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To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host’s cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of E. coli sigma factor 70 (σ 70 )- and B. subtilis σ B -, σ F - and σ W -dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems. Automated design tools and tailored subunits are beneficial in fine-tuning all components of a complex genetic circuit. Here the authors create E. coli and B. subtilis promoter libraries using FACS and HTS, from which an online promoter design tool has been developed using CNN.

Background Engineering bacterial strains to redirect the metabolism towards the production of a specific product has enabled the development of industrial biotechnology. However, rewiring the metabolism can have severe implications for a microorganism, rendering cells with stress symptoms such as a decreased growth rate, impaired protein synthesis, genetic instability and an aberrant cell size. On an industrial scale, this is reflected in processes that are not economically viable. Main text In literature, most stress symptoms are attributed to “metabolic burden”, however the actual triggers and stress mechanisms involved are poorly understood. Therefore, in this literature review, we aimed to get a better insight in how metabolic engineering affects Escherichia coli and link the observed stress symptoms to its cause. Understanding the possible implications that chosen engineering strategies have, will help to guide the reader towards optimising the envisioned process more efficiently. Conclusion This review addresses the gap in literature and discusses the triggers and effects of stress mechanisms that can be activated when (over)expressing (heterologous) proteins in Escherichia coli . It uncovers that the activation of the different stress mechanisms is complex and that many are interconnected. The reader is shown that care has to be taken when (over)expressing (heterologous) proteins as the cell’s metabolism is tightly regulated.

The transcriptional architecture of phages can deepen our understanding of the phage‐host infection process and can be of key importance for phage engineering and biotechnological applications. Here, we applied ONT‐cappable‐sequencing, a long‐read RNA‐sequencing technique, to study the regulatory mechanisms of Pseudomonas infecting giant phage 201ϕ2‐1. We identified 67 promoters and 132 terminators that together represent 92 transcriptional units. A full comparison of these data to the transcriptome of model Pseudomonas phage ϕKZ confirmed that the transcriptional programs of these prototypes of the Serwervirus and Phikzvirus genera are largely conserved, despite some subtle regulatory differences. Evidence supporting these shared mechanisms include the identification of highly similar sequence motifs for regulatory elements in both phages and the conservation of regulatory elements loci relative to homologous genes in each phage. Moreover, we discovered a sRNA in 201ϕ2‐1 that is highly conserved among prototype members of different giant phage genera. Sequencing of the 201ϕ2‐1 host genome resulted in its reclassification as Pseudomonas atacamensis, a close relative of the important agricultural biocontrol agent Pseudomonas chlororaphis. Finally, we conducted in vivo assays of eight 201ϕ2‐1 terminators and found them to strongly terminate transcription in P. chlororaphis. Control elements from phage transcriptional programs have a rich history for applications in biotechnology. In these studies, we demonstrate new insight into the transcriptional program of 201ϕ2‐1 and demonstrate the potential of its regulatory elements for novel and useful tools for synthetic biology circuitry. Transcriptomic studies on jumbo phages have been limited. From a phage biology perspective, insights into their transcriptome will improve our understanding of how they regulate their infection cycle. Moreover, phage transcriptomic studies are valuable for sourcing regulatory elements which can be exploited in microbial synthetic biology to tune gene expression.

The bio-based economy relies on sustainable, plant-derived resources for fuels, chemicals, materials, food and feed rather than on the evanescent usage of fossil resources. The cornerstone of this economy is the biorefinery, in which renewable resources are intelligently converted to a plethora of products, maximizing the valorization of the feedstocks. Innovation is a prerequisite to move a fossil-based economy toward sustainable alternatives, and the viability of the bio-based economy depends on the integration between plant (green) and industrial (white) biotechnology. Green biotechnology deals with primary production through the improvement of biomass crops, while white biotechnology deals with the conversion of biomass into products and energy. Waste streams are minimized during these processes or partly converted to biogas, which can be used to power the processing pipeline. The sustainability of this economy is guaranteed by a third technology pillar that uses thermochemical conversion to valorize waste streams and fix residual carbon as biochar in the soil, hence creating a carbon-negative cycle. These three different multidisciplinary pillars interact through the value chain of the bio-based economy.

Escherichia coli remains the best-established production organism in industrial biotechnology. However, when aerobic fermentation runs at high growth rates, considerable amounts of acetate are accumulated as by-product. This by-product has negative effects on growth and protein production. Over the last 20 years, substantial research efforts have been expended on reducing acetate accumulation during aerobic growth of E. coli on glucose. From the onset it was clear that this quest would not be a simple or uncomplicated one. Simple deletion of the acetate pathway reduced the acetate accumulation, but other by-products were formed. This mini review gives a clear outline of these research efforts and their outcome, including bioprocess level approaches and genetic approaches. Recently, the latter seems to have some promising results.

Promoter sequences are important genetic control elements. Through their interaction with RNA polymerase they determine transcription strength and specificity, thereby regulating the first step in gene expression. Consequently, they can be targeted as elements to control predictability and tuneability of a genetic circuit, which is essential in applications such as the development of robust microbial cell factories. This review considers the promoter elements implicated in the three stages of transcription initiation, detailing the complex interplay of sequence-specific interactions that are involved, and highlighting that DNA sequence features beyond the core promoter elements work in a combinatorial manner to determine transcriptional strength. In particular, we emphasize that, aside from promoter recognition, transcription initiation is also defined by the kinetics of open complex formation and promoter escape, which are also known to be highly sequence specific. Significantly, we focus on how insights into these interactions can be manipulated to lay the foundation for a more rational approach to promoter engineering. Unravelling the intricate and sequence-specific regulation of transcription initiation by promoter sequences is crucial, as an in-depth understanding of promoter–RNA polymerase interactions can pave the way to a more rational approach to promoter engineering.

Abstract In the innovative field of engineered living materials (ELMs) microbiology and material sciences meet. These materials incorporate living organisms, such as bacteria, fungi, plants, or algae, to enable unique functions like self-assembly, actuation, and dynamic interaction. By utilizing (micro)biological systems in material design, ELMs promise to transform industries including healthcare, construction, and agriculture. In the early phase of ELM technology development, researchers implemented a single living strain in an already established user material. However, the complexity and potential of these materials is limited by the abilities of this single strain. Even though synthetic biology brings the opportunity to add a range of nonnative bioactivities to these cells and thus the material, the increasing metabolic burden upon implementation of multiple nonnative pathways limits the capacity of a single strain. Furthermore, higher organisms and nonstandard hosts are often desired in material settings for their native physical or metabolic advantages. However these are not always straightforward to further engineer. Thus, the use of multiple, specialized strains broadens the functionalities and thus the applicability of ELMs. Multistrain ELMs are a brand-new technology, with many promising applications. This review describes a modular and rational design framework for engineered living materials, enabled by the functional diversity of multistrain microbial consortia, to create targeted, responsive, and fully biological materials.

Background Engineering bacteria with the purpose of optimizing the production of interesting molecules often leads to a decrease in growth due to metabolic burden or toxicity. By delaying the production in time, these negative effects on the growth can be avoided in a process called a two-stage fermentation. Main text During this two-stage fermentation process, the production stage is only activated once sufficient cell mass is obtained. Besides the possibility of using external triggers, such as chemical molecules or changing fermentation parameters to induce the production stage, there is a renewed interest towards autoinducible systems. These systems, such as quorum sensing, do not require the extra interference with the fermentation broth to start the induction. In this review, we discuss the different possibilities of both external and autoinduction methods to obtain a two-stage fermentation. Additionally, an overview is given of the tuning methods that can be applied to optimize the induction process. Finally, future challenges and prospects of (auto)inducible expression systems are discussed. Conclusion There are numerous methods to obtain a two-stage fermentation process each with their own advantages and disadvantages. Even though chemically inducible expression systems are well-established, an increasing interest is going towards autoinducible expression systems, such as quorum sensing. Although these newer techniques cannot rely on the decades of characterization and applications as is the case for chemically inducible promoters, their advantages might lead to a shift in future inducible expression systems.

Gene expression is regulated through a complex interplay of different transcription factors (TFs) which can enhance or inhibit gene transcription. ArcA is a global regulator that regulates genes involved in different metabolic pathways, while IclR as a local regulator, controls the transcription of the glyoxylate pathway genes of the aceBAK operon. This study investigates the physiological and metabolic consequences of arcA and iclR deletions on E. coli K12 MG1655 under glucose abundant and limiting conditions and compares the results with the metabolic characteristics of E. coli BL21 (DE3). The deletion of arcA and iclR results in an increase in the biomass yield both under glucose abundant and limiting conditions, approaching the maximum theoretical yield of 0.65 c-mole/c-mole glucose under glucose abundant conditions. This can be explained by the lower flux through several CO2 producing pathways in the E. coli K12 ΔarcAΔiclR double knockout strain. Due to iclR gene deletion, the glyoxylate pathway is activated resulting in a redirection of 30% of the isocitrate molecules directly to succinate and malate without CO2 production. Furthermore, a higher flux at the entrance of the TCA was noticed due to arcA gene deletion, resulting in a reduced production of acetate and less carbon loss. Under glucose limiting conditions the flux through the glyoxylate pathway is further increased in the ΔiclR knockout strain, but this effect was not observed in the double knockout strain. Also a striking correlation between the glyoxylate flux data and the isocitrate lyase activity was observed for almost all strains and under both growth conditions, illustrating the transcriptional control of this pathway. Finally, similar central metabolic fluxes were observed in E. coli K12 ΔarcA ΔiclR compared to the industrially relevant E. coli BL21 (DE3), especially with respect to the pentose pathway, the glyoxylate pathway, and the TCA fluxes. In addition, a comparison of the genome sequences of the two strains showed that BL21 possesses two mutations in the promoter region of iclR and rare codons are present in arcA implying a lower tRNA acceptance. Both phenomena presumably result in a reduced ArcA and IclR synthesis in BL21, which contributes to the similar physiology as observed in E. coli K12 ΔarcAΔiclR. The deletion of arcA results in a decrease of repression on transcription of TCA cycle genes under glucose abundant conditions, without significantly affecting the glyoxylate pathway activity. IclR clearly represses transcription of glyoxylate pathway genes under glucose abundance, a condition in which Crp activation is absent. Under glucose limitation, Crp is responsible for the high glyoxylate flux, but IclR still represses transcription. Finally, in E. coli BL21 (DE3), ArcA and IclR are poorly expressed, explaining the similar fluxes observed compared to the ΔarcAΔiclR strain.

Abstract 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.