Overuse or mistimed application of nitrogen fertilizer can cause nitrate contamination in groundwater and surrounding surface waters. Previous greenhouse studies have explored the use of graphene ...nanomaterials, including graphite nano additive (GNA), to reduce nitrate leaching in an agricultural soil while growing lettuce crops. To investigate the mechanism of GNA addition in suppressing nitrate leaching, we conducted soil column experiments using native agricultural soils under saturated or unsaturated flow conditions to simulate varied irrigation. We investigated the effects of temperature (4 °C compared with 20 °C) on microbial activity and dose effect of GNA was also explored (165 mg/kg soil and 1650 mg/kg soil) for biotic soil column experiments whereas a single temperature condition (20 °C) and GNA dose (165 mg/kg soil) was employed for abiotic (autoclaved) soil column experiments. Results showed GNA addition had minimal effects on nitrate leaching in saturated flow soil columns due to short hydraulic residence times (∼3.5 h). In comparison, longer residence times (∼3 d) in unsaturated soil columns reduced nitrate leaching by 25–31% relative to control soil columns without GNA addition. Furthermore, nitrate retention in the soil column was found to be suppressed at 4 °C compared with 20 °C, suggesting a bio-mediated mechanism for GNA addition to reduce nitrate leaching. In addition, the soil dissolved organic matter was found to be associated with nitrate leaching, where less nitrate leaching occurring when higher dissolved organic carbon (DOC) was measured in leachate water. Following studies of adding soil-derived organic carbon (SOC) resulted in greater nitrogen retention in the unsaturated soil columns only when GNA was present. Overall, the results suggest that GNA-amended soil reduces nitrate loss through increased N immobilization in the microbial biomass or loss of N in gaseous phase through enhanced nitrification and denitrification process.
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•Graphene nanomaterials (GNA) added with fertilizers to soil reduced nitrate leaching by up to 31%.•Higher temperatures and GNA addition reduced nitrate leaching, indicating an important biological mediated mechanism.•Solubilization of soil organic matter plays a crucial role in preventing nitrate leaching.•GNA-amended soil enhance nitrogen retention through microbial processes, reducing nitrate loss significantly.
Abstract
Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. However, its feedbacks to climate warming and underlying ...microbial mechanisms are still poorly understood. Here we show that the temperature sensitivity of soil microbial respiration (
Q
10
) in a temperate grassland ecosystem persistently decreases by 12.0 ± 3.7% across 7 years of warming. Also, the shifts of microbial communities play critical roles in regulating thermal adaptation of soil respiration. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improves the modeling performance of soil microbial respiration by 5–19%, and reduces model parametric uncertainty by 55–71%. In addition, modeling analyses show that the microbial thermal adaptation can lead to considerably less heterotrophic respiration (11.6 ± 7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.
The effect of genetic markers and reference databases on analyses of fungal communities were estimated using fungal large subunit (LSU) and internal transcribed spacer (ITS) amplicon datasets in ...consecutive years of rhizosphere samples from three candidate biofuel crops, corn (
Zea mays
), switchgrass (
Panicum virgatum
), and miscanthus (
Miscanthus
×
giganteus)
. These two marker genes were selected to contrast possible differences in biological conclusions. In addition, two ITS schemes based on two ITS reference databases were used to assess differences due to reference database composition. A taxonomy-supervised method was invoked using the Ribosomal Database Project naïve Bayesian classifier that accesses all three databases. The UNITE classification scheme had the highest number of classified taxa in the raw classification result; however, it also had the highest proportion of unknown taxa (sequences that were classified to “unclassified,” “unidentified,” incertae sedis or, in the case of Warcup, to matches containing two unique names). After removal of these unknown taxa, LSU had the highest classification rate followed by Warcup and UNITE. As expected, the communities resolved using the two ITS databases, based on the same sequences, were relatively more similar than those from the lower-coverage LSU classification scheme. The choice of marker gene or even the same reads with different classification databases revealed different community patterns due to database coverage, e.g., the relative abundance of the most abundant groups changed or were only detected in one or two of the classification schemes, such as for
Mortierella
,
Fusarium
, and
Phoma
. No marked difference in fungal beta-diversity was identified among the three methods. Differentiation between the three biofuel crops and between the drought and normal rainfall years was apparent, regardless of method. Though classification rates, taxonomic conflicts, and coverage differences within the high-abundance fungal groups varied according to classification scheme, there was no overall impact on beta diversity among the three methods.
Process and function that underlie the assembly of a rhizosphere microbial community may be strongly linked to the maintenance of plant health. However, their assembly processes and functional ...changes in the deterioration of soilborne disease remain unclear. Here, we investigated features of rhizosphere microbiomes related to Fusarium wilt disease and assessed their assembly by comparison pair of diseased/healthy sequencing data. The untargeted metabolomics was employed to explore potential community assembly drivers, and shotgun metagenome sequencing was used to reveal the mechanisms of metabolite-mediated process after soil conditioning.
Results showed the deterministic assembly process associated with diseased rhizosphere microbiomes, and this process was significantly correlated to five metabolites (tocopherol acetate, citrulline, galactitol, octadecylglycerol, and behenic acid). Application of the metabolites resulted in a deterministic assembly of microbiome with the high morbidity of watermelon. Furthermore, metabolite conditioning was found to weaken the function of autotoxin degradation undertaken by specific bacterial group (Bradyrhizobium, Streptomyces, Variovorax, Pseudomonas, and Sphingomonas) while promoting the metabolism of small-molecule sugars and acids initiated from another bacterial group (Anaeromyxobacter, Bdellovibrio, Conexibacter, Flavobacterium, and Gemmatimonas). Video Abstract CONCLUSION: These findings strongly suggest that shifts in a metabolite-mediated microbial community assembly process underpin the deterministic establishment of soilborne Fusarium wilt disease and reveal avenues for future research focusing on ameliorating crop loss due to this pathogen.
Agricultural soils with (M+) or without (M−) organic amendment were collected from four long-term field experiments to investigate soil fungal community composition and its relationship to the soil ...ionome by employing both the sequencing of fungal internal transcription spacer (ITS) fragments and inductively coupled plasma mass spectrometry (ICP-MS). Fungal community composition was primarily impacted by physical location while organic amendment triggered community shifts in the same direction in all four sites. Overall, the fungal community was strongly correlated to soil pH that, conversely, impacted soil ion availability. Fungal community dissimilarity was strongly correlated to soil ionome (ionic profile) variability. Network analysis has been conducted to explore the biotic interactions in soil ecosystem, in which species (nodes) are connected by pairwise interactions (links). The results revealed that organic amendment led to a higher number of correlated nodes to soil ions, links, modules (a group of nodes more densely connected to each other than to nodes outside the group), and positive links within and between modules. Moreover, specific fungal modules were independently correlated with soil ions, suggesting that each module represents a functional guild or collection of similar fungal ecotypes. Module size (number of nodes in a module) exhibited no apparent influence on the scale of these correlations. The increase in cooperative/synergistic interactions with organic amendment suggests that application results in a better-organized and more efficient community with enhanced potential soil fungal interactions mediated by alterations in the soil ionome. Overall, this study indicates that these less commonly measured soil ions play an important role and may be used to reveal previously undetermined drivers of the soil microbial community.
Soil-borne diseases, especially those caused by fungal pathogens, lead to profound annual yield losses. One key example for such a disease is Fusarium wilt disease in banana. In some soils, plants do ...not show disease symptoms, even if the disease-causing pathogens are present. However, the underlying agents that make soils suppressive against Fusarium wilt remain elusive. In this study, we aimed to determine the underlying microbial agents governing soil disease-suppressiveness. We traced the shift of microbiomes during the invasion of disease-causing
Fusarium oxysporum
f. sp.
cubense
in disease-suppressive and disease-conducive soils. We found distinct microbiome structures in the suppressive and conducive soils after pathogen invasion. The alpha diversity indices increased (or did not significantly change) and decreased, respectively, in the suppressive and conducive soils, indicating that the shift pattern of the microbiome with pathogen invasion was notably different between the suppressive and conductive soils. Microbiome networks were more complex with higher numbers of links and revealed more negative links, especially between bacterial taxa and the disease-causing
Fusarium
, in suppressive soils than in conducive soils. We identified the bacterial genera
Chryseolinea
,
Terrimonas
, and
Ohtaekwangia
as key groups that likely confer suppressiveness against disease-causing
Fusarium
. Overall, our study provides the first insights into agents potentially underlying the disease suppressiveness of soils against Fusarium wilt pathogen invasion. The results of this study may help to guide efforts for targeted cultivation and application of these potential biocontrol agents, which might lead to the development of effective biocontrol agents against Fusarium wilt disease.
The susceptibility of soil organic carbon (SOC) in tundra to microbial decomposition under warmer climate scenarios potentially threatens a massive positive feedback to climate change, but the ...underlying mechanisms of stable SOC decomposition remain elusive. Herein, Alaskan tundra soils from three depths (a fibric O horizon with litter and course roots, an O horizon with decomposing litter and roots, and a mineral-organic mix, laying just above the permafrost) were incubated. Resulting respiration data were assimilated into a 3-pool model to derive decomposition kinetic parameters for fast, slow, and passive SOC pools. Bacterial, archaeal, and fungal taxa and microbial functional genes were profiled throughout the 3-year incubation. Correlation analyses and a Random Forest approach revealed associations between model parameters and microbial community profiles, taxa, and traits. There were more associations between the microbial community data and the SOC decomposition parameters of slow and passive SOC pools than those of the fast SOC pool. Also, microbial community profiles were better predictors of model parameters in deeper soils, which had higher mineral contents and relatively greater quantities of old SOC than in surface soils. Overall, our analyses revealed the functional potential of microbial communities to decompose tundra SOC through a suite of specialized genes and taxa. These results portray divergent strategies by which microbial communities access SOC pools across varying depths, lending mechanistic insights into the vulnerability of what is considered stable SOC in tundra regions.
It is well-known that global warming has effects on high-latitude tundra underlain with permafrost. This leads to a severe concern that decomposition of soil organic carbon (SOC) previously stored in ...this region, which accounts for about 50% of the world's SOC storage, will cause positive feedback that accelerates climate warming. We have previously shown that short-term warming (1.5 years) stimulates rapid, microbe-mediated decomposition of tundra soil carbon without affecting the composition of the soil microbial community (based on the depth of 42684 sequence reads of 16S rRNA gene amplicons per 3 g of soil sample).
We show that longer-term (5 years) experimental winter warming at the same site altered microbial communities (p < 0.040). Thaw depth correlated the strongest with community assembly and interaction networks, implying that warming-accelerated tundra thaw fundamentally restructured the microbial communities. Both carbon decomposition and methanogenesis genes increased in relative abundance under warming, and their functional structures strongly correlated (R
> 0.725, p < 0.001) with ecosystem respiration or CH
flux.
Our results demonstrate that microbial responses associated with carbon cycling could lead to positive feedbacks that accelerate SOC decomposition in tundra regions, which is alarming because SOC loss is unlikely to subside owing to changes in microbial community composition. Video Abstract.
The sequencing chips and kits of the Ion Torrent Personal Genome Machine (PGM), which employs semiconductor technology to measure pH changes in polymerization events, have recently been upgraded. The ...quality of PGM sequences has not been reassessed, and results have not been compared in the context of a gene-targeted microbial ecology study. To address this, we compared sequence profiles across available PGM chips and chemistries and with 454 pyrosequencing data by determining error types and rates and diazotrophic community structures. The PGM was then used to assess differences in nifH-harboring bacterial community structure among four corn-based cropping systems. Using our suggested filters from mock community analyses, the overall error rates were 0.62, 0.36, and 0.39% per base for chips 318 and 314 with the 400-bp kit and chip 318 with the Hi-Q chemistry, respectively. Compared with the 400-bp kit, the Hi-Q kit reduced indel rates by 28 to 59% and produced one to seven times more reads acceptable for downstream analyses. The PGM produced higher frameshift rates than pyrosequencing that were corrected by the RDP FrameBot tool. Significant differences among platforms were identified, although the diversity indices and overall site-based conclusions remained similar. For the cropping system analyses, a total of 6,182 unique NifH operational taxonomic units at 5% amino acid dissimilarity were obtained. The current crop type, as well as the crop rotation history, significantly influenced the composition of the soil diazotrophic community detected.
Targeting sequencing to genes involved in key environmental processes, i.e., ecofunctional genes, provides an opportunity to sample nature's gene guilds to greater depth and help link community ...structure to process-level outcomes. Vastly different approaches have been implemented for sequence processing and, ultimately, for taxonomic placement of these gene reads. The overall quality of next generation sequence analysis of functional genes is dependent on multiple steps and assumptions of unknown diversity. To illustrate current issues surrounding amplicon read processing we provide examples for three ecofunctional gene groups. A combination of in silico, environmental and cultured strain sequences was used to test new primers targeting the dioxin and dibenzofuran degrading genes dxnA1, dbfA1, and carAa. The majority of obtained environmental sequences were classified into novel sequence clusters, illustrating the discovery value of the approach. For the nitrite reductase step in denitrification, the well-known nirK primers exhibited deficiencies in reference database coverage, illustrating the need to refine primer-binding sites and/or to design multiple primers, while nirS primers exhibited bias against five phyla. Amino acid-based OTU clustering of these two N-cycle genes from soil samples yielded only 114 unique nirK and 45 unique nirS genus-level groupings, likely a reflection of constricted primer coverage. Finally, supervised and non-supervised OTU analysis methods were compared using the nifH gene of nitrogen fixation, with generally similar outcomes, but the clustering (non-supervised) method yielded higher diversity estimates and stronger site-based differences. High throughput amplicon sequencing can provide inexpensive and rapid access to nature's related sequences by circumventing the culturing barrier, but each unique gene requires individual considerations in terms of primer design and sequence processing and classification.
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