596 research outputs found

    High resolution effect-directed analysis of steroid hormone (ant)agonists in surface and wastewater quality monitoring

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    Monitoring of chemical water quality is extremely challenging due to the large variety of compounds and the presence of biologically active compounds with unknown chemical identity. Previously, we developed a high resolution Effect-Directed Analysis (EDA) platform that combines liquid chromatography with high resolution mass spectrometry and parallel bioassay detection. In this study, the platform is combined with CALUX bioassays for (anti)androgenic, estrogenic and glucocorticoid activities, and the performance of the platform is evaluated. It appeared to render very repeatable results, with high recoveries of spiked compounds and high consistency between the mass spectrometric and bioassay results. Application of the platform to wastewater treatment plant effluent and surface water samples led to the identification of several compounds contributing to the measured activities. Eventually, a workflow is proposed for the application of the platform in a routine monitoring context. The workflow divides the platform into four phases, of which one to all can be performed depending on the research question and the results obtained. This allows one to make a balance between the effort put into the platform and the certainty and depth by which active compounds will be identified. The EDA platform is a valuable tool to identify unknown bioactive compounds, both in an academic setting as in the context of legislative, governmental or routine monitoring

    Identifying adverse outcome pathways (AOP) for Amsterdam City Fish by integrated field monitoring

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordThe European City Fish project aimed to develop a generic methodology for ecological risk assessment for urban rivers. Since traditional methods only consider a small fraction of substances present in the water cycle, biological effect monitoring is required for a more reliable assessment of the pollution status. A major challenge for environmental risk assessment (ERA) is the application of adverse outcome pathways (AOP), i.e. the linking of pollutant exposure via early molecular and biochemical changes to physiological effects and, ultimately, effects on populations and ecosystems. We investigated the linkage between responses at these different levels. Many AOP aspects were investigated, from external and internal exposure to different classes of micropollutants, via molecular key events (MKE) the impacts on organs and organisms (fish physiology), to changes in the population dynamics of fish. Risk assessment procedures were evaluated by comparing environmental quality standards, bioassay responses, biomarkers in caged and feral fish, and the impact on fish populations. Although no complete AOP was observed, indirect relationships linking pollutant exposure via MKE to impaired locomotion were demonstrated at the most polluted site near a landfill for chemical waste. The pathway indicated that several upstream key events requiring energy for stress responses and toxic defence are likely to converge at a single common MKE: increased metabolic demands. Both fish biomarkers and the bioanalytical SIMONI strategy are valuable indicators for micropollutant risks to fish communities.City of AmsterdamEuropean UnionWaternet Institute for the Urban Water Cycle, Amsterda

    Structural basis for CRISPR RNA-guided DNA recognition by Cascade

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    The CRISPR (clustered regularly interspaced short palindromic repeats) immune system in prokaryotes uses small guide RNAs to neutralize invading viruses and plasmids. In Escherichia coli, immunity depends on a ribonucleoprotein complex called Cascade. Here we present the composition and low-resolution structure of Cascade and show how it recognizes double-stranded DNA (dsDNA) targets in a sequence-specific manner. Cascade is a 405-kDa complex comprising five functionally essential CRISPR-associated (Cas) proteins (CasA1B2C6D1E1) and a 61-nucleotide CRISPR RNA (crRNA) with 5′-hydroxyl and 2′,3′-cyclic phosphate termini. The crRNA guides Cascade to dsDNA target sequences by forming base pairs with the complementary DNA strand while displacing the noncomplementary strand to form an R-loop. Cascade recognizes target DNA without consuming ATP, which suggests that continuous invader DNA surveillance takes place without energy investment. The structure of Cascade shows an unusual seahorse shape that undergoes conformational changes when it binds target DNA.

    Revealing determinants of translation efficiency via whole-gene codon randomization and machine learning

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    It has been known for decades that codon usage contributes to translation efficiency and hence to protein production levels. However, its role in protein synthesis is still only partly understood. This lack of understanding hampers the design of synthetic genes for efficient protein production. In this study, we generated a synonymous codon-randomized library of the complete coding sequence of red fluorescent protein. Protein production levels and the full coding sequences were determined for 1459 gene variants in Escherichia coli. Using different machine learning approaches, these data were used to reveal correlations between codon usage and protein production. Interestingly, protein production levels can be relatively accurately predicted (Pearson correlation of 0.762) by a Random Forest model that only relies on the sequence information of the first eight codons. In this region, close to the translation initiation site, mRNA secondary structure rather than Codon Adaptation Index (CAI) is the key determinant of protein production. This study clearly demonstrates the key role of codons at the start of the coding sequence. Furthermore, these results imply that commonly used CAI-based codon optimization of the full coding sequence is not a very effective strategy. One should rather focus on optimizing protein production via reducing mRNA secondary structure formation with the first few codons

    B cell immune profiles in dysbiotic vermiform appendixes of pancreatic cancer patients

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    Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid tumors and is resistant to immunotherapy. B cells play an essential role in PDAC progression and immune responses, both locally and systemically. Moreover, increasing evidence suggests that microbial compositions inside the tumor, as well as in the oral cavity and the gut, are important factors in shaping the PDAC immune landscape. However, the gut-associated lymphoid tissue (GALT) has not previously been explored in PDAC patients. In this study, we analyzed healthy vermiform appendix (VA) from 20 patients with PDAC and 32 patients with colon diseases by gene expression immune profiling, flow cytometry analysis, and microbiome sequencing. We show that the VA GALT of PDAC patients exhibits markers of increased inflammation and cytotoxic cell activity. In contrast, B cell function is decreased in PDAC VA GALT based on gene expression profiling; B cells express significantly fewer MHC class II surface receptors, whereas plasma cells express the immune checkpoint molecule HLA-G. Additionally, the vermiform appendix microbiome of PDAC patients is enriched with Klebsiella pneumoniae, Bifidobacterium animalis, and Adlercreutzia equolifaciens, while certain commensals are depleted. Our findings may suggest impaired B cell function within the GALT of PDAC patients, which could potentially be linked to microbial dysbiosis. Additional investigations are imperative to validate our observations and explore these potential targets of future therapies.</p

    B cell immune profiles in dysbiotic vermiform appendixes of pancreatic cancer patients

    Get PDF
    Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid tumors and is resistant to immunotherapy. B cells play an essential role in PDAC progression and immune responses, both locally and systemically. Moreover, increasing evidence suggests that microbial compositions inside the tumor, as well as in the oral cavity and the gut, are important factors in shaping the PDAC immune landscape. However, the gut-associated lymphoid tissue (GALT) has not previously been explored in PDAC patients. In this study, we analyzed healthy vermiform appendix (VA) from 20 patients with PDAC and 32 patients with colon diseases by gene expression immune profiling, flow cytometry analysis, and microbiome sequencing. We show that the VA GALT of PDAC patients exhibits markers of increased inflammation and cytotoxic cell activity. In contrast, B cell function is decreased in PDAC VA GALT based on gene expression profiling; B cells express significantly fewer MHC class II surface receptors, whereas plasma cells express the immune checkpoint molecule HLA-G. Additionally, the vermiform appendix microbiome of PDAC patients is enriched with Klebsiella pneumoniae, Bifidobacterium animalis, and Adlercreutzia equolifaciens, while certain commensals are depleted. Our findings may suggest impaired B cell function within the GALT of PDAC patients, which could potentially be linked to microbial dysbiosis. Additional investigations are imperative to validate our observations and explore these potential targets of future therapies.</p
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