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. 2021 Mar 23;6(13):9020–9027. doi: 10.1021/acsomega.1c00041

FRET-Based Genetically Encoded Nanosensor for Real-Time Monitoring of the Flux of α-Tocopherol in Living Cells

Habiba Kausar †, Ghazala Ambrin †, Mohammad K Okla ‡, Saud A Alamri ‡, Walid H Soufan §, Eid I Ibrahim §, Mostafa A Abdel-Maksoud ∥, Altaf Ahmad †,*
PMCID: PMC8028167  PMID: 33842772

Abstract

graphic file with name ao1c00041_0009.jpg

Vitamin E plays an exemplary role in living organisms. α-Tocopherol is the most superior and active form of naturally occurring vitamin E that meets the requirements of human beings as it possesses the α-tocopherol transfer protein (α-TTP). α-Tocopherol deficiency can lead to severe anemia, certain cancers, several neurodegenerative and cardiovascular diseases, and most importantly male infertility. As a result of the depletion of its natural sources, researchers have tried to employ metabolic engineering to enhance α-tocopherol production to meet the human consumption demand. However, the metabolic engineering approach relies on the metabolic flux of a metabolite in its biosynthetic pathway. Analysis of the metabolic flux of a metabolite needs a method that can monitor the α-tocopherol level in living cells. This study was undertaken to construct a FRET (fluorescence resonance energy transfer)-based nanosensor for monitoring the α-tocopherol flux in prokaryotic and eukaryotic living cells. The human α-TTP was sandwiched between a pair of FRET fluorophores to construct the nanosensor, which was denoted as FLIP-α (the fluorescence indicator for α-tocopherol). FLIP-α showed excellence in monitoring the α-tocopherol flux with high specificity. The sensor was examined for its pH stability for physiological applications, where it shows no pH hindrance to its activity. The calculated affinity of this nanosensor was 100 μM. It monitored the real-time flux of α-tocopherol in bacterial and yeast cells, proving its biocompatibility in monitoring the α-tocopherol dynamics in living cells. Being noninvasive, FLIP-α provides high temporal and spatial resolutions, which holds an indispensable significance in bioimaging metabolic pathways that are highly compartmentalized.

Introduction

It is amusing that oxygen, an indispensable component of life, under certain conditions, can have an inimical effect on living organisms. The deleterious effect of oxygen can be attributed to its property of forming reactive oxygen species, which can damage systematic cells, tissues, and DNA and lead to protein and lipid oxidation in cells. Being an inhibitor, antioxidants are potent enough to remove these free radical intermediates.1−3 Thus, antioxidants are generally regarded as nature’s answer to combat physiological and environmental stresses. Under normal circumstances, living beings possess an inbuilt mechanism to produce several enzymatic antioxidants such as glutathione peroxidase and superoxide dismutase4,5 and nonenzymatic antioxidants such as glutathione6 to scavenge free radicals.7 But these endogenous antioxidants cannot neutralize the increased level of free radicals under pathophysiological conditions. Therefore, exogenous supplementation of antioxidants has been recommended that has increased the demand for the antioxidants from external sources.8 The intake of sufficient levels of antioxidants through external sources can ameliorate the oxidative stress either by acting as a scavenger of free radicals or quenchers of reducing agents and singlet oxygen or by inhibiting the oxidative chain reaction.9 Nature possesses a large number of naturally occurring antioxidants, which differ in their chemical and physical properties, mechanisms of action, sources, and sites. Foods and medicinal plants are considered the main source of exogenous antioxidant supplementation. Additionally, one of the sources of natural antioxidants is processed agricultural products in industries. These plant-derived antioxidants include vitamins, polyphenols, and carotenoids.9−11 Among the vitamins, vitamin E is considered an essential component needed for various processes in living organisms. It is a fat-soluble vitamin consisting of four tocopherols and four tocotrienols. Among all of the vitamin E forms, the most superior and biologically active form that possesses the maximum vitamin E content is α-tocopherol.12 According to the reports, only this form of vitamin E meets the human vitamin E needs as the human body possesses the α-TTP, which can only recognize the α form of tocopherol. The human α-TTP helps in maintaining the α-tocopherol concentration in plasma and any defect in the α-TTP can cause a severe deficiency of vitamin E, resulting in severe anemia, spinocerebellar ataxia, myopathies, heart disease, permanent nerve damage, impaired thinking, and most importantly male infertility.13 The World Health Summit (WHS) reported that the intake of vitamin E supplements lowers the mortality risk from thromboembolism and that α-tocopherol has the ability to lower the clotting tendency in normal women.14 Besides, vitamin E supplements can lower the vitamin K level in humans.15 The α-tocopherol antioxidant effect is not only limited to humans and animals but also plays a beneficial role in plants. Its principal role is to scavenge peroxy radicals, which are responsible for peroxidation of lipids. α-Tocopherol in thylakoids can decrease the membrane permeability toward ions, which in turn affects the light-generated transmembrane proton gradient.16,17 A daily dose of 14 g/day has been recommended for the age group between 25 and 51 years.18−20 The animal nutrition market has also demanded an additional need for vitamin E where high doses are usually applied to improve shelf life and the quality of meat.21 The same upsurge of vitamin E has also been observed in pharmaceutical and cosmetic applications.22 Photosynthetic microorganisms and plants are mainly involved in the synthesis of α-tocopherol, but the highest concentrations are found in seeds. Soya bean is considered the richest source of vitamin E, in which the tocopherol content is 1 mg/1 g soya oil. However, due to the presence of abundant γ-tocopherol and δ-tocopherol and only ∼10% α-tocopherol, the vitamin E activity of the total tocopherol is considerably low.23,24 Besides, soya bean being the only commercial natural source of vitamin E suffers from limited availability and premium prices (>$20/kg) because of which it is predominantly reserved for human applications, causing lower availability for the other markets (animal nutrition, cosmetics, etc.).25 Despite the significant importance of vitamin E in the human diet, it has been shown in a number of dietary studies that the daily allowance of vitamin E has not been met as per the recommendations. Therefore, improvement in the composition and amount of vitamin E in plants has become a target in crop breeding.19 All of these facts and demands of vitamin E have triggered scientists to opt for metabolic engineering methods to improve the quantity of α-tocopherol so as to make it available for human consumption.26−28 However, the feasibility of developing any commercial pathway for the production of commercially important metabolites depends on various factors. There is information available regarding the metabolic pathway of the α-tocopherol biosynthesis, but the success rate for enhancing its production is still very low. This is because we lack an understanding of the regulatory network of the metabolic pathway (metabolic flux). The amalgamation of metabolic engineering with fluxomic analysis has provided a tool for successful genetic engineering by avoiding the generation of a large number of transgenic pathways or microorganisms on a trial basis to test the different strategies. In any metabolic pathway, the rate-limiting step controls the flux of the metabolite, which can be identified by performing fluxomic analysis of that pathway, and this step of the metabolic pathway can be manipulated using the metabolic engineering approach for improving the production of metabolites. Since most of the techniques available so far provide only static knowledge about the end product of the metabolic pathway, we need a tool that screens the metabolite flow in relation to the altered gene expression through the metabolic pathway by coupling the metabolic engineering approach. In this regard, the present study was conducted to develop such a tool, which would not only analyze the metabolite flux but, being noninvasive, also provide information in real time. The concentration of the metabolites in the living cells as monitored by the genetically encoded nanosensor can be transduced into differential expression patterns of the genes that allow for excellent screening of metabolite production. This tool being noninvasive offers good spatial as well as temporal resolutions.29,30 Presently, various nanosensors have been generated using the FRET phenomenon for various metabolites.31−37 A FRET-based genetically encoded nanosensor was developed in this study, denoted as FLIP-α. Hereafter, FLIP-α was utilized to monitor the real-time dynamics of α tocopherol in prokaryotic and eukaryotic systems even at single-cell levels.

Results

Designing and Construction

According to the sequences analysis, the selected human α tocopherol transfer protein belongs to the SEC-14-like protein family, which possesses the CRAL_TRIO lipid-binding domain.38,39 The crystal structure of the human α-TTP is available in Meier et al.40 The α-TTP deeply buries α-tocopherol in its hydrophobic pocket, which is closed by a lid, thus forming a closed structure.40 It is this property of the protein that was exploited to generate the sensor. In the present study, the donor and acceptor fluorophores were attached at both termini of the α-TTP, which alters its conformation upon binding with α-tocopherol and undergoes changes. This altered conformation in the α-TTP brought the donor and acceptor fluorophores closer to each other, thus resulting in the occurrence of FRET (Figure 1). The successful development of pGEMT-Easy_ECFP_TTPA_Venus and pRSET-B_ECFP_TTPA_Venus was confirmed by restriction digestion and validated by sequencing analysis (Supporting Information Figures S3–S8). The FLIP-α-transformed bacterial cells were allowed to express in the bacterial cells to produce the recombinant protein (sensor protein). Thereafter, the sensor proteins were purified by affinity chromatography. Before subjecting the eluted protein for various analyses (spectral analysis, pH and buffer stability, specificity, and affinity), it was kept overnight at 4 °C to restore the native conformation of the purified sensor.

Figure 1.

Figure 1

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(A) Construction scheme of the FLIP-α sensor and (B) the working strategy of the FLIP-α nanosensor illustrating the conformational change of the α-TTP in the presence of α-tocopherol.

Spectral Analysis

Spectral analysis of the recombinant protein validated the successful working of the developed sensor by showing an increase in the emission intensity ratio of Venus/ECFP in the presence of α-tocopherol (Figure 2). The changed FRET ratio in the absence and the presence of α-tocopherol itself indicates the occurrence of FRET between the FRET pair.

Figure 2.

Figure 2

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Spectral analysis of the purified protein of FLIP-α. α-Tocopherol (0.1 mM) was added to the diluted sensor protein, and the emission intensity was measured in the range of 460–610 nm. The emission intensity was also measured without addition of α-tocopherol. FLIP-α was excited at 430 nm. The concentration of the protein of the sensor was 0.20 mg/mL.

Buffer and pH Stability

To examine the sensor sensitivity in physiological conditions, fluorescence emission intensities of the sensor were studied after adding different buffers (Tris-Cl, MOPS, PBS, TBS) both in the absence and the presence of α-tocopherol. The pH of each buffer ranged from 5.0 to 8.5. However, the PBS buffer has been found to be the best, in which the maximum stability of the sensor was reported in a wider range of the pH, which shows its excellence for any in vivo analysis as the subcellular components of the cells are in a varying pH range. It was also observed that the sensor stability was not affected by the pH change (Figure 3). Therefore, this buffer (pH 7.5) was suitable for further studies.

Figure 3.

Figure 3

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Testing of the pH stability of the purified sensor protein in PBS buffer (pH 5.0–8.5) through the measurement of the ratio of the emission intensity of Venus/ECFP. The concentration of the protein of the sensor was 0.20 mg/mL. An excitation filter for ECFP (430/20 nm) and emission filters for ECFP (485/20 nm) and Venus (535/25 nm) were used. Values are means of three independent replicates. Vertical bars indicate the standard error.

Specificity Analysis

Specificity analysis of FLIP-α with α-tocopherol and different homologous antioxidants such as γ-tocopherol, β-tocotrienol, and β-carotene at concentrations of 0, 1.0, and 10 mM revealed an increase in the FRET ratio on the addition of α-tocopherol compared to the control (no addition). Addition of other similar metabolites did change the FRET ratio significantly when compared to the control. This showed the sensor specificity toward its target metabolite, i.e., α-tocopherol (Figure 4).

Figure 4.

Figure 4

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Specificity of FLIP-α. The specificity of the sensor was analyzed with various homologous metabolites of α-tocopherol. The concentration of the protein of the sensor was 0.20 mg/mL. The FRET ratio was recorded. The excitation filter for ECFP was 430/20 nm. Emission filters were 485/20 and 535/25 nm for ECFP and Venus, respectively. Values are means of three independent replicates. Vertical bars show the standard error.

Analysis of Affinity

Titration curve analysis of FLIP-α reported a sigmoidal curve. There was no change in the FRET ratio on addition of α-tocopherol in the range of 1.0 nM to 1.0 μM concentration. Further addition of α-tocopherol resulted in an increase in the FRET ratio with the increase in the concentration of α-tocopherol. An increase in the FRET ratio was observed with the increase in the concentration of α-tocopherol till it reached a saturation of 0.1 mM α-tocopherol. The affinity for FLIP-α was calculated and found to be 100 μM (Figure 5).

Figure 5.

Figure 5

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Titration curve of FLIP-α at different α-tocopherol concentrations. The concentration of the protein of the sensor was 0.20 mg/mL. The excitation filter for ECFP was 430/20 nm. Emission filters were 485/20 and 535/25 nm for ECFP and Venus, respectively. Values are means of three independent replicates. Vertical bars show the standard error.

Real-Time Monitoring of α-Tocopherol Flux

Flux monitoring of α-tocopherol in live cells of Escherichia coli BL21 (Prokaryotic system) and yeast (eukaryotic system) in the present study showed an increase in the ratio of FRET by the addition of α-tocopherol. A significant increase in the FRET ratio was observed after 5 min of addition of α-tocopherol and continued to increase till the 25 min. There was no significant increase after 25 min. The absence of α-tocopherol showed no significant alteration in the FRET ratio. The increase in the FRET ratio ranged from 0.8 to 1.05 on the addition of α-tocopherol (Figure 6).

Figure 6.

Figure 6

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Flux monitoring of α-tocopherol levels in live bacterial cells. The graph represents the measurement of the flux of α-tocopherol by FLIP-α in bacterial cells from 0 to 35 min as a change in the ratio of emission intensities of Venus/ECFP FLIP-α without and with α-tocopherol. The excitation filter for ECFP was 430/20 nm. Emission filters were 485/20 and 535/25 nm for ECFP and Venus, respectively. Values are means of three independent replicates. Vertical bars show the standard error.

The eukaryotic system also followed the same pattern. The measurement of the level of α-tocopherol by FLIP-α using a confocal microscope in live yeast cells expressing the sensor protein revealed an increased FRET ratio after the addition of 10 mM α-tocopherol. A FRET ratio of 0.08–1.0 was reported within 500 s of the addition of α-tocopherol (Figure 7). These results suggest that the developed sensor successfully expresses itself both in bacterial and yeast cells, and in both organisms, it is able to identify and monitor the uptake of α-tocopherol when added externally.

Figure 7.

Figure 7

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Time course flux monitoring of α-tocopherol in yeast cells. The ratio of the emission intensities of Venus/ECFP increased after addition of 10 mM α-tocopherol. Values are the mean of three independent replicates. Vertical bars indicate the standard error.

Discussion

The present study has provided a tool for real-time monitoring of the flux of α-tocopherol in prokaryotic and eukaryotic systems by successfully developing a FRET-based genetically encoded nanosensor, namely, FLIP-α, that is highly specific for α-tocopherol. The success of the sensor development depends mainly on the distance between the FRET fluorophore pair and the ligand-binding protein. However, the development of the sensor demands a ligand-binding protein that offers conformational flexibility. The distance between the fluorophores must be less than or equal to 10 nm, and, hence, employing such a ligand-binding protein, which brings the fluorophores at the required distance by undergoing structural changes, majorly contributes to the sensor development. The human α-tocopherol transfer protein used as the α-tocopherol-binding protein in the present study was efficient enough to undergo conformational changes in the presence of α-tocopherol, bringing the fluorophores closer to each other and resulting in the occurrence of FRET (Figure 1). The FRET phenomenon involves the transfer of energy nonradiatively between the ECFP and Venus fluorophores. The FRET pair, ECFP and EYFP, has been used in a number of studies. Compared to EYFP, Venus is a brighter, faster-folding fluorophore.41 Bajar et al.42 reported that a more robust FRET is obtained by the faster maturation of the acceptor fluorophore. Therefore, the ECFP/Venus FRET pair has been used. For efficient transfer of energy, the spectrum of the FRET pair must overlap with each other with inconsequential spectrum difference, which makes them distinguishable from each other. Earlier, the Förster radius of the ECFP/Venus pair has been reported to be 4.95 nm. The developed sensor was denoted as FLIP-α. FLIP-α was then subjected to different analyses so as to study the features of the developed sensor. The very first analysis was the spectral analysis, which confirmed the successful working of FLIP-α. The stability analysis of the sensor revealed that the pH versatility of FLIP-α that made it suitable for in vivo analysis and its activity is not subjected to any pH hindrance. The specificity of the FLIP-α nanosensor toward α-tocopherol confirmed that it is an exemplary tool for real-time measurement of α-tocopherol in a complex pool of diverse homologous antioxidant metabolites.

This nanosensor (FLIP-α) proved its excellence by showing exceptional capability in monitoring real-time flux of α-tocopherol in living systems. The successful expression of the FLIP-α protein in bacterial and yeast cells and the expected change in the FRET ratio observed externally in both the systems on the addition of α-tocopherol validated the successful development and working of the FLIP-α nanosensor. As shown in Figures 5 and 6, FLIP-α is capable of monitoring the uptake of α-tocopherol in both systems.

Conclusions

A genetically encoded FRET-based nanosensor has been developed in this study. The nanosensor was able to detect the α-tocopherol flux in real time with high spatial and temporal resolutions in the living cells of both prokaryotic and eukaryotic systems.

Experimental Section

Chemicals, Vectors, and Strains

The chemicals used in this study were procured from Sigma-Aldrich. The vectors, pDONR, and pYES-DEST52 were obtained from Thermo Fischer Scientific. Cloning and expression analysis in the bacterial system was carried out in E. coli DH5α and BL21, respectively. These strains of bacteria were procured from New England Biolabs (NEB). The source of yeast (Saccharomyces cerevisiae BY4742) was the Yeast Research Center, Washington. Various restriction endonuclease enzymes were purchased from NEB. Enzymes for the Gateway reaction (BP clonase and LR clonase) were obtained from Thermo Fischer Scientific. The same company also supplied ligase enzymes. Various components for affinity chromatography were procured from Novagen.

Designing and Constructing the Nanosensor

The human α-tocopherol transfer protein, which is encoded by the gene TTPA, was used as the α-tocopherol-binding protein in the present study. The protein structure was analyzed utilizing PDB databases, and the nucleotide sequence of the gene TTPA was retrieved from Kyoto Encyclopaedia of Genes and Genomes (code-7274). The cDNA of TTPA was procured from Genscript with the accession number NM_000370.3. After the procurement of the cDNA, the TTPA gene was amplified using the specific set of in-house designed forward primer with BstEII restriction sites 5′-gggttacccatggcagaggcgcgatc-3′ and reverse primer with AgeI restriction sites 5′-accggtttgaatgctctcagaa-3′ where italicized alphabets represent restriction sites. The next step was to choose a suitable pair of fluorophores. ECFP and Venus were used as the FRET pair, where the former acted as the donor and the latter acted as the acceptor fluorophores. Designing of the sensor involves attachment of ECFP and Venus at the N- and C-terminus of the α-tocopherol transfer protein. Amplification of ECFP and Venus was achieved using pGWF1 vector as the template, and the primers were designed in such a way that they added attB1 sites in ECFP at 5′ and attB2 sites in Venus at 3′. The forward and reverse primers used for ECFP were 5′-ggatccggggacaagtttgtacaaaaaagcaggctatggtgagcaagggcg-3′ and 5′-gggttaccccttgtacagctcgt-3′ with BamHI along with attB1 and BstEII restriction sites. Similarly, the forward and reverse primers for Venus were 5′-accggtatggtgagcaag-3′ and 5′-aagcttacccagctttcttgt acaaagtggttgtacagctcgtcat-3′ with AgeI along with attB2 and HindIII restriction sites. All of the genes were amplified excluding the stop codons. Subsequently, the TTPA gene containing BstEII and AgeI sites was inserted between ECFP and Venus, resulting in the ECFP_TTPA_Venus chimeric sequence. This chimeric sequence is cloned in the pGEMT vector, yielding pGEMT_ECFP_TTPA_Venus. This construct was then shuttled to the bacterial expression vector (pRSET-B), resulting in pRSET_ECFP_TTPA_Venus (Supporting Information Figures S1 and S2). The reason behind using pRSET-B as bacterial expression vectors was its property of adding an in-frame (His)6 tag with the chimeric protein (nanosensor) that helps in the purification of the sensor protein using affinity chromatography through the Ni–NTA His-tag. For expression, the pRSET-B_ECFP_TTPA_Venus construct was introduced into E. coli BL21(DE3) by electroporation. The designation of FLIP-α (a fluorescent indicator protein for α-tocopherol) was given to this recombinant construct. Employing the Gateway technology, the developed construct was then introduced into the yeast expression vector to study the expression of FLIP-α in eukaryotic model system yeast. To achieve this, pRSET_ECFP_TTPA_Venus was shuttled into an entry vector pDONR222 in a BP-mediated recombination reaction generating an entry clone pDONR222_ECFP_TTPA_Venus. This entry clone was further shuttled into the destination vector or yeast expression vector pYES-DEST52 using LR-mediated recombination, thereby generating the expression clone pYES-DEST52_ECFP_TTPA_Venus. The developed expression clone was transferred into the yeast cell to initiate the expression. Analysis of the developed recombinant sequence was performed to validate the results.

Purification of the FLIP-α Sensor Protein

Escherichia coli BL21(DE3) transformed with pRSET_ECFP_TTPA_Venus were grown in Luria Bertini medium in an incubator shaker for 24 h. The temperature of the incubator shaker was maintained at 20 °C. When the OD600 of the bacterial growth reached 0.6, an induction of 1 mM IPTG (isopropyl β-d-1 thiogalactopyranasoide) was provided to the culture to induce the expression of the recombinant construct (pRSET_ECFP_TTPA_Venus). After the induction, the culture was sealed with aluminum foil and grown in the dark at 20 °C for a further 48 h. After 48 h, the culture was centrifuged for 15 min at 6500g to harvest the expressed cells. The cell pellet was collected by discarding the supernatant and was later dissolved in 20 mM Tris-Cl of pH 8.0. To isolate the expressed proteins, the dissolved cell pellet was disrupted by an ultrasonicator. The purification of the FLIP-α sensor protein was carried out by loading the disrupted bacterial cell onto an affinity chromatography column containing a Ni-mixed resin. The FLIP-α sensor protein bound to Ni through its His-tag. After washing the column with a washing buffer (20 mM Tris-Cl and 20 mM imidazole), the elution of the FLIP-α sensor protein was carried out using an elution buffer (20 mM Tris-Cl and 250 mM imidazole). The eluted protein was stored at 4 °C. Storing the protein at 4 °C helped it achieve its native conformation.

Characterization of the Sensor Protein

To explore the working of the developed sensor, the purified protein was characterized with respect to different attributes. The first attribute is FRET occurrence. The FRET occurrence is an important attribute, which confirms the working of the nanosensor, which was achieved by performing a spectral analysis of FLIP-α. This was carried out using a microplate reader (Synergy H1, Biotek). The donor fluorophore (ECFP) was excited at 430 nm. The emission intensities were recorded between 450 and 610 nm at 5 nm intervals after addition of 0.1 mM α-tocopherol. Similar observations were recorded without adding α-tocopherol. The second attribute is pH stability. The pH stability of FLIP-α was investigated by measuring the ratio of the emission intensities of Venus/ECFP using a microplate reader after adding various buffers (pH 5.0–8.5) with the purified protein of FLIP-α. This observation was recorded with and without addition of α-tocopherol (0.1 mM). The excellence of any sensor is measured by the specificity of that sensor. The specificity testing of FLIP-α was monitored with various homologous antioxidant metabolites, α-tocopherol, γ-tocopherol, β-tocotrienol, and β-carotene at concentrations of 1.0 and 10 mM. The analysis was conducted by adding 20 μL of metabolites separately with 180 μL of the protein of FLIP-α in a microplate, and the recording of the FRET ratio was carried out with respect to different metabolites using the microplate reader. Titration of the FLIP-α sensor protein was carried out to measure its affinity. Different concentrations of α-tocopherol (1 nM to 100 mM) were added separately with the purified sensor protein, and the ratio of the emission intensities of Venus/ECFP was measured using the microplate reader. The binding affinity (Kd) of α-tocopherol was calculated by fitting the ligand titration curves with the simple binding isotherm according to Kausar et al.30

Real-Time Monitoring of α-Tocopherol

The FLIP-α-transformed bacterial cells [E. coli BL21(DE3)] were grown in Luria Bertini medium in an incubator shaker for 24 h. The temperature of the incubator shaker was maintained at 20 °C. When the OD600 of the bacterial growth reached 0.6, an induction of 1 mM IPTG (isopropyl β-d-1 thiogalactopyranasoide) was provided to the culture to induce the expression of the sensor protein. After the induction, the culture was sealed with aluminum foil and was allowed to grow again in the incubator shaker in dark conditions for 48 h at the same temperature. The expressed cells were taken in a multiwell plate and real-time monitoring of α-tocopherol was performed by adding 10 mM α-tocopherol. The value of the FRET ratio was measured at regular intervals of every 5 min for 35 min.

pYES-DEST52_ECFP_TTPA_Venus developed using the Gateway cloning strategy was transformed into yeast. The transformed yeast was allowed to grow in the SD medium. Dextrose (2%) was supplemented with the medium as the carbon source. Galactose (1%) was also added to the medium as an inducer. Live cells of yeast containing the expressed FLIP-α sensor were fixed on the glass slide and were subjected to analysis under a confocal microscope (SP5, Leica Microsystems, Germany), having an inbuilt Leica TCS–SPE scan head in addition to a 63× objective lens with an oil immersion system. Then, 10 mM α-tocopherol was gradually added to the expressed culture using a nanoliter pipette, followed by monitoring the real-time uptake of α-tocopherol. The FRET ratio was recorded at an interval of 20 s for 600 s. The data was collected using LAS-AF software (Leica, Germany).

Acknowledgments

The authors extend their appreciation to the Dean of Scientific Research, King Saud University, for funding the work through the research group project number RG-1440-126. The authors also thank the Deanship of Scientific Research and RSSU at King Saud University for their technical support.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.1c00041.

  • pGEMT_ECFP_TTPA_Venus construct (Figure S1); pRSET-ECFP_TTPA_Venus construct (Figure S2); nucleotide sequence of ECFP_TTPA_Venus (Figure S3); amplified product of TTPA gene (Figure S4); agarose gel analysis of pGEMT_ECFP_TTPA_Venus (Figure S5); validation of pGEMT_ECFP_TTPA_Venus through restriction digestion (Figure S6); and validation of pRSET_ECFP_TTPA_Venus through restriction digestion (Figure S7) (PDF)

Author Contributions

Conceptualization: H.K., G.A., M.K.O., S.A.A., M.A.A.-M., and A.A.; formal analysis: H.K., G.A., and M.K.O.; funding acquisition: M.K.O., S.A.A., and M.A.A.-M.; investigation: H.K. and A.A.; methodology: H.K. G.A., S.A.A., M.A.A.-M., and A.A.; resources: M.K.O. and A.A.; supervision: A.A.; validation: H.K.; and writing—original draft: H.K., G.A., M.K.O., S.A.A., M.A.A.-M., and A.A. and revision—H.K., G.A., E.I.I., W.H.S., M.A.A.-M., and A.A. All authors have given approval to the final version of the manuscript.

The authors declare no competing financial interest.

Supplementary Material

ao1c00041_si_001.pdf (454.2KB, pdf)

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