Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo developm...Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo development is of paramount importance.In this study,we established a stable porcine trophectoderm cell line expressing dual fluorescent reporter genes driven by the CDX2 and TEAD4 gene promoter segments using lentiviral transfection.Results Three amino acid metabolites—kynurenic acid,taurine,and tryptamine—met the minimum z-score criteria of 2.0 for both luciferase and Renilla luciferase activities and were initially identified as potential metabolites for embryo development,with their beneficial effects validated by qPCR.Given that the identified metabolites are closely related to methionine,arginine,and tryptophan,we selected these three amino acids,using lysine as a standard,and employed response surface methodology combined with our high-throughput screening cell model to efficiently screen and optimize amino acid combination conducive to early embryo development.The optimized candidate amino acid system included lysine(1.87 mmol/L),methionine(0.82 mmol/L),tryptophan(0.23 mmol/L),and arginine(3 mmol/L),with the ratio of 1:0.43:0.12:1.60.In vitro experiments confirmed that this amino acid system enhances the expression of key genes involved in early embryonic development and improves in vitro embryo adhesion.Transcriptomic analysis of blastocysts suggested that candidate amino acid system enhances early embryo development by regulating early embryonic cell cycle and differentiation,as well as improving nutrient absorption.Furthermore,based on response surface methodology,400 sows were used to verify this amino acid system,substituting arginine with the more cost-effective N-carbamoyl glutamate(NCG),a precursor of arginine.The optimal dietary amino acid requirement was predicted to be 0.71%lysine,0.32%methionine,0.22%tryptophan,and 0.10%NCG for sows during early gestation.The optimized amino acid system ratio of the feed,derived from the peripheral release of essential amino acids,was found to be 1:0.45:0.13,which is largely consistent with the results obtained from the cell model optimization.Subsequently,we furtherly verified that this optimal dietary amino acid system significantly increased total litter size,live litter size and litter weight in sows.Conclusions In summary,we successfully established a dual-fluorescent high-throughput screening cell model for the efficient identification of potential nutrients that would promote embryo development and implantation.This innovative approach overcomes the limitations of traditional amino acid nutrition studies in sows,providing a more effective model for enhancing reproductive outcomes.展开更多
Shoot architecture in maize is critical since it determines resource use,impacts wind and rain damage tolerance,and affects yield stability.Quantifying the diversity among inbred lines in heterosis breeding is essenti...Shoot architecture in maize is critical since it determines resource use,impacts wind and rain damage tolerance,and affects yield stability.Quantifying the diversity among inbred lines in heterosis breeding is essential,especially when describing germplasm resources.However,traditional geometric description methods oversimplify shoot architecture and ignore the plant’s overall architecture,making it difficult to reflect and illustrate diversity.This study presents a new method to describe maize shoot architecture and quantifies its diversity by combining computer vision algorithms and persistent homology.Our results reveal that persistent homology can capture key characteristics of shoot architecture in maize and other details often overlooked by traditional geometric analysis.Based on this method,the morphological diversity of shoot architecture can be mined(quantified),and the main shoot architecture types can be obtained.Consequently,this method can easily describe the diversity of shoot architecture in many maize materials.展开更多
Microcin J25(MccJ25)has received substantial attention as a potential solution to the global threat of infection caused by antibiotic-resistant bacteria.However,the industrial fermentation of MccJ25 faces production b...Microcin J25(MccJ25)has received substantial attention as a potential solution to the global threat of infection caused by antibiotic-resistant bacteria.However,the industrial fermentation of MccJ25 faces production bottlenecks.It is imperative to further explore the production optimization strategies for MccJ25 to formulate comprehensive approaches for its industrial-scale production and other downstream applications.Here,Fe^(2+)in tap water was identified as a critical inhibitor of MccJ25 biosynthesis,selectively repressing mcjA transcription,which was reversible via 2,2'-bipyridine-mediated chelation.To decouple production from growth phase dependency and Fe^(2+)interference,we engineered Escherichia coli BL21 cells by performing two genetic modifications.First,we replaced the native mcjA promoter with a constitutive promoter(PQ)to allow its mid-log phase expression.Second,we replaced the native mcjBCD promoter with a medium-strength variant(P2223)that delayed production kinetics without affecting final yields.However,the genomic integration of mcjD alleviated plasmid-borne toxicity,increasing the expression timing and doubling the yield to 240 mg/L.Finally,we computationally optimized the mcjA ribosome-binding site(RBS)to enhance translation efficiency.RBS optimization revealed that a moderate translation initiation efficiency(550,584 arbitrary units[au])maximized production,whereas excessive efficiency(2,019,712 au)impaired growth and output.These interventions synergistically increased the MccJ25 titer 10-fold,reaching 430 mg/L in batch culture.Our findings establish a robust platform for MccJ25 overproduction,highlighting promoter engineering and translational tuning as pivotal strategies for antimicrobial peptide biosynthesis.This study provides insights for overcoming metabolic constraints in microbial fermentation,advancing the development of peptide-based therapeutics against multidrug-resistant pathogens.展开更多
Rice biology research involves complex decision-making,requiring researchers to navigate a rapidly expanding body of knowledge encompassing extensive literature and multiomics data.The exponential increase in biologic...Rice biology research involves complex decision-making,requiring researchers to navigate a rapidly expanding body of knowledge encompassing extensive literature and multiomics data.The exponential increase in biological data and scientific publications presents significant challenges for efficiently extracting meaningful insights.Although large language models(LLMs)show promise for knowledge retrieval,their application to rice-specific research has been limited by the absence of specialized models and the challenge of synthesizing multimodal data integral to the field.Moreover,the lack of standardized evaluation frameworks for domain-specific tasks impedes the effective assessment of model performance.To address these challenges,we introduce SeedLLM·Rice(SeedLLM),a 7-billion-parameter model trained on 1.4 million rice-related publications,representing nearly 98.24%of global rice research output.Additionally,we present a novel human-centric evaluation framework designed to assess LLM performance in rice biology tasks.Initial evaluations demonstrate that SeedLLM outperforms general-purpose models,including OpenAI GPT-4o1 and DeepSeek-R1,achieving win rates of 57%to 88%on rice-specific tasks.Furthermore,SeedLLM is integrated with the Rice Biological Knowledge Graph(RBKG),which consolidates genome annotations for Nipponbare and large-scale synthesis of transcriptomic and proteomic information from over 1800 studies.This integration enhances the ability of SeedLLM to address complex research questions requiring the fusion of textual and multiomics data.To facilitate global collaboration,we provide free access to SeedLLM and the RBKG via an interactive web portal(https://seedllm.org.cn/).SeedLLM represents a transformative tool for rice biology research,enabling unprecedented discoveries in crop improvement and climate adaptation through advanced reasoning and comprehensive data integration.展开更多
基金supported by National Natural Science Foundation of China (32172747 and 32425052)
文摘Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo development is of paramount importance.In this study,we established a stable porcine trophectoderm cell line expressing dual fluorescent reporter genes driven by the CDX2 and TEAD4 gene promoter segments using lentiviral transfection.Results Three amino acid metabolites—kynurenic acid,taurine,and tryptamine—met the minimum z-score criteria of 2.0 for both luciferase and Renilla luciferase activities and were initially identified as potential metabolites for embryo development,with their beneficial effects validated by qPCR.Given that the identified metabolites are closely related to methionine,arginine,and tryptophan,we selected these three amino acids,using lysine as a standard,and employed response surface methodology combined with our high-throughput screening cell model to efficiently screen and optimize amino acid combination conducive to early embryo development.The optimized candidate amino acid system included lysine(1.87 mmol/L),methionine(0.82 mmol/L),tryptophan(0.23 mmol/L),and arginine(3 mmol/L),with the ratio of 1:0.43:0.12:1.60.In vitro experiments confirmed that this amino acid system enhances the expression of key genes involved in early embryonic development and improves in vitro embryo adhesion.Transcriptomic analysis of blastocysts suggested that candidate amino acid system enhances early embryo development by regulating early embryonic cell cycle and differentiation,as well as improving nutrient absorption.Furthermore,based on response surface methodology,400 sows were used to verify this amino acid system,substituting arginine with the more cost-effective N-carbamoyl glutamate(NCG),a precursor of arginine.The optimal dietary amino acid requirement was predicted to be 0.71%lysine,0.32%methionine,0.22%tryptophan,and 0.10%NCG for sows during early gestation.The optimized amino acid system ratio of the feed,derived from the peripheral release of essential amino acids,was found to be 1:0.45:0.13,which is largely consistent with the results obtained from the cell model optimization.Subsequently,we furtherly verified that this optimal dietary amino acid system significantly increased total litter size,live litter size and litter weight in sows.Conclusions In summary,we successfully established a dual-fluorescent high-throughput screening cell model for the efficient identification of potential nutrients that would promote embryo development and implantation.This innovative approach overcomes the limitations of traditional amino acid nutrition studies in sows,providing a more effective model for enhancing reproductive outcomes.
基金The study work was supported by the National Key Research and Development Program of China(2022ZD0401801)the Chinese Universities Scientific Funds(2023TC107).
文摘Shoot architecture in maize is critical since it determines resource use,impacts wind and rain damage tolerance,and affects yield stability.Quantifying the diversity among inbred lines in heterosis breeding is essential,especially when describing germplasm resources.However,traditional geometric description methods oversimplify shoot architecture and ignore the plant’s overall architecture,making it difficult to reflect and illustrate diversity.This study presents a new method to describe maize shoot architecture and quantifies its diversity by combining computer vision algorithms and persistent homology.Our results reveal that persistent homology can capture key characteristics of shoot architecture in maize and other details often overlooked by traditional geometric analysis.Based on this method,the morphological diversity of shoot architecture can be mined(quantified),and the main shoot architecture types can be obtained.Consequently,this method can easily describe the diversity of shoot architecture in many maize materials.
基金supported by the Young Scientists Fund of the National Natural Science Foundation of China(32402807)the National Key Research and Development Program of China(Grant number 32030105)+2 种基金the Pioneer Technology Project of the National Center for Technology Innovation for Pigs(NCTIP-XD/B05)the PinduoduoChina Agricultural University Research Fund(PC2023A01001)the Chongqing Technology Innovation and Application Development Special Project(cstc2021jscx dxwtBX0005)。
文摘Microcin J25(MccJ25)has received substantial attention as a potential solution to the global threat of infection caused by antibiotic-resistant bacteria.However,the industrial fermentation of MccJ25 faces production bottlenecks.It is imperative to further explore the production optimization strategies for MccJ25 to formulate comprehensive approaches for its industrial-scale production and other downstream applications.Here,Fe^(2+)in tap water was identified as a critical inhibitor of MccJ25 biosynthesis,selectively repressing mcjA transcription,which was reversible via 2,2'-bipyridine-mediated chelation.To decouple production from growth phase dependency and Fe^(2+)interference,we engineered Escherichia coli BL21 cells by performing two genetic modifications.First,we replaced the native mcjA promoter with a constitutive promoter(PQ)to allow its mid-log phase expression.Second,we replaced the native mcjBCD promoter with a medium-strength variant(P2223)that delayed production kinetics without affecting final yields.However,the genomic integration of mcjD alleviated plasmid-borne toxicity,increasing the expression timing and doubling the yield to 240 mg/L.Finally,we computationally optimized the mcjA ribosome-binding site(RBS)to enhance translation efficiency.RBS optimization revealed that a moderate translation initiation efficiency(550,584 arbitrary units[au])maximized production,whereas excessive efficiency(2,019,712 au)impaired growth and output.These interventions synergistically increased the MccJ25 titer 10-fold,reaching 430 mg/L in batch culture.Our findings establish a robust platform for MccJ25 overproduction,highlighting promoter engineering and translational tuning as pivotal strategies for antimicrobial peptide biosynthesis.This study provides insights for overcoming metabolic constraints in microbial fermentation,advancing the development of peptide-based therapeutics against multidrug-resistant pathogens.
基金SeedLLM research and development were supported by the Yazhouwan National Laboratory Project(grant no.2310CF01)the Shanghai Artificial Intelligence Laboratory+1 种基金Corpus preparation was supported by the Hainan Yazhou Bay Seed Laboratory Project(grant no.B21HJ0001)Human evaluation of LLM performance was supported by the Biological Breeding-National Science and Technology Major Project(grant no.2023ZD04076).
文摘Rice biology research involves complex decision-making,requiring researchers to navigate a rapidly expanding body of knowledge encompassing extensive literature and multiomics data.The exponential increase in biological data and scientific publications presents significant challenges for efficiently extracting meaningful insights.Although large language models(LLMs)show promise for knowledge retrieval,their application to rice-specific research has been limited by the absence of specialized models and the challenge of synthesizing multimodal data integral to the field.Moreover,the lack of standardized evaluation frameworks for domain-specific tasks impedes the effective assessment of model performance.To address these challenges,we introduce SeedLLM·Rice(SeedLLM),a 7-billion-parameter model trained on 1.4 million rice-related publications,representing nearly 98.24%of global rice research output.Additionally,we present a novel human-centric evaluation framework designed to assess LLM performance in rice biology tasks.Initial evaluations demonstrate that SeedLLM outperforms general-purpose models,including OpenAI GPT-4o1 and DeepSeek-R1,achieving win rates of 57%to 88%on rice-specific tasks.Furthermore,SeedLLM is integrated with the Rice Biological Knowledge Graph(RBKG),which consolidates genome annotations for Nipponbare and large-scale synthesis of transcriptomic and proteomic information from over 1800 studies.This integration enhances the ability of SeedLLM to address complex research questions requiring the fusion of textual and multiomics data.To facilitate global collaboration,we provide free access to SeedLLM and the RBKG via an interactive web portal(https://seedllm.org.cn/).SeedLLM represents a transformative tool for rice biology research,enabling unprecedented discoveries in crop improvement and climate adaptation through advanced reasoning and comprehensive data integration.
