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Rhizosphere-associated microbes have important implications for plant health, but knowledge of the association between the pathological conditions of soil-borne virus-infected wheat and soil microbial communities, especially changes in fungal communities, remains limited. We investigated the succession of fungal communities from bulk soil to wheat rhizosphere soil in both infected and healthy plants using amplicon sequencing methods, and assessed their potential role in plant health. The results showed that the diversity of fungi in wheat rhizosphere and bulk soils significantly differed post wheat yellow mosaic virus disease onset. The structure differences in fungal community at the two wheat health states or two compartment niches were evident, soil physicochemical properties (i.e., NH4+) contribute to differences in fungal community structure and alpha diversity. Comparison analysis showed Mortierellomycetes and Dothideomycetes as dominant communities in healthy wheat soils at class level. The genus Pyronemataceae and Solicoccozyma were significantly are significantly enriched in rhizosphere soil of diseased plant, the genus Cystofilobasidium, Cladosporium, Mortierella, and Stephanonectria are significantly enriched in bulk soil of healthy plant. Co-occurrence network analysis showed that the fungi in healthy wheat soil has higher mutual benefit and connectivity compared with diseased wheat. The results of this study demonstrated that the occurrence of wheat yellow mosaic virus diseases altered both fungal community diversity and composition, and that NH4+ is the most important soil physicochemical factor influencing fungal diversity and community composition.

Abstract Background Histone acetylation is a ubiquitous and reversible post-translational modification in eukaryotes and prokaryotes that is co-regulated by histone acetyltransferase (HAT) and histone deacetylase (HDAC). HAT activity is important for the modification of chromatin structure in eukaryotic cells, affecting gene transcription and thereby playing a crucial regulatory role in plant development. Comprehensive analyses of HAT genes have been performed in Arabidopsis thaliana, Oryza sativa, barley, grapes, tomato, litchi and Zea mays, but comparable identification and analyses have not been conducted in wheat (Triticum aestivum). Results In this study, 31 TaHATs were identified and divided into six groups with conserved gene structures and motif compositions. Phylogenetic analysis was performed to predict functional similarities between Arabidopsis thaliana, Oryza sativa and Triticum aestivum HAT genes. The TaHATs appeared to be regulated by cis-acting elements such as LTR and TC-rich repeats. The qRT–PCR analysis showed that the TaHATs were differentially expressed in multiple tissues. The TaHATs in expression also responded to temperature changes, and were all significantly upregulated after being infected by barley streak mosaic virus (BSMV), Chinese wheat mosaic virus (CWMV) and wheat yellow mosaic virus (WYMV). Conclusions These results suggest that TaHATs may have specific roles in the response to viral infection and provide a basis for further study of TaHAT functions in T. aestivum plant immunity.

Ubiquitination is a major post-translational modification (PTM) involved in almost all eukaryotic biological processes and plays an essential role in plant response to pathogen infection. However, to date, large-scale profiling of the changes in the ubiquitome in response to pathogens, especially viruses, in wheat has not been reported. This study aimed to identify the ubiquitinated proteins involved in Chinese wheat mosaic virus (CWMV) infection in wheat using a combination of affinity enrichment and high-resolution liquid chromatography-tandem mass spectroscopy. The potential biological functions of these ubiquitinated proteins were further analyzed using bioinformatics. A total of 2297 lysine ubiquitination sites in 1255 proteins were identified in wheat infected with CWMV, of which 350 lysine ubiquitination sites in 192 proteins were differentially expressed. These ubiquitinated proteins were related to metabolic processes, responses to stress and hormones, plant–pathogen interactions, and ribosome pathways, as assessed via Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Furthermore, we found that the ubiquitination of Ta14-3-3 and TaHSP90, which are essential components of the innate immune system, was significantly enhanced during CWMV infection, which suggested that ubiquitination modification plays a vital role in the regulatory network of the host response to CWMV infection. In summary, our study puts forward a novel strategy for further probing the molecular mechanisms of CWMV infection. Our findings will inform future research to find better, innovative, and effective solutions to deal with CWMV infection in wheat, which is the most crucial and widely used cereal grain crop.

Protein lysine acetylation (Kac) is an important post-translational modification mechanism in eukaryotes that is involved in cellular regulation. To investigate the role of Kac in virus-infected plants, we characterized the lysine acetylome of Nicotiana benthamiana plants with or without a Chinese wheat mosaic virus (CWMV) infection. We identified 4,803 acetylated lysine sites on 1,964 proteins. A comparison of the acetylation levels of the CWMV-infected group with those of the uninfected group revealed that 747 sites were upregulated on 422 proteins, including chloroplast localization proteins and histone H3, and 150 sites were downregulated on 102 proteins. Nineteen conserved motifs were extracted and 51 percent of the acetylated proteins located on chloroplast. Nineteen Kac sites were located on histone proteins, including 10 Kac sites on histone 3. Bioinformatics analysis results indicated that lysine acetylation occurs on a large number of proteins involved in biological processes, especially photosynthesis. Furthermore, we found that the acetylation level of chloroplast proteins, histone 3 and some metabolic pathway-related proteins were significantly higher in CWMV-infected plants than in uninfected plants. In summary, our results reveal the regulatory roles of Kac in response to CWMV infection.

Recent studies have shown that a large number of long noncoding RNAs (lncRNAs) can regulate various biological processes in animals and plants. Although lncRNAs have been identified in many plants, they have not been reported in the model plant Nicotiana benthamiana. Particularly, the role of lncRNAs in plant virus infection remains unknown. In this study, we identified lncRNAs in N. benthamiana response to Chinese wheat mosaic virus (CWMV) infection by RNA sequencing. A total of 1175 lncRNAs, including 65 differentially expressed lncRNAs, were identified during CWMV infection. We then analyzed the functions of some of these differentially expressed lncRNAs. Interestingly, one differentially expressed lncRNA, XLOC_006393, was found to participate in CWMV infection as a precursor to microRNAs in N. benthamiana. These results suggest that lncRNAs play an important role in the regulatory network of N. benthamiana in response to CWMV infection.

Anaerobic digestion (AD) is an economical and effective method to treat sludge. AD with several pretreatments is the prior process to treat surplus sludge for a wastewater treatment plant. During a sludge-treatment process, various methanogens play their specific role in each sludge-processing stage where different methanogens predominate. Therefore, an expert in the shift of methanogen community could facilitate the workers in a plant to understand the efficiency of the sludge-treatment process. In this paper, a membership-fusing model is established to characterize the shift of methanogen community in a three-stage sludge-treatment process. The introduction of fuzzy sets clarifies the vagueness of the methanogen community structure between two processing stages. Dempster–Shafer (DS) evidence theory effectively alleviates the data error generated among paralleling samples. The accuracy of the model was verified, and the result shows the model could clearly distinguish the methanogen community structure of the three stages and make accurate judgment on the processing stage affiliation. The reliability of the model in dealing with different numbers of conflict data was proved and the experiment indicates the model could make a reliable judgment on the processing stage affiliation by reasonably fusing the interference data.