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Received — 10 September 2026 ⏭ (Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)

Divergent lipid utilization strategies of SARS-CoV-2 and MERS-CoV revealed by comparative multi-omics profiling of infected mouse lung tissues

Front Immunol. 2026 Aug 25;17:1902981. doi: 10.3389/fimmu.2026.1902981. eCollection 2026.

ABSTRACT

BACKGROUND: Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models.

METHODS: We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling.

RESULTS: We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol-lipid droplet-interferon axis for SARS-CoV-2 and a phospholipid-sphingolipid-membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV.

CONCLUSION: These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

PMID:42712680 | PMC:PMC13550176 | DOI:10.3389/fimmu.2026.1902981

Received — 27 May 2026 ⏭ (Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)

A Non-Canonical Role of SMAD4 in Regulating 3D Genome Architecture to Inhibit Lung Squamous Cell Carcinoma Development

Adv Sci (Weinh). 2026 May 26:e75839. doi: 10.1002/advs.75839. Online ahead of print.

ABSTRACT

Lung squamous cell carcinoma (LUSC) lacks clearly defined key drivers and effective targeted therapies, reflecting an incomplete understanding of its molecular pathogenesis. Here, we identify SMAD4 as a critical regulator of three-dimensional (3D) genome organization in LUSC and uncover a mechanistic link between tumor suppressor loss and oncogenic transcriptional activation. By integrating clinical datasets, genetically engineered mouse models, human and murine LUSC cell lines, and multi-omics analyses, we demonstrate that SMAD4 deficiency promotes LUSC progression by unleashing EP300-mediated enhancer-promoter looping at the SOX2 locus. Mechanistically, SMAD4 does not directly bind SOX2 regulatory elements but instead constrains chromatin looping by sequestering EP300 away from loop anchor regions. Loss of SMAD4 leads to enhanced H3K27ac deposition, aberrant SOX2 activation, and increased LUSC tumor cell proliferation. Together, these findings reveal a non-canonical role for a transcription factor (e.g., SMAD4) in regulating dysregulated 3D genome architecture to inhibit tumor development.

PMID:42189071 | DOI:10.1002/advs.75839

Multi-Omics Identification of Biomarkers for High-Altitude Pulmonary Hypertension

J Cardiovasc Dev Dis. 2026 Apr 30;13(5):195. doi: 10.3390/jcdd13050195.

ABSTRACT

(1) Aim: The incidence of high-altitude pulmonary hypertension (HAPH) has risen in recent years and is expected to continue increasing; however, its diagnosis remains challenging. In this study, we employed proteomics and metabolomics to identify the proteins and metabolic biomarkers that contribute to the development of HAPH. (2) Methods: We applied integrated proteomics and metabolomics to match blood samples from 40 HAPH patients and 40 healthy controls in Yunnan's high-altitude regions to characterize molecular profiles, identify biomarkers, and develop a predictive model. (3) Results: Proteomic analysis identified four proteins (A2IPH7, K1C14, PSME2, SERPINE2) commonly dysregulated in HAPH patients from two high-altitude regions. SERPINE2 was notably downregulated and showed a negative correlation with clinical severity, which was further validated in HAPH rat lung tissues and supported by UK Biobank data for idiopathic PAH. Concurrent metabolomics uncovered 11 shared metabolites, largely acyl fatty acids, enriched in pathways such as unsaturated fatty acid synthesis. Integration of these multi-omics data enabled the development of a robust predictive model. (4) Conclusion: Our study identified key protein and metabolic biomarkers involved in HAPH development, which were validated in animal models. Based on these findings, a predictive model was developed, highlighting SERPINE2 and 11 metabolites as promising targets for the prediction and prevention of HAPH.

PMID:42188081 | DOI:10.3390/jcdd13050195

Received — 4 April 2026 ⏭ (Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)

A distinct plasma lipidomic signature and multi-omics network in depression of polycystic ovary syndrome

J Pharm Biomed Anal. 2026 Mar 29;276:117486. doi: 10.1016/j.jpba.2026.117486. Online ahead of print.

ABSTRACT

Patients with polycystic ovary syndrome (PCOS) are at an elevated risk of depression, yet the underlying mechanisms remain elusive. Emerging evidence implicates the gut-brain axis and systemic lipid homeostasis alterations as potential key contributors. We profiled untargeted plasma lipidomes of PCOS patients with and without comorbid depression (PCOS-DP) and integrated these data with our prior gut microbial and host transcriptomic datasets to construct multi-omics interaction networks. The causal role of the candidate gut microbial was preliminary explored in a germ-free PCOS mouse model using fecal microbiota transplantation, followed by behavioral phenotyping and ELISA-based protein quantification. We identified a distinct plasma lipidomic signature differentiating PCOS-DP from PCOS alone, characterized primarily by the downregulation of 26 lipid species. Most of these altered lipids were triacylglycerols (TAGs) enriched with FA18:1 and FA18:2, whose levels correlated with coagulation dysfunction. Multi-omics network analysis revealed significant interconnections between depression-associated gut microbiota (including Bacteroides eggerthii), specific altered lipids such as TAG (60:12/FA22:6), and host genes involved in inflammation (e.g., IL22, NLRP7), metabolism, and neural processes. Animal validation demonstrated that B. eggerthii colonization in PCOS mice specifically exacerbated anhedonia and hyperlocomotion, alongside modulating plasma IL-22 expression, suggesting its context-dependent neurobehavioral effect role. This study delineates a TAG-downregulated lipid signature with diagnostic potential and reveals a novel "gut microbiota-lipid-host gene" interaction network underpinning PCOS-DP, with B. eggerthii as a key microbial modulator of neurobehavioral phenotypes in the context of PCOS. These findings provide new pathophysiological insights and highlights potential diagnostic biomarkers for PCOS-DP.

PMID:41924769 | DOI:10.1016/j.jpba.2026.117486

Received — 14 March 2026 ⏭ (Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)

Autophagy-centered regulation of PI3K/Akt/mTOR and MAPK signaling by traditional Chinese medicine in gastric cancer

Tissue Cell. 2026 Mar 10;101:103409. doi: 10.1016/j.tice.2026.103409. Online ahead of print.

ABSTRACT

Gastric cancer (GC) remains a major global health burden, with high incidence and mortality rates, particularly in East Asia, driven by factors such as Helicobacter pylori infection, dietary risks, and genetic predispositions. Conventional treatments like surgery and chemotherapy are limited by resistance, toxicity, and poor outcomes in advanced stages. The PI3K/Akt/mTOR and MAPK signaling pathways are central to GC pathogenesis, promoting proliferation, survival, metabolic reprogramming, epithelial-mesenchymal transition (EMT), and metastasis through aberrations like PIK3CA mutations, PTEN loss, and KRAS alterations. These pathways exhibit extensive crosstalk, contributing to therapeutic resistance. This review explores the regulatory effects of Traditional Chinese Medicine (TCM) on these pathways in GC, grounded in TCM principles such as Qi deficiency, Damp-Heat, and disharmony of the Spleen and Stomach. Single herbal monomers (e.g., curcumin, berberine, resveratrol) inhibit PI3K/Akt/mTOR by upregulating PTEN and suppressing mTOR, inducing autophagy and apoptosis. Classical herbs like Huangqin and Huanglian modulate Akt and ERK phosphorylation, while compound formulas (e.g., Banxia Xiexin Decoction, Sijunzi Decoction) synergistically target both pathways, reversing EMT and chemoresistance. TCM addresses crosstalk by disrupting feedback loops and reducing inflammation, enhancing efficacy in combination with Western therapies like chemotherapy and immunotherapy. Network pharmacology and multi-omics analyses reveal TCM's multitarget mechanisms, aligning with ZHENG-based personalization. Challenges include research variability, standardization issues, and incomplete mechanistic validation. Future directions emphasize high-quality trials, omics integration, and precision TCM for clinical translation. TCM offers low-toxicity, holistic options for integrative GC management, potentially improving survival and quality of life.

PMID:41825157 | DOI:10.1016/j.tice.2026.103409

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