Global analysis of the eukaryotic pathways and networks regulated by Salmonella typhimurium in mouse intestinal infection in vivo

<p>Abstract</p> <p>Background</p> <p>Acute enteritis caused by <it>Salmonella </it>is a public health concern. <it>Salmonella </it>infection is also known to increase the risk of inflammatory bowel diseases and cancer. Therefore, it is important to understand how <it>Salmonella </it>works in targeting eukaryotic pathways in intestinal infection. However, the global physiological function of <it>Salmonella </it>typhimurium in intestinal mucosa <it>in vivo </it>is unclear. In this study, a whole genome approach combined with bioinformatics assays was used to investigate the <it>in vivo </it>genetic responses of the mouse colon to <it>Salmonella</it>. We focused on the intestinal responses in the early stage (8 hours) and late stage (4 days) after <it>Salmonella </it>infection.</p> <p>Results</p> <p>Of the 28,000 genes represented on the array, our analysis of mRNA expression in mouse colon mucosa showed that a total of 856 genes were expressed differentially at 8 hours post-infection. At 4 days post-infection, a total of 7558 genes were expressed differentially. 23 differentially expressed genes from the microarray data was further examined by real-time PCR. Ingenuity Pathways Analysis identified that the most significant pathway associated with the differentially expressed genes in 8 hours post-infection is oxidative phosphorylation, which targets the mitochondria. At the late stage of infection, a series of pathways associated with immune and inflammatory response, proliferation, and apoptosis were identified, whereas the oxidative phosphorylation was shut off. Histology analysis confirmed the biological role of <it>Salmonella</it>, which induced a physiological state of inflammation and proliferation in the colon mucosa through the regulation of multiple signaling pathways. Most of the metabolism-related pathways were targeted by down-regulated genes, and a general repression process of metabolic pathways was observed. Network analysis supported IFN-γ and TNF-α function as mediators of the immune/inflammatory response for host defense against pathogen.</p> <p>Conclusion</p> <p>Our study provides novel genome-wide transcriptional profiling data on the mouse colon mucosa's response to the <it>Salmonella typhimurium </it>infection. Building the pathways and networks of interactions between these genes help us to understand the complex interplay in the mice colon during <it>Salmonella </it>infection, and further provide new insights into the molecular cascade, which is mobilized to combat <it>Salmonella</it>-associated colon infection <it>in vivo</it>.</p

Robust Automatic Focus Algorithm for Low Contrast Images Using a New Contrast Measure

Low contrast images, suffering from a lack of sharpness, are easily influenced by noise. As a result, many local false peaks may be generated in contrast measurements, making it difficult for the camera’s passive auto-focus system to perform its function of locating the focused peak. In this paper, a new passive auto-focus algorithm is proposed to address this problem. First, a noise reduction preprocessing is introduced to make our algorithm robust to both additive noise and multiplicative noise. Then, a new contrast measure is presented to bring in local false peaks, ensuring the presence of a well defined focused peak. In order to gauge the performance of our algorithm, a modified peak search algorithm is used in the experiments. The experimental results from an actual digital camera validate the effectiveness of our proposed algorithm

Characterization of protein-protein interactions between the nucleocapsid protein and membrane protein of the avian infectious bronchitis virus

Avian infectious bronchitis virus (IBV) is one of the major viral respiratory diseases of chickens. Better understanding of the molecular mechanism of viral pathogenesis may contribute significantly to the development of prophylactic, therapeutic and diagnostic reagents as well as help in infection control. Avian IBV belongs to the Coronaviridaes and is similar to the other known coronaviruses. Previous studies have indicated that protein–protein interactions between nucleocapsid (N) and the membrane (M) proteins in coronavirus are related to coronavirus viral assembly. However, cases of IBV are seldom reported. In this study, yeast two-hybrid and  co-immunoprecipitation techniques were applied to investigate possible interactions between IBV N and M proteins. We found that interaction of the N and M proteins took place in vivo and the residues 168 – 225 of the M protein and the residues 150 - 210 of the N protein were determined to be involved in their interaction. These results may provide some useful information on the molecular mechanism of IBV’s N and M proteins, which will facilitate therapeutic strategies aiming at the disruption of the association between membrane and nucleocapsid proteins and indicate a new drug target for IBV.Key words: Co-immunoprecipitation, membrane protein, nucleocapsid protein, protein-protein interaction, yeast two-hybrid

Elongated Physiological Structure Segmentation via Spatial and Scale Uncertainty-aware Network

Robust and accurate segmentation for elongated physiological structures is challenging, especially in the ambiguous region, such as the corneal endothelium microscope image with uneven illumination or the fundus image with disease interference. In this paper, we present a spatial and scale uncertainty-aware network (SSU-Net) that fully uses both spatial and scale uncertainty to highlight ambiguous regions and integrate hierarchical structure contexts. First, we estimate epistemic and aleatoric spatial uncertainty maps using Monte Carlo dropout to approximate Bayesian networks. Based on these spatial uncertainty maps, we propose the gated soft uncertainty-aware (GSUA) module to guide the model to focus on ambiguous regions. Second, we extract the uncertainty under different scales and propose the multi-scale uncertainty-aware (MSUA) fusion module to integrate structure contexts from hierarchical predictions, strengthening the final prediction. Finally, we visualize the uncertainty map of final prediction, providing interpretability for segmentation results. Experiment results show that the SSU-Net performs best on cornea endothelial cell and retinal vessel segmentation tasks. Moreover, compared with counterpart uncertainty-based methods, SSU-Net is more accurate and robust

Chronic Effects of a Salmonella Type III Secretion Effector Protein AvrA In Vivo

Salmonella infection is a common public health problem that can become chronic and increase the risk of inflammatory bowel diseases and cancer. AvrA is a Salmonella bacterial type III secretion effector protein. Increasing evidence demonstrates that AvrA is a multi-functional enzyme with critical roles in inhibiting inflammation, regulating apoptosis, and enhancing proliferation. However, the chronic effects of Salmonella and effector AvrA in vivo are still unknown. Moreover, alive, mutated, non-invasive Salmonella is used as a vector to specifically target cancer cells. However, studies are lacking on chronic infection with non-pathogenic or mutated Salmonella in the host.We infected mice with Salmonella Typhimurium for 27 weeks and investigated the physiological effects as well as the role of AvrA in intestinal inflammation. We found altered body weight, intestinal pathology, and bacterial translocation in spleen, liver, and gallbladder in chronically Salmonella-infected mice. Moreover, AvrA suppressed intestinal inflammation and inhibited the secretion of cytokines IL-12, IFN-gamma, and TNF-alpha. AvrA expression in Salmonella enhanced its invasion ability. Liver abscess and Salmonella translocation in the gallbladder were observed and may be associated with AvrA expression in Salmonella.We created a mouse model with persistent Salmonella infection in vivo. Our study further emphasizes the importance of the Salmonella effector protein AvrA in intestinal inflammation, bacterial translocation, and chronic infection in vivo

Government subsidies in public-private partnership projects based on altruistic theory

Nowadays, the public-private partnership (PPP) scheme has been widely adopted in infrastructure projects around the world. In PPP projects, the governments participate as a principal and the investors play the role of an agent, and therefore their behaviours and incentive strategies can be explained and designed by the principal-agent theory. As “economic men” with limited rationality, both the governments and the investors have altruistic preferences during cooperation. This paper studies how project participants’ altruistic preferences affect government subsidies based on the principal-agent theory. To this end, a principal-agent model in the presence of altruism is developed. The results show that the amount of government compensation is related to the altruistic preferences, the expected revenue, costs and investors’ efforts. Contrary to intuition, the governments’ altruism actually undermines the investors’ enthusiasm in cooperation and the risk-sharing propensity, although it increases the utilities of both parties. Moreover, when selecting the investors, governments should examine their operating capacity carefully, which has a significant impact on the sustainable development of the projects and even PPP arrangements. The findings contribute new insights into the development of incentive mechanisms between governments and private investors from the perspective of the behavioural preferences. First published online 27 January 202

Application of chloroplast genome in the identification of Phyllanthus urinaria and its common adulterants

BackgroundPhyllanthus urinaria L. is extensively used as ethnopharmacological material in China. In the local marketplace, this medicine can be accidentally contaminated, deliberately substituted, or mixed with other related species. The contaminants in herbal products are a threat to consumer safety. Due to the scarcity of genetic information on Phyllanthus plants, more molecular markers are needed to avoid misidentification.MethodsIn this study, the complete chloroplast genome of nine species of the genus Phyllanthus was de novo assembled and characterized.ResultsThis study revealed that all of these species exhibited a conserved quadripartite structure, which includes a large single copy (LSC) region and small single copy (SSC) region, and two copies of inverted repeat regions (IRa and IRb), which separate the LSC and SSC regions. And the genome structure, codon usage, and repeat sequences were highly conserved and showed similarities among the nine species. Three highly variable regions (trnS-GCU-trnG-UCC, trnT-UGU-trnL-UAA, and petA-psbJ) might be helpful as potential molecular markers for identifying P. urinaria and its contaminants. In addition, the molecular clock analysis results showed that the divergence time of the genus Phyllanthus might occur at ~ 48.72 Ma.ConclusionThis study provides valuable information for further species identification, evolution, and phylogenetic research of Phyllanthus