Understanding and exploring the diversity of soil microorganisms in tea (Camellia sinensis) gardens: toward sustainable tea production.

Leaves of Camellia sinensis plants are used to produce tea, one of the most consumed beverages worldwide, containing a wide variety of bioactive compounds that help to promote human health. Tea cultivation is economically important, and its sustainable production can have significant consequences in providing agricultural opportunities and lowering extreme poverty. Soil parameters are well known to affect the quality of the resultant leaves and consequently, the understanding of the diversity and functions of soil microorganisms in tea gardens will provide insight to harnessing soil microbial communities to improve tea yield and quality. Current analyses indicate that tea garden soils possess a rich composition of diverse microorganisms (bacteria and fungi) of which the bacterial Proteobacteria, Actinobacteria, Acidobacteria, Firmicutes and Chloroflexi and fungal Ascomycota, Basidiomycota, Glomeromycota are the prominent groups. When optimized, these microbes' function in keeping garden soil ecosystems balanced by acting on nutrient cycling processes, biofertilizers, biocontrol of pests and pathogens, and bioremediation of persistent organic chemicals. Here, we summarize research on the activities of (tea garden) soil microorganisms as biofertilizers, biological control agents and as bioremediators to improve soil health and consequently, tea yield and quality, focusing mainly on bacterial and fungal members. Recent advances in molecular techniques that characterize the diverse microorganisms in tea gardens are examined. In terms of viruses there is a paucity of information regarding any beneficial functions of soil viruses in tea gardens, although in some instances insect pathogenic viruses have been used to control tea pests. The potential of soil microorganisms is reported here, as well as recent techniques used to study microbial diversity and their genetic manipulation, aimed at improving the yield and quality of tea plants for sustainable production.

High-Throughput Metabolic Pattern Screening Strategy for Early Colorectal and Gastric Cancers Based on Covalent Organic Frameworks-Assisted Laser Desorption/Ionization Mass Spectrometry.

Precise early diagnosis and staging are conducive to improving the prognosis of colorectal cancer (CRC) and gastric cancer (GC) patients. However, due to intrusive inspections and limited sensitivity, the prevailing diagnostic methods impede precisely large-scale screening. In this work, we reported a high-throughput serum metabolic patterns (SMP) screening strategy based on covalent organic frameworks-assisted laser desorption/ionization mass spectrometry (hf-COFsLDI-MS) for early diagnosis and staging of CRC and GC. Notably, 473 high-quality SMP were extracted without any tedious sample pretreatment and coupled with multiple machine learning algorithms; the area under the curve (AUC) value is 0.938 with 96.9% sensitivity for early CRC diagnosis, and the AUC value is 0.974 with 100% sensitivity for early GC diagnosis. Besides, the discrimination of CRC and GC is accomplished with an AUC value of 0.966 for the validation set. Also, the screened-out features were identified by MS/MS experiments, and 8 metabolites were identified as the biomarkers for CRC and GC. Finally, the corresponding disordered metabolic pathways were revealed, and the staging of CRC and GC was completed. This work provides an alternative high-throughput screening strategy for CRC and GC and highlights the potential of metabolic molecular diagnosis in clinical applications.

Dental and skeletal maturation of Chinese male children with unilateral cleft lip and palate.

The aim of this study was to determine whether the relationship between dental age (DA), cervical stage (CS) and chronological age (CA) in Chinese male children with unilateral cleft lip and palate (UCLP) is similar to that of children without clefts. Panoramic and cephalometric radiographs of 105 male UCLP patients, aged from 8 to 16 years, were collected and compared to 210 age-matched healthy control males. The Demirjian and cervical vertebral maturation (CVM) methods were used to visually examine the radiographs and Spearman's correlation analysis was used to identify differences between the two groups with regards to CS, DA and CA. There was a significant positive correlation between DA and CA in both groups and the mean CA-DA difference was significantly higher in children with UCLP when compared to controls (0.319 vs. 0.003, p < 0.05). A significant delay in tooth development was detected in UCLP children from 10 to 12 years-of-age. Both the UCLP and control groups showed high correlations between CS and DA. Calcification stage D appeared only before CS3; however, from CS5 to 6, all teeth have almost completed their maturation phase. Chinese male UCLP patients are likely to experience delayed tooth development compared to healthy controls, especially during the fast-growing period. Evaluating the stages of tooth mineralization could represent a rapid method to assess growth potential.

Three New Species of Russulaceae (Russulales, Basidiomycota) from Southern China.

The characterization of natural fungal diversity impacts our understanding of ecological and evolutionary processes and can lead to novel bioproduct discovery. Russula and Lactarius, both in the order Russulales, represent two large genera of ectomycorrhizal fungi that include edible as well as toxic varieties. Based on morphological and phylogenetic analyses, including nucleotide sequences of the internal transcribed spacer (ITS), the 28S large subunit of ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), the ribosomal mitochondrial small subunit (mtSSU), and the translation elongation factor 1-α (TEF1-α) gene sequences, we here describe and illustrate two new species of Russula and one new species of Lactarius from southern China. These three new species are: R. junzifengensis (R. subsect. Virescentinae), R. zonatus (R. subsect. Crassotunicatae), and L. jianyangensis (L. subsect. Zonarii).

Assessing the structure and diversity of fungal community in plant soil under different climatic and vegetation conditions.

Introduction: Understanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province. Methods: A total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline. Results: Our data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. ß-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy. Discussion: Our findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors.

Characterization of Terpenoids from the Ambrosia Beetle Symbiont and Laurel Wilt Pathogen Harringtonia lauricola.

Little is known concerning terpenoids produced by members of the fungal order Ophiostomales, with the member Harringtonia lauricola having the unique lifestyle of being a beetle symbiont but potentially devastating tree pathogen. Nine known terpenoids, including six labdane diterpenoids (1-6) and three hopane triterpenes (7-9), were isolated from H. lauricola ethyl acetate (EtOAc) extracts for the first time. All compounds were tested for various in vitro bioactivities. Six compounds, 2, 4, 5, 6, 7, and 9, are described functionally. Compounds 2, 4, 5, and 9 expressed potent antiproliferative activity against the MCF-7, HepG2 and A549 cancer cell lines, with half-maximal inhibitory concentrations (IC50s) ~12.54-26.06 µM. Antimicrobial activity bioassays revealed that compounds 4, 5, and 9 exhibited substantial effects against Gram-negative bacteria (Escherichia coli and Ralstonia solanacearum) with minimum inhibitory concentration (MIC) values between 3.13 and 12.50 µg/mL. Little activity was seen towards Gram-positive bacteria for any of the compounds, whereas compounds 2, 4, 7, and 9 expressed antifungal activities (Fusarium oxysporum) with MIC values ranging from 6.25 to 25.00 µg/mL. Compounds 4, 5, and 9 also displayed free radical scavenging abilities towards 2,2-diphenyl-1-picrylhydrazyl (DPPH) and superoxide (O2-), with IC50 values of compounds 2, 4, and 6 ~3.45-14.04 µg/mL and 22.87-53.31 µg/mL towards DPPH and O2-, respectively. These data provide an insight into the biopharmaceutical potential of terpenoids from this group of fungal insect symbionts and plant pathogens.

Characterization of an α-Amylase from the Honeybee Chalk Brood Pathogen Ascosphaera apis.

The insect pathogenic fungus, Ascosphaera apis, is the causative agent of honeybee chalk brood disease. Amylases are secreted by many plant pathogenic fungi to access host nutrients through the metabolism of starch, and the identification of new amylases can have important biotechnological applications. Production of amylase by A. apis in submerged culture was optimized using the response surface method (RSM). Media composition was modeled using Box-Behnken design (BBD) at three levels of three variables, and the model was experimentally validated to predict amylase activity (R2 = 0.9528). Amylase activity was highest (45.28 ± 1.16 U/mL, mean ± SE) in media composed of 46 g/L maltose and1.51 g/L CaCl2 at a pH of 6.6, where total activity was ~11-fold greater as compared to standard basal media. The enzyme was purified to homogeneity with a 2.5% yield and 14-fold purification. The purified enzyme had a molecular weight of 75 kDa and was thermostable and active in a broad pH range (> 80% activity at a pH range of 7-10), with optimal activity at 55 °C and pH = 7.5. Kinetic analyses revealed a Km of 6.22 mmol/L and a Vmax of 4.21 µmol/mL·min using soluble starch as the substrate. Activity was significantly stimulated by Fe2+ and completely inhibited by Cu2+, Mn2+, and Ba2+ (10 mM). Ethanol and chloroform (10% v/v) also caused significant levels of inhibition. The purified amylase essentially exhibited activity only on hydrolyzed soluble starch, producing mainly glucose and maltose, indicating that it is an endo-amylase (α-amylase). Amylase activity peaked at 99.38 U/mL fermented in a 3.7 L-bioreactor (2.15-fold greater than what was observed in flask cultures). These data provide a strategy for optimizing the production of enzymes from fungi and provide insight into the α-amylase of A. apis.

Morphological and phylogenetic analyzes reveal two new species of Melanconiella from Fujian Province, China.

Introduction: Species of Melanconiella include a diverse array of plant pathogens as well as endophytic fungi. Members of this genus have been frequently collected from the family Betulaceae (birches) in Europe and North America. Little, however, if known concerning the distribution of Melanconiella and/or their potential as pathogens of other plant hosts. Methods: Fungi were noted and isolated from diseased leaves of Loropetalum chinense (Chinese fringe flower) and Camellia sinensis (tea) in Fujian Province, China. Genomic DNA was extracted from fungal isolates and the nucleotide sequences of four loci were determined and sued to construct phylogenetic trees. Morphological characteristics of fungal structures were determined via microscopic analyses. Results: Four strains and two new species of Melanconiella were isolated from infected leaves of L. chinense and C. sinensis in Fujian Province, China. Based on morphology and a multi-gene phylogeny of the internal transcribed spacer regions with the intervening 5.8S nrRNA gene (ITS), the 28S large subunit of nuclear ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF1-α), Melanconiellaloropetali sp. nov. and Melanconiellacamelliae sp. nov. were identified and described herein. Detailed descriptions, illustrations, and a key to the known species of Melanconiella are provided. Discussion: These data identify new species of Melanconiella, expanding the potential range and distribution of these dark septate fungi. The developed keys provide a reference source for further characterization of these fungi.

Optimized Unilateral Magnetic Resonance Sensor with Constant Gradient and Its Applications in Composite Insulators.

In this study, an optimized unilateral magnetic resonance sensor with a three-magnet array is presented for assessing the aging of composite insulators in power grids. The sensor's optimization involved enhancing the static magnetic field strength and the homogeneity of the RF field while maintaining a constant gradient in the direction of the vertical sensor surface and maximizing homogeneity in the horizontal direction. The center layer of the target area was positioned 4 mm from the coil's upper surface, resulting in a magnetic field strength of 139.74 mT at the center point of the area, with a gradient of 2.318 T/m and a corresponding hydrogen atomic nuclear magnetic resonance frequency of 5.95 MHz. The magnetic field uniformity over a 10 mm × 10 mm range on the plane was 0.75%. The sensor measured 120 mm × 130.5 mm × 76 mm and weighed 7.5 kg. Employing the optimized sensor, magnetic resonance assessment experiments were conducted on composite insulator samples utilizing the CPMG (Carr-Purcell-Meiboom-Gill) pulse sequence. The T2 distribution provided visualizations of the T2 decay in insulator samples with different degrees of aging.

Hollow Crystallization COF Capsuled MOF Hybrids Depict Serum Metabolic Profiling for Precise Early Diagnosis and Risk Stratification of Acute Coronary Syndrome.

Acute coronary syndrome (ACS), comprising unstable angina (UA) and acute myocardial infarction (AMI), is the leading cause of death worldwide. Currently, lacking effective strategies for classifying ACS hinders the prognosis improvement of ACS patients. Disclosing the nature of metabolic disorders holds the potential to reflect disease progress and high-throughput mass spectrometry-based metabolic analysis is a promising tool for large-scale screening. Herein, a hollow crystallization COF capsuled MOF hybrids (UiO-66@HCOF) assisted serum metabolic analysis is developed for the early diagnosis and risk stratification of ACS. UiO-66@HCOF exhibits unrivaled chemical and structural stability as well as endowing satisfying desorption/ionization efficiency in the detection of metabolites. Paired with machine learning algorithms, early diagnosis of ACS is achieved with the area under the curve (AUC) value of 0.945 for validation sets. Besides, a comprehensive ACS risk stratification method is established, and the AUC value for the discrimination of ACS from healthy controls, and AMI from UA are 0.890, and 0.928. Moreover, the AUC value of the subtyping of AMI is 0.964. Finally, the potential biomarkers exhibit high sensitivity and specificity. This study makes metabolic molecular diagnosis a reality and provided new insight into the progress of ACS.

Technological development of multidimensional liquid chromatography-mass spectrometry in proteome research.

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for high-throughput proteomic research. Limited by the peak capacity, the separation performance of conventional single-dimensional LC hampers the development of proteomics. Combining different separation modes orthogonally, multidimensional liquid chromatography (MDLC) with high peak capacity was developed to address this challenge. MDLC has evolved rapidly since its establishment, and the progress of proteomics has been greatly facilitated by the advent of novel MDLC-MS-based methods. In this paper, we will review the advances of MDLC-MS-based methodologies and technologies in proteomics studies, from different perspectives including novel application scenarios and proteomic targets, automation, miniaturization, and the improvement of the classic methods in recent years. In addition, attempts regarding new MDLC-MS models are also mentioned together with the outlook of MDLC-MS-based proteomics methods.

New Method for Counting and Picking Out Single Circulating Tumor Cells from Microliter-Volume Samples for Tumor Progression Surveillance and Single-Cell Heterogeneity Analysis.

Circulating tumor cells (CTCs) are crucial in tumor progression and metastasis, but the knowledge of their roles grows slowly at single-cell levels. Characterizing the rarity and fragility of CTCs by nature, highly stable and efficient single-CTC sampling methods are still lacking, which impedes the development of single-CTC analysis. Herein, an improved, capillary-based single-cell sampling (SiCS) method, the so-called bubble-glue single-cell sampling (bubble-glue SiCS), is introduced. Benefiting from the characteristic that the cells tend to adhere to air bubbles in the solution, single cells can be sampled with bubbles as low as 20 pL with a self-designed microbubble-volume-controlled system. Benefiting from the excellent maneuverability, single CTCs are sampled directly from 10 µL volume of real blood samples after fluorescent labeling. Meanwhile, over 90% of the CTCs obtained survived and well proliferated after the bubble-glue SiCS process, which showed considerable superiority for downstream single-CTC profiling. Furthermore, a highly metastatic breast cancer model of the 4T1 cell line in vivo was employed for the real blood sample analysis. Increases in CTC numbers were observed during the tumor progression process, and significant heterogeneities among individual CTCs were discovered. In all, we propose a novel avenue for target SiCS and provide an alternative technique route for CTC separation and analysis.

Counting Protein Number in a Single Cell by a Picoliter Liquid Operating Technology.

Ultra-low-copy number proteins play a crucial role in exploring cellular heterogeneity and the insight of protein biomarkers in a single cell. However, counting ultra-low-copy number target proteins in a single cell remains a grand challenge. Herein, we developed a so-called single-cell picoliter liquid operating technology for counting target proteins in a single cell. An ingenious volume-controllable sampling technique was employed to capture a single cell for subsequent analysis. Remarkably, 50 pL of sample volume was employed for sample preparation, single-cell capture, in-droplet lysis, and target protein immobilization on a functionalized coverslip in a monolayer. Then, target protein antibodies coupled with quantum dots were added and incubated to label those immobilized proteins. After clean-up, a single-view image under 100× objective was taken, and the 80 × 80 µm2 view image was then applied to count the precise copy number of the target proteins in the single cell. Furthermore, good linearity and repeatability were achieved for ultra-low-copy number proteins, ranging from 1 to 1500. Finally, the expression level of human epidermal growth factor receptor 2 in single cells from both MCF-7 and MDA-MB-231 cell lines was also analyzed. In a word, this work stimulated the development of capillary-based single-cell analysis and updated the connotation of counting ultra-low-copy number proteins.

Precise Detection of Cataracts with Specific High-Risk Factors by Layered Binary Co-Ionizers Assisted Aqueous Humor Metabolic Analysis.

Diabetes and high myopia as well-known high-risk factors can aggravate cataracts, yet clinical coping strategy remains a bottleneck. Metabolic analysis tends to be powerful for precisely detection and mechanism exploration since most of diseases including cataracts are accompanied by metabolic disorder. Herein, a layered binary co-ionizers assisted aqueous humor metabolic analysis tool is proposed for potentially etiological typing and detection of cataracts, including age-related cataracts (ARC), cataracts with diabetes mellitus (CDM), and cataracts with high myopia (CHM). Startlingly, taking advantage of the optimal machine learning algorithm and all metabolic fingerprints, 100% of accuracy, precision, and recall rates are achieved for arbitrary comparison between groups. Moreover, 11, 9, and 7 key metabolites with explicit identities are confirmed as markers of discriminating CDM from ARC, CHM from ARC, and CDM from CHM, and the corresponding area under the curve values of validation cohorts are 0.985, 1.000, and 1.000. Finally, the critical impact of diabetes/high myopia on cataracts is revealed by excavating the change levels and metabolic pathways of key metabolites. This work updates the insights of prevention and treatment about cataracts at metabolic level and throws out huge surprises and progresses metabolic diagnosis toward a reality.

A marine-derived small molecule induces immunogenic cell death against triple-negative breast cancer through ER stress-CHOP pathway.

Although triple-negative breast cancer (TNBC) is the most refractory subtype among all breast cancers, it has been shown to have higher immune infiltration than other subtypes. We identified the marine-derived small molecule MHO7, which acts as a potent immunogenic cell death (ICD) inducer through the endoplasmic reticulum (ER) stress-C/EBP-homologous protein (CHOP) pathway, to treat TNBC. MHO7 exerted cytostatic and cytotoxic effects on TNBC cells at an IC50 of 0.96-1.75 µM and suppressed tumor growth with an approximately 80% inhibition rate at a dose of 60 mg/kg. In 4T1 cell tumor-bearing mice, 30 mg/kg MHO7 inhibited pulmonary metastasis with an efficacy of 70.26%. Transcriptome analyses revealed that MHO7 changed the transcription of genes related to ribosome and protein processes in the ER. MHO7 also triggered reactive oxygen species (ROS) generation and attenuated glutathione (GSH) levels, which caused excessive oxidative stress and ER stress via the PERK/eIF2α/AFT4/CHOP pathway and led to cell apoptosis. ER stress and ROS production facilitated the release of ICD-related danger-associated molecular patterns (DAMPs) from TNBC cells, which activated the immune response in vivo, as indicated by the release of antitumor cytokines such as IL-6, IL-1ß, IFN-γ, and TNF-α, increases in CD86+ and MHC-II dendritic cells and CD4+ and CD8+ T cells and a decrease in regulatory T cells (Tregs). These results reveal that MHO7 triggers an aggressive stress response to amplify tumor immunogenicity and induce a robust immune response. This synergistic effect inhibits primary breast cancer growth and spontaneous metastasis in TNBC, providing a new strategy for TNBC treatment.

Assessment of Skeletal Maturation in Male Children With Unilateral Cleft Lip and Palate.

OBJECTIVES: To assess the skeletal maturation in male children with unilateral cleft lip and palate (UCLP) in comparison to that of noncleft peers using the cervical vertebral maturation (CVM) method. METHODS: A sample of 149 male UCLP patients aged from 8- to 16-year-old and 447 age-matched orthodontic individuals without clefts was retrospectively compiled. Cervical vertebral maturation was assessed based on the cephalometric radiographs. RESULTS: The proportion of children in CVMSI and CVMSII was higher in the UCLP group compared to that in the noncleft group, but there was no significant difference in the CVM stage of the cleft patients compared to their noncleft peers. In the 12- to 14-year-old group, children with UCLP showed significantly delayed skeletal maturity in comparison with their noncleft peers. No significant difference was found in the other 3 age groups. There was a statistically significant correlation between the skeletal age and chronological age in both the UCLP group and the noncleft group. There was no significant difference in the mean age at CVMII and CVMIII between the cleft patients and noncleft peers. CONCLUSIONS: Males with UCLP aged 12- to 14-year-old have a statistically significant increased risk of delayed skeletal maturity in comparison with their noncleft peers. The chronological age is not an accurate indicator to assess the degree of skeletal maturation.

Mesoporous NiO@ZnO nanofiber membranes via single-nozzle electrospinning for urine metabolism analysis of smokers.

An effective matrix is very important for impact laser desorption/ionization mass spectrometry (LDI-MS), and the physicochemical properties of the matrix nanostructures can impact the LDI-MS performance. In this study, a simple and efficient single-nozzle electrospinning strategy using polystyrene (PS) spheres and polyvinyl pyrrolidone (PVP) to construct a mesoporous NiO@ZnO nanofiber membrane was developed. Compared with the NiO and ZnO nanomaterials alone, the obtained NiO@ZnO nanofiber membrane was proven to be an efficient material as the matrix to increase the intensity of the mass spectrum speaks of small molecules. The NiO@ZnO nanofiber membrane was used as the matrix for the LDI-MS method for the urine metabolism analysis of smokers, which revealed differences in the metabolic and the possible metabolic markers of smokers through the statistical analysis of the urine samples of 27 smokers and 11 nonsmoker controls.

Probing serum N-glycan patterns for rapid and precise detection of Crohn's disease.

Serum N-glycan patterns from 50 Crohn's disease (CD) patients and 50 healthy controls were acquired using a carbon matrix, from which eight N-glycans with significant difference were screened out to reveal remarkale performance for CD diagnosis. This research is expected to help future glycan-based disease detection not limited to CD.

Comparative transcriptomic analysis of the l-4i silkworm (Lepidoptera: Bombyx mori) mutants and its wild-type strain P33 by RNA-Seq.

The silkworm (Bombyx mori) is a domesticated holometabolous insect, and more than 400 Mendelian mutations have been identified. Investigating the mechanism behind these silkworm mutants is essential for understanding the development of silkworms and other lepidopterans, and lethal genes could be used for pest control. The lethal silkworm mutant in the fourth instar (l-4i) has been recently found; however, the underlying mechanism is not yet clear. Herein, we studied the l-4i mutant and its wild-type strain P33 using RNA sequencing (RNA-seq). Our results revealed that 2013 genes were significantly downregulated, and 20 biological processes, including spliceosomal snRNP assembly, protein folding and protein catabolic process, were significantly enriched in these downregulated genes. Moreover, 2405 genes were significantly upregulated in the l-4i mutant, and 20 biological processes, including purine nucleobase metabolic process, nucleoside metabolic process and de novo IMP biosynthetic process, were significantly enriched in these upregulated genes. The study suggests that the imbalance of multiple biological processes and pathways and abnormal protein generation from RNA alternative splicing may cause the death of the l-4i mutant.

Genome Mining Reveals a Multiproduct Sesterterpenoid Biosynthetic Gene Cluster in Aspergillus ustus.

Genome mining of Aspergillus ustus 094102 enabled the discovery of a multiproduct bifunctional terpene synthase (BTS), AuAS. Heterologous expression of AuAS led to the discovery of five new sesterterpenes, and coexpression of the upstream CYP450 monooxygenase (AuAP450) generated four new sesterterpene alcohols. Additionally, aspergilol A showed cytotoxic activities against MCF-7, MDA-MB231, and HepG2 cancer cells (IC50 21.20-48.76 µM), and aspergilol B exhibited a cytotoxic effect on MCF-7 cells (IC50 27.41 µM).