Transferring Annotator- and Instance-dependent Transition Matrix for Learning from Crowds.

Learning from crowds describes that the annotations of training data are obtained with crowd-sourcing services. Multiple annotators each complete their own small part of the annotations, where labeling mistakes that depend on annotators occur frequently. Modeling the label-noise generation process by the noise transition matrix is a powerful tool to tackle the label noise. In real-world crowd-sourcing scenarios, noise transition matrices are both annotator- and instance-dependent. However, due to the high complexity of annotator- and instance-dependent transition matrices (AIDTM), annotation sparsity, which means each annotator only labels a tiny part of instances, makes modeling AIDTM very challenging. Without prior knowledge, existing works simplify the problem by assuming the transition matrix is instance-independent or using simple parametric ways, which lose modeling generality. Motivated by this, we target a more realistic problem, estimating general AIDTM in practice. Without losing modeling generality, we parameterize AIDTM with deep neural networks. To alleviate the modeling challenge, we suppose every annotator shares its noise pattern with similar annotators, and estimate AIDTM via knowledge transfer. We hence first model the mixture of noise patterns by all annotators, and then transfer this modeling to individual annotators. Furthermore, considering that the transfer from the mixture of noise patterns to individuals may cause two annotators with highly different noise generations to perturb each other, we employ the knowledge transfer between identified neighboring annotators to calibrate the modeling. Theoretical analyses are derived to demonstrate that both the knowledge transfer from global to individuals and the knowledge transfer between neighboring individuals can effectively help mitigate the challenge of modeling general AIDTM. Experiments confirm the superiority of the proposed approach on synthetic and real-world crowd-sourcing data. The implementation is available at https://github.com/tmllab/TAIDTM.

A phase-separated protein hub modulates resistance to Fusarium head blight in wheat.

Fusarium head blight (FHB) is a devastating wheat disease. Fhb1, the most widely applied genetic locus for FHB resistance, is conferred by TaHRC of an unknown mode of action. Here, we show that TaHRC alleles distinctly drive liquid-liquid phase separation (LLPS) within a proteinaceous complex, determining FHB susceptibility or resistance. TaHRC-S (susceptible) exhibits stronger LLPS ability than TaHRC-R (resistant), and this distinction is further intensified by fungal mycotoxin deoxynivalenol, leading to opposing FHB symptoms. TaHRC recruits a protein class with intrinsic LLPS potentials, referred to as an "HRC-containing hub." TaHRC-S drives condensation of hub components, while TaHRC-R comparatively suppresses hub condensate formation. The function of TaSR45a splicing factor, a hub member, depends on TaHRC-driven condensate state, which in turn differentially directs alternative splicing, switching between susceptibility and resistance to wheat FHB. These findings reveal a mechanism for FHB spread within a spike and shed light on the roles of complex condensates in controlling plant disease.

Molecular mechanism of high glucose-induced mitochondrial DNA damage in retinal ganglion cells.

Mitochondrial DNA damage in retinal ganglion cells (RGCs) may be closely related to lesions of glaucoma. RGCs were cultured with different concentrations of glucose and grouped into 3 groups, namely normal control (NC) group, Low-Glu group, and High-Glu group. Cell viability was measured with cell counting kit-8, and cell apoptosis was measured using flow cytometry. The DNA damage was measured with comet assay, and the morphological changes of damaged mitochondria in RGCs were observed using TEM. Western blot analyzed the expression of MRE11, RAD50, and NBS1 protein. Cell viability of RGCs in Low-Glu and High-Glu groups were lower than that of NC group in 48 and 96 h. The cell apoptosis in NC group was 4.9%, the Low-Glu group was 12.2% and High-Glu group was 24.4%. The comet imaging showed that NC cells did not have tailings, but the low-Glu and high-Glu group cells had tailings, indicating that the DNA of RGCs had been damaged. TEM, mitochondrial membrane potential, ROS, mitochondrial oxygen consumption, and ATP content detection results showed that RGCs cultured with high glucose occurred mitochondrial morphology changes and dysfunction. MRE11, RAD50, and NBS1 protein expression associated with DNA damage repair pathway in High-Glu group declined compared with Low-Glu group. Mitochondrial DNA damage caused by high glucose will result in apoptosis of retinal ganglion cells in glaucoma.

Tackling Noisy Labels With Network Parameter Additive Decomposition.

Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization. The memorization effect of deep networks shows that although the networks have the ability to memorize all noisy data, they would first memorize clean training data, and then gradually memorize mislabeled training data. A simple and effective method that exploits the memorization effect to combat noisy labels is early stopping. However, early stopping cannot distinguish the memorization of clean data and mislabeled data, resulting in the network still inevitably overfitting mislabeled data in the early training stage. In this paper, to decouple the memorization of clean data and mislabeled data, and further reduce the side effect of mislabeled data, we perform additive decomposition on network parameters. Namely, all parameters are additively decomposed into two groups, i.e., parameters w are decomposed as [Formula: see text]. Afterward, the parameters [Formula: see text] are considered to memorize clean data, while the parameters [Formula: see text] are considered to memorize mislabeled data. Benefiting from the memorization effect, the updates of the parameters [Formula: see text] are encouraged to fully memorize clean data in early training, and then discouraged with the increase of training epochs to reduce interference of mislabeled data. The updates of the parameters [Formula: see text] are the opposite. In testing, only the parameters [Formula: see text] are employed to enhance generalization. Extensive experiments on both simulated and real-world benchmarks confirm the superior performance of our method.

P-aminobenzoic acid promotes retinal regeneration through activation of Ascl1a in zebrafish.

JOURNAL/nrgr/04.03/01300535-202408000-00040/figure1/v/2023-12-16T180322Z/r/image-tiff The retina of zebrafish can regenerate completely after injury. Multiple studies have demonstrated that metabolic alterations occur during retinal damage; however to date no study has identified a link between metabolites and retinal regeneration of zebrafish. Here, we performed an unbiased metabolome sequencing in the N-methyl-D-aspartic acid-damaged retinas of zebrafish to demonstrate the metabolomic mechanism of retinal regeneration. Among the differentially-expressed metabolites, we found a significant decrease in p-aminobenzoic acid in the N-methyl-D-aspartic acid-damaged retinas of zebrafish. Then, we investigated the role of p-aminobenzoic acid in retinal regeneration in adult zebrafish. Importantly, p-aminobenzoic acid activated Achaetescute complex-like 1a expression, thereby promoting Müller glia reprogramming and division, as well as Müller glia-derived progenitor cell proliferation. Finally, we eliminated folic acid and inflammation as downstream effectors of PABA and demonstrated that PABA had little effect on Müller glia distribution. Taken together, these findings show that PABA contributes to retinal regeneration through activation of Achaetescute complex-like 1a expression in the N-methyl-D-aspartic acid-damaged retinas of zebrafish.

Regularly Truncated M-Estimators for Learning With Noisy Labels.

The sample selection approach is very popular in learning with noisy labels. As deep networks "learn pattern first", prior methods built on sample selection share a similar training procedure: the small-loss examples can be regarded as clean examples and used for helping generalization, while the large-loss examples are treated as mislabeled ones and excluded from network parameter updates. However, such a procedure is arguably debatable from two folds: (a) it does not consider the bad influence of noisy labels in selected small-loss examples; (b) it does not make good use of the discarded large-loss examples, which may be clean or have meaningful information for generalization. In this paper, we propose regularly truncated M-estimators (RTME) to address the above two issues simultaneously. Specifically, RTME can alternately switch modes between truncated M-estimators and original M-estimators. The former can adaptively select small-losses examples without knowing the noise rate and reduce the side-effects of noisy labels in them. The latter makes the possibly clean examples but with large losses involved to help generalization. Theoretically, we demonstrate that our strategies are label-noise-tolerant. Empirically, comprehensive experimental results show that our method can outperform multiple baselines and is robust to broad noise types and levels.

Multi-genome comprehensive identification of SSR/SV and development of molecular markers database to serve Sorghum bicolor (L.) breeding.

BACKGROUND: As an important food and cash crop, identification of DNA molecular markers is of great significance for molecular marker-assisted breeding of Sorghum (Sorghum bicolor (L.) moench). Although some sorghum-related mutation databases have been published, the special SSR and SV databases still need to be constructed and updated. RESULTS: In this study, the quality of 18 different sorghum genomes was evaluated, and two genomes were assembled at chromosome level. Through the identification and comparative analysis of SSR loci in these genomes, the distribution characteristics of SSR in the above sorghum genomes were initially revealed. At the same time, five representative reference genomes were selected to identify the structural variation of sorghum. Finally, a convenient SSR/SV database of sorghum was constructed by integrating the above results ( http://www.sorghum.top:8079/ ; http://43.154.129.150:8079/ ; http://47.106.184.91:8079/ ). Users can query the information of related sites and primer pairs. CONCLUSIONS: Anyway, our research provides convenience for sorghum researchers and will play an active role in sorghum molecular marker-assisted breeding.

The accuracy of intraocular lens power calculation formulas based on artificial intelligence in highly myopic eyes: a systematic review and network meta-analysis.

Objective: To systematically compare and rank the accuracy of AI-based intraocular lens (IOL) power calculation formulas and traditional IOL formulas in highly myopic eyes. Methods: We screened PubMed, Web of Science, Embase, and Cochrane Library databases for studies published from inception to April 2023. The following outcome data were collected: mean absolute error (MAE), percentage of eyes with a refractive prediction error (PE) within ±0.25, ±0.50, and ±1.00 diopters (D), and median absolute error (MedAE). The network meta-analysis was conducted by R 4.3.0 and STATA 17.0. Results: Twelve studies involving 2,430 adult myopic eyes (with axial lengths >26.0 mm) that underwent uncomplicated cataract surgery with mono-focal IOL implantation were included. The network meta-analysis of 21 formulas showed that the top three AI-based formulas, as per the surface under the cumulative ranking curve (SUCRA) values, were XGBoost, Hill-RBF, and Kane. The three formulas had the lowest MedAE and were more accurate than traditional vergence formulas, such as SRK/T, Holladay 1, Holladay 2, Haigis, and Hoffer Q regarding MAE, percentage of eyes with PE within ±0.25, ±0.50, and ±1.00 D. Conclusions: The top AI-based formulas for calculating IOL power in highly myopic eyes were XGBoost, Hill-RBF, and Kane. They were significantly more accurate than traditional vergence formulas and ranked better than formulas with Wang-Koch AL modifications or newer generations of formulas such as Barrett and Olsen. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022335969.

Phosphoinositide 3-kinase as a therapeutic target in angiogenic disease.

Phosphoinositide 3-kinases (PI3Ks) generate lipids that control multitudinous intracellular cell signaling events which participate in cell survival and proliferation. In addition, PI3K signaling also contributes to metabolism, immunity, angiogenesis and cardiovascular homeostasis, and many diseases. The diverse actions of PI3K stem from the existence of their various isoforms and a variety of protein effectors. Hence, PI3K isoform-specific inhibitors have already achieved a wonderful effect on treating cancer. Herein, we summarize the molecular mechanism of PI3K inhibitors in preventing the permeability of vessels and neovascularization. Additionally, we briefly illustrate how PI3K signaling modulates blood vessel growth and discuss the different roles that PI3K isoforms play in angiogenesis.

Endoplasmic reticulum stress: molecular mechanism and therapeutic targets.

The endoplasmic reticulum (ER) functions as a quality-control organelle for protein homeostasis, or "proteostasis". The protein quality control systems involve ER-associated degradation, protein chaperons, and autophagy. ER stress is activated when proteostasis is broken with an accumulation of misfolded and unfolded proteins in the ER. ER stress activates an adaptive unfolded protein response to restore proteostasis by initiating protein kinase R-like ER kinase, activating transcription factor 6, and inositol requiring enzyme 1. ER stress is multifaceted, and acts on aspects at the epigenetic level, including transcription and protein processing. Accumulated data indicates its key role in protein homeostasis and other diverse functions involved in various ocular diseases, such as glaucoma, diabetic retinopathy, age-related macular degeneration, retinitis pigmentosa, achromatopsia, cataracts, ocular tumors, ocular surface diseases, and myopia. This review summarizes the molecular mechanisms underlying the aforementioned ocular diseases from an ER stress perspective. Drugs (chemicals, neurotrophic factors, and nanoparticles), gene therapy, and stem cell therapy are used to treat ocular diseases by alleviating ER stress. We delineate the advancement of therapy targeting ER stress to provide new treatment strategies for ocular diseases.

The correlation between primary open-angle glaucoma (POAG) and gut microbiota: a pilot study towards predictive, preventive, and personalized medicine.

Background: Glaucoma is the leading cause of irreversible blindness worldwide. Emerged evidence has shown that glaucoma is considered an immune system related disorder. The gut is the largest immune organ in the human body and the gut microbiota (GM) plays an irreversible role in maintaining immune homeostasis. But, how the GM influences glaucoma remains unrevealed. This study aimed at investigating the key molecules/pathways mediating the GM and the glaucoma to provide new biomarkers for future predictive, preventive, and personalized medicine. Methods: Datasets from the primary open-angle glaucoma (POAG) patients (GSE138125) and datasets for target genes of GM/GM metabolites were downloaded from a public database. For GSE138125, the differentially expressed genes (DEGs) between healthy and POAG samples were identified. And the online Venn diagram tool was used to obtain the DEGs from POAG related to GM. After which GM-related DEGs were analyzed by correlation analysis, pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. Human trabecular meshwork cells were used for validation, and the mRNA level of hub genes was verified by quantitative real-time polymerase chain reaction (RT-qPCR) in the in vitro glaucoma model. Results: A total of 16 GM-related DEGs in POAG were identified from the above 2 datasets (9 upregulated genes and 7 downregulated genes). Pathway enrichment analysis indicated that these genes are mostly enriched in immune regulation especially macrophages-related pathways. Then 6 hub genes were identified by PPI network analysis and construction of key modules. Finally, RT-qPCR confirmed that the expression of the hub genes in the in vitro glaucoma model was consistent with the results of bioinformatics analysis of the mRNA chip. Conclusion: This bioinformatic study elucidates NFKB1, IL18, KITLG, TLR9, FKBP2, and HDAC4 as hub genes for POAG and GM regulation. Immune response modulated by macrophages plays an important role in POAG and may be potential targets for future predictive, preventive, and personalized diagnosis and treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00336-2.

A Modified Single-Armed Suture Technique for Traumatic Cyclodialysis Cleft with Vitreoretinal Injury.

Our aim was to assess the therapeutic efficacy of a modified single-arm suture technique on traumatic cyclodialysis cleft with vitreoretinal injury. The procedure involved fixing a detached ciliary body using a single-armed 10-0 polypropylene suture under the assistance of a 29-gauge needle. Patients with a traumatic cyclodialysis cleft combined with an anterior and posterior segment injury who underwent modified internal cyclopexy together with vitreoretinal surgery were enrolled in this study. Ultrasound biomicroscopy (UBM) was used to diagnose and evaluate the cyclodialysis and anterior segment injury. B-scan ultrasonography was performed to assess the condition of the vitreous, retina and choroid. The surgical time and successful rate for repairing the cyclodialysis cleft were recorded. Preoperative and postoperative best-corrected visual acuity (BCVA), and intraocular pressure (IOP) were documented for assessment. The study included 20 eyes. The extent of the cyclodialysis cleft was from 30° to 360°. Besides a traumatic cyclodialysis cleft, the included cases also combined this with vitreous hemorrhages, retinal detachment, macular holes, choroid avulsion, and suprachoroidal hemorrhage. All the clefts were anatomically closed in one surgery. The average surgical time for fixing the cyclodialysis cleft was 2.68 ± 0.54 min/30° cleft. A significant improvement in LogMAR BCVA was observed from 2.94 ± 0.93 preoperatively to 1.81 ± 1.11 at the 6-month follow-up. IOP was elevated from 10.90 ± 6.18 mmHg preoperatively to 14.45 ± 2.35 mmHg at the 6-month follow-up. The modified single-armed suture technique was proved to be an effective method to fix the traumatic cyclodialysis cleft, which could facilitate the use of the procedure to repair chorioretinal disorders. It improved the BCVA and maintained the IOP with less postoperative complications.

The Epidemiology and Clinical Characteristics of Fungemia in a Tertiary Hospital in Southern China: A 6-Year Retrospective Study.

Knowledge of the epidemiology and clinical characteristics of fungemia in southern China is limited. We conducted a six-year retrospective descriptive study to analyze the epidemiological and clinical characteristics of fungemia at the largest tertiary hospital in Guangxi, southern China. Data were obtained from the laboratory registry of patients with fungemia between January 2014 and December 2019. Demographic characteristics, underlying medical conditions, and outcomes for each case were analyzed. A total of 455 patients with fungemia were identified. Unexpectedly, Talaromyces marneffei (T. marneffei) was the most frequently isolated agent causing fungemia in the region (149/475, 31.4%), and Candida albicans (C. albicans) was the most commonly isolated Candida spp. (100/475, 21.1%). We identified that more than 70% of talaromycosis fungemia developed in AIDS patients, whereas candidemia was most commonly associated with a history of recent surgery. Notably, the total mortality rate of fungemia and the mortality rate in patients with T. marneffei and Cryptococcus neoformans (C. neoformans) fungemia were significantly higher in HIV-uninfected patients than in HIV-infected patients. In conclusion, the clinical pattern of fungemia in Guangxi is different from that in previous studies. Our study may provide new guidance for the early diagnosis and prompt treatment of fungemia in similar geographic regions.

Genome-wide identification of the PYL gene family of tea plants (Camellia sinensis) revealed its expression profiles under different stress and tissues.

BACKGROUND: PYL (Pyrabactin resistance 1-like) protein is a receptor of abscisic acid (ABA), which plays an important role in ABA signaling and influences plant growth and development and stress response. However, studies on PYL gene family in tea plants have not been reported. RESULTS: In this study, we identified 20 PYL genes from the reference genome of tea plant ('Shuchazao'). Phylogeny analysis indicated that PYLs from tea and other plant species were clustered into seven groups. The promoter region of PYL genes contains a large number of cis-elements related to hormones and stresses. A large number of PYL genes responding to stress were found by analyzing the expression levels of abiotic stress and biotic stress transcriptome data. For example, CSS0047272.1 were up-regulated by drought stress, and CSS0027597.1 could respond to both anthracnose disease and geometrid feeding treatments. In addition, 10 PYL genes related to growth and development were verified by RT-qPCR and their tissue expression characteristics were revealed. CONCLUSIONS: Our results provided a comprehensive characteristic of the PYL gene family in tea plants and provided an important clue for further exploring its functions in the growth and development, and resistance to stress of tea plants.

Comparative transcriptomics identifies the key in planta-expressed genes of Fusarium graminearum during infection of wheat varieties.

Fusarium head blight (FHB), caused mainly by the fungus Fusarium graminearum, is one of the most devastating diseases in wheat, which reduces the yield and quality of grain. Fusarium graminearum infection of wheat cells triggers dynamic changes of gene expression in both F. graminearum and wheat, leading to molecular interactions between pathogen and host. The wheat plant in turn activates immune signaling or host defense pathways against FHB. However, the mechanisms by which F. graminearum infects wheat varieties with different levels of host resistance are largely limited. In this study, we conducted a comparative analysis of the F. graminearum transcriptome in planta during the infection of susceptible and resistant wheat varieties at three timepoints. A total of 6,106 F. graminearum genes including those functioning in cell wall degradation, synthesis of secondary metabolites, virulence, and pathogenicity were identified during the infection of different hosts, which were regulated by hosts with different genetic backgrounds. Genes enriched with metabolism of host cell wall components and defense response processes were specifically dynamic during the infection with different hosts. Our study also identified F. graminearum genes that were specifically suppressed by signals derived from the resistant plant host. These genes may represent direct targets of the plant defense against infection by this fungus. Briefly, we generated databases of in planta-expressed genes of F. graminearum during infection of two different FHB resistance level wheat varieties, highlighted their dynamic expression patterns and functions of virulence, invasion, defense response, metabolism, and effector signaling, providing valuable insight into the interactions between F. graminearum and susceptible/resistant wheat varieties.

Translocator protein 18 kDa regulates retinal neuron apoptosis and pyroptosis in glaucoma.

Glaucoma is the leading cause of blindness worldwide. However, our insufficient understanding of the pathogenesis of glaucoma has limited the development of effective treatments. Because recent research has highlighted the importance of non-coding RNAs (ncRNAs) in various diseases, we investigated their roles in glaucoma. Specifically, we detected expression changes of ncRNAs in cell and animal models of acute glaucoma. Further analysis revealed that the Ier2/miR-1839/TSPO axis was critical to cell loss and retinal damage. The knockdown of Ier2, the overexpression of miR-1839, and the silencing of TSPO effectively prevented retinal damage and cell loss. Furthermore, we found that the Ier2/miR-1839/TSPO axis regulated the pyroptosis and apoptosis of retinal neurons through the NLRP3/caspase1/GSDMD, cleaved-caspase3 pathways. In addition to high expression in the retina, TSPO expression was found to be significantly higher in the dorsal lateral geniculate nucleus (DLG) of the brain in the pathologically high intraocular pressure (ph-IOP) rat model, as well as in the peripheral blood mononuclear cells (PBMCs) of glaucoma patients with high IOP. These results indicate that TSPO, which is regulated by Ier2/miR-1839, plays an important role in the pathogenesis of glaucoma, and this study provides a theoretical basis and a new target for the diagnosis and treatment of glaucoma.

Pathologically high intraocular pressure induces mitochondrial dysfunction through Drp1 and leads to retinal ganglion cell PANoptosis in glaucoma.

Glaucoma is a common neurodegenerative disease characterized by progressive retinal ganglion cell (RGC) loss and visual field defects. Pathologically high intraocular pressure (ph-IOP) is an important risk factor for glaucoma, and it triggers molecularly distinct cascades that control RGC death and axonal degeneration. Dynamin-related protein 1 (Drp1)-mediated abnormalities in mitochondrial dynamics are involved in glaucoma pathogenesis; however, little is known about the precise pathways that regulate RGC injury and death. Here, we aimed to investigate the role of the ERK1/2-Drp1-reactive oxygen species (ROS) axis in RGC death and the relationship between Drp1-mediated mitochondrial dynamics and PANoptosis in ph-IOP injury. Our results suggest that inhibiting the ERK1/2-Drp1-ROS pathway is a potential therapeutic strategy for treating ph-IOP-induced injuries. Furthermore, inhibiting Drp1 can regulate RGC PANoptosis by modulating caspase3-dependent, nucleotide-binding oligomerization domain-like receptor-containing pyrin domain 3(NLRP3)-dependent, and receptor-interacting protein (RIP)-dependent pathways in the ph-IOP model. Overall, our findings provide new insights into possible protective interventions that could regulate mitochondrial dynamics to improve RGC survival.

New insight of metabolomics in ocular diseases in the context of 3P medicine.

Metabolomics refers to the high-through untargeted or targeted screening of metabolites in biofluids, cells, and tissues. Metabolome reflects the functional states of cells and organs of an individual, influenced by genes, RNA, proteins, and environment. Metabolomic analyses help to understand the interaction between metabolism and phenotype and reveal biomarkers for diseases. Advanced ocular diseases can lead to vision loss and blindness, reducing patients' quality of life and aggravating socio-economic burden. Contextually, the transition from reactive medicine to the predictive, preventive, and personalized (PPPM / 3P) medicine is needed. Clinicians and researchers dedicate a lot of efforts to explore effective ways for disease prevention, biomarkers for disease prediction, and personalized treatments, by taking advantages of metabolomics. In this way, metabolomics has great clinical utility in the primary and secondary care. In this review, we summarized much progress achieved by applying metabolomics to ocular diseases and pointed out potential biomarkers and metabolic pathways involved to promote 3P medicine approach in healthcare.

Investigating the Resistance Mechanism of Wheat Varieties to Fusarium Head Blight Using Comparative Metabolomics.

Fusarium head blight (FHB) is primarily caused by Fusarium graminearum and severely reduces wheat yield, causing mycotoxin contamination in grains and derived products. F. graminearum-secreted chemical toxins stably accumulate in plant cells, disturbing host metabolic homeostasis. We determined the potential mechanisms underlying FHB resistance and susceptibility in wheat. Three representative wheat varieties (Sumai 3, Yangmai 158, and Annong 8455) were inoculated with F. graminearum and their metabolite changes were assessed and compared. In total, 365 differentiated metabolites were successfully identified. Amino acids and derivatives, carbohydrates, flavonoids, hydroxycinnamate derivatives, lipids, and nucleotides constituted the major changes in response to fungal infection. Changes in defense-associated metabolites, such as flavonoids and hydroxycinnamate derivatives, were dynamic and differed among the varieties. Nucleotide and amino acid metabolism and the tricarboxylic acid cycle were more active in the highly and moderately resistant varieties than in the highly susceptible variety. We demonstrated that two plant-derived metabolites, phenylalanine and malate, significantly suppressed F. graminearum growth. The genes encoding the biosynthetic enzymes for these two metabolites were upregulated in wheat spike during F. graminearum infection. Thus, our findings uncovered the metabolic basis of resistance and susceptibility of wheat to F. graminearum and provided insights into engineering metabolic pathways to enhance FHB resistance in wheat.