The primary cilium is a ubiquitous, microtubule-based cellular organelle. Primary cilia dysfunction results in a group of disorders termed ciliopathies. C2 domain containing 3 centriole elongation regulator (C2cd3), encodes a centriolar protein essential for ciliogenesis. Mutations in human C2CD3 are associated with the human ciliopathy Oral-Facial-Digital syndrome type 14 (OFD14). In order to better understand the etiology of ciliopathies including OFD14, we generated numerous murine models targeting C2cd3. Initial analysis revealed several tissue-specific isoforms of C2cd3, and while the loss of C2cd3 has previously been reported to result in exencephaly, tight mesencephalic flexure, pericardial edema, abnormal heart looping and a twisted body axis, further analysis revealed that genetic background may also contribute to phenotypic variation. Additional analyses of a conditional allelic series targeting C-terminal PKC-C2 domains or the N-terminal C2CD3N-C2 domain of C2cd3 revealed a variable degree of phenotypic severity, suggesting that while the N-terminal C2CD3N-C2 domain was critical for early embryonic development as a whole, there was also a craniofacial specific role for the C2CD3N-C2 domains. Together, through generation of novel models and evaluation of C2cd3 expression, these data provide valuable insight into mechanisms of pathology for craniofacial ciliopathies that can be further explored in the future.Protein secondary structures have been identified as the links in the physical processes of primary sequences, typically random coils, folding into functional tertiary structures that enable proteins to involve a variety of biological events in life science. Therefore, an efficient protein secondary structure predictor is of importance especially when the structure of an amino acid sequence fragment is not solved by high-resolution experiments, such as X-ray crystallography, cryo-electron microscopy, and nuclear magnetic resonance spectroscopy, which are usually time consuming and expensive. In this paper, a reductive deep learning model MLPRNN has been proposed to predict either 3-state or 8-state protein secondary structures. The prediction accuracy by the MLPRNN on the publicly available benchmark CB513 data set is comparable with those by other state-of-the-art models. More importantly, taking into account the reductive architecture, MLPRNN could be a baseline for future developments.To enable a sustainable supply of chemicals, novel biotechnological solutions are required that replace the reliance on fossil resources. One potential solution is to utilize tailored biosynthetic modules for the metabolic conversion of CO2 or organic waste to chemicals and fuel by microorganisms. Currently, it is challenging to commercialize biotechnological processes for renewable chemical biomanufacturing because of a lack of highly active and specific biocatalysts. As experimental methods to engineer biocatalysts are time- and cost-intensive, it is important to establish efficient and reliable computational tools that can speed up the identification or optimization of selective, highly active, and stable enzyme variants for utilization in the biotechnological industry. Here, we review and suggest combinations of effective state-of-the-art software and online tools available for computational enzyme engineering pipelines to optimize metabolic pathways for the biosynthesis of renewable chemicals. Using examples relevant for biotechnology, we explain the underlying principles of enzyme engineering and design and illuminate future directions for automated optimization of biocatalysts for the assembly of synthetic metabolic pathways.In this work, an environment-friendly enzymatic strategy was developed for the valorisation of dye-containing wastewaters. We set up biocatalytic processes for the conversion of azo dyes representative of the main classes used in the textile industry into valuable aromatic compounds aromatic amines, phenoxazinones, phenazines, and naphthoquinones. First, purified preparations of PpAzoR azoreductase efficiently reduced mordant, acid, reactive, and direct azo dyes into aromatic amines, and CotA-laccase oxidised these compounds into phenazines, phenoxazinones, and naphthoquinones. Second, whole cells containing the overproduced enzymes were utilised in the two-step enzymatic conversion of the model mordant black 9 dye into sodium 2-amino-3-oxo-3H-phenoxazine-8-sulphonate, allowing to overcome the drawbacks associated with the use of expensive purified enzymes, co-factors, or exquisite reaction conditions. Third, cells immobilised in sodium alginate allowed recycling the biocatalysts and achieving very good to excellent final phenoxazine product yields (up to 80%) in water and with less impurities in the final reaction mixtures. Finally, one-pot systems using recycled immobilised cells co-producing both enzymes resulted in the highest phenoxazinone yields (90%) through the sequential use of static and stirring conditions, controlling the oxygenation of reaction mixtures and the successive activity of azoreductase (anaerobic) and laccase (aerobic).Medium-chain carboxylates (MCC) derived from biomass biorefining are attractive biochemicals to uncouple the production of a wide array of products from the use of non-renewable sources. Biological conversion of biomass-derived lactate during secondary fermentation can be steered to produce a variety of MCC through chain elongation. https://www.selleckchem.com/products/nvp-tae226.html We explored the effects of zero-valent iron nanoparticles (nZVI) and lactate enantiomers on substrate consumption, product formation and microbiome composition in batch lactate-based chain elongation. In abiotic tests, nZVI supported chemical hydrolysis of lactate oligomers present in concentrated lactic acid. In fermentation experiments, nZVI created favorable conditions for either chain-elongating or propionate-producing microbiomes in a dose-dependent manner. Improved lactate conversion rates and n-caproate production were promoted at 0.5-2 g nZVI⋅L-1 while propionate formation became relevant at ≥ 3.5 g nZVI⋅L-1. Even-chain carboxylates (n-butyrate) were produced when using enantiopure and racemic lactate with lactate conversion rates increased in nZVI presence (1 g⋅L-1).