Cell imaging signal enhancer and application thereof

Abstract

The invention provides a cell imaging signal enhancer which is prepared by optimizing a fluorescent environment stabilizing component, a refractive index micro-adjusting agent, a free radical quenching inhibitor, an optical homogeneity regulating agent, a background noise inhibiting component and other components and proportions. The novel cell imaging signal enhancer can be used for enhancing the stability of a local hydration structure and a refractive index, reducing the fluctuation of a micro-area light field and a concave liquid surface effect, improving the uniformity of a full view field and effectively inhibiting photobleaching and background noise, so that a novel cell imaging signal enhancer is obtained, and high-sensitivity and high-quality imaging of a cell sample is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of cell biology, in particular to a cell imaging signal enhancer and its application. BACKGROUND

[0002] Cell imaging technology is an important tool in modern life sciences and medical diagnosis, widely used in cell morphology observation, protein localization, gene expression analysis and drug screening. However, in the imaging process, often face the problem of weak signal, high background noise, low signal-to-noise ratio, especially for low abundance target or using weak fluorescent labeled sample. This leads to poor imaging quality, limited detection sensitivity, and difficulty in obtaining accurate quantitative or qualitative information.

[0003] Currently, the methods to improve the imaging signal mainly include: 1) increasing the dye / probe concentration; 2) extending the exposure time; 3) using high-power light source. However, increasing the dye / probe concentration may lead to an increase in non-specific staining background, and even toxicity to cells; extending the exposure time is easy to cause fluorescence quenching, and may amplify the background noise; using high-power light source may accelerate the photobleaching of fluorescent molecules, and cause phototoxicity damage to living cells. At the same time, although the existing cell imaging signal enhancers have certain signal enhancement effect, they generally have limited enhancement multiple, poor stability, weak universality (only effective for specific dyes) or greater impact on cell activity.

[0004] Therefore, there is an urgent need for a cell imaging signal enhancer that can significantly improve the signal-to-noise ratio of cell imaging, has strong universality, good stability and low cytotoxicity, in order to realize high sensitivity and high quality imaging of cell samples. SUMMARY

[0005] In order to solve the problems existing in the prior art, the present application provides a cell imaging signal enhancer and its application.

[0006] The first aspect of the present application provides a cell imaging signal enhancer, which comprises:

[0007] 0.05%-1.5% of a fluorescent environmental stabilizing component;

[0008] 1%-15% of a refractive index fine-tuning agent;

[0009] 0.01%-0.5% of a free radical quenching inhibitor;

[0010] 10mM-200mM of a buffer;

[0011] The fluorescent environmental stabilizing component comprises tetrahydropyrimidine and / or its derivative; the refractive index fine-tuning agent comprises glycerol carbonate.

[0012] Preferably, the radical quenching inhibitor is sodium ascorbate-2-phosphate.

[0013] Preferably, the cell imaging signal enhancer further comprises 0.1%-2% of an optical uniformity regulator, which is trimethylamine oxide and / or poloxamer 188.

[0014] Preferably, the cell imaging signal enhancer further comprises 5-100 ppm of a background noise suppression component, which is near-infrared fluorescent dye IRDye QC-1.

[0015] Preferably, the buffer is PIPES buffer or MOPS buffer. More preferably, the pH value of the buffer is 6.8-7.2.

[0016] The second aspect of the present application provides a method for enhancing the imaging signal of a cell imaging signal enhancer, comprising:

[0017] The cell imaging signal enhancer as described in the first aspect of the present application is added to cells, and mixed to obtain a cell solution with enhanced imaging signal.

[0018] The third aspect of the present application provides a method for evaluating the imaging signal enhancement effect of a cell imaging signal enhancer, comprising:

[0019] A cell solution is prepared by the method for enhancing the imaging signal of a cell imaging signal enhancer as described in the second aspect of the present application, and detected, and the imaging signal enhancement effect is evaluated according to the detection results.

[0020] Preferably, the detection comprises one or more of average fluorescence intensity detection, fluorescence signal retention rate detection, fluorescence uniformity detection, background signal relative reduction rate detection, background contrast detection, cell edge gradient value detection, and dead and live cell separation degree detection.

[0021] The fourth aspect of the present application provides a cell imaging signal enhancement kit, comprising the cell imaging signal enhancer as described in the first aspect of the present application and the method for enhancing the imaging signal as described in the second aspect of the present application.

[0022] The fifth aspect of the present application provides the use of the cell imaging signal enhancer as described in the first aspect of the present application, the method for enhancing the imaging signal as described in the second aspect of the present application, or the cell imaging signal enhancement kit as described in the fifth aspect of the present application in cell imaging signal processing.

[0023] Compared with the prior art, the present application has the following advantages:

[0024] The fluorescent environment stabilizing component tetrahydropyrimidine and / or its derivative constructs a low polarization microstructure environment, improves the quantum yield of the dye, and delays photobleaching. The phosphate bond of the free radical quenching inhibitor sodium ascorbate-2-phosphate can release ascorbic acid, which can persistently remove singlet oxygen and hydroxyl radicals, further inhibit the photobleaching of the fluorescent dye, avoid fluorescence quenching caused by transient high concentration of antioxidants, and simultaneously have pH stability and formulation compatibility. The refractive index fine-tuning agent glycerol carbonate can provide a refractive index matching close to but more stable than water, reduce light scattering and focal plane shift, and further improve imaging clarity. The optical uniformity control agent trimethylamine oxide and / or poloxamer 188 can further enhance the local hydration structure and refractive index stability, reduce micro-area light field fluctuations and meniscus effects, and improve the uniformity of the full field of view. The background noise suppression component near-infrared fluorescent dye IRDye QC-1 can suppress stray background light and autofluorescence through wide-spectrum near-infrared absorption, improve the signal-to-noise ratio (SNR), and not introduce its own fluorescence. By optimizing the above components and proportions, the present application obtains a cell imaging signal enhancer that can significantly improve the signal-to-noise ratio of cell imaging, has strong universality, good stability, and low cytotoxicity, thereby realizing high-sensitivity and high-quality imaging of cell samples. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 The GFP-CHO cell fluorescence imaging graph after treatment with the cell imaging signal enhancer provided in the embodiment of the present application; wherein Figure 1 A is the GFP fluorescence imaging graph of the cell after treatment with Example 3, and the image shows that the brightness is improved, the edge is clearer, and the cytoplasm is uniform; Figure 1 B is the GFP fluorescence imaging graph of the cell after treatment with Comparative Example 1, and the image shows that the brightness is low, and there are local hot spots and unevenness;

[0026] Figure 2 The AO / PI double-stained cell imaging graph after treatment with the cell imaging signal enhancer provided in the embodiment of the present application; wherein Figure 2 A is the AO / PI double-stained cell imaging graph after treatment with Example 9, and the image shows that the signal is brighter, the background is lower, and the cell outline is clear; Figure 2 B is the AO / PI double-stained cell imaging graph after treatment with Comparative Example 1, and the image shows that the fluorescent signal is weak and the background is high. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0028] A cell imaging signal enhancer, comprising:

[0029] 0.05%-1.5% of a fluorescent environmental stabilizing component;

[0030] 1%-15% of a refractive index fine-tuning agent;

[0031] 0.01%-0.5% of a free radical quenching inhibitor;

[0032] 10mM-200mM of a buffer;

[0033] wherein the fluorescent environmental stabilizing component comprises tetrahydropyrimidine and / or its derivative; and the refractive index fine-tuning agent comprises glycerol carbonate.

[0034] In some embodiments, the free radical quenching inhibitor is sodium ascorbate-2-phosphate.

[0035] In some embodiments, the cell imaging signal enhancer further comprises 0.1%-2% of an optical uniformity regulating agent, which is trimethylamine oxide and / or poloxamer 188.

[0036] In some embodiments, the cell imaging signal enhancer further comprises 5-100ppm of a background noise inhibiting component, which is near-infrared fluorescent dye IRDye QC-1.

[0037] In some embodiments, the buffer is PIPES buffer or MOPS buffer. Preferably, the buffer has a pH value of 6.8-7.2.

[0038] Embodiments

[0039]

[0040] In addition, it should be noted that the fluorescent environmental stabilizing component in the above embodiments selects tetrahydropyrimidine as an example, and those skilled in the art know that the replacement or superposition of tetrahydropyrimidine-related derivatives (such as hydroxytetrahydropyrimidine) can also be used as the fluorescent environmental stabilizing component in the present application. Similarly, the buffer in the above embodiments selects MOPS buffer as an example, and those skilled in the art know that the replacement or superposition of functionally similar PIPES buffer can also be used as the buffer in the present application.

[0041] Application Embodiment 1: Preparation of a cell imaging signal enhancer

[0042] Preparation method:

[0043] The cell imaging signal enhancers in the above embodiments 1-4 are prepared according to the following steps:

[0044] (1) Take an appropriate amount of MOPS buffer into a clean glass beaker;

[0045] (2) Add tetrahydroimidazole, glycerol carbonate, and sodium ascorbate-2-phosphate in sequence, and stir at 300 rpm until completely dissolved;

[0046] (3) Make up to the required volume with MOPS buffer;

[0047] (4) Filter sterilize with a 0.22 µm PES membrane, and store in a brown bottle in the dark;

[0048] (5) Store at 4°C, and can be stably stored for more than 6 months.

[0049] Application Example 2: Verification of fluorescence signal enhancement effect

[0050] 1. Purpose of the experiment

[0051] To verify whether the signal enhancer of the application can improve the brightness and clarity of cell fluorescence imaging.

[0052] 2. Experimental materials and equipment

[0053] Cells: GFP-expressing CHO-K1 stable strain;

[0054] Reagents: cell imaging signal enhancer (Examples 1-4) and PBS (Comparative Example 1);

[0055] Fluorescence photographic equipment: cell imaging system;

[0056] Consumables: 96-well transparent bottom black wall plate.

[0057] 3. Experimental method

[0058] 3.1 Seed GFP-CHO cells in a 96-well plate (1×10 4 cells / well) and culture for 24 h.

[0059] 3.2 Discard the culture medium and wash once with PBS.

[0060] 3.3 Seed GFP-CHO-K1 cells in a 96-well plate (1×10 4 cells / well) and culture for 24 h.

[0061] 3.4 Discard the culture medium and wash once with PBS.

[0062] 3.5 Add the cell imaging signal enhancers provided in Examples 1-4 (100 µL / well) respectively, and set Comparative Example 1 as the control group (100 µL / well).

[0063] 3.6 Stand for 5 min (enhancer and dye microenvironment fully act).

[0064] 3.7 Fluorescence imaging in the cell imaging system, the parameters remain the same:

[0065] Excitation: 470 ± 20 nm;

[0066] Emission: 525 ± 20 nm;

[0067] Exposure time: 800-1000 ms.

[0068] 3.8 Collect single-well 5 field images, calculate the average fluorescence intensity (gray value). The average fluorescence intensity (a.u.) is obtained by the pixel gray value of the fluorescence image collected by the cell imaging system, wherein 5 random fields are taken per well, the average gray value of the whole field is calculated, and the average value of the five fields is taken as the fluorescence intensity of the well. The average fluorescence intensity of the first exposure of Comparative Example 1 is taken as the benchmark, and the different treatment groups are compared by normalization.

[0069] 4. Experimental results

[0070]

[0071] 5. Result analysis

[0072] From the experimental results, the average fluorescence intensity of Examples 1-4 all showed a significant increase, which was significantly higher than that of Comparative Example 1.

[0073] Within a certain range, the enhancement of imaging signal intensity and the synergistic effect of "tetrahydro pyrimidine + glycerol carbonate + sodium ascorbate-2-phosphate" in the cell imaging signal enhancer showed a positive correlation trend (see Examples 1, 2, 3). Among them, the cell imaging signal intensity of Example 3 increased by 92%; at the same time, the fluorescence imaging diagram as shown in Figure 1 shows that after Example 3 treatment, its brightness is improved, the edge is clearer, and the cytoplasm is uniform (see Figure 1 A), and its imaging signal intensity is significantly better than that of Comparative Example 1 (see Figure 1 B).

[0074] Statistical analysis (one-way ANOVA) showed that Examples 2-4 were significantly different from Comparative Example 1 (p<0.01), and Example 1 also had a significant difference (p<0.05).

[0075] Application of Example 3: verification of photobleaching inhibition effect

[0076] 1. Experimental purpose

[0077] To verify the steady-state maintaining ability of the cell imaging signal enhancer of the present application under continuous exposure conditions, and to evaluate its anti-photobleaching effect.

[0078] 2. Experimental materials and equipment

[0079] Cells: GFP-expressing CHO-K1 stable strain

[0080] Reagents: cell imaging signal enhancer (formulation of the present application) and PBS (control group)

[0081] Fluorescence photographic equipment: cell imaging system

[0082] Consumables: 96-well transparent bottom black wall plate

[0083] 3. Experimental method

[0084] 3.1 Seed GFP-CHO-K1 cells in a 96-well plate (1x10 4 cells / well) and culture for 24 h.

[0085] 3.2 Discard the culture medium and wash once with PBS.

[0086] 3.3 Add the cell imaging signal enhancers provided in Examples 1-4 of the present application (100 μL / well), respectively, and set Comparative Example 1 as the control group (100 μL / well).

[0087] 3.4 Stand for 5 min to establish a stable dye microenvironment.

[0088] 3.5 Photobleaching experiment parameter settings

[0089] In the same cell imaging system, perform continuous fluorescence acquisition:

[0090] Excitation: 470±20 nm;

[0091] Emission: 525±20 nm;

[0092] Exposure time: 1000 ms;

[0093] Continuous shooting: 30 times;

[0094] No interval, no delay between each exposure, and all parameters remain completely consistent.

[0095] 3.6 Calculation method of fluorescence retention rate

[0096] Image acquisition method:

[0097] Select a fixed field of view (do not move the stage) per well, record 30 consecutive frames of fluorescence images, and record as: I 1, I2, I 3,…, I 30 ;

[0098] wherein:

[0099] • I 1: the average fluorescence intensity of the first exposure;

[0100] • I 30 : the average fluorescence intensity of the 30th exposure;

[0101] Method for calculating the average fluorescence intensity:

[0102] The "average fluorescence gray value of the whole field of view" of each frame of image was calculated by using the analysis tool of the cell imaging system or ImageJ software, which was defined as:

[0103]

[0104] wherein:

[0105] • p i = the gray value of the i-th pixel (0-255 or 0-4095);

[0106] • N = the total number of pixels of the image;

[0107] • I n = the average fluorescence intensity of the nth exposure;

[0108] Definition of the fluorescence retention rate:

[0109] The fluorescence retention rate was used to measure the proportion of effective fluorescence remaining after continuous exposure:

[0110]

[0111] • The higher the value, the slower the bleaching and the better the light stability;

[0112] • The average fluorescence intensity of the first exposure of Comparative Example 1 was used as the benchmark to facilitate the calculation of the relative difference.

[0113] 3.7 Experimental results

[0114]

[0115] 3.8 Analysis of results

[0116] From the experimental results, the fluorescence intensity of Comparative Example 1 was only maintained at 63% after 30 continuous exposures, and the photobleaching phenomenon was obvious. The fluorescence signal retention rates of Examples 1-4 were significantly better than that of Comparative Example 1.

[0117] Within a certain range, the fluorescence signal retention rate is positively correlated with the synergistic effect of "tetrahydropyrimidine + glycerol carbonate + sodium ascorbate-2-phosphate" in the cell imaging signal enhancer (see Examples 1, 2, and 3); among them, the fluorescence signal retention rate of Example 3 is the highest, reaching 93%.

[0118] The above results show that the cell imaging signal enhancer provided by the application can effectively inhibit photobleaching, and the microenvironment stabilizing factors (such as fluorescent environment stabilizing components, free radical quenching inhibitors, and components for improving dye energy recovery efficiency) in the system can effectively reduce the energy dissipation and free radical-induced decay of AO / fluorescent signal during continuous exposure, thereby significantly inhibiting the photobleaching process.

[0119] Application Example 4: Refractive Index Microenvironment Regulation and Optical Uniformity Verification

[0120] 1. Experimental purpose

[0121] To further enhance the local hydration structure and refractive index stability, reduce the micro-region light field fluctuation and meniscus effect, and improve the full field uniformity, trimethylamine oxide and poloxamer 188 are added as optical uniformity regulators on the basis of Example 3, and the specific components are as follows:

[0122]

[0123] The experiment verifies the regulation effect of the cell imaging signal enhancer provided by the application on the refractive index microenvironment and optical uniformity of the fluorescent liquid surface under cell-free conditions, and evaluates whether it can reduce the imaging dark angle and edge brightness attenuation caused by the meniscus.

[0124] 2. Experimental materials and methods

[0125] 2.1 Construction of fluorescent uniform system

[0126] Fluorescein solution (10 μM) was added to the 96-well black wall transparent bottom plate as an ideal uniform distribution standard fluorescent system, which was used to evaluate the optical uniformity without being affected by cell morphology or distribution.

[0127] 2.2 Treatment groups

[0128] n = 6 wells per group;

[0129] Enhancer group: 100 μL of the cell imaging signal enhancer provided by Examples 3, 5, 6, and 7 was added to each well, respectively;

[0130] Control group: 100 μL of the PBS buffer provided by Comparative Example 1 was added to each well;

[0131] Let stand for 3 min to allow the refractive index modulator to fully act in the liquid surface microstructure.

[0132] 2.3 Optical uniformity acquisition method

[0133] Whole-well montage scanning using cell imaging system:

[0134] Scan mode: 9x9 field montage (cover the whole well bottom area);

[0135] Excitation light: 470 ± 20 nm;

[0136] Emission light: 525 ± 20 nm;

[0137] Exposure time: fixed at 600 ms;

[0138] Auto montage correction off (avoid system algorithm automatically eliminate dark corners);

[0139] Output the whole-well montage image after scanning is completed.

[0140] 2.4 Fluorescence uniformity calculation method

[0141] The whole-well fluorescence intensity is calculated using cell imaging analysis software or ImageJ.

[0142] (1) Obtain the gray value distribution of all pixels in the whole well

[0143] Import the montage image and count:

[0144] Average brightness:

[0145]

[0146] Gray standard deviation:

[0147]

[0148] Where:

[0149] p i : Fluorescence intensity of each pixel (a.u.)

[0150] N : Total number of pixels

[0151] (2) Calculate the coefficient of variation (CV%) of the whole-well fluorescence uniformity

[0152] Explanation:

[0153] The lower the CV%, the more uniform the light field and the smaller the liquid surface refractive difference, which can reflect whether the brightening or uniform light mechanism is effective.

[0154] 3. Experimental results

[0155]

[0156] 4. Results analysis

[0157] The whole hole fluorescence uniformity coefficient of variation CV% of Comparative Example 1 was 14.20%, which was significantly higher than that of Examples 3, 5, 6 and 7, indicating that the whole hole fluorescence distribution was not uniform.

[0158] The whole hole fluorescence uniformity coefficient of variation CV% of Example 3 (tetrahydropyrimidine + glycerol carbonate system) was 8.10%, indicating that the optical uniformity was significantly improved, and the local hydration structure and refractive index regulation were initially effective.

[0159] The whole hole fluorescence uniformity coefficient of variation CV% of Example 5 was 6.50%, indicating that trimethylamine oxide as a moderate strength hydration layer regulator could reduce the refractive index fluctuation of the liquid surface micro area.

[0160] The whole hole fluorescence uniformity coefficient of variation CV% of Example 6 was 7.20%, suggesting that poloxamer 188 could improve the interfacial tension and meniscus structure, but the refractive index regulation effect was slightly weaker than that of trimethylamine oxide when acting alone.

[0161] The whole hole fluorescence uniformity coefficient of variation CV% of Example 7 was 5.80%, indicating that trimethylamine oxide and poloxamer 188 had obvious synergistic effect in refractive index microenvironment regulation and liquid surface flattening, which could maximize the reduction of optical field inhomogeneity and edge brightness decay.

[0162] In summary, the cell imaging signal enhancer provided by the present application can significantly reduce the optical uniformity from 14.20% of Comparative Example 1 to 5.80-8.10%, and the uniformity is increased by 43%-59%, which verifies that the refractive index regulation strategy has good effect on solving the meniscus effect and optical field instability.

[0163] Application Example 5: Background noise suppression performance verification

[0164] 1. Experimental purpose

[0165] In order to suppress background scattering signals and autofluorescence, and thus improve the background purity and the imaging contrast of target structure, near-infrared fluorescent dye IRDye QC-1 was added as a background noise suppression component on the basis of Example 5, and the specific components were as follows:

[0166]

[0167] The experiment verifies whether the cell imaging signal enhancer provided by the application can effectively reduce the background scattering signal and spontaneous fluorescence of the imaging system in the visible light channel (470 / 525 nm) through its wide spectrum absorption characteristics, thereby improving the background purity and imaging contrast of the target structure.

[0168] 2. Experimental method

[0169] 2.1 Take the cell-free blank well (only containing the conventional culture medium) as the detection system.

[0170] 2.2 Divide into two groups for processing:

[0171] Enhancer group: add the cell imaging signal enhancer provided by examples 5, 8, 9, and 10 (100 μL) to each well, respectively;

[0172] Control group: add the PBS buffer provided by comparative example 1 (100 μL) to each well;

[0173] 2.3 Collect the background under the imaging system 470 nm excitation / 525 nm emission channel, and set the exposure time to 1200 ms.

[0174] 2.4 Background signal analysis method

[0175] After image acquisition, import the two groups of images into the imaging analysis software, and calculate the average gray value (Mean intensity) of each field of view.

[0176] 2.5 Region selection

[0177] In the cell-free blank well, the entire field of view is automatically selected as the analysis region (ROI) to avoid bias caused by manual selection.

[0178] 2.6 Gray value statistics

[0179] The software automatically calculates the average gray value Mean of all pixels in the region and records the standard deviation SD.

[0180] In order to improve the statistical stability, 9 fields of view are taken from each well, and the average value and standard deviation within the group are calculated.

[0181] 2.7 Relative reduction ratio calculation

[0182] The background noise suppression effect is calculated by the difference between the average gray values of the control group (PBS) and the enhancer group, using the following formula:

[0183]

[0184] Wherein:

[0185] Average gray value of background of control group

[0186] Average gray value of background of QC-1 enhancer group

[0187] 2.8 Analyze the average gray value of the background signal of the two groups and calculate the relative reduction ratio.

[0188] 3. Experimental results

[0189]

[0190] 4. Result analysis

[0191] Compared with Comparative Example 1, the average gray value of the background of Example 5, 8, 9 and 10 is significantly reduced, which shows that the background brightness is reduced and the baseline noise is reduced. Among them:

[0192] Example 5 (without QC-1, only trimethylamine oxide) can reduce the background noise by 22%, which shows that Example 5 itself has a certain inhibitory effect on scattered light;

[0193] Example 8 (5 ppm QC-1) reduces by 34%, which shows that the wide-spectrum absorption of low-dose QC-1 has significantly absorbed the background stray light;

[0194] Example 9 (20 ppm QC-1) reduces by 40%, reaching the best inhibition level;

[0195] Example 10 (100 ppm QC-1) reduces by 39%, which is comparable to Example 9, and its ability to absorb stray light and suppress autofluorescence does not increase with the concentration of the background noise suppression component near-infrared fluorescent dye IRDye QC-1.

[0196] The overall results show that the enhancer of the present application can significantly remove non-specific light signals through the wideband absorption characteristics of the near-infrared absorbing dye QC-1, achieving a background noise suppression of 22%-40%, and providing higher background purity and more accurate quantitative basis for cell imaging.

[0197] Application Example 6: Comprehensive improvement verification of actual cell imaging effect

[0198] 1. Experimental purpose

[0199] Verify the comprehensive improvement effect of the signal enhancer of the present application on image brightness, contrast, edge definition and the ability to separate dead and live cells in actual cell fluorescence imaging tasks.

[0200] 2. Experimental materials and equipment

[0201] Cells: Hela cells;

[0202] Dye system: AO (live cells, Ex 470 / Em 525 nm) + PI (dead cells, Ex 535 / Em 620 nm) double staining;

[0203] Reagents:

[0204] Enhancer group: cell imaging signal enhancer (Example 3, Example 5, Example 9);

[0205] Control group: PBS buffer (Comparative Example 1);

[0206] Equipment: cell imaging system (containing multi-channel fluorescence module);

[0207] Consumables: 96-well transparent bottom black wall imaging plate.

[0208] 3. Experimental method

[0209] 3.1 Cell preparation

[0210] Hela cells were inoculated in 96-well plates (about 1 x 10 4 cells / well) and cultured for 24 h to adhere and stabilize.

[0211] 3.2 Double staining operation

[0212] Remove the culture medium and wash once with PBS. Add AO (5 μg / mL) + PI (5 μg / mL) mixed staining solution and incubate at room temperature for 5 min.

[0213] 3.3 Add enhancer / control reagent

[0214] Enhancer group: after discarding the staining solution, add 100 μL of cell imaging signal enhancer (Example 3, Example 5, Example 9) respectively;

[0215] Control group: after discarding the staining solution, add 100 μL of PBS buffer of Comparative Example 1.

[0216] 3.4 Image acquisition

[0217] Use the cell imaging system to acquire images in the green channel (AO) and the red channel (PI) respectively.

[0218] All parameters remain the same:

[0219] Exposure time: AO 900 ms; PI 1200 ms

[0220] Gain: fixed at 1.0

[0221] Take 5 random fields of view per well

[0222] 3.5 Image quantitative analysis

[0223] For AO and PI channels respectively:

[0224] 3.5.1 Mean intensity analysis:

[0225] 1) Select an area containing a large number of cells in each field image using a fixed size ROI (e.g. 200x200 pixels).

[0226] 2) Export the pixel gray matrix of the ROI.

[0227] 3) Calculate the mean gray value formula:

[0228]

[0229] Where:

[0230] I i : Gray value of the ith pixel

[0231] N : Total number of pixels in the ROI

[0232] 4) Calculate the average value of 5 fields for each well to obtain the final representative value.

[0233] 3.5.2 Signal-to-Background Ratio (SBR) analysis:

[0234] 1) Select a cell-free area in the image as the background ROI (100x100 pixels).

[0235] 2) Record the average gray value of the background:

[0236]

[0237] 3) Select a cell area (Cell ROI) and calculate the average gray value of the cell signal:

[0238]

[0239] 4) Calculate the contrast between the cell and the background:

[0240]

[0241] 5) Take the average value of 5 fields for each well.

[0242] 6) Explanation: The higher the SBR, the cleaner the background and the more prominent the cells; this index can quantify the "background depression ability" of the enhancer.

[0243] 3.5.3 Cell Edge Sharpness analysis method:

[0244] 1) Select a cell edge crossing line (about 50-80 pixel long) in each cell image, measure the intensity profile along the line using image software (ImageJ).

[0245] 2) Extract the intensity change curve, calculate the maximum gradient:

[0246]

[0247] Where:

[0248] I I is the intensity value

[0249] x is the pixel position

[0250] 3) Randomly measure 5-10 cell edges in each field, take the average value as the Edge Sharpness value of the field.

[0251] 4) The average value of each field is the final data.

[0252] 5) Description: The larger the Edge Gradient, the sharper the cell outline, and the improvement of the refractive index and light field uniformity by the enhancer can be directly reflected in this index.

[0253] 3.5.4 Dead and live cell separation degree analysis (AO / PI signal ratio distinguishability) analysis:

[0254] 1) Collect AO and PI channel intensity values

[0255] For each cell:

[0256] AO channel average intensity I AO

[0257] PI channel average intensity I PI

[0258] Use the automatic segmentation tool (Otsu) to identify the single cell outline.

[0259] 2) Calculate the cell PI / AO ratio

[0260] For each cell:

[0261]

[0262] Live cells: R is low

[0263] Dead cells: strong PI, R significantly increased

[0264] 3) Quantify "separability"

[0265] Using Inter-class Distance (ICD):

[0266]

[0267] Where:

[0268] Mean of R value

[0269] Standard deviation

[0270] The larger the ICD, the more obvious the separation between dead and live cells, and the more accurate the detection of dead and live cells.

[0271] 5) Data processing and statistics

[0272] Each well contains 5 fields of view, each field of view contains 20-50 cells, a total of 100-250 cells as statistical samples, all data are expressed as "mean ± standard deviation", and Student's t-test is used to analyze whether the difference between the enhancer group and the PBS group is significant (p<0.05).

[0273] 4. Experimental results

[0274] 4.1 Fluorescence brightness improvement

[0275]

[0276] 4.2 Image contrast improvement

[0277] The background of the enhancer group is significantly lower, and the cell / background ratio is improved:

[0278]

[0279] 4.3 Edge sharpness improvement

[0280] By calculating the edge gradient (unit: gray level change / pixel):

[0281]

[0282] 4.4 Dead and live cell separation ability

[0283]

[0284] 5. Experimental results

[0285] 1) Significant improvement in fluorescence brightness

[0286] The cell imaging signal enhancer provided in Examples 3, 5 and 9 shows obvious brightness enhancement in both AO and PI channels, and the enhancement effect of Example 9 is the highest (AO ↑ 48%, PI ↑ 36%). It is illustrated that the enhancer of the present application can effectively release the fluorescence quantum yield of the dye by improving the light field uniformity and reducing the local light quenching effect of the dye.

[0287] 2) The overall contrast of the image is enhanced, and the background is significantly reduced

[0288] The cell / background contrast (SBR) of the cell imaging signal enhancer provided in Examples 3, 5 and 9 is obviously improved, and the SBR of Example 9 is the highest (AO ↑ 52%, PI ↑ 44%), which indicates that the cell imaging signal enhancer provided in the present application can effectively suppress the background noise and make the cell signal more prominent. The cleaner background also makes the automatic segmentation and threshold selection more stable.

[0289] 3) The edge sharpness is obviously improved, and the cell contour is more sharp

[0290] The edge gradient of the cell imaging signal enhancer provided in Examples 3, 5 and 9 is improved by 27-41%, which indicates that the gray scale change of the cell edge is more steep, and the image sharpness is higher. This is related to the improvement of the refractive index matching and the reduction of light scattering by the enhancer, so that the refraction transition of light at the cell edge is clearer.

[0291] 4) The separation of dead and live cells is clearer, and the detection accuracy is improved

[0292] The inter-class distance (ICD) of the cell imaging signal enhancer provided in Examples 3, 5 and 9 is improved by 26-39%, which indicates that the signal ratio distribution of AO (live) and PI (dead) cells is better separated, and the enhancer can significantly improve the classification accuracy in actual dead and live cell detection and reduce the misjudgment of "weak positive" cells with blurred boundaries.

[0293] 5) The AO / PI double-stained cell imaging image is as shown in Figure 2 The fluorescence signal is weak, the background is high, and the fluorescence and background are not obviously distinguished (see Figure 2 B); and after being treated by Example 9, the signal is brighter, the background is lower, and the cell contour is clear (see Figure 2 A).

[0294] In summary, the enhancer of the present application can simultaneously improve the brightness, background purity, structural clarity and dead and live separation in actual cell imaging tasks, and realize the comprehensive enhancement of image quality.

[0295] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A cell imaging signal enhancer, characterized in that, include: 0.05%-1.5% of fluorescence-stabilizing components; 1%-15% refractive index fine-tuning agent; 0.01%-0.5% free radical quenching inhibitors; 10mM-200mM buffer solution; The fluorescent environment stabilizing component includes tetrahydropyrimidine and / or its derivatives; the refractive index fine-tuning agent includes glycerol carbonate.

2. The cell imaging signal enhancer as described in claim 1, characterized in that, The free radical quenching inhibitor is sodium ascorbate-2-phosphate.

3. The cell imaging signal enhancer as described in claim 1, characterized in that, The cell imaging signal enhancer also includes 0.1%-2% of an optical homogenizer, wherein the optical homogenizer is trimethylamine oxide and / or poloxamer 188.

4. The cell imaging signal enhancer as described in claim 1, characterized in that, The cell imaging signal enhancer also includes a background noise suppression component of 5-100 ppm, which is a near-infrared fluorescent dye IRDye QC-1.

5. The cell imaging signal enhancer as described in claim 1, characterized in that, The buffer solution is either PIPES buffer or MOPS buffer.

6. A method for enhancing imaging signals using a cell imaging signal enhancer, characterized in that, include: Add the cell imaging signal enhancer as described in any one of claims 1-5 to the cells, mix well, and you will get a cell solution with enhanced imaging signal.

7. A method for evaluating the imaging signal enhancement effect of a cell imaging signal enhancer, characterized in that, include: The cell imaging signal enhancement method described in claim 6 is used to prepare a cell solution, detect it, and evaluate the cell imaging signal enhancement effect based on the detection results.

8. The method for evaluating imaging signal enhancement effect as described in claim 7, characterized in that, The detection includes one or more of the following: average fluorescence intensity detection, fluorescence signal retention rate detection, fluorescence uniformity detection, background signal relative reduction rate detection, background contrast detection, cell edge gradient value detection, and dead / live cell separation degree detection.

9. A cell imaging signal enhancement kit, characterized in that, It includes the cell imaging signal enhancer as described in claim 1 and the imaging signal enhancement method as described in claim 6.

10. The application of the cell imaging signal enhancer of claim 1, the imaging signal enhancement method of claim 6, or the cell imaging signal enhancement kit of claim 9 in cell imaging signal processing.

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