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This paper aims to present the advances related to the biotechnological application of lipases Y. lipolytica, presenting their properties and more efficient ways to use them in different industrial applications. Waste treatment and bioremediation highlight recent studies and advances and the interest in large-scale applications in the food sector and biofuel production. The USA and China, two major world powers in industy, are of utmost importance in the search for the improvement in the development and properties of a controlled system for the large-scale production of a significant number of applications of lipase from Y. lipolytica.

Cold environments include deep ocean, alpine, and polar areas. Even if the cold conditions are harsh and extreme for certain habitats, various species have been adapted to survive in them. Microalgae are among the most abundant microbial communities which have adapted to live in low light, low temperature, and ice coverage conditions typical of cold environments by activating different stress-responsive strategies. These species have been shown to have bioactivities with possible exploitation capabilities for human applications. Even if they are less explored compared to species living in more accessible sites, various activities have been highlighted, such as antioxidant and anticancer activities. This review is focused on summarizing these bioactivities and discussing the possible exploitation of cold-adapted microalgae. Thanks to the possibility of mass cultivating algae in controlled photobioreactors, eco-sustainable exploitation is in fact possible by sampling a few microalgal cells without impacting the environment.

Cell-free systems are a rapidly expanding platform technology with an important role in the engineering of biological systems. The key advantages that drive their broad adoption are increased efficiency, versatility, and low cost compared to in vivo systems. Traditionally, in vivo platforms have been used to synthesize novel and industrially relevant proteins and serve as a testbed for prototyping numerous biotechnologies such as genetic circuits and biosensors. Although in vivo platforms currently have many applications within biotechnology, they are hindered by time-constraining growth cycles, homeostatic considerations, and limited adaptability in production. Conversely, cell-free platforms are not hindered by constraints for supporting life and are therefore highly adaptable to a broad range of production and testing schemes. The advantages of cell-free platforms are being leveraged more commonly by the biotechnology community, and cell-free applications are expected to grow exponentially in the next decade. In this study, new and emerging applications of cell-free platforms, with a specific focus on cell-free protein synthesis (CFPS), will be examined. The current and near-future role of CFPS within metabolic engineering, prototyping, and biomanufacturing will be investigated as well as how the integration of machine learning is beneficial to these applications.

Cyberlindnera jadinii is widely used as a source of single-cell protein and is known for its ability to synthesize a great variety of valuable compounds for the food and pharmaceutical industries. Its capacity to produce compounds such as food additives, supplements, and organic acids, among other fine chemicals, has turned it into an attractive microorganism in the biotechnology field. In this review, we performed a robust phylogenetic analysis using the core proteome of C. jadinii and other fungal species, from Asco- to Basidiomycota, to elucidate the evolutionary roots of this species. In addition, we report the evolution of this species nomenclature over-time and the existence of a teleomorph (C. jadinii) and anamorph state (Candida utilis) and summarize the current nomenclature of most common strains. Finally, we highlight relevant traits of its physiology, the solute membrane transporters so far characterized, as well as the molecular tools currently available for its genomic manipulation. The emerging applications of this yeast reinforce its potential in the white biotechnology sector. Nonetheless, it is necessary to expand the knowledge on its metabolism, regulatory networks, and transport mechanisms, as well as to develop more robust genetic manipulation systems and synthetic biology tools to promote the full exploitation of C. jadinii.

Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.