Search Results (5)

Carbonic anhydrase (CA), an enzyme catalyzing the reversible hydration reaction of carbon dioxide (CO₂), is considered a promising biocatalyst for CO₂ reduction. The α-CA of Thermovibrio ammonificans (taCA) has emerged as a compelling candidate due to its high thermostability, a critical factor for industrial applications. However, the low-level expression and poor in vitro solubility have hampered further utilization of taCA. Recently, these limitations have been addressed through the fusion of the NEXT tag, a marine-derived, intrinsically disordered small peptide that enhances protein expression and solubility. In this study, the solubility and stability of NEXT-taCA were further investigated. When the linker length between the NEXT tag and the taCA was shortened, the expression level decreased without compromising solubility-enhancing performance. A comparison between the NEXT tag and the NT11 tag demonstrated the NEXT tag’s superiority in improving both the expression and solubility of taCA. While the thermostability of taCA was lower than that of the extensively engineered DvCA10, the NEXT-tagged taCA exhibited a 30% improvement in long-term thermostability compared to the untagged taCA, suggesting that enhanced solubility can contribute to enzyme thermostability. Furthermore, the bioprospecting of two intrinsically disordered peptides (Hcr and Hku tags) as novel solubility-enhancing fusion tags was explored, demonstrating their performance in improving the expression and solubility of taCA. These efforts will advance the practical application of taCA and provide tools and insights for enzyme biochemistry and bioengineering. Full article

Protein engineering is the design and modification of protein structures to optimize their functions or create novel functionalities for applications in biotechnology, medicine or industry. It represents an essential scientific solution for many of the environmental and societal challenges ahead of us, such as polymer degradation. Unlike traditional chemical methods, enzyme-mediated degradation is selective and environmentally friendly and requires milder conditions. Computational methods will play a critical role in developing such solutions by enabling more efficient bioprospecting of natural polymer-degrading enzymes. They provide structural information, generate mechanistic studies, and formulate new hypotheses, facilitating the modeling and modification of these biocatalysts through enzyme engineering. The recent development of pluriZymes constitutes an example, providing a rational mechanism to integrate different biochemical processes into one single enzyme. In this review, we summarize our recent efforts in this line and introduce our early work towards polymer degradation using a pluriZyme-like technology, including our latest development in PET nanoparticle degradation. Moreover, we provide a comprehensive recipe for developing one’s own pluriZyme so that different laboratories can experiment with them and establish new limits. With modest computational resources and with help from this review, your first pluriZyme is one step closer. Full article

When bioprospecting for novel industrial enzymes, substrate promiscuity is a desirable property that increases the reusability of the enzyme. Among industrial enzymes, ester hydrolases have great relevance for which the demand has not ceased to increase. However, the search for new substrate promiscuous ester hydrolases is not trivial since the mechanism behind this property is greatly influenced by the active site’s structural and physicochemical characteristics. These characteristics must be computed from the 3D structure, which is rarely available and expensive to measure, hence the need for a method that can predict promiscuity from sequence alone. Here we report such a method called EP-pred, an ensemble binary classifier, that combines three machine learning algorithms: SVM, KNN, and a Linear model. EP-pred has been evaluated against the Lipase Engineering Database together with a hidden Markov approach leading to a final set of ten sequences predicted to encode promiscuous esterases. Experimental results confirmed the validity of our method since all ten proteins were found to exhibit a broad substrate ambiguity. Full article

Oceans possess tremendous diversity in microbial life. The enzymatic machinery that marine bacteria present is the result of extensive evolution to assist cell survival under the harsh and continuously changing conditions found in the marine environment. Several bacterial cells and enzymes are already used at an industrial scale, but novel biocatalysts are still needed for sustainable industrial applications, with benefits for both public health and the environment. Metagenomic techniques have enabled the discovery of novel biocatalysts, biosynthetic pathways, and microbial identification without their cultivation. However, a key stage for application of novel biocatalysts is the need for rapid evaluation of the feasibility of the bioprocess. Cultivation of not-yet-cultured bacteria is challenging and requires new methodologies to enable growth of the bacteria present in collected environmental samples, but, once a bacterium is isolated, its enzyme activities are easily measured. High-throughput screening techniques have also been used successfully, and innovative in vitro screening platforms to rapidly identify relevant enzymatic activities continue to improve. Small-scale approaches and process integration could improve the study and development of new bioprocesses to produce commercially interesting products. In this work, the latest studies related to (i) the growth of marine bacteria under laboratorial conditions, (ii) screening techniques for bioprospecting, and (iii) bioprocess development using microreactors and miniaturized systems are reviewed and discussed. Full article

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer–Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments. Full article