Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy
Open accessAbstract
Intravital microscopy (IVM) emerged and matured as a powerful tool for elucidating pathways in biological processes. Although label-free multiphoton IVM is attractive for its non-perturbative nature, its wide application has been hindered, mostly due to the limited contrast of each imaging modality and the challenge to integrate them. Here we introduce simultaneous label-free autofluorescence-multiharmonic (SLAM) microscopy, a single-excitation source nonlinear imaging platform that uses a custom-designed excitation window at 1110 nm and shaped ultrafast pulses at 10 MHz to enable fast (2-orders-of-magnitude improvement), simultaneous, and efficient acquisition of autofluorescence (FAD and NADH) and second/third harmonic generation from a wide array of cellular and extracellular components (e.g., tumor cells, immune cells, vesicles, and vessels) in living tissue using only 14 mW for extended time-lapse investigations. Our work demonstrates the versatility and efficiency of SLAM microscopy for tracking cellular events in vivo, and is a major enabling advance in label-free IVM.
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IVM technique has been developed as an integration of methods including CLSM, multiphoton microscopy, and epifluorescence to dynamically evaluate tumor structure and physiological courses from tissue to subcellular level.
“IVM technique has been developed as an integration of methods including CLSM, multiphoton microscopy, and epifluorescence to dynamically evaluate tumor structure and physiological courses from tissue to subcellular level [149,150].”
From Approaches to Improve EPR-Based Drug Delivery for Cancer Therapy and Diagnosis (2023) · cites this paper as [150]
The Abstract and Results (‘In vivo tumor microenvironment by SLAM microscopy’; no page numbers provided) describe dynamic, cellular-scale imaging of living tumor tissue. But the platform combines multiphoton autofluorescence with second- and third-harmonic imaging; the cited paper does not describe it as an integration of CLSM, multiphoton microscopy, and epifluorescence. (LLM, conf=0.87)
Experimental — accuracy not yet measuredLeukocyte recruitment and clustering, their interaction with collagen fibers, adipocytes, and blood vessels, was concurrently captured with dynamic leukocyte behavior in a framework with the tumor or tissue microenvironment offering more insight into leukocyte behavior.
“In addition to detected leukocyte recruitment and clustering, their interaction with the collagen fibers, adipocytes, and blood vessels, was concurrently captured with the dynamic leukocyte behavior in a framework with the tumor or tissue microenvironment offering more insight into leukocyte behavior [150].”
From Approaches to Improve EPR-Based Drug Delivery for Cancer Therapy and Diagnosis (2023) · cites this paper as [150]
In addition to intravascular motion tracking of leukocytes, leukocyte locomotion in the extravascular region was imaged with time-lapse imaging.
“In addition to the intravascular motion tracking of leukocytes, leukocyte locomotion in the extravascular region was imaged with time-lapse imaging.”
From Approaches to Improve EPR-Based Drug Delivery for Cancer Therapy and Diagnosis (2023) · cites this paper as [150]
Label-free multiphoton IVM's widespread uses have been mired mainly due to inadequate contrast of each imaging technique and difficulties to combine them.
“Although label-free multiphoton IVM is striking for its nonperturbative character, its widespread uses have been mired mainly due to the inadequate contrast of each imaging technique and difficulties to combine them [150].”
From Approaches to Improve EPR-Based Drug Delivery for Cancer Therapy and Diagnosis (2023) · cites this paper as [150]
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Cites
Angiogenesis in cancer and other diseases
Carmeliet, P., & Jain, R. K. (2000) · Nature · doi:10.1038/35025220 · Cited by 9,070 · see citing works
Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome
Galon, J., Costes, A., Sanchez-Cabo, F., Kirilovsky, A., Mlecnik, B., Lagorce-Pagès, C., Tosolini, M., Camus, M., Berger, A., Wind, P., et al. (2006) · Science · doi:10.1126/science.1129139 · Cited by 6,516 · see citing works
Neutrophil recruitment and function in health and inflammation
Kolaczkowska, E., & Kubes, P. (2013) · Nature Reviews Immunology · doi:10.1038/nri3399 · Cited by 5,472 · see citing works
Regulatory T Cells and Immune Tolerance
Sakaguchi, S., Yamaguchi, T., Nomura, T., & Ono, M. (2008) · Cell · doi:10.1016/j.cell.2008.05.009 · Cited by 5,357 · see citing works
Nonlinear magic: multiphoton microscopy in the biosciences
Zipfel, W. R., Williams, R. M., & Webb, W. W. (2003) · Nature Biotechnology · doi:10.1038/nbt899 · Cited by 3,911 · see citing works
Understanding the Intersections between Metabolism and Cancer Biology
Heiden, M. G. V., & DeBerardinis, R. J. (2017) · Cell · doi:10.1016/j.cell.2016.12.039 · Cited by 2,316 · see citing works
Bissell, M. J., & Radisky, D. (2001) · Nature Reviews Cancer · doi:10.1038/35094059 · Cited by 2,180 · see citing works
From Monocytes to M1/M2 Macrophages: Phenotypical vs. Functional Differentiation
Italiani, P., & Boraschi, D. (2014) · Frontiers in Immunology · doi:10.3389/fimmu.2014.00514 · Cited by 2,067 · see citing works
Neutrophils in cancer: Neutral no more
Coffelt, S. B., Wellenstein, M. D., & de Visser, K. E. (2016) · Nature reviews. Cancer · doi:10.1038/nrc.2016.52 · Cited by 1,830 · see citing works
Zipfel, W. R., Williams, R. M., Christie, R. H., Nikitin, A. Y., Hyman, B. T., & Webb, W. W. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0832308100 · Cited by 1,691 · see citing works
In vivo three-photon microscopy of subcortical structures within an intact mouse brain
Horton, N. G., Wang, K., Kobat, D., Clark, C. G., Wise, F. W., Schaffer, C. B., & Xu, C. (2013) · Nature Photonics · doi:10.1038/nphoton.2012.336 · Cited by 1,505 · see citing works
Campagnola, P. J., & Loew, L. M. (2003) · Nature Biotechnology · doi:10.1038/nbt894 · Cited by 1,326 · see citing works
Two-Photon Imaging of Lymphocyte Motility and Antigen Response in Intact Lymph Node
Miller, M. J., Wei, S. H., Parker, I., & Cahalan, M. D. (2002) · Science · doi:10.1126/science.1070051 · Cited by 1,207 · see citing works
Multiphoton fluorescence excitation: new spectral windows for biological nonlinear microscopy.
Xu, C., Zipfel, W. R., Shear, J. B., et al. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.20.10763 · Cited by 1,171 · see citing works
Leukocyte rolling and extravasation are severely compromised in P selectin-deficient mice
Mayadas, T. N., Johnson, R. C., Rayburn, H., Hynes, R. O., & Wagner, D. D. (1993) · Cell · doi:10.1016/0092-8674(93)80055-j · Cited by 1,040 · see citing works
Skala, M. C., Riching, K. M., Gendron‐Fitzpatrick, A., Eickhoff, J. C., Eliceiri, K. W., White, J. G., & Ramanujam, N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0708425104 · Cited by 1,004 · see citing works
Neutrophils support lung colonization of metastasis-initiating breast cancer cells
Wculek, S. K., & Malanchi, I. (2015) · Nature · doi:10.1038/nature16140 · Cited by 996 · see citing works
Second harmonic generation microscopy for quantitative analysis of collagen fibrillar structure
Chen, X., Nadiarynkh, O., Plotnikov, S., & Campagnola, P. J. (2012) · Nature Protocols · doi:10.1038/nprot.2012.009 · Cited by 985 · see citing works
Neutrophil swarms require LTB4 and integrins at sites of cell death in vivo
Lämmermann, T., Afonso, P. V., Angermann, B., Wang, J. M., Kastenmüller, W., Parent, C. A., & Germain, R. N. (2013) · Nature · doi:10.1038/nature12175 · Cited by 937 · see citing works
Zoumi, A., Yeh, A. T., & Tromberg, B. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.172368799 · Cited by 872 · see citing works
Two-Photon Fluorescence Spectroscopy and Microscopy of NAD(P)H and Flavoprotein
Huang, S., Heikal, A. A., & Webb, W. W. (2002) · Biophysical Journal · doi:10.1016/s0006-3495(02)75621-x · Cited by 763 · see citing works
Neural activity triggers neuronal oxidative metabolism followed by astrocytic glycolysis
Kasischke, K. A., Vishwasrao, H. D., Fisher, P. J., Zipfel, W. R., & Webb, W. W. (2004) · Science · doi:10.1126/science.1096485 · Cited by 742 · see citing works
Prespecification and plasticity: shifting mechanisms of cell migration
Friedl, P. (2004) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2003.11.001 · Cited by 670 · see citing works
Imaging lipid bodies in cells and tissues using third-harmonic generation microscopy
Débarre, D., Supatto, W., Pena, A., Fabre, A., Tordjmann, T., Combettes, L., Schanne‐Klein, M., & Beaurepaire, E. (2005) · Nature Methods · doi:10.1038/nmeth813 · Cited by 580 · see citing works
Monocytes and Macrophages in Pregnancy and Pre-Eclampsia
Faas, M. M., Spaans, F., & de Vos, P. (2014) · Frontiers in Immunology · doi:10.3389/fimmu.2014.00298 · Cited by 495 · see citing works
Highly Nonlinear Photodamage in Two-Photon Fluorescence Microscopy
Hopt, A., & Neher, E. (2001) · Biophysical Journal · doi:10.1016/s0006-3495(01)76173-5 · Cited by 442 · see citing works
Inferring Social Status and Rich Club Effects in Enterprise Communication Networks
Dong, Y., Tang, J., Chawla, N. V., Lou, T., Yang, Y., & Wang, B. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119446 · Cited by 439 · see citing works
Measuring Serotonin Distribution in Live Cells with Three-Photon Excitation
Maiti, S., Shear, J. B., Williams, R. M., Zipfel, W. R., & Webb, W. W. (1997) · Science · doi:10.1126/science.275.5299.530 · Cited by 417 · see citing works
Cellular autofluorescence--is it due to flavins?
Benson, R. C., Meyer, R., Zaruba, M. E., et al. (1979) · Journal of Histochemistry & Cytochemistry · doi:10.1177/27.1.438504 · Cited by 414 · see citing works
Metabolic Shifts in Immunity and Inflammation
Kominsky, D. J., Campbell, E. L., & Colgan, S. P. (2010) · The Journal of Immunology · doi:10.4049/jimmunol.0903002 · Cited by 413 · see citing works
Atherton, A., & Born, G. V. R. (1972) · The Journal of Physiology · doi:10.1113/jphysiol.1972.sp009808 · Cited by 387 · see citing works
Lebrero‐Fernández, C., Bergström, J. H., Pelaseyed, T., & Bas‐Forsberg, A. (2016) · Frontiers in Immunology · doi:10.3389/fimmu.2016.00001 · Cited by 371 · see citing works
Optical Imaging Using Endogenous Contrast to Assess Metabolic State
Georgakoudi, I., & Quinn, K. P. (2012) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071811-150108 · Cited by 316 · see citing works
Stringari, C., Edwards, R. A., Pate, K. T., Waterman, M. L., Donovan, P. J., & Gratton, E. (2012) · Scientific Reports · doi:10.1038/srep00568 · Cited by 251 · see citing works
Third harmonic generation microscopy of cells and tissue organization
Weigelin, B., Bakker, G., & Friedl, P. (2016) · Journal of Cell Science · doi:10.1242/jcs.152272 · Cited by 240 · see citing works
From seeing to believing: labelling strategies for in vivo cell-tracking experiments
Progatzky, F., Dallman, M. J., & Celso, C. L. (2013) · Interface Focus · doi:10.1098/rsfs.2013.0001 · Cited by 232 · see citing works
Stain-free histopathology by programmable supercontinuum pulses
Tu, H., Liu, Y., Turchinovich, D., Marjanović, M., Lyngsø, J. K., Lægsgaard, J., Chaney, E. J., Zhao, Y., You, S., Wilson, W. L., et al. (2016) · Nature Photonics · doi:10.1038/nphoton.2016.94 · Cited by 231 · see citing works
Self-citationNeutrophil Adhesion and Activation under Flow
Zarbock, A., & Ley, K. F. (2008) · Microcirculation · doi:10.1080/10739680802350104 · Cited by 218 · see citing works
Scope and perspectives of intravital microscopy - bridge over from in vitro to in vivo
Menger, M. D., & Lehr, H. (1993) · Immunology Today · doi:10.1016/0167-5699(93)90179-o · Cited by 175 · see citing works
Imaging ROS signaling in cells and animals
Wang, X., Fang, H., Huang, Z., Shang, W. H., Hou, T., Cheng, A., & Cheng, H. (2013) · Journal of Molecular Medicine · doi:10.1007/s00109-013-1067-4 · Cited by 163 · see citing works
Paquin‐Proulx, D., Santos, B. A. N., Carvalho, K. I., Toledo-Barros, M. A. M., de Oliveira, A. K. B., Kokron, C. M., Kalil, J. E., Moll, M., Kallas, E. G., & Sandberg, J. K. (2013) · PLoS ONE · doi:10.1371/journal.pone.0075199 · Cited by 158 · see citing works
Multimodal nonlinear spectral microscopy based on a femtosecond Cr:forsterite laser
Chu, S., Chen, I.-H., Liu, T., et al. (2001) · Optics Letters · doi:10.1364/ol.26.001909 · Cited by 158 · see citing works
Südmeyer, T., Brunner, F., Innerhofer, E., et al. (2003) · Optics Letters · doi:10.1364/ol.28.001951 · Cited by 132 · see citing works
LaComb, R. B., Nadiarnykh, O., & Campagnola, P. J. (2008) · Biophysical Journal · doi:10.1529/biophysj.107.114405 · Cited by 129 · see citing works
Expanding Two-Photon Intravital Microscopy to the Infrared by Means of Optical Parametric Oscillator
Herz, J., Siffrin, V., Hauser, A. E., Brandt, A. U., Leuenberger, T., Radbruch, H., Zipp, F., & Niesner, R. A. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2009.10.035 · Cited by 100 · see citing works
Tracking CNS and systemic sources of oxidative stress during the course of chronic neuroinflammation
Mossakowski, A. A., Pohlan, J., Bremer, D., Lindquist, R. L., Millward, J. M., Bock, M., Pollok, K., Mothes, R., Viohl, L., Radbruch, M., et al. (2015) · Acta Neuropathologica · doi:10.1007/s00401-015-1497-x · Cited by 93 · see citing works
Intraoperative intravital microscopy permits the study of human tumour vessels
Fisher, D. T., Muhitch, J. B., Kim, M., Doyen, K. C., Bogner, P. N., Evans, S. S., & Skitzki, J. J. (2016) · Nature Communications · doi:10.1038/ncomms10684 · Cited by 88 · see citing works
Débarre, D., Olivier, N., Supatto, W., & Beaurepaire, E. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104250 · Cited by 80 · see citing works
Six-color intravital two-photon imaging of brain tumors and their dynamic microenvironment
Ricard, C., & Debarbieux, F. C. (2014) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2014.00057 · Cited by 75 · see citing works
Kilarski, W. W., Güç, E., Teo, J. C. M., Oliver, S. R., Lund, A. W., & Swartz, M. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057135 · Cited by 64 · see citing works
Tu, H., Liu, Y., Marjanović, M., Chaney, E. J., You, S., Zhao, Y., & Boppart, S. A. (2017) · Science Advances · doi:10.1126/sciadv.1600675 · Cited by 55 · see citing works
Self-citationThree-photon excited fluorescence imaging of unstained tissue using a GRIN lens endoscope
Huland, D. M., Charan, K., Ouzounov, D. G., et al. (2013) · Biomedical Optics Express · doi:10.1364/boe.4.000652 · Cited by 49 · see citing works
Imaging granularity of leukocytes with third harmonic generation microscopy
Tsai, C., Chen, Y., Wu, P., et al. (2012) · Biomedical Optics Express · doi:10.1364/boe.3.002234 · Cited by 39 · see citing works
Ongoing Oxidative Stress Causes Subclinical Neuronal Dysfunction in the Recovery Phase of EAE
Radbruch, H., Bremer, D., Guenther, R., Cseresnyés, Z., Lindquist, R. L., Hauser, A. E., & Niesner, R. A. (2016) · Frontiers in Immunology · doi:10.3389/fimmu.2016.00092 · Cited by 36 · see citing works
Describing Directional Cell Migration with a Characteristic Directionality Time
Loosley, A., O’Brien, X. M., Reichner, J. S., & Tang, J. X. (2015) · PLoS ONE · doi:10.1371/journal.pone.0127425 · Cited by 32 · see citing works
Optical Windows for Imaging the Metastatic Tumour Microenvironment in vivo
Kitamura, T., Pollard, J. W., & Vendrell, M. (2016) · Trends in biotechnology · doi:10.1016/j.tibtech.2016.05.001 · Cited by 32 · see citing works
High-power widely tunable sub-20fs Gaussian laser pulses for ultrafast nonlinear spectroscopy
Metzger, B., Steinmann, A., & Giessen, H. W. (2011) · Optics Express · doi:10.1364/oe.19.024354 · Cited by 26 · see citing works
Huang, J.-Y., Guo, L., Wang, J.-Z., Li, T.-C., Lee, H., Chiu, P.-K., Peng, L., & Liu, T. (2017) · Journal of Biomedical Optics · doi:10.1117/1.jbo.22.3.036008 · Cited by 24 · see citing works
Imaging: Cancer caught in the act
Lok, C. (2014) · Nature · doi:10.1038/509148a · Cited by 8 · see citing works
Metabolic Imaging of Colon Cancer Tumors In Vivo by Phasor Fluorescence Lifetime Microscopy of NADH
Stringari, C., Pate, K. T., Edwards, R. A., et al. (2013) · Biophysical Journal · doi:10.1016/j.bpj.2012.11.1902 · Cited by 5 · see citing works
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Approaches to Improve EPR-Based Drug Delivery for Cancer Therapy and Diagnosis
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“Although label-free multiphoton IVM is striking for its nonperturbative character, its widespread uses have been mired mainly due to the inadequate contrast of each imaging technique and difficulties to combine them [150].”
BackgroundMethodInfluentialImproving nanotherapy delivery and action through image-guided systems pharmacology
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Self-citation
- Authors
- You, S., Tu, H., Chaney, E. J., Sun, Y., Zhao, Y., Bower, A. J., Liu, Y.-Z., Marjanovic, M., Sinha, S., Pu, Y., & Boppart, S. A.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Corresponding author
- Tu, Haohua
- Boppart, Stephen A.
- ORCID
- Venue
- Nature Communications
- Published
- 2018-05-29
- Volume
- 9
- Issue
- 1
- Pages
- 2125-2125
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC5974075
- OpenAlex
- W2805533175
- Cited by
- 271
- References
- 60
- Citations by year
- 2026: 28 · 2025: 29 · 2024: 48 · 2023: 31 · 2022: 41 · 2021: 38 · 2020: 25 · 2019: 24 · 2018: 6
- FWCI
- 12.03
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health
- National Cancer Institute (R01CA213149, R01CA166309)
- National Institute of Biomedical Imaging and Bioengineering (R01EB023232)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Keywords
- intravital microscopy, label-free imaging, autofluorescence, second harmonic generation, third harmonic generation, nonlinear optical imaging, FAD, NADH, cancer cells, immune cells, vesicles, blood vessels, time-lapse imaging
- MeSH terms
- Intravital Microscopy, Animals, Cell Movement, Female, Leukocytes, Rats, Inbred WF, Mammary Neoplasms, Animal, Imaging, Three-Dimensional, Microscopy, Fluorescence, Multiphoton, Rats, Cell Tracking, Tumor Microenvironment
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