Temperature and water availability drive insect seasonality across a temperate and a tropical region.

The more insects there are, the more food there is for insectivores and the higher the likelihood for insect-associated ecosystem services. Yet, we lack insights into the drivers of insect biomass over space and seasons, for both tropical and temperate zones. We used 245 Malaise traps, managed by 191 volunteers and park guards, to characterize year-round flying insect biomass in a temperate (Sweden) and a tropical (Madagascar) country. Surprisingly, we found that local insect biomass was similar across zones. In Sweden, local insect biomass increased with accumulated heat and varied across habitats, while biomass in Madagascar was unrelated to the environmental predictors measured. Drivers behind seasonality partly converged: In both countries, the seasonality of insect biomass differed between warmer and colder sites, and wetter and drier sites. In Sweden, short-term deviations from expected season-specific biomass were explained by week-to-week fluctuations in accumulated heat, rainfall and soil moisture, whereas in Madagascar, weeks with higher soil moisture had higher insect biomass. Overall, our study identifies key drivers of the seasonal distribution of flying insect biomass in a temperate and a tropical climate. This knowledge is key to understanding the spatial and seasonal availability of insects-as well as predicting future scenarios of insect biomass change.

New chemical and microbial perspectives on vitamin B1 and vitamer dynamics of a coastal system.

Vitamin B1 (thiamin, B1) is an essential micronutrient for cells, yet intriguingly in aquatic systems most bacterioplankton are unable to synthesize it de novo (auxotrophy), requiring an exogenous source. Cycling of this valuable metabolite in aquatic systems has not been fully investigated and vitamers (B1-related compounds) have only begun to be measured and incorporated into the B1 cycle. Here, we identify potential key producers and consumers of B1 and gain new insights into the dynamics of B1 cycling through measurements of B1 and vitamers (HMP: 4-amino-5-hydroxymethyl-2-methylpyrimidine, HET: 4-methyl-5-thiazoleethanol, FAMP: N-formyl-4-amino-5-aminomethyl-2-methylpyrimidine) in the particulate and dissolved pool in a temperate coastal system. Dissolved B1 was not the primary limiting nutrient for bacterial production and was relatively stable across seasons with concentrations ranging from 74-117 pM, indicating a balance of supply and demand. However, vitamer concentration changed markedly with season as did transcripts related to vitamer salvage and transport suggesting use of vitamers by certain bacterioplankton, e.g. Pelagibacterales. Genomic and transcriptomic analyses showed that up to 78% of the bacterioplankton taxa were B1 auxotrophs. Notably, de novo B1 production was restricted to a few abundant bacterioplankton (e.g. Vulcanococcus, BACL14 (Burkholderiales), Verrucomicrobiales) across seasons. In summer, abundant picocyanobacteria were important putative B1 sources, based on transcriptional activity, leading to an increase in the B1 pool. Our results provide a new dynamic view of the players and processes involved in B1 cycling over time in coastal waters, and identify specific priority populations and processes for future study.

Towards high-throughput parallel imaging and single-cell transcriptomics of microbial eukaryotic plankton.

Single-cell transcriptomics has the potential to provide novel insights into poorly studied microbial eukaryotes. Although several such technologies are available and benchmarked on mammalian cells, few have been tested on protists. Here, we applied a microarray single-cell sequencing (MASC-seq) technology, that generates microscope images of cells in parallel with capturing their transcriptomes, on three species representing important plankton groups with different cell structures; the ciliate Tetrahymena thermophila, the diatom Phaeodactylum tricornutum, and the dinoflagellate Heterocapsa sp. Both the cell fixation and permeabilization steps were adjusted. For the ciliate and dinoflagellate, the number of transcripts of microarray spots with single cells were significantly higher than for background spots, and the overall expression patterns were correlated with that of bulk RNA, while for the much smaller diatom cells, it was not possible to separate single-cell transcripts from background. The MASC-seq method holds promise for investigating "microbial dark matter", although further optimizations are necessary to increase the signal-to-noise ratio.

A comprehensive dataset on spatiotemporal variation of microbial plankton communities in the Baltic Sea.

The Baltic Sea is one of the largest brackish water environments on earth and is characterised by pronounced physicochemical gradients and seasonal dynamics. Although the Baltic Sea has a long history of microscopy-based plankton monitoring, DNA-based metabarcoding has so far mainly been limited to individual transect cruises or time-series of single stations. Here we report a dataset covering spatiotemporal variation in prokaryotic and eukaryotic microbial communities and physicochemical parameters. Within 13-months between January 2019 and February 2020, 341 water samples were collected at 22 stations during monthly cruises along the salinity gradient. Both salinity and seasonality are strongly reflected in the data. Since the dataset was generated with both metabarcoding and microscopy-based methods, it provides unique opportunities for both technical and ecological analyses, and is a valuable biodiversity reference for future studies, in the prospect of climate change.

Optimizing insect metabarcoding using replicated mock communities.

1: Metabarcoding (high-throughput sequencing of marker gene amplicons) has emerged as a promising and cost-effective method for characterizing insect community samples. Yet, the methodology varies greatly among studies and its performance has not been systematically evaluated to date. In particular, it is unclear how accurately metabarcoding can resolve species communities in terms of presence-absence, abundances, and biomass. 2: Here we use mock community experiments and a simple probabilistic model to evaluate the effect of different DNA extraction protocols on metabarcoding performance. Specifically, we ask four questions: (Q1) How consistent are the recovered community profiles across replicate mock communities?; (Q2) How does the choice of lysis buffer affect the recovery of the original community?; (Q3) How are community estimates affected by differing lysis times and homogenization?; and (Q4) Is it possible to obtain adequate species abundance estimates through the use of biological spike-ins? 3: We show that estimates are quite variable across community replicates. In general, a mild lysis protocol is better at reconstructing species lists and approximate counts, while homogenization is better at retrieving biomass composition. Small insects are more likely to be detected in lysates, while some tough species require homogenization to be detected. Results are less consistent across biological replicates for lysates than for homogenates. Some species are associated with strong PCR amplification bias, which complicates the reconstruction of species counts. Yet, with adequate spike-in data, species abundance can be determined with roughly 40% standard error for homogenates, and with roughly 50% standard error for lysates, under ideal conditions. In the latter case, however, this often requires species-specific reference data, while spike-in data generalizes better across species for homogenates. 4: We conclude that a non-destructive, mild lysis approach shows the highest promise for presence/absence description of the community, while also allowing future morphological or molecular work on the material. However, homogenization protocols perform better for characterizing community composition, in particular in terms of biomass.

FAVIS: Fast and versatile protocol for non-destructive metabarcoding of bulk insect samples.

Insects are diverse and sustain essential ecosystem functions, yet remain understudied. Recent reports about declines in insect abundance and diversity have highlighted a pressing need for comprehensive large-scale monitoring. Metabarcoding (high-throughput bulk sequencing of marker gene amplicons) offers a cost-effective and relatively fast method for characterizing insect community samples. However, the methodology applied varies greatly among studies, thus complicating the design of large-scale and repeatable monitoring schemes. Here we describe a non-destructive metabarcoding protocol that is optimized for high-throughput processing of Malaise trap samples and other bulk insect samples. The protocol details the process from obtaining bulk samples up to submitting libraries for sequencing. It is divided into four sections: 1) Laboratory workspace preparation; 2) Sample processing-decanting ethanol, measuring the wet-weight biomass and the concentration of the preservative ethanol, performing non-destructive lysis and preserving the insect material for future work; 3) DNA extraction and purification; and 4) Library preparation and sequencing. The protocol relies on readily available reagents and materials. For steps that require expensive infrastructure, such as the DNA purification robots, we suggest alternative low-cost solutions. The use of this protocol yields a comprehensive assessment of the number of species present in a given sample, their relative read abundances and the overall insect biomass. To date, we have successfully applied the protocol to more than 7000 Malaise trap samples obtained from Sweden and Madagascar. We demonstrate the data yield from the protocol using a small subset of these samples.

Large-scale phylogenomics of aquatic bacteria reveal molecular mechanisms for adaptation to salinity.

The crossing of environmental barriers poses major adaptive challenges. Rareness of freshwater-marine transitions separates the bacterial communities, but how these are related to brackish counterparts remains elusive, as do the molecular adaptations facilitating cross-biome transitions. We conducted large-scale phylogenomic analysis of freshwater, brackish, and marine quality-filtered metagenome-assembled genomes (11,248). Average nucleotide identity analyses showed that bacterial species rarely existed in multiple biomes. In contrast, distinct brackish basins cohosted numerous species, but their intraspecific population structures displayed clear signs of geographic separation. We further identified the most recent cross-biome transitions, which were rare, ancient, and most commonly directed toward the brackish biome. Transitions were accompanied by systematic changes in amino acid composition and isoelectric point distributions of inferred proteomes, which evolved over millions of years, as well as convergent gains or losses of specific gene functions. Therefore, adaptive challenges entailing proteome reorganization and specific changes in gene content constrains the cross-biome transitions, resulting in species-level separation between aquatic biomes.

Linking prokaryotic genome size variation to metabolic potential and environment.

While theories and models have appeared to explain genome size as a result of evolutionary processes, little work has shown that genome sizes carry ecological signatures. Our work delves into the ecological implications of microbial genome size variation in benthic and pelagic habitats across environmental gradients of the brackish Baltic Sea. While depth is significantly associated with genome size in benthic and pelagic brackish metagenomes, salinity is only correlated to genome size in benthic metagenomes. Overall, we confirm that prokaryotic genome sizes in Baltic sediments (3.47 Mbp) are significantly bigger than in the water column (2.96 Mbp). While benthic genomes have a higher number of functions than pelagic genomes, the smallest genomes coded for a higher number of module steps per Mbp for most of the functions irrespective of their environment. Some examples of this functions are amino acid metabolism and central carbohydrate metabolism. However, we observed that nitrogen metabolism was almost absent in pelagic genomes and was mostly present in benthic genomes. Finally, we also show that Bacteria inhabiting Baltic sediments and water column not only differ in taxonomy, but also in their metabolic potential, such as the Wood-Ljungdahl pathway or the presence of different hydrogenases. Our work shows how microbial genome size is linked to abiotic factors in the environment, metabolic potential and taxonomic identity of Bacteria and Archaea within aquatic ecosystems.

ASV portal: an interface to DNA-based biodiversity data in the Living Atlas.

BACKGROUND: The Living Atlas is an open source platform used to collect, visualise and analyse biodiversity data from multiple sources, and serves as the national biodiversity data hub in many countries. Although powerful, the Living Atlas has had limited functionality for species occurrence data derived from DNA sequences. As a step toward integrating this fast-growing data source into the platform, we developed the Amplicon Sequence Variant (ASV) portal: a web interface to sequence-based biodiversity observations in the Living Atlas. RESULTS: The ASV portal allows data providers to submit denoised metabarcoding output to the Living Atlas platform via an intermediary ASV database. It also enables users to search for existing ASVs and associated Living Atlas records using the Basic Local Alignment Search Tool, or via filters on taxonomy and sequencing details. The ASV portal is a Python-Flask/jQuery web interface, implemented as a multi-container docker service, and is an integral part of the Swedish Biodiversity Data Infrastructure. CONCLUSION: The ASV portal is a web interface that effectively integrates biodiversity data derived from DNA sequences into the Living Atlas platform.

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.

Evaluating metagenomic assembly approaches for biome-specific gene catalogues.

BACKGROUND: For many environments, biome-specific microbial gene catalogues are being recovered using shotgun metagenomics followed by assembly and gene calling on the assembled contigs. The assembly is typically conducted either by individually assembling each sample or by co-assembling reads from all the samples. The co-assembly approach can potentially recover genes that display too low abundance to be assembled from individual samples. On the other hand, combining samples increases the risk of mixing data from closely related strains, which can hamper the assembly process. In this respect, assembly on individual samples followed by clustering of (near) identical genes is preferable. Thus, both approaches have potential pros and cons, but it remains to be evaluated which assembly strategy is most effective. Here, we have evaluated three assembly strategies for generating gene catalogues from metagenomes using a dataset of 124 samples from the Baltic Sea: (1) assembly on individual samples followed by clustering of the resulting genes, (2) co-assembly on all samples, and (3) mix assembly, combining individual and co-assembly. RESULTS: The mix-assembly approach resulted in a more extensive nonredundant gene set than the other approaches and with more genes predicted to be complete and that could be functionally annotated. The mix assembly consists of 67 million genes (Baltic Sea gene set, BAGS) that have been functionally and taxonomically annotated. The majority of the BAGS genes are dissimilar (< 95% amino acid identity) to the Tara Oceans gene dataset, and hence, BAGS represents a valuable resource for brackish water research. CONCLUSION: The mix-assembly approach represents a feasible approach to increase the information obtained from metagenomic samples. Video abstract.

Short- and long-read metabarcoding of the eukaryotic rRNA operon: Evaluation of primers and comparison to shotgun metagenomics sequencing.

High-throughput sequencing-based analysis of microbial diversity has evolved vastly over the last decade. Currently, the go-to method for studying microbial eukaryotes is short-read metabarcoding of variable regions of the 18S rRNA gene with <500 bp amplicons. However, there is a growing interest in applying long-read sequencing of amplicons covering the rRNA operon for improving taxonomic resolution. For both methods, the choice of primers is crucial. It determines if community members are covered, if they can be identified at a satisfactory taxonomic level, and if the obtained community profile is representative. Here, we designed new primers targeting 18S and 28S rRNA based on 177,934 and 21,072 database sequences, respectively. The primers were evaluated in silico along with published primers on reference sequence databases and marine metagenomics data sets. We further evaluated a subset of the primers for short- and long-read sequencing on environmental samples in vitro and compared the obtained community profile with primer-unbiased metagenomic sequencing. Of the short-read pairs, a new V6-V8 pair and the V4_Balzano pair used with a simplified PCR protocol provided good results in silico and in vitro. Fewer differences were observed between the long-read primer pairs. The long-read amplicons and ITS1 alone provided higher taxonomic resolution than V4. Together, our results represent a reference and guide for selection of robust primers for research on and environmental monitoring of microbial eukaryotes.

Salivary Microbiota and Host-Inflammatory Responses in Periodontitis Affected Individuals With and Without Rheumatoid Arthritis.

Objectives: Periodontitis and rheumatoid arthritis (RA) are two widespread chronic inflammatory diseases with a previously suggested association. The objective of the current study was to compare the oral microbial composition and host´s inflammatory mediator profile of saliva samples obtained from subjects with periodontitis, with and without RA, as well as to predict biomarkers, of bacterial pathogens and/or inflammatory mediators, for classification of samples associated with periodontitis and RA. Methods: Salivary samples were obtained from 53 patients with periodontitis and RA and 48 non-RA with chronic periodontitis. The microbial composition was identified using 16S rRNA gene sequencing and compared across periodontitis patients with and without RA. Levels of inflammatory mediators were determined using a multiplex bead assay, compared between the groups and correlated to the microbial profile. The achieved data was analysed using PCoA, DESeq2 and two machine learning algorithms, OPLS-DA and sPLS-DA. Results: Differential abundance DESeq2 analyses showed that the four most highly enriched (log2 FC >20) amplicon sequence variants (ASVs) in the non-RA periodontitis group included Alloprevotella sp., Prevotella sp., Haemophilus sp., and Actinomyces sp. whereas Granulicatella sp., Veillonella sp., Megasphaera sp., and Fusobacterium nucleatum were the most highly enriched ASVs (log2 FC >20) in the RA group. OPLS-DA with log2 FC analyses demonstrated that the top ASVs with the highest importance included Vampirovibrio sp. having a positive correlation with non-RA group, and seven ASVs belonging to Sphingomonas insulae, Sphingobium sp., Novosphingobium aromaticivorans, Delftia acidovorans, Aquabacterium spp. and Sphingomonas echinoides with a positive correlation with RA group. Among the detected inflammatory mediators in saliva samples, TWEAK/TNFSF12, IL-35, IFN-α2, pentraxin-3, gp130/sIL6Rb, sIL-6Ra, IL-19 and sTNF-R1 were found to be significantly increased in patients with periodontitis and RA compared to non-RA group with periodontitis. Moreover, correlations between ASVs and inflammatory mediators using sPLS-DA analysis revealed that TWEAK/TNFSF12, pentraxin-3 and IL-19 were positively correlated with the ASVs Sphingobium sp., Acidovorax delafieldii, Novosphingobium sp., and Aquabacterium sp. Conclusion: Our results suggest that the combination of microbes and host inflammatory mediators could be more efficient to be used as a predictable biomarker associated with periodontitis and RA, as compared to microbes and inflammatory mediators alone.

Machine Learning Predicts the Presence of 2,4,6-Trinitrotoluene in Sediments of a Baltic Sea Munitions Dumpsite Using Microbial Community Compositions.

Bacteria are ubiquitous and live in complex microbial communities. Due to differences in physiological properties and niche preferences among community members, microbial communities respond in specific ways to environmental drivers, potentially resulting in distinct microbial fingerprints for a given environmental state. As proof of the principle, our goal was to assess the opportunities and limitations of machine learning to detect microbial fingerprints indicating the presence of the munition compound 2,4,6-trinitrotoluene (TNT) in southwestern Baltic Sea sediments. Over 40 environmental variables including grain size distribution, elemental composition, and concentration of munition compounds (mostly at pmol⋅g-1 levels) from 150 sediments collected at the near-to-shore munition dumpsite Kolberger Heide by the German city of Kiel were combined with 16S rRNA gene amplicon sequencing libraries. Prediction was achieved using Random Forests (RFs); the robustness of predictions was validated using Artificial Neural Networks (ANN). To facilitate machine learning with microbiome data we developed the R package phyloseq2ML. Using the most classification-relevant 25 bacterial genera exclusively, potentially representing a TNT-indicative fingerprint, TNT was predicted correctly with up to 81.5% balanced accuracy. False positive classifications indicated that this approach also has the potential to identify samples where the original TNT contamination was no longer detectable. The fact that TNT presence was not among the main drivers of the microbial community composition demonstrates the sensitivity of the approach. Moreover, environmental variables resulted in poorer prediction rates than using microbial fingerprints. Our results suggest that microbial communities can predict even minor influencing factors in complex environments, demonstrating the potential of this approach for the discovery of contamination events over an integrated period of time. Proven for a distinct environment future studies should assess the ability of this approach for environmental monitoring in general.

Ecologically coherent population structure of uncultivated bacterioplankton.

Bacterioplankton are main drivers of biogeochemical cycles and important components of aquatic food webs. While sequencing-based studies have revealed how bacterioplankton communities are structured in time and space, relatively little is known about intraspecies diversity patterns and their ecological relevance. Here, we use the newly developed software POGENOM (POpulation GENomics from Metagenomes) to investigate genomic diversity and differentiation in metagenome-assembled genomes from the Baltic Sea, and investigate their genomic variation using metagenome data spanning a 1700 km transect and covering seasonal variation at one station. The majority of the investigated species, representing several major bacterioplankton clades, displayed population structures correlating significantly with environmental factors such as salinity and temperature. Population differentiation was more pronounced over spatial than temporal scales. We discovered genes that have undergone adaptation to different salinity regimes, potentially responsible for the populations' existence along with the salinity range. This in turn implies the broad existence of ecotypes that may remain undetected by rRNA gene sequencing. Our findings emphasize the importance of physiological barriers, and highlight the role of adaptive divergence as a structuring mechanism of bacterioplankton species.

The Fennoscandian Shield deep terrestrial virosphere suggests slow motion 'boom and burst' cycles.

The deep biosphere contains members from all three domains of life along with viruses. Here we investigate the deep terrestrial virosphere by sequencing community nucleic acids from three groundwaters of contrasting chemistries, origins, and ages. These viromes constitute a highly unique community compared to other environmental viromes and sequenced viral isolates. Viral host prediction suggests that many of the viruses are associated with Firmicutes and Patescibacteria, a superphylum lacking previously described active viruses. RNA transcript-based activity implies viral predation in the shallower marine water-fed groundwater, while the deeper and more oligotrophic waters appear to be in 'metabolic standby'. Viral encoded antibiotic production and resistance systems suggest competition and antagonistic interactions. The data demonstrate a viral community with a wide range of predicted hosts that mediates nutrient recycling to support a higher microbial turnover than previously anticipated. This suggests the presence of 'kill-the-winner' oscillations creating slow motion 'boom and burst' cycles.

Deltaproteobacteria and Spirochaetes-Like Bacteria Are Abundant Putative Mercury Methylators in Oxygen-Deficient Water and Marine Particles in the Baltic Sea.

Methylmercury (MeHg), a neurotoxic compound biomagnifying in aquatic food webs, can be a threat to human health via fish consumption. However, the composition and distribution of the microbial communities mediating the methylation of mercury (Hg) to MeHg in marine systems remain largely unknown. In order to fill this knowledge gap, we used the Baltic Sea Reference Metagenome (BARM) dataset to study the abundance and distribution of the genes involved in Hg methylation (the hgcAB gene cluster). We determined the relative abundance of the hgcAB genes and their taxonomic identity in 81 brackish metagenomes that cover spatial, seasonal and redox variability in the Baltic Sea water column. The hgcAB genes were predominantly detected in anoxic water, but some hgcAB genes were also detected in hypoxic and normoxic waters. Phylogenetic analysis identified putative Hg methylators within Deltaproteobacteria, in oxygen-deficient water layers, but also Spirochaetes-like and Kiritimatiellaeota-like bacteria. Higher relative quantities of hgcAB genes were found in metagenomes from marine particles compared to free-living communities in anoxic water, suggesting that such particles are hotspot habitats for Hg methylators in oxygen-depleted seawater. Altogether, our work unveils the diversity of the microorganisms with the potential to mediate MeHg production in the Baltic Sea and pinpoint the important ecological niches for these microorganisms within the marine water column.

The environment drives microbial trait variability in aquatic habitats.

A prerequisite to improve the predictability of microbial community dynamics is to understand the mechanisms of microbial assembly. To study factors that contribute to microbial community assembly, we examined the temporal dynamics of genes in five aquatic metagenome time-series, originating from marine offshore or coastal sites and one lake. With this trait-based approach we expected to find gene-specific patterns of temporal allele variability that depended on the seasonal metacommunity size of carrier-taxa and the variability of the milieu and the substrates to which the resulting proteins were exposed. In more detail, we hypothesized that a larger seasonal metacommunity size would result in increased temporal variability of functional units (i.e., gene alleles), as shown previously for taxonomic units. We further hypothesized that multicopy genes would feature higher temporal variability than single-copy genes, as gene multiplication can result from high variability in substrate quality and quantity. Finally, we hypothesized that direct exposure of proteins to the extracellular environment would result in increased temporal variability of the respective gene compared to intracellular proteins that are less exposed to environmental fluctuations. The first two hypotheses were confirmed in all data sets, while significant effects of the subcellular location of gene products was only seen in three of the five time-series. The gene with the highest allele variability throughout all data sets was an iron transporter, also representing a target for phage infection. Previous work has emphasized the role of phage-prokaryote interactions as a major driver of microbial diversity. Our finding therefore points to a potentially important role of iron transporter-mediated phage infections for the assembly and maintenance of diversity in aquatic prokaryotes.

Genome sequence of segmented filamentous bacteria present in the human intestine.

Segmented filamentous bacteria (SFB) are unique immune modulatory bacteria colonizing the small intestine of a variety of animals in a host-specific manner. SFB exhibit filamentous growth and attach to the host's intestinal epithelium, offering a physical route of interaction. SFB affect functions of the host immune system, among them IgA production and T-cell maturation. Until now, no human-specific SFB genome has been reported. Here, we report the metagenomic reconstruction of an SFB genome from a human ileostomy sample. Phylogenomic analysis clusters the genome with SFB genomes from mouse, rat and turkey, but the genome is genetically distinct, displaying 65-71% average amino acid identity to the others. By screening human faecal metagenomic datasets, we identified individuals carrying sequences identical to the new SFB genome. We thus conclude that a unique SFB variant exists in humans and foresee a renewed interest in the elucidation of SFB functionality in this environment.

Gastric Microbiota in a Low-Helicobacter pylori Prevalence General Population and Their Associations With Gastric Lesions.

INTRODUCTION: Non-Helicobacter pylori microbiota might account for some cases with unexplained chronic gastritis that may in a minority eventually progress to gastric cancer through the Correa cascade. We characterized gastric microbiota by describing the normal stomach, compared it with early precancerous lesions and other disease states, and assessed whether H. pylori status affects bacterial diversity. METHODS: In a population-based study of those with and without gastrointestinal symptoms, cytology brush samples were collected during endoscopy from 316 individuals. Mucosal status was classified as normal mucosa (171), nonatrophic H. pylori gastritis (33), atrophic gastritis (12), or antral chemical gastritis (61). The 16S rRNA gene sequencing and analysis were performed to characterize the microbiota. RESULTS: Microbiota in atrophic gastritis and nonatrophic H. pylori gastritis stomachs were dysbiotic and differed from those in the normal stomach (P = 0.001). The normal stomach had the highest microbial diversity, followed by antral chemical gastritis. The atrophic gastritis and chronic H. pylori gastritis groups had the lowest diversity, a difference that was statistically significant (P = 0.01). Besides H. pylori, non-H. pylori bacteria accounted for group differences. Microbial network analysis showed that the normal group network was most highly connected, whereas the H. pylori gastritis group had the lowest connection. We found an increasing positive co-occurrence of oral bacteria in the stomach because samples deviated from the normal network, some of which were pathogens. The H. pylori-negative group had the highest microbial diversity (Shannon index) compared with the H. pylori-positive group (P = 0.001). DISCUSSION: In this low-H. pylori prevalence general population, the gastric mucosal microbiota of the normal stomach differed significantly from those with nonatrophic or atrophic gastritis. There was an increasing abundance of pathogenic bacteria from the normal state to early precancerous states.