Summary The progression from chronic gastritis to gastric cancer is a complex and multistep process. Early detection of this transition is critical for improving patient survival; however, the underlying molecular mechanisms remain incompletely understood. Recent advances in multi-omics technologies have provided powerful tools for high-resolution characterization of disease-associated molecular alterations. In this review, we summarize studies investigating the gastritis-to-carcinoma sequence using genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analyses. Particular emphasis is placed on evidence from human cohorts, single-cell sequencing, and spatial transcriptomics, which have helped characterize cellular heterogeneity, immune microenvironment remodeling, and cell-cell interactions. We also discuss the role of the microbiome, particularly Helicobacter pylori, in disease progression. Integration of these multi-layered datasets can generate mechanistic hypotheses and candidate biomarkers, but most findings require independent validation before clinical implementation. Overall, multi-omics approaches provide valuable insights into gastric carcinogenesis while highlighting the need for cautious interpretation and translational validation.
Jiayin Ou, Jiaxin Lin, Yuyang Cao et al.· iScience· 0 citations
Carminic acid (CA) is a high-value natural anthraquinone pigment used in foods, cosmetics, textiles, and pharmaceuticals, but its current industrial supply depends largely on extraction from the scale insect Dactylopius coccus, creating constraints in yield, cost, sustainability, and allergen control. This review summarizes recent progress from pathway elucidation to microbial production. We first outline the structure, occurrence, applications, and biosynthetic logic of CA, emphasizing the convergence of type III polyketide assembly with insect-associated tailoring reactions, especially C-glycosylation. We then compare heterologous production strategies in Escherichia coli, Saccharomyces cerevisiae, Yarrowia lipolytica, and Aspergillus nidulans, focusing on chassis-specific advantages, bottlenecks, precursor supply, malonyl-CoA engineering, dynamic regulation, enzyme compatibility, compartmentalization, and downstream processing. Structurally related anthraquinone pigments are further discussed to extract broader design principles for pathway diversification and synthetic biology. Finally, we highlight key challenges for industrial translation, including low titers, incomplete enzyme characterization, host–pathway incompatibility, and scalable purification, and propose integrated strategies combining precursor-pathway rewiring, AI-assisted enzyme engineering, biosensor-based regulation, and process optimization to develop competitive microbial cell factories.
Hongyu Li, Jia-Qi Liu, Jia-Shan Lu et al.· Microorganisms· 0 citations
Natural products remain a major source of structurally diverse and biologically active small molecules, yet traditional activity-guided discovery is labor-intensive and prone to rediscovery, while untargeted genome mining often lacks efficient prioritization criteria for biosynthetic gene clusters (BGCs). Self-resistance-gene guided discovery has emerged as a powerful strategy to address this limitation. In producing organisms, toxic metabolites are typically accompanied by genetically encoded self-protection mechanisms, such as resistant target homologs, duplicated housekeeping genes, detoxification enzymes, repair systems, or transporters. When co-localized with BGCs, these determinants serve as functional markers for predicting bioactivity and, in some cases, molecular targets prior to compound isolation. Over the past decade, this concept has evolved into a target-directed genome mining framework supported by tools and databases including ARTS, FunARTS, antiSMASH, and MIBiG. This review summarizes the biological basis, workflow, representative advances, and limitations of this strategy. Self-resistance genes can thus be viewed as functional beacons for accelerating bioactive natural product discovery.
Jiaxin Wu, Meng-Xu Qiao, Ya-Yue Ma et al.· Microorganisms· 0 citations
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