15 research outputs found

    Graphene oxide elicits microbiome-dependent type 2 immune responses via the aryl hydrocarbon receptor

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    The gut microbiome produces metabolites that interact with the aryl hydrocarbon receptor (AhR), a key regulator of immune homoeostasis in the gut(1,2). Here we show that oral exposure to graphene oxide (GO) modulates the composition of the gut microbiome in adult zebrafish, with significant differences in wild-type versus ahr2-deficient animals. Furthermore, GO was found to elicit AhR-dependent induction of cyp1a and homing of lck(+) cells to the gut in germ-free zebrafish larvae when combined with the short-chain fatty acid butyrate. To obtain further insights into the immune responses to GO, we used single-cell RNA sequencing to profile cells from whole germ-free embryos as well as cells enriched for lck. These studies provided evidence for the existence of innate lymphoid cell (ILC)-like cells(3) in germ-free zebrafish. Moreover, GO endowed with a 'corona' of microbial butyrate triggered the induction of ILC2-like cells with attributes of regulatory cells. Taken together, this study shows that a nanomaterial can influence the crosstalk between the microbiome and immune system in an AhR-dependent manner.Peer reviewe

    Increasing oxygen deficiency changes rare and moderately abundant bacterial communities in coastal soft sediments

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    Coastal hypoxia is a major environmental problem worldwide. Hypoxia-induced changes in sediment bacterial communities harm marine ecosystems and alter biogeochemical cycles. Nevertheless, the resistance of sediment bacterial communities to hypoxic stress is unknown. We investigated changes in bacterial communities during hypoxic-anoxic disturbance by artificially inducing oxygen deficiency to the seafloor for 0, 3, 7, and 48 days, with subsequent molecular biological analyses. We further investigated relationships between bacterial communities, benthic macrofauna and nutrient effluxes across the sediment-water-interface during hypoxic-anoxic stress, considering differentially abundant operational taxonomic units (OTUs). The composition of the moderately abundant OTUs changed significantly after seven days of oxygen deficiency, while the abundant and rare OTUs first changed after 48 days. High bacterial diversity maintained the resistance of the communities during oxygen deficiency until it dropped after 48 days, likely due to anoxia-induced loss of macrofaunal diversity and bioturbation. Nutrient fluxes, especially ammonium, correlated positively with the moderate and rare OTUs, including potential sulfate reducers. Correlations may reflect bacteria-mediated nutrient effluxes that accelerate eutrophication. The study suggests that even slightly higher bottom-water oxygen concentrations, which could sustain macrofaunal bioturbation, enable bacterial communities to resist large compositional changes and decrease the harmful consequences of hypoxia in marine ecosystems.Peer reviewe

    Contrasting microbiotas between Finnish and Estonian infants : exposure to Acinetobacter may contribute to the allergy gap

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    Background Allergic diseases are more common in Finland than in Estonia, which-according to the biodiversity hypothesis-could relate to differences in early microbial exposures. Methods We aimed at defining possible microbial perturbations preceding early atopic sensitization. Stool, nasal and skin samples of 6-month-old DIABIMMUNE study participants with HLA susceptibility to type 1 diabetes were collected. We compared microbiotas of sensitized (determined by specific IgE results at 18 months of age) and unsensitized Estonian and Finnish children. Results Sensitization was differentially targeted between populations, as egg-specific and birch pollen-specific IgE was more common in Finland. Microbial diversity and community composition also differed; the genusAcinetobacterwas more abundant in Estonian skin and nasal samples. Particularly, the strain-level profile ofAcinetobacter lwoffiiwas more diverse in Estonian samples. Early microbiota was not generally associated with later sensitization. Microbial composition tended to differ between children with or without IgE-related sensitization, but only in Finland. While land-use pattern (ie green areas vs. urban landscapes around the children's homes) was not associated with microbiota as a whole, it associated with the composition of the genusAcinetobacter. Breastfeeding affected gut microbial composition and seemed to protect from sensitization. Conclusions In accordance with the biodiversity hypothesis, our results support disparate early exposure to environmental microbes between Finnish and Estonian children and suggest a significant role of the genusAcinetobacterin the allergy gap between the two populations. The significance of the observed differences for later allergic sensitization remains open.Peer reviewe

    Microbe-host interplay in atopic dermatitis and psoriasis

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    Despite recent advances in understanding microbial diversity in skin homeostasis, the relevance of microbial dysbiosis in inflammatory disease is poorly understood. Here we perform a comparative analysis of skin microbial communities coupled to global patterns of cutaneous gene expression in patients with atopic dermatitis or psoriasis. The skin microbiota is analysed by 16S amplicon or whole genome sequencing and the skin transcriptome by microarrays, followed by integration of the data layers. We find that atopic dermatitis and psoriasis can be classified by distinct microbes, which differ from healthy volunteers microbiome composition. Atopic dermatitis is dominated by a single microbe (Staphylococcus aureus), and associated with a disease relevant host transcriptomic signature enriched for skin barrier function, tryptophan metabolism and immune activation. In contrast, psoriasis is characterized by co-occurring communities of microbes with weak associations with disease related gene expression. Our work provides a basis for biomarker discovery and targeted therapies in skin dysbiosis.Peer reviewe

    Effects of Organic Pollutants on Bacterial Communities Under Future Climate Change Scenarios

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    Coastal ecosystems are highly dynamic and can be strongly influenced by climate change, anthropogenic activities (e.g. pollution) and a combination of the two pressures. As a result of climate change, the northern hemisphere is predicted to undergo an increased precipitation regime, leading in turn to higher terrestrial runoff and increased river inflow. This increased runoff will transfer terrestrial dissolved organic matter (tDOM) and anthropogenic contaminants to coastal waters. Such changes can directly influence the resident biology, particularly at the base of the food web, and can influence the partitioning of contaminants and thus their potential impact on the food web. Bacteria have been shown to respond to high tDOM concentration and organic pollutants loads, and could represent the entry of some pollutants into coastal food webs. We carried out a mesocosm experiment to determine the effects of: 1) increased tDOM concentration, 2) organic pollutant exposure, and 3) the combined effect of these two factors, on pelagic bacterial communities. This study showed significant responses in bacterial community composition under the three environmental perturbations tested. The addition of tDOM increased bacterial activity and diversity, while the addition of organic pollutants led to an overall reduction of these parameters, particularly under concurrent elevated tDOM concentration. Furthermore, we identified 33 bacterial taxa contributing to the significant differences observed in community composition, as well as 35 bacterial taxa which responded differently to extended exposure to organic pollutants. These findings point to the potential impact of organic pollutants under future climate change conditions on the basal coastal ecosystem, as well as to the potential utility of natural bacterial communities as efficient indicators of environmental disturbance.Peer reviewe

    Characteristic T-RFs of bacterial communities in the estuary, coastal and open-sea sediment samples and in the sediment samples from different depths.

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    <p>Distance-based discriminant analysis was performed on bacterial T-RF data (produced by HaeIII), which were divided into <i>a priori</i> groups of (A) estuary, coastal and open-sea sediments as well as (B) depth classes. Taxonomic assignments of T-RFs (refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067061#pone.0067061.s005" target="_blank">Table S2</a>): Black numbers = <i>Alphaproteobacteria</i>, <i>Flavobacteria</i>, <i>Gammaproteobacteria</i> and/or <i>Sphingobacteria</i> (each T-RF represented more than one taxon), red numbers = <i>Chloroflexi</i> (mainly family <i>Anaerolineaceae</i>), green numbers = <i>Deltaproteobacteria</i>; sulphate reducing taxa, orange numbers = <i>Betaproteobacteria</i>, violet numers = <i>Clostridia</i>, and light blue numbers = <i>Planctomycetes</i>. Only those T-RFs that affected the differentiation of a <i>priori groups</i> (canonical scores of discriminant axes 1 and 2 were above 1.0) and which belonged to the most common bacterial groups in each <i>a priori</i> group were included.</p

    Ratios of organic carbon vs. organic nitrogen and organic carbon vs. organic phosphorus of the sediment samples.

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    <p>(A) Ratios of organic carbon vs. organic nitrogen and organic carbon vs. organic phosphorus along the continuum beginning from the Baltic Proper and western Gulf of Finland towards the eastern Gulf of Finland (sampling sites 1−9), (B) in the Ahvenkoskenlahti Bay estuary (sampling sites 10−12) and along the sediment depth. Refer to locations of the sediment sampling sites in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067061#pone-0067061-g001" target="_blank">Figures 1A and 1B</a>.</p

    Proportional effects of sediment chemical and spatial factors as well as other properties of the sampling sites on the variation in bacterial communities in organic-rich brackish sediments.

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    <p>Chemical parameters included those used in CAP (refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067061#pone-0067061-g003" target="_blank">Figure 3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067061#pone.0067061.s007" target="_blank">Dataset S2</a>). Spatial parameters included geographic coordinates and sediment depth, and other properties of the sampling sites consisted of sediment accumulation rate (SAR) and water depth (refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067061#pone.0067061.s004" target="_blank">Table S1</a>).</p
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