Andrographolide regulates H3 histone lactylation by interfering with p300 to alleviate aortic valve calcification

BACKGROUND AND PURPOSE

Our previous studies have found that andrographolide (AGP) alleviates calcific aortic valve disease (CAVD), but the underlying mechanism is unclear. This study explores the molecular target and signal mechanisms of AGP in inhibiting CAVD.

EXPERIMENTAL APPROACH

The anti-calcification effects of the aortic valve with AGP treatment were evaluated by alizarin red staining in vitro and ultrasound and histopathological assessment of a high-fat (HF)-fed ApoE-/- mouse valve calcification model. A correlation between the H3 histone lactylation (H3Kla) and calcification was detected. Molecular docking and surface plasmon resonance (SPR) experiments were further used to confirm p300 as a target for AGP. Overexpression (oe) and silencing (si) of p300 were used to verify the inhibitory effect of AGP targeting p300 on the H3Kla in vitro and ex vivo.

KEY RESULTS

AGP significantly inhibited calcium deposition in valve interstitial cells (VICs) and ameliorated aortic valve calcification. The multi-omics analysis revealed the glycolysis pathway involved in CAVD, indicating that AGP interfered with lactate production by regulating lactate dehydrogenase A (LDHA). In addition, lactylation, a new post-translational modification, was shown to have a role in promoting aortic valve calcification. Furthermore, H3Kla and H3K9la site were shown to correlate with Runx2 expression inhibition by AGP treatment. Importantly, we found that p300 transferase was the molecular target of AGP in inhibiting H3Kla.

CONCLUSIONS AND IMPLICATIONS

Our findings, for the first time, demonstrated that AGP alleviates calcification by interfering with H3Kla via p300, which might be a powerful drug to prevent CAVD.

Integrated multi-omics approach reveals the role of striated muscle preferentially expressed protein kinase in skeletal muscle including its relationship with myospryn complex

BACKGROUND

Autosomal-recessive mutations in SPEG (striated muscle preferentially expressed protein kinase) have been linked to centronuclear myopathy with or without dilated cardiomyopathy (CNM5). Loss of SPEG is associated with defective triad formation, abnormal excitation-contraction coupling, calcium mishandling and disruption of the focal adhesion complex in skeletal muscles. To elucidate the underlying molecular pathways, we have utilized multi-omics tools and analysis to obtain a comprehensive view of the complex biological processes and molecular functions.

METHODS

Skeletal muscles from 2-month-old SPEG-deficient (Speg-CKO) and wild-type (WT) mice were used for RNA sequencing (n = 4 per genotype) to profile transcriptomics and mass spectrometry (n = 4 for WT; n = 3 for Speg-CKO mice) to profile proteomics and phosphoproteomics. In addition, interactomics was performed using the SPEG antibody on pooled muscle lysates (quadriceps, gastrocnemius and triceps) from WT and Speg-CKO mice. Based on the multi-omics results, we performed quantitative real-time PCR, co-immunoprecipitation and immunoblot to verify the findings.

RESULTS

We identified that SPEG interacts with myospryn complex proteins CMYA5, FSD2 and RyR1, which are critical for triad formation, and that SPEG deficiency results in myospryn complex abnormalities (protein levels decreased to 22 ± 3% for CMYA5 [P < 0.05] and 18 ± 3% for FSD2 [P < 0.01]). Furthermore, SPEG phosphorylates RyR1 at S2902 (phosphorylation level decreased to 55 ± 15% at S2902 in Speg-CKO mice; P < 0.05), and its loss affects JPH2 phosphorylation at multiple sites (increased phosphorylation at T161 [1.90 ± 0.24-fold], S162 [1.61 ± 0.37-fold] and S165 [1.66 ± 0.13-fold]; decreased phosphorylation at S228 and S231 [39 ± 6%], S234 [50 ± 12%], S593 [48 ± 3%] and S613 [66 ± 10%]; P < 0.05 for S162 and P < 0.01 for other sites). On analysing the transcriptome, the most dysregulated pathways affected by SPEG deficiency included extracellular matrix-receptor interaction (P < 1e-15) and peroxisome proliferator-activated receptor signalling (P < 9e-14).

CONCLUSIONS

We have elucidated the critical role of SPEG in the triad as it works closely with myospryn complex proteins (CMYA5, FSD2 and RyR1), it regulates phosphorylation levels of various residues in JPH2 and S2902 in RyR1, and its deficiency is associated with dysregulation of several pathways. The study identifies unique SPEG-interacting proteins and their phosphorylation functions and emphasizes the importance of using a multi-omics approach to comprehensively evaluate the molecular function of proteins involved in various genetic disorders.

Gene networks and systems biology in Alzheimer's disease: Insights from multi-omics approaches

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Lysophospholipid acyltransferase-mediated formation of saturated glycerophospholipids maintained cell membrane integrity for hypoxic adaptation

Adaptation to hypoxia has attracted much public interest because of its clinical significance. However, hypoxic adaptation in the body is complicated and difficult to fully explore. To explore previously unknown conserved mechanisms and key proteins involved in hypoxic adaptation in different species, we first used a yeast model for mechanistic screening. Further multi-omics analyses in multiple species including yeast, zebrafish and mice revealed that glycerophospholipid metabolism was significantly involved in hypoxic adaptation with up-regulation of lysophospholipid acyltransferase (ALE1) in yeast, a key protein for the formation of dipalmitoyl phosphatidylcholine [DPPC (16:0/16:0)], which is a saturated phosphatidylcholine. Importantly, a mammalian homolog of ALE1, lysophosphatidylcholine acyltransferase 1 (LPCAT1), enhanced DPPC levels at the cell membrane and exhibited the same protective effect in mammalian cells under hypoxic conditions. DPPC supplementation effectively attenuated growth restriction, maintained cell membrane integrity and increased the expression of epidermal growth factor receptor under hypoxic conditions, but unsaturated phosphatidylcholine did not. In agreement with these findings, DPPC treatment could also repair hypoxic injury of intestinal mucosa in mice. Taken together, ALE1/LPCAT1-mediated DPPC formation, a key pathway of glycerophospholipid metabolism, is crucial for cell viability under hypoxic conditions. Moreover, we found that ALE1 was also involved in glycolysis to maintain sufficient survival conditions for yeast. The present study offers a novel approach to understanding lipid metabolism under hypoxia and provides new insights into treating hypoxia-related diseases.

Development of gene panel for predicting recurrence in early-stage cervical cancer patients

Cervical cancer (CC) is a common malignancy affecting women worldwide. Our objective was to develop a consensus-based gene panel using multi-omics data that could effectively predict recurrence in early-stage cervical cancer patients. We utilized the "Multi-Omics Consensus Integration Analysis (MOVICS)" package for consensus clustering design to integrate multiple omics datasets and improve the molecular classification landscape of early-stage CC. We identified the "resting and naive" tumor microenvironment (TME) as cancer subtype (CS) 2. Leveraging the feature genes from the CS classifier, we employed machine learning algorithms to identify a gene panel, including ALDH1A1, CLDN10, MUC13, and C10orf99, which could generate a consensus machine learning-driven score (CMLS) for each patient. Stratifying patients into high and low CMLS groups resulted in Kaplan-Meier curves demonstrating a significant difference in recurrence rates between the two groups. This difference remained significant even after adjusting for clinical features in multivariate Cox regression analysis, with the risk ratio of CMLS surpassing that of clinical characteristics. Furthermore, the TME exhibited notable differences between the different CMLS groups, suggesting that patients with low CMLS may exhibit a better response to immunotherapy. This study highlights the potential of the CMLS approach in predicting recurrence in early-stage cervical cancer patients and provides a screening model for selecting patients suitable for immunotherapy.

Multi-omics technologies and molecular biomarkers in brain tumor-related epilepsy

BACKGROUND

Brain tumors are one of the leading causes of epilepsy, and brain tumor-related epilepsy (BTRE) is recognized as the major cause of intractable epilepsy, resulting in huge treatment cost and burden to patients, their families, and society. Although optimal treatment regimens are available, the majority of patients with BTRE show poor resolution of symptoms. BTRE has a very complex and multifactorial etiology, which includes several influencing factors such as genetic and molecular biomarkers. Advances in multi-omics technologies have enabled to elucidate the pathophysiological mechanisms and related biomarkers of BTRE. Here, we reviewed multi-omics technology-based research studies on BTRE published in the last few decades and discussed the present status, development, opportunities, challenges, and prospects in treating BTRE.

METHODS

First, we provided a general review of epilepsy, BTRE, and multi-omics techniques. Next, we described the specific multi-omics (including genomics, transcriptomics, epigenomics, proteomics, and metabolomics) techniques and related molecular biomarkers for BTRE. We then presented the associated pathogenetic mechanisms of BTRE. Finally, we discussed the development and application of novel omics techniques for diagnosing and treating BTRE.

RESULTS

Genomics studies have shown that the BRAF gene plays a role in BTRE development. Furthermore, the BRAF V600E variant was found to induce epileptogenesis in the neuronal cell lineage and tumorigenesis in the glial cell lineage. Several genomics studies have linked IDH variants with glioma-related epilepsy, and the overproduction of D2HG is considered to play a role in neuronal excitation that leads to seizure occurrence. The high expression level of Forkhead Box O4 (FOXO4) was associated with a reduced risk of epilepsy occurrence. In transcriptomics studies, VLGR1 was noted as a biomarker of epileptic onset in patients. Several miRNAs such as miR-128 and miRNA-196b participate in BTRE development. miR-128 might be negatively associated with the possibility of tumor-related epilepsy development. The lncRNA UBE2R2-AS1 inhibits the growth and invasion of glioma cells and promotes apoptosis. Quantitative proteomics has been used to determine dynamic changes of protein acetylation in epileptic and non-epileptic gliomas. In another proteomics study, a high expression of AQP-4 was detected in the brain of GBM patients with seizures. By using quantitative RT-PCR and immunohistochemistry assay, a study revealed that patients with astrocytomas and oligoastrocytomas showed high BCL2A1 expression and poor seizure control. By performing immunohistochemistry, several studies have reported the relationship between D2HG overproduction and seizure occurrence. Ki-67 overexpression in WHO grade II gliomas was found to be associated with poor postoperative seizure control. According to metabolomics research, the PI3K/AKT/mTOR pathway is associated with the development of glioma-related epileptogenesis. Another metabolomics study found that SV2A, P-gb, and CAD65/67 have the potential to function as biomarkers for BTRE.

CONCLUSIONS

Based on the synthesized information, this review provided new research perspectives and insights into the early diagnosis, etiological factors, and personalized treatment of BTRE.

Integrated gut metabolome and microbiome fingerprinting reveals that dysbiosis precedes allergic inflammation in IgE-mediated pediatric cow's milk allergy

BACKGROUND

IgE-mediated cow's milk allergy (IgE-CMA) is one of the first allergies to arise in early childhood and may result from exposure to various milk allergens, of which β-lactoglobulin (BLG) and casein are the most important. Understanding the underlying mechanisms behind IgE-CMA is imperative for the discovery of novel biomarkers and the design of innovative treatment and prevention strategies.

METHODS

We report a longitudinal in vivo murine model, in which two mice strains (BALB/c and C57Bl/6) were sensitized to BLG using either cholera toxin or an oil emulsion (n = 6 per group). After sensitization, mice were challenged orally, their clinical signs monitored, antibody (IgE and IgG1) and cytokine levels (IL-4 and IFN-γ) measured, and fecal samples subjected to metabolomics. The results of the murine models were further extrapolated to fecal microbiome-metabolome data from our population of IgE-CMA (n = 22) and healthy (n = 23) children (Trial: NCT04249973), on which polar metabolomics, lipidomics and 16S rRNA metasequencing were performed. In vitro gastrointestinal digestions and multi-omics corroborated the microbial origin of proposed metabolic changes.

RESULTS

During mice sensitization, we observed multiple microbially derived metabolic alterations, most importantly bile acid, energy and tryptophan metabolites, that preceded allergic inflammation. We confirmed microbial dysbiosis, and its associated effect on metabolic alterations in our patient cohort, through in vitro digestions and multi-omics, which was accompanied by metabolic signatures of low-grade inflammation.

CONCLUSION

Our results indicate that gut dysbiosis precedes allergic inflammation and nurtures a chronic low-grade inflammation in children on elimination diets, opening important new opportunities for future prevention and treatment strategies.

Unveiling the mechanism of efficient β-phenylethyl alcohol conversion in wild-type Saccharomyces cerevisiae WY319 through multi-omics analysis

β-Phenylethanol (2-PE), as an important flavor component in wine, is widely used in the fields of flavor chemistry and food health. 2-PE can be sustainably produced through Saccharomyces cerevisiae. Although significant progress has been made in obtaining high-yield strains, as well as improving the synthesis pathways of 2-PE, there still lies a gap between these two fields to unpin. In this study, the macroscopic metabolic characteristics of high-yield and low-yield 2-PE strains were systematically compared and analyzed. The results indicated that the production potential of the high-yield strain might be contributed to the enhancement of respiratory metabolism and the high tolerance to 2-PE. Furthermore, this hypothesis was confirmed through comparative genomics. Meanwhile, transcriptome analysis at key specific growth rates revealed that the collective upregulation of mitochondrial functional gene clusters plays a more prominent role in the production process of 2-PE. Finally, findings from untargeted metabolomics suggested that by enhancing respiratory metabolism and reducing the Crabtree effect, the accumulation of metabolites resisting high 2-PE stress was observed, such as intracellular amino acids and purines. Hence, this strategy provided a richer supply of precursors and cofactors, effectively promoting the synthesis of 2-PE. In short, this study provides a bridge for studying the metabolic mechanism of high-yield 2-PE strains with the subsequent targeted strengthening of relevant synthetic pathways. It also provides insights for the synthesis of nonalcoholic products in S. cerevisiae.

Major quality regulation network of flavonoid synthesis governing the bioactivity of black wolfberry

Black wolfberry (Lycium ruthenicum Murr.) contains various bioactive metabolites represented by flavonoids, which are quite different among production regions. However, the underlying regulation mechanism of flavonoid biosynthesis governing the bioactivity of black wolfberry remains unclear. Presently, we compared the bioactivity of black wolfberry from five production regions. Multi-omics were performed to construct the regulation network associated with the fruit bioactivity. The detailed regulation mechanisms were identified using genetic and molecular methods. Typically, Qinghai (QH) fruit exhibited higher antioxidant and anti-inflammatory activities. The higher medicinal activity of QH fruit was closely associated with the accumulation of eight flavonoids, especially Kaempferol-3-O-rutinoside (K3R) and Quercetin-3-O-rutinoside (rutin). Flavonoid biosynthesis was found to be more active in QH fruit, and the upregulation of LrFLS, LrCHS, LrF3H and LrCYP75B1 caused the accumulation of K3R and rutin, leading to high medicinal bioactivities of black wolfberry. Importantly, transcription factor LrMYB94 was found to regulate LrFLS, LrCHS and LrF3H, while LrWRKY32 directly triggered LrCYP75B1 expression. Moreover, LrMYB94 interacted with LrWRKY32 to promote LrWRKY32-regulated LrCYP75B1 expression and rutin synthesis in black wolfberry. Transgenic black wolfberry overexpressing LrMYB94/LrWRKY32 contained higher levels of K3R and rutin, and exhibited high medicinal bioactivities. Importantly, the LrMYB94/LrWRKY32-regulated flavonoid biosynthesis was light-responsive, showing the importance of light intensity for the medicinal quality of black wolfberry. Overall, our results elucidated the regulation mechanisms of K3R and rutin synthesis, providing the basis for the genetic breeding of high-quality black wolfberry.

Multi-omics panoramic analysis of HBV integration, transcriptional regulation, and epigenetic modifications in PLC/PRF/5 cell line

The clearance or transcriptional silencing of integrated HBV DNA is crucial for achieving a functional cure in patients with chronic hepatitis B and reducing the risk of hepatocellular carcinoma development. The PLC/PRF/5 cell line is commonly used as an in vitro model for studying HBV integration. In this study, we employed a range of multi-omics techniques to gain a panoramic understanding of the characteristics of HBV integration in PLC/PRF/5 cells and to reveal the transcriptional regulatory mechanisms of integrated HBV DNA. Transcriptome long-read sequencing (ONT) was conducted to analyze and characterize the transcriptional activity of different HBV DNA integration sites in PLC/PRF/5 cells. Additionally, we collected data related to epigenetic regulation, including whole-genome bisulfite sequencing (WGBS), histone chromatin immunoprecipitation sequencing (ChIP-seq), and assays for transposase-accessible chromatin using sequencing (ATAC-seq), to explore the potential mechanisms involved in the transcriptional regulation of integrated HBV DNA. Long-read RNA sequencing analysis revealed significant transcriptional differences at various integration sites in the PLC/PRF/5 cell line, with higher HBV DNA transcription levels at integration sites on chr11, chr13, and the chr13/chr5 fusion chromosome t (13:5). Combining long-read DNA and RNA sequencing results, we found that transcription of integrated HBV DNA generally starts downstream of the SP1, SP2, or XP promoters. ATAC-seq data confirmed that chromatin accessibility has limited influence on the transcription of integrated HBV DNA in the PLC/PRF/5 cell line. Analysis of WGBS data showed that the methylation intensity of integrated HBV DNA was highly negatively correlated with its transcription level (r = -0.8929, p = 0.0123). After AzaD treatment, the transcription level of integrated HBV DNA significantly increased, especially for the integration chr17, which had the highest level of methylation. Through ChIP-seq data, we observed the association between histone modification of H3K4me3 and H3K9me3 with the transcription of integrated HBV DNA. Our findings suggest that the SP1, SP2 and XP in integrated HBV DNA, methylation level of surrounding host chromosome, and histone modifications affect the transcription of integrated HBV DNA in PLC/PRF/5 cells. This provides important clues for future studies on the expression and regulatory mechanisms of integrated HBV.

Integrated transcriptomic and proteomic profiling reveals the key molecular signatures of brain endothelial reperfusion injury

BACKGROUND

Reperfusion therapy after ischemic stroke often causes brain microvascular injury. However, the underlying mechanisms are unclear.

METHODS

Transcriptomic and proteomic analyses were performed on human cerebral microvascular endothelial cells following oxygen-glucose deprivation (OGD) or OGD plus recovery (OGD/R) to identify molecules and signaling pathways dysregulated by reperfusion. Major findings were further validated in a mouse model of cerebral ischemia and reperfusion.

RESULTS

Transcriptomic analysis identified 390 differentially expressed genes (DEGs) between the OGD/R and OGD group. Pathway analysis indicated that these genes were mostly associated with inflammation, including the TNF signaling pathway, TGF-β signaling pathway, cytokine-cytokine receptor interaction, NOD-like receptor signaling pathway, and NF-κB signaling pathway. Proteomic analysis identified 201 differentially expressed proteins (DEPs), which were primarily associated with extracellular matrix destruction and remodeling, impairment of endothelial transport function, and inflammatory responses. Six genes (DUSP1, JUNB, NFKBIA, NR4A1, SERPINE1, and THBS1) were upregulated by OGD/R at both the mRNA and protein levels. In mice with cerebral ischemia and reperfusion, brain TNF signaling pathway was activated by reperfusion, and inhibiting TNF-α with adalimumab significantly attenuated reperfusion-induced brain endothelial inflammation. In addition, the protein level of THBS1 was substantially upregulated upon reperfusion in brain endothelial cells and the peri-endothelial area in mice receiving cerebral ischemia.

CONCLUSION

Our study reveals the key molecular signatures of brain endothelial reperfusion injury and provides potential therapeutic targets for the treatment of brain microvascular injury after reperfusion therapy in ischemic stroke.

Integrated Multiomics Reveals Silencing of has_circ_0006646 Promotes TRIM21-Mediated NCL Ubiquitination to Inhibit Hepatocellular Carcinoma Metastasis

Recent studies suggest that circular RNA (circRNA)-mediated post-translational modification of RNA-binding proteins (RBP) plays a pivotal role in metastasis of hepatocellular carcinoma (HCC). However, the specific mechanism and potential clinical therapeutic significance remain vague. This study attempts to profile the regulatory networks of circRNA and RBP using a multi-omics approach. Has_circ_0006646 (circ0006646) is an unreported circRNA in HCC and is associated with a poor prognosis. Silencing of circ0006646 significantly hinders metastasis in vivo. Mechanistically, circ0006646 prevents the interaction between nucleolin (NCL) and the E3 ligase tripartite motif-containing 21 to reduce the proteasome-mediated degradation of NCL via K48-linked polyubiquitylation. Furthermore, the change of NCL expression is proven to affect the phosphorylation levels of multiple proteins and inhibit p53 translation. Moreover, patient-derived tumor xenograft and lentivirus injection, which is conducted to simulate clinical treatment confirmed the potential therapeutic value. Overall, this study describes the integrated multi-omics landscape of circRNA-mediated NCL ubiquitination degradation in HCC metastasis and provides a novel therapeutic target.

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD. We provided an overview of the ASD molecular mechanisms identified by multi-omics studies and convergent mechanism in different genetic backgrounds. The comorbidities, mechanisms associated with important physiological and metabolic abnormalities (i.e., inflammation, immunity, oxidative stress, and mitochondrial dysfunction), and gut microbial disorder in ASD were reviewed. The non-targeted omics and targeting studies of diagnostic markers for ASD were also reviewed. Moreover, we summarized the progress and methods of behavioral and educational interventions, intervention methods related to technological devices, and research on medical interventions and potential drug targets. This review highlighted the application of high-throughput omics methods in ASD research and emphasized the importance of seeking homogeneity from heterogeneity and exploring the convergence of disease mechanisms, biomarkers, and intervention approaches, and proposes that taking into account individuality and commonality may be the key to achieve accurate diagnosis and treatment of ASD.

Multi-omics integration reveals a nonlinear signature that precedes progression of lung fibrosis

Objectives

Idiopathic pulmonary fibrosis (IPF) is a devastating progressive interstitial lung disease with poor outcomes. While decades of research have shed light on pathophysiological mechanisms associated with the disease, our understanding of the early molecular events driving IPF and its progression is limited. With this study, we aimed to model the leading edge of fibrosis using a data-driven approach.

Methods

Multiple omics modalities (transcriptomics, metabolomics and lipidomics) of healthy and IPF lung explants representing different stages of fibrosis were combined using an unbiased approach. Multi-Omics Factor Analysis of datasets revealed latent factors specifically linked with established fibrotic disease (Factor1) and disease progression (Factor2).

Results

Features characterising Factor1 comprised well-established hallmarks of fibrotic disease such as defects in surfactant, epithelial-mesenchymal transition, extracellular matrix deposition, mitochondrial dysfunction and purine metabolism. Comparatively, Factor2 identified a signature revealing a nonlinear trajectory towards disease progression. Molecular features characterising Factor2 included genes related to transcriptional regulation of cell differentiation, ciliogenesis and a subset of lipids from the endocannabinoid class. Machine learning models, trained upon the top transcriptomics features of each factor, accurately predicted disease status and progression when tested on two independent datasets.

Conclusion

This multi-omics integrative approach has revealed a unique signature which may represent the inflection point in disease progression, representing a promising avenue for the identification of therapeutic targets aimed at addressing the progressive nature of the disease.

Naringenin prevents non-alcoholic steatohepatitis by modulating the host metabolome and intestinal microbiome in MCD diet-fed mice

Non-alcoholic steatohepatitis (NASH) is a severe inflammatory phase of the non-alcoholic fatty liver disease (NAFLD) spectrum and can progress to advanced stages of NAFLD if left untreated. This study uses multi-omics data to elucidate the underlying mechanism of naringenin's reported benefit in alleviating (NASH). Male mice were fed a NASH-inducing (methionine-choline-deficient) MCD diet with or without naringenin supplementation for 6 weeks. Naringenin prevented NASH-induced histopathological liver damage and reversed the abnormal levels of hepatic triglyceride (TG)/total cholesterol (TC), serum TG/TC, serum alanine aminotransferase/aspartate transaminase, and hepatic malondialdehyde and glutathione. Importantly, naringenin intervention significantly modulated the relative abundance of gut microbiota and the host metabolomic profile. We detected more than 700 metabolites in the serum and found that the gut genus levels of Anaeroplasma and the [Eubacterium] nodatum group were closely associated with xanthine, 2-picoline, and securinine, respectively. Tuzzerella alterations showed the highest number of associations with host endogenous metabolites such as FAHFA (8:0/10:0), FFA (20:2), carnitine C8:1, tridecanedioic acid, securinine, acetylvaline, DL-O-tyrosine, and Phe-Asn. This study indicates that the interplay between host serum metabolites and gut microbiota may contribute to the therapeutic effect of naringenin against NASH.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

Alteration of chromatin high-order conformation associated with oxaliplatin resistance acquisition in colorectal cancer cells

Oxaliplatin is a first-line chemotherapy drug widely adopted in colorectal cancer (CRC) treatment. However, a large proportion of patients tend to become resistant to oxaliplatin, causing chemotherapy to fail. At present, researches on oxaliplatin resistance mainly focus on the genetic and epigenetic alterations during cancer evolution, while the characteristics of high-order three-dimensional (3D) conformation of genome are yet to be explored. In order to investigate the chromatin conformation alteration during oxaliplatin resistance, we performed multi-omics study by combining DLO Hi-C, ChIP-seq as well as RNA-seq technologies on the established oxaliplatin-resistant cell line HCT116-OxR, as well as the control cell line HCT116. The results indicate that 19.33% of the genome regions have A/B compartments transformation after drug resistance, further analysis of the genes converted by A/B compartments reveals that the acquisition of oxaliplatin resistance in tumor cells is related to the reduction of reactive oxygen species and enhanced metastatic capacity. Our research reveals the spatial chromatin structural difference between CRC cells and oxaliplatin resistant cells based on the DLO Hi-C and other epigenetic omics experiments. More importantly, we provide potential targets for oxaliplatin-resistant cancer treatment and a new way to investigate drug resistance behavior under the perspective of 3D genome alteration.

Senescence-based colorectal cancer subtyping reveals distinct molecular characteristics and therapeutic strategies

Cellular senescence has been listed as a hallmark of cancer, but its role in colorectal cancer (CRC) remains unclear. We comprehensively evaluated the transcriptome, genome, digital pathology, and clinical data from multiple datasets of CRC patients and proposed a novel senescence subtype for CRC. Multi-omics data was used to analyze the biological features, tumor microenvironment, and mutation landscape of senescence subtypes, as well as drug sensitivity and immunotherapy response. The senescence score was constructed to better quantify senescence in each patient for clinical use. Unsupervised learning revealed three transcriptome-based senescence subtypes. Cluster 1, characterized by low senescence and activated proliferative pathways, was sensitive to chemotherapeutic drugs. Cluster 2, characterized by intermediate senescence and high immune infiltration, exhibited significant immunotherapeutic advantages. Cluster 3, characterized by high senescence, high immune, and stroma infiltration, had a worse prognosis and maybe benefit from targeted therapy. We further constructed a senescence scoring system based on seven senescent genes through machine learning. Lower senescence scores were highly predictive of longer disease-free survival, and patients with low senescence scores may benefit from immunotherapy. We proposed the senescence subtypes of CRC and our findings provide potential treatment interventions for each CRC senescence subtype to promote precision treatment.

Bridging the rodent to human translational gap: Marmosets as model systems for the study of Alzheimer's disease

Introduction

Our limited understanding of the mechanisms that trigger the emergence of Alzheimer's disease (AD) has contributed to the lack of interventions that stop, prevent, or fully treat this disease. We believe that the development of a non-human primate model of AD will be an essential step toward overcoming limitations of other model systems and is crucial for investigating primate-specific mechanisms underlying the cellular and molecular root causes of the pathogenesis and progression of AD.

Methods

A new consortium has been established with funding support from the National Institute on Aging aimed at the generation, characterization, and validation of Marmosets As Research Models of AD (MARMO-AD). This consortium will study gene-edited marmoset models carrying genetic risk for AD and wild-type genetically diverse aging marmosets from birth throughout their lifespan, using non-invasive longitudinal assessments. These include characterizing the genetic, molecular, functional, behavioral, cognitive, and pathological features of aging and AD.

Results

The consortium successfully generated viable founders carrying PSEN1 mutations in C410Y and A426P using CRISPR/Cas9 approaches, with germline transmission demonstrated in the C410Y line. Longitudinal characterization of these models, their germline offspring, and normal aging outbred marmosets is ongoing. All data and resources from this consortium will be shared with the greater AD research community.

Discussion

By establishing marmoset models of AD, we will be able to investigate primate-specific cellular and molecular root causes that underlie the pathogenesis and progression of AD, overcome limitations of other model organisms, and support future translational studies to accelerate the pace of bringing therapies to patients.

Multi-omic analyses in immune cell development with lessons learned from T cell development

Traditionally, flow cytometry has been the preferred method to characterize immune cells at the single-cell level. Flow cytometry is used in immunology mostly to measure the expression of identifying markers on the cell surface, but-with good antibodies-can also be used to assess the expression of intracellular proteins. The advent of single-cell RNA-sequencing has paved the road to study immune development at an unprecedented resolution. Single-cell RNA-sequencing studies have not only allowed us to efficiently chart the make-up of heterogeneous tissues, including their most rare cell populations, it also increasingly contributes to our understanding how different omics modalities interplay at a single cell resolution. Particularly for investigating the immune system, this means that these single-cell techniques can be integrated to combine and correlate RNA and protein data at the single-cell level. While RNA data usually reveals a large heterogeneity of a given population identified solely by a combination of surface protein markers, the integration of different omics modalities at a single cell resolution is expected to greatly contribute to our understanding of the immune system.

CTLA4-Mediated Immunosuppression in Glioblastoma is Associated with the Infiltration of Macrophages in the Tumor Microenvironment

Purpose

CTLA4, the immune checkpoint, has been widely reported to contribute to immune evasion in anti-tumor activity. The inhibitors of CTLA4 provide a novel strategy to improve the outcome of peripheral cancer, but their clinical effects are limited in glioblastoma (GBM), thus the comprehensive role of CTLA4 needs to be addressed.

Patients and Methods

A total of 471 GBM cases were enrolled in this study from 5 cohorts. In our works, the Cancer Genome Atlas (TCGA) cohort was divided into the training set, and the Chinese Glioma Genome Atlas (CGGA), REMBRANDT, and GSE84465 cohorts were divided into validation sets. Tissues from our cohort were collected for histopathologic validation. Then, the role of CTLA4 in the TME of GBM was comprehensively investigated.

Results

Significant differences exist in immunological characteristics between the low and high CTLA4 expression groups. Mutation analysis found different genomic patterns associated with CTLA4 expression. Next, network analysis found the module named c1-1562 including CTLA4 correlated with over survival (OS) in GBM. We also developed a predictive model to calculate the risk score for every GBM case and the risk score was independently related to OS. Furthermore, the expression of CTLA4 was positively related to the infiltration level and function of macrophage in GBM TME based on seven independent algorithms, single-cell RNA-seq data and immunohistochemistry.

Conclusion

These findings implicate that CTLA4 could serve as a novel target for prognosis and therapy in GBM patients. CTLA4-mediated immune suppression may be attributed to the infiltration of macrophages in the tumor microenvironment.

The hypoxia adaptation of small mammals to plateau and underground burrow conditions

Oxygen is one of the important substances for the survival of most life systems on the earth, and plateau and underground burrow systems are two typical hypoxic environments. Small mammals living in hypoxic environments have evolved different adaptation strategies, which include increased oxygen delivery, metabolic regulation of physiological responses and other physiological responses that change tissue oxygen utilization. Multi-omics predictions have also shown that these animals have evolved different adaptations to extreme environments. In particular, vascular endothelial growth factor (VEGF) and erythropoietin (EPO), which have specific functions in the control of O2 delivery, have evolved adaptively in small mammals in hypoxic environments. Naked mole-rats and blind mole-rats are typical hypoxic model animals as they have some resistance to cancer. This review primarily summarizes the main living environment of hypoxia tolerant small mammals, as well as the changes of phenotype, physiochemical characteristics and gene expression mode of their long-term living in hypoxia environment.

netDx: interpretable patient classification using integrated patient similarity networks

Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clinical predictor based on genomic data needs to be interpretable to drive hypothesis‐driven research into new treatments. We describe netDx, a novel supervised patient classification framework based on patient similarity networks, which meets these criteria. In a cancer survival benchmark dataset integrating up to six data types in four cancer types, netDx significantly outperforms most other machine‐learning approaches across most cancer types. Compared to traditional machine‐learning‐based patient classifiers, netDx results are more interpretable, visualizing the decision boundary in the context of patient similarity space. When patient similarity is defined by pathway‐level gene expression, netDx identifies biological pathways important for outcome prediction, as demonstrated in breast cancer and asthma. netDx can serve as a patient classifier and as a tool for discovery of biological features characteristic of disease. We provide a free software implementation of netDx with automation workflows.

Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets

Multi-omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy-chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multi-omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation.