Quantification of total and bioavailable lysine in feed protein sources by a whole-cell green fluorescent protein growth-based Escherichia coli biosensor

Effective Cryopreservation of a Bioluminescent Auxotrophic Escherichia coli-Based Amino Acid Array to Enable Long-Term Ready-to-Use Applications

Amino acid arrays comprising bioluminescent amino acid auxotrophic Escherichia coli are effective systems to quantitatively determine multiple amino acids. However, there is a need to develop a method for convenient long-term preservation of the array to enable its practical applications. Here, we reported a potential strategy to efficiently maintain cell viability within the portable array. The method involves immobilization of cells within agarose gel supplemented with an appropriate cryoprotectant in individual wells of a 96-well plate, followed by storage under freezing conditions. Six cryoprotectants, namely dimethyl sulfoxide, glycerol, ethylene glycol, polyethylene glycol, sucrose, and trehalose, were tested in the methionine (Met) auxotroph-based array. Carbohydrate-type cryoprotectants (glycerol, sucrose, and trehalose) efficiently preserved the linearity of determination of Met concentration. In particular, the array with 5% trehalose exhibited the best performance. The Met array with 5% trehalose could determine Met concentration with high linearity (R² value = approximately 0.99) even after storage at −20 °C for up to 3 months. The clinical utilities of the Met and Leu array, preserved at −20 °C for 3 months, were also verified by successfully quantifying Met and Leu in spiked blood serum samples for the diagnosis of the corresponding metabolic diseases. This long-term preservation protocol enables the development of a ready-to-use bioluminescent E. coli-based amino acid array to quantify multiple amino acids and can replace the currently used laborious analytical methods.

Development of Lactococcus lactis Biosensors for Detection of Sulfur-Containing Amino Acids

The sulfur-containing amino acids methionine and cysteine play an important role in food industry. These amino acids are used to confer a sulfur smell or meat-related aroma to food products. Besides their use as food additives, methionine and cysteine participate in flavor formation in dairy fermentations. For instance, the characteristic aroma of Cheddar cheeses is derived from methionine. Therefore, bacterial strains with the ability to overproduce and secrete these amino acids are relevant for the food industry. In addition, the quantification of these compounds in food matrices is a laborious task that involves sample preparation and specific analytical methods such as high-performance liquid chromatography. The ability of bacteria to naturally sense metabolites has successfully been exploited to develop biosensors. The presence of a specific metabolite is sensed by the biosensors, and it is subsequently translated into the expression of one or more reporter genes. In this study we aim to develop biosensors to detect methionine and cysteine, which are produced and secreted by wild-type Lactococcus lactis strains. We employed two strategies to create L. lactis biosensors, the first one is based on the methionine auxotrophy of this bacterium and the second strategy is based on a cysteine-responsive promoter. The characterization of the biosensors showed their specific response to the presence of these amino acids. Subsequently, we applied the methionine biosensor to quantify the presence of methionine in bacterial supernatants of wild-type L. lactis that naturally secretes methionine to benchmark the performance of our biosensors. The methionine biosensor responded linearly to the amounts of methionine present in the bacterial supernatants, i.e., the increases in the biosensor cell densities were proportional to the amounts of methionine present in the supernatants. The biosensors developed in this study tackle the limitations of amino acid quantification and the selection of strains with secretion of amino acids. These biosensors may eventually be used for screening of engineered strains to increase methionine and cysteine production, and may facilitate the detection of these amino acids in complex food matrices.

Syntrophic co-culture amplification of production phenotype for high-throughput screening of microbial strain libraries

Microbes can be engineered to synthesize a wide array of bioproducts, yet production phenotype evaluation remains a frequent bottleneck in the design-build-test cycle where strain development requires iterative rounds of library construction and testing. Here, we present Syntrophic Co-culture Amplification of Production phenotype (SnoCAP). Through a metabolic cross-feeding circuit, the production level of a target molecule is translated into highly distinguishable co-culture growth characteristics, which amplifies differences in production into highly distinguishable growth phenotypes. We demonstrate SnoCAP with the screening of Escherichia coli strains for production of two target molecules: 2-ketoisovalerate, a precursor of the drop-in biofuel isobutanol, and L-tryptophan. The dynamic range of the screening can be tuned by employing an inhibitory analog of the target molecule. Screening based on this framework requires compartmentalization of individual producers with the sensor strain. We explore three formats of implementation with increasing throughput capability: confinement in microtiter plates (102-104 assays/experiment), spatial separation on agar plates (104-105 assays/experiment), and encapsulation in microdroplets (105-107 assays/experiment). Using SnoCAP, we identified an efficient isobutanol production strain from a random mutagenesis library, reaching a final titer that is 5-fold higher than that of the parent strain. The framework can also be extended to screening for secondary metabolite production using a push-pull strategy. We expect that SnoCAP can be readily adapted to the screening of various microbial species, to improve production of a wide range of target molecules.

Determination of Gold Ions in Human Urine Using Genetically Engineered Microorganisms on a Paper Device

This paper presents a whole-cell biosensor that operates in conjunction with a smartphone-based fluorescence diagnostic system on a paper device to monitor the concentration of gold ions in human urine. The heavy metal-tolerant bacteria Cupriavidus metallidurans was genetically engineered for use as a chassis in a red fluorescent protein (RFP)-based microbial sensor. The biosensor is highly sensitive to gold ions, with a detection limit of 110 nM. The proposed smartphone-based analysis system provides a user-friendly approach to design tools of personal health monitoring for reporting the presence of gold ions in human urine.

Quantification of nitrogen in the liquid fraction and in vitro assessment of lysine bioavailability in the solid fraction of soybean meal hydrolysates

Soybean meal (SBM) is a product generated from the manufacture of soybean oil and has the potential for use as a source of fermentable sugars for ethanol production or as a protein source for animal feeds. Knowing the levels of nitrogen available from ammonium is a necessary element of the ethanolic fermentation process while identifying the levels of essential amino acids such as lysine is important in determining usage as a feed source. As such the purpose of this study was to quantify total nitrogen and ammonium in the liquid fraction of hydrolyzed SBM and to evaluate total and bioavailable lysine in the solid fraction of the hydrolyzed SBM. The effects of acid concentration, cellulase and β-glucosidase on total and ammonium nitrogen were studied with analysis indicating that higher acid concentrations increased nitrogen compounds with ammonium concentrations ranging from 0.20 to 1.24 g L-1 while enzymatic treatments did not significantly increase nitrogen levels. Total and bioavailable lysine was quantified by use of an auxotrophic gfpmut3 E.coli whole-cell bioassay organism incapable of lysine biosynthesis. Acid and enzymatic treatments were applied with lysine bioavailability increasing from a base of 82% for untreated SBM to up to 97%. Our results demonstrated that SBM has the potential to serve in ethanolic fermentation and as an optimal source essential amino acid lysine.

Toxicity assessment using different bioassays and microbial biosensors

Toxicity assessment of water streams, wastewater, and contaminated sediments, is a very important part of environmental pollution monitoring. Evaluation of biological effects using a rapid, sensitive and cost effective method can indicate specific information on ecotoxicity assessment. Recently, different biological assays for toxicity assessment based on higher and lower organisms such as fish, invertebrates, plants and algal cells, and microbial bioassays have been used. This review focuses on microbial biosensors as an analytical device for environmental, food, and biomedical applications. Different techniques which are commonly used in microbial biosensing include amperometry, potentiometry, conductometry, voltammetry, microbial fuel cells, fluorescence, bioluminescence, and colorimetry. Examples of the use of different microbial biosensors in assessing a variety of environments are summarized.

Cell-based method utilizing fluorescent Escherichia coli auxotrophs for quantification of multiple amino acids

A cell-based assay system for simultaneous quantification of the three amino acids, phenylalanine (Phe), methionine (Met), and leucine (Leu) in a single biological sample, was developed and applied in the multiplex diagnosis of three key metabolic diseases of newborn babies. The assay utilizes three Escherichia coli auxotrophs, which grow only in the presence of the corresponding target amino acids and which contain three different fluorescent reporter plasmids that produce distinguishable fluorescence signals (red, green, and cyan) in concert with cell growth. To mixtures of the three auxotrophs, immobilized on agarose gels arrayed on a well plate, is added a test sample. Following incubation, the concentrations of the three amino acids in the sample are simultaneously determined by measuring the intensities of three fluorescence signals that correspond to the reporter plasmids. The clinical utility of this assay system was demonstrated by employing it to identify metabolic diseases of newborn babies through the quantification of Phe, Met, and Leu in clinically derived dried blood spot specimens. The general strategy developed in this effort should be applicable to the design of new assay systems for the quantification of multiple amino acids derived from complex biological samples and, as such, to expand the utilization of cell-based analytical systems that replace conventional, yet laborious methods currently in use.

Design and characterization of auxotrophy-based amino acid biosensors

Efficient and inexpensive methods are required for the high-throughput quantification of amino acids in physiological fluids or microbial cell cultures. Here we develop an array of Escherichia coli biosensors to sensitively quantify eleven different amino acids. By using online databases, genes involved in amino acid biosynthesis were identified that - upon deletion - should render the corresponding mutant auxotrophic for one particular amino acid. This rational design strategy suggested genes involved in the biosynthesis of arginine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, threonine, tryptophan, and tyrosine as potential genetic targets. A detailed phenotypic characterization of the corresponding single-gene deletion mutants indeed confirmed that these strains could neither grow on a minimal medium lacking amino acids nor transform any other proteinogenic amino acid into the focal one. Site-specific integration of the egfp gene into the chromosome of each biosensor decreased the detection limit of the GFP-labeled cells by 30% relative to turbidometric measurements. Finally, using the biosensors to determine the amino acid concentration in the supernatants of two amino acid overproducing E. coli strains (i.e. ΔhisL and ΔtdcC) both turbidometrically and via GFP fluorescence emission and comparing the results to conventional HPLC measurements confirmed the utility of the developed biosensor system. Taken together, our study provides not only a genotypically and phenotypically well-characterized set of publicly available amino acid biosensors, but also demonstrates the feasibility of the rational design strategy used.

Computational design of auxotrophy-dependent microbial biosensors for combinatorial metabolic engineering experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools).

Potential for development of an Escherichia coli-based biosensor for assessing bioavailable methionine: a review

Methionine is an essential amino acid for animals and is typically considered one of the first limiting amino acids in animal feed formulations. Methionine deficiency or excess in animal diets can lead to sub-optimal animal performance and increased environmental pollution, which necessitates its accurate quantification and proper dosage in animal rations. Animal bioassays are the current industry standard to quantify methionine bioavailability. However, animal-based assays are not only time consuming, but expensive and are becoming more scrutinized by governmental regulations. In addition, a variety of artifacts can hinder the variability and time efficacy of these assays. Microbiological assays, which are based on a microbial response to external supplementation of a particular nutrient such as methionine, appear to be attractive potential alternatives to the already established standards. They are rapid and inexpensive in vitro assays which are characterized with relatively accurate and consistent estimation of digestible methionine in feeds and feed ingredients. The current review discusses the potential to develop Escherichia coli-based microbial biosensors for methionine bioavailability quantification. Methionine biosynthesis and regulation pathways are overviewed in relation to genetic manipulation required for the generation of a respective methionine auxotroph that could be practical for a routine bioassay. A prospective utilization of Escherichia coli methionine biosensor would allow for inexpensive and rapid methionine quantification and ultimately enable timely assessment of nutritional profiles of feedstuffs.

Escherichia coli, an Intestinal Microorganism, as a Biosensor for Quantification of Amino Acid Bioavailability

In animal diets optimal amino acid quantities and balance among amino acids is of great nutritional importance. Essential amino acid deficiencies have negative impacts on animal physiology, most often expressed in sub-optimal body weight gains. Over supplementation of diets with amino acids is costly and can increase the nitrogen emissions from animals. Although in vivo animal assays for quantification of amino acid bioavailability are well established, Escherichia coli-based bioassays are viable potential alternatives in terms of accuracy, cost, and time input. E. coli inhabits the gastrointestinal tract and although more abundant in colon, a relatively high titer of E. coli can also be isolated from the small intestine, where primary absorption of amino acids and peptides occur. After feed proteins are digested, liberated amino acids and small peptides are assimilated by both the small intestine and E. coli. The similar pattern of uptake is a necessary prerequisite to establish E. coli cells as accurate amino acid biosensors. In fact, amino acid transporters in both intestinal and E. coli cells are stereospecific, delivering only the respective biological l-forms. The presence of free amino- and carboxyl groups is critical for amino acid and dipeptide transport in both biological subjects. Di-, tri- and tetrapeptides can enter enterocytes; likewise only di-, tri- and tetrapeptides support E. coli growth. These similarities in addition to the well known bacterial genetics make E. coli an optimal bioassay microorganism for the assessment of nutritionally available amino acids in feeds.

A cad-gfpmut3 plasmid construct in Escherichia coli for gene induction-based quantification of lysine in acid hydrolysates of feedstuffs

AIMS

To generate an inducible plasmid-borne cad-gfpmut3 transcriptional fusion and develop a method for quantification of total lysine.

METHODS AND RESULTS

The cad-gfpmut3 transcriptional fusion was constructed by cloning the cad promoter (Pcad) upstream of a promotorless gfpmut3 located on a high-copy plasmid. The construct was electroporated into Escherichia coli ZK126 and the transformed strain was subsequently used to quantify lysine in feed ingredients. Lysine standard curves based on gene induction of the bacterial cells were used for estimating acid hydrolysate lysine concentrations in four feed ingredients. Except for sorghum, no substantial differences were observed when the data for lysine in soybean (2 x 49 +/- 0 x 37%), cottonseed (1 x 82 +/- 0 x 15%), and meat and bone meal (2 x 31 +/- 0 x 24%) generated by the newly developed construct were compared with previously published data.

CONCLUSIONS

Using the cad-gfpmut3 fusion, feed derived lysine induction was measured easily and accurately, and could be a useful tool for the estimation of lysine in acid hydrolysates of feed ingredients.

SIGNIFICANCE AND IMPACT OF THE STUDY

The described approach for lysine quantification in feed ingredients represents a cost- and time-efficient method offering rapid and accurate lysine quantification of multiple samples.