BACKGROUND: Camellia nitidissima is a rare, prized camellia species with golden-yellow flowers. It has a high ornamental, medicinal, and economic value. Previous studies have shown substantial flavonol accumulation in C. nitidissima petals during flower formation. However, the mechanisms underlying the golden flower formation in C. nitidissima remain largely unknown.
RESULTS: We performed an integrative analysis of the transcriptome, proteome, and metabolome of the petals at five flower developmental stages to construct the regulatory network underlying golden flower formation in C. nitidissima. Metabolome analysis revealed the presence of 323 flavonoids, and two flavonols, quercetin glycosides and kaempferol glycosides, were highly accumulated in the golden petals. Transcriptome and proteome sequencing suggested that the flavonol biosynthesis-related genes and proteins upregulated and the anthocyanin and proanthocyanidin biosynthesis-related genes and proteins downregulated in the golden petal stage. Further investigation revealed the involvement of MYBs and bHLHs in flavonoid biosynthesis. Expression analysis showed that flavonol synthase 2 (CnFLS2) was highly expressed in the petals, and its expression positively correlated with flavonol content at all flower developmental stages. Transient overexpression of CnFLS2 in the petals increased flavonol content. Furthermore, correlation analysis showed that the jasmonate (JA) pathways positively correlated with flavonol biosynthesis, and exogenous methyl jasmonate (MeJA) treatment promoted CnFLS2 expression and flavonol accumulation.
CONCLUSIONS: Our findings showed that the JA-CnFLS2 module regulates flavonol biosynthesis during golden petal formation in C. nitidissima.

Objective: This study aims to investigate how changes in peripheral blood metabolites in Alzheimer\'s Disease (AD) patients affect the development of Pelvic Organ Prolapse (POP) using a multi-omics approach. We specifically explore the interactions of signaling pathways, gene expression, and protein-metabolite interactions, with a focus on GZMA and cysteine in age-related diseases. Methods: This study utilized multi-omics analysis, including metabolomics and transcriptomics, to evaluate the perturbations in peripheral blood metabolites and their effect on POP in AD patients. Additionally, a comprehensive pan-cancer and immune infiltration analysis was performed on the core targets of AD combined with POP, exploring their potential roles in tumor progression and elucidating their pharmacological relevance to solid tumors. Results: We identified 47 differential metabolites linked to 9 significant signaling pathways, such as unsaturated fatty acid biosynthesis and amino acid metabolism. A thorough gene expression analysis revealed numerous differentially expressed genes (DEGs), with Gene Set Enrichment Analysis (GSEA) showing significant changes in gene profiles of AD and POP. Network topology analysis highlighted central nodes in the AD-POP co-expressed genes network. Functional analyses indicated involvement in critical biological processes and pathways. Molecular docking studies showed strong interactions between cysteine and proteins PTGS2 and GZMA, and molecular dynamics simulations confirmed the stability of these complexes. In vitro validation demonstrated that cysteine reduced ROS levels and protected cell viability. GZMA was widely expressed in various cancers, associated with immune cells, and correlated with patient survival prognosis. Conclusion: Multi-omics analysis revealed the role of peripheral blood metabolites in the molecular dynamics of AD and their interactions with POP. This study identified potential biomarkers and therapeutic targets, emphasizing the effectiveness of integrative approaches in treating AD and POP concurrently. The findings highlight the need for in-depth research on novel targets and biomarkers to advance therapeutic strategies.

BACKGROUND: The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days.
METHODS: Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets.
RESULTS: Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options.
CONCLUSIONS: We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.

Metabolic exchange plays a crucial role in shaping microbial community interactions and functions, including the exchange of small molecules such as cofactors. Cofactors are fundamental to enzyme catalytic activities; however, the role of cofactors in microbial stress tolerance is unclear. Here, we constructed a synergistic consortium containing two strains that could efficiently mineralize di-(2-ethylhexyl) phthalate under hyperosmotic stress. Integration of transcriptomic analysis, metabolic profiling, and a genome-scale metabolic model (GEM) facilitated the discovery of the potential mechanism of microbial interactions. Multi-omics analysis revealed that the vitamin B12-dependent methionine-folate cycle could be a key pathway for enhancing the hyperosmotic stress tolerance of synergistic consortium. Further GEM simulations revealed interspecies exchange of S-adenosyl-L-methionine and riboflavin, cofactors needed for vitamin B12 biosynthesis, which was confirmed by in vitro experiments. Overall, we proposed a new mechanism of bacterial hyperosmotic stress tolerance: bacteria might promote the production of vitamin B12 to enhance biofilm formation, and the species collaborate with each other by exchanging cofactors to improve consortium hyperosmotic stress tolerance. These findings offer new insights into the role of cofactors in microbial interactions and stress tolerance and are potentially exploitable for environmental remediation.
OBJECTIVE: Metabolic interactions (also known as cross-feeding) are thought to be ubiquitous in microbial communities. Cross-feeding is the basis for many positive interactions (e.g., mutualism) and is a primary driver of microbial community assembly. In this study, a combination of multi-omics analysis and metabolic modeling simulation was used to reveal the metabolic interactions of a synthetic consortium under hyperosmotic stress. Interspecies cofactor exchange was found to promote biofilm formation under hyperosmotic stress. This provides a new perspective for understanding the role of metabolic interactions in microbial communities to enhance environmental adaptation, which is significant for improving the efficiency of production activities and environmental bioremediation.

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

BACKGROUND: The rapid acceleration of female reproductive aging has become a major public health concern. He\'s Yangchao formula (HSYC), a compound comprising eight herbs, has demonstrated efficacy in enhancing ovarian function. Thus, an in-depth study of its anti-ovarian aging mechanism is required.
OBJECTIVE: To evaluate the anti-ovarian aging effect of HSYC in naturally aged mice and investigate the underlying mechanism by analyzing the gut microbiota (GM), metabolome, and transcriptome.
METHODS: Young and advanced maternal age (AMA) mice were selected for this study. Hematoxylin and eosin staining, fluorescence staining, western blotting, and qPCR analyses were used to detect the phenotypes associated with ovarian aging. Subsequently, analyses of the GM, transcriptome, and metabolome analyses were performed to explore the potential mechanisms of action of HSYC. Finally, in vivo and in vitro experiments were performed to verify potential therapeutic mechanisms.
RESULTS: HSYC promoted follicular development in AMA mice and ameliorated age-related mitochondrial dysfunction, apoptosis, and defects in DNA damage repair. GM analysis revealed that HSYC treatment significantly increased the abundance of Akkermansia and Turicibacter. Transcriptome and metabolome analyses showed that HSYC might mitigate ovarian aging by regulating metabolic pathways, amino acid metabolism, glutathione metabolism, and the synthesis of pantothenic acid and coenzyme A. Combined transcriptomic and metabolomic analyses identified the glutathione metabolic pathway as the key pathway through which HSYC counteracts ovarian aging. Additional experimental verification confirmed that HSYC upregulated the glutathione metabolic genes GPX8, GSTA1, and GSTA4, increased glutathione-related products (GSH), and reduced ROS levels.
CONCLUSIONS: HSYC exerts beneficial therapeutic effects on ovarian aging by regulating multiple endogenous metabolites, targets, and metabolic pathways, with an emphasis on its anti-ovarian aging effects through the glutathione metabolic pathway. These findings underscore the innovative potential of HSYC in addressing ovarian aging and offer a novel therapeutic approach that targets multiple biological pathways to improve the reproductive health of women with AMA..

BACKGROUND: Streptococcus suis is an important zoonotic pathogen. Biofilm formation largely explains the difficulty in preventing and controlling S. suis. However, little is known about the molecular mechanism of S. suis biofilm formation.
RESULTS: In this study, transcriptomic and metabolomic analyses of S. suis in biofilm and planktonic states were performed to identify key genes and metabolites involved in biofilm formation. A total of 789 differential genes and 365 differential metabolites were identified. By integrating transcriptomics and metabolomics, five main metabolic pathways were identified, including amino acid pathway, nucleotide metabolism pathway, carbon metabolism pathway, vitamin and cofactor metabolism pathway, and aminoacyl-tRNA biosynthesis metabolic pathway.
CONCLUSIONS: These results provide new insights for exploring the molecular mechanism of S. suis biofilm formation.

The microbial communities residing in the mosquito midgut play a key role in determining the outcome of mosquito pathogen infection. Elizabethkingia anophelis, originally isolated from the midgut of Anopheles gambiae possess a broad-spectrum antiviral phenotype, yet a gap in knowledge regarding the mechanistic basis of its interaction with viruses exists. The current study aims to identify pathways and genetic factors linked to E. anophelis antiviral activity. The understanding of E. anophelis antiviral mechanism could lead to novel transmission barrier tools to prevent arboviral outbreaks. We utilized a non-targeted multi-omics approach, analyzing extracellular lipids, proteins, metabolites of culture supernatants coinfected with ZIKV and E. anophelis. We observed a significant decrease in arginine and phenylalanine levels, metabolites that are essential for viral replication and progression of viral infection. This study provides insights into the molecular basis of E. anophelis antiviral phenotype. The findings lay a foundation for in-depth mechanistic studies.

Functional and pathological recovery after spinal cord injury (SCI) is often incomplete due to the limited regenerative capacity of the central nervous system (CNS), which is further impaired by several mechanisms that sustain tissue damage. Among these, the chronic activation of immune cells can cause a persistent state of local CNS inflammation and damage. However, the mechanisms that sustain this persistent maladaptive immune response in SCI have not been fully clarified yet. In this study, we integrated histological analyses with proteomic, lipidomic, transcriptomic, and epitranscriptomic approaches to study the pathological and molecular alterations that develop in a mouse model of cervical spinal cord hemicontusion. We found significant pathological alterations of the lesion rim with myelin damage and axonal loss that persisted throughout the late chronic phase of SCI. This was coupled by a progressive lipid accumulation in myeloid cells, including resident microglia and infiltrating monocyte-derived macrophages. At tissue level, we found significant changes of proteins indicative of glycolytic, tricarboxylic acid cycle (TCA), and fatty acid metabolic pathways with an accumulation of triacylglycerides with C16:0 fatty acyl chains in chronic SCI. Following transcriptomic, proteomic, and epitranscriptomic studies identified an increase of cholesterol and m6A methylation in lipid-droplet-accumulating myeloid cells as a core feature of chronic SCI. By characterizing the multiple metabolic pathways altered in SCI, our work highlights a key role of lipid metabolism in the chronic response of the immune and central nervous system to damage.

Ubiquitination, a post-translational modification, refers to the covalent attachment of ubiquitin molecules to substrates. This modification plays a critical role in diverse cellular processes such as protein degradation. The specificity of ubiquitination for substrates is regulated by E3 ubiquitin ligases. Dysregulation of ubiquitination has been associated with numerous diseases, including cancers. In our study, we first investigated the protein expression patterns of E3 ligases across 12 cancer types. Our findings indicated that E3 ligases tend to be up-regulated and exhibit reduced tissue specificity in tumors. Moreover, the correlation of protein expression between E3 ligases and substrates demonstrated significant changes in cancers, suggesting that E3-substrate specificity alters in tumors compared to normal tissues. By integrating transcriptome, proteome, and ubiquitylome data, we further characterized the E3-substrate regulatory patterns in lung squamous cell carcinoma. Our analysis revealed that the upregulation of the SKP2 E3 ligase leads to excessive degradation of BRCA2, potentially promoting tumor cell proliferation and metastasis. Furthermore, the upregulation of E3 ubiquitin-protein ligase TRIM33 was identified as a biomarker associated with a favorable prognosis by inhibiting the cell cycle. This work exemplifies how leveraging multi-omics data to analyze E3 ligases across various cancers can unveil prognosis biomarkers and facilitate the identification of potential drug targets for cancer therapy.