Leptin-mediated suppression of lipoprotein lipase cleavage enhances lipid uptake and facilitates lymph node metastasis in gastric cancer.

BACKGROUND: Lymph node metastasis (LNM) is the primary mode of metastasis in gastric cancer (GC). However, the precise mechanisms underlying this process remain elusive. Tumor cells necessitate lipid metabolic reprogramming to facilitate metastasis, yet the role of lipoprotein lipase (LPL), a pivotal enzyme involved in exogenous lipid uptake, remains uncertain in tumor metastasis. Therefore, the aim of this study was to investigate the presence of lipid metabolic reprogramming during LNM of GC as well as the role of LPL in this process. METHODS: Intracellular lipid levels were quantified using oil red O staining, BODIPY 493/503 staining, and flow cytometry. Lipidomics analysis was employed to identify alterations in intracellular lipid composition following LPL knockdown. Protein expression levels were assessed through immunohistochemistry, Western blotting, and enzyme-linked immunosorbent assays. The mouse popliteal LNM model was utilized to investigate differences in LNM. Immunoprecipitation and mass spectrometry were employed to examine protein associations. In vitro phosphorylation assays and Phos-tag sodium dodecyl-sulfate polyacrylamide gel electrophoresis assays were conducted to detect angiopoietin-like protein 4 (ANGPTL4) phosphorylation. RESULTS: We identified that an elevated intracellular lipid level represents a crucial characteristic of node-positive (N+) GC and further demonstrated that a high-fat diet can expedite LNM. LPL was found to be significantly overexpressed in N+ GC tissues and shown to facilitate LNM by mediating dietary lipid uptake within GC cells. Leptin, an obesity-related hormone, intercepted the effect exerted by ANGPTL4/Furin on LPL cleavage. Circulating leptin binding to the leptin receptor could induce the activation of inositol-requiring enzyme-1 (IRE1) kinase, leading to the phosphorylation of ANGPTL4 at the serine 30 residue and subsequently reducing its binding affinity with LPL. Moreover, our research revealed that LPL disrupted lipid homeostasis by elevating intracellular levels of arachidonic acid, which then triggered the cyclooxygenase-2/prostaglandin E2 (PGE2) pathway, thereby promoting tumor lymphangiogenesis. CONCLUSIONS: Leptin-induced phosphorylation of ANGPTL4 facilitates LPL-mediated lipid uptake and consequently stimulates the production of PGE2, ultimately facilitating LNM in GC.

Structure-Assisted Boronic Acid Implanted Mesoporous Metal-Organic Frameworks for Specific Extraction of cis-Diol Molecules.

cis-Diol-containing molecules, an essential type of compounds in living organisms, have attracted intensive research interest from various fields. The analysis of cis-diol-containing molecules is still suffering from some drawbacks, including low abundance and abundant interference. Metal-organic frameworks (MOFs) have proven to be an ideal sorbent for sample preparation. However, most of the reported MOFs are mainly restricted to a microporous regime (pore size <2 nm), which greatly limits the application. Herein, a facile strategy is established to construction of boronate affinity MOFs via the postsynthetic ligand-exchange process. Owing to the fact that the ligand-exchange process was assisted by the structural integrity of the primitive metal-organic framework and the great compatibility of click chemistry, the obtained EPBA-PCN-333(Fe) is able to realize the maximum maintaining the porosity and crystallinity of the parent material. Several intriguing features of EPBA-PCN-333(Fe) (e.g., excellent selectivity, efficient diffusion, good accessibility, and size exclusion effect) are experimentally demonstrated via a series of cis-diol-containing molecules with different molecular sizes (small molecules, glycopeptides, and glycoproteins). The binding performance of EPBA-PCN-333(Fe) is evaluated by employing catechol as the test molecule (binding capacity: 0.25 mmol/g, LOD: 200 ng/mL). Finally, the real-world applications of EPBA-PCN-333(Fe) were demonstrated by the detection of nucleosides of human urine samples.

Polymorphism rs2327430 in TCF21 predicts the risk and prognosis of gastric cancer by affecting the binding between TFAP2A and TCF21.

BACKGROUND: Single nuclear polymorphisms (SNPs) have been published to be correlated with multiple diseases. Transcription Factor 21 (TCF21) is a critical transcription factor involved in various types of cancers. However, the association of TCF21 genetic polymorphisms with gastric cancer (GC) susceptibility and prognosis remains unclear. METHODS: A case-control study comprising 890 patients diagnosed with GC and an equal number of cancer-free controls was conducted. After rigorous statistical analysis, molecular experiments were carried out to elucidate the functional significance of the SNPs in the context of GC. RESULTS: TCF21 rs2327430 (OR = 0.78, P = 0.026) provides protection against GC, while rs4896011 (OR = 1.39, P = 0.005) exhibit significant associations with GC risk. Furthermore, patients with the (TC + CC) genotype of rs2327430 demonstrate a relatively favorable prognosis (OR = 0.47, P = 0.012). Mechanistically, chromatin immunoprecipitation assay and luciferase reporter assay revealed that the C allele of rs2327430 disrupts the binding of Transcription Factor AP-2 Alpha (TFAP2A) to the promoter region of TCF21, resulting in increased expression of TCF21 and inhibition of malignant behaviors in GC cells. CONCLUSION: Our findings highlight the significant role of TCF21 SNPs in both the risk and prognosis of GC and provide valuable insights into the underlying molecular mechanisms. Specifically, the disruptive effect of rs2327430 on TCF21 expression and its ability to modulate malignant cell behaviors suggest that rs2327430 may serve as a potential predictive marker for GC risk and prognosis.

Construction of an enzyme-constrained metabolic network model for Myceliophthora thermophila using machine learning-based kcat data.

BACKGROUND: Genome-scale metabolic models (GEMs) serve as effective tools for understanding cellular phenotypes and predicting engineering targets in the development of industrial strain. Enzyme-constrained genome-scale metabolic models (ecGEMs) have emerged as a valuable advancement, providing more accurate predictions and unveiling new engineering targets compared to models lacking enzyme constraints. In 2022, a stoichiometric GEM, iDL1450, was reconstructed for the industrially significant fungus Myceliophthora thermophila. To enhance the GEM's performance, an ecGEM was developed for M. thermophila in this study. RESULTS: Initially, the model iDL1450 underwent refinement and updates, resulting in a new version named iYW1475. These updates included adjustments to biomass components, correction of gene-protein-reaction (GPR) rules, and a consensus on metabolites. Subsequently, the first ecGEM for M. thermophila was constructed using machine learning-based kcat data predicted by TurNuP within the ECMpy framework. During the construction, three versions of ecGEMs were developed based on three distinct kcat collection methods, namely AutoPACMEN, DLKcat and TurNuP. After comparison, the ecGEM constructed using TurNuP-predicted kcat values performed better in several aspects and was selected as the definitive version of ecGEM for M. thermophila (ecMTM). Comparing ecMTM to iYW1475, the solution space was reduced and the growth simulation results more closely resembled realistic cellular phenotypes. Metabolic adjustment simulated by ecMTM revealed a trade-off between biomass yield and enzyme usage efficiency at varying glucose uptake rates. Notably, hierarchical utilization of five carbon sources derived from plant biomass hydrolysis was accurately captured and explained by ecMTM. Furthermore, based on enzyme cost considerations, ecMTM successfully predicted reported targets for metabolic engineering modification and introduced some new potential targets for chemicals produced in M. thermophila. CONCLUSIONS: In this study, the incorporation of enzyme constraint to iYW1475 not only improved prediction accuracy but also broadened the model's applicability. This research demonstrates the effectiveness of integrating of machine learning-based kcat data in the construction of ecGEMs especially in situations where there is limited measured enzyme kinetic parameters for a specific organism.

Magnetic dendritic mesoporous silica nanoparticles based integrated platform for rapid and efficient analysis of saccharides.

BACKGROUND: As an essential compound in living organism, saccharides have attracted enormous attentions from scientists in various fields. Understanding the distribution of saccharides in various samples is of great scientific importance. However, the low signal response and lack of specific recognition technology of saccharides and the complex matrix of samples make the analysis of saccharides a very challenge task. Thus, the development of a simple and straightforward strategy for the analysis of saccharides would represent a great contribution to the field. RESULTS: In this study, by employing the sulfonyl functionalized magnetic dendritic mesoporous silica nanoparticles as the substrate, we develop an integrated platform for analysis of saccharides. The construction of the platform mainly relied on multi-functional boronic acid, which serves as separation and derivation ligands at the same time. In the general procedure, the boronic acid is first immobilized onto the surface of substrate, then the selective enrichment of saccharides can be realized via boronate affinity separation. Finally, by the rational choice of the solution, we are able to elute the labelled complex (boronic acid-saccharide) from the substrate, which can be direct subjected to HPLC-UV analysis. The reliable precision (<15 %), accuracy (80-100 %), reproducibility (<10 %), improved sensitivity (20x) and limited time-consuming (down to minutes) of the proposed platform are experimentally demonstrated. SIGNIFICANCE AND NOVELTY: The successful quantification of different saccharides (alditols, glucose) in real samples is achieved. The proposed strategy is not only straightforward and fast, but also avoid the requirement of special equipment. With these attractive features, we believe that this strategy will greatly prompt the analysis of saccharides in various samples (eg. food, pharmaceutics and biosamples).

Development of the thermophilic fungus Myceliophthora thermophila into glucoamylase hyperproduction system via the metabolic engineering using improved AsCas12a variants.

BACKGROUND: Glucoamylase is an important enzyme for starch saccharification in the food and biofuel industries and mainly produced from mesophilic fungi such as Aspergillus and Rhizopus species. Enzymes produced from thermophilic fungi can save the fermentation energy and reduce costs as compared to the fermentation system using mesophiles. Thermophilic fungus Myceliophthora thermophila is industrially deployed fungus to produce enzymes and biobased chemicals from biomass during optimal growth at 45 °C. This study aimed to construct the M. thermophila platform for glucoamylase hyper-production by broadening genomic targeting range of the AsCas12a variants, identifying key candidate genes and strain engineering. RESULTS: In this study, to increase the genome targeting range, we upgraded the CRISPR-Cas12a-mediated technique by engineering two AsCas12a variants carrying the mutations S542R/K607R and S542R/K548V/N552R. Using the engineered AsCas12a variants, we deleted identified key factors involved in the glucoamylase expression and secretion in M. thermophila, including Mtstk-12, Mtap3m, Mtdsc-1 and Mtsah-2. Deletion of four targets led to more than 1.87- and 1.85-fold higher levels of secretion and glucoamylases activity compared to wild-type strain MtWT. Transcript level of the major amylolytic genes showed significantly increased in deletion mutants. The glucoamylase hyper-production strain MtGM12 was generated from our previously strain MtYM6 via genetically engineering these targets Mtstk-12, Mtap3m, Mtdsc-1 and Mtsah-2 and overexpressing Mtamy1 and Mtpga3. Total secreted protein and activities of amylolytic enzymes in the MtGM12 were about 35.6-fold and 51.9‒55.5-fold higher than in MtWT. Transcriptional profiling analyses revealed that the amylolytic gene expression levels were significantly up-regulated in the MtGM12 than in MtWT. More interestingly, the MtGM12 showed predominantly short and highly bulging hyphae with proliferation of rough ER and abundant mitochondria, secretion vesicles and vacuoles when culturing on starch. CONCLUSIONS: Our results showed that these AsCas12a variants worked well for gene deletions in M. thermophila. We successfully constructed the glucoamylase hyper-production strain of M. thermophila by the rational redesigning and engineering the transcriptional regulatory and secretion pathway. This targeted engineering strategy will be very helpful to improve industrial fungal strains and promote the morphology engineering for enhanced enzyme production.

The rapid high-throughput screening of ω-transaminases via a colorimetric method using aliphatic α-diketones as amino acceptors.

ω-Transaminases (ω-TAs) are widely available for the production of chiral amines and unnatural amino acids. Herein, a rapid spectrophotometric method was developed for screening ω-TAs based on the colored products that can be generated from transamination reactions between aliphatic α-diketones and amino donors catalyzed by ω-TAs. The possible mechanism of the formation of the colored product was investigated according to LC-Q-TOF-MS analysis. Among seven diketones, 2,3-butanedione was selected as the most suitable amino acceptor for colorimetric screening of ω-TAs with high efficiency, high sensitivity, and low background interference. Meanwhile, the absorbance of the colored product generated by 2,3-butanedione catalyzed by ω-TAs in this method was linearly correlated with the results by HPLC analysis. This method was also confirmed to effectively screen ω-TA mutants with high activity towards isopropylamine.

A thermal adaptation landscape related to virulence in Mucor irregularis transcriptional profiles.

OBJECTIVES: Our study aimed to better understand the different thermal adaptation in Mucor irregularis (M. irregularis) strains under high temperature and the involved virulence-related genes, and to offer more appropriate explanation for the diverse pathogenicity of M. irregularis in human infections. METHODS: M. irregularis isolates were incubated at 30 and 35°C for Illumina HiSeq technology (RNA-seq), as well as the virulence difference detected through Galleria mellonella infection models. We verified their transcriptional profile with RT-PCR and analysed differentially expressed genes with GO and KEGG annotations. RESULTS: All 25 isolates formed the biggest colonies at 28°C and did not grow at 37°C, while were differently inhibited at 22 and 35°C. Six selected M. irregularis displayed virulence in sync with their growth condition at high temperature. From the outcomes of RNA-seq, a total of 1559 differentially expressed genes (FC ≥ 2, FDR < 0.05) were obtained, of which 1021 genes were upregulated, and 538 genes were downregulated. Cell wall structure genes related to Ras-like and GH16 proteins, influx-efflux pumps consist of transmembrane proteins as ABC and MFS proteins, and metabolic genes as DGKɛ and Hsfs, seem to be essential in thermal adaptation and virulence of M. irregularis. CONCLUSION: We found some common genes expressed at high temperature, while some others specifically related to M. irregularis isolates with different virulence and thermal adaptation. Further research of genes involved in the pathogenic process is needed for the development of potential targeted antifungal.

In Vitro activity of ravuconazole against Candida auris and vaginal candida isolates.

BACKGROUND: Ravuconazole is an extended-spectrum triazole agent that is efficient in vitro against Candida spp. and has been approved to work as an oral formulae for onychomycosis in Japan in 2018. However, nobody had determined the MIC of ravuconazole against the Candida auris, which is known as an emerging multidrug-resistant yeast. Meanwhile, rare is known of the in vitro activity of ravuconazole against vaginal Candida isolates. OBJECTIVES: To investigate the activity of ravuconazole against C. auris and vaginal Candida isolates of China and assess the feasibility of ravuconazole in the treatment of candidiasis caused by C. auris and other Candida spp. METHODS: We determined the in vitro activity of ravuconazole and 9 comparators against 15 C. auris isolates and determined the MIC of ravuconazole on 525 vaginal Candida isolates (Candida albicans, Candida tropicalis, Candida glabrata and Candida parapsilosis) from 9 provinces of China by Clinical and Laboratory Standards Institute (CLSI) methodology. RESULTS: The MICs of fluconazole and amphotericin B on C. auris were much higher than second-generation azoles and echinocandins. Ravuconazole was active against all the C. auris isolates and as effective as isavuconazole, posaconazole and echinocandins while showed a better antifungal activity than itraconazole, voriconazole to C. auris. For vaginal Candida isolates, the proportion of ravuconazole-resistant isolates is 0.19% (1/525). CONCLUSIONS: Ravuconazole was in good active against C. auris and vaginal Candida isolates, which suggested ravuconazole could be used in the treatment of drug-resistant candidiasis.

In Vitro Activities of Ravuconazole and Isavuconazole against Dematiaceous Fungi.

The in vitro activities of 11 antifungals against 84 dematiaceous fungi were tested. For most tested fungal species, the MIC values of ravuconazole and isavuconazole were lower than those obtained with itraconazole, voriconazole, and posaconazole. Ravuconazole and isavuconazole appear to be more efficient against most dematiaceous fungal infections than the other triazoles. However, some pigmented fungi, such as Bipolaris spicifera and Veronaea botryosa, remain more susceptible to other triazoles or to echinocandins.