Alkyne-Tag Raman Imaging for Visualization of Mobile Small Molecules in Live Cells

Yamakoshi, Hiroyuki; Dodo, Kosuke; Palonpon, Almar F.; Ando, Jun; Fujita, Katsumasa; Kawata, Satoshi; Sodeoka, Mikiko

doi:10.1021/ja308529n

Cited by 387 publications

(414 citation statements)

References 46 publications

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“…The epr-SRS dye palette can be expanded further, especially when going beyond conjugated C=C bonds and targeting triple bonds such as alkynes (C≡C) and nitriles (C≡N) that display a single sharp Raman peak in the wide silent window (from 1800 to 2800 cm −1 ) 12–15, 20 . The challenge here is that the triple bonds must be coupled with an electronic transition to enable pre-resonance enhancement, which will depend sensitively on the electronic-vibrational coupling strength 16 .…”

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confidence: 99%

Super-multiplex vibrational imaging

Chen

Shi

et al. 2017

Nature

413

452

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The ability to directly visualize a large number of distinct molecular species inside cells is increasingly essential for understanding complex systems and processes. Even though existing methods have been used successfully to explore structural-functional relationships in nervous systems, profile RNA in situ, reveal tumor microenvironment heterogeneity or study dynamic macromolecular assembly1–4, it remains challenging to image many species with high selectivity and sensitivity under biological conditions. For instance, fluorescence microscopy faces a “color barrier” due to the intrinsically broad (~1500 cm−1) and featureless nature of fluorescence spectra5 that limits the number of resolvable colors to 2 to 5 (or 7-9 if using complicated instrumentation and analysis)6–8. Spontaneous Raman microscopy probes vibrational transitions with much narrower resonances (peak width ~10 cm−1) and thus doesn’t suffer this problem, but its feeble signals make many demanding bio-imaging applications impossible. And while surface-enhanced Raman scattering offers remarkable sensitivity and multiplicity, it cannot be readily used to quantitatively image specific molecular targets inside live cells9. Here we show that carrying out stimulated Raman scattering under electronic pre-resonance conditions (epr-SRS) enables imaging with exquisite vibrational selectivity and sensitivity (down to 250 nM with 1-ms) in living cells. We also create a palette of triple-bond-conjugated near-infrared dyes that each display a single epr-SRS peak in the cell-silent spectral window, and that with available fluorescent probes give 24 resolvable colors with potential for further expansion. Proof-of-principle experiments on neuronal co-cultures and brain tissues reveal cell-type dependent heterogeneities in DNA and protein metabolism under physiological and pathological conditions, underscoring the potential of this super-multiplex optical imaging approach for untangling intricate interactions in complex biological systems.

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confidence: 99%

Super-multiplex vibrational imaging

Chen

Shi

et al. 2017

Nature

413

452

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“…As shown in Fig. 2B, the diyne-SM monolayer showed a strong peak at 2,263 cm −1 , which is attributed to the stretching vibrational mode of the diyne moiety (18). Because the peak appears in the silent region of membrane lipids, it would be possible to unambiguously identify diyne-SM in multicomponent membranes by means of Raman spectroscopy without any interference from intrinsic vibrational modes of other membrane constituents.…”

Section: Resultsmentioning

confidence: 93%

“…For the lipid head group, the number of sites available for introducing a Raman tag is relatively limited. Alkyne, particularly conjugated diyne, is a promising Raman tag for the head group because of its strong Raman intensity (18). We incorporated a conjugated diyne moiety into the ammonium group at the polar head and successfully recorded its image in an artificial monolayer with a raft-mimicking composition.…”

Section: Discussionmentioning

confidence: 99%

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Sphingomyelin distribution in lipid rafts of artificial monolayer membranes visualized by Raman microscopy

Ando

Kinoshita

Cui

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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120

102

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Sphingomyelin (SM) and cholesterol (chol)-rich domains in cell membranes, called lipid rafts, are thought to have important biological functions related to membrane signaling and protein trafficking. To visualize the distribution of SM in lipid rafts by means of Raman microscopy, we designed and synthesized an SM analog tagged with a Raman-active diyne moiety (diyne-SM). Diyne-SM showed a strong peak in a Raman silent region that is free of interference from intrinsic vibrational modes of lipids and did not appear to alter the properties of SM-containing monolayers. Therefore, we used Raman microscopy to directly visualize the distribution of diyne-SM in raft-mimicking domains formed in SM/dioleoylphosphatidylcholine/chol ternary monolayers. Raman images visualized a heterogeneous distribution of diyne-SM, which showed marked variation, even within a single ordered domain. Specifically, diyne-SM was enriched in the central area of raft domains compared with the peripheral area. These results seem incompatible with the generally accepted raft model, in which the raft and nonraft phases show a clear biphasic separation. One of the possible reasons is that gradual changes of SM concentration occur between SM-rich and -poor regions to minimize hydrophobic mismatch. We believe that our technique of hyperspectral Raman imaging of a single lipid monolayer opens the door to quantitative analysis of lipid membranes by providing both chemical information and spatial distribution with high (diffraction-limited) spatial resolution.lipid raft | Raman imaging | alkyne tag | supported monolayer | sphingomyelin

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“…Based on noteworthy studies, [2][3][4][5] today, bio-Raman research is applicable to the fields of cellular biology and biophysics, and thus attracting many researchers. [6][7][8][9][10][11][12][13] Multivariable analysis, such as principal component analysis (PCA) or a PCA-based approach, called chemometrics in chemistry, is frequently applied to bio-Raman research for visualizing and extracting intrinsic information. [12][13][14][15][16][17][18][19][20][21] This is because bio-Raman data are generally complicated and large, making it almost impossible to interpret the data in an intuitive manner.…”

mentioning

confidence: 99%