Engineering diverse fatty acid compositions of phospholipids in Escherichia coli.

Bacterial fatty acids (FAs) are an essential component of the cellular membrane and are an important source of renewable chemicals as they can be converted to fatty alcohols, esters, ketones, and alkanes, and used as biofuels, detergents, lubricants, and commodity chemicals. Most prior FA bioconversions have been performed on the carboxylic acid group. Modification of the FA hydrocarbon chain could substantially expand the structural and functional diversity of FA-derived products. Additionally, the effects of such modified FAs on the growth and metabolic state of their producing cells are not well understood. Here we engineer novel Escherichia coli phospholipid biosynthetic pathways, creating strains with distinct FA profiles enriched in ω7-unsaturated FAs (ω7-UFAs, 75%), Δ5-unsaturated FAs (Δ5-UFAs, 60%), cyclopropane FAs (CFAs, 55%), internally-branched FAs (IBFAs, 40%), and Δ5,ω7-double unsaturated FAs (DUFAs, 46%). Although bearing drastically different FA profiles in phospholipids, UFA, CFA, and IBFA enriched strains display wild-type-like phenotypic profiling and growth. Transcriptomic analysis reveals DUFA production drives increased differential expression and the induction of the fur iron starvation transcriptional cascade, but higher TCA cycle activation compared to the UFA producing strain. This likely reflects a slight cost imparted for DUFA production, which resulted in lower maximum growth in some, but not all, environmental conditions. The IBFA-enriched strain was further engineered to produce free IBFAs, releasing 96 mg/L free IBFAs from 154 mg/L of the total cellular IBFA pool. This work has resulted in significantly altered FA profiles of membrane lipids in E. coli, greatly increasing our understanding of the effects of FA structure diversity on the transcriptome, growth, and ability to react to stress.

The Growth Dependent Design Constraints of Transcription-Factor-Based Metabolite Biosensors.

Metabolite biosensors based on metabolite-responsive transcription factors are key synthetic biology components for sensing and precisely controlling cellular metabolism. Biosensors are often designed under laboratory conditions but are deployed in applications where cellular growth rate differs drastically from its initial characterization. Here we asked how growth rate impacts the minimum and maximum biosensor outputs and the dynamic range, which are key metrics of biosensor performance. Using LacI, TetR, and FadR-based biosensors in Escherichia coli as models, we find that the dynamic range of different biosensors have different growth rate dependencies. We developed a kinetic model to explore how tuning biosensor parameters impact the dynamic range growth rate dependence. Our modeling and experimental results revealed that the effects to dynamic range and its growth rate dependence are often coupled, and the metabolite transport mechanisms shape the dynamic range-growth rate response. This work provides a systematic understanding of biosensor performance under different growth rates, which will be useful for predicting biosensor behavior in broad synthetic biology and metabolic engineering applications.

Transient Antibiotic Tolerance Triggered by Nutrient Shifts From Gluconeogenic Carbon Sources to Fatty Acid.

Nutrient shifts from glycolytic-to-gluconeogenic carbon sources can create large sub-populations of extremely antibiotic tolerant bacteria, called persisters. Positive feedback in Escherichia coli central metabolism was believed to play a key role in the formation of persister cells. To examine whether positive feedback in nutrient transport can also support high persistence to ß-lactams, we performed nutrient shifts for E. coli from gluconeogenic carbon sources to fatty acid (FA). We observed tri-phasic antibiotic killing kinetics characterized by a transient period of high antibiotic tolerance, followed by rapid killing then a slower persister-killing phase. The duration of transient tolerance (3-44 h) varies with pre-shift carbon source and correlates strongly with the time needed to accumulate the FA degradation enzyme FadD after the shift. Additionally, FadD accumulation time and thus transient tolerance time can be reduced by induction of the glyoxylate bypass prior to switching, highlighting that two interacting feedback loops simultaneously control the length of transient tolerance. Our results demonstrate that nutrient switches along with positive feedback are not sufficient to trigger persistence in a majority of the population but instead triggers only a temporary tolerance. Additionally, our results demonstrate that the pre-shift metabolic state determines the duration of transient tolerance and that supplying glyoxylate can facilitate antibiotic killing of bacteria.

Enhanced microalgae cultivation using wastewater nutrients extracted by a microbial electrochemical system.

Cultivating algae using wastewater nutrients is a potential approach to realize resource recovery that can contribute to circular economy. However, growing algae directly in a wastewater has problems such as bacterial contamination and a low biomass density. To address those problems, we investigated microalgal cultivation in a photobioreactor (PBR) fed with the nutrients extracted from wastewater by a microbial nutrient recovery cell (MNRC). With an external voltage of 0.3 V, the MNRC-PBR system removed 96% of COD and recovered 44% of NH4+-N and 39% of PO43--P at a hydraulic retention time of 7.2 h. Microalgae cultivated in the nutrient recovery medium from the MNRC had 8.3-fold biomass density and 1.4-fold lipid contents, versus that cultivated in a food wastewater containing more nutrients. More significantly, 90% of biomass yielded from the MNRC-PBR system was microalgae, much higher than ∼30% in the food wastewater. A liquid exchange ratio of 30% achieved the highest microalgal density of 0.61 ± 0.06 g L-1, comparable to that in a standard BG11 medium. There was a tradeoff between recycling PBR medium and microalgal growth. The accumulated salinity was observed in the extended operation of the MNRC-PBR system treating an actual food wastewater. The results of this study have demonstrated an effective approach to extract nutrients from wastewater for enhanced microalgal growth and improved biomass quality.

Dynamic control in metabolic engineering: Theories, tools, and applications.

Metabolic engineering has allowed the production of a diverse number of valuable chemicals using microbial organisms. Many biological challenges for improving bio-production exist which limit performance and slow the commercialization of metabolically engineered systems. Dynamic metabolic engineering is a rapidly developing field that seeks to address these challenges through the design of genetically encoded metabolic control systems which allow cells to autonomously adjust their flux in response to their external and internal metabolic state. This review first discusses theoretical works which provide mechanistic insights and design choices for dynamic control systems including two-stage, continuous, and population behavior control strategies. Next, we summarize molecular mechanisms for various sensors and actuators which enable dynamic metabolic control in microbial systems. Finally, important applications of dynamic control to the production of several metabolite products are highlighted, including fatty acids, aromatics, and terpene compounds. Altogether, this review provides a comprehensive overview of the progress, advances, and prospects in the design of dynamic control systems for improved titer, rate, and yield metrics in metabolic engineering.

Metabolite Sequestration Enables Rapid Recovery from Fatty Acid Depletion in Escherichia coli.

Microbes adapt their metabolism to take advantage of nutrients in their environment. Such adaptations control specific metabolic pathways to match energetic demands with nutrient availability. Upon depletion of nutrients, rapid pathway recovery is key to release cellular resources required for survival under the new nutritional conditions. Yet, little is known about the regulatory strategies that microbes employ to accelerate pathway recovery in response to nutrient depletion. Using the fatty acid catabolic pathway in Escherichia coli, here, we show that fast recovery can be achieved by rapid release of a transcriptional regulator from a metabolite-sequestered complex. With a combination of mathematical modeling and experiments, we show that recovery dynamics depend critically on the rate of metabolite consumption and the exposure time to nutrients. We constructed strains with rewired transcriptional regulatory architectures that highlight the metabolic benefits of negative autoregulation over constitutive and positive autoregulation. Our results have wide-ranging implications for our understanding of metabolic adaptations, as well as for guiding the design of gene circuitry for synthetic biology and metabolic engineering.IMPORTANCE Rapid metabolic recovery during nutrient shift is critical to microbial survival, cell fitness, and competition among microbiota, yet little is known about the regulatory mechanisms of rapid metabolic recovery. This work demonstrates a previously unknown mechanism where rapid release of a transcriptional regulator from a metabolite-sequestered complex enables fast recovery to nutrient depletion. The work identified key regulatory architectures and parameters that control the speed of recovery, with wide-ranging implications for the understanding of metabolic adaptations as well as synthetic biology and metabolic engineering.

Engineering Microbial Metabolite Dynamics and Heterogeneity.

As yields for biological chemical production in microorganisms approach their theoretical maximum, metabolic engineering requires new tools, and approaches for improvements beyond what traditional strategies can achieve. Engineering metabolite dynamics and metabolite heterogeneity is necessary to achieve further improvements in product titers, productivities, and yields. Metabolite dynamics, the ensemble change in metabolite concentration over time, arise from the need for microbes to adapt their metabolism in response to the extracellular environment and are important for controlling growth and productivity in industrial fermentations. Metabolite heterogeneity, the cell-to-cell variation in a metabolite concentration in an isoclonal population, has a significant impact on ensemble productivity. Recent advances in single cell analysis enable a more complete understanding of the processes driving metabolite heterogeneity and reveal metabolic engineering targets. The authors present an overview of the mechanistic origins of metabolite dynamics and heterogeneity, why they are important, their potential effects in chemical production processes, and tools and strategies for engineering metabolite dynamics and heterogeneity. The authors emphasize that the ability to control metabolite dynamics and heterogeneity will bring new avenues of engineering to increase productivity of microbial strains.