Gut metabolome and microbiota signatures predict response to treatment with exclusive enteral nutrition in a prospective study in children with active Crohn's disease.

BACKGROUND: Predicting response to exclusive enteral nutrition (EEN) in active Crohn's disease (CD) could lead to therapy personalization and pretreatment optimization. OBJECTIVES: This study aimed to explore the ability of pretreatment parameters to predict fecal calprotectin (FCal) levels at EEN completion in a prospective study in children with CD. METHODS: In children with active CD, clinical parameters, dietary intake, cytokines, inflammation-related blood proteomics, and diet-related metabolites, metabolomics and microbiota in feces, were measured before initiation of 8 wk of EEN. Prediction of FCal levels at EEN completion was performed using machine learning. Data are presented with medians (IQR). RESULTS: Of 37 patients recruited, 15 responded (FCal < 250 µg/g) to EEN (responders) and 22 did not (nonresponders). Clinical and immunological parameters were not associated with response to EEN. Responders had lesser (µmol/g) butyrate [responders: 13.2 (8.63-18.4) compared with nonresponders: 22.3 (12.0-32.0); P = 0.03], acetate [responders: 49.9 (46.4-68.4) compared with nonresponders: 70.4 (57.0-95.5); P = 0.027], phenylacetate [responders: 0.175 (0.013-0.611) compared with nonresponders: 0.943 (0.438-1.35); P = 0.021], and a higher microbiota richness [315 (269-347) compared with nonresponders: 243 (205-297); P = 0.015] in feces than nonresponders. Responders consumed (portions/1000 kcal/d) more confectionery products [responders: 0.55 (0.38-0.72) compared with nonresponders: 0.19 (0.01-0.38); P = 0.045]. A multicomponent model using fecal parameters, dietary data, and clinical and immunological parameters predicted response to EEN with 78% accuracy (sensitivity: 80%; specificity: 77%; positive predictive value: 71%; negative predictive value: 85%). Higher taxon abundance from Ruminococcaceae, Lachnospiraceae, and Bacteroides and phenylacetate, butyrate, and acetate were the most influential variables in predicting lack of response to EEN. CONCLUSIONS: We identify microbial signals and diet-related metabolites in feces, which could comprise targets for pretreatment optimization and personalized nutritional therapy in pediatric CD.

Dose-dependent effects of enteral nutrition on the faecal microbiota and short chain fatty acids.

INTRODUCTION: Enteral nutrition (EN) involves replacing all or part of a person's habitual diet with a nutritional formula. The impact of varying doses of EN on the gut microbiome remains understudied. METHODS: Healthy adults replaced all (100% EN) or part (85% EN, 50% EN and 20% EN) of their energy requirements with EN for 7 days. Faecal samples were collected before and on day 7 of interventions. Faecal pH, short chain fatty acids (SCFAs), branched-chain fatty acids (BCFAs) and 16S rRNA sequencing were performed. Dietary assessment was performed with 7-day food diaries. RESULTS: Sixty-one participants (31 females; median (IQR) age: 24.7 (23.0-27.8) years) were recruited. A dose-dependent impact of EN on faecal microbiota, SCFAs, BCFAs) and pH was observed, with changes detectable at EN intakes of at least 50% of energy requirements. 100% and 85% EN reduced the abundance of fibre-fermenting taxa such as Agathobacter, Faecalibaterium, Succinivibrio and Acidaminococcus. In parallel, potentially harmful organisms like Eubacterium, Actinomyces, and Klebsiella increased. In the 50% EN group, adherence to a diet high in fish, vegetables, potatoes, non-alcoholic beverages, and fat spreads, and low in cereal products, milk, and meat negatively correlated with changes in microbiota structure (r = -0.75, P = 0.025). This signal was not observed when using compositional tools for microbiota analysis. CONCLUSIONS: EN detrimentally influences the faecal microbiota and diet-related bacterial metabolites in a dose-dependent manner, particularly at doses of at least 50%. The findings of this study have implications for the dietary management and counselling of patients receiving high volume EN.

High-quality metagenome assembly from long accurate reads with metaMDBG.

We introduce metaMDBG, a metagenomics assembler for PacBio HiFi reads. MetaMDBG combines a de Bruijn graph assembly in a minimizer space with an iterative assembly over sequences of minimizers to address variations in genome coverage depth and an abundance-based filtering strategy to simplify strain complexity. For complex communities, we obtained up to twice as many high-quality circularized prokaryotic metagenome-assembled genomes as existing methods and had better recovery of viruses and plasmids.

Adaptive radiations in natural populations of prokaryotes: innovation is key.

Prokaryote diversity makes up most of the tree of life and is crucial to the functioning of the biosphere and human health. However, the patterns and mechanisms of prokaryote diversification have received relatively little attention compared to animals and plants. Adaptive radiation, the rapid diversification of an ancestor species into multiple ecologically divergent species, is a fundamental process by which macrobiological diversity is generated. Here, we discuss whether ecological opportunity could lead to similar bursts of diversification in bacteria. We explore how adaptive radiations in prokaryotes can be kickstarted by horizontally acquired key innovations allowing lineages to invade new niche space that subsequently is partitioned among diversifying specialist descendants. We discuss how novel adaptive zones are colonized and exploited after the evolution of a key innovation and whether certain types of are more prone to adaptive radiation. Radiation into niche specialists does not necessarily lead to speciation in bacteria when barriers to recombination are absent. We propose that in this scenario, niche-specific genes could accumulate within a single lineage, leading to the evolution of an open pangenome.

Efficient High-Quality Metagenome Assembly from Long Accurate Reads using Minimizer-space de Bruijn Graphs.

We introduce a novel metagenomics assembler for high-accuracy long reads. Our approach, implemented as metaMDBG, combines highly efficient de Bruijn graph assembly in minimizer space, with both a multi-k' approach for dealing with variations in genome coverage depth and an abundance-based filtering strategy for simplifying strain complexity. The resulting algorithm is more efficient than the state-of-the-art but with better assembly results. metaMDBG was 1.5 to 12 times faster than competing assemblers and requires between one-tenth and one-thirtieth of the memory across a range of data sets. We obtained up to twice as many high-quality circularised prokaryotic metagenome assembled genomes (MAGs) on the most complex communities, and a better recovery of viruses and plasmids. metaMDBG performs particularly well for abundant organisms whilst being robust to the presence of strain diversity. The result is that for the first time it is possible to efficiently reconstruct the majority of complex communities by abundance as near-complete MAGs.

Antigen-driven colonic inflammation is associated with development of dysplasia in primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is an immune-mediated disease of the bile ducts that co-occurs with inflammatory bowel disease (IBD) in almost 90% of cases. Colorectal cancer is a major complication of patients with PSC and IBD, and these patients are at a much greater risk compared to patients with IBD without concomitant PSC. Combining flow cytometry, bulk and single-cell transcriptomics, and T and B cell receptor repertoire analysis of right colon tissue from 65 patients with PSC, 108 patients with IBD and 48 healthy individuals we identified a unique adaptive inflammatory transcriptional signature associated with greater risk and shorter time to dysplasia in patients with PSC. This inflammatory signature is characterized by antigen-driven interleukin-17A (IL-17A)+ forkhead box P3 (FOXP3)+ CD4 T cells that express a pathogenic IL-17 signature, as well as an expansion of IgG-secreting plasma cells. These results suggest that the mechanisms that drive the emergence of dysplasia in PSC and IBD are distinct and provide molecular insights that could guide prevention of colorectal cancer in individuals with PSC.

Enterosignatures define common bacterial guilds in the human gut microbiome.

The human gut microbiome composition is generally in a stable dynamic equilibrium, but it can deteriorate into dysbiotic states detrimental to host health. To disentangle the inherent complexity and capture the ecological spectrum of microbiome variability, we used 5,230 gut metagenomes to characterize signatures of bacteria commonly co-occurring, termed enterosignatures (ESs). We find five generalizable ESs dominated by either Bacteroides, Firmicutes, Prevotella, Bifidobacterium, or Escherichia. This model confirms key ecological characteristics known from previous enterotype concepts, while enabling the detection of gradual shifts in community structures. Temporal analysis implies that the Bacteroides-associated ES is "core" in the resilience of westernized gut microbiomes, while combinations with other ESs often complement the functional spectrum. The model reliably detects atypical gut microbiomes correlated with adverse host health conditions and/or the presence of pathobionts. ESs provide an interpretable and generic model that enables an intuitive characterization of gut microbiome composition in health and disease.

Metabolic independence drives gut microbial colonization and resilience in health and disease.

BACKGROUND: Changes in microbial community composition as a function of human health and disease states have sparked remarkable interest in the human gut microbiome. However, establishing reproducible insights into the determinants of microbial succession in disease has been a formidable challenge. RESULTS: Here we use fecal microbiota transplantation (FMT) as an in natura experimental model to investigate the association between metabolic independence and resilience in stressed gut environments. Our genome-resolved metagenomics survey suggests that FMT serves as an environmental filter that favors populations with higher metabolic independence, the genomes of which encode complete metabolic modules to synthesize critical metabolites, including amino acids, nucleotides, and vitamins. Interestingly, we observe higher completion of the same biosynthetic pathways in microbes enriched in IBD patients. CONCLUSIONS: These observations suggest a general mechanism that underlies changes in diversity in perturbed gut environments and reveal taxon-independent markers of "dysbiosis" that may explain why widespread yet typically low-abundance members of healthy gut microbiomes can dominate under inflammatory conditions without any causal association with disease.

Transient Suppression of Bacterial Populations Associated with Gut Health is Critical in Success of Exclusive Enteral Nutrition for Children with Crohn's Disease.

BACKGROUND AND AIMS: Exclusive enteral nutrition [EEN] is a dietary intervention to induce clinical remission in children with active luminal Crohn's disease [CD]. While changes in the gut microbial communities have been implicated in achieving this remission, a precise understanding of the role of microbial ecology in the restoration of gut homeostasis is lacking. METHODS: Here we reconstructed genomes from the gut metagenomes of 12 paediatric subjects who were sampled before, during and after EEN. We then classified each microbial population into distinct 'phenotypes' or patterns of response based on changes in their relative abundances throughout the therapy on a per-individual basis. RESULTS: Our data show that children achieving clinical remission during therapy were enriched with microbial populations that were either suppressed or that demonstrated a transient bloom as a function of EEN. In contrast, this ecosystem-level response was not observed in cases of EEN failure. Further analysis revealed that populations that were suppressed during EEN were significantly more prevalent in healthy children and adults across the globe compared with those that bloomed ephemerally during the therapy. CONCLUSIONS: These observations taken together suggest that successful outcomes of EEN are marked by a temporary emergence of microbial populations that are rare in healthy individuals, and a concomitant reduction in microbes that are commonly associated with gut homeostasis. Our work is a first attempt to highlight individual-specific, complex environmental factors that influence microbial response in EEN. This model offers a novel, alternative viewpoint to traditional taxonomic strategies used to characterize associations with health and disease states.

Population-level impacts of antibiotic usage on the human gut microbiome.

The widespread usage of antimicrobials has driven the evolution of resistance in pathogenic microbes, both increased prevalence of antimicrobial resistance genes (ARGs) and their spread across species by horizontal gene transfer (HGT). However, the impact on the wider community of commensal microbes associated with the human body, the microbiome, is less well understood. Small-scale studies have determined the transient impacts of antibiotic consumption but we conduct an extensive survey of ARGs in 8972 metagenomes to determine the population-level impacts. Focusing on 3096 gut microbiomes from healthy individuals not taking antibiotics we demonstrate highly significant correlations between both the total ARG abundance and diversity and per capita antibiotic usage rates across ten countries spanning three continents. Samples from China were notable outliers. We use a collection of 154,723 human-associated metagenome assembled genomes (MAGs) to link these ARGs to taxa and detect HGT. This reveals that the correlations in ARG abundance are driven by multi-species mobile ARGs shared between pathogens and commensals, within a highly connected central component of the network of MAGs and ARGs. We also observe that individual human gut ARG profiles cluster into two types or resistotypes. The less frequent resistotype has higher overall ARG abundance, is associated with certain classes of resistance, and is linked to species-specific genes in the Proteobacteria on the periphery of the ARG network.

Functional responses of key marine bacteria to environmental change - toward genetic counselling for coastal waters.

Coastal ecosystems deteriorate globally due to human-induced stress factors, like nutrient loading and pollution. Bacteria are critical to marine ecosystems, e.g., by regulating nutrient cycles, synthesizing vitamins, or degrading pollutants, thereby providing essential ecosystem services ultimately affecting economic activities. Yet, until now bacteria are overlooked both as mediators and indicators of ecosystem health, mainly due to methodological limitations in assessing bacterial ecosystem functions. However, these limitations are largely overcome by the advances in molecular biology and bioinformatics methods for characterizing the genetics that underlie functional traits of key bacterial populations - "key" in providing important ecosystem services, being abundant, or by possessing high metabolic rates. It is therefore timely to analyze and define the functional responses of bacteria to human-induced effects on coastal ecosystem health. We posit that categorizing the responses of key marine bacterial populations to changes in environmental conditions through modern microbial oceanography methods will allow establishing the nascent field of genetic counselling for our coastal waters. This requires systematic field studies of linkages between functional traits of key bacterial populations and their ecosystem functions in coastal seas, complemented with systematic experimental analyses of the responses to different stressors. Research and training in environmental management along with dissemination of results and dialogue with societal actors are equally important to ensure the role of bacteria is understood as fundamentally important for coastal ecosystems. Using the responses of microorganisms as a tool to develop genetic counselling for coastal ecosystems can ultimately allow for integrating bacteria as indicators of environmental change.

Crop management shapes the diversity and activity of DNA and RNA viruses in the rhizosphere.

BACKGROUND: The rhizosphere is a hotspot for microbial activity and contributes to ecosystem services including plant health and biogeochemical cycling. The activity of microbial viruses, and their influence on plant-microbe interactions in the rhizosphere, remains undetermined. Given the impact of viruses on the ecology and evolution of their host communities, determining how soil viruses influence microbiome dynamics is crucial to build a holistic understanding of rhizosphere functions. RESULTS: Here, we aimed to investigate the influence of crop management on the composition and activity of bulk soil, rhizosphere soil, and root viral communities. We combined viromics, metagenomics, and metatranscriptomics on soil samples collected from a 3-year crop rotation field trial of oilseed rape (Brassica napus L.). By recovering 1059 dsDNA viral populations and 16,541 ssRNA bacteriophage populations, we expanded the number of underexplored Leviviricetes genomes by > 5 times. Through detection of viral activity in metatranscriptomes, we uncovered evidence of "Kill-the-Winner" dynamics, implicating soil bacteriophages in driving bacterial community succession. Moreover, we found the activity of viruses increased with proximity to crop roots, and identified that soil viruses may influence plant-microbe interactions through the reprogramming of bacterial host metabolism. We have provided the first evidence of crop rotation-driven impacts on soil microbial communities extending to viruses. To this aim, we present the novel principal of "viral priming," which describes how the consecutive growth of the same crop species primes viral activity in the rhizosphere through local adaptation. CONCLUSIONS: Overall, we reveal unprecedented spatial and temporal diversity in viral community composition and activity across root, rhizosphere soil, and bulk soil compartments. Our work demonstrates that the roles of soil viruses need greater consideration to exploit the rhizosphere microbiome for food security, food safety, and environmental sustainability. Video Abstract.

Analysis of pit latrine microbiota reveals depth-related variation in composition, and key parameters and taxa associated with latrine fill-up rate.

Pit latrines are used by billions of people globally, often in developing countries where they provide a low-tech and low-cost sanitation method. However, health and social problems can arise from a lack of emptying or maintenance of these facilities. A better understanding of the biological and environmental parameters within pit latrines could inform attempts to enhance material decomposition rates, and therefore slow fill-up rate. In this study, we have performed a spatial analysis of 35 Tanzanian pit latrines to identify bacteria and environmental factors that are associated with faster or slower pit latrine fill-up rates. Using ordination of microbial community data, we observed a linear gradient in terms of beta diversity with increasing pit latrine sample depth, corresponding to a shift in microbial community structure from gut-associated families in the top layer to environmental- and wastewater-associated taxa at greater depths. We also investigated the bacteria and environmental parameters associated with fill-up rates, and identified pH, volatile solids, and volatile fatty acids as features strongly positively correlated with pit latrine fill-up rates, whereas phosphate was strongly negatively correlated with fill-up rate. A number of pit latrine microbiota taxa were also correlated with fill-up rates. Using a multivariate regression, we identified the Lactobacillaceae and Incertae_Sedis_XIII taxa as particularly strongly positively and negatively correlated with fill-up rate, respectively. This study therefore increases knowledge of the microbiota within pit latrines, and identifies potentially important bacteria and environmental variables associated with fill-up rates. These new insights may be useful for future studies investigating the decomposition process within pit latrines.

Single-cell genomics reveals population structures from in vitro evolutionary studies of Salmonella.

Single-cell DNA sequencing has the potential to reveal detailed hierarchical structures in evolving populations of cells. Single cell approaches are increasingly used to study clonal evolution in human ageing and cancer but have not yet been deployed to study evolving clonal microbial populations. Here, we present an approach for single bacterial genomic analysis for in vitro evolution experiments using FACS isolation of individual bacteria followed by whole-genome amplification and sequencing. We apply this to the experimental evolution of a hypermutator strain of Salmonella in response to antibiotic stress (ciprofloxacin). By analysing sequence polymorphisms in individual cells from populations we identified the presence and prevalence of sub-populations which have acquired polymorphisms in genes previously demonstrated to be associated with ciprofloxacin susceptibility. We were also able to identify that the population exposed to antibiotic stress was able to develop resistance whilst maintaining diversity. This population structure could not be resolved from bulk sequence data, and our results show how high-throughput single-cell sequencing can enhance experimental studies of bacterial evolution.

Systematic review of donor and recipient predictive biomarkers of response to faecal microbiota transplantation in patients with ulcerative colitis.

BACKGROUND: Faecal microbiota transplantation (FMT) has previously been explored as a treatment for ulcerative colitis (UC) however, biomarkers that predict and / or are associated with clinical response are poorly defined. The aim of this systematic review was to identify donor and recipient clinical, microbial and metabolomic predictive biomarkers of response to FMT in UC. METHODS: A systematic search of the relevant literature of studies exploring FMT in UC was conducted. Data on microbial diversity, taxonomic changes, metabolic changes, donor and recipient microbiota relationship and baseline predictors was examined. FINDINGS: 2852 studies were screened, and 25 papers were included in this systematic review. Following FMT, alpha diversity was seen to increase in responders along with increases in the abundance of Clostridiales clusters (order) and Bacteroides genus. Metabolomic analysis revealed short chain fatty acid (SCFA) production as a marker of FMT success. Donors or FMT batches with higher microbial alpha diversity and a greater abundance of taxa belonging to certain Bacteroides and Clostridia clusters were associated with clinical response to FMT. Baseline clinical predictors of response in patients with UC included younger age, less severe disease and possibly shorter disease duration. Baseline recipient microbial predictors at response consisted of higher faecal species richness, greater abundance of Candida and donor microbial profile similarity. INTERPRETATION: Distinct changes in gut microbiota profiles post-FMT indicate that certain baseline characteristics along with specific microbial and metabolomic alterations may predispose patients towards a successful therapeutic outcome. Opportunities towards a biomarker led precision medicine approach with FMT should be explored in future clinical studies. FUNDING: There no specific funding to declare.

Impact of sulfamethoxazole on a riverine microbiome.

The continued emergence of bacterial pathogens presenting antimicrobial resistance is widely recognised as a global health threat and recent attention focused on potential environmental reservoirs of antibiotic resistance genes (ARGs). Freshwater environments such as rivers represent a potential hotspot for ARGs and antibiotic resistant bacteria as they are receiving systems for effluent discharges from wastewater treatment plants (WWTPs). Effluent also contains low levels of different antimicrobials including antibiotics and biocides. Sulfonamides are antibacterial chemicals widely used in clinical, veterinary and agricultural settings and are frequently detected in sewage sludge and manure in addition to riverine ecosystems. The impact of such exposure on ARG prevalence and diversity is unknown, so the aim of this study was to investigate the release of a sub-lethal concentration of the sulfonamide compound sulfamethoxazole (SMX) on the river bacterial microbiome using a flume system. This system was a semi-natural in vitro flume using river water (30 L) and sediment (6 kg) with circulation to mimic river flow. A combination of 'omics' approaches were conducted to study the impact of SMX exposure on the microbiomes within the flumes. Metagenomic analysis showed that the addition of low concentrations of SMX (<4 µg L-1) had a limited effect on the bacterial resistome in the water fraction only, with no impact observed in the sediment. Metaproteomics did not show differences in ARGs expression with SMX exposure in water. Overall, the river bacterial community was resilient to short term exposure to sub-lethal concentrations of SMX which mimics the exposure such communities experience downstream of WWTPs throughout the year.

Swarm v3: towards tera-scale amplicon clustering.

MOTIVATION: Previously we presented swarm, an open-source amplicon clustering programme that produces fine-scale molecular operational taxonomic units (OTUs) that are free of arbitrary global clustering thresholds. Here, we present swarm v3 to address issues of contemporary datasets that are growing towards tera-byte sizes. RESULTS: When compared with previous swarm versions, swarm v3 has modernized C++ source code, reduced memory footprint by up to 50%, optimized CPU-usage and multithreading (more than 7 times faster with default parameters), and it has been extensively tested for its robustness and logic. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are available at https://github.com/torognes/swarm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Strainberry: automated strain separation in low-complexity metagenomes using long reads.

High-throughput short-read metagenomics has enabled large-scale species-level analysis and functional characterization of microbial communities. Microbiomes often contain multiple strains of the same species, and different strains have been shown to have important differences in their functional roles. Recent advances on long-read based methods enabled accurate assembly of bacterial genomes from complex microbiomes and an as-yet-unrealized opportunity to resolve strains. Here we present Strainberry, a metagenome assembly pipeline that performs strain separation in single-sample low-complexity metagenomes and that relies uniquely on long-read data. We benchmarked Strainberry on mock communities for which it produces strain-resolved assemblies with near-complete reference coverage and 99.9% base accuracy. We also applied Strainberry on real datasets for which it improved assemblies generating 20-118% additional genomic material than conventional metagenome assemblies on individual strain genomes. We show that Strainberry is also able to refine microbial diversity in a complex microbiome, with complete separation of strain genomes. We anticipate this work to be a starting point for further methodological improvements on strain-resolved metagenome assembly in environments of higher complexities.

STRONG: metagenomics strain resolution on assembly graphs.

We introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and stores the coassembly graph prior to variant simplification. This enables the subgraphs and their unitig per-sample coverages, for individual single-copy core genes (SCGs) in each MAG, to be extracted. A Bayesian algorithm, BayesPaths, determines the number of strains present, their haplotypes or sequences on the SCGs, and abundances. STRONG is validated using synthetic communities and for a real anaerobic digestor time series generates haplotypes that match those observed from long Nanopore reads.

The pathophysiology of bile acid diarrhoea: differences in the colonic microbiome, metabolome and bile acids.

Bile acid diarrhoea (BAD) is a common disorder resulting from increased loss of bile acids (BAs), overlapping irritable bowel syndrome with diarrhoea (IBS-D). The gut microbiota metabolises primary BAs to secondary BAs, with differing impacts on metabolism and homeostasis. The aim of this study was to profile the microbiome, metabolic products and bile acids in BAD. Patients with BAD diagnosed by SeHCAT testing, were compared with other IBS-D patients, and healthy controls. Faecal 16S ribosomal RNA gene analysis was undertaken. Faecal short chain fatty acid (SCFA) and urinary volatile organic compounds (VOCs) were measured. BAs were quantified in serum and faeces. Faecal bacterial diversity was significantly reduced in patients with BAD. Several taxa were enriched compared to IBS-D. SCFA amounts differed in BAD, controls and IBS-D, with significantly more propionate in BAD. Separation of VOC profiles was evident, but the greatest discrimination was between IBS-D and controls. Unconjugated and primary BA in serum and faeces were significantly higher in BAD. The faecal percentage primary BA was inversely related to SeHCAT. BAD produces dysbiosis, with metabolite differences, including VOC, SCFA and primary BAs when compared to IBS-D. These findings provide new mechanistic insights into the pathophysiology of BAD.