Methionine is an essential amino acid for animals and is involved in numerous metabolic processes [1–4]. In addition to being a building block in protein synthesis, methionine, after being transformed into S-adenosylmethionine, serves as a methyl donor in transmethylation reactions involved in the biosynthesis of lipids, biotin, and polyamines [5]. Since methionine cannot be synthesized de novo in mammal cells, its supplementation in animal diets is required to provide optimal growth and physiological performance of the animals. Plant proteins, however, are poor in methionine and its optimal level in animal diets is provided by supplementation with crystalline methionine [6] or methionine analogs such as 2-keto-4-(methylthio) butyric acid [7] and hydroxymethionine [8,9]. Therefore, timely and accurate pre-quantification of this amino acid in feed ingredients is necessary to improve cost efficiency of feed formulation and prevent its overdosage. According to Klasing and Austic [10] and Baker [11], excess of individual amino acids due to feed mixing errors can be potentially harmful to the animal, with methionine considered to be the amino acid possessing the highest toxicity. Feed compounds such as cysteine, vitamin B₁₂, arginine, choline, and sulfate that are related to methionine metabolism can affect the apparent methionine requirement of animals and additionally complicate the estimation of the optimal dosage of this amino acid in animal diets [12].

Chemical assays including high performance liquid chromatography (HPLC) are commonly used to quantify methionine level in feed ingredients. The analysis, however, involves pretreatment of the samples with performic acid followed by acid digestion [13,14]. The procedure results in a complete protein degradation and liberation of methionine which differs from protein digestion under physiological conditions. Feed-derived methionine, which is available to animals to assimilate, can be more accurately estimated by animal or microbial assays which are considered to correspond more directly to the physiological needs of animals [15,16]. Although considered standard, animal assays are laborious, expensive, and time consuming [17–19]. The types of animal assays that have been used for quantifying methionine availability have been reviewed extensively by Froelich and Ricke [18] and will not be discussed further in the current review. Microbial assays appear to be easier and more affordable for routine analysis. Rapid development and recent improvements in molecular techniques allow for constructing successful and accurate amino acid biosensors via more precise genetic targeting of specific genes in microbial cells. This review discusses methionine biosynthesis and regulation in Escherichia coli and the potential of genetically modifying this microorganism into practical whole cell biosensors for methionine bioavailability quantification.

Recently, numerous microbial biosensors have been created and used in medical diagnostics, food technology, biotechnology, and environmental monitoring. Microbial biosensors couple a biological element (enzymes, viable or non-viable microbial cells) and a transducer or a device which allows for rapid, accurate and sensitive detection of target analytes [20,21]. Their popularity is due to highly specific selectivity to the substrate of interest, relative inexpensiveness, and portability [22,23]. Versatile microorganisms have proven to be useful in development of biosensors. The bacterium Vibrio harveyi and Mycena citricolor, a fungal microorganism, demonstrated high sensitivity for detecting cyanide and sodium monofluoroacetate respectively [24]. A microbial biosensor for sensitive, selective, rapid, and direct determination of p-nitrophenyl (PNP) -substituted organophosphates was developed based on PNP oxidation metabolic pathway of the Moraxella sp. [25]. Flavobacterium sp. were employed for development of a biosensor for methyl parathion pesticide [26]. The variety and versatility among microbial species useful in the construction of biosensors for environmental application is more extensively discussed elsewhere [20,27] and will not be further discussed here.

In the food industry, microbial biosensors, derived from Gluconobacter oxydans and yeast have gained popularity for detecting total sugars, sucrose, and ethanol [28,29]. Respiratory activities of Gluconobacter oxydans DSM 2343 cells, immobilized on chitosan, were used in the quantification of glucose. A linear relationship (R² = 0.99) between sensor’s response and substrate concentration was achieved in the range of 0.05 to 0.1 mM glucose [23]. By using a microbial biosensor based on immobilized Saccharomyces ellipsoideus yeast cells, Rotariu et al. [29] were able to determine ethanol concentrations up to 50 mM in alcoholic beverages including two types of beer, vodka, and cognac. The comparison to the chemical assay used for the analyses of the same analyte revealed good correlation (correlation coefficient 0.998) between the biosensor and the spectrometric method. An Acetobacter pasteurianus-based biosensor has been proposed as an alternative to chemical methods available for quantifying lactate which is used as an indicator for specific fermentations activities including those of milk, yogurt, and wine [30,31]. Aeromonas phenologenes-, Pseudomonas fluorescens-, and Bacillus subtilis-based biosensors were proposed to serve as alternatives in quantification of amino acids including tyrosine, tryptophan, and glutamate [32,33].

Among all microorganisms, E. coli is one of the most highly investigated bacteria for the purposes of biosensor fabrication. It is easy to cultivate, with simple nutritive requirements and rapid growth [34]. E. coli is a Gram negative microorganism with very well known genetics which enables the construction of a wide variety of biosensors [20,21]. The complete E. coli genome has been sequenced and the information deposited to the National Center for Biotechnology Information (NCBI) [35]. Thus, each DNA sequence of interest is routinely available to the public and can be used for a wide range of potential further genetic manipulations. In promoter-based E. coli biosensors, a gene promoter, inducible by the analyte of interest, is fused to a reporter that generates a signal in response to the analyte that can be easily monitored and measured. A strong SOS E. coli promoter fused to a lux gene resulted in the development of a construct which served in a dose-dependent detection of 6 genotoxic chemicals including mitomycin C, N-methyl-N-nitro-N-nitrosoguanidine, nalidixic acid, dimethylsulfate, hydrogen peroxide, and formaldehyde [36]. An E. coli BL21 DE3 (RIL) biosensor strain displayed a specific response and high sensitivity to different aromatic aldehydes. The response was measured by monitoring the fluorescence of a reporter (green fluorescent protein) fused to an alcohol dehydrogenase inducible promoter (Sso2536adh) belonging to the archaeon Sulfolobus solfataricus [37]. A plasmid-borne transcriptional fusion between the E. coli nitrate reductase (narG) promoter and the Photorhabdus luminescens lux operon was used to generate a modified E. coli with a highly bioluminescent phenotype in the presence of nitrate that enabled the detection of nitrate to a level of 5 × 10⁻⁵ mol L⁻¹ (0.3 ppm) [38]. Following the same approach, biosensors for toluene, arsenite and arsenate, and lead have also been generated [39–41].

In addition to environmental testing and analyses, E. coli-based biosensors were found to be useful in the food industry as well. E. coli derived β-galactosidase, glucose oxidase, and horseradish peroxidase were immobilized on a glassy carbon electrode to generate a biosensor for quantification of lactose in raw milk [42]. Simultaneous determination of various mono- and disaccharides was performed by a sensor array comprised of bacterial mutants of E. coli K12 lacking different transport systems for individual carbohydrates [43].

Amino acids are building monomers in protein synthesis and indicators for protein quality which explains the interest in constructing microbial biosensors for their quantification. Successful whole-cell biosensors for the quantification of threonine, tryptophan, lysine and glutamine have been developed based on E. coli auxotrophy for the respective amino acids [44–46]. Wild type E. coli can synthesize all amino acids and does not require their supplementation in media. However, auxotrophic mutants that are defective in the biosynthesis of the amino acid of interest grow in a dose-dependent fashion in response to the external concentration of the amino acid. In addition, E. coli is a part of the intestinal microflora of most animals and humans with high similarity in the assimilation of amino acids and peptides which is a necessary prerequisite for the bacterium to serve as a representative biosensor microorganism for these compounds [47]. After pre-treating feed ingredients with pronase and peptidase, Erickson et al. [48] obtained a correlation of 0.94 between lysine bioavailability determined by using an E. coli lysine auxotroph and previously published chick bioassay data. Indeed, in a direct experimental comparison, the E. coli biosensor developed by Chalova et al. [19] proved to be as accurate as a chick bioassay for quantitation of bioavailable lysine in diverse feed ingredients and mixtures including soybean meal, cotton seed meal, meat and bone meal, chick starter and finisher, and swine starter.

Early efforts for microbial quantification of methionine have also been based on bacterial auxotrophy. Hitchens et al. [45] demonstrated that E. coli GUC41 could grow on DL-methionine sulfoxide but not on DL-methionine sulfone. The microbiological assay was as accurate as the chemical assay with high correlation coefficients between the two. The microbiological assay values for amino acid content were expressed as percentages of the HPLC values to obtain the bioavailability values. By using E. coli ATCC 23798, a methionine auxotroph, Zabala-Díaz et al. [49] were able to quantify crystalline methionine added to feed. The feed matrix had negligible influence on the assay and methionine recovery percentages for all supplementation levels ranged from 71 to 80% indicating consistency in the bacterial response to the supplemented methionine. The E. coli methionine growth assay has also been miniaturized and adapted to be conducted in microtiter plates where a linear response of the E. coli auxotroph to up to 26.8 μM methionine was achieved [50].

In general, this early assay work with E. coli methionine auxotrophs supports the feasibility of this approach and potential reliability for routine use. However, there are also limitations with these particular E. coli methionine auxotrophs. To the best of our knowledge, E. coli methionine auxotrophs used for methionine quantification so far have been generated via chemical mutation [51–53]. This mutation method is a “hit-or-miss” approach that mutates the organism in random locations, followed by a selection of a certain phenotype. As a result, the mutation is not target specific and various non-methionine related genes can be affected. Revertants or compensatory mutations may occur to abolish the desired functionality [54]. In addition, in the case of methionine, the auxotrophic requirements for this amino acid are not specific and can also be satisfied by a variety of compounds including methioninyl peptides, α-hydroxy methionine, N-acetylmethionine, and the α-keto analogue α-keto-λ-methiol butyrate [55]. When a chemically generated E. coli methionine auxotroph (ATCC 23798) was used, Froelich et al. [56] established no differences based on substrate affinities of an E. coli methionine auxotroph to methionine and methionine hydroxy analog, respectively. Estimated maximum growth rate of the E. coli auxotroph when grown on both substrates was also found to be similar.

Although the E. coli methionine auxotroph did not discriminate between methionine and its hydroxyl analog, it appears that both sources are not equally assimilated by animals. While studying the efficacy of both methionine and methionine hydroxyl analog supplementation of pig diets, Shoveller et al. [57] established that methionine hydroxyl analog is significantly less bioavailable compared to DL-methionine for protein deposition in growing pigs. Similar observations were made by Feng et al. [58] who reported the methionine hydroxyl analog to be 26.8% and 54.4% less effective than methionine for growing pigs with respect to nitrogen retention and plasma urea nitrogen respectively. Therefore, more specific mutagenesis that targets specific gene(s) without altering other metabolic pathways would be a more desirable approach to generate a microbial biosensor for discriminating and quantifying specific forms of methionine. Detailed knowledge about E. coli’s genomics and more specifically, the genes involved in methionine biosynthesis and transportation is a prerequisite to accomplish such a goal and is the focus of the discussion in the following sections.

Methionine’s carbon skeleton is initially derived from aspartate. The intermediates of this pathway, aspartyl semialdehyde and homoserine, are also used in the synthesis of lysine and threonine. Serine and cysteine are metabolically related to the methionine pathway: serine being the precursor in the synthesis of folate, which is the methyl donor for the synthesis of methionine and cysteine from the precursor of cystathionine, which is intermediate in methionine synthesis [59]. Methionine biosynthesis results from the coupling of homocysteine and a methyl group, but can be accomplished via two distinct pathways [55,60]. The E. coli K-12 methionine biosynthesis pathway http://biocyc.org/ECOLI/organism-summary?object=ECOLI&detail-level=3 has been schematically presented by EcoCys [61], a member of BioCys database collection (http://biocyc.org/publications.shtml), and is available via SRI International Pathway Tools, version 13.5 [62]. A summary of the consecutive reactions, participating genes and respective products is given in Table 1. The nonfolate branch of the methionine pathway includes metA, metB, metC, metH, and metK and the folate branch is comprised of metF and metE which are all negatively controlled by the metJ repressor system [73]. The final methyl transfer is catalyzed by either a B₁₂-dependent methyltransferase (metH gene product) or a non-B₁₂-methyl transferase (metE product). The metabolic intermediate, 5-methyltetrahydrafolate, encoded by the metF, provides the methyl group for both enzymes to attach. This is a convergence point through which the cells are able to balance the requirement for protein synthesis, methylation reactions, and nucleic acid synthesis on several levels and to regulate the pathway flow of methyl units [73]. Once methionine is formed, it is metabolized to S-adenosylmethionine (AdoMet) in the presence of ATP and AdoMet synthetase, a metK gene product [74–76].

The regulation of the methionine biosynthetic pathway consists of positive and negative feedback mechanisms depending on methionine availability and B₁₂. For example, MetE biosynthesis is autoregulated via a negative feedback loop. It can also function as an antagonist of the metR gene product, by either interfering directly in the activation mechanism or by repressing metR expression [73,77,78]. Alternatively, the activation depends not only on the presence of a functional MetR but also on a coactivator. A functional metF gene is required for vitamin B₁₂- mediated repression of metE gene, and 5-methyltetrahydrofolate may be involved in a negative feedback repression. Inactivation of the metE gene allows for accumulation of the methionine intermediates O-succinylhomoserine, cystathionine, homocysteine, and 5-methyltetrahydrafolate [60,75].

The first unique step in bacterial methionine biosynthesis involves the activation of homoserine, which in E. coli is accomplished through a succinylation reaction catalyzed by homoserine transsuccinylase (HTS). The activity of this enzyme is closely regulated in vivo and therefore represents a critical control point for cell growth and viability [79]. Born and Blanchard [80] cloned homoserine transsuccinylase from E. coli and demonstrated that the enzyme generates a complex with the succinyl group of succinyl-CoA before transferring it to homoserine to form the final product, O-succinylhomoserine. The enzyme can be inhibited by iodoacetamide in a pH-dependent manner which suggests the presence of cysteine in the active site that forms a succinyl-cysteine intermediate during enzymatic turnover. In E. coli, HTS is not only a key regulator of methionine biosynthesis but also of the bacterial growth at elevated temperatures [81]. E. coli growth is impaired at temperatures above 44 °C due to the instability of HTS. According to Biran et al. [79], the instability of the protein is determined by the amino-terminal part of the protein, and its removal or substitution by the N-terminal part of beta-galactosidase confers stability. Mordukhova et al. [82] reported that two amino acids in the enzyme, namely isoleucine 229 and asparagine 267, are responsible for HTS instability and their substitution leads to stabilization of HTS molecule and improved bacterial growth at elevated temperature. MetA is controlled by the expression of metJ [83].

MetE, a zinc-containing monomer, transfers the methyl group of N⁵-methyl-tetrahydrofolic to the thiolate group of homocysteine [68,75,78]. Several mechanisms for repression of metE exist. The interaction between methionine as S-adenosylmethionine with MetJ leads to a corepression of metE through a negative feedback loop [75]. The absence of MetR can also repress metE. MetR and MetE are of similar size and exist relatively in the same location but result from transcription in opposite directions [77]. MetR is a transactivator of both metE and metH gene [75,77,78]. Homocysteine coactivates both the expression of the metR gene and the MetR stimulation of metE expression.

The vitamin B₁₂ -mediated repression of the metE gene in E. coli requires the B₁₂-dependent transmethylase, a product of the metH gene. It has been proposed that the MetH-B₁₂ holoenzyme complex is involved directly in the repression mechanism [55,73,75]. According to Wu et al. [84], however, B₁₂-mediated repression of the metE gene derives primarily from a loss of MetR-mediated activation due to depletion of the coactivator homocysteine, rather than a direct repression by the MetH-B₁₂ holoenzyme. MetH has a higher constant of Michaelis-Menten (K_m) than MetE, which is compensated by the very strong expression of the metE gene [68]. N⁵-methyl-H₄-folate transfers a methyl unit to the MetH holoenzyme where it is subsequently attached to homocysteine [55,68,75,78]. The cobalamin-independent methyltransferase (MetE) shares no similarity with the sequence of the cobalamin-dependent protein (MetH), suggesting that the two have arisen by convergent evolution [85].

The metF gene codes for N⁵-methyl-H₄-folate and regulates metE in an indirect way. N⁵-methyl-H₄-folate is required for the transfer of a methyl group to the B₁₂ within the MetH holoenzyme forming a methyl-B₁₂ enzyme; the catalytically active methylated form of the MetH protein regulates metE expression [55,75,77,78]. Regulation by MetJ may occur more readily because of the existence of 5 met boxes in metF’s promotor region making it more sensitive than the other met genes to small increases of AdoMet that might occur in B₁₂ grown cells [75].

YagD is a third methionine synthase in E. coli. YagD is a zinc-dependent methyltransferase with a catalytic mechanism similar to MetH and synthesizes methionine from S-methylmethionine or S-adenosylmethionine and homocysteine. YagD does not contribute to the utilization of methionine sulfoxide as methionine sulfoxide is converted to methionine via reduction. YagD is subject to regulation by the MetJ-S-adenosyl-methionine system [68].

All met genes are regulated by MetJ. MetJ protein binds to a specific DNA region, met box, which is present in all met genes except metH. The met box region is a sequence with dyad symmetry (TGAA . . . TTCA) and produces a helical region containing four leucine residues seven amino acids apart. This motif is called a leucine zipper and has been proposed to play a role in protein dimerization that is required for DNA bindings. MetJ can bind to this region and prevent the transcription of most of the met genes (metA, metBL, metC, metF, metJ, metR, and metE) [55,59,71,74]. The interaction of the MetJ protein with the met operator region is markedly enhanced by the presence of AdoMet.

Although E. coli prototroph cells are capable of synthesizing methionine de novo, they can also acquire external methionine or methionine analogs to satisfy cellular needs for either methionine or sulfur which reflects the high flexibility of the organism under a wide range of environmental conditions. The activity of methionine transport systems in E. coli is influenced by the concentrations of both external and internal methionine pools [86]. Cells with increased internal methionine pool or pre-exposed to excess of external methionine exhibit decreased rates of methionine uptake. Conversely, starvation for methionine in a methionine auxotroph can increase the rate of external methionine transport [86].

At least two transport systems for methionine exist in E. coli. The high affinity transport system (metD) has a K_m of approximately 10⁻⁷ M and is responsible for the uptake of l- and d- methionine isomers [87]. MetD is an ABC transporter with Abc the ATPase, YaeE the permease, and YaeC the likely substrate binding protein. The expression of these genes is regulated by l-methionine and MetJ, the common repressor of the methionine regulon. Interestingly, l-methionine inhibits the uptake of d-methionine; however, d-methionine does little to affect the uptake of the l-isomer [88]. By performing competition experiments Kadner [88] established that MetD possesses a distinct substrate-binding site for each stereoisomer. The second system (metP) is a low affinity system with a K_m of approximately 40 μM and can transport l-methionine but not the d-isomer [88,89]. By using various deletion mutants, Merlin et al. [87] observed that only mutants with active MetD were able to grow on d-methionine.

Methionine can be transported across a concentration gradient (a temperature sensitive uptake process) with the assistance of MetD [90]. The accumulation against a concentration gradient and the temperature influence of the uptake indicates that methionine enters bacterial cells through active transport, which is an energy-dependent process. When starved of methionine, the rate of uptake of methionine is faster than those grown with methionine [91]. Both systems are regulated by the level of the internal methionine pool of the bacterium and differ in affinity by a factor of at least 400-fold [86,88,91]. In E. coli, the methionine, transported into the cells, accumulates in the form of AdoMet rather than as free methionine.

Active transport can be completely eliminated in the presence of glucose with the presence of azide and fluoride [86,91]. In the absence of glucose, cells could still accumulate methionine less efficiently. The methionine analogs that inhibit uptake required the −S (or Se)-CHS group [91]. The initial rate of uptake of l-methionine was poorly affected by the addition of α-keto-λ-methiol-butyrate, d-methionine, or methionine sulfoxide when they were added simultaneously with the substrate. However, methionine transport was reduced in cells exposed to analogs and methionine variations prior to the addition of a substrate [86].

As analytical tools, microbial biosensors are genetically engineered to produce a measurable signal in response to the compound of interest. These signals include but are not limited to light emission, reflection, fluorescence, or absorption. Although their function is based on different principles, a common feature is the proportionality between the intensity of the signal and the concentration of target analyte [107]. The choice of an appropriate detection system is an important point since each detection mode possesses advantages and disadvantages which are summarized in Table 2. Several detection methods for detecting microbial responses exist for potential implementation in respect to the microbiological assay for methionine quantification.

In conclusion, microbial sensors for methionine quantification in feed and feed ingredients are an alternative to animal assays because they have the advantage of being simpler, more rapid, and cost efficient. Versatile tools in molecular biology combined with current knowledge of E. coli genetics favor the generation of appropriate and successful constructs that may serve as methionine biosensors. However, more work needs to be done in understanding the bacterial genome to better target gene(s) that lead to generation of methionine auxotroph exhibiting a single phenotype. The wide variety of available detection modes should facilitate the choice of a reporting system which will contribute to the simplified operation and identification of a biosensor’s emitted signal.