Spatial metagenomic characterization of microbial biogeography in the gut

Deciphering the spatiotemporal transcriptional landscape of intestinal diseases (Review)

The intestines are the largest barrier organ in the human body. The intestinal barrier plays a crucial role in maintaining the balance of the intestinal environment and protecting the intestines from harmful bacterial invasion. Single‑cell RNA sequencing technology allows the detection of the different cell types in the intestine in two dimensions and the exploration of cell types that have not been fully characterized. The intestinal mucosa is highly complex in structure, and its proper functioning is linked to multiple structures in the proximal‑distal intestinal and luminal‑mucosal axes. Spatial localization is at the core of the efforts to explore the interactions between the complex structures. Spatial transcriptomics (ST) is a method that allows for comprehensive tissue analysis and the acquisition of spatially separated genetic information from individual cells, while preserving their spatial location and interactions. This approach also prevents the loss of fragile cells during tissue disaggregation. The emergence of ST technology allows us to spatially dissect enzymatic processes and interactions between multiple cells, genes, proteins and signals in the intestine. This includes the exchange of oxygen and nutrients in the intestine, different gradients of microbial populations and the role of extracellular matrix proteins. This regionally precise approach to tissue studies is gaining more acceptance and is increasingly applied in the investigation of disease mechanisms related to the gastrointestinal tract. Therefore, this review summarized the application of ST in gastrointestinal diseases.

Symbiotic symphony: Understanding host-microbiota dialogues in a spatial context

Modern precision sequencing techniques have established humans as a holobiont that live in symbiosis with the microbiome. Microbes play an active role throughout the life of a human ranging from metabolism and immunity to disease tolerance. Hence, it is of utmost significance to study the eukaryotic host in conjunction with the microbial antigens to obtain a complete picture of the host-microbiome crosstalk. Previous attempts at profiling host-microbiome interactions have been either superficial or been attempted to catalogue eukaryotic transcriptomic profile and microbial communities in isolation. Additionally, the nature of such immune-microbial interactions is not random but spatially organised. Hence, for a holistic clinical understanding of the interplay between hosts and microbiota, it's imperative to concurrently analyze both microbial and host genetic information, ensuring the preservation of their spatial integrity. Capturing these interactions as a snapshot in time at their site of action has the potential to transform our understanding of how microbes impact human health. In examining early-life microbial impacts, the limited presence of communities compels analysis within reduced biomass frameworks. However, with the advent of spatial transcriptomics we can address this challenge and expand our horizons of understanding these interactions in detail. In the long run, simultaneous spatial profiling of host-microbiome dialogues can have enormous clinical implications especially in gaining mechanistic insights into the disease prognosis of localised infections and inflammation. This review addresses the lacunae in host-microbiome research and highlights the importance of profiling them together to map their interactions while preserving their spatial context.

Spatial recovery of the murine gut microbiota after antibiotics perturbation

Bacterial communities are highly complex, with interaction networks dictating ecosystem function. Bacterial interactions are constrained by the spatial organization of these microbial communities, yet studying the spatial organization of microbial communities at the single-cell level has been technically challenging. Here, we use the recently developed high-phylogenetic-resolution microbiota mapping by fluorescence in situ hybridization technology to image the gut microbiota at the species and single-cell level. We simultaneously image 63 different bacterial species to spatially characterize the perturbation and recovery of the gut microbiota to ampicillin and vancomycin in the cecum and distal colon of mice. To decipher the biology in this complex imaging data, we developed an analytical framework to characterize the spatial changes of the gut microbiota to a perturbation. The three-tiered analytical approach includes image-level diversity, pairwise colocalization analysis, and hypothesis-driven neighborhood analysis. Through this workflow, we identify biogeographic and antibiotic-based differences in the spatial organization of the gut microbiota. We demonstrate that the cecal microbiota has increased micrometer-scale diversity than the colon at baseline and recovers better from perturbation. Also, we identify potential foundation and keystone species that have high baseline neighborhood richness and that are associated with recovery from antibiotics. Through this workflow, we add a spatial layer to the characterization of bacterial communities and progress toward a better understanding of bacterial interactions leading to improved microbiome modulation strategies.

IMPORTANCE

Antibiotics have broad off-target effects on the gut microbiome. When the microbial community is unable to recover from antibiotics, it can lead to increased susceptibility to gastrointestinal infections and increased risk of immunological and metabolic diseases. In this study, we work to better understand how the gut microbiota recovers from antibiotics by employing a recent technology to image the entire bacterial community at once. Through this approach, we characterize the spatial changes in the gut microbiota after treatment with model antibiotics in both the cecum and colon of mice. We find antibiotic- and biogeographic-dependent spatial changes between bacterial species and that many of these spatial colocalizations do not recover to baseline levels even 35 days after antibiotic administration.

Quantifying compositional variability in microbial communities with FAVA

Microbial communities vary across space, time, and individual hosts, presenting new challenges for the development of statistics measuring the variability of community composition. To understand differences across microbiome samples from different host individuals, sampling times, spatial locations, or experimental replicates, we present FAVA, a new normalized measure for characterizing compositional variability across multiple microbiome samples. FAVA quantifies variability across many samples of taxonomic or functional relative abundances in a single index ranging between 0 and 1, equaling 0 when all samples are identical and equaling 1 when each sample is entirely comprised of a single taxon. Its definition relies on the population-genetic statisticF S T , with samples playing the role of "populations" and taxa playing the role of "alleles." Its convenient mathematical properties allow users to compare disparate data sets. For example, FAVA values are commensurable across different numbers of taxonomic categories and different numbers of samples considered. We introduce extensions that incorporate phylogenetic similarity among taxa and spatial or temporal distances between samples. We illustrate how FAVA can be used to describe across-individual taxonomic variability in ruminant microbiomes at different regions along the gastrointestinal tract. In a second example, a longitudinal analysis of gut microbiomes of healthy human adults taking an antibiotic, we use FAVA to quantify the increase in temporal variability of microbiomes following the antibiotic course and to measure the duration of the antibiotic's influence on microbial variability. We have implemented this tool in an R package, FAVA, which can fit easily into existing pipelines for the analysis of microbial relative abundances.

A versatile tissue-rolling technique for spatial-omics analyses of the entire murine gastrointestinal tract

Tissues are dynamic and complex biological systems composed of specialized cell types that interact with each other for proper biological function. To comprehensively characterize and understand the cell circuitry underlying biological processes within tissues, it is crucial to preserve their spatial information. Here we report a simple mounting technique to maximize the area of the tissue to be analyzed, encompassing the whole length of the murine gastrointestinal (GI) tract, from mouth to rectum. Using this method, analysis of the whole murine GI tract can be performed in a single slide not only by means of histological staining, immunohistochemistry and in situ hybridization but also by multiplexed antibody staining and spatial transcriptomic approaches. We demonstrate the utility of our method in generating a comprehensive gene and protein expression profile of the whole GI tract by combining the versatile tissue-rolling technique with a cutting-edge transcriptomics method (Visium) and two cutting-edge proteomics methods (ChipCytometry and CODEX-PhenoCycler) in a systematic and easy-to-follow step-by-step procedure. The entire process, including tissue rolling, processing and sectioning, can be achieved within 2-3 d for all three methods. For Visium spatial transcriptomics, an additional 2 d are needed, whereas for spatial proteomics assays (ChipCytometry and CODEX-PhenoCycler), another 3-4 d might be considered. The whole process can be accomplished by researchers with skills in performing murine surgery, and standard histological and molecular biology methods.

Intraspecies warfare restricts strain coexistence in human skin microbiomes

Determining why only a fraction of encountered or applied bacterial strains engraft in a given person's microbiome is crucial for understanding and engineering these communities1. Previous work has established that metabolism can determine colonization success in vivo2-4, but relevance of bacterial warfare in preventing engraftment has been less explored. Here, we demonstrate that intraspecies warfare presents a significant barrier to strain transmission in the skin microbiome by profiling 14,884 pairwise interactions between Staphylococcus epidermidis cultured from eighteen human subjects from six families. We find that intraspecies antagonisms are abundant; these interactions are mechanistically diverse, independent of the relatedness between strains, and consistent with rapid evolution via horizontal gene transfer. Ability to antagonize more strains is associated with reaching a higher fraction of the on-person S. epidermidis community. Moreover, antagonisms are significantly depleted among strains residing on the same person relative to random assemblages. Two notable exceptions, in which bacteria evolved to become sensitive to antimicrobials found on the same host, are explained by mutations that provide phage resistance, contextualizing the importance of warfare among other lethal selective pressures. Taken together, our results emphasize that accounting for intraspecies bacterial warfare is essential to the design of long-lasting probiotic therapeutics.

Bacterial interactions on nutrient-rich surfaces in the gut lumen

The intestinal lumen is a turbulent, semi-fluid landscape where microbial cells and nutrient-rich particles are distributed with high heterogeneity. Major questions regarding the basic physical structure of this dynamic microbial ecosystem remain unanswered. Most gut microbes are non-motile, and it is unclear how they achieve optimum localization relative to concentrated aggregations of dietary glycans that serve as their primary source of energy. In addition, a random spatial arrangement of cells in this environment is predicted to limit sustained interactions that drive co-evolution of microbial genomes. The ecological consequences of random versus organized microbial localization have the potential to control both the metabolic outputs of the microbiota and the propensity for enteric pathogens to participate in proximity-dependent microbial interactions. Here, we review evidence suggesting that several bacterial species adopt organized spatial arrangements in the gut via adhesion. We highlight examples where localization could contribute to antagonism or metabolic interdependency in nutrient degradation, and we discuss imaging- and sequencing-based technologies that have been used to assess the spatial positions of cells within complex microbial communities.

Effect size of delayed freezing, diurnal variation, and hindgut location on the mouse fecal microbiome

Practical considerations in fecal sample collection for microbiome research include time to sample storage, time of collection, and hindgut position during terminal collections. Here, parallel experiments were performed to investigate the relative effect of these factors on microbiome composition in mice colonized with two different vendor-origin microbiomes. 16S rRNA amplicon sequencing of immediately flash-frozen feces showed no difference in alpha or beta diversity compared to samples incubated up to 9 h at room temperature. Samples collected in the morning showed greater alpha diversity compared to samples collected in the afternoon. While a significant effect of time was detected in all hindgut regions, the effect increased from cecum to distal colon. This study highlights common scenarios in microbiome research that may affect outcome measures of microbial community analysis. However, we demonstrate a relatively low effect size of these technical factors when compared to a primary experimental factor with large intergroup variability.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

Re-framing the importance of Group B Streptococcus as a gut-resident pathobiont

Streptococcus agalactiae (Group B Streptococcus, GBS) is a Gram-positive bacterial species that causes disease in humans across the lifespan. While antibiotics are used to mitigate GBS infections, it is evident that antibiotics disrupt human microbiomes (which can predispose people to other diseases later in life), and antibiotic resistance in GBS is on the rise. Taken together, these unintended negative impacts of antibiotics highlight the need for precision approaches for minimizing GBS disease. One possible approach involves selectively depleting GBS in its commensal niches before it can cause disease at other body sites or be transmitted to at-risk individuals. One understudied commensal niche of GBS is the adult gastrointestinal (GI) tract, which may predispose colonization at other body sites in individuals at risk for GBS disease. However, a better understanding of the host-, microbiome-, and GBS-determined variables that dictate GBS GI carriage is needed before precise GI decolonization approaches can be developed. In this review, we synthesize current knowledge of the diverse body sites occupied by GBS as a pathogen and as a commensal. We summarize key molecular factors GBS utilizes to colonize different host-associated niches to inform future efforts to study GBS in the GI tract. We also discuss other GI commensals that are pathogenic in other body sites to emphasize the broader utility of precise de-colonization approaches for mitigating infections by GBS and other bacterial pathogens. Finally, we highlight how GBS treatments could be improved with a more holistic understanding of GBS enabled by continued GI-focused study.

Emerging tools for uncovering genetic and transcriptomic heterogeneities in bacteria

Bacterial communities display an astonishing degree of heterogeneities among their constituent cells across both the genomic and transcriptomic levels, giving rise to diverse social interactions and stress-adaptation strategies indispensable for proliferating in the natural environment (Ackermann in Nat Rev Microbiol 13:497-508, 2015). Our knowledge about bacterial heterogeneities and their physiological ramifications critically depends on our ability to unambiguously resolve the genetic and phenotypic states of the individual cells that make up the population. In this short review, I highlight several recently developed methods for studying bacterial heterogeneities, primarily focusing on single-cell techniques based on advanced sequencing and microscopy technologies. I will discuss the working principle of each technique as well as the types of problems each technique is best positioned to address. With significant improvements in resolution and throughput, these emerging tools together offer unprecedented and complementary views of various types of heterogeneities found within bacterial populations, paving the way for mechanistic dissections and systematic interventions in laboratory and clinical settings.

The gut microbiota and its biogeography

Biogeography is the study of species distribution and diversity within an ecosystem and is at the core of how we understand ecosystem dynamics and interactions at the macroscale. In gut microbial communities, a historical reliance on bulk sequencing to probe community composition and dynamics has overlooked critical processes whereby microscale interactions affect systems-level microbiota function and the relationship with the host. In recent years, higher-resolution sequencing and novel single-cell level data have uncovered an incredible heterogeneity in microbial composition and have enabled a more nuanced spatial understanding of the gut microbiota. In an era when spatial transcriptomics and single-cell imaging and analysis have become key tools in mammalian cell and tissue biology, many of these techniques are now being applied to the microbiota. This fresh approach to intestinal biogeography has given important insights that span temporal and spatial scales, from the discovery of mucus encapsulation of the microbiota to the quantification of bacterial species throughout the gut. In this Review, we highlight emerging knowledge surrounding gut biogeography enabled by the observation and quantification of heterogeneity across multiple scales.

Micro-DeMix: A mixture beta-multinomial model for investigating the fecal microbiome compositions

Extensive research has uncovered the involvement of the human gut microbiome in various facets of human health, including metabolism, nutrition, physiology, and immune function. Researchers often study fecal microbiota as a proxy for understanding the gut microbiome. However, it has been demonstrated that this approach may not suffice to yield a comprehensive understanding of the entire gut microbial community. Emerging research is revealing the heterogeneity of the gut microbiome across different gastrointestinal (GI) locations in both composition and functions. While spatial metagenomics approach has been developed to address these variations in mice, limitations arise when applying it to human-subject research, primarily due to its invasive nature. With these restrictions, we introduce Micro-DeMix, a mixture beta-multinomial model that decomposes the fecal microbiome at compositional level to understand the heterogeneity of the gut microbiome across various GI locations and extract meaningful insights about the biodiversity of the gut microbiome. Moreover, Micro-DeMix facilitates the discovery of differentially abundant microbes between GI regions through a hypothesis testing framework. We utilize the Inflammatory Bowel Disease (IBD) data from the NIH Integrative Human Microbiome Project to demonstrate the effectiveness and efficiency of the proposed Micro-DeMix.

Insights into the composition and assembly mechanism of microbial communities on intertidal microsand grains

Introduction

Marine microorganisms are essential in marine ecosystems and have always been of interest. Currently, most marine microbial communities are studied at the bulk scale (millimeters to centimeters), and the composition, function and underlying assembly mechanism of microbial communities at the microscale (sub-100 micrometers) are unclear.

Methods

The microbial communities on microsand grains (40-100 µm, n = 150) from marine sediment were investigated and compared with those on macrosand grains (400-1000 µm, n = 60) and bulk sediments (n = 5) using amplicon sequencing technology.

Results

The results revealed a significant difference between microsand grains and macrosand grains. Microsand grains had lower numbers of operational taxonomic units (OTUs(97%)) and predicted functional genes than macrosand grains and bulk-scale samples. Microsand grains also showed greater intersample differences in the community composition and predicted functional genes than macrosand grains, suggesting a high level of heterogeneity of microbial communities at the microscale. Analyses based on ecological models indicated that stochastic processes dominated the assembly of microbial communities on sand grains. Consistently, cooccurrence network analyses showed that most microbial cooccurrence associations on sand grains were highly unstable. Metagenomic sequencing and further genome-scale metabolic modeling revealed that only a small number (1.3%) of microbe pairs showed high cooperative potential.

Discussion

This study explored the microbial community of marine sediments at the sub-100 µm scale, broadening the knowledge of the structure and assembly mechanism of marine microbial communities.

Spatial host-microbiome sequencing reveals niches in the mouse gut

Mucosal and barrier tissues, such as the gut, lung or skin, are composed of a complex network of cells and microbes forming a tight niche that prevents pathogen colonization and supports host-microbiome symbiosis. Characterizing these networks at high molecular and cellular resolution is crucial for understanding homeostasis and disease. Here we present spatial host-microbiome sequencing (SHM-seq), an all-sequencing-based approach that captures tissue histology, polyadenylated RNAs and bacterial 16S sequences directly from a tissue by modifying spatially barcoded glass surfaces to enable simultaneous capture of host transcripts and hypervariable regions of the 16S bacterial ribosomal RNA. We applied our approach to the mouse gut as a model system, used a deep learning approach for data mapping and detected spatial niches defined by cellular composition and microbial geography. We show that subpopulations of gut cells express specific gene programs in different microenvironments characteristic of regional commensal bacteria and impact host-bacteria interactions. SHM-seq should enhance the study of native host-microbe interactions in health and disease.

Genetic hypogonadal mouse model reveals niche-specific influence of reproductive axis and sex on intestinal microbial communities

BACKGROUND

The gut microbiome has been linked to many diseases with sex bias including autoimmune, metabolic, neurological, and reproductive disorders. While numerous studies report sex differences in fecal microbial communities, the role of the reproductive axis in this differentiation is unclear and it is unknown how sex differentiation affects microbial diversity in specific regions of the small and large intestine.

METHODS

We used a genetic hypogonadal mouse model that does not produce sex steroids or go through puberty to investigate how sex and the reproductive axis impact bacterial diversity within the intestine. Using 16S rRNA gene sequencing, we analyzed alpha and beta diversity and taxonomic composition of fecal and intestinal communities from the lumen and mucosa of the duodenum, ileum, and cecum from adult female (n = 20) and male (n = 20) wild-type mice and female (n = 17) and male (n = 20) hypogonadal mice.

RESULTS

Both sex and reproductive axis inactivation altered bacterial composition in an intestinal section and niche-specific manner. Hypogonadism was significantly associated with bacteria from the Bacteroidaceae, Eggerthellaceae, Muribaculaceae, and Rikenellaceae families, which have genes for bile acid metabolism and mucin degradation. Microbial balances between males and females and between hypogonadal and wild-type mice were also intestinal section-specific. In addition, we identified 3 bacterial genera (Escherichia Shigella, Lachnoclostridium, and Eggerthellaceae genus) with higher abundance in wild-type female mice throughout the intestinal tract compared to both wild-type male and hypogonadal female mice, indicating that activation of the reproductive axis leads to female-specific differentiation of the gut microbiome. Our results also implicated factors independent of the reproductive axis (i.e., sex chromosomes) in shaping sex differences in intestinal communities. Additionally, our detailed profile of intestinal communities showed that fecal samples do not reflect bacterial diversity in the small intestine.

CONCLUSIONS

Our results indicate that sex differences in the gut microbiome are intestinal niche-specific and that sampling feces or the large intestine may miss significant sex effects in the small intestine. These results strongly support the need to consider both sex and reproductive status when studying the gut microbiome and while developing microbial-based therapies.

Single-cell analysis and spatial resolution of the gut microbiome

Over the past decade it has become clear that various aspects of host physiology, metabolism, and immunity are intimately associated with the microbiome and its interactions with the host. Specifically, the gut microbiome composition and function has been shown to play a critical role in the etiology of different intestinal and extra-intestinal diseases. While attempts to identify a common pattern of microbial dysbiosis linked with these diseases have failed, multiple studies show that bacterial communities in the gut are spatially organized and that disrupted spatial organization of the gut microbiome is often a common underlying feature of disease pathogenesis. As a result, focus over the last few years has shifted from analyzing the diversity of gut microbiome by sequencing of the entire microbial community, towards understanding the gut microbiome in spatial context. Defining the composition and spatial heterogeneity of the microbiome is critical to facilitate further understanding of the gut microbiome ecology. Development in single cell genomics approach has advanced our understanding of microbial community structure, however, limitations in approaches exist. Single cell genomics is a very powerful and rapidly growing field, primarily used to identify the genetic composition of microbes. A major challenge is to isolate single cells for genomic analyses. This review summarizes the different approaches to study microbial genomes at single-cell resolution. We will review new techniques for microbial single cell sequencing and summarize how these techniques can be applied broadly to answer many questions related to the microbiome composition and spatial heterogeneity. These methods can be used to fill the gaps in our understanding of microbial communities.

Importance of Bacteroidetes in host-microbe interactions and ecosystem functioning

Bacteroidetes are prevalent in soil ecosystems and are associated with various eukaryotic hosts, including plants, animals, and humans. The ubiquity and diversity of Bacteroidetes exemplify their impressive versatility in niche adaptation and genomic plasticity. Over the past decade, a wealth of knowledge has been obtained on the metabolic functions of clinically relevant Bacteroidetes, but much less attention has been given to Bacteroidetes living in close association with plants. To improve our understanding of the functional roles of Bacteroidetes for plants and other hosts, we review the current knowledge of their taxonomy and ecology, in particular their roles in nutrient cycling and host fitness. We highlight their environmental distribution, stress resilience, genomic diversity, and functional importance in diverse ecosystems, including, but not limited to, plant-associated microbiomes.

spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content

Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.

The human gut phageome: composition, development, and alterations in disease

The human gastrointestinal tract is colonized by a large number of microorganisms, including bacteria, archaea, viruses, and eukaryotes. The bacterial community has been widely confirmed to have a significant impact on human health, while viruses, particularly phages, have received less attention. Phages are viruses that specifically infect bacteria. They are abundant in the biosphere and exist in a symbiotic relationship with their host bacteria. Although the application of high-throughput sequencing and bioinformatics technology has greatly improved our understanding of the genomic diversity, taxonomic composition, and spatio-temporal dynamics of the human gut phageome, there is still a large portion of sequencing data that is uncharacterized. Preliminary studies have predicted that the phages play a crucial role in driving microbial ecology and evolution. Prior to exploring the function of phages, it is necessary to address the obstacles that hinder establishing a comprehensive sequencing database with sufficient biological properties and understanding the impact of phage-bacteria interactions on human health. In this study, we provide an overview of the human gut phageome, including its composition, structure, and development. We also explore the various factors that may influence the phageome based on current research, including age, diet, ethnicity, and geographical location. Additionally, we summarize the relationship between the phageome and human diseases, such as IBD, IBS, obesity, diabetes, and metabolic syndrome.

Conditioning of the immune system by the microbiome

The human intestinal microbiome has coevolved with its host to establish a stable homeostatic relationship with hallmark features of mutualistic symbioses, yet the mechanistic underpinnings of host-microbiome interactions are incompletely understood. Thus, it is an opportune time to conceive a common framework for microbiome-mediated regulation of immune function. We propose the term conditioned immunity to describe the multifaceted mechanisms by which the microbiome modulates immunity. In this regard, microbial colonization is a conditioning exposure that has durable effects on immune function through the action of secondary metabolites, foreign molecular patterns, and antigens. Here, we discuss how spatial niches impact host exposure to microbial products at the level of dose and timing, which elicit diverse conditioned responses.

Moving beyond DNA: towards functional analysis of the vaginal microbiome by non-sequencing-based methods

Over the last two decades, sequencing-based methods have revolutionised our understanding of niche-specific microbial complexity. In the lower female reproductive tract, these approaches have enabled identification of bacterial compositional structures associated with health and disease. Application of metagenomics and metatranscriptomics strategies have provided insight into the putative function of these communities but it is increasingly clear that direct measures of microbial and host cell function are required to understand the contribution of microbe-host interactions to pathophysiology. Here we explore and discuss current methods and approaches, many of which rely upon mass-spectrometry, being used to capture functional insight into the vaginal mucosal interface. In addition to improving mechanistic understanding, these methods offer innovative solutions for the development of diagnostic and therapeutic strategies designed to improve women's health.

[Application of Droplet-Based Microfluidics in Microbial Research]

Droplet-based microfluidics is a technology that generates and manipulates highly uniform droplets, ranging from picoliter to nanoliter droplets, in microchannels under precise control. In biological research, each droplet can be used to encapsulate a small group of cells or even a single cell, and then serve as an individual container for biochemical reaction, which is well suited for high-throughput and high-resolution biochemical analysis. In the field of microbial research, from cultivation and identification of microbes to the investigation of the spatiotemporal dynamics of microbial communities, from precise quantitation of microbiota to systematic study of microbial interactions, and from the isolation of rare and unculturable microbes to the development of genetically engineered strains, droplet microfluidic technology has played an important promotional role in all these aspects. Droplet microfluidics shows potential for becoming a basic tool for exploring single-cell microbes in microbiological research. In this review, we gave a brief overview of the technical basis of droplet microfluidics. Then, we presented its latest applications in microbial research and had some discussions, aiming to provide a reference for relevant research on microorganisms.

"What I cannot create, I do not understand": elucidating microbe-microbe interactions to facilitate plant microbiome engineering

Plant-microbe interactions are important for both physiological and pathological processes. Despite the significance of plant-microbe interactions, microbe-microbe interactions themselves represent an important, complex, dynamic network that warrants deeper investigation. To understand how microbe-microbe interactions affect plant microbiomes, one approach is to systematically understand all the factors involved in successful engineering of a microbial community. This follows the physicist Richard Feynman's declaration: "what I cannot create, I do not understand". This review highlights recent studies that focus on aspects that we believe are important for building (ergo understanding) microbe-microbe interactions in the plant environment, including pairwise screening, intelligent application of cross-feeding models, spatial distributions of microbes, and understudied interactions between bacteria and fungi, phages, and protists. We offer a framework for systematic collection and centralized integration of data of plant microbiomes that could organize all the factors that can help ecologists understand microbiomes and help synthetic ecologists engineer beneficial microbiomes.

Spatial profiling of microbial communities by sequential FISH with error-robust encoding

Spatial analysis of microbiomes at single cell resolution with high multiplexity and accuracy has remained challenging. Here we present spatial profiling of a microbiome using sequential error-robust fluorescence in situ hybridization (SEER-FISH), a highly multiplexed and accurate imaging method that allows mapping of microbial communities at micron-scale. We show that multiplexity of RNA profiling in microbiomes can be increased significantly by sequential rounds of probe hybridization and dissociation. Combined with error-correction strategies, we demonstrate that SEER-FISH enables accurate taxonomic identification in complex microbial communities. Using microbial communities composed of diverse bacterial taxa isolated from plant rhizospheres, we apply SEER-FISH to quantify the abundance of each taxon and map microbial biogeography on roots. At micron-scale, we identify clustering of microbial cells from multiple species on the rhizoplane. Under treatment of plant metabolites, we find spatial re-organization of microbial colonization along the root and alterations in spatial association among microbial taxa. Taken together, SEER-FISH provides a useful method for profiling the spatial ecology of complex microbial communities in situ.

Microbiome and Human Health: Current Understanding, Engineering, and Enabling Technologies

The human microbiome is composed of a collection of dynamic microbial communities that inhabit various anatomical locations in the body. Accordingly, the coevolution of the microbiome with the host has resulted in these communities playing a profound role in promoting human health. Consequently, perturbations in the human microbiome can cause or exacerbate several diseases. In this Review, we present our current understanding of the relationship between human health and disease development, focusing on the microbiomes found across the digestive, respiratory, urinary, and reproductive systems as well as the skin. We further discuss various strategies by which the composition and function of the human microbiome can be modulated to exert a therapeutic effect on the host. Finally, we examine technologies such as multiomics approaches and cellular reprogramming of microbes that can enable significant advancements in microbiome research and engineering.

MetaTrass: A high-quality metagenome assembler of the human gut microbiome by cobarcoding sequencing reads

Metagenomic evidence of great genetic diversity within the nonconserved regions of the human gut microbial genomes appeals for new methods to elucidate the species-level variability at high resolution. However, current approaches cannot satisfy this methodologically challenge. In this study, we proposed an efficient binning-first-and-assembly-later strategy, named MetaTrass, to recover high-quality species-resolved genomes based on public reference genomes and the single-tube long fragment read (stLFR) technology, which enables cobarcoding. MetaTrass can generate genomes with longer contiguity, higher completeness, and lower contamination than those produced by conventional assembly-first-and-binning-later strategies. From a simulation study on a mock microbial community, MetaTrass showed the potential to improve the contiguity of assembly from kb to Mb without accuracy loss, as compared to other methods based on the next-generation sequencing technology. From four human fecal samples, MetaTrass successfully retrieved 178 high-quality genomes, whereas only 58 ones were provided by the optimal performance of other conventional strategies. Most importantly, these high-quality genomes confirmed the high level of genetic diversity among different samples and unveiled much more. MetaTrass was designed to work with metagenomic reads sequenced by stLFR technology, but is also applicable to other types of cobarcoding libraries. With the high capability of assembling high-quality genomes of metagenomic data sets, MetaTrass seeks to facilitate the study of spatial characters and dynamics of complex microbial communities at enhanced resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.

Can Red Yeast (Sporidiobolus pararoseus) Be Used as a Novel Feed Additive for Mycotoxin Binders in Broiler Chickens?

Mycotoxin-contaminated feeds may negatively affect broiler chickens’ health; hence, a sustainable approach to achieve mycotoxin elimination is necessary. This study aimed to evaluate the efficacy of red yeast (Sporidiobolus pararoseus; RY) as a novel mycotoxin binder in broilers. A total of 1440 one-week-old male broiler chicks were randomly assigned to 12 treatments in a 3 × 4 factorial design. The dietary treatments included three levels of mycotoxin-contaminated diets (0 µg kg−1 (0% of mycotoxin; MT), 50 µg kg−1 (50% MT), and 100 µg kg−1 (100% MT)) and four levels of mycotoxin binders (0.0 and 0.5 g kg−1 commercial binder, and 0.5 and 1.0 g kg−1 RY). Experimental diets were contaminated with aflatoxin B1, zearalenone, ochratoxin A, T-2 toxin, and deoxynivalenol in the basal diet. Furthermore, the parameters including feed intake, body weight, and mortality rate were recorded on a weekly basis. After feeding for 28 days, blood and organ samples were collected randomly to determine the blood biochemistry, relative organ weights, and gut health. The results indicated that mycotoxin-contaminated diets reduced the average daily weight gain (ADG), villus height (VH), and villus height per the crypt depth ratio (VH:CD) of the intestine, as well as the population of Lactobacillus sp. and Bifidobacterium sp. in the cecal (p < 0.05), whereas they increased the mycotoxins concentration in the blood samples and the apoptosis cells (TUNEL positive) in the liver tissue (p < 0.01) of broiler chicken. In contrast, RY-supplemented diets had better ADG values and lower chicken mortality rates (p < 0.05). Moreover, these combinations positively impacted the relative organ weights, blood parameters, bacteria population, intestinal morphology, and pathological changes in the hepatocytes (p < 0.05). In conclusion, RY supplementation effectively alleviated the toxicity that is induced by AFB1 and OTA, mainly, and could potentially be applied as a novel feed additive in the broiler industry.

Gastrointestinal Biogeography of Luminal Microbiota and Short-Chain Fatty Acids in Sika Deer (Cervus nippon)

The gut microbiota of sika deer has been widely investigated, but the spatial distribution of symbiotic microbes among physical niches in the gastrointestinal tract remains to be established. While feces are the most commonly used biological samples in these studies, the accuracy of fecal matter as a proxy of the microbiome at other gastrointestinal sites is as yet unknown. In the present study, luminal contents obtained along the longitudinal axis of deer gastrointestinal tract (rumen, reticulum, omasum, abomasum, small intestine, cecum, colon, and rectum) were subjected to 16S rRNA gene sequencing for profiling of the microbial composition, and samples from the rumen, small intestine, and cecum were subjected to metabolomic analysis to evaluate short-chain fatty acid (SCFA) profiles. Prevotella bacteria were the dominant gastric core microbes, while Christensenellaceae_R-7_group was predominantly observed in the intestine. While the eight gastrointestinal sites displayed variations in microbial diversity, abundance, and function, they could be clustered into stomach, small intestine, and large intestine segments, and the results further highlighted a specific microbial niche of the small intestine. SCFA levels in the rumen, small intestine, and cecum were significantly different, with Bacteroidetes and Spirochaetes were shown to play a critical role in SCFA production. Finally, the rectal microbial composition was significantly correlated with colonic and cecum communities but not those of the small intestine and four gastric sites. Quantification of the compositions and biogeographic relationships between gut microbes and SCFAs in sika deer should provide valuable insights into the interactions contributing to microbial functions and metabolites. IMPORTANCE Feces or specific segments of the gastrointestinal tract (in particular, the rumen) were sampled to explore the gut microbiome. The gastrointestinal biogeography of the luminal microbiota in ruminants, which is critical to guide accurate sampling for different purposes, is poorly understood at present. The microbial community of the rectal sample (as a proxy of fecal sample) showed higher correlation with those of other large intestinal sites relative to the small intestine or stomach, suggesting that the microbial composition is specifically shaped by the unique physiological characteristics of different gastrointestinal niches. In addition, significant differences in microbiomes and SCFAs were observed among the different gastrointestinal sites.

Gut Dysbiosis Promotes Preeclampsia by Regulating Macrophages and Trophoblasts

BACKGROUND

Preeclampsia is one of the leading causes of maternal and perinatal morbidity and is characterized by hypertension, inflammation, and placental dysfunction. Gut microbiota plays key roles in inflammation and hypertension. However, its roles and mechanisms in preeclampsia have not been fully elucidated.

METHODS

16S rRNA gene sequencing and targeted metabolomics were conducted on stool samples from 92 preeclamptic patients and 86 normal late-pregnant women. Then, fecal microbiota transplantation and in vitro and in vivo functional experiments were performed to explore the roles and mechanisms of gut microbiota in preeclampsia development.

RESULTS

We revealed the gut microbiota dysbiosis in preeclamptic patients, including significant reductions in short-chain fatty acid-producing bacteria and short-chain fatty acids. The gut microbiota of preeclamptic patients significantly exacerbated pathologies and symptoms of preeclamptic rats, whereas the gut microbiota of healthy pregnant women had significant protective effects. Akkermansia muciniphila, propionate, or butyrate significantly alleviated the symptoms of preeclamptic rats. Mechanistically, they significantly promoted autophagy and M2 polarization of macrophages in placental bed, thereby suppressing inflammation. Propionate also significantly promoted trophoblast invasion, thereby improved spiral arterial remodeling. Additionally, we identified a marker set consisting of Akkermansia, Oscillibacter, and short-chain fatty acids that could accurately diagnose preeclampsia.

CONCLUSIONS

Our study revealed that gut microbiota dysbiosis is an important etiology of preeclampsia. Gut microbiota and their active metabolites have great potential for the treatment and diagnosis of preeclampsia. Our findings enrich the gut-placenta axis theory and contribute to the development of microecological products for preeclampsia.

StrainPanDA: Linked reconstruction of strain composition and gene content profiles via pangenome-based decomposition of metagenomic data

Microbial strains of variable functional capacities coexist in microbiomes. Current bioinformatics methods of strain analysis cannot provide the direct linkage between strain composition and their gene contents from metagenomic data. Here we present Strain-level Pangenome Decomposition Analysis (StrainPanDA), a novel method that uses the pangenome coverage profile of multiple metagenomic samples to simultaneously reconstruct the composition and gene content variation of coexisting strains in microbial communities. We systematically validate the accuracy and robustness of StrainPanDA using synthetic data sets. To demonstrate the power of gene-centric strain profiling, we then apply StrainPanDA to analyze the gut microbiome samples of infants, as well as patients treated with fecal microbiota transplantation. We show that the linked reconstruction of strain composition and gene content profiles is critical for understanding the relationship between microbial adaptation and strain-specific functions (e.g., nutrient utilization and pathogenicity). Finally, StrainPanDA has minimal requirements for computing resources and can be scaled to process multiple species in a community in parallel. In short, StrainPanDA can be applied to metagenomic data sets to detect the association between molecular functions and microbial/host phenotypes to formulate testable hypotheses and gain novel biological insights at the strain or subspecies level.

Integrating Genome-Resolved Metagenomics with Trait-Based Process Modeling to Determine Biokinetics of Distinct Nitrifying Communities within Activated Sludge

Conventional bioprocess models for wastewater treatment are based on aggregated bulk biomass concentrations and do not incorporate microbial physiological diversity. Such a broad aggregation of microbial functional groups can fail to predict ecosystem dynamics when high levels of physiological diversity exist within trophic guilds. For instance, functional diversity among nitrite-oxidizing bacteria (NOB) can obfuscate engineering strategies for their out-selection in activated sludge (AS), which is desirable to promote energy-efficient nitrogen removal. Here, we hypothesized that different NOB populations within AS can have different physiological traits that drive process performance, which we tested by estimating biokinetic growth parameters using a combination of highly replicated respirometry, genome-resolved metagenomics, and process modeling. A lab-scale AS reactor subjected to a selective pressure for over 90 days experienced resilience of NOB activity. We recovered three coexisting Nitrospira population genomes belonging to two sublineages, which exhibited distinct growth strategies and underwent a compositional shift following the selective pressure. A trait-based process model calibrated at the NOB genus level better predicted nitrite accumulation than a conventional process model calibrated at the NOB guild level. This work demonstrates that trait-based modeling can be leveraged to improve our prediction, control, and design of functionally diverse microbiomes driving key environmental biotechnologies.

Historical contingencies and phage induction diversify bacterioplankton communities at the microscale

In many natural environments, microorganisms decompose microscale resource patches made of complex organic matter. The growth and collapse of populations on these resource patches unfold within spatial ranges of a few hundred micrometers or less, making such microscale ecosystems hotspots of heterotrophic metabolism. Despite the potential importance of patch-level dynamics for the large-scale functioning of heterotrophic microbial communities, we have not yet been able to delineate the ecological processes that control natural populations at the microscale. Here, we address this challenge by characterizing the natural marine communities that assembled on over 1,000 individual microscale particles of chitin, the most abundant marine polysaccharide. Using low-template shotgun metagenomics and imaging, we find significant variation in microscale community composition despite the similarity in initial species pools across replicates. Chitin-degrading taxa that were rare in seawater established large populations on a subset of particles, resulting in a wide range of predicted chitinolytic abilities and biomass at the level of individual particles. We show, through a mathematical model, that this variability can be attributed to stochastic colonization and historical contingencies affecting the tempo of growth on particles. We find evidence that one biological process leading to such noisy growth across particles is differential predation by temperate bacteriophages of chitin-degrading strains, the keystone members of the community. Thus, initial stochasticity in assembly states on individual particles, amplified through ecological interactions, may have significant consequences for the diversity and functionality of systems of microscale patches.

Material Engineering in Gut Microbiome and Human Health

Tremendous progress has been made in the past decade regarding our understanding of the gut microbiome's role in human health. Currently, however, a comprehensive and focused review marrying the two distinct fields of gut microbiome and material research is lacking. To bridge the gap, the current paper discusses critical aspects of the rapidly emerging research topic of "material engineering in the gut microbiome and human health." By engaging scientists with diverse backgrounds in biomaterials, gut-microbiome axis, neuroscience, synthetic biology, tissue engineering, and biosensing in a dialogue, our goal is to accelerate the development of research tools for gut microbiome research and the development of therapeutics that target the gut microbiome. For this purpose, state-of-the-art knowledge is presented here on biomaterial technologies that facilitate the study, analysis, and manipulation of the gut microbiome, including intestinal organoids, gut-on-chip models, hydrogels for spatial mapping of gut microbiome compositions, microbiome biosensors, and oral bacteria delivery systems. In addition, a discussion is provided regarding the microbiome-gut-brain axis and the critical roles that biomaterials can play to investigate and regulate the axis. Lastly, perspectives are provided regarding future directions on how to develop and use novel biomaterials in gut microbiome research, as well as essential regulatory rules in clinical translation. In this way, we hope to inspire research into future biomaterial technologies to advance gut microbiome research and gut microbiome-based theragnostics.

Micron-scale biogeography reveals conservative intra anammox bacteria spatial co-associations

Micron-scale resolution can help to reliably identify true taxon-taxon interactions in complex microbial communities. Despite widespread recognition of the critical role of metabolic interactions in anaerobic ammonium oxidation (anammox) system performance, no studies have examined microbial interactions at the micron-scale in anammox consortia. To fill this gap, we extensively sampled (totally 242 samples) the consortia of a lab-scale anammox reactor at different length scales, including bulk-scale (∼cm), macro-scale (300-500 µm) and micron-scale (70-100 µm). We firstly observed evident micron-scale heterogeneity in anammox consortia, with the relative abundance of anammox bacteria fluctuated greatly across individual clusters (2.0%-79.3%), indicating that the biotic interactions play a significant role in the assembly of anammox communities under well-controlled and well-mixed condition. Importantly, by mapping the spatial associations in anammox consortia at micron-scale, we demonstrated that the conserved co-associations for anammox bacteria were restricted to three different Brocadia species over time, and their co-associations with heterotrophs were random, implying that there was no statistically significant symbiotic interaction between anammox bacteria and other heterotrophic populations. Further metagenomic binning revealed that the quorum sensing with secondary messenger c-di-GMP potentially holding on the conservative metabolic cooperation among Brocadia species. These results shed new light on the social behavior of the anammox community. Overall, delineating of biological structures at micron-scale opens a new way of monitoring the microbial spatial structure and interactions, paving the way for improved community engineering of biotreatment systems.

Emergent evolutionary forces in spatial models of luminal growth and their application to the human gut microbiota

The genetic composition of the gut microbiota is constantly reshaped by ecological and evolutionary forces. These strain-level dynamics are challenging to understand because they depend on complex spatial growth processes that take place within a host. Here we introduce a population genetic framework to predict how stochastic evolutionary forces emerge from simple models of microbial growth in spatially extended environments like the intestinal lumen. Our framework shows how fluid flow and longitudinal variation in growth rate combine to shape the frequencies of genetic variants in simulated fecal samples, yielding analytical expressions for the effective generation times, selection coefficients, and rates of genetic drift. We find that over longer timescales, the emergent evolutionary dynamics can often be captured by well-mixed models that lack explicit spatial structure, even when there is substantial spatial variation in species-level composition. By applying these results to the human colon, we find that continuous fluid flow and simple forms of wall growth alone are unlikely to create sufficient bottlenecks to allow large fluctuations in mutant frequencies within a host. We also find that the effective generation times may be significantly shorter than expected from traditional average growth rate estimates. Our results provide a starting point for quantifying genetic turnover in spatially extended settings like the gut microbiota and may be relevant for other microbial ecosystems where unidirectional fluid flow plays an important role.

Spatial Resolution of Mycobacterium tuberculosis Bacteria and Their Surrounding Immune Environments Based on Selected Key Transcripts in Mouse Lungs

Mycobacterium tuberculosis (Mtb) bacilli are the causative agent of tuberculosis (TB), a major killer of mankind. Although it is widely accepted that local interactions between Mtb and the immune system in the tuberculous granuloma determine whether the outcome of infection is controlled or disseminated, these have been poorly studied due to methodological constraints. We have recently used a spatial transcriptomic technique, in situ sequencing (ISS), to define the spatial distribution of immune transcripts in TB mouse lungs. To further contribute to the understanding of the immune microenvironments of Mtb and their local diversity, we here present two complementary automated bacteria-guided analysis pipelines. These position 33 ISS-identified immune transcripts in relation to single bacteria and bacteria clusters. The analysis was applied on new ISS data from lung sections of Mtb-infected C57BL/6 and C3HeB/FeJ mice. In lungs from C57BL/6 mice early and late post infection, transcripts that define inflammatory macrophages were enriched at subcellular distances to bacteria, indicating the activation of infected macrophages. In contrast, expression patterns associated to antigen presentation were enriched in non-infected cells at 12 weeks post infection. T-cell transcripts were evenly distributed in the tissue. In Mtb-infected C3HeB/FeJ mice, transcripts characterizing activated macrophages localized in apposition to small bacteria clusters, but not in organized granulomas. Despite differences in the susceptibility to Mtb, the transcript patterns found around small bacteria clusters of C3HeB/FeJ and C57BL/6 mice were similar. Altogether, the presented tools allow us to characterize in depth the immune cell populations and their activation that interact with Mtb in the infected lung.

Disentangling host-microbiota complexity through hologenomics

Research on animal-microbiota interactions has become a central topic in biological sciences because of its relevance to basic eco-evolutionary processes and applied questions in agriculture and health. However, animal hosts and their associated microbial communities are still seldom studied in a systemic fashion. Hologenomics, the integrated study of the genetic features of a eukaryotic host alongside that of its associated microbes, is becoming a feasible - yet still underexploited - approach that overcomes this limitation. Acknowledging the biological and genetic properties of both hosts and microbes, along with the advantages and disadvantages of implemented techniques, is essential for designing optimal studies that enable some of the major questions in biology to be addressed.

Ruminococcus bromii enables the growth of proximal Bacteroides thetaiotaomicron by releasing glucose during starch degradation

Complex carbohydrates shape the gut microbiota, and the collective fermentation of resistant starch by gut microbes positively affects human health through enhanced butyrate production. The keystone species Ruminococcus bromii (Rb) is a specialist in degrading resistant starch; its degradation products are used by other bacteria including Bacteroides thetaiotaomicron (Bt). We analysed the metabolic and spatial relationships between Rb and Bt during potato starch degradation and found that Bt utilizes glucose that is released from Rb upon degradation of resistant potato starch and soluble potato amylopectin. Additionally, we found that Rb produces a halo of glucose around it when grown on solid media containing potato amylopectin and that Bt cells deficient for growth on potato amylopectin (∆sus Bt) can grow within the halo. Furthermore, when these ∆sus Bt cells grow within this glucose halo, they have an elongated cell morphology. This long-cell phenotype depends on the glucose concentration in the solid media: longer Bt cells are formed at higher glucose concentrations. Together, our results indicate that starch degradation by Rb cross-feeds other bacteria in the surrounding region by releasing glucose. Our results also elucidate the adaptive morphology of Bt cells under different nutrient and physiological conditions.

In situ analysis of variations of arsenicals, microbiome and transcriptome profiles along murine intestinal tract

In situ-based studies on microbiome-host interactions after arsenic exposure are few. In this study, the variations in arsenics, microbiota, and host genes along murine intestinal tracts were determined after arsenic exposure for two months. There was a gradual increase in the concentration of total As (C_tAs) in feces from ileum to colon, whereas C_tAs in the corresponding tissues were relatively stable. Differences in arsenic levels between feces and tissues were significantly different. The proportion of arsenite (iAs^Ⅲ) in feces gradually decreased, however, it gradually increased in tissues. After arsenic exposure, the diversity and abundance of microbial community and networks in each segment were significantly dysregulated. Notably, 328, 579 and 90 differently expressed genes were detected in ileum, cecum, and colon, respectively. In addition, microbiome and transcriptome analyses showed a significant correlation between the abundance of Faecalibaculum and expressions of Plb1, Hspa1b, Areg and Duoxa2 genes. This implies that they may be involved in arsenic biotransformation. In vitro experiments using Biofidobactrium and Lactobacillus showed that probiotics have arsenic transformation abilities. Therefore, gut microbiome may modulate arsenic accumulation, excretion and detoxification along the digestive tract. Moreover, the abundance and diversity of gut microbiome may be related to the changes in host health.

Gut microbial metabolome in inflammatory bowel disease: From association to therapeutic perspectives

Inflammatory bowel disease (IBD), comprising Crohn's disease (CD) and ulcerative colitis (UC), is a set of clinically chronic, relapsing gastrointestinal inflammatory disease and lacks of an absolute cure. Although the precise etiology is unknown, developments in high-throughput microbial genomic sequencing significantly illuminate the changes in the intestinal microbial structure and functions in patients with IBD. The application of microbial metabolomics suggests that the microbiota can influence IBD pathogenesis by producing metabolites, which are implicated as crucial mediators of host-microbial crosstalk. This review aims to elaborate the current knowledge of perturbations of the microbiome-metabolome interface in IBD with description of altered composition and metabolite profiles of gut microbiota. We emphasized and elaborated recent findings of several potentially protective metabolite classes in IBD, including fatty acids, amino acids and derivatives and bile acids. This article will facilitate a deeper understanding of the new therapeutic approach for IBD by applying metabolome-based adjunctive treatment.

A Novel Approach toward Less Invasive Multiomics Gut Analyses: a Pilot Study

Newer 'omics approaches, such as metatranscriptomics and metabolomics, allow functional assessments of the interaction(s) between the gut microbiome and the human host. However, in order to generate meaningful data with these approaches, the method of sample collection is critical. Prior studies have relied on expensive and invasive means toward sample acquisition, such as intestinal biopsy, while other studies have relied on easier methods of collection, such as fecal samples that do not necessarily represent those microbes in contact with the host. In this pilot study, we attempt to characterize a novel, minimally invasive method toward sampling the human microbiome using mucosal cytology brush sampling compared to intestinal gut biopsy samples on 5 healthy participants undergoing routine screening colonoscopy. We compared metatranscriptomic analyses between the two collection methods and identified increased taxonomic evenness and beta diversity in the cytology brush samples and similar community transcriptional profiles between the two methods. Metabolomics assessment demonstrated striking differences between the two methods, implying a difference in bacterial-derived versus human-absorbed metabolites. Put together, this study supports the use of microbiome sampling with cytology brushes, but caution must be exercised when performing metabolomics assessment, as this represents differential metabolite production but not absorption by the host. IMPORTANCE In order to generate meaningful metabolomic and microbiome data, the method of sample collection is critical. This study utilizes and compares two methods for intestinal tissue collection for evaluation of metabolites and microbiomes, finding that using a brush to sample the microbiome provides valuable data. However, for metabolomics assessment, biopsy samples may still be required.

Long-Term In Vitro Culture Systems to Study Human Microbiome

Microbial communities are eubiotic ecosystems that interact dynamically and synergistically with the human body. Imbalances in these interactions may cause dysbiosis by enhancing the occurrence of inflammatory conditions, such as periodontal or inflammatory bowel diseases. However, the mechanisms that lie behind eubiosis-dysbiosis transitions are still unclear and constantly being redefined. While the societal impact of these diseases is steadily increasing, the lack of a clear understanding behind the onset of the inflammatory conditions prevents the proper clinical strategies from being formulated. Although preclinical and clinical models and short-term planar in vitro cultures represent superb research tools, they are still lacking human relevance and long-term use. Bioreactors and organs-on-a-chip have attracted interest because of their ability to recreate and sustain the physical, structural, and mechanical features of the native environment, as well as to support long-term coculture of mammalian cells and the microbiome through modulation of pH and oxygen gradients. Existing devices, however, are still under development to sustain the microbiome-host coculture over long periods of time. In this scenario, to understand disease triggers and develop therapeutics, research efforts should command the development of three-dimensional constructs that would allow the investigation of processes underlying the microbial community assembly and how microorganisms influence host traits in both acute and chronic conditions.

High-throughput identification and quantification of single bacterial cells in the microbiota

The bacterial microbiota works as a community that consists of many individual organisms, i.e., cells. To fully understand the function of bacterial microbiota, individual cells must be identified; however, it is difficult with current techniques. Here, we develop a method, Barcoding Bacteria for Identification and Quantification (BarBIQ), which classifies single bacterial cells into taxa–named herein cell-based operational taxonomy units (cOTUs)–based on cellularly barcoded 16S rRNA sequences with single-base accuracy, and quantifies the cell number for each cOTU in the microbiota in a high-throughput manner. We apply BarBIQ to murine cecal microbiotas and quantify in total 3.4 × 10⁵ bacterial cells containing 810 cOTUs. Interestingly, we find location-dependent global differences in the cecal microbiota depending on the dietary vitamin A deficiency, and more differentially abundant cOTUs at the proximal location than the distal location. Importantly, these location differences are not clearly shown by conventional 16S rRNA gene-amplicon sequencing methods, which quantify the 16S rRNA genes, not the cells. Thus, BarBIQ enables microbiota characterization with the identification and quantification of individual constituent bacteria, which is a cornerstone for microbiota studies.

Here, Jin et al., develop a method called Barcoding Bacteria for Identification and Quantification (BarBIQ), which allows to both characterize the global microbiome and to identify and quantify single-cell bacterial members in a high-throughput manner.

Spatial-temporal dynamics of a microbial cooperative behavior resistant to cheating

Much of our understanding of bacterial behavior stems from studies in liquid culture. In nature, however, bacteria frequently live in densely packed spatially-structured communities. How does spatial structure affect bacterial cooperative behaviors? In this work, we examine rhamnolipid production—a cooperative and virulent behavior of Pseudomonas aeruginosa. Here we show that, in striking contrast to well-mixed liquid culture, rhamnolipid gene expression in spatially-structured colonies is strongly associated with colony specific growth rate, and is impacted by perturbation with diffusible quorum signals. To interpret these findings, we construct a data-driven statistical inference model which captures a length-scale of bacterial interaction that develops over time. Finally, we find that perturbation of P. aeruginosa swarms with quorum signals preserves the cooperating genotype in competition, rather than creating opportunities for cheaters. Overall, our data demonstrate that the complex response to spatial localization is key to preserving bacterial cooperative behaviors.

Bacteria often live in densely packed, spatially-structured communities; however, much of our understanding of their behavior stems from studies in liquid culture. Here, Monaco et al. show how spatial structure and quorum sensing modulate a cooperative behavior in colonies of Pseudomonas aeruginosa.

It's the Economy, Stupid: Applying (Micro)economic Principles to Microbiome Science

A key challenge in microbiome science is the scale mismatch problem, which arises when the scale at which microbial communities are sampled, interrogated, and averaged is different from the scale at which individual microorganisms within those communities interact with each other and with their environment. Profiling the microbial communities in a teaspoon of soil, from a scoop of fecal matter, or along a plant leaf surface represents a scale mismatch of multiple orders of magnitude, which may limit our ability to interpret or predict species interactions and community assembly within such samples. In this Perspective, we explore how economists, who are historically and topically split along the lines of micro- and macroeconomics, deal with the scale mismatch problem, and how taking clues from (micro)economists could benefit the field of microbiomics.

Altered microbial biogeography in an innate model of colitis

Changes in the spatial organization, or biogeography, of colonic microbes have been observed in human inflammatory bowel disease (IBD) and mouse models of IBD. We have developed a mouse model of IBD that occurs spontaneously and consistently in the absence of adaptive immunity. Mice expressing tumor necrosis factor-induced protein 3 (TNFAIP3) in intestinal epithelial cells (villin-TNFAIP3) develop colitis when interbred with Recombination Activating 1-deficient mice (RAG1^-/-). The colitis in villin-TNFAIP3 × RAG1^-/- (TRAG) mice is prevented by antibiotics, indicating a role for microbes in this innate colitis. We therefore explored the biogeography of microbes and responses to antibiotics in TRAG colitis. Laser capture microdissection and 16S rRNA sequencing revealed altered microbial populations across the transverse axis of the colon as the inner mucus layer of TRAG, but not RAG1^-/-, mice was infiltrated by microbes, which included increased abundance of the classes Gammaproteobacteria and Actinobacteria. Along the longitudinal axis differences in the efficacy of antibiotics to prevent colitis were evident. Neomycin was most effective for prevention of inflammation in the cecum, while ampicillin was most effective in the proximal and distal colon. RAG1^-/-, but not TRAG, mice exhibited a structured pattern of bacterial abundance with decreased Firmicutes and Proteobacteria but increased Bacteroidetes along the proximal to distal axis of the gut. TRAG mice exhibited increased relative abundance of potential pathobionts including <i>Bifidobacterium animalis</i> along the longitudinal axis of the gut whereas others, like <i>Helicobacter hepaticus</i> were increased only in the cecum. Potential beneficial organisms including <i>Roseburia</i> were decreased in the proximal regions of the TRAG colon, while <i>Bifidobacterium pseudolongulum</i> was decreased in the TRAG distal colon. Thus, the innate immune system maintains a structured, spatially organized, gut microbiome along the transverse and longitudinal axis of the gut, and disruption of this biogeography is a feature of innate immune colitis.

Combinatorial Click Chemistry Labeling to Study Live Human Gut-Derived Microbiota Communities

Gut bacteria were shown to exert pivotal effects on health and disease. However, mechanistic studies of gut bacterial communities are limited due to the lack of technologies for real-time studies on live bacteria. Here, we developed COMBInatorial cliCK-chemistry (COMBICK) labeling on human gut-derived bacteria, both aerobic and anaerobic strains, to enable dynamic tracing of live, heterogeneous bacterial communities on the strain level, including clinical isolates of the Enterobacteriaceae family. We further show that COMBICK labeling is applicable on anaerobic bacterial strains directly isolated from stool. In COMBICK, the number of labeled bacteria that can be simultaneously differentiated increases exponentially depending on the availability of fluorophores and machine capabilities. This method allows real-time studies of bacterial communities from a variety of ecosystems, and can significantly advance mechanistic research in the microbiome field.

Directional Gaussian Mixture Models of the Gut Microbiome Elucidate Microbial Spatial Structure

The gut microbiome is spatially heterogeneous, with environmental niches contributing to the distribution and composition of microbial populations. A recently developed mapping technology, MaPS-seq, aims to characterize the spatial organization of the gut microbiome by providing data about local microbial populations. However, information about the global arrangement of these populations is lost by MaPS-seq. To address this, we propose a class of Gaussian mixture models (GMM) with spatial dependencies between mixture components in order to computationally recover the relative spatial arrangement of microbial communities. We demonstrate on synthetic data that our spatial models can identify global spatial dynamics, accurately cluster data, and improve parameter inference over a naive GMM. We applied our model to three MaPS-seq data sets taken from various regions of the mouse intestine. On cecal and distal colon data sets, we find our model accurately recapitulates known spatial behaviors of the gut microbiome, including compositional differences between mucus and lumen-associated populations. Our model also seems to capture the role of a pH gradient on microbial populations in the mouse ileum and proposes new behaviors as well. IMPORTANCE The spatial arrangement of the microbes in the gut microbiome is a defining characteristic of its behavior. Various experimental studies have attempted to provide glimpses into the mechanisms that contribute to microbial arrangements. However, many of these descriptions are qualitative. We developed a computational method that takes microbial spatial data and learns many of the experimentally validated spatial factors. We can then use our model to propose previously unknown spatial behaviors. Our results demonstrate that the gut microbiome, while exceptionally large, has predictable spatial patterns that can be used to help us understand its role in health and disease.