Building a light sheet microscope around an AZ100 microscope, part 2

In my previous post I talked about the basics of building a light sheet microscope from an AZ100 scope. After our initial successes with the microscope, we wanted to upgrade it to multicolor imaging and add a motorized Z stage to allow easy sample movements and potential image stitching.

For the multicolor laser source, we added a 4-line (405 / 488 / 561 / 640 nm) Vortran VersaLase laser launch. Vortran was easy to work with; since they’re located in Sacramento, they even drove up to install it for us. It’s fiber coupled; we use a doublet lens to collimate the beam from the fiber and then a cylindrical lens to produce the light sheet. A slit in front of the cylindrical lens allows trading off the width at the beam waist and the convergence of the sheet, allowing you to choose whether you want a thin sheet over a small area or a wider sheet over a larger area.

To add an emission filter wheel, we turned to Ebay. I’ve mentioned before that you can get cheap ASI parts from old GAIIx sequencers. We bought one such set of parts for the light sheet system, and then designed mounts for the filter wheel between the objective nosepiece and the filter turret, where a DIC slider housing formerly went. I’m pretty sure that this is in infinity space, and in any event the filter wheel mount isn’t that much thicker than the DIC slider housing was, so I don’t expect this to add much aberration. I had a lot of fun designing the filter wheel adapter in Autocad Inventor; I 3D printed parts of it to test the fit, and then had it machined in aluminum by proto labs. The total cost for the custom machining was around $700 and the turnaround was around a week, so I would definitely use them again.

The ASI stage mounts on the transmitted light illuminator base in place of the manual stage that had been there, via a 3D printed adapter. A second adapter mounts to the top of the plate and allows interchangeable 3D printed holders for different size cuvettes to be installed. We started with a 30 mm ID cuvette from Hellma (type 704-OG), but it was too tall to fit underneath the 5x / 0.5 objective, so we now mostly use a custom made 2 cm x 2 cm x 1 cm cuvette from FireflySci.

Files for all the custom parts are available at Github, as is the source code for the plugin we use to specify the relationship between the cuvette and objective position..

Bidirectional Z-scanning with Micro-manager and an ASI Z-stage

Conventional (unidirectional) Z-stack acquisition as compared with bidirectional Z-stack acquisition. In the conventional case, the time for the Z-stage to return to its starting position (the rescan time) limits how fast stacks can be acquired. In the bidirectional case, the stage is continuously moving, first up, then down, allowing continuous image acquisition.

Long time readers of this blog know that I’ve spent a lot of time working to make acquisition on our systems as fast as possible. Recently, I was approached with a request from Saul Kato, a new faculty member at UCSF, to go even faster. He wanted to be able to image neuronal activity in C. elegans at > 5 volumes per second.

What limits the acquisition speed of multiple volumes in Micro-manager is that it acquires Z-stacks unidirectionally and then has to return to the start position at the end of the Z-stack. This return time, also known as the retrace time, can actually add quite a bit of overhead (> 100 ms). In part, this overhead is to allow time for the piezo to return to its start position (I remember working with a Micro-manager version, many years ago, that didn’t allow enough time to return to the start, so all Z stacks after the first were missing the first plane or two). There is also some software overhead in this retrace time.

To eliminate this overhead, Saul and I set up bidirectional Z-scanning in Micro-manager. To avoid the rescan time, bidirectional Z-scanning first acquires one Z-stack ascending, followed by one descending. Because there are no large stage moves, the camera can acquire continuously during the entire process and so the overall acquisition rate is much faster.

We implemented this by taking advantage of the same trick in talking to the ASI stage that I’ve used before: Micro-manager allows you to communicate directly with the stage over the already open serial port from a script. Saul’s script then loads the ring buffer on the ASI stage with positions for both the ascending and descending Z stacks, and sets it so that camera triggers cause it to move from one plane to the next. With this set up, you just acquire a time lapse with as many frames as you want, and the Z-stacks are automatically acquired. You need to post-process the resulting stack to assemble the frames in the right order but the acquisition is very simple.

The script for doing this is on Github, as is one for turning off the bidirectional movement.

Deep-UV excitation with oblique epi-illumination

For the last several years, I’ve been working on a project to make spectrally-encoded beads using luminescent lanthanide nanophosphors [1] [2]. We use the nanophosphors to make unique spectral fingerprints for different beads by varying the concentration of different lanthanide emitters with distinct emission spectra. In particular, the nanophosphors we use are ytrrium vanadate nanocrystals doped with lanthanide emitters such as europium or dysprosium. We use lanthanide nanophosphors, rather than other fluorophores because they have narrow emission lines, are photostable, and are chemically stable. However, they have one major drawback: their excitation maximum is at 280 nm. This wavelength is so short that it is not transmitted by glass or conventional optics; instead you must use fused silica or special plastics like cyclic olefin (co)polymer to get substantial transmission. This means that conventional epi-illumination (through the objective) cannot be used to excite our samples. While there are objectives optimized for transmission of such short wavelengths, they are very expensive. Instead, for our work to date, we have used transmitted light illumination to excite our samples. However, this is relatively low brightness, illuminates a small field of view, and uses an expensive arc lamp source.

The deep-UV illuminator mounted on a 4x / 0.2 NA objective.

To try and improve on this light source, I designed an epi-illuminator for 280 nm illumination of our samples. Rather than illuminating through the objective, it consists of six deep-UV LEDs aimed at the sample. The LEDs are 280 nm Optan LEDs from Crystal IS with a ball lens to produce a narrow beam of light. Each emits ~ 3-4 mW of light, for a total of ~ 24 mW at the sample. They are mounted in a 3D-printed mount designed to aim each LED at the focal point of the lens. Clean up filters are mounted in front of each LED. These are 300 / 80 nm bandpass filters from Semrock, custom cut to 9mm diameter. Continue reading

References

  1. R.E. Gerver, R. Gómez-Sjöberg, B.C. Baxter, K.S. Thorn, P.M. Fordyce, C.A. Diaz-Botia, B.A. Helms, and J.L. DeRisi, "Programmable microfluidic synthesis of spectrally encoded microspheres", Lab Chip, vol. 12, pp. 4716-4723, 2012. http://dx.doi.org/10.1039/C2LC40699C
  2. H.Q. Nguyen, B.C. Baxter, K. Brower, C.A. Diaz-Botia, J.L. DeRisi, P.M. Fordyce, and K.S. Thorn, "Programmable Microfluidic Synthesis of Over One Thousand Uniquely Identifiable Spectral Codes", Advanced Optical Materials, vol. 5, pp. 1600548, 2016. http://dx.doi.org/10.1002/adom.201600548

Position available at the NIC@UCSF

The Nikon Imaging Center at the University of California, San Francisco seeks an imaging specialist to work with the director of the center in maintaining the day to day operations of the center. The Nikon Imaging Center at UCSF (NIC@UCSF) is a partnership between Nikon Instruments, UCSF, and a number of other vendors that provides eight state-of-the-art microscopes for use by the UCSF community. These microscopes are used by approximately 300 scientists a year and contribute data to approximately 40 publications a year. To learn more, see our website.

The successful candidate will be the initial point of contact for users seeking to use the NIC and will be responsible for advising them on the choice of microscope for their experiment and will provide training on the microscopes. The candidate should be sufficiently knowledgeable about microscopy and biology to advise newcomers to microscopy about the appropriate microscopes to use, given their experimental requirements and constraints. This individual will also be responsible for routine cleaning and maintenance of microscopes, testing of microscope performance, and troubleshooting problems with the microscopes. Within these parameters, the successfulcandidate will have considerable freedom which could include collaborations with NIC users.

Qualifications:
A PhD degree in biology, physics, optics, or a related field is required as is previous experience with light microscopy. Previous experience with equipment maintenance and training in a core facility environment is desirable. We are particularly looking for candidates with experience in biophysics, programming, or development of microscopy hardware.

UC San Francisco seeks candidates whose experience, teaching, research, or community service that has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.

The official posting is not up yet, but when it is it will be available at https://aprecruit.ucsf.edu/apply/JPF01286

In the meantime, if you’re interested in the position please send your CV and a cover letter to DeLaine Larsen, delaine.larsen@ucsf.edu

Jobs at Chan Zuckerberg Biohub

The Chan Zuckerberg Biohub is looking for engineers both with and without microscopy expertise for their hardware engineering team.  I know the head of the hardware engineering team and he is a great guy. This is a very rare opportunity to get involved at the beginning of a new cutting-edge biomedical research facility. For more information, see this flyer: Chan Zuckerberg Biohub Bioengineering Jobs.

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]

References

  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. http://dx.doi.org/10.7554/eLife.19088
  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. http://dx.doi.org/10.1038/nmeth.4073
  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. http://dx.doi.org/10.1364/BOE.8.000484
  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. http://dx.doi.org/10.1364/BOE.8.000640
  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, pp. g3.116.038133, 2017. http://dx.doi.org/10.1534/g3.116.038133
  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. http://dx.doi.org/10.1021/acschembio.6b00586
  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. http://dx.doi.org/10.1038/nprot.2016.181
  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. http://dx.doi.org/10.1083/jcb.201610025
  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. http://dx.doi.org/10.1083/jcb.201610026
  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. http://dx.doi.org/10.1364/BOE.8.000695
  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. http://dx.doi.org/10.1364/OE.25.001732

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.

References

  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. http://dx.doi.org/10.1186/s13321-016-0185-8