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. 2024 Jul 5;128(28):6730–6741. doi: 10.1021/acs.jpcb.4c01816

Analysis of Fluorescent Proteins for Observing Single Gene Locus in a Live and Fixed Escherichia coli Cell

Jung Bae Son 1, Seunghyeon Kim 1, Sora Yang 1, Youmin Ahn 1, Nam Ki Lee 1,*
PMCID: PMC11264270  PMID: 38968413

Abstract

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Fluorescent proteins (FPs) are essential tools for advanced microscopy techniques such as super-resolution imaging, single-particle tracking, and quantitative single-molecule counting. Various FPs fused to DNA-binding proteins have been used to observe the subcellular location and movement of specific gene loci in living and fixed bacterial cells. However, quantitative assessments of the properties of FPs for gene locus measurements are still lacking. Here, we assessed various FPs to observe specific gene loci in live and fixed Escherichia coli cells using a fluorescent repressor-operator binding system (FROS), tet operator-Tet repressor proteins (TetR). Tsr-fused FPs were used to assess the intensity and photostability of various FPs (five red FPs: mCherry2, FusionRed, mRFP, mCrimson3, and dKatushka; and seven yellow FPs: SYFP2, Venus, mCitrine, YPet, mClover3, mTopaz, and EYFP) at the single-molecule level in living cells. These FPs were then used for gene locus measurements using FROS. Our results indicate that TetR-mCrimson3 (red) and TetR-EYFP (yellow) had better properties for visualizing gene loci than the other TetR-FPs. Furthermore, fixation procedures affected the clustering of diffusing TetR-FPs and altered the locations of the TetR-FP foci. Fixation with formaldehyde consistently disrupted proper DNA locus observations using TetR-FPs. Notably, the foci measured using TetR-mCrimson3 remained close to their original positions in live cells after glyoxal fixation. This in vivo study provides a cell-imaging guide for the use of FPs for gene-locus observation in E. coli and a scheme for evaluating the use of FPs for other cell-imaging purposes.

1. Introduction

Fluorescent proteins (FPs) have become indispensable tools in molecular and cellular biology, serving as unparalleled tools for the real-time visualization and tracking of dynamic biological processes.1,2 Studies on Escherichia coli cells often aim to measure in vivo spatiotemporal transcriptional dynamics,3−6 the spatial information on biomolecules related to gene expression,7−9 and transcriptional activity through mRNA imaging.10 Advancements in this field have led to the development of FPs with enhanced brightness, photostability, chemical stability, and photoconversion properties, expanding their utility in different biological contexts.11−13 Consequently, to ensure proper use of FPs, various properties of FPs, such as the excitation/emission spectrum, brightness, photostability, cytotoxicity, and monomeric property, have been typically evaluated in vitro or in bulk using live cells.14−17 However, the behavior of FPs could change when conjugated to other proteins, potentially altering their original properties.15,18,19 Moreover, the performance of FPs can vary according to the cellular environment in which they are expressed, adding another layer of complexity to their application in live-cell imaging.11 With the advent of advanced fluorescence microscopy techniques, such as super-resolution, single-protein imaging, and single-molecule fluorescence resonance energy transfer, evaluating FPs under conditions that closely mimic their actual usage has become crucial.20−28

Fluorescent repressor-operator binding systems, such as lac repressor (LacI-FP) and tet repressor (TetR-FP), have been widely used to observe specific DNA loci, chromosomal dynamics, transcription, and transcription factor dynamics in living cells.3,22,29−33 The balance between achieving high signal-to-noise ratios (SNRs) and avoiding physiological disruptions due to TetR-FPs bound to tet operator (tetO) sequences remains delicate.33 Fixation step is often required for complex imaging tasks or prolonged observations.30 However, fixation can introduce artifacts that complicate the interpretation of the results.34

Here, we conducted a systematic evaluation of various FPs: five red FPs-mCherry2, FusionRed, mRFP, mCrimson3, and dKatushka; and seven yellow FPs- SYFP2, Venus, mCitrine, YPet, mClover3, mTopaz, and EYFP, for their applicability in single-molecule and gene loci imaging in both living and fixed E. coli cells. TetR-mCrimson3 and TetR-EYFP were found to have better quality than the other TetR-FPs for visualizing gene loci. In addition, fixation procedures affected the clustering of diffusing TetR-FPs and altered the location of TetR-FP foci. Although fixation using formaldehyde constantly altered the location of DNA loci, TetR-mCrimson3 after glyoxal fixation revealed foci positions that were close to their original positions in live cells. By addressing the gap in the understanding of the performance of FPs in specific and physiologically relevant contexts, this study increases the precision and reliability of fluorescence microscopy, particularly for observing gene loci and chromosomal dynamics.

2. Methods

2.1. Scheme for Observing a Single FP in a Live Cell

The Tsr-FP system21 was used to observe a single FP in a living cell. FPs (five red FPs: mCherry2, FusionRed, mRFP, mCrimson3, and dKatushka; and seven yellow FPs: SYFP2, VENUS, mCitrine, YPet, mClover3, mTopaz, and EYFP) were selected from those publicly available (Addgene) with high brightness at the time we began our experiment and added to the C-terminal end of tsr and recombined into the lac operon (Figure 1A). The fluorescence intensity of a single FP was determined by using Tsr-FP. The basic properties and source of each FP are summarized in Table S1.35−46 Cells from a single colony were grown in minimal media to minimize autofluorescence and maintain low expression of Tsr-FP per cell. As Tsr is a homodimeric protein, we minimized its expression to use monomeric Tsr-FP. For in vivo single FP evaluation, we sequentially imaged ten times with a 200 ms exposure time to obtain an intensity-frame trace (Figure 1C). The majority of traces showed one-step photobleaching, with less than 5% exhibiting two-step photobleaching (Figure S1). Only the traces exhibiting one-step photobleaching were analyzed for accuracy. In addition, traces where the fluorescence intensity increased beyond the threshold (approximately 40% of the mean value of single intensities, which is the standard deviation of single intensities) following an initial drop were identified as blinking events and excluded from the analysis. A single FP spot was defined as 25 pixels (5 × 5 square) centered on the brightest pixel in the fluorescence image of a single E. coli cell.

Figure 1.

Figure 1

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Experimental scheme for observing single FP and specific gene loci in live cells. (A) Tsr-FP was expressed in the lac operon with 0 mM IPTG (basal expression) to minimize the expression level. Tsr is known to be tethered at the poles in E. coli cells. (B) TetR-FPs were expressed using an arabinose inducible plasmid. TetR forms homodimer in solution, and this dimer recognizes the TetO sequence. The TetO array is located downstream of the lacZ gene; a total of 24 TetO binding sites were used. (C) Sequential irradiation of Tsr-FP until photobleaching of most Tsr-FPs. Intensity-frame traces were extracted from a spot, and single FP intensity and photostability were measured. Scale bar = 1 μm. (D) Bound TetR-FPs on the TetO array are shown as bright foci. 0–2 foci were observed. For a super-resolution image, the spot was localized by Gaussian fitting. Scale bar = 1 μm.

2.2. Scheme for Observing Specific Gene Loci

The tetO-TetR binding system29,47 was used to image the subcellular locations of 24 tandem tetO sites (24× tetO) on the E. coli chromosome. FPs (five red FPs: mCherry2, FusionRed, mRFP, mCrimson3, and dKatushka; and seven yellow FPs: SYFP2, VENUS, mCitrine, YPet, mClover3, mTopaz, and EYFP) were tagged at the C-terminal end of the Tet repressor gene (tetR) under an arabinose-inducible promoter (Figure 1B). TetR-FPs bound to tetO array were imaged as bright foci in the cells (Figure 1D, left). The focus was defined as 25 pixels (a 5 × 5 square) centered by the brightest pixel with an SNR (defined as the ratio of the mean intensity of a spot divided by the standard deviation of the background intensity in a cell) threshold of 3.5 in the fluorescence image of a single E. coli. Cells expressing an average 120 ± 42 TetR-YFP or 50 ± 24 TetR-RFP molecules were used for the comparative analysis of FPs.

2.3. E. coli Strains and Plasmids

The tsr and FP genes were tagged using the linker sequence gggcctggcggccgc in the pBAD plasmid. The Tsr-FP product, containing a chloramphenicol antibiotic resistance gene, was amplified and recombinated into the BW25993 strain using two homologous sites: ggaattgtgagcggataacaatttcacacaggaaacagct and taggcctgataagcgcagcgtatcaggcaatttttataat. The lacZ-24× tetO strain was constructed by inserting a KanR-24× tetO fragment downstream of the lacZ gene, and the lacY and lacA genes were deleted. KanR was removed using the FRT cassette after successful cloning. The 24× tetO array was constructed using a compatible pair of restriction enzymes (EcoR1 and Mfe1).48 The initial cassettes of six operators29 containing EcoR1 and Mfe1 were assembled sequentially into units of 12 and 24 tetO. The tetR and FP genes were tagged with the linker sequence gcctccgcctccatgggatccctgcaggcctcagggcccgatcgatgcggccgc in the pACL08 plasmid and transformed into a 24× tetO strain.

2.4. Cell Growth Condition

For the Tsr-FP experiments, single colonies were grown overnight in an M9 glucose medium supplemented with vitamins and amino acids at 37 °C. The overnight cultures were reinoculated into fresh media at 1:200 dilution and grown for 5 h at 37 °C to mid log phase (OD600 ∼ 0.3). For DNA loci observation using the tetO-TetR system, cells from single colonies were grown overnight in LB media at 37 °C. Overnight cultures were reinoculated into M9 glycerol medium supplemented with vitamins, amino acids, and 0.2% l-arabinose at a 1:200 dilution and grown for 3 h to induce TetR-FP. The cells were then pelleted via centrifugation, resuspended in M9 glucose medium supplemented with vitamins and amino acids at a 1:3 dilution, and grown for another 3 h without l-arabinose until mid log phase (OD600 ∼ 0.3). This procedure was required to achieve the proper concentration of TetR-FPs in the cells for single-molecule detection and maturation of the expressed FPs.

2.5. Fixation Procedure

For the fixation of E. coli cells, 1 mL of the cells was pelleted via centrifugation, resuspended in precooled 3.7% formaldehyde solution or precooled 3% glyoxal solution, and then nutated for 30 min at room temperature. The fixed cells were subsequently centrifuged at 400 × g for 8 min, and the supernatants were discarded. The pellets were resuspended in 1 mL of 1× PBS, centrifuged twice at 600 g for 3.5 min, and then imaged. The composition of the fixation solution is provided in Supporting Information.

2.6. Image Acquisition and Data Analysis

All measurements were performed using a custom-built setup.3,49 Briefly, 0.2 μL of the sample was dropped onto 5 mm2 of a low melting temperature agarose gel pad and covered with a 40 mm round coverslip (1.5 thick, Bioptechs Inc.). Samples were observed under an inverted optical microscope (Olympus I×71) with a 100× oil-type objective lens (Olympus) and an additional 1.6× amplification. Phase contrast and fluorescence images were acquired at 160× magnification using a −80 °C cooled EMCCD camera (Andor iXon DU897) controlled using MetaMorph software (Molecular Devices). For YFP fluorescence imaging, an Ar-ion laser (Melles Griot 43 Series Ion laser) at 514 nm was used with a dichroic mirror (FF520-Di01-25 × 36, Semrock), an excitation filter (FF01-511/20, Semrock), and an emission filter (ET550/50, Chroma). For RFP fluorescence imaging, a fiber laser (VFL-P-Series, MPB Communications Inc.) at 580 nm was used with a dichroic mirror (FF593-Di02-25 × 36, Semrock), an excitation filter (FF01-572/28-25, Semrock), and an emission filter (FF01-641/75-25, Semrock). All measurements were performed with an exposure time of 200 ms and laser power of 43 mW (0.23 kW/cm2) at 514 nm (YFP) and 580 nm (RFP). Customized MATLAB codes were used for image analysis. For Tsr-FP imaging, single foci that did not overlap with other foci were collected prior to photobleaching. Single (isolated) cells were collected for TetR-FP imaging.

2.7. Quantification of the Copy Number of TetR-FPs

The copy number of TetR-FP in living cells was quantified using the following equation

2.7.

where (i) Npixel is the area of the cells, (ii) Icell is the average fluorescence intensity of the cell, (iii) Iauto is the average autofluorescence intensity of the cell, and (iv) Isingle FP is the average fluorescence intensity of a single FP in the cell measured over an area of 25 pixels obtained from the Tsr-FP system.

2.8. Visualization of Gene Loci Distribution

Homebuilt MATLAB codes were used for data analysis. The program determines the borders of individual cells from phase-contrast images using a Gaussian Mixture Model. The cell sizes were normalized by setting the average short-axis length to 1.50 The coordinates of each locus were obtained based on the distance from the origin in the axis direction, which were then projected onto the long and short axes. Each locus was averaged in a two-dimensional (2D) heat map in the first quadrant, and the data were mirrored along the short and long axes.

3. Results and Discussion

3.1. Evaluation of a Single FP in a Live Cell

Numerous libraries detailing the properties of FPs obtained from in vitro or bulk in vivo measurements are available.14−17,51 However, for advanced fluorescence imaging, it is crucial to understand the imaging capabilities of a single FP in a live cell. Therefore, we used FP-tagged Tsr protein (Tsr-FP) as a platform to evaluate single FP in live E. coli cells. Tsr is efficiently localized at the inner membrane of E. coli,52 and is confined to a small area (∼290 nm),53 enabling precise measurement of FP fluorescence intensity. By replacing the lacZ gene on the E. coli chromosome with the tsr-FP gene, low expression levels can be achieved that are suitable for single-protein detection under repressed conditions (without an inducer).21

After expressing Tsr-FP at the single-molecule level, we performed sequential irradiation with a laser for 200 ms exposure time until most of the FPs were photobleached, which typically indicates single-step photobleaching (Figure 1C). Intensity-frame traces were extracted from each Tsr-FP spot. Based on the change in fluorescence intensity over time, we defined the intensity difference before and after single-step bleaching as the single intensity and the number of frames before bleaching as the photostability (Figure 1C). High fluorescence signals above cell autofluorescence lead to a better resolution for imaging living cells. Thus, we measured the in vivo intensity of a single FP from the intensity frame traces that showed single-step photobleaching (Figure 2A). As for YFP, EYFP exhibited the highest intensity, followed by Venus and Ypet. In the case of RFPs, all RFPs presented a similar intensity. mCrimson3 had a slightly higher intensity than mCherry2 and mRFP; however, FusionRed exhibited significant variation between fluorescent spots. The average SNRs of each Tsr-FP spot are listed in Table S2. Owing to differences in the absorption and emission spectra of each FP, the single FP intensity may vary depending on the setup (e.g., excitation wavelengths, dichroic mirrors, and filter sets). However, because our data were obtained using a typical setup for YFP and RFP detection, they could provide relevant information in many cases.

Figure 2.

Figure 2

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Intensity and photostability of single FP in live cells. (A) Average pixel intensity of the Tsr-FP focus for Tsr-YFP (left) and Tsr-RFP (right). A focus was defined by 25 pixels. Therefore, the real fluorescence intensity of a single FP is 25* (average pixel intensity). These numbers were used to calculate the copy number of TetR-FPs per cell. Each circle corresponds to individual cells from a set of independent experiments. The line represents the mean value. (B) Photostability of single-FP in a live cell. The dashed line represents the mean value. (C) 2D plot of single intensity and photostability. The error bars indicate the mean ± s.e.m. from independent experiments. The number of analyzed cells for each FP was as follows: 744 for YPet, 712 for SYFP2, 637 for mTopaz, 623 for mCitrine, 287 for mClover3, 751 for Venus, 675 for EYFP, 607 for mCherry2, 940 for mRFP, 942 for FusionRed, 1106 for mCrimson3, and 255 for dKatushka. Statistical significance was assessed using one-way ANOVA followed by posthoc Tukey tests, and the results are shown in Table S4.

Next, we determined the in vivo photostability of FPs at the single-molecule level by counting the number of frames before photobleaching. The number of frames before bleaching represents the photostability of the FP. It is straightforward to estimate the duration of the imaging frame, which could simplify setting up experimental schemes. For tracking in living cells or imaging the same field for a given duration, FPs with sufficient photostability should be selected (Figure 2B). The number of frames until photobleaching varied among FPs. Among the YFPs, YPet and mClover3 displayed the best photostability (∼3 frames), and among RFPs, dKatushka lasted the longest (∼2.8 frames), followed by mCherry2 and mCrimson3 (∼2.3 frames). To quantitatively detect FP fluorescence, where both resolution and photostability are critical, both the single intensity and photostability should be considered (Figure 2C).

Based on our results, the brightness of the FPs can be derived from a single FP intensity (see Supporting Information). We compared the brightness of a single FP in live E. coli cells with that measured in the in vitro/bulk systems (Table S3 and Figure S3). Notably, differences in brightness were found between the previous data obtained in vitro/bulk and our results obtained in live cells at the single-molecule level. The in vitro/bulk brightness of EYFP was significantly lower than that of the other YFPs. However, at the in vivo single-molecule level, EYFP exhibited relatively high brightness. The main reasons for the discrepancies between in vitro/bulk measurements and in vivo single-molecule assessments may be buffer conditions such as salt concentrations, pH, and the presence of other macromolecules. The heterogeneity present in vivo biological fluids makes it challenging to replicate these conditions with in vitro solutions.54 Macromolecules exhibit an excluded volume effect and can influence the structural stability of proteins or alter their folded structures through macromolecular crowding.55,56 Various biomolecules can affect the fluorescence intensity of FPs through nonspecific intermolecular interactions or changes in viscosity, which can affect the nonradiative relaxation of excited FPs.57,58 These factors could account for the discrepancies between in vitro/bulk measurements and in vivo single-molecule assessments. This discrepancy underscores the necessity and usefulness of our evaluation scheme. Additionally, these in vivo single-molecule characteristics are valuable for observing transcription factor dynamics, cytoskeletal protein tracking, membrane protein tracking, and the kinetics of Cas proteins at the single-molecule level in live cells.22,25,59,60 When studying protein production at the single-molecule level, it is also important to consider parameters such as incomplete maturation and degradation.21,61

3.2. Gene Loci Observation Using the tetO-TetR System in a Live E. coli Cell

Observing specific DNA loci in living E. coli is crucial for studies on gene replication, transcription, and translation.3,30,32 FROS has been widely used in these studies (Figure 1B). After inserting the tetO sequence repeat downstream of the chromosomal DNA locus of interest, we recombinated the plasmid expressing FP-tagged TetR protein (TetR-FP) and controlled its expression level via arabinose induction. After TetR-FP expression in a live E. coli cell, a fraction of TetR-FPs was attached to the tetO sequence, whereas others diffused in the cells during image exposure time. Because the TetR-FPs attached to the tetO sequence remained relatively stationary during the exposure time, they were observed as a fluorescence spot above the signals from diffusing TetR-FPs. Therefore, only specific gene loci were identified. Because the number of specific DNA loci in E. coli is typically small (less than two per cell), the spots can be easily distinguished. Super-resolution images of DNA loci were obtained in living cells using the single-molecule localization of each spot through Gaussian fitting (Figure 1D). Although cells were grown under identical conditions, YFPs exhibited higher expression levels than RFPs. The average numbers of TetR-FPs were 180 and 64 for YFPs and RFPs, respectively, with slight variations in expression levels among individual FPs (Table S6). To ensure a quantitative comparison of TetR-FPs across different FPs under identical total expression levels, we selected cells expressing 120 ± 42 copies for YFPs and 50 ± 24 copies for RFPs. We also compared DNA binding between YFPs and RFPs at the same level of expression, as discussed later.

3.2.1. Average Number and SNR of TetR-FP Focus per Cell

If the FP-tagged protein is the object of observation in living cells, evaluating FP at the single-molecule level using Tsr-FP, as shown in Figure 2, could be helpful. However, when our interest shifts to imaging specific DNA loci using TetR-FPs attached to tetO sequences, the properties of TetR-FP are important, such as the background signal from diffusing TetR-FPs, the expression level of TetR-FP, the interaction between TetR and tetO, and the dimerization of TetR-FP which could be affected by tagging FP to TetR. In FROS, distinguishing between TetR-FPs attached to tetO and diffusing TetR-FPs is crucial. Therefore, controlling the expression level and binding efficiency of TetR-FPs to the tetO sequence is paramount. Consequently, we introduced each FP into the FROS and determined the FP that yielded the best results for observing specific gene loci (Figures 3 and 4).

Figure 3.

Figure 3

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Gene loci imaging using the tetO & TetR-FP system in live cells. (A) Average number of TetR-YFP focus per cell. The ratio of the number of the total analyzed focus and the number of total analyzed cells for TetR-YFP. TetR-mTopaz and TetR-EYFP exhibited better focus than other TetR-YFPs. The error bars indicate the mean ± s.e.m. from independent experiments. (B) Whisker box plot of the SNR distribution of TetR-FPs. (C) DNA foci distribution in E. coli cells using FROS with each YFP. The number of analyzed cells for each FP was as follows: 309 for YPet, 99 for SYFP2, 485 for mTopaz, 323 for mCitrine, 372 for mClover3, 259 for Venus, and 489 for EYFP. Statistical significance was assessed using one-way ANOVA followed by posthoc Tukey tests, and the results are shown in Table S4.

Figure 4.

Figure 4

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Gene loci imaging using tetO & TetR-FP system in live cells. (A) Average number of TetR-FP focus per cell. The ratio of the number of the total analyzed focus and the number of the total analyzed cells for TetR-RFP. TetR-mCrimson3 and TetR-dKatushka displayed better focus than other TetR-RFPs. The error bars indicate the mean ± s.e.m. from independent experiments. (B) Whisker box plot of the SNR distribution of tetR-FPs. (C) DNA foci distribution in E. coli cells using FROS with each RFPs. The number of analyzed cells for each FP was as follows: 718 for mRFP, 191 for FusionRed, 845 for mCrimson3, and 837 for dKatushka. Statistical significance was assessed using one-way ANOVA followed by posthoc Tukey tests, and the results are shown in Table S4.

We imaged DNA loci with FROS using seven YFPs and five RFPs, and measured the average number of DNA spots per cell for each TetR-FP. Among the YFPs, EYFP and mTopaz showed the highest number of spots per cell, indicating their suitability for observing DNA loci using FROS (Figure 3A). Interestingly, despite their high single FP intensities, Venus and Ypet did not present many spots per cell, suggesting that the properties of TetR-FP may vary depending on the type of FPs and that performance cannot be explained solely by the properties of the FP itself.

In fluorescence imaging, a high number of foci is preferable; however, the quality of these foci, which is related to the resolution, is also crucial. To assess the quality of the DNA spots, we compared the SNR of each spot (Figures 3B and 4B). Since the average SNR of the entire spot and the SNRs of individual spots are important, we analyzed the quality of the TetR-FP spots using a whisker-box plot of the SNR distribution. Among the YFPs, EYFP and mTopaz, which showed many spots per cell, had a high median SNR of ∼3.5. For EYFP, the median was similar to the mean value, and for mTopaz, the median was higher than the mean value, indicating that spots with high SNR were more prevalent than those with low SNR, which could be advantageous for imaging purposes.

Among the RFPs, mCrimson3 and dKatushka were found to be the most suitable for DNA locus observation as they had the most spots per cell (Figure 4A). Notably, despite its decent single-FP intensity, mCherry2 is unsuitable for FROS because it rarely produces a single DNA spot. Consistent with the YFPs, among the RFPs, dKatushka and mCrimson3 showed the highest median SNR (∼5) (Figure 4B). The median values of both dKatushka and mCrimson3 were lower than the mean values. However, dKatushka exhibited a more significant difference between the median and mean values. An excessive number of TetR-FPs bound to the tetO array may inhibit cell proliferation.33 In our experiments, TetR-dKatushka expression was associated with some elongated cells (Figure S4). As dKatushka is the only dimeric protein among the FPs that can lead to TetR-dKatushka aggregation in cells, monomer or weak dimer FPs seem to be suitable for observing DNA loci. Despite the high focus per cell and the SNR of TetR-dKatushka, similar to mCrimson3, the latter should be more appropriate for DNA locus observation owing to cell elongation issues with TetR-dKatushka.

The difference in the SNR between YFPs and RFPs may be attributed to the interaction between TetR and tetO. Despite having the same expression level of TetR-FP, TetR-YFPs exhibited fewer spots per cell than TetR-RFPs (Figure 5). This suggests that the interaction between TetR-YFPs and tetO may be weaker than that between TetR-RFPs and tetO. Consequently, the increased number of diffusing TetR-YFPs leads to a higher background signal and a lower SNR for YFPs.

Figure 5.

Figure 5

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Number of spots per cell varies with the expression level of TetR-FP. At an expression level of approximately 70 copies of TetR-FPs for both YFP and RFP, the maximum number of spots per cell was observed. Notably, RFPs tend to reveal a higher number of spots per cell than YFPs. The error bars indicate the mean ± s.e.m. from independent experiments.

3.2.2. DNA Foci Detection in E. coli Using TetR-FP

The number of DNA foci detected in a cell is shown in Figures 3C and 4C. Considering factors such as doubling time, replication time, and the relative position of the lacZ gene on the chromosome, the estimated number of gene loci to be detected was 1.57 in a cell (Table S7); 43% of cells had a copy of the lacZ gene, while 57% of cells had two copies of the lacZ gene. Because all cells contained at least one copy of the lacZ gene, those marked as “0 foci” indicated that a significant portion of the lacZ gene was not detected by TetR-FP FROS. This result indicates that TetR-FP FROS may not reveal all gene loci, underscoring the importance of awareness of the limitations in counting the absolute number of gene loci. Among the YFPs, EYFP and mTopaz had a better quality than the other YFPs for detecting gene loci (Figure 3C).

Compared with YFPs, RFPs exhibited better detection efficiencies for gene loci (Figure 4C). The average number of detected gene loci was ∼1.2 for mCrimson3 and dKatushka, which was close to the expected value of 1.7 (Figure 4A). mCrimson3 and dKatushka, with high foci per cell and SNR, exhibited distributions of two foci, one focus, and zero foci in approximately 30, 50, and 20% of the cells, respectively (Figure 4C). Notably, none of the cells showed DNA loci with mCherry2. Overall, these results indicate that RFPs, such as Crimson3 and dKatushka, may be better choices than YFPs for counting gene loci among the tested FPs, although RFPs still underestimate the number of gene loci.

Background signals, such as cellular autofluorescence and the signals from diffusing FPs in the cytoplasm, should be minimized to utilize FROS for gene loci observation.62 Further, adequate control of the FP expression level is necessary.29 Thus, we explored how the expression level of TetR-FPs affects the visibility of gene loci using FPs that exhibit a high number of spots per cell (Figure 5). We analyzed four FPs that showed the best results in this study: EYFP and mTopaz from the YFPs and mCrimson3 and dKatushka from the RFPs. Interestingly, for both the YFPs and RFPs, the optimal copy number of TetR-FPs was approximately 70 copies per cell to observe gene loci (Figure 5). This number may balance the need to avoid insufficient TetR-FPs, which would result in too few TetR-FPs binding to the gene, and excessive TetR-FPs, which would increase the background noise from diffusing TetR-FPs. Both cases hindered observation of the gene loci. Based on the concentration-dependent gene loci number, ∼1.2 gene loci were detected by RFPs; this number declined to ∼0.4 for YFPs, confirming that RFP was more effective than YFP for observing gene loci in our system. Concentration-dependent detection of gene loci numbers should be analyzed if quantitative gene loci numbers need to be observed.

3.3. Effect of Cell Fixation on DNA Loci Observation

To simultaneously observe DNA and other biomolecules, such as mRNAs, cell fixation is required.30,63,64 Fixation is also required to obtain the locations of molecules with fast dynamics, such as transcription factors, with a high resolution owing to the trade-off between spatial resolution and temporal resolution.65,66 Paraformaldehyde (PFA) has been generally used as a cross-linking fixation method, and fixation using glyoxal has recently been introduced.67 Each method has its own advantages and disadvantages depending on the types of cells or proteins.68−70 In this study, we tested both fixation methods to determine whether the gene loci remained visible in fixed E. coli cells. In live cells, one or two DNA loci spots were typically observed, representing signals from TetR-FPs bound to the tetO sequences (Figure 6, left, and 7, left). However, after fixation, fluorescent spots at the gene loci were significantly altered. More than two loci were observed or completely disappeared in both YFPs and RFPs (Figure 6, middle, right and 7, middle, right). In addition, the average intensity of TetR-FP in the cells changed after fixation (Figure S5). If fixation simply immobilizes the diffusing TetR-FPs, the abundance of TetR-FPs bound to the tetO sequence should dominate the signals, overshadowing those from immobilized TetR-FPs that are unbound to DNA. However, our results suggest that fixation may induce the clustering of diffusing TetR-FPs or detachment of TetR-FPs from the tetO sequences. The first case is in line with recent findings that indicate that fixation can affect the liquid–liquid phase separation of proteins, leading to the formation of droplet-like puncta in fixed mammalian cells, which is not observed in live cells.71 Clustering of membrane proteins has also been observed after fixation, which may lead to false-positive spots in fixed cells.72 In the second case, a similar phenomenon was observed in previous studies where the foci of DNA-binding proteins in the chromatin, observed in live mouse fibroblasts, disappeared after fixation.73 This result suggests that fixation significantly alters the localization of DNA-binding proteins. Because fixation occurs from outside the cell, if the fixation process is slower than the binding and unbinding kinetics of TetR to tetO, the local concentration around the DNA loci located inside the cell decreases. Consequently, the occurrence of TetR binding decreased without affecting unbinding kinetics, resulting in detachment of TetR-FP from the tetO sequence.74 Fixation seems to change the structure of TetR or DNA, altering the binding dynamics between tetO and TetR, leading to the detachment of TetR-FPs from DNA.34,75 Among the FPs tested, mTopaz, EYFP, mCrimson3, and dKatushka fixed by glyoxal presented clear gene loci images Figure 7.

Figure 6.

Figure 6

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Representative image of TetR-YFP in cells with the tetO sequence for gene loci imaging. Cells were imaged under three different conditions: live (left), PFA fixed (middle), and glyoxal fixed (right). Under the live cell condition, 1–2 spots were observed for all FPs. After fixation, the observed spots diverged from those in the live cell observations. Scale bar = 1 μm.

Figure 7.

Figure 7

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Representative image of TetR-RFP in cells with the tetO sequence for gene loci imaging. Cells were imaged under three different conditions: live (left), PFA fixed (middle), and glyoxal fixed (right). Under the live cell condition, 1–2 spots were observed for all FPs except mCherry2. After fixation, the observed spots diverged from those in the live cell observations. Scale bar = 1 μm.

3.4. Comparison of the Gene Loci Locations Between Live and Fixed Cells

Before comparing gene locus locations between live and fixed cells, we obtained the gene locus distributions of all 12 FPs in living cells (Figure S6). All FPs showed similar gene locus distributions. However, there was a slight difference between the YFPs and RFPs. The gene loci measured using YFPs were closer to the center of the cells than those measured using RFPs. The average gene locations from the center of the long axis obtained for each TetR-FP are summarized in Table S8. The average gene locations from the center on the long axis were measured to be 0.414 ± 0.024 and 0.507 ± 0.015 μm for YFPs and RFPs, respectively. For all 12 FPs, the average gene location is 0.448 ± 0.050 μm. Currently, we cannot clearly explain the discrepancy between the two types of FPs. The higher background signals of YFPs compared to RFPs may have contributed to the localization accuracy. These results suggest that the determination of gene locus location using FROS has an uncertainty, with a standard deviation of 0.05 μm (Table S8). Considering that RFPs have fewer background signals than YFPs, we suggest that the location of the gene locus measured using RFPs is more reliable.

As fixation can induce alterations in the spatial localization of intracellular biomolecules, such as proteins, chromatin, and organelles,76−80 we compared the positions of gene loci between live and fixed cells, as observed by mTopaz, EYFP, mCrimson3, and dKatushka (Figure 8). For the quantitative analysis, we used the cosine distance, which measures the difference between two functions. The cosine distances between the gene locus distributions in PFA/glyoxal-fixed cells and those in live cells are shown in Figure S7. PFA fixation resulted in severe alterations in the gene locus locations for all FPs. Glyoxal fixation typically resulted in less alteration of the DNA locus location in the tetO-TetR system than PFA fixation (Figure S7). However, many FPs are affected by glyoxal fixation, which limits their ability to preserve gene loci, as observed in live cells. In our test, mCrimson3 with glyoxal fixation preserved the localization of gene loci close to those observed in live cells (Figures 8 and S7). We noted that fixation could lead to misinterpretation of the DNA location in E. coli in the tetO-TetR system. Nonetheless, if fixation is unavoidable for gene locus observation using the tetO-TetR system, mCrimson3 with glyoxal fixation is recommended, and the results should be compared to those from live cells. However, because new FPs were developed after our initial experiment, new FPs, such as mScarlet3, mRuby3, and sfCherry, may offer improved performance. In addition, green FPs were not included in this study.

Figure 8.

Figure 8

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Spatial distribution of TetR-FP focus. Average spatial distribution of (A) TetR-EYFP (left), TetR-mTopaz (right), and (B) TetR-mCrimson3 (left), TetR-dKatushka (right) in cells with the tetO sequence. The location of the TetR-FP focus was examined under three different conditions (live, PFA, and glyoxal), and their spatial distribution for the short axis and long axis was compared. The foci of all four FPs do not represent the real position of the TetO array when cells are fixed with formaldehyde. Glyoxal fixation changes the spatial distribution of the short and long axes. However, glyoxal fixation of TetR-mCrimson3 closely represents the localization of gene loci to that in live cells.

4. Conclusion

In this study, we delineated the performance of various FPs at the single-molecule level in living E. coli cells using Tsr-FP for single-FP evaluation and TetR-FP and tetO sequences for gene locus observation. This analysis provides insights into the brightness and photostability of single FPs, highlighting the superior performance of certain YFPs and RFPs in live-cell single-molecule imaging. The discrepancies between in vitro/bulk measurements and in vivo single-molecule assessments underscore the importance of our evaluation scheme in living cells for advanced fluorescence imaging applications. Investigation of gene loci using TetR-FP and tetO sequences in live cells has elucidated the effectiveness of specific FPs in the visualization of DNA loci, with a particular focus on the number of spots per cell and SNR as critical determinants of imaging quality. We also explored the challenges associated with cell fixation, revealing that the fixation method could affect the integrity of the observed signals, leading to clustering or detachment of TetR-FPs and altered gene locus localization. Based on our comparative analysis of PFA and glyoxal fixation, although glyoxal fixation tended to preserve the gene locus positions more effectively than PFA, both methods were susceptible to fixation-induced artifacts. This study provides a guide for future studies that use FPs to observe gene loci in live and fixed E. coli strains.

Acknowledgments

This work was supported by the Creative-Pioneering Researchers Program of Seoul National University, and NRF-2023R1A2C2006606 and NRF-2020R1A5A1019141 of the National Research Foundation of Korea.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jpcb.4c01816.

  • Composition of the fixation solutions, relative brightness calculation in our experimental scheme, correction factor calculation, general properties of FPs used in this work, the average SNR of each Tsr-FP, comparison of brightness, statistical significance, literature value of brightness of FPs, total expression level of TetR-FP in E. coli, estimation of the average number of gene loci, average gene location, bleaching step number ratio, graphical explanation of correction, comparison of normalized brightness, elongated E. coli cells expressing TetR-dKatushka, the relative average intensity of each condition, gene locus distributions, cosine distance between distributions in PFA or glyoxal fixed cells and those in live cells (PDF)

Author Present Address

‡ Department of Physics, University of Illinois at Urbana—Champaign, Illinois 61801, USA

Author Present Address

§ Oncode Institute, Hubrecht Institute—KNAW and University Medical Center Utrecht, 3584 CT Utrecht, The Netherlands.

Author Contributions

† J.B.S., S.K., and S.Y. are contributed equally. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

The authors declare no competing financial interest.

Special Issue

Published as part of The Journal of Physical Chemistry Bvirtual special issue “Advances in Cellular Biophysics”.

Supplementary Material

jp4c01816_si_001.pdf (771KB, pdf)

References

  1. Shaner N. C.; Lambert G. G.; Chammas A.; Ni Y.; Cranfill P. J.; Baird M. A.; Sell B. R.; Allen J. R.; Day R. N.; Israelsson M.; et al. A bright monomeric green fluorescent protein derived from Branchiostoma lanceolatum. Nat. Methods 2013, 10 (5), 407–409. 10.1038/nmeth.2413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Day R. N.; Davidson M. W. The fluorescent protein palette: tools for cellular imaging. Chem. Soc. Rev. 2009, 38 (10), 2887–2921. 10.1039/b901966a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Yang S.; Kim S.; Kim D. K.; An H. J.; Son J. B.; Gynna A. H.; Lee N. K. Transcription and translation contribute to gene locus relocation to the nucleoid periphery in E. coli. Nat. Commun. 2019, 10 (1), 5131. 10.1038/s41467-019-13152-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Valencia-Burton M.; McCullough R. M.; Cantor C. R.; Broude N. E. RNA visualization in live bacterial cells using fluorescent protein complementation. Nat. Methods 2007, 4 (5), 421–427. 10.1038/nmeth1023. [DOI] [PubMed] [Google Scholar]
  5. Stracy M.; Lesterlin C.; de Leon F. G.; Uphoff S.; Zawadzki P.; Kapanidis A. N. Live-cell superresolution microscopy reveals the organization of RNA polymerase in the bacterial nucleoid. Proc. Natl. Acad. Sci. U.S.A. 2015, 112 (32), E4390–E4399. 10.1073/pnas.1507592112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Fan J.; El Sayyed H.; Pambos O. J.; Stracy M.; Kyropoulos J.; Kapanidis A. N. RNA polymerase redistribution supports growth in E. coli strains with a minimal number of rRNA operons. Nucleic Acids Res. 2023, 51 (15), 8085–8101. 10.1093/nar/gkad511. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bakshi S.; Choi H.; Weisshaar J. C. The spatial biology of transcription and translation in rapidly growing Escherichia coli. Front. Microbiol. 2015, 6, 636. 10.3389/fmicb.2015.00636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Weng X.; Xiao J. Spatial organization of transcription in bacterial cells. Trends Genet. 2014, 30 (7), 287–297. 10.1016/j.tig.2014.04.008. [DOI] [PubMed] [Google Scholar]
  9. Gray W. T.; Govers S. K.; Xiang Y.; Parry B. R.; Campos M.; Kim S.; Jacobs-Wagner C. Nucleoid Size Scaling and Intracellular Organization of Translation across Bacteria. Cell 2019, 177 (6), 1632.e20–1648.e20. 10.1016/j.cell.2019.05.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Golding I.; Cox E. C. RNA dynamics in live Escherichia coli cells. Proc. Natl. Acad. Sci. U.S.A. 2004, 101 (31), 11310–11315. 10.1073/pnas.0404443101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Campbell B. C.; Paez-Segala M. G.; Looger L. L.; Petsko G. A.; Liu C. F. Chemically stable fluorescent proteins for advanced microscopy. Nat. Methods 2022, 19 (12), 1612–1621. 10.1038/s41592-022-01660-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hirano M.; Ando R.; Shimozono S.; Sugiyama M.; Takeda N.; Kurokawa H.; Deguchi R.; Endo K.; Haga K.; Takai-Todaka R.; et al. Author Correction: A highly photostable and bright green fluorescent protein. Nat. Biotechnol. 2022, 40 (9), 1412. 10.1038/s41587-022-01469-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Pennacchietti F.; Alvelid J.; Morales R. A.; Damenti M.; Ollech D.; Oliinyk O. S.; Shcherbakova D. M.; Villablanca E. J.; Verkhusha V. V.; Testa I. Blue-shift photoconversion of near-infrared fluorescent proteins for labeling and tracking in living cells and organisms. Nat. Commun. 2023, 14 (1), 8402. 10.1038/s41467-023-44054-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Shaner N. C.; Steinbach P. A.; Tsien R. Y. A guide to choosing fluorescent proteins. Nat. Methods 2005, 2 (12), 905–909. 10.1038/nmeth819. [DOI] [PubMed] [Google Scholar]
  15. Snapp E. L. Fluorescent proteins: a cell biologist’s user guide. Trends Cell Biol. 2009, 19 (11), 649–655. 10.1016/j.tcb.2009.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Kleeman B.; Olsson A.; Newkold T.; Kofron M.; DeLay M.; Hildeman D.; Grimes H. L. A guide to choosing fluorescent protein combinations for flow cytometric analysis based on spectral overlap. Cytometry 2018, 93 (5), 556–562. 10.1002/cyto.a.23360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Cranfill P. J.; Sell B. R.; Baird M. A.; Allen J. R.; Lavagnino Z.; de Gruiter H. M.; Kremers G. J.; Davidson M. W.; Ustione A.; Piston D. W. Quantitative assessment of fluorescent proteins. Nat. Methods 2016, 13 (7), 557–562. 10.1038/nmeth.3891. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Chen X.; Zaro J. L.; Shen W. C. Fusion protein linkers: property, design and functionality. Adv. Drug Deliv. Rev. 2013, 65 (10), 1357–1369. 10.1016/j.addr.2012.09.039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Mo G. C.; Ross B.; Hertel F.; Manna P.; Yang X.; Greenwald E.; Booth C.; Plummer A. M.; Tenner B.; Chen Z.; et al. Genetically encoded biosensors for visualizing live-cell biochemical activity at super-resolution. Nat. Methods 2017, 14 (4), 427–434. 10.1038/nmeth.4221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Betzig E.; Patterson G. H.; Sougrat R.; Lindwasser O. W.; Olenych S.; Bonifacino J. S.; Davidson M. W.; Lippincott-Schwartz J.; Hess H. F. Imaging intracellular fluorescent proteins at nanometer resolution. Science 2006, 313 (5793), 1642–1645. 10.1126/science.1127344. [DOI] [PubMed] [Google Scholar]
  21. Yu J.; Xiao J.; Ren X.; Lao K.; Xie X. S. Probing gene expression in live cells, one protein molecule at a time. Science 2006, 311 (5767), 1600–1603. 10.1126/science.1119623. [DOI] [PubMed] [Google Scholar]
  22. Elf J.; Li G. W.; Xie X. S. Probing transcription factor dynamics at the single-molecule level in a living cell. Science 2007, 316 (5828), 1191–1194. 10.1126/science.1141967. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Choi P. J.; Cai L.; Frieda K.; Xie X. S. A stochastic single-molecule event triggers phenotype switching of a bacterial cell. Science 2008, 322 (5900), 442–446. 10.1126/science.1161427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Taniguchi Y.; Choi P. J.; Li G. W.; Chen H.; Babu M.; Hearn J.; Emili A.; Xie X. S. Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science 2010, 329 (5991), 533–538. 10.1126/science.1188308. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Jones D. L.; Leroy P.; Unoson C.; Fange D.; Curic V.; Lawson M. J.; Elf J. Kinetics of dCas9 target search in Escherichia coli. Science 2017, 357 (6358), 1420–1424. 10.1126/science.aah7084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Hwang J.; Kim J. Y.; Kim C.; Park S.; Joo S.; Kim S. K.; Lee N. K. Single-molecule observation of ATP-independent SSB displacement by RecO in Deinococcus radiodurans. Elife 2020, 9, e50945 10.7554/elife.50945. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kim Y.; Kim H.; Son J. B.; Filatov M.; Choi C. H.; Lee N. K.; Lee D. Single-Benzene Dual-Emitters Harness Excited-State Antiaromaticity for White Light Generation and Fluorescence Imaging. Angew. Chem., Int. Ed. Engl. 2023, 135 (20), e202302107 10.1002/ange.202302107. [DOI] [PubMed] [Google Scholar]
  28. Koh H. R.; Roy R.; Sorokina M.; Tang G. Q.; Nandakumar D.; Patel S. S.; Ha T. Correlating Transcription Initiation and Conformational Changes by a Single-Subunit RNA Polymerase with Near Base-Pair Resolution. Mol. Cell 2018, 70 (4), 695.e5–706.e5. 10.1016/j.molcel.2018.04.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hensel Z.; Weng X.; Lagda A. C.; Xiao J. Transcription-factor-mediated DNA looping probed by high-resolution, single-molecule imaging in live E. coli cells. PLoS Biol. 2013, 11 (6), e1001591 10.1371/journal.pbio.1001591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Wang M.; Zhang J.; Xu H.; Golding I. Measuring transcription at a single gene copy reveals hidden drivers of bacterial individuality. Nat. Microbiol. 2019, 4 (12), 2118–2127. 10.1038/s41564-019-0553-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Mirkin E. V.; Chang F. S.; Kleckner N. Protein-mediated chromosome pairing of repetitive arrays. J. Mol. Biol. 2014, 426 (3), 550–557. 10.1016/j.jmb.2013.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Lau I. F.; Filipe S. R.; Soballe B.; Okstad O. A.; Barre F. X.; Sherratt D. J. Spatial and temporal organization of replicating Escherichia coli chromosomes. Mol. Microbiol. 2003, 49 (3), 731–743. 10.1046/j.1365-2958.2003.03640.x. [DOI] [PubMed] [Google Scholar]
  33. Possoz C.; Filipe S. R.; Grainge I.; Sherratt D. J. Tracking of controlled Escherichia coli replication fork stalling and restart at repressor-bound DNA in vivo. EMBO J. 2006, 25 (11), 2596–2604. 10.1038/sj.emboj.7601155. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Schnell U.; Dijk F.; Sjollema K. A.; Giepmans B. N. Immunolabeling artifacts and the need for live-cell imaging. Nat. Methods 2012, 9 (2), 152–158. 10.1038/nmeth.1855. [DOI] [PubMed] [Google Scholar]
  35. Nguyen A. W.; Daugherty P. S. Evolutionary optimization of fluorescent proteins for intracellular FRET. Nat. Biotechnol. 2005, 23 (3), 355–360. 10.1038/nbt1066. [DOI] [PubMed] [Google Scholar]
  36. Kremers G. J.; Goedhart J.; van Munster E. B.; Gadella T. W. Cyan and Yellow Super Fluorescent Proteins with Improved Brightness, Protein Folding, and FRET Förster Radius,. Biochemistry 2006, 45 (21), 6570–6580. 10.1021/bi0516273. [DOI] [PubMed] [Google Scholar]
  37. Tsien R. Y. The green fluorescent protein. Annu. Rev. Biochem. 1998, 67, 509–544. 10.1146/annurev.biochem.67.1.509. [DOI] [PubMed] [Google Scholar]
  38. Griesbeck O.; Baird G. S.; Campbell R. E.; Zacharias D. A.; Tsien R. Y. Reducing the Environmental Sensitivity of Yellow Fluorescent Protein. J. Biol. Chem. 2001, 276 (31), 29188–29194. 10.1074/jbc.M102815200. [DOI] [PubMed] [Google Scholar]
  39. Bajar B. T.; Wang E. S.; Lam A. J.; Kim B. B.; Jacobs C. L.; Howe E. S.; Davidson M. W.; Lin M. Z.; Chu J. Improving brightness and photostability of green and red fluorescent proteins for live cell imaging and FRET reporting. Sci. Rep. 2016, 6, 20889. 10.1038/srep20889. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Nagai T.; Ibata K.; Park E. S.; Kubota M.; Mikoshiba K.; Miyawaki A. A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat. Biotechnol. 2002, 20 (1), 87–90. 10.1038/nbt0102-87. [DOI] [PubMed] [Google Scholar]
  41. Ormo M.; Cubitt A. B.; Kallio K.; Gross L. A.; Tsien R. Y.; Remington S. J. Crystal Structure of the Aequorea victoria Green Fluorescent Protein. Science 1996, 273 (5280), 1392–1395. 10.1126/science.273.5280.1392. [DOI] [PubMed] [Google Scholar]
  42. Chudakov D. M.; Matz M. V.; Lukyanov S.; Lukyanov K. A. Fluorescent proteins and their applications in imaging living cells and tissues. Physiol. Rev. 2010, 90 (3), 1103–1163. 10.1152/physrev.00038.2009. [DOI] [PubMed] [Google Scholar]
  43. Shen Y.; Chen Y.; Wu J.; Shaner N. C.; Campbell R. E. Engineering of mCherry variants with long Stokes shift, red-shifted fluorescence, and low cytotoxicity. PLoS One 2017, 12 (2), e0171257 10.1371/journal.pone.0171257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Campbell R. E.; Tour O.; Palmer A. E.; Steinbach P. A.; Baird G. S.; Zacharias D. A.; Tsien R. Y. A monomeric red fluorescent protein. Proc. Natl. Acad. Sci. U.S.A. 2002, 99 (12), 7877–7882. 10.1073/pnas.082243699. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Shemiakina I. I.; Ermakova G. V.; Cranfill P. J.; Baird M. A.; Evans R. A.; Souslova E. A.; Staroverov D. B.; Gorokhovatsky A. Y.; Putintseva E. V.; Gorodnicheva T. V.; et al. A monomeric red fluorescent protein with low cytotoxicity. Nat. Commun. 2012, 3, 1204. 10.1038/ncomms2208. [DOI] [PubMed] [Google Scholar]
  46. Landgraf D.; Okumus B.; Chien P.; Baker T. A.; Paulsson J. Segregation of molecules at cell division reveals native protein localization. Nat. Methods 2012, 9 (5), 480–482. 10.1038/nmeth.1955. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Orth P.; Schnappinger D.; Hillen W.; Saenger W.; Hinrichs W. Structural basis of gene regulation by the tetracycline inducible Tet repressor-operator system. Nat. Struct. Biol. 2000, 7 (3), 215–219. 10.1038/73324. [DOI] [PubMed] [Google Scholar]
  48. Robinett C. C.; Straight A.; Li G.; Willhelm C.; Sudlow G.; Murray A.; Belmont A. S. In vivo localization of DNA sequences and visualization of large-scale chromatin organization using lac operator/repressor recognition. J. Cell Biol. 1996, 135 (6), 1685–1700. 10.1083/jcb.135.6.1685. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Yang S.; Kim S.; Rim Lim Y.; Kim C.; An H. J.; Kim J. H.; Sung J.; Lee N. K. Contribution of RNA polymerase concentration variation to protein expression noise. Nat. Commun. 2014, 5, 4761. 10.1038/ncomms5761. [DOI] [PubMed] [Google Scholar]
  50. Kuhlman T. E.; Cox E. C. Gene location and DNA density determine transcription factor distributions in Escherichia coli. Mol. Syst. Biol. 2012, 8, 610. 10.1038/msb.2012.42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Botman D.; de Groot D. H.; Schmidt P.; Goedhart J.; Teusink B. In vivo characterisation of fluorescent proteins in budding yeast. Sci. Rep. 2019, 9 (1), 2234. 10.1038/s41598-019-38913-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Mowery P.; Ostler J. B.; Parkinson J. S. Different signaling roles of two conserved residues in the cytoplasmic hairpin tip of Tsr, the Escherichia coli serine chemoreceptor. J. Bacteriol. 2008, 190 (24), 8065–8074. 10.1128/JB.01121-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Oh D.; Yu Y.; Lee H.; Wanner B. L.; Ritchie K. Dynamics of the serine chemoreceptor in the Escherichia coli inner membrane: a high-speed single-molecule tracking study. Biophys. J. 2014, 106 (1), 145–153. 10.1016/j.bpj.2013.09.059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Zhou H. X.; Rivas G.; Minton A. P. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Annu. Rev. Biophys. 2008, 37, 375–397. 10.1146/annurev.biophys.37.032807.125817. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. McGuffee S. R.; Elcock A. H. Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. PLoS Comput. Biol. 2010, 6 (3), e1000694 10.1371/journal.pcbi.1000694. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. van den Berg B.; Ellis R. J.; Dobson C. M. Effects of macromolecular crowding on protein folding and aggregation. EMBO J. 1999, 18 (24), 6927–6933. 10.1093/emboj/18.24.6927. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Wang Q.; Zhuravleva A.; Gierasch L. M. Exploring weak, transient protein-protein interactions in crowded in vivo environments by in-cell nuclear magnetic resonance spectroscopy. Biochemistry 2011, 50 (43), 9225–9236. 10.1021/bi201287e. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Morikawa T. J.; Fujita H.; Kitamura A.; Horio T.; Yamamoto J.; Kinjo M.; Sasaki A.; Machiyama H.; Yoshizawa K.; Ichimura T.; et al. Dependence of fluorescent protein brightness on protein concentration in solution and enhancement of it. Sci. Rep. 2016, 6, 22342. 10.1038/srep22342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Kim S. Y.; Gitai Z.; Kinkhabwala A.; Shapiro L.; Moerner W. E. Single molecules of the bacterial actin MreB undergo directed treadmilling motion in Caulobacter crescentus. Proc. Natl. Acad. Sci. U.S.A. 2006, 103 (29), 10929–10934. 10.1073/pnas.0604503103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Deich J.; Judd E. M.; McAdams H. H.; Moerner W. E. Visualization of the movement of single histidine kinase molecules in live Caulobacter cells. Proc. Natl. Acad. Sci. U.S.A. 2004, 101 (45), 15921–15926. 10.1073/pnas.0404200101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Cai L.; Friedman N.; Xie X. S. Stochastic protein expression in individual cells at the single molecule level. Nature 2006, 440 (7082), 358–362. 10.1038/nature04599. [DOI] [PubMed] [Google Scholar]
  62. Xie X. S.; Choi P. J.; Li G. W.; Lee N. K.; Lia G. Single-molecule approach to molecular biology in living bacterial cells. Annu. Rev. Biophys. 2008, 37, 417–444. 10.1146/annurev.biophys.37.092607.174640. [DOI] [PubMed] [Google Scholar]
  63. Koh H. R.; Ghanbariniaki A.; Myong S. RNA stem structure governs coupling of dicing and gene silencing in RNA interference. Proc. Natl. Acad. Sci. U.S.A. 2017, 114 (48), E10349–E10358. 10.1073/pnas.1710298114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Kim S.; Beltran B.; Irnov I.; Jacobs-Wagner C. Long-Distance Cooperative and Antagonistic RNA Polymerase Dynamics via DNA Supercoiling. Cell 2019, 179 (1), 106.e16–119.e16. 10.1016/j.cell.2019.08.033. [DOI] [PubMed] [Google Scholar]
  65. Hammar P.; Wallden M.; Fange D.; Persson F.; Baltekin O.; Ullman G.; Leroy P.; Elf J. Direct measurement of transcription factor dissociation excludes a simple operator occupancy model for gene regulation. Nat. Genet. 2014, 46 (4), 405–408. 10.1038/ng.2905. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Choi H.; Son J. B.; Kang J.; Kwon J.; Kim J. H.; Jung M.; Kim S. K.; Kim S.; Mun J. Y. Leucine-induced localization of Leucyl-tRNA synthetase in lysosome membrane. Biochem. Biophys. Res. Commun. 2017, 493 (2), 1129–1135. 10.1016/j.bbrc.2017.09.008. [DOI] [PubMed] [Google Scholar]
  67. Richter K. N.; Revelo N. H.; Seitz K. J.; Helm M. S.; Sarkar D.; Saleeb R. S.; D’Este E.; Eberle J.; Wagner E.; Vogl C.; et al. Glyoxal as an alternative fixative to formaldehyde in immunostaining and super-resolution microscopy. EMBO J. 2018, 37 (1), 139–159. 10.15252/embj.201695709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Celikkan F. T.; Mungan C.; Sucu M.; Uysal F.; Hayme S. K.; Hayme S.; Kuscu N.; Ozkavukcu S.; Celik-Ozenci C.; Can A. PFA is superior to glyoxal in preserving oocyte, embryo, and stem cell proteins evidenced by super-resolution microscopical surveys of epitopes. J. Assist. Reprod. Genet. 2020, 37 (2), 369–384. 10.1007/s10815-019-01666-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Konno K.; Yamasaki M.; Miyazaki T.; Watanabe M. Glyoxal fixation: An approach to solve immunohistochemical problem in neuroscience research. Sci. Adv. 2023, 9 (28), eadf7084 10.1126/sciadv.adf7084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Thomas S.; Sadanandan J.; Blackburn S. L.; McBride D. W.; Dienel A.; Hong S.; Zeineddine H. A.; Thankamani P. K. Glyoxal Fixation Is Optimal for Immunostaining of Brain Vessels, Pericytes and Blood-Brain Barrier Proteins. Int. J. Mol. Sci. 2022, 23 (14), 7776. 10.3390/ijms23147776. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Irgen-Gioro S.; Yoshida S.; Walling V.; Chong S. Fixation can change the appearance of phase separation in living cells. Elife 2022, 11, e79903 10.7554/elife.79903. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Stanly T. A.; Fritzsche M.; Banerji S.; Garcia E.; Bernardino de la Serna J.; Jackson D. G.; Eggeling C. Critical importance of appropriate fixation conditions for faithful imaging of receptor microclusters. Biol. Open 2016, 5 (9), 1343–1350. 10.1242/bio.019943. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Schmiedeberg L.; Skene P.; Deaton A.; Bird A. A temporal threshold for formaldehyde crosslinking and fixation. PLoS One 2009, 4 (2), e4636 10.1371/journal.pone.0004636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Yoshida S. R.; Maity B. K.; Chong S. Visualizing Protein Localizations in Fixed Cells: Caveats and the Underlying Mechanisms. J. Phys. Chem. B 2023, 127 (19), 4165–4173. 10.1021/acs.jpcb.3c01658. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Srinivasan M.; Sedmak D.; Jewell S. Effect of fixatives and tissue processing on the content and integrity of nucleic acids. Am. J. Pathol. 2002, 161 (6), 1961–1971. 10.1016/S0002-9440(10)64472-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Li M. W.; Zhou L.; Lam H. M. Paraformaldehyde Fixation May Lead to Misinterpretation of the Subcellular Localization of Plant High Mobility Group Box Proteins. PLoS One 2015, 10 (8), e0135033 10.1371/journal.pone.0135033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Hua K.; Ferland R. J. Fixation methods can differentially affect ciliary protein immunolabeling. Cilia 2017, 6, 5. 10.1186/s13630-017-0045-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Jaiswal M.; Tran T. T.; Guo J.; Zhou M.; Kundu S.; Guo Z.; Fanucci G. E. Spin-Labeling Insights into How Chemical Fixation Impacts Glycan Organization on Cells. Appl. Magn. Reson. 2024, 55 (1–3), 317–333. 10.1007/s00723-023-01624-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Lorber D.; Volk T. Evaluation of chromatin mesoscale organization. APL Bioeng. 2022, 6 (1), 010902. 10.1063/5.0069286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Idziak A.; Inavalli V.; Bancelin S.; Arizono M.; Nagerl U. V. The Impact of Chemical Fixation on the Microanatomy of Mouse Organotypic Hippocampal Slices. eNeuro 2023, 10 (9), ENEURO.0104-23.2023 10.1523/eneuro.0104-23.2023. [DOI] [PMC free article] [PubMed] [Google Scholar]

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