Epidemiological characteristics of human metapneumovirus among children in Nanjing, China.

PURPOSE: The objective of this study was to examine the molecular epidemiology and clinical characteristics of HMPV infection among children with ARIs in Nanjing. METHODS: The respiratory samples were collected from 2078 children (≤ 14 years) with acute respiratory infections and were tested for HMPV using real-time RT-PCR. Amplification and sequencing of the HMPV G gene were followed by phylogenetic analysis using MEGA 7.0. RESULT: The detection rate of HMPV among children was 4.7% (97/2078), with a concentration in those under 5 years of age. Notably, the peak season for HMPV prevalence was observed in winter. Among the 97 HMPV-positive samples, 51.5% (50/97) were available for characterization of the HMPV G protein gene. Phylogenetic analysis indicated that the sequenced HMPV strains were classified into three sublineages: A2c111nt - dup (84.0%), B1 (2.0%), and B2 (14.0%). CONCLUSION: There was an incidence of HMPV among hospitalized children during 2021-2022 in Nanjing with A2c111nt - dup being the dominant strain. This study demonstrated the molecular epidemiological characteristics of HMPV among children with respiratory infections in Nanjing, China.

Comprehensive review on the elaboration of payloads derived from natural products for antibody-drug conjugates.

Antibody-drug conjugates (ADCs) have arisen as a promising class of biotherapeutics for targeted cancer treatment, combining the specificity of monoclonal antibodies with the cytotoxicity of small-molecule drugs. The choice of an appropriate payload is crucial for the success development of ADCs, as it determines the therapeutic efficacy and safety profile. This review focuses on payloads derived from natural products, including cytotoxic agents, DNA-damaging agents, and immunomodulators. These offer several advantages such as diverse chemical structures, unique mechanism of actions, and potential for improved therapeutic index. Challenges and opportunities associated with their development were highlighted. This review underscores the significance of natural product payloads in the elaboration of ADCs, which serves as a valuable resource for researchers involved in developing and optimizing next-generation ADCs for cancer treatment.

Relationship Between Microstructural Alterations and Cognitive Decline After Whole-Brain Radiation Therapy for Brain Metastases: An Exploratory Whole-Brain MR Analysis Based on Neurite Orientation Dispersion and Density Imaging.

BACKGROUND: Cognitive impairment frequently occurs in patients with brain metastases (BM) after whole-brain radiotherapy (WBRT). It is crucial to explore the underlying mechanisms of cognitive impairment in BM patients receiving WBRT. PURPOSE: To detect brain microstructural alterations in patients after WBRT by neurite orientation dispersion and density imaging (NODDI), and evaluate the performance of microstructural alterations in predicting cognitive impairment. STUDY TYPE: Prospective. POPULATION: Twenty-six patients (seven female; mean age, 60.9 years). FIELD STRENGTH/SEQUENCE: 3-T, multi-shell diffusion-weighted single-shot echo-planar sequence. Three-dimensional magnetization-prepared rapid acquisition with gradient echo sequence. ASSESSMENT: Mini-mental state examination (MMSE) evaluations were conducted prior to, following, 1 and 3 months after WBRT. The diffusion data were collected twice, 1 week before and 1 week after WBRT. NODDI analysis was conducted to assess microstructural alterations in whole brain (orientation dispersion index, neurite density index, volume fraction of isotropic water molecules). Reliable change indices (RCI) of MMSE were used to measure cognitive decline. The performance of support vector machine models based on NODDI parameters and clinical features (prednisone usage, tumor volume, etc.) in predicting MMSE-RCI was evaluated. STATISTICAL TESTS: Paired t-test to assess alterations of NODDI measures and MMSE during follow-up. Statistical significance level of P-value <0.05. RESULTS: Significantly decreased MMSE score was found at 3 months after WBRT. After WBRT, corpus callosum, medial prefrontal cortex, limbic lobe, occipital lobe, parietal lobe, putamen, globus pallidus lentiform, and thalamus demonstrated damage in NODDI parameters. The predicted MMSE-RCI based on NODDI features was significantly associated with the measured MMSE-RCI at 1 month (R = 0.573; P = 0.003) and 3 months (R = 0.687; P < 0.0001) after WBRT. DATA CONCLUSION: Microstructural alterations in several brain regions including the middle prefrontal and limbic cortexes were observed in patients with BM following WBRT, which may contribute to subsequent cognitive decline. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Impact of Varicella Immunization and Public Health and Social Measures on Varicella Incidence: Insights from Surveillance Data in Shanghai, 2013-2022.

To evaluate the impact of a two-dose VarV program on varicella incidence among the whole population, considering the influence of public health and social measures (PHSMs), we extracted surveillance data on varicella cases during 2013-2022 in Minhang, Shanghai. Then, we estimated the incidence trend of varicella through interrupted time-series analyses and quantified the impact of the immunization program and PHSMs using Serfling regression. We also explored the associations between PHSMs and varicella cases. The implementation of the two-dose VarV strategy was followed by a significant decrease in varicella incidence (-1.84% per month). After one year of the program, varicella incidence was estimated at a 45.25% reduction, which was higher in children (59.12% and 54.09%) than in adults (19.49%). The decrease attributed to PHSMs was 31.26% during 2020-2022, and school closing was identified as the most relevant PHSM (b = -8.03 cases, r = -0.67 with a 1-week lag). These findings indicate that the two-dose immunization program has more effectively reduced the varicella incidence compared with the one-dose vaccine, and interventions like school closings are also encouraged to serve as supplementary measures to prevent varicella epidemics.

Coverage and impact of influenza vaccination among children in Minhang District, China, 2013-2020.

Background: Young children have a great disease burden and are particularly vulnerable to influenza. This study aimed to assess the direct effect of influenza vaccination among children and to evaluate the indirect benefit of immunizing children. Methods: The influenza vaccination records for all children born during 2013-2019 in Minhang District and surveillance data for reported influenza cases were obtained from the Minhang CDC. 17,905 children were recorded in the vaccination system and included in this study. Descriptive epidemiology methods were used for data analysis, including an ecological approach to estimate the number of influenza cases averted by vaccination and linear regression to estimate the reduction in influenza cases in the general population per thousand additional childhood vaccination doses. Results: During the study period, the annual vaccination coverage rate ranged from 10.40% in 2013-2014 to 27.62% in 2015-2016. The estimated number of influenza cases averted by vaccination ranged from a low of 0.28 (range: 0.23-0.34) during 2013-2014 (PF: 6.15%, range: 5.11-7.38%) to a high of 15.34 (range: 12.38-18.51) during 2017-2018 (PF: 16.54%, range: 13.79-19.30%). When increasing vaccination coverage rate by 10% in each town/street, a ratio of 7.27-10.69% cases could be further averted on the basis of observed cases. In four selected periods, the number of influenza cases in the general population was most significantly correlated with the cumulative childhood vaccination doses in the prior 2-5 months, and the reduction in influenza cases ranged from 0.73 to 3.18 cases per thousand additional childhood vaccination doses. Conclusion: Influenza vaccination among children is estimated to have direct effects in terms of averted cases and might provide an underlying indirect benefit to the general population. Vaccination coverage in high-coverage areas should be further expanded to avert more influenza cases.

Whole brain atlas-based diffusion kurtosis imaging parameters for the evaluation of multiple cognitive-related brain microstructure injuries after radiotherapy in lung cancer patients with brain metastasis.

Background: Whole brain radiation therapy (WBRT) can cause cognitive dysfunctions in lung cancer patients with brain metastasis (BM). Diffusion kurtosis imaging (DKI) can detect brain microstructural alterations sensitivly. We aimed to identify the potential of DKI parameters for early radiation-induced brain injury and investigate the association between microstructure changes and neurocognitive function (NCF) decline. Methods: Lung cancer patients with BM (n=35) who underwent WBRT in a single center in Zhejiang, China, were consecutively and prospectively enrolled between June 24th, 2020 and December 22nd, 2021, and the median follow-up time was 6.0 months (3.6-6.6 months). DKI and T1-weighted (T1W) MRI scans were acquired prior to and following WBRT. Diffusivity-based (mean diffusivity, MD; fractional anisotropy, FA) and kurtosis-based (mean kurtosis, MK; axial kurtosis, AK) parameters were calculated within the automated anatomical labeling (AAL) atlas-based regions. Reliable change indices practice effects (RCI-PE) scores of the Mini-Mental State Examination (MMSE) were calculated to determine significant neurocognitive decline by a one-sample t-test from baseline to 2-6 months post-WBRT. To assess the subacute induced effects within the whole brain, percentage changes of DKI parameters were evaluated at 170 atlas-based regions by a one-sample t-test. Linear regression analyses were used to evaluate the association between DKI parameter changes and RCI-PE scores. Results: Finally, the study included 19 patients in the longitudinal follow-up. RCI-PE scores declined at 2-6 months post-WBRT (mean RCI-PE =-0.842, 95% CI, -0.376 to -1.310; P=0.002). With the atlas-based analysis of subacute effects after post-WBRT, a total of 28 regions changed in at least one diffusion parameter, revealing region-wise microstructural alterations in the brain. Significant correlations of at least one diffusion parameters with RCI-PEs were observed in 9 regions, such as the right orbital part of the inferior frontal gyrus [right IFGorb, r(AK) =0.47, P=0.03] and left middle temporal gyrus [left MTG, r(MK) =-0.49, P=0.03]. Conclusions: DKI parameters can be used to detect early microstructure changes and represent important imaging predictors for cognitive decline. The reported 9 regions are more particularly vulnerable to neurocognitive radiation-induced impairment for lung cancer patients with BM, representing potential dose-avoidance targets for cognitive function preservation.

Hypovirus infection induces proliferation and perturbs functions of mitochondria in the chestnut blight fungus.

Introduction: The chestnut blight fungus, Cryphonectria parasitica, and hypovirus have been used as a model to probe the mechanism of virulence and regulation of traits important to the host fungus. Previous studies have indicated that mitochondria could be the primary target of the hypovirus. Methods: In this study, we report a comprehensive and comparative study comprising mitochondrion quantification, reactive oxygen species (ROS) and respiratory efficiency, and quantitative mitochondrial proteomics of the wild-type and virus-infected strains of the chestnut blight fungus. Results and discussion: Our data show that hypovirus infection increases the total number of mitochondria, lowers the general ROS level, and increases mitochondrial respiratory efficiency. Quantification of mitochondrial proteomes revealed that a set of proteins functioning in energy metabolism and mitochondrial morphogenesis, as well as virulence, were regulated by the virus. In addition, two viral proteins, p29 and p48, were found to co-fractionate with the mitochondrial membrane and matrix. These results suggest that hypovirus perturbs the host mitochondrial functions to result in hypovirulence.

Membrane Protein Bcest Is Involved in Hyphal Growth, Virulence and Stress Tolerance of Botrytis cinerea.

Botrytis cinerea is a necrotrophic model fungal plant pathogen that causes grey mould, a devastating disease responsible for large losses in the agriculture sector. As important targets of fungicides, membrane proteins are hot spots in the research and development of fungicide products. We previously found that membrane protein Bcest may be closely related to the pathogenicity of Botrytis cinerea. Herein, we further explored its function. We generated and characterised ΔBcest deletion mutants of B. cinerea and constructed complemented strains. The ΔBcest deletion mutants exhibited reduced conidia germination and germ tube elongation. The functional activity of ΔBcest deletion mutants was investigated by reduced necrotic colonisation of B. cinerea on grapevine fruits and leaves. Targeted deletion of Bcest also blocked several phenotypic defects in aspects of mycelial growth, conidiation and virulence. All phenotypic defects were restored by targeted-gene complementation. The role of Bcest in pathogenicity was also supported by reverse-transcriptase real-time quantitative PCR results indicating that melanin synthesis gene Bcpks13 and virulence factor Bccdc14 were significantly downregulated in the early infection stage of the ΔBcest strain. Taken together, these results suggest that Bcest plays important roles in the regulation of various cellular processes in B. cinerea.

Radiomics for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Prospective Observational Trial.

(1) Background: An increasing amount of research has supported the role of radiomics for predicting pathological complete response (pCR) to neoadjuvant chemoradiation treatment (nCRT) in order to provide better management of locally advanced rectal cancer (LARC) patients. However, the lack of validation from prospective trials has hindered the clinical adoption of such studies. The purpose of this study is to validate a radiomics model for pCR assessment in a prospective trial to provide informative insight into radiomics validation. (2) Methods: This study involved a retrospective cohort of 147 consecutive patients for the development/validation of a radiomics model, and a prospective cohort of 77 patients from two institutions to test its generalization. The model was constructed using T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI to understand the associations with pCR. The consistency of physicians' evaluations and agreement on pathological complete response prediction were also evaluated, with and without the aid of the radiomics model. (3) Results: The radiomics model outperformed both physicians' visual assessments in the prospective test cohort, with an area under the curve (AUC) of 0.84 (95% confidence interval of 0.70-0.94). With the aid of the radiomics model, a junior physician could achieve comparable performance as a senior oncologist. (4) Conclusion: We have built and validated a radiomics model with pretreatment MRI for pCR prediction of LARC patients undergoing nCRT.

Comprehensive Analysis of Diabetes Mellitus-related Gene Expression and Associated Prognoses in Human Lung Cancer.

INTRODUCTION: Diabetes mellitus (DM) is a major public health problem worldwide. Cancer is the second most common cause of death in the United States and the leading cause of death in China. There is compelling evidence that individual risk for type 2 diabetes mellitus (T2DM) is strongly influenced by genetic factors. DM and cancer may interact with one another; some kinds of cancer accompany DM, and DM can also promote cancer. METHODS: An analysis was conducted of diabetes mellitus-related gene (DM-gene) expression levels in tumor and normal tissues, clinical parameters, tumor stages, mutations, copy number variations (CNVs), immune cell infiltration, survival, gene enrichment, and gene ontology annotations. RESULTS: This analysis revealed six genes that appear to play key roles in lung cancer survival: MTMR3 (in lung adenocarcinoma [LUAD]) and COBLL1, PPARG, PPIP5K2, RREB1, and WFS1 (in lung squamous cell carcinoma [LUSC]). CONCLUSION: The results suggested that clinical practitioners and researchers should account for PPARG and RREB1 expression when selecting or testing chemotherapy drugs.

Enhancing wuyiencin productivity of Streptomyces albulus (CK15) by mutagenesis breeding with atmospheric and room temperature plasma.

Streptomyces species are known for their ability to efficiently produce secondary metabolites, including various antibiotics. Wuyiencin, an antibiotic produced by Streptomyces albulus CK15, is commonly used in agriculture to control fungal diseases in crops and vegetables. In this study, we utilized atmospheric and room temperature plasma (ARTP) mutagenesis to generate mutant S. albulus strains with improved fermentation capabilities for wuyiencin production. After mutagenizing the wild-type S. albulus CK15 strain once and conducting two rounds of antimicrobial screening, three genetically stable mutants (M19, M26, and M28) were identified. These mutants showed increased wuyiencin production by 17.4%, 13.6%, and 18.5% in comparison to the CK15 strain in flask culture, respectively. The M28 mutant exhibited the highest wuyiencin activity, producing 1443.0 ± 134.6 U/mL in flask culture and 1673.8 ± 127.4 U/mL in a 5 L fermenter. These results demonstrate that ARTP is an efficient tool for microbial mutation breeding and improving wuyiencin production.

Identification of a novel adjuvant loperamide that enhances the antibacterial activity of colistin against MCR-1-positive pathogens in vitro/vivo.

Severe infection with multidrug-resistant Enterobacterales caused by the plasmid-induced colistin resistance gene MCR-1 is a serious public health challenge. In this case, it is necessary and pressing to find a treatment to overcome antibiotic resistance. Here, we investigated the synergistic effect and mechanism of loperamide combined with colistin against MCR-1-positive pathogens. We evaluated the combined effect of loperamide and colistin using the checkerboard method and the time-kill experiment. The results showed that loperamide could enhance the bactericidal ability of colistin, and this combination regimen could completely kill the tested bacteria within 4 h. Subsequently, spectrofluorimetric methods were used to explore the mechanism of loperamide combined with colistin. The results indicated that the mode of action of loperamide combined with colistin was found to involve mechanical disruption of the membrane. Furthermore, molecular simulation and microscale thermophoresis results revealed that loperamide reduced the impact of MCR-1 protein by directly binding to its active site. In addition, the combined regimen of loperamide and colistin effectively reduced the bacterial load in the thighs of mice while increasing the protection rate by 70%. In short, as a potential lead compound, loperamide can enhance the killing effect of colistin on pathogenic Enterobacterales carrying MCR-1 by causing membrane damage and inhibiting MCR-1 protein activity.

Nonintrusive wind blade fault detection using a deep learning approach by exploring acoustic information.

Various physical characteristics, including ultrasonic waves, active acoustic emissions, vibrations, and thermal imaging, have been used for blade fault detection. In this work, we propose using the sound produced by spinning wind blades to identify faults. To the best of our knowledge, passive acoustic information has not yet been explored for this task. In particular, we develop three networks targeting different scenarios. The main contributions of this work are threefold. First, when normal and aberrant data are available for supervised learning, an attention-convolutional recurrent neural network is designed to show the feasibility of using passive sound information to conduct fault detection. Second, in the absence of abnormal training data, we build a normal-encoder network to learn the distributions of normal data through semisupervised learning, which avoids the requirement of abnormal training data. Third, when multiple devices are used to collect the data, due to different properties of devices, there is a domain mismatch issue. To overcome this, we create an adversarial domain adaptive network to close the gap between the source and target domains. Acoustic signal datasets of actual wind turbine operations are collected to evaluate our fault detection systems. The findings demonstrate that the proposed systems offer high classification accuracy and indicate the feasibility of passive acoustic signal-based wind turbine blade fault detection with one step close to automatic detection.

The trace that is valuable: serum copper and copper to zinc ratio for survival prediction in younger patients with newly diagnosed acute myeloid leukaemia.

PURPOSE: No data on predicting the survival of AML patients based on the level of trace elements in the serum have been presented to date. The aims of this prospective cohort study were as follows: (i) to evaluate the serum Cu and Zn levels in people from Northeast China, (ii) to assess the association between the serum Cu level (SCL) and Cu to Zn ratio (SCZR) and clinical and nutrition data, and (iii) to investigate the predictive values of the SCL and SCZR in newly diagnosed de novo AML patients. METHODS: A total of 105 newly diagnosed AML patients and 82 healthy controls were recruited. The serum Cu and Zn levels were determined by inductively coupled plasma spectrometry. The associations of SCL and SCZR with the survival of these AML patients were assessed by Cox proportional hazards models. RESULTS: Both SCL and SCZR were positively related to the blast percentage of bone marrow and C-reactive protein, negatively related to albumin level and CEBPA double mutation and were significantly associated with worse overall survival and disease-free survival. Meanwhile, patients with higher SCL had worse CTCAE levels, and patients with higher SCZR showed less complete remission during the first course of induction chemotherapy. Moreover, higher SCZR was positively associated with ELN risk stratification, and was negatively associated with haemoglobin level and prognostic nutritional index (PNI). CONCLUSION: The SCL and SCZR are associated with long-term survival in patients with newly diagnosed AML undergoing intensive induction and may serve as important predictive biomarkers.

A multi-criteria analysis framework for water transfers to improve the water environments under strong artificial interventions in highly urbanized areas.

Water transfer is an effective measure to enhance hydrodynamic and water quality in highly urbanized areas. The effect of water transfer in highly urbanized areas is affected by strong artificial interventions, and it is difficult to evaluate the improvement of multiple indicators of many sections after water transfer. At present, there is no analysis framework directly evaluates the improvement of water environment under strong artificial interventions, making it difficult to determine the optimal scheduling of hydraulic projects. This study constructed a multi-criteria analysis framework for evaluating the improvement of water environment including index layers of water quality improvement, hydrodynamic improvement and economic cost, and designed corresponding element layers for each index layer. The weights of each element were determined based on fuzzy analytical hierarchy process, and the fuzzy comprehensive evaluation method was used for comprehensive evaluation. The framework was applied in Xishan District in highly urbanized Taihu Lake Basin, and the results showed that the proposed framework could effectively determine the optimal scheduling of hydraulic projects. Water quality compliance rate for the optimal water transfer scheme achieved in Xishan District was 82%, average rate of water quality improvement was 31%, and proportion of cross-sections meeting the Class III water quality standard was 61%. Average flow velocity was 0.10 m/s, proportion of the optimal velocity was 39%, and proportion of stagnant sections was 32%. Furthermore, the impact of regional control projects on the effect of water transfer was much greater than local projects, consequently, the best scheduling mode for regional control projects should be first determined, and then the scheduling combination for local projects. This study can provide a new framework for the assessment of water transfers to improve the water environments and a scientific basis for the dispatching of hydraulic projects in Taihu Lake Basin.

Induced Defense Response in Soybean to Sclerotinia sclerotiorum Using Wuyiencin from Streptomyces albulus CK-15.

Sclerotinia sclerotiorum (Lib) de Bary, a destructive fungal pathogen with an extensive host range, causes major economic losses to crop production activities globally. Streptomyces spp. produce secondary metabolites with diverse structures and biological activities with potential applications in the control of crop disease. This study explored the potential application of wuyiencin, a secondary metabolite of Streptomyces albulus CK-15, to induce defense responses in soybean against S. sclerotiorum. Lesion size was reduced by nearly 60% in wuyiencin-treated soybean plants compared with plants infected with S. sclerotiorum only in greenhouse experiments. Wuyiencin induced callose deposition at 6 h postinoculation and increased reactive-oxygen-scavenging enzyme activities, including superoxide dismutase, catalase, and peroxidase. Moreover, wuyiencin inoculated before S. sclerotiorum infection significantly increased polyphenol oxidase, phenylalanine ammonia lyase, chitinase, and ß-1,3-glucanase activity, suggesting their involvement in soybean defense responses to S. sclerotiorum. Further, qRT-PCR results showed expression levels of the hormone signaling markers CO11, MYC2, PR4, PR1, NPR1, and ERF1 were upregulated in infected leaves treated with wuyiencin.

Machine Learning for Predicting Hyperglycemic Cases Induced by PD-1/PD-L1 Inhibitors.

Objective: Immune checkpoint inhibitors, such as programmed death-1/ligand-1 (PD-1/L1), exhibited autoimmune-like disorders, and hyperglycemia was on the top of grade 3 or higher immune-related adverse events. Machine learning is a model from past data for future data prediction. From post-marketing monitoring, we aimed to construct a machine learning algorithm to efficiently and rapidly predict hyperglycemic adverse reaction in patients using PD-1/L1 inhibitors. Methods: In original data downloaded from Food and Drug Administration Adverse Event Reporting System (US FAERS), a multivariate pattern classification of support vector machine (SVM) was used to construct a classifier to separate adverse hyperglycemic reaction patients. With correct core SVM function, a 10-fold 3-time cross validation optimized parameter value composition in model setup with R language software. Results: The SVM prediction model was set up from the number type/number optimization method, as well as the kernel and type of "rbf" and "nu-regression" composition. Two key values (nu and gamma) and case number displayed high adjusted r 2 in curve regressions (nu = 0.5649 × e (- (case/6984)), gamma = 9.005 × 10-4 × case - 4.877 × 10-8 × case2). This SVM model with computable parameters greatly improved the assessing indexes (accuracy, F1 score, and kappa) as well as coequal sensitivity and the area under the curve (AUC). Conclusion: We constructed an effective machine learning model based on compositions of exact kernels and computable parameters; the SVM prediction model can noninvasively and precisely predict hyperglycemic adverse drug reaction (ADR) in patients treated with PD-1/L1 inhibitors, which could greatly help clinical practitioners to identify high-risk patients and perform preventive measurements in time. Besides, this model setup process provided an analytic conception for promotion to other ADR prediction, such ADR information is vital for outcome improvement by identifying high-risk patients, and this machine learning algorithm can eventually add value to clinical decision making.

Effects of ε-Poly-L-Lysine Combined with Wuyiencin as a Bio-Fungicide against Botryris cinerea.

This study mainly evaluated the broad-spectrum fungicidal activity of ε-poly L lysine (ε-PL) against 12 pathogenic fungi. We further demonstrated synergistic antifungal activity of ε-PL combined with wuyiencin against Botryris cinerea. The combined bio-fungicide achieved an inhibition rate of 100% for mycelial growth using ε-PL at 500 µg/mL + wuyiencin at 50 µg/mL and for spore germination using ε-PL at 200 µg/mL + wuyiencin at 80 µg/mL in vitro. This synergistic spore and mycelia-damaging effect of the combination was confirmed using scanning electron microscopy. In vivo assays with combined bio-fungicide (1500 µg/mL ε-PL + 60 µg/mL wuyiencin) on detached leaves showed depressed growth and development of the spores of B. cinerea. The synergistic effect was further tested in combinations of ε-PL with wuyiencin by measuring the fractional inhibition concentration index (FICI) value below 0.5. Moreover, ε-PL and wuyiencin inoculation before B. cinerea infection significantly increased the superoxide dismutase, peroxidase, catalase, and phenylalanine ammonia-lyase activities, which suggested their involvement in tomato defense responses to disease to minimize damage to B. cinerea. These findings revealed that a combined bio-fungicide comprising ε-PL and wuyiencin had a good prospect for controlling plant fungal disease.

Effect of toyF on wuyiencin and toyocamycin production by Streptomyces albulus CK-15.

Streptomyces albulus CK-15 produces various secondary metabolites, including the antibiotics wuyiencin and toyocamycin, which can reportedly control a broad range of plant fungal diseases. The production of these nucleoside antibiotics in CK-15 is regulated by two biosynthesis gene clusters. To investigate the potential effect of toyocamycin biosynthesis on wuyiencin production, we herein generated S. albulus strains in which a key gene in the toyocamycin biosynthesis gene cluster, namely toyF, was either deleted or overexpressed. The toyF deletion mutant ∆toyF did not produce toyocamycin, while the production of wuyiencin increased by 23.06% in comparison with that in the wild-type (WT) strain. In addition, ΔtoyF reached the highest production level of wuyiencin 4 h faster than the WT strain (60 h vs. and 64 h). Further, toyocamycin production by the toyF overexpression strain was two-fold higher than by the WT strain, while wuyiencin production was reduced by 29.10%. qRT-PCR showed that most genes in the toyocamycin biosynthesis gene cluster were expressed at lower levels in ∆toyF as compared with those in the WT strain, while the expression levels of genes in the wuyiencin biosynthesis gene cluster were upregulated. Finally, the growth rate of ∆toyF was much faster than that of the WT strain when cultured on solid or liquid medium. Based on our findings, we report that in industrial fermentation processes, ∆toyF has the potential to increase the production of wuyiencin and reduce the timeframe of fermentation.

Metagenomics revealed the mobility and hosts of antibiotic resistance genes in typical pesticide wastewater treatment plants.

Pesticide showed a crucial selective pressure of antibiotic resistance genes (ARGs) in the environmental dimension, especially in the pesticide wastewater treatment process, where the information on the mobility and hosts of ARGs was very important but limited. This study tried to clarify the mobile antibiotic resistome and ARG hosts in three typical pesticide wastewater treatment plants (PWWTPs) through metagenomics. Results showed that ARGs associated with antibiotic efflux and multi-drug resistance generally dominated in the PWWTPs, and the relative abundance of ARGs was generally higher in the water phase than that in sludge phase. The mobile antibiotic resistome accounted for 43.6% ± 16.2% and 44.8% ± 18.0% of the total relative abundance of ARGs in the water phase and sludge phase, respectively. The tnpA, IS91 and intI1 were the dominant mobile genetic elements (MGEs) closely associated with ARGs. MCR-5 and MCR-9 were first identified in the PWWTPs and located together with the tnpA, tnpA2 and int2. The potential human pathogens belonging to Citrobacter, Pseudomonas, Enterobacter, Acinetobacter, and Kluyvern were the major ARG hosts in the PWWTPs. Statistical analysis indicated that microbial community contributed the most to the occurrence of antibiotic resistome, and the reduction of the major ARG hosts was crucial from the perspective of ARGs control.