GOLGA7 is essential for NRAS trafficking from the Golgi to the plasma membrane but not for its palmitoylation.

NRAS mutations are most frequently observed in hematological malignancies and are also common in some solid tumors such as melanoma and colon cancer. Despite its pivotal role in oncogenesis, no effective therapies targeting NRAS has been developed. Targeting NRAS localization to the plasma membrane (PM) is a promising strategy for cancer therapy, as its signaling requires PM localization. However, the process governing NRAS translocation from the Golgi apparatus to the PM after lipid modification remains elusive. This study identifies GOLGA7 as a crucial factor controlling NRAS' PM translocation, demonstrating that its depletion blocks NRAS, but not HRAS, KRAS4A and KRAS4B, translocating to PM. GOLGA7 is known to stabilize the palmitoyltransferase ZDHHC9 for NRAS and HRAS palmitoylation, but we found that GOLGA7 depletion does not affect NRAS' palmitoylation level. Further studies show that loss of GOLGA7 disrupts NRAS anterograde trafficking, leading to its cis-Golgi accumulation. Remarkably, depleting GOLGA7 effectively inhibits cell proliferation in multiple NRAS-mutant cancer cell lines and attenuates NRASG12D-induced oncogenic transformation in vivo. These findings elucidate a specific intracellular trafficking route for NRAS under GOLGA7 regulation, highlighting GOLGA7 as a promising therapeutic target for NRAS-driven cancers.

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence and secondary structure features and neglect small molecule characteristics, and resulting in poor performance on unknown small molecule testing. To overcome this limitation, we developed a double-layer stacking-based machine learning model called ZHMol-RLinter. This approach more effectively predicts RNA-small molecule binding preferences by learning RNA and small molecule features to capture their interaction information. ZHMol-RLinter also combines sequence and secondary structural features with structural geometric and physicochemical environment information to capture the specificity of RNA spatial conformations in recognizing small molecules. Our results demonstrate that ZHMol-RLinter has a success rate of 90.8% on the published RL98 testing set, representing a significant improvement over existing methods. Additionally, ZHMol-RLinter achieved a success rate of 77.1% on the unknown small molecule UNK96 testing set, showing substantial improvement over the existing methods. The evaluation of predicted structures confirms that ZHMol-RLinter is reliable and accurate for predicting RNA-small molecule binding preferences, even for challenging unknown small molecule testing. Predicting RNA-small molecule binding preferences can help in the understanding of RNA-small molecule interactions and promote the design of RNA-related drugs for biological and medical applications.

Predicting Small Molecule Binding Nucleotides in RNA Structures Using RNA Surface Topography.

RNA small molecule interactions play a crucial role in drug discovery and inhibitor design. Identifying RNA small molecule binding nucleotides is essential and requires methods that exhibit a high predictive ability to facilitate drug discovery and inhibitor design. Existing methods can predict the binding nucleotides of simple RNA structures, but it is hard to predict binding nucleotides in complex RNA structures with junctions. To address this limitation, we developed a new deep learning model based on spatial correlation, ZHmolReSTasite, which can accurately predict binding nucleotides of small and large RNA with junctions. We utilize RNA surface topography to consider the spatial correlation, characterizing nucleotides from sequence and tertiary structures to learn a high-level representation. Our method outperforms existing methods for benchmark test sets composed of simple RNA structures, achieving precision values of 72.9% on TE18 and 76.7% on RB9 test sets. For a challenging test set composed of RNA structures with junctions, our method outperforms the second best method by 11.6% in precision. Moreover, ZHmolReSTasite demonstrates robustness regarding the predicted RNA structures. In summary, ZHmolReSTasite successfully incorporates spatial correlation, outperforms previous methods on small and large RNA structures using RNA surface topography, and can provide valuable insights into RNA small molecule prediction and accelerate RNA inhibitor design.

Rodent model of metabolic dysfunction-associated fatty liver disease: a systematic review.

Although significant progress has been made in developing preclinical models for metabolic dysfunction-associated steatotic liver disease (MASLD), few have encapsulated the essential biological and clinical outcome elements reflective of the human condition. We conducted a comprehensive literature review of English-language original research articles published from 1990 to 2023, sourced from PubMed, Embase, and Web of Science, aiming to collate studies that provided a comparative analysis of physiological, metabolic, and hepatic histological characteristics between MASLD models and control groups. The establishment of a robust metabolic dysfunction-associated steatotic liver rodent model hinges on various factors, including animal species and strains, sex, induction agents and methodologies, and the duration of induction. Through this review, we aim to guide researchers in selecting suitable induction methods and animal species for constructing preclinical models aligned with their specific research objectives and laboratory conditions. Future studies should strive to develop simple, reliable, and reproducible models, considering the model's sensitivity to factors such as light-dark cycles, housing conditions, and environmental temperature. Additionally, the potential of diverse in vitro models, including 3D models and liver organ technology, warrants further exploration as valuable tools for unraveling the cellular mechanisms underlying fatty liver disease.

Modular metabolic engineering of Bacillus amyloliquefaciens for high-level production of green biosurfactant iturin A.

As a kind of biosurfactants, iturin A has attracted people's wide attentions due to their features of biodegradability, environmentally friendly, etc.; however, high production cost limited its extensive application, and the aim of this research wants to improve iturin A production in Bacillus amyloliquefaciens. Firstly, dual promoter was applied to strengthen iturin A synthetase expression, and its yield was increased to 1.25 g/L. Subsequently, original 5'-UTRs of downstream genes (ituA, ituB, and ituC) in iturin A synthetase cluster were optimized, which significantly increased mRNA secondary stability, and iturin A yield produced by resultant strain HZ-T3 reached 2.32 g/L. Secondly, synthetic pathway of α-glucosidase inhibitor 1-deoxynojirimycin was blocked to improve substrate corn starch utilization, and iturin A yield was increased by 34.91% to 3.13 g/L. Thirdly, efficient precursor (fatty acids, Ser, and Pro) supplies were proven as the critical role in iturin A synthesis, and 5.52 g/L iturin A was attained by resultant strain, through overexpressing yngH, serC, and introducing ocD. Meanwhile, genes responsible for poly-γ-glutamic acid, extracellular polysaccharide, and surfactin syntheses were deleted, which led to a 30.98% increase of iturin A yield. Finally, lipopeptide transporters were screened, and iturin A yield was increased by 17.98% in SwrC overexpression strain, reached 8.53 g/L, which is the highest yield of iturin A ever reported. This study laid a foundation for industrial production and application development of iturin A, and provided the guidance of metabolic engineering breeding for efficient production of other metabolites synthesized by non-ribosomal peptide synthetase. KEY POINTS: • Optimizing 5'-UTR is an effective tactics to regulate synthetase cluster expression. • Blocking 1-DNJ synthesis benefited corn starch utilization and iturin A production. • The iturin A yield attained in this work was the highest yield reported so far.

Mutual regulation between GDF11 and TET2 prevents senescence of mesenchymal stem cells.

Growth differentiation factor 11 (GDF11) is a putative systemic rejuvenation factor. In this study, we characterized the mechanism by which GDF11 reversed aging of mesenchymal stem cells (MSCs). In culture, aged MSCs proliferate slower and are positive for senescence markers senescence-associated ß-galactosidase and P16ink4a . They have shortened telomeres, decreased GDF11 expression, and reduced osteogenic potential. GDF11 can block MSC aging in vitro and reverse age-dependent bone loss in vivo. The antiaging effect of GDF11 is via activation of the Smad2/3-PI3K-AKT-mTOR pathway. Unexpectedly, GDF11 also upregulated a DNA demethylase Tet2, which served as a key mediator for GDF11 to autoregulate itself via demethylation of the GDF11 promoter. Mutation of Tet2 facilitates MSC aging by blocking GDF11 expression. Mutagenesis of Tet2-regulated CpG sites also blocks GDF11 expression, leading to MSC aging. Together, a novel mutual regulatory relationship between GDF11 and an epigenetic factor Tet2 unveiled their antiaging roles.

Synthesis and Antitumor Activity of Panaxadiol Pyrazole and Isooxazole Derivatives.

In this study, we designed and synthesized 19 nitrogen-containing heterocyclic derivatives of panaxadiol (PD). We first reported the antiproliferative activity of these compounds against four different tumor cells. The results of the MTT assay showed that the PD pyrazole derivative (compound 12b) had the best antitumor activity and could significantly inhibit the proliferation of four tested tumor cells. For A549 cells, the IC50 value was as low as 13.44±1.23 µM. Western blot analysis showed that the PD pyrazole derivative was a bifunctional regulator. On the one hand, it can down-regulate the expression of HIF-1α by acting on PI3 K/AKT signaling pathway in A549 cells. On the other hand, it can induce the decrease of CDKs protein family and E2F1 protein expression levels, thus playing a crucial role in cell cycle arrest. According to the results of molecular docking, we found that multiple hydrogen bonds were formed between the PD pyrazole derivative and two related proteins, and the docking score of the derivative was also significantly higher than that of the crude drug. In summary, the study of the PD pyrazole derivative laid a foundation for the development of ginsenoside as an antitumor agent.

[Mechanism of Buyang Huanwu Decoction in protecting ischemic myocardium by regulating platelet autophagy in rats with acute myocardial infarction].

This study explored the effects of Buyang Huanwu Decoction(BYHWD) on platelet activation and differential gene expression after acute myocardial infarction(AMI). SD rats were randomly divided into a sham-operated group, a model group, a positive drug(aspirin) group, and a BYHWD group. Pre-treatment was conducted for 14 days with a daily oral dose of 1.6 g·kg~(-1) BYHWD and 0.1 g·kg~(-1) aspirin. The AMI model was established using the high ligation of the left anterior descending coronary artery method. The detection indicators included myocardial infarct size, heart function, myocardial tissue pathology, peripheral blood flow perfusion, platelet aggregation rate, platelet membrane glycoprotein CD62p expression, platelet transcriptomics, and differential gene expression. The results showed that compared with the sham-operated group, the model group showed reduced ejection fraction and cardiac output, decreased peripheral blood flow, and increased platelet aggregation rate and CD62p expression, and activated platelets. At the same time, TXB_2 content increased and 6-keto-PGF1α content decreased in serum. Compared with the model group, BYHWD increased ejection fraction and cardiac output, improved blood circulation in the foot and tail regions and cardiomyocytes arrangement, reduced myocardial infarct size and inflammatory infiltration, down-regulated platelet aggregation rate and CD62p expression, reduced serum TXB_2 content, and increased 6-keto-PGF1α content. Platelet transcriptome sequencing results revealed that BYHWD regulated mTOR-autophagy pathway-related genes in platelets. The differential gene expression levels were detected using real-time quantitative PCR. BYHWD up-regulated mTOR, down-regulated autophagy-related FUNDC1 and PINK genes, and up-regulated p62 gene expression. The results demonstrated that BYHWD could regulate platelet activation, improve blood circulation, and protect ischemic myocardium in AMI rats, and its mechanism is related to the regulation of the mTOR-autophagy pathway in platelets.

[Effects of Qilong Capsules on myocardial fibrosis and insufficient blood circulation in ischemic cardiomyopathy with Qi deficiency and blood stasis].

Protective effect of Qilong Capsules(QL) on the myocardial fibrosis and blood circulation of rats with coronary heart disease of Qi deficiency and blood stasis type was investigated. Sleep deprivation and coronary artery ligation were used to construct a disease-symptom combination model, and 60 SD rats were divided into sham operation(sham) group, syndrome(S) group, disease and syndrome(M) group and QL group randomly. The treatment group received administration of QL 0.4 g·kg~(-1)·d~(-1). Other groups were given the same amount of normal saline. The disease indexes of each group [left ventricular end diastolic diameter(LVESD), left ventricular end systolic diameter(LVEDD), left ventricular ejection fraction(LVEF), left ventricular axis shortening rate(LVFS), myocardial histopathology, platelet morphology, peripheral blood flow] and syndrome indexes(tongue color, pulse, grip power) were detected. In sham group, cardiomyocytes and myocardial fibers were arranged neatly and densely with clear structures. The tongues' color in sham were light red, and the pulse shape were regular. RGB is a parameter reflected the brightness of the image of the tongue. In the S group, the amplitude and frequency of the animal's pulse increased accompanied by decreasing R,G,B, however, the decreased R,G,B was accompanied by reduced pulse amplitude in M group. And in M group, we observed fuzzy cell morphology, hypertrophied myocytes, disordered arrangement of cardiomyocytes and myocardial fibers, reduced peripheral blood flow and increased collagen volume fraction(CVF). Increased LVESD and LVEDD, and decreased LVEF and LVFS represented cardiac function in S group was significantly lower than that in sham. In QL group, the tongue's color was red and the pulse was smooth. The myocardial fibers of the QL group were arranged neatly and secreted less collagen. It improved the blood circulation in the sole and tail, and reversed the increasing of LVEDD, LVESD and the decreasing of LVEF and LVFS of M group. Platelets in M and S group showed high reactivity, and QL could decrease aggregation risk. In conclusion, Qilong Capsules has an obvious myocardial protective effect on ischemic cardiomyopathy, which may inhibit the degree of myocardial fibrosis and reduce platelet reactivity.

Characterization of Nuclear and Mitochondrial Genomes of Two Tobacco Endophytic Fungi Leptosphaerulina chartarum and Curvularia trifolii and Their Contributions to Phylogenetic Implications in the Pleosporales.

The symbiont endophytic fungi in tobacco are highly diverse and difficult to classify. Here, we sequenced the genomes of Curvularia trifolii and Leptosphaerulina chartarum isolated from tobacco plants. Finally, 41.68 Mb and 37.95 Mb nuclear genomes were sequenced for C. trifolii and L. chartarum with the scaffold N50, accounting for 638.94 Kb and 284.12 Kb, respectively. Meanwhile, we obtained 68,926 bp and 59,100 bp for their mitochondrial genomes. To more accurately classify C. trifolii and L. chartarum, we extracted seven nuclear genes and 12 mitochondrial genes from these two genomes and their closely related species. The genes were then used for calculation of evolutionary rates and for phylogenetic analysis. Results showed that it was difficult to achieve consistent results using a single gene due to their different evolutionary rates, while the phylogenetic trees obtained by combining datasets showed stable topologies. It is, therefore, more accurate to construct phylogenetic relationships for endophytic fungi based on multi-gene datasets. This study provides new insights into the distribution and characteristics of endophytic fungi in tobacco.