Different extractable pools of Cd and Pb in agricultural soil under amendments: Water-soluble concentration sensitively indicates metal availability.

Identification of the most appropriate chemically extractable pool for evaluating Cd and Pb availability remains elusive, hindering accurate assessment on environmental risks and effectiveness of remediation strategies. This study evaluated the feasibility of European Community Bureau of Reference (BCR) sequential extraction, Ca(NO3)2 extraction, and water extraction on assessing Cd and Pb availability in agricultural soil amended with slaked lime, magnesium hydroxide, corn stover biochar, and calcium dihydrogen phosphate. Moreover, the enriched isotope tracing technique (112Cd and 206Pb) was employed to evaluate the aging process of newly introduced Cd and Pb within 56 days' incubation. Results demonstrated that extractable pools by BCR and Ca(NO3)2 extraction were little impacted by amendments and showed little correlation with soil pH. This is notable because soil pH is closely linked to metal availability, indicating these extraction methods may not adequately reflect metal availability. Conversely, water-soluble concentrations of Cd and Pb were markedly influenced by amendments and exhibited strong correlations with pH (Pearson's r: -0.908 to -0.825, P < 0.001), suggesting water extraction as a more sensitive approach. Furthermore, newly introduced metals underwent a more evident aging process as demonstrated by acid-soluble and water-soluble pools. Additionally, water-soluble concentrations of essential metals were impacted by soil amendments, raising caution on their potential effects on plant growth. These findings suggest water extraction as a promising and attractive method to evaluate Cd and Pb availability, which will help provide assessment guidance for environmental risks caused by heavy metals and develop efficient remediation strategies.

Water-extractable metals as indicators of wheat metal accumulation: Insights from Cd, Pb, Mn, Cu, and Zn.

There is a long-standing debate over the effectiveness of chemical extraction methods in assessing soil metal phytoavailability. This study addresses the limitations of widely-used chemical extraction methods and presents the water-extractable pool as a more reliable indicator based on wheat pot experiments using homogenized agricultural soil amended with lime materials, phosphate, and biochar. Over 120 days' pot experiments, Cd accumulation in whole wheat plants and tissues exhibited positive relationships with water-extractable Cd concentrations at heading and maturity stage (Spearman's rho: 0.521-0.851; P < 0.05), revealing that the water-extractable pool instead of other pools better indicates wheat metal accumulation. Water-extractable metal concentrations are effective in assessing phytoavailability of metals primarily in ionic forms in soil solution (e.g, Zn, Cd), but less reliable for metals strongly complexed with dissolved organic matter (DOM) or sensitive to redox conditions. It demonstrated that water-extractable metal concentrations and chemical forms are key factors, fundamentally determined by metal properties and impacted by environmental factors. This study clarifies a more direct link between chemical extraction and plant metal uptake mechanisms. Given the extensive application of chemical extraction methods over several decades, this study will help advance soil metal risk assessment and remediation practices.

A global survey of bicarbonate stress-induced pre-mRNA alternative splicing in soybean via integrative analysis of Iso-seq and RNA-seq.

Alternative splicing (AS) plays important roles in modulating environmental stress responses in plants. However, little is known about the functions of bicarbonate-induced AS in cultivated soybean (Glycine max L. Merr.). In this study, we combined PacBio isoform sequencing (Iso-seq) and Illumina RNA sequencing (RNA-seq) to elucidate the bicarbonate-induced AS events in soybean root and leaf tissues. Compared to RNA-seq, Iso-seq identified more novel genes and transcripts, as well as more AS events, indicating that Iso-seq is more efficient in AS detection. Combining these two technologies, we found that intron retention (IR) is the most frequent AS event type. We identified a total of 913 and 1974 bicarbonate stress-responsive differentially alternative spliced genes (DAGs) in soybean leaves and roots respectively, from our RNA-seq results. Additionally, we determined a transcription factor (GmNTL9) and a splicing factor (GmRSZ22), and validated their roles in bicarbonate stress response by AS. Overall, our study opens an avenue for evaluating plant AS regulatory networks, and the obtained global landscape of alternative splicing provides valuable insights into the AS-mediated bicarbonate-responsive mechanisms in plant species.

Scalable parameterized quantum circuits classifier.

As a generalized quantum machine learning model, parameterized quantum circuits (PQC) have been found to perform poorly in terms of classification accuracy and model scalability for multi-category classification tasks. To address this issue, we propose a scalable parameterized quantum circuits classifier (SPQCC), which performs per-channel PQC and combines the measurements as the output of the trainable parameters of the classifier. By minimizing the cross-entropy loss through optimizing the trainable parameters of PQC, SPQCC leads to a fast convergence of the classifier. The parallel execution of identical PQCs on different quantum machines with the same structure and scale reduces the complexity of classifier design. Classification simulations performed on the MNIST Dataset show that the accuracy of our proposed classifier far exceeds that of other quantum classification algorithms, achieving the state-of-the-art simulation result and surpassing/reaching classical classifiers with a considerable number of trainable parameters. Our classifier demonstrates excellent scalability and classification performance.

Blurred interface induced control of electrical transport properties in Josephson junctions.

The interfacial microstructures of Josephson junctions are vital for understanding the microscopic mechanism to improve the performance of superconducting qubits further. However, there remain significant concerns about well understanding the correlation between atomic structures and electrical behaviors. Here, we propose a new method to define the interface of the barrier in Josephson junctions, and investigate the factors that affect the electrical properties of junctions using material analysis techniques and first principles. We find that the aluminium-oxygen ratio of the interface contributes greatly to the electrical properties of junctions, which is consistent with the conclusions obtained by utilizing the generative adversarial network for data augmentation. When the aluminium-oxygen ratio of the interface is 0.67-1.1, the model exhibits a lower barrier height and better electrical properties of the junction. Moreover, when the thickness of the barrier is fixed, the impact of the aluminium-oxygen ratio becomes prominent. A detailed analysis of Josephson junctions using a microscopic model has led to identifying of process defects that can enhance the yield rate of chips. It has a great boost for determining the relationship between microstructures and macroscopic performances.

Recurrent quantum embedding neural network and its application in vulnerability detection.

In recent years, deep learning has been widely used in vulnerability detection with remarkable results. These studies often apply natural language processing (NLP) technologies due to the natural similarity between code and language. Since NLP usually consumes a lot of computing resources, its combination with quantum computing is becoming a valuable research direction. In this paper, we present a Recurrent Quantum Embedding Neural Network (RQENN) for vulnerability detection. It aims to reduce the memory consumption of classical models for vulnerability detection tasks and improve the performance of quantum natural language processing (QNLP) methods. We show that the performance of RQENN achieves the above goals. Compared with the classic model, the space complexity of each stage of its execution is exponentially reduced, and the number of parameters used and the number of bits consumed are significantly reduced. Compared with other QNLP methods, RQENN uses fewer qubit resources and achieves a 15.7% higher accuracy in vulnerability detection.

Regulation of plant resistance to salt stress by the SnRK1-dependent splicing factor SRRM1L.

Most splicing factors are extensively phosphorylated but their physiological functions in plant salt resistance are still elusive. We found that phosphorylation by SnRK1 kinase is essential for SRRM1L nuclear speckle formation and its splicing factor activity in plant cells. In Arabidopsis, loss-of-function of SRRM1L leads to the occurrence of alternative pre-mRNA splicing events and compromises plant resistance to salt stress. In Arabidopsis srrm1l mutant line, we identified an intron-retention Nuclear factor Y subunit A 10 (NFYA10) mRNA variant by RNA-Seq and found phosphorylation-dependent RNA-binding of SRRM1L is indispensable for its alternative splicing activity. In the wild-type Arabidopsis, salt stress can activate SnRK1 to phosphorylate SRRM1L, triggering enrichment of functional NFYA10.1 variant to enhance plant salt resistance. By contrast, the Arabidopsis srrm1l mutant accumulates nonfunctional NFYA10.3 variant, sensitizing plants to salt stress. In summary, this work deciphered the molecular mechanisms and physiological functions of SnRK1-SRRM1L-NFYA10 module, shedding light on a regulatory pathway to fine-tune plant adaptation to abiotic stress at the post-transcriptional and post-translational levels.

Quercus wutaishanica shrub affects temperate forest community composition and soil properties under different restoration stage.

Quercus wutaishanica is the dominant tree species in the natural ecosystem restoration of temperate forests in China, and it plays an active role in maintaining ecological balance. However, little is known about how ecosystem versatility develops during the restoration of forest ecosystems dominated by Q. wutaishanica. In this study, we investigated the species composition of the Q. wutaishanica community, soil nutrients, and their functional traits at various restoration stages, and comprehensively analyzed the correlations among them. At the early stage of restoration (10 years of restoration), there were Spiraea pubescens and Syringa pubescens in Q. wutaishanica community (87% of the total species), while had a larger niche width. In the middle of restoration (30 years of restoration), shannon and evenness indices were the largest, while soil total carbon, ammonium nitrogen and chlorophyll content of Q. wutaishanica leaves were the highest; among them, soil total carbon was 15.7% higher than that in 10 years of restoration, 32.4% higher than that in 40 years of restoration, ammonium nitrogen was 71.7% higher than that in 40 years of restoration, and chlorophyll content was 217.9% higher than that in 10 years of restoration, and 51.8% higher than that in 40 years of restoration. At the later stage of restoration (40 years of restoration), Lonicera ferdinandii occupied the dominant ecological niche, and soil available nitrogen, available phosphorus content and leaf thickness were the largest; while AN was 10.9% higher than that of 10 years of restoration, 16.5% higher than that of 30 years of restoration, AP was 60.6% higher than that of 10 years of restoration, 21.6% higher than that of 30 years of restoration, leaf thickness was 22.3% higher than that of 10 years of restoration, 84.9% higher than that of 30 years of restoration. However, the restriction of various soil nutrients was reduced. Our study highlighted the effectiveness of soil resource availability in plant communities during restoration, reduced competition for light among plants, and altered species richness. Furthermore, changes in the interrelationship between plant community composition and leaf functional traits of the dominant species responded positively to community restoration. These results further deepen our understanding of forest management and restoration of forest communities. In the future, it is necessary to comprehensively consider the influence of various factors on forest community restoration.

Responses of Soil Microbial Survival Strategies and Functional Changes to Wet-Dry Cycle Events.

Soil microbial taxa have different functional ecological characteristics that influence the direction and intensity of plant-soil feedback responses to changes in the soil environment. However, the responses of soil microbial survival strategies to wet and dry events are poorly understood. In this study, soil physicochemical properties, enzyme activity, and high-throughput sequencing results were comprehensively anal0079zed in the irrigated cropland ecological zone of the northern plains of the Yellow River floodplain of China, where Oryza sativa was grown for a long period of time, converted to Zea mays after a year, and then Glycine max was planted. The results showed that different plant cultivations in a paddy-dryland rotation system affected soil physicochemical properties and enzyme activity, and G. max field cultivation resulted in higher total carbon, total nitrogen, soil total organic carbon, and available nitrogen content while significantly increasing α-glucosidase, ß-glucosidase, and alkaline phosphatase activities in the soil. In addition, crop rotation altered the r/K-strategist bacteria, and the soil environment was the main factor affecting the community structure of r/K-strategist bacteria. The co-occurrence network revealed the inter-relationship between r/K-strategist bacteria and fungi, and with the succession of land rotation, the G. max sample plot exhibited more stable network relationships. Random forest analysis further indicated the importance of soil electrical conductivity, total carbon, total nitrogen, soil total organic carbon, available nitrogen, and α-glucosidase in the composition of soil microbial communities under wet-dry events and revealed significant correlations with r/K-strategist bacteria. Based on the functional predictions of microorganisms, wet-dry conversion altered the functions of bacteria and fungi and led to a more significant correlation between soil nutrient cycling taxa and environmental changes. This study contributes to a deeper understanding of microbial functional groups while helping to further our understanding of the potential functions of soil microbial functional groups in soil ecosystems.

Quantitative Phosphoproteomic Analysis Provides Insights into the Sodium Bicarbonate Responsiveness of Glycine max.

Sodium bicarbonate stress caused by NaHCO3 is one of the most severe abiotic stresses affecting agricultural production worldwide. However, little attention has been given to the molecular mechanisms underlying plant responses to sodium bicarbonate stress. To understand phosphorylation events in signaling pathways triggered by sodium bicarbonate stress, TMT-labeling-based quantitative phosphoproteomic analyses were performed on soybean leaf and root tissues under 50 mM NaHCO3 treatment. In the present study, a total of 7856 phosphopeptides were identified from cultivated soybeans (Glycine max L. Merr.), representing 3468 phosphoprotein groups, in which 2427 phosphoprotein groups were newly identified. These phosphoprotein groups contained 6326 unique high-probability phosphosites (UHPs), of which 77.2% were newly identified, increasing the current soybean phosphosite database size by 43.4%. Among the phosphopeptides found in this study, we determined 67 phosphopeptides (representing 63 phosphoprotein groups) from leaf tissue and 554 phosphopeptides (representing 487 phosphoprotein groups) from root tissue that showed significant changes in phosphorylation levels under sodium bicarbonate stress (fold change >1.2 or <0.83, respectively; p < 0.05). Localization prediction showed that most phosphoproteins localized in the nucleus for both leaf and root tissues. GO and KEGG enrichment analyses showed quite different enriched functional terms between leaf and root tissues, and more pathways were enriched in the root tissue than in the leaf tissue. Moreover, a total of 53 different protein kinases and 7 protein phosphatases were identified from the differentially expressed phosphoproteins (DEPs). A protein kinase/phosphatase interactor analysis showed that the interacting proteins were mainly involved in/with transporters/membrane trafficking, transcriptional level regulation, protein level regulation, signaling/stress response, and miscellaneous functions. The results presented in this study reveal insights into the function of post-translational modification in plant responses to sodium bicarbonate stress.

Volatile fatty acids changed the microbial community during feammox in coastal saline-alkaline paddy soil.

In order to indicate the effect of volatile fatty acids (VFAs) on the characteristics of feammox and dissimilatory iron reducing bacteria (DIRB) in paddy soils, different VFAs were selected with paddy soils for anaerobic cultivation. Five treatments were set up, respectively, only adding N and both adding N and C (formate + NH4+ (Fo-N), acetate + NH4+ (Ac-N), propionate + NH4+ (Pr-N), and butyrate + NH4+ (Bu-N)) treatments. The concentration of Fe(II), Fe(III), NH4+, and VFAs was assessed within 45 d, and the bacterial community was determined after cultivation. The oxidation rates of NH4+ were the highest in N treatment, while it was the lowest in Fo-N treatment. Under the four C treatments, the consumption of NH4+ and Fe(III) was the fastest in Pr-N treatment, which was consumed by 31.2% and 76.3%, respectively. Different VFAs selected for distinct DIRB. Compared with N treatment, Ac-N and Bu-N treatment increased the relative abundance of DIRB, such as Geobacter and Clostridia, which increased the consumption of VFAs during incubation. Overall, VFAs, especially formate, could promote Fe(III) reduction and compete with the feammox process for the electron acceptors to decrease the feammox reaction, and prohibited soil NH4+ loss. Therefore, VFAs, which was released from organic fertilizer, could reduce NH4+ loss in feammox process of saline-alkaline paddy soils.

An Enhanced Quantum K-Nearest Neighbor Classification Algorithm Based on Polar Distance.

The K-nearest neighbor (KNN) algorithm is one of the most extensively used classification algorithms, while its high time complexity limits its performance in the era of big data. The quantum K-nearest neighbor (QKNN) algorithm can handle the above problem with satisfactory efficiency; however, its accuracy is sacrificed when directly applying the traditional similarity measure based on Euclidean distance. Inspired by the Polar coordinate system and the quantum property, this work proposes a new similarity measure to replace the Euclidean distance, which is defined as Polar distance. Polar distance considers both angular and module length information, introducing a weight parameter adjusted to the specific application data. To validate the efficiency of Polar distance, we conducted various experiments using several typical datasets. For the conventional KNN algorithm, the accuracy performance is comparable when using Polar distance for similarity measurement, while for the QKNN algorithm, it significantly outperforms the Euclidean distance in terms of classification accuracy. Furthermore, the Polar distance shows scalability and robustness superior to the Euclidean distance, providing an opportunity for the large-scale application of QKNN in practice.

The Role of GmSnRK1-GmNodH Module in Regulating Soybean Nodulation Capacity.

SnRK1 protein kinase plays hub roles in plant carbon and nitrogen metabolism. However, the function of SnRK1 in legume nodulation and symbiotic nitrogen fixation is still elusive. In this study, we identified GmNodH, a putative sulfotransferase, as an interacting protein of GmSnRK1 by yeast two-hybrid screen. The qRT-PCR assays indicate that GmNodH gene is highly expressed in soybean roots and could be induced by rhizobial infection and nitrate stress. Fluorescence microscopic analyses showed that GmNodH was colocalized with GsSnRK1 on plasma membrane. The physical interaction between GmNodH and GmSnRK1 was further verified by using split-luciferase complementary assay and pull-down approaches. In vitro phosphorylation assay showed that GmSnRK1 could phosphorylate GmNodH at Ser193. To dissect the function and genetic relationship of GmSnRK1 and GmNodH in soybean, we co-expressed the wild-type and mutated GmSnRK1 and GmNodH genes in soybean hairy roots and found that co-expression of GmSnRK1/GmNodH genes significantly promoted soybean nodulation rates and the expression levels of nodulation-related GmNF5α and GmNSP1 genes. Taken together, this study provides the first biological evidence that GmSnRK1 may interact with and phosphorylate GmNodH to synergistically regulate soybean nodulation.

Functional characterization of wild soybean (Glycine soja) GsSnRK1.1 protein kinase in plant resistance to abiotic stresses.

Protein kinases play crucial roles in the regulation of plant resistance to various stresses. In this work, we determined that GsSnRK1.1 was actively responsive to saline-alkali, drought, and abscisic acid (ABA) stresses by histochemical staining and qRT-PCR analyses. The wild-type GsSnRK1.1 but not the kinase-dead mutant, GsSnRK1.1(K49M), demonstrated in vitro kinase activity by phosphorylating GsABF2. Intriguingly, we found that GsSnRK1.1 could complement the loss of SNF1 kinase in yeast Msy1193 (-snf1) mutant, rescue growth defects of yeast cells on medium with glycerol as a carbon resource, and promote yeast resistance to NaCl or NaHCO3. To further elucidate GsSnRK1.1 function in planta, we knocked out SnRK1.1 gene from the Arabidopsis genome by the CRISPR/Cas9 approach, and then expressed GsSnRK1.1 and a series of mutants into snrk1.1-null lines. The transgenic Arabidopsis lines were subjected to various abiotic stress treatments. The results showed that GsSnRK1.1(T176E) mutant with enhanced protein kinase activity significantly promoted, but GsSnRK1.1(K49M) and GsSnRK1.1(T176A) mutants with disrupted protein kinase activity abrogated, plant stomatal closure and tolerance to abiotic stresses. In conclusion, this study provides the molecular clues to fully understand the physiological functions of plant SnRK1 protein kinases.

Effect of Fe-based substance on Cr leaching behavior in hazardous waste incineration fly ash after thermal treatment.

This study investigated the influence of the interaction between Fe-based substances and thermal treatment parameters on the leaching behavior of Cr in hazardous waste incineration fly ash (HWIFA) after thermal treatment. The results revealed that the interaction between the addition of Fe-based substance and the thermal treatment parameters and their effects on static and dynamic leaching behaviors of Cr had significant differences when Fe2O3, Fe3O4, and Fe were added, respectively. Specifically, when Fe2O3 or Fe was added, the thermal treatment temperature was the most significant factor affecting the static leaching of Cr in thermal treated HWIFA, and the interaction effect of other factors was not significant. The most important influence on the dynamic leaching behavior of Cr was the interaction between the thermal treatment temperature and the addition of Fe2O3. Different from the addition of Fe2O3, the effect of the addition of Fe3O4 on the static leaching of Cr in thermal treated HWIFA was more significant than that of thermal treatment temperature; meanwhile, the interaction between the thermal treatment temperature and the addition of Fe3O4 was also significant. However, when Fe3O4 was added, the effect of interaction between factors on the dynamic leaching of Cr in thermal treated HWIFA was consistent with that when Fe2O3 was added.

A Hybrid Quantum Image-Matching Algorithm.

Image matching is an important research topic in computer vision and image processing. However, existing quantum algorithms mainly focus on accurate matching between template pixels, and are not robust to changes in image location and scale. In addition, the similarity calculation of the matching process is a fundamentally important issue. Therefore, this paper proposes a hybrid quantum algorithm, which uses the robustness of SIFT (scale-invariant feature transform) to extract image features, and combines the advantages of quantum exponential storage and parallel computing to represent data and calculate feature similarity. Finally, the quantum amplitude estimation is used to extract the measurement results and realize the quadratic acceleration of calculation. The experimental results show that the matching effect of this algorithm is better than the existing classical architecture. Our hybrid algorithm broadens the application scope and field of quantum computing in image processing.

Valorization of hexoses into 5-hydroxymethylfurfural and levulinic acid in acidic seawater under microwave hydrothermal conditions.

Typical value-added platform chemicals 5-hydroxymethylfurfural (HMF) and levulinic acid (LA) can be obtained from hexoses under microwave hydrothermal (MHT) conditions. This study explored the detailed transformation process regarding the MHT products in acidic seawater obtained using glucose and fructose as raw materials. The facile conversion of fructose compared with glucose was mainly ascribed to their different activation energies (56.721 and 88.594 kJ mol-1, respectively). The HMF and LA product yields were strongly affected by the MHT temperature and holding time in two types of hexose solution. Undesirable humins were found to inevitably form under each set of reaction conditions. The carbon balance results for reactants and products showed that up to 60% of fructose carbon was converted into value-added chemicals, while 47% of glucose carbon underwent the same conversion in acidic seawater under the optimal MHT conditions. This study provides further knowledge regarding the role of microwave heating combined with acidic seawater in green chemistry and is a useful reference for the biorefinery industry.

A comparison of microbial composition under three tree ecosystems using the stochastic process and network complexity approaches.

Soil microbes act as "players" in regulating biogeochemical cycles, whereas environmental heterogeneity drives microbial community assembly patterns and is influenced by stochastic and deterministic ecological processes. Currently, the limited understanding of soil microbial community assembly patterns and interactions under temperate forest stand differences pose a challenge in studying the soil microbial involvement during the succession from coniferous to broad-leaved forests. This study investigated the changes in soil bacterial and fungal community diversity and community structure at the regional scale and identified the pathways influencing soil microbial assembly patterns and their interactions. The results showed that broad-leaved forest cover in temperate forests significantly increased soil pH, and effectively increased soil water content, total carbon (TC), total nitrogen (TN), and total phosphorus (TP) contents. Both soil bacterial and fungal alpha diversity indices were correlated with soil physicochemical properties, especially in broad-leaved forest. The bacterial and fungal community composition of coniferous forest was dominated by deterministic process (bacteria: 69.4%; fungi: 88.9%), while the bacterial community composition of broad-leaved forest was dominated by stochastic process (77.8%) and the fungal community composition was dominated by deterministic process (52.8%). Proteobacteria, Acidobacteriota, Actinobacteriota, and Verrucomicrobiota were the dominant phyla of soil bacterial communities in temperate forests. Whereas Ascomycota, Mortierellomycota, Basidiomycota, and Rozellomycota were the dominant phyla of soil fungal communities in temperate forests. Most members of dominant phylum were regulated by soil physical and chemical properties. In addition, the succession from temperate coniferous forest to broad-leaved forest was conducive to maintaining the complex network of soil bacteria and fungi, and the top 20 degree of the major taxa in the network reflected the positive response of microbial interactions to the changes of soil nutrients during forest succession. This study not only shows the mechanism by which species differences in temperate forests of northern China affect soil microbial community assembly processes, but also further emphasizes the importance of the soil microbiome as a key ecosystem factor through co-occurrence network analysis.

Development of nitrile rubber/eucommia ulmoides gum composites for controllable dynamic damping and sound absorption performance.

Aiming at enhancing the damping and sound absorption performances of nitrile rubber (NBR) incorporated Eucommia ulmoides gum (EUG), a series of NBR/EUG composites were successfully fabricated using an open mixing mill. The co-vulcanization behaviors, fracture surface morphology observations, mechanical and thermal properties and damping and sound absorption performances of NBR/EUG composites were investigated systematically. It was shown that the crystalline area and the amorphous area in NBR/EUG composites displayed a sea-island phase distribution and most of the EUG crystals were ß-form crystals. Compared to that of neat NBR, the tensile strength and storage modulus of NBR/EUG composites increased dramatically with the increasing EUG content, owing to the gradually increasing number of crystals in the NBR/EUG composites. In addition, the incorporation of EUG into the NBR matrix distinctly improved the sound absorption performance of NBR/EUG composites. This work is expected to provide a new insight into the fabrication of other composite materials with controllable damping and sound absorption properties.

Epigenetic Regulation of Plant Tolerance to Salt Stress by Histone Acetyltransferase GsMYST1 From Wild Soybean.

Salt stress is one of the most devastating environmental factors threatening soybean growth and yield. However, the molecular link between salt stress and epigenetics has not been well-elucidated in soybean. In this study, from the wild soybean cDNA library, we isolated a GsSnRK1 kinase interacting protein (GsMSTY1) which is phylogenetically homologous with histone acetyltransferase MYST family with unknown function. GsMSTY1 gene is dominantly expressed in wild soybean roots and is highly responsive to abiotic stresses. GsMYST1 was able to be phosphorylated at the Ser44 site by GsSnRK1 and demonstrated in vivo acetyltransferase activity in transgenic soybean roots revealed by an anti-H4ace antibody. A transcription factor protein GsNAC83 was identified to interact with both GsMYST1 and GsSnRK1, and GsNAC83 could recruit the GsMYST1-GsSnRK1 module to COR15B gene promoter determined by ChIP-qPCR assay. To dissect the molecular functions of this ternary complex, we treated the transgenic soybean roots with salt stress and found that the stress could activate GsSnRK1, and the activated GsSnRK1 subsequently phosphorylated GsMYST1 to enhance its acetyltransferase activity which may epigenetically promote the target gene expression. To explore the physiological functions, we coexpressed GsSnRK1 and GsMYST1 genes in soybean hairy roots and found that only GsSnRK1(wt)/GsMYST1(wt) but not the mutant genes could promote soybean resistance to salt stress, implicating that phosphorylation of GsMYST1 is required for it to acetylate histone H4 on the target genes to upregulate expression of the stress-related genes. Our data shed new light on the functions of the GsSnRK1-GsMYST1-GsNAC83 module and its regulatory mechanism on plant tolerance to abiotic stresses.