Interface engineering of cellobiose dehydrogenase improves interdomain electron transfer.

Cellobiose dehydrogenase (CDH) is a bioelectrocatalyst that enables direct electron transfer (DET) in biosensors and biofuel cells. The application of this bidomain hemoflavoenzyme for physiological glucose measurements is limited by its acidic pH optimum and slow interdomain electron transfer (IET) at pH 7.5. The reason for this rate-limiting electron transfer step is electrostatic repulsion at the interface between the catalytic dehydrogenase domain and the electron mediating cytochrome domain (CYT). We applied rational interface engineering to accelerate the IET for the pH prevailing in blood or interstitial fluid. Phylogenetic and structural analyses guided the design of 17 variants in which acidic amino acids were mutated at the CYT domain. Five mutations (G71K, D160K, Q174K, D177K, M180K) increased the pH optimum and IET rate. Structure-based analysis of the variants suggested two mechanisms explaining the improvements: electrostatic steering and stabilization of the closed state by hydrogen bonding. Combining the mutations into six combinatorial variants with up to five mutations shifted the pH optimum from 4.5 to 7.0 and increased the IET at pH 7.5 over 12-fold from 0.1 to 1.24 s-1 . While the mutants sustained a high enzymatic activity and even surpassed the IET of the wild-type enzyme, the accumulated positive charges on the CYT domain decreased DET, highlighting the importance of CYT for IET and DET. This study shows that interface engineering is an effective strategy to shift the pH optimum and improve the IET of CDH, but future work needs to maintain the DET of the CYT domain for bioelectronic applications.

Resource, Collaborator, or Individual Cow? Applying Q Methodology to Investigate Austrian Farmers' Viewpoints on Motivational Aspects of Improving Animal Welfare.

One keystone to successful welfare improvement endeavors is a respected cooperation between farmer and advisor (e.g., veterinarian), which requires a thorough understanding of what motivates farmer behavior. In this respect, Q methodology offers a promising approach in investigating individual motivational patterns and to discriminate between and describe typologies of farmers. In our study we explored, based on a sample of 34 Austrian dairy farmers, how 39 potentially motivating statements regarding the improvement of dairy cow health and welfare were assessed. We were able to identify and describe four different viewpoints, explaining 47% of total study variance. All four viewpoints have in common that pride in a healthy herd is motivating to work toward improved animal health and welfare to a certain extent, but meeting legal requirements is rather not. Viewpoint 1 acknowledges welfare for economic performance, ease of work and short working hours but does not make allowance for outside interference. Participants loading on Viewpoint 2 also show a focus on economic aspects but, keep close track of the animal welfare debate recognizing its potential to improve the public image of dairy farming. Even though they cautiously criticize an exploitative application of dairy farming, they do not want to be understood as role models. With regards to animal welfare, farmers sharing Viewpoint 3 perceive themselves as superior to and show little reluctance of comparison with mainstream farming. For them, the animal as sentient being itself owns some intrinsic value and it is necessary to strike a balance between economic and other, ethical considerations. Viewpoint 4 perceives cows as equal collaborators who deserve to be treated with respect and appreciation and is willing to accept certain economic losses in order to maintain high standards regarding animal health and welfare. Using Q methodology, we have been able to draw high resolution images of different farmer typologies, enabling advisors to tailor intervention strategies specifically addressing leverage points with a high chance of farmer compliance.