Comparative metabolomics combined with genome sequencing provides insights into novel wolfberry-specific metabolites and their formation mechanisms.

Wolfberry (Lycium, of the family Solanaceae) has special nutritional benefits due to its valuable metabolites. Here, 16 wolfberry-specific metabolites were identified by comparing the metabolome of wolfberry with those of six species, including maize, rice, wheat, soybean, tomato and grape. The copy numbers of the riboflavin and phenyllactate degradation genes riboflavin kinase (RFK) and phenyllactate UDP-glycosyltransferase (UGT1) were lower in wolfberry than in other species, while the copy number of the phenyllactate synthesis gene hydroxyphenyl-pyruvate reductase (HPPR) was higher in wolfberry, suggesting that the copy number variation of these genes among species may be the main reason for the specific accumulation of riboflavin and phenyllactate in wolfberry. Moreover, the metabolome-based neighbor-joining tree revealed distinct clustering of monocots and dicots, suggesting that metabolites could reflect the evolutionary relationship among those species. Taken together, we identified 16 specific metabolites in wolfberry and provided new insight into the accumulation mechanism of species-specific metabolites at the genomic level.

OsBCAT2, a gene responsible for the degradation of branched-chain amino acids, positively regulates salt tolerance by promoting the synthesis of vitamin B5.

Salt stress negatively affects rice growth, development and yield. Metabolic adjustments contribute to the adaptation of rice under salt stress. Branched-chain amino acids (BCAA) are three essential amino acids that cannot be synthesized by humans or animals. However, little is known about the role of BCAA in response to salt stress in plants. Here, we showed that BCAAs may function as scavengers of reactive oxygen species (ROS) to provide protection against damage caused by salinity. We determined that branched-chain aminotransferase 2 (OsBCAT2), a protein responsible for the degradation of BCAA, positively regulates salt tolerance. Salt significantly induces the expression of OsBCAT2 rather than BCAA synthesis genes, which indicated that salt mainly promotes BCAA degradation and not de novo synthesis. Metabolomics analysis revealed that vitamin B5 (VB5) biosynthesis pathway intermediates were higher in the OsBCAT2-overexpressing plants but lower in osbcat2 mutants under salt stress. The salt stress-sensitive phenotypes of the osbcat2 mutants are rescued by exogenous VB5, indicating that OsBCAT2 affects rice salt tolerance by regulating VB5 synthesis. Our work provides new insights into the enzymes involved in BCAAs degradation and VB5 biosynthesis and sheds light on the molecular mechanism of BCAAs in response to salt stress.

Integrated Metabolome and Transcriptome during Fruit Development Reveal Metabolic Differences and Molecular Basis between Lycium barbarum and Lycium ruthenicum.

Wolfberry (Lycium barbarum) is a traditional cash crop in China and is well-known worldwide for its outstanding nutritional and medicinal value. Lycium ruthenicum is a close relative of Lycium barbarum but differs significantly in size, color, flavor and nutritional composition. To date, the metabolic differences between the fruits of the two wolfberry varieties and the genetic basis behind them are unclear. Here, we compared metabolome and transcriptome data of two kinds of wolfberry fruits at five stages of development. Metabolome results show that amino acids, vitamins and flavonoids had the same accumulation pattern in various developmental stages of fruit but that Lycium ruthenicum accumulated more metabolites than Lycium barbarum during the same developmental stage, including L-glutamate, L-proline, L-serine, abscisic acid (ABA), sucrose, thiamine, naringenin and quercetin. Based on the metabolite and gene networks, many key genes that may be involved in the flavonoid synthesis pathway in wolfberry were identified, including PAL, C4H, 4CL, CHS, CHI, F3H, F3'H and FLS. The expression of these genes was significantly higher in Lycium ruthenicum than in Lycium barbarum, indicating that the difference in the expression of these genes was the main reason for the variation in flavonoid accumulation between Lycium barbarum and Lycium ruthenicum. Taken together, our results reveal the genetic basis of the difference in metabolomics between Lycium barbarum and Lycium ruthenicum and provide new insights into the flavonoid synthesis of wolfberry.

tRF-Gln-CTG-026 ameliorates liver injury by alleviating global protein synthesis.

tsRNAs (tRNA-derived small RNAs), as products of the stress response, exert considerable influence on stress response and injury regulation. However, it remains largely unclear whether tsRNAs can ameliorate liver injury. Here, we demonstrate the roles of tsRNAs in alleviating liver injury by utilizing the loss of NSun2 (NOP2/Sun domain family, member 2) as a tsRNAs-generating model. Mechanistically, the loss of NSun2 reduces methyluridine-U5 (m5U) and cytosine-C5 (m5C) of tRNAs, followed by the production of various tsRNAs, especially Class I tsRNAs (tRF-1s). Through further screening, we show that tRF-Gln-CTG-026 (tG026), the optimal tRF-1, ameliorates liver injury by repressing global protein synthesis through the weakened association between TSR1 (pre-rRNA-processing protein TSR1 homolog) and pre-40S ribosome. This study indicates the potential of tsRNA-reduced global protein synthesis in liver injury and repair, suggesting a potential therapeutic strategy for liver injury.

Temporal-spatial evolution analysis of severe traffic violations using three functional forms of models considering the diurnal variation of meteorology.

Traffic violations and crashes are inherently associated. Analysis of traffic violation frequency is a prerequisite for improvements in crash prevention and corresponding countermeasures. One of the essential works in the field of traffic violations relates to the exploration of the correlations between a certain violation type (e.g., speeding or safety belt use) and its causal factors (e.g., demographics and road types). Till now, the effects of spatiotemporal and meteorological factors on severe traffic violations, a general term for dangerous driving behaviors, have not been fully considered. Using the dataset consisting of daily severe traffic violations and meteorological conditions during 12 months in Jiangsu Province, China, violation performance functions were developed for three violation types (total violations, driving under the influence, and speeding) based on three models (Poisson regression, zero-inflated Poisson regression, and negative binomial model). The findings indicate that the negative binomial model has a better performance for traffic violation frequency estimation. Additionally, elastic analysis for three violation types relying on the negative binomial model was conducted to present the relationships between the explanatory variables and the expected violation frequency. The effects of spatiotemporal factors have revealed that the violation situations are significantly different in varying cities and the frequency of drunk driving shows a significant time instability. It is also found that rainy days will generate a decrease in the possibility of violation occurrence. With regard to temperature, a significant negative effect is found and the decrease in temperature will bring about an increase in violation frequency. Besides, traffic violation frequency is significantly increased during holidays with comfortable weather conditions. The conclusion of this study can provide insightful suggestions for the department of traffic enforcement to adjust the patrol plans according to the specified periods (weeks, months, or holidays) and weather conditions. Special rectification actions and targeted educational activities are also advised to be put forward simultaneously.

Lactate Dehydrogenase B Is Required for Pancreatic Cancer Cell Immortalization Through Activation of Telomerase Activity.

Telomerase activity is elevated in most cancer cells and is required for telomere length maintenance and immortalization of cancer cells. Glucose metabolic reprogramming is a hallmark of cancer and accompanied with increased expression of key metabolic enzymes. Whether these enzymes influence telomerase activity and cell immortalization remains unclear. In the current study, we screened metabolic enzymes using telomerase activity assay and identified lactate dehydrogenase B (LDHB) as a regulator of telomerase activity. Sodium lactate and sodium pyruvate did not influence telomerase activity, indicating LDHB regulates telomerase activity independent of its metabolism regulating function. Further studies revealed that LDHB directly interacted with TERT and regulated the interaction between TERT and TERC. Additionally, long-term knockdown of LDHB inhibited cancer cell growth and induced cell senescence in vitro and in vivo. Higher LDHB expression was detected in pancreatic cancer tissues compared with that in adjacent normal tissues and expression of LDHB correlated negatively with prognosis. Thus, we identified LDHB as the first glucose metabolic enzyme contributing to telomerase activity and pancreatic cancer cell immortalization.

Modeling the temporal relationship between contributing factors and injury severities in rural single-vehicle alcohol-impaired driving crashes: Insights from random parameters logit models in the means and variances.

OBJECTIVES: Alcohol-impaired driving (A-ID) crashes have been acknowledged as fatality-concentrated while there is a limited understanding of how contributors relating to A-ID influence crash severity and lead to more severe injuries in rural areas. The current paper utilized North Carolina crash data to investigate the unobserved heterogeneity and temporal stability of the rural single-vehicle A-ID crash injury-severity determinants over a five-year period from 2014-2018. METHODS: Crash injury severities were estimated using a group of random parameters logit models in the means and variances with three categories of injury-severity determined as outcome variables including no injury, minor injury, and severe injury. Explanatory variables were selected across multiple factors that could be classified as roadway characteristics, environmental characteristics, crash characteristics, temporal characteristics, vehicle characteristics and driver characteristics. The temporal stability of the models was examined through a series of likelihood ratio tests. Marginal effects were also adopted to analyze the temporal stability of the explanatory variables. RESULTS: The result uncovers an overall temporal instability. Some contributors present relatively temporal stability such as female, turning, passenger car, motorcycle, vehicle age (5-9 years old), speed limit (<45 mph), curved segment, dry road surface, animal collision and overturned collision. Curved segment and dry road surface are found to consistently increase the possibility of severe injuries in rural alcohol-involved crashes. CONCLUSIONS: This paper can provide insights into preventing single-vehicle A-ID crashes and could potentially facilitate the development of single-vehicle A-ID crash injury mitigation policies in rural areas. More studies could be conducted adopting the advanced data-driven methods for A-ID crash prediction.

A Proactive Recognition System for Detecting Commercial Vehicle Driver's Distracted Behavior.

Road traffic accidents regarding commercial vehicles have been demonstrated as an important culprit restricting the steady development of the social economy, which are closely related to the distracted behavior of drivers. However, the existing driver's distracted behavior surveillance systems for monitoring and preventing the distracted behavior of drivers still have some shortcomings such as fewer recognition objects and scenarios. This study aims to provide a more comprehensive methodological framework to demonstrate the significance of enlarging the recognition objects, scenarios and types of the existing driver's distracted behavior recognition systems. The driver's posture characteristics were primarily analyzed to provide the basis of the subsequent modeling. Five CNN sub-models were established for different posture categories and to improve the efficiency of recognition, accompanied by a holistic multi-cascaded CNN framework. To suggest the best model, image data sets of commercial vehicle driver postures including 117,410 daytime images and 60,480 night images were trained and tested. The findings demonstrate that compared to the non-cascaded models, both daytime and night cascaded models show better performance. Besides, the night models exhibit worse accuracy and better speed relative to their daytime model counterparts for both non-cascaded and cascaded models. This study could be used to develop countermeasures to improve driver safety and provide helpful information for the design of the driver's real-time monitoring and warning system as well as the automatic driving system. Future research could be implemented to combine the vehicle state parameters with the driver's microscopic behavior to establish a more comprehensive proactive surveillance system.

Complement receptor 3 mediates Aspergillus fumigatus internalization into alveolar epithelial cells with the increase of intracellular phosphatidic acid by activating FAK.

Complement receptor 3 (CD11b/CD18) is an important receptor that mediates adhesion, phagocytosis and chemotaxis in various immunocytes. The conidia of the medically-important pathogenic fungus, Aspergillus fumigatus can be internalized into alveolar epithelial cells to disseminate its infection in immunocompromised host; however, the role of CR3 in this process is poorly understood. In the present study, we investigated the potential role of CR3 on A. fumigatus internalization into type II alveolar epithelial cells and its effect on host intracellular PA content induced by A. fumigatus. We found that CR3 is expressed in alveolar epithelial cells and that human serum and bronchoalveolar lavage fluid (BALF) could improve A. fumigatus conidial internalization into A549 type II alveolar epithelial cell line and mouse primary alveolar epithelial cells, which were significantly inhibited by the complement C3 quencher and CD11b-blocking antibody. Serum-opsonization of swollen conidia, but not resting conidia led to the increase of cellular phosphatidic acid (PA) in A549 cells during infection. Moreover, both conidial internalization and induced PA production were interfered by CD11b-blocking antibody and dependent on FAK activity, but not Syk in alveolar epithelial cells. Overall, our results revealed that CR3 is a critical modulator of Aspergillus fumigatus internalization into alveolar epithelial cells.

Exploring relationships between microscopic kinetic parameters of tires under normal driving conditions, road characteristics and accident types.

INTRODUCTION: Freeway accidents are a leading cause of death in China, which also triggers substantial economic loss and an emotional burden to society. However, the internal mechanism of how microscopic kinetic parameters of vehicles influenced by road characteristics determine the occurrence of different types of accidents has not been explicitly studied. This research aimed to explore the "link role" of tire microscopic kinetic parameters in road characteristic variables and traffic accidents to aid in facilitating the traffic design and management, and thus to prevent traffic accident. METHOD: A mountain freeway in Zhejiang Province, China was used as the research object and the data used in this paper were obtained through a real-time vehicle experiment. Multiple estimation models, including the standard ordered logit (SOL) model, fixed parameters logit (FPL) model, and random parameters logit (RPL) model were established. RESULTS: The findings show that road characteristics will affect the longitudinal kinetic characteristics of the vehicle and, consequently, map the level of risk of rear-end accidents. Driving compensation effects were also identified in this paper (i.e., the drivers tend to be more cautious in complicated driving circumstances). Another finding relating to the mountain freeway is that different tunnel characteristics (e.g., tunnel entrance and tunnel exit) have different effects on different types of traffic accidents. Practical Applications: The framework proposed in this article can provide new insight for researchers to enlarge the research subjects of both explanatory and outcome variables in accident analysis. Future research could be implemented to consider more driving conditions.

Aspergillus fumigatus Induces the Release of IL-8 and MCP-1 by Activating Nuclear Transcription Through Dectin-1 and CR3 Receptors in Alveolar Epithelial Cells.

Invasive pulmonary aspergillosis induced by the pathogenic fungus Aspergillus fumigatus is one of the common fatal complications in immunocompromised patients. Lung epithelial cells play an important role in host immune defense against A. fumigatus. However, the interaction between lung epithelial cells and A. fumigatus conidia is not fully understood. In this study, we used the swollen conidia of A. fumigatus to stimulate the type II lung epithelial A549 cells. Results showed that swollen conidia could significantly increase RNA transcription and protein expression of interleukin 8 (IL-8) and monocyte chemoattractant protein 1 (MCP-1), but not TNF-α in A549 cells in a time-dependent manner. Moreover, serum opsonization was able to improve the release of inflammatory factors induced by swollen conidia. Blocking of the dectin-1 or CR3 receptors, or both simultaneously, in the A549 cells could decrease the release of IL-8 and MCP-1. Additionally, blocking dectin-1 or CR3 could inhibit the transcription of nuclear factor NF-κB that was activated by swollen conidia. Here we reported for the first time that dectin-1 and CR3 receptors in A549 cells mediate the release of pro-inflammatory factors IL-8 and MCP-1 induced by A. fumigatus.

Assessing emission reduction effects from shifts of urban passenger transport modes by implementing targeted emission tax considering the whole fuel cycle.

Controlling the emission of urban passenger transport modes has become one of the most important tasks of governing urban air pollution. Most strategies only focused on carbon emission, whereas neglecting the influences of other pollutants (CO, HC, NOx, PM2.5), especially for upstream emissions from electricity generation caused by the electricity consumed during the operation of electrified transport modes. Based on the multinomial logit model (MNL), this study firstly calculated and evaluated the emission reduction effects brought about by the implementation of targeted emission taxes on different transport modes from the perspective of whole fuel cycle. Taking Jiangning District as an example, our research found that the policy implementing targeted emission tax for different transport modes can not only bring reduce 13.104 tons of CO, 0.327 tons of HC, 0.568 tons of NOx, and 0.140 tons of PM2.5, but also 26,726.82 (euro) of eco-environmental benefits for the treatment of air pollution. Our study can provide useful insights for shifting the structure of urban passenger transport modes, especially promoting the transfer of private cars to the urban green transport systems, to alleviate urban air pollution by formulating effective emission reduction strategies.

Single-vehicle crash severity outcome prediction and determinant extraction using tree-based and other non-parametric models.

Single-vehicle crashes are more fatality-concentrated and have posed increasing challenges in traffic safety, which is of great research necessity. Tremendous previous studies have conducted relevant analysis with econometric modeling approaches, whereas the ability of non-parametric methods to predict crash severity is still smattering of knowledge. Consequently, the main objective of this paper is to conduct single-vehicle crash severity prediction with different tree-based and non-parameter models. An alternate aim is to identify the intrinsic mechanism of how contributing factors determine single-vehicle crash severity. By virtue of Grid-Search method, this paper conducted fine-tuning of different models to obtain the best performances based on five crash severity sub-datasets. For model evaluation, the accuracy indicators were calculated in training, validation and test sets, respectively. Besides, feature importance extraction was undertaken based on the results of model comparison. The finding indicated that these models didn't exhibit a huge performance difference for crash severity prediction in the same severity level; however, the performances of the models did vary among different datasets, with an average training accuracy of 99.27 %, 96.4 %, 86.98 %, 86.84 %, 71.76 % in fatal injury, severe injury, visible injury, complaint of pain, PDO crash datasets, respectively. Additionally, it was found that in each severity dataset, the indicator urban freeways is a determinant factor that leads to the occurrence of crashes while rural freeways is more related to more severe crashes (i.e., fatal and severe crashes). This paper can provide valuable information for model selection and tuning in accident severity prediction. Future research could consider the influences that temporal instability of contributing features has on the model performances.

Effect of Dose Ratio on Mitoxantrone and Daunorubicin in Acute Myeloid Leukemia: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

PURPOSE: To investigate the effects of mitoxantrone and daunorubicin in induced chemotherapy on complete remission (CR), death during induction therapy, overall survival (OS), disease-free survival (DFS), and relapse in patients of all ages with acute myeloid leukemia (AML). METHODS: We searched published reports at the Medline, Embase, and Cochrane Databases as well as other databases from inception through July 2019. There was no restriction on date of publication or language (PROSPERO registration CRD42018095843). RESULTS: We enrolled 12 randomized controlled trials that included data of 4583 AML patients whose disease was untreated or relapsed/refractory, and compared the CR, death during induction therapy, DFS, and OS between mitoxantrone and daunorubicin. Mitoxantrone significantly increased the CR rate (relative risk = 1.07; 95% confidence interval [CI], 1.01, 1.14; P = .03) and DFS (hazard ratio = 0.87; 95% CI, 0.79, 0.96; P = .005) compared to daunorubicin. However, there was no significant difference in death during induction therapy (relative risk = 1.00; 95% CI, 0.81, 1.24; P = .99) and OS (hazard ratio = 0.94; 95% CI, 0.87, 1.01; P = .077) between the two drugs. CONCLUSION: Although more studies are needed to compare mitoxantrone with higher-dose daunorubicin, the results showed that compared to daunorubicin, mitoxantrone can significantly improve CR and DFS in patients of all ages. These findings suggest that mitoxantrone may be a better choice than daunorubicin as an induction chemotherapy agent for AML patients, especially in developing countries.

A crash risk identification method for freeway segments with horizontal curvature based on real-time vehicle kinetic response.

With the development and maturation of vehicle-based data acquisition technology, in-vehicle data is increasingly being used to explore road safety. This paper reports on research that analyzed the real-time tire force data (kinetic response) obtained from vehicle kinetic experiments, and constructed a new approach for identifying the high-risk of crashes on freeway segments with horizontal curvature. First, the road was divided into 1km units. Then, taking into account the characteristics of freeway alignment, each segment with horizontal curve was selected as the object of subsequent analysis. Automotive instrumentation was used to obtain a measure of tire force in the course of normal driving. The entire data set was preprocessed according to rate of change and the density of the data was reduced. By defining the outliers of the kinetic data and conducting factor analysis, two representative crash risk indicators of longitudinal and lateral stability were obtained. Negative binomial regression model (NBR model) and random effects negative binomial regression model (RENBR model) were constructed and jointly applied based on the new indicators to predict the risk value of horizontal curve segments. The method showed good prediction performance (71.8 %) for high-risk road segments with design flaws, but the predicted effect for low-risk road segments was not ideal. This study not only illustrated the effectiveness of in-vehicle data in assessing road crash risk by coupling multiple kinetic parameters, but also provided support for freeway safety research using surrogate measures of risk when there is a lack of crash statistics.

Video Summarization Based on Mutual Information and Entropy Sliding Window Method.

This paper proposes a video summarization algorithm called the Mutual Information and Entropy based adaptive Sliding Window (MIESW) method, which is specifically for the static summary of gesture videos. Considering that gesture videos usually have uncertain transition postures and unclear movement boundaries or inexplicable frames, we propose a three-step method where the first step involves browsing a video, the second step applies the MIESW method to select candidate key frames, and the third step removes most redundant key frames. In detail, the first step is to convert the video into a sequence of frames and adjust the size of the frames. In the second step, a key frame extraction algorithm named MIESW is executed. The inter-frame mutual information value is used as a metric to adaptively adjust the size of the sliding window to group similar content of the video. Then, based on the entropy value of the frame and the average mutual information value of the frame group, the threshold method is applied to optimize the grouping, and the key frames are extracted. In the third step, speeded up robust features (SURF) analysis is performed to eliminate redundant frames in these candidate key frames. The calculation of Precision, Recall, and Fmeasure are optimized from the perspective of practicality and feasibility. Experiments demonstrate that key frames extracted using our method provide high-quality video summaries and basically cover the main content of the gesture video.

Electron-hole hybridization in bilayer graphene.

Band structure determines the motion of electrons in a solid, giving rise to exotic phenomena when properly engineered. Drawing an analogy between electrons and photons, artificially designed optical lattices indicate the possibility of a similar band modulation effect in graphene systems. Yet due to the fermionic nature of electrons, modulated electronic systems promise far richer categories of behaviors than those found in optical lattices. Here, we uncovered a strong modulation of electronic states in bilayer graphene subject to periodic potentials. We observed for the first time the hybridization of electron and hole sub-bands, resulting in local band gaps at both primary and secondary charge neutrality points. Such hybridization leads to the formation of flat bands, enabling the study of correlated effects in graphene systems. This work may provide a novel way to manipulate electronic states in layered systems, which is important to both fundamental research and application.

Gliotoxin Induces Cofilin Phosphorylation to Promote Actin Cytoskeleton Dynamics and Internalization of Aspergillus fumigatus Into Type II Human Pneumocyte Cells.

Aspergillus fumigatus is able to internalize into lung epithelial cells to escape from immune attack for further dissemination. We previously reported that gliotoxin, a major mycotoxin of A. fumigatus, promotes this internalization; however, the mechanism remained unclear. Here, we report that gliotoxin is able to induce cofilin phosphorylation in A549 type II human pneumocytes. Either too high or too low a level of cofilin phosphorylation blocked the gliotoxin-induced actin cytoskeleton rearrangement and A. fumigatus internalization. LIM domain kinase 1 (LIMK1) and its upstream small GTPases (Cdc42 and RhoA, but not Rac1) predominantly mediated the gliotoxin-induced cofilin phosphorylation and A. fumigatus internalization. Simultaneously, gliotoxin significantly stimulated an increase in cAMP; however, adding an antagonist of PKA did not block gliotoxin-induced A. fumigatus internalization. In vivo, exogenous gliotoxin helped gliotoxin synthesis deficient strain gliPΔ invade into the lung tissue and the lung fungal burden increased markedly in immunosuppressed mice. In conclusion, these data revealed a novel role of gliotoxin in inducing cofilin phosphorylation mostly through the Cdc42/RhoA-LIMK1 signaling pathway to promote actin cytoskeleton rearrangement and internalization of A. fumigatus into type II human pneumocytes.

Role of the small GTPase Rho1 in cell wall integrity, stress response, and pathogenesis of Aspergillus fumigatus.

Aspergillus fumigatus is a major pathogen of invasive pulmonary aspergillosis. The small GTPase, Rho1, of A. fumigatus is reported to comprise a potential regulatory subunit of ß-1,3-glucan synthase and is indispensable for fungal viability; however, the role of AfRho1 on the growth, cell wall integrity, and pathogenesis of A. fumigatus is still poorly understood. We constructed A. fumigatus mutants with conditional- and overexpression of Rho1 and found that defects of AfRho1 expression led to the reduction of ß-1,3-glucan and glucosamine moieties on the cell wall, with down-regulated transcription of genes in the cell wall integrity signaling pathway and a decrease of calcofluor white (CFW)-stimulated mitogen-activated protein kinase (MpkA) phosphorylation and cytoplasmic leakage compared to those of the wild-type strain (WT). In addition, down-regulation of AfRho1 expression caused much higher sensitivity of A. fumigatus to H2O2 and alkaline pH compared to that of WT. Decrease of AfRho1 expression also attenuated the A. fumigatus pathogenicity in Galleria mellonella and inhibited conidial internalization into lung epithelial cells and inflammatory factor release. In contrast, overexpression of Rho1 did not alter A. fumigatus morphology, susceptibility to cell wall stresses, or pathogenicity relative to its parental strain. Taken together, our findings support AfRho1 as an essential regulator of the cell wall integrity, stress response, and pathogenesis of A. fumigatus.

Gliotoxin destructs the pulmonary epithelium barrier function by reducing cofilin oligomer formation to promote the dissolution of actin stress fibers.

The destruction of pulmonary epithelium is a major feature of lung diseases caused by the fungal pathogen Aspergillus fumigatus (A. fumigatus). Gliotoxin, a major mycotoxin of A. fumigatus, is widely postulated to be associated with the tissue invasion. However, the mechanism is unclear. In this study, we first discovered that cofilin, a regulator of actin dynamics in the pulmonary epithelial cells, existed mainly in the form of oligomer, which kept it unable to depolymerize actin filaments. Gliotoxin could reduce the formation of cofilin oligomer and promote the release of active cofilin monomer by regulating cofilin phosphorylation balance. Then, the active cofilin induced the dissolution of actin stress fibers to result in the disruption of pulmonary epithelium barrier function. Collectively, our study revealed a novel mechanism of gliotoxin destructing lung epithelium barrier function and for the first time indicated the role of cofilin oligomer in this process.