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Social interactions substantially influence the dynamics and functions of microbial communities. Cooperative behaviors serve to benefit populations, yet they are often exploited by cheating cells, thus creating a conflict between individuals in the microbial population. However, the underlying mechanisms by which cooperative behaviors are stabilized are incompletely elucidated. Here, we used quorum sensing (QS) as a model of cooperation, and functionally studied QS regulator LasR variant strains in the context of cooperative behaviors. We found that a LasR228 variant strain, bearing a non-conserved substitution in LasR, exhibited minimal LasR-dependent phenotypes. However, the function of this LasR228 variant strain was restored by inactivation of the transcriptional repressor PsdR, and the phenotypes of this variant strain were similar to the parental strain. Furthermore, we illustrate a post-transcriptional regulatory mechanism responsible for the activation of the LasR228 variant. Unlike LasR228, the PsdR-null-LasR228 strain demonstrated cooperative behaviors in competition with the LasR-null strain. Since psdR mutations precede the emergence of LasR variants in the evolution of P. aeruginosa using casein broth, this PsdR-mediated cooperative mechanism serves as an anticipatory control against potential cheating LasR variant strains. Additionally, our cell-killing assay showed that the cooperative PsdR-null-LasR228 strain was associated with increased bacterial pathogenicity to eukaryotic host cells. In conclusion, our study reveals the functional plasticity of LasR variants, which can be modulated by secondary mutations, affecting cooperation and conflict within populations. Our identification of a novel cooperative molecular mechanism offers insight into the maintenance of cooperation within microbial communities.

Bradyrhizobium diazoefficiens USDA110 is one of the most effective nitrogen-fixing symbionts of soybeans. Here we carried out a large-scale transposon insertion sequencing (Tn-seq) analysis of strain Bd110 spc4 , which is derived from USDA110, with the goal of increasing available resources for identifying genes crucial for the survival of this plant symbiont under diverse conditions. We prepared two transposon (Tn) insertion libraries of Bd110 spc4 with 155,042 unique Tn insertions when the libraries were combined, which is an average of one insertion every 58.7 bp of the reference USDA110 genome. Application of bioinformatic filtering steps to remove genes too small to be expected to have Tn insertions, resulted in a list of genes that were classified as putatively essential. Comparison of this gene set with genes putatively essential for the growth of the closely related alpha-proteobacterium, Rhodopseudomonas palustris , revealed a small set of five genes that may be collectively essential for closely related members of the family Bradyrhizobiaceae. This group includes bacteria with diverse lifestyles ranging from plant symbionts to animal-associated species to free-living species.

Using data-driven models to predict floods in advance is one of the current effective methods and hot researches to reduce urban flood disasters. In order to improve the prediction accuracy, it is necessary to select the appropriate flood hazard factors and the number of training samples to construct the prediction model. In our current research, an artificial neural network (i.e., the back-propagation neural network, BPNN) model was developed to predict the flood depth in the next hour. A case study of the urban flood during six typhoons in Macau of China was conducted to prove the performance of the proposed model. The flood depth was collected as output; after analyzing their correlation to the flood typhoon optimum track, urban weather, tides, geographic height and water depth increment of the submerged area were used as input. As a result, four models trained with different sample numbers were developed for training and testing. The model performances were examined using average absolute error, root mean square error and the coefficient of determination. The results show that in this case study, the 30-min scale model provides reliable predictions and can provide useful decision support for the prevention and mitigation of flood disasters in coastal urban.

The use of light energy to drive asymmetric organic transformations to produce high-value-added organic compounds is attracting increasing interest as a sustainable strategy for solving environmental problems and addressing the energy crisis. Chiral covalent organic frameworks (COFs), as porous crystalline chiral materials, have become an important platform on which to explore new chiral photocatalytic materials due to their precise tunability, chiral structure, and function. This review highlights recent research progress on chiral COFs and their crystalline composites, evaluating their application as catalysts in asymmetric photocatalytic organic transformations in terms of their structure. Finally, the limitations and challenges of chiral COFs in asymmetric photocatalysis are discussed, with future opportunities for research being identified.

XRE-cupin family proteins containing an DNA-binding domain and a cupin signal-sensing domain are widely distributed in bacteria. In Pseudomonas aeruginosa , XRE-cupin transcription factors have long been recognized as regulators exclusively controlling cellular metabolism pathways. However, their potential functional roles beyond metabolism regulation remain unknown. PsdR, a typical XRE-cupin transcriptional regulator, was previously characterized as a local repressor involved solely in dipeptide metabolism. Here, by measuring quorum-sensing (QS) activities and QS-controlled metabolites, we uncover that PsdR is a new QS regulator in P . aeruginosa . Our RNA-seq analysis showed that rather than a local regulator, PsdR controls a large regulon, including genes associated with both the QS circuit and non-QS pathways. To unveil the underlying mechanism of PsdR in modulating QS, we developed a comparative transcriptome approach named “transcriptome profile similarity analysis” (TPSA). Using this TPSA method, we revealed that PsdR expression causes a QS-null-like transcriptome profile, resulting in QS-inactive phenotypes. Based on the results of TPSA, we further demonstrate that PsdR directly binds to the promoter for the gene encoding the QS master transcription factor LasR, thereby negatively regulating its expression and influencing QS activation. Moreover, our results showed that PsdR functions as a negative virulence regulator, as inactivation of PsdR enhanced bacterial cytotoxicity on host cells. In conclusion, we report on a new QS regulation role for PsdR, providing insights into its role in manipulating QS-controlled virulence. Most importantly, our findings open the door for a further discovery of untapped functions for other XRE-Cupin family proteins.

Reducing the impact of artificial neural networks (ANN) affected by sources of uncertainty is crucial to improving the reliability of the flood prediction model. This study proposes an ensemble artificial neural network (EANN) model to predict the degree of flooding in coastal cities. Combined methods are used to reduce the model’s uncertainty, heuristic neural pathway strength feature selection is used to select inputs, the coupling method is used to optimize network architecture and parameters, and the integration method which paralleling three ANN models with different predicted lead periods ensemble together is used to capture output uncertainty. The EANN model has successfully predicted flooding in the Chinese coastal city of Macao during a typhoon, with convincing accuracy. The study also analyzed the impacts of both long and short training datasets with appropriate time intervals on ANN modeling performance. It was found that the performance of short training datasets, with appropriate time intervals, was similar to or better than models with long training datasets.

Pseudomonas aeruginosa strain PAO1 has been commonly used in the laboratory, with frequent genome variations reported. Quorum sensing (QS), a cell–cell communication system, plays important role in controlling a variety of virulence factors. However, the evolution and adaptability of QS in those laboratory strains are still poorly understood. Here we used the QS reporter and whole-genome sequencing (WGS) to systematically investigate the QS phenotypes and corresponding genetic basis in collected laboratory PAO1 strains. We found that the PAO1-z strain has an inactive LasR protein, while bearing an active Rhl QS system and exhibiting QS-controlled protease-positive activity. Our study revealed that an 18-bp insertion in mexT gene gave rise to the active QS system in the PAO1-z strain. This MexT inactivation restored the QS activity caused by the inactive LasR, showing elevated production of pyocyanin, cyanide and elastase. Our results implied the evolutionary trajectory for the PAO1-z strain, with the evulutionary order from the first Las QS inactivation to the final Rhl QS activation. Our findings point out that QS homeostasis occurs in the laboratory P. aeruginosa strain, offering a potential platform for the QS study in clinical isolates.

In order to solve the problem of reciprocating motion in no beam supported mining machines, putting energy saving as a starting point in Coal Bed Methane (CBM) exploitation, this paper designs a completely non-circular gear automatic reversing vertical drainage machine based on the theory of non-circular gear transmission. In the field of CBM exploitation, the use of non-circular gears is an attempt at an innovation. First of all, according to the working conditions of the pump and use requirements, a scheme is established whereby the one-way rotary motion of the motor is changed into reciprocating motion so that it could drive the oil pumping rod to achieve the upper and lower mining. Secondly, this paper has designed a new type non-circular gear reversing box as the core component to replace the traditional four beam linkage mechanism and also provides elaborate calculations. Finally, the movement simulation of the non-circular gear reversing gear system is completed. Comparing the motion simulation results with the theoretical ones, the correctness of our theoretical analysis can be verified. Compared with the traditional devices, the new coal seam gas drainage machine model design has nearly 11% higher efficiency, which has obvious energy saving effects and reduces the cost of mining coal seam gas.

Exopolysaccharides (EPS) play critical roles in rhizobium-plant interactions. However, the EPS biosynthesis pathway in Bradyrhizobium diazoefficiens USDA110 remains elusive. Here we used transposon (Tn) mutagenesis with the aim to identify genetic elements required for EPS biosynthesis in B. diazoefficiens USDA110. Phenotypic screening of Tn5 insertion mutants grown on agar plates led to the identification of a mutant with a transposon insertion site in the blr2358 gene. This gene is predicted to encode a phosphor-glycosyltransferase that transfers a phosphosugar onto a polyprenol phosphate substrate. The disruption of the blr2358 gene resulted in defective EPS synthesis. Accordingly, the blr2358 mutant showed a reduced capacity to induce nodules and stimulate the growth of soybean plants. Glycosyltransferase genes related to blr2358 were found to be well conserved and widely distributed among strains of the Bradyrhizobium genus. In conclusion, our study resulted in identification of a gene involved in EPS biosynthesis and highlights the importance of EPS in the symbiotic interaction between USDA110 and soybeans.

A typhoon passing through or making landfall in a coastal city may result in seawater intrusion and continuous rainfall, which may cause urban flooding. The urban flood disaster caused by a typhoon is a dynamic process that changes over time, and a dynamic Gaussian Bayesian network (DGBN) is used to model the time series events in this paper. The scene data generated by each typhoon are different, which means that each typhoon has different characteristics. This paper establishes multiple DGBNs based on the historical data of Macau flooding caused by multiple typhoons, and similar analysis is made between the scene data related to the current flooding to be predicted and the scene data of historical flooding. The DGBN most similar to the scene characteristics of the current flooding is selected as the predicting network of the current flooding. According to the topography, the influence of the surface confluence is considered, and the Manning formula analysis method is proposed. The Manning formula is combined with the DGBN to obtain the final prediction model, DGBN-m, which takes into account the effects of time series and non-time-series factors. The flooding data provided by the Macau Meteorological Bureau are used to carry out experiments, and it is proved that the proposed model can predict the flooding depth well in a specific area of Macau under the condition of a small amount of data and that the best predicting accuracy can reach 84%. Finally, generalization analysis is performed to further confirm the validity of the proposed model.