Human-like adrenal features in Chinese tree shrews revealed by multi-omics analysis of adrenal cell populations and steroid synthesis

The Chinese tree shrew ( Tupaia belangeri chinensis) has emerged as a promising model for investigating adrenal steroid synthesis, but it is unclear whether the same cells produce steroid hormones and whether their production is regulated in the same way as in humans. Here, we comprehensively mapped the cell types and pathways of steroid metabolism in the adrenal gland of Chinese tree shrews using single-cell RNA sequencing, spatial transcriptome analysis, mass spectrometry, and immunohistochemistry. We compared the transcriptomes of various adrenal cell types across tree shrews, humans, macaques, and mice. Results showed that tree shrew adrenal glands expressed many of the same key enzymes for steroid synthesis as humans, including CYP11B2, CYP11B1, CYB5A, and CHGA. Biochemical analysis confirmed the production of aldosterone, cortisol, and dehydroepiandrosterone but not dehydroepiandrosterone sulfate in the tree shrew adrenal glands. Furthermore, genes in adrenal cell types in tree shrews were correlated with genetic risk factors for polycystic ovary syndrome, primary aldosteronism, hypertension, and related disorders in humans based on genome-wide association studies. Overall, this study suggests that the adrenal glands of Chinese tree shrews may consist of closely related cell populations with functional similarity to those of the human adrenal gland. Our comprehensive results (publicly available at http://gxmujyzmolab.cn:16245/scAGMap/) should facilitate the advancement of this animal model for the investigation of adrenal gland disorders.

Deciphering smooth muscle cell heterogeneity in atherosclerotic plaques and constructing model: a multi-omics approach with focus on KLF15/IGFBP4 axis

BACKGROUND

Ruptured atherosclerotic plaques often precipitate severe ischemic events, such as stroke and myocardial infarction. Unraveling the intricate molecular mechanisms governing vascular smooth muscle cell (VSMC) behavior in plaque stabilization remains a formidable challenge.

METHODS

In this study, we leveraged single-cell and transcriptomic datasets from atherosclerotic plaques retrieved from the gene expression omnibus (GEO) database. Employing a combination of single-cell population differential analysis, weighted gene co-expression network analysis (WGCNA), and transcriptome differential analysis techniques, we identified specific genes steering the transformation of VSMCs in atherosclerotic plaques. Diagnostic models were developed and validated through gene intersection, utilizing the least absolute shrinkage and selection operator (LASSO) and random forest (RF) methods. Nomograms for plaque assessment were constructed. Tissue localization and expression validation were performed on specimens from animal models, utilizing immunofluorescence co-localization, western blot, and reverse-transcription quantitative-polymerase chain reaction (RT-qPCR). Various online databases were harnessed to predict transcription factors (TFs) and their interacting compounds, with determination of the cell-specific localization of TF expression using single-cell data.

RESULTS

Following rigorous quality control procedures, we obtained a total of 40,953 cells, with 6,261 representing VSMCs. The VSMC population was subsequently clustered into 5 distinct subpopulations. Analyzing inter-subpopulation cellular communication, we focused on the SMC2 and SMC5 subpopulations. Single-cell subpopulation and WGCNA analyses revealed significant module enrichments, notably in collagen-containing extracellular matrix and cell-substrate junctions. Insulin-like growth factor binding protein 4 (IGFBP4), apolipoprotein E (APOE), and cathepsin C (CTSC) were identified as potential diagnostic markers for early and advanced plaques. Notably, gene expression pattern analysis suggested that IGFBP4 might serve as a protective gene, a hypothesis validated through tissue localization and expression analysis. Finally, we predicted TFs capable of binding to IGFBP4, with Krüppel-like family 15 (KLF15) emerging as a prominent candidate showing relative specificity within smooth muscle cells. Predictions about compounds associated with affecting KLF15 expression were also made.

CONCLUSION

Our study established a plaque diagnostic and assessment model and analyzed the molecular interaction mechanisms of smooth muscle cells within plaques. Further analysis revealed that the transcription factor KLF15 may regulate the biological behaviors of smooth muscle cells through the KLF15/IGFBP4 axis, thereby influencing the stability of advanced plaques via modulation of the PI3K-AKT signaling pathway. This could potentially serve as a target for plaque stability assessment and therapy, thus driving advancements in the management and treatment of atherosclerotic plaques.

A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework

Neuroblastoma (NB) is one of the leading causes of cancer-associated death in children. MYCN amplification is a prominent genetic marker for NB, and its targeting to halt NB progression is difficult to achieve. Therefore, an in-depth understanding of the molecular interactome of NB is needed to improve treatment outcomes. Analysis of NB multi-omics unravels valuable insight into the interplay between MYCN transcriptional and miRNA post-transcriptional modulation. Moreover, it aids in the identification of various miRNAs that participate in NB development and progression. This study proposes an integrated computational framework with three levels of high-throughput NB data (mRNA-seq, miRNA-seq, and methylation array). Similarity Network Fusion (SNF) and ranked SNF methods were utilized to identify essential genes and miRNAs. The specified genes included both miRNA-target genes and transcription factors (TFs). The interactions between TFs and miRNAs and between miRNAs and their target genes were retrieved where a regulatory network was developed. Finally, an interaction network-based analysis was performed to identify candidate biomarkers. The candidate biomarkers were further analyzed for their potential use in prognosis and diagnosis. The candidate biomarkers included three TFs and seven miRNAs. Four biomarkers have been previously studied and tested in NB, while the remaining identified biomarkers have known roles in other types of cancer. Although the specific molecular role is yet to be addressed, most identified biomarkers possess evidence of involvement in NB tumorigenesis. Analyzing cellular interactome to identify potential biomarkers is a promising approach that can contribute to optimizing efficient therapeutic regimens to target NB vulnerabilities.

Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis

Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.

Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma

We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10-7.67, Cox P = 2.63e-05) and PFS (HR = 3.72, 95% CI 2.06-6.73, Cox P = 1.38e-05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24-6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16-3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2-3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08-3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH.

Nanoplastic toxicity induces metabolic shifts in Populus × euramericana cv. '74/76' revealed by multi-omics analysis

There is increasing global concern regarding the pervasive issue of plastic pollution. We investigated the response of Populus × euramericana cv. '74/76' to nanoplastic toxicity via phenotypic, microanatomical, physiological, transcriptomic, and metabolomic approaches. Polystyrene nanoplastics (PS-NPs) were distributed throughout the test plants after the application of PS-NPs. Nanoplastics principally accumulated in the roots; minimal fractions were translocated to the leaves. In leaves, however, PS-NPs easily penetrated membranes and became concentrated in chloroplasts, causing thylakoid disintegration and chlorophyll degradation. Finally, oxidant damage from the influx of PS-NPs led to diminished photosynthesis, stunted growth, and etiolation and/or wilting. By integrating dual-omics data, we found that plants could counteract mild PS-NP-induced oxidative stress through the antioxidant enzyme system without initiating secondary metabolic defense mechanisms. In contrast, severe PS-NP treatments promoted a shift in metabolic pattern from primary metabolism to secondary metabolic defense mechanisms, an effect that was particularly pronounced during the upregulation of flavonoid biosynthesis. Our findings provide a useful framework from which to further clarify the roles of key biochemical pathways in plant responses to nanoplastic toxicity. Our work also supports the development of effective strategies to mitigate the environmental risks of nanoplastics by biologically immobilizing them in contaminated lands.

Implications of GCLC in prognosis and immunity of lung adenocarcinoma and multi-omics regulation mechanisms

BACKGROUND

Ferroptosis is an iron-dependent type of regulated cell death, and has been implicated in lung adenocarcinoma (LUAD). Evidence has proved the key role of glutamate-cysteine ligase catalytic subunit (GCLC) in ferroptosis, but its role in LUAD remains unclear. Herein, we explored the implications of GCLC and relevant genes in LUAD prognosis and immunity as well as underlying molecular mechanisms.

METHODS

This work gathered mRNA, miRNA, DNA methylation, somatic mutation and copy-number variation data from TCGA-LUAD. WGCNA was utilized for selecting GCLC-relevant genes, and a GCLC-relevant prognostic signature was built by uni- and multivariate-cox regression analyses. Immune compositions were estimated via CIBERSORT, and two immunotherapy cohorts of solid tumors were analyzed. Multi-omics regulatory mechanisms were finally assessed.

RESULTS

Our results showed that GCLC was overexpressed in LUAD, and potentially resulted in undesirable survival. A prognostic model was generated, which owned accurate and independent performance in prognostication. GCLC, and relevant genes were notably connected with immune compositions and immune checkpoints. High GCLC expression was linked with better responses to anti-PD-L1 and anti-CTLA-4 treatment. Their possible DNA methylation sites were inferred, e.g., hypomethylation in cg19740353 might contribute to GCLC up-regulation. Frequent genetic mutations also affected their expression. Upstream transcription factors (E2F1/3/4, etc.), post-transcriptional regulation of miRNAs (hsa-mir-30c-1, etc.), lncRNAs (C8orf34-AS1, etc.), and IGF2BP1-mediated m6A modification were identified. It was also found NOP58-mediated SUMOylation post-translational modification.

CONCLUSIONS

Together, we show that GCLC and relevant genes exert crucial roles in LUAD prognosis and immunity, and their expression can be controlled by complex multi-omics mechanisms.

Dynamic molecular choreography induced by acute heat exposure in human males: a longitudinal multi-omics profiling study

Introduction

Extreme heat events caused by occupational exposure and heat waves are becoming more common. However, the molecular changes underlying the response to heat exposure in humans remain to be elucidated.

Methods

This study used longitudinal multi-omics profiling to assess the impact of acute heat exposure (50°C for 30 min) in 24 subjects from a mine rescue team. Intravenous blood samples were collected before acute heat exposure (baseline) and at 5 min, 30 min, 1 h, and 24 h after acute heat exposure (recovery). In-depth multi-omics profiling was performed on each sample, including plasma proteomics (untargeted) and metabolomics (untargeted).

Results

After data curation and annotation, the final dataset contained 2,473 analytes, including 478 proteins and 1995 metabolites. Time-series analysis unveiled an orchestrated molecular choreography of changes involving the immune response, coagulation, acid-base balance, oxidative stress, cytoskeleton, and energy metabolism. Further analysis through protein-protein interactions and network analysis revealed potential regulators of acute heat exposure. Moreover, novel blood-based analytes that predicted change in cardiopulmonary function after acute heat exposure were identified.

Conclusion

This study provided a comprehensive investigation of the dynamic molecular changes that underlie the complex physiological processes that occur in human males who undergo heat exposure. Our findings will help health impact assessment of extreme high temperature and inspire future mechanistic and clinical studies.

Multiomics unravels potential molecular switches in the C3 to CAM transition of Mesembryanthemum crystallinum

Mesembryanthemum crystallinum (common ice plant), a facultative CAM plant, shifts from C3 to CAM photosynthesis under salt stress, enhancing water use efficiency. Here we used transcriptomics, proteomics, and targeted metabolomics to profile molecular changes during the diel cycle of C3 to CAM transition. The results confirmed expected changes associated with CAM photosynthesis, starch biosynthesis and degradation, and glycolysis/gluconeogenesis. Importantly, they yielded new discoveries: 1) Transcripts displayed greater circadian regulation than proteins. 2) Oxidative phosphorylation and inositol methylation may play important roles in initiating the transition. 3) V-type H+-ATPases showed consistent transcriptional regulation, aiding in vacuolar malate uptake. 4) A protein phosphatase 2C, a major component in the ABA signaling pathway, may trigger the C3 to CAM transition. Our work highlights the potential molecular switches in the C3 to CAM transition, including the potential role of ABA signaling. SIGNIFICANCE: The common ice plant is a model facultative CAM plant, and under stress conditions it can shift from C3 to CAM photosynthesis within a three-day period. However, knowledge about the molecular changes during the transition and the molecular switches enabling the transition is lacking. Multi-omic analyses not only revealed the molecular changes during the transition, but also highlighted the importance of ABA signaling, inositol methylation, V-type H+-ATPase in initiating the shift. The findings may explain physiological changes and nocturnal stomatal opening, and inform future synthetic biology effort in improving crop water use efficiency and stress resilience.

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.

Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease

Parkinson's disease (PD) is a complex neurodegenerative disorder without a cure. The onset of PD symptoms corresponds to 50% loss of midbrain dopaminergic (mDA) neurons, limiting early-stage understanding of PD. To shed light on early PD development, we study time series scRNA-seq datasets of mDA neurons obtained from patient-derived induced pluripotent stem cell differentiation. We develop a new data integration method based on Non-negative Matrix Tri-Factorization that integrates these datasets with molecular interaction networks, producing condition-specific "gene embeddings". By mining these embeddings, we predict 193 PD-related genes that are largely supported (49.7%) in the literature and are specific to the investigated PINK1 mutation. Enrichment analysis in Kyoto Encyclopedia of Genes and Genomes pathways highlights 10 PD-related molecular mechanisms perturbed during early PD development. Finally, investigating the top 20 prioritized genes reveals 12 previously unrecognized genes associated with PD that represent interesting drug targets.

Developing and validating multi-omics prediction models for late patient-reported dysphagia in head and neck radiotherapy

Background and purpose. To investigate models developed using radiomic and dosiomic (multi-omics) features from planning and treatment imaging for late patient-reported dysphagia in head and neck radiotherapy.Materials and methods. Training (n = 64) and testing (n = 23) cohorts of head and neck cancer patients treated with curative intent chemo-radiotherapy with a follow-up time greater than 12 months were retrospectively examined. Patients completed the MD Anderson Dysphagia Inventory and a composite score ≤60 was interpreted as patient-reported dysphagia. A chart review collected baseline dysphagia and clinical factors. Multi-omic features were extracted from planning and last synthetic CT images using the pharyngeal constrictor muscle contours as a region of interest. Late patient-reported dysphagia models were developed using a random forest backbone, with feature selection and up-sampling methods to account for the imbalanced data. Models were developed and validated for multi-omic feature combinations for both timepoints.Results. A clinical and radiomic feature model developed using the planning CT achieved good performance (validation: sensitivity = 80 ± 27% / balanced accuracy = 71 ± 23%, testing: sensitivity = 80 ± 10% / balanced accuracy = 73 ± 11%). The synthetic CT models did not show improvement over the plan CT multi-omics models, with poor reliability of the radiomic features on these images. Dosiomic features extracted from the synthetic CT showed promise in predicting late patient-reported dysphagia.Conclusion. Multi-omics models can predict late patient-reported dysphagia in head and neck radiotherapy patients. Synthetic CT dosiomic features show promise in developing successful models to account for changes in delivered dose distribution. Multi-center or prospective studies are required prior to clinical implementation of these models.

A study protocol to characterise pathophysiological and molecular markers of rheumatic heart disease and degenerative aortic stenosis using multiparametric cardiovascular imaging and multiomics techniques

INTRODUCTION

Rheumatic heart disease (RHD), degenerative aortic stenosis (AS), and congenital valve diseases are prevalent in sub-Saharan Africa. Many knowledge gaps remain in understanding disease mechanisms, stratifying phenotypes, and prognostication. Therefore, we aimed to characterise patients through clinical profiling, imaging, histology, and molecular biomarkers to improve our understanding of the pathophysiology, diagnosis, and prognosis of RHD and AS.

METHODS

In this cross-sectional, case-controlled study, we plan to recruit RHD and AS patients and compare them to matched controls. Living participants will undergo clinical assessment, echocardiography, CMR and blood sampling for circulatory biomarker analyses. Tissue samples will be obtained from patients undergoing valve replacement, while healthy tissues will be obtained from cadavers. Immunohistology, proteomics, metabolomics, and transcriptome analyses will be used to analyse circulatory- and tissue-specific biomarkers. Univariate and multivariate statistical analyses will be used for hypothesis testing and identification of important biomarkers. In summary, this study aims to delineate the pathophysiology of RHD and degenerative AS using multiparametric CMR imaging. In addition to discover novel biomarkers and explore the pathomechanisms associated with RHD and AS through high-throughput profiling of the tissue and blood proteome and metabolome and provide a proof of concept of the suitability of using cadaveric tissues as controls for cardiovascular disease studies.

EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays

Multiomic droplet-based technologies allow different molecular modalities, such as chromatin accessibility and gene expression (scATAC-seq and scRNA-seq), to be probed in the same nucleus. We develop EmptyDropsMultiome, an approach that distinguishes true nuclei-containing droplets from background. Using simulations, we show that EmptyDropsMultiome has higher statistical power and accuracy than existing approaches, including CellRanger-arc and EmptyDrops. On real datasets, we observe that CellRanger-arc misses more than half of the nuclei identified by EmptyDropsMultiome and, moreover, is biased against certain cell types, some of which have a retrieval rate lower than 20%.

Multi-omics integration highlights the role of ubiquitination in endometriosis fibrosis

BACKGROUND

Endometriosis, characterized by the presence of active endometrial-like tissues outside the uterus, causes symptoms like dysmenorrhea and infertility due to the fibrosis of endometrial cells, which involves excessive deposition of extracellular matrix (ECM) proteins. Ubiquitination, an important post-transcriptional modification, regulates various biological processes in human diseases. However, its role in the fibrosis process in endometriosis remains unclear.

METHODS

We employed multi-omics approaches on two cohorts of endometriosis patients with 39 samples. GO terms and KEGG pathways enrichment analyses were used to investigate the functional changes involved in endometriosis. Pearson's correlation coefficient analysis was conducted to explore the relationship between global proteome and ubiquitylome in endometriosis. The protein expression levels of ubiquitin-, fibrosis-related proteins, and E3 ubiquitin-protein ligase TRIM33 were validated via Western blot. Transfecting human endometrial stroma cells (hESCs) with TRIM33 small interfering RNA (siRNA) in vitro to explore how TRIM33 affects fibrosis-related proteins.

RESULTS

Integration of proteomics and transcriptomics showed genes with concurrent change of both mRNA and protein level which involved in ECM production in ectopic endometria. Ubiquitylomics distinguished 1647 and 1698 ubiquitinated lysine sites in the ectopic (EC) group compared to the normal (NC) and eutopic (EU) groups, respectively. Further multi-omics integration highlighted the essential role of ubiquitination in key fibrosis regulators in endometriosis. Correlation analysis between proteome and ubiquitylome showed correlation coefficients of 0.32 and 0.36 for ubiquitinated fibrosis proteins in EC/NC and EC/EU groups, respectively, indicating positive regulation of fibrosis-related protein expression by ubiquitination in ectopic lesions. We identified ubiquitination in 41 pivotal proteins within the fibrosis-related pathway of endometriosis. Finally, the elevated expression of TGFBR1/α-SMA/FAP/FN1/Collagen1 proteins in EC tissues were validated across independent samples. More importantly, we demonstrated that both the mRNA and protein levels of TRIM33 were reduced in endometriotic tissues. Knockdown of TRIM33 promoted TGFBR1/p-SMAD2/α-SMA/FN1 protein expressions in hESCs but did not significantly affect Collagen1/FAP levels, suggesting its inhibitory effect on fibrosis in vitro.

CONCLUSIONS

This study, employing multi-omics approaches, provides novel insights into endometriosis ubiquitination profiles and reveals aberrant expression of the E3 ubiquitin ligase TRIM33 in endometriotic tissues, emphasizing their critical involvement in fibrosis pathogenesis and potential therapeutic targets.

An integrated multi-omics approach reveals polymethoxylated flavonoid biosynthesis in Citrus reticulata cv. Chachiensis

Citrus reticulata cv. Chachiensis (CRC) is an important medicinal plant, its dried mature peels named "Guangchenpi", has been used as a traditional Chinese medicine to treat cough, indigestion, and lung diseases for several hundred years. However, the biosynthesis of the crucial natural products polymethoxylated flavonoids (PMFs) in CRC remains unclear. Here, we report a chromosome-scale genome assembly of CRC with the size of 314.96 Mb and a contig N50 of 16.22 Mb. Using multi-omics resources, we discover a putative caffeic acid O-methyltransferase (CcOMT1) that can transfer a methyl group to the 3-hydroxyl of natsudaidain to form 3,5,6,7,8,3',4'-heptamethoxyflavone (HPMF). Based on transient overexpression and virus-induced gene silencing experiments, we propose that CcOMT1 is a candidate enzyme in HPMF biosynthesis. In addition, a potential gene regulatory network associated with PMF biosynthesis is identified. This study provides insights into PMF biosynthesis and may assist future research on mining genes for the biosynthesis of plant-based medicines.

Integrative multiomics enhancer activity profiling identifies therapeutic vulnerabilities in cholangiocarcinoma of different etiologies

OBJECTIVES

Cholangiocarcinoma (CCA) is a heterogeneous malignancy with high mortality and dismal prognosis, and an urgent clinical need for new therapies. Knowledge of the CCA epigenome is largely limited to aberrant DNA methylation. Dysregulation of enhancer activities has been identified to affect carcinogenesis and leveraged for new therapies but is uninvestigated in CCA. Our aim is to identify potential therapeutic targets in different subtypes of CCA through enhancer profiling.

DESIGN

Integrative multiomics enhancer activity profiling of diverse CCA was performed. A panel of diverse CCA cell lines, patient-derived and cell line-derived xenografts were used to study identified enriched pathways and vulnerabilities. NanoString, multiplex immunohistochemistry staining and single-cell spatial transcriptomics were used to explore the immunogenicity of diverse CCA.

RESULTS

We identified three distinct groups, associated with different etiologies and unique pathways. Drug inhibitors of identified pathways reduced tumour growth in in vitro and in vivo models. The first group (ESTRO), with mostly fluke-positive CCAs, displayed activation in estrogen signalling and were sensitive to MTOR inhibitors. Another group (OXPHO), with mostly BAP1 and IDH-mutant CCAs, displayed activated oxidative phosphorylation pathways, and were sensitive to oxidative phosphorylation inhibitors. Immune-related pathways were activated in the final group (IMMUN), made up of an immunogenic CCA subtype and CCA with aristolochic acid (AA) mutational signatures. Intratumour differences in AA mutation load were correlated to intratumour variation of different immune cell populations.

CONCLUSION

Our study elucidates the mechanisms underlying enhancer dysregulation and deepens understanding of different tumourigenesis processes in distinct CCA subtypes, with potential significant therapeutics and clinical benefits.

Integrated multi-omic approach reveals the effect of a Graminaceae-derived biostimulant and its lighter fraction on salt-stressed lettuce plants

Plant biostimulants are widely applied in agriculture for their ability to improve plant fitness. In the present work, the impact of Graminaceae-derived protein hydrolysate (P) and its lighter molecular fraction F3 (< 1 kDa) on lettuce plants, subjected to either no salt or high salt conditions, was investigated through the combination of metabolomics and transcriptomics. The results showed that both treatments significantly modulated the transcriptome and metabolome of plants under salinity stress, highlighting an induction of the hormonal response. Nevertheless, P and F3 also displayed several peculiarities. F3 specifically modulated the response to ethylene and MAPK signaling pathway, whereas P treatment induced a down-accumulation of secondary metabolites, albeit genes controlling the biosynthesis of osmoprotectants and antioxidants were up-regulated. Moreover, according with the auxin response modulation, P promoted cell wall biogenesis and plasticity in salt-stressed plants. Notably, our data also outlined an epigenetic control of gene expression induced by P treatment. Contrarily, experimental data are just partially in agreement when not stressed plants, treated with P or F3, were considered. Indeed, the reduced accumulation of secondary metabolites and the analyses of hormone pathways modulation would suggest a preferential allocation of resources towards growth, that is not coherent with the down-regulation of the photosynthetic machinery, the CO2 assimilation rate and leaves biomass. In conclusion, our data demonstrate that, although they might activate different mechanisms, both the P and F3 can result in similar benefits, as far as the accumulation of protective osmolytes and the enhanced tolerance to oxidative stress are concerned. Notably, the F3 fraction exhibits slightly greater growth promotion effects under high salt conditions. Most importantly, this research further corroborates that biostimulants' mode of action is dependent on plants' physiological status and their composition, underscoring the importance of investigating the bioactivity of the different molecular components to design tailored applications for the agricultural practice.

Multiomics-based molecular subtyping based on the commensal microbiome predicts molecular characteristics and the therapeutic response in breast cancer

The gut microbiota has been demonstrated to be correlated with the clinical phenotypes of diseases, including cancers. However, there are few studies on clinical subtyping based on the gut microbiota, especially in breast cancer (BC) patients. Here, using machine learning methods, we analysed the gut microbiota of BC, colorectal cancer (CRC), and gastric cancer (GC) patients to identify their shared metabolic pathways and the importance of these pathways in cancer development. Based on the gut microbiota-related metabolic pathways, human gene expression profile and patient prognosis, we established a novel BC subtyping system and identified a subtype called "challenging BC". Tumours with this subtype have more genetic mutations and a more complex immune environment than those of other subtypes. A score index was proposed for in-depth analysis and showed a significant negative correlation with patient prognosis. Notably, activation of the TPK1-FOXP3-mediated Hedgehog signalling pathway and TPK1-ITGAE-mediated mTOR signalling pathway was linked to poor prognosis in "challenging BC" patients with high scores, as validated in a patient-derived xenograft (PDX) model. Furthermore, our subtyping system and score index are effective predictors of the response to current neoadjuvant therapy regimens, with the score index significantly negatively correlated with both treatment efficacy and the number of immune cells. Therefore, our findings provide valuable insights into predicting molecular characteristics and treatment responses in "challenging BC" patients.

Research on the mechanism of regulating spleen-deficient obesity in rats by bawei guben huashi jiangzhi decoction based on multi-omics analysis

ETHNOPHARMACOLOGY RELEVANCE

Bawei Guben Huashi Jiangzhi Decoction (BGHJ), a traditional Chinese compound formula, comprises eight Chinese medicinal herbs: Codonopsis Radix, Atractylodis Macrocephalae Rhizoma, Cassiae Semen, Lysimachiae Herba, Edgeworthiae Gardner Flos, Oryzae Semen cum Monasco, Nelumbinis Folium, and Alismatis Rhizoma. It has the therapeutic effects of improving digestive and absorptive functions of the gastrointestinal tract, reducing cholesterol levels, and helping to lose weight. Therefore, BGHJ is mainly used to treat spleen-deficient obesity (SDO) clinically.

AIM OF THE STUDY

This study aims to examine the efficacy and mechanism of BGHJ in a model of SDO in rats, as well as the potentially involved constituents entering the blood and differential metabolites.

METHODS

The SDO rat model was replicated utilizing a high-fat and high-sugar diet in conjunction with exhaustive swimming. Subsequently, the rats were subjected to a six-week intervention comprising varying dosages of BGHJ and a positive control, orlistat. To evaluate the efficacy of BGHJ on SDO model rats, we first measured the rats' body weight, body surface temperature, spleen index, as well as biochemical indicators in the serum and colon, and then assessed the pathological state of the colon and liver. Afterward, we analyzed the 16S rDNA gut microbiota, non-targeted serum metabolomics, and serum pharmacology to study the main active components of BGHJ and its action mechanism against SDO model rats. In addition, we constructed a network diagram for overall visualization and analysis, and experimentally verified the predicted results. Finally, we used quantitative polymerase chain reaction (qPCR) to detect the gene expression of proopiomelanocortin (POMC) and neuropeptide Y (NPY) indicators in rat hypothalamic neurons. We quantitatively targeted the detection of neurotransmitters dopamine (DA), acetylcholine (Ach), 5-hydroxytryptamine (5-HT), and noradrenaline (NA) in rat hypothalamus.

RESULTS

The results demonstrated that all dosage regimens of BGHJ exhibited the capacity to moderately modulate parameters including body weight, surface temperature, spleen index, total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), glucagon-like peptide-1 (GLP-1), cholecystokinin (CCK), 5-HT, interleukin 6 (IL-6) and interleukin 17 (IL-17), while concurrently reducing hepatic lipid droplet deposition and restoring intestinal integrity. Subsequent experimental results showed that we successfully identified 27 blood components of BGHJ and identified 52 differential metabolites in SDO model rats. At the same time, the experiment proved that BGHJ could effectively inhibit the metabolic pathway of arachidonic acid. In addition, BGHJ can also restore the intestinal microbiota composition of SDO model rats. Finally, we also found that BGHJ could regulate the expression of hypothalamic neurons and neurotransmitters.

CONCLUSIONS

The research revealed the main active ingredients of BGHJ and its mechanism against SDO model rats through gut microbiota, non-target serum metabolomics, and serum drug chemistry.

Multi-omics reveals the testosterone promotion effect mechanism of Cordyceps Sobolifera on Leydig cells

ETHNOPHARMACOLOGICAL RELEVANCE

Cordyceps sobolifera (CS) has been traditionally utilized as an ethnic remedy for various health conditions, including chronic kidney diseases, anti-fatigue interventions, and management of chronic inflammation. Notably, CS is recognized for its substantial content of bioactive compounds, among which nucleosides prominently feature as constituents with diverse therapeutic advantages.

AIM OF THE STUDY

This study aims to investigate the effects of CS on testosterone secretion in Leydig cells and explore the underlying mechanism.

MATERIALS AND METHODS

Leydig cells were isolated from rat testes to establish a primary rat Leydig cells model. Cell proliferation and testosterone secretion were assessed via the methyl-piperidino-pyrazole (MTT) assay and enzyme-linked immunosorbent assay (ELISA), respectively. Samples earmarked for RNA sequencing (RNA-Seq) analysis facilitated the identification of significantly differentially expressed genes (DEGs), and we conducted Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation and enrichment analyses. The veracity of our findings was validated through quantitative real time polymerase chain reaction (qRT-PCR) and western blotting.

RESULTS

The results showed that CS and guanosine could promote Leydig cell proliferation and bolster testosterone secretion. Our integrative analysis of metabolomics and transcriptomics has unveiled the potential mechanisms governing testosterone synthesis. Specifically, metabolomics has illuminated striking correlations within cholesterol metabolism, and bile secretion. Concurrently, transcriptomics has underscored the pivotal roles played by the cyclic adenosine monophosphate (cAMP) signaling pathway and steroid hormone biosynthesis. Furthermore, our investigation has demonstrated CS's aptitude in elevating the expression of proteins and genes. Notably, our findings have elucidated that these effects can be mitigated by protein kinase A (PKA) and adenylate cyclase (AC) specific inhibitors.

CONCLUSION

This study delineates the cAMP-PKA pathways as plausible mechanisms underpinning the testosterone-enhancing properties of CS, with guanosine emerging as a fundamental bioactive constituent.

A time-resolved multi-omics atlas of transcriptional regulation in response to high-altitude hypoxia across whole-body tissues

High-altitude hypoxia acclimatization requires whole-body physiological regulation in highland immigrants, but the underlying genetic mechanism has not been clarified. Here we use sheep as an animal model for low-to-high altitude translocation. We generate multi-omics data including whole-genome sequences, time-resolved bulk RNA-Seq, ATAC-Seq and single-cell RNA-Seq from multiple tissues as well as phenotypic data from 20 bio-indicators. We characterize transcriptional changes of all genes in each tissue, and examine multi-tissue temporal dynamics and transcriptional interactions among genes. Particularly, we identify critical functional genes regulating the short response to hypoxia in each tissue (e.g., PARG in the cerebellum and HMOX1 in the colon). We further identify TAD-constrained cis-regulatory elements, which suppress the transcriptional activity of most genes under hypoxia. Phenotypic and transcriptional evidence indicate that antenatal hypoxia could improve hypoxia tolerance in offspring. Furthermore, we provide time-series expression data of candidate genes associated with human mountain sickness (e.g., BMPR2) and high-altitude adaptation (e.g., HIF1A). Our study provides valuable resources and insights for future hypoxia-related studies in mammals.

GametesOmics: A Comprehensive Multi-omics Database for Exploring the Gametogenesis in Humans and Mice

Gametogenesis plays an important role in the reproduction and evolution of species. The transcriptomic and epigenetic alterations in this process can influence the reproductive capacity, fertilization, and embryonic development. The rapidly increasing single-cell studies have provided valuable multi-omics resources. However, data from different layers and sequencing platforms have not been uniformed and integrated, which greatly limits their use for exploring the molecular mechanisms that underlie oogenesis and spermatogenesis. Here, we develop GametesOmics, a comprehensive database that integrates the data of gene expression, DNA methylation, and chromatin accessibility during oogenesis and spermatogenesis in humans and mice. GametesOmics provides a user-friendly website and various tools, including Search and Advanced Search for querying the expression and epigenetic modification(s) of each gene; Tools with Differentially expressed gene (DEG) analysis for identifying DEGs, Correlation analysis for demonstrating the genetic and epigenetic changes, Visualization for displaying single-cell clusters and screening marker genes as well as master transcription factors (TFs), and MethylView for studying the genomic distribution of epigenetic modifications. GametesOmics also provides Genome Browser and Ortholog for tracking and comparing gene expression, DNA methylation, and chromatin accessibility between humans and mice. GametesOmics offers a comprehensive resource for biologists and clinicians to decipher the cell fate transition in germ cell development, and can be accessed at http://gametesomics.cn/.

An integrative multi-omic analysis defines gut microbiota, mycobiota, and metabolic fingerprints in ulcerative colitis patients

Background

Ulcerative colitis (UC) is a multifactorial chronic inflammatory bowel disease (IBD) that affects the large intestine with superficial mucosal inflammation. A dysbiotic gut microbial profile has been associated with UC. Our study aimed to characterize the UC gut bacterial, fungal, and metabolic fingerprints by omic approaches.

Methods

The 16S rRNA- and ITS2-based metataxonomics and gas chromatography-mass spectrometry/solid phase microextraction (GC-MS/SPME) metabolomic analysis were performed on stool samples of 53 UC patients and 37 healthy subjects (CTRL). Univariate and multivariate approaches were applied to separated and integrated omic data, to define microbiota, mycobiota, and metabolic signatures in UC. The interaction between gut bacteria and fungi was investigated by network analysis.

Results

In the UC cohort, we reported the increase of Streptococcus, Bifidobacterium, Enterobacteriaceae, TM7-3, Granulicatella, Peptostreptococcus, Lactobacillus, Veillonella, Enterococcus, Peptoniphilus, Gemellaceae, and phenylethyl alcohol; and we also reported the decrease of Akkermansia; Ruminococcaceae; Ruminococcus; Gemmiger; Methanobrevibacter; Oscillospira; Coprococus; Christensenellaceae; Clavispora; Vishniacozyma; Quambalaria; hexadecane; cyclopentadecane; 5-hepten-2-ol, 6 methyl; 3-carene; caryophyllene; p-Cresol; 2-butenal; indole, 3-methyl-; 6-methyl-3,5-heptadiene-2-one; 5-octadecene; and 5-hepten-2-one, 6 methyl. The integration of the multi-omic data confirmed the presence of a distinctive bacterial, fungal, and metabolic fingerprint in UC gut microbiota. Moreover, the network analysis highlighted bacterial and fungal synergistic and/or divergent interkingdom interactions.

Conclusion

In this study, we identified intestinal bacterial, fungal, and metabolic UC-associated biomarkers. Furthermore, evidence on the relationships between bacterial and fungal ecosystems provides a comprehensive perspective on intestinal dysbiosis and ecological interactions between microorganisms in the framework of UC.