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

Microbial micronutrient sharing, gut redox balance and keystone taxa as a basis for a new perspective to solutions targeting health from the gut

In health, the gut microbiome functions as a stable ecosystem maintaining overall balance and ensuring its own survival against environmental stressors through complex microbial interaction. This balance and protection from stressors is maintained through interactions both within the bacterial ecosystem as well as with its host. As a consequence, the gut microbiome plays a critical role in various physiological processes including maintaining the structure and function of the gut barrier, educating the gut immune system, and modulating the gut motor, digestive/absorptive, as well as neuroendocrine system all of which are crucial for human health and disease pathogenesis. Pre- and probiotics, widely available and clinically established, offer various health benefits primarily by beneficially modulating the gut microbiome. However, their clinical outcomes can vary significantly due to differences in host physiology, diets, individual microbiome compositions, and other environmental factors. This perspective paper highlights emerging scientific insights into the importance of microbial micronutrient sharing, gut redox balance, keystone species, and the gut barrier in maintaining a diverse and functional microbial ecosystem, and their relevance to human health. We propose a novel approach that targets microbial ecosystems and keystone taxa performance by supplying microbial micronutrients in the form of colon-delivered vitamins, and precision prebiotics [e.g. human milk oligosaccharides (HMOs) or synthetic glycans] as components of precisely tailored ingredient combinations to optimize human health. Such a strategy may effectively support and stabilize microbial ecosystems, providing a more robust and consistent approach across various individuals and environmental conditions, thus, overcoming the limitations of current single biotic solutions.

Brief antibiotic use drives human gut bacteria towards low-cost resistance

Understanding the relationship between antibiotic use and the evolution of antimicrobial resistance is vital for effective antibiotic stewardship. Yet, animal models and in vitro experiments poorly replicate real-world conditions1. To explain how resistance evolves in vivo, we exposed 60 human participants to ciprofloxacin and used longitudinal stool samples and a new computational method to assemble the genomes of 5,665 populations of commensal bacterial species within participants. Analysis of 2.3 million polymorphic sequence variants revealed 513 populations that underwent selective sweeps. We found convergent evolution focused on DNA gyrase and evidence of dispersed selective pressure at other genomic loci. Roughly 10% of susceptible bacterial populations evolved towards resistance through sweeps that involved substitutions at a specific amino acid in gyrase. The evolution of gyrase was associated with large populations that decreased in relative abundance during exposure. Sweeps persisted for more than 10 weeks in most cases and were not projected to revert within a year. Targeted amplification showed that gyrase mutations arose de novo within the participants and exhibited no measurable fitness cost. These findings revealed that brief ciprofloxacin exposure drives the evolution of resistance in gut commensals, with mutations persisting long after exposure. This study underscores the capacity of the human gut to promote the evolution of resistance and identifies key genomic and ecological factors that shape bacterial adaptation in vivo.

Gut microbiome evolution from infancy to 8 years of age

The human gut microbiome is most dynamic in early life. Although sweeping changes in taxonomic architecture are well described, it remains unknown how, and to what extent, individual strains colonize and persist and how selective pressures define their genomic architecture. In this study, we combined shotgun sequencing of 1,203 stool samples from 26 mothers and their twins (52 infants), sampled from childbirth to 8 years after birth, with culture-enhanced, deep short-read and long-read stool sequencing from a subset of 10 twins (20 infants) to define transmission, persistence and evolutionary trajectories of gut species from infancy to middle childhood. We constructed 3,995 strain-resolved metagenome-assembled genomes across 399 taxa, and we found that 27.4% persist within individuals. We identified 726 strains shared within families, with Bacteroidales, Oscillospiraceae and Lachnospiraceae, but not Bifidobacteriaceae, vertically transferred. Lastly, we identified weaning as a critical inflection point that accelerates bacterial mutation rates and separates functional profiles of genes accruing mutations.

Wine Fermentation as a Model System for Microbial Ecology and Evolution

In vitro microbial communities have proven to be invaluable model systems for studying ecological and evolutionary processes experimentally. However, it remains unclear whether quantitative insights obtained from these laboratory systems can be applied to complex communities assembling and evolving in their natural ecological context. To bridge the gap between the lab and the 'real-world', there is a need for laboratory model systems that better approximate natural and semi-natural ecosystems. Wine fermentation presents an ideal system for this purpose, balancing experimental tractability with rich ecological and evolutionary dynamics. In this perspective piece we outline the key features that make wine fermentation a fruitful model system for ecologists and evolutionary biologists. We highlight the diversity of environmentally mediated interactions that shape community dynamics during fermentation, the complex evolutionary history of wine microbial populations, and the opportunity to study the impact of complex ecologies on evolutionary dynamics. By integrating knowledge from both wine research and microbial ecology and evolution we aim to enhance understanding and foster collaboration between these fields.

Quantifying compositional variability in microbial communities with FAVA

Microbial communities vary across space, time, and individual hosts, generating a need for statistical methods capable of quantifying variability across multiple microbiome samples at once. To understand heterogeneity across microbiome samples from different host individuals, sampling times, spatial locations, or experimental replicates, we present FAVA (FST-based Assessment of Variability across vectors of relative Abundances), a framework for characterizing compositional variability across two or more 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 1 when each sample is entirely composed of a single taxon (and at least two distinct taxa are present across samples). Its definition relies on the population-genetic statistic FST, with samples playing the role of "populations" and taxa playing the role of "alleles." Its mathematical properties allow users to compare datasets with different numbers of samples and taxonomic categories. We introduce extensions that incorporate phylogenetic similarity among taxa and spatial or temporal distances between samples. We demonstrate FAVA in two examples. First, we use FAVA to measure how the taxonomic and functional variability of gastrointestinal microbiomes across individuals from seven ruminant species changes along the gastrointestinal tract. Second, we use FAVA to quantify the increase in temporal variability of gut microbiomes in healthy humans following an antibiotic course and to measure the duration of the antibiotic's influence on temporal microbiome variability. We have implemented this tool in an R package, FAVA, for use in pipelines for the analysis of microbial relative abundances.

Antibiotic-perturbed microbiota and the role of probiotics

The disruptive effect of antibiotics on the composition and function of the human microbiota is well established. However, the hypothesis that probiotics can help restore the antibiotic-disrupted microbiota has been advanced, with little consideration of the strength of evidence supporting it. Some clinical data suggest that probiotics can reduce antibiotic-related side effects, including Clostridioides difficile-associated diarrhoea, but there are no data that causally link these clinical effects to microbiota protection or recovery. Substantial challenges hinder attempts to address this hypothesis, including the absence of consensus on the composition of a 'normal' microbiota, non-standardized and evolving microbiome measurement methods, and substantial inter-individual microbiota variation. In this Review, we explore these complexities. First, we review the known benefits and risks of antibiotics, the effect of antibiotics on the human microbiota, the resilience and adaptability of the microbiota, and how microbiota restoration might be defined and measured. Subsequently, we explore the evidence for the efficacy of probiotics in preventing disruption or aiding microbiota recovery post-antibiotic treatment. Finally, we offer insights into the current state of research and suggest directions for future research.

Uniform bacterial genetic diversity along the guts of mice inoculated with human stool

Environmental gradients exist throughout the digestive tract, driving spatial variation in the membership and abundance of bacterial species along the gut. However, less is known about the distribution of genetic diversity within bacterial species along the gut. Understanding this distribution is important because bacterial genetic variants confer traits important for the functioning of the microbiome and are also known to impart phenotypes to the hosts, including local inflammation along the gut and the ability to digest food. Thus, to be able to understand how the microbiome functions at a mechanistic level, it is essential to understand how genetic diversity is organized along the gut and the ecological and evolutionary processes that give rise to this organization. In this study, we analyzed bacterial genetic diversity of approximately 30 common gut commensals in five regions along the gut lumen in germ-free mice colonized with the same healthy human stool sample. While species membership and abundances varied considerably along the gut, genetic diversity within species was substantially more uniform. Driving this uniformity were similar strain frequencies along the gut, implying that multiple, genetically divergent strains of the same species can coexist within a host without spatially segregating. Additionally, the approximately 60 unique evolutionary adaptations arising within mice tended to sweep throughout the gut, showing little specificity for particular gut regions. Together, our findings show that genetic diversity may be more uniform along the gut than species diversity, which implies that species presence-absence may play a larger role than genetic variation in responding to varied environments along the gut.

Impact of trace metal supplementation on anaerobic biological methanation under hydrogen and carbon dioxide starvation

Biomethanation is a crucial process occurring in natural and engineered systems which can reduce carbon dioxide to methane impacting the global carbon cycle. However, little is known about the effect of on-and-off gaseous provision and micronutrients on bioconversion. Here, anaerobic microbiomes underwent intermittent feeding with incremental starvations and selective metal supplementation to assess the impact of hydrogen and carbon dioxide availability on microbial physiology. Resilience was tested under differential cultivations in basal medium supplemented with either nickel or cobalt. Nickel-augmented cultures exhibited faster recovery upon starvation, suggesting a beneficial effect. Dominant Methanothermobacter thermautotrophicus demonstrated robust growth, genetic stability and transcriptional downregulation when starved. Conversely, bacteria were plastic and prone to genetic fluctuations, accumulating mutations on genes encoding for ABC-transporters and C-metabolism enzymes. This study pioneers cellular resilience and response to micronutrient supplementation in anaerobic carbon dioxide-fixating microbiomes, offering valuable insights into microbial activity recovery after carbon and electron donor deprivation.

[Did humans co-evolve with the gut microbiota?]

The gut microbiome plays an important role in animal physiology and development. While the molecular, cellular and ecological mechanisms that determine its diversity and impact on animal health are beginning to unfold, we still know relatively little about its evolutionary history. Fundamental questions such as "Is the microbiota evolving and at what race?", "What are its origins?", "What are the consequences of microbiota evolution for human health?" or "Did we co-evolve with our gut bacteria?" are only beginning to be explored. In the short term (from a few days to a few years, or microevolution), gut microbes can evolve and adapt very rapidly within an individual in responses to environmental changes, such as diet shifts, which can affect human health. On the longer term (ten to millions of years, or macroevolution), evolution within individuals is counterbalanced by the transfer of microbes from other people, so that human evolution is decoupled from the evolution of most gut microbes over many generations. This suggests that, while gut microbes have probably evolved rapidly within humans, most of them have a history of exchange between host populations over millennia. Whether the evolution of the microbiota over the last hundreds of thousands of years has facilitated human adaptations remains an open question and an exciting avenue for future research.

Pervasive selective sweeps across human gut microbiomes

The human gut microbiome is composed of a highly diverse consortia of species which are continually evolving within and across hosts. The ability to identify adaptations common to many human gut microbiomes would not only reveal shared selection pressures across hosts, but also key drivers of functional differentiation of the microbiome that may affect community structure and host traits. However, to date there has not been a systematic scan for adaptations that have spread across human gut microbiomes. Here, we develop a novel selection scan statistic named the integrated Linkage Disequilibrium Score (iLDS) that can detect the spread of adaptive haplotypes across host microbiomes via migration and horizontal gene transfer. Specifically, iLDS leverages signals of hitchhiking of deleterious variants with the beneficial variant. Application of the statistic to ~30 of the most prevalent commensal gut species from 24 populations around the world revealed more than 300 selective sweeps across species. We find an enrichment for selective sweeps at loci involved in carbohydrate metabolism-potentially indicative of adaptation to features of host diet-and we find that the targets of selection significantly differ between Westernized and non-Westernized populations. Underscoring the potential role of diet in driving selection, we find a selective sweep absent from non-Westernized populations but ubiquitous in Westernized populations at a locus known to be involved in the metabolism of maltodextrin, a synthetic starch that has recently become a widespread component of Western diets. In summary, we demonstrate that selective sweeps across host microbiomes are a common feature of the evolution of the human gut microbiome, and that targets of selection may be strongly impacted by host diet.

pan-Draft: automated reconstruction of species-representative metabolic models from multiple genomes

The accurate reconstruction of genome-scale metabolic models (GEMs) for unculturable species poses challenges due to the incomplete and fragmented genetic information typical of metagenome-assembled genomes (MAGs). While existing tools leverage sequence homology from single genomes, this study introduces pan-Draft, a pan-reactome-based approach exploiting recurrent genetic evidence to determine the solid core structure of species-level GEMs. By comparing MAGs clustered at the species-level, pan-Draft addresses the issues due to the incompleteness and contamination of individual genomes, providing high-quality draft models and an accessory reactions catalog supporting the gapfilling step. This approach will improve our comprehension of metabolic functions of uncultured species.

The Bioinformatic Applications of Hi-C and Linked Reads

Long-range sequencing grants insight into additional genetic information beyond what can be accessed by both short reads and modern long-read technology. Several new sequencing technologies, such as "Hi-C" and "Linked Reads", produce long-range datasets for high-throughput and high-resolution genome analyses, which are rapidly advancing the field of genome assembly, genome scaffolding, and more comprehensive variant identification. In this review, we focused on five major long-range sequencing technologies: high-throughput chromosome conformation capture (Hi-C), 10X Genomics Linked Reads, haplotagging, transposase enzyme linked long-read sequencing (TELL-seq), and single- tube long fragment read (stLFR). We detailed the mechanisms and data products of the five platforms and their important applications, evaluated the quality of sequencing data from different platforms, and discussed the currently available bioinformatics tools. This work will benefit the selection of appropriate long-range technology for specific biological studies.

Clinical sequelae of gut microbiome development and disruption in hospitalized preterm infants

Aberrant preterm infant gut microbiota assembly predisposes to early-life disorders and persistent health problems. Here, we characterize gut microbiome dynamics over the first 3 months of life in 236 preterm infants hospitalized in three neonatal intensive care units using shotgun metagenomics of 2,512 stools and metatranscriptomics of 1,381 stools. Strain tracking, taxonomic and functional profiling, and comprehensive clinical metadata identify Enterobacteriaceae, enterococci, and staphylococci as primarily exploiting available niches to populate the gut microbiome. Clostridioides difficile lineages persist between individuals in single centers, and Staphylococcus epidermidis lineages persist within and, unexpectedly, between centers. Collectively, antibiotic and non-antibiotic medications influence gut microbiome composition to greater extents than maternal or baseline variables. Finally, we identify a persistent low-diversity gut microbiome in neonates who develop necrotizing enterocolitis after day of life 40. Overall, we comprehensively describe gut microbiome dynamics in response to medical interventions in preterm, hospitalized neonates.

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

Predicting the first steps of evolution in randomly assembled communities

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

Transient colonizing microbes promote gut dysbiosis and functional impairment

Species composition of the healthy adult gut microbiota tends to be stable over time. Destabilization of the gut microbiome under the influence of different factors is the main driver of the microbial dysbiosis and subsequent impacts on host physiology. Here, we used metagenomics data from a Swedish longitudinal cohort, to determine the stability of the gut microbiome and uncovered two distinct microbial species groups; persistent colonizing species (PCS) and transient colonizing species (TCS). We validated the continuation of this grouping, generating gut metagenomics data for additional time points from the same Swedish cohort. We evaluated the existence of PCS/TCS across different geographical regions and observed they are globally conserved features. To characterize PCS/TCS phenotypes, we performed bioreactor fermentation with faecal samples and metabolic modeling. Finally, using chronic disease gut metagenome and other multi-omics data, we identified roles of TCS in microbial dysbiosis and link with abnormal changes to host physiology.

Synergistic functional activity of a landfill microbial consortium in a microplastic-enriched environment

Plastic pollution of the soil is a global issue of increasing concern, with far-reaching impact on the environment and human health. To fully understand the medium- and long-term impact of plastic dispersal in the environment, it is necessary to define its interaction with the residing microbial communities and the biochemical routes of its degradation and metabolization. However, despite recent attention on this problem, research has largely focussed on microbial functional potential, failing to clearly identify collective adaptation strategies of these communities. Our study combines genome-centric metagenomics and metatranscriptomics to characterise soil microbial communities adapting to high polyethylene and polyethylene terephthalate concentration. The microbiota were sampled from a landfill subject to decades-old plastic contamination and enriched through prolonged cultivation using these microplastics as the only carbon source. This approach aimed to select the microorganisms that best adapt to these specific substrates. As a result, we obtained simplified communities where multiple plastic metabolization pathways are widespread across abundant and rare microbial taxa. Major differences were found in terms of expression, which on average was higher in planktonic microbes than those firmly adhered to plastic, indicating complementary metabolic roles in potential microplastic assimilation. Moreover, metatranscriptomic patterns indicate a high transcriptional level of numerous genes in emerging taxa characterised by a marked accumulation of genomic variants, supporting the hypothesis that plastic metabolization requires an extensive rewiring in energy metabolism and thus provides a strong selective pressure. Altogether, our results provide an improved characterisation of the impact of microplastics derived from common plastics types on terrestrial microbial communities and suggest biotic responses investing contaminated sites as well as potential biotechnological targets for cooperative plastic upcycling.

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.

Genome-resolved metagenomics: a game changer for microbiome medicine

Recent substantial evidence implicating commensal bacteria in human diseases has given rise to a new domain in biomedical research: microbiome medicine. This emerging field aims to understand and leverage the human microbiota and derivative molecules for disease prevention and treatment. Despite the complex and hierarchical organization of this ecosystem, most research over the years has relied on 16S amplicon sequencing, a legacy of bacterial phylogeny and taxonomy. Although advanced sequencing technologies have enabled cost-effective analysis of entire microbiota, translating the relatively short nucleotide information into the functional and taxonomic organization of the microbiome has posed challenges until recently. In the last decade, genome-resolved metagenomics, which aims to reconstruct microbial genomes directly from whole-metagenome sequencing data, has made significant strides and continues to unveil the mysteries of various human-associated microbial communities. There has been a rapid increase in the volume of whole metagenome sequencing data and in the compilation of novel metagenome-assembled genomes and protein sequences in public depositories. This review provides an overview of the capabilities and methods of genome-resolved metagenomics for studying the human microbiome, with a focus on investigating the prokaryotic microbiota of the human gut. Just as decoding the human genome and its variations marked the beginning of the genomic medicine era, unraveling the genomes of commensal microbes and their sequence variations is ushering us into the era of microbiome medicine. Genome-resolved metagenomics stands as a pivotal tool in this transition and can accelerate our journey toward achieving these scientific and medical milestones.

Predicting the First Steps of Evolution in Randomly Assembled Communities

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

A metagenomics pipeline reveals insertion sequence-driven evolution of the microbiota

Insertion sequence (IS) elements are mobile genetic elements in bacterial genomes that support adaptation. We developed a database of IS elements coupled to a computational pipeline that identifies IS element insertions in the microbiota. We discovered that diverse IS elements insert into the genomes of intestinal bacteria regardless of human host lifestyle. These insertions target bacterial accessory genes that aid in their adaptation to unique environmental conditions. Using IS expansion in Bacteroides, we show that IS activity leads to the insertion of "hot spots" in accessory genes. We show that IS insertions are stable and can be transferred between humans. Extreme environmental perturbations force IS elements to fall out of the microbiota, and many fail to rebound following homeostasis. Our work shows that IS elements drive bacterial genome diversification within the microbiota and establishes a framework for understanding how strain-level variation within the microbiota impacts human health.

Bacteroidales-Specific Antimicrobial Genes Can Influence the Selection of the Dominant Fecal Strain of Bacteroides vulgatus and Bacteroides uniformis from the Gastrointestinal Tract Microbial Community

Bacteroides vulgatus and Bacteroides uniformis are known to be abundant in the human fecal microbial community. Although these strains typically remain stable over time in humans, disruption of this microbial community following antibiotics resulted in the transient change to new strains suggesting that a complex, dynamic strain community exists in humans. To further study the selection of dominant fecal microbial strains from the gastrointestinal tract (GIT) community, we analyzed three longitudinal metagenomic sequencing data sets using BLAST+ to identify genes encoding Bacteroidales-specific antimicrobial proteins (BSAP) that have known functions to restrict species-specific replication of B. uniformis (BSAP-2) or B. vulgatus (BSAP-3) and have been postulated to provide a competitive advantage in microbial communities. In the HMP (Human Microbiome Project) data set, we found fecal samples from individuals had B. vulgatus or B. uniformis with either complete or deleted BSAP genes that did not change over time. We also examined fecal samples from two separate longitudinal data sets of individuals who had been given either single or multiple antibiotics. The BSAP gene pattern from most individuals given either single or multiple antibiotics recovered to be the same as the pre-antibiotic strain. However, in a few individuals, we found incomplete BSAP-3 genes at early times during the recovery that were replaced by B. vulgatus with the complete BSAP-3 gene, consistent with the function of the BSAP to specifically restrict Bacteroides spp. The results of these studies provide insights into the fluxes that occur in the Bacteroides spp. GIT community following perturbation and the dynamics of the selection of a dominant fecal strain of Bacteroides spp.

Impact of evolution on lifestyle in microbiome

This chapter analyses the interaction between microbiota and humans from an evolutionary point of view. Long-term interactions between gut microbiota and host have been generated as a result of dietary choices through coevolutionary processes, where mutuality of advantage is essential. Likewise, the characteristics of the intestinal environment have made it possible to describe different intrahost evolutionary mechanisms affecting microbiota. For its part, the intestinal microbiota has been of great importance in the evolution of mammals, allowing the diversification of dietary niches, phenotypic plasticity and the selection of host phenotypes. Although the origin of the human intestinal microbial community is still not known with certainty, mother-offspring transmission plays a key role, and it seems that transmissibility between individuals in adulthood also has important implications. Finally, it should be noted that certain aspects inherent to modern lifestyle, including refined diets, antibiotic intake, exposure to air pollutants, microplastics, and stress, could negatively affect the diversity and composition of our gut microbiota. This chapter aims to combine current knowledge to provide a comprehensive view of the interaction between microbiota and humans throughout evolution.

A metagenomics pipeline reveals insertion sequence-driven evolution of the microbiota

Insertion sequence (IS) elements are mobile genetic elements in bacterial genomes that support adaptation. We developed a database of IS elements coupled to a computational pipeline that identifies IS element insertions in the microbiota. We discovered that diverse IS elements insert into the genomes of intestinal bacteria regardless of human host lifestyle. These insertions target bacterial accessory genes that aid in their adaptation to unique environmental conditions. Using IS expansion in Bacteroides, we show that IS activity leads to insertion "hot spots" in accessory genes. We show that IS insertions are stable and can be transferred between humans. Extreme environmental perturbations force IS elements to fall out of the microbiota and many fail to rebound following homeostasis. Our work shows that IS elements drive bacterial genome diversification within the microbiota and establishes a framework for understanding how strain level variation within the microbiota impacts human health.

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking

Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the dynamics of this process are difficult to characterize in dominant gut species in their complex in vivo environment. Here we show that the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By analyzing >400,000 lineages across four human Bacteroides strains in gnotobiotic mice, we observed positive selection on thousands of cryptic variants - most of which were unrelated to their original gene knockouts. The spectrum of fitness benefits varied between species, and displayed diverse tradeoffs over time and in different dietary conditions, enabling inferences of their underlying function. These results suggest that within-host adaptations arise from an intense competition between numerous contending variants, which can strongly influence their emergent evolutionary tradeoffs.

Dynamics of bacterial recombination in the human gut microbiome

Horizontal gene transfer (HGT) is a ubiquitous force in microbial evolution. Previous work has shown that the human gut is a hotspot for gene transfer between species, but the more subtle exchange of variation within species-also known as recombination-remains poorly characterized in this ecosystem. Here, we show that the genetic structure of the human gut microbiome provides an opportunity to measure recent recombination events from sequenced fecal samples, enabling quantitative comparisons across diverse commensal species that inhabit a common environment. By analyzing recent recombination events in the core genomes of 29 human gut bacteria, we observed widespread heterogeneities in the rates and lengths of transferred fragments, which are difficult to explain by existing models of ecological isolation or homology-dependent recombination rates. We also show that natural selection helps facilitate the spread of genetic variants across strain backgrounds, both within individual hosts and across the broader population. These results shed light on the dynamics of in situ recombination, which can strongly constrain the adaptability of gut microbial communities.

Commensal antimicrobial resistance mediates microbiome resilience to antibiotic disruption

Despite their therapeutic benefits, antibiotics exert collateral damage on the microbiome and promote antimicrobial resistance. However, the mechanisms governing microbiome recovery from antibiotics are poorly understood. Treatment of Mycobacterium tuberculosis, the world's most common infection, represents the longest antimicrobial exposure in humans. Here, we investigate gut microbiome dynamics over 20 months of multidrug-resistant tuberculosis (TB) and 6 months of drug-sensitive TB treatment in humans. We find that gut microbiome dynamics and TB clearance are shared predictive cofactors of the resolution of TB-driven inflammation. The initial severe taxonomic and functional microbiome disruption, pathobiont domination, and enhancement of antibiotic resistance that initially accompanied long-term antibiotics were countered by later recovery of commensals. This resilience was driven by the competing evolution of antimicrobial resistance mutations in pathobionts and commensals, with commensal strains with resistance mutations reestablishing dominance. Fecal-microbiota transplantation of the antibiotic-resistant commensal microbiome in mice recapitulated resistance to further antibiotic disruption. These findings demonstrate that antimicrobial resistance mutations in commensals can have paradoxically beneficial effects by promoting microbiome resilience to antimicrobials and identify microbiome dynamics as a predictor of disease resolution in antibiotic therapy of a chronic infection.

Adaptation of Anaerobic Digestion Microbial Communities to High Ammonium Levels: Insights from Strain-Resolved Metagenomics

Ammonia release from proteinaceous feedstocks represents the main inhibitor of the anaerobic digestion (AD) process, which can result in a decreased biomethane yield or even complete failure of the process. The present study focused on the adaptation of mesophilic AD communities to a stepwise increase in the concentration of ammonium chloride in synthetic medium with casein used as the carbon source. An adaptation process occurring over more than 20 months allowed batch reactors to reach up to 20 g of NH4+ N/L without collapsing in acidification nor ceasing methane production. To decipher the microbial dynamics occurring during the adaptation and determine the genes mostly exposed to selective pressure, a combination of biochemical and metagenomics analyses was performed, reconstructing the strains of key species and tracking them over time. Subsequently, the adaptive metabolic mechanisms were delineated by following the single nucleotide variants (SNVs) characterizing the strains and prioritizing the associated genes according to their function. An in-depth exploration of the archaeon Methanoculleus bourgensis vb3066 and the putative syntrophic acetate-oxidizing bacteria Acetomicrobium sp. ma133 identified positively selected SNVs on genes involved in stress adaptation. The intraspecies diversity with multiple coexisting strains in a temporal succession pattern allows us to detect the presence of an additional level of diversity within the microbial community beyond the species level.

LRTK: a platform agnostic toolkit for linked-read analysis of both human genome and metagenome

BACKGROUND

Linked-read sequencing technologies generate high-base quality short reads that contain extrapolative information on long-range DNA connectedness. These advantages of linked-read technologies are well known and have been demonstrated in many human genomic and metagenomic studies. However, existing linked-read analysis pipelines (e.g., Long Ranger) were primarily developed to process sequencing data from the human genome and are not suited for analyzing metagenomic sequencing data. Moreover, linked-read analysis pipelines are typically limited to 1 specific sequencing platform.

FINDINGS

To address these limitations, we present the Linked-Read ToolKit (LRTK), a unified and versatile toolkit for platform agnostic processing of linked-read sequencing data from both human genome and metagenome. LRTK provides functions to perform linked-read simulation, barcode sequencing error correction, barcode-aware read alignment and metagenome assembly, reconstruction of long DNA fragments, taxonomic classification and quantification, and barcode-assisted genomic variant calling and phasing. LRTK has the ability to process multiple samples automatically and provides users with the option to generate reproducible reports during processing of raw sequencing data and at multiple checkpoints throughout downstream analysis. We applied LRTK on linked reads from simulation, mock community, and real datasets for both human genome and metagenome. We showcased LRTK's ability to generate comparative performance results from preceding benchmark studies and to report these results in publication-ready HTML document plots.

CONCLUSIONS

LRTK provides comprehensive and flexible modules along with an easy-to-use Python-based workflow for processing linked-read sequencing datasets, thereby filling the current gap in the field caused by platform-centric genome-specific linked-read data analysis tools.

Strain-resolved metagenomics approaches applied to biogas upgrading

Genetic heterogeneity is a common trait in microbial populations, caused by de novo mutations and changes in variant frequencies over time. Microbes can thus differ genetically within the same species and acquire different phenotypes. For instance, performance and stability of anaerobic reactors are linked to the composition of the microbiome involved in the digestion process and to the environmental parameters imposing selective pressure on the metagenome, shaping its evolution. Changes at the strain level have the potential to determine variations in microbial functions, and their characterization could provide new insight into ecological and evolutionary processes driving anaerobic digestion. In this work, single nucleotide variant dynamics were studied in two time-course biogas upgrading experiments, testing alternative carbon sources and the response to exogenous hydrogen addition. A cumulative total of 76,229 and 64,289 high-confidence single nucleotide variants were discerned in the experiments related to carbon substrate availability and hydrogen addition, respectively. By combining complementary bioinformatic approaches, the study reconstructed the precise strain count-two for both hydrogenotrophic archaea-and tracked their abundance over time, while also characterizing tens of genes under strong selection. Results in the dominant archaea revealed the presence of nearly 100 variants within genes encoding enzymes involved in hydrogenotrophic methanogenesis. In the bacterial counterparts, 119 mutations were identified across 23 genes associated with the Wood-Ljungdahl pathway, suggesting a possible impact on the syntrophic acetate-oxidation process. Strain replacement events took place in both experiments, confirming the trends suggested by the variants trajectories and providing a comprehensive understanding of the biogas upgrading microbiome at the strain level. Overall, this resolution level allowed us to reveal fine-scale evolutionary mechanisms, functional dynamics, and strain-level metabolic variation that could contribute to the selection of key species actively involved in the carbon dioxide fixation process.

Effect of diet on the evolution of gut commensal bacteria

The gut microbiota, comprising trillions of diverse microorganisms inhabiting the intestines of animals, forms a complex and indispensable ecosystem with profound implications for the host's well-being. Its functions include contributing to developing the host's immune response, aiding in nutrient digestion, synthesizing essential compounds, acting as a barrier against pathogen invasion, and influencing the development or regression of various pathologies. The dietary habits of the host directly impact this intricate community of gut microbes. Diet influences the composition and function of the gut microbiota through alterations in gene expression, enzymatic activity, and metabolome. While the impact of diet on gut ecology is well-established, the investigation into the relationship between dietary consumption and microbial genotypic diversity has been limited. This review provides an overview of the relationship between diet and gut microbiota, emphasizing the impact of host nutrition on both short- and long-term evolution in the mammalian gut. It is evident that the evolution of the gut microbiota occurs even on short timescales through the acquisition of novel mutations, within the gut bacteria of individual hosts. Consequently, we discuss the importance of considering alterations in bacterial genomic diversity when analyzing microbiota-dependent effects on host physiology. Future investigations into the various microbiota-related traits shall greatly benefit from a deeper understanding of commensal bacterial evolutionary adaptation.

Cross-cohort single-nucleotide-variant profiling of gut microbiota suggests a novel gut-health assessment approach

IMPORTANCE

Most studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

Gut immune responses and evolution of the gut microbiome-a hypothesis

The gut microbiome is an assemblage of microbes that have profound effects on their hosts. The composition of the microbiome is affected by bottom-up, among-taxa interactions and by top-down, host effects, which includes the host immune response. While the high-level composition of the microbiome is generally stable over time, component strains and genotypes will constantly be evolving, with both bottom-up and top-down effects acting as selection pressures, driving microbial evolution. Secretory IgA is a major feature of the gut's adaptive immune response, and a substantial proportion of gut bacteria are coated with IgA, though the effect of this on bacteria is unclear. Here we hypothesize that IgA binding to gut bacteria is a selection pressure that will drive the evolution of IgA-bound bacteria, so that they will have a different evolutionary trajectory than those bacteria not bound by IgA. We know very little about the microbiome of wild animals and even less about their gut immune responses, but it must be a priority to investigate this hypothesis to understand if and how host immune responses contribute to microbiome evolution.

Eco-evolutionary feedbacks in the human gut microbiome

Gut microbiota can evolve within their hosts on human-relevant timescales, but little is known about how these changes influence (or are influenced by) the composition of their local community. Here, by combining ecological and evolutionary analyses of a large cohort of human gut metagenomes, we show that the short-term evolution of the microbiota is linked with shifts in its ecological structure. These correlations are not simply explained by expansions of the evolving species, and often involve additional fluctuations in distantly related taxa. We show that similar feedbacks naturally emerge in simple resource competition models, even in the absence of cross-feeding or predation. These results suggest that the structure and function of host microbiota may be shaped by their local evolutionary history, which could have important implications for personalized medicine and microbiome engineering.

Prolonged delays in human microbiota transmission after a controlled antibiotic perturbation

Humans constantly encounter new microbes, but few become long-term residents of the adult gut microbiome. Classical theories predict that colonization is determined by the availability of open niches, but it remains unclear whether other ecological barriers limit commensal colonization in natural settings. To disentangle these effects, we used a controlled perturbation with the antibiotic ciprofloxacin to investigate the dynamics of gut microbiome transmission in 22 households of healthy, cohabiting adults. Colonization was rare in three-quarters of antibiotic-taking subjects, whose resident strains rapidly recovered in the week after antibiotics ended. In contrast, the remaining antibiotic-taking subjects exhibited lasting responses, with extensive species losses and transient expansions of potential opportunistic pathogens. These subjects experienced elevated rates of commensal colonization, but only after long delays: many new colonizers underwent sudden, correlated expansions months after the antibiotic perturbation. Furthermore, strains that had previously transmitted between cohabiting partners rarely recolonized after antibiotic disruptions, showing that colonization displays substantial historical contingency. This work demonstrates that there remain substantial ecological barriers to colonization even after major microbiome disruptions, suggesting that dispersal interactions and priority effects limit the pace of community change.

Emerging threat of antimicrobial resistance in Neisseria gonorrhoeae: pathogenesis, treatment challenges, and potential for vaccine development

The continuous rise of antimicrobial resistance (AMR) is a serious concern as it endangers the effectiveness of healthcare interventions that rely on antibiotics in the long run. The increasing resistance of Neisseria gonorrhoeae, the bacteria responsible for causing gonorrhea, to commonly used antimicrobial drugs, is a major concern. This has now become a critical global health crisis. In the coming years, there is a risk of a hidden epidemic caused by the emergence of gonococcal AMR. This will worsen the global situation. Infections caused by N. gonorrhoeae were once considered easily treatable. However, over time, they have become increasingly resistant to commonly used therapeutic medications, such as penicillin, ciprofloxacin, and azithromycin. As a result, this pathogen is developing into a true "superbug," which means that ceftriaxone is now the only available option for initial empirical treatment. Effective management strategies are urgently needed to prevent severe consequences, such as infertility and pelvic inflammatory disease, which can result from delayed intervention. This review provides a thorough analysis of the escalating problem of N. gonorrhoeae, including its pathogenesis, current treatment options, the emergence of drug-resistant mechanisms, and the potential for vaccine development. We aim to provide valuable insights for healthcare practitioners, policymakers, and researchers in their efforts to combat N. gonorrhoeae antibiotic resistance by elucidating the multifaceted aspects of this global challenge.

Intrahost evolution of the gut microbiota

A massive number of microorganisms, belonging to different species, continuously divide inside the guts of animals and humans. The large size of these communities and their rapid division times imply that we should be able to watch microbial evolution in the gut in real time, in a similar manner to what has been done in vitro. Here, we review recent findings on how natural selection shapes intrahost evolution (also known as within-host evolution), with a focus on the intestines of mice and humans. The microbiota of a healthy host is not as static as initially thought from the information measured at only one genomic marker. Rather, the genomes of each gut-colonizing species can be highly dynamic, and such dynamism seems to be related to the microbiota species diversity. Genetic and bioinformatic tools, and analysis of time series data, allow quantification of the selection strength on emerging mutations and horizontal transfer events in gut ecosystems. The drivers and functional consequences of gut evolution can now begin to be grasped. The rules of this intrahost microbiota evolution, and how they depend on the biology of each species, need to be understood for more effective development of microbiota therapies to help maintain or restore host health.

Guidelines for microbiome studies in renal physiology

Gut microbiome research has increased dramatically in the last decade, including in renal health and disease. The field is moving from experiments showing mere association to causation using both forward and reverse microbiome approaches, leveraging tools such as germ-free animals, treatment with antibiotics, and fecal microbiota transplantations. However, we are still seeing a gap between discovery and translation that needs to be addressed, so that patients can benefit from microbiome-based therapies. In this guideline paper, we discuss the key considerations that affect the gut microbiome of animals and clinical studies assessing renal function, many of which are often overlooked, resulting in false-positive results. For animal studies, these include suppliers, acclimatization, baseline microbiota and its normalization, littermates and cohort/cage effects, diet, sex differences, age, circadian differences, antibiotics and sweeteners, and models used. Clinical studies have some unique considerations, which include sampling, gut transit time, dietary records, medication, and renal phenotypes. We provide best-practice guidance on sampling, storage, DNA extraction, and methods for microbial DNA sequencing (both 16S rRNA and shotgun metagenome). Finally, we discuss follow-up analyses, including tools available, metrics, and their interpretation, and the key challenges ahead in the microbiome field. By standardizing study designs, methods, and reporting, we will accelerate the findings from discovery to translation and result in new microbiome-based therapies that may improve renal health.

Ariadne: synthetic long read deconvolution using assembly graphs

Synthetic long read sequencing techniques such as UST's TELL-Seq and Loop Genomics' LoopSeq combine 3[Formula: see text] barcoding with standard short-read sequencing to expand the range of linkage resolution from hundreds to tens of thousands of base-pairs. However, the lack of a 1:1 correspondence between a long fragment and a 3[Formula: see text] unique molecular identifier confounds the assignment of linkage between short reads. We introduce Ariadne, a novel assembly graph-based synthetic long read deconvolution algorithm, that can be used to extract single-species read-clouds from synthetic long read datasets to improve the taxonomic classification and de novo assembly of complex populations, such as metagenomes.

A macroecological perspective on genetic diversity in the human gut microbiome

While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of the genetic diversity that it harbors. Research efforts have demonstrated that a considerable fraction of within-host genetic variation in the human gut is driven by the ecological dynamics of co-occurring strains belonging to the same species, suggesting that an ecological lens may provide insight into empirical patterns of genetic diversity. Indeed, an ecological model of self-limiting growth and environmental noise known as the Stochastic Logistic Model (SLM) was recently shown to successfully predict the temporal dynamics of strains within a single human host. However, its ability to predict patterns of genetic diversity across human hosts has yet to be tested. In this manuscript I determine whether the predictions of the SLM explain patterns of genetic diversity across unrelated human hosts for 22 common microbial species. Specifically, the stationary distribution of the SLM explains the distribution of allele frequencies across hosts and predicts the fraction of hosts harboring a given allele (i.e., prevalence) for a considerable fraction of sites. The accuracy of the SLM was correlated with independent estimates of strain structure, suggesting that patterns of genetic diversity in the gut microbiome follow statistically similar forms across human hosts due to the existence of strain-level ecology.

Pulsed antibiotic treatments of gnotobiotic mice manifest in complex bacterial community dynamics and resistance effects

Bacteria can evolve to withstand a wide range of antibiotics (ABs) by using various resistance mechanisms. How ABs affect the ecology of the gut microbiome is still poorly understood. We investigated strain-specific responses and evolution during repeated AB perturbations by three clinically relevant ABs, using gnotobiotic mice colonized with a synthetic bacterial community (oligo-mouse-microbiota). Over 80 days, we observed resilience effects at the strain and community levels, and we found that they were correlated with modulations of the estimated growth rate and levels of prophage induction as determined from metagenomics data. Moreover, we tracked mutational changes in the bacterial populations, and this uncovered clonal expansion and contraction of haplotypes and selection of putative AB resistance-conferring SNPs. We functionally verified these mutations via reisolation of clones with increased minimum inhibitory concentration (MIC) of ciprofloxacin and tetracycline from evolved communities. This demonstrates that host-associated microbial communities employ various mechanisms to respond to selective pressures that maintain community stability.

Assembly and analytical validation of a metagenomic reference catalog of human gut microbiota based on co-barcoding sequencing

Human gut microbiota is associated with human health and disease, and is known to have the second-largest genome in the human body. The microbiota genome is important for their functions and metabolites; however, accurate genomic access to the microbiota of the human gut is hindered due to the difficulty of cultivating and the shortcomings of sequencing technology. Therefore, we applied the stLFR library construction method to assemble the microbiota genomes and demonstrated that assembly property outperformed standard metagenome sequencing. Using the assembled genomes as references, SNP, INDEL, and HGT gene analyses were performed. The results demonstrated significant differences in the number of SNPs and INDELs among different individuals. The individual displayed a unique species variation spectrum, and the similarity of strains within individuals decreased over time. In addition, the coverage depth analysis of the stLFR method shows that a sequencing depth of 60X is sufficient for SNP calling. HGT analysis revealed that the genes involved in replication, recombination and repair, mobilome prophages, and transposons were the most transferred genes among different bacterial species in individuals. A preliminary framework for human gut microbiome studies was established using the stLFR library construction method.

Ecological Stability Emerges at the Level of Strains in the Human Gut Microbiome

The human gut microbiome harbors substantial ecological diversity at the species level as well as at the strain level within species. In healthy hosts, species abundance fluctuations in the microbiome are thought to be stable, and these fluctuations can be described by macroecological laws. However, it is less clear how strain abundances change over time. An open question is whether individual strains behave like species themselves, exhibiting stability and following the macroecological relationships known to hold at the species level, or whether strains have different dynamics, perhaps due to the relatively close phylogenetic relatedness of cocolonizing lineages. Here, we analyze the daily dynamics of intraspecific genetic variation in the gut microbiomes of four healthy, densely longitudinally sampled hosts. First, we find that the overall genetic diversity of a large majority of species is stationary over time despite short-term fluctuations. Next, we show that fluctuations in abundances in approximately 80% of strains analyzed can be predicted with a stochastic logistic model (SLM), an ecological model of a population experiencing environmental fluctuations around a fixed carrying capacity, which has previously been shown to capture statistical properties of species abundance fluctuations. The success of this model indicates that strain abundances typically fluctuate around a fixed carrying capacity, suggesting that most strains are dynamically stable. Finally, we find that the strain abundances follow several empirical macroecological laws known to hold at the species level. Together, our results suggest that macroecological properties of the human gut microbiome, including its stability, emerge at the level of strains. IMPORTANCE To date, there has been an intense focus on the ecological dynamics of the human gut microbiome at the species level. However, there is considerable genetic diversity within species at the strain level, and these intraspecific differences can have important phenotypic effects on the host, impacting the ability to digest certain foods and metabolize drugs. Thus, to fully understand how the gut microbiome operates in times of health and sickness, its ecological dynamics may need to be quantified at the level of strains. Here, we show that a large majority of strains maintain stable abundances for periods of months to years, exhibiting fluctuations in abundance that can be well described by macroecological laws known to hold at the species level, while a smaller percentage of strains undergo rapid, directional changes in abundance. Overall, our work indicates that strains are an important unit of ecological organization in the human gut microbiome.

Within-host evolution of the gut microbiome

Gut bacteria inhabit a complex environment that is shaped by interactions with their host and the other members of the community. While these ecological interactions have evolved over millions of years, mounting evidence suggests that gut commensals can evolve on much shorter timescales as well, by acquiring new mutations within individual hosts. In this review, we highlight recent progress in understanding the causes and consequences of short-term evolution in the mammalian gut, from experimental evolution in murine hosts to longitudinal tracking of human cohorts. We also discuss new opportunities for future progress by expanding the repertoire of focal species, hosts, and surrounding communities, and by combining deep-sequencing technologies with quantitative frameworks from population genetics.

Advances in Lactobacillus Restoration for β-Lactam Antibiotic-Induced Dysbiosis: A System Review in Intestinal Microbiota and Immune Homeostasis

A balanced gut microbiota and their metabolites are necessary for the maintenance of the host's health. The antibiotic-induced dysbiosis can cause the disturbance of the microbial community, influence the immune homeostasis and induce susceptibility to metabolic- or immune-mediated disorders and diseases. The Lactobacillus and their metabolites or components affect the function of the host's immune system and result in microbiota-mediated restoration. Recent data have indicated that, by altering the composition and functions of gut microbiota, antibiotic exposure can also lead to a number of specific pathologies, hence, understanding the potential mechanisms of the interactions between gut microbiota dysbiosis and immunological homeostasis is very important. The Lactobacillus strategies for detecting the associations between the restoration of the relatively imbalanced microbiome and gut diseases are provided in this discussion. In this review, we discuss the recently discovered connections between microbial communities and metabolites in the Lactobacillus treatment of β-lactam antibiotic-induced dysbiosis, and establish the relationship between commensal bacteria and host immunity under this imbalanced homeostasis of the gut microbiota.

Genome-Centric Dynamics Shape the Diversity of Oral Bacterial Populations

Two major viewpoints have been put forward for how microbial populations change, differing in whether adaptation is driven principally by gene-centric or genome-centric processes. Longitudinal sampling at microbially relevant timescales, i.e., days to weeks, is critical for distinguishing these mechanisms. Because of its significance for both microbial ecology and human health and its accessibility and high level of curation, we used the oral microbiota to study bacterial intrapopulation genome dynamics. Metagenomes were generated by shotgun sequencing of total community DNA from the healthy tongues of 17 volunteers at four to seven time points obtained over intervals of days to weeks. We obtained 390 high-quality metagenome-assembled genomes (MAGs) defining population genomes from 55 genera. The vast majority of genes in each MAG were tightly linked over the 2-week sampling window, indicating that the majority of the population's genomes were temporally stable at the MAG level. MAG-defined populations were composed of up to 5 strains, as determined by single-nucleotide-variant frequencies. Although most were stable over time, individual strains carrying over 100 distinct genes that rose from low abundance to dominance in a population over a period of days were detected. These results indicate a genome-wide as opposed to a gene-level process of population change. We infer that genome-wide selection of ecotypes is the dominant mode of adaptation in the oral populations over short timescales. IMPORTANCE The oral microbiome represents a microbial community of critical relevance to human health. Recent studies have documented the diversity and dynamics of different bacteria to reveal a rich, stable ecosystem characterized by strain-level dynamics. However, bacterial populations and their genomes are neither monolithic nor static; their genomes are constantly evolving to lose, gain, or alter their functional potential. To better understand how microbial genomes change in complex communities, we used culture-independent approaches to reconstruct the genomes (MAGs) for bacterial populations that approximated different species, in 17 healthy donors' mouths over a 2-week window. Our results underscored the importance of strain-level dynamics, which agrees with and expands on the conclusions of previous research. Altogether, these observations reveal patterns of genomic dynamics among strains of oral bacteria occurring over a matter of days.

Genotyping Microbial Communities with MIDAS2: From Metagenomic Reads to Allele Tables

The Metagenomic Intra-Species Diversity Analysis System 2 (MIDAS2) is a scalable pipeline that identifies single nucleotide variants and gene copy number variants in metagenomes using comprehensive reference databases built from public microbial genome collections (metagenotyping). MIDAS2 is the first metagenotyping tool with functionality to control metagenomic read mapping filters and to customize the reference database to the microbial community, features that improve the precision and recall of detected variants. In this article we present four basic protocols for the most common use cases of MIDAS2, along with supporting protocols for installation and use. In addition, we provide in-depth guidance on adjusting command line parameters, editing the reference database, optimizing hardware utilization, and understanding the metagenotyping results. All the steps of metagenotyping, from raw sequencing reads to population genetic analysis, are demonstrated with example data in two downloadable sequencing libraries of single-end metagenomic reads representing a mixture of multiple bacterial species. This set of protocols empowers users to accurately genotype hundreds of species in thousands of samples, providing rich genetic data for studying the evolution and strain-level ecology of microbial communities. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Species prescreening Basic Protocol 2: Download MIDAS reference database Basic Protocol 3: Population single nucleotide variant calling Basic Protocol 4: Pan-genome copy number variant calling Support Protocol 1: Installing MIDAS2 Support Protocol 2: Command line inputs Support Protocol 3: Metagenotyping with a custom collection of genomes Support Protocol 4: Metagenotyping with advanced parameters.

Detecting bacterial adaptation within individual microbiomes

The human microbiome harbours a large capacity for within-person adaptive mutations. Commensal bacterial strains can stably colonize a person for decades, and billions of mutations are generated daily within each person's microbiome. Adaptive mutations emerging during health might be driven by selective forces that vary across individuals, vary within an individual, or are completely novel to the human population. Mutations emerging within individual microbiomes might impact the immune system, the metabolism of nutrients or drugs, and the stability of the community to perturbations. Despite this potential, relatively little attention has been paid to the possibility of adaptive evolution within complex human-associated microbiomes. This review discusses the promise of studying within-microbiome adaptation, the conceptual and technical limitations that may have contributed to an underappreciation of adaptive de novo mutations occurring within microbiomes to date, and methods for detecting recent adaptive evolution. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Gut Bacteria and Neurotransmitters

Gut bacteria play an important role in the digestion of food, immune activation, and regulation of entero-endocrine signaling pathways, but also communicate with the central nervous system (CNS) through the production of specific metabolic compounds, e.g., bile acids, short-chain fatty acids (SCFAs), glutamate (Glu), γ-aminobutyric acid (GABA), dopamine (DA), norepinephrine (NE), serotonin (5-HT) and histamine. Afferent vagus nerve (VN) fibers that transport signals from the gastro-intestinal tract (GIT) and gut microbiota to the brain are also linked to receptors in the esophagus, liver, and pancreas. In response to these stimuli, the brain sends signals back to entero-epithelial cells via efferent VN fibers. Fibers of the VN are not in direct contact with the gut wall or intestinal microbiota. Instead, signals reach the gut microbiota via 100 to 500 million neurons from the enteric nervous system (ENS) in the submucosa and myenteric plexus of the gut wall. The modulation, development, and renewal of ENS neurons are controlled by gut microbiota, especially those with the ability to produce and metabolize hormones. Signals generated by the hypothalamus reach the pituitary and adrenal glands and communicate with entero-epithelial cells via the hypothalamic pituitary adrenal axis (HPA). SCFAs produced by gut bacteria adhere to free fatty acid receptors (FFARs) on the surface of intestinal epithelial cells (IECs) and interact with neurons or enter the circulatory system. Gut bacteria alter the synthesis and degradation of neurotransmitters. This review focuses on the effect that gut bacteria have on the production of neurotransmitters and vice versa.

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.