Paper Roundup – April 2014

  • A new buffer system for stabilizing single molecule fluorescence and preventing blinking and bleaching using a redox system combined with a thiol. [1]
  • A paper characterizing small carbon dots as fluorescent reporters. Interestingly they can be excited at multiple different wavelengths, giving rise to different emission spectra. [2]
  • Bright upconverting nanoparticles for single molecule imaging. [3]
  • A review of environmentally sensitive small molecule dyes. [4]
  • A review of fluorescence fluctuation approaches, such as image correlation spectroscopy. [5]
  • A two photon version of multifocal SIM for super-resolution imaging in thick tissues. [6]
  • A review of and protocol for constructing a Bessel-beam light-sheet system. [7]
  • An advanced compressed sensing approach to reconstructing localization microscopy data [8]
  • A protocol for intensity calibration and flat-field correction for fluorescence microscopes [9]
  • A low-cost single color localization microscopy system using a single diode laser and an arc lamp for activation [10]
  • A new algorithm for structured illumination reconstruction at low light levels [11]
  • Optimized scan and tube lenses for confocal microscopes [12]
  • A DMD-based multi-angle TIRF illuminator [13]
  • A FRET sensor for abscisic acid in plants; the interesting thing about this paper is the systematic optimization of the FRET biosensor by testing multiple fluorescent proteins and linkers. [14]
  • A novel point-spread function engineering approach for isotropic 3D localization of single molecules over large thicknesses [15]
  • A very impressive adaptive optics confocal system from the Betzig group. It uses a two-photon excited guide star to correct the wavefront across large scan areas and enables diffraction limited one-photon confocal imaging to 200 μm deep. [16]
  • Stimulated Raman scattering imaging of alkyne-labeled molecules in live cells [17]
  • Rotating polarization excitation and polarization dependent stimulated depletion used to generate super-resolution images in widefield microscopy [18]
  • Single molecule imaging in C. elegans using near-TIRF imaging and GFP RNAi to reduce the expression level, combined with an analysis of replacement of photobleached GFPs to infer transport kinetics. [19]
  • A good review on labeling and imaging methods for whole-embryo imaging [20]
  • A new brain clearing procedure for imaging whole mouse brains [21]
  • Multiview deconvolution for fusing light sheet images taken from different direction [22]
  • A simple, lens-free, holographic imaging system for imaging cell migration over large fields of view [23]
  • A note about the (in)applicability of structured illumination to coherent imaging [24]
  • An Airy beam light sheet microscope [25]
  • ThunderSTORM, an ImageJ plugin for analysis and simulation of 2D/3D localization microscopy data (code and plugin here) [26]


  1. P. Holzmeister, A. Gietl, and P. Tinnefeld, "Geminate Recombination as a Photoprotection Mechanism for Fluorescent Dyes", Angewandte Chemie International Edition, vol. 53, pp. 5685-5688, 2014.
  2. G.E. LeCroy, S.K. Sonkar, F. Yang, L.M. Veca, P. Wang, K.N. Tackett, J. Yu, E. Vasile, H. Qian, Y. Liu, P.(. Luo, and Y. Sun, "Toward Structurally Defined Carbon Dots as Ultracompact Fluorescent Probes", ACS Nano, vol. 8, pp. 4522-4529, 2014.
  3. D.J. Gargas, E.M. Chan, A.D. Ostrowski, S. Aloni, M.V.P. Altoe, E.S. Barnard, B. Sanii, J.J. Urban, D.J. Milliron, B.E. Cohen, and P.J. Schuck, "Engineering bright sub-10-nm upconverting nanocrystals for single-molecule imaging", Nature Nanotechnology, vol. 9, pp. 300-305, 2014.
  4. Z. Yang, J. Cao, Y. He, J.H. Yang, T. Kim, X. Peng, and J.S. Kim, "Macro-/micro-environment-sensitive chemosensing and biological imaging", Chem. Soc. Rev., vol. 43, pp. 4563-4601, 2014.
  5. N. Bag, and T. Wohland, "Imaging Fluorescence Fluctuation Spectroscopy: New Tools for Quantitative Bioimaging", Annual Review of Physical Chemistry, vol. 65, pp. 225-248, 2014.
  6. M. Ingaramo, A.G. York, P. Wawrzusin, O. Milberg, A. Hong, R. Weigert, H. Shroff, and G.H. Patterson, "Two-photon excitation improves multifocal structured illumination microscopy in thick scattering tissue", Proceedings of the National Academy of Sciences, vol. 111, pp. 5254-5259, 2014.
  7. L. Gao, L. Shao, B. Chen, and E. Betzig, "3D live fluorescence imaging of cellular dynamics using Bessel beam plane illumination microscopy", Nature Protocols, vol. 9, pp. 1083-1101, 2014.
  8. J. Min, C. Vonesch, H. Kirshner, L. Carlini, N. Olivier, S. Holden, S. Manley, J.C. Ye, and M. Unser, "FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data", Scientific Reports, vol. 4, 2014.
  9. M. Model, "Intensity Calibration and Flat-Field Correction for Fluorescence Microscopes", Current Protocols in Cytometry, vol. 68, pp. 10.14.1-10.14.10, 2014.
  10. Z. Yuan, J. Sun, R. Zhai, X. Li, and Z. Shao, "Mercury arc lamp based super-resolution imaging with conventional fluorescence microscopes", Micron, vol. 59, pp. 24-27, 2014.
  11. K. Chu, P.J. McMillan, Z.J. Smith, J. Yin, J. Atkins, P. Goodwin, S. Wachsmann-Hogiu, and S. Lane, "Image reconstruction for structured-illumination microscopy with low signal level", Optics Express, vol. 22, pp. 8687, 2014.
  12. A. Negrean, and H.D. Mansvelder, "Optimal lens design and use in laser-scanning microscopy", Biomedical Optics Express, vol. 5, pp. 1588, 2014.
  13. W. Zong, X. Huang, C. Zhang, T. Yuan, L. Zhu, M. Fan, and L. Chen, "Shadowless-illuminated variable-angle TIRF (siva-TIRF) microscopy for the observation of spatial-temporal dynamics in live cells", Biomedical Optics Express, vol. 5, pp. 1530, 2014.
  14. A.M. Jones, J.. Danielson, S.N. ManojKumar, V. Lanquar, G. Grossmann, and W.B. Frommer, "Abscisic acid dynamics in roots detected with genetically encoded FRET sensors", eLife, vol. 3, 2014.
  15. S. Jia, J.C. Vaughan, and X. Zhuang, "Isotropic three-dimensional super-resolution imaging with a self-bending point spread function", Nature Photonics, vol. 8, pp. 302-306, 2014.
  16. K. Wang, D.E. Milkie, A. Saxena, P. Engerer, T. Misgeld, M.E. Bronner, J. Mumm, and E. Betzig, "Rapid adaptive optical recovery of optimal resolution over large volumes", Nature Methods, vol. 11, pp. 625-628, 2014.
  17. L. Wei, F. Hu, Y. Shen, Z. Chen, Y. Yu, C. Lin, M.C. Wang, and W. Min, "Live-cell imaging of alkyne-tagged small biomolecules by stimulated Raman scattering", Nature Methods, vol. 11, pp. 410-412, 2014.
  18. N. Hafi, M. Grunwald, L.S. van den Heuvel, T. Aspelmeier, J. Chen, M. Zagrebelsky, O.M. Schütte, C. Steinem, M. Korte, A. Munk, and P.J. Walla, "Fluorescence nanoscopy by polarization modulation and polarization angle narrowing", Nature Methods, vol. 11, pp. 579-584, 2014.
  19. F.B. Robin, W.M. McFadden, B. Yao, and E.M. Munro, "Single-molecule analysis of cell surface dynamics in Caenorhabditis elegans embryos", Nature Methods, vol. 11, pp. 677-682, 2014.
  20. P. Pantazis, and W. Supatto, "Advances in whole-embryo imaging: a quantitative transition is underway", Nature Reviews Molecular Cell Biology, vol. 15, pp. 327-339, 2014.
  21. E. Susaki, K. Tainaka, D. Perrin, F. Kishino, T. Tawara, T. Watanabe, C. Yokoyama, H. Onoe, M. Eguchi, S. Yamaguchi, T. Abe, H. Kiyonari, Y. Shimizu, A. Miyawaki, H. Yokota, and H. Ueda, "Whole-Brain Imaging with Single-Cell Resolution Using Chemical Cocktails and Computational Analysis", Cell, vol. 157, pp. 726-739, 2014.
  22. S. Preibisch, F. Amat, E. Stamataki, M. Sarov, R.H. Singer, E. Myers, and P. Tomancak, "Efficient Bayesian-based multiview deconvolution", Nature Methods, vol. 11, pp. 645-648, 2014.
  23. I. Pushkarsky, Y. Liu, W. Weaver, T. Su, O. Mudanyali, A. Ozcan, and D. Di Carlo, "Automated single-cell motility analysis on a chip using lensfree microscopy", Scientific Reports, vol. 4, 2014.
  24. K. Wicker, and R. Heintzmann, "Resolving a misconception about structured illumination", Nature Photonics, vol. 8, pp. 342-344, 2014.
  25. T. Vettenburg, H.I.C. Dalgarno, J. Nylk, C. Coll-Lladó, D.E.K. Ferrier, T. Čižmár, F.J. Gunn-Moore, and K. Dholakia, "Light-sheet microscopy using an Airy beam", Nature Methods, vol. 11, pp. 541-544, 2014.
  26. M. Ovesný, P. Křížek, J. Borkovec, Z. Švindrych, and G.M. Hagen, "ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging", Bioinformatics, vol. 30, pp. 2389-2390, 2014.

Motorized Correction Collar

CorrCollar-1While organizing photos I can across this contraption that I built several years ago. It’s a 3D-printer servo motor mount for moving an objective correction collar under computer control. It’s mounted on a Nikon 40x / 1. 15 water immersion lens. It uses a hobbyist airplane servo which can be controlled by a Polulu servo driver board for which there is a Micro-Mananger driver. It worked fine but I didn’t develop a reliable way for calibrating the best collar setting as a function of Z before the user it was designed for decided that he got good enough results with a single collar position. If anyone is interested in it, I can find and post the 3D design files so you can print your own. [Edit: files available here].

Photobleaching and Photoactivation

A few months ago, we purchased a Rapp Optoelectronics galvo-scanning system, along with 405 and 473 nm lasers from Vortran Laser Technology, to provide a photoactivation and photobleaching system for our high speed widefield system. This system is capable of photoactivating or photoconverting any protein that is switched by 405nm light (which is most of them) and photobleaching GFP, while simultaneously acquiring in the GFP, RFP, and Cy5 channels. The entire system is controlled through Micro-Manager.

Today, with help from Nico Stuurman, we took it out for a spin. Nico provided Drosophila S2 cells with either mEos2 or GFP-tubulin as well as help getting everything set up correctly. Here are two videos demonstrating what it can do. Both were acquired on a widefield microscope with a 100x / 1.4 NA objective.

Photoconversion of mEos2-labeled tubulin in the spindle of a Drosophila S2 cell. The video is sped up 20-fold from real time.
Photobleaching of GFP-labeled tubulin in a Drosophila S2 cell. First, a GFP aggregate is bleached, which rapidly recovers. Second, nearby microtubules are bleached, which do not recover over the same time scale. The acquisition doesn't stop during the bleaching, so you can see the bright flash as the bleaching laser is turned on. The video is sped up 1.5x from real time.

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Adaptive optics confocal from the Betzig lab

This new paper from the Betzig lab [1] will be mentioned in the monthly paper roundup, but it’s too appealing not to devote a separate post to. In the paper, they describe a new confocal microscope combining adaptive optics and the use of a two-photon excited “guide star” (a single point of fluorescence excited from a ubiquitously expressed fluorescent protein) to achieve diffraction-limited resolution through a depth of hundreds of microns in living zebrafish. The trick that makes this possible is averaging the measured aberration over small subregions in the scan volume so that updating the aberration correction at each scan position is not required. This makes imaging fast enough to be practical (although still moderately slow; the scan speed is 100k pixels/s for most images in the paper).  However, the improvement in optical quality from the adaptive optics is stunning.  See figure 1 from the paper, below:

Wang et al. Fig 1.

a) 3D rendering of final image; b) two-photon image without adaptive optics; c) two-photon image, with adaptive optics; d) the same image, deconvolved.

I’m not sure when this will reach commercially available microscopes, but the optics look relatively straightforward to implement. The control software is probably a bit trickier, but building one of these seems doable for a reasonably skilled imaging lab. I am deeply envious of this microscope and would love to have one in our facility.  You can read a nice overview of it in the HHMI press release, including a cool video.


  1. K. Wang, D.E. Milkie, A. Saxena, P. Engerer, T. Misgeld, M.E. Bronner, J. Mumm, and E. Betzig, "Rapid adaptive optical recovery of optimal resolution over large volumes", Nature Methods, vol. 11, pp. 625-628, 2014.

Okolab Incubators

Okolab recently agreed to provide us a set of new incubators for growing mammalian cells on the microscope. They gave us several stage top incubators as well as a microscope enclosure for our spinning disk system. We installed these last week, so we don’t have a great deal of experience with them yet, but so far we’ve been impressed with their performance.

The enclosures and stage top incubators share a number of common features. Both have touch screen controls for setting the temperature, humidity, and gas flow rate. They also feature interchangeable inserts for different sample types (slide, plate, dish, etc.). These are held in place magnetically and they have a wide selection of inserts for different samples (see bottom of this page for the complete list).


The touch screen controller.

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Book Chapter on Digital Microscopy

Nico Stuurman and I have written a chapter on digital microscopy for the forthcoming Handbook of Digital Imaging from Wiley.  Thanks to the UC open access policy, you can read the manuscript of the chapter for free.  The chapter provides an overview of biological light microscopy with specific details on camera choice and computer control of microscope hardware for automated acquisition and high speed hardware synchronization.  You can access the manuscript here.

Shading correction for different objectives and channels

I’ve finished my testing of concentrated dye solutions for flat-fielding images. As described previously (1, 2), we’re using concentrated dye solutions to collect shading correction images, following the work of Michael Model. Following his protocol, we use 100 mg/ml fluorescein, rose bengal, and acid blue 9 for correcting the FITC, Cy3, and Cy5 channels, respectively. Additionally, we’ve found that 50 mg/ml 7-diethylamino-4-methylcoumarin is a good dye for collecting shading images for the DAPI channel.

A detailed protocol for collecting the shading images is posted on the NIC wiki, but in brief we first collect a dark image with no light going to the camera, and then collect multiple images of each dye at different positions, and calculate the median of these images to eliminate any spatial nonuniformities (e.g. dust particles) in the dye itself. Example dark and flat-field images are shown below.

Darkfield FITC_10x

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