RESUMO
The translocation of non-indigenous species (NIS) around the world, especially in marine systems, is increasingly being recognized as a matter of concern. Species translocations have been shown to lead to wide ranging changes in food web structure and functioning. In addition to the direct effects of NIS, they could facilitate the accumulation or translocation of bacteria as part of their microbiomes. The Baltic Sea harbours many non-indigenous species, with most recent detection of the jellyfish Blackfordia virginica and the comb jelly Mnemiopsis leidyi in the low saline southwestern Baltic Sea. In this study, we used a multidisciplinary approach and investigated three gelatinous zooplankton species that co-occur in the same environment and feed on similar zooplankton food sources but show different histories of origin. The aim was to conduct a comparative microbiome analysis of indigenous and non-indigenous gelatinous zooplankton species in the low-saline southwestern Baltic Sea. Next-generation 16S rRNA marker gene sequencing of the V1/V2 region was employed to study the bacterial microbiome compositions. All tested species showed significant differences in their microbiome compositions (one way ANOSIM, R = 1, P < 0.008) with dissimilarities ranging from 85 to 92%. The indigenous jellyfish Aurelia aurita showed the highest bacterial operational taxonomic unit (OTU) richness. The overall differentiation between microbiomes was driven by eight indicator OTUs, which included Mycoplasma and Vibrio species. These bacteria can be problematic, as they include known pathogenic strains that are relevant to human health and aquaculture activities. Our results suggest that the impact assessment of NIS should consider potential pathogenic bacteria, enriched in the environment due to invasion, as potential risks to aquaculture activities.
Assuntos
Microbiota , Animais , RNA Ribossômico 16S , Cifozoários , Vibrio , ZooplânctonRESUMO
Obesity and type 2 diabetes (T2D) are metabolic disorders that are linked to microbiome alterations. However, their co-occurrence poses challenges in disentangling microbial features unique to each condition. We analyzed gut microbiomes of lean non-diabetic (n = 633), obese non-diabetic (n = 494), and obese individuals with T2D (n = 153) from German population and metabolic disease cohorts. Microbial taxonomic and functional profiles were analyzed along with medical histories, serum metabolomics, biometrics, and dietary data. Obesity was associated with alterations in microbiome composition, individual taxa, and functions with notable changes in Akkermansia, Faecalibacterium, Oscillibacter, and Alistipes, as well as in serum metabolites that correlated with gut microbial patterns. However, microbiome associations were modest for T2D, with nominal increases in Escherichia/Shigella. Medications, including antihypertensives and antidiabetics, along with dietary supplements including iron, were significantly associated with microbiome variation. These results differentiate microbial components of these interrelated metabolic diseases and identify dietary and medication exposures to consider in future studies.