Inflammatory bowel disease(IBD)is a complex,immune-mediated gastrointestinal disorder with ill-defined etiology,multifaceted diagnostic criteria,and unpredictable treatment response.Innovations in IBD diagnostics,incl...Inflammatory bowel disease(IBD)is a complex,immune-mediated gastrointestinal disorder with ill-defined etiology,multifaceted diagnostic criteria,and unpredictable treatment response.Innovations in IBD diagnostics,including developments in genomic sequencing and molecular analytics,have generated tremendous interest in leveraging these large data platforms into clinically meaningful tools.Artificial intelligence,through machine learning facilitates the interpretation of large arrays of data,and may provide insight to improving IBD outcomes.While potential applications of machine learning models are vast,further research is needed to generate standardized models that can be adapted to target IBD populations.展开更多
Omics data address key issues in liver transplantation(LT)as the most effective therapeutic means for end-stage liver disease.The purpose of this study was to review the current application and future direction for om...Omics data address key issues in liver transplantation(LT)as the most effective therapeutic means for end-stage liver disease.The purpose of this study was to review the current application and future direction for omics in LT.We reviewed the use of multiomics to elucidate the pathogenesis leading to LT and prognostication.Future directions with respect to the use of omics in LT are also described based on perspectives of surgeons with experience in omics.Significant molecules were identified and summarized based on omics,with a focus on post-transplant liver fibrosis,early allograft dysfunction,tumor recurrence,and graft failure.We emphasized the importance omics for clinicians who perform LTs and prioritized the directions that should be established.We also outlined the ideal workflow for omics in LT.In step with advances in technology,the quality of omics data can be guaranteed using an improved algorithm at a lower price.Concerns should be addressed on the translational value of omics for better therapeutic effects in patients undergoing LT.展开更多
Nonalcoholic fatty liver disease(NAFLD)is a heterogeneous and complex disease that is imprecisely diagnosed by liver biopsy.NAFLD covers a spectrum that ranges from simple steatosis,nonalcoholic steatohepatitis(NASH)w...Nonalcoholic fatty liver disease(NAFLD)is a heterogeneous and complex disease that is imprecisely diagnosed by liver biopsy.NAFLD covers a spectrum that ranges from simple steatosis,nonalcoholic steatohepatitis(NASH)with varying degrees of fibrosis,to cirrhosis,which is a major risk factor for hepatocellular carcinoma.Lifestyle and eating habit changes during the last century have made NAFLD the most common liver disease linked to obesity,type 2 diabetes mellitus and dyslipidemia,with a global prevalence of 25%.NAFLD arises when the uptake of fatty acids(FA)and triglycerides(TG)from circulation and de novo lipogenesis saturate the rate of FAβ-oxidation and verylow density lipoprotein(VLDL)-TG export.Deranged lipid metabolism is also associated with NAFLD progression from steatosis to NASH,and therefore,alterations in liver and serum lipidomic signatures are good indicators of the disease’s development and progression.This review focuses on the importance of the classification of NAFLD patients into different subtypes,corresponding to the main alteration(s)in the major pathways that regulate FA homeostasis leading,in each case,to the initiation and progression of NASH.This concept also supports the targeted intervention as a key approach to maximize therapeutic efficacy and opens the door to the development of precise NASH treatments.展开更多
Traditional Chinese Medicine(TCM)has been extensively used to ameliorate diseases in Asia for over thousands of years.However,owing to a lack of formal scientific validation,the absence of information regarding the me...Traditional Chinese Medicine(TCM)has been extensively used to ameliorate diseases in Asia for over thousands of years.However,owing to a lack of formal scientific validation,the absence of information regarding the mechanisms underlying TCMs restricts their application.After oral administration,TCM herbal ingredients frequently are not directly absorbed by the host,but rather enter the intestine to be transformed by gut microbiota.The gut microbiota is a microbial community living in animal intestines,and functions to maintain host homeostasis and health.Increasing evidences indicate that TCM herbs closely affect gut microbiota composition,which is associated with the conversion of herbal components into active metabolites.These may significantly affect the therapeutic activity of TCMs.Microbiota analyses,in conjunction with modern multiomics platforms,can together identify novel functional metabolites and form the basis of future TCM research.展开更多
Natural products, and especially the active ingredients found in traditional Chinese medicine(TCM), have a thousand-year-long history of clinical use and a strong theoretical basis in TCM. As such,traditional remedies...Natural products, and especially the active ingredients found in traditional Chinese medicine(TCM), have a thousand-year-long history of clinical use and a strong theoretical basis in TCM. As such,traditional remedies provide shortcuts for the development of original new drugs in China, and increasing numbers of natural products are showing great therapeutic potential in various diseases. This paper reviews the molecular mechanisms of action of natural products from different sources used in the treatment of inflammatory diseases and cancer, introduces the methods and newly emerging technologies used to identify and validate the targets of natural active ingredients, enumerates the expansive list of TCM used to treat inflammatory diseases and cancer, and summarizes the patterns of action of emerging technologies such as single-cell multiomics, network pharmacology, and artificial intelligence in the pharmacological studies of natural products to provide insights for the development of innovative natural product-based drugs. Our hope is that we can make use of advances in target identification and singlecell multiomics to obtain a deeper understanding of actions of mechanisms of natural products that will allow innovation and revitalization of TCM and its swift industrialization and internationalization.展开更多
Despite the success of antiretroviral therapy,human immunodeficiency virus(HIV)cannot be cured because of a reservoir of latently infected cells that evades therapy.To understand the mechanisms of HIV latency,we emplo...Despite the success of antiretroviral therapy,human immunodeficiency virus(HIV)cannot be cured because of a reservoir of latently infected cells that evades therapy.To understand the mechanisms of HIV latency,we employed an integrated single-cell RNA sequencing(scRNA-seq)and single-cell assay for transposase-accessible chromatin with sequencing(scATAC-seq)approach to simultaneously profile the transcriptomic and epigenomic characteristics of~125,000 latently infected primary CD4^(+)T cells after reactivation using three different latency reversing agents.Differentially expressed genes and differentially accessible motifs were used to examine transcriptional pathways and transcription factor(TF)activities across the cell population.We identified cellular transcripts and TFs whose expression/activity was correlated with viral reactivation and demonstrated that a machine learning model trained on these data was 75%-79%accurate at predicting viral reactivation.Finally,we validated the role of two candidate HIV-regulating factors,FOXP1 and GATA3,in viral transcription.These data demonstrate the power of integrated multimodal single-cell analysis to uncover novel relationships between host cell factors and HIV latency.展开更多
During the process of carcinogenesis and tumor progression,various molecular alternations occur in different omics levels.In recent years,multiomics approaches including genomics,epigenetics,transcriptomics,proteomics...During the process of carcinogenesis and tumor progression,various molecular alternations occur in different omics levels.In recent years,multiomics approaches including genomics,epigenetics,transcriptomics,proteomics,metabolomics,single-cell omics,and spatial omics have been applied in mapping diverse omics profiles of cancers.The development of high-throughput technologies such as sequencing and mass spectrometry has revealed different omics levels of tumor cells or tissues separately.While focusing on a single omics level results in a lack of accuracy,joining multiple omics approaches together undoubtedly benefits accurate molecular subtyping and precision medicine for cancer patients.With the deepening of tumor research in recent years,taking pathological classification as the only criterion of diagnosis and predicting prognosis and treatment response is found to be not accurate enough.Therefore,identifying precise molecular subtypes by exploring the molecular alternations during tumor occurrence and development is of vital importance.The review provides an overview of the advanced technologies and recent progress in multiomics applied in cancer molecular subtyping and detailedly explains the application of multiomics in identifying cancer driver genes and metastasis-related genes,exploring tumor microenvironment,and selecting liquid biopsy biomarkers and potential therapeutic targets.展开更多
Background:Intrahepatic cholangiocarcinoma(iCCA)is a highly heteroge-neous and lethal hepatobiliary tumor with few therapeutic strategies.The metabolic reprogramming of tumor cells plays an essential role in the devel...Background:Intrahepatic cholangiocarcinoma(iCCA)is a highly heteroge-neous and lethal hepatobiliary tumor with few therapeutic strategies.The metabolic reprogramming of tumor cells plays an essential role in the develop-ment of tumors,while the metabolic molecular classification of iCCA is largely unknown.Here,we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients,hoping to provide a novel perspective to understand and treat iCCA.Methods:We performed integrated multiomics analysis in 116 iCCA samples,including whole-exome sequencing,bulk RNA-sequencing and proteome anal-ysis.Based on the non-negative matrix factorization method and the protein abundance of metabolic genes in human genome-scale metabolic models,the metabolic subtype of iCCA was determined.Survival and prognostic gene analy-ses were used to compare overall survival(OS)differences between metabolic subtypes.Cell proliferation analysis,5-ethynyl-2’-deoxyuridine(EdU)assay,colony formation assay,RNA-sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinaseα(DGKA)in iCCA cells.Results:Three metabolic subtypes(S1-S3)with subtype-specific biomarkers of iCCA were identified.These metabolic subtypes presented with distinct prog-noses,metabolic features,immune microenvironments,and genetic alterations.The S2 subtype with the worst survival showed the activation of some special metabolic processes,immune-suppressed microenvironment and Kirsten ratsar-coma viral oncogene homolog(KRAS)/AT-rich interactive domain 1A(ARID1A)mutations.Among the S2 subtype-specific upregulated proteins,DGKA was further identified as a potential drug target for iCCA,which promoted cell proliferation by enhancing phosphatidic acid(PA)metabolism and activating mitogen-activated protein kinase(MAPK)signaling.Conclusion:Viamultiomics analyses,we identified three metabolic subtypes of iCCA,revealing that the S2 subtype exhibited the poorest sur展开更多
Aging is a contributor to liver disease.Hence,the concept of liver aging has become prominent and has attracted considerable interest,but its underlying mechanism remains poorly understood.In our study,the internal me...Aging is a contributor to liver disease.Hence,the concept of liver aging has become prominent and has attracted considerable interest,but its underlying mechanism remains poorly understood.In our study,the internal mechanism of liver aging was explored via multi-omics analysis and molecular experiments to support future targeted therapy.An aged rat liver model was established with D-galactose,and two other senescent hepatocyte models were established by treating HepG2 cells with D-galactose and H2O2.We then performed transcriptomic and metabolomic assays of the aged liver model and transcriptome analyses of the senescent hepatocyte models.In livers,genes related to peroxisomes,fatty acid elongation,and fatty acid degradation exhibited down-regulated expression with aging,and the hepatokine Fgf21 expression was positively correlated with the down-regulation of these genes.In senescent hepatocytes,similar to the results found in aged livers,FGF21 expression was also decreased.Moreover,the expressions of cell cycle-related genes were significantly down-regulated,and the down-regulated gene E2F8 was the key cell cycle-regulating transcription factor.We then validated that FGF21 overexpression can protect against liver aging and that FGF21 can attenuate the declines in the antioxidant and regenerative capacities in the aging liver.We successfully validated the results from cellular and animal experiments using human liver and blood samples.Our study indicated that FGF21 is an important target for inhibiting liver aging and suggested that pharmacological prevention of the reduction in FGF21 expression due to aging may be used to treat liver aging-related diseases.展开更多
Background Hepatic steatosis is a prevalent manifestation of fatty liver, that has detrimental effect on the health and productivity of laying hens, resulting in economic losses to the poultry industry. Here, we aimed...Background Hepatic steatosis is a prevalent manifestation of fatty liver, that has detrimental effect on the health and productivity of laying hens, resulting in economic losses to the poultry industry. Here, we aimed to systematically investigate the genetic regulatory mechanisms of hepatic steatosis in laying hens.Methods Ninety individuals with the most prominent characteristics were selected from 686 laying hens according to the accumulation of lipid droplets in the liver, and were graded into three groups, including the control, mild hepatic steatosis and severe hepatic steatosis groups. A combination of transcriptome, proteome, acetylome and lipidome analyses, along with bioinformatics analysis were used to screen the key biological processes, modifications and lipids associated with hepatic steatosis.Results The rationality of the hepatic steatosis grouping was verified through liver biochemical assays and RNA-seq. Hepatic steatosis was characterized by increased lipid deposition and multiple metabolic abnormalities. Integration of proteome and acetylome revealed that differentially expressed proteins(DEPs) interacted with differentially acetylated proteins(DAPs) and were involved in maintaining the metabolic balance in the liver. Acetylation alterations mainly occurred in the progression from mild to severe hepatic steatosis, i.e., the enzymes in the fatty acid oxidation and bile acid synthesis pathways were significantly less acetylated in severe hepatic steatosis group than that in mild group(P < 0.05). Lipidomics detected a variety of sphingolipids(SPs) and glycerophospholipids(GPs) were negatively correlated with hepatic steatosis(r ≤-0.5, P < 0.05). Furthermore, the severity of hepatic steatosis was associated with a decrease in cholesterol and bile acid synthesis and an increase in exogenous cholesterol transport.Conclusions In addition to acquiring a global and thorough picture of hepatic steatosis in laying hens, we were able to reveal the role of acetylation in hepatic steatosis and depict the 展开更多
文摘Inflammatory bowel disease(IBD)is a complex,immune-mediated gastrointestinal disorder with ill-defined etiology,multifaceted diagnostic criteria,and unpredictable treatment response.Innovations in IBD diagnostics,including developments in genomic sequencing and molecular analytics,have generated tremendous interest in leveraging these large data platforms into clinically meaningful tools.Artificial intelligence,through machine learning facilitates the interpretation of large arrays of data,and may provide insight to improving IBD outcomes.While potential applications of machine learning models are vast,further research is needed to generate standardized models that can be adapted to target IBD populations.
基金supported by Innovative Research Groups of National Natural Science Foundation of China(81721091)Major Program of National Natural Science Foundation of China(91542205)+8 种基金National S&T Major Project(2017ZX 10203205)National Natural Science Foundation of China(81902813)Zhejiang International Science and Technology Cooperation Project(2016C04003)Zhejiang Provincial Natural Science Foundation of China(LY18H030002)Zhejiang Medical Association(grant no.2019ZYC-A81)International Youth Exchange Programme by China Association for Science and Technology(2019),Tianqing Liver Diseases Research Fund(TQGB20200114)Medical Health Science and Technology Project of Zhejiang Provincial Health Commission(2021KY145)Organ Transplantation Overseas Training for Youth Talents from Shulan Excellent Talent Project,CSCO(Chinese Society Of Clinical Oncology)-Bayer Tumor Research Funding(Y-bayer202001/zb-0003)Open Fund of Key laboratory of High-Incidence-Tumor Prevention&Treatment(Guangxi Medical University)belonged to Ministry of Education.
文摘Omics data address key issues in liver transplantation(LT)as the most effective therapeutic means for end-stage liver disease.The purpose of this study was to review the current application and future direction for omics in LT.We reviewed the use of multiomics to elucidate the pathogenesis leading to LT and prognostication.Future directions with respect to the use of omics in LT are also described based on perspectives of surgeons with experience in omics.Significant molecules were identified and summarized based on omics,with a focus on post-transplant liver fibrosis,early allograft dysfunction,tumor recurrence,and graft failure.We emphasized the importance omics for clinicians who perform LTs and prioritized the directions that should be established.We also outlined the ideal workflow for omics in LT.In step with advances in technology,the quality of omics data can be guaranteed using an improved algorithm at a lower price.Concerns should be addressed on the translational value of omics for better therapeutic effects in patients undergoing LT.
文摘Nonalcoholic fatty liver disease(NAFLD)is a heterogeneous and complex disease that is imprecisely diagnosed by liver biopsy.NAFLD covers a spectrum that ranges from simple steatosis,nonalcoholic steatohepatitis(NASH)with varying degrees of fibrosis,to cirrhosis,which is a major risk factor for hepatocellular carcinoma.Lifestyle and eating habit changes during the last century have made NAFLD the most common liver disease linked to obesity,type 2 diabetes mellitus and dyslipidemia,with a global prevalence of 25%.NAFLD arises when the uptake of fatty acids(FA)and triglycerides(TG)from circulation and de novo lipogenesis saturate the rate of FAβ-oxidation and verylow density lipoprotein(VLDL)-TG export.Deranged lipid metabolism is also associated with NAFLD progression from steatosis to NASH,and therefore,alterations in liver and serum lipidomic signatures are good indicators of the disease’s development and progression.This review focuses on the importance of the classification of NAFLD patients into different subtypes,corresponding to the main alteration(s)in the major pathways that regulate FA homeostasis leading,in each case,to the initiation and progression of NASH.This concept also supports the targeted intervention as a key approach to maximize therapeutic efficacy and opens the door to the development of precise NASH treatments.
基金We would like to express our thankfulness for funding provided from CORPD1F0013 and CORPD1J0052 from Chang Gung Memorial Hospital,Microbiota Research Center from Chang Gung Universitythe Research Center for Emerging Viral Infections from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project(MOST109-2634-F-182-001,109-2320-B-030-010,109-2327-B-182-001).
文摘Traditional Chinese Medicine(TCM)has been extensively used to ameliorate diseases in Asia for over thousands of years.However,owing to a lack of formal scientific validation,the absence of information regarding the mechanisms underlying TCMs restricts their application.After oral administration,TCM herbal ingredients frequently are not directly absorbed by the host,but rather enter the intestine to be transformed by gut microbiota.The gut microbiota is a microbial community living in animal intestines,and functions to maintain host homeostasis and health.Increasing evidences indicate that TCM herbs closely affect gut microbiota composition,which is associated with the conversion of herbal components into active metabolites.These may significantly affect the therapeutic activity of TCMs.Microbiota analyses,in conjunction with modern multiomics platforms,can together identify novel functional metabolites and form the basis of future TCM research.
基金supported by National Natural Science Foundation of China(Nos.81872877,81730100,91853109,82073975)School of Life Science(NJU)-Sipimo Joint Funds,Characteristic Innovation Project of Guangdong Provincial Education Department(Nos.2019GKTSCX039,2020KTSCX295,China),School-Level Scientific Research Project of Shenzhen Polytechnic(No.6021310023K,China)+1 种基金Natural Science Research of Jiangsu Higher Education Institutions of China(No.22KJB360005)Fundamental Research Funds for the Central Universities(No.020814380174,China).
文摘Natural products, and especially the active ingredients found in traditional Chinese medicine(TCM), have a thousand-year-long history of clinical use and a strong theoretical basis in TCM. As such,traditional remedies provide shortcuts for the development of original new drugs in China, and increasing numbers of natural products are showing great therapeutic potential in various diseases. This paper reviews the molecular mechanisms of action of natural products from different sources used in the treatment of inflammatory diseases and cancer, introduces the methods and newly emerging technologies used to identify and validate the targets of natural active ingredients, enumerates the expansive list of TCM used to treat inflammatory diseases and cancer, and summarizes the patterns of action of emerging technologies such as single-cell multiomics, network pharmacology, and artificial intelligence in the pharmacological studies of natural products to provide insights for the development of innovative natural product-based drugs. Our hope is that we can make use of advances in target identification and singlecell multiomics to obtain a deeper understanding of actions of mechanisms of natural products that will allow innovation and revitalization of TCM and its swift industrialization and internationalization.
基金supported by the following grants from the National Institutes of Health:the National Institute of Allergy and Infectious Diseases(NIAID)(Grant No.R01 AI143381)to Edward P.Brownethe NIAID(Grant No.UM1 AI164567)to David M.Murdoch,the National Institute on Drug Abuse(NIDA)(Grant No.R61 DA047023)to Edward P.Browne+2 种基金the NIAID(Grant No.T32 AI007419)to Jackson J.Petersonthe UNC-Chapel Hill Molecular Biology of Viral Diseases T32 to Jackson J.Peterson,the National Institute of General Medical Sciences(NIGMS)(Grant No.R35 GM138342)to Yuchao Jiangthe NIDA(Grant No.R01 DA054994)to Cynthia D.Rudin.
文摘Despite the success of antiretroviral therapy,human immunodeficiency virus(HIV)cannot be cured because of a reservoir of latently infected cells that evades therapy.To understand the mechanisms of HIV latency,we employed an integrated single-cell RNA sequencing(scRNA-seq)and single-cell assay for transposase-accessible chromatin with sequencing(scATAC-seq)approach to simultaneously profile the transcriptomic and epigenomic characteristics of~125,000 latently infected primary CD4^(+)T cells after reactivation using three different latency reversing agents.Differentially expressed genes and differentially accessible motifs were used to examine transcriptional pathways and transcription factor(TF)activities across the cell population.We identified cellular transcripts and TFs whose expression/activity was correlated with viral reactivation and demonstrated that a machine learning model trained on these data was 75%-79%accurate at predicting viral reactivation.Finally,we validated the role of two candidate HIV-regulating factors,FOXP1 and GATA3,in viral transcription.These data demonstrate the power of integrated multimodal single-cell analysis to uncover novel relationships between host cell factors and HIV latency.
基金National Natural Science Foundation of China(82173332).
文摘During the process of carcinogenesis and tumor progression,various molecular alternations occur in different omics levels.In recent years,multiomics approaches including genomics,epigenetics,transcriptomics,proteomics,metabolomics,single-cell omics,and spatial omics have been applied in mapping diverse omics profiles of cancers.The development of high-throughput technologies such as sequencing and mass spectrometry has revealed different omics levels of tumor cells or tissues separately.While focusing on a single omics level results in a lack of accuracy,joining multiple omics approaches together undoubtedly benefits accurate molecular subtyping and precision medicine for cancer patients.With the deepening of tumor research in recent years,taking pathological classification as the only criterion of diagnosis and predicting prognosis and treatment response is found to be not accurate enough.Therefore,identifying precise molecular subtypes by exploring the molecular alternations during tumor occurrence and development is of vital importance.The review provides an overview of the advanced technologies and recent progress in multiomics applied in cancer molecular subtyping and detailedly explains the application of multiomics in identifying cancer driver genes and metastasis-related genes,exploring tumor microenvironment,and selecting liquid biopsy biomarkers and potential therapeutic targets.
基金This project was supported by grants from the National Natural Science Foundation of China(82273387,82273386,82073217,32270711,82073218 and 82003084)the National Key Research and Develop-ment Program of China(2018YFC1312100)+3 种基金Beijing Nova Program(20220484230)Shanghai Municipal Science and Technology Major Project(2018SHZDZX05)Shanghai Municipal Key Clinical Specialty,CAMS Innovation Fund for Medical Sciences(CIFMS)(2019-I2M-5-058)the State Key Laboratory of Proteomics(SKLP-K202004).
文摘Background:Intrahepatic cholangiocarcinoma(iCCA)is a highly heteroge-neous and lethal hepatobiliary tumor with few therapeutic strategies.The metabolic reprogramming of tumor cells plays an essential role in the develop-ment of tumors,while the metabolic molecular classification of iCCA is largely unknown.Here,we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients,hoping to provide a novel perspective to understand and treat iCCA.Methods:We performed integrated multiomics analysis in 116 iCCA samples,including whole-exome sequencing,bulk RNA-sequencing and proteome anal-ysis.Based on the non-negative matrix factorization method and the protein abundance of metabolic genes in human genome-scale metabolic models,the metabolic subtype of iCCA was determined.Survival and prognostic gene analy-ses were used to compare overall survival(OS)differences between metabolic subtypes.Cell proliferation analysis,5-ethynyl-2’-deoxyuridine(EdU)assay,colony formation assay,RNA-sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinaseα(DGKA)in iCCA cells.Results:Three metabolic subtypes(S1-S3)with subtype-specific biomarkers of iCCA were identified.These metabolic subtypes presented with distinct prog-noses,metabolic features,immune microenvironments,and genetic alterations.The S2 subtype with the worst survival showed the activation of some special metabolic processes,immune-suppressed microenvironment and Kirsten ratsar-coma viral oncogene homolog(KRAS)/AT-rich interactive domain 1A(ARID1A)mutations.Among the S2 subtype-specific upregulated proteins,DGKA was further identified as a potential drug target for iCCA,which promoted cell proliferation by enhancing phosphatidic acid(PA)metabolism and activating mitogen-activated protein kinase(MAPK)signaling.Conclusion:Viamultiomics analyses,we identified three metabolic subtypes of iCCA,revealing that the S2 subtype exhibited the poorest sur
基金the Research Unit Project of the Chinese Academy of Medical Sciences(No.2019-I2M-5-030)the Research Project of Jinan Microecological Biomedicine Shandong Laboratory(China)(No.JNL2022002A)the Fundamental Research Funds for the Central Universities(China)(No.226-2023-00107).
文摘Aging is a contributor to liver disease.Hence,the concept of liver aging has become prominent and has attracted considerable interest,but its underlying mechanism remains poorly understood.In our study,the internal mechanism of liver aging was explored via multi-omics analysis and molecular experiments to support future targeted therapy.An aged rat liver model was established with D-galactose,and two other senescent hepatocyte models were established by treating HepG2 cells with D-galactose and H2O2.We then performed transcriptomic and metabolomic assays of the aged liver model and transcriptome analyses of the senescent hepatocyte models.In livers,genes related to peroxisomes,fatty acid elongation,and fatty acid degradation exhibited down-regulated expression with aging,and the hepatokine Fgf21 expression was positively correlated with the down-regulation of these genes.In senescent hepatocytes,similar to the results found in aged livers,FGF21 expression was also decreased.Moreover,the expressions of cell cycle-related genes were significantly down-regulated,and the down-regulated gene E2F8 was the key cell cycle-regulating transcription factor.We then validated that FGF21 overexpression can protect against liver aging and that FGF21 can attenuate the declines in the antioxidant and regenerative capacities in the aging liver.We successfully validated the results from cellular and animal experiments using human liver and blood samples.Our study indicated that FGF21 is an important target for inhibiting liver aging and suggested that pharmacological prevention of the reduction in FGF21 expression due to aging may be used to treat liver aging-related diseases.
基金funded in part by grants from the National Natural Science Foundation of China (No.31930105)National Key Research and Development Program of China (2022YFF1000204)China Agriculture Research Systems (CARS-40)。
文摘Background Hepatic steatosis is a prevalent manifestation of fatty liver, that has detrimental effect on the health and productivity of laying hens, resulting in economic losses to the poultry industry. Here, we aimed to systematically investigate the genetic regulatory mechanisms of hepatic steatosis in laying hens.Methods Ninety individuals with the most prominent characteristics were selected from 686 laying hens according to the accumulation of lipid droplets in the liver, and were graded into three groups, including the control, mild hepatic steatosis and severe hepatic steatosis groups. A combination of transcriptome, proteome, acetylome and lipidome analyses, along with bioinformatics analysis were used to screen the key biological processes, modifications and lipids associated with hepatic steatosis.Results The rationality of the hepatic steatosis grouping was verified through liver biochemical assays and RNA-seq. Hepatic steatosis was characterized by increased lipid deposition and multiple metabolic abnormalities. Integration of proteome and acetylome revealed that differentially expressed proteins(DEPs) interacted with differentially acetylated proteins(DAPs) and were involved in maintaining the metabolic balance in the liver. Acetylation alterations mainly occurred in the progression from mild to severe hepatic steatosis, i.e., the enzymes in the fatty acid oxidation and bile acid synthesis pathways were significantly less acetylated in severe hepatic steatosis group than that in mild group(P < 0.05). Lipidomics detected a variety of sphingolipids(SPs) and glycerophospholipids(GPs) were negatively correlated with hepatic steatosis(r ≤-0.5, P < 0.05). Furthermore, the severity of hepatic steatosis was associated with a decrease in cholesterol and bile acid synthesis and an increase in exogenous cholesterol transport.Conclusions In addition to acquiring a global and thorough picture of hepatic steatosis in laying hens, we were able to reveal the role of acetylation in hepatic steatosis and depict the
