Next Article in Journal
Closely Located but Totally Distinct: Highly Contrasting Prokaryotic Diversity Patterns in Raised Bogs and Eutrophic Fens
Next Article in Special Issue
Microbiota Modulating Nutritional Approaches to Countering the Effects of Viral Respiratory Infections Including SARS-CoV-2 through Promoting Metabolic and Immune Fitness with Probiotics and Plant Bioactives
Previous Article in Journal
Novel Clinical Campylobacter jejuni Infection Models Based on Sensitization of Mice to Lipooligosaccharide, a Major Bacterial Factor Triggering Innate Immune Responses in Human Campylobacteriosis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Beyond Just Bacteria: Functional Biomes in the Gut Ecosystem Including Virome, Mycobiome, Archaeome and Helminths

1
Department of Pathology, Section of Comparative Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA
2
School of Basic and Applied Sciences, Central University of Tamil Nadu, Thiruvarur 610005, India
3
National Institute of Gastroenterology “S. de Bellis”, Research Hospital, 70013 Castellana Grotte (Bari), Italy
4
School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston 7248, Australia
*
Author to whom correspondence should be addressed.
Microorganisms 2020, 8(4), 483; https://doi.org/10.3390/microorganisms8040483
Submission received: 6 March 2020 / Revised: 26 March 2020 / Accepted: 26 March 2020 / Published: 28 March 2020
(This article belongs to the Special Issue Gut Microbiome and Aging)

Abstract

:
Gut microbiota refers to a complex network of microbes, which exerts a marked influence on the host’s health. It is composed of bacteria, fungi, viruses, and helminths. Bacteria, or collectively, the bacteriome, comprises a significant proportion of the well-characterized microbiome. However, the other communities referred to as ‘dark matter’ of microbiomes such as viruses (virome), fungi (mycobiome), archaea (archaeome), and helminths have not been completely elucidated. Development of new and improved metagenomics methods has allowed the identification of complete genomes from the genetic material in the human gut, opening new perspectives on the understanding of the gut microbiome composition, their importance, and potential clinical applications. Here, we review the recent evidence on the viruses, fungi, archaea, and helminths found in the mammalian gut, detailing their interactions with the resident bacterial microbiota and the host, to explore the potential impact of the microbiome on host’s health. The role of fecal virome transplantations, pre-, pro-, and syn-biotic interventions in modulating the microbiome and their related concerns are also discussed.

1. Introduction

The human gut contains a collection of microbes that include commensal, symbiotic, and pathogenic bacteria, as well as fungi, viruses, archaea, and helminths. Collectively, the microbes in the gut are known as gut microbiota, and their respective genomes are collectively known as the gut microbiome [1]. The normal human gut is unique to each individual and influenced by factors such as diet, early-life microbiota exposure, changing hygiene status, pollution, socioeconomic status, and other environmental factors [2,3]. During the past decade, the gut microbiota has been implicated as an essential factor in the pathogenesis of inflammatory bowel disease (IBD), cancer, cardio-metabolic diseases, obesity, and diabetes [2,3,4,5,6].
The human gut microbiome diversity is characterized in ecological terms by its species evenness (the number of different kinds of species present in an ecological community) and richness (the number of different species represented in an ecological community) [7]. Next-generation sequencing (NGS) revolutions enabling the 16S DNA-based quantitative identification of enteric bacteria sparked numerous microbiome-wide studies that correlated gut bacterial diversity and its composition shifts, termed as ‘dysbiosis’, with human disease [8]. Most of the available research literature on the microbiome has focused on bacteria or bacteriome but not the other components [4]. The number of studies on the gut microbiome (many correspond to bacteriome only) have skyrocketed, reaching up to 3500 papers in 2018 (Figure 1) (Supplemental Table S1). Although bacteria dominate microbial communities, viruses, archaea, and fungi may also play pivotal roles in maintaining the gut homeostasis [9], as evidenced by a more recent steep increase in studies assessing the role of viral and fungal components of the microbiome. However, the viral and fungal biomes remain relatively uncharacterized thus far, due to their lower abundance as well as lack of optimized tools and curated reference databases for their identification and classification [10,11].
Owing to advances in NGS technologies, researchers are now starting to understand the dark matter of the microbiota as summarized in Table 1. Emerging studies indicate that the gut virome mainly includes DNA or RNA bacteriophages [12]. In addition, fungi, which primarily comprises Aspergillus, Candida, Fusarium, Penicillium, and Saccharomyces [13], and likewise gut archaea, especially methanogens [14], represent notable members of the microbiome. Data on the role of helminth species in human health is very limited and more population-based studies are required to evaluate their role in the gut [15,16]. Clearly, though, viruses, fungi, archaea, and helminths also comprise a significant composition of the gut ecosystem, and their existence could account for host–microbe interactions [12]. In this review, we used human and animal studies to discuss gut virome, mycobiome, archaeome, helminths, and their interaction and health impacts.

2. Gut Virome

The bacterial and fungal communities residing in the gastrointestinal (GI) tract have undeniable far-reaching effects in regulating host health [1,12]. In contrast, the composition and dynamics of the gut virome are largely unknown, mainly due to limitations in identification. This is likely because of the lack of availability of viral genomes in the NCBI databases due to diverse global viral populations and their size. However, the impediments to identify and classify the virome have been now overcome with advancements in NGS, allowing us to make more substantial analyses of viromes [25]. Bioinformatics tools, such as the Metavir (versions 1 and 2) [26], bioinformatics pipeline VIROME (Viral Informatics Resource for Metagenome Exploration) [27], VIROMEScan [28], PHACCS (Phage Communities from Contig Spectrum) [29], CLAssification of Mobile genetic Elements (ACLAME) [30], VirusSeeker [31], the Phage SEED, and OptItDBA (Optimized Iterative de Bruijn Graph Assembly) have greatly improved the breadth and accessibility of virome analysis by improving assembly and annotating viromes against multiple annotated sequence databases, which improves the analytic capabilities beyond the constraints of individual sequence databases [32,33].

2.1. Gut Phages

The gut virome includes diverse commensal and pathogenic viruses that have abilities to infect host cells as well as other microbes, both avenues are able to directly affect the host’s health (Table 2). With a high inter-individual variation, the gut virome is mostly dominated by bacteriophages [34]. It also includes prophages, eukaryotic viruses, and retroviruses (Table 3). Very recently, studies on metagenomic sequencing of fecal DNA have begun to consistently unravel the extremely complex composition of the gut virome [10,35]. The DNA and RNA viruses that collectively make up the gut virome are at least comparable in number to bacterial cells, but on the gut mucosal surfaces and within the mucous layers; they may outnumber bacterial cells by 20:1 [36,37]. Each gram of human gut content is estimated to contain at least 108–109 virus-like particles, the vast majority of which are cross-assembly phage (DNA) phages belonging to the family Podoviridae [38,39]. Several studies have characterized the gut phage communities in newborn children, demonstrating a high richness and diversity and low stability during the initial days of life [17,40]. This diversity diminishes over the first two years, contrary to what has been observed in bacterial populations, which shift from low to high diversity [41]. Gut phages are primarily classified as members of the double-stranded (ds) DNA virus families such as Myoviridae, Podoviridae, and Siphoviridae within the order Caudovirales, or of the single-stranded (ss) DNA Microviridae family [12]. Recognizing the high abundance of phages in the gut, a Bacteroidetes-infecting phage family was identified and its founding phage alone represented up to 22% of all reads in the human gut metagenome project [42]. Another study characterizing Microviridae from healthy human donors also clustered with the Bacteroides and Prevotella prophages 72, suggesting that Microviridae could be an important viral family in the human gut. These prophages are considered lytic phages, which can integrate into bacterial hosts in an environment that encourages a temperate (lysogenic) viral-host lifestyle [39,41,43].

2.2. Enteric Viruses

While the number of eukaryotic viruses present in the gut is lesser than that of phages, they are detected in metagenomic studies by PCR-based fecal shedding analyses in healthy individuals [45,63]. For example, viruses from the Anelloviridae, Picobirnaviridae, Adenoviridae, and Astroviridae families and species such as Bocavirus, Rotavirus, Enterovirus, and Sapovirus were identified in the fecal DNA samples of healthy children [41,45]. As the presence of eukaryotic viruses in the gut is far less well characterized, some studies have shed light on the dynamics of these viruses, with at least 16 different DNA viral families and 10 RNA families having been detected in gut samples [64]. These observations demonstrate that intestinal colonization with eukaryotic viruses, some of which are known to have pathogenic potential, can be tolerated without apparent symptomatic disease.

2.3. Role of the Gut Virome in Gastrointestinal Health and Disease

When considering the role of the enteric virome in the pathophysiology of GI diseases, the bridge from association to causation needs to be crossed. The gut virome, including enteric eukaryotic viruses and bacteriophages, can elicit chronic inflammation by infecting and killing the host cell as well as bacteria [65]. The first gut virome studies linked the presence or absence of certain viral components to diseases such as IBD and type 1 diabetes (T1D) [9,66]. The decreasing richness of gut bacteria occurring with IBD (both Crohn’s disease (CD) and ulcerative colitis (UC)) patients is well established [2]. In contrast, the fecal virome component’s richness was increased in those disease states when compared to healthy controls [67,68]. Specifically, the number of Caudovirales bacteriophages were increased and associated with viral richness relative to healthy controls [66,68]. Similar results were reported by another study that found reduced Caudovirales phages in healthy individuals when compared to CD and UC patients [51]. Studies of viral communities of diarrheic specimens for unknown causes in individuals from the Americas and Europe resulted in finding a common group of viruses that included Anelloviruses, Picobirnaviruses, and Aichivirus [69,70]. The role of these viruses, as well as if their presence is the cause or a consequence of a diseased GI tract, remains undetermined. In contrast to the richer gut virome observed in IBD patients, the gut viromes of individuals developing T1D were found to be less diverse than the ones from healthy controls, with the latter harboring significantly more viruses of the Circoviridae family [67], suggesting that viruses in the GI tract, such as Circoviridae in T1D, may alternatively exert beneficial functions for preserving host health [71].

2.4. Viromes in Fecal Microbial Transplants and Fecal Virome Transplants

Fecal microbiota transplantation (FMT) has played a significant role in treating recurrent Clostridium associated diarrhea. FMT or a nature-tailored probiotic treatment appears to restore normal or donor-like gut microbial (specifically bacterial) diversity. However, understanding the complex nature of gut microbiome, investigation into the presence and contribution of viromes in such fecal transplants has also begun, shown in Table 4. It is now certain that fecal microbiota contains a high abundance of viruses, primarily bacteriophages (90%) helping to repopulate gut bacterial diversity. As discussed, phages outnumber bacteria on mucosal surface and concerns persist about the unwanted transfer of pathogenic viruses from donor to recipient. The findings from a study by Chehoud and colleagues on FMT treatment in children with UC confirmed the transfer of viral-like particles [72]. Specifically, the members of Siphoviridae (temperate phages) were transferred with greater efficiency; however, none of the viral groups infected human cells. Zuo et al. investigated the presence and role of virome in patients with C. difficile infection (CDI) [73]. This particular study [73] confirmed the presence of phages from Caudovirales (tailed bacteriophages) before FMT treatment, but lower diversity, richness, and evenness compared to healthy controls. More recently, it was found that the impact of a successful FMT on the virome lasted for 12 months and resultant colonization of specific phages depended on donor-recipient combination [74]. This is consistent with a pilot study in which FMT devoid of bacteria was effective in CDI treatment, and increases the possibility that phages may be involved in the success of FMT [75].
In line with the studies mentioned above [75], a few researchers have recently developed a novel therapeutic intervention known as fecal virome transplantation (FVT), where only the viral component from FMT is transplanted [76,77,78]. Draper et al. confirmed the role of the virome in health and disease and showed that FVT, primarily consisting of phages, ameliorated antibiotic-induced bacterial dysbiosis [74]. FVT in mice resulted in a significant impact on not only abundance and diversity of bacteriome, but also the virome. The transplanted phages were able to colonize the gut and reshape the bacteriome similarly to a pre-antibiotic state. Likewise, a study by Rasmussen et al. utilized FVT in a type-2-diabetes and murine-obesity model [78], whereby only the virome in transplants from lean mice fed with a low-fat diet (LFD) to both obese mice (diet-induced obesity (DIO)) and mice fed a high-fat diet (HFD) + antibiotics, unlike Turnbaugh et al. [79]. FVT from lean donors partially reshaped the gut microbial composition in both of the recipient groups and decreased weight gain in DIO mice. In both these FVT studies [78], the gut viral composition was dominated by order Caudovirales and family Microviridae viruses. In another study, treatment with FVT (lytic and temperate gut phages) modulated gut microbial composition; the lytic phages enhanced the beneficial species of gut microbiota, and temperate phages stimulated the growth of commensal in the gut [76]. Interestingly, Hsu et al. confirmed that phages not only modulate the microbiome but also its associated metabolome [80]. In this particular study [80], gnotobiotic mice were subjected to lytic phages (FVT) after they were colonized with commensals, resulting in the finding that phage-led microbiome modulation was indeed due to intense microbe–microbe (intra- and inter-microbial) interactions which led to changes in the metabolome. More recently, Lin et al. compared FVT against FMT treatment on the ileal microbiome in mice fed with HFD [77], which promoted small intestinal bacterial overgrowth. They found reduced bacterial diversity in HFD mice receiving either FMT or FVT, compared to controls. Moreover, fecal transplants to control mice from HFD donor mice subjected to FVT shifted the ileal microbial composition similar to HFD mice, suggesting a causative role for FVT. Indeed, virome transplants could be beneficial as a therapy for many metabolic diseases related to gut microbiota, in addition to recurrent CDI.

3. Mycobiome

Mycobiome, mycome, fungeome, or mycobiota is the collection of the fungal community and their respective genomes associated with the human body. Fungi are detected within the gut of many mammals, including humans, mice, rats, pigs, and numerous ruminant and non-ruminant herbivores [82]. NGS of the internal-transcribed-spacer (ITS) regions to identify the fungal ribosomal genes indicated the mycobiome as a third important dimension of the gut microbiomes [20]. However, the characterization of the mycobiome is complicated by the lack of comprehensive, accurate, and high-resolution taxonomic annotation within fungal databases [83]. Existing databases containing fungal targets include UNITE fungal ITS (1 and 2) database [84], Findley, ITSoneDB, RefSeq targeted loci (RTL), targeted host-associated fungi (THF) database, International Society for Human and Animal Mycology (ISHAM) ITS database, and SILVA [83,84,85,86,87,88,89,90,91]. The bioinformatics tools used in data analyses include MaAsLin [92] and MEGA software [93].
Several studies in recent years have detailed the importance of fungi within the human gut (Table 5) [82]. Shotgun metagenomics sequencing approaches suggest that fungi account for approximately 0.1% of the gut microbiome. An early study by Quin and colleagues that included 96 stool samples from healthy volunteers found 66 genera [94]. Fungi are detectable in all sections of the GI tract of about 70% of healthy adults, normally at up to 103 cfu per mL or g of intestinal contents [82]. Fungal genera commonly detected in mycobiome include Candida, Saccharomyces, Fusarium, Debaromyces, Penicillium, Galactomyces, Pichia, Cladosporium, Malassezia, Aspergillus, Cryptococcus, Trichosporon, and Cyberlindnera [95]. The potential roles played by these microbes in the human gut, however, is poorly understood.
Recent findings support the notion that a competitive association exists between bacterial and fungal microorganisms in the gut [6]. As an example, studies have shown that prolonged antibiotic usage is linked to fungal infection and overgrowth, particularly in the gut, and that germ-free mice are susceptible to infection with fungi such as Candida spp. [96]. Mycobiome dysbiosis is relevant in diseases such as IBD; the gut mycobiome of IBD patients has been characterized by reduced fungal diversity and a dysbiosis in community populations relative to healthy controls [97]. At the phylum level, the fungal ratio of Basidiomycota to Ascomycota was altered, with significantly higher relative abundance of Basidiomycota and a corresponding lower abundance of Ascomycota. More specifically, these trends have been attributed to higher relative abundances of the taxa Candida, Filobasidiaceae, and Malasseziales and a concurrent lower abundances of Saccharomyces, Penicillium, and Kluyveromyces [82,95].
Some emerging factors thought to be associated with composition of the mycobiota include host genotype and host physiology, including sex, age, and presence of comorbid conditions, lifestyles such as diet, hygiene, and occupation, and the immune system [98]. Diet represents a significant factor influencing the fungal mycobiome composition [6,99]. For example, Candida abundance is found to be strongly associated with the recent ingestion of carbohydrates [100]. However, further research is needed to establish the causality and explore the importance of additional factors that may influence the mycobiota, such as other lifestyle factors (e.g., exercise), medications (e.g., antibiotics or antifungals), and comorbid conditions.

4. Gut Archaea

Like bacteria, archaea are prokaryotes and categorized under the single-cell domain. Although morphologically they resemble bacteria, archaea have genes and metabolic pathways like other eukaryotes. The archaeal part of the gut microbiome is referred to as archaeome (Table 6). A range of human fecal NGS studies worldwide has reported archaeal prevalence up to 0.8 to 0.10% of the whole gut microbiome [5,94,110]. The most prominent archaeal microbes are methanogens (methane producers) and less prominent are halophilic (salt-loving microbes) archaea [110]. Molecular studies have indicated the presence of members of the orders Methanosarcinales, Thermoplasmatales, Methanomicrobiales, and Nitrososphaerales in the human gut microbiota; however, to date these microbes have not been isolated [14,111].
Methanogens are strict anaerobes that belong to the order Methanobacteriales, the most common genera being the closely related Methaonbrevibacter and Methanosphaera [110,112]. The abundance of methanogens increases from 0.03% to 11% of total gut microbes present between the proximal and distal colon [112]. M. smithii produces methane from the byproducts of bacterial fermentation and is present in up to 95% of fecal samples from human subjects [113]. Interestingly, M. smithii’s abundance was found to be stable over time, even after major changes in diet [14,114]. In the human gut, methanogenic archaea may impact host metabolism, especially energy homeostasis and may contribute to obesity [79], by syntrophic interactions with gut bacteria, which increase short-chain fatty acid production and contribute to an excess of calories available to the host [115]. Moreover, methanogens produce methane, shown to slow intestinal transit and lead to constipation [116]. In the case of IBD, methanogens like M. smithii and Methanosphaera stadtmanae have been most prevalent and shown to induce strong pro-inflammatory responses via monocyte-derived dendritic cells [117,118,119]. Halophilic archaea, or halophiles, are salt-loving microbes; the human gut environment is moderately salty, and a few IBD studies have isolated halophilic archaea from intestinal mucosal samples [120]. Currently, the studies on archaeal association with human disease are limited and further investigation is needed to elucidate its role in human health.

5. Helminths

Helminths are a type of multicellular parasitic intestinal worms found in various locations such as intestinal lumen, blood, or muscles of the host, and are usually referred to as macrobiome, and are known to be present in one-third of the global human population. Enteric helminths should be considered as a part of the gut microbiota as they co-reside in the gut with bacteria, viruses, and fungi [131]. Most of the helminth’s lifecycle is completed in the host’s intestine by disrupting the intestinal microbial ecosystem and imparting epithelial damage (Table 7). To control this damage, hosts promote the rapid expansion of intestinal epithelial cell numbers, mucus production, promotion of Th2 responses, and activation of T regulatory (Treg) cells to limit inflammation and increase wound healing capacity. Although most of these worms are considered parasitic, Allen et al. [132] suggested a symbiotic relation between helminths and host, whereby helminths are tolerated, and intestinal tissue damage is minimized. In a Malaysian population-based study, individuals with helminths had higher microbial diversity as compared to individuals without helminths [16,133]. Increasing evidence suggests that helminths also regulate mucosal inflammation [134,135]. Infection with helminths may lead to anti-inflammatory effects in the gut; specifically, in the case of IBD with Trichiuris suis, helminthic worms have ameliorated disease activities [136,137]. However, the exact mechanism of how helminths may protect the host from the development of IBD remains unknown. More studies on helminths and their relationship with host immune responses could lead to highly effective therapeutic strategies for human IBD, and other autoimmune disorders.

6. Cross-Kingdom Interactions

Advances in ‘omics’ technologies have enabled researchers to better describe host–microbiome and microbiome–microbiome interactions, including the insight that different strains and species of microbes typically compete with each other for limited space and nutrients [145]. Emerging research suggests that the gut microbial system is densely colonized, promoting intense niche competitions for adhesion sites and nutrients (their limitations), and cooperation within and between microbial species [146]. Microbial competition occurs during initial encounters and gradually numbers reduce by co-exclusion, or niche separation or through spatial separation, enabling the coexistence of diverse communities [145]. Like environmental ecosystems, the gut microbial community is dynamic and regulated by cross-kingdom interactions (Figure 2). These intricate microbe–microbe and microbe–host–microbe interactions enable one microbial species to influence another and induce host response. Determining the role of the host in regulating these interactions and maintenance of homeostasis is vital to understanding species-level interactions in the gut.
It is clear that interdependence between bacteriome, virome, and mycobiome exist and any imbalance in the gut microbial composition can impact overall human health [1,136]. For example, the phage can lyse commensal or pathogenic bacteria and drive bacterial evolution in the gut, molding the gut bacteriome [36]. In turn, the bacteriome inhibits pathogen colonization via competition, produces secondary metabolites, energizes host intestinal epithelium and enhances immune responses by host–microbe cross talk. For example, metabolites produced by bacteria can inhibit C. albicans colonization and translocation across the intestinal barrier [20]. Moreover, the efficacy of FMT was reduced due to the presence of C. albicans in donor stool, suggesting a strong relationship between fungal dysbiosis and FMT outcome [147].
Most of the studies on the microbiome suggest common themes between bacteriome, virome, mycobiome, and host genetics; however, there is no study indicating their direct relationships. Multiple factors determine the effect of the microbiome on homeostasis. Until recently, most of the studies have characterized interactions between bacteria and the host, while the relationships involving virome and mycobiome have received less attention. A few studies reported that interactions between components of microbiome and host could modulate the infectivity of viruses, such as the interaction between bacteria, poliovirus, and reovirus [10]. Bacteria can enable viral replication and cellular binding, facilitating chronic infections [37], or can also negatively affect viral infections. Most studies utilizing lactic acid probiotic bacteria such as Lactobacillus have efficiently blocked virus infections caused by rotavirus [148]. Conversely, the introduction of fungi can alter the composition of local, downstream, and upstream bacterial microbiota, while bacterial microbiota and the intestinal epithelium influence the ability of fungi to colonize the gut [13]. The commensal mycobiome-associated metabolites and products can also influence immune homeostasis, while helminths have immuno-regulatory effects evolved from host–parasite interactions [96]. Together, the above findings suggest that each member of the microbiome can individually affect the host immune system via basal stimulation (Table 8).
Host immune responses are determined based on the characteristics of an individual member of the microbiome and its location (intra or extracellular) [149]. Bacteria, viruses, and fungi activate the innate part of the immune system via macrophages, which in turn actuate the adaptive immune system by employing T cells (pro-inflammatory) and their subsets such as T helper (Th) 1 and Th17 cells, respectively [150,151,152]. Similarly, helminths can activate macrophages and Th2 cells, leading to worm expulsion and inflammation. Excessive pro-inflammatory responses can cause damage to the host and thus are regulated by initiation tolerogenic regulatory responses via Treg cells [132] which reduce inflammation (Figure 3). Thus, the immunomodulatory effect of the microbiome promotes microbiome–immune tolerance and immune homeostasis. However, imbalance in the commensal microbial composition may play an important role in the development of autoimmune and chronic inflammatory responses. Trans-kingdom interplay, therefore, adds a layer of complexity in terms of host–microbial and immune homeostasis. Apart from bacteria, more definitively elucidating the roles of human gut virome, mycobiome, and helminths may have the potential to augment detection of disorders and act as disease markers. New developments in metagenomics, enrichment cultures, and bioinformatics tools are urgently required to improve our ability to define and characterize these biomes.

7. Modulation of the Microbiome and Related Concerns

To manipulate the microbiota, one should account for all the members of the gut microbial community; to that end, diet is considered a vital factor to positively modulate the gut microbiome. Different diets, such as LFD and HFD, have varied effects on each microbial community of the gut. For instance, Bacteroides and Prevotella genera were found to correlate with different diets inversely. Abundance of Bacteroides was associated with high fats, amino acids, and choline consumption, whereas Prevotella is correlated with carbohydrate consumption [153]. Additionally, the phage community of the gut is significantly altered by diet based upon pre-existing populations, indicating that individuals with the same diet may have similar, but not identical, viromes [50]. Similar trends were observed in both mycobiome and archaeome. Recent and high consumption of carbohydrates is directly linked to abundance of Candida, whereas a long term patterns of carbohydrates consumption is linked to profusion of Methobrevibacter spp. [100].
A growing body of evidence demonstrates the use of probiotics, prebiotics, synbiotics (pre- and probiotics together), FMT, and recently FVT, to modulate the microbiome [1,2,3]. Although these therapies produced promising outcomes in a few clinical and experimental models, most of them have not been consistent and may not provide consistent clinical benefits. For example, probiotics (single or multi-strained) are considered natural, safe, and beneficial modulators of the gut microbial composition, but their efficacy is strain- and dose-dependent and not all probiotics function against all disorders and diseases [154]. Fundamentally, to confer health benefits a probiotic needs to survive the acidic gastric digestion, other digestive enzymes, reach the intestine and colonize on the intestinal epithelium in good numbers [114]. In most of the probiotic trials, the vehicles for probiotic intake used are yoghurt, biscuits, bars, and capsules, per oral, which is not consistent across the studies and can potentially confound the outcomes [155]. While the exact probiotic mechanism is still unknown, the route of administration and dosage form may influence colonization. The colonization of probiotic strains is also dependent on competition or cooperation (microbe–microbe interactions) with the resident microbiota. Recently, several commercially available probiotics are increasingly multi-strain rather than a single strain [155], but how these multi-strains work and interact with each other to confer health benefits is still unknown. Specific probiotic strains and their combinations need to be further investigated to deploy them to their full potential.
Synbiotics, combinations of pro- and prebiotics, are also arbitrarily chosen in many studies [156]. Sometimes the selected probiotic may not be able to even ferment the selected prebiotic strains [2,156]. The components of synbiotics are rarely tested individually in clinical or pre-clinical studies. Similarly, FMT is currently being explored for virome and mycobiome in the donor fecal samples and but also has not undergone rigorous component-based testing.

8. Conclusions

It is imperative to understand that gut microbiome/macrobiome is not limited to bacteria but also viruses, fungi, and helminths. All these microbes interacting with each other, and with the host, in combination or alone, influence the health of the host. Advances in NGS technologies enable us to study the whole microbiome in an integrative way by exploring the taxonomic profiles and functional attributes of the various microbial communities. Considerable further study will be required to understand the development and regulation of gut microbial communities and the factors mediating the balance between long-term stability and dynamic response to the environment.

Supplementary Materials

The following are available online at https://www.mdpi.com/2076-2607/8/4/483/s1, Table S1: Number of studies published in Web of Science and PubMed databases related to gut microbiome, gut virome, gut mycobiome, gut archaeome and helminths.

Author Contributions

Conceptualization, R.V..; Methodology, R.V.; Writing—Original Draft Preparation, R.V.; Writing—Review & Editing, K.K., R.E., M.C., and E.M.S. All authors have read and agreed to the published version of the manuscript.

Funding

No funding was involved.

Conflicts of Interest

Authors declare no conflict of interest.

References

  1. Vemuri, R.; Gundamaraju, R.; Shastri, M.D.; Shukla, S.D.; Kalpurath, K.; Ball, M.; Tristram, S.; Shankar, E.M.; Ahuja, K.D.; Eri, R. Gut Microbial Changes, Interactions, and Their Implications on Human Lifecycle: An Ageing Perspective. BioMed Res. Int. 2018, 2018, 1–13. [Google Scholar] [CrossRef] [PubMed]
  2. Vemuri, R.; Gundamaraju, R.; Eri, R. Role of lactic acid probiotic bacteria in IBD. Curr. Pharm. Des. 2017, 23, 1. [Google Scholar] [CrossRef] [PubMed]
  3. Vemuri, R.; Sylvia, K.; Klein, S.L.; Forster, S.C.; Plebanski, M.; Eri, R.; Flanagan, K.L. The microgenderome revealed: Sex differences in bidirectional interactions between the microbiota, hormones, immunity and disease susceptibility. Semin. Immunopathol. 2018, 41, 265–275. [Google Scholar] [CrossRef] [PubMed]
  4. Gilbert, J.A.; Blaser, M.J.; Caporaso, J.G.; Jansson, J.K.; Lynch, S.V.; Knight, R. Current understanding of the human microbiome. Nat. Med. 2018, 24, 392–400. [Google Scholar] [CrossRef]
  5. Yatsunenko, T.; Rey, F.E.; Manary, M.J.; Trehan, I.; Dominguez-Bello, M.G.; Contreras, M.; Magris, M.; Hidalgo, G.; Baldassano, R.N.; Anokhin, A.P.; et al. Human gut microbiome viewed across age and geography. Nature 2012, 486, 222–227. [Google Scholar] [CrossRef] [PubMed]
  6. Zuo, T.; Kamm, M.A.; Colombel, J.-F.; Ng, S.C. Urbanization and the gut microbiota in health and inflammatory bowel disease. Nat. Rev. Gastroenterol. Hepatol. 2018, 15, 440–452. [Google Scholar] [CrossRef]
  7. Hugerth, L.W.; Seifert, M.; Pennhag, A.A.L.; Du, J.; Hamsten, M.C.; Schuppe-Koistinen, I.; Engstrand, L. A comprehensive automated pipeline for human microbiome sampling, 16S rRNA gene sequencing and bioinformatics processing. BioRxiv 2018, 286526. [Google Scholar] [CrossRef]
  8. Knight, R.; Vrbanac, A.; Taylor, B.C.; Aksenov, A.; Callewaert, C.; Debelius, J.; González, A.; Kosciolek, T.; McCall, L.-I.; McDonald, D.; et al. Best practices for analysing microbiomes. Nat. Rev. Genet. 2018, 16, 410–422. [Google Scholar] [CrossRef] [Green Version]
  9. Stefanaki, C.; Peppa, M.; Mastorakos, G.; Chrousos, G.P. Examining the gut bacteriome, virome, and mycobiome in glucose metabolism disorders: Are we on the right track? Metabolism 2017, 73, 52–66. [Google Scholar] [CrossRef]
  10. Mukhopadhya, I.; Segal, J.P.; Carding, S.R.; Hart, A.L.; Hold, G.L. The gut virome: The ‘missing link’ between gut bacteria and host immunity? Ther. Adv. Gastroenterol. 2019, 12. [Google Scholar] [CrossRef]
  11. Forbes, J.D.; Bernstein, C.N.; Tremlett, H.; van Domselaar, G.; Knox, N. A Fungal World: Could the Gut Mycobiome Be Involved in Neurological Disease? Front. Microbiol. 2019, 9, 3249. [Google Scholar] [CrossRef]
  12. Yutin, N.; Makarova, K.S.; Gussow, A.B.; Krupovic, M.; Segall, A.; Edwards, R.A.; Koonin, E.V. Discovery of an expansive bacteriophage family that includes the most abundant viruses from the human gut. Nat. Microbiol. 2017, 3, 38–46. [Google Scholar] [CrossRef] [PubMed]
  13. Witherden, E.; Moyes, D.L. Mycobiome and Gut Inflammation. In Immunity and Inflammation in Health and Disease; Elsevier: Amsterdam, The Netherlands, 2018; pp. 271–280. [Google Scholar]
  14. Gaci, N.; Borrel, G.; Tottey, W.; O’Toole, P.W.; Brugère, J.-F. Archaea and the human gut: New beginning of an old story. World J. Gastroenterol. 2014, 20, 16062–16078. [Google Scholar] [CrossRef] [PubMed]
  15. Giacomin, P.; Agha, Z.; Loukas, A. Helminths and Intestinal Flora Team Up to Improve Gut Health. Trends Parasitol. 2016, 32, 664–666. [Google Scholar] [CrossRef] [PubMed]
  16. Weinstock, J.V.; Elliott, D. Helminths and the IBD hygiene hypothesis. Inflamm. Bowel Dis. 2009, 15, 128–133. [Google Scholar] [CrossRef] [PubMed]
  17. Moreno-Gallego, J.L.; Chou, S.-P.; Di Rienzi, S.C.; Goodrich, J.K.; Spector, T.D.; Bell, J.T.; Youngblut, N.D.; Hewson, I.; Reyes, A.; Ley, R.E. Virome Diversity Correlates with Intestinal Microbiome Diversity in Adult Monozygotic Twins. Cell Host Microbe 2019, 25, 261–272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Shkoporov, A.; Clooney, A.G.; Sutton, T.D.; Ryan, F.J.; Daly, K.M.; Nolan, J.A.; McDonnell, S.A.; Khokhlova, E.V.; Draper, L.A.; Forde, A.; et al. The Human Gut Virome Is Highly Diverse, Stable, and Individual Specific. Cell Host Microbe 2019, 26, 527–541. [Google Scholar] [CrossRef]
  19. Reyes, A.; Haynes, M.; Hanson, N.; Angly, F.E.; Heath, A.C.; Rohwer, F.; Gordon, J.I. Viruses in the faecal microbiota of monozygotic twins and their mothers. Nature 2010, 466, 334–338. [Google Scholar] [CrossRef]
  20. Nash, A.K.; Auchtung, T.; Wong, M.C.; Smith, D.; Gesell, J.; Ross, M.; Stewart, C.J.; Metcalf, G.A.; Muzny, D.; Gibbs, R.A.; et al. The gut mycobiome of the Human Microbiome Project healthy cohort. Microbiome 2017, 5, 153. [Google Scholar] [CrossRef]
  21. Motooka, D.; Fujimoto, K.; Tanaka, R.; Yaguchi, T.; Gotoh, K.; Maeda, Y.; Furuta, Y.; Kurakawa, T.; Goto, N.; Yasunaga, T.; et al. Fungal ITS1 Deep-Sequencing Strategies to Reconstruct the Composition of a 26-Species Community and Evaluation of the Gut Mycobiota of Healthy Japanese Individuals. Front. Microbiol. 2017, 8, 238. [Google Scholar] [CrossRef] [Green Version]
  22. Bhute, S.; Suryavanshi, M.V.; Joshi, S.M.; Yajnik, C.S.; Shouche, Y.S.; Ghaskadbi, S.S. Gut Microbial Diversity Assessment of Indian Type-2-Diabetics Reveals Alterations in Eubacteria, Archaea, and Eukaryotes. Front. Microbiol. 2017, 8, 399. [Google Scholar] [CrossRef] [PubMed]
  23. Eckburg, P.B.; Bik, E.M.; Bernstein, C.N.; Purdom, E.; Dethlefsen, L.; Sargent, M.; Gill, S.R.; Nelson, K.E.; Relman, D.A. Diversity of the Human Intestinal Microbial Flora. Science 2005, 308, 1635–1638. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Raymann, K.; Moeller, A.H.; Goodman, A.L.; Ochman, H. Unexplored Archaeal Diversity in the Great Ape Gut Microbiome. mSphere 2017, 2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Miller, S.; Chiu, C. Metagenomic Next-Generation Sequencing for Pathogen Detection and Identification. In Advanced Techniques in Diagnostic Microbiology; Springer Science and Business Media LLC: Berlin/Heidelberg, Germany, 2018; pp. 617–632. [Google Scholar]
  26. Roux, S.; Tournayre, J.; Mahul, A.; Debroas, D.; Enault, F. Metavir 2: New tools for viral metagenome comparison and assembled virome analysis. BMC Bioinform. 2014, 15, 76. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Wommack, K.E.; Bhavsar, J.; Polson, S.W.; Chen, J.; Dumas, M.; Srinivasiah, S.; Furman, M.; Jamindar, S.; Nasko, D.J. VIROME: A standard operating procedure for analysis of viral metagenome sequences. Stand. Genom. Sci. 2012, 6, 427–439. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Rampelli, S.; Soverini, M.; Turroni, S.; Quercia, S.; Biagi, E.; Brigidi, P.; Candela, M. ViromeScan: A new tool for metagenomic viral community profiling. BMC Genom. 2016, 17, 165. [Google Scholar] [CrossRef] [Green Version]
  29. Angly, F.; Rodriguez-Brito, B.; Bangor, D.; McNairnie, P.; Breitbart, M.; Salamon, P.; Felts, B.; Nulton, J.; Mahaffy, J.; Rohwer, F. PHACCS, an online tool for estimating the structure and diversity of uncultured viral communities using metagenomic information. BMC Bioinform. 2005, 6, 41. [Google Scholar] [CrossRef] [Green Version]
  30. Leplae, R.; Lima-Mendez, G.; Toussaint, A. ACLAME: A CLAssification of Mobile genetic Elements, update 2010. Nucleic Acids Res. 2009, 38, D57–D61. [Google Scholar] [CrossRef] [Green Version]
  31. Zhao, G.; Wu, G.; Lim, E.S.; Droit, L.; Krishnamurthy, S.R.; Barouch, D.H.; Virgin, H.W.; Wang, D. VirusSeeker, a computational pipeline for virus discovery and virome composition analysis. Virology 2017, 503, 21–30. [Google Scholar] [CrossRef]
  32. Pal, R.R.; More, R.P.; Purohit, H.J. Bioinformatics Tools for Shotgun Metagenomic Data Analysis. In Soft Computing for Biological Systems; Springer Science and Business Media LLC: Berlin/Heidelberg, Germany, 2018; pp. 91–110. [Google Scholar]
  33. Barrientos-Somarribas, M.; Messina, D.; Pou, C.; Lysholm, F.; Bjerkner, A.; Allander, T.; Andersson, B.; Sonnhammer, E. Discovering viral genomes in human metagenomic data by predicting unknown protein families. Sci. Rep. 2018, 8, 28. [Google Scholar] [CrossRef] [Green Version]
  34. Du Toit, A. Nature Reviews Microbiology. Nat. Rev. Genet. 2019. [Google Scholar] [CrossRef]
  35. Shkoporov, A.; Khokhlova, E.V.; Fitzgerald, C.B.; Stockdale, S.R.; Draper, L.A.; Ross, R.; Hill, C. ΦCrAss001 represents the most abundant bacteriophage family in the human gut and infects Bacteroides intestinalis. Nat. Commun. 2018, 9, 4781. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Moya, A.; Brocal, V.P. The Human Virome; Springer: New York, NY, USA, 2018. [Google Scholar]
  37. Barr, J.J.; Auro, R.; Furlan, M.; Whiteson, K.; Erb, M.L.; Pogliano, J.; Stotland, A.; Wolkowicz, R.; Cutting, A.S.; Doran, K.S.; et al. Bacteriophage adhering to mucus provide a non-host-derived immunity. Proc. Natl. Acad. Sci. USA 2013, 110, 10771–10776. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Abeles, S.R.; Pride, D.T. Molecular Bases and Role of Viruses in the Human Microbiome. J. Mol. Boil. 2014, 426, 3892–3906. [Google Scholar] [CrossRef] [PubMed]
  39. Kim, M.-S.; Park, E.-J.; Roh, S.W.; Bae, J.-W. Diversity and Abundance of Single-Stranded DNA Viruses in Human Feces. Appl. Environ. Microbiol. 2011, 77, 8062–8070. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Moreno-Gallego, J.L.; Chou, S.-P.; Di Rienzi, S.; Goodrich, J.K.; Spector, T.; Bell, J.T.; Youngblut, N.; Hewson, I.; Reyes, A.; Ley, R.E. The virome in adult monozygotic twins with concordant or discordant gut microbiomes. bioRxiv 2019. [Google Scholar] [CrossRef] [Green Version]
  41. Breitbart, M.; Haynes, M.; Kelley, S.; Angly, F.; Edwards, R.A.; Felts, B.; Mahaffy, J.M.; Mueller, J.; Nulton, J.; Rayhawk, S.; et al. Viral diversity and dynamics in an infant gut. Res Microbiol 2008, 159, 367–373. [Google Scholar] [CrossRef]
  42. Kolde, R.; Franzosa, E.A.; Rahnavard, G.; Hall, A.B.; Vlamakis, H.; Stevens, C.; Daly, M.J.; Xavier, R.J.; Huttenhower, C. Host genetic variation and its microbiome interactions within the Human Microbiome Project. Genome Med. 2018, 10, 6. [Google Scholar] [CrossRef]
  43. Lim, E.S.; Zhou, Y.; Zhao, G.; Bauer, I.K.; Droit, L.; Ndao, I.M.; Warner, B.B.; Tarr, P.I.; Wang, D.; Holtz, L.R. Early life dynamics of the human gut virome and bacterial microbiome in infants. Nat. Med. 2015, 21, 1228–1234. [Google Scholar] [CrossRef]
  44. Minot, S.; Bryson, A.; Chehoud, C.; Wu, G.D.; Lewis, J.D.; Bushman, F.D. Rapid evolution of the human gut virome. Proc. Natl. Acad. Sci. USA 2013, 110, 12450–12455. [Google Scholar] [CrossRef] [Green Version]
  45. Reyes, A.; Blanton, L.V.; Cao, S.; Zhao, G.; Manary, M.; Trehan, I.; Smith, M.I.; Wang, D.; Virgin, H.W.; Rohwer, F.; et al. Gut DNA viromes of Malawian twins discordant for severe acute malnutrition. Proc. Natl. Acad. Sci. USA 2015, 112, 11941–11946. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Maya-Lucas, O.; Murugesan, S.; Nirmalkar, K.; Alcaraz, L.D.; Hoyo-Vadillo, C.; Pizano-Zárate, M.L.; García-Mena, J.J.A. The gut microbiome of Mexican children affected by obesity. Anaerobe 2019, 55, 11–23. [Google Scholar] [CrossRef] [PubMed]
  47. Breitbart, M.; Hewson, I.; Felts, B.; Mahaffy, J.M.; Nulton, J.; Salamon, P.; Rohwer, F. Metagenomic analyses of an uncultured viral community from human feces. J. Bacteriol. 2003, 185, 6220–6223. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Zhang, T.; Breitbart, M.; Lee, W.H.; Run, J.-Q.; Wei, C.L.; Soh, S.W.L.; Hibberd, M.L.; Liu, E.T.; Rohwer, F.; Ruan, Y. RNA viral community in human feces: Prevalence of plant pathogenic viruses. PLoS Biol. 2005, 4, e3. [Google Scholar] [CrossRef] [Green Version]
  49. Stockdale, S.R.; Ryan, F.J.; McCann, A.; Dalmasso, M.; Ross, P.R.; Hill, C. Viral Dark Matter in the Gut Virome of Elderly Humans. Preprints 2018. [Google Scholar] [CrossRef]
  50. Minot, S.; Sinha, R.; Chen, J.; Li, H.; Keilbaugh, S.A.; Wu, G.D.; Lewis, J.D.; Bushman, F.D. The human gut virome: Inter-individual variation and dynamic response to diet. Genome Res. 2011, 21, 1616–1625. [Google Scholar] [CrossRef] [Green Version]
  51. Zuo, T.; Lu, X.J.; Zhang, Y.; Cheung, C.P.; Lam, S.; Zhang, F.; Tang, W.; Ching, J.Y.L.; Zhao, R.; Chan, P.K.S.; et al. Gut mucosal virome alterations in ulcerative colitis. Gut 2019. [Google Scholar] [CrossRef] [Green Version]
  52. Norman, J.M.; Handley, S.A.; Baldridge, M.T.; Droit, L.; Liu, C.Y.; Keller, B.C.; Kambal, A.; Monaco, C.L.; Zhao, G.; Fleshner, P.J.C. Disease-specific alterations in the enteric virome in inflammatory bowel disease. Cell 2015, 160, 447–460. [Google Scholar] [CrossRef] [Green Version]
  53. Ma, Y.; You, X.; Mai, G.; Tokuyasu, T.; Liu, C.J.M. A human gut phage catalog correlates the gut phageome with type 2 diabetes. Microbiome 2018, 6, 24. [Google Scholar] [CrossRef]
  54. Monaco, C.L.; Gootenberg, D.B.; Zhao, G.; Handley, S.A.; Ghebremichael, M.S.; Lim, E.S.; Lankowski, A.; Baldridge, M.T.; Wilen, C.B.; Flagg, M.J.; et al. Altered virome and bacterial microbiome in human immunodeficiency virus-associated acquired immunodeficiency syndrome. Cell Host Microbe 2016, 19, 311–322. [Google Scholar] [CrossRef] [Green Version]
  55. D’arc, M.; Furtado, C.; Siqueira, J.D.; Seuánez, H.N.; Ayouba, A.; Peeters, M.; Soares, M.A. Assessment of the gorilla gut virome in association with natural simian immunodeficiency virus infection. Retrovirology 2018, 15, 19. [Google Scholar] [CrossRef] [PubMed]
  56. Tan, Z.; Yu, H.; Xu, L.; Zhao, Z.; Zhang, P.; Qu, Y.; He, B.; Tu, C. Virome profiling of rodents in Xinjiang Uygur Autonomous Region, China: Isolation and characterization of a new strain of Wenzhou virus. Virology 2019, 529, 122–134. [Google Scholar] [CrossRef]
  57. Phan, T.G.; Kapusinszky, B.; Wang, C.; Rose, R.K.; Lipton, H.L.; Delwart, E.L. The fecal viral flora of wild rodents. PLoS Pathog. 2011, 7, e1002218. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Hansen, T.A.; Mollerup, S.; Nguyen, N.P.; White, N.E.; Coghlan, M.; Alquezar-Planas, D.E.; Joshi, T.; Jensen, R.H.; Fridholm, H.; Kjartansdóttir, K.R.; et al. High diversity of picornaviruses in rats from different continents revealed by deep sequencing. Emerging Microbes Infections 2016, 5, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Williams, S.H.; Che, X.; Garcia, J.A.; Klena, J.D.; Lee, B.; Muller, D.; Ulrich, W.; Corrigan, R.M.; Nichol, S.; Jain, K.J.M. Viral diversity of house mice in New York City. Am. Soc. Microbiol. 2018, 9, e01354-17. [Google Scholar] [CrossRef] [Green Version]
  60. Duerkop, B.A.; Kleiner, M.; Paez-Espino, D.; Zhu, W.; Bushnell, B.; Hassell, B.; Winter, S.E.; Kyrpides, N.C.; Hooper, L.V. Murine colitis reveals a disease-associated bacteriophage community. Nat. Microbil. 2018, 3, 1023. [Google Scholar] [CrossRef]
  61. Seth, R.; Maqsood, R.; Mondal, A.; Bose, D.; Kimono, D.; Holland, L.; Janulewicz, P.A.; Klimas, N.; Horner, R.D.; Sullivan, K.; et al. Gut DNA Virome Diversity and Its Association with Host Bacteria Regulate Inflammatory Phenotype and Neuronal Immunotoxicity in Experimental Gulf War Illness. Viruses 2019, 11, 968. [Google Scholar] [CrossRef] [Green Version]
  62. Reyes, A.; Wu, M.; McNulty, N.P.; Rohwer, F.L.; Gordon, J.I. Gnotobiotic mouse model of phage-bacterial host dynamics in the human gut. Proc. Natl. Acad. Sci. USA 2013, 110, 20236–20241. [Google Scholar] [CrossRef] [Green Version]
  63. Minot, S.S.; Wu, G.D.; Lewis, J.D.; Bushman, F.D. Conservation of Gene Cassettes among Diverse Viruses of the Human Gut. PLoS ONE 2012, 7, e42342. [Google Scholar] [CrossRef] [Green Version]
  64. Finkbeiner, S.R.; Allred, A.F.; Tarr, P.I.; Klein, E.J.; Kirkwood, C.D.; Wang, D. Metagenomic Analysis of Human Diarrhea: Viral Detection and Discovery. PLOS Pathog. 2008, 4, e1000011. [Google Scholar] [CrossRef] [Green Version]
  65. Ogilvie, L.; Jones, B.V. The human gut virome: A multifaceted majority. Front. Microbiol. 2015, 6, 918. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Lopetuso, L.R.; Ianiro, G.; Scaldaferri, F.; Cammarota, G.; Gasbarrini, A. Gut Virome and Inflammatory Bowel Disease. Inflamm. Bowel Dis. 2016, 22, 1708–1712. [Google Scholar] [CrossRef] [PubMed]
  67. Zhao, G.; Vatanen, T.; Droit, L.; Park, A.; Kostic, A.D.; Poon, T.W.; Vlamakis, H.; Siljander, H.; Härkönen, T.; Hämäläinen, A.-M.; et al. Intestinal virome changes precede autoimmunity in type I diabetes-susceptible children. Proc. Natl. Acad. Sci. USA 2017, 114, E6166–E6175. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Waller, A.S.; Yamada, T.; Kristensen, D.M.; Kultima, J.R.; Sunagawa, S.; Koonin, E.V.; Bork, P. Classification and quantification of bacteriophage taxa in human gut metagenomes. ISME J. 2014, 8, 1391–1402. [Google Scholar] [CrossRef] [PubMed]
  69. Phan, T.G.; Da Costa, A.C.; Del Valle-Mendoza, J.; Bucardo-Rivera, F.; Nordgren, J.; O’Ryan, M.; Deng, X.; Delwart, E. The fecal virome of South and Central American children with diarrhea includes small circular DNA viral genomes of unknown origin. Arch. Virol. 2016, 161, 959–966. [Google Scholar] [CrossRef] [PubMed]
  70. Smits, S.L.; Schapendonk, C.M.; Van Beek, J.; Vennema, H.; Schürch, A.C.; Schipper, D.; Bodewes, R.; Haagmans, B.L.; Osterhaus, A.D.M.E.; Koopmans, M. New Viruses in Idiopathic Human Diarrhea Cases, the Netherlands. Emerg. Infect. Dis. 2014, 20, 1218–1222. [Google Scholar] [CrossRef] [Green Version]
  71. Park, A.; Zhao, G. Mining the Virome for Insights into Type 1 Diabetes. DNA Cell Boil. 2018, 37, 422–425. [Google Scholar] [CrossRef]
  72. Chehoud, C.; Dryga, A.; Hwang, Y.; Nagy-Szakal, R.; Hollister, E.B.; Luna, R.A.; Versalovic, J.; Kellermayer, R.; Bushman, F.D. Transfer of Viral Communities between Human Individuals during Fecal Microbiota Transplantation. mBio 2016, 7, e00322-16. [Google Scholar] [CrossRef] [Green Version]
  73. Zuo, T.; Wong, S.H.; Lam, K.; Lui, R.; Cheung, K.; Tang, W.; Ching, J.Y.L.; Chan, P.K.S.; Chan, M.; Wu, J.C.Y.; et al. Bacteriophage transfer during faecal microbiota transplantation inClostridium difficileinfection is associated with treatment outcome. Gut 2017, 67, 634–643. [Google Scholar] [CrossRef] [Green Version]
  74. Draper, L.A.; Ryan, F.; Smith, M.K.; Jalanka, J.; Mattila, E.; Arkkila, P.A.; Ross, R.; Satokari, R.; Hill, C. Long-term colonisation with donor bacteriophages following successful faecal microbial transplantation. Microbiome 2018, 6, 220. [Google Scholar] [CrossRef] [Green Version]
  75. Ott, S.J.; Waetzig, G.H.; Rehman, A.; Anderson, J.M.; Bharti, R.; Grasis, J.A.; Cassidy, L.; Tholey, A.; Fickenscher, H.; Seegert, D.; et al. Efficacy of Sterile Fecal Filtrate Transfer for Treating Patients With Clostridium difficile Infection. Gastroenterol. 2017, 152, 799–811. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Bao, H.-D.; Pang, M.-D.; Olaniran, A.; Zhang, X.-H.; Zhang, H.; Zhou, Y.; Sun, L.-C.; Schmidt, S.; Wang, R. Alterations in the diversity and composition of mice gut microbiota by lytic or temperate gut phage treatment. Appl. Microbiol. Biotechnol. 2018, 102, 10219–10230. [Google Scholar] [CrossRef] [PubMed]
  77. Lin, D.M.; Koskella, B.; Ritz, N.L.; Lin, D.; Carroll-Portillo, A.; Lin, H.C. Transplanting Fecal Virus-Like Particles Reduces High-Fat Diet-Induced Small Intestinal Bacterial Overgrowth in Mice. Front. Microbiol. 2019, 9, 348. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Rasmussen, T.S.; Mentzel, C.M.J.; Kot, W.; Castro-Mejía, J.L.; Zuffa, S.; Swann, J.R.; Hansen, L.H.; Vogensen, F.K.; Hansen, A.K.; Nielsen, D.S. Faecal virome transplantation decreases symptoms of type 2 diabetes and obesity in a murine model. Gut 2020. [Google Scholar] [CrossRef]
  79. Turnbaugh, P.J.; Ley, R.E.; Mahowald, M.A.; Magrini, V.; Mardis, E.R.; Gordon, J.I. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006, 444, 1027–1031. [Google Scholar] [CrossRef]
  80. Hsu, B.B.; Gibson, T.E.; Yeliseyev, V.; Liu, Q.; Lyon, L.; Bry, L.; Silver, P.A.; Gerber, G.K. Dynamic Modulation of the Gut Microbiota and Metabolome by Bacteriophages in a Mouse Model. Cell Host Microbe 2019, 25, 803–814. [Google Scholar] [CrossRef] [Green Version]
  81. Conceição-Neto, N.; Deboutte, W.; Dierckx, T.; Machiels, K.; Wang, J.; Yinda, K.C.; Maes, P.; Van Ranst, M.; Joossens, M.; Raes, J.; et al. Low eukaryotic viral richness is associated with faecal microbiota transplantation success in patients with UC. Gut 2017, 67, 1558–1559. [Google Scholar] [CrossRef]
  82. Jones, L.; Kumar, J.; Mistry, A.; Sankar Chittoor Mana, T.; Perry, G.; Reddy, V.P.; Obrenovich, M. The Transformative Possibilities of the Microbiota and Mycobiota for Health, Disease, Aging, and Technological Innovation. Biomedicines 2019, 7, 24. [Google Scholar] [CrossRef] [Green Version]
  83. Tang, J.; Iliev, I.D.; Brown, J.; Underhill, D.M.; Funari, V.A. Mycobiome: Approaches to Analysis of Intestinal Fungi. J. Immunol. Methods 2015, 421, 112–121. [Google Scholar] [CrossRef] [Green Version]
  84. Kõljalg, U.; Nilsson, R.H.; Abarenkov, K.; Tedersoo, L.; Taylor, A.F.S.; Bahram, M.; Bates, S.T.; Bruns, T.D.; Bengtsson-Palme, J.; Callaghan, T.M.; et al. Towards a unified paradigm for sequence-based identification of fungi. Mol. Ecol. 2013, 22, 5271–5277. [Google Scholar] [CrossRef] [Green Version]
  85. Abarenkov, K.; Nilsson, R.H.; Larsson, K.-H.; Alexander, I.J.; Eberhardt, U.; Erland, S.; Høiland, K.; Kjøller, R.; Larsson, E.; Pennanen, T.; et al. The UNITE database for molecular identification of fungi - recent updates and future perspectives. New Phytol. 2010, 186, 281–285. [Google Scholar] [CrossRef] [PubMed]
  86. Findley, K.; Oh, J.; Yang, J.; Conlan, S.; Deming, C.; Meyer, J.A.; Schoenfeld, D.; Nomicos, E.; Park, M.; NIH Intramural Sequencing Center Comparative Sequencing Program; et al. Topographic diversity of fungal and bacterial communities in human skin. Nature 2013, 498, 367–370. [Google Scholar] [CrossRef] [PubMed]
  87. Santamaria, M.; Fosso, B.; Consiglio, A.; De Caro, G.; Grillo, G.; Licciulli, F.; Liuni, S.; Marzano, M.; Alonso-Alemany, D.; Valiente, G.; et al. Reference databases for taxonomic assignment in metagenomics. Briefings Bioinform. 2012, 13, 682–695. [Google Scholar] [CrossRef] [Green Version]
  88. Koetschan, C.; Hackl, T.; Müller, T.; Wolf, M.; Förster, F.; Schultz, J. ITS2 Database IV: Interactive taxon sampling for internal transcribed spacer 2 based phylogenies. Mol. Phylogenetics Evol. 2012, 63, 585–588. [Google Scholar] [CrossRef]
  89. Schoch, C.L.; Robbertse, B.; Robert, V.; Vu, D.; Cardinali, G.; Irinyi, L.; Meyer, W.; Nilsson, R.H.; Hughes, K.; Miller, A.N.; et al. Finding needles in haystacks: Linking scientific names, reference specimens and molecular data for Fungi. Database 2014. [Google Scholar] [CrossRef]
  90. Irinyi, L.; Serena, C.; Garcia-Hermoso, D.; Arabatzis, M.; Desnos-Ollivier, M.; Vu, D.; Cardinali, G.; Arthur, I.; Normand, A.-C.; Giraldo, A.; et al. International Society of Human and Animal Mycology (ISHAM)-ITS reference DNA barcoding database—The quality controlled standard tool for routine identification of human and animal pathogenic fungi. Med Mycol. 2015, 53, 313–337. [Google Scholar] [CrossRef]
  91. Pruesse, E.; Quast, C.; Knittel, K.; Fuchs, B.M.; Ludwig, W.; Peplies, J.; Glöckner, F.O. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007, 35, 7188–7196. [Google Scholar] [CrossRef] [Green Version]
  92. Standaert, A.; Sendid, B.; Joossens, M.; François, N.; Khoury, P.V.-E.; Branche, J.; Van Kruiningen, H.; Jouault, T.; Rutgeerts, P.; Gower, C.; et al. Candida albicans Colonization and ASCA in Familial Crohn’s Disease. Am. J. Gastroenterol. 2009, 104, 1745–1753. [Google Scholar] [CrossRef] [PubMed]
  93. Tamura, K.; Dudley, J.; Nei, M.; Kumar, S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) Software Version 4.0. Mol. Boil. Evol. 2007, 24, 1596–1599. [Google Scholar] [CrossRef] [PubMed]
  94. Qin, J.; Li, R.; Raes, J.; Arumugam, M.; Burgdorf, K.; Manichanh, C.; Nielsen, T.; Pons, N.; Levenez, F.; Yamada, T.; et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010, 464, 59–65. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Hallen-Adams, H.E.; Suhr, M.J. Fungi in the healthy human gastrointestinal tract. Virulence 2016, 8, 352–358. [Google Scholar] [CrossRef]
  96. Wheeler, M.L.; Limon, J.J.; Bar, A.S.; Leal, C.A.; Gargus, M.; Tang, J.; Brown, J.; Funari, V.A.; Wang, H.L.; Crother, T.R.; et al. Immunological Consequences of Intestinal Fungal Dysbiosis. Cell Host Microbe 2016, 19, 865–873. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  97. Sokol, H.; Leducq, V.; Aschard, H.; Pham, H.-P.; Jegou, S.; Landman, C.; Cohen, D.; Liguori, G.; Bourrier, A.; Nion-Larmurier, I.; et al. Fungal microbiota dysbiosis in IBD. Gut 2016, 66, 1039–1048. [Google Scholar] [CrossRef] [Green Version]
  98. Limon, J.J.; Skalski, J.; Underhill, D.M. Commensal Fungi in Health and Disease. Cell Host Microbe 2017, 22, 156–165. [Google Scholar] [CrossRef]
  99. Lai, G.C.; Tan, T.G.; Pavelka, N. The mammalian mycobiome: A complex system in a dynamic relationship with the host. Wiley Interdiscip. Rev. Syst. Boil. Med. 2018, 11, e1438. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  100. Hoffmann, C.; Dollive, S.; Grunberg, S.; Chen, J.; Li, H.; Wu, G.D.; Lewis, J.D.; Bushman, F.D. Archaea and Fungi of the Human Gut Microbiome: Correlations with Diet and Bacterial Residents. PLoS ONE 2013, 8, e66019. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  101. Schei, K.; Avershina, E.; Øien, T.; Rudi, K.; Follestad, T.; Salamati, S.; Ødegård, R.A. Early gut mycobiota and mother-offspring transfer. Microbiome 2017, 5, 107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Rosin, M.; Lee, A.; Boxen, K.; Duncan, A.; Rosendale, D.; Villas-Boas, S.; McKenzie, E.J. The New Zealand human gut mycobiome. In Proceedings of the Foodomics 2019 High Value Nutrition National Science Challenge, Auckland, New Zealand, 9–11 April 2019. [Google Scholar]
  103. Ahmad, H.F.B.; Mejia, J.L.C.; Kot, W.; Bechshøft, R.L.; Reitelseder, S.; Holm, L.; Nielsen, D.S. The Gut Mycobiome of Elderly Danes. In Proceedings of the Danish Microbiological Society Annual Congress 2016, Comenhagen, Denmark, 14 November 2016. [Google Scholar]
  104. Borges, F.M.; De Paula, T.O.; Sarmiento, M.R.A.; De Oliveira, M.G.; Pereira, M.L.M.; Toledo, I.V.; Nascimento, T.C.; Ferreira-Machado, A.B.; Silva, V.L.; Diniz, C.G. Fungal Diversity of Human Gut Microbiota Among Eutrophic, Overweight, and Obese Individuals Based on Aerobic Culture-Dependent Approach. Curr. Microbiol. 2018, 75, 726–735. [Google Scholar] [CrossRef]
  105. Botschuijver, S.; Roeselers, G.; Levin, E.; Jonkers, D.M.; Welting, O.; Heinsbroek, S.E.M.; De Weerd, H.H.; Boekhout, T.; Fornai, M.; Masclee, A.A.; et al. Intestinal Fungal Dysbiosis Is Associated With Visceral Hypersensitivity in Patients With Irritable Bowel Syndrome and Rats. Gastroenterol. 2017, 153, 1026–1039. [Google Scholar] [CrossRef]
  106. Li, J.; Li, L.; Jiang, H.; Yuan, L.; Zhang, L.; Ma, J.-E.; Zhang, X.; Cheng, M.; Chen, J. Fecal Bacteriome and Mycobiome in Bats with Diverse Diets in South China. Curr. Microbiol. 2018, 75, 1352–1361. [Google Scholar] [CrossRef]
  107. Foster, M.L.; Dowd, S.E.; Stephenson, C.; Steiner, J.M.; Suchodolski, J.S. Characterization of the Fungal Microbiome (Mycobiome) in Fecal Samples from Dogs. Veter. Med. Int. 2013, 2013, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Aykut, B.; Pushalkar, S.; Chen, R.; Li, Q.; Abengozar, R.; Kim, J.I.; Shadaloey, S.A.; Wu, D.; Preiss, P.; Verma, N.; et al. The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL. Nature 2019, 574, 264–267. [Google Scholar] [CrossRef] [PubMed]
  109. Sun, B.; Huffman, M.A.; Li, J.-H. The Gut Microbiome of Tibetan Macaques: Composition, Influencing Factors and Function in Feeding Ecology. In The Evolution of Feathers; Springer Science and Business Media LLC: Berlin/Heilderbeg, Germany, 2019; pp. 207–222. [Google Scholar]
  110. Lurie-Weinberger, M.N.; Gophna, U. Archaea in and on the Human Body: Health Implications and Future Directions. PLOS Pathog. 2015, 11, e1004833. [Google Scholar] [CrossRef] [PubMed]
  111. Dridi, B.; Fardeau, M.-L.; Ollivier, B.; Raoult, D.; Drancourt, M. Methanomassiliicoccus luminyensis gen. nov., sp. nov., a methanogenic archaeon isolated from human faeces. Int. J. Syst. Evol. Microbiol. 2012, 62, 1902–1907. [Google Scholar] [CrossRef] [Green Version]
  112. Dridi, B.; Henry, M.; El Khéchine, A.; Raoult, D.; Drancourt, M. High Prevalence of Methanobrevibacter smithii and Methanosphaera stadtmanae Detected in the Human Gut Using an Improved DNA Detection Protocol. PLoS ONE 2009, 4, e7063. [Google Scholar] [CrossRef] [PubMed]
  113. Mihajlovski, A.; Doré, J.; Levenez, F.; Alric, M.; Brugère, J.-F. Molecular evaluation of the human gut methanogenic archaeal microbiota reveals an age-associated increase of the diversity. Environ. Microbiol. Rep. 2010, 2, 272–280. [Google Scholar] [CrossRef] [PubMed]
  114. Vemuri, R.; Shinde, T.; Shastri, M.D.; Perera, A.P.; Tristram, S.; Martoni, C.J.; Gundamaraju, R.; Ahuja, K.D.K.; Ball, M.; Eri, R. A human origin strain Lactobacillus acidophilus DDS-1 exhibits superior in vitro probiotic efficacy in comparison to plant or dairy origin probiotics. Int. J. Med Sci. 2018, 15, 840–848. [Google Scholar] [CrossRef] [Green Version]
  115. Goodrich, J.K.; Waters, J.L.; Poole, A.; Sutter, J.L.; Koren, O.; Blekhman, R.; Beaumont, M.; Van Treuren, W.; Knight, R.; Bell, J.T.; et al. Human Genetics Shape the Gut Microbiome. Cell 2014, 159, 789–799. [Google Scholar] [CrossRef] [Green Version]
  116. Pimentel, M.; Lin, H.; Enayati, P.; Burg, B.V.D.; Lee, H.-R.; Chen, J.H.; Park, S.; Kong, Y.; Conklin, J. Methane, a gas produced by enteric bacteria, slows intestinal transit and augments small intestinal contractile activity. Am. J. Physiol. Liver Physiol. 2006, 290, G1089–G1095. [Google Scholar] [CrossRef] [Green Version]
  117. Lurie-Weinberger, M.N.; Peeri, M.; Tuller, T.; Gophna, U. Extensive Inter-Domain Lateral Gene Transfer in the Evolution of the Human Commensal Methanosphaera stadtmanae. Front. Genet. 2012, 3, 182. [Google Scholar] [CrossRef] [Green Version]
  118. Lurie-Weinberger, M.N.; Peeri, M.; Gophna, U. Contribution of lateral gene transfer to the gene repertoire of a gut-adapted methanogen. Genome 2012, 99, 52–58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  119. Bang, C.; Weidenbach, K.; Gutsmann, T.; Heine, H.; Schmitz-Streit, R.A. The Intestinal Archaea Methanosphaera stadtmanae and Methanobrevibacter smithii Activate Human Dendritic Cells. PLoS ONE 2014, 9, e99411. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  120. Oxley, A.P.A.; Lanfranconi, M.P.; Würdemann, D.; Ott, S.; Stefánsson, K.; McGenity, T.J.; Timmis, K.N.; Nogales, B. Halophilic archaea in the human intestinal mucosa. Environ. Microbiol. 2010, 12, 2398–2410. [Google Scholar] [CrossRef]
  121. Wampach, L.; Heintz-Buschart, A.; Hogan, A.; Muller, E.; Narayanasamy, S.; Laczny, C.C.; Hugerth, L.W.; Bindl, L.; Bottu, J.; Andersson, A.F.; et al. Colonization and Succession within the Human Gut Microbiome by Archaea, Bacteria, and Microeukaryotes during the First Year of Life. Front. Microbiol. 2017, 8, 434. [Google Scholar] [CrossRef] [PubMed]
  122. Mbakwa, C.A.; Penders, J.; Savelkoul, P.H.; Thijs, C.; Dagnelie, P.C.; Mommers, M.; Arts, I.C. Gut colonization with Methanobrevibacter smithii is associated with childhood weight development. Obesity 2015, 23, 2508–2516. [Google Scholar] [CrossRef] [PubMed]
  123. Abell, G.C.; Conlon, M.A.; McOrist, A.L. Methanogenic archaea in adult human faecal samples are inversely related to butyrate concentration. Microb. Ecol. Heal. Dis. 2006, 18, 154–160. [Google Scholar]
  124. Jalanka, J.; Salonen, A.; Nikkilä, J.; Immonen, O.; Kekkonen, R.; Lahti, L.; Palva, A.; De Vos, W.M. Intestinal Microbiota in Healthy Adults: Temporal Analysis Reveals Individual and Common Core and Relation to Intestinal Symptoms. PLoS ONE 2011, 6, e23035. [Google Scholar]
  125. Falony, G.; Joossens, M.; Vieira-Silva, S.; Wang, J.; Darzi, Y.; Faust, K.; Kurilshikov, A.; Bonder, M.-J.; Valles-Colomer, M.; Vandeputte, D.; et al. Population-level analysis of gut microbiome variation. Science 2016, 352, 560–564. [Google Scholar] [CrossRef]
  126. Dridi, B.; Henry, M.; Richet, H.; Raoult, D.; Drancourt, M.J.A. Age-related prevalence of M ethanomassiliicoccus luminyensis in the human gut microbiome. Apmis 2012, 120, 773–777. [Google Scholar] [CrossRef]
  127. Borrel, G.; McCann, A.; Deane, J.; Neto, M.C.; Lynch, D.B.; Brugère, J.-F.; O’Toole, P.W. Genomics and metagenomics of trimethylamine-utilizing Archaea in the human gut microbiome. ISME J. 2017, 11, 2059–2074. [Google Scholar] [CrossRef] [Green Version]
  128. Lecours, P.B.; Marsolais, D.; Cormier, Y.; Berberi, M.; Haché, C.; Bourdages, R.; Duchaine, C. Increased Prevalence of Methanosphaera stadtmanae in Inflammatory Bowel Diseases. PLoS ONE 2014, 9, e87734. [Google Scholar] [CrossRef]
  129. Ghavami, S.B.; Rostami, E.; Sephay, A.A.; Shahrokh, S.; Balaii, H.; Aghdaei, H.A.; Zali, M.R. Alterations of the human gut Methanobrevibacter smithii as a biomarker for inflammatory bowel diseases. Microb. Pathog. 2018, 117, 285–289. [Google Scholar] [CrossRef]
  130. Zhu, Y.; Sun, Y.; Wang, C.; Li, F. Impact of dietary fibre: Starch ratio in shaping caecal archaea revealed in rabbits. J. Anim. Physiol. Anim. Nutr. 2016, 101, 635–640. [Google Scholar] [CrossRef] [PubMed]
  131. Weinstock, J.V.; Summers, R.; Elliott, D. Helminths and harmony. Gut 2004, 53, 7–9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Allen, J.E.; Maizels, R.M. Diversity and dialogue in immunity to helminths. Nat. Rev. Immunol. 2011, 11, 375–388. [Google Scholar] [CrossRef]
  133. Weinstock, J.V.; Summers, R.W.; Elliott, D.; Qadir, K.; Urban, J.F.; Thompson, R. The possible link between de-worming and the emergence of immunological disease. J. Lab. Clin. Med. 2002, 139, 334–338. [Google Scholar] [CrossRef] [PubMed]
  134. Giacomin, P.; Croese, J.; Krause, L.; Loukas, A.; Cantacessi, C. Suppression of inflammation by helminths: A role for the gut microbiota? Philos. Trans. R. Soc. B: Boil. Sci. 2015, 370, 20140296. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  135. Ramanan, D.; Bowcutt, R.; Lee, S.C.; Tang, M.S.; Kurtz, Z.D.; Ding, Y.; Honda, K.; Gause, W.C.; Blaser, M.J.; Bonneau, R.A.; et al. Helminth infection promotes colonization resistance via type 2 immunity. Science 2016, 352, 608–612. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  136. Helmby, H. Human helminth therapy to treat inflammatory disorders—Where do we stand? BMC Immunol. 2015, 16, 12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  137. Summers, R.W.; Elliott, D.; Urban, J.F.; Thompson, R.A.; Weinstock, J.V. Trichuris suis therapy for active ulcerative colitis: A randomized controlled trial. Gastroenterol. 2005, 128, 825–832. [Google Scholar] [CrossRef] [Green Version]
  138. Moreels, T.G.; Nieuwendijk, R.J.; De Man, J.G.; De Winter, B.Y.; Herman, A.G.; Van Marck, E.A.; Pelckmans, P.A. Concurrent infection with Schistosoma mansoni attenuates inflammation induced changes in colonic morphology, cytokine levels, and smooth muscle contractility of trinitrobenzene sulphonic acid induced colitis in rats. Gut 2004, 53, 99–107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  139. Broadhurst, M.J.; Ardeshir, A.; Kanwar, B.; Mirpuri, J.; Gundra, U.M.; Leung, J.; Wiens, K.; Vujkovic-Cvijin, I.; Kim, C.C.; Yarovinsky, F.; et al. Therapeutic Helminth Infection of Macaques with Idiopathic Chronic Diarrhea Alters the Inflammatory Signature and Mucosal Microbiota of the Colon. PLOS Pathog. 2012, 8, e1003000. [Google Scholar] [CrossRef] [PubMed]
  140. Sabin, E.A.; Carvalho, E.M.; Araujo, M.I.; Pearce, E.J. Impairment of Tetanus Toxoid-Specific Thl-like Immune Responses in Humans Infected with Schistosoma mansoni. J. Infect. Dis. 1996, 173, 269–272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  141. Summers, R.W.; Elliott, D.E.; Qadir, K.; Urban, J.F., Jr.; Thompson, R.; Weinstock, J.V. Trichuris suis seems to be safe and possibly effective in the treatment of inflammatory bowel disease. Am. J. Gastoeneorol. 2003, 98, 2034. [Google Scholar] [CrossRef]
  142. Sandborn, W.; Elliott, D.; Weinstock, J.; Summers, R.; Landry-Wheeler, A.; Silver, N.; Harnett, M.; Hanauer, S. Randomised clinical trial: The safety and tolerability of T richuris suis ova in patients with Crohn’s disease. Aliment Pharnacol. Ther. 2013, 38, 255–263. [Google Scholar] [CrossRef]
  143. Croese, J.; O’neil, J.; Masson, J.; Cooke, S.; Melrose, W.; Pritchard, D.; Speare, R. A proof of concept study establishing Necator americanus in Crohn’s patients and reservoir donors. Gut 2006, 55, 136–137. [Google Scholar] [CrossRef] [Green Version]
  144. Fleming, J.O.; Isaák, A.; Lee, J.E.; Luzzio, C.C.; Carrithers, M.D.; Cook, T.D.; Field, A.S.; Boland, J.; Fabry, Z. Probiotic helminth administration in relapsing—Remitting multiple sclerosis: A phase 1 study. Mult. Scler. J. 2011, 17, 743–754. [Google Scholar] [CrossRef]
  145. Ghoul, M.; Mitri, S. The Ecology and Evolution of Microbial Competition. Trends Microbiol. 2016, 24, 833–845. [Google Scholar] [CrossRef]
  146. Hibbing, M.E.; Fuqua, C.; Parsek, M.R.; Peterson, S.B. Bacterial competition: Surviving and thriving in the microbial jungle. Nat. Rev. Genet. 2010, 8, 15–25. [Google Scholar] [CrossRef] [Green Version]
  147. Zuo, T.; Wong, S.H.; Cheung, C.P.; Lam, K.; Lui, R.; Cheung, K.; Zhang, F.; Tang, W.; Ching, J.Y.L.; Wu, J.C.Y.; et al. Gut fungal dysbiosis correlates with reduced efficacy of fecal microbiota transplantation in Clostridium difficile infection. Nat. Commun. 2018, 9, 1–11. [Google Scholar] [CrossRef]
  148. Karst, S.M. The influence of commensal bacteria on infection with enteric viruses. Nat. Rev. Genet. 2016, 14, 197–204. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  149. Filyk, H.A.; Osborne, L.C. The Multibiome: The Intestinal Ecosystem’s Influence on Immune Homeostasis, Health, and Disease. EBioMedicine 2016, 13, 46–54. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  150. Underhill, D.M.; Iliev, I.D. The mycobiota: Interactions between commensal fungi and the host immune system. Nat. Rev. Immunol. 2014, 14, 405–416. [Google Scholar] [CrossRef] [PubMed]
  151. Kernbauer, E.; Ding, Y.; Cadwell, K. An enteric virus can replace the beneficial function of commensal bacteria. Nature 2014, 516, 94–98. [Google Scholar] [CrossRef]
  152. Belkaid, Y.; Hand, T.W. Role of the microbiota in immunity and inflammation. Cell 2014, 157, 121–141. [Google Scholar] [CrossRef] [Green Version]
  153. Arumugam, M.; Raes, J.; Pelletier, E.; Lepaslier, D.; Yamada, T.; Mende, D.R.; Fernandes, G.D.R.; Tap, J.; Bruls, T.; Batto, J.-M.; et al. Enterotypes of the human gut microbiome. Nature 2011, 473, 174–180. [Google Scholar] [CrossRef]
  154. Ouwehand, A.C. A review of dose-responses of probiotics in human studies. Benef. Microbes 2017, 8, 143–151. [Google Scholar] [CrossRef]
  155. Joseph, J.; Law, C. Cross-species examination of single- and multi-strain probiotic treatment effects on neuropsychiatric outcomes. Neurosci. Biobehav. Rev. 2019, 99, 160–197. [Google Scholar] [CrossRef]
  156. Kearney, S.M.; Gibbons, S.M. Designing synbiotics for improved human health. Microb. Biotechnol. 2017, 11, 141–144. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Scientific publications on various microbial communities of the gut microbiome. The number of peer-reviewed scientific publications for (A) microbiome, (B) virome (C) mycobiome and (D) archaeome studies. The list of peer-reviewed literature was collated in a non-systematic manner from the web of science (WOS) all database collection (MEDLINE, Inspec, Biological abstracts, scIELO, KCI, WOS core collection, Russian science index) from 2009 to 2019. The research of literature was performed using keywords like "microbiome”, “gut microbiome”, “gut virome”, “virome”, “gut fungi”, and “gut mycobiome”. * For careful selection of gut archaeome studies, we used PubMed only with keywords like “gut archaea”, “gut archaeon” and “gut archaeome/archaeon” and “archaeome” which includes whole microbiome analysis studies but not limited to only archaeome. Document types excluded were review of the literature (including systematic and meta-analysis), case studies, reports, and abstracts in conferences, workshops, and book chapters.
Figure 1. Scientific publications on various microbial communities of the gut microbiome. The number of peer-reviewed scientific publications for (A) microbiome, (B) virome (C) mycobiome and (D) archaeome studies. The list of peer-reviewed literature was collated in a non-systematic manner from the web of science (WOS) all database collection (MEDLINE, Inspec, Biological abstracts, scIELO, KCI, WOS core collection, Russian science index) from 2009 to 2019. The research of literature was performed using keywords like "microbiome”, “gut microbiome”, “gut virome”, “virome”, “gut fungi”, and “gut mycobiome”. * For careful selection of gut archaeome studies, we used PubMed only with keywords like “gut archaea”, “gut archaeon” and “gut archaeome/archaeon” and “archaeome” which includes whole microbiome analysis studies but not limited to only archaeome. Document types excluded were review of the literature (including systematic and meta-analysis), case studies, reports, and abstracts in conferences, workshops, and book chapters.
Microorganisms 08 00483 g001
Figure 2. The microbial cross-kingdom interactions between members of microbiome. All the microbes in the gut interact with each other; Microbes interact with each other (A), with helminths (B) and their hosts, establishing trophic relationship (either symbiotic or parasitic). These interactions are categorized as competition or cooperation for survival, nutrients (C) and adhesion sites (D) on the mucosa. Most of these microbes produce specific metabolites (Short chain fatty acids) (E) and supply energy to intestinal epithelial cells (IEC), influencing the immune system (F–G), and overall homeostasis. DC = Dendritic cells; Mo = Macrophages.
Figure 2. The microbial cross-kingdom interactions between members of microbiome. All the microbes in the gut interact with each other; Microbes interact with each other (A), with helminths (B) and their hosts, establishing trophic relationship (either symbiotic or parasitic). These interactions are categorized as competition or cooperation for survival, nutrients (C) and adhesion sites (D) on the mucosa. Most of these microbes produce specific metabolites (Short chain fatty acids) (E) and supply energy to intestinal epithelial cells (IEC), influencing the immune system (F–G), and overall homeostasis. DC = Dendritic cells; Mo = Macrophages.
Microorganisms 08 00483 g002
Figure 3. The known microbe–immune interactions in inflammation and homeostasis. A. Certain members of bacteria (intracellular, systemic commensals, Proteobacteria, and opportunist pathogens) and viruses induce inflammatory responses (IR 1) by promoting T cells and their subsets T helper 1 cells (Th 1) releasing pro-inflammatory cytokines such as interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), etc., initiated by microbe-associated molecular patterns (Black arrow). B–C. Segmented filamentous bacteria (extracellular), member of Fungi, and helminths (GATA 3) induce inflammatory responses initiated at the mucosal sites, which promote the expansion of T cells expressing Th 17 and Th 2 cells releasing Interleukins (IL) 17A, IL-22, and IFN-γ, respectively (Brown and green). D. Certain members of Archaea (Methanomassiliicoccus luminyensis, Methanosphaera stadtmanae and M. smithii) promote surface markers CD86, CD197 expressed on T cells releasing Monocyte-derived dendritic cells (MODC), type 1 IFN (Orange). All the factors involving A–D may lead to tissue damage and ultimately inflammation. E–F. Certain members of Clostridia, Bacteroides fragilis, archaea, and helminths induce regulatory responses by promoting Foxp3-expressing T regulatory (Tregs) cells, limiting the activation of Th1, Th2, and Th17 cells (Blue). This regulation and tolerance promote homeostasis.
Figure 3. The known microbe–immune interactions in inflammation and homeostasis. A. Certain members of bacteria (intracellular, systemic commensals, Proteobacteria, and opportunist pathogens) and viruses induce inflammatory responses (IR 1) by promoting T cells and their subsets T helper 1 cells (Th 1) releasing pro-inflammatory cytokines such as interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), etc., initiated by microbe-associated molecular patterns (Black arrow). B–C. Segmented filamentous bacteria (extracellular), member of Fungi, and helminths (GATA 3) induce inflammatory responses initiated at the mucosal sites, which promote the expansion of T cells expressing Th 17 and Th 2 cells releasing Interleukins (IL) 17A, IL-22, and IFN-γ, respectively (Brown and green). D. Certain members of Archaea (Methanomassiliicoccus luminyensis, Methanosphaera stadtmanae and M. smithii) promote surface markers CD86, CD197 expressed on T cells releasing Monocyte-derived dendritic cells (MODC), type 1 IFN (Orange). All the factors involving A–D may lead to tissue damage and ultimately inflammation. E–F. Certain members of Clostridia, Bacteroides fragilis, archaea, and helminths induce regulatory responses by promoting Foxp3-expressing T regulatory (Tregs) cells, limiting the activation of Th1, Th2, and Th17 cells (Blue). This regulation and tolerance promote homeostasis.
Microorganisms 08 00483 g003
Table 1. Summary of a few significant clinical studies on the viral, fungal, and archaeal microbiomes.
Table 1. Summary of a few significant clinical studies on the viral, fungal, and archaeal microbiomes.
Microbial ComponentSamplesSorting/Analysis MethodReads/Contigs */SequencesRef.
Viral21Hidden Markov Models/STARAssembled: 107,307 contigs.
Total taxonomically assigned: 12,751 contigs (29.62% only)
[17]
10Assembled: 294,211 contigs
Alignment of reads to contigs: 57,721
Final catalogue: 39,254 contigs
[18]
32CD-Hit-estTotal reads: 1,386,331 (32 datasets)
Date normalized: 14,000 reads/dataset
Annotated yield: 5004 contigs
[19]
Fungal317 (147 subjects)Internal Transcribed Spacer 2 (ITS)Total reads per 1 sample/subject: 756,316 reads
Total reads/sample: 17,189
[20]
14ITS1 (IonPGM, MiSeq, PacBio Sequence comparisons)IonPGM: 219,756 reads
MiSeq: 181,436 reads
PacBio: 2984/sample
Total: 41,776 reads
[21]
49ITS106,185 reads[22]
Archaeal
(Methanogens)
2116S gene analysis1521 sequences[23]
1010,000 reads/sample[24]
49109,561 reads[22]
* Contigs = either a DNA segment or set of overlapping DNA sequences.
Table 2. Summary of significant study findings on the gut virome.
Table 2. Summary of significant study findings on the gut virome.
Model TypeStudy TypeFindingsRef
Human
Healthy infant1 week old infant N = 1Taxa identified: Siphoviruses and prophages (the majority (72%)[41]
Infants/mothers (healthy)Healthy adult female monozygotic co-twins and their mothers at three time points over a one-year period N = 12Eukaryotic viral genomes: 73.3%, phages and prophages: 25.8%
dsDNA phage (Caudovirales): 76.9%
[19]
N = 8 (4 twin pairs)Taxa identified: Siphoviridae, Inoviridae, Myoviridae and Podoviridae [43]
N = 24 longitudinal fecal samples Taxa identified: Microviridae, Podoviridae, Myoviridae, and Siphoviridae[44]
Healthy vs. malnourished infants/childrenTime-series from fecal samples (Malawian) healthy control (HC)= twins, Mal Nutr = 12 twin pairs↑ Anelloviridae (ssDNA eukaryotic viruses) in healthy infants and children (up to 15–18 mo), With age: ↑ Alpavirinae (ssDNA phages), ↑ Siphoviridae in 0 to 10 mo of age and then slowly decrease.[45]
Obese childrenN = 20 (HC = 10, Obese = 10)Obese to HC: ↑ Human herpesvirus 4[46]
Human (Healthy)Longitudinal metagenomics analysis (Ireland) of fecal viruses N = 6 (3 Males, 3 Females)Taxa identified: ↑ Virulent crAss-like and Microviridae bacteriophages [18]
Uncultured viral community from human feces. N = 1Taxa identified: Bacteriophages A118 of Listeria monocytogenes, E125 of Burkholderia thailandensis, and bIL285 of Lactococcus lactis[47]
Analysis of the RNA viruses (N = 2)Pepper mild mottle virus = 109 virions/gram of dry fecal matter, ↑ RNA viruses[48]
Virome of the ELDERMETFirst-ever in elders (>65 yrs)Taxa identified:Gokushovirinae (Microviridae) [49]
Diet variationssequencing (N = 6) high-fat/low-fiber dietHigh fat to low fiber: Siphoviridae (18%), 686 (10%) to Myoviridae, 344 (4.8%) to Podoviridae, 68 (0.9%) to Microviridae, and 0.4% others[50]
Human Virome (IBD)Virus-like particle preparations on the rectal mucosa (N = 167, (UC = 91; HC = 76)). (Chinese study)UC to HC = ↓ mucosal Caudovirales diversity, richness
and evenness relative to HC
[51]
metagenomics sequencing of stool filtrates using the Roche 454 platform (UK) The viromes of CD and UC patients were disease- and cohort-specific. ↑ Caudovirales bacteriophages compared to HC[52]
T2D vs. HCType II diabetes (T2D) patients (n  =  71) and normal Chinese adults (HC) n  =  74)).T2D to HC: ↑ phages (Siphoviridae (55.3  ±  9.8%) Myoviridae (21.7  ±  9.9%), Podoviridae (10.6  ±  8.4%))[53]
HIV study(N = 122, untreated HIV = 42, HIV ART= 40, HIV uninfected= 40)HIV to uninfected: ↑ Anelloviridae, Adenoviruses[54]
Animal
Gorilla simian immunodeficiency virus infection (SIV).(N = 22, SIV = 11, HC = 11)SIV to HC: ↑ Herpesviridae and Reoviridae
Identified: Siphoviridae, Myoviridae and Podoviridae
[55]
Rodents N = 314 wild rodentTaxa identified: Parvovirus, Dicistrovirus, Iflavirus, and Iridovirus[56]
viral RNA and DNA in the feces of 105 wild rodentsTaxa identified:Circoviridae, Picobirnaviridae, Picornaviridae, Astroviridae, Parvoviridae, Papillomaviridae, Adenoviridae, and Coronaviridae.[57]
viral content in rat fecal matter (N = 29)Picornaviridae[58]
Mouse N = 416 miceTaxa identified: Parvovirinae, Chapparvovirus, Polyomavirus, Astroviruses, Sapovirus, Picornavirus[59]
Mouse model of IBDC57BL6/J mice (HC) and C57BL6/J Rag1-/- mice (IBD induced)IBD to HC= ↑ Spounaviridae, ↓ Clostridiales phages[60]
Gulf War illness (GWI) mouse model (IBD)(N = 22, HC = 11, GWI = 11)GWI mice to HC = ↓ Microviridae bacteriophages, ↑ Siphoviridae and Myoviridae bacteriophages[61]
Gnotobiotic mouse model of phage-bacterial host dynamics(N = 5 per group).T7 phages are undetectable for 1 wk in germ-free animals before they rise in abundance after gavage of a bacterial host.[62]
↑ increase; ↓ decrease; HC = healthy control; IBD = inflammatory bowel disease; ss = single stranded; T2D = type 2 diabetes.
Table 3. Viral communities identified in the mammalian gut.
Table 3. Viral communities identified in the mammalian gut.
Phagesds DNAss DNAds RNAss RNA
MicroviridaePapillomaviridaeCircoviridaeReoviridaeRetroviridae
PodoviridaePolyomaviridaeAnelloviridae Togaviridae
SiphoviridaePoxviridae Astroviridae
Adenoviridae Virgaviridae
Iridoviridae Caliciviridae
Marseilleviridae
ds = double stranded; ss = single stranded.
Table 4. Summary of studies and their findings involving in viromes from fecal microbial transplantations (FMT).
Table 4. Summary of studies and their findings involving in viromes from fecal microbial transplantations (FMT).
ModelStudy DetailsFindingsRef.
Infant IBDN = 4, Infant UC = 3, HC = 1 (22 to 30 FMT treatmentsUC to HC: ↑ Siphoviridae[72]
Adult IBDN = 15, UC= 9, HC = 8UC to HC: ↓ DNA phage,
richness of donor viromes ≠ outcome of therapy
Most abundant: Anelloviridae, Circoviridae, Picobirnaviridae and Virgaviridae
[81]
Clostridium difficile infection (CDI)N = 44, CDI= 24, HC = 20CDI to HC: ↑ Caudovirales (may play a role in FMT efficacy in CDI)[73]
Recurrent CDI (rCDI) 1-year follow-uprCDI = 14; donors (D) = 3rCDI to D: ↑ Caudovirales, Anelloviridae ↓ Microviridae[74]
↑ = increase; ↓ = decrease; N = total; HC = healthy control; IBD = inflammatory bowel disease; UC = ulcerative colitis; CDI = Clostridium difficile infection; rCDI= recurrent CDI.
Table 5. Summary of significant studies and their findings on the gut mycobiome.
Table 5. Summary of significant studies and their findings on the gut mycobiome.
Model typeStudy detailsFindingsRef
Human
Mycobiome of Human microbiome project (HMP)N = 317 Taxa identified: Saccharomyces, Malassezia, and Candida. (↓ Mycobiome diversity)[20,101]
Mother/offspring
(prospective cohort)
N = 298 pairs (mothers and offspring) From Mothers to off springs: ↑ Debaryomyces hansenii (breast-feeding)
S. cerevisiae (after weaning)
[101]
The New Zealand human healthy gut mycobiome N = 21 healthy, non-obese (age: 18–65 yr)Taxa identified: Candida albicans, Candida parapsilosis, and S. cerevisiae.
New species identified: C. bracarensis, Coniochaeta hoffmannii, Hanseniaspora
pseudoguilliermondii, Aspergillus foetidus, A. tubingensis, and Paecilomyces
dactylethromorphus
[102]
Healthy Aging study: Gut mycobiome of elderly Danish people (Age: 65–81 yr)N = 99 (age:65 to 81 yr) Phyla: Ascomycota, Basidiomycota and Zygomycota
Genera: Penicillium, Candida, and Aspergillus
[103]
Mycobiota among Eutrophic, overweight, and obeseN = 72, Eutrophic =  24, Overweight =  24, Obese = 24).Eutrophic: Zygomycota and Basidiomycota,
Overweight: Zygomycota and Basidiomycota,
Obese: Zygomycota, Basidiomycota and Syncephalastrum sp. (Zygomycota)
Taxa identified include:
↑ Ascomycota (species): Paecilomyces sp., Penicillium sp., Candida sp., Aspergillus sp., Fonsecaea sp., and Geotrichum sp.
↑ Basidiomycota (species): Trichosporon sp. and Rhodotorula sp.
↑ Zygomycota (species) Rhizopus sp. and Mucor sp.
[104]
Healthy Japanese gut MycobiotaN = 14Taxa identified: ↑ Candida and Saccharomyces[21]
Intestinal mycobiome of patients with irritable bowel syndrome (IBS).N = 57, HC = 18 healthy IBS = 39S. cerevisiae and C albicans identified in all samples/groups[105]
Animal
Rat model of visceral hypersensitivityN = 6S. cerevisiae and C. albicans in all samples.[105]
BatN = 14↑ Ascomycota and Basidiomycota[106]
Dog N = 19, HC= 12, acute diarrhea (AD)= 7Ascomycota (HC: 97.9% and AD: 98.2%) and Basidiomycota (HC: 1.0%, AD: 0.5%)[107]
Mouse Pancreatic ductal adenocarcinoma (PDA) and C57BL/6 mice (HC). PDA to HC: ↑ Malassezia species promote PDA [108]
Tibetan macaquen.aTaxa identified:Zygomycota, Chytridiomycota, Glomeromycota and Rozellomycota[109]
↑ = increase; ↓ = decrease; N = total; HC = healthy control.
Table 6. Significant studies and their findings on the gut archaeome.
Table 6. Significant studies and their findings on the gut archaeome.
Model typeStudy detailsFindingsRef
Human
Healthy infantsN = 15, Cesarean section-delivered (CSD) = 8, Vaginally-derived(VD) = 7CSD to VD: ↑ Methanosphaera spp.[121]
Infants/mothers (healthy)N = 8 (4 twin pairs)Lipothrixviridae[43]
Obese childrenN = 20 (HC = 10, Obese = 10)Obese to HC: ↑ Methanobrevibacter spp. [46]
N = 476Obese to HC: ↑ M. smithii[122]
Healthy adultsN = 8M. smithii (99–100%)[123]
N = 15 (Finnish)Taxa identified: Methanobrevibacter–specific[124]
Population-basedBelgian Flemish Gut Flora Project (FGFP; discovery cohort; N = 1106) and the Dutch LifeLines-DEEP study (LLDeep; replication; N = 1135)Methanobrevibacter spp. in all samples[125]
Aging studyN = 500Taxa identified: M. smithii
Methanosphaera stadtmanae
Methanomassiliicoccus luminyensis
[126]
Archaea of ELDERMET study N = 371Taxa identified: Methanomassiliicoccales[127]
Type 2 diabetes N = 49 HC= 19, New (type 2) = 14, Known (type 2)= 16 NGTs to Known = ↓ Methanobrevibacter[22]
Human IBDN = 58, HC = 29, IBD = 29IBD to HC: ↑ M. stadtmanae[128]
N = 108, HC= 47, IBD = 61IBD to HC: ↓ M. smithii[129]
Animal
Human/ape studyHumans (N = 10) Apes: Pan troglodytes (chimpanzee = 14), Pan paniscus (bonobo = 18), Gorilla gorilla (gorilla = 20), and Pongo pygmaeus (orangutan = 8)Taxa identified: M. smithii and M. stadtmanae in all samples (more in humans)[24]
Rabbit cecal archaeaN = 40Taxa identified: Methanobrevibacter and Methanosphaera spp. in all samples[130]
↑ = increase; ↓ = decrease; N= total; HC = healthy control; IBD = inflammatory bowel disease; NGT= long-standing diabetic subjects.
Table 7. Summary of significant study findings on the role of helminths in health and disease.
Table 7. Summary of significant study findings on the role of helminths in health and disease.
Model TypeStudy DetailsFindingsRef.
Rat model
(2, 4, 6 Trinitrobenzene sulphonic acid (TNBS) induced colitis model
N = 24: HC = 6, Schistosoma mansoni group = 6, TNBS group = 6 and S. mansoni + TNBS group= 6S. mansoni group: ↑ IL-2, IL-4
TNBS group: ↑ IL-2 ↑ T helper 1 (Th1)
S. mansoni plus TNBS group:
↑ Th2 ↓ Th 1 (↓ Inflammation)
Concurrent infection with S. mansoni significantly attenuates TNBS induced colitis in the rats.
[138]
Rhesus macaques with idiopathic chronic diarrhea (ICD) w/o T suis infectionN = 7, ICD = 5
ICD with T suis = 5, HC = 2
ICD group = ↓ Mucosal bacterial diversity, ↓ Th2
ICD with T suis = ↑ Mucosal bacterial diversity (Cyanobacteria), ↑ Th2
[139]
Human (Tetanus toxoid (TT) and S mansoni infection)TT + S. mansoni = 11
HC= 5
TT + S. mansoni group: ↓ Interferon gamma (IFN-ɤ), ↑ Th 2
HC: ↑ IFN-ɤ ↓ Th1
[140]
Human
(helminthic ova in the treatment of active IBD)
N = 4 (IBD), 2500 live Trichuris suis eggs/12 weeks/subjectIBD: ↑ Inflammation: ↑ Th1
T. suis treated: ↓ Inflammation: ↑ Th2 and ↓ Th1
[141]
Human (RCT T suis therapy for ulcerative colitis (UC))N = 54, Therapy group= 30, HC = 24Therapy group =↓ UC disease activity index (DAI)[137]
Human (RCT T suis therapy for Crohn’s disease (CD))N = 36, Treated group = 27, HC = 9 T. suis therapy was well tolerated[142]
Human (Necator americanus therapy for CD)N = 18, (inoculation)CD: ↑ DAI
N. americanus treated: ↓ CD (DAI)
[143]
Human (T suis therapy multiple sclerosis)N = 5Multiple sclerosis: ↑ Inflammation
T. suis treated: ↑ IL-4, ↑ IL-10
(↓ Inflammation = ↑ Th 2?)
[144]
↑ = increase; ↓ = decrease; HC = healthy control; N = total, RCT = randomized control trial, TT = Tetanus toxoid, UC = ulcerative colitis, CD = Crohn’s disease, DAI = disease activity index, IL = interleukins; Th = T helper cells; IFN = interferon.
Table 8. The immune responses associated with different members of the microbiome ([1,149,150]).
Table 8. The immune responses associated with different members of the microbiome ([1,149,150]).
Microbial ConstituentResponse TypeImmune Cells/ExpressionsCytokinesInitiation
Bacteria (intracellular): Systemic commensals, Proteobacteria, pathogensInflammatory response (IR) 1T helper 1 (Th 1) cellsInterferon gamma (IFN-ɤ), Tumor necrosis factor (TNF-α)Microbe-associated molecular patterns (Pro-inflammatory)
Virus IR 1CD4, CD8 T cellsIFN-α/β, IFN-λ
Segmented filamentous bacteria (extracellular), FungiIR 2Th 17 cellsInterleukins (IL) 17A, IL-22Mucosal epithelial cells
HelminthsIR 2Th 2 cellsIFN-ɤGATA 3
Archaea ((Methanomassiliicoccus luminyensis, Methanosphaera stadtmanae and M. smithii))Inflammatory/regulatory responseT cells- CD86, CD197Monocyte-derived dendritic cells (MODC), type 1 IFNMucosal epithelial cells
Clostridia, Bacteroides fragilis, archaea and helminthsRegulatory responseT regulatory cells (Foxp3 + Tregs)IL-10, Transforming growth factor beta (TGF-β)Resolution of IR 1, 2
IR = Inflammatory response; Th = T helper cells; IFN = Interferon gamma; TNF = Tumor necrosis factor; IL = Interleukins; MODC = Monocyte-derived dendritic cells; TGF = Transforming growth factor.

Share and Cite

MDPI and ACS Style

Vemuri, R.; Shankar, E.M.; Chieppa, M.; Eri, R.; Kavanagh, K. Beyond Just Bacteria: Functional Biomes in the Gut Ecosystem Including Virome, Mycobiome, Archaeome and Helminths. Microorganisms 2020, 8, 483. https://doi.org/10.3390/microorganisms8040483

AMA Style

Vemuri R, Shankar EM, Chieppa M, Eri R, Kavanagh K. Beyond Just Bacteria: Functional Biomes in the Gut Ecosystem Including Virome, Mycobiome, Archaeome and Helminths. Microorganisms. 2020; 8(4):483. https://doi.org/10.3390/microorganisms8040483

Chicago/Turabian Style

Vemuri, Ravichandra, Esaki M. Shankar, Marcello Chieppa, Rajaraman Eri, and Kylie Kavanagh. 2020. "Beyond Just Bacteria: Functional Biomes in the Gut Ecosystem Including Virome, Mycobiome, Archaeome and Helminths" Microorganisms 8, no. 4: 483. https://doi.org/10.3390/microorganisms8040483

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop