Summary: In the past several years, we have witnessed an increased interest in understanding the structure and function of the indigenous microbiota that inhabits the human body. It is hoped that this will yield novel insight into the role of these complex microbial communities in human health and disease. What is less appreciated is that this recent activity owes a great deal to the pioneering efforts of microbial ecologists who have been studying communities in non-host-associated environments. Interactions between environmental microbiologists and human microbiota researchers have already contributed to advances in our understanding of the human microbiome. We review the work that has led to these recent advances and illustrate some of the possible future directions for continued collaboration between these groups of researchers. We discuss how the application of ecological theory to the human-associated microbiota can lead us past descriptions of community structure and toward an understanding of the functions of the human microbiota. Such an approach may lead to a shift in the prevention and treatment of human diseases that involves conservation or restoration of the normal community structure and function of the host-associated microbiota.
The gut microbiota is amongst the most densely populated microbial ecosystem on earth. While the microbiome exerts numerous health beneficial functions, the high density of micro-organisms within this ecosystem also facilitates horizontal transfer of antimicrobial resistance (AMR) genes to potential pathogenic bacteria. Over the past decades antibiotic susceptibility testing of specific indicator bacteria from the microbiome, such as Escherichia coli, has been the method of choice in most studies. These studies have greatly enlarged our understanding on the prevalence and distribution of AMR and associated risk factors. Recent studies using (functional) metagenomics, however, highlighted the unappreciated diversity of AMR genes in the human microbiome and identified genes that had not been described previously. Next to metagenomics, more targeted approaches such as polymerase chain reaction for detection and quantification of AMR genes within a population are promising, in particular for large-scale epidemiological screening. Here we present an overview of the indigenous microbiota as a reservoir of AMR genes, the current knowledge on this “resistome” and the recent and upcoming advances in the molecular diagnostic approaches to unravel this reservoir.
antimicrobial resistance; resistome; metagenomics; gut microbiota; microbiome
Next-generation sequencing technologies have revolutionized the analysis of microbial communities in diverse environments, including the human body. This article reviews several aspects of one of these technologies, the pyrosequencing technique, including its principles, applications, and significant contribution to the study of the human microbiome, with especial emphasis on the oral microbiome. The results brought about by pyrosequencing studies have significantly contributed to refining and augmenting the knowledge of the community membership and structure in and on the human body in healthy and diseased conditions. Because most oral infectious diseases are currently regarded as biofilm-related polymicrobial infections, high-throughput sequencing technologies have the potential to disclose specific patterns related to health or disease. Further advances in technology hold the perspective to have important implications in terms of accurate diagnosis and more effective preventive and therapeutic measures for common oral diseases.
next-generation DNA sequencing; pyrosequencing; human microbiome; oral microbiome
Investigation of the lung microbiome is a relatively new field. Although the lungs were classically believed to be sterile, recently published investigations have identified microbial communities in the lungs of healthy humans. At the present time, there are significant methodologic and technical hurdles that must be addressed in ongoing investigations, including distinguishing the microbiota of the upper and lower respiratory tracts. However, characterization of the lung microbiome is likely to provide important pathogenic insights into cystic fibrosis, respiratory disease of the newborn, chronic obstructive pulmonary disease, and asthma. In addition to characterization of the lung microbiome, the microbiota of the gastrointestinal tract have profound influence on development and maintenance of lung immunity and inflammation. Further study of gastrointestinal-respiratory interactions are likely to yield important insights into the pathogenesis of pulmonary diseases, including asthma. As this field advances over the next several years, we anticipate that studies utilizing larger cohorts, multi-center designs, and longitudinal sampling will add to our knowledge and understanding of the lung microbiome.
Over the past decade researchers have begun to characterize viral diversity using metagenomic methods. These studies have shown that viruses, the majority of which infect bacteria (bacteriophages), are likely the most genetically diverse components of the biosphere. Here we briefly review the incipient rise of a phage biology renaissance catalyzed by recent advances in next generation sequencing. We explore how work characterizing phage diversity and their lifestyles in the gut is changing our view of ourselves as supra-organisms. Finally, we discuss how a new appreciation of phage dynamics may yield new applications for phage therapies designed to manipulate the structure and functions of our gut microbiomes.
Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such ‘ecosystems biology’ approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.
16S rRNA biodiversity; binning; bioinformatics; Genomic Standards Consortium; metagenomics; next-generation sequencing
Rapidly developing sequencing methods and analytical techniques are enhancing our ability to understand the human microbiome, and, indeed, how we define the microbiome and its constituents. In this review we highlight recent research that expands our ability to understand the human microbiome on different spatial and temporal scales, including daily timeseries datasets spanning months. Furthermore, we discuss emerging concepts related to defining operational taxonomic units, diversity indices, core versus transient microbiomes and the possibility of enterotypes. Additional advances in sequencing technology and in our understanding of the microbiome will provide exciting prospects for exploiting the microbiota for personalized medicine.
To analyze the vast number and variety of microorganisms inhabiting the human intestine, emerging metagenomic technologies are extremely powerful. The intestinal microbes are taxonomically complex and constitute an ecologically dynamic community (microbiota) that has long been believed to possess a strong impact on human physiology. Furthermore, they are heavily involved in the maturation and proliferation of human intestinal cells, helping to maintain their homeostasis and can be causative of various diseases, such as inflammatory bowel disease and obesity. A simplified animal model system has provided the mechanistic basis for the molecular interactions that occur at the interface between such microbes and host intestinal epithelia. Through metagenomic analysis, it is now possible to comprehensively explore the genetic nature of the intestinal microbiome, the mutually interacting system comprising the host cells and the residing microbial community. The human microbiome project was recently launched as an international collaborative research effort to further promote this newly developing field and to pave the way to a new frontier of human biology, which will provide new strategies for the maintenance of human health.
microbiome; microbiota; gut; metagenomics
Purpose of review
The microbiome continues to demonstrate an important role in immune and metabolic programming. This review will focus on the mechanistic implications of recent findings for diabetes pathogenesis and treatment.
Multiple techniques are developing to specify the microbiome. At the same time, new insights have emerged into local interactions of microbial products with human development. New findings demonstrate that key bacteria and their products result in the programming of diabetes-modulating Th17 and regulatory T lymphocytes within and outside the intestine. The role of the bacterial metagenome in programming human metabolism has also revealed new insights. In turn, these findings suggest a framework in which the microbiome may be modified to change the course of diabetes.
The microbiome is a key regulator of metabolism and immunity. Specific bacteria and their secreted products are now known to program Th17 and regulatory T-cell development, which may change the course of diabetes. Bacterial genomics are demonstrating important, modifiable roles of bacterial gene products in metabolism. Further understanding of this symbiotic relationship will provide new avenues for intervention in diabetes.
diabetes; immunity; metabolism; microbiome; T regulatory cells; Th17
Purpose of review
The review aims to update the reader on current developments in our understanding of how the gut microbiota impact on inflammatory bowel disease and the irritable bowel syndrome. It will also consider current efforts to modulate the microbiota for therapeutic effect.
Gene polymorphisms associated with inflammatory bowel disease increasingly suggest that interaction with the microbiota drives pathogenesis. This may be through modulation of the immune response, mucosal permeability or the products of microbial metabolism. Similar findings in irritable bowel syndrome have reinforced the role of gut-specific factors in this ‘functional’ disorder. Metagenomic analysis has identified alterations in pathways and interactions with the ecosystem of the microbiome that may not be recognized by taxonomic description alone, particularly in carbohydrate metabolism. Treatments targeted at the microbial stimulus with antibiotics, probiotics or prebiotics have all progressed in the past year. Studies on the long-term effects of treatment on the microbiome suggest that dietary intervention may be needed for prolonged efficacy.
The microbiome represents ‘the other genome’, and to appreciate its role in health and disease will be as challenging as with our own genome. Intestinal diseases occur at the front line of our interaction with the microbiome and their future treatment will be shaped as we unravel our relationship with it.
carbohydrates; inflammatory bowel disease; irritable bowel syndrome; metagenomics; microbiota
Recent advances in molecular technique have now made it possible to interrogate the human microbiome in depth to better understand the interactions with the host organism and its role in diseases. We now report the utility of using Length Heterogeneity Polymerase Chain Reaction (LH-PCR) to survey samples and a proprietary Multitagged Pyrosequencing (MTPS) methodology to interrogate the gut microbiome in healthy and disease states. We present an overview of our studies demonstrating that the application of these molecular biology techniques to an example disease state such as Inflammatory Bowel Disease (IBD). The findings show that there is a core mucosal bacterial microbiome (i.e. a mucosal biofilm) that is distinct from the luminal microbiome in health and that the mucosal microbiome appears to be dysbiotic in IBD. We propose that the mucosal microbiome forms a synergistic and stable interaction with the host immune system, while the lumen microbiome varies based on diet or other environmental factors. We define this composite ecosystem of the human microbiome and human host as the Human Metabiome.
Recent advances in next-generation DNA sequencing enable rapid high-throughput quantitation of microbial community composition in human samples, opening up a new field of microbiomics. One of the promises of this field is linking abundances of microbial taxa to phenotypic and physiological states, which can inform development of new diagnostic, personalized medicine, and forensic modalities. Prior research has demonstrated the feasibility of applying machine learning methods to perform body site and subject classification with microbiomic data. However, it is currently unknown which classifiers perform best among the many available alternatives for classification with microbiomic data.
In this work, we performed a systematic comparison of 18 major classification methods, 5 feature selection methods, and 2 accuracy metrics using 8 datasets spanning 1,802 human samples and various classification tasks: body site and subject classification and diagnosis.
We found that random forests, support vector machines, kernel ridge regression, and Bayesian logistic regression with Laplace priors are the most effective machine learning techniques for performing accurate classification from these microbiomic data.
Microbiomic data; Machine learning; Classification; Feature selection
Over the last two decades, advanced molecular genetics technology has enabled analysis of complex microbial communities and the study of microbial genomics. Interest has grown in characterizing the microbiome, defined as a collective microbial community and its extensive genome, as a clue to disease mechanisms. “The Human Microbiome Project,” sponsored by the NIH Common Fund, was established to characterize the pathology-associated human microbiome in nasal passages, oral cavities, skin, the gastrointestinal tract, and the urogenital compartment. In particular, characterization of urogenital microbiota may elucidate etiologies of complex obstetrical syndromes and factors in fetal development that define risk for pathology in adulthood. This article summarizes recent findings defining the microbiome associated with the female urogenital compartment in child-bearing age women. We also describe our analysis of microbiome samples from the oral, vaginal, and rectal compartments in a cohort of pregnant women. Findings present technical considerations in the characterization of microbial diversity and composition associated with gestational diabetes as a model pregnancy-associated pathology.
Micro-organisms; microbiology; microbiota; microbiome; metagenome; gynecology; obstetrics
It is increasingly clear that the interaction between host and microbiome profoundly affects health. There are 10 times more bacteria in and on our bodies than the total of our own cells, and the human intestine contains approximately 100 trillion bacteria. Interrogation of microbial communities by using classic microbiology techniques offers a very restricted view of these communities, allowing us to see only what we can grow in isolation. However, recent advances in sequencing technologies have greatly facilitated systematic and comprehensive studies of the role of the microbiome in human health and disease. Comprehensive understanding of our microbiome will enhance understanding of disease pathogenesis, which in turn may lead to rationally targeted therapy for a number of conditions, including autoimmunity.
Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges.
meta'omics; microbial communities; microbiome computational models
In this commentary, we will review some of the early efforts aimed at understanding the role of the enteric microbiota in the causality of inflammatory bowel diseases. By examining these studies and drawing on our own experiences bridging clinical gastroenterology and microbial ecology as part of the NIH-funded Human Microbiome Project (Turnbaugh et al., 2007), we hope to help define some of the “growing pains” that have hampered these initial efforts. It is our sincere hope that this discussion will help advance future efforts in this area by identifying current challenges and limitations and by suggesting strategies to overcome these obstacles.
inflammatory bowel diseases; human enteric microbiome; microbial dysbiosis; microbial ecology; new generation DNA sequencing
Culture-independent molecular techniques have demonstrated that the majority of the gut microbiota is uncultivable. Application of these molecular techniques to more accurately identify the indigenous gut microbiome has moved with great pace over recent years, leading to a substantial increase in understanding of gut microbial communities in both health and a number of disorders, including irritable bowel syndrome (IBS). Use of culture-independent molecular techniques already employed to characterise faecal and, to a lesser extent, colonic mucosal microbial populations in IBS, without reliance on insensitive, traditional microbiological culture techniques, has the potential to more accurately determine microbial composition in the small intestine of patients with this disorder, at least that occurring proximally and within reach of sampling. Current data concerning culture-based and culture-independent analyses of the small intestinal microbiome in IBS are considered here.
Gut microbiome; Small intestinal bacterial overgrowth; Irritable bowel syndrome
Purpose of review
Interactions of the gut microbiome with the host are important in health and disease. Microbial translocation releases bacterial products that play a key role in progression of chronic liver disease by promoting hepatic injury and inflammation. Although this has long been recognized, we are just beginning to understand the circumstances under which the gut becomes leaky and to discover bacterial metabolites that promote liver disease. In this review we will summarize recent findings from the last two years.
Chronic liver disease is associated with an altered microbiome with both qualitative (dysbiosis) and quantitative (overgrowth) differences. This can be viewed as a loss of the symbiotic relationship between the microflora and the host. An imbalanced intestinal homeostasis results in a breach of the gut barrier and subsequent microbial translocation. However, the contribution of the intestinal microflora is beyond simple microbial translocation as pathogenic factor. Bacterial metabolites resulting from an imbalanced homeostasis and dysbiosis play also a crucial role in liver disease.
A combination between an initiating liver insult and a disturbance of the gut – host symbiosis synergize in progression of liver disease.
bacterial translocation; bacterial dysbiosis; microbiota composition; microbiome; intestinal inflammation; intestinal bacterial overgrowth
Analysis of human body microbial diversity is fundamental to understanding community structure, biology and ecology. The National Institutes of Health Human Microbiome Project (HMP) has provided an unprecedented opportunity to examine microbial diversity within and across body habitats and individuals through pyrosequencing-based profiling of 16 S rRNA gene sequences (16 S) from habits of the oral, skin, distal gut, and vaginal body regions from over 200 healthy individuals enabling the application of statistical techniques. In this study, two approaches were applied to elucidate the nature and extent of human microbiome diversity. First, bootstrap and parametric curve fitting techniques were evaluated to estimate the maximum number of unique taxa, Smax, and taxa discovery rate for habitats across individuals. Next, our results demonstrated that the variation of diversity within low abundant taxa across habitats and individuals was not sufficiently quantified with standard ecological diversity indices. This impact from low abundant taxa motivated us to introduce a novel rank-based diversity measure, the Tail statistic, (“τ”), based on the standard deviation of the rank abundance curve if made symmetric by reflection around the most abundant taxon. Due to τ’s greater sensitivity to low abundant taxa, its application to diversity estimation of taxonomic units using taxonomic dependent and independent methods revealed a greater range of values recovered between individuals versus body habitats, and different patterns of diversity within habitats. The greatest range of τ values within and across individuals was found in stool, which also exhibited the most undiscovered taxa. Oral and skin habitats revealed variable diversity patterns, while vaginal habitats were consistently the least diverse. Collectively, these results demonstrate the importance, and motivate the introduction, of several visualization and analysis methods tuned specifically for next-generation sequence data, further revealing that low abundant taxa serve as an important reservoir of genetic diversity in the human microbiome.
Purpose of review
The indigenous gut microbiota has been shown to be a key player in maintaining gastrointestinal homeostasis. This review discusses some of the recent work that reveals how the gut microbiome helps establish and protect intestinal health and how disturbances in this microbial community can lead to disease states.
The use of culture-independent methods has greatly improved our ability to determine the structure and function of the gut microbiome. The gut microbiota has critical interactions with the host immune system and metabolism with bilateral influences shaping both the host and the microbiome. Alterations in the gut microbiome are associated with a variety of disease states but we are only now beginning to understand the mechanisms by which this occurs.
Understanding how the gut microbiome contributes to intestinal health should lead to novel preventative strategies and therapies for a variety of gastrointestinal conditions.
Microbiome; host-microbe interactions; microbiota
Obesity, metabolic syndrome, and type 2 diabetes are major public health challenges. Recently, interest has surged regarding the possible role of the intestinal microbiota as potential novel contributors to the increased prevalence of these 3 disorders.
Recent advances in microbial DNA sequencing technologies have resulted in the widespread application of whole-genome sequencing technologies for metagenomic DNA analysis of complex ecosystems such as the human gut. Current evidence suggests that the gut microbiota affect nutrient acquisition, energy harvest, and a myriad of host metabolic pathways.
Advances in the Human Microbiome Project and human metagenomics research will lead the way toward a greater understanding of the importance and role of the gut microbiome in metabolic disorders such as obesity, metabolic syndrome, and diabetes.
Recent explorations of the human gut microbiota suggest that perturbations of microbial communities may increase predisposition to different disease phenotypes. Dietary nutrients may be converted into metabolites by intestinal microbes that serve as biologically active molecules affecting regulatory functions in the host. Probiotics may restore the composition of the gut microbiome and introduce beneficial functions to gut microbial communities, resulting in amelioration or prevention of gut inflammation and other intestinal or systemic disease phenotypes. This review describes how diet and intestinal luminal conversion by gut microbes play a role in shaping the structure and function of intestinal microbial communities. Proposed mechanisms of probiosis include alterations of composition and function of the human gut microbiome, and corresponding effects on immunity and neurobiology.
diet; gut microbiota; immunomodulation; Lactobacillus; nervous system; probiotics
Large-scale ‘meta-omic’ projects are greatly advancing our knowledge of the human microbiome and its specific role in governing health and disease states. A myriad of ongoing studies aim at identifying links between microbial community disequilibria (dysbiosis) and human diseases. However, due to the inherent complexity and heterogeneity of the human microbiome, cross-sectional, case–control and longitudinal studies may not have enough statistical power to allow causation to be deduced from patterns of association between variables in high-resolution omic datasets. Therefore, to move beyond reliance on the empirical method, experiments are critical. For these, robust experimental models are required that allow the systematic manipulation of variables to test the multitude of hypotheses, which arise from high-throughput molecular studies. Particularly promising in this respect are microfluidics-based in vitro co-culture systems, which allow high-throughput first-pass experiments aimed at proving cause-and-effect relationships prior to testing of hypotheses in animal models. This review focuses on widely used in vivo, in vitro, ex vivo and in silico approaches to study host-microbial community interactions. Such systems, either used in isolation or in a combinatory experimental approach, will allow systematic investigations of the impact of microbes on the health and disease of the human host. All the currently available models present pros and cons, which are described and discussed. Moreover, suggestions are made on how to develop future experimental models that not only allow the study of host-microbiota interactions but are also amenable to high-throughput experimentation.
Causality; Diet; Human microbiome; Hypothesis testing; In vivo model; In vitro model; Ex vivo model; In silico model; Dysbiosis; Disease; Microfluidics; Host-microbe interactions
Microbes are the most abundant biological entities found in the biosphere. Identification and measurement of microorganisms (including viruses, bacteria, archaea, fungi, and protists) in the biosphere cannot be readily achieved due to limitations in culturing methods. A non-culture based approach, called “metagenomics”, was developed that enabled researchers to comprehensively analyse microbial communities in different ecosystems. In this study, we highlight recent advances in the field of metagenomics for analyzing microbial communities in different ecosystems ranging from oceans to the human microbiome. Developments in several bioinformatics approaches are also discussed in context of microbial metagenomics that include taxonomic systems, sequence databases, and sequence-alignment tools. In summary, we provide a snapshot for the recent advances in metagenomics approach for analyzing changes in the microbial communities in different ecosystems.
metagenomics; sequencing; microbial diversity; bioinformatics; microbial changes
Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications.
Microbial metabolism affects biogeochemical cycles and human health. In most natural environments, multiple microbial species interact with each other, forming complex ecosystems whose properties are poorly understood. In an effort to understand inter-microbial interactions, and to explore new metabolic engineering avenues, researchers have started building artificial microbial ecosystems, e.g. pairs of genetically engineered strains that require each other for survival. Here we computationally explore the possibility of creating artificial microbial ecosystems without re-engineering the microbes themselves, but rather by manipulating the environment in which they grow. Specifically, using the framework of flux balance analysis, we predict environments in which either one or both microbes in a pair would not be able to grow without the other, inducing commensal (one-way) or mutualistic (two-way) interactions, respectively. Our algorithms can successfully recapitulate known inter-microbial interactions, and predict millions of new ones across any pair amongst different microbial species. Surprisingly, we find that it is always possible to identify conditions that induce mutualistic or commensal interactions between any two species. Hence, our method should help in mapping naturally occurring microbe-microbe interactions, and in engineering new ones through a novel, environment-driven branch of synthetic ecology.