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Engineering Recombinant Protein Sensors for Quantifying Histone Acetylation Oscar F. Sanchez, Agnes Mendonca, Ana D. Carneiro, and Chongli Yuan* School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, Indiana 47907, United States S Supporting Information *

ABSTRACT: H3K14ac (acetylation of lysine 14 of histone H3) is one of the most important epigentic modifications. Aberrant changes in H3K14ac have been associated with various diseases, including cancers and neurological disorders. Tools that enable detection and quantification of H3K14ac levels in cell extracts and in situ are thus of critical importance to reveal its role in various biological processes. Current detection techniques of specific histone modifications, however, are constrained by tedious sample pretreatments, lack of quantitative accuracy, and reliance on high quality antibodies. To address this issue, we engineered recombinant sensors that are suitable for probing histone acetylation levels using various biological samples. The protein sensor contains recongition domain(s) with sequences derived from the bromodomain of human polybromo-1 (PB1), a natural H3K14ac reader domain. Various sensor designs were tested using nuclear extracts and live cells. The sensor containing dimeric repeats of bromodomain was found most effective in quantifying H3K14ac level in both in vitro and in situ assays. The sensor has a linear detection range of 0.5−50 nM when mixed with nuclear extracts. The sensor colocalizes with H3K14ac antibodies in situ when transfected into human embryonic kidney 293T (HEK293T) cells and is thus capable of providing spatial details of histone modification within the nucleus. Corrected nuclear fluorescence intensity was used to quantify the modification level in situ and found to correlate well with our in vitro assays. Our sensor offers a novel tool to characterize the histone modification level using nuclear extracts and probe histone modification change in live cells. KEYWORDS: histone acetylation, human polybromo-1, HEK293T, fluorescence correlation spectroscopy, single cell probe

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Conventionally, histone acetylation levels are characterized by fluorescence or colorimetric assays via the use of antibodies. These assays require disruption of cells and can be performed using either cell extracts or fixed cells.9,10 Specifically, to analyze the epigenetic content of cells, nuclear extracts can be obtained using a hypotonic or isotonic lysis buffer or via harnessing a physical process (e.g., sonication).11 Nuclear extracts are then mixed with antibodies specific for the modification of interest. The mixture can then be analyzed using various assays including blotting, colorimetry, fluorescence, and sedimentation to enable the quantification of the histone modification of interest.12−15 Similarly, cells can be immunostained and analyzed using fluorescent techniques such as flow cytometry and fluorescence microscopy.16,17 Recent literature compared results of immunoassays performed using antibodies from different manufacturers and showed significant distinctions.15 A control validation assay of antibody activity prior to any quantification is recommended based on these observations,15 which further adds to the complexity of the immunobased assays.

pigenetic modifications including DNA methylation and histone post-translational modifications (PTMs) can regulate gene expression and contribute to the establishment of inheritable phenotypes responding to environmental and dietary changes.1 There are several types of histone epigenetic modification, such as lysine acetylation, lysine methylation, and serine phosphorylation.2 Among them, lysine acetylation is one of the most well-studied modifications and has been affiliated with many important biological processes. For instance, acetylation of H3 such as acetylation of H3 at lysine 14 (H3K14ac) is associated with transcription activation by facilitating the recruitment of transcription factor TFIID for assembling a preinitiation complex.3 H3K9ac and H3K14ac have been associated with memory formation and consolidation in mice.4,5 Aberrant changes in histone acetylation levels, e.g., hyper-acetylation of H3K14 in the occipital cortex, are common observations in patients with neurodegenerative diseases such as Alzheimer’s disease.6 Hyper-acetylation of H3K14 at a pluripotent gene such as NANOG has been observed in human breast and skin cancers.7,8 Detecting and quantifying histone acetylation level is thus of critical importance for dissecting histone-acetylation-affiliated molecular events that are attributed to distinctive cellular behavior and potentially the establishment of a phenotype. © XXXX American Chemical Society

Received: January 13, 2017 Accepted: February 8, 2017 Published: February 8, 2017 A

DOI: 10.1021/acssensors.7b00026 ACS Sens. XXXX, XXX, XXX−XXX

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ACS Sensors Conventional immunoassays, however, cannot be used to monitor histone acetylation levels in live cells. To address this concern, assays based on a specific region of the antibody (e.g., antigen binding fragment, Fab),18 modified Fab fragments (e.g., scFv),19 as well as native acetylation reader domains have been developed.20−22 Fab and scFv (also known as “mintbodies” when fused to a fluorescent protein) can be used to monitor epigenetic modification levels in live cells and inform the spatial distribution of the modifications within cell nuclei.18,19 These approaches, however, still require antibody fragments to be generated, which is a lengthy process. Additionally, the light chains of Fab have a tendency to form aggregation of homodimers, rendering the quantification difficult since false positive signals can be present.23 scFv requires the production of hybridomas or scFv libraries which is expensive and timeconsuming.24,25 Epigenetic “reader” domains are naturally evolved to target specific epigenetic modifications in cells. Bromodomain(s) fused to a histone protein as well as a pair of fluorescent proteins suitable for the Förster Resonance Energy Transfer (FRET) study has been used to quantify histone acetylation changes in live cells.20,22 When the fused “model” histone protein (assumed to be representative of cellular histones) is of a high modification level, the fused “reader” domain will refold to bind to the model histone, generate high FRET, enable characterization of the modification level in the model histone, and collectively inform the modification level of a single cell.20 This approach has also been used to quantify histone methylation levels.26 Although appealing, this approach has one major limitation. The assay directly probes the modification level of the fused model histone, instead of cellular histones, and thus does not provide any spatial information on histone modifications. The goal of this study is to develop engineered protein sensors to monitor histone acetylation levels in cell extracts and live cells. For live cell applications, specifically, we want to utilize epigenetic reader domains to eliminate the lengthy development process required for Fab or Fab-like fragments. Additionally, we want to eliminate the use of model histones (as required in FRET sensor20,22,26) and consequently enable the characterization of the spatial distribution of histone modifications in live cells. Different from previous studies,20,26,22 we will select and engineer an epigenetic “reader” domain, have it fused to an enhanced fluorescence protein, and use it as an acetylation probe. The genomic region rich in H3K14ac is expected to show high fluorescence intensity, due to the high abundance of engineered sensors bound to the cellular histones. Compared with antibodies, these protein sensors are less prone to induce cell stress, cheaper to produce, and are thus more feasible for various applications. Compared with FRET-based sensors, these protein sensors provide spatial information about epigenetic modifications and use fluorescence intensity as a direct read-out.

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Figure 1. (A) Schematic illustration of the protein sensor in a mono-, di-, and tetrameric form (from top to bottom). (B) Schematic illustration of the designed dimeric protein sensor in the selected mammalian expression vector. (C) Typical SDS-PAGE of fluorescently tagged protein sensors expressed in E. coli. The first and third panels show the 18% SDS-PAGE before Coomassie blue staining. The second and fourth panels show the same 18% SDS-PAGE after Coomassie blue staining. Equivalent fluorescent intensity was observed suggesting high labeling efficiency.

Plasmids encoding for sensors containing tandem repeats of PB1(2) domains were prepared using compatible restriction enzyme pairs (i.e., EcoRI, MfeI, and SalI) following an established protocol.31 The coding fragment of in situ sensors was prepared by subcloning the tandem recognition domain into a pRK5 mammalian expression vector (Karel Svoboda, Addgene plasmid No. 18696).32 pRK5 vector was modified with a SV40 nuclear localization signal (NLS) followed by a (GS)5 linker on the N-terminus. It contains a fluorescence protein conjugate (mEGFP) on the C-terminus. The schematics of the mammalian plasmid is shown in Figure 1B. Size and sequence of the constructed plasmids were verified using DNA-PAGE (Figure S1, Supporting Information) and DNA sequencing, respectively. Recombinant H3K14ac sensors were produced using E. coli culture. Specifically, cells (E. coli cells, (DE3)-RIPL, Stratagene, CA, US) were transformed with the coding plasmid and induced with IPTG at 0.5 mM. Protein sensor was expressed, purified, and tagged with fluorescein on its C-terminus following the established approach we described previously.29 The labeling efficiency of the sensor was typically found to be ≥85%. SDS-PAGE showing purified recombinant sensors of different designs was included in Figure 1C. Molecular weight of the purified protein sensors was further validated using MALDI-TOF analysis. Characterize the Secondary Structure of Engineered Sensors. Circular dichroism (CD) was used to evaluate the secondary structure of protein sensors. CD spectra were collected using a Jasco J1500 spectrometer (Jasco Spectroscopic Cp., Japan) at wavelength between 190 to 260 nm and a scanning rate of 50 nm/min. All samples were measured at 4 °C using a quartz cuvette of 0.1 mm path length (Starna, CA, US). Each spectrum was collected in four repeats and reported as an average. Instrument units were converted to the mean residue molar ellipticity following a standard expression: [θ] = millidegree/(molar concentration × number of amino acids). The α-

EXPERIMENTAL SECTION

Design and Production of H3K14ac Sensors. The second bromodomain of human poly bromodomain 1 (PB1(2)) was selected as the recognition domain for histone modification H3K14ac. This domain is a known epigenetic reader for H3K14ac with a relatively high affinity (Kd ≈ 1.9 ± 0.5 μM) as we demonstrated in our previous work and the literature.27−30 To further improve the binding affinity of the recognition domain, we engineered H3K14ac sensors containing tandem repeats of PB1(2). The schematics of the sensor design is shown in Figure 1A and the detailed amino acid sequence of various sensor designs is included in Table S1 (Supporting Information). B


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Figure 2. (A) Diffusivity and (B) Bound % of the protein sensors mixed with nuclear extracts of varying H3K14ac concentrations. A negative correlation was found between the diffusivity and the concentration of H3K14ac. A correlation coefficient of −0.82, −0.85, and −0.78 was found for monomeric, dimeric, and tetrameric protein sensors, respectively. (C) Bound % measured using dimeric probes mixed with nuclear extracts of varying H3K14ac concentrations. Three different probe concentrations were tested. Data = mean ± S.D., n ≥ 4. helix content of the protein sensor was quantified as the percentage of helicity (% helicity) following eq 1.33,34 %helicity = =

Cell nuclei were then extracted using a Nuclear Extraction Kit (Abcam, CA, US). Nuclear extracts (NE) were analyzed by SDS-PAGE and Western blotting using an anti-histone H3 antibody (ab1791, Abcam, CA, US) as shown in Figure S2 (Supporting Information). The total protein concentration of nuclear extracts was determined using a BCA protein quantification kit (Pierce, PA, US). Acetylation levels of nuclear extracts were determined using an ELISA kit (Histone H3 (acetyl K14) Quantification Kit (Colorimetric), Abcam, CA, USA) following the manufacturer’s protocol. Quantification of Histone Acetylation Level of Nuclear Extracts Using Recombinant Sensors. We devised an assay to quantify the histone acetylation level of nuclear extracts by combining our recombinant sensors with fluorescence correlation spectroscopy (FCS). FCS is an optical technique that measures the diffusivity of fluorescence species via fluorescent fluctuations within a small focal volume. The protein sensors were directly mixed with nuclear extracts at different ratios. The mixture was then examined using a confocal spectrometer (ALBA FCS system, ISS, IL, US). The laser intensity was optimized to minimize the effect of triplet state and photobleaching on the quality of the correlation curve.43 The collected correlation curve (G(τ)) was then analyzed using eq 2

θ222 θ222(max) − 40000 × ⎡⎣1 −

θ222

2.5 ⎤ ( number of amino acid residues )⎦

(1)

where θ222 is the observed residue molar ellipticity at 222 nm. Mammalian Cell Culture. Human embryonic kidney 293T (HEK293T) cells were seeded (∼5 × 105 cells) onto a 10 cm culture dish. Cells were maintained and passaged in Dulbecco modified Eagle medium supplemented with 10% (v/v) fetal bovine serum and 1% (v/ v) of a penicillin−streptomycin solution (Gibco, CA, US) following a standard protocol.35 Sodium butyrate (NaB, Sigma, MO, US) and Trichostatin A (TSA, Sigma, MO, US), known histone deacetylase (HDAC) inhibitors,36−39 were added individually to the culture media for inducing changes in histone acetylation level. These drugs were added after cells reached a confluency of 40−50% (typically ∼24 h post-seeding) to prevent changes in mitotic rate and development of cell phenotypes.40,41 Cells were treated for the following 24 h at NaB concentrations of 3 or 5 mM, or TSA concentrations of 0.5 and 1.0 μM. The exposure dose and duration were selected because they were found to be effective in altering histone acetylation levels while cell viability remains minimally affected.42 After treatment, cells were either detached from the surface of a culture dish using a solution of 0.05% Trypsin-EDTA or imaged via fluorescence microscopy. Detached cells were harvested and lysed.

−1/2 −1 ⎛ τ ⎞ ⎛ τ ⎞ G(τ ) = G(0)⎜1 + ⎟ ⎜1 + 2 ⎟ τD ⎠ ⎝ ω τD ⎠ ⎝

(2)

where τD is the average translational diffusion time, inversely related to the translational diffusion coefficient (DTrans) of the fluorescently tagged species and ω is the aspect ratio of the detection volume calculated as z0/r0. z0 and r0 are the axial and lateral dimensions of the C


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ACS Sensors observation volume, respectively, and were calibrated using a rhodamine 110 dye solution with a known diffusivity.44 All measurements were performed at room temperature in a binding buffer containing 20 mM Tris-HCl pH 7.5, 50 mM KCl, 50 mM MgCl2, 0.1% (w/v) BSA, and 0.01% (v/v) Tween 20. Probe Histone Acetylation Levels in Situ. To probe histone acetylation level in individual cells, we transiently transfected HEK293T cells using the plasmid DNA encoding the in situ sensor. Cells were seeded onto μslide 8-well coverslips (Ibidi, WI, US) or μslide 8-well grid-500 (Ibidi, WI, US) for live cell imaging. Transfection was carried out using Lipofectamine 3000 (Life Technologies, MD, US), following the manufacturer’s protocol. Images of transfected cells were collected using a Nikon A1 confocal microscope. All images were analyzed using ImageJ to reveal the fluorescence intensity of cell body and nucleus individually. Briefly, the area and mean gray value of the pixels in the nucleus and total cell body were obtained using the Analyze function. This information was used to calculate the fluorescence intensity of total cell and nucleus. To adjust for cell-to-cell variations in expression level, we calculated the corrected nuclear fluorescence (CNF) intensity as a ratio of nuclear and cytoplasmic GFP intensity. The value of CNF is expected to be proportional to the amount of in situ sensors binding specifically to acetylated H3K14 with a fluorescence intensity well above the background (noise). To validate the specificity of our in situ sensors, we compared the fluorescent images of cells transfected with our sensors to that obtained by immunostaining (detailed in Supporting Methods). Immunostained coverslips were then imaged using a fluorescence microscope with a 488 and 544 nm laser line for probe and antibody excitation, respectively. FITC and TRITC emission filters were applied to collect the probe and antibody signals, respectively. Collected images were then subject to a colocalization analysis using the JACOP plugin in ImageJ.45 No fluorescence images can be obtained from the control well. Statistical Analysis. The in vitro results were reported as mean ± standard deviation (S.D.) with at least three independent repeats. The in situ results were reported as mean ± standard error (S.E.) with >30 independent repeats. S.E. was selected because of the large sample size. Statistical difference was anlyzed using an ANOVA, followed by the Duncan’s multiple-range test. Differences between groups were considered significant when p < 0.05 and highly significant when p < 0.01 on OriginPro (v 2015, OriginLab Corp, Northhampton, MA). Correaltion analysis was performed using Statgraphics Centurion XVI (v 16.2.04, Statpoint Technologies Inc., Warrantown, VA).

extracts were then mixed with sensors and examined using FCS. Sensor diffusivity was determined by fitting the correlation curve as shown in Figure S4 (Supporting Information). Results are summarized in Figure 2A. Specifically, at a sensor concentration of 50 nM, we found that the measured sensor diffusivity decreases with increasing H3K14ac concentration. To rule out the possibility that the observed diffusivity change may arise from viscosity changes in nuclear extracts, we performed control experiments by mixing nuclear extracts with Rhodamine 110 dye molecules. Our results (see Figure S5 in Supporting Information) show that the diffusivity of the dye was not affected by the concentration of H3K14ac. The observed changes in diffusivity are thus likely to originate from engineered sensors specifically binding to H3K14ac targets. A statistical correlation analysis was performed between measured diffusivity and H3K14ac concentrations. The obtained Pearson’s correlation coefficient was −0.82, −0.85, and −0.78 for the monomeric, dimeric, and tetrameric construct, respectively. These results suggest a negative correlation between the measured diffusivity and the H3K14ac concentration. Among three sensors, the diffusivity of dimeric sensor has the strongest correlation with [H3K14ac]. To compare the performance of various sensor designs, we estimated the percentage of sensors that are bound to acetylated histones of nuclear extracts (Bound %) following eq 3. Bound% =

Df − Dm Df − Dc

(3)

where Df, Dc, and Dm stand for the diffusivity of free sensor, sensor−histone complex, and experimental mixture, respectively. Df was determined to be 114.1 ± 3.2, 88.9 ± 2.3, and 75.8 ± 0.9 μm2 s−1, and Dc was determined to be 63.4 ± 1.2, 40.9 ± 2.3, and 25.6 ± 2.6 μm2 s−1 for the monomeric, dimeric, and tetrameric sensors, respectively. Compared with monomeric and tetrameric sensors, the dimeric one exhibited significantly larger Bound %, suggesting higher affinity as shown in Figure 2B. Surprisingly, the tetrameric PB1(2) did not exhibit higher Bound % when compared to the dimeric one. A similar trend was observed in our previous statistical correlation analysis, where dimeric sensors exhibit the strongest correlation with H3K14ac concentrations. This observation can be potentially attributed to the large size of the tetrameric sensors which can cause steric hindrance for binding. Additionally, since we performed diffusion-based measurements, the relative size increase of large sensors when binding to the target is smaller compared to that of small-sized sensors, which also make a large number of tandem repeats less desirable for probing H3K14ac levels using FCS. We thus chose to proceed with the dimeric sensor design to perform assays using cell extracts. Bound % as defined was used as our sensing signal in the application. Although we expect our sensors to exhibit high selectivity toward H3K14ac as we demonstrated in our previous publication using histone peptides,29 a binding assay using Bio-Layer Interferometry (BLI) was performed to further verify its binding selectivity (detailed in Supporting Methods). Wildtype and H3K9ac peptides were used along with H3K14ac peptides (with sequence detailed in Table S2 in Supporting Information) in the binding assay, since they can potentially be recognized by the selected “reader” domain.28,47 As shown in Figure S6A (Supporting Information), the dimeric protein

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RESULTS AND DISCUSSION Characterization of the Performance of Protein Sensors Using Nuclear Extracts. Engineered protein sensors containing tandem repeats of PB1(2) domains were successfully cloned and expressed using bacterial culture. We compared the secondary folding of sensors containing varying numbers of PB1(2) domains to evaluate whether neighboring domains may affect the folding of each other. The collective CD spectra of all three sensors are shown in Figure S3 (Supporting Information) suggest that all sensors assume similar folding. The percentage of helicity of the monomeric, dimeric, and tetrameric sensor was found to be 61.9%, 61.2%, and 60.0%, respectively, in close agreement with the theoretical helicity value of 62% (estimated using the software DichroCalc46 based on PB1(2) crystal structure (PDB: 3LJW)27). To determine the activity of sensors, we prepared nuclear extracts from cultured HEK293T cells. SDS-PAGE and Western blot were used to examine the quality of nuclear extracts as shown in Figure S2 (Supporting Information). H3K14ac levels were determined using an ELISA kit prior to performing any assays using our engineered sensors. Nuclear D


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ACS Sensors sensor (2 μM) only exhibits a significant binding (association) and unbinding (dissociation) curve when mixed with H3K14ac peptides (0.5 μM). When mixed with wild-type and H3K9ac peptides of the same concentration, no significant binding was observed. Similar trends were observed under other selected peptide (0.1 and 1.0 μM) and sensor concentrations (1, 3, and 6 μM). The Kd value (dimeric sensor to H3K9ac peptides) was determined to be 0.14 ± 0.02 μM by varying the concentration of H3K14ac peptides as shown in Figure S6B (Supporting Information), being 12-fold lower than that reported for the monomeric form of the probe (Kd ≈ 1.9 ± 0.5 μM).28,30 We thus explored the possibility of utilizing the engineered dimeric sensors to directly probe histone acetylation levels in nuclear extracts via measurements of Bound %. To do so, we prepared nuclear extracts containing various concentrations of H3K14ac ranging from 0.02 to 100 nM. Bound % values measured under varying sensor and H3K14ac concentrations are summarized in Figure 2C. Based on these graphs, we determined the linear detection range (LDR) of our sensor using the linear region of the curve, where the measured Bound % changes with H3K14ac concentration in a close-to linear manner (with R2 > 0.9). The LDR was found to be 0.5−10 nM, 0.5−20 nM, and 1.0−50 nM of H3K14ac for probing using 50, 75, and 100 nM sensors, respectively. The upper detection limit (i.e., the highest concentration detectable within LDR) was significantly increased upon increasing sensor concentrations, while the lower detection limit also increased slightly. We can therefore vary the protein sensor concentration to probe H3K14ac in a broader concentration range. Probe H3K14 Acetylation Levels in Situ. To probe H3K14ac levels in situ, we transiently transfected the plasmid encoding for protein sensor into HEK293T. We also prepared a negative control using the same expression vector encoding the same nuclear localization signal fused to mEGFP without the “reader” domain. As shown in Figures 3A and S7 (Supporting Information), the negative control and protein sensors can be successfully transfected, expressed in situ and localized to the nucleus. Upon transfection, the negative control showed an almost even illumination between the cell body and the nucleus. The protein sensors, however, exhibit distinctive fluorescent patterns inside the cell nucleus. The observed pattern is fairly diffusive with no punctuated spots. Round areas deprived of fluorescent protein probes were also observed. These areas vary in size and are likely to originate from nucleoli (free of protein) and heterochromatin foci (lacking histone acetylation). Interestingly, in some cells, a ring-like structure was observed surrounding the void area corresponding to nucleoli. This feature is the most distinct in cells transfected with monomeric sensors, followed by dimeric and tetrameric ones. Among all sensors, the tetrameric one has a relatively high fluorescent background level, which can potentially be attributed to the relatively large size of this protein sensor as compared with the other two. It is possible that once expressed, this sensor does not manage to be transported to cell nuclei efficiently although all sensors share the same nuclear localization signaling peptide. Although dimeric sensors seem to exhibit the desirable traits in our assays using cell extracts, a side-by-side comparison of immunostained and probe transfected cells is needed to interpret the binding pattern and validate the binding specificity of sensors in situ. Transfected cells were stained with H3K14ac antibody. Figure 3B shows the colocalization of the sensors with the antibody. Analysis of the extent of colocalization was

Figure 3. (A) PB1(2)-GFP monomer, dimer, and tetramer constructs transfected into HEK293T cells and imaged 24 h post transfection. Successfully transfected cells (n > 30) were imaged and analyzed from three independent transfections. (B) Mono-, di-, and tetrameric sensors colocalized with H3K14ac antibodies and an Alexa 564 secondary. The Pearson’s correlation coefficient, r, was highest for the dimeric construct (r = 0.95) indicating positive correlation. The score was lower for the monomeric and tetrameric constructs (r = 0.5 and 0.7, respectively) indicating only partial colocalization. A total of n = 30 cells were imaged from independent transfections.

performed using ImageJ via a Colocalization plugin.48 A Pearson’s correlation coefficient r was computed for each construct. An r-value close to 1 indicates complete positive correlation, suggesting that two patterns are essentially identical to each other. Our analysis suggests that the dimeric sensor has the highest r value (r = 0.95, n = 30) among all the constructs, indicating that it colocalizes almost perfectly with the antibody. The monomeric and tetrameric sensors had lower correlation scores of 0.5 and 0.7, respectively. We thus proceeded with the dimeric sensor for probing the H3K14ac level in live cells. Figure 4A shows a typical image of cells expressing the dimeric sensor counterstained with DAPI. DAPI preferentially binds to a DNA-dense area, and is thus typically used to identify heterochromatin regions.49,50 A few, but not all, areas void of transfected sensors match exactly with DAPI dense regions, indicated by solid arrows in Figure 4A. Interestingly, some areas that are poorly stained with DAPI also exhibit high GFP intensity, exemplified by a dashed arrow in Figure 4A. A pixel intensity profile analysis was performed and the results E


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Figure 5. HEK293T cell density over time (○, untransfected cells; Δ, transfected cells). The arrow indicates the time when cells were transfected. Viability of transfected cells (■) was not significantly affected (p > 0.05) during our observation window.

compared with that of untransfected ones (Figure 5, and Figure S10 in Supporting Information). We determined the doubling time of cells by fitting the cell density course over time using an exponential growth model. The doubling time was found to be 14.7 ± 0.2 and 15.6 ± 0.2 h for untransfected and transfected cells, respectively. Combining all effects, we consider that our protein sensor has minimal toxicity for cell growth and thus is feasible for monitoring live cell behavior. Live-Cell Imaging of Transfected Cells. We followed single cells for ∼60 h after transfection. During this time window, we expect cells to have gone through multiple division cycles. To follow the same adherent cells, we used a gridded slide and imaged the same area at successive time points as shown in Figure 6A using a low magnification (10×). In order to track specific cells, the selected areas were then further examined using a high magnification objective (60×) as shown in Figure 6B. We followed two cells as indicated in panel B of Figure 6; the two cells (marked 1 and 2) undergo division between 30 and 40 h. The resulting daughter cells are smaller initially and express the acetylation probe with varying intensity levels. The same cell seems to exhibit a different probe distribution pattern at varying time points, suggesting that H3K14ac distribution changes during a cell cycle, which is consistent with existing literature.54,55 Quantification of H3K14ac Level in Live Cells. HEK293T cells were treated with a well-known HDAC inhibitor, i.e., sodium butyrate (NaB). Images of transfected HEK293T cells at varying concentrations of NaB are shown in Figure S11 (Supporting Information). Similar fluorescent patterns were observed in all transfected cells independent of treatment. To characterize the fluorescent intensity in cell nucleus that corresponds to H3K14ac levels, we used corrected nuclear fluorescence (CNF) intensity. CNF essentially corrects fluorescence intensity of nucleus by (1) subtracting background fluorescence of freely diffusing GFP in the cytoplasm as a measure of unbound protein; and (2) accounting for variations in expression levels by normalizing to the diffusing background of each cell individually. The value of CNF is expected to be proportional to the amount of sensors binding to their specific chromatin targets (H3K14ac) which give rise to fluorescent intensity above background originated from unbound (freediffusing) sensors. A similar approach has been used in the literature to characterize the nuclear expression levels of epigenetic probes.18 We analyzed ∼30 cells under each

Figure 4. (A) Cells expressing the dimeric probe counterstained with DAPI. The solid arrows indicate two regions that are void of our sensor, but exhibit intense DAPI staining. The dashed arrow indicates GFP dense regions that lack the DAPI stain. (B) Normalized pixel profile of a line drawn across the areas of interest. The analysis was performed using ImageJ’s Plot Profile tool. Solid arrows indicate DAPI peaks colocalized with GFP valleys, while dashed arrows suggest the opposite. A colocalization analysis of the cells shows weak correlation between the pattern of our probe and DAPI (r = 0.38 for 30 cells).

was presented in Figure 4B. A weak anticorrelation was observed between the GFP and DAPI pattern, where some GFP peaks correlate with DAPI valleys and vice versa. This weak correlation is expected since H3K14ac is highly enriched in euchromatin regions and are required for gene activation.51 Euchromatin regions are thus expected to exhibit high GFP but low DAPI intensity. Similarly, heterochromatin regions are expected to show high DAPI but low GFP intensity. It is noteworthy that some DAPI rich regions are not devoid of our sensors, suggesting the existence of H3K14ac in these heterochromatin areas as well. Although the distribution of H3K14ac has not been fully mapped in human cells, previous study has found that H3K14ac located in actively transcribed, bivalent, as well as selected inactive promoters.52 Our observation is thus in line with our expectation and previous observations. Effects of Transfected Protein Sensors on Cytotoxicity. To test the feasibility of our sensor in probing acetylation level in live cells, we examined the effect of transfected sensors on cell viability following a standard protocol using trypan blue.53 Since the dimeric sensor was encoded by plasmid DNA and introduced to cells via a transient transfection, it will remain exogenically. We thus expect minimum cytotoxicity. After transfection with sensors, cell morphology remains unchanged as shown in Figure S8 (Supporting Information). Transfected cells remain viable, on average 96% of the control within our observation time window (72 h), and maintain a normal growth pattern (Figure 5). The initial fluorescence signal was observed 12 h after transfection, with a transfection efficiency (calculated as the % of green cells) of ∼60 ± 5%. After 24 h of transfection, the efficiency remained fairly constant (∼72%) and persisted during our experiment window (72 h; see also Figure S9 in Supporting Information). The proliferation rate of transfected cells was slightly lowered F


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Figure 6. (A) Selection of a defined area using cells transfected with the dimeric PB1(2) probe over successive time points. A gridded slide was used to monitor the same area and the number 2 indicates the number of the well that was used for imaging. The area was imaged using a 10× objective to provide a view of the entire box. T indicates the time in hours after transfection and the scale bars = 100 μM. In (B), the channel for probe-mEGFP detection is shown and the area of the box was zoomed in at 60×, to show finer details of the probe in two cells. At 24 h, two cells in this area were transfected with the probe (marked 1 and 2). Between 30 and 40 h, the cells undergo division with the daughter cells (1A, 1B, 2A, and 2B) also expressing the probe. Scale bars = 10 μM. Figure 7. (A) CNF values of cells transfected with the dimeric protein sensor and treated with NaB of varying concentrations. Data is showed as Mean ± S.E, n = 30 cells. Sensor-transfected cells exhibit a significantly higher CNF value compared to the negative control (#: p < 0.01). NaB significantly (*: p < 0.05) increased H3K14ac level compared to untreated cells. (B) Comparison of relative acetylation level (defined as the ratio of measured H3K14ac concentrations between treated and untreated cells) measured via different approaches under varying NaB concentrations. *: p < 0.05 denotes statistical difference with regard to untreated samples.

treatment condition, and the results are summarized in Figure 7A. A significant difference (p < 0.01) was observed between cells transfected with the protein probes and the negative control lacking the “reader” domain. The values of CNF found for NaB treated cells were significantly (p < 0.05) higher than that of untreated cells. Compared to untreated cells, the CNF values of cells treated with NaB of 3 and 5 mM increased by 19 ± 5% and 29 ± 6%, respectively. No significant difference, however, was observed between the two treatments. Additionally, we analyzed the correlation between CNF vales and NaB concentrations. A positive correlation was found with a Pearson’s correlation coefficient of 0.98. For comparison, a similar analysis was performed using cells transfected with monomeric sensors (Figure S12 in Supporting Information). No significant difference was observed between untreated and treated cells. Our finding indicates that the dimeric sensor can uniquely capture changes in acetylation levels within the nucleus, making it a powerful tool for the analysis of H3K14ac levels in live cells. Additionally, we analyzed the H3K14ac content of nuclear extracts from NaB treated and untreated cells via FCS and enzyme-linked immunosorbent assay (ELISA) as summarized in Figure 7B. The relative acetylation level, calculated as the ratio of H3K14ac concentrations in NaB-treated and untreated cells, was found to be 1.38 ± 0.10 and 1.37 ± 0.20 for cells treated with NaB of 3 and 5 mM, respectively, by FCS analysis. Similar numbers were found using immunoassays. When combined, three analytical approaches consistently suggest that our selected NaB treatment significantly increased the acetylation level of cells compared to the untreated group. No significant difference, however, was observed among the

treatments. The observed changes in acetylation level are also consistent with previous literature reports.52,56 Similarly, and to further challenge our protein sensor, we assessed the effect of Trichostatin A (TSA), which is also known as a potent HDAC inhibitor,39 on the acetylation level of H3K14. HEK293T cells were exposed to concentrations of 0.5 μM and 1.0 μM of TSA for 24 h. Similarly, we observed a positive correlation between CNF values and TSA concentration with a Pearson’s correlation score of 0.96. The obtained CNF values showed an increment of 40 ± 6% and 53 ± 8% in the acetylation level of H3K14 relative to the untreated cells under 0.5 μM and 1.0 μM of TSA, respectively. We corroborated our in situ observations by FCS and immunoassay using nuclear extracts harvested under the aforementioned conditions. Figure 8 compared the H3K14ac levels estimated using immuno-, FCS-, and imaging-based assays. A similar trend was observed. At TSA of 0.5 μM, all assays suggest ∼27− 39% in acetylation levels. At a higher TSA concentration (1 μM), a broad variation range was observed suggesting ∼37− 67% increase in acetylation levels. G


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in vitro and in situ applications. It has a linear detection range of 0.5−50 nM when probing changes using nuclear extracts. The low detection limit is much improved compared with our previous work (∼30 nM29), and slightly better than a typical ELISA based assay (0.04 ng μL−1 or ∼3 nM). In addition, our probe has a linear range that is broader compared to that of ELISA. The production cost of the sensor, however, is about one-third that of an antibody. The sensor was successfully transfected into live cells and exhibits a binding pattern almost identical to that of a commercial antibody. The corrected nuclear fluorescence intensity can be utilized to quantify changes in H3K14ac levels in live cells. Cell morphology, viability, and proliferation remain minimally impacted by sensors expressed in situ. To the best of our knowledge, this is the first live cell sensor based on engineered epigenetic “reader” domains that directly probes host cell H3K14ac levels with a spatial resolution comparable to that of a commercial antibody. Our novel sensor thus opens up many possibilities of exploring histone epigenetic changes in live cells.

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ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssensors.7b00026. Amino acid sequence of protein sensors and synthetic peptides, digested plasmids of the protein sensor, Western blot for histone acetylation in nuclear cell extracts (NCE), FCS autocorrelation curves and diffusivity change induced by H3K14ac, BLI measurements, HEK293T cells transfected with the protein probes, time course of transfection efficiency using the dimeric protein sensor, dimeric protein sensor toxicity and effect on HEK293T, CNF values of the monomeric protein sensor, effect of TSA on HEK293T growth, and costaining of transfected HEK293T cells with H3K14acantibody (PDF)

Figure 8. Effects of TSA on H3K14ac levels of HEK293T cells. (A) CNF values for cells treated with TSA of varying concentrations. Data = Mean ± S.E., n = 30 cells. TSA significantly increased H3K14ac level compared to untreated samples. #: p < 0.01 denotes statistical difference from the negative control; *: p < 0.05 denotes statistical difference from untreated samples. (B) Comparison of relative acetylation level (defined as the ratio value between treated and untreated cells) of cells treated using varying TSA concentrations. *: p < 0.05 denotes statistical difference with regard to untreated samples.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel.: +1 7654945824. Fax: +1 7654940805.

Finally, the ability of the protein sensor to capture changes in acetylation level was compared to an antibody (see Figures S13 and S14 in Supporting Information). It is worth mentioning that our sensor is live-cell compatible, while the use of an antibody is limited to fixed cells. Although similar trends in CNF values were observed under NaB or TSA treatments, the measured CNF values have much larger variations (ranging from 0.12 to 0.31 compared to 0.03 to 0.09) as compared to our protein sensor. This variation arises from cell-to-cell differences and can be potentially attributed to multiple steps involved in obtaining immuno-stained images, e.g., the fixation and permeabilization process can affect cell staining.57

ORCID

Chongli Yuan: 0000-0003-3765-0931 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by US Army Medical Research (Award Number: W81XWH-14-1-0012), National Science Foundation (Award Number: CBET-1512285), Indiana Clinical and Translational Science Institute and School of Chemical Engineering, Purdue University. O.F.S. acknowledges funding from Administrative Department of Science, Technology and Innovation (COLCIENCIAS) from Colombia and Fulbright (Grant 529). We thank Prof. Julie Liu for access to confocal microscopy. O.S. and A.M. would like to thank Dr. James A. Schaber from the Bindley Bioscience Imaging Facility for helping with cell imaging. Drew Williamson assisted in performing some of the described experimental work.

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CONCLUSIONS In this study, we demonstrated the capability of our engineered epigenetic sensors in probing histone post-translational modifications using both cell extracts and in situ. The sensor is designed based on a known epigenetic reader domain. Engineered sensors containing multiple “reader” domains demonstrate the improved ability to recognize H3K14ac. Among them, the dimeric sensor was found most suitable for H


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