Time-resolved multiomics analysis of the genetic regulation of maize kernel moisture

Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are complex traits governed by multiple quantitative trait loci(QTL).Their genetic architecture is incompletely understood.We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR.A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98and 279 loci significantly associated with KMC and KDR.Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks,from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC.Integrating multiomics analysis,several promising candidate genes for KMC and KDR,including Zm00001d047799 and Zm00001d035920,were identified.Further mutant experiments showed that Zm00001d047799,a gene encoding heat shock 70 kDa protein 5,reduced KMC in the late stage of kernel development.Our study provides resources for the identification of candidate genes influencing maize KMC and KDR,shedding light on the genetic architecture of dynamic changes in maize KMC.

Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma

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 survival outcomes.We further identified DGKA as a potential target for the S2 subtype.

An overview of multiomics:a powerful tool applied in cancer molecular subtyping for cancer therapy

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.

Function,mechanism and drug discovery of ubiquitin and ubiquitin-like modification with multiomics profiling for cancer therapy

Ubiquitin(Ub)and ubiquitin-like(Ubl)pathways are critical post-translational modifications that determine whether functional proteins are degraded or activated/inactivated.To date,>600 associated enzymes have been reported that comprise a hierarchical task network(e.g.,E1–E2–E3 cascade enzymatic reaction and deubiquitination)to modulate substrates,including enormous oncoproteins and tumor-suppressive proteins.Several strategies,such as classical biochemical approaches,multiomics,and clinical sample analysis,were combined to elucidate the functional relations between these enzymes and tumors.In this regard,the fundamental advances and follow-on drug discoveries have been crucial in providing vital information concerning contemporary translational efforts to tailor individualized treatment by targeting Ub and Ubl pathways.Correspondingly,emphasizing the current progress of Ub-related pathways as therapeutic targets in cancer is deemed essential.In the present review,we summarize and discuss the functions,clinical significance,and regulatory mechanisms of Ub and Ubl pathways in tumorigenesis as well as the current progress of small-molecular drug discovery.In particular,multiomics analyses were integrated to delineate the complexity of Ub and Ubl modifications for cancer therapy.The present review will provide a focused and up-to-date overview for the researchers to pursue further studies regarding the Ub and Ubl pathways targeted anticancer strategies.

Single-cell protein-DNA interactomics and multiomics tools for deciphering genome regulation

The emergence of single-cell genomic and transcriptomic sequencing accelerates the development of single-cell epigenomic technologies,providing an unprecedented opportunity for decoding cell fate decisions largely encoded in the epigenome.Recent advances in single-cell multimodality epigenomic technologies facilitate directly interrogating the reg-ulatory relationship between multi-layer molecular information in the same cell.In this review,we discuss recent progress in development of single-cell multimodality epigenomic technologies and applications in elucidating cellular diversifications in development and diseases,with a focus on protein-DNA interactomics and regulatory links between epigenome and tran-scriptome.Further,we provide perspective on the future direction of single-cell multiomics tool development as well as challenges facing ahead.

Hepatic steatosis is associated with dysregulated cholesterol metabolism and altered protein acetylation dynamics in chickens

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 changes in hepatic cholesterol metabolism. The findings provides a wealth of information to facilitate a deeper understanding of the pathophysiology of fatty liver and contributes to the development of therapeutic strategies.

New opportunities and challenges of natural products research:When target identification meets single-cell multiomics

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.

Multiomics metabolic and epigenetics regulatory network in cancer:A systems biology perspective

Genetic,epigenetic,and metabolic alterations are all hallmarks of cancer.However,the epigenome and metabolome are both highly complex and dynamic biological networks in vivo.The interplay between the epigenome and metabolome contributes to a biological system that is responsive to the tumor microenvironment and possesses a wealth of unknown biomarkers and targets of cancer therapy.From this perspective,we first review the state of high-throughput biological data acquisition(i.e.multiomics data)and analysis(i.e.computational tools)and then propose a conceptual in silico metabolic and epigenetic regulatory network(MER-Net)that is based on these current high-throughput methods.The conceptual MER-Net is aimed at linking metabolomic and epigenomic networks through observation of biological processes,omics data acquisition,analysis of network information,and integration with validated database knowledge.Thus,MER-Net could be used to reveal new potential biomarkers and therapeutic targets using deep learning models to integrate and analyze large multiomics networks.We propose that MER-Net can serve as a tool to guide integrated metabolomics and epigenomics research or can be modified to answer other complex biological and clinical questions using multiomics data.

Recent Progress and Future Direction for the Application of Multiomics Data in Clinical Liver Transplantation

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.

Integration and implementation of precision medicine in the multifaceted inflammatory bowel disease

Inflammatory bowel disease(IBD)is a complex disease with variability in genetic,environmental,and lifestyle factors affecting disease presentation and course.Precision medicine has the potential to play a crucial role in managing IBD by tailoring treatment plans based on the heterogeneity of clinical and temporal variability of patients.Precision medicine is a population-based approach to managing IBD by integrating environmental,genomic,epigenomic,transcriptomic,proteomic,and metabolomic factors.It is a recent and rapidly developing medicine.The widespread adoption of precision medicine worldwide has the potential to result in the early detection of diseases,optimal utilization of healthcare resources,enhanced patient outcomes,and,ultimately,improved quality of life for individuals with IBD.Though precision medicine is promising in terms of better quality of patient care,inadequacies exist in the ongoing research.There is discordance in study conduct,and data collection,utilization,interpretation,and analysis.This review aims to describe the current literature on precision medicine,its multiomics approach,and future directions for its application in IBD.

Advancing the precision management of inflammatory bowel disease in the era of omics approaches and new technology

There is great heterogeneity among inflammatory bowel disease(IBD)patients in terms of pathogenesis,clinical manifestation,response to treatment,and prognosis,which requires the individualized and precision management of patients.Many studies have focused on prediction biomarkers and models for assessing IBD disease type,activity,severity,and prognosis.During the era of biologics,how to predict the response and side effects of patients to different treatments and how to quickly recognize the loss of response have also become important topics.Multiomics is a promising area for investigating the complex network of IBD pathogenesis.Integrating numerous amounts of data requires the use of artificial intelligence.

Biomarkers and subtypes of deranged lipid metabolism in nonalcoholic fatty liver disease

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.

Precision Medicine in Cardiovascular Diseases

Since President Obama announced the Precision Medicine Initiative in the United States,more and more attention has been paid to precision medicine.However,clinicians have already used it to treat conditions such as cancer.Many cardiovascular diseases have a familial presentation,and genetic variants are associated with the prevention,diagnosis,and treatment of cardiovascular diseases,which are the basis for providing precise care to patients with cardiovascular diseases.Large-scale cohorts and multiomics are critical components of precision medicine.Here we summarize the application of precision medicine to cardiovascular diseases based on cohort and omic studies,and hope to elicit discussion about future health care.

Emerging use of artificial intelligence in inflammatory bowel disease

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.

Integrative analysis of the transcriptome and metabolome reveals the importance of hepatokine FGF21 in liver aging

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.

Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation

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.

Role of gut microbiota in identification of novel TCM-derived active metabolites

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.

20(S)-Protopanaxatriol promotes the binding of P53 and DNA to regulate the antitumor network via multiomic analysis

Although the tumor suppressor P53 is known to regulate a broad network of signaling pathways,it is still unclear how certain drugs influence these P53 signaling netw orks.Here,we used a comprehensive singlecell multiomics view of the effects of ginsenosides on cancer cells.Transcriptome and proteome profiling revealed that the antitumor activity of ginsenosides is closely as sociated with P53 protein.A miRNA-proteome interaction network revealed that P53 controlled the transcription of at least 38 proteins,and proteomemetabolome profiling analysis revealed that P53 regulated proteins involved in nucleotide metabolism,amino acid metabolism and"Warburg effect".The results of integrative multiomics analysis revealed P53 protein as a potential key target that influences the anti-tumor activity of ginsenosides.Furthermore,by applying affinity mass spectrometry(MS)screening and surface plasmon resonance fragment library screening,we confirmed that 20(S)-protopanaxatriol directly targeted adj acent regions of the P53 DNA-binding pocket and promoted the stability of P53-DNA interactions,which further induced a series of omics changes.

Unveiling E2F4,TEAD1 and AP-1 as regulatory transcription factors of the replicative senescence program by multi-omics analysis

Senescence,a stable state of growth arrest,affects many physiological and pathophysiological processes,especially aging.Previous work has indicated that transcription factors(TFs)play a role in regulating senescence.However,a systematic study of regulatory TFs during replicative senescence(RS)using multiomics analysis is still lacking.Here,we generated timeresolved RNA-seq,reduced representation bisulfite sequencing(RRBS)and ATAC-seq datasets during RS of mouse skin fibroblasts,which demonstrated that an enhanced inflammatory response and reduced proliferative capacity were the main characteristics of RS in both the transcriptome and epigenome.Through integrative analysis and genetic manipulations,we found that transcription factors E2F4,TEAD1 and AP-1 are key regulators of RS.Overexpression of E2f4 improved cellular proliferative capacity,attenuated SA-β-Gal activity and changed RS-associated differentially methylated sites(DMSs).Moreover,knockdown of Tead1 attenuated SA-β-Gal activity and partially altered the RS-associated transcriptome.In addition,knockdown of Atf3,one member of AP-1 superfamily TFs,reduced Cdkn2a(p16)expression in pre-senescent fibroblasts.Taken together,the results of this study identified transcription factors regulating the senescence program through multi-omics analysis,providing potential therapeutic targets for anti-aging.

Oxidized Black Phosphorus Nanosheets as an Inorganic Antiresorptive Agent

Black phosphorus(BP)is a newly discovered two-dimensional material that has promising applications from bioelectronics to biomedicine.However,facile oxidation of BP leads to changes in surface chemical composition and physical properties,often being referred to as the degradation process of BP.Degradation products of BP nanosheets,namely,oxidized BP nanosheets(oBPNSs),are routinely considered as by-products without many uses.Herein,we found that oBPNSs displayed excellent osteoclastogenesis inhibition effects without impairing cell viability.In contrast to the classic antiresorptive bisphosphonate drugs,oBPNSs showed a different mode of action by suppressing the maturation of osteoclasts.Bone resorption assays,osteoclast actin ring analysis,and tartrate-resistant acid phosphate activity assay results indicated that oBPNSs suppressed receptor activator of nuclear factor-κB(NF-κB)ligand(RANKL)-induced osteoclastogenesis in a dose-and oxidation-dependent manner.Transcriptomic and proteomic analyses indicated that oBPNSs inhibited the activation of the NF-κB signaling pathway and phosphorylation of mitogen-activated protein kinase(MAPK)in differentiated osteoclasts,as confirmed by Western blot analysis.Our results suggest that oBPNSs might be potential antiresorptive nanomaterials to treat osteoporosis.