Integrative Multi-omics Analysis Research Articles

Investigation of the biocontrol mechanism of a novel Pseudomonas species against phytopathogenic Fusarium graminearum revealed by multi-omics integration analysis.

Pseudomonas spp. produces various antifungal substances, making it an effective natural biocontrol agent against pathogenic fungi. However, the inhibitory effects and the associated antagonistic mechanisms of Pseudomonas spp. against Fusarium spp. are unclear. Multi-omics integration analyses of the in vitro antifungal effects of novel Pseudomonas species, P13, against F. graminearum T1 revealed the ability of P13 to produce antifungal components (PCA, HCN, Pvd, and Hcs), strategically upregulate PCA and HCN biosynthesis during logarithmic growth phase, and enhance the TCA cycle during stationary growth phase. These findings improved our understanding of the biocontrol mechanisms of P13 and its potential application against pathogenic fungi.

Multi-omics profiling reveals dysregulated ribosome biogenesis and impaired cell proliferation following knockout of CDR2L

BackgroundCerebellar degeneration-related (CDR) proteins are associated with paraneoplastic cerebellar degeneration (PCD) – a rare, neurodegenerative disease caused by tumour-induced autoimmunity against neural antigens resulting in degeneration of Purkinje neurons in the cerebellum. The pathogenesis of PCD is unknown, in large part due to our limited understanding of the functions of CDR proteins. To this end, we performed an extensive, multi-omics analysis of CDR-knockout cells focusing on the CDR2L protein, to gain a deeper understanding of the properties of the CDR proteins in ovarian cancer.MethodsOvarian cancer cell lines lacking either CDR1, CDR2, or CDR2L were analysed using RNA sequencing and mass spectrometry-based proteomics to assess changes to the transcriptome, proteome and secretome in the absence of these proteins.ResultsFor each knockout cell line, we identified sets of differentially expressed genes and proteins. CDR2L-knockout cells displayed a distinct expression profile compared to CDR1- and CDR2-knockout cells. Knockout of CDR2L caused dysregulation of genes involved in ribosome biogenesis, protein translation, and cell cycle progression, ultimately causing impaired cell proliferation in vitro. Several of these genes showed a concurrent upregulation at the transcript level and downregulation at the protein level.ConclusionsOur study provides the first integrative multi-omics analysis of the impact of knockout of the CDR genes, providing both new insights into the biological properties of the CDR proteins in ovarian cancer, and a valuable resource for future investigations into the CDR proteins.

Integrative Multi-Omics Analysis for Etiology Classification and Biomarker Discovery in Stroke: Advancing towards Precision Medicine.

Recent advancements in high-throughput omics technologies have opened new avenues for investigating stroke at the molecular level and elucidating the intricate interactions among various molecular components. We present a novel approach for multi-omics data integration on knowledge graphs and have applied it to a stroke etiology classification task of 30 stroke patients through the integrative analysis of DNA methylation and mRNA, miRNA, and circRNA. This approach has demonstrated promising performance as compared to other existing single technology approaches.

Multilayer regulatory landscape and new regulators identification for bud dormancy release and bud break in Populus.

For trees originating from boreal and temperate regions, the dormancy-to-active transition, also known as bud dormancy release and bud break, are crucial processes that allow trees to reactive growth in the spring. The molecular mechanisms underlying these two processes remain poorly understood. Here, through integrative multiomics analysis of the transcriptome, DNA methylome, and proteome, we gained insights into the reprogrammed cellular processes associated with bud dormancy release and bud break. Our findings revealed multilayer regulatory landscapes governing bud dormancy release and bud break regulation, providing a valuable reference framework for future functional studies. Based on the multiomics analysis, we have determined a novel long intergenic noncoding RNAnamed Phenology Responsive Intergenic lncRNA 1 (PRIR1) plays a role in the activation of bud break. that the molecular mechanism of PRIR1 has been preliminary explored, and it may partially promote bud break by activating its neighbouring gene, EXORDIUM LIKE 5 (PtEXL5), which has also been genetically confirmed as an activator for bud break. This study has revealed a lncRNA-mediated regulatory mechanism for the control of bud break in Populus, operating independently of known regulatory pathways.

D-mannose alleviates intervertebral disc degeneration through glutamine metabolism

BackgroundIntervertebral disc degeneration (IVDD) is a multifaceted condition characterized by heterogeneity, wherein the balance between catabolism and anabolism in the extracellular matrix of nucleus pulposus (NP) cells plays a central role. Presently, the available treatments primarily focus on relieving symptoms associated with IVDD without offering an effective cure targeting its underlying pathophysiological processes. D-mannose (referred to as mannose) has demonstrated anti-catabolic properties in various diseases. Nevertheless, its therapeutic potential in IVDD has yet to be explored.MethodsThe study began with optimizing the mannose concentration for restoring NP cells. Transcriptomic analyses were employed to identify the mediators influenced by mannose, with the thioredoxin-interacting protein (Txnip) gene showing the most significant differences. Subsequently, small interfering RNA (siRNA) technology was used to demonstrate that Txnip is the key gene through which mannose exerts its effects. Techniques such as colocalization analysis, molecular docking, and overexpression assays further confirmed the direct regulatory relationship between mannose and TXNIP. To elucidate the mechanism of action of mannose, metabolomics techniques were employed to pinpoint glutamine as a core metabolite affected by mannose. Next, various methods, including integrated omics data and the Gene Expression Omnibus (GEO) database, were used to validate the one-way pathway through which TXNIP regulates glutamine. Finally, the therapeutic effect of mannose on IVDD was validated, elucidating the mechanistic role of TXNIP in glutamine metabolism in both intradiscal and orally treated rats.ResultsIn both in vivo and in vitro experiments, it was discovered that mannose has potent efficacy in alleviating IVDD by inhibiting catabolism. From a mechanistic standpoint, it was shown that mannose exerts its anti-catabolic effects by directly targeting the transcription factor max-like protein X-interacting protein (MondoA), resulting in the upregulation of TXNIP. This upregulation, in turn, inhibits glutamine metabolism, ultimately accomplishing its anti-catabolic effects by suppressing the mitogen-activated protein kinase (MAPK) pathway. More importantly, in vivo experiments have further demonstrated that compared with intradiscal injections, oral administration of mannose at safe concentrations can achieve effective therapeutic outcomes.ConclusionsIn summary, through integrated multiomics analysis, including both in vivo and in vitro experiments, this study demonstrated that mannose primarily exerts its anti-catabolic effects on IVDD through the TXNIP-glutamine axis. These findings provide strong evidence supporting the potential of the use of mannose in clinical applications for alleviating IVDD. Compared to existing clinically invasive or pain-relieving therapies for IVDD, the oral administration of mannose has characteristics that are more advantageous for clinical IVDD treatment.

The multi-omic response to exercise training across rat tissues: interactive tools for data dissemination through the MoTrPAC data hub

The Molecular Transducers of Physical Activity Consortium (MoTrPAC) aims to map the molecular responses to exercise and training to elucidate how exercise improves health and prevents disease. The first MoTrPAC data provides an extensive temporal map of the dynamic multi-omic response to endurance training across multiple rat tissues. All results can be viewed, interrogated, and downloaded in a user-friendly, publicly accessible data portal ( https://motrpac-data.org ). The MoTrPAC data compendium includes transcriptomics, proteomics, metabolomics, phosphoproteomics, acetylproteomics, ubiquitylproteomics, DNA methylation, chromatin accessibility, and multiplexed immunoassay data. This compilation of 211 datasets across 19 tissues, 25 molecular assays, and 4 training time points in adult male and female rats constitutes 19 terabytes of data. Over 35,000 analytes were found to be differentially regulated in response to endurance training, with many displaying sexual dimorphism. We observed a male-specific recruitment of immune cells to adipose tissues and an anticorrelated transcriptional response in the adrenal gland related to the stress response. Temporal multi-omic and multi-tissue integration demonstrated similar temporal responses in the heart and skeletal muscle, reflecting a concerted adaptation of mitochondrial biogenesis and metabolism. Integrative multi-omic network analysis revealed connections between the heat shock-mediated stress response and mitochondrial biogenesis. Training increased phospholipids and decreased triacylglycerols in the liver, and there were extensive changes to mitochondrial protein acetylation. Many changes were relevant for human health conditions, such as non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular wellness, and tissue damage and repair. Altogether, this MoTrPAC resource provides an unprecedented view of the effects of exercise across an organism, revealing mechanistic details of how exercise impacts mammalian health. The MoTrPAC data hub is the primary online resource to disseminate this large scale multi-omics data. The MoTrPAC Study is supported by NIH grants U24OD026629 (Bioinformatics Center), U24DK112349, U24DK112342, U24DK112340, U24DK112341, U24DK112326, U24DK112331, U24DK112348 (Chemical Analysis Sites), U24AR071113 (Consortium Coordinating Center), U01AG055133, U01AG055137 and U01AG055135 (PASS/Animal Sites). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5×10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (pvalue <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

PI3K/mTOR inhibition induces tumour microenvironment remodelling and sensitises pS6high uterine leiomyosarcoma to PD-1 blockade.

Uterine leiomyosarcomas (uLMS) are aggressive tumours with poor prognosis and limited treatment options. Although immune checkpoint blockade (ICB) has proven effective in some 'challenging-to-treat' cancers, clinical trials showed that uLMS do not respond to ICB. Emerging evidence suggests that aberrant PI3K/mTOR signalling can drive resistance to ICB. We therefore explored the relevance of the PI3K/mTOR pathway for ICB treatment in uLMS and explored pharmacological inhibition of this pathway to sensitise these tumours to ICB. We performed an integrated multiomics analysis based on TCGA data to explore the correlation between PI3K/mTOR dysregulation and immune infiltration in 101 LMS. We assessed response to PI3K/mTOR inhibitors in immunodeficient and humanized uLMS patient-derived xenografts (PDXs) by evaluating tumour microenvironment modulation using multiplex immunofluorescence. We explored response to single-agent and a combination of PI3K/mTOR inhibitors with PD-1 blockade in humanized uLMS PDXs. We mapped intratumoural dynamics using single-cell RNA/TCR sequencing of serially collected biopsies. PI3K/mTOR over-activation (pS6high) associated with lymphocyte depletion and wound healing immune landscapes in (u)LMS, suggesting it contributes to immune evasion. In contrast, PI3K/mTOR inhibition induced profound tumour microenvironment remodelling in an ICB-resistant humanized uLMS PDX model, fostering adaptive anti-tumour immune responses. Indeed, PI3K/mTOR inhibition induced macrophage repolarisation towards an anti-tumourigenic phenotype and increased antigen presentation on dendritic and tumour cells, but also promoted infiltration of PD-1+ T cells displaying an exhausted phenotype. When combined with anti-PD-1, PI3K/mTOR inhibition led to partial or complete tumour responses, whereas no response to single-agent anti-PD-1 was observed. Combination therapy reinvigorated exhausted T cells and induced clonal hyper-expansion of a cytotoxic CD8+ T-cell population supported by a CD4+ Th1 niche. Our findings indicate that aberrant PI3K/mTOR pathway activation contributes to immune escape in uLMS and provides a rationale for combining PI3K/mTOR inhibition with ICB for the treatment of this patient population.

Insights into the effects of saline forage on the meat quality of Tibetan sheep by metabolome and multivariate analysis

This work aimed to investigate how two different types of forage (saline and alkaline) impact the meat quality and muscle metabolism of Tibetan sheep. An integrative multi-omics analysis of meat quality and different metabolites was performed using untargeted and targeted metabolomics approaches. The research results indicated that GG grass (saline and alkaline forage) possessed superior characteristics in terms of apparent quality and secondary metabolite content compared with HG grass (Non saline alkali forage), regardless of the targeted metabolites or non-targeted ones. Simultaneously, under stress conditions, the carbohydrates-rich salt-alkali grass play a significant role in slowing down the decline in pH, increasing the unsaturated fatty acid content and reducing the thawing loss in Tibetan sheep. This study provides an understanding of the impact of different salt-alkali grass on the quality of Tibetan sheep meat, while providing a scientific basis for the future development of salt-alkali livestock industry.

Mineral crude drug mirabilite (Mangxiao) inhibits the occurrence of colorectal cancer by regulating the Lactobacillus-bile acid-intestinal farnesoid X receptor axis based on multiomics integration analysis.

Mineral crude drug has revolutionized the treatment landscape in precision oncology niche that leads to the improvement in therapeutic efficiency on various tumor subtypes. Mangxiao (MX), a mineral crude drug in traditional Chinese medicine, has been used for treating gastrointestinal diseases for thousands of years. However, the action mechanisms are still ambiguous. Here, we attempt to explore inhibitory roles and associated pharmacological mechanisms of MX upon colorectal cancer (CRC) in APCMin/+ male mice by integrating metabolomics, 16S rDNA sequencing analyses, and metagenomic-based microbiota analysis. We found that MX can significantly inhibit the occurrence of CRC through the regulation of the dysregulated gut microbe metabolism. Furthermore, the correlation analysis of metabolomes and 16S rDNA revealed that MX could restore the disorders of gut microbes by specifically enriching the abundance of Lactobacilli to improve bile acid metabolism, which further activated the farnesoid X receptor (FXR) in CRC mice, then the improvement of gut dysbiosis could inhibit the development of CRC. Collectively, our effort confirmed MX has the capacity to intervene the development of CRC and further discovered that it targets Lactobacillus-bile acid-intestinal FXR axis, which can be regarded as a candidate medicine for future drug discovery and development against CRC.

Prioritization of therapeutic targets for cancers using integrative multi-omics analysis

BackgroundThe integration of transcriptomic, proteomic, druggable genetic and metabolomic association studies facilitated a comprehensive investigation of molecular features and shared pathways for cancers’ development and progression.MethodsComprehensive approaches consisting of transcriptome-wide association studies (TWAS), proteome-wide association studies (PWAS), summary-data-based Mendelian randomization (SMR) and MR were performed to identify genes significantly associated with cancers. The results identified in above analyzes were subsequently involved in phenotype scanning and enrichment analyzes to explore the possible health effects and shared pathways. Additionally, we also conducted MR analysis to investigate metabolic pathways related to cancers.ResultsTotally 24 genes (18 transcriptomic, 1 proteomic and 5 druggable genetic) showed significant associations with cancers risk. All genes identified in multiple methods were mainly enriched in nuclear factor erythroid 2-related factor 2 (NRF2) pathway. Additionally, biosynthesis of ubiquinol and urate were found to play an important role in gastrointestinal tumors.ConclusionsA set of putatively causal genes and pathways relevant to cancers were identified in this study, shedding light on the shared biological processes for tumorigenesis and providing compelling genetic evidence to prioritize anti-cancer drugs development.

Integrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks

Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.

ScButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders

Recent advancements for simultaneously profiling multi-omics modalities within individual cells have enabled the interrogation of cellular heterogeneity and molecular hierarchy. However, technical limitations lead to highly noisy multi-modal data and substantial costs. Although computational methods have been proposed to translate single-cell data across modalities, broad applications of the methods still remain impeded by formidable challenges. Here, we propose scButterfly, a versatile single-cell cross-modality translation method based on dual-aligned variational autoencoders and data augmentation schemes. With comprehensive experiments on multiple datasets, we provide compelling evidence of scButterfly’s superiority over baseline methods in preserving cellular heterogeneity while translating datasets of various contexts and in revealing cell type-specific biological insights. Besides, we demonstrate the extensive applications of scButterfly for integrative multi-omics analysis of single-modality data, data enhancement of poor-quality single-cell multi-omics, and automatic cell type annotation of scATAC-seq data. Moreover, scButterfly can be generalized to unpaired data training, perturbation-response analysis, and consecutive translation.

Abstract LB008: Integrative dynamic MultiOMICs analysis identifies cell cycle and DNA damage response phenotypes as downstream consequences of using the PRMT5 inhibitor AZD3470

Abstract Background: PRMT5 is an epigenetic enzyme that catalyzes symmetric di-methylation of arginine (SDMA) of multiple substrates that regulate biological processes including RNA splicing and cell cycle. The role of PRMT5 in controlling chromatin accessibility has been investigated in some cancer contexts, but its role in non-small cell lung cancer (NSCLC) global chromatin regulation is not known. AstraZeneca has developed an MTA-cooperative PRMT5 inhibitor (AZD3470) that selectively inhibits PRMT5 in MTAP-null tumors and currently is in Phase I clinical trial (NCT06130553, NCT06130553). Here we applied integrative dynamic MultiOMICs analysis upon AZD3470 treatment in six MTAP-null NSCLC cancer cell lines to inform on PRMT5’s function in maintaining tumor cell growth and survival. Methods: Utilizing an integrative approach, our study explored the effects of AZD3470 on human MTAP-deleted NSCLC cells. MultiOMICs analysis including SDMA post-translational modification (PTM) scans, ATAC-seq, RNA-seq, and mass spectrometry proteomics were employed to delineate the immediate effects and downstream phenotypes of AZD3470 PRMT5 inhibition. Results: AZD3470 induced significant SDMA modification of splicing factors consistent with known roles for PRMT5. PRMT5 inhibition by AZD3470 led to changes in global chromatin accessibility in NSCLC cells. Specific changes in genes involved in the cell cycle pathway were observed including CDK6. Integrative analysis of transcriptomics and proteomics data consistently showed alterations in cell cycle, DNA damage repair and splicing related pathways upon treatment, consistent with the established biological roles of PRMT5. Alternative splicing analysis showed that AZD3470 treatment induced a unique retained intron within the ATM gene and resulted in reduced ATM protein levels. Conclusion: Here we identify AZD3470-induced changes to protein post-translational modification, chromatin accessibility, gene expression and RNA splicing in MTAP-deficient NSCLC cancer cell lines. Different area of MultiOMICs data together pointed to changes in cell cycle and DNA repair pathways. Further, we identified alternative splicing of ATM as a consequence of AZD3470 PRMT5i treatment resulting in significant reduction of ATM protein expression. Keywords: AZD3470, NSCLC, PRMT5 Inhibition, Chromatin Accessibility, Alternative Splicing, DNA Repair, ATM Gene. Citation Format: Ted Hong, Steven Criscione, Andrew Jarnuczak, Jelena Urosevic, Stephanie Ashenden, Ghaith Hamza, Praveen Kumar, Nevena Cvetesic, Lauren Bradshaw, Shaun Moore, Daniel Karl, Tianhui Zhang, Abel Sousa, Jonathan Cairns, Anthony Iannetta, Andrew Zhang, Eric Miele, John Reicha, Chris Chambers, Ramy Elgendy, Julia Lindgren, Daniel Jachimowicz, Maryam Clausen, Graham Belfield, Tony Cheung, Michael Grondine, James T. Lynch, Ho Man Chan, Susan Critchlow, Emma Dean. Integrative dynamic MultiOMICs analysis identifies cell cycle and DNA damage response phenotypes as downstream consequences of using the PRMT5 inhibitor AZD3470 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB008.

Integrating transcriptomics, glycomics and glycoproteomics to characterize hepatitis B virus-associated hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) ranks as the third most common cause of cancer related death globally, representing a substantial challenge to global healthcare systems. In China, the primary risk factor for HCC is the hepatitis B virus (HBV). Aberrant serum glycoconjugate levels have long been linked to the progression of HBV-associated HCC (HBV-HCC). Nevertheless, few study systematically explored the dysregulation of glycoconjugates in the progression of HBV-associated HCC and their potency as the diagnostic and prognostic biomarker.MethodsAn integrated strategy that combined transcriptomics, glycomics, and glycoproteomics was employed to comprehensively investigate the dynamic alterations in glyco-genes, N-glycans, and glycoproteins in the progression of HBV- HCC.ResultsBioinformatic analysis of Gene Expression Omnibus (GEO) datasets uncovered dysregulation of fucosyltransferases (FUTs) in liver tissues from HCC patients compared to adjacent tissues. Glycomic analysis indicated an elevated level of fucosylated N-glycans, especially a progressive increase in fucosylation levels on IgA1 and IgG2 determined by glycoproteomic analysis.ConclusionsThe findings indicate that the abnormal fucosylation plays a pivotal role in the progression of HBV-HCC. Systematic and integrative multi-omic analysis is anticipated to facilitate the discovery of aberrant glycoconjugates in tumor progression.

Prognosis and immunological characteristics of HDAC family in pan-cancer through integrative multi-omic analysis

BackgroundThe histone deacetylase (HDAC) family plays a significant role in a variety of biological processes related to cancer, such as metabolism and cancer progression, and recognized as a target of anti-cancer drugs. Nevertheless, there has been limited systematic research available regarding HDAC family in human cancers using multi-omics approaches.ObjectiveTo evaluate the prognostic implications and immunological features of the HDAC family across multiple cancer types through comprehensive multi-omics analysis.MethodsWe studied the associations of HDAC activity and a variety of factors, encompassing immune checkpoint genes, the tumor microenvironment (TME), instability of microsatellites (MSI), inherited mutations, variation in copy number, tumor mutation burden (TMB), and sensitivity to drugs in a variety of cancer types. Moreover, we analyzed the link between the degree of HDAC activity and the effectiveness of immunotherapy in several cohorts, providing significant details about the possible impact of HDACs on immunotherapeutic responses. Furthermore, we explored potential signaling pathways of HDACs in bladder cancer (BC) using gene set enrichment analysis (GSEA). Immune infiltration analysis in bladder cancer was performed based on HDACs expression, copy number or somatic mutations. Furthermore, the Human Protein Atlas (HPA) dataset has been used to validate the expression of the HDACs protein in BC.ResultsThe HDACs expression exhibits significant heterogeneity across different cancer types and is significantly correlated with patient prognosis, clinical traits, mutations, TME, TMB, MSI, immune checkpoint genes, and objective responses in immunotherapy. The drug sensitivity of cancers was found to be correlated with the gene expression of specific HDAC familial members. In BC, GSEA demonstrates enrichment of multiple immune-related functions and pathways; moreover, there are significant associations between genomic variations in HDACs and the degree of typical immunological cell recruitment. Furthermore, findings from differential expression analysis in BC are validated by protein expression analysis obtained from the HPA database.ConclusionsThese findings reveal the significance of HDAC family in survival prognosis and treatment guidance of human cancers, and some of them have the potential to be used as immunotherapy biomarkers.

Multi-omics Data Integration Analysis Identified Therapeutic Targets and Potential Reuse Drugs for Osteoporosis.

To facilitate drug discovery and development for the treatment of osteoporosis. With global aging, osteoporosis has become a common problem threatening the health of the elderly. It is of important clinical value to explore new targets for drug intervention and develop promising drugs for the treatment of osteoporosis. To understand the major molecules that mediate the communication between the cell populations of bone marrow-derived mesenchymal stem cells (BM-MSCs) in osteoporosis and osteoarthritis patients and identify potential reusable drugs for the treatment of osteoporosis. Single-cell RNA sequencing (scRNA-seq) data of BM-MSCs in GSE147287 dataset were classified using the Seurat package. CellChat was devoted to analyzing the ligand-receptor pairs (LR pairs) contributing to the communication between BM-MSCs subsets. The LR pairs that were differentially expressed between osteoporosis samples and control samples and significantly correlated with immune score were screened in the GSE35959 dataset, and the differentially expressed gene in both GSE35959 and GSE13850 data sets were identified as targets from a single ligand or receptor. The therapeutic drugs for osteoporosis were screened by network proximity method, and the top-ranked drugs were selected for molecular docking and molecular dynamics simulation with the target targets. Twelve subsets of BM-MSCs were identified, of which CD45-BM-MSCS_4, CD45-BM- MSCS_5, and CD45+ BM-MSCs_5 subsets showed significantly different distributions between osteoporosis samples and osteoarthritis samples. Six LR pairs were identified in the bidirectional communication between these three BM-MSCs subsets and other BM-MSCs subsets. Among them, MIF-CD74 and ITGB2-ICAM2 were significantly correlated with the immune score. CD74 was identified as the target, and a total of 48 drugs targeting CD47 protein were identified. Among them, DB01940 had the lowest free energy binding score with CD74 protein and the binding state was very stable. This study provided a new network-based framework for drug reuse and identified initial insights into therapeutic agents targeting CD74 in osteoporosis, which may be meaningful for promoting the development of osteoporosis treatment.

Integrative Multi-omics Analysis Identifies Genetic Variants Contributing to Non-syndromic Cleft Lip with or without Cleft Palate.

To provide novel insights into the aetiology of non-syndromic cleft lip with or without cleft palate (NSCL/P) by integrating multi-omics data and exploring susceptibility genes associated with NSCL/P. A two-stage genome-wide association study (GWAS) of NSCL/P was performed, involving a total of 1,069 cases and 1,724 controls. Using promoter capture Hi-C (pCHi-C) datasets in human embryonic stem cells (hESC) and chromatin immunoprecipitation sequencing (ChIP-seq) in craniofacial tissues, we filtered out single nucleotide polymorphisms (SNPs) with active cis-regulation and their target genes. Additionally, we employed expression quantitative trait loci (eQTL) analysis to identify candidate genes. Thirteen SNPs were identified as cis-regulation units associated with the risk of NSCL/P. Five of these were proven to be active in chromatin states in early human craniofacial development (rs7218002: odds ratio [OR] 1.50, P = 8.14E-08; rs835367: OR 0.78, P = 3.48E- 05; rs77022994: OR 0.55, P = 1.05E-04; rs961470: OR 0.73, P = 1.38E-04; rs17314727: OR 0.73, P = 1.85E-04). Additionally, pCHi-C and eQTL analysis prioritised three candidate genes (rs7218002: NTN1, rs835367: FGGY, LINC01135). NTN1 and FGGY were expressed in mouse orofacial development. Deficiencies in NTN1, FGGY and LINC01135 were associated with cleft palate and cleft lip, abnormal facial shape and bifid uvula, and abnormality of the face, respectively. Our study identified five SNPs (rs7218002, rs835367, rs77022994, rs961470 and rs17314727) and three susceptibility genes (NTN1, FGGY and LINC01135) associated with NSCL/P. These findings contribute to a better understanding of the genetic factors involved.

Integrative chemical and multiomics analyses of tetracycline removal mechanisms in Pseudomonas sp. DX-21

Tetracycline (TC), widely found in various environments, poses significant risks to ecosystems and human health. While efficient biodegradation removes TC, the mechanisms underlying this process have not been elucidated. This study investigated the molecular mechanisms underlying TC biosorption and transfer within the extracellular polymeric substances (EPS) of strain DX-21 and its biodegradation process using fourier transform infrared spectroscopy, molecular docking, and multiomics. Under TC stress, DX-21 increased TC biosorption by secreting more extracellular polysaccharides and proteins, particularly the latter, mitigating toxicity. Moreover, specialized transporter proteins with increased binding capacity facilitated TC movement from the EPS to the cell membrane and within the cell. Transcriptomic and untargeted metabolomic analyses revealed that the presence of TC led to the differential expression of 306 genes and significant alterations in 37 metabolites. Notably, genes related to key enzymes, such as electron transport, peroxidase, and oxidoreductase, exhibited significant differential expression. DX-21 combated and degraded TC by regulating metabolism, altering cell membrane permeability, enhancing oxidative defense, and enhancing energy availability. Furthermore, integrative omics analyses indicated that DX-21 degrades TC via various enzymes, reallocating resources from other biosynthetic pathways. These results advance the understanding of the metabolic responses and regulatory mechanisms of DX-21 in response to TC.

HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification.

The rapid development of high-throughput biomedical technologies can provide researchers with detailed multi-omics data. The multi-omics integrated analysis approach based on machine learning contributes a more comprehensive perspective to human disease research. However, there are still significant challenges in representing single-omics data and integrating multi-omics information. This article presents HyperTMO, a Trusted Multi-Omics integration framework based on Hypergraph convolutional network for patient classification. HyperTMO constructs hypergraph structures to represent the association between samples in single-omics data, then evidence extraction is performed by hypergraph convolutional network, and multi-omics information is integrated at an evidence level. Last, we experimentally demonstrate that HyperTMO outperforms other state-of-the-art methods in breast cancer subtype classification and Alzheimer's disease classification tasks using multi-omics data from TCGA (BRCA) and ROSMAP datasets. Importantly, HyperTMO is the first attempt to integrate hypergraph structure, evidence theory, and multi-omics integration for patient classification. Its accurate and robust properties bring great potential for applications in clinical diagnosis. HyperTMO and datasets are publicly available at https://github.com/ippousyuga/HyperTMO.