Are microbiome studies ready for hypothesis-driven research?

Gut dysbiosis: Ecological causes and causative effects on human disease

The gut microbiota plays a role in many human diseases, but high-throughput sequence analysis does not provide a straightforward path for defining healthy microbial communities. Therefore, understanding mechanisms that drive compositional changes during disease (gut dysbiosis) continues to be a central goal in microbiome research. Insights from the microbial pathogenesis field show that an ecological cause for gut dysbiosis is an increased availability of host-derived respiratory electron acceptors, which are dominant drivers of microbial community composition. Similar changes in the host environment also drive gut dysbiosis in several chronic human illnesses, and a better understanding of the underlying mechanisms informs approaches to causatively link compositional changes in the gut microbiota to an exacerbation of symptoms. The emerging picture suggests that homeostasis is maintained by host functions that control the availability of resources governing microbial growth. Defining dysbiosis as a weakening of these host functions directs attention to the underlying cause and identifies potential targets for therapeutic intervention.

Human Microbiomes and Disease for the Biomedical Data Scientist

The human microbiome is complex, variable from person to person, essential for health, and related to both the risk for disease and the efficacy of our treatments. There are robust techniques to describe microbiota with high-throughput sequencing, and there are hundreds of thousands of already-sequenced specimens in public archives. The promise remains to use the microbiome both as a prognostic factor and as a target for precision medicine. However, when used as an input in biomedical data science modeling, the microbiome presents unique challenges. Here, we review the most common techniques used to describe microbial communities, explore these unique challenges, and discuss the more successful approaches for biomedical data scientists seeking to use the microbiome as an input in their studies.

Discovering functional small molecules in the gut microbiome

The human microbiome has emerged as a source of bacterially produced, functional small molecules that help regulate health and disease, and their discovery and annotation has become a popular research topic. Identifying these molecules provides an essential step in unraveling the molecular mechanisms underlying biological outcomes. The relevance of specific bacterial members of the microbiome has been demonstrated in a variety of correlative studies, and there are many possible paths from these correlations to the responsible metabolites. Herein, we summarize two studies that have recently identified gut microbiome metabolites that modulate immune responses or promote physical activity. Aside from the deep insights gained, these studies provide blueprints for successfully uncovering the molecules and mechanisms that control important physiological pathways.

A Comparison of Hypothesis-Driven and Data-Driven Research: A Case Study in Multimodal Data Science in Gut-Brain Axis Research

Data science, bioinformatics, and machine learning are the advent and progression of the fourth paradigm of exploratory science. The need for human-supported algorithms to capture patterns in big data is at the center of personalized healthcare and directly related to translational research. This paper argues that hypothesis-driven and data-driven research work together to inform the research process. At the core of these approaches are theoretical underpinnings that drive progress in the field. Here, we present several exemplars of research on the gut-brain axis that outline the innate values and challenges of these approaches. As nurses are trained to integrate multiple body systems to inform holistic human health promotion and disease prevention, nurses and nurse scientists serve an important role as mediators between this advancing technology and the patients. At the center of person-knowing, nurses need to be aware of the data revolution and use their unique skills to supplement the data science cycle from data to knowledge to insight.

The need for an integrated multi-OMICs approach in microbiome science in the food system

Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome-based technologies that provide added-value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different -omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex -omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/), a project supported by the European Commission, the workshop "Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research" gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome-based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.

The fecal bacterial microbiota of healthy and sick newborn foals

BACKGROUND

The fecal bacterial microbiota of normal foals and foals with enterocolitis has been characterized using next-generation sequencing technology; however, there are no reports investigating the gut microbiota in foals hospitalized for other perinatal diseases.

OBJECTIVE

To describe and compare the fecal bacterial microbiota in healthy and sick foals using next-generation sequencing techniques.

ANIMALS

Hospitalized (17) and healthy foals (21).

METHODS

Case-control study. Fecal samples were collected from healthy and sick foals on admission. Sick foals were further divided into sick nonseptic (SNS, n = 9) and septic (n = 8) foals. After extraction of DNA, the V4 region of the 16 S rRNA gene was amplified using a PCR assay, and the final product was sequenced with an Illumina MiSeq.

RESULTS

Diversity was significantly lower in healthy than sick foals (P < .05). The bacterial membership (Jaccard index) and structure (Yue & Clayton index) of the fecal microbiota of healthy, septic, and SNS foals were similar (AMOVA, P > .05). Bacterial membership (AMOVA, P = .06) and structure (AMOVA, P = .33) were not different between healthy and sick foals. Enterobacteriaceae, Enterococcus, and Streptococcus were among the 5 more abundant taxa identified in both groups.

CONCLUSION AND CLINICAL IMPORTANCE

Higher fecal microbiota diversity in sick than healthy foals might suggest a high exposure to environmental microorganisms or an unstable colonic microbiota. The presence of microorganisms causing bacteremia in foals in a high relative abundance in the feces of foals suggests the intestine might play an essential role in the causation of bacteremia in foals.

Exploring the Microbiome Analysis and Visualization Landscape

Research on the microbiome has boomed recently, which resulted in a wide range of tools, packages, and algorithms to analyze microbiome data. Here we investigate and map currently existing tools that can be used to perform visual analysis on the microbiome, and associate the including methods, visual representations and data features to the research objectives currently of interest in microbiome research. The analysis is based on a combination of a literature review and workshops including a group of domain experts. Both the reviewing process and workshops are based on domain characterization methods to facilitate communication and collaboration between researchers from different disciplines. We identify several research questions related to microbiomes, and describe how different analysis methods and visualizations help in tackling them.

Contribution of single-cell omics to microbial ecology

Micro-organisms play key roles in various ecosystems, but many of their functions and interactions remain undefined. To investigate the ecological relevance of microbial communities, new molecular tools are being developed. Among them, single-cell omics assessing genetic diversity at the population and community levels and linking each individual cell to its functions is gaining interest in microbial ecology. By giving access to a wider range of ecological scales (from individual to community) than culture-based approaches and meta-omics, single-cell omics can contribute not only to micro-organisms' genomic and functional identification but also to the testing of concepts in ecology. Here, we discuss the contribution of single-cell omics to possible breakthroughs in concepts and knowledge on microbial ecosystems and ecoevolutionary processes.

Latitudinal gradient in the intensity of biotic interactions in terrestrial ecosystems: Sources of variation and differences from the diversity gradient revealed by meta-analysis

The Latitudinal Biotic Interaction Hypothesis (LBIH) states that the intensity of biotic interactions increases from high to low latitudes. This hypothesis, which may partly explain latitudinal gradients in biodiversity, remains hotly debated, largely due to variable outcomes of published studies. We used meta-analysis to identify the scope of the LBIH in terrestrial ecosystems. For this purpose, we explored the sources of variation in the strength of latitudinal changes in herbivory, carnivory and parasitism (119 publications) and compared these gradients with gradients in the diversity of the respective groups of animals (102 publications). Overall, both herbivory and carnivory decreased towards the poles, while parasitism increased. The latitudinal gradient in herbivory and carnivory was threefold stronger above 50-60° than at lower latitudes and was significant due to interactions involving ectothermic consumers, studies using standardised prey (i.e. prey lacking local anti-predator adaptations) and studies aimed at testing LBIH. The poleward decrease in biodiversity did not differ between ectothermic and endothermic animals or among climate zones and was fourfold stronger than decrease in herbivory and carnivory. The discovered differences between the gradients in biotic interactions and biodiversity suggest that these two global macroecological patterns are likely shaped by different factors.

Rethinking microbial infallibility in the metagenomics era

The 'principle of microbial infallibility' was a mainstay of microbial physiology and environmental microbiology in earlier decades. This principle asserts that wherever there is an energetic gain to be made from environmental resources, microorganisms will find a way to take advantage of the situation. Although previously disputed, this claim was revived with the discovery of anammox bacteria and other major contributors to biogeochemistry. Here, we discuss the historical background to microbial infallibility, and focus on its contemporary relevance to metagenomics. Our analysis distinguishes exploration-driven metagenomics from hypothesis-driven metagenomics. In particular, we show how hypothesis-driven metagenomics can use background assumptions of microbial infallibility to enable the formulation of hypotheses to be tested by enrichment cultures. Discoveries of comammox and the anaerobic oxidation of methane are major instances of such strategies, and we supplement them with outlines of additional examples. This overview highlights one way in which metagenomics is making the transition from an exploratory data-analysis programme of research to a hypothesis-testing one. We conclude with a discussion of how microbial infallibility is a heuristic with far-reaching implications for the investigation of life.

Optimizing the quality of clinical studies on oral microbiome: A practical guide for planning, performing, and reporting

With this review, we aim to increase the quality standards for clinical studies with microbiome as an output parameter. We critically address the existing body of evidence for good quality practices in oral microbiome studies based on 16S rRNA gene amplicon sequencing. First, we discuss the usefulness of microbiome profile analyses. Is a microbiome study actually the best approach for answering the research question? This is followed by addressing the criteria for the most appropriate study design, sample size, and the necessary data (study metadata) that should be collected. Next, we evaluate the available evidence for best practices in sample collection, transport, storage, and DNA isolation. Finally, an overview of possible sequencing options (eg, 16S rRNA gene hypervariable regions, sequencing platforms), processing and data interpretation approaches, as well as requirements for meaningful data storage, sharing, and reporting are provided.

Gut microbiota And Human Body Interactions; Its Impact on Health: a review

Gut microbiota (GM) as an organ of the human body has a particular and autonomous function that related to it. This review aimed to investigate human intestinal and gut microbiota interaction and its impact on health. As a creation referable database about this dynamic and complex organ, several comprehensive projects are implemented by using culture-dependent (culturomics), culture independent methods (e.g metagenomics, mathematics model), and Gnotobiological together. This study was done by searching PubMed, Scopus and Google scholar database in the gut, health microbiota and interaction keywords. The first acquired microbiota during pregnancy or childbirth is colonized in the gut by using specific and non-specific mechanisms. That`s structure and shape reach relative stability with selection pressure along with host development until adulthood and keep its resilience against external or internal variables depending on the host genetics and negative feedback. Due to several research individuals have 2 functional group microbiota including the core (common between vast majorities human) and flexible (transient population) microbiome. The most important role of the GM in the human body can be summarized in three basic landscapes: metabolic, immune system, and gut-brain axis interaction. So that loss of microbial population balance will lead to disorder and disease.

How gut microbiome interactions affect nutritional traits of Drosophila melanogaster

Most research on the impact of the gut microbiome on animal nutrition is designed to identify the effects of single microbial taxa and single metabolites of microbial origin, without considering the potentially complex network of interactions among co-occurring microorganisms. Here, we investigated how different microbial associations and their fermentation products affect host nutrition, using Drosophila melanogaster colonized with three gut microorganisms (the bacteria Acetobacter fabarum and Lactobacillus brevis, and the yeast Hanseniaspora uvarum) in all seven possible combinations. Some microbial effects on host traits could be attributed to single taxa (e.g. yeast-mediated reduction of insect development time), while other effects were sex specific and driven by among-microbe interactions (e.g. male lipid content determined by interactions between the yeast and both bacteria). Parallel analysis of nutritional indices of microbe-free flies administered different microbial fermentation products (acetic acid, acetoin, ethanol and lactic acid) revealed a single consistent effect: that the lipid content of both male and female flies is reduced by acetic acid. This effect was recapitulated in male flies colonized with both yeast and A. fabarum, but not for any microbial treatment in females or males with other microbial complements. These data suggest that the effect of microbial fermentation products on host nutritional status is strongly context dependent, with respect to both the combination of associated microorganisms and host sex. Taken together, our findings demonstrate that among-microbe interactions can play a critically important role in determining the physiological outcome of host-microbiome interactions in Drosophila and, likely, in other animal hosts.

Host Genotype and Colonist Arrival Order Jointly Govern Plant Microbiome Composition and Function

The composition of host-associated microbiomes can have important consequences for host health and fitness [1-3]. Yet we still lack understanding of many fundamental processes that determine microbiome composition [4, 5]. There is mounting evidence that historical contingency during microbiome assembly may overshadow more deterministic processes, such as the selective filters imposed by host traits [6-8]. More specifically, species arrival order has been frequently shown to affect microbiome composition [9-12], a phenomenon known as priority effects [13-15]. However, it is less clear whether priority effects during microbiome assembly are consequential for the host [16] or whether intraspecific variation in host traits can alter the trajectory of microbiome assembly under priority effects. In a greenhouse inoculation experiment using the black cottonwood (Populus trichocarpa) foliar microbiome, we manipulated host genotype and the colonization order of common foliar fungi. We quantified microbiome assembly outcomes using fungal marker gene sequencing and measured susceptibility of the colonized host to a leaf rust pathogen, Melampsora × columbiana. We found that the effect of species arrival order on microbiome composition, and subsequent disease susceptibility, depended on the host genotype. Additionally, we found that microbiome assembly history can affect host disease susceptibility independent of microbiome composition at the time of pathogen exposure, suggesting that the interactive effects of species arrival order and host genotype can decouple community composition and function. Overall, these results highlight the importance of a key process underlying stochasticity in microbiome assembly while also revealing which hosts are most likely to experience these effects.

Oligosaccharides and Complex Carbohydrates: A New Paradigm for Cranberry Bioactivity

Cranberry is a well-known functional food, but the compounds directly responsible for many of its reported health benefits remain unidentified. Complex carbohydrates, specifically xyloglucan and pectic oligosaccharides, are the newest recognized class of biologically active compounds identified in cranberry materials. Cranberry oligosaccharides have shown similar biological properties as other dietary oligosaccharides, including effects on bacterial adhesion, biofilm formation, and microbial growth. Immunomodulatory and anti-inflammatory activity has also been observed. Oligosaccharides may therefore be significant contributors to many of the health benefits associated with cranberry products. Soluble oligosaccharides are present at relatively high concentrations (~20% w/w or greater) in many cranberry materials, and yet their possible contributions to biological activity have remained unrecognized. This is partly due to the inherent difficulty of detecting these compounds without intentionally seeking them. Inconsistencies in product descriptions and terminology have led to additional confusion regarding cranberry product composition and the possible presence of oligosaccharides. This review will present our current understanding of cranberry oligosaccharides and will discuss their occurrence, structures, ADME, biological properties, and possible prebiotic effects for both gut and urinary tract microbiota. Our hope is that future investigators will consider these compounds as possible significant contributors to the observed biological effects of cranberry.

More Arrows in the Ancient DNA Quiver: Use of Paleoepigenomes and Paleomicrobiomes to Investigate Animal Adaptation to Environment

Whether and how epigenetic mechanisms and the microbiome play a role in mammalian adaptation raised considerable attention and controversy, mainly because they have the potential to add new insights into the Modern Synthesis. Recent attempts to reconcile neo-Darwinism and neo-Lamarckism in a unified theory of molecular evolution give epigenetic mechanisms and microbiome a prominent role. However, supporting empirical data are still largely missing. Because experimental studies using extant animals can hardly be done over evolutionary timescales, we propose that advances in ancient DNA techniques provide a valid alternative. In this piece, we evaluate 1) the possible roles of epigenomes and microbiomes in animal adaptation, 2) advances in the retrieval of paleoepigenome and paleomicrobiome data using ancient DNA techniques, and 3) the plasticity of either and interactions between the epigenome and the microbiome, while emphasizing that it is essential to take both into account, as well as the underlying genetic factors that may confound the findings. We propose that advanced ancient DNA techniques should be applied to a wide range of past animals, so novel dynamics in animal evolution and adaption can be revealed.

tmap: an integrative framework based on topological data analysis for population-scale microbiome stratification and association studies

Untangling the complex variations of microbiome associated with large-scale host phenotypes or environment types challenges the currently available analytic methods. Here, we present tmap, an integrative framework based on topological data analysis for population-scale microbiome stratification and association studies. The performance of tmap in detecting nonlinear patterns is validated by different scenarios of simulation, which clearly demonstrate its superiority over the most commonly used methods. Application of tmap to several population-scale microbiomes extensively demonstrates its strength in revealing microbiome-associated host or environmental features and in understanding the systematic interrelations among their association patterns. tmap is available at https://github.com/GPZ-Bioinfo/tmap.

A horizon scan of priorities for coastal marine microbiome research

Research into the microbiomes of natural environments is changing the way ecologists and evolutionary biologists view the importance of microorganisms in ecosystem function. This is particularly relevant in ocean environments, where microorganisms constitute the majority of biomass and control most of the major biogeochemical cycles, including those that regulate Earth's climate. Coastal marine environments provide goods and services that are imperative to human survival and well-being (for example, fisheries and water purification), and emerging evidence indicates that these ecosystem services often depend on complex relationships between communities of microorganisms (the 'microbiome') and the environment or their hosts - termed the 'holobiont'. Understanding of coastal ecosystem function must therefore be framed under the holobiont concept, whereby macroorganisms and their associated microbiomes are considered as a synergistic ecological unit. Here, we evaluate the current state of knowledge on coastal marine microbiome research and identify key questions within this growing research area. Although the list of questions is broad and ambitious, progress in the field is increasing exponentially, and the emergence of large, international collaborative networks and well-executed manipulative experiments are rapidly advancing the field of coastal marine microbiome research.

Making the Most of Trait-Based Approaches for Microbial Ecology

There is an increasing interest in applying trait-based approaches to microbial ecology, but the question of how and why to do it is still lagging behind. By anchoring our discussion of these questions in a framework derived from epistemology, we broaden the scope of trait-based approaches to microbial ecology from one oriented mostly around explanation towards one inclusive of the predictive and integrative potential of these approaches. We use case studies from macro-organismal ecology to concretely show how these goals for knowledge development can be fulfilled and propose clear directions, adapted to the biological reality of microbes, to make the most of recent advancements in the measurement of microbial phenotypes and traits.