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Background and aims: The diversity and stability of belowground microbiota communities influence plant health. However, changes over time in the microbiome composition associated with healthy and diseased trees remains poorly understood. The goal of this study is to understand the changes in belowground microbial community associated with Verticillium wilt of smoke trees to provide a basis for the combination of biological agents and chemical measures to combat Verticillium wilt of smoke trees. Methods: In this study, we used an amplicon-based approach to reveal distinct differences in the diversity, structure and composition of the belowground microbial communities of healthy and diseased smoke trees from June to October. Results: The structure, composition and interactions of the belowground microbial communities are different between healthy and diseased smoke trees from June to October. The co-occurrence networks of the belowground microbial community changed with the severity of the disease over time. Additionally, the structural community of healthy and diseased trees showed a shift in keystone OTUs. Conclusions: This study improves our understanding of the belowground microbial community composition associated with smoke trees in healthy and diseased conditions, offering the potential to both manipulate the plant microbiome to promote plant health and to provide an integrated management strategy of smoke tree. [ABSTRACT FROM AUTHOR]

Highland birds evolve multiple adaptive abilities to cope with the harsh environments; however, how they adapt to the high-altitude habitats via the gut microbiota remains understudied. Here we integrated evidences from comparative analysis of gut microbiota to explore the adaptive mechanism of black-necked crane, a typical highland bird in the Qinghai-Tibet Plateau. Firstly, the gut microbiota diversity and function was compared among seven crane species (one high-altitude species and six low-altitude species), and then among three populations of contrasting altitudes for the black-necked crane. Microbiota community diversity in black-necked crane was significantly lower than its low-altitude relatives, but higher microbiota functional diversity was observed in black-necked crane, suggesting that unique bacteria are developed and acquired due to the selection pressure of high-altitude environments. The functional microbial genes differed significantly between the low- and high-altitude black-necked cranes, indicating that altitude significantly impacted microbial communities' composition and structure. Adaptive changes in microbiota diversity and function are observed in response to high-altitude environments. These findings provide us a new insight into the adaptation mechanism to the high-altitude environment for birds via the gut microbiota. Key points: • The diversity and function of gut microbiota differed significantly between the low- and high-altitude crane species. • Black-necked crane adapts to the high-altitude environment via specific gut microbiota. • Altitude significantly impacted microbial communities' composition and structure. [ABSTRACT FROM AUTHOR]

Aims: Gut microbiota significantly impacts human health and is influenced by dietary changes. We evaluated the effects of diets naturally rich in polyphenols (PP) and/or long-chain n-3 polyunsaturated fatty acids (LCn3) on microbiota composition in an ancillary analysis of a randomized controlled trial in individuals at high cardiometabolic risk. Methods: Seventy-eight individuals with high waist circumference and at least one additional component of the metabolic syndrome were randomized to an isoenergetic 8-week diet: (a) low LCn3 and PP; (b) high LCn3; (c) high PP; or (d) high LCn3 and PP. Microbiota analysis was performed on feces collected before and after the intervention. DGGE analysis of the predominant bacteria, Eubacterium rectale and Blautia coccoides group (Lachnospiraceae, EREC), Clostridium leptum (Ruminococcaceae, CLEPT), Bacteroides spp., Bifidobacteria, and Lactobacillus group was performed. A quantitative real-time PCR was performed for the same group, additionally including Atopobium cluster (Coriobatteriaceae). Before and after the intervention, participants underwent a 75 g OGTT and a high-fat test meal to evaluate glucose and lipid response. Results: Adherence to the four diets was optimal. PP significantly increased microbial diversity (p = 0.006) and CLEPT (p = 0.015), while it reduced EREC (p = 0.044). LCn3 significantly increased the numbers of Bifidobacteria (p = 0.041). Changes in CLEPT numbers correlated with changes in early insulin secretion (r = 0.263, p = 0.030). Changes in Atopobium numbers correlated with postprandial triglycerides in plasma (r = 0.266, p = 0.026) and large VLDL (r = 0.313, p = 0.009), and cholesterol in large VLDL (r = 0.319, p = 0.008). Conclusions: Diets naturally rich in PP or LCn3 influenced gut microbiota composition in individuals at high cardiometabolic risk. These modifications were associated with changes in glucose/lipid metabolism. [ABSTRACT FROM AUTHOR]

The major parcel of the degradation occurring along wastewater biotreatments is performed either by the native microbiota or by added microbial inocula. The main aim of this study was to apply two fingerprinting methods, temperature gradient gel electrophoresis (TGGE) and length heterogeneity-PCR (LH-PCR) analysis of 16S rRNA gene fragments, in order to assess the microbiota structure and dynamics during mixed olive oil and winery wastewaters aerobic biotreatment performed in a jet-loop reactor (JLR). Sequence homology analysis showed the presence of bacterial genera Gluconacetobacter, Klebsiella, Lactobacillus, Novosphingobium, Pseudomonas, Prevotella, Ralstonia, Sphingobium and Sphingomonas affiliated with five main phylogenetic groups: alpha-, beta- and gamma-Proteobacteria, Firmicutes and Bacteroidetes. LH-PCR analysis distinguished eight predominant DNA fragments correlated with the samples showing highest performance (COD removal rates of 67 up to 75%). Cluster analysis of both TGGE and LH-PCR fingerprinting profiles established five main clusters, with similarity coefficients higher than 79% (TGGE) and 62% (LH-PCR), and related with hydraulic retention time, indicating that this was the main factor responsible for the shifts in the microbiota structure. Canonical correspondence analysis revealed that changes observed on temperature and O level were also responsible for shifts in microbiota composition. Community level metabolic profile analysis was used to test metabolic activities in samples. Integrated data revealed that the microbiota structure corresponds to bacterial groups with high degradative potential and good suitability for this type of effluents biotreatments. [ABSTRACT FROM AUTHOR]