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.

Structured community transitions explain the switching capacity of microbial systems.

Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.

Fast and accurate variant identification tool for sequencing-based studies.

BACKGROUND: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness. RESULTS: We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations. CONCLUSIONS: We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes.

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Salt-responsive gut commensal modulates TH17 axis and disease.

A Western lifestyle with high salt consumption can lead to hypertension and cardiovascular disease. High salt may additionally drive autoimmunity by inducing T helper 17 (TH17) cells, which can also contribute to hypertension. Induction of TH17 cells depends on gut microbiota; however, the effect of salt on the gut microbiome is unknown. Here we show that high salt intake affects the gut microbiome in mice, particularly by depleting Lactobacillus murinus. Consequently, treatment of mice with L. murinus prevented salt-induced aggravation of actively induced experimental autoimmune encephalomyelitis and salt-sensitive hypertension by modulating TH17 cells. In line with these findings, a moderate high-salt challenge in a pilot study in humans reduced intestinal survival of Lactobacillus spp., increased TH17 cells and increased blood pressure. Our results connect high salt intake to the gut-immune axis and highlight the gut microbiome as a potential therapeutic target to counteract salt-sensitive conditions.

Metagenomic mining of regulatory elements enables programmable species-selective gene expression.

Robust and predictably performing synthetic circuits rely on the use of well-characterized regulatory parts across different genetic backgrounds and environmental contexts. Here we report the large-scale metagenomic mining of thousands of natural 5' regulatory sequences from diverse bacteria, and their multiplexed gene expression characterization in industrially relevant microbes. We identified sequences with broad and host-specific expression properties that are robust in various growth conditions. We also observed substantial differences between species in terms of their capacity to utilize exogenous regulatory sequences. Finally, we demonstrate programmable species-selective gene expression that produces distinct and diverse output patterns in different microbes. Together, these findings provide a rich resource of characterized natural regulatory sequences and a framework that can be used to engineer synthetic gene circuits with unique and tunable cross-species functionality and properties, and also suggest the prospect of ultimately engineering complex behaviors at the community level.

Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites.

Direct sampling of building wastewater has the potential to enable "precision public health" observations and interventions. Temporal sampling offers additional dynamic information that can be used to increase the informational content of individual metabolic "features", but few studies have focused on high-resolution sampling. Here, we sampled three spatially close buildings, revealing individual metabolomics features, retention time (rt) and mass-to-charge ratio (mz) pairs, that often possess similar stationary statistical properties, as expected from aggregate sampling. However, the temporal profiles of features-providing orthogonal information to physicochemical properties-illustrate that many possess different feature temporal dynamics (fTDs) across buildings, with large and unpredictable single day deviations from the mean. Internal to a building, numerous and seemingly unrelated features, with mz and rt differences up to hundreds of Daltons and seconds, display highly correlated fTDs, suggesting non-obvious feature relationships. Data-driven building classification achieves high sensitivity and specificity, and extracts building-identifying features found to possess unique dynamics. Analysis of fTDs from many short-duration samples allows for tailored community monitoring with applicability in public health studies.

Daily, oral FMT for long-term maintenance therapy in ulcerative colitis: results of a single-center, prospective, randomized pilot study.

BACKGROUND: Fecal microbiota transplantation (FMT) is a promising new strategy in the treatment of Inflammatory Bowel Disease, but long-term delivery systems are lacking. This randomized study was designed as a safety and feasibility study of long-term FMT in subjects with mild to moderate UC using frozen, encapsulated oral FMT (cFMT). METHODS: Subjects were randomized 1:1 to receive FMT induction by colonoscopy, followed by 12 weeks of daily oral administration of frozen encapsulated cFMT or sham therpay. Subjects were followed for 36 weeks and longitudenal clinical assessments included multiple subjective and objective markers of disease severity. Ribosomal 16S bacterial sequencing was used to assess donor-induced changes in the gut microbiota. Changes in T regulatory (Treg) and mucosal associated invariant T (MAIT) cell populations were evaluated by flow cytometry as an exploratory endpoint. RESULTS: Twelve subjects with active UC were randomized: 6 subjects completed the full 12-week course of FMT plus cFMT, and 6 subjects received sham treatment by colonic installation and longitudinal oral placebo capules. Chronic administration of cFMT was found to be safe and well-tolerated but home storage concerns exist. Protocol adherence was high, and none of the study subjects experienced FMT-associated treatment emergent adverse events. Two subjects that received cFMT achieved clinical remission versus none in the placebo group (95% CI = 0.38-infinity, p = 0.45). cFMT was associated with sustained donor-induced shifts in fecal microbial composition. Changes in MAIT cell cytokine production were observed in cFMT recipients and correlated with treatment response. CONCLUSION: These pilot data suggest that daily encapsulated cFMT may extend the durability of index FMT-induced changes in gut bacterial community structure and that an association between MAIT cell cytokine production and clinical response to FMT may exist in UC populations. Oral frozen encapsulated cFMT is a promising FMT delivery system and may be preferred for longterm treatment strategies in UC and other chronic diseases but further evaluations will have to address home storage concerns. Larger trials should be done to explore the benefits of cFMT and to determine its long-term impacts on the colonic microbiome. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02390726). Registered 17 March 2015, https://clinicaltrials.gov/ct2/show/NCT02390726?term=NCT02390726&draw=2&rank=1 .

Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in highly public receptors.

BACKGROUND: The adaptive immune system maintains a diversity of T cells capable of recognizing a broad array of antigens. Each T cell's specificity for antigens is determined by its T cell receptors (TCRs), which together across all T cells form a repertoire of millions of unique receptors in each individual. Although many studies have examined how TCR repertoires change in response to disease or drugs, few have explored the temporal dynamics of the TCR repertoire in healthy individuals. RESULTS: Here we report immunosequencing of TCR ß chains (TCRß) from the blood of three healthy individuals at eight time points over one year. TCRß repertoires of all peripheral-blood T cells and sorted memory T cells clustered clearly by individual, systematically demonstrating that TCRß repertoires are specific to individuals across time. This individuality was absent from TCRßs from naive T cells, suggesting that the differences resulted from an individual's antigen exposure history, not genetic background. Many characteristics of the TCRß repertoire (e.g., diversity, clonality) were stable across time, although we found evidence of T cell expansion dynamics even within healthy individuals. We further identified a subset of "persistent" TCRßs present across all time points. These receptors were rich in clonal and highly public receptors and may play a key role in immune system maintenance. CONCLUSIONS: Our results highlight the importance of longitudinal sampling of the immune system, providing a much-needed baseline for TCRß dynamics in healthy individuals. Such a baseline will improve interpretation of changes in the TCRß repertoire during disease or treatment.

Virtual microfluidics for digital quantification and single-cell sequencing.

We have developed hydrogel-based virtual microfluidics as a simple and robust alternative to complex engineered microfluidic systems for the compartmentalization of nucleic acid amplification reactions. We applied in-gel digital multiple displacement amplification (dMDA) to purified DNA templates, cultured bacterial cells and human microbiome samples in the virtual microfluidics system, and demonstrated whole-genome sequencing of single-cell MDA products with excellent coverage uniformity and markedly reduced chimerism compared with products of liquid MDA reactions.

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.

Evolution of a Vegetarian Vibrio: Metabolic Specialization of Vibrio breoganii to Macroalgal Substrates.

While most Vibrionaceae are considered generalists that thrive on diverse substrates, including animal-derived material, we show that Vibrio breoganii has specialized for the consumption of marine macroalga-derived substrates. Genomic and physiological comparisons of V. breoganii with other Vibrionaceae isolates revealed the ability to degrade alginate, laminarin, and additional glycans present in algal cell walls. Moreover, the widely conserved ability to hydrolyze animal-derived polymers, including chitin and glycogen, was lost, along with the ability to efficiently grow on a variety of amino acids. Ecological data showing associations with particulate algal material but not zooplankton further support this shift in niche preference, and the loss of motility appears to reflect a sessile macroalga-associated lifestyle. Together, these findings indicate that algal polysaccharides have become a major source of carbon and energy in V. breoganii, and these ecophysiological adaptations may facilitate transient commensal associations with marine invertebrates that feed on algae.IMPORTANCE Vibrios are often considered animal specialists or generalists. Here, we show that Vibrio breoganii has undergone massive genomic changes to become specialized on algal carbohydrates. Accompanying genomic changes include massive gene import and loss. These vibrios may help us better understand how algal biomass is degraded in the environment and may serve as a blueprint on how to optimize the conversion of algae to biofuels.

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.

Microbial lysate upregulates host oxytocin.

Neuropeptide hormone oxytocin has roles in social bonding, energy metabolism, and wound healing contributing to good physical, mental and social health. It was previously shown that feeding of a human commensal microbe Lactobacillus reuteri (L. reuteri) is sufficient to up-regulate endogenous oxytocin levels and improve wound healing capacity in mice. Here we show that oral L. reuteri-induced skin wound repair benefits extend to human subjects. Further, dietary supplementation with a sterile lysate of this microbe alone is sufficient to boost systemic oxytocin levels and improve wound repair capacity. Oxytocin-producing cells were found to be increased in the caudal paraventricular nucleus [PVN] of the hypothalamus after feeding of a sterile lysed preparation of L. reuteri, coincident with lowered blood levels of stress hormone corticosterone and more rapid epidermal closure, in mouse models. We conclude that microbe viability is not essential for regulating host oxytocin levels. The results suggest that a peptide or metabolite produced by bacteria may modulate host oxytocin secretion for potential public or personalized health goals.

Temporal Dynamics of In-Field Bioreactor Populations Reflect the Groundwater System and Respond Predictably to Perturbation.

Temporal variability complicates testing the influences of environmental variability on microbial community structure and thus function. An in-field bioreactor system was developed to assess oxic versus anoxic manipulations on in situ groundwater communities. Each sample was sequenced (16S SSU rRNA genes, average 10,000 reads), and biogeochemical parameters are monitored by quantifying 53 metals, 12 organic acids, 14 anions, and 3 sugars. Changes in dissolved oxygen (DO), pH, and other variables were similar across bioreactors. Sequencing revealed a complex community that fluctuated in-step with the groundwater community and responded to DO. This also directly influenced the pH, and so the biotic impacts of DO and pH shifts are correlated. A null model demonstrated that bioreactor communities were driven in part not only by experimental conditions but also by stochastic variability and did not accurately capture alterations in diversity during perturbations. We identified two groups of abundant OTUs important to this system; one was abundant in high DO and pH and contained heterotrophs and oxidizers of iron, nitrite, and ammonium, whereas the other was abundant in low DO with the capability to reduce nitrate. In-field bioreactors are a powerful tool for capturing natural microbial community responses to alterations in geochemical factors beyond the bulk phase.

Rapid evolutionary innovation during an Archaean genetic expansion.

The natural history of Precambrian life is still unknown because of the rarity of microbial fossils and biomarkers. However, the composition of modern-day genomes may bear imprints of ancient biogeochemical events. Here we use an explicit model of macroevolution including gene birth, transfer, duplication and loss events to map the evolutionary history of 3,983 gene families across the three domains of life onto a geological timeline. Surprisingly, we find that a brief period of genetic innovation during the Archaean eon, which coincides with a rapid diversification of bacterial lineages, gave rise to 27% of major modern gene families. A functional analysis of genes born during this Archaean expansion reveals that they are likely to be involved in electron-transport and respiratory pathways. Genes arising after this expansion show increasing use of molecular oxygen (P = 3.4 × 10(-8)) and redox-sensitive transition metals and compounds, which is consistent with an increasingly oxygenating biosphere.

Ecology drives a global network of gene exchange connecting the human microbiome.

Horizontal gene transfer (HGT), the acquisition of genetic material from non-parental lineages, is known to be important in bacterial evolution. In particular, HGT provides rapid access to genetic innovations, allowing traits such as virulence, antibiotic resistance and xenobiotic metabolism to spread through the human microbiome. Recent anecdotal studies providing snapshots of active gene flow on the human body have highlighted the need to determine the frequency of such recent transfers and the forces that govern these events. Here we report the discovery and characterization of a vast, human-associated network of gene exchange, large enough to directly compare the principal forces shaping HGT. We show that this network of 10,770 unique, recently transferred (more than 99% nucleotide identity) genes found in 2,235 full bacterial genomes, is shaped principally by ecology rather than geography or phylogeny, with most gene exchange occurring between isolates from ecologically similar, but geographically separated, environments. For example, we observe 25-fold more HGT between human-associated bacteria than among ecologically diverse non-human isolates (P = 3.0 × 10(-270)). We show that within the human microbiome this ecological architecture continues across multiple spatial scales, functional classes and ecological niches with transfer further enriched among bacteria that inhabit the same body site, have the same oxygen tolerance or have the same ability to cause disease. This structure offers a window into the molecular traits that define ecological niches, insight that we use to uncover sources of antibiotic resistance and identify genes associated with the pathology of meningitis and other diseases.

Methanogenic burst in the end-Permian carbon cycle.

The end-Permian extinction is associated with a mysterious disruption to Earth's carbon cycle. Here we identify causal mechanisms via three observations. First, we show that geochemical signals indicate superexponential growth of the marine inorganic carbon reservoir, coincident with the extinction and consistent with the expansion of a new microbial metabolic pathway. Second, we show that the efficient acetoclastic pathway in Methanosarcina emerged at a time statistically indistinguishable from the extinction. Finally, we show that nickel concentrations in South China sediments increased sharply at the extinction, probably as a consequence of massive Siberian volcanism, enabling a methanogenic expansion by removal of nickel limitation. Collectively, these results are consistent with the instigation of Earth's greatest mass extinction by a specific microbial innovation.

Transfer of noncoding DNA drives regulatory rewiring in bacteria.

Understanding the mechanisms that generate variation is a common pursuit unifying the life sciences. Bacteria represent an especially striking puzzle, because closely related strains possess radically different metabolic and ecological capabilities. Differences in protein repertoire arising from gene transfer are currently considered the primary mechanism underlying phenotypic plasticity in bacteria. Although bacterial coding plasticity has been extensively studied in previous decades, little is known about the role that regulatory plasticity plays in bacterial evolution. Here, we show that bacterial genes can rapidly shift between multiple regulatory modes by acquiring functionally divergent nonhomologous promoter regions. Through analysis of 270,000 regulatory regions across 247 genomes, we demonstrate that regulatory "switching" to nonhomologous alternatives is ubiquitous, occurring across the bacterial domain. Using comparative transcriptomics, we show that at least 16% of the expression divergence between Escherichia coli strains can be explained by this regulatory switching. Further, using an oligonucleotide regulatory library, we establish that switching affects bacterial promoter architecture. We provide evidence that regulatory switching can occur through horizontal regulatory transfer, which allows regulatory regions to move across strains, and even genera, independently from the genes they regulate. Finally, by experimentally characterizing the fitness effect of a regulatory transfer on a pathogenic E. coli strain, we demonstrate that regulatory switching elicits important phenotypic consequences. Taken together, our findings expose previously unappreciated regulatory plasticity in bacteria and provide a gateway for understanding bacterial phenotypic variation and adaptation.

Horizontal gene transfer and the evolution of bacterial and archaeal population structure.

Many bacterial and archaeal lineages have a history of extensive and ongoing horizontal gene transfer and loss, as evidenced by the large differences in genome content even among otherwise closely related isolates. How ecologically cohesive populations might evolve and be maintained under such conditions of rapid gene turnover has remained controversial. Here we synthesize recent literature demonstrating the importance of habitat and niche in structuring horizontal gene transfer. This leads to a model of ecological speciation via gradual genetic isolation triggered by differential habitat-association of nascent populations. Further, we hypothesize that subpopulations can evolve through local gene-exchange networks by tapping into a gene pool that is adaptive towards local, continuously changing organismic interactions and is, to a large degree, responsible for the observed rapid gene turnover. Overall, these insights help to explain how bacteria and archaea form populations that display both ecological cohesion and high genomic diversity.