Protein-Protein Interaction Prediction via Structure-Based Deep Learning.

Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with various sequence lengths and suffer from low generalization and prediction accuracy. In this study, we proposed a novel end-to-end deep learning framework, RSPPI, combining residual neural network (ResNet) and spatial pyramid pooling (SPP), to predict PPIs based on the protein sequence physicochemistry properties and spatial structural information. In the RSPPI model, ResNet was employed to extract the structural and physicochemical information from the protein three-dimensional structure and primary sequence; the SPP layer was used to transform feature maps to a single vector and avoid the fixed-length requirement. The RSPPI model possessed excellent cross-species performance and outperformed several state-of-the-art methods based either on protein sequence or gene ontology in most evaluation metrics. The RSPPI model provides a novel strategy to develop an AI PPI prediction algorithm.

The Effect of Broccoli Glucoraphanin Supplementation on Ameliorating High-Fat-Diet-Induced Obesity through the Gut Microbiome and Metabolome Interface.

SCOPE: Obesity and its metabolic comorbidities pose a major global challenge for public health. Glucoraphanin (GRN) is a natural bioactive compound enriched in broccoli that is known to have potential health benefits against various human chronic diseases. METHODS AND RESULTS: This study investigats the effects of broccoli GRN supplementation on body weight, metabolic parameters, gut microbiome and metabolome associated with obesity. The study is conducted on an obese-related C57BL/6J mouse model through the treatment of normal control diet, high-fat diet (HFD)and GRN-supplemented HFD (HFD-GRN) to determine the metabolic protection of GRN. The results shows that GRN treatment alleviates obesity-related traits leading to improved glucose metabolism in HFD-fed animals. Mechanically, the study noticed that GRN significantly shifts the gut microbial diversity and composition to an eubiosis status. GRN supplement also significantly alters plasma metabolite profiles. Further integrated analysis reveal a complex interaction between the gut microbes and host metabolism that may contribute to GRN-induced beneficial effects against HFD. CONCLUSION: These results indicate that beneficial effects of broccoli GRN on reversing HFD-induced adverse metabolic parameters may be attributed to its impacts on reprogramming microbial community and metabolites. Identification of the mechanistic functions of GRN further warrants it as a dietary candidate for obesity prevention.

High-performance ferroelectric field-effect transistors with ultra-thin indium tin oxide channels for flexible and transparent electronics.

With the development of wearable devices and hafnium-based ferroelectrics (FE), there is an increasing demand for high-performance flexible ferroelectric memories. However, developing ferroelectric memories that simultaneously exhibit good flexibility and significant performance has proven challenging. Here, we developed a high-performance flexible field-effect transistor (FeFET) device with a thermal budget of less than 400 °C by integrating Zr-doped HfO2 (HZO) and ultra-thin indium tin oxide (ITO). The proposed FeFET has a large memory window (MW) of 2.78 V, a high current on/off ratio (ION/IOFF) of over 108, and high endurance up to 2×107 cycles. In addition, the FeFETs under different bending conditions exhibit excellent neuromorphic properties. The device exhibits excellent bending reliability over 5×105 pulse cycles at a bending radius of 5 mm. The efficient integration of hafnium-based ferroelectric materials with promising ultrathin channel materials (ITO) offers unique opportunities to enable high-performance back-end-of-line (BEOL) compatible wearable FeFETs for edge intelligence applications.

A molecular arm: the molecular bending-unbending mechanism of integrin.

The balance of integrin activation and deactivation regulates its function and mediates cell behaviors. Mechanical force triggers the unbending and activation of integrin. However, how an activated and extended integrin spontaneously bends back is unclear. I performed all-atom molecular dynamics simulations on an integrin or its subunits to reveal the bending-unbending mechanism of integrin. According to the simulations, the integrin structure works like a human arm. The integrin α subunit serves as the bones, while the ß leg serves as the bicep. The integrin extension results in the stretching of the ß leg, and the extended integrin spontaneously bends as a consequence of the contraction of the ß leg. This study provides new insights into the mechanism of how the integrin secures in the bent inactivated state and sheds light on how the integrin could achieve a stable extended state.

Low-power and high-speed HfLaO-based FE-TFTs for artificial synapse and reconfigurable logic applications.

Emulating the human nervous system to build next-generation computing architectures is considered a promising way to solve the von Neumann bottleneck. Transistors based on ferroelectric layers are strong contenders for the basic unit of artificial neural systems due to their advantages of high speed and low power consumption. In this work, the potential of Fe-TFTs integrating the HfLaO ferroelectric film and ultra-thin ITO channel for artificial synaptic devices is demonstrated for the first time. The Fe-TFTs can respond significantly to pulses as low as 14 ns with an energy consumption of 93.1 aJ, which is at the leading level for similar devices. In addition, Fe-TFTs exhibit essential synaptic functions and achieve a recognition rate of 93.2% for handwritten digits. Notably, a novel reconfigurable approach involving the combination of two types of electrical pulses to realize Boolean logic operations ("AND", "OR") within a single Fe-TFT has been introduced for the first time. The simulations of array-level operations further demonstrated the potential for parallel computing. These multifunctional Fe-TFTs reveal new hardware options for neuromorphic computing chips.

Force-Regulated Spontaneous Conformational Changes of Integrins α5ß1 and αVß3.

Integrins are cell surface nanosized receptors crucial for cell motility and mechanosensing of the extracellular environment, which are often targeted for the development of biomaterials and nanomedicines. As a key feature of integrins, their activity, structure and behavior are highly mechanosensitive, which are regulated by mechanical forces down to pico-Newton scale. Using single-molecule biomechanical approaches, we compared the force-modulated ectodomain bending/unbending conformational changes of two integrin species, α5ß1 and αVß3. It was found that the conformation of integrin α5ß1 is determined by a threshold head-to-tail tension. By comparison, integrin αVß3 exhibits bistability even without force and can spontaneously transition between the bent and extended conformations with an apparent transition time under a wide range of forces. Molecular dynamics simulations observed almost concurrent disruption of ∼2 hydrogen bonds during integrin α5ß1 unbending, but consecutive disruption of ∼7 hydrogen bonds during integrin αVß3 unbending. Accordingly, we constructed a canonical energy landscape for integrin α5ß1 with a single energy well that traps the integrin in the bent state until sufficient force tilts the energy landscape to allow the conformational transition. In contrast, the energy landscape of integrin αVß3 conformational changes was constructed with hexa-stable intermediate states and intermediate energy barriers that segregate the conformational change process into multiple small steps. Our study elucidates the different biomechanical inner workings of integrins α5ß1 and αVß3 at the submolecular level, helps understand their mechanosignaling processes and how their respective functions are facilitated by their distinctive mechanosensitivities, and provides useful design principles for the engineering of protein-based biomechanical nanomachines.

PARylated PDHE1α generates acetyl-CoA for local chromatin acetylation and DNA damage repair.

Chromatin relaxation is a prerequisite for the DNA repair machinery to access double-strand breaks (DSBs). Local histones around the DSBs then undergo prompt changes in acetylation status, but how the large demands of acetyl-CoA are met is unclear. Here, we report that pyruvate dehydrogenase 1α (PDHE1α) catalyzes pyruvate metabolism to rapidly provide acetyl-CoA in response to DNA damage. We show that PDHE1α is quickly recruited to chromatin in a polyADP-ribosylation-dependent manner, which drives acetyl-CoA generation to support local chromatin acetylation around DSBs. This process increases the formation of relaxed chromatin to facilitate repair-factor loading, genome stability and cancer cell resistance to DNA-damaging treatments in vitro and in vivo. Indeed, we demonstrate that blocking polyADP-ribosylation-based PDHE1α chromatin recruitment attenuates chromatin relaxation and DSB repair efficiency, resulting in genome instability and restored radiosensitivity. These findings support a mechanism in which chromatin-associated PDHE1α locally generates acetyl-CoA to remodel the chromatin environment adjacent to DSBs and promote their repair.

Mechanical force regulates ligand binding and function of PD-1.

Immune checkpoint blockade targeting PD-1 shows great success in cancer therapy. However, the mechanism of how ligand binding initiates PD-1 signaling remains unclear. As prognosis markers of multiple cancers, soluble PD-L1 is found in patient sera and can bind PD-1, but fails to suppress T cell function. This and our previous observations that T cells exert endogenous forces on PD-1-PD-L2 bonds prompt the hypothesis that mechanical force might be critical to PD-1 triggering, which is missing in the soluble ligand case due to the lack of mechanical support afforded by surface-anchored ligand. Here we show that PD-1 function is eliminated or reduced when mechanical support on ligand is removed or dampened, respectively. Force spectroscopic analysis reveals that PD-1 forms catch bonds with both PD-Ligands <7 pN where force prolongs bond lifetime, but slip bonds >8 pN where force accelerates dissociation. Steered molecular dynamics finds PD-1-PD-L2 complex very sensitive to force due to the two molecules' "side-to-side" binding via ß sheets. Pulling causes relative rotation and translation between the two molecules by stretching and aligning the complex along the force direction, yielding new atomic contacts not observed in the crystal structure. Compared to wild-type, PD-1 mutants targeting the force-induced new interactions maintain the same binding affinity but display lower rupture force, shorter bond lifetime, reduced tension, and most importantly, impaired capacity to suppress T cell activation. Our results uncover a mechanism for cells to probe the mechanical support of PD-1-PD-Ligand bonds using endogenous forces to regulate PD-1 triggering.

Early-season and refined mapping of winter wheat based on phenology algorithms - a case of Shandong, China.

Winter wheat is one of the major food crops in China, and timely and effective early-season identification of winter wheat is crucial for crop yield estimation and food security. However, traditional winter wheat mapping is based on post-season identification, which has a lag and relies heavily on sample data. Early-season identification of winter wheat faces the main difficulties of weak remote sensing response of the vegetation signal at the early growth stage, difficulty of acquiring sample data on winter wheat in the current season in real time, interference of crops in the same period, and limited image resolution. In this study, an early-season refined mapping method with winter wheat phenology information as priori knowledge is developed based on the Google Earth Engine cloud platform by using Sentinel-2 time series data as the main data source; these data are automated and highly interpretable. The normalized differential phenology index (NDPI) is adopted to enhance the weak vegetation signal at the early growth stage of winter wheat, and two winter wheat phenology feature enhancement indices based on NDPI, namely, wheat phenology differential index (WPDI) and normalized differential wheat phenology index (NDWPI) are developed. To address the issue of " different objects with the same spectra characteristics" between winter wheat and garlic, a plastic mulched index (PMI) is established through quantitative spectral analysis based on the differences in early planting patterns between winter wheat and garlic. The identification accuracy of the method is 82.64% and 88.76% in the early overwintering and regreening periods, respectively, These results were consistent with official statistics (R2 = 0.96 and 0.98, respectively). Generalization analysis demonstrated the spatiotemporal transferability of the method across different years and regions. In conclusion, the proposed methodology can obtain highly precise spatial distribution and planting area information of winter wheat 4_6 months before harvest. It provides theoretical and methodological guidance for early crop identification and has good scientific research and application value.

Flexible aluminum-doped hafnium oxide ferroelectric synapse devices for neuromorphic computing.

The HfO2-based ferroelectric tunnel junction has received outstanding attention owing to its high-speed and low-power characteristics. In this work, aluminum-doped HfO2 (HfAlO) ferroelectric thin films are deposited on a muscovite substrate (Mica). We investigate the bending effect on the ferroelectric characteristics of the Au/Ti/HfAlO/Pt/Ti/Mica device. After 1000 bending times, the ferroelectric properties and the fatigue characteristics are largely degraded. The finite element analysis indicates that crack formation is the main reason for the fatigue damage under threshold bending diameters. Moreover, the HfAlO-based ferroelectric synaptic device exhibits excellent performance of neuromorphic computing. The artificial synapse can mimic the paired-pulse facilitation and long-term potentiation/depression of biological synapses. Meanwhile, the accuracy of digit recognition is 88.8%. This research provides a new research idea for the further development of hafnium-based ferroelectric devices.

Binding kinetics study of SARS-CoV-2 main protease and potential inhibitors via molecular dynamics simulations.

The pandemic COVID-19 was induced by the novel coronavirus SARS-CoV-2. The virus main protease (Mpro) cleaves the coronavirus polyprotein translated from the viral RNA in the host cells. Because of its crucial role in virus replication, Mpro is a potential drug target for COVID-19 treatment. Herein, we study the interactions between Mpro and three HIV-1 protease (HIV-1 PR) inhibitors, Lopinavir (LPV), Saquinavir (SQV), Ritonavir (RIT), and an inhibitor PF-07321332, by conventional and replica exchange molecular dynamics (MD) simulations. The association/dissociation rates and the affinities of the inhibitors were estimated. The three HIV-1 PR inhibitors exhibit low affinities, while PF-07321332 has the highest affinity among these four simulated inhibitors. Based on cluster analysis, the HIV-1 PR inhibitors bind to Mpro at multiple sites, while PF-07321332 specifically binds to the catalytically activated site of Mpro. The stable and specific binding is because PF-07321332 forms multiple H-bonds to His163 and Glu166 simultaneously. The simulations suggested PF-07321332 could serve as an effective inhibitor with high affinity and shed light on the strategy of drug design and drug repositioning.

The Doping Effect on the Intrinsic Ferroelectricity in Hafnium Oxide-Based Nano-Ferroelectric Devices.

Hafnium oxide (HfO2)-based ferroelectric tunnel junctions (FTJs) have been extensively evaluated for high-speed and low-power memory applications. Herein, we investigated the influence of Al content in HfAlO thin films on the ferroelectric characteristics of HfAlO-based FTJs. Among HfAlO devices with different Hf/Al ratios (20:1, 34:1, and 50:1), the HfAlO device with Hf/Al ratio of 34:1 exhibited the highest remanent polarization and excellent memory characteristics and, thereby, the best ferroelectricity among the investigated devices. Furthermore, first-principal analyses verified that HfAlO thin films with Hf/Al ratio of 34:1 promoted the formation of the orthorhombic phase against the paraelectric phase as well as alumina impurities and, thus, enhanced the ferroelectricity of the device, providing theoretical support for supporting experimental results. The findings of this study provide insights for developing HfAlO-based FTJs for next-generation in-memory computing applications.

Structural basis for TRIM72 oligomerization during membrane damage repair.

Tripartite Motif Protein 72 (TRIM72, also named MG53) mediates membrane damage repair through membrane fusion and exocytosis. During injury, TRIM72 molecules form intermolecular disulfide bonds in response to the oxidative environment and TRIM72 oligomers are proposed to connect vesicles to the plasma membrane and promote membrane fusion in conjunction with other partners like dysferlin and caveolin. However, the detailed mechanism of TRIM72 oligomerization and action remains unclear. Here we present the crystal structure of TRIM72 B-box-coiled-coil-SPRY domains (BCC-SPRY), revealing the molecular basis of TRIM72 oligomerization, which is closely linked to disulfide bond formation. Through structure-guided mutagenesis, we have identified and characterized key residues that are important for the membrane repair function of TRIM72. Our results also demonstrate that TRIM72 interacts with several kinds of negatively charged lipids in addition to phosphatidylserine. Our work provides a structural foundation for further mechanistic studies as well as the clinical application of TRIM72.

Force-regulated spontaneous conformational changes of integrins α 5 ß 1 and α V ß 3.

Force can modulate the properties and functions of macromolecules by inducing conformational changes, such as coiling/uncoiling, zipping/unzipping, and folding/unfolding. Here we compared force-modulated bending/unbending of two purified integrin ectodomains, α 5 ß 1 and α V ß 3 , using single-molecule approaches. Similar to previously characterized mechano-sensitive macromolecules, the conformation of α 5 ß 1 is determined by a threshold head-to-tail tension, suggesting a canonical energy landscape with a deep energy well that traps the integrin in the bent state until sufficient force tilts the energy landscape to accelerate transition to the extended state. By comparison, α V ß 3 exhibits bi-stability even without force and can spontaneously transition between the bent and extended conformations in a wide range of forces without energy supplies. Molecular dynamics simulations revealed consecutive formation and disruption of 7 hydrogen bonds during α V ß 3 bending and unbending, respectively. Accordingly, we constructed an energy landscape with hexa-stable intermediate states to break down the energy barrier separating the bent and extended states into smaller ones, making it possible for the thermal agitation energy to overcome them sequentially and to be accumulated and converted into mechanical work required for α V ß 3 to bend against force. Our study elucidates the different inner workings of α 5 ß 1 and α V ß 3 at the sub-molecular level, sheds lights on how their respectively functions are facilitated by their distinctive mechano-sensitivities, helps understand their signal initiation processes, and provides critical concepts and useful design principles for engineering of protein-based biomechanical nanomachines.

The ßI domain promotes active ß1 integrin clustering into mature adhesion sites.

Modulation of integrin function is required in many physiological and pathological settings, such as angiogenesis and cancer. Integrin allosteric changes, clustering, and trafficking cooperate to regulate cell adhesion and motility on extracellular matrix proteins via mechanisms that are partly defined. By exploiting four monoclonal antibodies recognizing distinct conformational epitopes, we show that in endothelial cells (ECs), the extracellular ßI domain, but not the hybrid or I-EGF2 domain of active ß1 integrins, promotes their FAK-regulated clustering into tensin 1-containing fibrillar adhesions and impairs their endocytosis. In this regard, the ßI domain-dependent clustering of active ß1 integrins is necessary to favor fibronectin-elicited directional EC motility, which cannot be effectively promoted by ß1 integrin conformational activation alone.

Assessing SIRT7 Activity In Vivo and In Vitro in Response to DNA Damage.

The class III histone deacetylase (HDACs) also known as sirtuins (SIRTs 1-7) are ubiquitously expressed, but SIRT7 mainly resides as nucleolar protein. In this chapter a couple of methods are described that are used to detect modulation of SIRT7 in response to DNA damage. SIRT7 is localized in the nucleoli and binds to the chromatin after DNA damage. Therefore, a protocol was optimized by our lab for chromatin fractionation. By this method, the movement of SIRT7 can be detected from the soluble part (cytosol+nucleoplasm) to the solid part (chromatin) of the cell. Change of SIRT7 expression levels, in different cells or after different treatment, can be detected by isolating whole-cell lysate followed by Western blotting. For analyzing binding of SIRT7 to other substrates, we have also optimized manual immunoprecipitation assays by using 1% NP40 buffer. This protocol is very helpful to pull down SIRT7 and associated proteins by using a single buffer. SIRT7 is a deacetylase, and its deacetylation activity can be checked both inside the cell by in vivo deacetylation assay and outside the cell by in vitro deacetylation assays. Recently it was also discovered that SIRT7 has desuccinylase activity which can be detected by histone desuccinylation assay. This chapter provides the methodology of SIRT7 detection in the whole cell lysate, binding of SIRT7 to the chromatin and other proteins for performing deacetylation and desuccinylation activity.

Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics.

Neuromorphic computing memristors are attractive to construct low-power- consumption electronic textiles due to the intrinsic interwoven architecture and promising applications in wearable electronics. Developing reconfigurable fiber-based memristors is an efficient method to realize electronic textiles that capable of neuromorphic computing function. However, the previously reported artificial synapse and neuron need different materials and configurations, making it difficult to realize multiple functions in a single device. Herein, a textile memristor network of Ag/MoS2/HfAlOx/carbon nanotube with reconfigurable characteristics was reported, which can achieve both nonvolatile synaptic plasticity and volatile neuron functions. In addition, a single reconfigurable memristor can realize integrate-and-fire function, exhibiting significant advantages in reducing the complexity of neuron circuits. The firing energy consumption of fiber-based memristive neuron is 1.9 fJ/spike (femtojoule-level), which is at least three orders of magnitude lower than that of the reported biological and artificial neuron (picojoule-level). The ultralow energy consumption makes it possible to create an electronic neural network that reduces the energy consumption compared to human brain. By integrating the reconfigurable synapse, neuron and heating resistor, a smart textile system is successfully constructed for warm fabric application, providing a unique functional reconfiguration pathway toward the next-generation in-memory computing textile system.

Estimation of the nitrogen content of potato plants based on morphological parameters and visible light vegetation indices.

Plant nitrogen content (PNC) is an important indicator to characterize the nitrogen nutrition status of crops, and quickly and efficiently obtaining the PNC information aids in fertilization management and decision-making in modern precision agriculture. This study aimed to explore the potential to improve the accuracy of estimating PNC during critical growth periods of potato by combining the visible light vegetation indices (VIs) and morphological parameters (MPs) obtained from an inexpensive UAV digital camera. First, the visible light VIs and three types of MPs, including the plant height (H), canopy coverage (CC) and canopy volume (CV), were extracted from digital images of the potato tuber formation stage (S1), tuber growth stage (S2), and starch accumulation stage (S3). Then, the correlations of VIs and MPs with the PNC were analyzed for each growth stage, and the performance of VIs and MPs in estimating PNC was explored. Finally, three methods, multiple linear regression (MLR), k-nearest neighbors, and random forest, were used to explore the effect of MPs on the estimation of potato PNC using VIs. The results showed that (i) the values of potato H and CC extracted based on UAV digital images were accurate, and the accuracy of the pre-growth stages was higher than that of the late growth stage. (ii) The estimation of potato PNC by visible light VIs was feasible, but the accuracy required further improvement. (iii) As the growing season progressed, the correlation between MPs and PNC gradually decreased, and it became more difficult to estimate the PNC. (iv) Compared with individual MP, multi-MPs can more accurately reflect the morphological structure of the crop and can further improve the accuracy of estimating PNC. (v) Visible light VIs combined with MPs improved the accuracy of estimating PNC, with the highest accuracy of the models constructed using the MLR method (S1: R 2 = 0.79, RMSE=0.27, NRMSE=8.19%; S2:R 2 = 0.80, RMSE=0.27, NRMSE=8.11%; S3: R 2 = 0.76, RMSE=0.26, NRMSE=8.63%). The results showed that the combination of visible light VIs and morphological information obtained by a UAV digital camera could provide a feasible method for monitoring crop growth and plant nitrogen status.

Estimation of potato above-ground biomass based on unmanned aerial vehicle red-green-blue images with different texture features and crop height.

Obtaining crop above-ground biomass (AGB) information quickly and accurately is beneficial to farmland production management and the optimization of planting patterns. Many studies have confirmed that, due to canopy spectral saturation, AGB is underestimated in the multi-growth period of crops when using only optical vegetation indices. To solve this problem, this study obtains textures and crop height directly from ultrahigh-ground-resolution (GDS) red-green-blue (RGB) images to estimate the potato AGB in three key growth periods. Textures include a grayscale co-occurrence matrix texture (GLCM) and a Gabor wavelet texture. GLCM-based textures were extracted from seven-GDS (1, 5, 10, 30, 40, 50, and 60 cm) RGB images. Gabor-based textures were obtained from magnitude images on five scales (scales 1-5, labeled S1-S5, respectively). Potato crop height was extracted based on the generated crop height model. Finally, to estimate potato AGB, we used (i) GLCM-based textures from different GDS and their combinations, (ii) Gabor-based textures from different scales and their combinations, (iii) all GLCM-based textures combined with crop height, (iv) all Gabor-based textures combined with crop height, and (v) two types of textures combined with crop height by least-squares support vector machine (LSSVM), extreme learning machine, and partial least squares regression techniques. The results show that (i) potato crop height and AGB first increase and then decrease over the growth period; (ii) GDS and scales mainly affect the correlation between GLCM- and Gabor-based textures and AGB; (iii) to estimate AGB, GLCM-based textures of GDS1 and GDS30 work best when the GDS is between 1 and 5 cm and 10 and 60 cm, respectively (however, estimating potato AGB based on Gabor-based textures gradually deteriorates as the Gabor convolution kernel scale increases); (iv) the AGB estimation based on a single-type texture is not as good as estimates based on multi-resolution GLCM-based and multiscale Gabor-based textures (with the latter being the best); (v) different forms of textures combined with crop height using the LSSVM technique improved by 22.97, 14.63, 9.74, and 8.18% (normalized root mean square error) compared with using only all GLCM-based textures, all Gabor-based textures, the former combined with crop height, and the latter combined with crop height, respectively. Therefore, different forms of texture features obtained from RGB images acquired from unmanned aerial vehicles and combined with crop height improve the accuracy of potato AGB estimates under high coverage.

Maternal soybean diet on prevention of obesity-related breast cancer through early-life gut microbiome and epigenetic regulation.

Overnutrition-induced obesity and metabolic dysregulation are considered major risk factors contributing to breast cancer. The origin of both obesity and breast cancer can retrospect to early development in human lifespan. Genistein (GE), a natural isoflavone enriched in soybean products, has been proposed to associate with a lower risk of breast cancer and various metabolic disorders. Our study aimed to determine the effects of maternal exposure to soybean dietary GE on prevention of overnutrition-induced breast cancer later in life and explore potential mechanisms in different mouse models. Our results showed that maternal dietary GE treatment improved offspring metabolic functions by significantly attenuating high-fat diet-induced body fat accumulation, lipid panel abnormalities and glucose intolerance in mice offspring. Importantly, maternal dietary GE exposure effectively delayed high-fat diet-simulated mammary tumor development in female offspring. Mechanistically, we found that maternal dietary GE may exert its chemopreventive effects through affecting essential regulatory gene expression in control of metabolism, inflammation and tumor development via, at least in part, regulation of offspring gut microbiome, bacterial metabolites and epigenetic profiles. Altogether, our findings indicate that maternal GE consumption is an effective intervention approach leading to early-life prevention of obesity-related metabolic disorders and breast cancer later in life through dynamically influencing the interplay between early-life gut microbiota, key microbial metabolite profiles and offspring epigenome.