Soil warming duration and magnitude affect the dynamics of fine roots and rhizomes and associated C and N pools in subarctic grasslands.

BACKGROUND AND AIMS: The response of subarctic grassland's below-ground to soil warming is key to understanding this ecosystem's adaptation to future climate. Functionally different below-ground plant organs can respond differently to changes in soil temperature (Ts). We aimed to understand the below-ground adaptation mechanisms by analysing the dynamics and chemistry of fine roots and rhizomes in relation to plant community composition and soil chemistry, along with the duration and magnitude of soil warming. METHODS: We investigated the effects of the duration [medium-term warming (MTW; 11 years) and long-term warming (LTW; > 60 years)] and magnitude (0-8.4 °C) of soil warming on below-ground plant biomass (BPB), fine root biomass (FRB) and rhizome biomass (RHB) in geothermally warmed subarctic grasslands. We evaluated the changes in BPB, FRB and RHB and the corresponding carbon (C) and nitrogen (N) pools in the context of ambient, Ts < +2 °C and Ts > +2 °C scenarios. KEY RESULTS: BPB decreased exponentially in response to an increase in Ts under MTW, whereas FRB declined under both MTW and LTW. The proportion of rhizomes increased and the C-N ratio in rhizomes decreased under LTW. The C and N pools in BPB in highly warmed plots under MTW were 50 % less than in the ambient plots, whereas under LTW, C and N pools in warmed plots were similar to those in non-warmed plots. Approximately 78 % of the variation in FRB, RHB, and C and N concentration and pools in fine roots and rhizomes was explained by the duration and magnitude of soil warming, soil chemistry, plant community functional composition, and above-ground biomass. Plant's below-ground biomass, chemistry and pools were related to a shift in the grassland's plant community composition - the abundance of ferns increased and BPB decreased towards higher Ts under MTW, while the recovery of below-ground C and N pools under LTW was related to a higher plant diversity. CONCLUSION: Our results indicate that plant community-level adaptation of below ground to soil warming occurs over long periods. We provide insight into the potential adaptation phases of subarctic grasslands.

The effect of synthetic silver nanoparticles on the antibiotic resistome and the removal efficiency of antibiotic resistance genes in a hybrid filter system treating municipal wastewater.

Engineered nanoparticles, including silver nanoparticles (AgNPs), are released into the environment mainly through wastewater treatment systems. Knowledge of the impact of AgNPs on the abundance and removal efficiency of antibiotic resistance genes (ARGs) in wastewater treatment facilities, including constructed wetlands (CWs), is essential in the context of public health. This study evaluated the effect of increased (100-fold) collargol (protein-coated AgNPs) and ionic Ag+ in municipal wastewater on the structure, abundance, and removal efficiency of the antibiotic resistome, integron-integrase genes, and pathogens in a hybrid CW using quantitative PCR and metagenomic approaches. The abundance of ARGs in wastewater and the removal efficiency of ARGs in the hybrid system were significantly affected by higher Ag concentrations, especially with collargol treatment, resulting in an elevated ARG discharge of system effluent into the environment. The accumulated Ag in the filters had a more profound effect on the absolute and relative abundance of ARGs in the treated water than the Ag content in the water. This study recorded significantly enhanced relative abundance values for tetracycline (tetA, tetC, tetQ), sulfonamide (sul1, sul2), and aminoglycoside (aadA) resistance genes, which are frequently found on mobile genetic elements in collargol- and, to a lesser extent, AgNO3-treated subsystems. Elevated plasmid and integron-integrase gene levels, especially intI1, in response to collargol presence indicated the substantial role of AgNPs in promoting horizontal gene transfer in the treatment system. The pathogenic segment of the prokaryotic community was similar to a typical sewage community, and strong correlations between pathogen and ARG proportions were recorded in vertical subsurface flow filters. Furthermore, the proportion of Salmonella enterica was positively related to the Ag content in these filter effluents. The effect of AgNPs on the nature and characteristics of prominent resistance genes carried by mobile genetic elements in CWs requires further investigation.

Impact of synthetic silver nanoparticles on the biofilm microbial communities and wastewater treatment efficiency in experimental hybrid filter system treating municipal wastewater.

Silver nanoparticles (AgNPs) threaten human and ecosystem health, and are among the most widely used engineered nanomaterials that reach wastewater during production, usage, and disposal phases. This study evaluated the effect of a 100-fold increase in collargol (protein-coated AgNP) and Ag+ ions concentrations in municipal wastewater on the microbial community composition of the filter material biofilms (FMB) and the purification efficiency of the hybrid treatment system consisting of vertical (VF) and horizontal (HF) subsurface flow filters. We found that increased amounts of collargol and AgNO3 in wastewater had a modest effect on the prokaryotic community composition in FMB and did not significantly affect the performance of the studied system. Regardless of how Ag was introduced, 99.9% of it was removed by the system. AgNPs and AgNO3 concentrations did not significantly affect the purification efficiency of the system. AgNO3 induced a higher increase in the genetic potential of certain Ag resistance mechanisms in VFs than collargol; however, the increase in Ag resistance potential was similar for both substances in HF. Hence, the microbial community composition in biofilms of vertical and horizontal flow filters is largely resistant, resilient, or functionally redundant in response to AgNPs addition in the form of collargol.

Application of data integration for rice bacterial strain selection by combining their osmotic stress response and plant growth-promoting traits.

Agricultural application of plant-beneficial bacteria to improve crop yield and alleviate the stress caused by environmental conditions, pests, and pathogens is gaining popularity. However, before using these bacterial strains in plant experiments, their environmental stress responses and plant health improvement potential should be examined. In this study, we explored the applicability of three unsupervised machine learning-based data integration methods, including principal component analysis (PCA) of concatenated data, multiple co-inertia analysis (MCIA), and multiple kernel learning (MKL), to select osmotic stress-tolerant plant growth-promoting (PGP) bacterial strains isolated from the rice phyllosphere. The studied datasets consisted of direct and indirect PGP activity measurements and osmotic stress responses of eight bacterial strains previously isolated from the phyllosphere of drought-tolerant rice cultivar. The production of phytohormones, such as indole-acetic acid (IAA), gibberellic acid (GA), abscisic acid (ABA), and cytokinin, were used as direct PGP traits, whereas the production of hydrogen cyanide and siderophore and antagonistic activity against the foliar pathogens Pyricularia oryzae and Helminthosporium oryzae were evaluated as measures of indirect PGP activity. The strains were subjected to a range of osmotic stress levels by adding PEG 6000 (0, 11, 21, and 32.6%) to their growth medium. The results of the osmotic stress response experiments showed that all bacterial strains accumulated endogenous proline and glycine betaine (GB) and exhibited an increase in growth, when osmotic stress levels were increased to a specific degree, while the production of IAA and GA considerably decreased. The three applied data integration methods did not provide a similar grouping of the strains. Especially deviant was the ordination of microbial strains based on the PCA of concatenated data. However, all three data integration methods indicated that the strains Bacillus altitudinis PB46 and B. megaterium PB50 shared high similarity in PGP traits and osmotic stress response. Overall, our results indicate that data integration methods complement the single-table data analysis approach and improve the selection process for PGP microbial strains.

The Foliar Application of Rice Phyllosphere Bacteria induces Drought-Stress Tolerance in Oryza sativa (L.).

This study assessed the potential of Bacillus endophyticus PB3, Bacillus altitudinis PB46, and Bacillus megaterium PB50 to induce drought tolerance in a susceptible rice cultivar. The leaves of the potted rice plants subjected to physical drought stress for 10 days during the flowering stage were inoculated with single-strain suspensions. Control pots of irrigated and drought-stressed plants were included in the experiment for comparison. In all treatments, the plant stress-related physiochemical and biochemical changes were examined and the expression of six stress-responsive genes in rice leaves was evaluated. The colonization potential on the surface of the rice leaves and stomata of the most successful strain in terms of induced tolerance was confirmed in the gnotobiotic experiment. The plants sprayed with B. megaterium PB50 showed an elevated stress tolerance based on their higher relative water content and increased contents of total sugars, proteins, proline, phenolics, potassium, calcium, abscisic acid, and indole acetic acid, as well as a high expression of stress-related genes (LEA, RAB16B, HSP70, SNAC1, and bZIP23). Moreover, this strain improved yield parameters compared to other treatments and also confirmed its leaf surface colonization. Overall, this study indicates that the foliar application of B. megaterium PB50 can induce tolerance to drought stress in rice.