The advantages of multi-level omics research on stem cell-based therapies for ischemic stroke

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.

Omics-based biomarkers as useful tools in metabolic dysfunctionassociated steatotic liver disease clinical practice:How far are we?

Unmet needs exist in metabolic dysfunction-associated steatotic liver disease(MASLD)risk stratification.Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is still limited.Incorporating novel biomarkers could represent a meaningful improvement to current risk predictors.With this aim,omics technologies have revolutionized the process of MASLD biomarker discovery over the past decades.While the research in this field is thriving,much of the publication has been haphazard,often using single-omics data and specimen sets of convenience,with many identified candidate biomarkers but lacking clinical validation and utility.If we incorporate these biomarkers to direct patients’management,it should be considered that the roadmap for translating a newly discovered omics-based signature to an actual,analytically valid test useful in MASLD clinical practice is rigorous and,therefore,not easily accomplished.This article presents an overview of this area’s current state,the conceivable opportunities and challenges of omics-based laboratory diagnostics,and a roadmap for improving MASLD biomarker research.

Recent omics progress in nanobiotechnology for plant abiotic stress tolerance improvement

Use of nanomaterials(NMs)to improve plant abiotic stress tolerance(AST)is a hot topic in NM-enabled agriculture.Previous studies mainly focused on the physiological and biochemical responses of plants treated with NMs under abiotic stress.To use NMs for improving plant AST,it is necessary to understand how they act on this tolerance at the omics and epigenetics levels.In this review,we summarized the knowledge of NM-improved abiotic stress tolerance in relation to omics(such as metabolic,transcriptomic,proteomic,and microRNA),DNA methylation,and histone modifications.Overall,NMs can improve plant abiotic stress tolerance through the modulation at omics and epigenetics levels.

New perspectives on biology,disease progression,and therapy response of head and neck cancer gained from single cell RNA sequencing and spatial transcriptomics

Head and neck squamous cell carcinoma(HNSCC)is one of the most frequent cancers worldwide.The main risk factors are consumption of tobacco products and alcohol,as well as infection with human papilloma virus.Approved therapeutic options comprise surgery,radiation,chemotherapy,targeted therapy through epidermal growth factor receptor inhibition,and immunotherapy,but outcome has remained unsatisfactory due to recurrence rates of~50%and the frequent occurrence of second primaries.The availability of the human genome sequence at the beginning of the millennium heralded the omics era,in which rapid technological progress has advanced our knowledge of the molecular biology of malignant diseases,including HNSCC,at an unprecedented pace.Initially,microarray-based methods,followed by approaches based on next-generation sequencing,were applied to study the genetics,epigenetics,and gene expression patterns of bulk tumors.More recently,the advent of single-cell RNA sequencing(scRNAseq)and spatial transcriptomics methods has facilitated the investigation of the heterogeneity between and within different cell populations in the tumor microenvironment(e.g.,cancer cells,fibroblasts,immune cells,endothelial cells),led to the discovery of novel cell types,and advanced the discovery of cell-cell communication within tumors.This review provides an overview of scRNAseq,spatial transcriptomics,and the associated bioinformatics methods,and summarizes how their application has promoted our understanding of the emergence,composition,progression,and therapy responsiveness of,and intercellular signaling within,HNSCC.

Progress in research on tumor microenvironment-based spatial omics technologies

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.

Integration of meta-QTL discovery with omics: Towards a molecular breeding platform for improving wheat resistance to Fusarium head blight

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.

Application of omics technologies for a deeper insight into quali-quantitative production traits in broiler chickens:A review

The poultry industry is continuously facing substantial and different challenges such as the increasing cost of feed ingredients, the European Union’s ban of antibiotic as growth promoters, the antimicrobial resistance and the high incidence of muscle myopathies and breast meat abnormalities. In the last decade, there has been an extraordinary development of many genomic techniques able to describe global variation of genes, proteins and metabolites expression level. Proper application of these cutting-edge omics technologies(mainly transcriptomics, proteomics and metabolomics) paves the possibility to understand much useful information about the biological processes and pathways behind different complex traits of chickens. The current review aimed to highlight some important knowledge achieved through the application of omics technologies and proteo-genomics data in the field of feed efficiency, nutrition, meat quality and disease resistance in broiler chickens.

Utilization of multiple "omics" studies in microbial pathogeny for microbiology insights

In the present day,bioinfomiatics becomes the modern science with several advantages.Several new"omics"sciences have been introduced for a few years and those sciences can he applied in biomedical work.Here,the author will summarize and discuss on important applications of omics studies in microbiology focusing on microbial pathogeny.It can be seen that genomics and proteinomics can be well used in this area of biomedical studies.

Application of single-cell omics in inflammatory bowel disease

Over the past decade,the advent of single cell RNA-sequencing has revolutionized the approach in cellular transcriptomics research.The current technology offers an unbiased platform to understand how genotype correlates to phenotype.Single-cell omics applications in gastrointestinal(GI)research namely inflammatory bowel disease(IBD)has become popular in the last few years with multiple publications as single-cell omics techniques can be applied directly to the target organ,the GI tract at the tissue level.Through examination of mucosal tissue and peripheral blood in IBD,the recent boom in single cell research has identified a myriad of key immune players from enterocytes to tissue resident memory T cells,and explored functional heterogeneity within cellular subsets previously unreported.As we begin to unravel the complex mucosal immune system in states of health and disease like IBD,the power of exploration through single-cell omics can change our approach to translational research.As novel techniques evolve through multiplexing single-cell omics and spatial transcriptomics come to the forefront,we can begin to fully comprehend the disease IBD and better design targets of treatment.In addition,hopefully these techniques can ultimately begin to identify biomarkers of therapeutic response and answer clinically relevant questions in how to tailor individual therapy to patients through personalized medicine.

Metabolomics and gene expression levels reveal the positive effects of teaseed oil on lifespan and aging process in Caenorhabditis elegans

As an irreplaceable dietary constituent,lipids play a vital important role in health,but their effects on aging process and longevity are still not well known yet.In this paper,the metabolic profiling and gene expression levels of Caenorhabditis elegans were investigated to explore the effects of different edible oils on senescence and lifespan.The results showed that teaseed oil(TO)could prolong the life expectancy and slow down the aging process of C.elegans.Compared to the control group,the intake of lard oil(LO)and TO increased the expression levels of genes related to inhibition of protein aggregation(akt-1,daf-16,hsf-1,hsp-16.2)and lipid metabolism(daf-7,daf-1,mdt-15,lipl-4,fat-5,fat-6,fat-7),with a more significant alteration in TO group.Metabolomics revealed that palm oil can upregulated plenty of fatty acids(palmitic acid,stearic acid,tetracosanoic acid),together with some amino acids(tryptophan,L-aspartate,L-valine)and carbohydrate(D-glucose),while the trend was opposite in TO group.Besides,moderate-to-strong correlations were found between differential metabolites and changed genes.In general,this paper claimed that TO could prolong lifespan and slow down aging process via regulating the lipids,amino acids and carbohydrates metabolism.

Omics era in type 2 diabetes:From childhood to adulthood

Parallel to the dramatic rise of pediatric obesity, estimates reported an increasedprevalence of type 2 diabetes (T2D) already in childhood. The close relationshipbetween obesity and T2D in children is mainly sustained by insulin resistance(IR). In addition, the cardiometabolic burden of T2D including nonalcoholic fattyliver disease, cardiovascular disease and metabolic syndrome is also strictlyrelated to IR. Although T2D pathophysiology has been largely studied in anattempt to improve therapeutic options, molecular mechanisms are still not fullyelucidated. In this perspective, omics approaches (including lipidomics,metabolomics, proteomics and metagenomics) are providing the most attractivetherapeutic options for T2D. In particular, distinct both lipids and metabolites areemerging as potential therapeutic tools. Of note, among lipid classes, thepathogenic role of ceramides in T2D context has been supported by several data.Thus, selective changes of ceramides expression might represent innovativetherapeutic strategies for T2D treatment. More, distinct metabolomics pathwayshave been also found to be associated with higher T2D risk, by providing novelpotential T2D biomarkers. Taken together, omics data are responsible for theexpanding knowledge of T2D pathophysiology, by providing novel insights toimprove therapeutic strategies for this tangled disease. We aimed to summarizethe most recent evidence in the intriguing field of the omics approaches in T2Dboth in adults and children.

Systemic omics analysis of the hub genes, proteins, metabolites and metabolic pathways related to the hypoxia preconditioning in mice

Hypoxia preconditioning （HPC） is associated with many complicated pathophysiological and biochemical processes that integrated and regulated via molecular levels. HPC could protect cells, tissues, organs and systems from hypoxia injury, but up to date, the molecular mechanism still remained unclear. The acute and repetitive hy- poxia preconditioning model was constructed and the related parameters were observed. The high-throughput mi- croarray analysis and multiple bioinformatics were used to explore the differentially expressed genes in HPC mice brain and the related gene network, pathways and biological processes related to HPC. The 2D-DIGE coupled with MALDI-TOF/TOF-MS was performed to identify these proteins that were differentially expressed during HPC. The UPLC-HRMS based metabolomics method was utilized to explore the key endogenous metabolites and metabolic pathways related to HPC. The results showed that （1） 1175 differentially expressed genes in HPC mice brain were identified. Fourteen of these genes were the related hub genes for HPC, including Cacna2dl, Grin2a, Npylr, Mef2c, Epha4, Rxfpl, Chrm3, Pdela, Atp2b4, Glral, Idil , Fgfl, Grin2b and Cda. The change trends of all the detected genes by RT-PCR were consistent with the data of gene chips. There were 113 significant functions up- regulated and 138 significant functions down-regulated in HPC mice. （2） About 2100 proteins were revealed via the gel imaging and spot detection. 66, 45 and 70 of proteins were found to have significantly difference between the control group and three times of HPC group, the control and six times of HPC, and the three times of HPC and six times of HPC group. （3）Some endogenous metabolites such as phenylalanine, valine, proline, leucine and glu- tamine were increased, while ereatine was decreased, both in HPC brain and heart; in addition, y-aminobutyric acid was markedly decreased in brain. The sphingolipid metabolic pathways were noticed due to the low p-value and high pathway impact. Especially, the sphingolipid compound sphingomyelin, ceramide, glucosyleeramide, galactosylceramide and laetosylceramide were mapping in this metabolic pathway. Interestingly, these sphingolipid metabolites with olefinic bond in the long fatty chain were up-regulated, while those sphingolipids without olefinic bond were down-regulated. The functions of these differentially expressed genes mainly involved the cellular proces- ses including MAPK pathway, ion transport, neurotransmitter transport and neuropeptide signal pathway. The pro- tein levels related the ATP synthesis and citric acid cycle decreased while the proteins with the glycolysis and oxy- gen-binding increased. Glutathione, GNBP-1 and GPD1L were related to preventing hypoxic damage. The results indicated that C24：l-Cers played a critical role in HPC and had potential in endogenous protective mechanism. The combinations of the system omies data of the different molecules were sufficient to give a further understanding of the molecular pathways affected by HPC. Our data provided an important insight to reveal the protection mechanism of HPC.

Analysis of the key networks,metabolic pathways,and regulation substances of hypoxia based on the omics and zebrafish model

OBJECTIVE Hypoxia is associated with many complicated pathophysiological and biochemical processes that integrated and regulated via the key gene,protein and endogenous metabolite levels.Up to date,the exact molecular mechanism of hypoxia still remains unclear.In this work,we further explore the molecular mechanism of hypoxia and adaption to attenuate the damage in zebrafish model that have potential to resist hypoxic environment.METHODS The hypoxic zebrafish model was established in different concentration of oxygen with 3%,5%,10%,21%in water.The brain tissue was separated and the RNA-seq was used to identify the differentially expressed genes.The related endogenous metabolites profiles were obtained by LC-HDMS,and the multivariate statistics was applied to discover the important metabolites candidates in hypoxic zebrafish.The candidates were searched in HMDB,KEGG and Lipid Maps databases.RESULTS The zebrafish hypoxic model was successfully constructed via the different concentration of oxygen,temperature and hypoxic time.The activities of the related hypoxic metabolic enzymes and factors including HIF-1a,actate dehydrogenase(LDH)and citrate synthase(CS)were evaluated.Significant differences(P<0.05 and fold change>2)in the expression of 422 genes were observed between the normal and 3% hypoxic model.Among them,201 genes increased depended on the lower concentration of oxygen.53 metabolites were identified that had significant difference between the hypoxia and control groups(P<0.05,fold change>1.5 and VIP>1.5).The ten key metabolites were increased gradually while six compounds were decreased.The endogenous hypoxic metabolites of phenylalanine,D-glucosamine-6P and several important lipids with the relevant hub genes had similar change in hypoxic model.In addition,the metabolic pathways of phenylalanine,glutamine and glycolipid were influenced in both the levels of genes and metabolites.CONCLUSION The up-regulation of phenylalanine,D-glucosamine-6P and lipid may have further understanding of protective effect in hypoxia.Our data provided an insight to further reveal the hypoxia and adaptation mechanism.

Integration of multi-omics in investigations on the mechanisms of action of Chinese herbal medicine interventions in metabolic diseases

The rapid development of bioinformatics has provided novel approaches and methods for exploring the mechanisms of disease treatment via Chinese herbal medicines.Compound Chinese herbal medicines formulas have complex compositions and are characterized by their multiple constituents and diverse array of biological targets.Therefore,the mechanisms of action of most compound Chinese herbal medicines formulas cannot be adequately explained using a single pathway.Omics technologies describe high-throughput-based analytical and detection techniques,which include transcriptomics,proteomics,and metabolomics and provide multilayer parameter information that can be integrated to characterize the overall relationships involved in the therapeutic effects of Chinese herbal medicines formulas.Through their combination with network biology and drug effect networks,omics technologies also enable investigations into the mechanisms of disease treatment in traditional Chinese medicine.The integration of multiple omics technologies is in line with the concept of holism in traditional Chinese medicine and provides an approach for combining modern science and technology with traditional Chinese medicine theories.In recent years,omics technologies have been widely used to elucidate the mechanisms of action of Chinese herbal medicines.The latest studies employing multi-omics integration for investigating the mechanisms of action of Chinese herbal medicines interventions in metabolic diseases have devoted greater attention to in-depth explorations of disease pathogenesis.This paper provides a review of the following multi-omics technologies,which are used in research on the treatment of common metabolic diseases(e.g.,type-2 diabetes mellitus,nonalcoholic fatty liver disease):network pharmacology combined with metabolomics,16S rRNA sequencing combined with transcriptomics,16S rRNA sequencing combined with metabolomics,and 16S rRNA sequencing combined with network pharmacology and metabolomics.

The application of omics technologies to toxicology

The application of omics technologies,including genomics,transcriptomics,proteomics and metabolomics,has the potential to revolutionize toxicology by providing a more comprehensive understanding of the molecular mechanisms of toxicity,identifying potential biomarkers of exposure or effect,and enabling personalized risk assessments for individuals.Each omics approach has its own challenges,including data analysis and interpretation,but the integration of multiple omics approaches can provide a more comprehensive understanding of toxicity.The use of omics technologies for personalized risk assessments can inform targeted interventions and improve public health outcomes.While challenges remain,the potential benefits of omics technologies in toxicology make it an exciting area of research for the future.

Artificial intelligence and omics in cancer

Cancer is a major public health problem worldwide.Current predictions suggest that 13 million people will die each year from cancer by 2030.Thus,new ideas are urgently needed to change paradigms in the global fight against cancer.Over the last decades,artificial intelligence(AI)emerged in the field of cancer research as a new and promising discipline.Although emerging,a great potential is appreciated in AI to improve cancer diagnosis and prognosis,as well as to identify relevant therapeutics in the current era of personalized medicine.Developing pipelines connecting patient-generated health data easily translatable into clinical practice to assist clinicians in decision making represents a challenging but fascinating task.AI algorithms are mainly fueled by multi omics data which,in the case of cancer research,have been largely derived from international cancer programs,including The Cancer Genome Atlas(TCGA).Here,I briefly review some examples of supervised and unsupervised big data derived from TCGA programs and comment on how AI algorithms have been applied to improve the management of patients with cancer.In this context,Artificial Intelligence in Cancer journal was specifically launched to promote the development of this discipline,by serving as a forum to publish high-quality basic and clinical research articles in various fields of AI in oncology.

Advances and applications in spatial transcriptomics

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.

Neglected scrub typhus:An updated review with a focus on omics technologies

Scrub typhus is a neglected disease and one of the most serious health problems in the Asia-Pacific region.The disease is caused by an obligate intracellular bacteria Orientia tsutsugamushi,which is transmitted by chigger bites or larval mite bites.Scrub typhus is a threat to billions of people worldwide causing different health complications and acute encephalitis in infants and growing children.The disease causes multiple organ failure and mortality rates may reach up to 70%due to a lack of appropriate healthcare.Currently available genome and proteome databases,and bioinformatics methods are valuable tools to develop novel therapeutics to curb the pathogen.This review discusses the state-of-the-art of information about Orientia tsutsugamushi-mediated scrub typhus and delineates the role of omics technologies to develop drugs against the pathogen.The role of proteome-wide in silico approaches for the identification of therapeutic targets is also highlighted.

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.

Plant-associated fungal communities in the light of meta’omics

Approaches for the cultivation-independent analysis of microbial communities are summarized as meta’omics,which predominantly includes metagenomic,-transcriptomic,-proteomic and-metabolomic studies.These have shown that endophytic,root-associated and soil fungal communities are strongly shaped by associated plant species.The impact of plant identity on the composition of its litterssociated fungal community remains to be disentangled from the impact of litter chemistry.The composition of the plant community also shapes the fungal community.Most strikingly,adjacent plant species may share mycorrhizal symbionts even if the plants usually have different types of mycorrhizal fungi associated with them(ectomycorrhizal,ericoid and arbuscular mycorrhizal fungi).Environmental parameters weakly explain fungal community composition globally,and their effect is inconsistent at local and regional scales.Decrease in similarity among communities with increasing distance(i.e.distance decay)has been reported from local to global scales.This pattern is only exceptionally caused by spatial dispersal limitation of fungal propagules,but mostly due to the inability of the fungi to establish at the particular locality(i.e.environmental filtering or competitive exclusion).Fungal communities usually undergo pronounced seasonal changes and also differ between consecutive years.This indicates that development of the communities is usually not solely cyclic.Meta’omic studies challenge the classical view of plant litter decomposition.They show that mycorrhizal and(previously)endophytic fungi may be involved in plant litter decomposition and only partly support the idea of a succession from an Ascomycota to a Basidiomycota-dominated community.Furthermore,vertical separation of saprotrophic and mycorrhizal species in soil and sequential degradation from easily accessible to‘recalcitrant’plant compounds,such as lignin,can probably not be generalized.The current models of litter decomposition may therefore have to be eventually refined for certain ecosystems and environmental conditions.To gain deeper insights into fungal ecology,a meta’omic study design is outlined which focuses on environmental processes,because fungal communities are usually taxonomically diverse,but functionally redundant.This approach would initially identify dynamics of chemical shifts in the host and/or substrate by metametabolomics.Detected shifts would be subsequently linked to microbial activity by correlation with metatranscriptomic and/or metaproteomic data.A holistic trait-based approach might finally identify factors shaping taxonomic composition in communities against the dynamics of the environmental process(es)they are involved in.