Inferring dynamic signatures of microbes in complex host ecosystems

The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe will prove instrumental for future studies in this field.     

The Influence of Iron Availability on Human Salivary Microbial Community Composition

It is a well-recognized fact that the composition of human salivary microbial community is greatly affected by its nutritional environment. However, most studies are currently focused on major carbon or nitrogen sources with limited attention to trace elements like essential mineral ions. In this study, we examined the effect of iron availability on the bacterial profiles of an in vitro human salivary microbial community as iron is an essential trace element for the survival and proliferation of virtually all microorganisms. Analysis via a combination of PCR with denaturing gradient gel electrophoresis demonstrated a drastic change in species composition of an in vitro human salivary microbiota when iron was scavenged from the culture medium by addition of the iron chelator 2,2'-bipyridyl. This shift in community profile was prevented by the presence of excessive ferrous iron (Fe(2+)). Most interestingly, under iron deficiency, the in vitro grown salivary microbial community became dominated by several hemolytic bacterial species, including Streptococcus spp., Gemella spp., and Granulicatella spp. all of which have been implicated in infective endocarditis. These data provide evidence that iron availability can modulate host-associated oral microbial communities, resulting in a microbiota with potential clinical impact.     

Comparative analysis of microbiota along the length of the gastrointestinal tract of two tree squirrel species (Sciurus aberti and S. niger) living in sympatry

Microbiota inhabiting the gastrointestinal (GI) tract of animals has important impacts on many host physiological processes. Although host diet is a major factor influencing the composition of the gut micro‐organismal community, few comparative studies have considered how differences in diet influence community composition across the length of the GI tract. We used 16S sequencing to compare the microbiota along the length of the GI tract in Abert's (Sciurus aberti) and fox squirrels (S. niger) living in the same habitat. While fox squirrels are generalist omnivores, the diet of Abert's squirrels is unusually high in plant fiber, particularly in winter when they extensively consume fiber‐rich inner bark of ponderosa pine (Pinus ponderosa). Consistent with previous studies, microbiota of the upper GI tract of both species consisted primarily of facultative anaerobes and was less diverse than that of the lower GI tract, which included mainly obligate anaerobes. While we found relatively little differentiation between the species in the microbiota of the upper GI tract, the community composition of the lower GI tract was clearly delineated. Notably, the Abert's squirrel lower GI community was more stable in composition and enriched for microbes that play a role in the degradation of plant fiber. In contrast, overall microbial diversity was higher in fox squirrels. We hypothesize that these disparities reflect differences in diet quality and diet breadth between the species.     

Alterations in the Colonic Microbiota in Response to Osmotic Diarrhea

Background & Aims

Diseases of the human gastrointestinal (GI) tract are often accompanied by diarrhea with profound alterations in the GI microbiota termed dysbiosis. Whether dysbiosis is due to the disease itself or to the accompanying diarrhea remains elusive. With this study we characterized the net effects of osmotic diarrhea on the composition of the GI microbiota in the absence of disease.

Methods

We induced osmotic diarrhea in four healthy adults by oral administration of polyethylene glycol 4000 (PEG). Stool as well as mucosa specimens were collected before, during and after diarrhea and 16S rDNA-based microbial community profiling was used to assess the microbial community structure.

Results

Stool and mucosal microbiotas were strikingly different, with Firmicutes dominating the mucosa and Bacteroidetes the stools. Osmotic diarrhea decreased phylotype richness and showed a strong tendency to equalize the otherwise individualized microbiotas on the mucosa. Moreover, diarrhea led to significant relative shifts in the phyla Bacteroidetes and Firmicutes and to a relative increase in the abundance of Proteobacteria on the mucosa, a phenomenon also noted in several inflammatory and diarrheal GI diseases.

Conclusions

Changes in microbial community structure induced by osmotic diarrhea are profound and show similarities to changes observed in other GI diseases including IBD. These effects so must be considered when specimens from diarrheal diseases (i.e. obtained by stratification of samples according to diarrheal status) or conditions wherein bowel preparations like PEG (i.e. specimens obtained during endoscopy) are used.     

Gut region induces gastrointestinal microbiota community shift in Ujimqin sheep (Ovis aries): from a multi-domain perspective

Gastrointestinal (GI) microbiota is one of the most complicated microbial ecosystems and is vital in regulating biological processes associated with nutrient absorption and homeostatic maintenance. Although several efforts have been achieved in characterizing bacterial communities across gut regions, the variation of non-bacterial communities across GI tracts is still largely unexplored. To address this, we investigated microbial biogeography throughout the whole GI tracts of Ujimqin sheep (Ovis aries) by amplicon sequencing which targeted bacteria, fungi, and archaea. The results indicated that the community structures of all three domains were significantly distinguished according to GI tracts (stomach, small intestine, and large intestine), and a more strong and efficient species interaction was detected in small intestine based on cross-domain network analysis. Moreover, a between-domain difference in microbial assembly mechanism of among-GI regions was revealed here, wherein bacterial community is dominantly governed by variable selection (explaining ~62% of taxa turnover), while fungal and archaeal communities mainly governed by homogenizing dispersal (explaining ~49% and 60% of the turnover, respectively). Overall, these data highlight the GI section- and domain-dependence of GI microbial structure and assembly mechanism, suggesting that multi-domain should be explicitly considered when evaluating the influences of GI selection on gut microbial communities.     

How Microbes Shape Their Communities? A Microbial Community Model Based on Functional Genes

Exploring the mechanisms of maintaining microbial community structure is important to understand biofilm development or microbiota dysbiosis. In this paper, we propose a functional gene-based composition prediction(FCP) model to predict the population structure composition within a microbial community. The model predicts the community composition well in both a low-complexity community as acid mine drainage(AMD) microbiota, and a complex community as human gut microbiota. Furthermore, we define community structure shaping(CSS) genes as functional genes crucial for shaping the microbial community. We have identified CSS genes in AMD and human gut microbiota samples with FCP model and find that CSS genes change with the conditions. Compared to essential genes for microbes, CSS genes are significantly enriched in the genes involved in mobile genetic elements, cell motility, and defense mechanisms, indicating that the functions of CSS genes are focused on communication and strategies in response to the environment factors. We further find that it is the minority, rather than the majority, which contributes to maintaining community structure. Compared to health control samples, we find that some functional genes associated with metabolism of amino acids, nucleotides, and lipopolysaccharide are more likely to be CSS genes in the disease group. CSS genes may help us to understand critical cellular processes and be useful in seeking addable gene circuitries to maintain artificial self-sustainable communities. Our study suggests that functional genes are important to the assembly of microbial communities.     

Supervised classification of human microbiota

Recent advances in DNA sequencing technology have allowed the collection of high-dimensional data from human-associated microbial communities on an unprecedented scale. A major goal of these studies is the identification of important groups of microorganisms that vary according to physiological or disease states in the host, but the incidence of rare taxa and the large numbers of taxa observed make that goal difficult to obtain using traditional approaches. Fortunately, similar problems have been addressed by the machine learning community in other fields of study such as microarray analysis and text classification. In this review, we demonstrate that several existing supervised classifiers can be applied effectively to microbiota classification, both for selecting subsets of taxa that are highly discriminative of the type of community, and for building models that can accurately classify unlabeled data. To encourage the development of new approaches to supervised classification of microbiota, we discuss several structures inherent in microbial community data that may be available for exploitation in novel approaches, and we include as supplemental information several benchmark classification tasks for use by the community.     

Human Gut Microbiota and Gastrointestinal Cancer

Human gut microbiota play an essential role in both healthy and diseased states of humans. In the past decade, the interactions between microorganisms and tumors have attracted much attention in the efforts to understand various features of the complex microbial communities, as well as the possible mechanisms through which the microbiota are involved in cancer prevention, carcinogenesis, and anti-cancer therapy. A large number of studies have indicated that microbial dysbiosis contributes to cancer susceptibility via multiple pathways. Further studies have suggested that the microbiota and their associated metabolites are not only closely related to carcinogenesis by inducing inflammation and immune dysregulation, which lead to genetic instability, but also interfere with the pharmacodynamics of anticancer agents. In this article, we mainly reviewed the influence of gut microbiota on cancers in the gastrointestinal (GI) tract (including esophageal, gastric, colorectal, liver, and pancreatic cancers) and the regulation of microbiota by diet, prebiotics, probiotics, synbiotics, antibiotics, or the Traditional Chinese Medicine. We also proposed some new strategies in the prevention and treatment of GI cancers that could be explored in the future. We hope that this review could provide a comprehensive overview of the studies on the interactions between the gut microbiota and GI cancers, which are likely to yield translational opportunities to reduce cancer morbidity and mortality by improving prevention, diagnosis, and treatment.     

Gut microbiome in gastrointestinal cancer: a friend or foe?

The impact of the gut microbiome on host health is becoming increasingly recognized. To date, there is growing evidence that the complex characteristics of the microbial community play key roles as potential biomarkers and predictors of responses in cancer therapy. Many studies have shown that altered commensal bacteria lead to cancer susceptibility and progression in diverse pathways. In this review, we critically assess the data for gut microbiota related to gastrointestinal cancer, including esophageal, gastric, pancreatic, colorectal cancer, hepatocellular carcinoma and cholangiocarcinoma. Importantly, the underlying mechanisms of gut microbiota involved in cancer occurrence, prevention and treatment are elucidated. The purpose of this review is to provide novel insights for applying this understanding to the development of new therapeutic strategies in gastrointestinal cancer by targeting the microbial community.     

Minority species influences microbiota formation: the role of Bifidobacterium with extracellular glycosidases in bifidus flora formation in breastfed infant guts

The human body houses a variety of microbial ecosystems, such as the microbiotas on the skin, in the oral cavity and in the digestive tract. The gut microbiota is one such ecosystem that contains trillions of bacteria, and it is well established that it can significantly influence host health and diseases. With the advancement in bioinformatics tools, numerous comparative studies based on 16S ribosomal RNA (rRNA) gene sequences, metabolomics, pathological and epidemical analyses have revealed the correlative relationship between the abundance of certain taxa and disease states or amount of certain causative bioactive compounds. However, the 16S rRNA-based taxonomic analyses using next-generation sequencing (NGS) technology essentially detect only the majority species. Although the entire gut microbiome consists of 10¹³ microbial cells, NGS read counts are given in multiples of 10⁶, making it difficult to determine the diversity of the entire microbiota. Some recent studies have reported instances where certain minority species play a critical role in creating locally stable conditions for other species by stabilizing the fundamental microbiota, despite their low abundance. These minority species act as ‘keystone species’, which is a species whose effect on the community is disproportionately large compared to its relative abundance. One of the attributes of keystone species within the gut microbiota is its extensive enzymatic capacity for substrates that are rare or difficult to degrade for other species, such as dietary fibres or host-derived complex glycans, like human milk oligosaccharides (HMOs). In this paper, we propose that more emphasis should be placed on minority taxa and their possible role as keystone species in gut microbiota studies by referring to our recent studies on HMO-mediated microbiota formation in the infant gut.     

Optimization of terminal restriction fragment polymorphism (TRFLP) analysis of human gut microbiota

Some compounds originating from the human gut microbial metabolism of exogenous and endogenous substrates may have properties that profoundly affect the host's physiological processes. The influence of these metabolites on differences in disease risk among individuals could be mediated by metabolism specific to the gut microbial community composition. In this study, we evaluated the effectiveness of terminal restriction fragment polymorphism (TRFLP) as a biomarker of the fecal microbial community (as a surrogate of gut microbiota) for application in human population-based studies. We tested the effects of experimental conditions on DNA quality, DNA quantity, and TRFLP patterns derived from gut bacterial communities. Genomic DNA was extracted from fecal slurries and the bacterial 16S rDNA genes were amplified and analyzed by TRFLP. We found that the composition of the TRFLP fingerprints varied by different extraction procedure. The best quality and quantity of community DNA extracted from fecal material was obtained by using the QIAamp DNA stool minikit (Qiagen, Valencia, CA) with 95 degrees C incubation and moderate bead beating treatment during the cell-lysis step. Homogenization of fecal samples reduced variation among replicates. Once the TRFLP procedure was optimized, we assessed the methodological and inter-individual variation in gut microbial community fingerprints. The methodological variation ranged from 4.5-8.1% and inter-individual variation was 50.3% for common peaks. In conclusion, standardized TRFLP is a robust, reproducible, and high-throughput method that will provide a useful biomarker for characterizing gut microbiota in human fecal samples.     

人体肠道微生物多样性和功能研究进展

人体肠道中庞大而复杂的微生物群落对人体自身代谢表型有深远的影响.肠道微生物群落在亚种或菌株水平上表现出极大的多样性.利用微生物分子生态学、元基因组学和代谢组学研究方法,发现肠道微生物与宿主表现出共进化的特点,肠道微生物群落及其基因组为宿主提供了互补的遗传和代谢功能,表现出互惠共生关系.但是,肠道微生物群落中影响宿主代谢表型的关键功能菌鉴定及其作用模式问题仍然悬而未决,综合运用多种高通量研究方法和多维数据分析方法可能成为解决这个问题的突破口.     

Role of neuromediators in the functioning of the human microbiota: “Business talks” among microorganisms and the microbiota-host dialogue

Current concepts concerning the social behavior of microorganisms inhabiting the human gastrointestinal (GI) tract and their role in the formation of integrated supracellular structures and in intercellular communication in the host–microbiota system are reviewed. The analysis of the literature data and of the results obtained by the authors indicates an important role of neuromediators (biogenic amines, amino acids, peptides, and nitric oxide) in intra- and interspecies microbial communication, as well as in the microbiota–host dialogue. The role of this dialogue for human health, its effect on the human psyche and social behavior, and the possibility of construction of probiotic preparations with a target-oriented neurochemical effect are discussed.     

Control of mucosal polymicrobial populations by innate immunity

The gastrointestinal tract carries out the complex process of localizing the polymicrobial populations of the indigenous microbiota to the lumenal side of the GI mucosa while absorbing nutrients from the lumen and preventing damage to the mucosa. This process is accomplished through a combination of physical, innate and adaptive host defences and a 'strategic alliance' with members of the microbiota. To cope with the constant exposure to a diverse microbial community, the GI tract, through the actions of a number of specialized cells in the epithelium and lamina propria, has layers of humoral, physical and cellular defences that limit attachment, invasion and dissemination of the indigenous microbiota. However, the role of the microbiota in this dynamic balance is vital and serves as another level of 'innate' defence. We are just beginning to understand how bacterial metabolites aid in the control of potential pathogens within the microbiota and limit inflammatory responses to the microbiota, concepts that will impact our understanding of the biological effects of antibiotics, diet and probiotics on mucosal inflammatory responses.     

Differential Effects of Antibiotic Therapy on the Structure and Function of Human Gut Microbiota

The human intestinal microbiota performs many essential functions for the host. Antimicrobial agents, such as antibiotics (AB), are also known to disturb microbial community equilibrium, thereby having an impact on human physiology. While an increasing number of studies investigate the effects of AB usage on changes in human gut microbiota biodiversity, its functional effects are still poorly understood. We performed a follow-up study to explore the effect of ABs with different modes of action on human gut microbiota composition and function. Four individuals were treated with different antibiotics and samples were taken before, during and after the AB course for all of them. Changes in the total and in the active (growing) microbiota as well as the functional changes were addressed by 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. We have found that the class of antibiotic, particularly its antimicrobial effect and mode of action, played an important role in modulating the gut microbiota composition and function. Furthermore, analysis of the resistome suggested that oscillatory dynamics are not only due to antibiotic-target resistance, but also to fluctuations in the surviving bacterial community. Our results indicated that the effect of AB on the human gut microbiota relates to the interaction of several factors, principally the properties of the antimicrobial agent, and the structure, functions and resistance genes of the microbial community.     

Web of ecological interactions in an experimental gut microbiota

The dynamics of all ecosystems are dictated by intrinsic, density‐dependent mechanisms and by density‐independent environmental forcing. In spite of the importance of the gastrointestinal microbiota in health and disease, the ecology of this system remains largely unknown. Here, we take an ecological approach to gut microbial community analysis, with statistical modelling of time series data from chemostats. This approach removes effects of host forcing, allowing us to describe a network of intrinsic interactions determining the dynamic structure of an experimental gut microbiota. Surprisingly, the main colonization pattern in this simplified model system resembled that of the human infant gut, suggesting a potentially important role of density‐dependent interactions in the early gut microbiota. Knowledge of ecological structures in microbial systems may provide us with a means of controlling such systems by modifying the strength and nature of interactions among microbes and between the microbes and their environment.     

The macaque gut microbiome in health, lentiviral infection, and chronic enterocolitis

The vertebrate gut harbors a vast community of bacterial mutualists, the composition of which is modulated by the host immune system. Many gastrointestinal (GI) diseases are expected to be associated with disruptions of host-bacterial interactions, but relatively few comprehensive studies have been reported. We have used the rhesus macaque model to investigate forces shaping GI bacterial communities. We used DNA bar coding and pyrosequencing to characterize 141,000 sequences of 16S rRNA genes obtained from 100 uncultured GI bacterial samples, allowing quantitative analysis of community composition in health and disease. Microbial communities of macaques were distinct from those of mice and humans in both abundance and types of taxa present. The macaque communities differed among samples from intestinal mucosa, colonic contents, and stool, paralleling studies of humans. Communities also differed among animals, over time within individual animals, and between males and females. To investigate changes associated with disease, samples of colonic contents taken at necropsy were compared between healthy animals and animals with colitis and undergoing antibiotic therapy. Communities from diseased and healthy animals also differed significantly in composition. This work provides comprehensive data and improved methods for studying the role of commensal microbiota in macaque models of GI diseases and provides a model for the large-scale screening of the human gut microbiome.