Abstract

Simultaneous quantification of multifarious cellular metabolites and the extracellular matrix in vivo has been long sought. Simultaneous label-free autofluorescence and multi-harmonic (SLAM) microscopy has achieved simultaneous four-channel nonlinear imaging to study tissue structure and metabolism. In this study, we implemented two laser systems and directly compared SLAM microscopy with conventional two-photon microscopy for in vivo imaging. We found that three-photon imaging of adenine dinucleotide (phosphate) (NAD(P)H) in SLAM microscopy using our tailored laser source provided better resolution, contrast, and background suppression than conventional two-photon imaging of NAD(P)H. We also integrated fluorescence lifetime imaging with SLAM microscopy, and enabled differentiation of free and bound NAD(P)H. We imaged murine skin in vivo and showed that changes in tissue structure, cell dynamics, and metabolism can be monitored simultaneously in real-time. We also discovered an increase in metabolism and protein-bound NAD(P)H in skin cells during the early stages of wound healing.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2019 (1)

D. Tokarz, R. Cisek, A. Joseph, A. Golaraei, K. Mirsanaye, S. Krouglov, S. L. Asa, B. C. Wilson, and V. Barzda, “Characterization of pancreatic cancer tissue using multiphoton excitation fluorescence and polarization-sensitive harmonic generation microscopy,” Front. Oncol. 9, 272 (2019).
[Crossref]

2018 (6)

C. J. Lin, S. L. Lee, W. H. Wang, V. A. Hovhannisyan, Y. D. Huang, H. S. Lee, and C. Y. Dong, “Multiphoton dynamic imaging of the effect of chronic hepatic diseases on hepatobiliary metabolism in vivo,” J. Biophotonics 11(9), e201700338 (2018).
[Crossref]

S. You, H. Tu, E. J. Chaney, Y. Sun, Y. Zhao, A. J. Bower, Y.-Z. Liu, M. Marjanovic, S. Sinha, Y. Pu, and S. A. Boppart, “Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy,” Nat. Commun. 9(1), 2125 (2018).
[Crossref]

P. Obeidy, P. L. Tong, and W. Weninger, “Research techniques made simple: two-photon intravital imaging of the skin,” J. Invest. Dermatol. 138(4), 720–725 (2018).
[Crossref]

J. Li, A. J. Bower, Z. Arp, E. J. Olson, C. Holland, E. J. Chaney, M. Marjanovic, P. Pande, A. Alex, and S. A. Boppart, “Investigating the healing mechanisms of an angiogenesis-promoting topical treatment for diabetic wounds using multimodal microscopy,” J. Biophotonics 11(3), e201700195 (2018).
[Crossref]

A. J. Bower, J. Li, E. J. Chaney, M. Marjanovic, D. R. Spillman, and S. A. Boppart, “High-speed imaging of transient metabolic dynamics using two-photon fluorescence lifetime imaging microscopy,” Optica 5(10), 1290–1296 (2018).
[Crossref]

F. Akhoundi, Y. Qin, N. Peyghambarian, J. K. Barton, and K. Kieu, “Compact fiber-based multi-photon endoscope working at 1700 nm,” Biomed. Opt. Express 9(5), 2326–2335 (2018).
[Crossref]

2017 (4)

C. J. Rowlands, D. Park, O. T. Bruns, K. D. Piatkevich, D. Fukumura, R. K. Jain, M. G. Bawendi, E. S. Boyden, and P. T. So, “Wide-field three-photon excitation in biological samples,” Light: Sci. Appl. 6(5), e16255 (2017).
[Crossref]

D. G. Ouzounov, T. Wang, M. Wang, D. D. Feng, N. G. Horton, J. C. Cruz-Hernández, Y.-T. Cheng, J. Reimer, A. S. Tolias, and N. Nishimura, “In vivo three-photon imaging of activity of GCaMP6-labeled neurons deep in intact mouse brain,” Nat. Methods 14(4), 388–390 (2017).
[Crossref]

C. Stringari, L. Abdeladim, G. Malkinson, P. Mahou, X. Solinas, I. Lamarre, S. Brizion, J.-B. Galey, W. Supatto, and R. Legouis, “Multicolor two-photon imaging of endogenous fluorophores in living tissues by wavelength mixing,” Sci. Rep. 7(1), 3792 (2017).
[Crossref]

A. V. Meleshina, V. V. Dudenkova, A. S. Bystrova, D. S. Kuznetsova, M. V. Shirmanova, and E. V. Zagaynova, “Two-photon FLIM of NAD (P) H and FAD in mesenchymal stem cells undergoing either osteogenic or chondrogenic differentiation,” Stem Cell Res. Ther. 8(1), 15 (2017).
[Crossref]

2016 (6)

I. N. Druzhkova, M. V. Shirmanova, M. M. Lukina, V. V. Dudenkova, N. M. Mishina, and E. V. Zagaynova, “The metabolic interaction of cancer cells and fibroblasts–coupling between NAD (P) H and FAD, intracellular pH and hydrogen peroxide,” Cell Cycle 15(9), 1257–1266 (2016).
[Crossref]

V. Huck, C. Gorzelanny, K. Thomas, V. Getova, V. Niemeyer, K. Zens, T. R. Unnerstall, J. S. Feger, M. A. Fallah, and D. Metze, “From morphology to biochemical state–intravital multiphoton fluorescence lifetime imaging of inflamed human skin,” Sci. Rep. 6(1), 22789 (2016).
[Crossref]

K. P. Quinn, E. C. Leal, A. Tellechea, A. Kafanas, M. E. Auster, A. Veves, and I. Georgakoudi, “Diabetic wounds exhibit distinct microstructural and metabolic heterogeneity through label-free multiphoton microscopy,” J. Invest. Dermatol. 136(1), 342–344 (2016).
[Crossref]

D. Pouli, M. Balu, C. A. Alonzo, Z. Liu, K. P. Quinn, F. Rius-Diaz, R. M. Harris, K. M. Kelly, B. J. Tromberg, and I. Georgakoudi, “Imaging mitochondrial dynamics in human skin reveals depth-dependent hypoxia and malignant potential for diagnosis,” Sci. Transl. Med. 8(367), 367ra169 (2016).
[Crossref]

J. Janda, V. Nfonsam, F. Calienes, J. E. Sligh, and J. Jandova, “Modulation of ROS levels in fibroblasts by altering mitochondria regulates the process of wound healing,” Arch. Dermatol. Res. 308(4), 239–248 (2016).
[Crossref]

J. Li, Y. Pincu, M. Marjanovic, A. J. Bower, E. J. Chaney, T. Jensen, M. D. Boppart, and S. A. Boppart, “In vivo evaluation of adipose-and muscle-derived stem cells as a treatment for nonhealing diabetic wounds using multimodal microscopy,” J. Biomed. Opt. 21(8), 086006 (2016).
[Crossref]

2015 (2)

T. Kurahashi and J. Fujii, “Roles of antioxidative enzymes in wound healing,” J. Dev. Biol. 3(2), 57–70 (2015).
[Crossref]

A. T. Shah, K. E. Diggins, A. J. Walsh, J. M. Irish, and M. C. Skala, “In vivo autofluorescence imaging of tumor heterogeneity in response to treatment,” Neoplasia (N. Y., NY, U. S.) 17(12), 862–870 (2015).
[Crossref]

2014 (2)

A. Varone, J. Xylas, K. P. Quinn, D. Pouli, G. Sridharan, M. E. McLaughlin-Drubin, C. Alonzo, K. Lee, K. Münger, and I. Georgakoudi, “Endogenous two-photon fluorescence imaging elucidates metabolic changes related to enhanced glycolysis and glutamine consumption in precancerous epithelial tissues,” Cancer Res. 74(11), 3067–3075 (2014).
[Crossref]

F. Fereidouni, A. N. Bader, A. Colonna, and H. C. Gerritsen, “Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin,” J. Biophotonics 7(8), 589–596 (2014).
[Crossref]

2013 (2)

E. E. Hoover and J. A. Squier, “Advances in multiphoton microscopy technology,” Nat. Photonics 7(2), 93–101 (2013).
[Crossref]

N. G. Horton, K. Wang, D. Kobat, C. G. Clark, F. W. Wise, C. B. Schaffer, and C. Xu, “In vivo three-photon microscopy of subcortical structures within an intact mouse brain,” Nat. Photonics 7(3), 205–209 (2013).
[Crossref]

2012 (4)

N. Bryan, H. Ahswin, N. Smart, Y. Bayon, S. Wohlert, and J. A. Hunt, “Reactive oxygen species (ROS)–a family of fate deciding molecules pivotal in constructive inflammation and wound healing,” Eur. Cells Mater. 24, 249–265 (2012).
[Crossref]

X. Jiang, S. Zhuo, R. A. Xu, and J. Chen, “Multiphoton microscopic imaging of in vivo hair mouse skin based on two-photon excited fluorescence and second harmonic generation,” Scanning 34(3), 170–173 (2012).
[Crossref]

Y. Zhang, M. L. Akins, K. Murari, J. Xi, M.-J. Li, K. Luby-Phelps, M. Mahendroo, and X. Li, “A compact fiber-optic SHG scanning endomicroscope and its application to visualize cervical remodeling during pregnancy,” Proc. Natl. Acad. Sci. U. S. A. 109(32), 12878–12883 (2012).
[Crossref]

B. W. Graf and S. A. Boppart, “Multimodal in vivo skin imaging with integrated optical coherence and multiphoton microscopy,” IEEE J. Sel. Top. Quantum Electron. 18(4), 1280–1286 (2012).
[Crossref]

2011 (2)

A. C.-H. Chen, C. McNeilly, A. P.-Y. Liu, C. J. Flaim, L. Cuttle, M. Kendall, R. M. Kimble, H. Shimizu, and J. R. McMillan, “Second harmonic generation and multiphoton microscopic detection of collagen without the need for species specific antibodies,” Burns 37(6), 1001–1009 (2011).
[Crossref]

A. M. Lee, H. Wang, Y. Yu, S. Tang, J. Zhao, H. Lui, D. I. McLean, and H. Zeng, “In vivo video rate multiphoton microscopy imaging of human skin,” Opt. Lett. 36(15), 2865–2867 (2011).
[Crossref]

2010 (1)

J. H. Ostrander, C. M. McMahon, S. Lem, S. R. Millon, J. Q. Brown, V. L. Seewaldt, and N. Ramanujam, “Optical redox ratio differentiates breast cancer cell lines based on estrogen receptor status,” Cancer Res. 70(11), 4759–4766 (2010).
[Crossref]

2009 (4)

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2008 (2)

W. Jung, S. Tang, D. T. McCormic, T. Xie, Y.-C. Ahn, J. Su, I. V. Tomov, T. B. Krasieva, B. J. Tromberg, and Z. Chen, “Miniaturized probe based on a microelectromechanical system mirror for multiphoton microscopy,” Opt. Lett. 33(12), 1324–1326 (2008).
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2006 (3)

U. Auf Dem Keller, A. Kümin, S. Braun, and S. Werner, “Reactive oxygen species and their detoxification in healing skin wounds,” J. Invest. Dermatol. Symp. Proc. 11(1), 106–111 (2006).
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2003 (3)

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2002 (1)

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1996 (4)

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U. Auf Dem Keller, A. Kümin, S. Braun, and S. Werner, “Reactive oxygen species and their detoxification in healing skin wounds,” J. Invest. Dermatol. Symp. Proc. 11(1), 106–111 (2006).
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D. Tokarz, R. Cisek, A. Joseph, A. Golaraei, K. Mirsanaye, S. Krouglov, S. L. Asa, B. C. Wilson, and V. Barzda, “Characterization of pancreatic cancer tissue using multiphoton excitation fluorescence and polarization-sensitive harmonic generation microscopy,” Front. Oncol. 9, 272 (2019).
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J. Li, A. J. Bower, Z. Arp, E. J. Olson, C. Holland, E. J. Chaney, M. Marjanovic, P. Pande, A. Alex, and S. A. Boppart, “Investigating the healing mechanisms of an angiogenesis-promoting topical treatment for diabetic wounds using multimodal microscopy,” J. Biophotonics 11(3), e201700195 (2018).
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J. Li, A. J. Bower, Z. Arp, E. J. Olson, C. Holland, E. J. Chaney, M. Marjanovic, P. Pande, A. Alex, and S. A. Boppart, “Investigating the healing mechanisms of an angiogenesis-promoting topical treatment for diabetic wounds using multimodal microscopy,” J. Biophotonics 11(3), e201700195 (2018).
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A. J. Bower, J. Li, E. J. Chaney, M. Marjanovic, D. R. Spillman, and S. A. Boppart, “High-speed imaging of transient metabolic dynamics using two-photon fluorescence lifetime imaging microscopy,” Optica 5(10), 1290–1296 (2018).
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J. Li, Y. Pincu, M. Marjanovic, A. J. Bower, E. J. Chaney, T. Jensen, M. D. Boppart, and S. A. Boppart, “In vivo evaluation of adipose-and muscle-derived stem cells as a treatment for nonhealing diabetic wounds using multimodal microscopy,” J. Biomed. Opt. 21(8), 086006 (2016).
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U. Auf Dem Keller, A. Kümin, S. Braun, and S. Werner, “Reactive oxygen species and their detoxification in healing skin wounds,” J. Invest. Dermatol. Symp. Proc. 11(1), 106–111 (2006).
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E. Brown, T. McKee, A. Pluen, B. Seed, Y. Boucher, and R. K. Jain, “Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation,” Nat. Med. 9(6), 796–800 (2003).
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E. B. Brown, R. B. Campbell, Y. Tsuzuki, L. Xu, P. Carmeliet, D. Fukumura, and R. K. Jain, “In vivo measurement of gene expression, angiogenesis and physiological function in tumors using multiphoton laser scanning microscopy,” Nat. Med. 7(7), 864–868 (2001).
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N. Bryan, H. Ahswin, N. Smart, Y. Bayon, S. Wohlert, and J. A. Hunt, “Reactive oxygen species (ROS)–a family of fate deciding molecules pivotal in constructive inflammation and wound healing,” Eur. Cells Mater. 24, 249–265 (2012).
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K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech. 70(5), 398–402 (2007).
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E. B. Brown, R. B. Campbell, Y. Tsuzuki, L. Xu, P. Carmeliet, D. Fukumura, and R. K. Jain, “In vivo measurement of gene expression, angiogenesis and physiological function in tumors using multiphoton laser scanning microscopy,” Nat. Med. 7(7), 864–868 (2001).
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D. L. Wokosin, V. E. Centonze, S. Crittenden, and J. White, “Three-photon excitation fluorescence imaging of biological specimens using an all-solid-state laser,” Bioimaging 4(3), 208–214 (1996).
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S. You, H. Tu, E. J. Chaney, Y. Sun, Y. Zhao, A. J. Bower, Y.-Z. Liu, M. Marjanovic, S. Sinha, Y. Pu, and S. A. Boppart, “Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy,” Nat. Commun. 9(1), 2125 (2018).
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D. L. Wokosin, V. E. Centonze, S. Crittenden, and J. White, “Three-photon excitation fluorescence imaging of biological specimens using an all-solid-state laser,” Bioimaging 4(3), 208–214 (1996).
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Supplementary Material (2)

NameDescription
» Visualization 1       Depth-Resolved 3D Imaging
» Visualization 2       Cell Dynamics in Tissue

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Figures (5)

Fig. 1.
Fig. 1. Label-free simultaneous multimodal imaging setup and system characterization. (A) The layout of the multimodal nonlinear optical imaging system. HWP: half-wave plate; PBS: polarization beam splitter; PCF: photonic crystal fiber; PM: parabolic mirror; L: lens; M: mirror; FM: flip mirror; G: grating; SLM: spatial light modulator; GM: galvo mirror; DM: dichroic mirror; PMT: photomultiplier tube; CH: channel. (B) Spectra from the tailored coherent light source after pulse shaping, and from the tunable femtosecond laser. (C) Comparing NAD(P)H and FAD signals in 4 channels using our tailored light source versus a traditional tunable laser at 750 nm and 950 nm excitation.
Fig. 2.
Fig. 2. Comparison between two laser sources for NAD(P)H and FAD imaging. (A) A 2PEF NAD(P)H image, and (B) a 3PEF NAD(P)H image from keratinocyte cells in the epidermis of living mouse skin. Ten (10) cells, as indicated in the figure, were selected to compare with panel A for signal-to-noise ratio improvement. (C) 2PEF (green line) and 3PEF (red line) intensity profiles obtained from the white lines shown in panels (A) and (B), respectively. (D) and (E) are 2PEF NAD(P)H images from the dermal layer of mouse skin using the tunable laser source (750 nm) obtained with excitation powers of 6 mW and 50 mW at the sample, respectively. (F) 3PEF NAD(P)H image of the same location in (D) but using the tailored coherent light source with an excitation power of 6 mW at the sample. Arrows point out blood vessel walls. (G) and (H) show autofluorescence detected from the FAD channel (CH4) using the tunable laser source at 750 nm. The arrows in panel (G) indicate hair follicles. (I) FAD signal from the same location in (G) using the tailored light source.
Fig. 3.
Fig. 3. 3D imaging of skin in vivo. (A) Depth-resolved images from mouse skin. The images were obtained using multimodal microscopy based on the tailored coherent light source. The images display different depth sections separated by 8 µm, obtained from the epidermal and dermal layers (∼50 µm deep) below the skin surface. The 5 channels including THG, 3PEF (for NAD(P)H), SHG, 2PEF (for FAD), and FLIM, were directly obtained from 4 PMT channels. The redox images were calculated using the FAD/(FAD + NAD(P)H) intensity ratio. A total of 6 contrasts were generated, as shown. (B) and (C) Magnified FLIM images from the stratum corneum and the stratum basale layers from panel (A). The color bar unit for redox images is an arbitrary unit, and for FLIM images, the unit is picoseconds.
Fig. 4.
Fig. 4. Time-lapse monitoring of cell dynamics in mouse skin. (A) Multimodal images from an area of interest in the dermis. THG and SHG images show structures from membranes/interfaces and collagen, respectively, while 3PEF NAD(P)H and 2PEF FAD images show metabolic information. (B) Zoomed-in time-lapse images from the dashed square areas shown in panel (A). Image interval is 2 seconds. Arrows point out the moving particle in each image. For THG, TPEF, and 2PEF images, the arrows point to a micro-particle, likely a cell. For SHG, the arrows point to collagen fibers. Dashed lines are used as location references.
Fig. 5.
Fig. 5. Monitoring metabolic changes in vivo during wound healing. (A) Photograph showing a wound area on mouse dorsal skin. (B) Photograph showing a mouse positioned on the stage for in vivo dorsal skin imaging. (C) Redox ratio images from non-wounded (upper row) and wounded (lower row) mouse skin monitored over 14 days. (D) NAD(P)H FLIM images from non-wounded (upper row) and wounded (lower row) mouse skin monitored over 14 days. (E) Redox ratio changes from wounded (red line) and non-wounded (black line) groups over 14 days. (F) NAD(P)H fluorescence lifetime change from wounded (red line) and non-wounded (black line) groups over 14 days. The wound was made on Day 1 in the wounded group. The color bar unit for (C) is arbitrary units, and for (D) is picoseconds.