scholarly journals Biogeography & environmental conditions shape bacteriophage-bacteria networks across the human microbiome

2017 ◽  
Author(s):  
Geoffrey D Hannigan ◽  
Melissa B Duhaime ◽  
Danai Koutra ◽  
Patrick D Schloss
Keyword(s):  
Microbial Communities ◽  
Human Body ◽  
Complex Dynamics ◽  
Learning Algorithm ◽  
Human Microbiome ◽  
Metagenomic Sequence ◽  
Future Studies ◽  
Disease States ◽  
Health And Disease ◽  
Extinction Events

AbstractViruses and bacteria are critical components of the human microbiome and play important roles in health and disease. Most previous work has relied on studying bacteria and viruses independently, thereby reducing them to two separate communities. Such approaches are unable to capture how these microbial communities interact, such as through processes that maintain community robustness or allow phage-host populations to co-evolve. We implemented a network-based analytical approach to describe phage-bacteria network diversity throughout the human body. We built these community networks using a machine learning algorithm to predict which phages could infect which bacteria in a given microbiome. Our algorithm was applied to paired viral and bacterial metagenomic sequence sets from three previously published human cohorts. We organized the predicted interactions into networks that allowed us to evaluate phage-bacteria connectedness across the human body. We observed evidence that gut and skin network structures were person-specific and not conserved among cohabitating family members. High-fat diets appeared to be associated with less connected networks. Network structure differed between skin sites, with those exposed to the external environment being less connected and likely more susceptible to network degradation by microbial extinction events. This study quantified and contrasted the diversity of virome-microbiome networks across the human body and illustrated how environmental factors may influence phage-bacteria interactive dynamics. This work provides a baseline for future studies to better understand system perturbations, such as disease states, through ecological networks.Author SummaryThe human microbiome, the collection of microbial communities that colonize the human body, is a crucial component to health and disease. Two major components of the human microbiome are the bacterial and viral communities. These communities have primarily been studied separately using metrics of community composition and diversity. These approaches have failed to capture the complex dynamics of interacting bacteria and phage communities, which frequently share genetic information and work together to maintain ecosystem homestatsis (e.g. kill-the-winner dynamics). Removal of bacteria or phage can disrupt or even collapse those ecosystems. Relationship-based network approaches allow us to capture this interaction information. Using this network-based approach with three independent human cohorts, we were able to present an initial understanding of how phage-bacteria networks differ throughout the human body, so as to provide a baseline for future studies of how and why microbiome networks differ in disease states.

scholarly journals Complementary Methodologies To Investigate Human Gut Microbiota in Host Health, Working towards Integrative Systems Biology

2017 ◽  
Vol 200 (3) ◽  
Author(s):  
Celia Méndez-García ◽  
Coral Barbas ◽  
Manuel Ferrer ◽  
David Rojo
Keyword(s):  
Human Subjects ◽  
Human Microbiome ◽  
Fecal Microbiota ◽  
Microbiome Composition ◽  
Disease States ◽  
Microbial Product ◽  
Host Health ◽  
Health And Disease ◽  
The Cost ◽  
Biological State

ABSTRACT In 1680, Antonie van Leeuwenhoek noted compositional differences in his oral and fecal microbiota, pioneering the study of the diversity of the human microbiome. From Leeuwenhoek's time to successful modern attempts at changing the gut microbial landscape to cure disease, there has been an exponential increase in the recognition of our resident microbes as part of ourselves. Thus, the human host and microbiome have evolved in parallel to configure a balanced system in which microbes survive in homeostasis with our innate and acquired immune systems, unless disease occurs. A growing number of studies have demonstrated a correlation between the presence/absence of microbial taxa and some of their functional molecules (i.e., genes, proteins, and metabolites) with health and disease states. Nevertheless, misleading experimental design on human subjects and the cost and lack of standardized animal models pose challenges to answering the question of whether changes in microbiome composition are cause or consequence of a certain biological state. In this review, we evaluate the state of the art of methodologies that enable the study of the gut microbiome, encouraging a change in broadly used analytic strategies by choosing effector molecules (proteins and metabolites) in combination with coding nucleic acids. We further explore microbial and effector microbial product imbalances that relate to disease and health.

scholarly journals Identifying biases and their potential solutions in human microbiome studies

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jacob T. Nearing ◽  
André M. Comeau ◽  
Morgan G. I. Langille
Keyword(s):  
Microbial Communities ◽  
Human Body ◽  
Human Microbiome ◽  
Sample Collection ◽  
Sequencing Technology ◽  
Microbial Composition ◽  
Significant Bias ◽  
Typical Sequence ◽  
Entire Experiment ◽  
The Impact

AbstractAdvances in DNA sequencing technology have vastly improved the ability of researchers to explore the microbial inhabitants of the human body. Unfortunately, while these studies have uncovered the importance of these microbial communities to our health, they often do not result in similar findings. One possible reason for the disagreement in these results is due to the multitude of systemic biases that are introduced during sequence-based microbiome studies. These biases begin with sample collection and continue to be introduced throughout the entire experiment leading to an observed community that is significantly altered from the true underlying microbial composition. In this review, we will highlight the various steps in typical sequence-based human microbiome studies where significant bias can be introduced, and we will review the current efforts within the field that aim to reduce the impact of these biases.

scholarly journals Improving characterization of understudied human microbiomes using targeted phylogenetics

2019 ◽  
Author(s):  
Bruce A Rosa ◽  
Kathie Mihindukulasuriya ◽  
Kymberlie Hallsworth-Pepin ◽  
Aye Wollam ◽  
John Martin ◽  
...  
Keyword(s):  
Human Microbiome ◽  
Human Microbiome Project ◽  
Genomic Sequences ◽  
Bacterial Strains ◽  
Bacterial Genomes ◽  
Genomic Databases ◽  
Disease States ◽  
Health And Disease ◽  
Taxonomic Groups

AbstractWhole genome bacterial sequences are required to better understand microbial functions, niches-pecific bacterial metabolism, and disease states. Although genomic sequences are available for many of the human-associated bacteria from commonly tested body habitats (e.g. stool), as few as 13% of bacterial-derived reads from other sites such as the skin map to known bacterial genomes. To facilitate a better characterization of metagenomic shotgun reads from under-represented body sites, we collected over 10,000 bacterial isolates originating from 14 human body habitats, identified novel taxonomic groups based on full length 16S rRNA sequences, clustered the sequences to ensure that no individual taxonomic group was over-selected for sequencing, prioritized bacteria from under-represented body sites (such as skin, respiratory and urinary tract), and sequenced and assembled genomes for 665 new bacterial strains. Here we show that addition of these genomes improved read mapping rates of HMP metagenomic samples by nearly 30% for the previously under-represented phylum Fusobacteria, and 27.5% of the novel genomes generated here had high representation in at least one of the tested HMP samples, compared to 12.5% of the sequences in the public databases, indicating an enrichment of useful novel genomic sequences resulting from the prioritization procedure. As our understanding of the human microbiome continues to improve and to enter the realm of therapy developments, targeted approaches such as this to improve genomic databases will increase in importance from both an academic and clinical perspective.ImportanceThe human microbiome plays a critically important role in health and disease, but current understanding of the mechanisms underlying the interactions between the varying microbiome and the different host environments is lacking. Having access to a database of fully sequenced bacterial genomes provides invaluable insights into microbial functions, but currently sequenced genomes for the human microbiome have largely come from a limited number of body sites (primarily stool), while other sites such as the skin, respiratory tract and urinary tracts are under-represented, resulting in as little as 13% of bacterial-derived reads mapping to known bacterial genomes. Here, we sequenced and assembled 665 new bacterial genomes, prioritized from a larger database to select under-represented body sites and bacterial taxa in the existing databases. As a result, we substantially improve mapping rates for samples from the Human Microbiome Project and provide an important contribution to human bacterial genomic databases for future studies.

scholarly journals Temporal variability is a personalized feature of the human microbiome

2014 ◽  
Author(s):  
Gilberto E Flores ◽  
J Gregory Caporaso ◽  
Jessica B Henley ◽  
Jai Ram Rideout ◽  
Daniel Domogala ◽  
...  
Keyword(s):  
Community Structure ◽  
Microbial Communities ◽  
Human Body ◽  
Temporal Variability ◽  
Temporal Dynamics ◽  
Human Microbiome ◽  
Wide Range ◽  
Diverse Communities ◽  
Study Population ◽  
Over Time

Background: It is now apparent that the complex microbial communities found on and in the human body (the human microbiome) vary across individuals. What has largely been missing from previous studies is an understanding of how these communities vary over time within individuals. To the extent to which it has been considered, it is often assumed that temporal variability is negligible for healthy adults. Here we address this gap in understanding by profiling the forehead, gut (fecal), palm, and tongue microbial communities in 85 adults, weekly over three months. Results: We found that skin (forehead and palm) varied most in the number of taxa present, whereas gut and tongue communities varied more in the relative abundances of taxa. Within each body habitat, there was a wide range of temporal variability across the study population, with some individuals consistently harboring more variable communities than others. The best predictor of these differences in variability across individuals was microbial diversity; individuals with more diverse gut or tongue communities were less variable than individuals with less diverse communities. Conclusions: This expanded sampling allowed us to observe consistently high levels of temporal variability in both diversity and community structure in all body habitats studied. These findings suggest that temporal dynamics may need to be considered when attempting to link changes in microbiome structure to changes in health status.Furthermore, our findings show that, not only is the composition of an individual’s microbiome highly personalized, but their degree of temporal variability is also a personalized feature.

scholarly journals A phylogenetic transform enhances analysis of compositional microbiota data

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Justin D Silverman ◽  
Alex D Washburne ◽  
Sayan Mukherjee ◽  
Lawrence A David
Keyword(s):  
Microbial Communities ◽  
Relative Abundance ◽  
Human Body ◽  
Compositional Data ◽  
Level Structure ◽  
Evolutionary Models ◽  
Phylogenetic Relatedness ◽  
Health And Disease ◽  
Log Ratio ◽  
Phylogenetic Models

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

scholarly journals From Structure to Function: the Ecology of Host-Associated Microbial Communities

2010 ◽  
Vol 74 (3) ◽  
pp. 453-476 ◽  
Author(s):  
Courtney J. Robinson ◽  
Brendan J. M. Bohannan ◽  
Vincent B. Young
Keyword(s):  
Community Structure ◽  
Microbial Communities ◽  
Human Microbiome ◽  
Structure And Function ◽  
Future Directions ◽  
Human Microbiota ◽  
Health And Disease ◽  
Indigenous Microbiota ◽  
And Function

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.

scholarly journals Microbiome, Immunosenescence, and Chronic Kidney Disease

2021 ◽  
Vol 8 ◽  
Author(s):  
Elisavet Stavropoulou ◽  
Konstantia Kantartzi ◽  
Christina Tsigalou ◽  
Konstantina Aftzoglou ◽  
Chrysa Voidarou ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Diseases ◽  
Human Microbiome ◽  
Renal Diseases ◽  
Predictive Tool ◽  
Gut Dysbiosis ◽  
Multiple Factors ◽  
Disease States ◽  
Genetic Endowment ◽  
Health And Disease

The gut microbiome is known as an important predictive tool for perceiving characteristic shifts in disease states. Multiple renal diseases and pathologies seem to be associated with gut dysbiosis which directly affects host homeostasis. The gastrointestinal-kidney dialogue confers interesting information about the pathogenesis of multiple kidney diseases. Moreover, aging is followed by specific shifts in the human microbiome, and gradual elimination of physiological functions predisposes the microbiome to inflammaging, sarcopenia, and disease. Aging is characterized by a microbiota with an abundance of disease-associated pathobionts. Multiple factors such as the immune system, environment, medication, diet, and genetic endowment are involved in determining the age of the microbiome in health and disease. Our present review promotes recently acquired knowledge and is expected to inspire researchers to advance studies and investigations on the involved pathways of the gut microbiota and kidney axis.

scholarly journals Temporal variability is a personalized feature of the human microbiome

2014 ◽  
Author(s):  
Gilberto E Flores ◽  
J Gregory Caporaso ◽  
Jessica B Henley ◽  
Jai Ram Rideout ◽  
Daniel Domogala ◽  
...  
Keyword(s):  
Community Structure ◽  
Microbial Communities ◽  
Human Body ◽  
Temporal Variability ◽  
Temporal Dynamics ◽  
Human Microbiome ◽  
Wide Range ◽  
Diverse Communities ◽  
Study Population ◽  
Over Time

Background: It is now apparent that the complex microbial communities found on and in the human body (the human microbiome) vary across individuals. What has largely been missing from previous studies is an understanding of how these communities vary over time within individuals. To the extent to which it has been considered, it is often assumed that temporal variability is negligible for healthy adults. Here we address this gap in understanding by profiling the forehead, gut (fecal), palm, and tongue microbial communities in 85 adults, weekly over three months. Results: We found that skin (forehead and palm) varied most in the number of taxa present, whereas gut and tongue communities varied more in the relative abundances of taxa. Within each body habitat, there was a wide range of temporal variability across the study population, with some individuals consistently harboring more variable communities than others. The best predictor of these differences in variability across individuals was microbial diversity; individuals with more diverse gut or tongue communities were less variable than individuals with less diverse communities. Conclusions: This expanded sampling allowed us to observe consistently high levels of temporal variability in both diversity and community structure in all body habitats studied. These findings suggest that temporal dynamics may need to be considered when attempting to link changes in microbiome structure to changes in health status.Furthermore, our findings show that, not only is the composition of an individual’s microbiome highly personalized, but their degree of temporal variability is also a personalized feature.

scholarly journals The Human Microbiome and Its Impacts on Health

2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
Author(s):  
Grace A. Ogunrinola ◽  
John O. Oyewale ◽  
Oyewumi O. Oshamika ◽  
Grace I. Olasehinde
Keyword(s):  
Immune System ◽  
Human Body ◽  
Human Microbiome ◽  
Skin Surface ◽  
Host Susceptibility ◽  
Anatomical Site ◽  
Immune Functions ◽  
Microbial Composition ◽  
Health And Disease ◽  
Micro Organisms

The human microbiome comprises bacteria, archaea, viruses, and eukaryotes which reside within and outside our bodies. These organisms impact human physiology, both in health and in disease, contributing to the enhancement or impairment of metabolic and immune functions. Micro-organisms colonise various sites on and in the human body, where they adapt to specific features of each niche. Facultative anaerobes are more dominant in the gastrointestinal tract, whereas strict aerobes inhabit the respiratory tract, nasal cavity, and skin surface. The indigenous organisms in the human body are well adapted to the immune system, due to the biological interaction of the organisms with the immune system over time. An alteration in the intestinal microbial community plays a major role in human health and disease pathogenesis. These alterations result from lifestyle and the presence of an underlying disease. Dysbiosis increases host susceptibility to infection, and the nature of which depends on the anatomical site involved. The unique diversity of the human microbiota accounts for the specific metabolic activities and functions of these micro-organisms within each body site. It is therefore important to understand the microbial composition and activities of the human microbiome as they contribute to health and disease.

scholarly journals GutCyc: a Multi-Study Collection of Human Gut Microbiome Metabolic Models

2016 ◽  
Author(s):  
Aria S. Hahn ◽  
Tomer Altman ◽  
Kishori M. Konwar ◽  
Niels W. Hanson ◽  
Dongjae Kim ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Human Microbiome ◽  
Therapeutic Interventions ◽  
Human Gut ◽  
Human Gut Microbiome ◽  
Disease States ◽  
Health And Disease ◽  
Inflammatory Bowel

AbstractAdvances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GUTCYC, a compendium of environmental pathway genome databases constructed from 418 assembled human microbiome datasets using METAPATHWAYS, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the PATHWAY TOOLS software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GUTCYC provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GUTCYC data products are searchable online, or may be downloaded and explored locally using METAPATHWAYS and PATHWAY TOOLS.

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