Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Video-rate imaging of biological dynamics at centimetre scale and micrometre resolution

Abstract

Large-scale imaging of biological dynamics with high spatiotemporal resolution is indispensable to system biology studies. However, conventional microscopes have an inherent compromise between the achievable field of view and spatial resolution due to the space–bandwidth product theorem. In addition, a further challenge is the ability to handle the enormous amount of data generated by a large-scale imaging platform. Here, we break these bottlenecks by proposing the use of a flat–curved–flat imaging strategy, in which the sample plane is magnified onto a large spherical image surface and then seamlessly conjugated to multiple planar sensors. Our real-time, ultra-large-scale, high-resolution (RUSH) imaging platform operates with a 10 × 12 mm2 field of view, a uniform resolution of ~1.20 μm after deconvolution and a data throughput of 5.1 gigapixels per second. We use the RUSH platform to perform video-rate, gigapixel imaging of biological dynamics at centimetre scale and micrometre resolution, including brain-wide structural imaging and functional imaging in awake, behaving mice.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Schematic and characterization of a RUSH system.
Fig. 2: High-throughput calcium imaging of cardiac cellular ensembles and neuron ensembles.
Fig. 3: In vitro calcium imaging of spontaneous epileptiform activity in acute human cortical slices.
Fig. 4: In vivo brain-wide imaging of a Cx3Cr1-GFP mouse.
Fig. 5: Simultaneous imaging of vascular morphological dynamics and neural calcium signals in awake, behaving mice.
Fig. 6: In vivo brain-wide calcium imaging of adult C57BL/6 mice at dendritic resolution.

Data availability

The data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request.

References

  1. 1.

    Anderson, P. W. More is different. Science 177, 93–396 (1972).

    Google Scholar 

  2. 2.

    Aderem, A. Systems biology: its practice and challenges. Cell 121, 511–513 (2005).

    Google Scholar 

  3. 3.

    Ji, N., Freeman, J. & Smith, S. L. Technologies for imaging neural activity in large volumes. Nat. Neurosci. 19, 1154–1164 (2016).

    Google Scholar 

  4. 4.

    Jung, S. et al. Analysis of fractalkine receptor CX3CR1 function by targeted deletion and green fluorescent protein reporter gene insertion. Mol. Cell Biol. 20, 4106–4114 (2000).

    Google Scholar 

  5. 5.

    Valastyan, S. & Weinberg, R. A. Tumor metastasis: molecular insights and evolving paradigms. Cell 147, 275–292 (2011).

    Google Scholar 

  6. 6.

    Lohmann, A. W., Dorsch, R. G., Mendlovic, D., Zalevsky, Z. & Ferreira, C. Space–bandwidth product of optical signals and systems. J. Opt. Soc. Am. A 13, 470–473 (1996).

    ADS  Google Scholar 

  7. 7.

    Goda, K., Tsia, K. K. & Jalali, B. Serial time-encoded amplified imaging for real-time observation of fast dynamic phenomena. Nature 458, 1145–1149 (2009).

    ADS  Google Scholar 

  8. 8.

    McConnell, G. et al. A novel optical microscope for imaging large embryos and tissue volumes with sub-cellular resolution throughout. eLife 5, e18659 (2016).

    Google Scholar 

  9. 9.

    Sofroniew, N. J., Flickinger, D., King, J. & Svoboda, K. A large field of view two-photon mesoscope with subcellular resolution for in vivo imaging. eLife 5, e14472 (2016).

    Google Scholar 

  10. 10.

    Tian, L. et al. Computational illumination for high-speed in vitro Fourier ptychographic microscopy. Optica 2, 904–911 (2015).

    ADS  Google Scholar 

  11. 11.

    Zheng, G., Horstmeyer, R. & Yang, C. Wide-field, high-resolution Fourier ptychographic microscopy. Nat. Photon. 7, 739–745 (2013).

    ADS  Google Scholar 

  12. 12.

    Tsai, P. S. et al. Ultra-large field-of-view two-photon microscopy. Opt. Express 23, 13833–13847 (2015).

    ADS  Google Scholar 

  13. 13.

    Potsaid, B., Bellouard, Y. & Wen, J. T. Adaptive scanning optical microscope (ASOM): a multidisciplinary optical microscope design for large field of view and high resolution imaging. Opt. Express 13, 6504–6518 (2005).

    ADS  Google Scholar 

  14. 14.

    Werley, C. A., Chien, M. & Cohen, A. E. An ultrawidefield microscope for high-speed fluorescence imaging and targeted optogenetic stimulation. Bio. Opt. Express 8, 5794–5813 (2017).

    Google Scholar 

  15. 15.

    Stirman, J. N., Smith, I. T., Kudenov, M. W. & Smith, S. L. Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain. Nat. Biotechnol. 34, 857–862 (2016).

    Google Scholar 

  16. 16.

    Li, A. et al. Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330, 1404–1408 (2010).

    ADS  Google Scholar 

  17. 17.

    Economo, M. N. et al. A platform for brain-wide imaging and reconstruction of individual neurons. eLife 5, e10566 (2016).

    Google Scholar 

  18. 18.

    Luo, W., Zhang, Y., Feizi, A., Göröcs, Z. & Ozcan, A. Pixel super-resolution using wavelength scanning. Light Sci. Appl. 5, e16060 (2016).

    ADS  Google Scholar 

  19. 19.

    Grayson, T. P. Curved focal plane wide-field-of-view telescope design. Proc. SPIE 4849, 269–275 (2002).

    ADS  Google Scholar 

  20. 20.

    Brady, D. J. et al. Multiscale gigapixel photography. Nature 486, 386–389 (2012).

    ADS  Google Scholar 

  21. 21.

    Brady, D. J. et al. Parallel cameras. Optica 5, 127–137 (2018).

    ADS  Google Scholar 

  22. 22.

    Elad, M. & Yacov, H. A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur. IEEE Trans. Image Process 10, 1187–1193 (2001).

    ADS  MATH  Google Scholar 

  23. 23.

    Herron, T. J., Lee, P. & Jalife, J. Optical imaging of voltage and calcium in cardiac cells and tissues. Circ. Res. 110, 609–623 (2012).

    Google Scholar 

  24. 24.

    Ikegaya, Y., Bon-Jego, M. L. & Yuste, R. Large-scale imaging of cortical network activity with calcium indicators. Neurosci. Res. 52, 132–138 (2005).

    Google Scholar 

  25. 25.

    Gao, P. & Ganguli, S. On simplicity and complexity in the brave new world of large-scale neuroscience. Curr. Opin. Neurobiol. 32, 148–155 (2015).

    Google Scholar 

  26. 26.

    Kann, O. & Kovács, R. Mitochondria and neuronal activity. Am. J. Physiol. Cell Physiol. 292, C641–C657 (2007).

    Google Scholar 

  27. 27.

    Wenzel, M., Hamm, J. P., Peterka, D. S. & Yuste, R. Reliable and elastic propagation of cortical seizures in vivo. Cell Rep. 19, 2681–2693 (2017).

    Google Scholar 

  28. 28.

    Wang, Y., Goodfellow, M., Taylor, P. N. & Baier, G. Dynamic mechanisms of neocortical focal seizure onset. PLoS Comput. Biol. 10, e1003787 (2014).

    ADS  Google Scholar 

  29. 29.

    Logothetis, N. K. What we can do and what we cannot do with fMRI. Nature 453, 869–878 (2008).

    ADS  Google Scholar 

  30. 30.

    Wandell, B. A. What’s in your mind? Nat. Neurosci. 11, 384–385 (2008).

    Google Scholar 

  31. 31.

    Pantanowitz, L. et al. Review of the current state of whole slide imaging in pathology. J. Pathol. Inform. 2, 36 (2011).

    Google Scholar 

  32. 32.

    Dittrich, P. S. & Manz, A. Lab-on-a-chip: microfluidics in drug discovery. Nat. Rev. Drug Discov. 5, 210–218 (2006).

    Google Scholar 

  33. 33.

    Lim, D., Chu, K. K. & Mertz, J. Wide-field fluorescence sectioning with hybrid speckle and uniform-illumination microscopy. Opt. Lett. 33, 1819–1821 (2008).

    ADS  Google Scholar 

  34. 34.

    Ahrens, M. B., Orger, M. B., Robson, D. N., Li, J. M. & Keller, P. J. Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat. Methods 10, 413–420 (2013).

    Google Scholar 

  35. 35.

    Zhu, G., Howe, J. V., Durst, M., Zipfel, W. & Xu, C. Simultaneous spatial and temporal focusing of femtosecond pulses. Opt. Express 13, 2153–2159 (2005).

    ADS  Google Scholar 

  36. 36.

    Oron, D., Tal, E. & Silberberg, Y. Scanningless depth-resolved microscopy. Opt. Express 13, 1468–1476 (2005).

    ADS  Google Scholar 

  37. 37.

    Lin, X., Wu, J., Zheng, G. & Dai, Q. Camera array based light field microscopy. Biomed. Opt. Express 6, 3179–3189 (2015).

    Google Scholar 

  38. 38.

    Wilburn, B. et al. High performance imaging using large camera arrays. ACM Trans. Graph. 24, 765–776 (2005).

    Google Scholar 

  39. 39.

    Gomez, J., Potreau, D., Branka, J. & Raymond, G. Developmental changes in Ca2+ currents from newborn rat cardiomyocytes in primary culture. Pflügers Arch. 428, 241–249 (1994).

    Google Scholar 

  40. 40.

    Favaron, M. et al. Gangliosides prevent glutamate and kainate neurotoxicity in primary neuronal cultures of neonatal rat cerebellum and cortex. Proc. Natl Acad. Sci. USA 85, 7351–7355 (1988).

    ADS  Google Scholar 

  41. 41.

    Chen, T. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).

    ADS  Google Scholar 

  42. 42.

    Kong, L. et al. Continuous volumetric imaging via an optical phase-locked ultrasound lens. Nat. Methods 12, 759–762 (2015).

    Google Scholar 

  43. 43.

    Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).

    Google Scholar 

  44. 44.

    Giovannucci, A. et al. CaImAn an open source tool for scalable calcium imaging data analysis. eLife 8, e38173 (2019).

    Google Scholar 

  45. 45.

    Longair, M. H., Baker, D. A. & Armstrong, J. D. Simple Neurite Tracer: open source software for reconstruction, visualization and analysis of neuronal processes. Bioinformatics 27, 2453–2454 (2011).

    Google Scholar 

  46. 46.

    Julier, S. J. & Uhlmann, J. K. New extension of the Kalman filter to nonlinear systems. Proc. SPIE 3068, 182–194 (1997).

    ADS  Google Scholar 

Download references

Acknowledgements

We thank Y. Shu, S. Wang, Y. Li, Z. Guo, B. Zhou, W. Wang and Y. Jia for assistance with sample preparation. We also thank members of Dai’s group for helping with experiments and data analysis: X. Zhang, Y. Zhang, Y. Cheng, K. Liu, C. Zhuang, C. Qiao, Z. Zhao, X. Han, T. Zhou, Y. Zhang, X. Chen, W. Liu, T. Yan, G. Zhang, L. Wang, Y. Ma, X. Hu, J. Hu, T. Zhu, X. Chen, J. Bao and X. Zhang. We acknowledge P. Xi, L. Fang and G. Holtom for their assistance with editing the manuscript. This work is supported by the National Natural Science Foundation of China (61327902, 61671265, 61771287, 61741116, 61722110, 61831014, 31430038 and 81571275) and the Beijing Municipal Science & Technology Commission (Z181100003118014).

Author information

Affiliations

Authors

Contributions

J.F., J.S. and J.W. designed the system architecture. J.F. performed system integration and calibration, aided by F.C. and G.W. J.W. and H.X. conducted performance optimization. H.X. conducted most biological experiments, data capturing and analysis, and Y.S. led the optical and mechanical manufacturing. F.C. and G.W. developed the graphical user interface software. L.C. and G.J. contributed to the optimization of system design. Q.H. designed and conducted experiments on acute human cortical slices from epilepsy patients. T.L. and G.L. contributed to human tissue processing. L.K. conceived and supervised the biological experiments and data analysis, aided by H.X. Z.Z. designed the optical system, aided by J.F., J.S. and J.W. Q.D. conceived and supervised the project, and all authors contributed to the writing and editing of the manuscript.

Corresponding authors

Correspondence to Lingjie Kong, Zhenrong Zheng or Qionghai Dai.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Objective lens design, optical transfer function, point spread function, calcium imaging data.

Supplementary Video 1

Calcium imaging of cardiac cells with periodic behaviour.

Supplementary Video 2

Calcium imaging of cardiac cells with non-periodic dynamics.

Supplementary Video 3

Calcium imaging of neurons.

Supplementary Video 4

Calcium imaging of human cortical slices.

Supplementary Video 5

Calcium imaging of human cortical slices with single-cell resolution.

Supplementary Video 6

Tracking of immune cells.

Supplementary Video 7

Imaging of vascular and calcium signals in awake mice.

Supplementary Video 8

Calcium imaging of neural activity in mice.

Supplementary Video 9

Calcium imaging of cardiac tissue in a microfluidic device.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fan, J., Suo, J., Wu, J. et al. Video-rate imaging of biological dynamics at centimetre scale and micrometre resolution. Nat. Photonics 13, 809–816 (2019). https://doi.org/10.1038/s41566-019-0474-7

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing