Complex systems in metabolic engineering

Build-a-bug workshop: Using microbial-host interactions and synthetic biology tools to create cancer therapies

Many systemically administered cancer therapies exhibit dose-limiting toxicities that reduce their effectiveness. To increase efficacy, bacterial delivery platforms have been developed that improve safety and prolong treatment. Bacteria are a unique class of therapy that selectively colonizes most solid tumors. As delivery vehicles, bacteria have been genetically modified to express a range of therapies that match multiple cancer indications. In this review, we describe a modular "build-a-bug" method that focuses on five design characteristics: bacterial strain (chassis), therapeutic compound, delivery method, immune-modulating features, and genetic control circuits. We emphasize how fundamental research into gut microbe pathogenesis has created safe bacterial therapies, some of which have entered clinical trials. The genomes of gut microbes are fertile grounds for discovery of components to improve delivery and modulate host immune responses. Future work coupling these delivery vehicles with insights from gut microbes could lead to the next generation of microbial cancer therapy.

Real-Time Monitoring of Dynamic Microbial Fe(III) Respiration Metabolism with a Living Cell-Compatible Electron-Sensing Probe

Monitoring microbial metabolism is vital for biomanufacturing processes optimization. However, it remains a grand challenge to offer insight into microbial metabolism due to particularly complex and dynamic processes. Here, we report an electron-sensing probe Zn₂ GeO₄ :Mn@Fe³⁺ for real-time and dynamic monitoring of Fe(III) respiration metabolism. The quenched persistent luminescence of Zn₂ GeO4:Mn@Fe³⁺ is recovered when Fe³⁺ accepted electrons from the dynamic Fe(III) respiration metabolism, enabling the real-time monitoring of microbial metabolism. The probe shows the capability to verify the role of related biomolecules in microbial Fe(III) respiration metabolism, to track the dynamic Fe(III) respiration metabolic response to environmental stress and microbial co-culture interactions. Furthermore, the Zn₂ GeO₄ :Mn@Fe³⁺ probe provides guidance for improving biosynthesis efficiency by monitoring Fe redox recycling in microbial co-culture.

Engineered protein switches for exogenous control of gene expression

There is an ongoing need in the synthetic biology community for novel ways to regulate gene expression. Protein switches, which sense biological inputs and respond with functional outputs, represent one way to meet this need. Despite the fact that there is already a large pool of transcription factors and signaling proteins available, the pool of existing switches lacks the substrate specificities and activities required for certain applications. Therefore, a large number of techniques have been applied to engineer switches with novel properties. Here we discuss some of these techniques by broadly organizing them into three approaches. We show how novel switches can be created through mutagenesis, domain swapping, or domain insertion. We then briefly discuss their use as biosensors and in complex genetic circuits.

Biosystems Design by Machine Learning

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desirable features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find nonobvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocesses. Finally, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

Tailor-made transcriptional biosensors for optimizing microbial cell factories

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

Engineering membrane and cell-wall programs for tolerance to toxic chemicals: Beyond solo genes

Metabolite toxicity in microbes, particularly at the membrane, remains a bottleneck in the production of fuels and chemicals. Under chemical stress, native adaptation mechanisms combat hyper-fluidization by modifying the phospholipids in the membrane. Recent work in fluxomics reveals the mechanism of how membrane damage negatively affects energy metabolism while lipidomic and transcriptomic analyses show that strains evolved to be tolerant maintain membrane fluidity under stress through a variety of mechanisms such as incorporation of cyclopropanated fatty acids, trans-unsaturated fatty acids, and upregulation of cell wall biosynthesis genes. Engineered strains with modifications made in the biosynthesis of fatty acids, peptidoglycan, and lipopolysaccharide have shown increased tolerance to exogenous stress as well as increased production of desired metabolites of industrial importance. We review recent advances in elucidation of mechanisms or toxicity and tolerance as well as efforts to engineer the bacterial membrane and cell wall.