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Raman spectroscopy and Raman-based imaging are powerful emerging tools in the bio sciences. Currently, this is particularly true for the in vivo and in vitro study of cellular metabolism and metabolic disorders in processing and storage of lipids. Most bio-macromolecules contain a large number of similar, mostly carbon-based molecular bonds, so that the Raman spectra obtained from cells and organisms are typically a convolution of contributions from lipids, proteins, nucleic acids, sugars, etc. Lipids are relatively easy to isolate from these complex spectra, because of their tendency to form dense droplets or bilayers and because they contain extended chains with a large number of aliphatic CH bonds. Our ability to isolate specific proteins, amino acids, RNA, or DNA within the complex cellular environment is, however, very limited. This is particularly true if these molecules of interest are only present at μM concentrations and below. Here, the ability to probe weak Raman resonances utilizing our newly introduced DR-CARS difference imaging technique provides a potentially powerful approach for their chemical microanalysis and imaging. Admittedly, the most complicated portion of this protocol is the alignment and synchronization of the laser system. When starting from scratch, the synchronization of the pulses, i.e. ensuring that the pulses are overlapped in time despite the different paths they take can be facilitated by the use of a pulse autocorrelator. Once spatial and temporal overlap is achieved, CARS and DR-CARS signals should be readily detectable. However, the first alignment is often crude, resulting in weak signals. The best practice for aligning this system well is to initially generate weak signals and then to improve the signal strength by gently tweaking the mirrors along each path and adjusting the temporal overlap using the delay stages. Although the spectrometer/monochromator acts as a very efficient baffle for room light the cleanest results can be achieved by operating the system with the room lights turned off and curtains or lens tubing to minimize background introduced by the various other light sources (e.g computer monitors, indicator lights, LEDs, etc.).
Our particular setup utilizes single-photon counting avalanche photo-diode (APD) detectors and time-correlated single photon counting (TCSPC) hardware for detection 5. This enables us to detect extremely weak signals with relatively low noise but many groups have found photo-multiplier tubes (PMT's) with variable gain advantageous when making similar measurements. The advantage of PMT's is that they offer variable gain and have a much larger detection area which can simplify alignment of the detector. Additionally, our setup utilizes piezo stages to translate the objective in order to achieve beam scanning. The advantage of this is that we have the ability to return to any spot within the previously scanned image with a high degree of accuracy and take additional measurements including spontaneous Raman spectra. Other groups have been successful utilizing scanning mirror assemblies, or even entire confocal scanning units such as the Olympus FluoView system, which offers much faster imaging but is limited in its ability to precisely return to arbitrary locations within an image.
Tuning the lasers to match the Raman resonance is also a critical step that may require some optimization. Although the Raman peaks may be known the maximum spectral peak intensity obtained from DR-CARS and CARS does not necessarily correspond to the maximum of the spontaneous Raman peak. This is due to the intrinsic interference of signals generated by four-wave mixing leading to a non-resonant background signal and CARS, which distorts CARS spectra relative to spontaneous Raman spectra. The spectral location of the peak of the CARS signal can be calculated, but a more practical approach is to tune the OPOs in several, small spectral steps across the expected location of the Raman resonance. This process should yield a clear maximum. In fact, for the greatest sensitivity from DR-FWM both resonances must be tuned to this maximum.
One last potential problem of the DR-CARS approach has to also be discussed, i.e. the DR-CARS signal will depend on a homogeneous distribution of the Raman-active amplifying molecule. For most biological objects, this could well be the broad OH resonance from water, which is abundant and almost omnipresent. Water is, however, excluded from hydrophobic regions with a cell, such as lipid droplets, leading a distortion of the signals obtained when utilizing the water resonance to amplify lipid modes. In our example, we have used a solution of deuterated glucose to generate an easily detectable and abundant signal for our biological sample. Similarly, deuterated water or deuterated biological buffers, such as d-HEPES could be used. In our example, the lipid droplets within the C. elegans worm were small enough to always contain both, the deuterated glucose solution and lipids within the focused laser spot of our system. This, however, is not generally true. A particular example would be adipocytes, which generate rather large lipid droplets within their cytoplasm. This means, any experiment conducted with the DR-CARS technique requires careful preparation and control experiments to verify the results.