43 research outputs found
Inhibition of lpmos by fermented persimmon juice
Fermented persimmon juice, Kakishibu, has traditionally been used for wood and paper protection. This protective effect stems at least partially from inhibition of microbial cellulose degrading enzymes. The inhibitory effect of Kakishibu on lytic polysaccharide monooxygenases (LPMOs) and on a cocktail of cellulose hydrolases was studied, using three different cellulosic substrates. Dose dependent inhibition of LPMO activity by a commercial Kakishibu product was assessed for the well-characterized LPMO from Thermoascus aurantiacus TaAA9A, and the inhibitory effect was confirmed on five additional microbial LPMOs. The model tannin compound, tannic acid exhibited a similar inhibitory effect on TaAA9A as Kakishibu. It was further shown that both polyethylene glycol and tannase can alleviate the inhibitory effect of Kakishibu and tannic acid, indicating a likely mechanism of inhibition caused by unspecific tannin–protein interactions
Exploiting photosynthesis-driven P450 activity to produce indican in tobacco chloroplasts
Photosynthetic organelles offer attractive features for engineering small molecule bioproduction by their ability to convert solar energy into chemical energy required for metabolism. The possibility to couple biochemical production directly to photosynthetic assimilation as a source of energy and substrates has intrigued metabolic engineers. Specifically, the chemical diversity found in plants often relies on cytochrome P450-mediated hydroxylations that depend on reductant supply for catalysis and which often lead to metabolic bottlenecks for heterologous production of complex molecules. By directing P450 enzymes to plant chloroplasts one can elegantly deal with such redox prerequisites. In this study, we explore the capacity of the plant photosynthetic machinery to drive P450-dependent formation of the indigo precursor indoxyl-β-D-glucoside (indican) by targeting an engineered indican biosynthetic pathway to tobacco (Nicotiana benthamiana) chloroplasts. We show that both native and engineered variants belonging to the human CYP2 family are catalytically active in chloroplasts when driven by photosynthetic reducing power and optimize construct designs to improve productivity. However, while increasing supply of tryptophan leads to an increase in indole accumulation, it does not improve indican productivity, suggesting that P450 activity limits overall productivity. Co-expression of different redox partners also does not improve productivity, indicating that supply of reducing power is not a bottleneck. Finally, in vitro kinetic measurements showed that the different redox partners were efficiently reduced by photosystem I but plant ferredoxin provided the highest light-dependent P450 activity. This study demonstrates the inherent ability of photosynthesis to support P450-dependent metabolic pathways. Plants and photosynthetic microbes are therefore uniquely suited for engineering P450-dependent metabolic pathways regardless of enzyme origin. Our findings have implications for metabolic engineering in photosynthetic hosts for production of high-value chemicals or drug metabolites for pharmacological studies
A fungal lytic polysaccharide monooxygenase is required for cell wall integrity, thermotolerance, and virulence of the fungal human pathogen Cryptococcus neoformans
Fungi often adapt to environmental stress by altering their size, shape, or rate of cell division. These morphological changes require reorganization of the cell wall, a structural feature external to the cell membrane composed of highly interconnected polysaccharides and glycoproteins. Lytic polysaccharide monooxygenases (LPMOs) are copper-dependent enzymes that are typically secreted into the extracellular space to catalyze initial oxidative steps in the degradation of complex biopolymers such as chitin and cellulose. However, their roles in modifying endogenous microbial carbohydrates are poorly characterized. The CEL1 gene in the human fungal pathogen Cryptococcus neoformans (Cn) is predicted by sequence homology to encode an LPMO of the AA9 enzyme family. The CEL1 gene is induced by host physiological pH and temperature, and it is primarily localized to the fungal cell wall. Targeted mutation of the CEL1 gene revealed that it is required for the expression of stress response phenotypes, including thermotolerance, cell wall integrity, and efficient cell cycle progression. Accordingly, a cel1Δ deletion mutant was avirulent in two models of C. neoformans infection. Therefore, in contrast to LPMO activity in other microorganisms that primarily targets exogenous polysaccharides, these data suggest that CnCel1 promotes intrinsic fungal cell wall remodeling events required for efficient adaptation to the host environment
A Federated Database for Obesity Research:An IMI-SOPHIA Study
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders
A Federated Database for Obesity Research:An IMI-SOPHIA Study
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p
A Federated Database for Obesity Research:An IMI-SOPHIA Study
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p
En Sjæl Efter Døden : en Apokalyptisk Komedie / Johan Ludvig Heiberg. Udg. af Dansklærerforeningen Ved Alfr. Ipsen
EN SJÆL EFTER DØDEN : EN APOKALYPTISK KOMEDIE / JOHAN LUDVIG HEIBERG. UDG. AF DANSKLÆRERFORENINGEN VED ALFR. IPSEN
En Sjæl Efter Døden : en Apokalyptisk Komedie / Johan Ludvig Heiberg. Udg. af Dansklærerforeningen Ved Alfr. Ipsen (1)
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