Paper Roundup – January 2017

  • Incorporating Cy dyes into proteins by nonsense supression [1]
  • An approach for extracting 3D information from 2D localization data [2]
  • Quantitative optimization of staining of fixed and cleared spheroids [3]
  • Large field-of-view imaging by imaging samples mounted on a rotating disk [4]
  • mNeonGreen is 3-5x brighter than GFP in C. elegans [5]
  • A ‘turn-on’ probe for RNA imaging by recruiting an unstable aptamer to the RNA to be monitored [6]
  • A protocol for automated imaging of bacterial collections on agar pads [7]
  • A review of single molecule imaging in biology [8]
  • A review of machine learning for biological imaging [9]
  • A blind SIM reconstruction algorithm [10]
  • A microfabricated mirror system for light sheet imaging [11]


  1. L. Leisle, R. Chadda, J.D. Lueck, D.T. Infield, J.D. Galpin, V. Krishnamani, J.L. Robertson, and C.A. Ahern, "Cellular encoding of Cy dyes for single-molecule imaging", eLife, vol. 5, 2016.
  2. C. Franke, M. Sauer, and S. van de Linde, "Photometry unlocks 3D information from 2D localization microscopy data", Nature Methods, vol. 14, pp. 41-44, 2016.
  3. I. Smyrek, and E.H.K. Stelzer, "Quantitative three-dimensional evaluation of immunofluorescence staining for large whole mount spheroids with light sheet microscopy", Biomedical Optics Express, vol. 8, pp. 484, 2017.
  4. A.H.L. Tang, P. Yeung, G.C.F. Chan, B.P. Chan, K.K.Y. Wong, and K.K. Tsia, "Time-stretch microscopy on a DVD for high-throughput imaging cell-based assay", Biomedical Optics Express, vol. 8, pp. 640, 2017.
  5. L. Hostettler, L. Grundy, S. Käser-Pébernard, C. Wicky, W.R. Schafer, and D.A. Glauser, " The Bright Fluorescent Protein mNeonGreen Facilitates Protein Expression Analysis In Vivo ", G3: Genes|Genomes|Genetics, vol. 7, pp. 607-615, 2017.
  6. W.Q. Ong, Y.R. Citron, S. Sekine, and B. Huang, "Live Cell Imaging of Endogenous mRNA Using RNA-Based Fluorescence “Turn-On” Probe", ACS Chemical Biology, vol. 12, pp. 200-205, 2017.
  7. H. Shi, A. Colavin, T.K. Lee, and K.C. Huang, "Strain Library Imaging Protocol for high-throughput, automated single-cell microscopy of large bacterial collections arrayed on multiwell plates", Nature Protocols, vol. 12, pp. 429-438, 2017.
  8. E. Monachino, L.M. Spenkelink, and A.M. van Oijen, "Watching cellular machinery in action, one molecule at a time", The Journal of Cell Biology, vol. 216, pp. 41-51, 2016.
  9. B.T. Grys, D.S. Lo, N. Sahin, O.Z. Kraus, Q. Morris, C. Boone, and B.J. Andrews, "Machine learning and computer vision approaches for phenotypic profiling", The Journal of Cell Biology, vol. 216, pp. 65-71, 2016.
  10. L. Yeh, L. Tian, and L. Waller, "Structured illumination microscopy with unknown patterns and a statistical prior", Biomedical Optics Express, vol. 8, pp. 695, 2017.
  11. E. Zagato, T. Brans, S. Verstuyft, D. van Thourhout, J. Missinne, G. van Steenberge, J. Demeester, S. De Smedt, K. Remaut, K. Neyts, and K. Braeckmans, "Microfabricated devices for single objective single plane illumination microscopy (SoSPIM)", Optics Express, vol. 25, pp. 1732, 2017.

Why I’m leaving UCSF; or thoughts on running an imaging center for those who might consider it

After a little over ten years running the Nikon Imaging Center at UCSF, I’ve decided to take a job in industry. On March 6th, I will start work at Zymergen. DeLaine Larsen will take over as director of the NIC. At Zymergen, I won’t be doing much, if any, microscopy. Instead, I’ll be learning a lot and working to help them with their strain optimization efforts. It’s bittersweet to be leaving – I’ve really enjoyed my time at UCSF and I love microscopy, but it’s time to move on and to try something new. Here, I want to say a few words about why I’ve decided to leave UCSF, with the goal of hopefully shedding some light on the challenges of running a core facility that might be of interest to someone considering this career path. Continue reading

Nikon and UCSF parting ways; thoughts on managing core facility funding

Nikon has supported the Nikon Imaging Center at UCSF since its inception in 2006. During that time they have provided both direct financial support as well as providing six microscopes to the center, and then replacing and upgrading those microscopes in 2009/2010. Our relationship with Nikon is now coming to an end; we will retain the microscopes we have and Nikon will provide service on them for some time, but we will not get new hardware, nor we will get financial support after 2017.

(For those of you worried about the future of the NIC; we’ll be fine. Recharge rates will go up, but that will be the only change in the near term.)

Not surprisingly, given this change in affairs, I’ve been thinking a lot about our financial model and I wanted to share some of that thinking here in case it’s useful to someone else who is new at core management. Continue reading

Database of fluorescent protein sequences

A paper recently came out on a web server for predicting the oligomeric state of fluorescent proteins [1]. It’s only about 80% accurate, which isn’t so nice, but they have a github page with sequences for hundreds of fluorescent proteins in a csv file. Tracking down all these sequences can be tedious, so this is a nice resource.


  1. S. Simeon, W. Shoombuatong, N. Anuwongcharoen, L. Preeyanon, V. Prachayasittikul, J.E.S. Wikberg, and C. Nantasenamat, "osFP: a web server for predicting the oligomeric states of fluorescent proteins", Journal of Cheminformatics, vol. 8, 2016.

More thoughts on fluorescent lifetime

Since my previous post on fluorescent lifetimes of fluorescent proteins, I’ve been doing some more reading on what governs fluorescence lifetime of fluorophores. It turns out that there is a theoretical model for the instrinsic radiative lifetime, the Strickler-Berg equation [1]. This is a generalization of an equation originally derived by Einstein for predicting atomic spectra, and is roughly valid for for molecules where the structure does not change between ground and excited states.

The Strickler-Berg Equation. kr is the radiative rate (1/lifetime), n is refractive index, I(ν) is the emission spectrum, and ε(ν) is the absorption spectrum, where ν is the wavenumber.

This gives results accurate to within about a factor of 2 for CFP and YFP [2], so it’s not completely accurate. Interestingly, however, it only depends on the absorption and emission spectra of the molecule, so this provides an explanation for why all fluorescent proteins seem to have similar intrinsic radiative lifetimes – they have similar spectra (the whole visible range of light only spans a factor of two in wavenumber) and absorption coefficients (mostly in the range of 50,000 – 100,000). So from first principles we might expect that intrinsic lifetimes of all visible dyes should be within a small range, unless they have very small or very large extinction coefficients.

It predicts that molecules with larger absorption coefficients should have shorter lifetimes, which makes sense if you think of the absorption coefficient as measuring the coupling strength between light and the molecule. It also predicts that molecules with emission at longer wavenumbers ( = shorter wavelengths) should have shorter lifetimes.


  1. S.J. Strickler, and R.A. Berg, "Relationship between Absorption Intensity and Fluorescence Lifetime of Molecules", The Journal of Chemical Physics, vol. 37, pp. 814-822, 1962.
  2. J.W. Borst, M.A. Hink, A. van Hoek, and A.J.W.G. Visser, "Effects of Refractive Index and Viscosity on Fluorescence and Anisotropy Decays of Enhanced Cyan and Yellow Fluorescent Proteins", Journal of Fluorescence, vol. 15, pp. 153-160, 2005.

Michael Davidson and Roger Tsien Commemorative Travel Awards from Addgene

Addgene is offering travel awards for students or postdocs using fluorescent proteins in their research. The award is named in honor of Michael Davidson and Roger Tsien – two giants in the fluorescent protein field. While Roger Tsien is well known, Michael Davidson is one of the unsung heroes of fluorescent protein research – his lab built thousands of fluorescent protein fusions to test the performance of fluorescent proteins in a wide variety of contexts. He then distributed these plasmids to many labs, and eventually deposited nearly all of them in Addgene.

Fluorescence lifetime and quantum yield

Two months ago I saw a tweet noting the linear relationship between quantum yield and fluorescence lifetime in fluorescent proteins. I hadn’t seen this before, so I wanted to see if it held on a wider range of fluorescent proteins, so I added the ability to plot lifetimes on my fluorescent protein visualization and added lifetimes for all the proteins I could find (37 in total).

Quantum yield vs. fluorescent lifetime (ns) for 37 fluorescent proteins, colored by emission wavelength and brightness. Click for full size image.

Continue reading

Paper Roundup – December 2016

  • A software tool for cell segmentation, tracking, and lineage tracing from phase contrast images [1]
  • A turn-on fluorescence probe for specifc RNAs [2]
  • Using a bacterial pore-forming toxin to get cell-impermeant molecules and fluorophores into mammalian cells [3]
  • Optical techniques for membrane voltage measurement in freely moving mice [4]
  • A nice review of super-resolution microscopy as applied to biology [5]
  • A discussion of the future of computational image analysis [6]
  • Interferometeric imaging for nm precision imaging of single molecules in vivo [7]
  • A 3D random access scanning microscope using an acousto-optic lens system [8]
  • Photoactivatible versions of the Janelia Fluor dyes [9]
  • An aberration-corrected doublet metalens [10]
  • Imaging of RNAs throughout a cleared Drosophila brain [11]
  • Nanometer precision localization of single molecules with minimal photon fluxes [12]
  • A new far-red emitting (598 nm ex / 671 nm em) fluorescent protein [13]


  1. M. Winter, W. Mankowski, E. Wait, S. Temple, and A.R. Cohen, "LEVER: software tools for segmentation, tracking and lineaging of proliferating cells", Bioinformatics, pp. btw406, 2016.
  2. W.Q. Ong, Y.R. Citron, S. Sekine, and B. Huang, "Live Cell Imaging of Endogenous mRNA Using RNA-Based Fluorescence “Turn-On” Probe", ACS Chemical Biology, vol. 12, pp. 200-205, 2017.
  3. K.W. Teng, Y. Ishitsuka, P. Ren, Y. Youn, X. Deng, P. Ge, S.H. Lee, A.S. Belmont, and P.R. Selvin, "Labeling proteins inside living cells using external fluorophores for microscopy", eLife, vol. 5, 2016.
  4. J.D. Marshall, J.Z. Li, Y. Zhang, Y. Gong, F. St-Pierre, M.Z. Lin, and M.J. Schnitzer, "Cell-Type-Specific Optical Recording of Membrane Voltage Dynamics in Freely Moving Mice", Cell, vol. 167, pp. 1650-1662.e15, 2016.
  5. T.J. Lambert, and J.C. Waters, "Navigating challenges in the application of superresolution microscopy", The Journal of Cell Biology, vol. 216, pp. 53-63, 2016.
  6. E. Meijering, A.E. Carpenter, H. Peng, F.A. Hamprecht, and J. Olivo-Marin, "Imagining the future of bioimage analysis", Nature Biotechnology, vol. 34, pp. 1250-1255, 2016.
  7. G. Wang, J. Hauver, Z. Thomas, S.A. Darst, and A. Pertsinidis, "Single-Molecule Real-Time 3D Imaging of the Transcription Cycle by Modulation Interferometry", Cell, vol. 167, pp. 1839-1852.e21, 2016.
  8. K.M.N.S. Nadella, H. Roš, C. Baragli, V.A. Griffiths, G. Konstantinou, T. Koimtzis, G.J. Evans, P.A. Kirkby, and R.A. Silver, "Random-access scanning microscopy for 3D imaging in awake behaving animals", Nature Methods, vol. 13, pp. 1001-1004, 2016.
  9. J.B. Grimm, B.P. English, H. Choi, A.K. Muthusamy, B.P. Mehl, P. Dong, T.A. Brown, J. Lippincott-Schwartz, Z. Liu, T. Lionnet, and L.D. Lavis, "Bright photoactivatable fluorophores for single-molecule imaging", Nature Methods, vol. 13, pp. 985-988, 2016.
  10. A. Arbabi, E. Arbabi, S.M. Kamali, Y. Horie, S. Han, and A. Faraon, "Miniature optical planar camera based on a wide-angle metasurface doublet corrected for monochromatic aberrations", Nature Communications, vol. 7, pp. 13682, 2016.
  11. X. Long, J. Colonell, A.M. Wong, R.H. Singer, and T. Lionnet, "Quantitative mRNA Imaging Throughout the Entire Drosophila Brain", 2016.
  12. F. Balzarotti, Y. Eilers, K.C. Gwosch, A.H. Gynna, V. Westphal, F.D. Stefani, J. Elf, and S.W. Hell, "Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes", Science, 2016.
  13. G. Matela, P. Gao, G. Guigas, A.F. Eckert, K. Nienhaus, and G. Ulrich Nienhaus, "A far-red emitting fluorescent marker protein, mGarnet2, for microscopy and STED nanoscopy", Chem. Commun., vol. 53, pp. 979-982, 2017.