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.
Abstract Climate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models ( ESM s) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming‐induced biotic changes may influence biologically related parameters and the consequent projections in ESM s. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5 years from a soil warming experiment at the Eight Mile Lake, Alaska, into the Terrestrial ECO system ( TECO ) model with a probabilistic inversion approach. The TECO model used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment‐corrected) turnover rates of SOC in both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. The TECO model predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87 g/m 2 , respectively, without or with changes in those parameters. Thus, warming‐induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes in ESM s to improve the model performance in predicting C dynamics in permafrost regions.
In a warmer world, microbial decomposition of previously frozen organic carbon (C) is one of the most likely positive climate feedbacks of permafrost regions to the atmosphere. However, mechanistic understanding of microbial mediation on chemically recalcitrant C instability is limited; thus, it is crucial to identify and evaluate active decomposers of chemically recalcitrant C, which is essential for predicting C-cycle feedbacks and their relative strength of influence on climate change. Using stable isotope probing of the active layer of Arctic tundra soils after depleting soil labile C through a 975-day laboratory incubation, the identity of microbial decomposers of lignin and, their responses to warming were revealed.The β-Proteobacteria genus Burkholderia accounted for 95.1% of total abundance of potential lignin decomposers. Consistently, Burkholderia isolated from our tundra soils could grow with lignin as the sole C source. A 2.2 °C increase of warming considerably increased total abundance and functional capacities of all potential lignin decomposers. In addition to Burkholderia, α-Proteobacteria capable of lignin decomposition (e.g. Bradyrhizobium and Methylobacterium genera) were stimulated by warming by 82-fold. Those community changes collectively doubled the priming effect, i.e., decomposition of existing C after fresh C input to soil. Consequently, warming aggravates soil C instability, as verified by microbially enabled climate-C modeling.Our findings are alarming, which demonstrate that accelerated C decomposition under warming conditions will make tundra soils a larger biospheric C source than anticipated. Video Abstract.
Increases in carbon (C) inputs to soil can replenish soil organic C (SOC) through various mechanisms. However, recent studies have suggested that the increased C input can also stimulate the decomposition of old SOC via priming. Whether the loss of old SOC by priming can override C replenishment has not been rigorously examined. Here we show, through data-model synthesis, that the magnitude of replenishment is greater than that of priming, resulting in a net increase in SOC by a mean of 32% of the added new C. The magnitude of the net increase in SOC is positively correlated with the nitrogen-to-C ratio of the added substrates. Additionally, model evaluation indicates that a two-pool interactive model is a parsimonious model to represent the SOC decomposition with priming and replenishment. Our findings suggest that increasing C input to soils likely promote SOC accumulation despite the enhanced decomposition of old C via priming.
Panama disease caused by Fusarium oxysporum f. sp. cubense infection on banana is devastating banana plantations worldwide. Biological control has been proposed to suppress Panama disease, though the stability and survival of bio-control microorganisms in field setting is largely unknown. In order to develop a bio-control strategy for this disease, 16S rRNA gene sequencing was used to assess the microbial community of a disease-suppressive soil. Bacillus was identified as the dominant bacterial group in the suppressive soil. For this reason, B. amyloliquefaciens NJN-6 isolated from the suppressive soil was selected as a potential bio-control agent. A bioorganic fertilizer (BIO), formulated by combining this isolate with compost, was applied in nursery pots to assess the bio-control of Panama disease. Results showed that BIO significantly decreased disease incidence by 68.5%, resulting in a doubled yield. Moreover, bacterial community structure was significantly correlated to disease incidence and yield and Bacillus colonization was negatively correlated with pathogen abundance and disease incidence, but positively correlated to yield. In total, the application of BIO altered the rhizo-bacterial community by establishing beneficial strains that dominated the microbial community and decreased pathogen colonization in the banana rhizosphere, which plays an important role in the management of Panama disease.
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.
ABSTRACT Previously available primer sets for detecting anaerobic ammonium-oxidizing (anammox) bacteria are inefficient, resulting in a very limited database of such sequences, which limits knowledge of their ecology. To overcome this limitation, we designed a new primer set that was 100% specific in the recovery of ∼700-bp 16S rRNA gene sequences with >96% homology to the “ Candidatus Scalindua” group of anammox bacteria, and we detected this group at all sites studied, including a variety of freshwater and marine sediments and permafrost soil. A second primer set was designed that exhibited greater efficiency than previous primers in recovering full-length (1,380-bp) sequences related to “ Ca . Scalindua,” “ Candidatus Brocadia,” and “ Candidatus Kuenenia.” This study provides evidence for the widespread distribution of anammox bacteria in that it detected closely related anammox 16S rRNA gene sequences in 11 geographically and biogeochemically diverse freshwater and marine sediments.
ABSTRACT Soil fungi play a major role in terrestrial ecosystem functioning through interactions with soil structure, plants, micro- and mesofauna, and nutrient cycling through predation, pathogenesis, mutualistic, and saprotrophic roles. The diversity of soil fungi was assessed by sequencing their 28S rRNA gene in Alaskan permafrost and Oklahoma tallgrass prairie soils at experimental sites where the effect of climate warming is under investigation. A total of 226,695 reads were classified into 1,063 genera, covering 62% of the reference data set. Using the Bayesian Classifier offered by the Ribosomal Database Project (RDP) with 50% bootstrapping classification confidence, approximately 70% of sequences were returned as “unclassified” at the genus level, although the majority (∼65%) were classified at the class level, which provided insight into these lesser-known fungal lineages. Those unclassified at the genus level were subjected to BLAST analysis against the ARB-SILVA database, where ∼50% most closely matched nonfungal taxa. Compared to the more abundant sequences, a higher proportion of rare operational taxonomic units (OTU) were successfully classified to genera at 50% bootstrap confidence, indicating that the fungal rare biosphere in these sites is not composed of sequencing artifacts. There was no significant effect after 1 year of warming on the fungal community structure at both sites, except perhaps for a few minor members, but there was a significant effect of sample depth in the permafrost soils. Despite overall significant community structure differences driven by variations in OTU dominance, the prairie and permafrost soils shared 90% and 63% of all fungal sequences, respectively, indicating a fungal “seed bank” common between both sites.
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