Integration of Transcriptomic and Proteomic Approaches Reveals the Temperature-Dependent Virulence of Pseudomonas plecoglossicida

Pseudomonas plecoglossicida is a facultative pathogen that is associated with diseases of multiple fish, mainly at 15–20°C. Although fish disease caused by P. plecoglossicida has led to significant economic losses, the mechanisms of the temperature-dependent virulence are unclear. Here, we identify potential pathogenicity mechanisms and demonstrate the direct regulation of several virulence factors by temperature with transcriptomic and proteomic analyses, quantitative real-time PCR (qRT-PCR), RNAi, pyoverdine (PVD) quantification, the chrome azurol S (CAS) assay, growth curve measurements, a biofilm assay, and artificial infection. The principal component analysis, the heat map generation and hierarchical clustering, together with the functional annotations of the differentially expressed genes (DEGs) demonstrated that, under different growth temperatures, the animation and focus of P. plecoglossicida are quite different, which may be the key to pathogenicity. Genes involved in PVD synthesis and in the type VI secretion system (T6SS) are specifically upregulated at the virulent temperature of 18°C. Silencing of the PVD-synthesis-related genes reduces the iron acquisition, growth, biofilm formation, distribution in host organs and virulence of the bacteria. Silencing of the T6SS genes also leads to the reduction of biofilm formation, distribution in host organs and virulence. These findings reveal that temperature regulates multiple virulence mechanisms in P. plecoglossicida, especially through iron acquisition and T6SS secretion. Meanwhile, integration of transcriptomic and proteomic data provide us with a new perspective into the pathogenesis of P. plecoglossicida, which would not have been easy to catch at either the protein or mRNA differential analyses alone, thus illustrating the power of multi-omics analyses in microbiology

Dual RNA-Seq Unveils Pseudomonas plecoglossicida htpG Gene Functions During Host-Pathogen Interactions With Epinephelus coioides

Pseudomonas plecoglossicida is a temperature-dependent opportunistic pathogen which is associated with a variety of diseases in fish. During the development of “white nodules” disease, the expression of htpG in P. plecoglossicida was found to be significantly up-regulated at its virulent temperature of 18°C. The infection of htpG-RNAi strain resulted in the onset time delay, reduction in mortality and infection symptoms in spleen of Epinephelus coioides, and affected the bacterial tissue colonization. In order to reveal the effect of htpG silencing of P. plecoglossicida on the virulence regulation in P. plecoglossicida and immune response in E. coioides, dual RNA-seq was performed and a pathogen-host integration network was constructed. Our results showed that infection induced the expression of host genes related to immune response, but attenuated the expression of bacterial virulence genes. Novel integration was found between host immune genes and bacterial virulence genes, while IL6, IL1R2, IL1B, and TLR5 played key roles in the network. Further analysis with GeneMANIA indicated that flgD and rplF might play key roles during the htpG-dependent virulence regulation, which was in accordance with the reduced biofilm production, motility and virulence in htpG-RNAi strain. Meanwhile, IL6 and IL1B were found to play key roles during the defense against P. plecoglossicida, while CELA2, TRY, CPA1, CPA2, and CPB1 were important targets for P. plecoglossicida attacking to the host

Effects of N-G-monomethyl-L-arginine (NMMA) and catalase on intracellular survival of Vibrio alginolyticus in macrophages of large yellow croaker Pseudosciaena crocea

The intracellular survival of Vibrio alginolyticus and Vibrio parahaemolyticus in large yellow croaker macrophages of Pseudosciaena crocea was investigated. In addition, the effects of N-G-monomethyl-L-arginine (NMMA) and catalase on the interaction of V. alginolyticus with macrophages from head kidney and on macrophages reactive nitrogen intermediate (RNI) and reactive oxygen intermediate (ROI) in vitro were determined. V. alginolyticus ND-01 was able to survive in macrophages from head kidney of large yellow croakers for at least 3 h, while V. paraheamolyticus 1.1614 could not survive in the macrophages for 1 h. Intracellular bacterial survival was affected by the addition of specific inhibitors of macrophage oxidative function. Exposure of macrophages to NMMA and catalase decreased the number of viable cells of V. alginolyticus inside large yellow croaker macrophages. Furthermore, a close correlation was observed between the number of intracellular survival bacteria with the amount of NO and H2O2 produced by macrophages.National Department Public Benefit Research Foundation of China [200903029]; Natural Science Foundation of Fujian Province [2011J06014

Few-Shot Object Detection Using Multimodal Sensor Systems of Unmanned Surface Vehicles

The object detection algorithm is a key component for the autonomous operation of unmanned surface vehicles (USVs). However, owing to complex marine conditions, it is difficult to obtain large-scale, fully labeled surface object datasets. Shipborne sensors are often susceptible to external interference and have unsatisfying performance, compromising the results of traditional object detection tasks. In this paper, a few-shot surface object detection method is proposed based on multimodal sensor systems for USVs. The multi-modal sensors were used for three-dimensional object detection, and the ability of USVs to detect moving objects was enhanced, realizing metric learning-based few-shot object detection for USVs. Compared with conventional methods, the proposed method enhanced the classification results of few-shot tasks. The proposed approach achieves relatively better performance in three sampled sets of well-known datasets, i.e., 2%, 10%, 5% on average precision (AP) and 28%, 24%, 24% on average orientation similarity (AOS). Therefore, this study can be potentially used for various applications where the number of labeled data is not enough to acquire a compromising result

Method for quickly delineating Merzbacher Lake extent based on Environment and Disaster Monitoring small Satellite images

The Merzbacher Glacial Lake located in the Sary Jaz-Kumarik River Basin has severe impacts on the environment and human well-being in downstream of the AKSU River in China. The Merzbacker Lake has flooded with increased frequency in recent years with the climate warming. It is vital to strengthen observation and monitoring of the Merzbacker Lake, especially by remote sensing data. Large portion by floating ice is the key issues of monitoring the lake. Based on the high temporal and spatial resolution Environment and Disaster Monitoring Satellite images, an improved method focused on threshold and mask technique were presented. Parts of the lake which is clear of ice was extracted mainly by Normalized Difference Water Index method. Parts of the lake covered by floating ice were relarively accurately extracted by using the Band B image of the HSV images. The area change information of Merzbacher Lake then were extracted by the post-processing of the areas in different periods. As an example, the changing areas series of Merbacher Lake in 2009 were analyzed. The results suggests that the date of the Merbacher Lake flood was around 30th July, and the flood lasted for no more than a week. The application indicates that the method can provid quick and relatively accurate monitoring of the lake flood, which is very import to construct forecasting and warning systems of Merzbacher Lake

Disruption of chemotaxis-related genes affects multiple cellular processes and the virulence of pathogenic Vibrio harveyi

National Natural Science Foundation of China [31272699, 41176115]; National Department Public Benefit Research Foundation of China [200903029]; Natural Science Foundation of Fujian Province [2011J06014]; National Hi-Tech Research and Development Program of China (863 Program) [2007AA09Z115]Chemotactic motility is involved in the virulence of many pathogenic bacteria. In order to understand the role of chemotactic motility of Vibrio harveyi in cellular processes and virulence, mini-Tn10/Kan transposon-induced mutants with deficient chemotactic motility were constructed, screened, and identified. Sequence analysis revealed that the 465-bp fragment (Gen Bank accession number HM630274) flanking the transposon insertion site in mutant TS-CM1 had the highest identity (96.9%) with a hypothetical protein gene of V. harveyi ATCC BAA-1116 and the second-highest identity (91.8%) with the pgk gene of V. parahaemolyticus RIMD 2210633. In another mutant, TS-CM2, 356 bp of transposon-flanking sequence (Gen Bank accession number HM630275) also showed the highest identity (94.6%) with a hypothetical protein gene of V. harveyi ATCC BAA-1116 and the second-highest identity (92.4%) with the flaB gene of V. alginolyticus HY9901. Studies on virulence-related biological characteristics such as growth, motility, adhesion, and infectivity of themutants showed that disruption of either the flagellin gene or energy metabolism gene led to subsequent loss of chemotactic motility and changes in growth, motility, adhesion, and virulence of the pathogenic V. harveyi. Hence, the flagellin gene and crucial energy metabolism gene played an important role in the chemotactic motility of V. harveyi

Boundary-Match U-Shaped Temporal Convolutional Network for Vulgar Action Segmentation

The advent of deep learning has provided solutions to many challenges posed by the Internet. However, efficient localization and recognition of vulgar segments within videos remain formidable tasks. This difficulty arises from the blurring of spatial features in vulgar actions, which can render them indistinguishable from general actions. Furthermore, issues of boundary ambiguity and over-segmentation complicate the segmentation of vulgar actions. To address these issues, we present the Boundary-Match U-shaped Temporal Convolutional Network (BMUTCN), a novel approach for the segmentation of vulgar actions. The BMUTCN employs a U-shaped architecture within an encoder–decoder temporal convolutional network to bolster feature recognition by leveraging the context of the video. Additionally, we introduce a boundary-match map that fuses action boundary inform ation with greater precision for frames that exhibit ambiguous boundaries. Moreover, we propose an adaptive internal block suppression technique, which substantially mitigates over-segmentation errors while preserving accuracy. Our methodology, tested across several public datasets as well as a bespoke vulgar dataset, has demonstrated state-of-the-art performance on the latter