 2022), FindFungi (Donovan et al., 2018), etc. These pipelines are friendly to beginners, but lack flexibility. For example, FunOmic has constructed a fungal marker gene (FunOmic-T) and protein (FunOmic-P) database (Xie & Manichanh, 2022). The users can input human metagenomic sequencing data directly. And then, the fungal taxonomic and functional profiling would be obtained. However, this pipeline is computational resource-consuming and fails to identify novel fungi. Among these pipelines from the literature, FindFungi has been the most widely used. It has placed 942 fungal genomes into Kraken2 for fungal identification from public metagenome datasets (Donovan et al., 2018). Generally, there is no standard process for all these current methods (Suhr & Hallen-Adams, 2015; Wickes & Wiederhold, 2018). Different pipelines can result in various outcomes, which may be the main issue in the identification of fungi (Nilsson et al., 2019). All described above highlight the importance of carefully selecting appropriate bioinformation methods based on the available data to achieve the most accurate and reliable results (Thielemann et al., 2022).

4.1 The origin of pig gut fungi

Fungi are widely found in a variety of environments. According to the existing reports, it has generally been considered that fungi in the gastrointestinal tract mainly originate from food and the environments. A study on the origin of chicken gut fungi suggested that the majority of gut fungi were derived from food and the environments by using the Source Tracker software (Robinson et al., 2022). Similarly, another study showed that the gut mycobiome of healthy mice was shaped by the environment (Mims et al., 2021). However, it remains unclear which fungi merely pass through the gut from food and the environments, and which fungi actually can establish a permanent colonisation in the gut. The sources of fungi in the gut of pigs should be similar to that in the chickens, which primarily originated from diets and the environments (Figure 3). Fungi were detected in the feces of piglets on the first day after birth (Arfken et al., 2020; Summers et al., 2019). However, whether fungi presented in the gut of newborn piglets originated from the sow's feces, breast milk, or the vaginal tract has not been reported. The maternal mycobiome plays an essential role in shaping the gut mycobiome of piglets in early life (Prisnee et al., 2022). Previous studies have shown that the gut mycobiomes of piglets was closely similar to that in feces of their maternal sows. Additionally, another study revealed that K. slooffiae in the pig gut has been maintained in the same status as their mothers until the end of the production cycle (Prisnee et al., 2023). In summary, all of these findings suggest that maternal fungal colonisation is the driving factor in piglet mycobiome development (Prisnee et al., 2022; Prisnee et al., 2023). As we have well known, pigs have the habit of digging their noses through the earth, which may lead to some fungi in the gut being original from the soil. In a previous study, the Source Tracker software was used to track whether the fungi found in pig colonic content were derived from their diets. The results found that the fungal composition in diets was completely different from that in colonic content samples (Luo et al., 2021b). This observation suggested that fungi in diets was not easy to colonise in the gut. Whether other sources, such as sow's feces, breast milk, or vaginal tract contributed to the gut fungi in newborn piglets remains unknown at present.

The compositions of gut fungi vary greatly among individuals, which has inhibited to deeply investigate their origin (Nash et al., 2017). Moreover, the temporary presence of many fungi in the gastrointestinal tract has suggested a limited capacity for colonisation. The colonisation of fungi in the intestine is influenced by various factors, including fungal abundance, intrinsic characteristics of fungi, and the unique gastrointestinal microenvironments. Some members of fungi are able to grow under various environments. Factors, such as temperature, humidity, pH, nutrients, and competition with other microbes play crucial roles in fungal growth. Different pH values, nutrient levels, oxygen concentrations, and the interactions between microbes determined the colonisation and composition of fungi in the pig gastrointestinal tract. Understanding the factors influencing fungal colonisation can provide valuable insights into the origin of pig gut fungi and the interactions between fungi and other microbes in the gut microecosystem.

4.2 The diversity of pig gut fungal compositions

Fungi have been detected in the feces of healthy piglets at birth. From birth to 2 weeks after weaning, bacterial diversity gradually increases, while fungal diversity is variable (Arfken et al., 2020) (Figure 3). A recent study in weaned and finishing pigs found that the α-diversity of fungi in the feces of pigs was increased following the age from amplicon and metagenomic sequencing analysis (Hu et al., 2023). However, in healthy people, this tendency was not observed and the α-diversity of gut fungi remains low in the adults. Increased diversity and abundance of fungi often mean the emergence of diseases (Ott et al., 2008; Raimondi et al., 2019). Therefore, low fungal diversity and abundance in piglets may be considered a sign of good health. For instance, a recent study showed that the observed species and Chao1 indices were significantly higher in diarrheal piglets than in healthy control piglets (Zhou et al., 2023a). In human studies, the composition of gut fungi varies widely between individuals, suggesting that the composition of gut fungi may be more personalised (Shuai et al., 2022). Nonetheless, a recent study has found that the β-diversity of gut fungi in different breeds of Chinese indigenous pigs was highly similar (Wang et al., 2023b). This may be due to the fact that these experimental animals were raised in the same environments and fed the same diets.

Apart from the observations mentioned above, another previous research demonstrated that the α-diversity of gut mycobiome and ASV counts were highest in the stomach tissue (Arfken et al., 2019). The high diversity of fungal composition in the stomach may be due to the stronger ability of fungi to survive in an environment with low pH, or it may be that the stomach has less competition from bacteria compared to other parts of the gut locations, but certainly it is also possible that there is a bias in the detection. The reason for this phenomenon needs to be further clarified. Another study found that the α-diversity of cecal fungi in weaned piglets was significantly higher than that in the colon (Li et al., 2020b). In addition, even with the same diet and feeding environment, pigs with similar genetic backgrounds and body weights may have completely different fungi diversity along the gastrointestinal tract (Li et al., 2022a). These different results mentioned above would need to be confirmed in future studies.

4.3 The composition of pig gut fungi

Similar to the composition of fungal phyla in the gut of humans and mice, Ascomycota and Basidiomycota are the dominant phyla of fungi in the pig gut microbiota (Arfken et al., 2019; Hu et al., 2023; Li et al., 2018) (Figure 3). At the weaning stage, the fungal composition in the gut varies greatly among pigs. However, from 24 to 35 days after weaning, the composition of piglet gut fungi became more and more similar to that of adult pigs (Arfken et al., 2019; Kong et al., 2021). K. slooffiae was a commensal fungus with a high prevalence and abundance in pigs (Figure 3). Its abundance achieved the highest level at the weaning stage. After that, it decreased to a stable level until adulthood (Davies et al., 2021). A recent study presented that K. slooffiae was the most abundant fungus in the gut of weaned piglets from seven different breeds (Hu et al., 2023). K. slooffiae could be isolated and cultured from the gastrointestinal contents and feces of weaned piglets (Summers et al., 2021). As a core fungus in the gut, K. slooffiae has been detected in all gut locations of weaned piglets (Arfken et al., 2019; Li et al., 2020b; Ramayo-Caldas et al., 2020; Summers et al., 2019). However, the abundance of this fungus is very low or even undetectable in the gut of humans and mice (Auchtung et al., 2018; Gupta et al., 2023; Li et al., 2018), indicating that there may be a unique fungal ecosystem in the gastrointestinal tract of pigs. In addition, previous studies have shown that the compositions of fungi in different gut locations of weaned piglets are significantly different (Li et al., 2020b). Recent studies found that the dominant fungi in the cecum were Saccharomycopsis, Wallemia, Bifiguratus, Mrakia, and Kazachstania, while the predominant genera in colon were identified as Kazachstania, Saccharomycopsis, Aspergillus, Scheffersomyces, and Issatchenkia (Hu et al., 2023; Li et al., 2020b).

In finishing pigs, the most abundant fungi in the gut are different in different pig breeds. In Chenghua, Yorkshire, and Tibetan pigs, Loreleia, Russula, and Candida were the core fungi whose abundances were listed in the top three. These fungi were related to the production of short-chain fatty acids (SCFAs) (Li et al., 2020a). In another study, K. slooffiae had the most abundance in the gut of Duchangda, Shaziling and Ningxiang finishing pigs, while Aspergillus was the most abundant fungal genus in Laiwu and Congjiang finishing pigs (Hu et al., 2023). Most of Aspergillus spp. are harmful, and its metabolites have also been reported to show disadvantage to the host (Kanora & Maes, 2018). High abundance of these fungal species may suggest that pigs are at a higher risk of pathological state. These differential core fungi among pig breeds should be caused by different host genetic background, diets, pig farms, and environments. Similar to that in the gut of humans, the fungal community in the gastrointestinal tract of pigs is highly variable. Compared with bacteria, the development of the mycobiome is more variable and more likely transient and environmentally driven (Tiew et al., 2020).

4.4 The factors influencing the composition of pig gut fungi

Gut microbiota is a dynamic microecosystem influenced by multiple factors, mainly including host factors and external factors. Host factors include genetics, age, sex, and health states, while external factors are mainly comprised of diets, housing, and environmental factors. Environmental factors account for a large proportion of the variations of the gut microbial composition, while host factors are always underestimated because of the interference from other factors (Rothschild et al., 2018). Early studies have shown that species, diet, host genetics, environments, age, sex, lifestyle, bacteria, antibiotics and other factors can impact the composition of the gut fungi in mammals (Lai et al., 2019). However, few studies have definitively established the extent to which these factors influence the variation of gut fungi. This is likely due to the low abundance of fungi in the gut, as well as the fact that many studies have shown the instability of fungal colonisation in the gut. Furthermore, the core fungi present in the gut are still unknown and require further elucidation through relevant studies. Existing studies have shown that various factors, such as pig breed (Hu et al., 2023), age (Hu et al., 2023), diets (Luo et al., 2021b), farm environments (Ramayo-Caldas et al., 2020), host genetics (Ramayo-Caldas et al., 2020), health status (Kong et al., 2021), antibiotics, and maternal fungi (Prisnee et al., 2022), have significant impacts on the composition of gut fungi (Figure 3). Fungi are not relatively stable between and within individuals. Li et al. (2020a) reported for the first time that the fungal composition of feces in different pig breeds varied at both phylum and genus level. A more recent study reported that the fungal composition of colonic contents varied in different breeds (Wang et al., 2023b). Summers et al. (2019) characterised the changes in the gut fungal community of piglets throughout the whole-weaning period (seven time points) using 20 piglets from three litters by ITS sequencing and culture-dependent method. Their results confirmed that both the dominant fungal species and their abundances in piglets were changed during the whole-weaning period. The changed structure of the gut mycobiome might be caused by dietary changes, immune system maturation, and weanling stress. Especially, a previous study showed that dietary carbohydrates caused the differences in the composition of colon fungi in piglets (Luo et al., 2021b). The composition and diversity of fungi were also distinct in different parts of gastrointestinal tract (Li et al., 2020b; Li et al., 2022a). Furthermore, the utilisation of antibiotics can cause the dysbacteriosis of gut microbiota, which further influences the composition of gut fungi because of the complex interaction between gut bacteria and fungi (Hedin et al., 2022; Spatz et al., 2023). Previous studies have demonstrated that antibiotics alter the bacterial composition of piglets at birth and have some impact on fungi as well (Prisnee et al., 2022). At the same time, researchers also found that the colonisation of fungi in the maternal body was a driving factor for fungal development in piglets (Prisnee et al., 2022). For other factors, farm and pig ages explained 44% of the fungal variation (Ramayo-Caldas et al., 2020). The extent of these factors on gut fungal composition was not consistent in different studies. This instability in the compositions hampers the progress of the studies about gut fungi. Understanding the effects of different influencing factors on intestinal fungi is of great theoretical and potential practical significance for implementing interventions that target gut fungi to improve the growth and health of pigs.

4.5 The function capacities of pig intestinal fungi

Fungal colonisation in the gastrointestinal tract not only affects the physiological functions of the intestinal tract, but also influences the physiological functions of other organs of the host, and has important correlations with many diseases. In the gastrointestinal tract, fungi may regulate host energy metabolism by interacting with bacteria, or competing with each other (Seelbinder et al., 2023). The effect of gut fungi on immune function is similar to that of bacteria. Some fungi affect host health by producing metabolites to mediate immune response (Belvoncikova et al., 2022; Wu et al., 2021). Some fungi colonising in the gut are treated as immunologically active components can influence host immunophysiology through both commensal and synergistic effects with intestinal bacteria (Zeng et al., 2023).

To date, there have been limited reports on the roles of gut fungi in pigs. A study in pigs showed that fungi could degrade dietary carbohydrates in the colon, but the mechanism was unknown (Luo et al., 2021b) (Figure 3). The other two studies have indicated that fungi in the gut of weaned piglets and fishing pigs were related to the production of SCFAs. SCFAs may indicate the interaction between fungi and bacteria (Li et al., 2020a; 2020b). K. slooffiae shows probiotic characterisation and is a potential probiotic (Arfken et al., 2019). Previous studies discovered that K. slooffiae could rapidly colonise in all gut locations of weaned piglets and was positively correlated with SCFAs, especially butyric acid, acetic acid, and propionic acid (Urubschurov et al., 2017, 2018). Several reports have suggested that K. slooffiae showed positive interactions with gut bacteria, such as Prevotella and Lactobacillus (Arfken et al., 2019, 2020). Moreover, K. slooffiae may also be a novel protein source, which provides amino acids that benefit the growth of both microorganisms and piglets as an energy source (Summers et al., 2021; Urubschurov et al., 2017). A recent study found that K. slooffiae can promote glycolysis of pig intestinal epithelium through de-succinylation modification of lysine (Hu et al., 2023). Gut fungi were also involved in the health of pigs. A recent study revealed that decreased abundance of C. tropicalis leaded to reduced phosphocholine consumption in diarrheal piglets. Phosphocholine accumulation in the colon subsequently drove water efflux through decreasing fluid absorption mediated by adenylyl cyclase activation, and finally resulted in diarrhea (Zhou et al., 2023a). As mentioned above, nutrient metabolism and immunity are two most key functions of fungi in the pig gut. Further explorations about the roles of porcine intestinal fungi in vivo can provide new knowledge and strategies for improving energy metabolism and growth of pigs by regulating the composition of gut fungi. As an example, β-glucan is a major component of fungal cell walls. It plays crucial roles in keeping the intestinal microecological balance and the interactions between fungi and hosts. Although there are few studies about the fungal β-glucan in the pig gut, and its roles in pig physiology are largely unknown, the extensive roles of β-glucan in immune responses of human gut suggest great research values in pigs.

4.6 The application of pig intestinal fungi

In humans, the main methods for effectively regulating intestinal fungi include fecal microbiota transplantation, antifungal medications, antibiotics, dietary interventions, and probiotics (Zhang et al., 2022). Recent years, the utilisation of fungi in pig production has been increasing quickly. Probiotics are a group of microorganisms that can provide beneficial effects on the host (Hill et al., 2014). Most of the probiotics currently used belong to bacteria, such as some species of Lactobacillus and Bifidobacterium. Although it has been used less frequently than bacterial probiotics, fungal probiotics have been studied in more comprehensive areas. S. cerevisiae, Candida yeast, Brady yeast, and Pichia are among the fungal probiotics that have been extensively studied. In livestock production, these fungal probiotics have played important roles in immune regulation, metabolic activity, regulation of intestinal microbiome, and removal of oxygen (Elghandour et al., 2020). The European Commission approved S. cerevisiae as a feed additive for pigs as an animal nutrition additive, and classified it into the additive category of “Animal Technical Additives” and the functional group as “Intestinal Microbiota Stabiliser”. Adding S. cerevisiae to pig diets can enhance mucosal immunity by increasing the activity of immunoglobulin M and immunoglobulin A against pathogenic bacteria, promoting intestinal development and function, improving the excretion of mycotoxins, regulating gut microbiota, and reducing diarrhea after weaning (Elghandour et al., 2020; Hill et al., 2014; Jiang et al., 2015; Kogan & Kocher, 2007; Shen et al., 2009; Xu et al., 2018) (Figure 3). These findings have demonstrated the potential of S. cerevisiae as a beneficial addition to pig diets, with impacts on multiple aspects of pig health and performance. Interestingly, the studies also have found that the supplementation of S. cerevisiae YST2 can significantly decrease methane production in pig intestine (Gong et al., 2018). This would benefit the protection of the environment by reducing methane emissions. Supplementation of active S. cerevisiae Actisaf Sc 47 to newborn piglets from birth to weaning improved average daily feed intake and average daily weight gain of piglets, and altered the microbial composition in the hindgut of piglets by positively interacting with beneficial bacteria from Actinobacteria and Firmicutes (Kiros et al., 2018). Compared to bacteria, one advantage of using yeast as probiotics is that yeast is not affected by antibiotics (Hatoum et al., 2012). Therefore, probiotic fungi not only become an alternative to antibiotics, promote the growth of animals, but also prevent and treat some diseases.

Preventing the proliferation of harmful fungi in pigs is another crucial aspect in the application of fungi. Pigs that consume diets contaminated by molds, such as Aspergillus, Penicillium, and Fusarium, etc., have been reported to exhibit various toxic symptoms caused by secondary metabolites of mycotoxins, including aflatoxin, citrinin, F-2 toxin, and fumonisin, which are produced by the growth of these molds (Bryden, 2012; Holanda & Kim, 2021) (Figure 3). The presence of toxins in feed can increase the translocation of bacteria; and impair the immune response making animals more susceptible to infectious diseases (Pierron et al., 2016). Furthermore, these toxins can also easily cause human food poisoning through the food chain. In general, harmful fungal metabolites in the gut at low concentrations are not sufficient to cause obvious diseases, but may lead to economic losses through adverse effects on pig growth, production performance, and immunity. Therefore, we need to continuously strengthen the studies on harmful fungi, and clarify the deleterious effect of these fungi and their metabolites on the host. This would help us to better prevent their harmful effects on pigs.