Abstract

Fiber-optic epifluorescence imaging with one-photon excitation benefits from its ease of use, cheap light sources, and full-frame acquisition, which enables it for favorable temporal resolution of image acquisition. However, it suffers from a lack of robustness against autofluorescence and light scattering. Moreover, it cannot easily eliminate the out-of-focus background, which generally results in low-contrast images. In order to overcome these limitations, we have implemented fast out-of-phase imaging after optical modulation (Speed OPIOM) for dynamic contrast in fluorescence endomicroscopy. Using a simple and cheap optical-fiber bundle-based endomicroscope integrating modulatable light sources, we first showed that Speed OPIOM provides intrinsic optical sectioning, which restricts the observation of fluorescent labels at targeted positions within a sample. We also demonstrated that this imaging protocol efficiently eliminates the interference of autofluorescence arising from both the fiber bundle and the specimen in several biological samples. Finally, we could perform multiplexed observations of two spectrally similar fluorophores differing by their photoswitching dynamics. Such attractive features of Speed OPIOM in fluorescence endomicroscopy should find applications in bioprocessing, clinical diagnostics, plant observation, and surface imaging.

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

Full Article  |  PDF Article

Corrections

30 July 2019: Typographical corrections were made to the numeric labels of Sections 3 and 4.


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2018 (3)

R. Zhang, R. Chouket, M.-A. Plamont, Z. Kelemen, A. Espagne, A. G. Tebo, A. Gautier, L. Gissot, J.-D. Faure, L. Jullien, V. Croquette, and T. L. Saux, “Macroscale fluorescence imaging against autofluorescence under ambient light,” Light: Sci. Appl. 7, 97 (2018).
[Crossref]

R. P. Harrison and V. M. Chauhan, “Enhancing cell and gene therapy manufacture through the application of advanced fluorescent optical sensors (review),” Biointerphases 13, 01A301 (2018).
[Crossref]

E. M. Zhao, Y. Zhang, J. Mehl, H. Park, M. A. Lalwani, J. E. Toettcher, and J. L. Avalos, “Optogenetic regulation of engineered cellular metabolism for microbial chemical production,” Nature 555, 683–687 (2018).
[Crossref]

2017 (4)

L. Dekker and K. M. Polizzi, “Sense and sensitivity in bioprocessing-detecting cellular metabolites with biosensors,” Curr. Opin. Chem. Biol. 40, 31–36 (2017).
[Crossref]

W. Yang and R. Yuste, “In vivo imaging of neural activity,” Nat. Methods 14, 349–359 (2017).
[Crossref]

J. Quérard, R. Zhang, Z. Kelemen, M.-A. Plamont, X. Xie, R. Chouket, I. Roemgens, Y. Korepina, S. Albright, E. Ipendey, M. Volovitch, H. L. Sladitschek, P. Neveu, L. Gissot, A. Gautier, J.-D. Faure, V. Croquette, T. L. Saux, and L. Jullien, “Resonant out-of-phase fluorescence microscopy and remote imaging overcome spectral limitations,” Nat. Commun. 8, 969 (2017).
[Crossref]

T. Nagaya, Y. A. Nakamura, P. L. Choyke, and H. Kobayashi, “Fluorescence-guided surgery,” Front. Oncol. 7, 314 (2017).
[Crossref]

2016 (5)

F. Nooshabadi, H.-J. Yang, J. N. Bixler, Y. Kong, J. D. Cirillo, and K. C. Maitland, “Intravital fluorescence excitation in whole animal optical imaging,” PLoS ONE 11, e0149932 (2016).
[Crossref]

M. J. Landau, D. J. Gould, and K. M. Patel, “Advances in fluorescent-image guided surgery,” Ann. Transl. Med. 4, 392 (2016).
[Crossref]

P. Keahey, P. Ramalingam, K. Schmeler, and R. R. Richards-Kortum, “Differential structured illumination microendoscopy for in vivo imaging of molecular contrast agents,” Proc. Natl. Acad. Sci. USA 113, 10769–10773 (2016).
[Crossref]

G. Calafiore, A. Koshelev, F. I. Allen, S. Dhuey, S. Sassolini, E. Wong, P. Lum, K. Munechika, and S. Cabrini, “Nanoimprint of a 3d structure on an optical fiber for light wavefront manipulation,” Nanotechnology 27, 375301 (2016).
[Crossref]

R. S. R. Ribeiro, P. Dahal, A. Guereiro, P. Jorge, and J. Viegas, “Optical fibers as beam shapers: from Gaussian beams to optical vortices,” Opt. Lett. 41, 2137–2140 (2016).
[Crossref]

2015 (6)

Y. Ziv and K. K. Ghosh, “Miniature microscopes for large-scale imaging of neuronal activity in freely behaving rodents,” Curr. Opin. Neurobiol. 32, 141–147 (2015).
[Crossref]

J. Han, M. Sparkes, and W. O’Neill, “Controlling the optical fiber output beam profile by focused ion beam machining of a phase hologram on fiber tip,” Appl. Opt. 54, 890–894 (2015).
[Crossref]

D. P. Mahoney, E. A. Owens, C. Fan, J.-C. Hsiang, M. M. Henary, and R. M. Dickson, “Tailoring cyanine dark states for improved optically modulated fluorescence recovery,” J. Phys. Chem. B 119, 4637–4643 (2015).
[Crossref]

I. Mihalcescu, M. V.-M. Gateau, B. Chelli, C. Pinel, and J.-L. Ravanat, “Green autofluorescence, a double edged monitoring tool for bacterial growth and activity in micro-plates,” Phys. Biol. 12, 066016 (2015).
[Crossref]

K. M. Polizzi and C. Kontoravdi, “Genetically-encoded biosensors for monitoring cellular stress in bioprocessing,” Curr. Opin. Biotechnol. 31, 50–56 (2015).
[Crossref]

J. Quérard, T.-Z. Markus, M.-A. Plamont, C. Gauron, P. Wang, A. Espagne, M. Volovitch, S. Vriz, V. Croquette, A. Gautier, T. Le Saux, and L. Jullien, “Photoswitching kinetics and phase-sensitive detection add discriminative dimensions for selective fluorescence imaging,” Angew. Chem. Int. Ed. 127, 2671–2675 (2015).
[Crossref]

2014 (2)

C. A. Lichten, R. White, I. B. Clark, and P. S. Swain, “Unmixing of fluorescence spectra to resolve quantitative time-series measurements of gene expression in plate readers,” BMC Biotechnol. 14, 11 (2014).
[Crossref]

R. Klajn, “Spiropyran-based dynamic materials,” Chem. Soc. Rev. 43, 148–184 (2014).
[Crossref]

2013 (5)

S. Berthoumieux, H. de Jong, G. Baptist, C. Pinel, C. Ranquet, D. Ropers, and J. Geiselmann, “Shared control of gene expression in bacteria by transcription factors and global physiology of the cell,” Mol. Syst. Biol. 9, 634 (2013).
[Crossref]

G. Oh, E. Chung, and S. H. Yun, “Optical fibers for high-resolution in vivo microendoscopic fluorescence imaging,” Opt. Fiber Technol. 19, 760–771 (2013).
[Crossref]

D. Xu, T. Jiang, A. Li, B. Hu, Z. Feng, H. Gong, S. Zeng, and Q. Luo, “Fast optical sectioning obtained by structured illumination microscopy using a digital mirror device,” J. Biomed. Opt. 18, 060503 (2013).
[Crossref]

J. Ahn, H. Yoo, and D.-G. Gweon, “Endoscopic focal modulation microscopy,” J. Microsc. 250, 116–121 (2013).
[Crossref]

T. K. Miriam Athmann, R. Pude, and U. Köpke, “Root growth in biopores—evaluation with in situ endoscopy,” Plant Soil 371, 179–190 (2013).
[Crossref]

2012 (5)

J. M. Jabbour, M. A. Saldua, J. N. Bixler, and K. C. Maitland, “Confocal endomicroscopy: instrumentation and medical applications,” Ann. Biomed. Eng. 40, 378–397 (2012).
[Crossref]

T. J. Muldoon, D. Roblyer, M. D. Williams, V. M. Stepanek, R. Richards-Kortum, and A. M. Gillenwater, “Noninvasive imaging of oral neoplasia with a high-resolution fiber-optic microendoscope,” Head Neck Oncol. 34, 305–312 (2012).
[Crossref]

T. N. Ford, D. Lim, and J. Mertz, “Fast optically sectioned fluorescence HiLo endomicroscopy,” J. Biomed. Opt. 17, 021105 (2012).
[Crossref]

D. Bourgeois and V. Adam, “Reversible photoswitching in fluorescent proteins: a mechanistic view,” IUBMB Life 64, 482–491 (2012).
[Crossref]

C. D. Saunter, S. Semprini, C. Buckley, J. Mullins, and J. M. Girkin, “Micro-endoscope for in vivo widefield high spatial resolution fluorescent imaging,” Biomed. Opt. Express 3, 1274–1278 (2012).
[Crossref]

2011 (1)

M. Pierce, D. Yu, and R. Richards-Kortum, “High-resolution fiber-optic microendoscopy for in situ cellular imaging,” J. Vis. Exp. 47, e2306 (2011).
[Crossref]

2010 (4)

Y. Zhao, H. Nakamura, and R. J. Gordon, “Development of a versatile two-photon endoscope for biological imaging,” Biomed. Opt. Express 1, 1159–1172 (2010).
[Crossref]

D. M. Chudakov, M. V. Matz, S. Lukyanov, and K. A. Lukyanov, “Fluorescent proteins and their applications in imaging living cells and tissues,” Physiol. Rev. 90, 1103–1163 (2010).
[Crossref]

C. I. Richards, J.-C. Hsiang, and R. M. Dickson, “Synchronously amplified fluorescence image recovery (SAFIRe),” J. Phys. Chem. B 114, 660–665 (2010).
[Crossref]

J. Widengren, “Fluorescence-based transient state monitoring for biomolecular spectroscopy and imaging,” J. R. Soc. Interface 7, 1135–1144 (2010).
[Crossref]

2009 (1)

S. Santos, K. K. Chu, D. Lim, N. Bozinovic, T. N. Ford, C. Hourtoule, A. C. Bartoo, S. K. Singh, and J. Mertz, “Optically sectioned fluorescence endomicroscopy with hybrid-illumination imaging through a flexible fiber bundle,” J. Biomed. Opt. 14, 030502 (2009).
[Crossref]

2008 (6)

P. Kim, M. Puoris’haag, D. Coté, C. P. Lin, and S. H. Yun, “In vivo confocal and multiphoton microendoscopy,” J. Biomed. Opt 13, 010501 (2008).
[Crossref]

N. Bozinovic, C. Ventalon, T. Ford, and J. Mertz, “Fluorescence endomicroscopy with structured illumination,” Opt. Express 16, 8016–8025 (2008).
[Crossref]

G. Marriott, S. Mao, T. Sakata, J. Ran, D. K. Jackson, C. Petchprayoon, T. J. Gomez, E. Warp, O. Tulyathan, H. L. Aaron, E. Y. Isacoff, and Y. Yan, “Optical lock-in detection imaging microscopy for contrast-enhanced imaging in living cells,” Proc. Natl. Acad. Sci. USA 105, 17789–17794 (2008).
[Crossref]

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B. A. Flusberg, J. C. Jung, E. D. Cocker, E. P. Anderson, and M. J. Schnitzer, “In vivo brain imaging using a portable 3.9 gram two-photon fluorescence microendoscope,” Opt. Lett. 30, 2272–2274 (2005).
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M. Andresen, A. C. Stiel, J. Follig, D. Wenzel, A. Schoenle, A. Egner, C. Eggeling, S. W. Hell, and S. Jakobs, “Photoswitchable fluorescent proteins enable monochromatic multilabel imaging and dual color fluorescence nanoscopy,” Nat. Biotechnol. 26, 1035–1040 (2008).
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Supplementary Material (1)

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Figures (6)

Fig. 1.
Fig. 1. (a) Principle of Speed OPIOM. Sinusoidally modulated light sources synchronized in antiphase at two wavelengths drive the exchange between two states of distinct brightness of reversibly photoswitchable fluorescent labels. Speed OPIOM exploits the resulting quadrature-delayed component S (in red) of their fluorescence emission. (b),(c) Speed OPIOM for optical sectioning and selective imaging. The normalized Speed-OPIOM signal S norm exhibits a narrow resonance both in the space of the control parameters of illumination [(b) here parametered by I 2 0 / I 1 0 and ω / I 1 0 , where I 1 0 , and I 2 0 , and ω respectively designate the average light intensities at both wavelengths and the angular frequency of the modulated lights] and in the space of the rate constants, which govern forward and backward photoswitching of the labels [(c) parametered by K 12 0 and ω τ 12 0 , where K 12 0 and τ 12 0 respectively designate the ratio of the average rate constants associated to forward and backward photoswitching and the photoswitching relaxation time at a steady state]. The signal level in Speed OPIOM is displayed on the gray scale at the right of each figure.
Fig. 2.
Fig. 2. Fluorescence endoscopy setup for Speed-OPIOM imaging. (a) Optical layout of the endoscope and its interface to a PC-based synchronized modulation and imaging acquisition system; (b) experimental light intensity profile visualized by autofluorescence of a lysogeny broth (LB) solution along the pathway of 405 nm UV light emitted from the fiber; (c) simulation of the excitation light intensity at the distal end of the fiber as a function of the sample depth. The computation was performed for a multimode fiber of 0.72 mm in diameter and 0.39 NA plunging into water ( n = 1.34 ) (see Section 2 of Supplement 1). The light intensity is displayed in linear scale at the right of the image. Scale bar: 1 mm. (d),(e) Normalized light intensity pattern at (d) 480 nm and (e) 405 nm measured at the distal end of the fiber bundle by microscopy. A uniformity better than 90% was observed over the whole surface of the fiber bundle. The normalized light intensity is displayed in linear scale at the right of the images in (d) and (e). (f) Autofluorescence of the fiber bundle recorded under constant illumination at 480 and 405 nm upon filtering at 525 nm. The zoomed image depicts the detail of the cores and cladding giving rise to a honeycomb artifact and the slight core-to-core coupling as evidenced from detecting fluorescence in the non-illuminated cores close to the edge of the illuminated zone. Scale bar in (d)–(f): 100 μm.
Fig. 3.
Fig. 3. Speed OPIOM for optical sectioning. (a),(d) Pre-OPIOM (circles) and Speed-OPIOM (disks) signals collected from (a) a 1 μm Dronpa-2 solution and (d) a dense suspension of Dronpa-2-expressing bacteria as a function of the thickness z of the sample under illumination. The Pre-OPIOM and Speed-OPIOM signals have been obtained after spatial averaging over a disk of 50 pixels (equivalent to a disk 60 μm in the sample) of the Pre-OPIOM and Speed-OPIOM images. In (a), the theoretical calculations of the Pre-OPIOM and Speed-OPIOM signals based on the simulated illumination pattern displayed in Fig. 2(c) are shown as dashed and solid lines, respectively (see Section 2 of Supporting information). (b),(e) Normalized Pre-OPIOM and (c),(f) Speed-OPIOM responses to the spatial profiles of exiting light intensity at the distal end of the fiber bundle based on the simulated illumination pattern through (b),(c) the Dronpa-2 solution and (e),(f) a scattering medium with a penetration length of λ c = 3 mm . The signal levels in Pre-OPIOM and Speed OPIOM are displayed in common decimal logarithmic scale at the right of each image. Axis unit: millimeter. Scale bar: 1 mm. (g) Pre-OPIOM and (j) Speed-OPIOM images of 1 μm Dronpa-2 solution observed by fluorescence endomicroscopy upon illuminating a small area (a few fiber cores of the bundle; 15 μm diameter) at the proximal end of the fiber bundle. (h) Normalized Pre-OPIOM and (k) Speed-OPIOM responses to the spatial profiles of exiting light intensity at the distal end of a single microfiber based on simulated illumination pattern through the Dronpa-2 solution. The signal levels in Pre-OPIOM and Speed OPIOM are displayed in common decimal logarithmic scale at the right of each image. Axis unit: micrometer. (i) Experimental and (l) simulated (for an illuminated area of 15 μm diameter) signal profiles along the dashed line in (g) and (j) (dotted and solid lines correspond to Pre-OPIOM and Speed OPIOM, respectively). Scale bar in (g),(h) and (j),(k): 100 μm. See Table S1 of Supplement 1 for the acquisition conditions.
Fig. 4.
Fig. 4. In situ monitoring of Dronpa-2 expression in E. coli cultured in LB for 24 h using (a) Pre-OPIOM and (b) Speed OPIOM. In (b), the insert zooms on the 0–5 h temporal window. Spatial averaging over a disk of 50 pixels at the center of the Pre-OPIOM and Speed-OPIOM images yielded the signals represented in the figures. For each imaging protocol, the average background level and its incertitude ( ± 1 σ ) were measured with non-transfected E. coli BL21 strains cultured in LB ( n = 8 ). They are displayed in the figures as dashed lines and gray areas, respectively. See Table S1 of Supplement 1 for the acquisition conditions.
Fig. 5.
Fig. 5. Images of Camelina sativa roots in soil obtained by fluorescence endomicroscopy. (a),(b) Pre-OPIOM and (c),(d) Speed-OPIOM images of a root from a genetically transformed plant expressing (a),(c) Dronpa-2 or a (b),(d) wild-type plant as a control. Scale bar: 100 μm. See Table S1 of Supplement 1 for the acquisition conditions. The signal levels in Pre-OPIOM and Speed OPIOM are displayed in linear scale at the right of the images.
Fig. 6.
Fig. 6. Speed OPIOM selectively discriminates RSFPs in fixed HeLa cells in the presence of a strong autofluorescent background. (a)–(c) Pre-OPIOM images; (d)–(i) Speed-OPIOM images collected under resonance conditions for (d)–(f) Dronpa-2 and for (g)–(i) Padron. Systems: Fixed HeLa cells expressing Lyn11-eGFP tagging the cell membrane, H2B-Dronpa-2 tagging the nucleus, and Mito-Padron tagging the mitochondria as indicated in (a)–(c). (a),(d),(g) HeLa cells expressing H2B-Dronpa and Lyn11-EGFP; (b),(e),(h) HeLa cells expressing Mito-Padron and Lyn11-EGFP; (c),(f),(i) HeLa cells expressing Mito-Padron and Lyn11-EGFP. Images (e) and (g) act as negative controls to show the absence of spectral interference of (i) Padron and EGFP when using the resonance condition of Dronpa-2 and of (ii) Dronpa-2 and EGFP when using the resonance condition of Padron. The signal level in Pre-OPIOM and Speed OPIOM is displayed on the linear scale at the right of each image. Scale bar: 100 μm. See Table S1 of Supplement 1 for the acquisition conditions.

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