116 research outputs found

    Table_1_The intricate dance: host autophagy and Coxiella burnetii infection.DOCX

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    Q fever is a zoonotic disease caused by Coxiella burnetii, an obligatory intracellular bacterial pathogen. Like other intracellular pathogens, C. burnetii is able to survive and reproduce within host cells by manipulating host cellular processes. In particular, the relationship between C. burnetii infection and host autophagy, a cellular process involved in degradation and recycling, is of great interest due to its intricate nature. Studies have shown that autophagy can recognize and target intracellular pathogens such as Legionella and Salmonella for degradation, limiting their replication and promoting bacterial clearance. However, C. burnetii can actively manipulate the autophagic pathway to create an intracellular niche, known as the Coxiella-containing vacuole (CCV), where it can multiply and evade host immune responses. C. burnetii promotes the fusion of CCVs with lysosomes through mechanisms involving virulence factors such as Cig57 and CvpF. This review summarizes the latest findings on the dynamic interaction between host autophagy and C. burnetii infection, highlighting the complex strategies employed by both the bacterium and the host. A better understanding of these mechanisms could provide important insights into the development of novel therapeutic interventions and vaccine strategies against C. burnetii infections.</p

    Space-Confined Growth of Defect-Rich Molybdenum Disulfide Nanosheets Within Graphene: Application in The Removal of Smoke Particles and Toxic Volatiles

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    In this work, molybdenum disulfide/reduced graphene oxide (MoS<sub>2</sub>/RGO) hybrids are synthesized by a spatially confined reaction to insert the growth of defect-rich MoS<sub>2</sub> nanosheets within graphene to enable incorporation into the polymer matrix for the application in the removal of smoke particles and toxic volatiles. The steady-state tube furnace result demonstrates that MoS<sub>2</sub>/RGO hybrid could considerably reduce the yield of CO and smoke particles. The TG-IR coupling technique was utilized to identify species of toxic volatiles including aromatic compounds, CO, and hydrocarbons and to investigate the removal effect of MoS<sub>2</sub>/RGO hybrids on reducing toxic volatiles. The removal of smoke particles and toxic volatiles was attributed to the adsorption capacity derived from edges sites of MoS<sub>2</sub> and the honeycomb lattice of graphene, as well as the inhibition of nanobarrier resulting from two-dimensional structure. The work will offer a strategy for fabricating graphene-based hybrids by the space-confined synthesis and exploiting the application of space-confined graphene-based hybrid

    Data_Sheet_2_viGEN: An Open Source Pipeline for the Detection and Quantification of Viral RNA in Human Tumors.DOCX

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    <p>An estimated 17% of cancers worldwide are associated with infectious causes. The extent and biological significance of viral presence/infection in actual tumor samples is generally unknown but could be measured using human transcriptome (RNA-seq) data from tumor samples. We present an open source bioinformatics pipeline viGEN, which allows for not only the detection and quantification of viral RNA, but also variants in the viral transcripts. The pipeline includes 4 major modules: The first module aligns and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral-gene level thus allowing for downstream differential expression analysis of viral genes between case and controls groups. The fourth module calls variants in these viruses. To the best of our knowledge, there are no publicly available pipelines or packages that would provide this type of complete analysis in one open source package. In this paper, we applied the viGEN pipeline to two case studies. We first demonstrate the working of our pipeline on a large public dataset, the TCGA cervical cancer cohort. In the second case study, we performed an in-depth analysis on a small focused study of TCGA liver cancer patients. In the latter cohort, we performed viral-gene quantification, viral-variant extraction and survival analysis. This allowed us to find differentially expressed viral-transcripts and viral-variants between the groups of patients, and connect them to clinical outcome. From our analyses, we show that we were able to successfully detect the human papilloma virus among the TCGA cervical cancer patients. We compared the viGEN pipeline with two metagenomics tools and demonstrate similar sensitivity/specificity. We were also able to quantify viral-transcripts and extract viral-variants using the liver cancer dataset. The results presented corresponded with published literature in terms of rate of detection, and impact of several known variants of HBV genome. This pipeline is generalizable, and can be used to provide novel biological insights into microbial infections in complex diseases and tumorigeneses. Our viral pipeline could be used in conjunction with additional type of immuno-oncology analysis based on RNA-seq data of host RNA for cancer immunology applications. The source code, with example data and tutorial is available at: https://github.com/ICBI/viGEN/.</p

    Data_Sheet_1_viGEN: An Open Source Pipeline for the Detection and Quantification of Viral RNA in Human Tumors.PDF

    No full text
    <p>An estimated 17% of cancers worldwide are associated with infectious causes. The extent and biological significance of viral presence/infection in actual tumor samples is generally unknown but could be measured using human transcriptome (RNA-seq) data from tumor samples. We present an open source bioinformatics pipeline viGEN, which allows for not only the detection and quantification of viral RNA, but also variants in the viral transcripts. The pipeline includes 4 major modules: The first module aligns and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral-gene level thus allowing for downstream differential expression analysis of viral genes between case and controls groups. The fourth module calls variants in these viruses. To the best of our knowledge, there are no publicly available pipelines or packages that would provide this type of complete analysis in one open source package. In this paper, we applied the viGEN pipeline to two case studies. We first demonstrate the working of our pipeline on a large public dataset, the TCGA cervical cancer cohort. In the second case study, we performed an in-depth analysis on a small focused study of TCGA liver cancer patients. In the latter cohort, we performed viral-gene quantification, viral-variant extraction and survival analysis. This allowed us to find differentially expressed viral-transcripts and viral-variants between the groups of patients, and connect them to clinical outcome. From our analyses, we show that we were able to successfully detect the human papilloma virus among the TCGA cervical cancer patients. We compared the viGEN pipeline with two metagenomics tools and demonstrate similar sensitivity/specificity. We were also able to quantify viral-transcripts and extract viral-variants using the liver cancer dataset. The results presented corresponded with published literature in terms of rate of detection, and impact of several known variants of HBV genome. This pipeline is generalizable, and can be used to provide novel biological insights into microbial infections in complex diseases and tumorigeneses. Our viral pipeline could be used in conjunction with additional type of immuno-oncology analysis based on RNA-seq data of host RNA for cancer immunology applications. The source code, with example data and tutorial is available at: https://github.com/ICBI/viGEN/.</p

    Presentation_2_A Novel Regulator Modulates Glucan Production, Cell Aggregation and Biofilm Formation in Streptococcus sanguinis SK36.ZIP

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    <p>Streptococcus sanguinis is an early colonizer of tooth surfaces and a key player in plaque biofilm development. However, the mechanism of biofilm formation of S. sanguinis is still unclear. Here, we showed that deletion of a transcription factor, brpL, promotes cell aggregation and biofilm formation in S. sanguinis SK36. Glucan, a polysaccharide synthesized from sucrose, was over-produced and aggregated in the biofilm of ΔbrpL, which was necessary for better biofilm formation ability of ΔbrpL. Quantitative RT-PCR demonstrated that gtfP was significantly up-regulated in ΔbrpL, which increased the productions of water-insoluble and water-soluble glucans. The ΔbrpLΔgtfP double mutant decreased biofilm formation ability of ΔbrpL to a level similar like that of ΔgtfP. Interestingly, the biofilm of ΔbrpL had an increased tolerance to ampicillin treatment, which might be due to better biofilm formation ability through the mechanisms of cellular and glucan aggregation. RNA sequencing and quantitative RT-PCR revealed the modulation of a group of genes in ΔbrpL was mediated by activating the expression of ciaR, another gtfP-related biofilm formation regulator. Double deletion of brpL and ciaR decreased biofilm formation ability to the phenotype of a ΔciaR mutant. Additionally, RNA sequencing elucidated a broad range of genes, related to carbohydrate metabolism and uptake, were activated in ΔbrpL. SSA_0222, a gene involved in the phosphotransferase system, was dramatically up-regulated in ΔbrpL and essential for S. sanguinis survival under our experimental conditions. In summary, brpL modulates glucan production, cell aggregation and biofilm formation by regulating the expression of ciaR in S. sanguinis SK36.</p

    Tuning Oxygen Vacancies of the Co<sub>3</sub>O<sub>4</sub> Catalyst through an Ethanol-Assisted Hydrothermal Method for Low-Temperature CO Oxidation

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    Co3O4 is considered to be the most promising catalyst for CO oxidation due to its superior activity and low cost. Oxygen vacancies can improve the low-temperature catalytic activity due to their ability to activate oxygen. In this work, Co3O4-xET samples with different oxygen vacancies are synthesized through an ethanol-assisted hydrothermal method and applied to low-temperature CO oxidation. The catalytic activity and stability of the Co3O4 catalyst could be significantly improved with the increase of ethanol concentration and display a “volcanic” curve. The Co3O4-50ET catalyst displays the best catalytic performance with the complete oxidation of CO at 110 °C and excellent stability. With Raman spectroscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), O2 temperature-programmed desorption (TPD), in situ diffuse reflectance infrared spectroscopy (DRIFTS), and other characterization methods, the relationship between surface oxygen vacancies and catalytic properties is studied. It can be found that the ethanol reduction process could promote the redox performance and oxygen migration ability and increase the oxygen vacancies of the Co3O4 catalyst
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