Characterization of CsUGT73AC15 as a Multifunctional Glycosyltransferase Impacting Flavonol Triglycoside Biosynthesis in Tea Plants.

Flavonol glycosides, contributing to the health benefits and distinctive flavors of tea (Camellia sinensis), accumulate predominantly as diglycosides and triglycosides in tea leaves. However, the UDP-glycosyltransferases (UGTs) mediating flavonol multiglycosylation remain largely uncharacterized. In this study, we employed an integrated proteomic and metabolomic strategy to identify and characterize key UGTs involved in flavonol triglycoside biosynthesis. The recombinant rCsUGT75AJ1 exhibited flavonoid 4'-O-glucosyltransferase activity, while rCsUGT75L72 preferentially catalyzed 3-OH glucosylation. Notably, rCsUGT73AC15 displayed substrate promiscuity and regioselectivity, enabling glucosylation of rutin at multiple sites and kaempferol 3-O-rutinoside (K3R) at the 7-OH position. Kinetic analysis revealed rCsUGT73AC15's high affinity for rutin (Km = 9.64 µM). Across cultivars, CsUGT73AC15 expression inversely correlated with rutin levels. Moreover, transient CsUGT73AC15 silencing increased rutin and K3R accumulation while decreasing their respective triglycosides in tea plants. This study offers new mechanistic insights into the key roles of UGTs in regulating flavonol triglycosylation in tea plants.

Genome-Wide Investigation of Oxidosqualene Cyclase Genes Deciphers the Genetic Basis of Triterpene Biosynthesis in Tea Plants.

Triterpenoids from Camellia species comprise a diverse class of bioactive compounds with great therapeutic potential. However, triterpene biosynthesis in tea plants (Camellia sinensis) remains elusive. Here, we identified eight putative 2,3-oxidosqualene cyclase (OSC) genes (CsOSC1-8) from the tea genome and characterized the functions of five through heterologous expression in yeast and tobacco and transient overexpression in tea plants. CsOSC1 was found to be a ß-amyrin synthase, whereas CsOSC4, 5, and 6 exhibited multifunctional α-amyrin synthase activity. Molecular docking and site-directed mutagenesis showed that the CsOSC6M259T/W260L double mutant yielded >40% lupeol, while the CsOSC1 W259L single mutant alone was sufficient for lupeol production. The V732F mutation in CsOSC5 altered product formation from friedelin to taraxasterol and ψ-taraxasterol. The L254 M mutation in the cycloartenol synthase CsOSC8 enhanced the catalytic activity. Our findings shed light on the molecular basis governing triterpene diversity in tea plants and offer potential avenues for OSC engineering.

Shoot-to-root communication via GmUVR8-GmSTF3 photosignaling and flavonoid biosynthesis fine-tunes soybean nodulation under UV-B light.

Legume nodulation requires light perception by plant shoots and precise long-distance communication between shoot and root. Recent studies have revealed that TGACG-motif binding factors (GmSTFs) integrate light signals to promote root nodulation; however, the regulatory mechanisms underlying nodule formation in changing light conditions remain elusive. Here, we applied genetic engineering, metabolite measurement, and transcriptional analysis to study soybean (Glycine max) nodules. We clarify a fine-tuning mechanism in response to ultraviolet B (UV-B) irradiation and rhizobia infection, involving GmUVR8-dependent UV-B perception and GmSTF3/4-GmMYB12-GmCHS-mediated (iso)flavonoid biosynthesis for soybean nodule formation. GmUVR8 receptor-perceived UV-B signal triggered R2R3-MYB transcription factors GmMYB12-dependent flavonoid biosynthesis separately in shoot and root. In shoot, UV-B-triggered flavonoid biosynthesis relied on GmUVR8a, b, c receptor-dependent activation of GmMYB12L-GmCHS8 (chalcone synthase) module. In root, UV-B signaling distinctly promotes the accumulation of the isoflavones, daidzein, and its derivative coumestrol, via GmMYB12B2-GmCHS9 module, resulting in hypernodulation. The mobile transcription factors, GmSTF3/4, bind to cis-regulatory elements in the GmMYB12L, GmMYB12B2, and GmCHS9 promoters, to coordinate UV-B light perception in shoot and (iso)flavonoid biosynthesis in root. Our findings establish a novel shoot-to-root communication module involved in soybean nodulation and reveal an adaptive strategy employed by soybean roots in response to UV-B light.

SERS combined with QuEChERS using NBC and Fe3O4 MNPs as cleanup agents to rapidly and reliably detect chlorpyrifos pesticide in citrus.

The surface-enhanced Raman spectroscopy (SERS) technique is being increasingly used for the detection of pesticide residues in agricultural products. However, there are large amounts of fluorescence-producing substances in agricultural products, which seriously affect the Raman signal of the analyte. In this paper, the QuEChERS method was used to remove interfering fluorescent substances in the analyte, and the purification effects of different doses of nano bamboo charcoal (NBC) and Fe3O4 magnetic nanoparticle (Fe3O4 MNP) adsorbents were studied. Meanwhile, the Raman spectral acquisition conditions (AuNPs, test solution, and NaCl) were optimized based on the orthogonal test method. The results showed that 300 µL AuNPs, 40 µL test solution, and 100 µL 1.5% NaCl gave the best SERS response effect. 12.5 mg NBC combined with 10 mg Fe3O4 MNPs could effectively remove the interfering substances from citrus. The Raman spectra of chlorpyrifos molecules were theoretically modeled using density-functional theory (DFT). By comparing the DFT results with the actual tests, five feature peaks, at 338, 522, 558, 672, and 1600 cm-1, were obtained for the detection of chlorpyrifos pesticide residues in citrus. Based on the Raman feature peak intensity at 672 cm-1, the concentration of chlorpyrifos in citrus showed a good linear relationship (R2 = 0.9979) in the concentration range of 3-20 mg kg-1. The recovery rate was 92.12% to 98.38%, and the relative standard deviation (RSD) was 1.77% to 5.29%. The lowest detection concentration was about 3 mg kg-1, and the detection time of a single sample could be completed within 15 min. This study showed that the combination of SERS and QuEChERS preprocessing methods could achieve rapid detection of chlorpyrifos pesticide residues in citrus.

A machine learning strategy-incorporated BiFeO3/Ti3C2 MXene electrochemical platform for simple, rapid detection of Pb2+ with high sensitivity.

The electrochemical technique has been increasingly used for the detection of heavy metal ions in the water system. However, the process for determining the optimum experimental conditions was cumbersome, time-consuming, and unsynchronized, resulting in unsatisfactory detection efficiency. Herein, a new machine learning (ML) strategy combined with BiFeO3/Ti3C2 MXene (BiFeO3/MXene) was used to fabricate a simple but efficient electrochemical Pb2+ sensor. The interconnected BiFeO3/MXene composites prepared by a hydrothermal method possessed an interconnected conductive framework, abundant active sites, and a large surface area, which gave them excellent electronic conductivity and high accumulation of Pb2+. Meanwhile, ML methods such as back-propagation artificial neural network (BPANN) and genetic algorithm (GA) combined with orthogonal experimental design (OED) were used to optimize sensor parameters such as the pH of the supporting electrolyte, the BiFeO3/MXene content, deposition potential, and deposition time. Compared with OED and the one factor at a time (OFAT) methods, the OED-ML method greatly simplified the experimental procedures and improved the electrochemical detection performance. The developed sensor showed superior detection performance for Pb2+ with a detection limit of 0.0001 µg L-1 using the OED-ML method, which was much lower than that of the OED and OFAT methods (0.0003 µg L-1). In addition, the sensor showed good repeatability, reproducibility, stability, and interference capability. The feasibility of the method was verified by detecting Pb2+ in lake samples with recoveries ranging from 98.79% to 101.3%. To our knowledge, the ML strategy was introduced for the first time in an electrochemical sensor for Pb2+ detection, which proved the feasibility and practicality of ML.

Antifungal effects and biocontrol potential of lipopeptide-producing Streptomyces against banana Fusarium wilt fungus Fusarium oxysporum f. sp. cubense.

Fusarium wilt of banana (FWB), caused by Fusarium oxysporum f. sp. cubense (Foc), especially tropical race 4 (TR4), presents the foremost menace to the global banana production. Extensive efforts have been made to search for efficient biological control agents for disease management. Our previous study showed that Streptomyces sp. XY006 exhibited a strong inhibitory activity against several phytopathogenic fungi, including F. oxysporum. Here, the corresponding antifungal metabolites were purified and determined to be two cyclic lipopeptide homologs, lipopeptin A and lipopeptin B. Combined treatment with lipopeptin complex antagonized Foc TR4 by inhibiting mycelial growth and conidial sporulation, suppressing the synthesis of ergosterol and fatty acids and lowering the production of fusaric acid. Electron microscopy observation showed that lipopeptide treatment induced a severe disruption of the plasma membrane, leading to cell leakage. Lipopeptin A displayed a more pronounced antifungal activity against Foc TR4 than lipopeptin B. In pot experiments, strain XY006 successfully colonized banana plantlets and suppressed the incidence of FWB, with a biocontrol efficacy of up to 87.7%. Additionally, XY006 fermentation culture application improved plant growth parameters and induced peroxidase activity in treated plantlets, suggesting a possible role in induced resistance. Our findings highlight the potential of strain XY006 as a biological agent for FWB, and further research is needed to enhance its efficacy and mode of action in planta.

Fe-MnO2 nanosheets loading dihydroartemisinin for ferroptosis and immunotherapy.

Ferroptosis has emerged as a therapeutic tactic to trigger cancer cell death driven by abnormal accumulation of reactive oxygen species (ROS). However, a single ferroptosis treatment modality is often limited. In this work, a combination therapy of ferroptosis and immunotherapy for cancer was proposed. Specifically, a versatile nanodrug was designed for the multiple treatment of hepatocellular carcinoma (HCC) by loading dihydroartemisinin (DHA) on Fe3+-doped MnO2 nanosheets (Fe-MnO2/DHA). Firstly, Fe-MnO2/DHA was degraded by glutathione (GSH) in the tumor microenvironment (TME) to release Fe2+, Mn2+ and DHA, leading to aberrant ROS accumulation due to Fenton/Fenton-like reaction. Secondly, breakage of endoperoxide bridge from DHA was caused by Fe2+ to further induce oxidative stress. Thirdly, the depleted GSH promoted the inactivation of glutathione peroxidase 4 (GPX4), resulting in lipid peroxide (LPO) accumulation. The resulting LPO and ROS could induce ferroptosis and apoptosis of liver cancer cells. Furthermore, Fe-MnO2/DHA mediated three-pronged stimulation of oxidative stress, resulting in high levels of targeted immunogenic cell death (ICD). It could enhance the infiltration of CD4+ T and CD8+ T cells, and promote macrophage polarization. DHA also acted as an immunomodulator to inhibit regulatory T cells (Tregs) for systemic antitumor. Overall, Fe-MnO2/DHA presents a multi-modal therapy for HCC driven by ferroptosis, apoptosis and immune activation, significantly advancing synergistic cancer treatment.

Intelligent analysis of carbendazim in agricultural products based on a ZSHPC/MWCNT/SPE portable nanosensor combined with machine learning methods.

A nano-ZnS-decorated hierarchically porous carbon (ZSHPC) was mixed with MWCNTs to obtain ZSHPC/MWCNT nanocomposites. Then, ZSHPC/MWCNTs were used to modify a screen-printed electrode, and a portable electrochemical detection system combined with machine learning methods was used to investigate carbendazim (CBZ) residues in rice and tea. The electrochemical performance of the constructed electrode showed that the electrode had good electrocatalytic ability, large effective surface area, strong stability and anti-interference ability. Support Vector Machine (SVM), Least Square Support Vector Machine (LS-SVM) and Back Propagation-Artificial Neural Network (BP-ANN) were used to establish the prediction model for CBZ residues in rice and tea, and the traditional linear regression was developed. The investigated results showed that the LS-SVM model had the best prediction performance and the lowest prediction error compared with the traditional linear regression, BP-ANN and SVM models. The R2, RMSE, and MAE for the training set samples were 0.9969, 0.3605 and 0.2968, respectively. The R2, RMSE, MAE and RPD for the prediction set samples were 0.9924, 0.6190, 0.5360 and 10.3097, respectively. The average recovery range of CBZ in tea and rice was 98.77-109.32% and that of RSD was 0.47-2.58%, indicating that the rapid analysis of CBZ pesticide residues in agricultural products based on a portable electrochemical detection system combined with machine learning was feasible.

Exploring Surface-Enhanced Raman Spectroscopy (SERS) Characteristic Peaks Screening Methods for the Rapid Determination of Chlorpyrifos Residues in Rice.

Surface-enhanced Raman spectroscopy (SERS), coupled with characteristic peak screening methods, was developed for analyzing chlorpyrifos (CM) pesticide residues in rice. Au nanoparticles (AuNPs) were prepared as Raman signal enhancement. Magnesium sulfate (MgSO4), primary secondary amine (PSA), and C18 were used to purify the rice extraction. A successive projections algorithm (SPA) was performed to identify the optimal characteristic peaks of CM in rice from full Raman spectroscopy. Support vector machine (SVM) and partial least squares (PLS) were implemented to investigate the quantitative analysis models. The results demonstrated that six Raman peaks such as 671, 834, 1016, 1114, 1436, and 1444 cm-1 were selected by the SPA and SVM models and had better performance using six peaks (only 0.92% of the full spectra variables) with R2p = 0.97, RMSEP = 2.89 and RPD = 4.26, and the experiment time for a sample was accomplished within 10 min. Recovery for five unknown concentration samples was 97.45-103.96%, and T-test results also displayed no obvious differences between the measured value and the predicted value. The study stated that SERS, combined with characteristic peak screening methods, can be applied to rapidly monitor the chlorpyrifos residue in rice.

Rapid detection of sulfonamide antibiotics residues in swine urine by surface-enhanced Raman spectroscopy.

Surface enhanced Raman spectroscopy (SERS) combined with rapid pretreatment technique was used to determine sulfonamide antibiotics (sulfadiazine and sulfathiazole) residue in swine urine. Au nanoparticles (AuNPs) were synthesized as Raman enhance substrate and the extraction of swine urine was purified with primary secondary amine (PSA), octadecyl silane (C18) and graphitized carbon (GCB) to eliminate the interference of the matrix and different dosages of adsorbents (PSA, C18, GCB) were investigated. The results showed that the treatment with C18 of 150 mg, GCB of 200 mg and PSA of 200 mg were an excellent approach for rapidly detecting sulfonamide antibiotics residue in swine urine. Combined with density functional theory calculation (DFT), Raman characteristic peaks of 819, 1102, 1173, 1588 cm-1 and 825, 1127 cm-1 were selected for qualitative and quantitative assessment of sulfadiazine and sulfathiazole in swine urine, respectively. Based on raman characteristic peak of 819 cm-1, a good linear relationship between sulfadiazine concentration and Raman intensity was developed with R2 = 0.9912, and based on raman characteristic peak of 825 cm-1, a good linear relationship between sulfathiazole concentration and Raman intensity was developed with R2 = 0.9941. And recoveries for five unknown concentration samples predicted were 98.47 âˆ¼ 105.18% with relative standard deviation (RSD) of 1.53% ∼ 5.18%. This study demonstrated that SERS coupled with a quick, easy, cheap, effective, rugged, and safe (QuEChERS) method could be employed to rapidly examine the sulfonamide antibiotics residue in swine urine towards its quality and safety monitoring.

New Insights into Stress-Induced ß-Ocimene Biosynthesis in Tea (Camellia sinensis) Leaves during Oolong Tea Processing.

As the major contributors to the floral odors of tea products, terpenoid volatiles play critical roles in the defense response of plants to multiple stresses. Until now, only a few TPS genes in tea plants (Camellia sinensis) have been functionally validated. In this study, by comparative studies conducted at gene, protein, and metabolite levels during oolong tea processing, we isolated an ocimene synthase gene, CsOCS, which displays a low similarity to previously characterized tea ocimene synthases. Further prokaryotic expression and subcellular localization analysis showed that it is plastid-located and could produce (E)-ß-ocimene and (Z)-ß-ocimene using GPP as the substrate. The optimum temperature and pH of the enzyme were 30 °C and 7.5, respectively. Treatment with exogenous methyl jasmonate elevated the transcript level of CsOCS and enhanced the emission of ocimene from tea leaves. Collectively, CsOCS is implicated as a key enzyme for ß-ocimene synthesis during oolong tea processing.

Intelligent analysis of maleic hydrazide using a simple electrochemical sensor coupled with machine learning.

A simple electrochemical sensing platform based on a low-cost disposable laser-induced porous graphene (LIPG) flexible electrode for the intelligent analysis of maleic hydrazide (MH) in potatoes and peanuts coupled with machine learning (ML) was successfully designed. The LIPG electrode was patterned by a simple one-step laser-induced procedure on commercial polyimide film using a computer-controlled direct laser writing micromachining system and displayed excellent flexibility, 3D porous structure, large specific surface area, and preferable conductivity. A data partitioning technique was proposed for the optimal MH concentration ranges by selecting the size of datasets, including the size of the training set and the size of the test set combined with the performance metrics of ML models. Different algorithms such as artificial neural networks (ANN), random forest (RF), and least squares support vector machine (LS-SVM) were selected to build the ML models. Three ML models were evaluated, and the LS-SVM model displayed unique superiority. Both the recoveries and RSD of practical application were further measured to assess the feasibility of the selected LS-SVM model. This will have important theoretical and practical significance for the intelligent analysis of harmful residuals in agro-product safety using an electrochemical sensing platform.

A Homeodomain-Containing Transcriptional Factor PoHtf1 Regulated the Development and Cellulase Expression in Penicillium oxalicum.

Homeodomain-containing transcription factors (Htfs) play important roles in animals, fungi, and plants during some developmental processes. Here, a homeodomain-containing transcription factor PoHtf1 was functionally characterized in the cellulase-producing fungi Penicillium oxalicum 114-2. PoHtf1 was shown to participate in colony growth and conidiation through regulating the expression of its downstream transcription factor BrlA, the key regulator of conidiation in P. oxalicum 114-2. Additionally, PoHtf1 inhibited the expression of the major cellulase genes by coordinated regulation of cellulolytic regulators CreA, AmyR, ClrB, and XlnR. Furthermore, transcriptome analysis showed that PoHtf1 participated in the secondary metabolism including the pathway synthesizing conidial yellow pigment. These data show that PoHtf1 mediates the complex transcriptional-regulatory network cascade between developmental processes and cellulolytic gene expression in P. oxalicum 114-2. Our results should assist the development of strategies for the metabolic engineering of mutants for applications in the enzymatic hydrolysis for biochemical production.

Portable wireless intelligent sensing of ultra-trace phytoregulator α-naphthalene acetic acid using self-assembled phosphorene/Ti3C2-MXene nanohybrid with high ambient stability on laser induced porous graphene as nanozyme flexible electrode.

The harm of pesticide residues to human health via environmental pollution in agriculture has recently become a significant livelihood issue. Herein, a new strategy for smart ultra-trace analysis of phytoregulator α-naphthalene acetic acid (NAA) residues in farmland environments and agro-products via machine learning (ML) using a nanozyme flexible electrode fabricated by two-dimensional phosphorene (BP) nanohybrid with graphene-like titanium carbide MXene (Ti3C2-MXene) on the flexible substrate surface of laser-induced porous graphene (LIPG) is proposed. Highly ambient-stable BP nanohybrid with Ti3C2-MXene is prepared by ultrasonic-assisted liquid-phase exfoliation in organic solvent containing grinding black phosphorus, cuprous chloride and, Ti3C2-MXene that is obtained by selectively etching Al layers of Ti3AlC2. Nanozyme flexible electrode is fabricated by drop-coating Ti3C2-MXene/BP that is formed through electrostatic self-assembly between positively charged BP and negatively charged Ti3C2-MXene onto LIPG that is obtained by direct laser writing on commercial polyimide and patterned via a computer-aided design system as a flexible substrate. The ML model via artificial neural network algorithm for smart output of NAA is discussed. NAA is electrochemically detected in a wide linear range of 0.02-40 µM with a low limit of detection (LOD) of 1.6 nM using a portable mini-workstation. Large and rough surfaces, excellent electrochemical response, and satisfactory practicability demonstrated the feasibility and detectability of the proposed method. This will provide a portable wireless intelligent nanozyme flexible sensing platform for cost-effective, simple, fast and, ultra-trace detection of hazardous substances in the safety of environments, products, and food in agriculture.

Rapid detection of chlorpyrifos pesticide residue in tea using surface-enhanced Raman spectroscopy combined with chemometrics.

Surface enhanced Raman spectroscopy based on rapid pretreatment combined with Chemometrics was used to determine chlorpyrifos residue in tea. Au nanoparticles were used to as enhance substrate. Different dosages of PSA and NBC were investigated to eliminate the tea substrate influence. Competitive adaptive reweighted sampling (CARS) was used to optimize the characteristic peaks, and compared to full spectra variables and the experiment selected variables. The results showed that PSA of 80 mg and NBC of 20 mg was an excellent approach for rapid detecting. CARS - PLS had better accuracy and stability using only 1.7% of full spectra variables. SVM model achieved better performance with R2p = 0.981, RMSEP = 1.42 and RPD = 6.78. Recoveries for five unknown concentration samples were 98.47 ~ 105.18% with RSD - 1.53% ~ 5.18%. T-test results showed that t value was 0.720, less than t0.05,4 = 2.776, demonstrating that no clear difference between the real value and predicted value. The detection time of a single sample is completed within 15 min. This study demonstrated that SERS coupled with Chemometrics and QuEChERS may be employed to rapidly examine the chlorpyrifos residue in tea towards its quality and safety monitoring.

Revealing mechanism of Caulis Sargentodoxae for the treatment of ulcerative colitis based on network pharmacology approach.

OBJECTIVE: The traditional Chinese medicine Caulis Sargentodoxae is widely used in the treatment of ulcerative colitis (UC), but the mechanism remains unknown. The present study aims to reveal its effective components, targets and pathways through network pharmacology and bioinformatics approaches. MATERIALS AND METHODS: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to identify effective components. The ligand-based targets prediction was achieved through SwissTargetPrediction and TargetNet. UC-related targets were identified using Gene Expression Omnibus (GEO) data and DisGeNET. The common targets of disease and components were constructed and analyzed by PPI network. Lastly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses are used to explain the functions of these common targets. Components-Targets-Pathways network was visualized and analyzed to further reveal the connection between the components and targets. RESULTS: Eight active components and 102 key targets were identified to play an important role in UC. These targets were related to regulation of protein serine/threonine kinase activity, positive regulation of cell motility, response to molecule of bacterial origin, response to toxic substance, ERK1 and ERK2 cascade, peptidyl-tyrosine modification, inositol lipid-mediated signaling, cellular response to drug, regulation of inflammatory response and leukocyte migration. Moreover, HIF-1 signaling pathway and PI3K-Akt signaling pathway were the key targets involved in UC-related signaling pathways. CONCLUSION: The eight active components of Caulis Sargentodoxae mainly play a therapeutic role for UC through synergistic regulation of HIF-1 signaling pathway and PI3K-Akt signaling pathway.

Density Functional Theory Calculation and Raman Spectroscopy Studies of Carbamate Pesticides.

In order to obtain the molecular structure vibration information of carbamate pesticide, three carbamate pesticides (carbaryl, carbofuran and aldicarb) were optimized and calculated with B3LYP hybrid functional and 6-31G(d,p) basis set, and their experimental spectra were collected with the Raman spectrometer. The theoretically calculated spectra were compared with the experimental spectra carefully. The results indicated that the theoretically calculated spectra have a very good match with the experimental spectra. The vibrational peaks of three carbamate pesticides were assigned between the range of 400～3 200 cm-1, and the characteristic peaks of carbamate pesticide were found at 874, 1 014, 1 162 and 1 716 cm-1. The characteristic peaks of three carbamate pesticides were found by the contrast of the experimental spectra. The results can provide a theoretical basis for the detection of carbamate pesticide, and will be applied to the identification of carbamate pesticide residues in agricultural products.

[Study on the Rapid Detection of Triazophos Residues in Flesh of Navel Orange by Using Surface-Enhanced Raman Scattering].

Surface enhanced Raman spectroscopy (SERS) and quick pre-treatment technology were used to detect triazophos residues in flesh of navel orange. Quantitative analysis model was developed by partial least squares (PLS) algorithm. SERS of different concentration (0.5 to 20 mg x L(-1)) triazophos juice solution with flesh extract as the matrix were collected by laser Raman spectrometer. Three preprocessing methods such as normalization, MSC and SNV were used to optimize Raman signals and PLS models were set up. The results showed that minimum detection concentration for triazophos in navel orange below 0.5 mg L(-1). The model built with normalization pre-processing gave the best result; the values of correlation (R(p)) and Root mean square error of prediction set (RMSEP) were 1.38 and 0.976 6, respectively. The predict recoveries were 95.97%-103.18%, and the absolute values of relative errors were below 5%. T-test (t = -0.018) showed that there was no significant difference between the true values and prediction values. This study demonstrates that this method is accurate and reliable.

Production of a high-efficiency cellulase complex via ß-glucosidase engineering in Penicillium oxalicum.

BACKGROUND: Trichoderma reesei is a widely used model cellulolytic fungus, supplying a highly effective cellulase production system. Recently, the biofuel industry discovered filamentous fungi from the Penicillium genus as a promising alternative to T. reesei. RESULTS: In our study, we present a systematic over-expression analysis of nine ß-glucosidase encoding genes in the wild-type strain 114-2 of Penicillium oxalicum. We found that the over-expression of BGL1, BGL4, or BGL5 significantly enhanced both ß-glucosidase activity and hydrolysis efficiency of the enzyme system on filter paper. We utilised two strategies to over-express ß-glucosidase in the strain RE-10 that-although over-producing cellulase, does so at the cost of the cellulase mixture deficiency. The constitutive promoter of gene pde_02864 encoding 40S ribosomal protein S8 was used to over-express three ß-glucosidases: BGL1, BGL4, and BGL5. We found that all mutants show significantly enhanced levels of ß-glucosidase at transcriptional, protein, and activity levels. Furthermore, the inducible promoter from bgl2 was used to conditionally over-express the ß-glucosidases BGL1 and BGL4. Surprisingly, this induced expression strategy enables significantly improved expression efficiency. The BGL1 over-expressing mutant I1-13 particularly improved the ß-glucosidase activity at a factor of 65-folds, resulting in levels of up to 150 U/ml. All our BGL over-expression mutants displayed significant enhancement of cellulolytic ability on both microcrystalline cellulose and filter paper. In addition, they substantially reduced the enzyme loads in the saccharification of a natural lignocellulose material delignified corncob residue (DCCR). The mutant I4-32 with over-expression of BGL4 achieved the highest glucose yield in the saccharification of DCCR at only 25 % enzyme load compared to the parental strain RE-10. CONCLUSIONS: In summary, genetically engineering P. oxalicum to significantly improve ß-glucosidase activity is a potent strategy to substantially boost the hydrolytic efficiency of the cellulase cocktail, which will ultimately lead to a considerable reduction of cost for biomass-based biofuel.

Penicillium oxalicum PoFlbC regulates fungal asexual development and is important for cellulase gene expression.

Filamentous fungi can initiate vegetative growth on complex plant polysaccharides in nature through secreting a large amount of lignocellulose-degrading enzymes. These fungi develop a large amount of asexual spores to disperse and survive under harsh conditions, such as carbon and nitrogen depletion. Numerous studies report the presence of a cross-talk between asexual development and extracellular enzyme production, especially at the regulation level. This study identified and characterized a C2H2-type transcription factor called PoFlbC, which is an Aspergillus FlbC ortholog, in cellulolytic fungus Penicillium oxalicum. Results showed that the native level of PoFlbC was crucial for the normal growth and asexual development of P. oxalicum. Importantly, deletion of the PoflbC gene substantially reduced cellulase and hemicellulase productions. Comparative transcriptome analysis by RNA sequencing revealed a global downregulation of genes encoding cellulases, hemicellulases, and other proteins with functions in lignocellulose degradation. A similar defect was also observed in the OEPoflbC strain, suggesting that the production of cellulolytic enzymes was maintained by native expression of the PoflbC. In this study, an essential activator for both fungal asexual development and cellulase production was established in P. oxalicum.