Our solution to the current barriers to live-cell phononic imaging comprises a series of experimental design choices to minimise exposure of the sample to injurious photon or thermal doses. It uses a novel illumination geometry, novel transducer design, and thermally-conductive substrate to shield and manage the light and thermal exposures. A simplified schematic of our system is presented in Fig. 2. The optical pump (390 nm, ~0.5 mW) and optical probe (~780 nm, 1 mW) beams approach the sample through the substrate, which is selected for minimal optical exposure and optimal thermal dissipation. An opto-acoustic transducer fabricated on top of the substrate consists of an optical cavity composed of three layers. The cavity is precisely designed to strongly absorb the pump light (for phonon generation) while allowing high transmission of the probe beam (for phonon detection). The design parameters of this novel transducer are tuned to produce mechanical as well as optical resonances in the desired performance bands. This configuration thus offers several key advantages over other phonon detection methods: significantly reduced exposure of the sample to both pump and probe beams, increase in signal amplitude through mechanical resonance within the transducer and enhanced thermal management by the use of a high-thermal-conductivity substrate (sapphire). These advantages manifest as greatly improved signal-to-noise ratio (SNR) and minimised thermal disruption to the sample. Increased SNR may be traded for acquisition speed allowing, in our pump-probe ASOPS configuration, acquisition of approximately 5000 traces per second which are averaged to obtain SNR of ~40–70, depending on input power, substrate material and transducer characteristics24,33. This SNR is sufficient to to image the sample at each point in the x,y dimensions and from the acquired traces, axial information is extracted.

Figure 2 Experimental schematic. (a) Experimental setup. Two pulsed lasers in ASOPS pump-probe configuration are combined by an objective lens (0.55 NA) and focused into the transducer substrate interface where the probe beam is captured by a second objective (0.42 NA) and detected in a photodiode. The system is built around a microscope to enable complementary optical imaging. A fluorescence detection arrangement allows the state of a cell to be assessed. (b) Transducer and sample arrangement. The pump beam is absorbed while the probe beam is transmitted by the transducer (with dimensions Au = 20 nm, ITO = 140 nm and Au = 20 nm) to allow detection while protecting the cell from optical exposure. The substrate is sapphire to prevent temperature rise. Full size image

Sectioning and resolution

Resolving the Brillouin frequency in time gives the possibility of sectioning the optical volume with acoustic resolution. Each cycle of the detected signal corresponds spatially to one acoustic wavelength which is typically shorter than the optical wavelength. By calculating the Brillouin frequency for a small number of cycles, the optical volume can be sectioned. From a theoretical point of view, at least one cycle is necessary to measure the frequency of a sinusoidal function. However in practice this is difficult to achieve. In this section, the axial resolution achievable by processing the Brillouin signals with the short time Fourier transforms (STFT)34,35 method is analysed based on modelling and single edge experimental targets.

Based on a theoretical thermo-elastic model36 (see supplementary information), the generation, propagation of sound and its interaction with light (at λ probe ) was simulated for one dimensional space (z). The simulation considered one or two objects immersed in a medium (see Fig. 3(a)) where the width (O w ) and separation of the objects (O gap ) was varied to observe the optical response. The time of flight of the signals can be converted to axial position z. The resultant temporal variation of the simulated light intensity was then post-processed for sectioning. Based on the STFT method, f B was calculated against time (see Fig. 3(b)). In this method, each window lasted for a few cycles of the Brillouin signal and each cycle of the signal spatially corresponds to an acoustic wavelength λ a = λ probe /2n. The width of each section in spatial units is given by S w = λ a N λ where N λ is the processing window width and is selected to match an integer number of cycles greater or equal than one (see Fig. 3(b)).

Figure 3 Simulated measurements and axial response upon stimulation. (a) Schematic of the simulated geometry. (b) Simulation of an edge response to represent sectioning. (c) Simulated response from a single object with various sizes for N λ = 2. (d) Simulated response by two near objects at various edge to edge distances using N λ = 2. Resolution in both cases is half of the measuring window S w /2. Full size image

Figure 3 shows a simulation of optical sectioning using phonons. Figure 3(a) shows the geometry of the model. The pump wavelength (λ pump = 390 nm) is absorbed in a metallic film. The generated sound then propagates in the z direction and induces Brillouin oscillations for the probe wavelength (λ probe = 780 nm). Figure 3(c) shows the response to a single object immersed in medium. The simulated object is made up of layers of pseudo-materials with slightly different mechanical but identical optical properties. In Figs 3(c) and 3(d) the dotted lines represent the ideal response expected from the object and the solid lines show the response measured from the simulations. The width of the section S w and a half of the section S w /2 (for N λ = 2) are shown as yellow and orange areas respectively. As the object becomes smaller, the response changes until the measured Brillouin frequency of the object does not reach the expected frequency value calculated from the known object properties. This is because the first edge is not fully resolved before the second edge of the object arrives. However, the object is still visible. Here we shall arbitrarily define a resolved object by this method is that one whose measured frequency is within 5% of the expected value. From this definition it was observed that the width of a resolvable object is typically around half the width of the window S w (see Fig. 3(c)). For the case of two objects separated by a gap (see Fig. 3(d)), the minimum resolved gap is also half of the section width (since the edge response remains the same). As the object becomes smaller than this, the measured frequency shift is reduced - equivalent to a loss of contrast in optical imaging. If the quantitative measurement of the frequency is not of interest and all that matters is contrast, then relaxing the resolution requirement allows the observation of objects of a quarter of the measuring window (analogous to Sparrow criteria in optics37).

The extracted f B in Fig. 3c,d shows artifacts in the form of ripples, these arise for two main reasons. When the sectioning window, which is fixed in size, transitions from one object to the other, its size is no longer a complete number of cycles producing false phase transitions. To reduce this effect the time trace is windowed (typically by a Hann window) to smooth the edges. Applying this process to a single cycle introduces significant distortions (which limits N λ > 1). These effects are reduced as N λ increases.

A resolution target to experimentally demonstrate the z resolution of this method is difficult to fabricate and characterise accurately, however the response to an edge can confirm the observations from the model. Figure 4 shows the experimental response to an edge made out of polystyrene and water. Experimental and simulated (fitted) variations in intensity are shown in Fig. 4(a). In Fig. 4(b–d), both simulated and experimental signals are processed by STFT using N λ = 2, 4 and 6 respectively. The experimental response to the edge follows well the simulations confirming that the edge is resolved within half the width of the section. In Fig. 4(b), the ripples in the a simulated trace (artifacts) are smaller to the variations caused by noise. For N λ = 4 and 6, the ripples are no longer visible (see Fig. 4(c,d)).

Figure 4 Experimental measurement of edge response between polystyrene and water. (a) Experimental and simulated (fitted) traces with a sharp edge made out of polystyrene-water transition. (b) Edge response with N λ = 2. (c) Edge response with N λ = 4. (d) Edge response with N λ = 6. In all N λ cases the resolution is half of the section width. Full size image

The axial resolution obtained using the method presented here has been observed to be approximately half the width of each section S w /2. A fixed number of acoustic cycles N λ is used in the STFT process where a minimum of N λ = 2 has been observed as viable. The size of each section is given by S w = N λ λ a which gives a simple expression for resolution:

where λ probe is the optical probing wavelength and n the refractive index. The frequency resolution, which governs the smallest detectable variation in f B is directly proportional to N λ and inversely proportional to the axial resolution. Which means that in a practical situation, a trade must be made between frequency and axial resolutions; high frequency resolution will allow the detection of wide objects with weak frequency contrast while high axial resolution of thinner objects will require stronger frequency contrast to be viable. This trade is observable in Fig. 4 where the shorter window shows greater influence from noise than the longer ones.

In practise imaging cells, the thinnest possible section (N λ = 2) gives the resolution equals to one λ a ~ 280 nm at 780 nm. However, due to the presence of noise, the number of acoustic cycles N λ used for the sectioning windows in cell imaging is typically four to six reducing the axial resolution. For N λ = 4 or 6, the resolution is 560 and 840 nm which can only be matched by confocal microscopy using very high NA (~1.7) objective lens, whereas a 0.42 NA lens is used in this work.

Phononic cell imaging

Cells can be expected to show mechanical contrast between stiff, aligned structures such as the nucleus or sarcomeres compared to the cytoplasm. In the case of the imaging modality presented here, the sound is detected with Brillouin scattering where stiff structures reveal themselves with a higher sound velocity (and therefore higher f B ) than soft structures. Figure 5 shows an example of our approach applied to a fixed adipose cell cultured on our transducer with a glass substrate. The acoustic wavelength in this case is approximately 280 nm if a refractive index of 1.36 is assumed38. A brightfield image of the scanned area is shown in Fig. 5(a). The Brillouin frequency map shown in Fig. 5(b) was obtained by calculating the Fourier transform over the complete temporal extent of the acquired signal. The fat droplets show distinct contrast compared to the rest of the cell. This contrast is expected as fat has different mechanical properties from the rest of the cell. By assuming a refractive index it is possible to convert the temporal axis to a spatial axis (z). By doing so and sectioning spatially the measurement of the Brillouin frequency with N λ = 4, three critically sampled z sections with resolution of 560 nm were obtained. Such sections are shown in Fig. 5(c–e). From there it is clear to see that the fat droplet marked with a black circle appears in the second section and disappears in the third. This shows that the object is ~560 nm in height and its position is near the centre of the second section (~1 μm) as there is little influence from it on the other sections.

Figure 5 Imaging of an adipose cell using ~5 GHz phonons. (a) Optical picture taken with a conventional brightfield microscope showing an adipose cell. Fat droplets are clearly visible. (b) The Brillouin frequency map of the area shown in (a). This map was obtained using the complete temporal extent of the detected signals. (c–e) Subsections of the measured volume. The central position of the windows in the z direction are 0.6,1 and 1.4 μm to figures (c–e) respectively. The fat droplet marked with a circle appears and disappears within the measured volume. (f) Typical time trace observed from the cell cytoplasm shown as a star in (a). (g) Fourier transform of the time trace presented in (f) showing the Brillouin frequency peak. Full size image

Live cell imaging

Imaging living cells using laser-generated phonons requires the specimen to survive exposure to the light and heat of the system and the imaging time must be as short as possible to prevent motion artifact and capture dynamic processes. The damage threshold of cells caused by near-infrared (NIR) laser pulses were reported to be safe for power densities of 1.7 × 1014 W/m2 scanning a sub-micron spot for over 35 minutes39. In our measurements the power density is approximately 8.5 × 1012 W/m2 scanning a one micron spot for ~38 minutes which is comparable to what has been reported as safe. It is well known that UV light is particularly harmful to cells, however, damage thresholds for single cells using short 390 nm pulses have not been reported in the literature and are anecdotally low and to be avoided if at all possible. Using our schema the sample receives a typical reduction of probe (5x) and pump (15x) beam intensity for the same input power compared to previously reported phonon detection methods22,32. While beam exposures are thus minimised by the transducer and measurement geometry, thermal exposure remains a problem when using glass as substrate due to the low thermal conductivity of the substrate. Numerical models (see supplementary information) show the steady state temperature rises at the cell/substrate interface to be around 25 °C above room temperature (20 °C) when a glass substrate is used. This is due to absorption of the laser pulse train and poor thermal conduction. Such temperatures can be fatal to cells, particularly if heat accumulates over the large numbers of measurements needed to build images using phonons. Sapphire, which has ~30 times the thermal conductivity of glass, was used as a substrate with living cells to minimise interfacial temperature rises to ~7 °C above room temperature. Managing the thermal load during imaging restricts temperature rise to the physiological tolerable range, allowing acquisition of thousands of measurements without compromising cell viability.

Figure 6 shows an example of live cell imaging (3T3 mouse fibroblasts) using a sapphire substrate and 280 nm wavelength phonons. There is good visual agreement between the optical (Fig. 6(a)) and ultrasonic (Fig. 6(b)) images. The average power applied to the transducer was 0.4 and 1 mW for pump and probe beams, of which the cell receives ~0.04 and 0.3 mW respectively. Our methods thus irradiates the sample with far less optical power than required in other phononic (~7.5 mW pump and 2.2 mW probe32) and Brillouin microscopy (2–5 mW17,18) approaches. To confirm compatibility with living cells, the state of the cells was dynamically assessed through the presence of propidium iodide (PI) in the bathing medium. PI fluoresces strongly in the red when bound to DNA, from which it is excluded by the cell membrane in living cells. Continued exclusion of PI throughout the experiments showed that cells remained alive throughout and after the imaging process had finished. Adding detergent to the solution post-experiment killed the cells and confirmed the presence and function of PI (see supplementary information). This demonstrates that the thermal load is a dominant damaging factor and that the characteristics of our approach have provided adequate protection against thermal and photon damage.

Figure 6 Imaging of live 3T3 cells with phonons. (a) Optical image of the scanned area. (b) Brillouin shift measured from (a) sampling every 1 μm, taking ~1.5 s per point and a total of 38 minutes total acquisition time. (c) Section obtained at d = 1 μm. (d) Section obtained at d = ~1.8 μm. As sound propagates, thin filopodia (marked by white circle, square) are resolved axially as the section moves deeper into the cell. Full size image

Sectioning of living cells was also possible. By selecting N λ = 6 for 840 nm resolution, contrast is obtained along the z axis (see Fig. 6(c,d)). Filopodial features are shown to be thinner than the axial section (Fig. 6 circle, square), thus morphology and extent are seen to change as the section is shifted through the cell.

Previous reports of cell imaging using phonons have historically been performed in treated cells (fixed and/or dehydrated). The use of detergent to kill the cells post-experiment offered further opportunity to assess the mechanical contrast of cells whose membranes are delipidated by the detergent. Figure 7 shows cells that were deliberately killed using detergent which changed their appearance not only optically but mechanically as well (see Fig. 6 for comparison). Higher frequencies are observed in the dead cells compared to the living. These higher frequencies arise possibly because when the cell collapses due to the dissolution of its lipid membrane, all the stiff structural material is packed closely together.