Exploration of Core Genes in ACTH-Independent Macronodular Adrenal Hyperplasia

Abstract

This study explores the core genes involved in the pathogenesis of ACTH-independent macronodular adrenal hyperplasia (AIMAH), so as to provide robust biomarkers for the clinical diagnosis and treatment of this disease. Gene Expression Omnibus (GEO) database was used to obtain GSE25031 microarray dataset. R package “limma” was applied to identify differentially expressed genes (DEGs) between AIMAH and normal samples. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to perform Gene Ontology (GO) annotation for the DEGs, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted. A protein-protein interaction network (PPI) was constructed using the STRING online website and visualized using the Cytoscape software. The key modules and hub genes were then identified. Finally, Gene Set Enrichment Analysis (GESA) enrichment analysis was carried out to find the signaling pathways of significant clinical value in AIMAH. A total of 295 DEGs between AIMAH and healthy samples were screened out, including 164 upregulated genes and 131 downregulated genes. Combining enrichment analysis and PPI network construction, there were 5 signifiant pathways and 10 hub genes, among which 3 genes (FOS, FOSB, and DUSP1) were identified as potential core genes of clinical significance in AIMAH. In conclusion, the 3 core genes, FOS, FOSB, and DUSP1, identified here might be potential biomarkers for AIMAH, and the current study is of guiding significance for clinical diagnosis and treatment of this disease.

Co‐Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction

“…We also improved the method compatibility and validated the analytical capability in a threestrain non-linear synthetic consortium for the synthesis of rosmarinic acid. [10] CulECpy accurately predicted the optimal initial inoculation ratio CA:SAA:RA for each module to be 2:3:1, which is consistent with literature results.…”

“…Various synthetic consortia, such as salidroside, [ 8 ] or cadaverine, [ 11 ] synthesis system, were selected to verify the accuracy of the method. CulECpy successfully predicted the initial inoculation ratios of modular co‐culture systems such as two‐strain linear co‐culture systems ( E.coli & E.coli , E.coli & C. glutamicum) , [ 12 ] two‐strain complex crossover co‐culture systems [ 8 ] and three‐strain non‐linear co‐culture systems [ 10 ] to reach the metabolic equilibrium state. The root mean square error of maximum theoretical yield predicted by SCMs was less than or equal to 0.25.…”

“…Researchers need to consider not only the genetic modification of individual strains, but also explore the selection of optimal strains, complex interactions between strains, and optimal allocation of synthetic pathways for synthetic consortia. [8][9][10][11] To meet these challenges, our construction methods need to be adapted to the desired chassis and meet the need for rapid modeling. We propose a novel method called CulECpy.…”

“…To validate the effectiveness of this method for more complex systems, we carried out simulations using a reference three-strain non-linear pathway biosynthesis system for the production of rosmarinic acid (RA). [10] ("predicted" refers to data predicted by the model and "measured" refers to wet experimental data from the literature.) a) Biosynthesis of the modular metabolic pathway of rosmarinic acid by two-strain co-cultures.…”

“…Synthetic consortia have been constructed and applied to the biosynthesis of various biochemicals, all with improved synthetic yields compared to monoculture systems. [8][9][10][11][12] However, when employing synthetic consortia for biosynthesis, researchers must thoroughly investigate the impact of various complex conditions on the yield of the target product. This involves the exploration of how the intricate synthetic pathways within each module can be strategically allocated to achieve the highest possible synthetic efficiency in the co-culture system, which cannot be achieved by existing modeling methods.…”