Arbuscular mycorrhizal fungi reduce soil N2O emissions by altering root traits and soil denitrifier community composition.

Arbuscular mycorrhizal fungi (AMF) increase the ability of plants to obtain nitrogen (N) from the soil, and thus can affect emissions of nitrous oxide (N2O), a long-lived potent greenhouse gas. However, the mechanisms underlying the effects of AMF on N2O emissions are still poorly understood, particularly in agroecosystems with different forms of N fertilizer inputs. Utilizing a mesocosm experiment in field, we examined the effects of AMF on N2O emissions via their influence on maize root traits and denitrifying microorganisms under ammonia and nitrate fertilizer input using 15N isotope tracer. Here we show that the presence of AMF alone or both maize roots and AMF increased maize biomass and their 15N uptake, root length, root surface area, and root volume, but led to a reduction in N2O emissions under both N input forms. Random forest model showed that root length and surface area were the most important predictors of N2O emissions. Additionally, the presence of AMF reduced the (nirK + nirS)/nosZ ratio by increasing the relative abundance of nirS-Bradyrhizobium and Rubrivivax with ammonia input, but reducing nosZ-Azospirillum, Cupriavidus and Rhodopseudomonas under both fertilizer input. Further, N2O emissions were significantly and positively correlated with the nosZ-type Azospirillum, Cupriavidus and Rhodopseudomonas, but negatively correlated with the nirS-type Bradyrhizobium and Rubrivivax. These results indicate that AMF reduce N2O emissions by increasing root length to explore N nutrients and altering the community composition of denitrifiers, suggesting that effective management of N fertilizer forms interacting with the rhizosphere microbiome may help mitigate N2O emissions under future N input scenarios.

Intermediate soil acidification induces highest nitrous oxide emissions.

Global potent greenhouse gas nitrous oxide (N2O) emissions from soil are accelerating, with increases in the proportion of reactive nitrogen emitted as N2O, i.e., N2O emission factor (EF). Yet, the primary controls and underlying mechanisms of EFs remain unresolved. Based on two independent but complementary global syntheses, and three field studies determining effects of acidity on N2O EFs and soil denitrifying microorganisms, we show that soil pH predominantly controls N2O EFs and emissions by affecting the denitrifier community composition. Analysis of 5438 paired data points of N2O emission fluxes revealed a hump-shaped relationship between soil pH and EFs, with the highest EFs occurring in moderately acidic soils that favored N2O-producing over N2O-consuming microorganisms, and induced high N2O emissions. Our results illustrate that soil pH has a unimodal relationship with soil denitrifiers and EFs, and the net N2O emission depends on both the N2O/(N2O + N2) ratio and overall denitrification rate. These findings can inform strategies to predict and mitigate soil N2O emissions under future nitrogen input scenarios.

Moderate precipitation reduction enhances nitrogen cycling and soil nitrous oxide emissions in a semi-arid grassland.

The ongoing climate change is predicted to induce more weather extremes such as frequent drought and high-intensity precipitation events, causing more severe drying-rewetting cycles in soil. However, it remains largely unknown how these changes will affect soil nitrogen (N)-cycling microbes and the emissions of potent greenhouse gas nitrous oxide (N2 O). Utilizing a field precipitation manipulation in a semi-arid grassland on the Loess Plateau, we examined how precipitation reduction (ca. -30%) influenced soil N2 O and carbon dioxide (CO2 ) emissions in field, and in a complementary lab-incubation with simulated drying-rewetting cycles. Results obtained showed that precipitation reduction stimulated plant root turnover and N-cycling processes, enhancing soil N2 O and CO2 emissions in field, particularly after each rainfall event. Also, high-resolution isotopic analyses revealed that field soil N2 O emissions primarily originated from nitrification process. The incubation experiment further showed that in field soils under precipitation reduction, drying-rewetting stimulated N mineralization and ammonia-oxidizing bacteria in favor of genera Nitrosospira and Nitrosovibrio, increasing nitrification and N2 O emissions. These findings suggest that moderate precipitation reduction, accompanied with changes in drying-rewetting cycles under future precipitation scenarios, may enhance N cycling processes and soil N2 O emissions in semi-arid ecosystems, feeding positively back to the ongoing climate change.

Arbuscular Mycorrhizal Fungi Shift Soil Bacterial Community Composition and Reduce Soil Ammonia Volatilization and Nitrous Oxide Emissions.

Arbuscular mycorrhizal fungi (AMF) establish mutualistic relationships with the majority of terrestrial plants, increasing plant uptake of soil nitrogen (N) in exchange for photosynthates. And may influence soil ammonia (NH3) volatilization and nitrous oxide (N2O) emissions directly by improving plant N uptake, and/or indirectly by modifying soil bacterial community composition for the soil C availability increasing. However, the effects of AMF on soil NH3 volatilization and N2O emissions and their underlying mechanisms remain unclear. We carried out two independent experiments using contrasting methods, one with a compartmental box device (in 2016) and the other with growth pot experiment (in 2020) to examine functional relationships between AMF and soil NH3 volatilization and N2O emissions under varying N input. The presence of AMF significantly reduced soil NH3 volatilization and N2O emissions while enhancing plant biomass and plant N acquisition, and reducing soil NH4+ and NO3-, even with high N input. The presence of AMF also significantly reduced the relative abundance within the bacterial orders Sphingomonadales and Rhizobiales. Sphingomonadales correlated significantly and positively with soil NH3 volatilization in 2016 and N2O emissions, whereas Rhizobiales correlated positively with soil N2O emissions. High N input significantly increased soil NH3 volatilization and N2O emissions with increasing relative abundance of Sphingomonadales and Rhizobiales. These findings demonstrate the contribution of AMF in regulating NH3 and N2O emission by improving plant N uptake and altering soil bacterial communities. They also suggest that altering the rhizosphere microbiome might offer additional potential for restoration of N-enriched agroecosystems.

Climate warming suppresses abundant soil fungal taxa and reduces soil carbon efflux in a semi-arid grassland.

Soil microorganisms critically affect the ecosystem carbon (C) balance and C-climate feedback by directly controlling organic C decomposition and indirectly regulating nutrient availability for plant C fixation. However, the effects of climate change drivers such as warming, precipitation change on soil microbial communities, and C dynamics remain poorly understood. Using a long-term field warming and precipitation manipulation in a semi-arid grassland on the Loess Plateau and a complementary incubation experiment, here we show that warming and rainfall reduction differentially affect the abundance and composition of bacteria and fungi, and soil C efflux. Warming significantly reduced the abundance of fungi but not bacteria, increasing the relative dominance of bacteria in the soil microbial community. In particular, warming shifted the community composition of abundant fungi in favor of oligotrophic Capnodiales and Hypocreales over potential saprotroph Archaeorhizomycetales. Also, precipitation reduction increased soil total microbial biomass but did not significantly affect the abundance or diversity of bacteria. Furthermore, the community composition of abundant, but not rare, soil fungi was significantly correlated with soil CO2 efflux. Our findings suggest that alterations in the fungal community composition, in response to changes in soil C and moisture, dominate the microbial responses to climate change and thus control soil C dynamics in semi-arid grasslands.

Kangxianruangan granule­containing serum mediated inhibition of hepatic oval cell differentiation into hepatocellular carcinoma cells via the Wnt­1/ß­catenin signaling pathway.

Hepatocellular carcinoma is a malignancy with poor clinical prognosis. Hepatic oval cells (HOCs) tend to differentiate into cancerous hepatocellular carcinoma cells (HCCs) in the tumor microenvironment. The purpose of the present study was to explore the role of kangxianruangan granule (KXRG)­containing serum in inhibiting the differentiation of HOCs into HCCs via the Wnt­1/ß­catenin signaling pathway. N­methyl­N'­nitro­N­nitrosoguanidine (MNNG) was applied to induce the transformation of the rat HOC cell line WB­F344 into HCCs. The overexpression plasmid, Wnt­1­up, was utilized to increase Wnt­1 expression. Subsequently, high, medium and low concentrations of KXRG were applied to MNNG­treated WB­F344 cells to assess the inhibitory effect of KXRG on cell differentiation. Flow cytometry was conducted to detect the cell cycle distribution, apoptotic rate and expression of cytokeratin­19 (CK­19) protein in cells. An immunofluorescence double staining protocol was used to detect the expression of Wnt­1 and ß­catenin. ELISAs were performed to detect α fetoprotein in the cell supernatants. Reverse transcription­quantitative PCR and western blotting were conducted to detect the mRNA and protein expression levels of Wnt­1, ß­catenin, Cyclin D1, C­myc, matrix metalloproteinase­7 (MMP­7), Axin2 and epithelial cell adhesion molecule (EpCAM) in cells. Compared with the normal group, the apoptotic rate, proportion of S phase cells, concentration of AFP in the cell supernatant, level of CK­19 protein, and mRNA and protein expression levels of Wnt­1, ß­catenin, Cyclin D1, C­myc, MMP­7, Axin2 and EpCAM were all significantly increased in the model group. Addition of KXRG significantly reduced the aforementioned indicators compared with the model group. Moreover, Wnt­1 overexpression further increased the aforementioned indicators compared with the model group, whereas KXRG significantly inhibited these effects. The results indicated that KXRG inhibited the differentiation of HOCs into HCCs via the Wnt­1/ß­catenin signaling pathway, which suggested the potential clinical application of KXRG for the prevention of hepatocellular carcinoma.

Symptom-based network classification identifies distinct clinical subgroups of liver diseases with common molecular pathways.

BACKGROUND AND OBJECTIVE: Liver disease is a multifactorial complex disease with high global prevalence and poor long-term clinical efficacy and liver disease patients with different comorbidities often incorporate multiple phenotypes in the clinic. Thus, there is a pressing need to improve understanding of the complexity of clinical liver population to help gain more accurate disease subtypes for personalized treatment. METHODS: Individualized treatment of the traditional Chinese medicine (TCM) provides a theoretical basis to the study of personalized classification of complex diseases. Utilizing the TCM clinical electronic medical records (EMRs) of 6475 liver inpatient cases, we built a liver disease comorbidity network (LDCN) to show the complicated associations between liver diseases and their comorbidities, and then constructed a patient similarity network with shared symptoms (PSN). Finally, we identified liver patient subgroups using community detection methods and performed enrichment analyses to find both distinct clinical and molecular characteristics (with the phenotype-genotype associations and interactome networks) of these patient subgroups. RESULTS: From the comorbidity network, we found that clinical liver patients have a wide range of disease comorbidities, in which the basic liver diseases (e.g. hepatitis b, decompensated liver cirrhosis), and the common chronic diseases (e.g. hypertension, type 2 diabetes), have high degree of disease comorbidities. In addition, we identified 303 patient modules (representing the liver patient subgroups) from the PSN, in which the top 6 modules with large number of cases include 51.68% of the whole cases and 251 modules contain only 10 or fewer cases, which indicates the manifestation diversity of liver diseases. Finally, we found that the patient subgroups actually have distinct symptom phenotypes, disease comorbidity characteristics and their underlying molecular pathways, which could be used for understanding the novel disease subtypes of liver conditions. For example, three patient subgroups, namely Module 6 (M6, n = 638), M2 (n = 623) and M1 (n = 488) were associated to common chronic liver disease conditions (hepatitis, cirrhosis, hepatocellular carcinoma). Meanwhile, patient subgroups of M30 (n = 36) and M36 (n = 37) were mostly related to acute gastroenteritis and upper respiratory infection, respectively, which reflected the individual comorbidity characteristics of liver subgroups. Furthermore, we identified the distinct genes and pathways of patient subgroups and the basic liver diseases (hepatitis b and cirrhosis), respectively. The high degree of overlapping pathways between them (e.g. M36 with 93.33% shared enriched pathways) indicates the underlying molecular network mechanisms of each patient subgroup. CONCLUSIONS: Our results demonstrate the utility and comprehensiveness of disease classification study based on community detection of patient network using shared TCM symptom phenotypes and it can be used to other more complex diseases.