BACKGROUND: Microbial communities in both natural and applied settings reliably carry out myriads of functions, yet how stable these taxonomically diverse assemblages can be and what causes them to transition between states remains poorly understood. We studied monthly activated sludge (AS) samples collected over 9 years from a full-scale wastewater treatment plant to answer how complex AS communities evolve in the long term and how the community functions change when there is a disturbance in operational parameters. RESULTS: Here, we show that a microbial community in activated sludge (AS) system fluctuated around a stable average for 3 years but was then abruptly pushed into an alternative stable state by a simple transient disturbance (bleaching). While the taxonomic composition rapidly turned into a new state following the disturbance, the metabolic profile of the community and system performance remained remarkably stable. A total of 920 metagenome-assembled genomes (MAGs), representing approximately 70% of the community in the studied AS ecosystem, were recovered from the 97 monthly AS metagenomes. Comparative genomic analysis revealed an increased ability to aggregate in the cohorts of MAGs with correlated dynamics that are dominant after the bleaching event. Fine-scale analysis of dynamics also revealed cohorts that dominated during different periods and showed successional dynamics on seasonal and longer time scales due to temperature fluctuation and gradual changes in mean residence time in the reactor, respectively. CONCLUSIONS: Our work highlights that communities can assume different stable states under highly similar environmental conditions and that a specific disturbance threshold may lead to a rapid shift in community composition. Video Abstract.

BACKGROUND: Intestinal Peyer's patches (PPs) form unique niches for bacteria-immune cell interactions that direct host immunity and shape the microbiome. Here we investigate how peroral administration of probiotic bacterium Limosilactobacillus reuteri R2LC affects B lymphocytes and IgA induction in the PPs, as well as the downstream consequences on intestinal microbiota and susceptibility to inflammation. RESULTS: The B cells of PPs were separated by size to circumvent activation-dependent cell identification biases due to dynamic expression of markers, which resulted in two phenotypically, transcriptionally, and spatially distinct subsets: small IgD+/GL7-/S1PR1+/Bcl6, CCR6-expressing pre-germinal center (GC)-like B cells with innate-like functions located subepithelially, and large GL7+/S1PR1-/Ki67+/Bcl6, CD69-expressing B cells with strong metabolic activity found in the GC. Peroral L. reuteri administration expanded both B cell subsets and enhanced the innate-like properties of pre-GC-like B cells while retaining them in the sub-epithelial compartment by increased sphingosine-1-phosphate/S1PR1 signaling. Furthermore, L. reuteri promoted GC-like B cell differentiation, which involved expansion of the GC area and autocrine TGFβ-1 activation. Consequently, PD-1-T follicular helper cell-dependent IgA induction and production was increased by L. reuteri, which shifted the intestinal microbiome and protected against dextran-sulfate-sodium induced colitis and dysbiosis. CONCLUSIONS: The Peyer's patches sense, enhance and transmit probiotic signals by increasing the numbers and effector functions of distinct B cell subsets, resulting in increased IgA production, altered intestinal microbiota, and protection against inflammation. Video abstract.

BACKGROUND: The magnitude of microbiota perturbations after exposure to antibiotics varies among individuals. It has been suggested that the composition of pre-treatment microbiota underpins personalized responses to antibiotics. However, this hypothesis has not been directly tested in humans. In this high-throughput amplicon study, we analyzed 16S ribosomal RNA gene sequences of 260 stool samples collected twice weekly from 39 patients with acute leukemia during their ~ 4 weeks of hospitalization for chemotherapy while they received multiple antibiotics. RESULTS: Despite heavy and sustained antibiotic pressure, microbial communities in samples from the same patient remained more similar to one another than to those from other patients. Principal component mixed effect regression using microbiota and granular antibiotic exposure data showed that microbiota departures from baseline depend on the composition of the pre-treatment microbiota. Penalized generalized estimating equations identified 6 taxa within pre-treatment microbiota that predicted the extent of antibiotic-induced perturbations. CONCLUSIONS: Our results indicate that specific species in pre-treatment microbiota determine personalized microbiota responses to antibiotics in humans. Thus, precision interventions targeting pre-treatment microbiota may prevent antibiotic-induced dysbiosis and its adverse clinical consequences. Video abstract.

BACKGROUND: Nitrogen-fixing prokaryotes (diazotrophs) contribute substantially to nitrogen input in mangrove sediments, and their structure and nitrogen fixation rate (NFR) are significantly controlled by environmental conditions. Despite the well-known studies on diazotrophs in surficial sediments, the diversity, structure, and ecological functions of diazotrophic communities along environmental gradients of mangrove sediment across different depths are largely unknown. Here, we investigated how biological nitrogen fixation varied with the depth of mangrove sediments from the perspectives of both NFR and diazotrophic communities. RESULTS: Through acetylene reduction assay, nifH gene amplicon and metagenomic sequencing, we found that the NFR increased but the diversity of diazotrophic communities decreased with the depth of mangrove sediments. The structure of diazotrophic communities at different depths was largely driven by salinity and exhibited a clear divergence at the partitioning depth of 50 cm. Among diazotrophic genera correlated with NFR, Agrobacterium and Azotobacter were specifically enriched at 50-100 cm sediments, while Anaeromyxobacter, Rubrivivax, Methylocystis, Dickeya, and Methylomonas were more abundant at 0-50 cm. Consistent with the higher NFR, metagenomic analysis demonstrated the elevated abundance of nitrogen fixation genes (nifH/D/K) in deep sediments, where nitrification genes (amoA/B/C) and denitrification genes (nirK and norB) became less abundant. Three metagenome-assembled genomes (MAGs) of diazotrophs from deep mangrove sediments indicated their facultatively anaerobic and mixotrophic lifestyles as they contained genes for low-oxygen-dependent metabolism, hydrogenotrophic respiration, carbon fixation, and pyruvate fermentation. CONCLUSIONS: This study demonstrates the depth-dependent variability of biological nitrogen fixation in terms of NFR and diazotrophic communities, which to a certain extent relieves the degree of nitrogen limitation in deep mangrove sediments. Video Abstract.

BACKGROUND: The intestinal microbiota plays an important role in regulating gastrointestinal (GI) physiology in part through interactions with the enteric nervous system (ENS). Alterations in the gut microbiome frequently occur together with disturbances in enteric neural control in pathophysiological conditions. However, the mechanisms by which the microbiota regulates GI function and the structure of the ENS are incompletely understood. Using a mouse model of antibiotic (Abx)-induced bacterial depletion, we sought to determine the molecular mechanisms of microbial regulation of intestinal function and the integrity of the ENS. Spontaneous reconstitution of the Abx-depleted microbiota was used to assess the plasticity of structure and function of the GI tract and ENS. Microbiota-dependent molecular mechanisms of ENS neuronal survival and neurogenesis were also assessed. RESULTS: Adult male and female Abx-treated mice exhibited alterations in GI structure and function, including a longer small intestine, slower transit time, increased carbachol-stimulated ion secretion, and increased intestinal permeability. These alterations were accompanied by the loss of enteric neurons in the ileum and proximal colon in both submucosal and myenteric plexuses. A reduction in the number of enteric glia was only observed in the ileal myenteric plexus. Recovery of the microbiota restored intestinal function and stimulated enteric neurogenesis leading to increases in the number of enteric glia and neurons. Lipopolysaccharide (LPS) supplementation enhanced neuronal survival alongside bacterial depletion, but had no effect on neuronal recovery once the Abx-induced neuronal loss was established. In contrast, short-chain fatty acids (SCFA) were able to restore neuronal numbers after Abx-induced neuronal loss, demonstrating that SCFA stimulate enteric neurogenesis in vivo. CONCLUSIONS: Our results demonstrate a role for the gut microbiota in regulating the structure and function of the GI tract in a sex-independent manner. Moreover, the microbiota is essential for the maintenance of ENS integrity, by regulating enteric neuronal survival and promoting neurogenesis. Molecular determinants of the microbiota, LPS and SCFA, regulate enteric neuronal survival, while SCFA also stimulates neurogenesis. Our data reveal new insights into the role of the gut microbiota that could lead to therapeutic developments for the treatment of enteric neuropathies. Video abstract.

Erratum in Microbiome. 2021 Nov 7;9(1):219.

BACKGROUND: Winter carbon loss in northern ecosystems is estimated to be greater than the average growing season carbon uptake and is primarily driven by microbial decomposers. Viruses modulate microbial carbon cycling via induced mortality and metabolic controls, but it is unknown whether viruses are active under winter conditions (anoxic and sub-freezing temperatures). RESULTS: We used stable isotope probing (SIP) targeted metagenomics to reveal the genomic potential of active soil microbial populations under simulated winter conditions, with an emphasis on viruses and virus-host dynamics. Arctic peat soils from the Bonanza Creek Long-Term Ecological Research site in Alaska were incubated under sub-freezing anoxic conditions with H218O or natural abundance water for 184 and 370 days. We sequenced 23 SIP-metagenomes and measured carbon dioxide (CO2) efflux throughout the experiment. We identified 46 bacterial populations (spanning 9 phyla) and 243 viral populations that actively took up 18O in soil and respired CO2 throughout the incubation. Active bacterial populations represented only a small portion of the detected microbial community and were capable of fermentation and organic matter degradation. In contrast, active viral populations represented a large portion of the detected viral community and one third were linked to active bacterial populations. We identified 86 auxiliary metabolic genes and other environmentally relevant genes. The majority of these genes were carried by active viral populations and had diverse functions such as carbon utilization and scavenging that could provide their host with a fitness advantage for utilizing much-needed carbon sources or acquiring essential nutrients. CONCLUSIONS: Overall, there was a stark difference in the identity and function of the active bacterial and viral community compared to the unlabeled community that would have been overlooked with a non-targeted standard metagenomic analysis. Our results illustrate that substantial active virus-host interactions occur in sub-freezing anoxic conditions and highlight viruses as a major community-structuring agent that likely modulates carbon loss in peat soils during winter, which may be pivotal for understanding the future fate of arctic soils' vast carbon stocks. Video abstract.

Erratum in Microbiome. 2021 Nov 9;9(1):221.

BACKGROUND: Long-read sequencing has shown its tremendous potential to address genome assembly challenges, e.g., achieving the first telomere-to-telomere assembly of a gapless human chromosome. However, many issues remain unresolved when leveraging error-prone long reads to characterize high-complexity metagenomes, for instance, complete/high-quality genome reconstruction from highly complex systems. RESULTS: Here, we developed an iterative haplotype-resolved hierarchical clustering-based hybrid assembly (HCBHA) approach that capitalizes on a hybrid (error-prone long reads and high-accuracy short reads) sequencing strategy to reconstruct (near-) complete genomes from highly complex metagenomes. Using the HCBHA approach, we first phase short and long reads from the highly complex metagenomic dataset into different candidate bacterial haplotypes, then perform hybrid assembly of each bacterial genome individually. We reconstructed 557 metagenome-assembled genomes (MAGs) with an average N50 of 574 Kb from a deeply sequenced, highly complex activated sludge (AS) metagenome. These high-contiguity MAGs contained 14 closed genomes and 111 high-quality (HQ) MAGs including full-length rRNA operons, which accounted for 61.1% of the microbial community. Leveraging the near-complete genomes, we also profiled the metabolic potential of the AS microbiome and identified 2153 biosynthetic gene clusters (BGCs) encoded within the recovered AS MAGs. CONCLUSION: Our results established the feasibility of an iterative haplotype-resolved HCBHA approach to reconstruct (near-) complete genomes from highly complex ecosystems, providing new insights into "complete metagenomics". The retrieved high-contiguity MAGs illustrated that various biosynthetic gene clusters (BGCs) were harbored in the AS microbiome. The high diversity of BGCs highlights the potential to discover new natural products biosynthesized by the AS microbial community, aside from the traditional function (e.g., organic carbon and nitrogen removal) in wastewater treatment. Video Abstract.

BACKGROUND: The microorganisms that inhabit food processing environments (FPE) can strongly influence the associated food quality and safety. In particular, the possibility that FPE may act as a reservoir of antibiotic-resistant microorganisms, and a hotspot for the transmission of antibiotic resistance genes (ARGs) is a concern in meat processing plants. Here, we monitor microbial succession and resistome dynamics relating to FPE through a detailed analysis of a newly opened pork cutting plant over 1.5 years of activity. RESULTS: We identified a relatively restricted principal microbiota dominated by Pseudomonas during the first 2 months, while a higher taxonomic diversity, an increased representation of other taxa (e.g., Acinetobacter, Psychrobacter), and a certain degree of microbiome specialization on different surfaces was recorded later on. An increase in total abundance, alpha diversity, and β-dispersion of ARGs, which were predominantly assigned to Acinetobacter and associated with resistance to certain antimicrobials frequently used on pig farms of the region, was detected over time. Moreover, a sharp increase in the occurrence of extended-spectrum β-lactamase-producing Enterobacteriaceae and vancomycin-resistant Enterococcaceae was observed when cutting activities started. ARGs associated with resistance to β-lactams, tetracyclines, aminoglycosides, and sulphonamides frequently co-occurred, and mobile genetic elements (i.e., plasmids, integrons) and lateral gene transfer events were mainly detected at the later sampling times in drains. CONCLUSIONS: The observations made suggest that pig carcasses were a source of resistant bacteria that then colonized FPE and that drains, together with some food-contact surfaces, such as equipment and table surfaces, represented a reservoir for the spread of ARGs in the meat processing facility. Video Abstract.

BACKGROUND: Microbiome-metabolome studies of the human gut have been gaining popularity in recent years, mostly due to accumulating evidence of the interplay between gut microbes, metabolites, and host health. Statistical and machine learning-based methods have been widely applied to analyze such paired microbiome-metabolome data, in the hope of identifying metabolites that are governed by the composition of the microbiome. Such metabolites can be likely modulated by microbiome-based interventions, offering a route for promoting gut metabolic health. Yet, to date, it remains unclear whether findings of microbially associated metabolites in any single study carry over to other studies or cohorts, and how robust and universal are microbiome-metabolites links. RESULTS: In this study, we addressed this challenge by performing a comprehensive meta-analysis to identify human gut metabolites that can be predicted based on the composition of the gut microbiome across multiple studies. We term such metabolites "robustly well-predicted". To this end, we processed data from 1733 samples from 10 independent human gut microbiome-metabolome studies, focusing initially on healthy subjects, and implemented a machine learning pipeline to predict metabolite levels in each dataset based on the composition of the microbiome. Comparing the predictability of each metabolite across datasets, we found 97 robustly well-predicted metabolites. These include metabolites involved in important microbial pathways such as bile acid transformations and polyamines metabolism. Importantly, however, other metabolites exhibited large variation in predictability across datasets, suggesting a cohort- or study-specific relationship between the microbiome and the metabolite. Comparing taxonomic contributors to different models, we found that some robustly well-predicted metabolites were predicted by markedly different sets of taxa across datasets, suggesting that some microbially associated metabolites may be governed by different members of the microbiome in different cohorts. We finally examined whether models trained on a control group of a given study successfully predicted the metabolite's level in the disease group of the same study, identifying several metabolites where the model was not transferable, indicating a shift in microbial metabolism in disease-associated dysbiosis. CONCLUSIONS: Combined, our findings provide a better understanding of the link between the microbiome and metabolites and allow researchers to put identified microbially associated metabolites within the context of other studies. Video abstract.

BACKGROUND: Obtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite improvements in bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenome binners obtain population consensus genomes but they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a framework for the integration of single-cell genomics and metagenomics, referred to as single-cell (sc) metagenomics, to reconstruct strain-resolved genomes from microbial communities at once. RESULTS: Our sc-metagenomics integration framework, termed SMAGLinker, uses single-cell amplified genomes (SAGs) generated using microfluidic technology as binning guides and integrates them with metagenome-assembled genomes (MAGs) to recover improved draft genomes. We compared sc-metagenomics with the metagenomics-alone approach using conventional metagenome binners. The sc-metagenomics approach showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids than conventional metagenomics in genome reconstruction from the cell mock community. In human microbiota samples, sc-metagenomics recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ, with 65 showing >90% completeness) and 45 skin microbial genomes (10 HQ, with 40 showing >90% completeness), respectively. Conventional metagenomics recovered one Staphylococcus hominis genome, whereas sc-metagenomics recovered two S. hominis genomes from identical skin microbiota sample. Single-cell sequencing revealed that these S. hominis genomes were derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had a substantial lack or excess of genome sequences and contamination from other Staphylococcus species (S. epidermidis). CONCLUSIONS: SMAGLinker enabled us to obtain strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. SMAGLinker will provide HQ genomes that are difficult to obtain using metagenomics alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks. SMAGLinker is available at https://github.com/kojiari/smaglinker . Video abstract.

BACKGROUND: The development of suppressive soils is a promising strategy to protect plants against soil-borne diseases in a sustainable and viable manner. The use of crop rotation and the incorporation of plant residues into the soil are known to alleviate the stress imposed by soil pathogens through dynamics changes in soil biological and physicochemical properties. However, relatively little is known about the extent to which specific soil amendments of plant residues trigger the development of plant-protective microbiomes. Here, we investigated how the incorporation of pineapple residues in soils highly infested with the banana Fusarium wilt disease alleviates the pathogen pressure via changes in soil microbiomes. RESULTS: The addition of above- and below-ground pineapple residues in highly infested soils significantly reduced the number of pathogens in the soil, thus resulting in a lower disease incidence. The development of suppressive soils was mostly related to trackable changes in specific fungal taxa affiliated with Aspergillus fumigatus and Fusarium solani, both of which displayed inhibitory effects against the pathogen. These antagonistic effects were further validated using an in vitro assay in which the pathogen control was related to growth inhibition via directly secreted antimicrobial substances and indirect interspecific competition for nutrients. The disease suppressive potential of these fungal strains was later validated using microbial inoculation in a well-controlled pot experiment. CONCLUSIONS: These results mechanistically demonstrated how the incorporation of specific plant residues into the soil induces trackable changes in the soil microbiome with direct implications for disease suppression. The incorporation of pineapple residues in the soil alleviated the pathogen pressure by increasing the relative abundance of antagonistic fungal taxa causing a negative effect on pathogen growth and disease incidence. Taken together, this study provides a successful example of how specific agricultural management strategies can be used to manipulate the soil microbiome towards the development of suppressive soils against economically important soil-borne diseases. Video Abstract.

BACKGROUND: Although considered as holobionts, macroalgae and their surface microbiota share intimate interactions that are still poorly understood. Little is known on the effect of environmental parameters on the close relationships between the host and its surface-associated microbiota, and even more in a context of coastal pollutions. Therefore, the main objective of this study was to decipher the impact of local environmental parameters, especially trace metal concentrations, on an algal holobiont dynamics using the Phaeophyta Taonia atomaria as a model. Through a multidisciplinary multi-omics approach combining metabarcoding and untargeted LC-MS-based metabolomics, the epibacterial communities and the surface metabolome of T. atomaria were monitored along a spatio-temporal gradient in the bay of Toulon (Northwestern Mediterranean coast) and its surrounding. Indeed, this geographical area displays a well-described trace metal gradient particularly relevant to investigate the effect of such pollutants on marine organisms. RESULTS: Epibacterial communities of T. atomaria exhibited a high specificity whatever the five environmentally contrasted collecting sites investigated on the NW Mediterranean coast. By integrating metabarcoding and metabolomics analyses, the holobiont dynamics varied as a whole. During the occurrence period of T. atomaria, epibacterial densities and α-diversity increased while the relative proportion of core communities decreased. Pioneer bacterial colonizers constituted a large part of the specific and core taxa, and their decrease might be linked to biofilm maturation through time. Then, the temporal increase of the Roseobacter was proposed to result from the higher temperature conditions, but also the increased production of dimethylsulfoniopropionate (DMSP) at the algal surface which could constitute of the source of carbon and sulfur for the catabolism pathways of these taxa. Finally, as a major result of this study, copper concentration constituted a key factor shaping the holobiont system. Thus, the higher expression of carotenoids suggested an oxidative stress which might result from an adaptation of the algal surface metabolome to high copper levels. In turn, this change in the surface metabolome composition could result in the selection of particular epibacterial taxa. CONCLUSION: We showed that associated epibacterial communities were highly specific to the algal host and that the holobiont dynamics varied as a whole. While temperature increase was confirmed to be one of the main parameters associated to Taonia dynamics, the originality of this study was highlighting copper-stress as a major driver of seaweed-epibacterial interactions. In a context of global change, this study brought new insights on the dynamics of a Mediterranean algal holobiont submitted to heavy anthropic pressures. Video abstract.