Adaptive Evolution within Gut Microbiomes of Healthy People

Phenotyping of Fecal Microbiota of Winnie, a Rodent Model of Spontaneous Chronic Colitis, Reveals Specific Metabolic, Genotoxic, and Pro-inflammatory Properties

Winnie, a mouse carrying a missense mutation in the MUC2 mucin gene, is a valuable model for inflammatory bowel disease (IBD) with signs and symptoms that have multiple similarities with those observed in patients with ulcerative colitis. MUC2 mucin is present in Winnie, but is not firmly compacted in a tight inner layer. Indeed, these mice develop chronic intestinal inflammation due to the primary epithelial defect with signs of mucosal damage, including thickening of muscle and mucosal layers, goblet cell loss, increased intestinal permeability, enhanced susceptibility to luminal inflammation-inducing toxins, and alteration of innervation in the distal colon. In this study, we show that the intestinal environment of the Winnie mouse, genetically determined by MUC2 mutation, selects an intestinal microbial community characterized by specific pro-inflammatory, genotoxic, and metabolic features that could imply a direct involvement in the pathogenesis of chronic intestinal inflammation. We report results obtained by using a variety of in vitro approaches for fecal microbiota functional characterization. These approaches include Caco-2 cell cultures and Caco-2/THP-1 cell co-culture models for evaluation of geno-cytotoxic and pro-inflammatory properties using a panel of 43 marker RNAs assayed by RT-qPCR, and cell-based phenotypic testing for metabolic profiling of the intestinal microbial communities by Biolog EcoPlates. While adding a further step towards understanding the etiopathogenetic mechanisms underlying IBD, the results of this study provide a reliable method for phenotyping gut microbial communities, which can complement their structural characterization by providing novel functional information.

Time for Some Group Therapy: Update on Identification, Antimicrobial Resistance, Taxonomy, and Clinical Significance of the Bacteroides fragilis Group

Bacteroides fragilis group (BFG) species are common members of the human microbiota that provide several benefits to healthy hosts, yet BFG are also the most common anaerobes isolated from human infections, including intra-abdominal infections, abscesses, and bloodstream infection. Compared to many other anaerobes associated with disease, members of the BFG are more likely to be resistant to commonly used antimicrobials, including penicillin (>90% resistant), carbapenems (2 to 20% resistant), and metronidazole (0.2 to 4% resistant). As a result, infection with BFG bacteria can be associated with poor clinical outcomes. Here, we discuss the role of BFG in human health and disease, proposed taxonomic reclassifications within the BFG, and updates in methods for species-level identification. The increasing availability of whole-genome sequencing (WGS) supports recent proposals that the BFG now span two families (Bacteroidaceae and "Tannerellaceae") and multiple genera (Bacteroides, Parabacteroides, and Phocaeicola) within the phylum Bacteroidota. While members of the BFG are often reported to "group" rather than "species" level in many clinical settings, new reports of species-specific trends in antimicrobial resistance profiles and improved resolution of identification tools support routine species-level reporting in clinical practice. Empirical therapy may not be adequate for treatment of serious infections with BFG, warranting susceptibility testing for serious infections. We summarize methods for antimicrobial susceptibility testing and resistance prediction for BFG, including broth microdilution, agar dilution, WGS, and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). We examine global trends in BFG antimicrobial resistance and review genomics of BFG, revealing insights into rapid activation and dissemination of numerous antimicrobial resistance mechanisms.

High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome

Characterizing complex microbial communities with single-cell resolution has been a long-standing goal of microbiology. We present Microbe-seq, a high-throughput method that yields the genomes of individual microbes from complex microbial communities. We encapsulate individual microbes in droplets with microfluidics and liberate their DNA, which we then amplify, tag with droplet-specific barcodes, and sequence. We explore the human gut microbiome, sequencing more than 20,000 microbial single-amplified genomes (SAGs) from a single human donor and coassembling genomes of almost 100 bacterial species, including several with multiple subspecies strains. We use these genomes to probe microbial interactions, reconstructing the horizontal gene transfer (HGT) network and observing HGT between 92 species pairs; we also identify a significant in vivo host-phage association between crAssphage and one strain of Bacteroides vulgatus. Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution.

The developing infant gut microbiome: A strain-level view

At birth, neonates provide a vast habitat awaiting microbial colonization. Microbiome assembly is a complex process involving microbial seeding and succession driven by ecological forces and subject to environmental conditions. These successional events not only significantly affect the ecology and function of the microbiome, but also impact host health. While the establishment of the infant microbiome has been a point of interest for decades, an integrated view focusing on strain level colonization has been lacking until recently. Technological and computational advancements enabling strain-level analyses of the infant microbiome have demonstrated the immense complexity of this system and allowed for an improved understanding of how strains of the same species spread, colonize, evolve, and affect the host. Here, we review the current knowledge of the establishment and maturation of the infant gut microbiome with particular emphasis on newer discoveries achieved through strain-centric analyses.

Rapid evolution and strain turnover in the infant gut microbiome

While the ecological dynamics of the infant gut microbiome have been intensely studied, relatively little is known about evolutionary dynamics in the infant gut microbiome. Here we analyze longitudinal fecal metagenomic data from >700 infants and their mothers over the first year of life and find that the evolutionary dynamics in infant gut microbiomes are distinct from that of adults. We find evidence for more than 10-fold increase in the rate of evolution and strain turnover in the infant gut compared to healthy adults, with the mother-infant transition at delivery being a particularly dynamic period in which gene loss dominates. Within a few months after birth, these dynamics stabilize, and gene gains become increasingly frequent as the microbiome matures. We furthermore find that evolutionary changes in infants show signatures of being seeded by a mixture of de novo mutations and transmissions of pre-evolved lineages from the broader family. Several of these evolutionary changes occur in parallel across infants, highlighting candidate genes that may play important roles in the development of the infant gut microbiome. Our results point to a picture of a volatile infant gut microbiome characterized by rapid evolutionary and ecological change in the early days of life.

Eco-Evolutionary Dynamics of the Human-Gut Microbiota Symbiosis in a Changing Nutritional Environment

The operational harmony between living beings and their circumstances, their ever-changing environment, is a constitutive condition of their existence. Nutrition and symbiosis are two essential aspects of this harmony. Disruption of the symbiosis between host and gut microbiota, the so-called dysbiosis, as well as the inadequate diet from which it results, contribute to the etiology of immunometabolic disorders. Research into the development of these diseases is highly influenced by our understanding of the evolutionary roots of metabolic functioning, thereby considering that chronic non-communicable diseases arise from an evolutionary mismatch. However, the lens has been mostly directed toward energy availability and metabolism, but away from our closest environmental factor, the gut microbiota. Thus, this paper proposes a narrative thread that places symbiosis in an evolutionary perspective, expanding the traditional framework of humans’ adaptation to their food environment.

State of Residency: Microbial Strain Diversity in the Skin

Human skin hosts a diversity of microbiota. Advances in sequencing and analytical methods have increasingly illuminated the importance of the finest resolution in understanding the genetic diversity of the skin microbiota, highlighting strain-level differences and their functional implications. Such genetic diversity, which exists within an individual and is strongly individual specific underscores the difficulty in elucidating functionality. Integrated investigations of the microbial strain diversity through sequencing and culture-based approaches with host immunology and physiology will be critical in expanding our understanding of the roles of the skin microbiome.

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas

Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

Microbiota dynamics in a randomized trial of gut decontamination during allogeneic hematopoietic cell transplantation

BACKGROUNDGut decontamination (GD) can decrease the incidence and severity of acute graft-versus-host disease (aGVHD) in murine models of allogeneic hematopoietic cell transplantation (HCT). In this pilot study, we examined the impact of GD on gut microbiome composition and the incidence of aGVHD in HCT patients.METHODSWe randomized 20 patients undergoing allogeneic HCT to receive (GD) or not receive (no-GD) oral vancomycin-polymyxin B from day -5 through neutrophil engraftment. We evaluated shotgun metagenomic sequencing of serial stool samples to compare the composition and diversity of the gut microbiome between study arms. We assessed clinical outcomes in the 2 arms and performed strain-specific analyses of pathogens that caused bloodstream infections (BSI).RESULTSThe 2 arms did not differ in the predefined primary outcome of Shannon diversity of the gut microbiome at 2 weeks post-HCT (genus, P = 0.8; species, P = 0.44) or aGVHD incidence (P = 0.58). Immune reconstitution of T cell and B cell subsets was similar between groups. Five patients in the no-GD arm had 8 BSI episodes versus 1 episode in the GD arm (P = 0.09). The BSI-causing pathogens were traceable to the gut in 7 of 8 BSI episodes in the no-GD arm, including Staphylococcus species.CONCLUSIONWhile GD did not differentially affect Shannon diversity or clinical outcomes, our findings suggest that GD may protect against gut-derived BSI in HCT patients by decreasing the prevalence or abundance of gut pathogens.TRIAL REGISTRATIONClinicalTrials.gov NCT02641236.FUNDINGNIH, Damon Runyon Cancer Research Foundation, V Foundation, Sloan Foundation, Emerson Collective, and Stanford Maternal & Child Health Research Institute.

Eco-evolutionary responses of the microbial loop to surface ocean warming and consequences for primary production

Predicting the response of ocean primary production to climate warming is a major challenge. One key control of primary production is the microbial loop driven by heterotrophic bacteria, yet how warming alters the microbial loop and its function is poorly understood. Here we develop an eco-evolutionary model to predict the physiological response and adaptation through selection of bacterial populations in the microbial loop and how this will impact ecosystem function such as primary production. We find that the ecophysiological response of primary production to warming is driven by a decrease in regenerated production which depends on nutrient availability. In nutrient-poor environments, the loss of regenerated production to warming is due to decreasing microbial loop activity. However, this ecophysiological response can be opposed or even reversed by bacterial adaptation through selection, especially in cold environments: heterotrophic bacteria with lower bacterial growth efficiency are selected, which strengthens the "link" behavior of the microbial loop, increasing both new and regenerated production. In cold and rich environments such as the Arctic Ocean, the effect of bacterial adaptation on primary production exceeds the ecophysiological response. Accounting for bacterial adaptation through selection is thus critically needed to improve models and projections of the ocean primary production in a warming world.

Comparative Genomics of Bacteroides fragilis Group Isolates Reveals Species-Dependent Resistance Mechanisms and Validates Clinical Tools for Resistance Prediction

Bacteroides fragilis group (BFG) are the most frequently recovered anaerobic bacteria from human infections, and resistance to frontline antibiotics is emerging. In the absence of routine antimicrobial susceptibility testing (AST) for BFG in most clinical settings, we assessed the utility of clinical and modern genomics tools to determine BFG species-level identification and resistance patterns. A total of 174 BFG clinical isolates supplemented with 20 archived carbapenem-resistant B. fragilis sensu stricto (BFSS) isolates underwent antimicrobial susceptibility testing, MALDI-ToF mass-spectrometry, and whole-genome sequencing (WGS). Bruker BioTyper and VITEK-MS MALDI-ToF systems demonstrated accurate species-level identifications (91% and 90% agreement, respectively) compared to average nucleotide identity (ANI) analysis of WGS data. Distinct β-lactamase gene profiles were observed between BFSS and non-fragilis Bacteroides species, with significantly higher MICs to piperacillin-tazobactam in B. vulgatus and B. thetaiotaomicron relative to BFSS (P ≤ 0.034). We also uncovered phylogenetic diversity at the genomospecies level between division I and division II BFSS (ANI <0.95) and demonstrate that division II BFSS strains harbor an increased capacity to achieve carbapenem resistance through chromosomal activation of the CfiA carbapenemase. Finally, we report that CfiA detection by the Bruker BioTyper Subtyping Module accurately detected carbapenem resistance in BFSS with positive and negative percent agreement of 94%/90% and 95%/95% compared to ertapenem and meropenem susceptibility, respectively. These comparative analyses indicate that resistance mechanisms are distinct at both the phenotypic and genomic level across species within the BFG and that modern MALDI-ToF identification systems can be used for accurate species-level identification and resistance prediction of the BFG. IMPORTANCE Anaerobic infections present unique challenges in terms of detecting and identifying the etiologic agent and selecting the optimal antimicrobial therapy. Antimicrobial resistance is increasing in anaerobic pathogens, and it is critical to understand the prevalence and mechanisms of resistance to commonly prescribed antimicrobial therapies. This study uses comparative genomics to validate clinical tools for species-level identification and phenotypic resistance prediction in 194 isolates of Bacteroides fragilis group (BFG) bacteria, which represent the most commonly isolated organisms among anaerobic infections. We demonstrate species-specific patterns in antimicrobial resistance and validate new strategies for species-level organism identification and phenotypic resistance prediction in a routine clinical laboratory setting. These findings expand our understanding and management of anaerobic infections and justify further investigations into the molecular basis for species-specific resistance patterns observed within this study.

Anatomy promotes neutral coexistence of strains in the human skin microbiome

What enables strains of the same species to coexist in a microbiome? Here, we investigate whether host anatomy can explain strain co-residence of Cutibacterium acnes, the most abundant species on human skin. We reconstruct on-person evolution and migration using whole-genome sequencing of C. acnes colonies acquired from healthy subjects, including from individual skin pores, and find considerable spatial structure at the level of pores. Although lineages (sets of colonies separated by <100 mutations) with in vitro fitness differences coexist within centimeter-scale regions, each pore is dominated by a single lineage. Moreover, colonies from a pore typically have identical genomes. An absence of adaptive signatures suggests a genotype-independent source of low within-pore diversity. We therefore propose that pore anatomy imposes random single-cell bottlenecks; the resulting population fragmentation reduces competition and promotes coexistence. Our findings suggest that therapeutic interventions involving pore-dwelling species might focus on removing resident populations over optimizing probiotic fitness.

Microbial Evolution: An overlooked biomarker of host diet

The evolutionary dynamics of gut microbiota are still being explored. In this issue of Cell Host & Microbe, Dapa et al. conduct an experimental evolution study in mice to track the rapid adaptation of the gut microbiome based on host diet.

Polysaccharide utilization loci in Bacteroides determine population fitness and community-level interactions

Polysaccharide utilization loci (PULs) are co-regulated bacterial genes that sense nutrients and enable glycan digestion. Human gut microbiome members, notably Bacteroides, contain numerous PULs that enable glycan utilization and shape ecological dynamics. To investigate the role of PULs on fitness and inter-species interactions, we develop a CRISPR-based genome editing tool to study 23 PULs in Bacteroides uniformis (BU). BU PULs show distinct glycan-degrading functions and transcriptional coordination that enables the population to adapt upon loss of other PULs. Exploiting a BU mutant barcoding strategy, we demonstrate that in vitro fitness and BU colonization in the murine gut are enhanced by deletion of specific PULs and modulated by glycan availability. PULs mediate glycan-dependent interactions with butyrate producers that depend on the degradation mechanism and glycan utilization ability of the butyrate producer. Thus, PULs determine community dynamics and butyrate production and provide a selective advantage or disadvantage depending on the nutritional landscape.

Interactions between strains govern the eco-evolutionary dynamics of microbial communities

Genomic data has revealed that genotypic variants of the same species, that is, strains, coexist and are abundant in natural microbial communities. However, it is not clear if strains are ecologically equivalent, and at what characteristic genetic distance they might exhibit distinct interactions and dynamics. Here, we address this problem by tracking 10 taxonomically diverse microbial communities from the pitcher plant Sarracenia purpurea in the laboratory for more than 300 generations. Using metagenomic sequencing, we reconstruct their dynamics over time and across scales, from distant phyla to closely related genotypes. We find that most strains are not ecologically equivalent and exhibit distinct dynamical patterns, often being significantly more correlated with strains from another species than their own. Although even a single mutation can affect laboratory strains, on average, natural strains typically decouple in their dynamics beyond a genetic distance of 100 base pairs. Using mathematical consumer-resource models, we show that these taxonomic patterns emerge naturally from ecological interactions between community members, but only if the interactions are coarse-grained at the level of strains, not species. Finally, by analyzing genomic differences between strains, we identify major functional hubs such as transporters, regulators, and carbohydrate-catabolizing enzymes, which might be the basis for strain-specific interactions. Our work suggests that fine-scale genetic differences in natural communities could be created and stabilized via the rapid diversification of ecological interactions between strains.

Genetically stable CRISPR-based kill switches for engineered microbes

Microbial biocontainment is an essential goal for engineering safe, next-generation living therapeutics. However, the genetic stability of biocontainment circuits, including kill switches, is a challenge that must be addressed. Kill switches are among the most difficult circuits to maintain due to the strong selection pressure they impart, leading to high potential for evolution of escape mutant populations. Here we engineer two CRISPR-based kill switches in the probiotic Escherichia coli Nissle 1917, a single-input chemical-responsive switch and a 2-input chemical- and temperature-responsive switch. We employ parallel strategies to address kill switch stability, including functional redundancy within the circuit, modulation of the SOS response, antibiotic-independent plasmid maintenance, and provision of intra-niche competition by a closely related strain. We demonstrate that strains harboring either kill switch can be selectively and efficiently killed inside the murine gut, while strains harboring the 2-input switch are additionally killed upon excretion. Leveraging redundant strategies, we demonstrate robust biocontainment of our kill switch strains and provide a template for future kill switch development.

Diet leaves a genetic signature in a keystone member of the gut microbiota

Switching from a low-fat and high-fiber diet to a Western-style high-fat and high-sugar diet causes microbiota imbalances that underlay many pathological conditions (i.e., dysbiosis). Although the effects of dietary changes on microbiota composition and functions are well documented, their impact in gut bacterial evolution remains unexplored. We followed the emergence of mutations in Bacteroides thetaiotaomicron, a prevalent fiber-degrading microbiota member, upon colonization of the murine gut under different dietary regimens. B. thetaiotaomicron evolved rapidly in the gut and Western-style diet selected for mutations that promote degradation of mucin-derived glycans. Periodic dietary changes caused fluctuations in the frequency of such mutations and were associated with metabolic shifts, resulting in the maintenance of higher intraspecies genetic diversity compared to constant dietary regimens. These results show that dietary changes leave a genetic signature in microbiome members and suggest that B. thetaiotaomicron genetic diversity could be a biomarker for dietary differences among individuals.

Comparative Population Genetics in the Human Gut Microbiome

Genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of coexisting species in the microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we reanalyze patterns of purifying selection across ∼40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

Symbiosis in Digital Evolution: Past, Present, and Future

Symbiosis, the living together of unlike organisms as symbionts, is ubiquitous in the natural world. Symbioses occur within and across all scales of life, from microbial to macro-faunal systems. Further, the interactions between symbionts are multimodal in both strength and type, can span from parasitic to mutualistic within one partnership, and persist over generations. Studying the ecological and evolutionary dynamics of symbiosis in natural or laboratory systems poses a wide range of challenges, including the long time scales at which symbioses evolve de novo, the limited capacity to experimentally control symbiotic interactions, the weak resolution at which we can quantify interactions, and the idiosyncrasies of current model systems. These issues are especially challenging when seeking to understand the ecological effects and evolutionary pressures on and of a symbiosis, such as how a symbiosis may shift between parasitic and mutualistic modes and how that shift impacts the dynamics of the partner population. In digital evolution, populations of computational organisms compete, mutate, and evolve in a virtual environment. Digital evolution features perfect data tracking and allows for experimental manipulations that are impractical or impossible in natural systems. Furthermore, modern computational power allows experimenters to observe thousands of generations of evolution in minutes (as opposed to several months or years), which greatly expands the range of possible studies. As such, digital evolution is poised to become a keystone technique in our methodological repertoire for studying the ecological and evolutionary dynamics of symbioses. Here, we review how digital evolution has been used to study symbiosis, and we propose a series of open questions that digital evolution is well-positioned to answer.

Unraveling differences in fecal microbiota stability in mammals: from high variable carnivores and consistently stable herbivores

Background

Through the rapid development in DNA sequencing methods and tools, microbiome studies on a various number of species were performed during the last decade. This advance makes it possible to analyze hundreds of samples from different species at the same time in order to obtain a general overview of the microbiota. However, there is still uncertainty on the variability of the microbiota of different animal orders and on whether certain bacteria within a species are subject to greater fluctuations than others. This is largely due to the fact that the analysis in most extensive comparative studies is based on only a few samples per species or per study site. In our study, we aim to close this knowledge gap by analyzing multiple individual samples per species including two carnivore suborders Canoidea and Feloidea as well as the orders of herbivore Perissodactyla and Artiodactyla held in different zoos. To assess microbial diversity, 621 fecal samples from 31 species were characterized by sequencing the V3–V4 region of the 16S rRNA gene using Illumina MiSeq.

Results

We found significant differences in the consistency of microbiota composition and in fecal microbial diversity between carnivore and herbivore species. Whereas the microbiota of Carnivora is highly variable and inconsistent within and between species, Perissodactyla and Ruminantia show fewer differences across species boundaries. Furthermore, low-abundance bacterial families show higher fluctuations in the fecal microbiota than high-abundance ones.

Conclusions

Our data suggest that microbial diversity is significantly higher in herbivores than in carnivores, whereas the microbiota in carnivores, unlike in herbivores, varies widely even within species. This high variability has methodological implications and underlines the need to analyze a minimum amount of about 10 samples per species. In our study, we found considerable differences in the occurrence of different bacterial families when looking at just three and six samples. However, from a sample number of 10 onwards, these within-species fluctuations balanced out in most cases and led to constant and more reliable results.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-021-00141-0.

Compositional and genetic alterations in Graves' disease gut microbiome reveal specific diagnostic biomarkers

Graves' Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves' disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson's Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.

Molecular signatures of resource competition: Clonal interference favors ecological diversification and can lead to incipient speciation

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages - clonal interference. We find that in large populations, more intense clonal interference can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

MOSGA 2: Comparative genomics and validation tools

Due to the highly growing number of available genomic information, the need for accessible and easy-to-use analysis tools is increasing. To facilitate eukaryotic genome annotations, we created MOSGA. In this work, we show how MOSGA 2 is developed by including several advanced analyses for genomic data. Since the genomic data quality greatly impacts the annotation quality, we included multiple tools to validate and ensure high-quality user-submitted genome assemblies. Moreover, thanks to the integration of comparative genomics methods, users can benefit from a broader genomic view by analyzing multiple genomic data sets simultaneously. Further, we demonstrate the new functionalities of MOSGA 2 by different use-cases and practical examples. MOSGA 2 extends the already established application to the quality control of the genomic data and integrates and analyzes multiple genomes in a larger context, e.g., by phylogenetics.

Functions predict horizontal gene transfer and the emergence of antibiotic resistance

Phylogenetic distance, shared ecology, and genomic constraints are often cited as key drivers governing horizontal gene transfer (HGT), although their relative contributions are unclear. Here, we apply machine learning algorithms to a curated set of diverse bacterial genomes to tease apart the importance of specific functional traits on recent HGT events. We find that functional content accurately predicts the HGT network [area under the receiver operating characteristic curve (AUROC) = 0.983], and performance improves further (AUROC = 0.990) for transfers involving antibiotic resistance genes (ARGs), highlighting the importance of HGT machinery, niche-specific, and metabolic functions. We find that high-probability not-yet detected ARG transfer events are almost exclusive to human-associated bacteria. Our approach is robust at predicting the HGT networks of pathogens, including Acinetobacter baumannii and Escherichia coli, as well as within localized environments, such as an individual’s gut microbiome.

Microbial adaptive evolution

Bacterial species can adapt to significant changes in their environment by mutation followed by selection, a phenomenon known as “adaptive evolution.” With the development of bioinformatics and genetic engineering, research on adaptive evolution has progressed rapidly, as have applications of the process. In this review, we summarize various mechanisms of bacterial adaptive evolution, the technologies used for studying it, and successful applications of the method in research and industry. We particularly highlight the contributions of Dr. L. O. Ingram. Microbial adaptive evolution has significant impact on our society not only from its industrial applications, but also in the evolution, emergence, and control of various pathogens.

Probiotic consumption influences universal adaptive mutations in indigenous human and mouse gut microbiota

The adaptive evolution in indigenous intestinal microbes derived from probiotics is critical to safety and efficacy evaluation of probiotics, yet it is still largely underexplored. Here, through 11 publicly accessible datasets, we demonstrated that probiotic consumption can lead to widespread single-nucleotide variants (SNVs) in the native microbiota. Interestingly, the same probiotic strains introduced far more SNVs in mouse gut than humans. Furthermore, the pattern of probiotics-induced SNVs was highly probiotic-strain specific, and 17 common SNVs in Faecalibacterium prausnitzii genome were identified cross studies, which might lead to changes in bacterial protein structure. Further, nearly 50% of F. prausnitzii SNVs can be inherited for six months in an independent human cohort, whereas the other half only transiently occurred. Collectively, our study substantially extended our understanding of co-evolution of the probiotics and the indigenous gut microbiota, highlighting the importance of assessment of probiotics efficacy and safety in an integrated manner.

Chenchen Ma, Chengcheng Zhang, and Denghui Chen et al. examine how probiotic consumption impacts gut microbiota composition in human and mice through a global, cross-cohort metagenomic analysis. Their results suggest that probiotic consumption may result in widespread variation among the native microbiota in both the human and mouse gut.

Time-course alterations of gut microbiota and short-chain fatty acids after short-term lincomycin exposure in young swine

Increasing evidence suggests that antibiotic administration causes gut injury, negatively affecting nutrient digestion, immune regulation, and colonization resistance against pathogens due to the disruption of gut microbiota. However, the time-course effects of therapeutic antibiotics on alterations of gut microbes and short-chain fatty acids (SCFAs) in young swine are still unknown. In this study, twenty piglets were assigned into two groups and fed commercial diets with or without lincomycin in the first week for a 28-day trial period. Results showed that 1-week lincomycin exposure (LE) did reduce the body weight on day 14 (p = 0.0450) and 28 (p = 0.0362). The alpha-diversity notably reduced after 1-week LE, and then gradually raised and reached the control group level in the second week on cessation of LE, indicated by the variation of Sobs, Chao, Shannon, and ACE index (p < 0.05). Beta-diversity analysis revealed that the distinct microbial cluster existed persistently for the whole trial period between two groups (p < 0.001). The relative abundance of most microbes including fiber-degrading (e.g., Agathobacter and Coprococcus), beneficial (e.g., Lactobacillus and Mitsuokella), or pathogenic bacteria (e.g., Terrisporobacter and Lachnoclostridium) decreased (LDA score > 3), and the concentration of SCFAs also diminished in the feces of 1-week lincomycin-administrated young swine, indicating that therapeutic LE killed most bacteria and reduced SCFA production with gut dysbiosis occurring. After the LE stopped, the state of gut dysbiosis gradually attenuated and formed new gut-microbe homeostasis distinct from microbial homeostasis of young pigs unexposed to lincomycin. The increased presence of potential pathogens, such as Terrisporobacter, Negativibacillus, and Escherichia-Shigella, and decreased beneficial bacteria, such as Lactobacillus and Agathobacter, were observed in new homeostasis reshaped by short-lincomycin administration (LDA score > 3 or p < 0.05), adversely affecting gut development and health of young pigs. Collectively, these results suggested that severe disruption of the commensal microbiota occurred after short-term LE or termination of LE in young swine. KEY POINTS: • Therapeutic lincomycin exposure induced gut dysbiosis, killing most bacteria and reducing short-chain fatty acid production. • Gut dysbiosis gradually attenuated and formed new homeostasis after lincomycin exposure stopped. • The new homeostasis, increased Escherichia-Shigella etc. and decreased Lactobacillus etc., was potentially harmful to gut health.

Cultivation of common bacterial species and strains from human skin, oral, and gut microbiota

BACKGROUND

Genomics-driven discoveries of microbial species have provided extraordinary insights into the biodiversity of human microbiota. In addition, a significant portion of genetic variation between microbiota exists at the subspecies, or strain, level. High-resolution genomics to investigate species- and strain-level diversity and mechanistic studies, however, rely on the availability of individual microbes from a complex microbial consortia. High-throughput approaches are needed to acquire and identify the significant species- and strain-level diversity present in the oral, skin, and gut microbiome. Here, we describe and validate a streamlined workflow for cultivating dominant bacterial species and strains from the skin, oral, and gut microbiota, informed by metagenomic sequencing, mass spectrometry, and strain profiling.

RESULTS

Of total genera discovered by either metagenomic sequencing or culturomics, our cultivation pipeline recovered between 18.1-44.4% of total genera identified. These represented a high proportion of the community composition reconstructed with metagenomic sequencing, ranging from 66.2-95.8% of the relative abundance of the overall community. Fourier-Transform Infrared spectroscopy (FT-IR) was effective in differentiating genetically distinct strains compared with whole-genome sequencing, but was less effective as a proxy for genetic distance.

CONCLUSIONS

Use of a streamlined set of conditions selected for cultivation of skin, oral, and gut microbiota facilitates recovery of dominant microbes and their strain variants from a relatively large sample set. FT-IR spectroscopy allows rapid differentiation of strain variants, but these differences are limited in recapitulating genetic distance. Our data highlights the strength of our cultivation and characterization pipeline, which is in throughput, comparisons with high-resolution genomic data, and rapid identification of strain variation.

Effect of Fiber and Fecal Microbiota Transplantation Donor on Recipient Mice Gut Microbiota

Both fecal microbiota transplantation (FMT) and dietary fiber intervention were verified as effective ways to manipulate the gut microbiota, whereas little is known about the influence of the combined methods on gut microbiota. Here, we constructed "non-industrialized" and "industrialized" gut microbiota models to investigate the donor effect of FMT and diet effect in shaping the gut microbiota. Mice were transplanted fecal microbiota from domestic pig and received a diet with low-fiber (D) or high-fiber (DF), whereas the other two groups were transplanted fecal microbiota from wild pig and then received a diet with low-fiber (W) or high-fiber (WF), respectively. Gut microbiota of WF mice showed a lower Shannon and Simpson index (P < 0.05), whereas gut microbiota of W mice showed no significant difference than that of D and DF mice. Random forest models revealed the major differential bacteria genera between four groups, including Anaeroplasma or unclassified_o_Desulfovibrionales, which were influenced by FMT or diet intervention, respectively. Besides, we found a lower out-of-bag rate in the random forest model constructed for dietary fiber (0.086) than that for FMT (0.114). Linear discriminant analysis effective size demonstrated that FMT combined with dietary fiber altered specific gut microbiota, including Alistipes, Clostridium XIVa, Clostridium XI, and Akkermansia, in D, DF, W, and WF mice, respectively. Our results revealed that FMT from different donors coupled with dietary fiber intervention could lead to different patterns of gut microbiota composition, and dietary fiber might play a more critical role in shaping gut microbiota than FMT donor. Strategies based on dietary fiber can influence the effectiveness of FMT in the recipient.

A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations

BACKGROUND

Microbiome-metabolome studies of the human gut have been gaining popularity in recent years, mostly due to accumulating evidence of the interplay between gut microbes, metabolites, and host health. Statistical and machine learning-based methods have been widely applied to analyze such paired microbiome-metabolome data, in the hope of identifying metabolites that are governed by the composition of the microbiome. Such metabolites can be likely modulated by microbiome-based interventions, offering a route for promoting gut metabolic health. Yet, to date, it remains unclear whether findings of microbially associated metabolites in any single study carry over to other studies or cohorts, and how robust and universal are microbiome-metabolites links.

RESULTS

In this study, we addressed this challenge by performing a comprehensive meta-analysis to identify human gut metabolites that can be predicted based on the composition of the gut microbiome across multiple studies. We term such metabolites "robustly well-predicted". To this end, we processed data from 1733 samples from 10 independent human gut microbiome-metabolome studies, focusing initially on healthy subjects, and implemented a machine learning pipeline to predict metabolite levels in each dataset based on the composition of the microbiome. Comparing the predictability of each metabolite across datasets, we found 97 robustly well-predicted metabolites. These include metabolites involved in important microbial pathways such as bile acid transformations and polyamines metabolism. Importantly, however, other metabolites exhibited large variation in predictability across datasets, suggesting a cohort- or study-specific relationship between the microbiome and the metabolite. Comparing taxonomic contributors to different models, we found that some robustly well-predicted metabolites were predicted by markedly different sets of taxa across datasets, suggesting that some microbially associated metabolites may be governed by different members of the microbiome in different cohorts. We finally examined whether models trained on a control group of a given study successfully predicted the metabolite's level in the disease group of the same study, identifying several metabolites where the model was not transferable, indicating a shift in microbial metabolism in disease-associated dysbiosis.

CONCLUSIONS

Combined, our findings provide a better understanding of the link between the microbiome and metabolites and allow researchers to put identified microbially associated metabolites within the context of other studies. Video abstract.

Precise quantification of bacterial strains after fecal microbiota transplantation delineates long-term engraftment and explains outcomes

Fecal microbiota transplantation (FMT) has been successfully applied to treat recurrent Clostridium difficile infection in humans, but a precise method to measure which bacterial strains stably engraft in recipients and evaluate their association with clinical outcomes is lacking. We assembled a collection of >1,000 different bacterial strains that were cultured from the fecal samples of 22 FMT donors and recipients. Using our strain collection combined with metagenomic sequencing data from the same samples, we developed a statistical approach named Strainer for the detection and tracking of bacterial strains from metagenomic sequencing data. We applied Strainer to evaluate a cohort of 13 FMT longitudinal clinical interventions and detected stable engraftment of 71% of donor microbiota strains in recipients up to 5 years post-FMT. We found that 80% of recipient gut bacterial strains pre-FMT were eliminated by FMT and that post-FMT the strains present persisted up to 5 years later, together with environmentally acquired strains. Quantification of donor bacterial strain engraftment in recipients independently explained (precision 100%, recall 95%) the clinical outcomes (relapse or success) after initial and repeat FMT. We report a compendium of bacterial species and strains that consistently engraft in recipients over time that could be used in defined live biotherapeutic products as an alternative to FMT. Our analytical framework and Strainer can be applied to systematically evaluate either FMT or defined live bacterial therapeutic studies by quantification of strain engraftment in recipients.

Transient Eco-Evolutionary Dynamics and the Window of Opportunity for Establishment of Immigrants

AbstractTo what extent does landscape genetic structure bear the signature of arrival order of lineages during population assembly? Rapid genetic adaptation of resident populations founded by early colonists to local conditions might prevent establishment of later-arriving lineages, resulting in an evolution-mediated priority effect. This might result in a limited window of opportunity for establishment during which the resident population did not have sufficient time yet to monopolize the patch through local adaptation. The length of this window of opportunity is expected to depend on the degree to which early colonists and immigrants are preadapted to local habitat conditions. We present an intraspecific competition model of the initial transient population and evolutionary dynamics that quantifies the window of opportunity for establishment for asexual species. The model explicitly addresses the long-lasting effects of evolution-mediated priority effects by tracking lineages through time. Our results show that the difference in initial preadaptation between early colonists and late immigrants and the speed of evolution codetermine the window of opportunity for establishment. Our results also suggest that local populations should often be dominated by descendants of just a few early colonist lineages and that landscape genetic structure should often reflect the legacy of colonization history.

Infant gut strain persistence is associated with maternal origin, phylogeny, and traits including surface adhesion and iron acquisition

Gut microbiome succession affects infant development. However, it remains unclear what factors promote persistence of initial bacterial colonizers in the developing gut. Here, we perform strain-resolved analyses to compare gut colonization of preterm and full-term infants throughout the first year of life and evaluate associations between strain persistence and strain origin as well as genetic potential. Analysis of fecal metagenomes collected from 13 full-term and 9 preterm infants reveals that infants' initially distinct microbiomes converge by age 1 year. Approximately 11% of early colonizers, primarily Bacteroides and Bifidobacterium, persist during the first year of life, and those are more prevalent in full-term, compared with preterm infants. Examination of 17 mother-infant pairs reveals maternal gut strains are significantly more likely to persist in the infant gut than other strains. Enrichment in genes for surface adhesion, iron acquisition, and carbohydrate degradation may explain persistence of some strains through the first year of life.

The digestive and reproductive tract microbiotas and their association with body weight in laying hens

Body weight at the onset of egg production is a major factor influencing hen productivity, as suitable body weight is crucial to laying performance in laying hens. To better understand the association between body weight and microbial community membership and structure in different sites of the digestive and reproductive tracts in chickens, we performed 16S rRNA sequencing surveys and focused on how the microbiota may interact to influence body weight. Our results demonstrated that the microbial community and structure of the digestive and reproductive tracts differed between low and high body weight groups. In particular, we found that the species Pseudomonas viridiflava was negatively associated with body weight in the 3 digestive tract sites, while Bacteroides salanitronis was negatively associated with body weight in the 3 reproductive tract sites; and further in-depth studies are needed to explore their function. These findings will help extend our understanding of the influence of the bird digestive and reproductive tract microbiotas on body weight trait and provide future directions regarding the control of body weight in the production of laying hens.

Ecological and Evolutionary responses to Antibiotic Treatment in the Human Gut Microbiota

The potential for antibiotics to affect the ecology and evolution of the human gut microbiota is well recognised and has wide-ranging implications for host health. Here, we review the findings of key studies that surveyed the human gut microbiota during antibiotic treatment. We find several broad patterns including the loss of diversity, disturbance of community composition, suppression of bacteria in the Actinobacteria phylum, amplification of bacteria in the Bacteroidetes phylum, and promotion of antibiotic resistance. Such changes to the microbiota were often, but not always, recovered following the end of treatment. However, many studies reported unique and/or contradictory results, which highlights our inability to meaningfully predict or explain the effects of antibiotic treatment on the human gut microbiome. This problem arises from variation between existing studies in three major categories: differences in dose, class and combinations of antibiotic treatments used; differences in demographics, lifestyles, and locations of subjects; and differences in measurements, analyses and reporting styles used by researchers. To overcome this, we suggest two integrated approaches: (i) a top-down approach focused on building predictive models through large sample sizes, deep metagenomic sequencing, and effective collaboration; and (ii) a bottom-up reductionist approach focused on testing hypotheses using model systems.

Human gut-derived B. longum subsp. longum strains protect against aging in a D-galactose-induced aging mouse model

BACKGROUND

Probiotics have been used to regulate the gut microbiota and physiology in various contexts, but their precise mechanisms of action remain unclear.

RESULTS

By population genomic analysis of 418 Bifidobacterium longum strains, including 143 newly sequenced in this study, three geographically distinct gene pools/populations, BLAsia1, BLAsia2, and BLothers, were identified. Genes involved in cell wall biosynthesis, particularly peptidoglycan biosynthesis, varied considerably among the core genomes of the different populations, but accessory genes that contributed to the carbohydrate metabolism were significantly distinct. Although active transmission was observed inter-host, inter-country, inter-city, intra-community, and intra-family, a single B. longum clone seemed to reside within each individual. A significant negative association was observed between host age and relative abundance of B. longum, while there was a strong positive association between host age and strain genotype [e.g., single nucleotide polymorphisms in the arginine biosynthesis pathway]. Further animal experiments performed with the B. longum isolates via using a D-galactose-induced aging mouse model supported these associations, in which B. longum strains with different genotypes in arginine biosynthesis pathway showed divergent abilities on protecting against host aging possibly via their different abilities to modify the metabolism of gut microbes.

CONCLUSIONS

This is the first known example of research on the evolutionary history and transmission of this probiotic species. Our results propose a new mechanistic insight for promoting host longevity via the informed use of specific probiotics or molecules. Video abstract.

Bacterial evolution during human infection: Adapt and live or adapt and die

Microbes are constantly evolving. Laboratory studies of bacterial evolution increase our understanding of evolutionary dynamics, identify adaptive changes, and answer important questions that impact human health. During bacterial infections in humans, however, the evolutionary parameters acting on infecting populations are likely to be much more complex than those that can be tested in the laboratory. Nonetheless, human infections can be thought of as naturally occurring in vivo bacterial evolution experiments, which can teach us about antibiotic resistance, pathogenesis, and transmission. Here, we review recent advances in the study of within-host bacterial evolution during human infection and discuss practical considerations for conducting such studies. We focus on 2 possible outcomes for de novo adaptive mutations, which we have termed "adapt-and-live" and "adapt-and-die." In the adapt-and-live scenario, a mutation is long lived, enabling its transmission on to other individuals, or the establishment of chronic infection. In the adapt-and-die scenario, a mutation is rapidly extinguished, either because it carries a substantial fitness cost, it arises within tissues that block transmission to new hosts, it is outcompeted by more fit clones, or the infection resolves. Adapt-and-die mutations can provide rich information about selection pressures in vivo, yet they can easily elude detection because they are short lived, may be more difficult to sample, or could be maladaptive in the long term. Understanding how bacteria adapt under each of these scenarios can reveal new insights about the basic biology of pathogenic microbes and could aid in the design of new translational approaches to combat bacterial infections.

Embracing Metagenomic Complexity with a Genome-Free Approach

A central paradigm in microbiome data analysis, which we term the genome-centric paradigm, is that a linear (non-branching) DNA sequence is the ideal representation of a microbial genome. This representation is natural, as microbes indeed have non-branching genomes. Tremendous discoveries in microbiology were made under this paradigm, but is it always optimal for microbiome research? In this Commentary, we claim that the realization of this paradigm in metagenomic assembly, a fundamental step in the “metagenomics analysis pipeline,” suboptimally models the extensive genomic variability present in the microbiome. We outline our efforts to address these issues with a “genome-free” approach that eschews linear genomic representations in favor of a pan-metagenomic graph.

A Combination of Metagenomic and Cultivation Approaches Reveals Hypermutator Phenotypes within Vibrio cholerae-Infected Patients

Vibrio cholerae can cause a range of symptoms, from severe diarrhea to asymptomatic infection. Previous studies using whole-genome sequencing (WGS) of multiple bacterial isolates per patient showed that V. cholerae can evolve modest genetic diversity during symptomatic infection. To further explore the extent of V. cholerae within-host diversity, we applied culture-based WGS and metagenomics to a cohort of both symptomatic and asymptomatic cholera patients from Bangladesh. While metagenomics allowed us to detect more mutations in symptomatic patients, WGS of cultured isolates was necessary to detect V. cholerae diversity in asymptomatic carriers, likely due to their low V. cholerae load. Using both metagenomics and isolate WGS, we report three lines of evidence that V. cholerae hypermutators evolve within patients. First, we identified nonsynonymous mutations in V. cholerae DNA repair genes in 5 out of 11 patient metagenomes sequenced with sufficient coverage of the V. cholerae genome and in 1 of 3 patients with isolate genomes sequenced. Second, these mutations in DNA repair genes tended to be accompanied by an excess of intrahost single nucleotide variants (iSNVs). Third, these iSNVs were enriched in transversion mutations, a known hallmark of hypermutator phenotypes. While hypermutators appeared to generate mostly selectively neutral mutations, nonmutators showed signs of convergent mutation across multiple patients, suggesting V. cholerae adaptation within hosts. Our results highlight the power and limitations of metagenomics combined with isolate sequencing to characterize within-patient diversity in acute V. cholerae infections, while providing evidence for hypermutator phenotypes within cholera patients.

IMPORTANCE Pathogen evolution within patients can impact phenotypes such as drug resistance and virulence, potentially affecting clinical outcomes. V. cholerae infection can result in life-threatening diarrheal disease or asymptomatic infection. Here, we describe whole-genome sequencing of V. cholerae isolates and culture-free metagenomic sequencing from stool of symptomatic cholera patients and asymptomatic carriers. Despite the typically short duration of cholera, we found evidence for adaptive mutations in the V. cholerae genome that occur independently and repeatedly within multiple symptomatic patients. We also identified V. cholerae hypermutator phenotypes within several patients, which appear to generate mainly neutral or deleterious mutations. Our work sets the stage for future studies of the role of hypermutators and within-patient evolution in explaining the variation from asymptomatic carriage to symptomatic cholera.

The Tempo and Mode of Adaptation in a Complex Natural Population: the Microbiome

Adaptation is a fundamental process by which populations evolve to grow more fit in their environments. Recent studies are starting to show us that commensal microbes can evolve on short timescales of days and months, suggesting that ecological changes are not the only means by which microbes in complex natural populations respond to selection pressures. However, we still lack a complete understanding of the tempo and mode of adaptation in microbiomes given the many complex forces that natural populations experience, which include ecological pressures, changes in population size, spatial structure, and fluctuations in selection pressures. Advances in modeling complex populations and scenarios will allow us to understand adaptation not only in microbiomes but also more generically in other natural populations that experience similar complexities.

Ultra-resolution Metagenomics: When Enough Is Not Enough

Technological advances in community sequencing have steadily increased the taxonomic resolution at which microbes can be delineated. In high-resolution metagenomics, bacterial strains can now be resolved, enhancing medical microbiology and the description of microbial evolution in vivo. In the Hildebrand lab, we are researching novel approaches to further increase the phylogenetic resolution of metagenomics. I propose that ultra-resolution metagenomics will be the next qualitative level of community sequencing, classified by the accurate resolution of ultra-rare genetic events, such as subclonal mutations present in all populations of evolving cells. This will be used to quantify evolutionary processes at ecologically relevant scales, monitor the progress of infections within a patient, and accurately track pathogens in food and infection chains. However, to develop this next metagenomic generation, we first need to understand the currently imposed limits of sequencing technologies, metagenomic strain delineation, and genome reconstructions.

Evolution in a Community Context: towards Understanding the Causes and Consequences of Adaptive Evolution in the Human Gut Microbiota over Short Time Scales

How important is adaptive evolution to the unique diversity that we can observe for each individual human gut microbiome? How do gut microbes evolve in response to changes in their environment, and how does evolution in real time impact microbial functionality in the context of host health? My interdisciplinary research uses in vitro microcosm models to test how different abiotic and biotic factors impact microbial evolution in a community context. We complement this approach by tracking focal species as they evolve in real time and in their natural environment of the human gut. Our aim is to provide a better understanding of how the dynamics and outcomes of microbial evolution differ between individual gut environments, and in response to different selection pressures, so that we can move closer to rational gut microbiome treatments that promote host health and prevent and treat human disease.

Causative Microbes in Host-Microbiome Interactions

Despite identification of numerous associations between microbiomes and diseases, the complexity of the human microbiome has hindered identification of individual species and strains that are causative in host phenotype or disease. Uncovering causative microbes is vital to fully understand disease processes and to harness the potential therapeutic benefits of microbiota manipulation. Developments in sequencing technology, animal models, and bacterial culturing have facilitated the discovery of specific microbes that impact the host and are beginning to advance the characterization of host-microbiome interaction mechanisms. We summarize the historical and contemporary experimental approaches taken to uncover microbes from the microbiota that affect host biology and describe examples of commensals that have specific effects on the immune system, inflammation, and metabolism. There is still much to learn, and we lay out challenges faced by the field and suggest potential remedies for common pitfalls encountered in the hunt for causative commensal microbes. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Comparative genomics of in vitro and in vivo evolution of probiotics reveals energy restriction not the main evolution driving force in short term

Probiotics have attracted much attention because of their health-promoting effects, but little is known about the in vivo evolution of probiotics. This study analyzed the genome adaptation of the probiotic Lactiplantibacillus plantarum P-8 strain cultivated in ordinary and glucose restrictive growth media. Then, this study re-analyzed genomes of P-8 isolates recovered from the gut contents of subjects in two feeding trials (in rat and human). The sampling time points were similar to that of the in vitro evolution experiment, which might give parallel comparison of the in vitro and in vivo evolution processes. Our results showed that intra-individual specific microbial genomic variants of the original strain were detected in all human and some rat subjects. The divergent patterns of evolution within the host gastrointestinal tract suggested intra-individual-specific environmental adaptation. Based on comprehensive analysis of adapted-isolates recovered from these experiments, our results showed that the energy restriction was not the main driving force for evolution of probiotics. The individual-specific adaptation of probiotics might partially explain the varying extent of health effects seen between different individuals after probiotic consumption. In addition, the results suggest that probiotics should not only adapt to the environment of the birth canal, but also adapt to other species in the gut, revealing the Red Queen hypothesis in the process of intestinal flora.

Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment

Gut microbial communities can respond to antibiotic perturbations by rapidly altering their taxonomic and functional composition. However, little is known about the strain-level processes that drive this collective response. Here, we characterize the gut microbiome of a single individual at high temporal and genetic resolution through a period of health, disease, antibiotic treatment, and recovery. We used deep, linked-read metagenomic sequencing to track the longitudinal trajectories of thousands of single nucleotide variants within 36 species, which allowed us to contrast these genetic dynamics with the ecological fluctuations at the species level. We found that antibiotics can drive rapid shifts in the genetic composition of individual species, often involving incomplete genome-wide sweeps of pre-existing variants. These genetic changes were frequently observed in species without obvious changes in species abundance, emphasizing the importance of monitoring diversity below the species level. We also found that many sweeping variants quickly reverted to their baseline levels once antibiotic treatment had concluded, demonstrating that the ecological resilience of the microbiota can sometimes extend all the way down to the genetic level. Our results provide new insights into the population genetic forces that shape individual microbiomes on therapeutically relevant timescales, with potential implications for personalized health and disease.

Examining horizontal gene transfer in microbial communities

Bacteria acquire novel DNA through horizontal gene transfer (HGT), a process that enables an organism to rapidly adapt to changing environmental conditions, provides a competitive edge and potentially alters its relationship with its host. Although the HGT process is routinely exploited in laboratories, there is a surprising disconnect between what we know from laboratory experiments and what we know from natural environments, such as the human gut microbiome. Owing to a suite of newly available computational algorithms and experimental approaches, we have a broader understanding of the genes that are being transferred and are starting to understand the ecology of HGT in natural microbial communities. This Review focuses on these new technologies, the questions they can address and their limitations. As these methods are applied more broadly, we are beginning to recognize the full extent of HGT possible within a microbiome and the punctuated dynamics of HGT, specifically in response to external stimuli. Furthermore, we are better characterizing the complex selective pressures on mobile genetic elements and the mechanisms by which they interact with the bacterial host genome.

Candidate probiotic Lactiplantibacillus plantarum HNU082 rapidly and convergently evolves within human, mice, and zebrafish gut but differentially influences the resident microbiome

BACKGROUND

Improving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods.

RESULTS

We combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10-70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice.

CONCLUSIONS

Collectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans. Video abstract.

Dispersal strategies shape persistence and evolution of human gut bacteria

Human gut bacterial strains can co-exist with their hosts for decades, but little is known about how these microbes persist and disperse, and evolve thereby. Here, we examined these processes in 5,278 adult and infant fecal metagenomes, longitudinally sampled in individuals and families. Our analyses revealed that a subset of gut species is extremely persistent in individuals, families, and geographic regions, represented often by locally successful strains of the phylum Bacteroidota. These “tenacious” bacteria show high levels of genetic adaptation to the human host but a high probability of loss upon antibiotic interventions. By contrast, heredipersistent bacteria, notably Firmicutes, often rely on dispersal strategies with weak phylogeographic patterns but strong family transmissions, likely related to sporulation. These analyses describe how different dispersal strategies can lead to the long-term persistence of human gut microbes with implications for gut flora modulations.

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Bacterial strains may persist within family members through transfer

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Bacteria adapt dispersal strategies: heredipersistent, spatiopersistent, and tenacious

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Dispersal strategies correlate with genetic bottlenecks and effective population size