Alternate succession of aggregate-forming cyanobacterial genera correlated with their attached bacteria by co-pathways.

Freshwater lakes are threatened by harmful blooms characterized by Cyanobacterial Aggregates (CAs) that are normally aggregated with extracellular polysaccharides released by cyanobacteria to form a phycosphere. It is possible that mutualistic relationships exist between bacteria and cyanobacteria in these CAs wherein bacterial products supplement cyanobacterial growth, and cyanobacterial exudates, in turn, serve as substrates for bacteria, thus augmenting the stability of each constituent. However, little is known about the exact interaction between cyanobacteria and their attached bacteria in CAs. Therefore, in this study, we collected 26 CA samples from Lake Taihu, a large freshwater lake in China from March of 2015 to February of 2016. We then sequenced both the V4 regions of 16S rRNA genes and full metagenomes, resulting in 610 Mb of 16S rRNA gene data and 198.98 Gb of high-quality metagenomic data. We observed that two cyanobacteria genera (Microcystis and Dolichospermum) alternately dominated CAs along the sampling time and specific bacterial genera attached to different cyanobacteria genera dominated CAs. More specifically, Dolichospermum dominates CAs when water temperature is low and total nitrogen is high, while Microcystis dominates CAs when water temperature is high and total nitrogen is low. Moreover, we found specific bacterial genera attached to different cyanobacteria genera dominated CAs. The cyanobacteria-bacteria related pairs Dolichospermum-Burkholderia and Microcystis-Hyphomonas were detected by ecological networks construction. Bacterial communities in CAs were found to be more correlated with the cyanobacterial community (Mantel's r = 0.76, P = 0.001) than with environmental factors (Mantel's r = 0.27, P = 0.017). A potential codependent nitrogen-cycling pathway between cyanobacteria and their attached bacteria was constructed, indicating their functional link. Overall, these results demonstrated that mutualistic relationships do, indeed, exist between cyanobacteria and bacteria in CAs at both taxonomic and gene levels, providing biological clues potentially leading to the control of blooms by interventional strategies to disrupt bacteria-cyanobacteria relationships and co-pathways.

Environmental and spatial variables determine the taxonomic but not functional structure patterns of microbial communities in alpine grasslands.

There is considerable debate regarding how the taxonomic diversity of microbial communities relates to the functional diversity across space while similar questions have been explored in macro-organism communities. Here, we investigated the taxonomic and functional diversity patterns of soil microbial communities by coupling the data obtained from marker genes sequencing and functional gene surveys. Meanwhile, we evaluated the relative effects of environment and geographic distance on shaping these patterns in alpine grasslands of northern China. Although the taxonomic diversity and composition of microbial communities varied across sites, we found no consistent changes in the functional structure. Both the environmental factors and geographic distance concurrently affected the taxonomic diversity patterns but they had no effects on the spatial variations in functional genes. The functional alpha diversity was weakly correlated to the taxonomic alpha diversity across sites. Moreover, we found no significant relationship between the taxonomic and functional composition similarity among microbial communities. Together, our results provide evidence that spatial variation in microbial functions could be independent of their variations in taxonomic diversity. Even the drivers of spatial variations in the functional structure could be totally different from those of taxonomic variations such as environmental differences and dispersal limitation. Our findings suggest that spatial variations of microbial function structure within a community would not follow the variations of taxonomic structures due to different drivers between both of them over space.

Habitat-specific patterns and drivers of bacterial ß-diversity in China's drylands.

The existence of biogeographic patterns among most free-living microbial taxa has been well established, yet little is known about the underlying mechanisms that shape these patterns. Here, we examined soil bacterial ß-diversity across different habitats in the drylands of northern China. We evaluated the relative importance of environmental factors versus geographic distance to a distance-decay relationship, which would be explained by the relative effect of basic ecological processes recognized as drivers of diversity patterns in macrobial theoretical models such as selection and dispersal. Although the similarity of bacterial communities significantly declined with increasing geographic distance, the distance-decay slope and the relative importance of factors driving distance-decay patterns varied across different habitats. A strong distance-decay relationship was observed in the alpine grassland, where the community similarity was influenced only by the environmental factors. In contrast, geographic distance was solely responsible for community similarity in the desert. Even the average compositional similarity among locations in the desert was distinctly lower compared with those in other habitats. We found no evidence that dispersal limitation strongly influenced the ß-diversity of bacterial communities in the desert grassland and typical grassland. Together, our results provide robust evidence of habitat specificity for microbial diversity patterns and their underlying drivers. Our findings suggest that microorganisms also have multiple drivers of diversity patterns and some of which may be parallel to some fundamental processes for explaining biodiversity patterns in macroorganisms.

Elemental sulfur recovery and spatial distribution of functional bacteria and expressed genes under different carbon/nitrate/sulfide loadings in up-flow anaerobic sludge blanket reactors.

To characterize the impact of influent loading on elemental sulfur (S0) recovery during the denitrifying and sulfide oxidation process, three identical, lab-scale UASB reactors (30cm in length) were established in parallel under different influent acetate/nitrate/sulfide loadings, and the reactor performance and functional community structure were investigated. The highest S0 recovery was achieved at 77.9% when the acetate/nitrate/sulfide loading was set to 1.9/1.6/0.7kgd-1m-3. Under this condition, the genera Thauera, Sulfurimonas, and Azoarcus were predominant at 0-30, 0-10 and 20-30cm, respectively; meanwhile, the sqr gene was highly expressed at 0-30cm. However, as the influent loading was halved and doubled, S0 recovery was decreased to 27.9% and 45.1%, respectively. As the loading was halved, the bacterial distribution became heterogeneous, and certain autotrophic sulfide oxidation genera, such as Thiobacillus, dominated, especially at 20-30cm. As the loading doubled, the bacterial distribution was relatively homogeneous with Thauera and Azoarcus being predominant, and the nirK and sox genes were highly expressed. The study verified the importance of influent loading to regulate S0 recovery, which could be achieved as Thauera and Sulfurimonas dominated. An influent loading that was too low or too high gave rise to insufficient oxidation or over-oxidation of the sulfide and low S0 recovery performance.

Efficient regulation of elemental sulfur recovery through optimizing working height of upflow anaerobic sludge blanket reactor during denitrifying sulfide removal process.

In this study, two lab-scale UASB reactors were established to testify S(0) recovery efficiency, and one of which (M-UASB) was improved from the previous T-UASB by shortening reactor height once S(2-) over oxidation was observed. After the height was shortened from 60 to 30cm, S(0) recovery rate was improved from 7.4% to 78.8%, and while, complete removal of acetate, nitrate and S(2-) was simultaneously maintained. Meanwhile, bacterial community distribution was homogenous throughout the reactor, with denitrifying sulfide oxidization bacteria predominant, such as Thauera and Azoarcus spp., indicating the optimized condition for S(0) recovery. The effective control of working height/volume in reactors plays important roles for the efficient regulation of S(0) recovery during DSR process.

Microbial community structure and function in response to the shift of sulfide/nitrate loading ratio during the denitrifying sulfide removal process.

Influence of acetate-C/NO3(-)-N/S(2-) ratio to the functional microbial community during the denitrifying sulfide removal process is poorly understood. Here, phylogenetic and functional bacterial community for elemental sulfur (S(0)) recovery and nitrate (NO3(-)) removal were investigated with the switched S(2-)/NO3(-) molar ratio ranged from 5/2 to 5/9. Optimized S(2-)/NO3(-) ratio was evaluated as 5/6, with the bacterial genera predominated with Thauera, Enterobacter, Thiobacillus and Stappia, and the sqr gene highly expressed. However, insufficient or high loading of acetate and NO3(-) resulted in the low S(0) recovery, and also significantly modified the bacterial community and genetic activity. With S(2-)/NO3(-) ratio of 5/2, autotrophic S(2-) oxidization genera were dominated and NO3(-) reduction activity was low, confirmed by the low expressed nirK gene. In contrast, S(2-)/NO3(-) ratio switched to 5/8 and 5/9 introduced diverse heterotrophic nitrate reduction and S(0) over oxidization genera in accompanied with the highly expressed nirK and sox genes.

Israeli acute paralysis virus: epidemiology, pathogenesis and implications for honey bee health.

Israeli acute paralysis virus (IAPV) is a widespread RNA virus of honey bees that has been linked with colony losses. Here we describe the transmission, prevalence, and genetic traits of this virus, along with host transcriptional responses to infections. Further, we present RNAi-based strategies for limiting an important mechanism used by IAPV to subvert host defenses. Our study shows that IAPV is established as a persistent infection in honey bee populations, likely enabled by both horizontal and vertical transmission pathways. The phenotypic differences in pathology among different strains of IAPV found globally may be due to high levels of standing genetic variation. Microarray profiles of host responses to IAPV infection revealed that mitochondrial function is the most significantly affected biological process, suggesting that viral infection causes significant disturbance in energy-related host processes. The expression of genes involved in immune pathways in adult bees indicates that IAPV infection triggers active immune responses. The evidence that silencing an IAPV-encoded putative suppressor of RNAi reduces IAPV replication suggests a functional assignment for a particular genomic region of IAPV and closely related viruses from the Family Dicistroviridae, and indicates a novel therapeutic strategy for limiting multiple honey bee viruses simultaneously and reducing colony losses due to viral diseases. We believe that the knowledge and insights gained from this study will provide a new platform for continuing studies of the IAPV-host interactions and have positive implications for disease management that will lead to mitigation of escalating honey bee colony losses worldwide.

[SVM-based spectral recognition of corn and weeds at seedling stage in fields].

A handheld FieldSpec 3 Spectroradiometer manufactured by ASD Incorporated Company in USA was used to measure the spectroscopic data of canopies of seedling corns, Dchinochloa crasgalli, and Echinochloa crusgalli weeds within the 350-2 500 nm wavelength range in the field. Each canopy was measured five times continuously. The five original spectroscopic data were averaged over the whole wavelength range in order to eliminate random noise. Then the averaged original data were converted into reflectance data, and the unsmooth parts of reflectance spectral curves with large noise were removed. The effective wavelength range for spectral data process was selected as 350-1 300 and 1 400-1 800 nm. Support vector machine (SVM) was chosen as a method of pattern recognition in this paper. SVM has the advantages of solving the problem of small sample size, being able to reach a global optimization, minimization of structure risk, and having higher generalization capability. Two classes of classifier SVM models were built up respectively using "linear", "polynomial", "RBF"(radial basis function), and "mlp (multilayer perception)" kernels. Comparison of different kernel functions for SVM shows that higher precision can be obtained by using "polynomial" kernel function with 3 orders. The accuracy can be above 80%, but the SV ratio is relatively low. On the basis of two-class classification model, taking use of voting procedure, a model based on one-against-one-algorithm multi-class classification SVM was set up. The accuracy reaches 80%. Although the recognition accuracy of the model based on SVM algorithm is not above 90%, the authors still think that the research on weeds recognition using spectrum technology combining SVM method discussed in this paper is tremendously significant. Because the data used in this study were measured over plant canopies outdoor in the field, the measurement is affected by illumination intensity, soil background, atmosphere temperature and instrument accuracy. This method proposes a kind of research ideology and application foundation for weeds recognition in the field.