Reactor control system in bacterial co-culture based on fluorescent proteins using an Arduino-based home-made device

Synthetic microbial ecology: engineering habitats for modular consortia

Microbiomes, the complex networks of micro-organisms and the molecules through which they interact, play a crucial role in health and ecology. Over at least the past two decades, engineering biology has made significant progress, impacting the bio-based industry, health, and environmental sectors; but has only recently begun to explore the engineering of microbial ecosystems. The creation of synthetic microbial communities presents opportunities to help us understand the dynamics of wild ecosystems, learn how to manipulate and interact with existing microbiomes for therapeutic and other purposes, and to create entirely new microbial communities capable of undertaking tasks for industrial biology. Here, we describe how synthetic ecosystems can be constructed and controlled, focusing on how the available methods and interaction mechanisms facilitate the regulation of community composition and output. While experimental decisions are dictated by intended applications, the vast number of tools available suggests great opportunity for researchers to develop a diverse array of novel microbial ecosystems.

Metabolome analysis of metabolic burden in Escherichia coli caused by overexpression of green fluorescent protein and delta-rhodopsin

Overexpression of proteins by introducing a DNA vector is among the most important tools for the metabolic engineering of microorganisms such as Escherichia coli. Protein overexpression imposes a burden on metabolism because metabolic pathways must supply building blocks for protein and DNA synthesis. Different E. coli strains have distinct metabolic capacities. In this study, two proteins were overexpressed in four E. coli strains (MG1655(DE3), W3110(DE3), BL21star(DE3), and Rosetta(DE3)), and their effects on metabolic burden were investigated. Metabolomic analysis showed that E. coli strains overexpressing green fluorescent protein had decreased levels of several metabolites, with a positive correlation between the number of reduced metabolites and green fluorescent protein expression levels. Moreover, nucleic acid-related metabolites decreased, indicating a metabolic burden in the E. coli strains, and the growth rate and protein expression levels were improved by supplementation with the five nucleosides. In contrast, two strains overexpressing delta rhodopsin, a microbial membrane rhodopsin from Haloterrigena turkmenica, led to a metabolic burden and decrease in the amino acids Ala, Val, Leu, Ile, Thr, Phe, Asp, and Trp, which are the most frequent amino acids in the delta rhodopsin protein sequence. The metabolic burden caused by protein overexpression was influenced by the metabolic capacity of the host strains and the sequences of the overexpressed proteins. Detailed characterization of the effects of protein expression on the metabolic state of engineered cells using metabolomics will provide insights into improving the production of target compounds.

Recent advances in screening amino acid overproducers

Microbial fermentation has contributed to 80% of global amino acid production. The key to microbial fermentation is to obtain fermentation strains with high performance to produce target amino acids with a high yield. These strains are primarily derived from screening enormous mutant libraries. Therefore, a high-throughput, rapid, accurate, and universal screening strategy for amino acid overproducers has become a guarantee for obtaining optional amino acid overproducers. In recent years, the rapid development of various novel screening strategies has been witnessed. However, proper analysis and discussion of these innovative technologies are lacking. Here we systematically reviewed recent advances in screening strategies: the auxotrophic-based strategy, the biosensor-based strategy, and the latest translation-based screening strategy. The design principle, application scope, working efficiency, screening accuracy, and universality of these strategies were discussed in detail. The potential for screening nonstandard amino acid overproducers was also analyzed. Guidance for the improvement of future screening strategies is provided in this review, which could expedite the reconstruction of amino acid overproducers and help promote the fermentation industry to reduce cost, increase yield, and improve quality.

Arduino Soft Sensor for Monitoring Schizochytrium sp. Fermentation, a Proof of Concept for the Industrial Application of Genome-Scale Metabolic Models in the Context of Pharma 4.0

Schizochytrium sp. is a microorganism cultured for producing docosahexaenoic acid (DHA). Genome-scale metabolic modeling (GEM) is a promising technique for describing gen-protein-reactions in cells, but with still limited industrial application due to its complexity and high computation requirements. In this work, we simplified GEM results regarding the relationship between the specific oxygen uptake rate (−rO2), the specific growth rate (µ), and the rate of lipid synthesis (rL) using an evolutionary algorithm for developing a model that can be used by a soft sensor for fermentation monitoring. The soft sensor estimated the concentration of active biomass (X), glutamate (N), lipids (L), and DHA in a Schizochytrium sp. fermentation using the dissolved oxygen tension (DO) and the oxygen mass transfer coefficient (kLa) as online input variables. The soft sensor model described the biomass concentration response of four reported experiments characterized by different kLa values. The average range normalized root-mean-square error for X, N, L, and DHA were equal to 1.1, 1.3, 1.1, and 3.2%, respectively, suggesting an acceptable generalization capacity. The feasibility of implementing the soft sensor over a low-cost electronic board was successfully tested using an Arduino UNO, showing a novel path for applying GEM-based soft sensors in the context of Pharma 4.0.

Cybergenetic control of microbial community composition

The use of bacterial communities in bioproduction instead of monocultures has potential advantages including increased productivity through division of labour, ability to utilise cheaper substrates, and robustness against perturbations. A key challenge in the application of engineered bacterial communities is the ability to reliably control the composition of the community in terms of its constituent species. This is crucial to prevent faster growing species from outcompeting others with a lower relative fitness, and to ensure that all species are present at an optimal ratio during different steps in a biotechnological process. In contrast to purely biological approaches such as synthetic quorum sensing circuits or paired auxotrophies, cybergenetic control techniques - those in which computers interface with living cells-are emerging as an alternative approach with many advantages. The community composition is measured through methods such as fluorescence intensity or flow cytometry, with measured data fed real-time into a computer. A control action is computed using a variety of possible control algorithms and then applied to the system, with actuation taking the form of chemical (e.g., inducers, nutrients) or physical (e.g., optogenetic, mechanical) inputs. Subsequent changes in composition are then measured and the cycle repeated, maintaining or driving the system to a desired state. This review discusses recent and future developments in methods for implementing cybergenetic control systems, contrasts their capabilities with those of traditional biological methods of population control, and discusses future directions and outstanding challenges for the field.

Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback

Communities of microbes play important roles in natural environments and hold great potential for deploying division-of-labor strategies in synthetic biology and bioproduction. However, the difficulty of controlling the composition of microbial consortia over time hinders their optimal use in many applications. Here, we present a fully automated, high-throughput platform that combines real-time measurements and computer-controlled optogenetic modulation of bacterial growth to implement precise and robust compositional control of a two-strain E. coli community. In addition, we develop a general framework for dynamic modeling of synthetic genetic circuits in the physiological context of E. coli and use a host-aware model to determine the optimal control parameters of our closed-loop compositional control system. Our platform succeeds in stabilizing the strain ratio of multiple parallel co-cultures at arbitrary levels and in changing these targets over time, opening the door for the implementation of dynamic compositional programs in synthetic bacterial communities.

Establishment of Green- and Red-Fluorescent Reporter Proteins Based on the Fluorescence-Activating and Absorption-Shifting Tag for Use in Acetogenic and Solventogenic Anaerobes

Anaerobic bacteria are promising biocatalysts to produce industrially relevant products from nonfood feedstocks. Several anaerobes are genetically accessible, and various molecular tools for metabolic engineering are available. Still, the use of bright fluorescent reporters, which are commonly used in molecular biological approaches is limited under anaerobic conditions. Therefore, the establishment of different anaerobic fluorescent reporter proteins is of great interest. Here, we present the establishment of the green- and red-fluorescent reporter proteins greenFAST and redFAST for use in different solventogenic and acetogenic bacteria. Green fluorescence of greenFAST was bright in Clostridium saccharoperbutylacetonicum, Clostridium acetobutylicum, Acetobacterium woodii, and Eubacterium limosum, while only C. saccharoperbutylacetonicum showed bright red fluorescence when producing redFAST. We used both reporter proteins in C. saccharoperbutylacetonicum for multicolor approaches. These include the investigation of the co-culture dynamics of metabolically engineered strains. Moreover, we established a tightly regulated inducible two-plasmid system and used greenFAST and redFAST to track the coexistence and interaction of both plasmids under anaerobic conditions in C. saccharoperbutylacetonicum. The establishment of greenFAST and redFAST as fluorescent reporters opens the door for further multicolor approaches to investigate cell dynamics, gene expression, or protein localization under anaerobic conditions.