Restricting detergent protease action to surface of protein fibres by chemical modification

Due to their excellent properties, such as thermostability, activity over a broad range of pH and efficient stain removal, proteases from Bacillus sp. are commonly used in the textile industry including industrial processes and laundry and represent one of the most important groups of enzymes. However, due to the action of proteases, severe damage on natural protein fibres such as silk and wool result after washing with detergents containing proteases. To include the benefits of proteases in a wool fibre friendly detergent formulation, the soluble polymer polyethylene glycol (PEG) was covalently attached to a protease from Bacillus licheniformis. In contrast to activation of PEG with cyanuric chloride (50%) activation with 1,1′-carbonyldiimidazole (CDI) lead to activity recovery above 90%. With these modified enzymes, hydrolytic attack on wool fibres could be successfully prevented up to 95% compared to the native enzymes. Colour difference (ΔE) measured in the three dimensional colour space showed good stain removal properties for the modified enzymes. Furthermore, half-life of the modified enzymes in buffers and commercial detergents solutions was nearly twice as high as those of the non-modified enzymes with values of up to 63 min. Out of the different modified proteases especially the B. licheniformis protease with the 2.0-kDa polymer attached both retained stain removal properties and did not hydrolyse/damage wool fibres

Impact of salt exposure on N-acetylgalactosamine-4-sulfatase (arylsulfatase B) activity, glycosaminoglycans, kininogen, and bradykinin

N -acetylgalactosamine-4-sulfatase (Arylsulfatase B; ARSB) is the enzyme that removes sulfate groups from the N-acetylgalactosamine-4-sulfate residue at the non-reducing end of chondroitin-4-sulfate (C4S) and dermatan sulfate (DS). Previous studies demonstrated reduction in cell-bound high molecular weight kininogen in normal rat kidney (NRK) epithelial cells when chondroitin-4-sulfate content was reduced following overexpression of ARSB activity, and chondroitinase ABC produced similar decline in cell-bound kininogen. Reduction in the cell-bound kininogen was associated with increase in secreted bradykinin. In this report, we extend the in vitro findings to in vivo models, and present findings in Dahl salt-sensitive (SS) rats exposed to high (SSH) and low salt (SSL) diets. In the renal tissue of the SSH rats, ARSB activity was significantly less than in the SSL rats, and chondroitin-4-sulfate and total sulfated glycosaminoglycan content were significantly greater. Disaccharide analysis confirmed marked increase in C4S disaccharides in the renal tissue of the SSH rats. In contrast, unsulfated, hyaluronan-derived disaccharides were increased in the rats on the low salt diet. In the SSH rats, with lower ARSB activity and higher C4S levels, cell-bound, high-molecular weight kininogen was greater and urinary bradykinin was lower. ARSB activity in renal tissue and NRK cells declined when exogenous chloride concentration was increased in vitro. The impact of high chloride exposure in vivo on ARSB, chondroitin-4-sulfation, and C4S-kininogen binding provides a mechanism that links dietary salt intake with bradykinin secretion and may be a factor in blood pressure regulation

DNA methylation-based classification of central nervous system tumours

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challengingwith substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology