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Sugar beet is vulnerable to years of continuous cropping, and allelopathy is one of the important factors leading to continuous cropping disorder. To explore the physiological and molecular mechanisms behind continuous cropping obstacles on sugar beet, this study combined transcriptomics and metabolomics to analyze the effects of different years of continuous cropping on metabolite changes, differential gene expression, and root exudate regulation in sugar beet. We collected sugar beet’s root samples from 1–, 3–, and 5-year continuous cropping systems for metabolome and transcriptome analyses. Our data revealed that T3 and T5 had 50 and 33 metabolites significantly different from T1, respectively. The autotoxic substance salicylaldehyde was found to continuously accumulate in root exudates with increasing years of continuous cropping. Sucrose was highly reduced in T3 (4.05-fold decrease) and T5 (2.01-fold decrease) compared to T1. Respectively, 2,660 and 3,515 differentially expressed genes (DEGs) were significantly regulated in T3 and T5 compared to T1. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that metabolic pathways and biosynthesis of secondary metabolites were perturbed in T3 and T5 vs. T1. Integrated metabolomics analyses identified 73 DEGs involved in enriched metabolic pathways, all of which were the oxidation-reduction process pathways. In conclusion, this study provides evidence that continuous cropping obstacles can change the metabolome and transcriptome of sugar beet, affecting its growth and quality.

Plant–microbe interactions can modulate the plant metabolome, but there is no information about how different soil microbiomes could affect the sugarcane metabolome and its quality. Here, we collected soil and stalk samples from bitter sugarcane (BS) and sweet sugarcane (SS) to conduct chemical analysis, microbiome and metabolome analysis. Our data revealed lower species diversity in the BS group than in the SS group, and 18 discriminatory OTUs (relative abundance ≥ 0.01%) were identified. Sugarcane metabolomic analysis indicated the different abundances of 247 metabolites between the two groups in which 22 distinct metabolites involved in two flavonoid biosynthesis pathways were revealed. Integrated analysis between soil microbial taxa, stalk chemical components, and soil properties showed that the flavonoid content in stalks and the nitrogen concentration in soil were highly correlated with the soil microbiome composition. Bacteria at the genus level exhibited greater associations with distinct metabolites, and six genera were independently associated with 90.9% of the sugarcane metabolites that play a major metabolic role in sugarcane. In conclusion, this study provided evidences that the interaction between plant–microbiome can change the plant metabolome.

The cultivation and production of passion fruit ( Passiflora edulis ) are severely affected by viral disease. Yet there have been few studies of the molecular response of passion fruit to virus attack. In the present study, RNA-based transcriptional profiling (RNA-seq) was used to identify the gene expression profiles in yellow passion fruit ( Passiflora edulis f. flavicarpa ) leaves following inoculation with cucumber mosaic virus (CMV). Six RNA-seq libraries were constructed comprising a total of 42.23 Gb clean data. 1,545 differentially expressed genes (DEGs) were obtained (701 upregulated and 884 downregulated). Gene annotation analyses revealed that genes associated with plant hormone signal transduction, transcription factors, protein ubiquitination, detoxification, phenylpropanoid biosynthesis, photosynthesis and chlorophyll metabolism were significantly affected by CMV infection. The represented genes activated by CMV infection corresponded to transcription factors WRKY family, NAC family, protein ubiquitination and peroxidase. Several DEGs encoding protein TIFY, pathogenesis-related proteins, and RNA-dependent RNA polymerases also were upregualted by CMV infection. Overall, the information obtained in this study enriched the resources available for research into the molecular-genetic mechanisms of the passion fruit/CMV interaction, and might provide a theoretical basis for the prevention and management of passion fruit viral disease in the field.

Fungal dissemination into the bloodstream is a critical step leading to invasive fungal infections. Here, using intravital imaging, we show that Kupffer cells (KCs) in the liver have a prominent function in the capture of circulating Cryptococcus neoformans and Candida albicans , thereby reducing fungal dissemination to target organs. Complement C3 but not C5, and complement receptor CRIg but not CR3, are involved in capture of C. neoformans . Internalization of C. neoformans by KCs is subsequently mediated by multiple receptors, including CR3, CRIg, and scavenger receptors, which work synergistically along with C5aR signaling. Following phagocytosis, the growth of C. neoformans is inhibited by KCs in an IFN-γ independent manner. Thus, the liver filters disseminating fungi from circulation via KCs, providing a mechanistic explanation for the enhanced risk of cryptococcosis among individuals with liver diseases, and suggesting a therapeutic strategy to prevent fungal dissemination through enhancing KC functions. Patients with liver diseases are at increased risk of fungal infections. Here the authors show that Kupffer cells are critical for the filtration of fungi out of the blood and thereby for liver-mediated protection against disseminating fungal infection.

Background Inflammatory bowel disease (IBD) is a global health problem in which gut microbiota dysbiosis plays a pivotal pathogenic role. Mesenchymal stem cells (MSCs) therapy has emerged as a prospective novel tool for managing IBD, and which can also regulate the composition of gut microbiota. However, the functional significance of MSCs-induced changes in gut microbiome is poorly understood. Methods Here, we investigated for the first time the role of gut microbiota in mediating the protective effect of human umbilical cord MSCs (HUMSCs) on DSS-induced colitis. Gut microbiota alteration and short-chain fatty acids (SCFAs) production were analyzed through 16S rRNA sequencing and targeted metabolomics. Spectrum antibiotic cocktail (ABX), fecal microbiota transplantation (FMT) and sterile fecal filtrate (SFF) were employed to evaluate the protective effect of intestinal flora and its metabolites. Cytokine microarray, Enzyme-linked immunosorbent assay (ELISA), and flow cytometry were conducted to assess the effect on CD4 + T homeostasis. Results Here, we investigated for the first time the role of gut microbiota in mediating the protective effect of MSCs on DSS-induced colitis. By performing gut microbiota depletion and fecal microbiota transplantation (FMT) experiments, we revealed that MSCs derived from human umbilical cord ameliorated colon inflammation and reshaped T-cells immune homeostasis via remodeling the composition and diversity of gut flora, especially up-regulated SCFAs-producing bacterial abundance, such as Akkermansia , Faecalibaculum , and Clostridia_UCG_014 . Consistently, targeted metabolomics manifested the increased SCFAs production with MSCs administration, and there was also a significant positive correlation between differential bacteria and SCFAs. Meanwhile, combined with sterile fecal filtrate (SFF) gavage experiments, the underlying protective mechanism was further associated with the improved Treg/Th2/Th17 balance in intestinal mucosa mediated via the increased microbiota-derived SCFAs production. Conclusion The present study advances understanding of MSCs in the protective effects on colitis, providing evidence for the new role of the microbiome-metabolite-immune axis in the recovery of colitis by MSCs.

Ulcerative colitis (UC) is characterized by an abnormal immune response, and the pathogenesis lacks clear understanding. The cGAS-STING pathway is an innate immune signaling pathway that plays a significant role in various pathophysiological processes. However, the role of the cGAS-STING pathway in UC remains largely unclear. In this study, we obtained transcriptome sequencing data from multiple publicly available databases. cGAS-STING related genes were obtained through literature search, and differentially expressed genes (DEGs) were analyzed using R package limma. Hub genes were identified through protein–protein interaction (PPI) network analysis and module construction. The ConsensuClusterPlus package was utilized to identify molecular subtypes based on hub genes. The therapeutic response, immune microenvironment, and biological pathways of subtypes were further investigated. A total of 18 DEGs were found in UC patients. We further identified IFI16 , MB21D1 (CGAS) , TMEM173 (STING) and TBK1 as the hub genes. These genes are highly expressed in UC. IFI16 exhibited the highest diagnostic value and predictive value for response to anti-TNF therapy. The expression level of IFI16 was higher in non-responders to anti-TNF therapy. Furthermore, a cluster analysis based on genes related to the cGAS-STING pathway revealed that patients with higher gene expression exhibited elevated immune burden and inflammation levels. This study is a pioneering analysis of cGAS-STING pathway-related genes in UC. These findings provide new insights for the diagnosis of UC and the prediction of therapeutic response.

Ultimately, this study concluded that the QCR7 gene of C. albicans promoted fungal colonization by enabling adaptation to multiple carbon source as well as regulation of filamentous growth and biofilm formation. [...]they reviewed current knowledge on mechanisms of DC migration and DC-T cell interaction during pathogen infection, and highlighted remarkable studies that have exploited imaging techniques. [...]this Research Topic comprises four exemplary studies that employ various imaging techniques to explore host-pathogen interactions.

The rapid development of renewable energy sources has led to critical voltage problems in sending‐end systems, necessitating reactive power auxiliary devices and corresponding control strategies. This paper proposes a novel model predictive excitation controller for synchronous condenser, coordinated with the wind farms (WFs) without communication, to provide reactive power and mitigate voltage fluctuations. The proposed controller predicts the future behavior of the system and determines the optimal control input using model predictive control (MPC) algorithm with extended and linearized state space model of sending‐end system. An extended state observer (ESO) is designed to estimate the reactive power output of the WFs for noncommunication coordination and to account for unmeasurable disturbances, providing the estimated states to the model predictive excitation controller. The effectiveness of suppressing voltage fluctuations and providing sufficient reactive power support is verified through time‐domain simulations in MATLAB/Simulink, compared with the traditional excitation controller.

The aim of the present study was to comprehensively analyze and identify the metabolites of different varieties of raw peanut, as well as provide a reference for the utilization of different varieties of peanuts. In this study, three varieties of peanuts, namely ZKH1H, ZKH13H, and CFD, were investigated via ultrahigh-performance liquid chromatography (UPLC) and widely targeted metabolomics methods based on tandem mass spectrometry (MS) and solid-phase microextraction-gas chromatography–mass spectrometry (SPME-GC–MS). In total, 417 nonvolatile and 55 volatile substances were detected. The nonvolatile substances were classified into the following 10 categories: organic acids and derivatives (28.9%); organic oxygen compounds (21.9%); lipids and lipid-like molecules (12.6%); organoheterocyclic compounds (9.9%); nucleosides, nucleotides, and analogues (9.4%); benzenoids (7.8%); phenylpropanoids and polyketides (6.1%); organic nitrogen compounds (2.7%); lignans, neolignans, and related compounds (0.5%); and alkaloids and their derivatives (0.3%). The volatile compounds (VOCs) were classified into the following eight categories: organic oxygen compounds (24.1%); organic cyclic compounds (20.4%); organic nitrogen compounds (13%); organic acids and their derivatives (13%); lipids and lipid-like molecules (11.2%); benzenoids (11.1%); hydrocarbons (3.7%); and homogeneous non-metallic compounds (3.7%). Differentially abundant metabolites among the different peanut varieties (ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H) were investigated via multivariate statistical analyses, which identified 213, 204, and 157 nonvolatile differentially abundant metabolites, respectively, and 12, 11, and 10 volatile differentially abundant metabolites, respectively. KEGG metabolic pathway analyses of the differential non-VOCs revealed that the most significant metabolic pathways among ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H were galactose metabolism, purine metabolism, and aminoacyl-tRNA, while the nitrogen metabolism pathway was identified as a significant metabolic pathway for the VOCs. The present findings provide a theoretical foundation for the development and utilization of these three peanut species, as well as for the breeding of new peanut varieties.

Macrophages are essential for host defense, yet how parenchyma-residing macrophages detect pathogens without direct contact remains unclear. Cryptococcus neoformans is an encapsulated fungal pathogen that infects the brain. Using in situ imaging of mouse model, we showed that brain-resident microglia vigilantly detect capillary-residing C. neoformans prior to its blood–brain barrier transmigration, but are less responsive to nonencapsulated fungi or parenchyma-injected C. neoformans . Microglia migrate to and enwrap leaky capillaries harboring fungi, leading to fungal uptake but not clearance, instead promoting fungal growth. Microglial response is triggered by released capsule components, rather than the assembled capsule. In particular, glucuronoxylomannan (GXM) plays a critical role by activating endothelial cells to release nucleotides which act on microglia P2Y12. Our findings revealed a novel paradigm by which microglia detect pathogens without direct contact, offering new insights for microglia-directed antifungal therapies.