Stochastic neutral modelling of the Gut Microbiota's relative species abundance from next generation sequencing data

Island biogeography theory provides a plausible explanation for why larger vertebrates and taller humans have more diverse gut microbiomes

Prior work has shown a positive scaling relationship between vertebrate body size, human height, and gut microbiome alpha diversity. This observation mirrors commonly observed species area relationships (SARs) in many other ecosystems. Here, we expand these observations to several large datasets, showing that this size-diversity scaling relationship is independent of relevant covariates, like diet, body mass index, age, sex, bowel movement frequency, antibiotic usage, and cardiometabolic health markers. Island biogeography theory (IBT), which predicts that larger islands tend to harbor greater species diversity through neutral demographic processes, provides a simple mechanism for positive SARs. Using a gut-adapted IBT model, we demonstrated that increasing the length of a flow-through ecosystem led to increased species diversity, closely matching our empirical observations. We delve into the possible clinical implications of these SARs in the American Gut cohort. Consistent with prior observations that lower alpha diversity is a risk factor for Clostridioides difficile infection (CDI), we found that individuals who reported a history of CDI were shorter than those who did not and that this relationship was mediated by alpha diversity. We observed that vegetable consumption had a much stronger association with CDI history, which was also partially mediated by alpha diversity. In summary, we find that the positive scaling observed between body size and gut alpha diversity can be plausibly explained by a gut-adapted IBT model, may be related to CDI risk, and vegetable intake appears to independently mitigate this risk, although additional work is needed to validate the potential disease risk implications.

Evidence for saponin diversity-mycobiome links and conservatism of plant-fungi interaction patterns across Holarctic disjunct Panax species

Although interplays between plant and coevolved microorganisms are believed to drive landscape formation and ecosystem services, the relationships between the mycobiome and phytochemical evolution and the evolutionary characteristics of plant-mycobiome interaction patterns are still unclear. The present study explored fungal communities from 405 multiniche samples of three Holarctic disjunct Panax species. The overall mycobiomes showed compartment-dominated variations and dynamic universality. Neutral models were fitted for each compartment at the Panax genus (I) and species (II) levels to infer the community assembly mechanism and identify fungal subgroups potentially representing different plant-fungi interaction results, i.e., the potentially selected, opposed, and neutral taxa. Selection contributed more to the endosphere than to external compartments. The nonneutral taxa showed significant phylogenetic clustering. In Model I, the opposed subgroups could best reflect Panax saponin diversities (r = 0.69), and genera with highly positive correlations to specific saponins were identified using machine learning. Although mycobiomes in the three species differed significantly, subgroups in Model II were phylogenetically clustered based on potential interaction type rather than plant species, indicating potentially conservative plant-fungi interactions. In summary, the finding of strong links between invaders and saponin diversity can help explore the underlying mechanisms of saponin biosynthesis evolution from microbial insights, which is important to understanding the formation of the current landscape. The potential conservatism of plant-fungi interaction patterns suggests that the related genetic modules and selection pressures were convergent across Panax species, advancing our understanding of plant interplay with biotic environments.

Clinical Parasitology and Parasitome Maps as Old and New Tools to Improve Clinical Microbiomics

A growing body of evidence shows that dysbiotic gut microbiota may correlate with a wide range of disorders; hence, the clinical use of microbiota maps and fecal microbiota transplantation (FMT) can be exploited in the clinic of some infectious diseases. Through direct or indirect ecological and functional competition, FMT may stimulate decolonization of pathogens or opportunistic pathogens, modulating immune response and colonic inflammation, and restoring intestinal homeostasis, which reduces host damage. Herein, we discuss how diagnostic parasitology may contribute to designing clinical metagenomic pipelines and FMT programs, especially in pediatric subjects. The consequences of more specialized diagnostics in the context of gut microbiota communities may improve the clinical parasitology and extend its applications to the prevention and treatment of several communicable and even noncommunicable disorders.

Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota

In this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.

Stochastic colonization of hosts with a finite lifespan can drive individual host microbes out of equilibrium

Macroorganisms are inhabited by microbial communities that often change through the lifespan of an individual. One of the factors contributing to this change is colonization from the environment. The colonization of initially microbe-free hosts is particularly interesting, as their microbiome depends entirely on microbes of external origin. We present a mathematical model of this process with a particular emphasis on the effect of ecological drift and a finite host lifespan. Our results indicate the host lifespan becomes especially relevant for short-living organisms (e.g. Caenorhabditis elegans, Drosophila melanogaster, and Danio rerio). In this case, alternative microbiome states (often called enterotypes), the coexistence of microbe-free and colonized hosts, and a reduced probability of colonization can be observed in our model. These results unify multiple reported observations around colonization and suggest that no selective or deterministic drivers are necessary to explain them.

Microbial communities are prevalent not only in the environment but also in hosts. Although the drivers of environmental microbiomes have been studied extensively, less is known about the drivers distinguishing a host environment. Recent experimental observations have highlighted the influence of ecological drift in hosts with short lifespan, including model organisms like C. elegans, D. melanogaster and D. rerio. We have developed a theoretical model to study the effect of a finite host lifespan on relevant observables of the microbiome, including the microbial load, probability of colonization of a microbial taxon, and distribution of microbiome composition in a host population. Although we focus on a case free of any selection, our results indicate the possible coexistence of hosts with alternative microbiome composition, and to a larger extent the coexistence of colonized and microbe-free hosts. A quantitative description is provided.

Gut microbiota ecology: Biodiversity estimated from hybrid neutral-niche model increases with health status and aging

In this work we propose an index to estimate the gut microbiota biodiversity using a modeling approach with the aim of describing its relationship with health and aging. The gut microbiota, a complex ecosystem that links nutrition and metabolism, has a pervasive effect on all body organs and systems, undergoes profound changes with age and life-style, and substantially contributes to the pathogenesis of age-related diseases. For these reasons, the gut microbiota is a suitable candidate for assessing and quantifying healthy aging, i.e. the capability of individuals to reach an advanced age, avoiding or postponing major age-related diseases. The importance of the gut microbiota in health and aging has been proven to be related not only to its taxonomic composition, but also to its ecological properties, namely its biodiversity. Following an ecological approach, here we intended to characterize the relationship between the gut microbiota biodiversity and healthy aging through the development a parsimonious model of gut microbiota from which biodiversity can be estimated. We analysed publicly available metagenomic data relative to subjects of different ages, countries, nutritional habits and health status and we showed that a hybrid niche-neutral model well describes the observed patterns of bacterial relative abundance. Moreover, starting from such ecological modeling, we derived an estimate of the gut microbiota biodiversity that is consistent with classical indices, while having a higher statistical power. This allowed us to unveil an increase of the gut microbiota biodiversity during aging and to provide a good predictor of health status in old age, dependent on life-style and aging disorders.

Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling

Metagenomic sequencing has enabled detailed investigation of diverse microbial communities, but understanding their spatiotemporal variability remains an important challenge. Here, we present decomposition of variance using replicate sampling (DIVERS), a method based on replicate sampling and spike-in sequencing. The method quantifies the contributions of temporal dynamics, spatial sampling variability, and technical noise to the variances and covariances of absolute bacterial abundances. We applied DIVERS to investigate a high-resolution time series of the human gut microbiome and a spatial survey of a soil bacterial community in Manhattan's Central Park. Our analysis showed that in the gut, technical noise dominated the abundance variability for nearly half of the detected taxa. DIVERS also revealed substantial spatial heterogeneity of gut microbiota, and high temporal covariances of taxa within the Bacteroidetes phylum. In the soil community, spatial variability primarily contributed to abundance fluctuations at short time scales (weeks), while temporal variability dominated at longer time scales (several months).

Neutrality in the Metaorganism

Almost all animals and plants are inhabited by diverse communities of microorganisms, the microbiota, thereby forming an integrated entity, the metaorganism. Natural selection should favor hosts that shape the community composition of these microbes to promote a beneficial host-microbe symbiosis. Indeed, animal hosts often pose selective environments, which only a subset of the environmentally available microbes are able to colonize. How these microbes assemble after colonization to form the complex microbiota is less clear. Neutral models are based on the assumption that the alternatives in microbiota community composition are selectively equivalent and thus entirely shaped by random population dynamics and dispersal. Here, we use the neutral model as a null hypothesis to assess microbiata composition in host organisms, which does not rely on invoking any adaptive processes underlying microbial community assembly. We show that the overall microbiota community structure from a wide range of host organisms, in particular including previously understudied invertebrates, is in many cases consistent with neutral expectations. Our approach allows to identify individual microbes that are deviating from the neutral expectation and are therefore interesting candidates for further study. Moreover, using simulated communities, we demonstrate that transient community states may play a role in the deviations from the neutral expectation. Our findings highlight that the consideration of neutral processes and temporal changes in community composition are critical for an in-depth understanding of microbiota-host interactions.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

Detecting rare asymmetrically methylated cytosines and decoding methylation patterns in the honeybee genome

Context-dependent gene expression in eukaryotes is controlled by several mechanisms including cytosine methylation that primarily occurs in the CG dinucleotides (CpGs). However, less frequent non-CpG asymmetric methylation has been found in various cell types, such as mammalian neurons, and recent results suggest that these sites can repress transcription independently of CpG contexts. In addition, an emerging view is that CpG hemimethylation may arise not only from deregulation of cellular processes but also be a standard feature of the methylome. Here, we have applied a novel approach to examine whether asymmetric CpG methylation is present in a sparsely methylated genome of the honeybee, a social insect with a high level of epigenetically driven phenotypic plasticity. By combining strand-specific ultra-deep amplicon sequencing of illustrator genes with whole-genome methylomics and bioinformatics, we show that rare asymmetrically methylated CpGs can be unambiguously detected in the honeybee genome. Additionally, we confirm differential methylation between two phenotypically and reproductively distinct castes, queens and workers, and offer new insight into the heterogeneity of brain methylation patterns. In particular, we challenge the assumption that symmetrical methylation levels reflect symmetry in the underlying methylation patterns and conclude that hemimethylation may occur more frequently than indicated by methylation levels. Finally, we question the validity of a prior study in which most of cytosine methylation in this species was reported to be asymmetric.

Detecting rare asymmetrically methylated cytosines and decoding methylation patterns in the honeybee genome

Context-dependent gene expression in eukaryotes is controlled by several mechanisms including cytosine methylation that primarily occurs in the CG dinucleotides (CpGs). However, less frequent non-CpG asymmetric methylation has been found in various cell types, such as mammalian neurons, and recent results suggest that these sites can repress transcription independently of CpG contexts. In addition, an emerging view is that CpG hemimethylation may arise not only from deregulation of cellular processes but also be a standard feature of the methylome. Here, we have applied a novel approach to examine whether asymmetric CpG methylation is present in a sparsely methylated genome of the honeybee, a social insect with a high level of epigenetically driven phenotypic plasticity. By combining strand-specific ultra-deep amplicon sequencing of illustrator genes with whole-genome methylomics and bioinformatics, we show that rare asymmetrically methylated CpGs can be unambiguously detected in the honeybee genome. Additionally, we confirm differential methylation between two phenotypically and reproductively distinct castes, queens and workers, and offer new insight into the heterogeneity of brain methylation patterns. In particular, we challenge the assumption that symmetrical methylation levels reflect symmetry in the underlying methylation patterns and conclude that hemimethylation may occur more frequently than indicated by methylation levels. Finally, we question the validity of a prior study in which most of cytosine methylation in this species was reported to be asymmetric.

A 3-dimensional mathematical model of microbial proliferation that generates the characteristic cumulative relative abundance distributions in gut microbiomes

The gut microbiome is highly variable among individuals, largely due to differences in host lifestyle and physiology. However, little is known about the underlying processes or rules that shape the complex microbial community. In this paper, we show that the cumulative relative abundance distribution (CRAD) of microbial species can be approximated by a power law function, and found that the power exponent of CRADs generated from 16S rRNA gene and metagenomic data for normal gut microbiomes of humans and mice was similar consistently with ∼0.9. A similarly robust power exponent was observed in CRADs of gut microbiomes during dietary interventions and several diseases. However, the power exponent was found to be ∼0.6 in CRADs from gut microbiomes characterized by lower species richness, such as those of human infants and the small intestine of mice. In addition, the CRAD of gut microbiomes of mice treated with antibiotics differed slightly from those of infants and the small intestines of mice. Based on these observations, in addition to data on the spatial distribution of microbes in the digestive tract, we developed a 3-dimensional mathematical model of microbial proliferation that reproduced the experimentally observed CRAD patterns. Our model indicated that the CRAD may be determined by the ratio of emerging to pre-existing species during non-uniform spatially competitive proliferation, independent of species composition.

Escherichia coli, cattle and the propagation of disease

Several early models describing host–pathogen interaction have assumed that each individual host has approximately the same likelihood of becoming infected or of infecting others. More recently, a concept that has been increasingly emphasized in many studies is that for many infectious diseases, transmission is not homogeneous but highly skewed at the level of populations. In what became known as the ‘20/80 rule’, about 20% of the hosts in a population were found to contribute to about 80% of the transmission potential. These heterogeneities have been described for the interaction between many microorganisms and their human or animal hosts. Several epidemiological studies have reported transmission heterogeneities for Escherichia coli by cattle, a phenomenon with far-reaching agricultural, medical and public health implications. Focusing on E. coli as a case study, this paper will describe super-spreading and super-shedding by cattle, review the main factors that shape these transmission heterogeneities and examine the interface with human health. Escherichia coli super-shedding and super-spreading by cattle are shaped by microorganism-specific, cattle-specific and environmental factors. Understanding the factors that shape heterogeneities in E. coli dispersion by cattle and the implications for human health represent key components that are critical for targeted infection control initiatives.

Microbial nutrient niches in the gut

The composition and function of the mammalian gut microbiota has been the subject of much research in recent years, but the principles underlying the assembly and structure of this complex community remain incompletely understood. Processes that shape the gut microbiota are thought to be mostly niche‐driven, with environmental factors such as the composition of available nutrients largely determining whether or not an organism can establish. The concept that the nutrient landscape dictates which organisms can successfully colonize and persist in the gut was first proposed in Rolf Freter's nutrient niche theory. In a situation where nutrients are perfectly mixed and there is balanced microbial growth, Freter postulated that an organism can only survive if it is able to utilize one or a few limiting nutrients more efficiently than its competitors. Recent experimental work indicates, however, that nutrients in the gut vary in space and time. We propose that in such a scenario, Freter's nutrient niche theory must be expanded to account for the co‐existence of microorganisms utilizing the same nutrients but in distinct sites or at different times, and that metabolic flexibility and mixed‐substrate utilization are common strategies for survival in the face of ever‐present nutrient fluctuations.