Genetically encoded sensors enable real-time observation--论文代写范文精选

与单个细胞表现出荧光强度成正比的代谢物，生产方法可用于遗传变异的条件。我们观察生产几种可再生塑料，与荧光读数和产品效价是一个指标。使用荧光作为指导,确定工艺参数。下面的paper代写范文进行详述。

Abstract
Engineering cells to produce valuable metabolic products is hindered by the slow and laborious methods available for evaluating product concentration. Consequently, many designs go unevaluated, and the dynamics of product formation over time go unobserved. In this work, we develop a framework for observing product formation in real time without the need for sample preparation or laborious analytical methods. We use genetically encoded biosensors derived from small-molecule responsive transcription factors to provide a fluorescent readout that is proportional to the intracellular concentration of a target metabolite. 

Combining an appropriate biosensor with cells designed to produce a metabolic product allows us to track product formation by observing fluorescence. With individual cells exhibiting fluorescent intensities proportional to the amount of metabolite they produce, high-throughput methods can be used to rank the quality of genetic variants or production conditions. We observe production of several renewable plastic precursors with fluorescent readouts and demonstrate that higher fluorescence is indeed an indicator of higher product titer. Using fluorescence as a guide, we identify process parameters that produce 3-hydroxypropionate at 4.2 g/L, 23-fold higher than previously reported. We also report, to our knowledge, the first engineered route from glucose to acrylate, a plastic precursor with global sales of $14 billion. Finally, we monitor the production of glucarate, a replacement for environmentally damaging detergents, and muconate, a renewable precursor to polyethylene terephthalate and nylon with combined markets of $51 billion, in real time, demonstrating that our method is applicable to a wide range of molecules.

Biological production of valuable products such as pharmaceuticals or renewable chemicals holds the potential to transform the global economy. However, the rate at which bioengineers are able to engineer new living catalysts is hampered by an exceedingly slow design–build–test cycle. We describe a method to accelerate the design–build–test cycle for metabolic engineering by enabling the observation of product formation within microbes as it occurs. Biological production of a desired product is accomplished by guiding a low-cost starting material such as glucose through a series of intracellular enzymatic reactions, ultimately yielding a molecule of economic interest. 

The choice of culture conditions, the creation of enzyme variants, and the tuning of endogenous cellular metabolism create a vast universe of potential designs. Because of the complexity of biology, appropriate genetic designs and culture conditions are not known a priori. Even sophisticated modeling paradigms can result in very large design spaces (1, 2). Evaluating genetic designs or modulating process parameters to achieve a desired outcome is therefore a major bottleneck in the bioengineering design–build–test cycle. 

Current methods for evaluating biological production of chemicals rely on slow and laborious techniques such as HPLC and mass spectrometry (MS) (3). Estimates of the throughput of these methods are thousands of samples per day in highly specialized laboratories and hundreds of samples per day in more typical laboratories (3). These rates of evaluation are exceedingly small compared with typical enzyme library sizes, or the 1 × 109 unique genomes that can be built in a day by using multiplexed genome engineering (2). If product formation kinetics are to be observed, many time points over the course of production must be analyzed, further reducing the number of conditions than can be evaluated. Engineers have begun developing strategies for multiplexed evaluation of metabolite production phenotypes to enable a fully multiplexed design–build–test cycle (1, 4–7). 

In cases of genetic engineering, such a design cycle would more closely resemble biological evolution, rather than the design approaches inspired by electrical engineering that currently dominate the fields of synthetic biology and metabolic engineering. Strategies for multiplexed design evaluation include selections and screens. Selections, which only allow cells exhibiting a desired phenotype to live, have the potential to evaluate billions of designs simultaneously (3). Selections are limited by their false-positive rate and can be challenging to troubleshoot, especially if high production of the metabolite of interest provides a negative growth phenotype. Genetically encoded biosensors link intracellular metabolite levels to fluorescent protein expression and enable fluorescence-based screens. Combined with fluorescent activated cell sorting (FACS), biosensor-based screens provide evaluation rates of up to 1 × 108 designs per day (8, 9). 

Genetically encoded biosensors are the most versatile method for coupling cellular fluorescence to the quality of a metabolic engineering design. Genetically encoded biosensors link the expression of a fluorescent protein to the intracellular concentration of a target metabolite through the use of intracellular switches such as allosterically regulated transcription factors. In addition to the classic small-molecule inducible systems such as lacI-IPTG and tetR-aTC (10), many new biosensors have been characterized that respond to valuable products as diverse as macrolide antibiotics, flavonoids, and plastic precursors (11). Our group has previously published detailed characterizations of biosensors that respond to commercially important compounds. Although these studies primarily focused on the biosensors themselves, we did demonstrate that end-point measurements of fluorescence reflect product titers for a single catalytic step (11). 

However, engineers are typically dealing with metabolic pathways that start with low-cost carbon and energy sources, such as glucose, and proceed through many catalytic steps that are mediated by many gene products, before reaching the target compound. In this work, we monitor product formation through full metabolic pathways and show that the kinetics of product formation can be observed in real time Advances in the deployment of biosensors to monitor product formation has been a topic of great interest in recent years and has been well reviewed (12). In many cases, biosensors are used to estimate product titer at a single time point rather than to observe product formation as it takes place. 

A biosensor designed to respond to a product, while ignoring intermediates, allows the fluorescent readout to act as a real-time proxy for product formation from glucose or other precursors (Fig. 1). This method allows simple observation of performance characteristics such as the rate of product formation or the titer, all without the need for low-throughput analytical pipelines (13). Observing product formation in real time provides engineers with much greater flexibility in phenotype evaluation than biosensors that are only used to provide a snapshot of the intracellular cell state. 

For example, the kinetics of production can be used to rank genetic designs when titers exceed biosensor detection limits: Cells with faster production rates can be isolated before sensor saturation. In situations where the pathway being optimized is destined for extracellular use—or the end product is toxic and the optimized enzymes will be ported to a new host—the rate of product formation may be more important than final titer. Supplementing various pathway intermediates and evaluating the kinetics of product formation at each step enables engineers to determine pathway bottlenecks and even probe complicated behaviors like product or substrate inhibition. 

In this work, we develop a strategy for real-time monitoring of metabolic product formation and demonstrate its utility in observing the production of 3-hydroxypropionate (3HP; a renewable plastic precursor) (14), acrylate (the monomer for several common plastics), glucarate (a renewable building block for superabsorbent polymers and a replacement for phosphates in detergents) (15), and muconate (a building block for renewable nylon) (16). We develop two unique biosensors for 3HP and compare their ability to observe 3HP production. We use the real-time observation of 3HP formation to select process parameters that result in a 23-fold increase in 3HP production over previously reported titers. We achieve, to our knowledge, the first direct heterologous route to acrylate by converting 3HP to acrylate in vivo. We go on to demonstrate that this method is applicable to a range of compounds by deploying glucarate and muconate biosensors with their respective heterologous metabolic pathways.(paper代写)

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