Search Results (131)

Pancreatic cancer is frequently accompanied by cancer-associated cachexia, a debilitating metabolic syndrome marked by progressive skeletal muscle wasting and systemic metabolic dysfunction. This study presents a systems biology framework to simultaneously identify therapeutic targets for both pancreatic ductal adenocarcinoma (PDAC) and its associated cachexia (PDAC-CX), using cell-specific genome-scale metabolic models (GSMMs). The human metabolic network Recon3D was extended to include protein synthesis, degradation, and recycling pathways for key inflammatory and structural proteins. These enhancements enabled the reconstruction of cell-specific GSMMs for PDAC and PDAC-CX, and their respective healthy counterparts, based on transcriptomic datasets. Medium-independent metabolic biomarkers were identified through Parsimonious Metabolite Flow Variability Analysis and differential expression analysis across five nutritional conditions. A fuzzy multi-objective optimization framework was employed within the anticancer target discovery platform to evaluate cell viability and metabolic deviation as dual criteria for assessing therapeutic efficacy and potential side effects. While single-enzyme targets were found to be context-specific and medium-dependent, eight combinatorial targets demonstrated robust, medium-independent effects in both PDAC and PDAC-CX cells. These include the knockout of SLC29A2, SGMS1, CRLS1, and the RNF20–RNF40 complex, alongside upregulation of CERK and PIKFYVE. The proposed integrative strategy offers novel therapeutic avenues that address both tumor progression and cancer-associated cachexia, with improved specificity and reduced off-target effects, thereby contributing to translational oncology. Full article

Cordycepin, a bioactive adenosine analog, holds promise in pharmaceutical and health product development. However, large-scale production remains constrained by the limitations of natural producers, Cordyceps spp. Herein, we report the reconstruction of the first genome-scale metabolic model (GSMM) for a cordycepin-producing strain of recombinant Aspergillus oryzae. The model, iNR1684, incorporated 1684 genes and 1947 reactions with 93% gene-protein-reaction coverage, which was validated by the experimental biomass composition and growth rate. In silico analyses identified key gene amplification targets in the pentose phosphate and one-carbon metabolism pathways, indicating that folate metabolism is crucial for enhancing cordycepin production. Nutrient optimization simulations revealed that chitosan, D-glucosamine, and L-aspartate preferentially supported cordycepin biosynthesis. Additionally, a carbon-to-nitrogen ratio of 11.6:1 was identified and experimentally validated to maximize production, higher than that reported for Cordyceps militaris. These findings correspond to a faster growth rate, enhanced carbon assimilation, and broader substrate utilization by A. oryzae. This study demonstrates the significant role of GSMM in uncovering rational engineering strategies and provides a quantitative framework for precision fermentation, offering scalable and sustainable solutions for industrial cordycepin production. Full article

As an important class of microorganisms, filamentous fungi have crucial roles in protein secretion, secondary metabolite production and environmental pollution control. However, characteristics such as apical growth, heterokaryon, low homologous recombination (HR) efficiency and the scarcity of genetic markers mean that the application of traditional gene editing technology in filamentous fungi faces great challenges. The introduction of the RNA-mediated CRISPR/Cas (clustered regularly interspaced short palindromic repeat/CRlSPR-associated protein) system in filamentous fungi in recent years has revolutionized gene editing in filamentous fungi. In addition, the continuously expressed CRISPR system has significantly improved the editing efficiency, while the optimized sgRNA design and reduced cas9 concentration have effectively reduced the off-target effect, further enhancing the safety and reliability of the technology. In this review, we systematically analyze the molecular mechanism and regulatory factors of CRISPR/Cas9, focus on the optimization of its expression system and the improvement of the transformation efficiency in filamentous fungi, and reveal the core regulatory roles of HR and non-homologous end-joining (NHEJ) pathways in gene editing. Based on the analysis of various filamentous fungi applications, this review reveals the outstanding advantages of CRISPR/Cas9 in the enhancement of protein secretion, addresses the reconstruction of secondary metabolic pathways and pollutant degradation in the past decade, and provides a theoretical basis and practical guidance for the optimization of the technology and engineering applications. Full article

Metagenome-assembled genomes (MAGs) have revolutionized microbial ecology by enabling the genome-resolved study of uncultured microorganisms directly from environmental samples. By leveraging high-throughput sequencing, advanced assembly algorithms, and genome binning techniques, researchers can reconstruct microbial genomes without the need for cultivation. These methodological advances have expanded the known microbial diversity, revealing novel taxa and metabolic pathways involved in key biogeochemical cycles, including carbon, nitrogen, and sulfur transformations. MAG-based studies have identified microbial lineages form Archaea and Bacteria responsible for methane oxidation, carbon sequestration in marine sediments, ammonia oxidation, and sulfur metabolism, highlighting their critical roles in ecosystem stability. From a sustainability perspective, MAGs provide essential insights for climate change mitigation, sustainable agriculture, and bioremediation. The ability to characterize microbial communities in diverse environments, including soil, aquatic ecosystems, and extreme habitats, enhances biodiversity conservation and supports the development of microbial-based environmental management strategies. Despite these advancements, challenges such as assembly biases, incomplete metabolic reconstructions, and taxonomic uncertainties persist. Continued improvements in sequencing technologies, hybrid assembly approaches, and multi-omics integration will further refine MAG-based analyses. As methodologies advance, MAGs will remain a cornerstone for understanding microbial contributions to global biogeochemical processes and developing sustainable interventions for environmental resilience. Full article

Background/Objectives: Bone metastasis is a frequent and life-threatening event in advanced cancers, affecting up to 70–85% of prostate cancer patients. Understanding the cellular and molecular mechanisms underlying bone metastasis is essential for developing targeted therapies. This study aimed to systematically characterize the heterogeneity and microenvironmental adaptation of prostate cancer bone metastases using single-cell transcriptomics. Methods: We integrated the largest single-cell transcriptome dataset to date, encompassing 124 samples from primary prostate tumors, various bone metastatic sites, and non-malignant tissues (e.g., benign prostatic hyperplasia, normal bone marrow). After quality control, 602,497 high-quality single-cell transcriptomes were analyzed. We employed unsupervised clustering, gene expression profiling, mutation analysis, and metabolic pathway reconstruction to characterize cancer cell subtypes and tumor microenvironmental remodeling. Results: Cancer epithelial cells dominated the tumor microenvironment but exhibited pronounced heterogeneity, posing challenges for conventional clustering methods. By integrating genetic and metabolic features, we revealed key evolutionary trajectories of epithelial cancer cells during metastasis. Notably, we identified a novel epithelial subpopulation, NEndoCs, characterized by unique differentiation patterns and distinct spatial distribution across metastatic niches. We also observed significant metabolic reprogramming and recurrent mutations linked to prostate-to-bone microenvironmental transitions. Conclusions: This study comprehensively elucidates the mutation patterns, metabolic reprogramming, and microenvironment adaptation mechanisms of bone metastasis in prostate cancer, providing key molecular targets and clinical strategies for the precise treatment of bone metastatic prostate cancer. Full article

Background: Burn injuries constitute a significant global health challenge, especially in pediatric populations, where they are a leading cause of morbidity and mortality. Pediatric burns require particular attention due to their unique pathophysiology, long-term consequences on growth and development, and psychological impacts. Methods: We propose a comprehensive review of recent advancements in understanding the key aspects of hormonal and metabolic changes in burned children, aiming to guide therapeutic interventions, improve outcomes, and reduce the global burden of these injuries. Results: Effective management of the physiological stress response in pediatric burn patients necessitates a multidisciplinary approach integrating medical, nutritional, and rehabilitative strategies. Timely nutritional support and individualized plans preserve muscle mass, promote wound healing, and reduce complications and organ dysfunction risk. Advances in pharmacological interventions, such as beta-blockers, anabolic agents, and hormonal treatment, offer promising pathways to improve recovery and mitigate long-term complications. Early mobilization and physiotherapy are essential for preventing complications of prolonged immobility, including muscle wasting, joint contractures, and functional decline; their effectiveness is closely tied to advancements in minimally invasive procedures, regenerative medicine, and reconstructive techniques, particularly for pediatric patients. Conclusions: While current strategies have significantly improved survival and outcomes for pediatric burn patients, ongoing research is critical to refine these new care strategies. Full article

Microbial communities in wastewater treatment plants (WWTPs) play a crucial role in the decontamination of polluted water. An uncultured order-level lineage AKYH767 of the phylum Bacteroidota has been consistently detected in microbial consortia of activated sludge at WWTPs worldwide, but its functional role remains elusive. Representatives of AKYH767 were also detected in soils and freshwater bodies, which may be their natural reservoirs. Here, we obtained ten high-quality metagenome-assembled genomes, including one closed circular genome, of AKYH767 bacteria from metagenomes of the wastewater and activated sludge and used genomic data to uncover the metabolic potential of these bacteria and to predict their functional role. The cells of the AKYH767 bacteria were inferred to be rod-shaped and non-motile. Genome-based metabolic reconstruction predicted the Embden–Meyerhof pathway, the non-oxidative stage of the pentose phosphate pathway, and the complete tricarboxylic acid cycle. A facultatively anaerobic chemoheterotrophic lifestyle with the capacity to oxidize low organic substrates through aerobic respiration was suggested. Under anaerobic conditions AKYH767 bacteria can perform different steps of denitrification. They have limited capacities to hydrolyze carbohydrates and proteinaceous substrates but can utilize fatty acids. A peculiar property of AKYH767 bacteria is the presence of the phenylacetyl-CoA pathway for the utilization of phenylacetate, and about half of the genomes encoded the benzoate degradation pathway. Apparently, in bioreactors at WWTPs, the AKYH767 bacteria could be involved in the denitrification and biodegradation of aromatic compounds. Based on phylogenetic and genomic analyses, the novel AKYH767 bacterium is proposed to be classified as Candidatus Pollutiaquabacter aromativorans, within the candidate order Pollutiaquabacterales. Full article

Background/objectives: Amino acids (AAs) play a critical role in diseases such as cystic fibrosis where Pseudomonas aeruginosa PAO1 adapts its metabolism in response to host-derived nutrients. The adaptation influences virulence and complicates antibiotic treatment mainly for the antimicrobial resistance context. D- and L-AAs have been analyzed for their impact on quorum sensing (QS), a mechanism that regulates virulence factors. This research aimed to reconstruct the genome-scale metabolic model (GEM) of P. aeruginosa PAO1 to investigate the metabolic roles of D- and L-AAs in QS-related pathways. Methods: The updated GEM, iJD1249, was reconstructed by using protocols to integrate data from previous models and refined with well-standardized in silico media (LB, M9, and SCFM) to improve flux balance analysis accuracy. The model was used to explore the metabolic impact of D-Met, D-Ala, D-Glu, D-Ser, L-His, L-Glu, L-Arg, and L-Ornithine (L-Orn) at 5 and 50 mM in QS-related pathways, focusing on the effects on bacterial growth and carbon flux distributions. Results: Among the tested AAs, D-Met was the only one that did not enhance the growth rate of P. aeruginosa PAO1, while L-Arg and L-Orn increased fluxes in the L-methionine biosynthesis pathway, influencing the metH gene. These findings suggest a differential metabolic role for D-and L-AAs in QS-related pathways. Conclusions: Our results shed some light on the metabolic impact of AAs on QS-related pathways and their potential role in P. aeruginosa virulence. Future studies should assess D-Met as a potential adjuvant in antimicrobial strategies, optimizing the concentration in combination with antibiotics to maximize its therapeutic effectiveness. Full article

The syndrome “bassess richesses” is a vector-borne disease of sugar beet in Germany. The gammaproteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ causes reduced sugar content and biomass, growth abnormalities, and yellowing. Co-infection with the 16SrXII-P stolbur phytoplasmas often leads to more severe symptoms and a risk of complete economic loss. This yellowing agent of the Mollicutes class had not been described before, so its differences from other stolbur phytoplasmas remained unanswered. The genome of strain GOE was sequenced, providing a resource to analyze its characteristics. Phylogenetic position was revised, genome organization was compared, and functional reconstructions of metabolic and virulence factors were performed. Average nucleotide identity analysis indicates that GOE represents a new ‘Ca. Phytoplasma’ species. Our results show that GOE is also distinct from other stolbur phytoplasmas in terms of smaller genome size and G+C content. Its reductive evolution is reflected in conserved membrane protein repertoire and minimal metabolism. The encoding of a riboflavin kinase indicates a lost pathway of phytoplasmas outside the groups 16SrXII and 16SrXIII. GOE shows a complete tra5 transposon harboring orthologs of SAP11, SAP54, and SAP05 effectors indicating an original phytoplasma pathogenicity island. Our results deepen the understanding of phytoplasma evolution and reaffirm the heterogeneity of stolbur phytoplasmas. Full article

Amasi, a traditional fermented milk produced in Southern Africa, is associated with several health benefits, such as probiotic activities, immune system modulation, and pharmacological (antimicrobial, antitumor and antioxidant) potential. This study investigated the microbial diversity in Amasi (produced from cow’s and goat’s milk) through targeted metagenomic bacterial 16S rRNA and fungal ITS sequencing, the metabolic functional prediction of Amasi samples using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) and profiled amino acids constituents using Liquid Chromatographic-Mass Spectrophotometry (LC-MS). The results obtained revealed Firmicutes, Bacteroidetes, and Proteobacteria as the most prevalent bacterial phyla, with Lactococcus and Lactobacillus being the most abundant genera. On the other hand, Ascomycota, Basidiomycota, and Mucoromycota were the main fungal phyla, while Aspergillus, Kazachstania, and Debaryomyces spp. dominated the fungal genera. Also, Pseudomonas spp., Bacillus spp., Clostridium spp., Cronobacter spp., Alternaria spp., Diaporthe spp., and Penicillium spp. were the probable pathogenic bacteria and fungi genera found, respectively. Atopobium, Synechococcus, and Parabacteroides were found less often as rare genera. It was found that the amino acid and drug metabolism pathway prediction values in Amasi samples were significantly higher (p < 0.05) than in raw cow and goat milk, according to the inferred analysis (PICRUSt). The amino acid validation revealed glutamine and asparagine values as the most significant (p < 0.05) for Amasi cow milk (ACM) and Amasi goat milk (AGM), respectively. Comparatively, ACM showed more microbial diversity than AGM, though there were relative similarities in their microbiome composition. PICRUSt analysis revealed significant metabolites in the two Amasi samples. Overall, data from this study showed heterogeneity in microbial diversity, abundance distributions, metabolites, and amino acid balance between raw cow/goat milk and Amasi samples. Full article

Host genetics and environmental factors have been associated with effects on the mouse fecal microbiome; however, the commercial source of mice remains the dominant factor. Increasing evidence indicates that supplier-specific microbiomes confer differences in disease susceptibility in models of inflammatory conditions, as well as baseline behavior and body morphology. However, current knowledge regarding the compositional differences between suppliers is based on targeted-amplicon sequencing data, and functional differences between these communities remain poorly defined. We applied a multi-omic (metagenomic and metatranscriptomic) approach to biomolecules extracted from murine feces representative of two U.S. suppliers of research mice, which differ in composition, and influence baseline physiology and behavior as well as disease severity in models of intestinal disease. We reconstructed high-quality metagenome-assembled genomes, frequently containing genomic content unique to each supplier. Transcriptional activity and pathway analyses revealed key functional differences between the metagenomes associated with each supplier including carbohydrate, fatty acid, and sulfite metabolism. These data provide a detailed characterization of the baseline differences in the fecal metagenome of mice from two U.S. commercial suppliers, suggesting that these functional differences are influenced by differences in the initial inoculum of colony founders, as well as additional taxa gained during growth of the production colony. Full article

Despite considerable investigative efforts, the molecular mechanisms of postoperative delirium (POD) remain unresolved. The present investigation employs innovative methodologies for identifying potential primary and secondary metabolic markers of POD by analyzing serum metabolomic profiles utilizing the genetic algorithm and artificial neural networks. The primary metabolomic markers constitute a combination of metabolites that optimally distinguish between POD and non-POD groups of patients. Our analysis revealed L-lactic acid, inositol, and methylcysteine as the most salient primary markers upon which the prediction accuracy of POD manifestation achieved AUC = 99%. The secondary metabolomic markers represent metabolites that exhibit perturbed correlational patterns within the POD group. We identified 54 metabolites as the secondary markers of POD, incorporating neurotransmitters such as gamma-aminobutyric acid (GABA) and serotonin. These findings imply a systemic disruption in metabolic processes in patients with POD. The deployment of gene network reconstruction techniques facilitated the postulation of hypotheses describing the role of established genomic POD markers in the molecular-genetic mechanisms of metabolic pathways dysregulation, and involving the identified primary and secondary metabolomic markers. This study not only expands the understanding of POD pathogenesis but also introduces a novel technology for the bioinformatic analysis of metabolomic data that could aid in uncovering potential primary and secondary markers in diverse research domains. Full article

Background: Altered patterns of bile acids (BAs) are frequently present in liver fibrosis, and BAs function as signaling molecules to initiate inflammatory responses. Silybin meglumine (SLB-M) is widely used in treating various liver diseases including liver fibrosis. However, research on its effects on bile acid (BA) metabolism is limited. This study investigated the therapeutic effects of SLB-M on liver fibrosis and BA metabolism in a CCl₄-induced murine model. Methods: A murine liver fibrosis model was induced by CCl4. Fibrosis was evaluated using HE, picrosirius red, and Masson’s trichrome staining. Liver function was assessed by serum and hepatic biochemical markers. Bile acid (BA) metabolism was analyzed using LC-MS/MS. Bioinformatics analyses, including PPI network, GO, and KEGG pathway analyses, were employed to explore molecular mechanisms. Gene expression alterations in liver tissue were examined via qRT-PCR. Results: SLB-M treatment resulted in significant histological improvements in liver tissue, reducing collagen deposition and restoring liver architecture. Biochemically, SLB-M not only normalized serum liver enzyme levels (ALT, AST, TBA, and GGT) but also mitigated disruptions in both systemic and hepatic BA metabolism by increased unconjugated BAs like cholic acid and chenodeoxycholic acid but decreased conjugated BAs including taurocholic acid and taurodeoxycholic acid, compared to that in CCl₄-induced murine model. Notably, SLB-M efficiently improved the imbalance of BA homeostasis in liver caused by CCl₄ via activating Farnesoid X receptor. Conclusions: These findings underscore SLB-M decreased inflammatory response, reconstructed BA homeostasis possibly by regulating key pathways, and gene expressions in BA metabolism. Full article

Tomato is an economically and nutritionally important crop and is vulnerable to drought. Under drought, soil microbes provide beneficial effects to plants and alleviate stress. We suggest a reconstruction of the soil microbiome using biofumigation, an organic farming method, to protect tomatoes. In this study, we treated soil in four ways with varied concentrations: biofumigation (BF0.5, BF1.0, and BF1.5), green manure treatment (GM0.5, GM1.0, and GM1.5), autoclaving (AT), and non-treatment (NT). Tomatoes were grown in each treated soil, subjected to water shortages, and were rewatered. We investigated plant phenotypes and soil properties, focused on microbial communities using the Illumina MiSeq^® System. Relative Water Content and malondialdehyde were measured as plant stress. The results showed that the 1% biofumigation treatment had 105% and 108.8% RWC during drought and after rewatering, compared to the non-treated soil. The highest concentration, the 1.5% treatment, lowered RWC due to an excess of NO₃⁻, K⁺, Ca²⁺, and decreased alpha diversity. Through PLS-PM, bacterial alpha diversity was found to be the largest factor in the increase in RWC (coefficient = 0.3397), and both biofumigant and green manure significantly increased the Shannon index and observed species. In addition, biofumigation increased beneficial functional genes (purine metabolism, pyrimidine metabolism, carbon fixation pathways, and zeatin bio-synthesis) of soil microorganisms (p value < 0.05, <0.01, >0.05, and <0.05, respectively). The 1% biofumigation treatment enriched the core five genera of the fungal network (Enterocarpus, Aspergillus, Leucothecium, Peniophora, and Wallemia) of the fungal network which might suppress the most dominant pathogen, Plectosphaerella. In conclusion, biofumigation-derived soil microbiome alterations have the potential to lower plant stress under drought. Full article

Sandalwood essential oil is extracted from the heartwood part of mature sandalwood and is known for its pleasant fragrance and exceptional medicinal activities, including antimicrobial, antitumor, and anti-inflammatory properties. The (Z)-α-santalol and (Z)-β-santalol are the most vital ingredients contributing to sandalwood oil’s bioactivities and unique woody odor characteristics. Metabolic engineering strategies have shown promise in transforming microorganisms such as yeast and bacteria into effective cell factories for enhancing the production of vital sesquiterpenes (santalene and santalol) found in sandalwood oil. This review aims to summarize sources of sandalwood oil, its components/ingredients, and its applications. It also highlights the biosynthesis of santalene and santalol and the various metabolic engineering strategies employed to reconstruct and enhance santalene and santalol biosynthesis pathways in heterologous hosts. Full article