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Non-invasive In Vivo Brain Astrogenesis and Astrogliosis Quantification Using a Far-red E2-Crimson Transgenic Reporter Mouse

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Abstract

Despite the adaptation of major clinical imaging modalities for small animals, optical bioluminescence imaging technology is the main approach readily reporting gene activity. Yet, in vivo bioluminescence monitoring requires the administration and diffusion of a substrate to the tissues of interest, resulting in experimental variability, high reagent cost, long acquisition time, and stress to the animal. In our study, we avoid such issues upon generating a new transgenic mouse (GFAP-E2crimson) expressing the far-red fluorescent protein E2-crimson under the control of the glial fibrillary acidic protein (GFAP) promoter. Using microscopy, we validated the selective expression of the reporter in the astrocyte cell population and by non-invasive in vivo fluorescence imaging its detection through the scalps and skulls of live animals. In addition, we performed a longitudinal study validating by in vivo imaging that the E2-crimson fluorescence signal is up-regulated, in pups during astrogenesis and in adult mice during astrogliosis upon kainic acid administration. Furthermore, upon crossing GFAP-E2crimson transgenic with 5XFAD Alzheimer’s disease mice model, we were able to quantify the chronic inflammation triggered by amyloid deposit and aging over 18 months. As many diseases and conditions can trigger neuroinflammation, we believe that the GFAP-E2crimson reporter mice model delivers tremendous value for the non-invasive quantification of astrogliosis responses in living animals.

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Data Availability

Source data of graphs plotted in Figs. 1, 3, and 4 and Supplementary Figs. 1, 2, and 12 are available as source data files. Other data are available from the corresponding author upon reasonable request.

References

  1. Lauber DT, Fülöp A, Kovács T, Szigeti K, Máthé D, Szijártó A (2017) State of the art in vivo imaging techniques for laboratory animals. Lab Anim 51(5):465–478. https://doi.org/10.1177/0023677217695852

    Article  CAS  Google Scholar 

  2. Dall’Ara E et al (2016) Longitudinal imaging of the ageing mouse. Mech Ageing Dev. 160:93–116. https://doi.org/10.1016/j.mad.2016.08.001

    Article  PubMed  Google Scholar 

  3. Sato A, Klaunberg B, Tolwani R (2004) In vivo bioluminescence imaging. Comp Med 54(6):631–634

    CAS  PubMed  Google Scholar 

  4. Luker KE, Luker GD (2010) Bioluminescence imaging of reporter mice for studies of infection and inflammation. Antiviral Res 86(1):93–100. https://doi.org/10.1016/j.antiviral.2010.02.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Patterson AP, Booth SA, Saba R, Patterson AP, Booth SA, Saba R (2014) The emerging use of in vivo optical imaging in the study of neurodegenerative diseases. Biomed Res Int 2014:1–14. https://doi.org/10.1155/2014/401306

    Article  CAS  Google Scholar 

  6. Badr CE (2014) Bioluminescence imaging: basics and practical limitations. Methods Mol Biol Clifton 1098(August). https://doi.org/10.1007/978-1-62703-718-1

  7. Aswendt M, Adamczak J, Couillard-Despres S, Hoehn M (2013) Boosting bioluminescence neuroimaging: an optimized protocol for brain studies. PLoS One 8(2):e55662. https://doi.org/10.1371/journal.pone.0055662

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Leblond F, Davis SC, Valdés PA, Pogue BW (2010) Pre-clinical whole-body fluorescence imaging: Review of instruments, methods and applications. J Photochem Photobiol B 98(1):77–94. https://doi.org/10.1016/j.jphotobiol.2009.11.007

    Article  CAS  PubMed  Google Scholar 

  9. Luker KE et al (2015) Comparative study reveals better far-red fluorescent protein for whole body imaging. Sci Rep 5:1–9. https://doi.org/10.1038/srep10332

    Article  CAS  Google Scholar 

  10. Kredel S et al (2008) Optimized and far-red-emitting variants of fluorescent protein eqFP611. Chem Biol 15(3):224–233. https://doi.org/10.1016/j.chembiol.2008.02.008

    Article  CAS  PubMed  Google Scholar 

  11. Richie CT et al (2017) Near-infrared fluorescent protein iRFP713 as a reporter protein for optogenetic vectors, a transgenic Cre-reporter rat, and other neuronal studies. J Neurosci Methods 284:1–14. https://doi.org/10.1016/j.jneumeth.2017.03.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Montecinos-Franjola F, Lin JY, Rodriguez EA (2020) Fluorescent proteins for in vivo imaging, where’s the biliverdin? Biochem Soc Trans 48(6):2657–2667. https://doi.org/10.1042/BST20200444

    Article  CAS  PubMed  Google Scholar 

  13. Strack RL, Hein B, Bhattacharyya D, Hell SW, Keenan RJ, Glick BS (2009) A rapidly maturing far-red derivative of DsRed-Express2 for whole-cell labeling. Biochemistry 48(35):8279–8281. https://doi.org/10.1021/bi900870u

    Article  PubMed  Google Scholar 

  14. Zhu L, Ramboz S, Hewitt D, Boring L, Grass DS, Purchio AF (2004) Non-invasive imaging of GFAP expression after neuronal damage in mice. Neurosci Lett 367(2):210–212. https://doi.org/10.1016/j.neulet.2004.06.020

    Article  CAS  PubMed  Google Scholar 

  15. Lalancette-Hbert M, Phaneuf D, Soucy G, Weng YC, Kriz J (2009) Live imaging of toll-like receptor 2 response in cerebral ischaemia reveals a role of olfactory bulb microglia as modulators of inflammation. Brain 132(4):940–954. https://doi.org/10.1093/brain/awn345

    Article  Google Scholar 

  16. Inoue Y, Kiryu S, Watanabe M, Tojo A, Ohtomo K (2010) Timing of imaging after D-luciferin injection affects the longitudinal assessment of tumor growth using in vivo bioluminescence imaging. Int J Biomed Imaging 2010. https://doi.org/10.1155/2010/471408

  17. Oakley H et al (2006) Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s Disease mutations: potential factors in amyloid plaque formation. J Neurosci 26(40):10129–10140. https://doi.org/10.1523/JNEUROSCI.1202-06.2006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lee Y, Messing A, Su M, Brenner M (2008) GFAP promoter elements required for region-specific and astrocyte-specific expression. Glia 56(5):481–493. https://doi.org/10.1002/glia.20622

    Article  PubMed  Google Scholar 

  19. Griffin JM, Fackelmeier B, Fong DM, Mouravlev A, Young D, O’Carroll SJ (2019) Astrocyte-selective AAV gene therapy through the endogenous GFAP promoter results in robust transduction in the rat spinal cord following injury. Gene Ther 26(5):198–210. https://doi.org/10.1038/s41434-019-0075-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Nolte C et al (2001) GFAP promoter-controlled EGFP-expressing transgenic mice: a tool to visualize astrocytes and astrogliosis in living brain tissue. Glia 33(1):72–86. https://doi.org/10.1002/1098-1136(20010101)33:1%3c72::AID-GLIA1007%3e3.0.CO;2-A

    Article  CAS  PubMed  Google Scholar 

  21. Kostoula C et al (2018) Development of in vivo imaging tools for investigating astrocyte activation in epileptogenesis. Mol Neurobiol 55(5):4463–4472. https://doi.org/10.1007/s12035-017-0660-x

    Article  CAS  PubMed  Google Scholar 

  22. Ho G, Zhang C, Zhuo L (2007) Non-invasive imaging of transgenic GFP expression in neonatal mouse brain. Photonic Ther Diagnostics III 6424:642425. https://doi.org/10.1117/12.700066

    Article  CAS  Google Scholar 

  23. Nolte C (2016) GFAP promoter-controlled EGFP- expressing transgenic mice : a tool to visualize astrocytes and astrogliosis in living brain tissue 86(November):72–86. https://doi.org/10.1002/1098-1136(20010101)33

  24. Daschil N, Humpel C (2016) Green-fluorescent protein+ astrocytes attach to beta-amyloid plaques in an Alzheimer mouse model and are sensitive for clasmatodendrosis. Front Aging Neurosci 8(APR):1–6. https://doi.org/10.3389/fnagi.2016.00075

  25. Farhy-Tselnicker I, Allen NJ (2018) Astrocytes, neurons, synapses: a tripartite view on cortical circuit development. Neural Dev 13(1):1–12. https://doi.org/10.1186/s13064-018-0104-y

    Article  CAS  Google Scholar 

  26. Youngjin Lee MB, Su M, Messing A (2006) Astrocyte heterogeneity revealed by expression of a GFAP-LacZ transgene. Glia. https://doi.org/10.1002/glia

  27. Zhang X-M, Zhu J (2011) Kainic acid-induced neurotoxicity: targeting glial responses and glia-derived cytokines. Curr Neuropharmacol 9:388–398. https://doi.org/10.2174/157015911795596540

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kang K-K et al (2020) A comparative study of the phenotype with kainic acid-induced seizure in DBA/2 mice from three different sources. Lab Anim Res 36(1):1–7. https://doi.org/10.1186/s42826-020-00072-y

    Article  Google Scholar 

  29. Mccord MC, Lorenzana A, Bloom CS, Chancer ZO, Schauwecker PE (2008) Effect of age on kainate-induced seizure severity and cell death. Neuroscience 154(3):1143–1153. https://doi.org/10.1016/j.neuroscience.2008.03.082

    Article  CAS  PubMed  Google Scholar 

  30. Ho G, Zhang C, Zhuo L (2007) Non-invasive fluorescent imaging of gliosis in transgenic mice for profiling developmental neurotoxicity. https://doi.org/10.1016/j.taap.2007.01.023

  31. Watts JC, Giles K, Grillo SK, Lemus A, DeArmond SJ, Prusiner SB (2011) Bioluminescence imaging of Abeta deposition in bigenic mouse models of Alzheimer’s disease. Proc Natl Acad Sci U S A 108(6):2528–2533. https://doi.org/10.1073/pnas.1019034108

    Article  PubMed  PubMed Central  Google Scholar 

  32. Forner S, Kawauchi S, Balderrama-Gutierrez G et al (2021) Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease. Sci Data 8:270. https://doi.org/10.1038/s41597-021-01054-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Manji Z, Rojas A, Wang W, Dingledine R, Varvel NH, Ganesh T (2019) 5xFAD mice display sex-dependent inflammatory gene induction during the prodromal stage of alzheimer’s disease. J Alzheimers Dis. 70(4):1259–1274. https://doi.org/10.3233/JAD-180678

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Hillman EMC et al (2011) In vivo optical imaging and dynamic contrast methods for biomedical research. Philos Trans A Math Phys Eng Sci 369(1955):4620–4643. https://doi.org/10.1098/rsta.2011.0264

    Article  PubMed  PubMed Central  Google Scholar 

  35. Jacques SL (2013) Optical properties of biological tissues: a review. Phys Med Biol 58(14):5007–5008. https://doi.org/10.1088/0031-9155/58/14/5007

    Article  Google Scholar 

  36. Middeldorp J, Hol EM (2011) GFAP in health and disease. Prog Neurobiol 93(3):421–443. https://doi.org/10.1016/j.pneurobio.2011.01.005

    Article  CAS  PubMed  Google Scholar 

  37. Isomura M, Yamada K, Noguchi K, Nishizono A (2017) Near-infrared fluorescent protein iRFP720 is optimal for in vivo fluorescence imaging of rabies virus infection. J Gen Virol 98(11):2689–2698. https://doi.org/10.1099/jgv.0.000950

    Article  CAS  PubMed  Google Scholar 

  38. Overhaus M, Moore BA, Barbato JE, Behrendt FF, Doering JG, Bauer AJ (2006) Biliverdin protects against polymicrobial sepsis by modulating inflammatory mediators. Am J Physiol - Gastrointest Liver Physiol 290(4):695–703. https://doi.org/10.1152/ajpgi.00152.2005

    Article  CAS  Google Scholar 

  39. Dunn-Meynell AA, Dowling P, Marchese M, Rodriguez E, Blumberg B, Choi Y-B, Gaindh D, Lu W (2019) In vivo bioluminescence imaging used to monitor disease activity and therapeutic response in a mouse model of tauopathy. Front Aging Neurosci 11:252. https://doi.org/10.3389/fnagi.2019.00252

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Sofroniew MV, Vinters HV (2010) Astrocytes: biology and pathology. Acta Neuropathol 119(1):7–35. https://doi.org/10.1007/s00401-009-0619-8

    Article  PubMed  Google Scholar 

  41. Luo J, Ho P, Steinman L, Wyss-Coray T (2008) Bioluminescence in vivo imaging of autoimmune encephalomyelitis predicts disease. J Neuroinflammation 5:6. https://doi.org/10.1186/1742-2094-5-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Sofroniew MV (2015) Astrogliosis perspectives. Cold Spring Harb Perspect Biol 7(2):1–16. https://doi.org/10.1101/cshperspect.a020420

    Article  Google Scholar 

  43. Johnson ECB et al (2020) Large-scale proteomic analysis of Alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation. Nat Med 26(5):769–780. https://doi.org/10.1038/s41591-020-0815-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hanslik KL, Marino KM, Ulland TK (2021) Modulation of glial function in health, aging, and neurodegenerative disease. Front Cell Neurosci 15(August):1–18. https://doi.org/10.3389/fncel.2021.718324

    Article  CAS  Google Scholar 

  45. Callahan MJ, Lipinski WJ, Bian F, Durham RA, Pack A, Walker LC (2001) Augmented senile plaque load in aged female β-amyloid precursor protein-transgenic mice. Am J Pathol 158(3):1173–1177. https://doi.org/10.1016/S0002-9440(10)64064-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Biechele G et al (2020) Glial activation is moderated by sex in response to amyloidosis but not to tau pathology in mouse models of neurodegenerative diseases. J Neuroinflammation 17(1):1–10. https://doi.org/10.1186/s12974-020-02046-2

    Article  CAS  Google Scholar 

  47. Matias I, Morgado J, Gomes FCA (2019) Astrocyte Heterogeneity: impact to brain aging and disease. Front Aging Neurosci 11(March):1–18. https://doi.org/10.3389/fnagi.2019.00059

    Article  CAS  Google Scholar 

  48. Burda JE, Sofroniew MV (2014) Reactive gliosis and the multicellular response to CNS damage and disease. Neuron 81(2):229–248. https://doi.org/10.1016/j.neuron.2013.12.034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors would like to express their very great appreciation to Dr. William T. Dauer, M.D for his valuable and constructive suggestions as well as to thank Dr. Connor Wood, Ph.D. for his editing inputs.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) [NRF-2017M3A9G6068257]. This research was supported by a grant of the Medical Cluster R&D Support Project through the Daegu-Gyengbuk Medical Innovation Foundation (DGMIF), funded by the Ministry of Health & Welfare, Republic of Korea [grant number: HT13C1015].

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Authors and Affiliations

  1. Technology Development Platform, Institut Pasteur Korea, Seongnam, 13488, Republic of Korea

    Maylis Boitet, Hyeju Eun & Regis Grailhe

  2. Department of Biological Chemistry, IPK Campus, Korea University of Science and Technology, 217 Gajeong-ro Yuseong-gu, Daejeon, 34113, Republic of Korea

    Maylis Boitet & Regis Grailhe

  3. Korea Brain Research Institute, Daegu, Republic of Korea

    Taekwan Lee

  4. Screening Discovery Platform, Institut Pasteur Korea, Seongnam, 13488, Republic of Korea

    Jiho Kim

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Contributions

Maylis Boitet, Hyeju Eun and Jiho Kim participated in the experimental studies. Maylis Boitet analyzed data and wrote the draft of the manuscript. Taekwan Lee participated in the mice husbandry. Regis Grailhe designed and supervised the study and wrote the manuscript. All authors read and approved the final manuscript.

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Correspondence to Regis Grailhe.

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All animal protocols were approved by the Institutional Animal Care and Use Committee of Institut Pasteur Korea (approved protocol number IPK-16001, IPK-17007, and IPK-18005).

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ESM 1

(PNG 413 kb) Fluorescence excitation and emission spectra of common far-red fluorescent probes used for in vivo optical imaging. (a) Fluorescence excitation spectra of 7 bright far-red fluorescent proteins, highlighting protein excitability at 633 nm (Wavelength used for in vivo and ex vivo imaging). Data obtained from https://www.fpbase.org/. (b) Fluorescence emission spectra of 7 bright far-red fluorescent proteins. Data obtained from https://www.fpbase.org/. (c) Summary table of excitation and emission wavelengths used in this study according to fluorescence imaging systems

High resolution image (TIF 18073 kb)

ESM 2

(PNG 254 kb) Daily quantification of the E2-crimson fluorescence probe in GFAP-E2crimson mice. (a) 2D FLI fluorescent quantification of E2-Crimson expression in adult females (n=5) and males (n=3) during 30 days. (b) Summary of the E2-crimson average intensity and standard deviation measured for each animal over a month

High resolution image (TIF 18079 kb)

ESM 3

(PNG 1908 kb) Postmortem tissue distribution of E2-Crimson protein in coronal brain slices of GFAP-E2crimson transgenic mice, 5 days after injection of kainic acid or saline. Coronal brain slices (30 µm) from a GFAP-E2crimson mouse arranged in a rostral-to-caudal manner were directly visualized by fluorescent microscopy (Operetta, Perkin Elmer) and show the major increase in E2-crimson-positive cells in the isocortex, hippocampus and thalamus after kainic acid administration (black labeling)

High resolution image (TIF 18085 kb)

ESM 4

(PNG 2653 kb) Postmortem tissue distribution of E2-Crimson protein, GFAP and IBA1 markers in GFAP-E2crimson transgenic mouse,after kainic acid administration. Coronal brain sections (30 µm) show E2-Crimson–positive cells (in red), counterstained (in green) with anti-IBA1 (microglia) in left, or anti-GFAP (astrocyte) antibodies, in right. Strong colocalization of E2-crimson and GFAP staining in activated astrocytes was mostly found in the isocortex, hippocampus, and thalamus and are highlighted in the boxes 1, 2 3 (250 µm × 250 µm)

High resolution image (TIF 18115 kb)

ESM 5

(PNG 2854 kb) High magnification of hippocampus showing tissue distribution of E2-Crimson protein, GFAP and IBA1 markers in saline and kainic acid injected mouse using confocal microscopy

High resolution image (TIF 18091 kb)

ESM 6

(PNG 2399 kb) Postmortem tissue distribution of GFAP and E2-Crimson proteins, in GFAP-E2crimson transgenic mice brain tissues, after injection of saline or kainic acid. GFAP and E2-crimson proteins are found to be upregulated in cortex, hippocampus and thalamus upon kainic acid injection

High resolution image (TIF 18047 kb)

ESM 7

(PNG 2240 kb) Postmortem tissue distribution of E2-Crimson protein in coronal brain slices of aged 17-months old GFAP-E2crimson/CTRL and GFAP-E2crimson/5xFAD transgenic mice. Coronal brain slices (30 µm) from a GFAP-E2crimson mouse arranged in a rostral-to-caudal manner were directly visualized by fluorescent microscopy (Operetta, Perkin Elmer) and show the increase in E2-crimson-positive cells in the isocortex, and thalamus ain GFAP-E2crimson/5xFAD compared to control (black labeling)

High resolution image (TIF 18053 kb)

ESM 8

(PNG 2417 kb) Postmortem tissue distribution of E2-Crimson protein, GFAP and IBA1 markers in aged 17 months-old GFAP-E2crimson/CTRL mouse. Coronal brain sections (30 µm) show E2-Crimson–positive cells (in red), counterstained (in green) with anti-IBA1 (microglia) in left, or anti-GFAP (astrocyte) antibodies, in right. Colocalization of E2-crimson and GFAP staining in activated astrocytes could be found in the isocortex, hippocampus, and thalamus and are highlighted in the boxes 1, 2 3 (250 µm × 250 µm)

High resolution image (TIF 18047 kb)

ESM 9

(PNG 2409 kb) Postmortem tissue distribution of E2-Crimson protein, GFAP and IBA1 markers in aged 17 months-old GFAP-E2crimson/5xFAD mouse. Coronal brain sections (30 µm) show E2-Crimson–positive cells (in red), counterstained (in green) with anti-IBA1 (microglia) in left, or anti-GFAP (astrocyte) antibodies, in right. Strong colocalization of E2-crimson and GFAP staining in activated astrocytes was found in the isocortex, hippocampus, and thalamus and are highlighted in the boxes 1, 2 3 (250 µm × 250 µm)

High resolution image (TIF 18037 kb)

ESM 10

(PNG 2343 kb) High magnification of hippocampus showing tissue distribution of E2-Crimson protein, GFAP and IBA1 markers in 17 months-old GFAP-E2crimson/5xFAD mouse

High resolution image (TIF 18064 kb)

ESM 11

(PNG 2616 kb) Postmortem tissue distribution of E2-Crimson protein and amyloid plaques in coronal brain slices of aged 17 months-old GFAP-E2crimson/5xFAD and GFAP-E2crimson/CTRL mice. (a) Coronal brain slices (30 µm) were directly visualized under a 10X magnification using conventional epi-fluorescence microscopy to evaluate E2-Crimson and amyloid plaques distribution in 3 distinct GFAP-E2crimson/5xFAD and GFAP-E2crimson/CTRL mice. Overexpression of E2-Crimson correlates with the high density of amyloid plaques. (b) Coronal brain section (30 µm) of GFAP-E2crimson/5xFAD showing E2-Crimson–positive cells (in red) and amyloid plaques (in green). Reactive astrocytes over-expressing E2-crimson found in the vicinity of amyloid plaques in the isocortex, hippocampus, and thalamus as highlighted in the boxes 1, 2 3 (650 µm × 650 µm)

High resolution image (TIF 18062 kb)

ESM 12

(PNG 973 kb) In vivo fluorescent imaging of FVB wild-type and GFAP-E2crimson transgenic mouse using other fluorescent imaging modalities. (a) In vivo 2D epi-fluorescence imaging (2D FLI) of aged FVB wild-type and hemizygous mice captured by the low-cost fluorescent in vivo imaging system FOBI (NeoScience). (b) In vivo 2D epi-fluorescence imaging (2D FLI) of aged FVB wild-type and hemizygous mice captured by Newton 7.0 instrumentation (Vilber), with a 300-ms exposure, equipped with a cooled CCD camera. (c) Intensity plots of signal dynamics in GFAP-E2crimsonand FVB mice using FOBI system. (d) Intensity plots of signal dynamics in GFAP-E2crimson and FVB miceusing Newton 7.0 system

High resolution image (TIF 18044 kb)

12035_2022_2997_MOESM13_ESM.docx

Supplementary file1 (DOCX 13 KB) Comparison of characteristics among common bright far-red fluorescent probes used for in vivo optical imaging. Comparison of excitation peak, emission peak, extinction coefficient (EC), quantum yield (QY), brightness, pKa, maturation, cofactor requirement, and protein excitability at 633 nm among eight far-red fluorescent proteins. Data obtained from https://www.fpbase.org/

Supplementary file2 (XLSX 133 KB)

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Boitet, M., Eun, H., Lee, T. et al. Non-invasive In Vivo Brain Astrogenesis and Astrogliosis Quantification Using a Far-red E2-Crimson Transgenic Reporter Mouse. Mol Neurobiol 59, 6740–6753 (2022). https://doi.org/10.1007/s12035-022-02997-y

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