A thread to discuss New Biotech

A marine photosynthetic microbial cell factory as a platform for spider silk production

Photosynthetic microorganisms such as cyanobacteria, purple bacteria and microalgae have attracted great interest as promising platforms for economical and sustainable production of bioenergy, biochemicals, and biopolymers. Here, we demonstrate heterotrophic production of spider dragline silk proteins, major ampullate spidroins (MaSp), in a marine photosynthetic purple bacterium, Rhodovulum sulfidophilum , under both photoheterotrophic and photoautotrophic growth conditions. Spider silk is a biodegradable and biocompatible material with remarkable mechanical properties. R. sulfidophilum grow by utilizing abundant and renewable nonfood bioresources such as seawater, sunlight, and gaseous CO2 and N2, thus making this photosynthetic microbial cell factory a promising green and sustainable production platform for proteins and biopolymers, including spider silks.


Sustainable Wood-Based Hierarchical Solar Steam Generator: A Biomimetic Design with Reduced Vaporization Enthalpy of Water

Water purification by solar distillation is considered a promising technology for producing clean water from undrinkable water resources. A solar steam generator is a central part of a solar distillation process to separate water and contaminants. Here, we report an efficient and sustainable hierarchical solar steam generator (HSSG) with reduced vaporization enthalpy based on bacterial cellulose (BC) nanocomposites.



Tropane alkaloids from nightshade plants are neurotransmitter inhibitors that are used for treating neuromuscular disorders and are classified as essential medicines by the World Health Organization1,2. Challenges in global supplies have resulted in frequent shortages of these drugs3,4. Further vulnerabilities in supply chains have been revealed by events such as the Australian wildfires5 and the COVID-19 pandemic6. Rapidly deployable production strategies that are robust to environmental and socioeconomic upheaval7,8 are needed. Here we engineered baker’s yeast to produce the medicinal alkaloids hyoscyamine and scopolamine, starting from simple sugars and amino acids. We combined functional genomics to identify a missing pathway enzyme, protein engineering to enable the functional expression of an acyltransferase via trafficking to the vacuole, heterologous transporters to facilitate intracellular routing, and strain optimization to improve titres. Our integrated system positions more than twenty proteins adapted from yeast, bacteria, plants and animals across six sub-cellular locations to recapitulate the spatial organization of tropane alkaloid biosynthesis in plants. Microbial biosynthesis platforms can facilitate the discovery of tropane alkaloid derivatives as new therapeutic agents for neurological disease and, once scaled, enable robust and agile supply of these essential medicines.


Abstract: A machine learning Automated Recommendation Tool for synthetic biology

Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, fatty acids, and tryptophan. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing.