Cross-Scale Analyses of Animal and Human Gut Microbiome Assemblies from Metacommunity to Global Landscape

Critical complex network structures in animal gastrointestinal tract microbiomes

BACKGROUND

Living things from microbes to their hosts (plants, animals and humans) interact with each other, and their relationships may be described with complex network models. The present study focuses on the critical network structures, specifically the core/periphery nodes and backbones (paths of high-salience skeletons) in animal gastrointestinal microbiomes (AGMs) networks. The core/periphery network (CPN) mirrors nearly ubiquitous nestedness in ecological communities, particularly dividing the network as densely interconnected core-species and periphery-species that only sparsely linked to the core. Complementarily, the high-salience skeleton network (HSN) mirrors the pervasive asymmetrical species interactions (strictly microbial species correlations), particularly forming heterogenous pathways in AGM networks with both "backbones" and "rural roads" (regular or weak links). While the cores and backbones can act as critical functional structures, the periphery nodes and weak links may stabilize network functionalities through redundancy.

RESULTS

Here, we build and analyze 36 pairs of CPN/HSN for the AGMs based on 4903 gastrointestinal-microbiome samples containing 473,359 microbial species collected from 318 animal species covering all vertebrate and four major invertebrate classes. The network analyses were performed at host species, order, class, phylum, kingdom scales and diet types with selected and comparative taxon pairs. Besides diet types, the influence of host phylogeny, measured with phylogenetic (evolutionary) timeline or "age", were integrated into the analyses. For example, it was found that the evolutionary trends of three primary microbial phyla (Bacteroidetes/Firmicutes/Proteobacteria) and their pairwise abundance-ratios in animals do not mirror the patterns in modern humans phylogenetically, although they are consistent in terms of diet types.

CONCLUSIONS

Overall, the critical network structures of AGMs are qualitatively and structurally similar to those of the human gut microbiomes. Nevertheless, it appears that the critical composition (the three phyla of Bacteroidetes, Firmicutes, and Proteobacteria) in human gut microbiomes has broken the evolutionary trend from animals to humans, possibly attributable to the Anthropocene epoch and reflecting the far-reaching influences of agriculture and industrial revolution on the human gut microbiomes. The influences may have led to the deviations between modern humans and our hunter-gather ancestors and animals.

Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes

BACKGROUND

Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists' (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies-amplicon sequencing and whole-genome (shotgun sequencing)-respectively generate two contrastingly different categories of metagenomic reads (data)-OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes.

RESULTS

The ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan's near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project.

CONCLUSIONS

All of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.

Sex, health status and habitat alter the community composition and assembly processes of symbiotic bacteria in captive frogs

BACKGROUND

Frogs are critical economic animals essential to agricultural ecosystem equilibrium. However, Meningitis-like Infectious Disease (MID) often affects them in agricultural settings. While frog-associated microbiota contribute to elemental cycling and immunity, the effects of frog sex and health on gut bacteria remain understudied, and the relationship between frog habitat and soil microbes is unclear. We aimed to determine how frog sex, health status and habitat influence symbiotic bacteria and community assembly mechanism to provide guidance for sustainable frog farming and conservation.

RESULTS

We employed 16S rRNA sequencing to investigate gut microbiota differences in relation to frog sex and health status. We also compared symbiotic communities in frog-aggregation, native and soybean soil on the farm. Results showed that gut bacterial β-diversity and taxonomy were markedly influenced by frog sex and health. Healthy frogs had more robust gut bacterial metabolism than frogs infected with MID. Cooccurrence network analysis revealed that healthy female frogs had more complex microbial network structure than males; however, diseased males showed the greatest network complexity. The assembly mechanism of gut bacteria in male frogs was dominated by deterministic processes, whereas in female frogs it was dominated by stochastic processes. Among symbiotic bacteria in frog habitat soils, deterministic processes predominantly shaped the community assembly of soybean soil. In particular, soybean soil was enriched in pathogens and nitrogen functions, whereas frog-aggregation soil was markedly increased in sulphur respiration and hydrocarbon degradation.

CONCLUSION

Our study reveals that sex mainly alters the interaction network and assembly mechanism of frog intestinal bacteria; MID infection significantly inhibits the metabolic functions of intestinal bacteria. Furthermore, diverse frog habitat soils could shape more symbiotic bacteria to benefit frog farming. Our findings provide new horizons for symbiotic bacteria among frogs, which could contribute to sustainable agriculture and ecological balance.

Three species of axenic mosquito larvae recruit a shared core of bacteria in a common garden experiment

In this study, we describe the generation of two new species of axenic mosquito, Aedes albopictus and Aedes triseriatus. Along with Aedes aegypti, axenic larvae of these three species were exposed to an environmental water source to document the assembly of the microbiome in a common garden experiment. Additionally, the larvae were reared either individually or combinatorially with the other species to characterize the effects of co-rearing on the composition of the microbiome. We found that the microbiome of the larvae was composed of a relatively low-diversity collection of bacteria from the colonizing water. The abundance of bacteria in the water was a poor predictor of their abundance in the larvae, suggesting the larval microbiome is made up of a subset of relatively rare aquatic bacteria. We found 11 bacterial 16S rRNA gene amplicon sequence variants (ASVs) that were conserved among ≥90% of the mosquitoes sampled, including 2 found in 100% of the larvae, pointing to a conserved core of bacteria capable of colonizing all three species of mosquito. Yet, the abundance of these ASVs varied widely between larvae, suggesting individuals harbored largely unique microbiome structures, even if they overlapped in membership. Finally, larvae reared in a tripartite mix of the host-species consistently showed a convergence in the structure of their microbiome, indicating that multi-species interactions between hosts potentially lead to shifts in the composition of their respective microbiomes. IMPORTANCE This study is the first report of the axenic (free of external microbes) rearing of two species of mosquito, Aedes albopictus and Aedes triseriatus. Our previous report of axenic Aedes aegypti brings the number of axenic species to three. We designed a method to perform a common garden experiment to characterize the bacteria the three species of axenic larvae assemble from their surroundings. Furthermore, species could be reared in isolation or in multi-species combinations to assess how host-species interactions influence the composition of the microbiome. We found all three species recruited a common core of bacteria from their rearing water, with a large contingent of rare and sporadically detected bacteria. Finally, we also show that co-rearing of mosquito larvae leads to a coalescence in the composition of their microbiome, indicating that host-species interactions potentially influence the composition of the microbiome.

Seasonal variation significantly influenced the stochasticity of community assembly of amphibian symbiotic bacteria

Seasonal variation has been shown to influence symbiotic bacterial community composition and structure in amphibians. It is still unknown how the symbiotic bacterial community assembly changes during different seasons, especially for amphibians who are particularly sensitive to environmental change. We found significant differences in the composition and diversity (alpha and beta diversity) of amphibian skin and gut bacteria. Co-occurrences network analysis showed that seasonal variation reduced the microbial network complexity of amphibians from summer to autumn. The normalized stochastic ratio (NST) and phylogenetic bin-based null model analysis (iCAMP) models showed that the same result that stochastic processes was the major factor regulating the symbiotic bacterial community assembly mechanisms of amphibians. From summer to autumn, the symbiotic bacterial community assembly mechanisms declined in the contribution of stochastic processes, while increasing in the contribution of deterministic processes. Dispersal limitation was the dominant microbial assembly mechanism, followed by homogeneous selection, and then heterogeneous selection in the symbiotic bacterial community communities of amphibians between summer and autumn. Furthermore, higher niche width of the symbiotic bacterial community of amphibians was found in summer than autumn. Overall, these results demonstrated that seasonal variation influenced amphibian symbiotic bacterial community between summer and autumn.

Diet, Microbes, and Cancer Across the Tree of Life: a Systematic Review

PURPOSE OF REVIEW

Cancers are a leading cause of death in humans and for many other species. Diet has often been associated with cancers, and the microbiome is an essential mediator between diet and cancers. Here, we review the work on cancer and the microbiome across species to search for broad patterns of susceptibility associated with different microbial species.

RECENT FINDINGS

Some microbes, such as Helicobacter bacteria, papillomaviruses, and the carnivore-associated Fusobacteria, consistently induce tumorigenesis in humans and other species. Other microbes, such as the milk-associated Lactobacillus, consistently inhibit tumorigenesis in humans and other species. We systematically reviewed over a thousand published articles and identified links between diet, microbes, and cancers in several species of mammals, birds, and flies. Future work should examine a larger variety of host species to discover new model organisms for human preclinical trials, to better understand the observed variance in cancer prevalence across species, and to discover which microbes and diets are associated with cancers across species. Ultimately, this could help identify microbial and dietary interventions to diagnose, prevent, and treat cancers in humans as well as other animals.

Niche-Neutral Continuum Seems to Explain the Global Niche Differentiation and Local Drift of the Human Digestive Tract Microbiome

The human digestive tract (DT) is differentiated into diverse niches and harbors the greatest microbiome diversity of our bodies. Segata et al. (2012) found that the microbiome of diverse habitats along the DT may be classified as four categories or niches with different microbial compositions and metabolic potentials. Nonetheless, few studies have offered theoretical interpretations of the observed patterns, not to mention quantitative mechanistic parameters. Such parameters should capture the essence of the fundamental processes that shape the microbiome distribution, beyond simple ecological metrics such as diversity or composition descriptors, which only capture the manifestations of the mechanisms. Here, we aim to get educated guesses for such parameters by adopting an integrated approach with multisite neutral (MSN) and niche-neutral hybrid (NNH) modeling, via reanalyzing Segata’s 16s-rRNA samples covering 10 DT-sites from over 200 healthy individuals. We evaluate the relative importance of the four essential processes (drift, dispersal, speciation, and selection) in shaping the microbiome distribution and dynamics along DT, which are assumed to form a niche-neutral continuum. Furthermore, the continuum seems to be hierarchical: the selection or niche differentiations seem to play a predominant role (> 90% based on NNH) at the global (the DT metacommunity) level, but the neutral drifts seem to be prevalent (> 90% based on MSN/NNH) at the local sites except for the gut site. An additional finding is that the DT appears to have a fifth niche for the DT microbiome, namely, Keratinized gingival (KG), while in Segata’s original study, only four niches were identified. Specifically, in Segata’s study, KG was classified into the same niche type including buccal mucosa (BM), hard palate (HP), and KG. However, it should be emphasized that the proposal of the fifth niche of KG requires additional verification in the future studies.

Material Engineering in Gut Microbiome and Human Health

Tremendous progress has been made in the past decade regarding our understanding of the gut microbiome's role in human health. Currently, however, a comprehensive and focused review marrying the two distinct fields of gut microbiome and material research is lacking. To bridge the gap, the current paper discusses critical aspects of the rapidly emerging research topic of "material engineering in the gut microbiome and human health." By engaging scientists with diverse backgrounds in biomaterials, gut-microbiome axis, neuroscience, synthetic biology, tissue engineering, and biosensing in a dialogue, our goal is to accelerate the development of research tools for gut microbiome research and the development of therapeutics that target the gut microbiome. For this purpose, state-of-the-art knowledge is presented here on biomaterial technologies that facilitate the study, analysis, and manipulation of the gut microbiome, including intestinal organoids, gut-on-chip models, hydrogels for spatial mapping of gut microbiome compositions, microbiome biosensors, and oral bacteria delivery systems. In addition, a discussion is provided regarding the microbiome-gut-brain axis and the critical roles that biomaterials can play to investigate and regulate the axis. Lastly, perspectives are provided regarding future directions on how to develop and use novel biomaterials in gut microbiome research, as well as essential regulatory rules in clinical translation. In this way, we hope to inspire research into future biomaterial technologies to advance gut microbiome research and gut microbiome-based theragnostics.

Shared Species Analysis, Augmented by Stochasticity Analysis, Is More Effective Than Diversity Analysis in Detecting Variations in the Gut Microbiomes

Diversity analysis is a de facto standard procedure for most existing microbiome studies. Nevertheless, diversity metrics can be insensitive to changes in community composition (identities). For example, if species A (e.g., a beneficial microbe) is replaced by equal number of species B (e.g., an opportunistic pathogen), the diversity metric may not change, but the community composition has changed. The shared species analysis (SSA) is a computational technique that can discern changes of community composition by detecting the increase/decrease of shared species between two sets of microbiome samples, and it should be more sensitive than standard diversity analysis in discerning changes in microbiome structures. Here, we investigated the effects of ethnicity and lifestyles in China on the structure of Chinese gut microbiomes by reanalyzing the datasets of a large Chinese cohort with 300+ individuals covering 7 biggest Chinese ethnic groups (>95% Chinese population). We found: (i) Regarding lifestyles, SSA revealed significant differences between 100% of pair-wise comparisons in community compositions across all but phylum taxon levels (phylum level = 29%), but diversity analysis only revealed 14–29% pair-wise differences in community diversity across all four taxon levels. (ii) Regarding ethnicities, SSA revealed 100% pair-wise differences in community compositions across all but phylum (phylum level = 48–62%) levels, but diversity analysis only revealed 5–57% differences in community diversity across all four taxon levels. (iii) Ethnicity seems to have more prevalent effects on community structures than lifestyle does (iv) Community structures of the gut microbiomes are more stable at the phylum level than at the other three levels. (v) SSA is more powerful than diversity analysis in detecting the changes of community structures; furthermore, SSA can produce lists of unique and shared OTUs. (vi) Finally, we performed stochasticity analysis to mechanistically interpret the observed differences revealed by the SSA and diversity analyses.

Ecology of Human Medical Enterprises: From Disease Ecology of Zoonoses, Cancer Ecology Through to Medical Ecology of Human Microbiomes

In nature, the interaction between pathogens and their hosts is only one of a handful of interaction relationships between species, including parasitism, predation, competition, symbiosis, commensalism, and among others. From a non-anthropocentric view, parasitism has relatively fewer essential differences from the other relationships; but from an anthropocentric view, parasitism and predation against humans and their well-beings and belongings are frequently related to heinous diseases. Specifically, treating (managing) diseases of humans, crops and forests, pets, livestock, and wildlife constitute the so-termed medical enterprises (sciences and technologies) humans endeavor in biomedicine and clinical medicine, veterinary, plant protection, and wildlife conservation. In recent years, the significance of ecological science to medicines has received rising attentions, and the emergence and pandemic of COVID-19 appear accelerating the trend. The facts that diseases are simply one of the fundamental ecological relationships in nature, and the study of the relationships between species and their environment is a core mission of ecology highlight the critical importance of ecological science. Nevertheless, current studies on the ecology of medical enterprises are highly fragmented. Here, we (i) conceptually overview the fields of disease ecology of wildlife, cancer ecology and evolution, medical ecology of human microbiome-associated diseases and infectious diseases, and integrated pest management of crops and forests, across major medical enterprises. (ii) Explore the necessity and feasibility for a unified medical ecology that spans biomedicine, clinical medicine, veterinary, crop (forest and wildlife) protection, and biodiversity conservation. (iii) Suggest that a unified medical ecology of human diseases is both necessary and feasible, but laissez-faire terminologies in other human medical enterprises may be preferred. (iv) Suggest that the evo-eco paradigm for cancer research can play a similar role of evo-devo in evolutionary developmental biology. (v) Summarized 40 key ecological principles/theories in current disease-, cancer-, and medical-ecology literatures. (vi) Identified key cross-disciplinary discovery fields for medical/disease ecology in coming decade including bioinformatics and computational ecology, single cell ecology, theoretical ecology, complexity science, and the integrated studies of ecology and evolution. Finally, deep understanding of medical ecology is of obvious importance for the safety of human beings and perhaps for all living things on the planet.

EasyMap - An Interactive Web Tool for Evaluating and Comparing Associations of Clinical Variables and Microbiome Composition

One of the most common tasks in microbiome studies is comparing microbial profiles across various groups of people (e.g., sick vs. healthy). Routinely, researchers use multivariate linear regression models to address these challenges, such as linear regression packages, MaAsLin2, LEfSe, etc. In many cases, it is unclear which metadata variables should be included in the linear model, as many human-associated variables are correlated with one another. Thus, multiple models are often tested, each including a different set of variables, however the challenge of selecting the metadata variables in the final model remains. Here, we present EasyMap, an interactive online tool allowing for (1) running multiple multivariate linear regression models, on the same features and metadata; (2) visualizing the associations between microbial features and clinical metadata found in each model; and (3) comparing across the various models to identify the critical metadata variables and select the optimal model. EasyMap provides a side-by-side visualization of association results across the various models, each with additional metadata variables, enabling us to evaluate the impact of each metadata variable on the associated feature. EasyMap’s interface enables filtering associations by significance, focusing on specific microbes and finding the robust associations that are found across multiple models. While EasyMap was designed to analyze microbiome data, it can handle any other tabular data with numeric features and metadata variables. EasyMap takes the common task of multivariate linear regression to the next level, with an intuitive and simple user interface, allowing for wide comparisons of multiple models to identify the robust microbial feature associations. EasyMap is available at http://yassour.rcs.huji.ac.il/easymap.

Microbiome Transmission During Sexual Intercourse Appears Stochastic and Supports the Red Queen Hypothesis

Microbes inhabit virtually everywhere on and/or in our bodies, including the seminal and vaginal fluids. They have significant importance in maintaining reproductive health and protecting hosts from diseases. The exchange of microbes during sexual intercourse is one of the most direct and significant microbial transmissions between men and women. Nevertheless, the mechanism of this microbial transmission was little known. Is the transmission mode stochastic, passive diffusion similar to the random walk of particles, or driven by some deterministic forces? What is the microbial transmission probability? What are the possible evolutionary implications, particularly from the perspective of sexual reproduction (selection)? We tackle these intriguing questions by leveraging the power of Hubbell's unified neutral theory of biodiversity, specifically implemented as the HDP-MSN (hierarchical Dirichlet process approximated multi-site neutral model), which allows for constructing truly multi-site metacommunity models, simultaneously including vaginal and semen microbiomes. By reanalyzing the microbiome datasets of seminal and vaginal fluids from 23 couples both before and after sexual intercourses originally reported by Mändar and colleagues, we found that the microbial transmission between seminal and vaginal fluids is a stochastic, passive diffusion similar to the random walk of particles in physics, rather than driven by deterministic forces. The transmission probability through sexual intercourse seems to be approximately 0.05. Inspired by the results from the HDP-MSN model, we further conjecture that the stochastic drifts of microbiome transmissions during sexual intercourses can be responsible for the homogeneity between semen and vaginal microbiomes first identified in a previous study, which should be helpful for sexual reproduction by facilitating the sperm movement/survival and/or egg fertilization. This inference seems to be consistent with the classic Red Queen hypothesis, which, when extended to the co-evolutionary interactions between humans and their symbiotic microbiomes, would predict that the reproductive system microbiomes should support sexual reproduction.

Stochastic neutral drifts seem prevalent in driving human virome assembly: neutral, near-neutral and non-neutral theoretic analyses

It is estimated that human body is inhabited by approximately 380 trillions of viruses, which exist in the form of viral communities and are collectively termed as human virome. How virome is assembled and what kind of forces maintain the composition and diversity of viral communities is still an open question. The question is of obvious importance because of its implications to human health and diseases. Here we address the question by harnessing the power of Hubbell’s unified neutral theory of biodiversity (UNTB) in terms of three neutral models including standard Hubbell’s neutral model (HNM), Sloan’s near-neutral model (SNM) and Harris et al. (2017) multi-site neutral model (MSN), further augmented by Ning et al. (2019) normalized stochasticity ratio (NSR) and Hammal et al. (2015) power analysis for the neutral test (PNT). With the five models applied to 179 virome samples, we aim to obtain robust findings given both Type-I and Type-II errors are addressed and possible alternative, non-neutral processes are detected. It was found that stochastic neutral drifts seem prevalent: approximately 65–92% at metacommunity/landscape scales and 67–80% at virus species scale. The non-neutral selection is approximately 26–28% at community scale and 23% at species scale. The false negative rate is about 2–3%, which suggested rather limited confounding effects of non-neutral process on neutrality tests. We postulate that prevalence of neutrality in human virome is likely due to extremely simple structure of viruses (stands of DNA/RNA) and their inter-species homogeneities, forming the foundation of species equivalence—the hallmark of neutral theory.