Elevated rates of horizontal gene transfer in the industrialized human microbiome.

Industrialization has impacted the human gut ecosystem, resulting in altered microbiome composition and diversity. Whether bacterial genomes may also adapt to the industrialization of their host populations remains largely unexplored. Here, we investigate the extent to which the rates and targets of horizontal gene transfer (HGT) vary across thousands of bacterial strains from 15 human populations spanning a range of industrialization. We show that HGTs have accumulated in the microbiome over recent host generations and that HGT occurs at high frequency within individuals. Comparison across human populations reveals that industrialized lifestyles are associated with higher HGT rates and that the functions of HGTs are related to the level of host industrialization. Our results suggest that gut bacteria continuously acquire new functionality based on host lifestyle and that high rates of HGT may be a recent development in human history linked to industrialization.

Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease.

BACKGROUND: The human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case-control results has made the identification of consistent and generalizable URT-disease associations difficult. RESULTS: In order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case-control URT studies, with approximately 2-3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states. CONCLUSIONS: We found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Longitudinal analysis reveals transition barriers between dominant ecological states in the gut microbiome.

The Pioneer 100 Wellness Project involved quantitatively profiling 108 participants' molecular physiology over time, including genomes, gut microbiomes, blood metabolomes, blood proteomes, clinical chemistries, and data from wearable devices. Here, we present a longitudinal analysis focused specifically around the Pioneer 100 gut microbiomes. We distinguished a subpopulation of individuals with reduced gut diversity, elevated relative abundance of the genus Prevotella, and reduced levels of the genus Bacteroides We found that the relative abundances of Bacteroides and Prevotella were significantly correlated with certain serum metabolites, including omega-6 fatty acids. Primary dimensions in distance-based redundancy analysis of clinical chemistries explained 18.5% of the variance in bacterial community composition, and revealed a Bacteroides/Prevotella dichotomy aligned with inflammation and dietary markers. Finally, longitudinal analysis of gut microbiome dynamics within individuals showed that direct transitions between Bacteroides-dominated and Prevotella-dominated communities were rare, suggesting the presence of a barrier between these states. One implication is that interventions seeking to transition between Bacteroides- and Prevotella-dominated communities will need to identify permissible paths through ecological state-space that circumvent this apparent barrier.

Correcting for batch effects in case-control microbiome studies.

High-throughput data generation platforms, like mass-spectrometry, microarrays, and second-generation sequencing are susceptible to batch effects due to run-to-run variation in reagents, equipment, protocols, or personnel. Currently, batch correction methods are not commonly applied to microbiome sequencing datasets. In this paper, we compare different batch-correction methods applied to microbiome case-control studies. We introduce a model-free normalization procedure where features (i.e. bacterial taxa) in case samples are converted to percentiles of the equivalent features in control samples within a study prior to pooling data across studies. We look at how this percentile-normalization method compares to traditional meta-analysis methods for combining independent p-values and to limma and ComBat, widely used batch-correction models developed for RNA microarray data. Overall, we show that percentile-normalization is a simple, non-parametric approach for correcting batch effects and improving sensitivity in case-control meta-analyses.

Systems biology approaches towards predictive microbial ecology.

Through complex interspecies interactions, microbial processes drive nutrient cycling and biogeochemistry. However, we still struggle to predict specifically which organisms, communities and biotic and abiotic processes are determining ecosystem function and how environmental changes will alter their roles and stability. While the tools to create such a predictive microbial ecology capability exist, cross-disciplinary integration of high-resolution field measurements, detailed laboratory studies and computation is essential. In this perspective, we emphasize the importance of pursuing a multiscale, systems approach to iteratively link ecological processes measured in the field to testable hypotheses that drive high-throughput laboratory experimentation. Mechanistic understanding of microbial processes gained in controlled lab systems will lead to the development of theory that can be tested back in the field. Using N2 O production as an example, we review the current status of field and laboratory research and layout a plausible path to the kind of integration that is needed to enable prediction of how N-cycling microbial communities will respond to environmental changes. We advocate for the development of realistic and predictive gene regulatory network models for environmental responses that extend from single-cell resolution to ecosystems, which is essential to understand how microbial communities involved in N2 O production and consumption will respond to future environmental conditions.

Two dynamic regimes in the human gut microbiome.

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)-a multivariate method developed for econometrics-to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.

Spatial scale drives patterns in soil bacterial diversity.

Soil microbial communities are essential for ecosystem function, but linking community composition to biogeochemical processes is challenging because of high microbial diversity and large spatial variability of most soil characteristics. We investigated soil bacterial community structure in a switchgrass stand planted on soil with a history of grassland vegetation at high spatial resolution to determine whether biogeographic trends occurred at the centimeter scale. Moreover, we tested whether such heterogeneity, if present, influenced community structure within or among ecosystems. Pronounced heterogeneity was observed at centimeter scales, with abrupt changes in relative abundance of phyla from sample to sample. At the ecosystem scale (> 10 m), however, bacterial community composition and structure were subtly, but significantly, altered by fertilization, with higher alpha diversity in fertilized plots. Moreover, by comparing these data with data from 1772 soils from the Earth Microbiome Project, it was found that 20% of bacterial taxa were shared between their site and diverse globally sourced soil samples, while grassland soils shared approximately 40% of their operational taxonomic units with the current study. By spanning several orders of magnitude, the analysis suggested that extreme patchiness characterized community structure at smaller scales but that coherent patterns emerged at larger length scales.

Evidence for a persistent microbial seed bank throughout the global ocean.

Do bacterial taxa demonstrate clear endemism, like macroorganisms, or can one site's bacterial community recapture the total phylogenetic diversity of the world's oceans? Here we compare a deep bacterial community characterization from one site in the English Channel (L4-DeepSeq) with 356 datasets from the International Census of Marine Microbes (ICoMM) taken from around the globe (ranging from marine pelagic and sediment samples to sponge-associated environments). At the L4-DeepSeq site, increasing sequencing depth uncovers greater phylogenetic overlap with the global ICoMM data. This site contained 31.7-66.2% of operational taxonomic units identified in a given ICoMM biome. Extrapolation of this overlap suggests that 1.93 × 10(11) sequences from the L4 site would capture all ICoMM bacterial phylogenetic diversity. Current technology trends suggest this limit may be attainable within 3 y. These results strongly suggest the marine biosphere maintains a previously undetected, persistent microbial seed bank.

The short-chain fatty acid receptor, FFA2, contributes to gestational glucose homeostasis.

The structure of the human gastrointestinal microbiota can change during pregnancy, which may influence gestational metabolism; however, a mechanism of action remains unclear. Here we observed that in wild-type (WT) mice the relative abundance of Actinobacteria and Bacteroidetes increased during pregnancy. Along with these changes, short-chain fatty acids (SCFAs), which are mainly produced through gut microbiota fermentation, significantly changed in both the cecum and peripheral blood throughout gestation in these mice. SCFAs are recognized by G protein-coupled receptors (GPCRs) such as free fatty acid receptor-2 (FFA2), and we have previously demonstrated that the fatty acid receptor-2 gene (Ffar2) expression is higher in pancreatic islets during pregnancy. Using female Ffar2-/- mice, we explored the physiological relevance of signaling through this GPCR and found that Ffar2-deficient female mice developed fasting hyperglycemia and impaired glucose tolerance in the setting of impaired insulin secretion compared with WT mice during, but not before, pregnancy. Insulin tolerance tests were similar in Ffar2-/- and WT mice before and during pregnancy. Next, we examined the role of FFA2 in gestational ß-cell mass, observing that Ffar2-/- mice had diminished gestational expansion of ß-cells during pregnancy. Interestingly, mouse genotype had no significant impact on the composition of the gut microbiome, but did affect the observed SCFA profiles, suggesting a functional difference in the microbiota. Together, these results suggest a potential link between increased Ffar2 expression in islets and the alteration of circulating SCFA levels, possibly explaining how changes in the gut microbiome contribute to gestational glucose homeostasis.

Ecological succession and viability of human-associated microbiota on restroom surfaces.

Human-associated bacteria dominate the built environment (BE). Following decontamination of floors, toilet seats, and soap dispensers in four public restrooms, in situ bacterial communities were characterized hourly, daily, and weekly to determine their successional ecology. The viability of cultivable bacteria, following the removal of dispersal agents (humans), was also assessed hourly. A late-successional community developed within 5 to 8 h on restroom floors and showed remarkable stability over weeks to months. Despite late-successional dominance by skin- and outdoor-associated bacteria, the most ubiquitous organisms were predominantly gut-associated taxa, which persisted following exclusion of humans. Staphylococcus represented the majority of the cultivable community, even after several hours of human exclusion. Methicillin-resistant Staphylococcus aureus (MRSA)-associated virulence genes were found on floors but were not present in assembled Staphylococcus pan-genomes. Viral abundances, which were predominantly enterophages, human papilloma virus, and herpesviruses, were significantly correlated with bacterial abundances and showed an unexpectedly low virus-to-bacterium ratio in surface-associated samples, suggesting that bacterial hosts are mostly dormant on BE surfaces.

Aquarium microbiome response to ninety-percent system water change: Clues to microbiome management.

The bacterial community composition and structure of water from an established teleost fish system was examined before, during and after a major water change to explore the impact of such a water-change disturbance on the stability of the aquarium water microbiome. The diversity and evenness of the bacterial community significantly increased following the 90% water replacement. While the change in bacterial community structure was significant, it was slight, and was also weakly correlated with changes in physicochemical parameters. Interestingly there was a significant shift in the correlative network relationships between operational taxonomic units from before to after the water replacement. We suggest this shift in network structure is due to the turnover of many taxa during the course of water replacement. These observations will inform future studies into manipulation of the microbiome by changing system environmental parameter values to optimize resident animal health.

Metagenomic estimation of dietary intake from human stool.

Dietary intake is tightly coupled to gut microbiota composition, human metabolism, and to the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually quantified using dietary questionnaires, which tend to focus on broad food categories, suffer from self-reporting biases, and require strong compliance from study participants. Here, we present MEDI (Metagenomic Estimation of Dietary Intake): a method for quantifying dietary intake using food-derived DNA in stool metagenomes. We show that food items can be accurately detected in metagenomic shotgun sequencing data, even when present at low abundances (>10 reads). Furthermore, we show how dietary intake, in terms of DNA abundance from specific organisms, can be converted into a detailed metabolic representation of nutrient intake. MEDI could identify the onset of solid food consumption in infants and it accurately predicted food questionnaire responses in an adult population. Additionally, we were able to identify specific dietary features associated with metabolic syndrome in a large clinical cohort, providing a proof-of-concept for detailed quantification of individual-specific dietary patterns without the need for questionnaires.

Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut.

Clostridioides difficile colonizes up to 30-40% of community-dwelling adults without causing disease. C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S. and typically develop in individuals following disruption of the gut microbiota due to antibiotic or chemotherapy treatments. Further treatment of CDI with antibiotics is not always effective and can lead to antibiotic resistance and recurrent infections (rCDI). The most effective treatment for rCDI is the reestablishment of an intact microbiota via fecal microbiota transplants (FMTs). However, the success of FMTs has been difficult to generalize because the microbial interactions that prevent engraftment and facilitate the successful clearance of C. difficile are still only partially understood. Here we show how microbial community-scale metabolic models (MCMMs) accurately predicted known instances of C. difficile colonization susceptibility or resistance in vitro and in vivo. MCMMs provide detailed mechanistic insights into the ecological interactions that govern C. difficile engraftment, like cross-feeding or competition involving metabolites like succinate, trehalose, and ornithine, which differ from person to person. Indeed, three distinct C. difficile metabolic niches emerge from our MCMMs, two associated with positive growth rates and one that represents non-growth, which are consistently observed across 15,204 individuals from five independent cohorts. Finally, we show how MCMMs can predict personalized engraftment and C. difficile growth suppression for a probiotic cocktail (VE303) designed to replace FMTs for the treatment rCDI. Overall, this powerful modeling approach predicts personalized C. difficile engraftment risk and can be leveraged to assess probiotic treatment efficacy. MCMMs could be extended to understand the mechanistic underpinnings of personalized engraftment of other opportunistic bacterial pathogens, beneficial probiotic organisms, or more complex microbial consortia.

Island biogeography theory provides a plausible explanation for why larger vertebrates and taller humans have more diverse gut microbiomes.

Prior work has shown a positive scaling relationship between vertebrate body size, human height, and gut microbiome alpha diversity. This observation mirrors commonly observed species area relationships (SAR) in many other ecosystems. Here, we expand these observations to several large data sets, showing that this size-diversity scaling relationship is independent of relevant covariates, like diet, body mass index, age, sex, bowel movement frequency, antibiotic usage, and cardiometabolic health markers. Island biogeography theory (IBT), which predicts that larger islands tend to harbor greater species diversity through neutral demographic processes, provides a simple mechanism for positive SARs. Using gut-adapted IBT model, we demonstrated that increasing the length of a flow-through ecosystem led to increased species diversity, closely matching our empirical observations. We delve into the possible clinical implications of these SARs in the American Gut cohort. Consistent with prior observations that lower alpha diversity is a risk factor for Clostridioides difficile infection (CDI), we found that individuals who reported a history of CDI were shorter than those who did not and that this relationship was mediated by alpha diversity. We observed that vegetable consumption had a much stronger association with CDI history, which was also partially mediated by alpha diversity. In summary, we find that the positive scaling observed between body size and gut alpha diversity can be plausibly explained by a gut-adapted IBT model, may be related to CDI risk, and vegetable intake appears to independently mitigate this risk, although additional work is needed to validate the potential disease risk implications.

Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes.

The human gut pathogen Clostridioides difficile displays extreme genetic variability and confronts a changeable nutrient landscape in the gut. We mapped gut microbiota inter-species interactions impacting the growth and toxin production of diverse C. difficile strains in different nutrient environments. Although negative interactions impacting C. difficile are prevalent in environments promoting resource competition, they are sparse in an environment containing C. difficile-preferred carbohydrates. C. difficile strains display differences in interactions with Clostridium scindens and the ability to compete for proline. C. difficile toxin production displays substantial community-context dependent variation and does not trend with growth-mediated inter-species interactions. C. difficile shows substantial differences in transcriptional profiles in the presence of the closely related species C. hiranonis or C. scindens. In co-culture with C. hiranonis, C. difficile exhibits massive alterations in metabolism and other cellular processes, consistent with their high metabolic overlap. Further, Clostridium hiranonis inhibits the growth and toxin production of diverse C. difficile strains across different nutrient environments and ameliorates the disease severity of a C. difficile challenge in a murine model. In sum, strain-level variability and nutrient environments are major variables shaping gut microbiota interactions with C. difficile.

Generally-healthy individuals with aberrant bowel movement frequencies show enrichment for microbially-derived blood metabolites associated with reduced kidney function.

Bowel movement frequency (BMF) has been linked to changes in the composition of the human gut microbiome and to many chronic conditions, like metabolic disorders, neurodegenerative diseases, chronic kidney disease (CKD), and other intestinal pathologies like irritable bowel syndrome and inflammatory bowel disease. Lower BMF (constipation) can lead to compromised intestinal barrier integrity and a switch from saccharolytic to proteolytic fermentation within the microbiota, giving rise to microbially-derived toxins that may make their way into circulation and cause damage to organ systems. However, the connections between BMF, gut microbial metabolism, and the early-stage development and progression of chronic disease remain underexplored. Here, we examined the phenotypic impact of BMF variation in a cohort of generally-healthy, community dwelling adults with detailed clinical, lifestyle, and multi-omic data. We showed significant differences in microbially-derived blood plasma metabolites, gut bacterial genera, clinical chemistries, and lifestyle factors across BMF groups that have been linked to inflammation, cardiometabolic health, liver function, and CKD severity and progression. We found that the higher plasma levels of 3-indoxyl sulfate (3-IS), a microbially-derived metabolite associated with constipation, was in turn negatively associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. Causal mediation analysis revealed that the effect of BMF on eGFR was significantly mediated by 3-IS. Finally, we identify self-reported diet, lifestyle, and psychological factors associated with BMF variation, which indicate several common-sense strategies for mitigating constipation and diarrhea. Overall, we suggest that aberrant BMF is an underappreciated risk factor in the development of chronic diseases, even in otherwise healthy populations.

Microbial community-scale metabolic modelling predicts personalized short-chain fatty acid production profiles in the human gut.

Microbially derived short-chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. Here we use a microbial community-scale metabolic modelling (MCMM) approach to predict individual-specific SCFA production profiles to assess the impact of different dietary, prebiotic and probiotic inputs. We evaluate the quantitative accuracy of our MCMMs using in vitro and ex vivo data, plus published human cohort data. We find that MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic and probiotic interventions aimed at optimizing SCFA production in the gut. Our model represents an approach to direct gut microbiome engineering for precision health and nutrition.

Long-term NMN treatment increases lifespan and healthspan in mice in a sex dependent manner.

Nicotinamide adenine dinucleotide (NAD) is essential for many enzymatic reactions, including those involved in energy metabolism, DNA repair and the activity of sirtuins, a family of defensive deacylases. During aging, levels of NAD + can decrease by up to 50% in some tissues, the repletion of which provides a range of health benefits in both mice and humans. Whether or not the NAD + precursor nicotinamide mononucleotide (NMN) extends lifespan in mammals is not known. Here we investigate the effect of long-term administration of NMN on the health, cancer burden, frailty and lifespan of male and female mice. Without increasing tumor counts or severity in any tissue, NMN treatment of males and females increased activity, maintained more youthful gene expression patterns, and reduced overall frailty. Reduced frailty with NMN treatment was associated with increases in levels of Anerotruncus colihominis, a gut bacterium associated with lower inflammation in mice and increased longevity in humans. NMN slowed the accumulation of adipose tissue later in life and improved metabolic health in male but not female mice, while in females but not males, NMN increased median lifespan by 8.5%, possible due to sex-specific effects of NMN on NAD + metabolism. Together, these data show that chronic NMN treatment delays frailty, alters the microbiome, improves male metabolic health, and increases female mouse lifespan, without increasing cancer burden. These results highlight the potential of NAD + boosters for treating age-related conditions and the importance of using both sexes for interventional lifespan studies.

Coarse graining the human gut microbiome.

The composition of the human gut microbiome is heterogeneous across people. However, if you squint, co-abundant microbial genera emerge, accounting for much of this ecological variability. In this issue of Cell Host & Microbe, Frioux et al. provide a workflow for identifying these bacterial guilds, or "enterosignatures."