Biomedical subjects

Tong Wang

Publications and source records attributed to Tong Wang.

15 recordsLinked to original sources

PubMed2026

Bacterial motility in rhizosphere colonization: mechanisms, constraints, and implications for microbial inoculants.

Although the potential of microbial inoculants for sustainable agriculture and environmental restoration has been widely recognized, their field performance remains highly variable and often unpredictable. Current research and development frameworks for microbial inoculants primarily focus on their plant growth-promoting functions and metabolic traits, often overlooking the ecological processes that determine whether introduced strains can successfully disperse, access, and establish within the rhizosphere. Increasing evidence suggests that successful dispersal and establishment cannot be assumed in the highly heterogeneous conditions of soil systems. Here, we summarize the key mechanisms underlying bacterial motility and discuss its role within the broader framework of microbial dispersal, highlighting how motility-mediated processes contribute to rhizosphere colonization. We propose that bacterial motility represents a key mechanistic determinant of biofertilizer efficacy. Its role extends beyond the ability of inoculant strains to physically reach the rhizosphere, encompassing competitive colonization on the root surface, long-term persistence, and the ability to respond to dynamic root-derived chemical gradients associated with newly developing root tissues. We argue that inoculant motility should be elevated from a passive descriptive trait to a core design parameter that can be systematically incorporated and regulated during the development and optimization of microbial inoculants. We outline a multi-tiered strategic framework for next-generation biofertilizer engineering that integrates strain selection, community design, motility regulation, and deployment strategies, thereby unlocking the full potential of synthetic microbial consortia for sustainable agriculture, ecosystem restoration, and climate change mitigation.

Biofertilizer↗

PubMed2026

ToxiVerse: chemical bioprofiling, toxicity data sharing and customizable predictive modeling.

MOTIVATION: Chemical toxicity assessment is critical for drug development and environmental safety. Computational models have emerged as a promising alternative to animal testing and now play a significant role in efficiently evaluating new chemicals. To address the urgent need for user-friendly machine learning tools in computational toxicology, we developed ToxiVerse, a public web-based platform. RESULTS: ToxiVerse provides automatic chemical bioprofiling, curated toxicity datasets, and a predictive modeling interface designed for researchers who lack programming expertise. The platform comprises three integrated modules: (i) Bioprofiler, which provides chemical descriptors by combining chemical-bioactivity data from PubChem assays with a machine learning-based data gap-filling procedure; (ii) Database, which hosts ∼50 000 curated chemicals covering diverse toxicity endpoints; and (iii) Cheminformatics, which enables dataset upload, chemical curation, and automatic generation of quantitative structure-activity relationship models for toxicity prediction. AVAILABILITY: The tool is accessible at www.toxiverse.com, and source code is available at https://github.com/zhu-research-group/toxiverse.

Quantitative Structure-Activity Relationship↗

PubMed2026

hnRNPC facilitates coronavirus replication by directly binding the frameshift-stimulatory element of viral genomic RNA.

Translation of key viral replicative proteins in coronaviruses requires a programmed -1 ribosomal frameshifting (-1 PRF) event controlled by the viral frameshift-stimulatory element (FSE). Although previous studies have analyzed host factor dependencies of coronaviruses, how host cellular factors alter -1 PRF efficiency and affect viral replication remains poorly understood. Here, using RNA pull-down combined with LC-MS/MS analysis, we identified heterogeneous nuclear ribonucleoprotein C (hnRNPC) as a major interacting protein of FSE RNA. Coronavirus infection triggers hnRNPC mRNA decay, alters hnRNPC protein levels, and induces its cytoplasmic relocalization, where it appears to bind directly to FSE RNA through residues Asn7 and Asn83. This binding is associated with increased -1 PRF efficiency and may facilitate coronavirus replication. Deletion mapping analysis shows that hnRNPC preferentially binds U-rich regions of the FSE RNA. Finally, we demonstrated that the small molecule Elbasvir directly binds hnRNPC, disrupting the interaction between hnRNPC and FSE RNA and inhibiting coronavirus replication by decreasing -1 PRF efficiency. Collectively, our study identifies hnRNPC as a key host cofactor for coronaviruses and provides a novel target for broad-spectrum antiviral drug development.

RNA, Viral↗

PubMed2026

Integrating structure and experimental data annotations with computational modeling framework for predicting micro-nanoplastics toxicities.

The wide use of plastic materials leads to increased emissions of micro-nanoplastics (MNPs) into the environment, raising significant concerns about their impact on human health. Traditional experimental approaches for assessing MNPs toxicity are costly, time-consuming, and there are no experimental protocols that are universally acceptable. Computational modeling using machine learning (ML) approaches provides an efficient alternative to MNP toxicity assessment. However, most modeling studies of MNPs are limited due to the lack of high-quality data and there are few previous modeling studies considering complex structures of MNPs for model training. To address this challenge, we constructed three MNP datasets with popular toxicity endpoints from various resources and used nanostructure annotation techniques to create virtual MNPs (vMNPs) for all MNP structures. The MNP structures were digitalized from annotated vMNPs, and geometrical descriptors were calculated using the Delaunay Tessellation approach. Moreover, important experimental information, such as concentrations and cell lines, were transformed into extra training variables. Partial least squares regression (PLSR) models were built using both experimental and geometrical descriptors and validated through a leave-one-out cross validation procedure. The resulting models showed reasonable performance in predicting toxicity potentials of MNPs for the three endpoints in the present datasets. Moreover, an additional library of vMNPs with their predicted properties and bioactivities was constructed, directing further research of new MNPs. This study provides three novel ML models for MNPs by integrating geometrical and experimental descriptors, which have the potential to assess new MNPs for their toxicity. The modeling strategy developed in this study can be easily expanded to model other MNP toxicity endpoints and create promising new models for MNP toxicity assessments.

Data annotation↗

PubMed2026

High-frequency contralesional dorsal premotor cortex and low-frequency contralesional primary motor cortex rTMS in subacute stroke with severe upper limb impairment: comparable motor outcomes and differential regional degree centrality changes.

BACKGROUND: The contralesional dorsal premotor cortex has been proposed as a potential neuromodulatory target for patients with severe upper limb impairment due to subacute ischemic stroke. This proof-of-concept study aimed to compare behavioral outcomes and resting-state neuroimaging findings between high-frequency repetitive transcranial magnetic stimulation (rTMS) over the contralesional dorsal premotor cortex and guideline-supported low-frequency stimulation over the contralesional primary motor cortex. METHODS: In this randomized trial, 46 patients with severe upper limb impairment in the subacute stage after ischemic stroke were randomly assigned to receive either high-frequency rTMS over the contralesional dorsal premotor cortex or low-frequency rTMS over the contralesional primary motor cortex. Low-frequency stimulation over the contralesional primary motor cortex served as an evidence-supported active comparator for poststroke upper limb motor recovery. Stimulation was administered five times per week for two weeks using magnetic resonance imaging-guided neuronavigation. All participants received concurrent standard rehabilitation therapy. The primary outcome was the Fugl-Meyer Assessment for Upper Extremity. Secondary outcomes included the Arm Subscore of the Motricity Index, the Hong Kong version of the Functional Test for the Hemiplegic Upper Extremity, the Modified Barthel Index, and resting-state functional magnetic resonance imaging-derived degree centrality. RESULTS: Both groups showed significant improvements in the primary and secondary behavioral measures (p < 0.01), with no significant between-group differences in the magnitude of change (p > 0.05). In neuroimaging analyses, patients receiving high-frequency rTMS over the contralesional dorsal premotor cortex showed significantly greater degree centrality changes in the ipsilesional middle occipital gyrus, contralesional medial superior frontal gyrus, and contralesional middle frontal gyrus than those receiving low-frequency rTMS over the contralesional primary motor cortex (p < 0.05). Within the high-frequency stimulation group, degree centrality changes in the ipsilesional middle occipital gyrus were positively correlated with improvements in the Fugl-Meyer Assessment for Upper Extremity (r = 0.619, false discovery rate-corrected p = 0.018). CONCLUSIONS: High-frequency rTMS over the contralesional dorsal premotor cortex produced behavioral improvements comparable to guideline-supported low-frequency rTMS over the contralesional primary motor cortex, without establishing superiority or formal non-inferiority. Exploratory neuroimaging analyses showed greater degree centrality changes in the ipsilesional middle occipital gyrus after high-frequency premotor stimulation, and these changes correlated with upper-limb motor improvement. These findings support further investigation of contralesional dorsal premotor cortex-targeted high-frequency rTMS for severe subacute post-stroke upper limb impairment. REGISTRATION: URL: http://www.chictr.org.cn; Unique identifier: ChiCTR2000038049.

Humans↗

PubMed2026

Necroptosis in alveolar epithelium orchestrates lung ischemia-reperfusion injury: a multi-omics study.

BACKGROUND: Lung ischemia-reperfusion injury (LIRI) is a leading cause of early morbidity and mortality following lung transplantation and other cardiopulmonary procedures. It is characterized by acute sterile inflammation driven by regulated cell death (RCD). While various RCD modalities, including apoptosis, necroptosis, pyroptosis, and ferroptosis, have been implicated in lung injury, their relative contributions and distinct activation patterns in LIRI remain poorly defined. METHODS: We employed an integrated multi-omics approach combining transcriptomics and proteomics with histological and functional validations in a murine hilar clamping model of LIRI. Key findings were further corroborated using single-cell RNA sequencing (scRNA-seq) data from human lung transplant recipients. The functional role of necroptosis was validated using pharmacological inhibitors (Nec-1, GSK'872) and Mlkl-deficient (Mlkl-/-) mice. RESULTS: LIRI triggered acute, time-dependent lung injury peaking within 24 h of reperfusion. Although transcriptomic profiling suggested broad activation of multiple RCD pathways, proteomic and biochemical analyses revealed a distinct landscape in our experimental setting: markers of apoptosis, pyroptosis, and ferroptosis were either downregulated or showed no significant positive correlation with injury severity and inflammatory peaks. In contrast, the necroptotic pathway emerged as a highly activated modality. Specifically, necroptosis, marked by phosphorylated RIPK1, RIPK3, and MLKL, was localized primarily in alveolar epithelial cells, correlated strongly with cytokine release and histological lung injury, and preceded the inflammatory response. Pharmacological inhibition or genetic ablation of necroptosis significantly attenuated tissue damage and inflammation. This pronounced necroptotic signature appeared distinct from the broad multi-pathway activation observed in lipopolysaccharide (LPS)-induced lung injury. Translational analysis of human scRNA-seq data further confirmed the selective upregulation of necroptosis signatures in alveolar type 2 (AT2) cells following lung transplantation. CONCLUSION: Our multi-omics analysis identifies necroptosis, particularly in alveolar epithelial cells, as a critical driver of sterile inflammation and tissue injury in the early phase of LIRI. Targeting alveolar epithelial necroptosis may represent a precise and promising therapeutic strategy for lung transplantation and ischemia-reperfusion-associated pulmonary disorders.

Animals↗

PubMed2026

Advances in the diagnosis and classification of B-ALL: comparative insights from updated guidelines.

Accurate molecular classification is essential for diagnosis, risk stratification, and treatment selection in B-cell lymphoblastic leukemia (B-ALL). In this study, we performed a comprehensive, real-world reclassification of 1015 consecutively diagnosed B-ALL patients using the fifth edition of the World Health Organization Classification of Haematolymphoid Tumours (WHO-HAEM5) and the International Consensus Classification (ICC). An integrative genomic strategy that combined whole transcriptome sequencing, fusion detection, mutational analysis, and cytogenetics enabled reclassification according to both the WHO-HAEM5 and ICC frameworks, thereby substantially reducing the proportion of unclassifiable B-ALL from 41.9% (2016 WHO revision [WHO-HAEM4R]) to 15.9% (WHO-HAEM5) and 11.9% (ICC). Distinct clinical and prognostic features were identified across newly defined subtypes. Multivariable analysis confirmed that this genomic classification is a robust, independent predictor of survival after adjusting for age, minimal residual disease status, and transplant intervention. Specifically, HLF-rearranged and MEF2D-rearranged B-ALL conferred a persistently poor prognosis across all age groups despite allogeneic hematopoietic stem cell transplantation, highlighting an urgent need for novel therapeutic strategies. Gene expression profiling resolved cryptic subtypes, including ETV6::RUNX1-like, ZNF384-rearranged-like, and BCR::ABL1-like B-ALL, and uncovered diagnostic ambiguity in patients with concurrent lesions. In addition, we report emerging high-risk groups, including IDH1/2- and ZEB2 Q1072-mutated B-ALL, that may warrant recognition as distinct molecular entities. Our findings demonstrate the clinical use of integrative transcriptomic profiling in refining B-ALL taxonomy in guiding risk-adapted therapies and informing future revisions of diagnostic standards. This study supports the incorporation of high-throughput molecular diagnostics into routine leukemia classification and precision treatment planning.

Humans↗

PubMed2026

Microbiota-gut-muscle axis shapes fish muscle texture by regulating collagen synthesis.

BACKGROUND: Increasing studies have emphasized the communication network between the gut microbiome and host organs, revealing that such interactions significantly influence host physiological performances. However, whether a gut-muscle axis exists to regulate muscle quality in animal production is unknown. RESULTS: In two independent cohorts, the muscle hardness of tilapia subjected to a long-term faba bean diet exhibited significant inter-individual variation. RNA-Seq analyses of the high-hardness (H) and low-hardness (L) groups pointed to collagen-based extracellular matrix as a possible factor driving muscle hardness development. Transplantation of gut microbiota from the H donor resulted in enhanced collagen synthesis in gnotobiotic zebrafish. Muscular collagen deposition was featured with an increased abundance of gut Cetobacterium. Gnotobiotic models colonized with live C. somerae exhibited enhanced collagen synthesis. Integrated analyses of microbiome function, bacterial genome, and metabolic profiles identified acetate as a key effector of C. somerae. Acetate incubation upregulated collagen I expression in TGF-β-activated fibroblasts in an acetylation-dependent manner. Mechanistically, acetate promoted the acetylation of SMAD2/3, enhancing its nuclear transport and stability, which ultimately increased collagen expression. An acetate-supplemented feeding experiment corroborated these findings. CONCLUSION: The comprehensive results provided evidences that gut microbes regulated tilapia muscle texture through SMAD2/3 acetylation-driven collagen synthesis. This study expands our understanding of the multifaceted role of the gut-muscle axis in muscle physiology. Furthermore, our findings highlight that targeting gut microbiota and the downstream collagen synthesis pathway could be promising for manipulating muscle quality in animal production. Video Abstract.

Animals↗

PubMed2026

Multistrategy metabolic engineering of Talaromyces pinophilus for α-amylase production from lignocellulosic biomass.

Filamentous fungi are important hosts for industrial enzyme production. Growing demand for α-amylase has increased reliance on food-derived carbon substrates, necessitating fungal strains that efficiently utilize nongrain biomass. In this study, Talaromyces pinophilus Y117 was metabolically engineered to produce α-amylase from lignocellulosic biomass. A strong cellobiohydrolase I gene (cbh1) promoter (Pcbh1Tru) was identified to drive expression. Multiple rounds of multilocus integration of the α-amylase gene were performed using homologous multicopy genomic sequences as recombination arms with a Cre/loxP-based recyclable selection system, yielding the multicopy strain Tp4, which achieved 4124.5 U/mL α-amylase activity in shake-flask fermentation with corncob powder as the sole carbon source. To minimize enzyme degradation, the protease gene 8538 was deleted using the Cre/lox2272 system, generating Tp4Δp. This strain showed a 50% increase in shake-flask α-amylase activity (6208.4 U/mL). In 3-L bioreactor cultivation, Tp4Δp exhibited excellent production performance, achieving 26 712.2 U/mL α-amylase activity. When corncob powder was used as the sole substrate, the cellulose and hemicellulose degradation rates reached 90.00% and 70.01%, respectively, and the enzyme yield reached 213 697.5 U per gram of corncob powder. This engineered strain demonstrates strong potential for industrial applications. The synthesis-degradation synergistic optimization strategy provides a practical approach for engineering filamentous fungal cell factories to produce enzymes directly from lignocellulosic biomass. One sentence summary Metabolic engineering of Talaromyces pinophilus through promoter optimization, multicopy integration, and protease deletion enables efficient α-amylase production from lignocellulosic biomass, achieving 26 712 U/mL in bioreactor fermentation.

Talaromyces↗

PubMed2025

Cetobacterium somerae ZNN-1 promotes goblet cell differentiation through glutamine-mediated Notch signaling suppression.

INTRODUCTION: The gut microbiota acts as a crucial mediator in the interaction between the diet components and the host metabolism. However, the molecular mechanism by which the gut microbiota adapts to dietary components and subsequently regulates host physiological responses remains unclear. OBJECTIVES: This study aimed to investigate the response of gut microbiota to a plant-based protein diet (soybean meal, SM) and the effects of gut microbiota on host intestinal barrier function, along with the underlying mechanisms in a fish model. METHODS: Histopathological examination, and transepithelial electrical resistance test were used to evaluate the effects of Cetobacterium somerae on intestinal barrier function. Potential molecular mechanisms were validated by integrating whole-genome sequencing, microbiota composition sequencing, transcriptomics, and metabolomics, and utilizing in vitro cell models and mouse-derived organoid models. RESULTS: The results revealed that the SM diet significantly increased the abundance of Cetobacterium somerae in fish. Administration of C.somerae ZNN-1, a dominant strain isolated from the intestine of fish fed with the SM diet, enhanced the intestinal barrier function, particularly increasing the number of goblet cells in the intestine. Whole genome analysis of C. somerae ZNN-1 showed carbohydrate metabolism-associated genes were the most abundant in its metabolic modules. C.somerae ZNN-1 supplementation significantly inhibited the Notch signaling pathway in fish intestine. Metabolomics analysis revealed that administration of C.somerae ZNN-1 increased the glutamine level in fish gut. In vitro experiments demonstrated that glutamine regulated the differentiation of goblet cell by inhibiting the Notch signaling pathway in both human intestinal epithelial cell model and mouse intestinal organoid model. CONCLUSION: C. somerae served as a key bacterium adapted to soybean meal-derived carbohydrates, and it promoted goblet cell differentiation by inhibiting the Notch pathway. This study provides a new perspective for unraveling the interaction mechanisms among diet components, intestinal microbiota and host health.

Animals↗

PubMed2025

In vitro activity of contezolid and other comparators against clinical Staphylococcus and Enterococcus: a multicenter study in China.

OBJECTIVE: To evaluate the in vitro activity of contezolid against clinical Staphylococcus and Enterococcus isolates from across China, and compare its performance with linezolid and other key agents. METHODS: A total of 2510 non-duplicate Gram-positive cocci isolates were collected from 70 hospitals in seven Chinese regions. Minimum inhibitory concentrations (MICs) were determined using broth microdilution (BMD) per CLSI guidelines. MIC50/90 values, susceptibility rates, cumulative MIC curves and MIC distribution agreement between contezolid and linezolid were assessed. Linezolid-resistant isolates and contezolid-resistant isolates-defined as those based on CLSI 2025 linezolid breakpoints-underwent whole-genome sequencing and comprehensive screening for known oxazolidinone resistance determinants, including acquired resistance genes, 23S rRNA mutations and amino acid substitutions in ribosomal proteins L3, L4 and L22. RESULTS: Contezolid exhibited potent in vitro activity, with >99% of isolates inhibited at ≤4 mg/L and showed lower MIC50/90 than linezolid, with a consistently left-shifted cumulative MIC distribution. Cohen's kappa analysis supporting enhanced activity of contezolid. Notably, we report for the first time clinical isolates with contezolid MICs up to 16 mg/L. Whole-genome analysis of 14 linezolid-resistant isolates (including five resistant to contezolid) revealed universal presence of optrA, cfr, fexA and other resistance genes, alongside domain V 23S rRNA mutations and substitutions in ribosomal proteins L3 and L4, supporting a shared genetic basis and potential cross-resistance between the two agents. CONCLUSIONS: Contezolid demonstrated potent and consistent activity against drug-resistant Gram-positive cocci, supporting its potential as a therapeutic alternative to linezolid. Further studies are needed to confirm resistance mechanisms and clinical utility.

Microbial Sensitivity Tests↗

PubMed2025

Sensitive, direct detection of non-coding off-target base editor unwinding and editing in primary cells.

Base editors create precise nucleotide changes in DNA, but their off-target activity remains challenging to quantify. Here, we develop and deploy a direct, in cellulo sequencing assay that simultaneously measures both Cas9-mediated unwinding and deaminase editing of genomic DNA (beCasKAS). Our strategy nominates >460-fold more potential off-target sites than other methods by enriching for Cas9-dependent R-loops immediately preceding editing. Using beCasKAS in primary human T-cells, we observe that mRNA-encoded ABE8e and PAMless ABE8e-SpRY base editors have distinct off-target profiles that can be mitigated by optimizing mRNA dose. Finally, we combine beCasKAS with base-resolution deep learning models to risk-stratify off-target edits by their likelihood of epigenetic dysregulation. Collectively, beCasKAS offers a sensitive and facile tool to optimize the balance between base editor on- and off-target activity.

Journal Article↗

PubMed2025

Identifying novel protein biomarkers with cross-psychiatric disorders effects and potential intervention targets: Evidence from proteomic-Mendelian randomization.

Plasma proteins are the potential therapeutic targets for psychiatric disorders due to their important roles in signal transduction. We aimed to explore the plasma protein biomarkers with cross-psychiatric disorders effects. Proteome-wide Mendelian randomization (MR) and colocalization analyses were performed to investigate the potential causal relationship between plasma protein biomarkers and 12 psychiatric disorders and further identify the potential proteins with cross-effects. To assess the directionality and exclude potential reverse causation, Steiger directionality tests and reverse MR analyses were additionally conducted. Then, validation analysis was performed by employing summary data from cross-psychiatric disorder GWAS to validate the cross-psychiatric effects of proteins. Protein-protein interactions were conducted to evaluate the interaction between candidate proteins and druggability assessment was used to prioritize potential drug targets for psychiatric disorders. We identified novel plasma proteins that possessed cross-psychiatric disorder effects, especially BTN2A1 and BTN3A2 associated with major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BIP); ITIH1, ITIH3, ITIH4 and FES associated with SCZ and BIP, and the cross-effects of these proteins on SCZ and BIP were confirmed by validation analyses. Steiger tests and reverse MR supported causal directionality. Besides, the protein-protein interactions (PPI) analysis indicated cross-effects proteins had significant interaction, especially ITIH1-ITIH3. The druggability assessment prioritized eight proteins, two of which (ITIH3 and NCAM1) has been targeted by antipsychotic drugs. Our findings provided insights into shared biological mechanisms underlying these conditions.

Humans↗

PubMed2025

A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data.

Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. This can be effectively applied in genomics when we learn the gene associations in a target tissue, and data from other tissues can be integrated. However, heavy-tail distribution and outliers are common in genomics data, which poses challenges to the effectiveness of current transfer learning approaches. In this paper, we study the transfer learning problem under high-dimensional linear models with t-distributed error (Trans-PtLR), which aims to improve the estimation and prediction of target data by borrowing information from useful source data and offering robustness to accommodate complex data with heavy tails and outliers. In the oracle case with known transferable source datasets, a transfer learning algorithm based on penalized maximum likelihood and expectation-maximization algorithm is established. To avoid including non-informative sources, we propose to select the transferable sources based on cross-validation. Extensive simulation experiments as well as an application demonstrate that Trans-PtLR demonstrates robustness and better performance of estimation and prediction when heavy-tail and outliers exist compared to transfer learning for linear regression model with normal error distribution. Data integration, Variable selection, T distribution, Expectation maximization algorithm, Genotype-Tissue Expression, Cross validation.

Linear Models↗

PubMed2025

High temperature induces MdGATA15 to suppress anthocyanin accumulation in apple peels.

Although GATA transcription factors are known to play broad roles in plant growth, development, and stress responses, their involvement in high-temperature-induced anthocyanin suppression remains largely unexplored. In this study, using "Otome" as the experimental material, we revealed the important role of MdGATA15 in inhibiting anthocyanin accumulation under high temperature through multiple molecular mechanisms. A series of physiological and biochemical experiments demonstrated that MdGATA15 directly binds to the promoters of anthocyanin activators MdMYB11, MdANS, and the transporter gene MdGSTF12, repressing their expression. Simultaneously, MdGATA15 activates the expression of the anthocyanin biosynthesis repressor MdMYB308, further enhancing the inhibition. Notably, MdGATA15 binds to its own promoter, forming a positive feedback loop that significantly enhances its expression under high-temperature conditions. This mechanism provides new insights into understanding how apple responds to high-temperature stress. Additionally, we identified the bHLH transcription factor MdPIF4-Like3 in apple as an interactor of MdGATA15, which stabilizes and enhances the transcriptional activity of MdGATA15, thereby further reinforcing the inhibition of anthocyanin biosynthesis. These findings highlight the central role of MdGATA15 in high-temperature-mediated suppression of anthocyanin synthesis in apple and provide significant advances in understanding the molecular mechanisms of apple's response to heat stress. This study provides a theoretical basis for breeding heat-resistant apple cultivars with improved fruit quality by targeting key transcription factors involved in high-temperature stress response.

Anthocyanins↗