Assembly of root-associated bacteria communities: interactions between abiotic and biotic factors

Recruitment of copiotrophic and autotrophic bacteria by hyperaccumulators enhances nutrient cycling to reclaim degraded soils at abandoned rare earth elements mining sites

Hyperaccumulators harbor potentials for remediating rare earth elements (REEs)-contaminated soils. However, how they thrive in low-nutrient abandoned REEs mining sites is poorly understood. Three ferns (REEs-hyperaccumulators Dicranopteris pedata and Blechnum orientale, and non-hyperaccumulator Pteris vittata) along with their rhizosphere soils were collected to answer this question by comparing differences in soil nutrient levels, soil and plant REEs concentrations, and bacterial diversity, composition, and functions. Results observed lower soil pH (4.67-4.95 vs. 7.96), total carbon (TC) (0.35-0.62 vs. 2.84 g kg-1), total nitrogen (TN) (20-23 vs. 133 mg kg-1), and total phosphorus (TP) (81-91 vs. 133 mg kg-1) at sites Dp and Bo than site Pv. Hyperaccumulators efficiently extracted soil REEs and translocated them to fronds (up to 6897-7759 mg kg-1). Bacterial α diversity in three soils did not significantly vary. In contrast, bacterial composition at sites Dp and Bo was dominant by higher abundances of copiotrophic bacteria (18 % vs. 12 %, p_Actinomycetota; 3.3-8.3 % vs. 1.9 %, p_Bacteroidota; 8.3-14 % vs. 6.9 %, c_Gammaproteobacteria) and autotrophic bacteria (18 % vs. 13 %, p_Chloroflexota; 13 % vs. 8.6 %, p_Cyanobacteriota) when compared to site Pv. These bacteria likely acted as nutrient cyclers that promoted the growth of hyperaccumulators, based on functional predictions from DiTing analyses. This study provides new insights into nutrient recovery in abandoned REEs mining sites, offering strategies to reclaim degraded soils using phyto-microbial technology.

Correlating Microbial Community Characteristics with Environmental Factors along a Two-Stage Biological Aerated Filter

The purification effect of a biological aerated filter (BAF) mainly comes from the microorganisms in the reactor. Understanding the correlation between microbial community characteristics and environmental factors along the filter has great significance for maintaining good operation and improving the removal efficiency of the filter. A two-stage BAF was employed to treat domestic sewage under organic loads of 1.02 and 1.55 kg/m3·d for 15 days each. 16S rDNA high-throughput sequencing technology and redundancy analysis were applied to explore the correlation between microbial community characteristics and environmental variables. The results showed that: (1) the crucial organic-degrading bacteria in the A-stage filter were of the genus Novosphingobium, which had a significant increase in terms of relative abundance at sampling outlet A3 (135 cm of the filling height) after the increase of organic load; (2) the microbial communities at different positions in the B-stage filter were similarly affected by environmental factors, and the main bacteria associated with nitrogen removal in the B-stage filter were Zoogloea and Rhodocyclus; and (3) to improve the pollutant removal performance of this two-stage biological aerated filter, a strategy of adding an internal circulation in the B-stage filter can be adopted.

Bacterial communities of the Salvia lyrata rhizosphere explained by spatial structure and sampling grain

Advancements in molecular technology have reduced the constraints that the grain of observation, or the spatial resolution and volume of the sampling unit, has on the characterization of plant-associated microbiomes. With discrete ecological sampling and massive parallel sequencing, we can more precisely portray microbiome community assembly and microbial recruitment to host tissue over space and time. Here, we differentiate rarefied community richness and relative abundance in bacterial microbiomes of Salvia lyrata dependent on three spatial depths, which are discrete physical distances from the soil surface within the rhizosphere microhabitat as a proxy for the root system zones. To assess the impact of sampling grain on rarefied community richness and relative abundance, we evaluated the variation of these metrics between samples pooled prior to DNA extraction and samples pooled after sequencing. A distance-based redundancy analysis with the quantitative Jaccard distance revealed that rhizosphere microbiomes vary in richness between rhizosphere soil depths. At all orders of diversity, rarefied microbial richness was consistently lowest at the deepest samples taken (approximately 4 cm from soil surface) in comparison with other rhizosphere soil depths. We additionally show that finer grain sampling (i.e., three samples of equal volume pooled after sequencing) recovers greater microbial richness when using 16S rRNA gene sequencing to describe microbial communities found within the rhizosphere system. In summary, to further elucidate the extent host-specific microbiomes assemble within the rhizosphere, the grain at which bacterial communities are sampled should reflect and encompass fine-scale heterogeneity of the system.

Advantages of phylogenetic distance based constrained ordination analyses for the examination of microbial communities

Recently developed high throughput molecular techniques such as massively parallel sequencing and phylogenetic microarrays generate vast datasets providing insights into microbial community structure and function. Because of the high dimensionality of these datasets, multivariate ordination analyses are often employed to examine such data. Here, we show how the use of phylogenetic distance based redundancy analysis provides ecological interpretation of microbial community differences. We also extend the previously developed method of principal response curves to incorporate phylogenetic distance measure, and we demonstrate the improved ability of this approach to provide ecologically relevant insights into temporal alterations of microbial communities.

Leaf endophytic fungus interacts with precipitation to alter belowground microbial communities in primary successional dunes

Understanding interactions between above- and belowground components of ecosystems is an important next step in community ecology. These interactions may be fundamental to predicting ecological responses to global change because indirect effects occurring through altered species interactions can outweigh or interact with the direct effects of environmental drivers. In a multiyear field experiment (2010-2015), we tested how experimental addition of a mutualistic leaf endophyte (Epichloë amarillans) associated with American beachgrass (Ammophila breviligulata) interacted with an altered precipitation regime (±30%) to affect the belowground microbial community. Epichloë addition increased host root biomass at the plot scale, but reduced the length of extraradical arbuscular mycorrhizal (AM) fungal hyphae in the soil. Under ambient precipitation alone, the addition of Epichloë increased root biomass per aboveground tiller and reduced the diversity of AM fungi in A. breviligulata roots. Furthermore, with Epichloë added, the diversity of root-associated bacteria declined with higher soil moisture, whereas in its absence, bacterial diversity increased with higher soil moisture. Thus, the aboveground fungal mutualist not only altered the abundance and composition of belowground microbial communities but also affected how belowground communities responded to climate, suggesting that aboveground microbes have potential for cascading influences on community dynamics and ecosystem processes that occur belowground.

Plant community and soil chemistry responses to long-term nitrogen inputs drive changes in alpine bacterial communities

Bacterial community composition and diversity was studied in alpine tundra soils across a plant species and moisture gradient in 20 y-old experimental plots with four nutrient addition regimes (control, nitrogen (N), phosphorus (P) or both nutrients). Different bacterial communities inhabited different alpine meadows, reflecting differences in moisture, nutrients and plant species. Bacterial community alpha-diversity metrics were strongly correlated with plant richness and the production of forbs. After meadow type, N addition proved the strongest determinant of bacterial community structure. Structural Equation Modeling demonstrated that tundra bacterial community responses to N addition occur via changes in plant community composition and soil pH resulting from N inputs, thus disentangling the influence of direct (resource availability) vs. indirect (changes in plant community structure and soil pH) N effects that have remained unexplored in past work examining bacterial responses to long-term N inputs in these vulnerable environments. Across meadow types, the relative influence of these indirect N effects on bacterial community structure varied. In explicitly evaluating the relative importance of direct and indirect effects of long-term N addition on bacterial communities, this study provides new mechanistic understandings of the interaction between plant and microbial community responses to N inputs amidst environmental change.