Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physio...Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physiological processes.To achieve a targeted improvement of their adaptability to various environments,a detail analysis of their evolutionary physiological processes is required.While several studies have been carried out in the past by using single-omics techniques to investigate their response to environmental stress,most researchers are now using a multi-omics approach to explore more detail in the biological regulatory networks and molecular mechanisms of lactic acid bacteria in response to environmental stress,thereby overcoming the limitations of single-omics analysis.In this review,we describe the various single-omics approaches that have been used to study environmental stress in lactic acid bacteria,present the advantages of various multi-omics combined analysis approaches,and discuss the potential and practicality of applying emerging single-cell transcriptomics and single-cell metabolomics techniques to the molecular mechanism study of microbes response to environmental stress.Multi-omics approaches enable the accurate identification of complex microbial physiological processes in different environments,allow people to comprehensively reveal the molecular mechanisms of microbes response to stress from different perspectives.Single-cell omics techniques,analyze the targeted regulation of microbial functions in a multi-dimensional space,provides a new perspective on understanding microbes responses environment stress.展开更多
In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics,...In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.展开更多
Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of ...Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.展开更多
Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,a...Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.展开更多
Soybean(Glycine max)is a vital foundation of global food security,providing a primary source of highquality protein and oil for human consumption and animal feed.The rising global population has significantly increase...Soybean(Glycine max)is a vital foundation of global food security,providing a primary source of highquality protein and oil for human consumption and animal feed.The rising global population has significantly increased the demand for soybeans,emphasizing the urgency of developing high-yield,stresstolerant,and nutritionally superior cultivars.The extensive collection of soybean germplasm resources—including wild relatives,landraces,and cultivars—represents a valuable reservoir of genetic diversity critical for breeding advancements.Recent breakthroughs in genomic technologies,particularly highthroughput sequencing and multi-omics approaches,have revolutionized the identification of key genes associated with essential agronomic traits within these resources.These innovations enable precise and strategic utilization of genetic diversity,empowering breeders to integrate traits that improve yield potential,resilience to biotic and abiotic stresses,and nutritional quality.This review highlights the critical role of genetic resources and omics-driven innovations in soybean breeding.It also offers insights into strategies for accelerating the development of elite soybean cultivars to meet the growing demands of global soybean production.展开更多
Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underly...Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood,limiting the development of precise and effective treatments.The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract.By mapping expression profiles across various molecular levels,these omics approaches enhance our understanding of the disease’s etiological mechanisms,aid in the identification of novel biomarkers and key pathways,and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies.In this review,we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade,encompassing genomics,transcriptomics,proteomics,and metabolomics.Furthermore,we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.展开更多
In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicin...In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicine(TCM)with the modern technology of network pharmacology(NP)and omics sequencing.GC is a heterogenous disease,as it incorporates several biochemical pathways that contribute to pathogenesis.TCM acknowledges the multifactorial,heterogenous nature of disease and utilizes an integrative approach to medicine.NP,a modern philosophy within drug development,integrates traditional knowledge of nutraceuticals and modern technologies to address the complex interactions of pathways within the body.Omics technologies,which is at the core of precision medicine,has allowed for this newfound principle of drug development.Metabolic pathways are better distinguished,leading to more targeted drug development.However,the use of omics technology needs to be employed to better characterize the subtypes of GC.This will allow TCM’s use of nutraceuticals in the application of NP to better target metabolic pathways that may aid in the prevention of GC as well as enhance treatment.展开更多
Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed...Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.Methods:To quantify CRD,the HCC CRD score(HCCcrds)was developed.Using machine learning algorithms,we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort(n=369),and the robustness of this method was validated.Furthermore,we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.Results:We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis.The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis,higher pathological grade,and advanced clinical stages,while the CRD-related subtype with low HCCcrds had better clinical outcomes.We also identified novel biomarkers for each subtype,such as nicotinamide nmethyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.Conclusion:We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers.Within these groups greater HCCcrds was associated with worse prognosis.This approach has the potential to improve prediction of an individual’s prognosis,guide precision treatments,and assist clinical decision making for HCC patients.展开更多
There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative...There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.展开更多
Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex inte...Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment(TIME).Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME.Furthermore,integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior.In this review,we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC,highlighting their utility in identifying metastasis dissemination,recurrence risk,and therapeutic resistance in patients treated with immunotherapeutic approaches.This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms.Additionally,an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.展开更多
Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of prec...Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular,metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed： 1） the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2） the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.展开更多
Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visuali...Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.展开更多
Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to ...Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to quantify the mRNA expression of a large number of genes in the spatial context of tissues and cells.As a paradigm shift in biological research,spatial transcriptomics can provide both spatial location information and transcriptome-level cellular gene expression data,elucidating the interactions between cells and the microenvironment.From the understanding of the entire functional life cycle of RNA to the characterization of molecular mechanisms to the mapping of gene expression in various tissue regions,by choosing the appropriate spatial transcriptome technology,researchers can achieve a deeper exploration of biological developmental processes,disease pathogenesis,etc.In recent years,the field of spatial transcriptomics has ushered in several challenges along with its rapid development,such as the dependence on sample types,the resolution of visualized genes,the difficulty of commercialization,and the ability to obtain detailed single-cell information.In this paper,we summarize and review the four major categories of spatial transcriptome technologies and compare and analyze the technical advantages and major challenges of multiple research strategies to assist current experimental design and research analysis.Finally,the importance of spatial transcriptomics in the integration of multi-omics analysis and disease modeling as well as the future development prospects are summarized and outlined.展开更多
Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Altho...Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Although stem cell therapy can be highly beneficial in promoting functional recovery, the precise mechanisms of action that are responsible for this effect have yet to be fully elucidated. Omics analysis provides us with a new perspective to investigate the physiological mechanisms and multiple functions of stem cells in ischemic stroke. Transcriptomic, proteomic, and metabolomic analyses have become important tools for discovering biomarkers and analyzing molecular changes under pathological conditions. Omics analysis could help us to identify new pathways mediated by stem cells for the treatment of ischemic stroke via stem cell therapy, thereby facilitating the translation of stem cell therapies into clinical use. In this review, we summarize the pathophysiology of ischemic stroke and discuss recent progress in the development of stem cell therapies for the treatment of ischemic stroke by applying multi-level omics. We also discuss changes in RNAs, proteins, and metabolites in the cerebral tissues and body fluids under stroke conditions and following stem cell treatment, and summarize the regulatory factors that play a key role in stem cell therapy. The exploration of stem cell therapy at the molecular level will facilitate the clinical application of stem cells and provide new treatment possibilities for the complete recovery of neurological function in patients with ischemic stroke.展开更多
This review comprehensively explores the core application of artificial intelligence (AI) in the fields of genomics and bioinformatics, and deeply analyzes how it leads the innovative progress of science. In the cutti...This review comprehensively explores the core application of artificial intelligence (AI) in the fields of genomics and bioinformatics, and deeply analyzes how it leads the innovative progress of science. In the cutting-edge fields of genomics and bioinformatics, the application of AI is propelling a deeper understanding of complex genetic mechanisms and the development of innovative therapeutic approaches. The precision of AI in genomic sequence analysis, coupled with breakthroughs in precise gene editing, such as AI-designed gene editors, significantly enhances our comprehension of gene functions and disease associations . Moreover, AI’s capabilities in disease prediction, assessing individual disease risks through genomic data analysis, provide robust support for personalized medicine. AI applications extend beyond gene identification, gene expression pattern prediction, and genomic structural variant analysis, encompassing key areas such as epigenetics, multi-omics data integration, genetic disease diagnosis, evolutionary genomics, and non-coding RNA function prediction. Despite challenges including data privacy, algorithm transparency, and bioethical issues, the future of AI is expected to continue revolutionizing genomics and bioinformatics, ushering in a new era of personalized medicine and precision treatments.展开更多
Although there has been a notable decrease in cancer mortality rates for many common cancers over the last decades,there remains a concerning lack of progress in understanding and treating rare tumors[1].Rare tumors a...Although there has been a notable decrease in cancer mortality rates for many common cancers over the last decades,there remains a concerning lack of progress in understanding and treating rare tumors[1].Rare tumors are types of tumors that are rare in clinical practice,which are the subclass of rare diseases.The classification of rare tumors varies internationally,with the US Food and Drug Administration and National Cancer Institute defining them as tumors with an incidence rate of less than 15 per 100,000 individuals annually,while the European Medicines Agency set the threshold at 6 per 100,000.According to the results from the National Cancer Center PLATFORM study in China,rare tumors are defined as an annual incidence rate of 2.5/100,000 or less.Although the incidence of each rare tumor is low,the total number of rare tumors is not low.The total number of rare tumor incidence in China is about 560,000 per year,accounting for 14.2%of all cancer patients[2].More than half of the rare tumors lack clinical treatment guidelines,or there is no standard treatment in clinical practice,suggesting there is a huge unmet medical need for effective treatments for rare tumors.展开更多
Fruit quality is the main factor determining market competitiveness;it represents the combination of fruit flavor,color,size,and the contents of aromatic and bioactive substances.Research on the genetic basis of fruit...Fruit quality is the main factor determining market competitiveness;it represents the combination of fruit flavor,color,size,and the contents of aromatic and bioactive substances.Research on the genetic basis of fruit quality can provide new information about fruit biology,promote genomic-assisted breeding,and provide technological support for the regulation of fruit quality via habitat selection and/or the control of environmental conditions.High-throughput sequencing is a powerful research method for studying fruit quality traits,and reference genome sequences for many important fruit crops have provided vast amounts of genomic data.To study fruit quality,it is important to select appropriate omics strategies and to analyze omics data meaningfully.Here,we summarize genomic mechanisms of fruit quality formation:gene duplication,transposable element insertion,structural variations and genome methylation in functional genes.We review the genomic,transcriptomic,and metabolomic strategies that have been used to study the genetic basis of fruit quality traits.We also describe some of the genes associated with fruit traits;these genes are a valuable resource for genomics-assisted breeding and are useful models for deciphering the mechanisms of agronomic traits,such as fruit color,size,hardness,aroma components,sugar and acid content.Finally,to maximize the application of omics information,we propose some further directions for research using omics strategies.展开更多
Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistan...Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.展开更多
基金supported by the National Natural Science Foundation of China(32160578)the Ningxia Hui Autonomous Region Key Research and Develoment Program(2023BCF01027).
文摘Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physiological processes.To achieve a targeted improvement of their adaptability to various environments,a detail analysis of their evolutionary physiological processes is required.While several studies have been carried out in the past by using single-omics techniques to investigate their response to environmental stress,most researchers are now using a multi-omics approach to explore more detail in the biological regulatory networks and molecular mechanisms of lactic acid bacteria in response to environmental stress,thereby overcoming the limitations of single-omics analysis.In this review,we describe the various single-omics approaches that have been used to study environmental stress in lactic acid bacteria,present the advantages of various multi-omics combined analysis approaches,and discuss the potential and practicality of applying emerging single-cell transcriptomics and single-cell metabolomics techniques to the molecular mechanism study of microbes response to environmental stress.Multi-omics approaches enable the accurate identification of complex microbial physiological processes in different environments,allow people to comprehensively reveal the molecular mechanisms of microbes response to stress from different perspectives.Single-cell omics techniques,analyze the targeted regulation of microbial functions in a multi-dimensional space,provides a new perspective on understanding microbes responses environment stress.
基金supported by Professor of Chang Jiang Scholars Program,NSFC(No.81230090)Shanghai Leading Academic Discipline Project(B906)+3 种基金Key laboratory of drug research for special environments,PLA,Shanghai Engineering Research Center for the Preparation of Bioactive Natural Products(No.10DZ2251300)the Scientific Foundation of Shanghai,China(Nos.12401900801,13401900 101)National Major Project of China(No.2011ZX09307-002-03)the National Key Technology R&D Program of China(No.2012BAI29B06)
文摘In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.
基金supported by two DoD grants(HT94252310534 to R.J.T.and HT94252310519 to C.M.K.)the following NIH/NIAMS grants:R01 grants(AR078035 and AR076900 to C.L.+10 种基金AG069401 and AG067698 to L.Q.AI186118,HD112474,and HD107034 to R.J.T.AR076325 and AR071967 to C.M.K.AR080902 and AR072999 to F.G.AR074441 and AR077678 to S.Y.T.AR082667 and AR077527 to A.E.L.AR083900,AR075860 and AR077616 to J.S.),R21 grants(AR077226 to J.S.AR083217 to A.E.L.AR081517 to S.Y.T.)a T32 grant(HD007434 to D.R.K.)P30 center grants(AR074992 and AR073752).
文摘Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.
基金supported by the National Natural Science Foundation of China(82302757)Shenzhen Science and Technology Program(JCY20240813145204006,SGDX20201103095600002,JCYJ20220818103417037,KJZD20230923115200002)+1 种基金Shenzhen Key Laboratory of Digital Surgical Printing Project(ZDSYS201707311542415)Shenzhen Development and Reform Program(XMHT20220106001).
文摘Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.
基金supported by the National Key Research and Development Program of China(2022YFF1003301,2023YFF1000101,2022YFE0130200)the Taishan Scholars Program。
文摘Soybean(Glycine max)is a vital foundation of global food security,providing a primary source of highquality protein and oil for human consumption and animal feed.The rising global population has significantly increased the demand for soybeans,emphasizing the urgency of developing high-yield,stresstolerant,and nutritionally superior cultivars.The extensive collection of soybean germplasm resources—including wild relatives,landraces,and cultivars—represents a valuable reservoir of genetic diversity critical for breeding advancements.Recent breakthroughs in genomic technologies,particularly highthroughput sequencing and multi-omics approaches,have revolutionized the identification of key genes associated with essential agronomic traits within these resources.These innovations enable precise and strategic utilization of genetic diversity,empowering breeders to integrate traits that improve yield potential,resilience to biotic and abiotic stresses,and nutritional quality.This review highlights the critical role of genetic resources and omics-driven innovations in soybean breeding.It also offers insights into strategies for accelerating the development of elite soybean cultivars to meet the growing demands of global soybean production.
基金supported by the General Program of Natural Science Foundation of Guangdong Province(2023A1515011102).
文摘Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood,limiting the development of precise and effective treatments.The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract.By mapping expression profiles across various molecular levels,these omics approaches enhance our understanding of the disease’s etiological mechanisms,aid in the identification of novel biomarkers and key pathways,and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies.In this review,we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade,encompassing genomics,transcriptomics,proteomics,and metabolomics.Furthermore,we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.
文摘In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicine(TCM)with the modern technology of network pharmacology(NP)and omics sequencing.GC is a heterogenous disease,as it incorporates several biochemical pathways that contribute to pathogenesis.TCM acknowledges the multifactorial,heterogenous nature of disease and utilizes an integrative approach to medicine.NP,a modern philosophy within drug development,integrates traditional knowledge of nutraceuticals and modern technologies to address the complex interactions of pathways within the body.Omics technologies,which is at the core of precision medicine,has allowed for this newfound principle of drug development.Metabolic pathways are better distinguished,leading to more targeted drug development.However,the use of omics technology needs to be employed to better characterize the subtypes of GC.This will allow TCM’s use of nutraceuticals in the application of NP to better target metabolic pathways that may aid in the prevention of GC as well as enhance treatment.
基金supported by Tianjian advanced biomedical laboratory key research and development projectHenan Province Natural Science Foundation(grant number:242300421283)+1 种基金Henan Province Science and Technology Research and Development(grant number:242102311176)Henan Province medical science and technology research project(grant number:SBGJ202403038)。
文摘Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.Methods:To quantify CRD,the HCC CRD score(HCCcrds)was developed.Using machine learning algorithms,we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort(n=369),and the robustness of this method was validated.Furthermore,we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.Results:We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis.The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis,higher pathological grade,and advanced clinical stages,while the CRD-related subtype with low HCCcrds had better clinical outcomes.We also identified novel biomarkers for each subtype,such as nicotinamide nmethyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.Conclusion:We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers.Within these groups greater HCCcrds was associated with worse prognosis.This approach has the potential to improve prediction of an individual’s prognosis,guide precision treatments,and assist clinical decision making for HCC patients.
基金supported by the China Science and Technology Innovation 2030-Major Project(Nos.2022ZD0211701,2021ZD0200700)the National Natural Science Foundation of China(Nos.82130042,81830040,22176195,82127801)+3 种基金Shenzhen Science and Technology Serial Funds(Nos.GJHZ20210705141400002,KCXFZ20211020164543006,JCYJ20220818101615033,ZDSYS20220606100606014,KQTD 20221101093608028)the National Key R&D Program of China(No.2022YFF0705003)Guangdong Province Zhu Jiang Talents Plan(No.2021QN02Y028)the Guangdong Science and Technology Department(No.2021B1212030004)。
文摘There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.
基金supported by the Zhejiang Province Traditional Chinese Medicine Science and Technology Project(GZY-ZJ-KJ-24063)the Natural Science Foundation of Zhejiang Province(Q24H290031)the Key Laboratory for Molecular Medicine and Chinese Medicine Preparations(No.GZY-ZJ-SY-2303).
文摘Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment(TIME).Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME.Furthermore,integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior.In this review,we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC,highlighting their utility in identifying metastasis dissemination,recurrence risk,and therapeutic resistance in patients treated with immunotherapeutic approaches.This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms.Additionally,an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.
基金financially supported by grants from the National Natural Science Foundation of China (Nos.31371515 and 3150040263)the Special Financial Grant awarded to S.M. Lam from the China Postdoctoral Science Foundation (No.2014T70137)
文摘Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular,metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed： 1） the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2） the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.
基金supported by Basic and Applied Basic Research Foundation of Guangdong Province(No.2022A1111220217)Medical Scientific Research Foundation of Guangdong Province(Nos.A2023216,A2022124)+3 种基金Science and Technology Program of Guangzhou(Nos.202201010840,202201010810,202102080132,202002030032,202002020023)Health Commission Program of Guangzhou(20212A010021,20201A010081,20211A011116)Science and Technology Project of Panyu,Guangzhou(2022-Z04-009,2022-Z04-090,2022-Z04-072,2021-Z04-013,2020-Z04-026,2019-Z04-02)Scientific Research Project of Guangzhou Panyu Central Hospital(Nos.2022Y002,2021Y004,2021Y002).
文摘Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.
基金supported by the National Natural Science Foundation of China(Grant No.22275071)
文摘Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to quantify the mRNA expression of a large number of genes in the spatial context of tissues and cells.As a paradigm shift in biological research,spatial transcriptomics can provide both spatial location information and transcriptome-level cellular gene expression data,elucidating the interactions between cells and the microenvironment.From the understanding of the entire functional life cycle of RNA to the characterization of molecular mechanisms to the mapping of gene expression in various tissue regions,by choosing the appropriate spatial transcriptome technology,researchers can achieve a deeper exploration of biological developmental processes,disease pathogenesis,etc.In recent years,the field of spatial transcriptomics has ushered in several challenges along with its rapid development,such as the dependence on sample types,the resolution of visualized genes,the difficulty of commercialization,and the ability to obtain detailed single-cell information.In this paper,we summarize and review the four major categories of spatial transcriptome technologies and compare and analyze the technical advantages and major challenges of multiple research strategies to assist current experimental design and research analysis.Finally,the importance of spatial transcriptomics in the integration of multi-omics analysis and disease modeling as well as the future development prospects are summarized and outlined.
基金supported by the National Key Research and Development Program of China,No.2018YFA0108602the CAMS Initiative for Innovative Medicine,No.2021-1-I2M-019the National High Level Hospital Clinical Research Funding,No.2022-PUMCH-C-042(all to XB).
文摘Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Although stem cell therapy can be highly beneficial in promoting functional recovery, the precise mechanisms of action that are responsible for this effect have yet to be fully elucidated. Omics analysis provides us with a new perspective to investigate the physiological mechanisms and multiple functions of stem cells in ischemic stroke. Transcriptomic, proteomic, and metabolomic analyses have become important tools for discovering biomarkers and analyzing molecular changes under pathological conditions. Omics analysis could help us to identify new pathways mediated by stem cells for the treatment of ischemic stroke via stem cell therapy, thereby facilitating the translation of stem cell therapies into clinical use. In this review, we summarize the pathophysiology of ischemic stroke and discuss recent progress in the development of stem cell therapies for the treatment of ischemic stroke by applying multi-level omics. We also discuss changes in RNAs, proteins, and metabolites in the cerebral tissues and body fluids under stroke conditions and following stem cell treatment, and summarize the regulatory factors that play a key role in stem cell therapy. The exploration of stem cell therapy at the molecular level will facilitate the clinical application of stem cells and provide new treatment possibilities for the complete recovery of neurological function in patients with ischemic stroke.
文摘This review comprehensively explores the core application of artificial intelligence (AI) in the fields of genomics and bioinformatics, and deeply analyzes how it leads the innovative progress of science. In the cutting-edge fields of genomics and bioinformatics, the application of AI is propelling a deeper understanding of complex genetic mechanisms and the development of innovative therapeutic approaches. The precision of AI in genomic sequence analysis, coupled with breakthroughs in precise gene editing, such as AI-designed gene editors, significantly enhances our comprehension of gene functions and disease associations . Moreover, AI’s capabilities in disease prediction, assessing individual disease risks through genomic data analysis, provide robust support for personalized medicine. AI applications extend beyond gene identification, gene expression pattern prediction, and genomic structural variant analysis, encompassing key areas such as epigenetics, multi-omics data integration, genetic disease diagnosis, evolutionary genomics, and non-coding RNA function prediction. Despite challenges including data privacy, algorithm transparency, and bioethical issues, the future of AI is expected to continue revolutionizing genomics and bioinformatics, ushering in a new era of personalized medicine and precision treatments.
基金supported by the grant:The National Key Research and Development Program of China(Grant No.2023YFC2508500)Beijing Municipal Health Commission(Beijing Demonstration Research Ward BCRW20200303)+1 种基金National Natural Science Foundation of China(82272951,82272953)Chinese Academy of Medical Sciences(2022-I2M-C&T-B-070).
文摘Although there has been a notable decrease in cancer mortality rates for many common cancers over the last decades,there remains a concerning lack of progress in understanding and treating rare tumors[1].Rare tumors are types of tumors that are rare in clinical practice,which are the subclass of rare diseases.The classification of rare tumors varies internationally,with the US Food and Drug Administration and National Cancer Institute defining them as tumors with an incidence rate of less than 15 per 100,000 individuals annually,while the European Medicines Agency set the threshold at 6 per 100,000.According to the results from the National Cancer Center PLATFORM study in China,rare tumors are defined as an annual incidence rate of 2.5/100,000 or less.Although the incidence of each rare tumor is low,the total number of rare tumors is not low.The total number of rare tumor incidence in China is about 560,000 per year,accounting for 14.2%of all cancer patients[2].More than half of the rare tumors lack clinical treatment guidelines,or there is no standard treatment in clinical practice,suggesting there is a huge unmet medical need for effective treatments for rare tumors.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFD1000200)the Chinese National Natural Science Foundation(Grant No.31800573)+1 种基金the China Postdoctoral Science Foundation(Grant No.2019M662416)We thank Jennifer Smith,PhD,from Liwen Bianji,Edanz Group China(www.liwenbianji.cn/ac),for editing the English text of a draft of this manuscript.
文摘Fruit quality is the main factor determining market competitiveness;it represents the combination of fruit flavor,color,size,and the contents of aromatic and bioactive substances.Research on the genetic basis of fruit quality can provide new information about fruit biology,promote genomic-assisted breeding,and provide technological support for the regulation of fruit quality via habitat selection and/or the control of environmental conditions.High-throughput sequencing is a powerful research method for studying fruit quality traits,and reference genome sequences for many important fruit crops have provided vast amounts of genomic data.To study fruit quality,it is important to select appropriate omics strategies and to analyze omics data meaningfully.Here,we summarize genomic mechanisms of fruit quality formation:gene duplication,transposable element insertion,structural variations and genome methylation in functional genes.We review the genomic,transcriptomic,and metabolomic strategies that have been used to study the genetic basis of fruit quality traits.We also describe some of the genes associated with fruit traits;these genes are a valuable resource for genomics-assisted breeding and are useful models for deciphering the mechanisms of agronomic traits,such as fruit color,size,hardness,aroma components,sugar and acid content.Finally,to maximize the application of omics information,we propose some further directions for research using omics strategies.
基金supported by the National Key R&D Program,Intergovernmental Key Items for International Scientific and Technological Innovation Cooperation(2018YFE0107700)the National Natural Science Foundation of China(31771772)+2 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX19_2109)the National Key R&D Program for Breeding of Top-seven Crops(2017YFD0100801)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
文摘Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.
