Introduction

Fluorescent imaging and sensing with high spatio-temporal resolution and sensitivity allow the direct visualization of dynamic biological interests at different levels of components from the molecules, cells in vitro to the tissues, organs in vivoFull size table

To further elucidate the influence of diethylamino substitution on the photophysical properties of BTCs, we performed TDDFT calculations at the B3LYP/6–311 G(d,p) level. As shown in Fig. 2, both nitrogen atoms of BTC982 and BTC1070 contribute to the HOMO orbitals, increasing their energy levels. The difference is that in BTC1070, the distribution of HOMO on the diethylamino group is significantly delocalized onto the p-methoxy phenyl group of LUMO upon photoexcitation. This suggests that an ICT state is formed, resulting in a significant decrease of the LUMO level. Furthermore, the S0–S1 excitation energies from HOMOs to LUMOs verify the absorption wavelength change trend of BTCs, and the corresponding oscillator strengths correlate well with their high absorption coefficients. Surprisingly, the π-electron contribution of two nitrogen atoms in BTC982 do not obviously lower the S0–S1 excitation energy or bathochromically shift the wavelength. A plausible reason could be the non-coplanar geometry of BTC982 with a higher torsional angle of 29.35° compared with that of BTC980 (15.48°) and BTC1070 (18.59°) (Supplementary Figure 7).

Fig. 2
figure 2

Theoretical calculations for investigation of photophysical properties. Comparison of the HOMO and LUMO energy levels, S0–S1 excitation energies, and oscillator strengths for BTC980, BTC982, and BTC1070, based on TDDFT calculations at the B3LYP/6–311 G(d,p) level

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Optical penetration study of NIR-II BTCs in tissue phantom

Encouraged by the above results, we then assayed the penetration properties of these BTCs in mimic biological tissue (1% Intralipid33) to probe the benefits of anti-quenching effect by using a home-built InGaAs setup (Fig. 3a). Taking BTC1070 with the longest wavelength as an example, capillary filled with BTC1070 micelle solution immersed into Intralipid was excited at 1064 nm and the emission was collected beyond 1200 nm at varying depths. The imaging performance was further compared with that of IR26, and benchmarked against the NIR-I (850–950 nm) and NIR-II (> 1000 nm) phantom imaging of ICG excited at 808 nm. With increase of penetration depth, attenuation of image intensities and blurring of capillary profiles are observed for all fluorophores, but only images of BTC1070 resolve sharp edges of the capillary at a depth up to 8 mm (Fig. 3b). We define the penetration depth as the maximum imaging depth beyond which the signal-to-background ratio (SBR) of image drops below a threshold value of 2, where capillary profiles also cannot be resolved. As a result, BTC1070 has a penetration depth of 8 mm, which is fourfold deeper than IR26 (2 mm), and 8- and 2.7-fold deeper than ICG imaged in NIR-I (1 mm) and NIR-II (3 mm) range, respectively (Fig. 3c). In addition, cross-sectional profiles of capillary show clear feature integrity for BTC1070 compared with IR26 and ICG (Fig. 3d, Supplementary Figure 8), which can be attributed to the higher brightness and reduced scattering events at longer emission wavelength of BTC1070.

Fig. 3
figure 3

Deep penetration of bright and long-wavelength BTC1070 in mimic tissue. a A home-built NIR fluorescence imaging setup for tissue phantom study. b Fluorescence images of capillaries filled with BTC1070, IR26, and ICG in PBS (pH 7.4), respectively, immersed in 1% Intralipid with varying depth. BTC1070 and IR26 imaging signals were collected in 1200–1700 nm region under 1064 nm excitation. ICG imaging signals were collected both in NIR-I (850–950 nm) and NIR-II (1000–1700 nm) region under 808 nm excitation. Color bar ranges from 0 to 20,000 for BTC1070 and ICG, 0–5,000 for IR26. The detailed imaging parameters for each image are listed in Supplementary Table 1. c Measured signal-to-background ratio (SBR, defined in Supplementary Figure 8) of capillary images as a function of depth. By selecting a threshold SBR (SBR = 2, red dotted line) to define the level at which structure are minimally resolvable, the maximum penetration depth range for all fluorophores are showed as origin boxes in b. The bars represent mean ± s.d. derived from n = 3 line profiles measured at different positions in the capillary images. d Wavelength-dependent full-width at half-maximum (FWHM) of cross-sectional profiles in capillary images as a function of depth. The bars represent mean ± s.d. derived from the uncertainty in the Gaussian fitting of feature width. Source data are provided as a Source Data file

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The longer excitation wavelength (1064 nm) of BTC1070 also improves the penetration depth, image SBR and feature contrast by decreasing signal attenuation in Intralipid. Fitting exponential function to the intensity decay curves give a much lower attenuation coefficient (τ) for BTC1070 (0.6662) compared with ICG (808 nm excitation) both in NIR-I (0.9264) and NIR-II (0.9002) range, consistent with the deep penetration of 1064 nm (Supplementary Figure 9). According to the Lambert–Beer law, signal attenuation depends exponentially on the depth (optical length) of an emitting structure and the attenuation coefficient of the medium to photon. This signal attenuation coefficient is contributed equally by the attenuation of excitation and emission photons traveled through turbid media, which is a direct result of photon scattering and absorption (Supplementary Note 1). Therefore, to eliminate the influence of different emission wavelength, phantom imaging of BTC1070 under 915 nm excitation was performed and parallelly compared with that under 1064 nm excitation at the same filter sets (Supplementary Figure 10, 11). The results also show that 1064 nm excitation gives a lower signal attenuation coefficient (0.6662 for 1064 nm excitation vs 0.7946 for 915 nm excitation) and deeper penetration depth (8 mm for 1064 nm vs 7 mm for 915 nm) (Supplementary Table 4), consistent with the light attenuation property in Intralipid (Supplementary Figure 12). In additionally, despite imaging at the same emission wavelength, the reduced signal attenuation under 1064 nm excitation gives improved image SBR and feature contrast (Supplementary Table 5). Overall, the results demonstrate the significance of developing long-wavelength absorbing fluorophores for high-contrast deep-penetration imaging.

In vivo lymphatic imaging and photobleaching study

To further investigate the advantages of these anti-quenching BTCs for NIR-II biomedical imaging, we compared the lymphatic imaging quality in nude mice by using BTC1070, IR26, and ICG as contrast agents (Fig. 4, Supplementary Figure 14–17). Fluorescence images were acquired 1 h after intradermal injection of contrast agents at rear paw of nude mice (Fig. 4a). Because of the severe fluorescence quenching, IR26 shows weak signal in lymphatic drainage, indicating its limitation for biological application (Fig. 4c). In contrast to the blurry lymphatic structure imaged with ICG in the short-wavelength region (850–950 nm) (Fig. 4d), much sharper images with distinguished lymph nodes as well as the afferent and efferent lymph vessels are acquired in the NIR-II range of both ICG (Fig. 4e) and BTC1070 (Fig. 4f, Supplementary Figure 17). However, crowded collateral lymph vessels are only observed by detecting longer wavelength photons of BTC1070 excited at 1064 nm (Fig. 4g). A cross-sectional intensity profile shows a minimum feature size (full-width at half-maximum) of 84μm and maximum SBR of 9.42 (Fig. 4h). The results clearly demonstrate anti-quenching BTC1070 outperforms IR26 and ICG in lymphatic imaging.

Fig. 4
figure 4

Superior lymphatic imaging with BTC1070 to ICG and IR26. a Digital photograph of a nude mouse fixed on imaging plate, showing the injection site (yellow arrow) of contrast agents and the lymphatic drainage imaging window (dash square). b Schematic illustration of the anatomical structure of lymphatic system in the hindlimb of nude mice, green arrow represents the lymphatic drainage from the paw to the sciatic lymph node. c–g Fluorescence images of lymphatic drainage using IR26 c, ICG d, e, and BTC1070 f, g as contrast agents in the hindlimb of nude mice on an InGaAs camera. Scale bar, 2.5 mm. IR26 and BTC1070 imaging signals were collected at wavelength of 1200–1700 nm under 1064 nm excitation. ICG was excited at 808 nm, and images were collected in the NIR-I (850–950 nm) and NIR-II (1000–1700 nm) region, respectively. g High-magnification (× 3) image of the ankle (red square in f), showing at least five collateral lymph vessels were resolved. h Cross-sectional fluorescence intensity profiles (black solid) and Gaussian fit (red dotted) along the yellow bar in g. i–l In vivo photobleaching studies of ICG and BTC1070. i, k Fluorescence images of lymphatic drainage at different time points post-injection using ICG i/BTC1070 k. 808 ( + )/1064 ( + ) represents that the 808/1064 nm laser irradiation was conducted according to the set on the time line (purple segments on orange lines, each segment in i represents 3 min) with the same fluence rate ( ~ 150 mW cm−2), whereas 808 (−)/1064 (−) represents no laser irradiation was conducted. Scale bar, 5 mm. j, l Fluorescence intensity signals of popliteal lymph nodes (green arrows/red arrows in i, k) versus time. Blue rectangles represent time windows of laser irradiation. Color bar ranges from 1000 to 30,000 for d–f,i, and k, 500–5000 for c, 2000–20,000 for g. The detailed imaging parameters for each image are listed in Supplementary Table 1. The bars represent mean ± s.d. derived from n = 3 biologically independent mice. Source data are provided as a Source Data file

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Next, a time window with stable NIR-II signal during lymphatic drainage imaging was used to verify the superior photostability of BTC1070 in vivo via continuous laser irradiation. As a contrast, ICG is absolutely photobleached after 6 min of 808 nm laser irradiation (Fig. 4i, j). The signals of lymph nodes recover after 15 min, confirming it is indeed caused by photobleaching instead of the damage of lymphatic vessels. However, for BTC1070, after 60 min of 1064 nm laser irradiation with the same fluence rate, the lymph nodes and vessels could still be clearly distinguished (Fig. 4k), and the signal of popliteal lymph nodes is bleached only by ~ 30% (Fig. 4l). The results demonstrate the superior photostability of BTC1070, which will be beneficial for long-time observation such as imaging-guided surgical operation.

pH-responsive properties of NIR-II BTCs

The superior NIR-II bioimaging performance as well as the interesting photophysical properties of diethylamino-substituted BTCs inspired us to explore the possibility to develop fluorescent probes by studying their pH-responsive properties. Owing to the anti-quenching properties, these fluorophores are able to exhibit spectra responses to pH in aqueous solution (Fig. 5, Supplementary Figure 18, 19). For example, BTC1070 exhibits decrease of the absorbance band at 1015 nm with the appearance of a new broad band ~ 600–900 nm when downregulating the pH from 5 to 2 (Fig. 5b). And an intense peak at 950 nm is observed when pH further decreased to 0. The pKa values are calculated to be 0.29 and 3.81, clearly demonstrating the double protonation feature (Fig. 5c). In addition, ratiometric fluorescence response with large peak shift from 1065 to 980 nm when pH changed from 5 to 0 is observed under 808 nm excitation, accompanying with obvious intensity changes (Fig. 5d). Plot of integrated intensity ratio from two wavelength regions (1000–1300 nm and 900–1300 nm) at pH 0-7 is well fitted by a sigmoidal equation (r2 = 0.99), suggesting an optimal pH-sensitive range is 1–4 (Fig. 5e).

Fig. 5
figure 5

Protonation of BTC1070 and the corresponding spectra changes. a Protonation mechanism of BTC1070 derived from the 1H-NMR titration in Supplementary Figure 22, showing stepwise protonation on nitrogen atoms. b Absorption spectra of 10 μm BTC1070 loaded into phospholipid nanomicelle in PBS at various pH values. Detailed data in a wider pH range of 0–9 are shown in Supplementary Figure 19. c Plot of absorbance at 950 nm versus pH values in the range of 0–7. The pKa values are calculated to be 0.29 and 3.81, respectively, based on Boltzmann curve fitting in origin software. d The corresponding fluorescence spectra excited at 808 nm at various pH values. e Plot of fluorescence ratio changes as a function of pH values. Ratio = F1000LP/F900LP, F1000LP and F900LP denote the integrated intensity at wavelength of 1000–1300 nm and 900–1300 nm, respectively

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We further performed 1H-NMR titration with deuterated TFA to study the protonation mechanism (Supplementary Figure 22). The downfield shifts of resonances of methylene protons on diethylamino groups reveal the stepwise protonation process on nitrogen atoms (Fig. 5a). Therefore, the complex absorption changes can be elucidated by the symmetry breaking and recovery, and the inhibition of ICT effect during the protonation process29,34. Specifically, the first protonation on one side strongly polarizes the polymethine chain, forming an unsymmetrical cyanine structure (BTC1070H+) featuring hypsochromic and broaden absorption. Then the second protonation on another side regenerates a new symmetrical cyanine structure (BTC1070H22+), resulting in intense absorption again. Owing to the inhibition of ICT effect, BTC1070H22+ exhibits blue-shifted absorption and fluorescence as well as significant enhanced fluorescence intensity.

Ratiometric fluorescence imaging of pH in tissue phantom

As a proof of concept, we further performed ratiometric fluorescence imaging of pH in vivo by using BTC1070 as a probe. Given that wavelength-dependent light attenuation in vivo will compromise the accuracy and reliability, we investigated the influence of tissue thickness on the performance of pH ratiometric sensing via phantom imaging. As shown in Fig. 6a, blurry capillary edges and significantly reduced fluorescent signals are observed from red channel (900–1700 nm) and cyan channel (1000–1700 nm) with increase of penetration depth, which can be attributed to the light attenuation and scattering. By contrast, ratiometric imaging clearly recognizes the capillaries against the background with consistent pseudo-colors for all pH groups (Fig. 6b). Furthermore, the ratios derived from different depths have the coefficient of variation lower than 4.12% for all pH groups, indicating high reliability of the ratiometric signals with respect to penetration depth (Supplementary Table 6). By analyzing the signal attenuation coefficients of red channel (τ1) and cyan channel (τ2), little difference (Δτ) between them are observed for all pH groups (Fig. 6c), which indicates that the attenuation of fluorescence signals at these two channels are synchronous. Through a mathematic model shown in Supplementary Note 2, we confirm that a small Δτ (|Δτ| < 0.03) is vital for the high reliability of the ratiometric signals (Supplementary Figure 23, Supplementary Table 6). Thus, even taking consideration of the absorption and scattering of tissue, ratiometric signals in different depths as a function of pH could be well calibrated by sigmoidal equations (r2 > 0.98, Fig. 6d, Supplementary Note 3), in accordance with the fluorescence spectra results.

Fig. 6
figure 6

Ratiometric fluorescence imaging of pH with BTC1070 in mimic tissue. Fluorescence images a and corresponding ratiometric fluorescence images b of capillary tubes filled with BTC1070 micelle solution of different pH with varying depth from 0 to 4 mm. Excitation wavelength: 808 nm. Emitted signals were collected through passing 900LP (F900LP, red channel) and 1000LP (F1000LP, cyan channel) filters, respectively. F1000LP/F900LP denotes the ratio signals. The detailed imaging parameters for each image are listed in Supplementary Table 1. Scale bar, 2.5 mm. c Measured intensity of capillaries as a function of depth (0–4 mm) in 1% Intralipid, corresponding to the fluorescence images of each pH value. τ1 and τ2 denote the signal attenuation coefficients of red and cyan channels, respectively, derived from the single-exponential fitting curves. The little differences between τ1 and τ2 (Δτ = τ1–τ2) are responsible for the reliable ratio signals with increased depth (Supplementary Note 2, Supplementary Figure 23). d Plots of measured ratio changes as a function of pH with varying depth. Curve fitting (r2 > 0.98) is based on Boltzmann function in origin software (Supplementary Equation 2), generating the calibration functions at different depths (Supplementary Note 3). Data point with its error bar stands for mean ± s.d. derived from n = 3 replicated measurements of every pixel in the capillaries. Source data are provided as a Source Data file

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In vivo ratiometric fluorescence imaging of gastric pH

Based on the calibration results, we further tested the ability of BTC1070 for ratiometric imaging of gastric pH in vivo, as the gastric pH has a crucial role in maintaining the stomach’s digestive function, preventing infection and affecting the availability of oral drugs35. Mice were administrated simulated gastric fluid with different pH (pH 1.3 and pH 2.5) to mimic the pH environment of human stomach. Following gavage of BTC1070 micelle solution, the mice were anaesthetized and further imaged on an InGaAs camera under 808-nm excitation. As shown in Fig. 7a, noninvasive ratiometric imaging not only recognizes stomach profile from the left lateral aspect of the abdomen, at a tissue depth of ~ 2–4 mm (Supplementary Figure 24), but also differentiates the two pH environments with sharp pseudo-color contrast. Similar results also emerge in invasive ratiometric imaging of gastric fluid wrapped in a thin gastric wall ( ~ 1 mm depth, Fig. 7b) and imaging of exposed gastric fluid (0 mm depth, Fig. 7c). Furthermore, tissue thickness has negligible influence on the ratio values of each group (Supplementary Figure 25, 26). We then converted the ratios to pH values by means of the calibration curves (Supplementary Note 3). The results show good agreement with that measured by standard pH meter, and the differences between them (ΔpHs) are determined to be lower than 0.18 and 0.22 pH units for low (pH = 2.10 ± 0.11) and high pH groups (pH = 3.08 ± 0.27), respectively (Fig. 7d, Supplementary Table 7). By the same method, gastric pH in normal mice (pH = 3.95 ± 0.18) can also be clearly visualized and accurately measured (ΔpHs ≤ 0.27, Supplementary Figure 27, 28). These results strongly suggest that BTC1070 is capable of noninvasively detecting gastric pH in a wide pH range by high-contrast deep-tissue ratiometric imaging.

Fig. 7
figure 7

In vivo ratiometric fluorescence imaging of gastric pH. a–c Left: digital photographs of mice and dissected stomach denote three imaging modes. a noninvasive imaging at ~ 2–4 mm tissue depth; b invasive imaging of gastric fluid covered by ~ 1 mm thickness of gastric wall; c imaging of exposed gastric fluid. The measurement of tissue depth/thickness is shown in Supplementary Figure 24. Black dash square represents imaging window in mice. Right: fluorescence images and corresponding ratiometric fluorescence images of mice stomach at two different pH environments (red channel: 900–1700 nm; cyan channel: 1000–1700 nm; ratio channel: F1000LP/F900LP). Color bar ranges from 5000 to 30000 for the red/cyan channel in a and b, 0–30000 for the red/cyan channel in c. The detailed imaging parameters for each image are listed in Supplementary Table 1. Scale bar, 5 mm. d, Comparison of pH values in mice stomach measured by ratiometric fluorescence imaging and standard pH meter. The true gastric pH determined by pH meter is higher than that of simulated gastric fluid due to the buffering effect (see Methods). Ratios derived from the ratio images are converted to pH values by means of the calibration functions at corresponding depth (Supplementary Note 3). ΔpH = average pH resolved from ratiometric imaging−average pH measured by standard pH meter. Detailed pH data are summarized in Supplementary Table 7. Data point with its error bar stands for mean ± s.d. derived from n = 3 biologically independent mice. Source data are provided as a Source Data file

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