Exciting Advances Push the Limits of Visualization

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Exciting Advances
Push the Limits of

Cell signaling and clathrin-mediated endocytosis. Lipid rafts and molecular motion within the membrane. Movement of organelles within a cell and cell division. Protein organization and co-localization. Virus entry.

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Above: TIRF microscopy of HeLa cells labeled with d2EosFP, 100× lens (0.35× relay lens). Video courtesy of Zhen-li Huang, Professor, Huazhong University of Science and Technology.

Many of cell and molecular biology’s most critical events are occurring in the mid- to low-nanometer scale, which has hampered direct study through microscopy. But recent technological advances are shattering the 200 nm light diffraction limit, providing unprecedented and highly detailed views into the life of a cell. Processes that were hidden behind a veil of unresolved features are suddenly being brought into crystal-sharp clarity.

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Diffraction barrier: At 200 nm, the point spread function (PSF) of two airy discs are no longer individually distinguishable.


And we’re still in the exciting early stages of the technology’s development. Papers announcing new ways to gain insight into biological questions are appearing rapidly, such as the recent report from Huang, et al,1 from Joerg Bewersdorf’s lab at Yale University and an international team of collaborators.


By taking advantage of new detector technology and developing algorithms that capitalize on the strengths of this new technology, they are able to acquire single-molecule localization super-resolution images that reveal features at 22 nm precision and capture clathrin-coated structures moving at 13 nm/sec.

Read the Paper (login may be required)

Huang, F. et al. Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms.
Nat. Methods 10, 653–658 (2013).

Above: Super-resolution video of mEos3.2-labeled clathrin-coated pits in a live HeLa cell recorded using a 256 by 256 pixel field of view at a speed of 600 frames per second. Eash super-resolution image was assembled from 1200 camera frames corresponding to 2 s per super-resolution frame. The movie is played at 15 super-resolution images per second with a smoothing filter applied to aid visualization.
Courtesy of the Bewersdorf Lab at Yale University.



Past studies using single-molecule switching nanoscopy (SMSN) have been limited by the number of photons emitted by single molecule per frame, which places high demands on the detector. With such low signal, most studies are done using back-illuminated electron-multiplying charge-coupled devices (EM-CCDs) because of the technology’s low noise and high quantum efficiency (QE).




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These limitations are especially problematic when trying to use SMSN for live-cell imaging or high content screening, where fast speeds are essential for achieving meaningful throughputs.


A new generation of sCMOS detectors have a higher quantum efficiency, reaching up to 73% at 600 nm. But a wide and non-uniform pixel-to-pixel variability in noise has prevented early implementations of this technology from optimal use in SMSN.

Changing the Game

See how the Gen II sCMOS technology differs from EM-CCD in terms of QE and noise—read now.

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Huang, et al,1 turned to the newer second generation sCMOS sensors (Gen II sCMOS) to achieve low noise and wide fields-of-view with fast image acquisition times in both live and fixed cells.


The key advance Huang, et al,1 made in implementing Gen II sCMOS was the recognition that this novel technology is inherently different from EM-CCD, and that—particularly in SMSN conditions where noise is a major limitation and precise quantitative data analysis is crucial—different image processing algorithms are needed to yield optimal results

Right: Fixed Focal Adhesion image captured in conventional and super-resolution formats. Image courtesy of Joerg Bewersdorf, Assistant Professor, Yale University.



By thoroughly characterizing their Gen II sCMOS camera, they were able to develop algorithms that accounted for observed noise more effectively than just using a Poisson model that is typically done for EM-CCD detectors.


Implications for high content screening

  • Imaged focal adhesion protein paxillin labeled with Alexa Fluor 647 in a 26 x 26 μm field of view and at 800 frames per second.
  • Potential to record 1,000 different cells per hour with average precision of 22 μm.

Left: Super-resolution image of mEOS3.2-tagged paxillin in focal adhesions in live HeLa cells. The shown figure represents a sub-region of a super-resolution image obtained from a dataset that was recorded in a 256 by 256 pixel camera region at 600 frames per second aquisition speed in 41 s using a Hamamatsu ORCA-Flash4.0 sCMOS camera and analyzed using sCMOS-specific single-emitter fitting algorithms

Huang et. al. Nature Methods, published online May 26, 2013; Courtesy of the Bewersdorf Lab at Yale University.

Image courtesy of Joerg Bewersdorf, Assistant Professor, Yale University.


Implications for live cell imaging

Imaged clathrin-coated structures at an average precision of 22 nm using super-resolution image based on 34,800 camera frames acquired over 58 seconds. These structures often moved in a directed fashion at a speed of ~13 nm/sec.

Right: Super-resolution video of tdEOS-labeled PDHA1 (pyruvate dehydrogenase (lipoamide) alpha 1) accumulated in mitochondria in live COS-7 cell recorded using a 256 by 256 pixels field of view at a speed of 400 frames per second. Each super-resolution image was assembled from 400 camera frames corresponding to 1 s per super-resolution frame. The movie is played at 15 super-resolution images per second with a smoothing filter applied to aid visualization.
Courtesy of the Bewersdorf Lab at Yale University.


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Implications for using Gen II sCMOS cameras

Through their characterization, Huang, et al,1 show distinct regions where sCMOS or EM-CCD are more effective detectors.

Left: Predicted regions where EM-CCD yields better localization performance than the ORCA-Flash4.0, and common experimental conditions. For most experiments, sCMOS cameras offer comparable sensitivy with faster frame rates and wider fields-of-view. Image from Huang, et al,1 Supplemental Information.

Understanding the math

The key to Huang, et al.'s,1 success with Hamamatsu's sCMOS camera lies in careful consideration of noise—read more about how they dealt with noise in sCMOS and EM-CCDs.

Accounting for imperfection

No camera is perfect. As Huang, et al,1 powerfully illustrate, understanding your camera's imperfections can lead to better performance and better science. Read more about how to correct for noise for computational microscopy in Bridging the Gap.



“Amazing video rate #superresolution microscopy using a sCMOS camera. Definitely one for the wish list!



“Fang Huang and coworkers demonstrate a significant improvement in super-resolution image acquisition speed. By equipping a standard microscope with higher power lasers and a sCMOS camera, and evaluating each pixel quantitatively, they provide a clear path forward towards live-cell nanoscopy. Importantly, they accomplished this with both genetically encoded FPs and immunofluorescence methods. Honestly, I think that as these experiments become more routine, nanoscopy will no longer be the focus of specialty labs, but a tool that any biologists may harness in a 'turn-key' fashion. It's just a matter of time...”


We are just now at the beginning of a visualization revolution, as teams of biologists, chemists, physicists and engineers labor to develop the best methods and instruments to extract as much insight into the underlying nature of biology.

The advances offered by Huang, et al,1 open new opportunities not just for understanding processes within a cell but also for high-throughput screening of compounds that can alter how these processes occur.

As this technology continues to move forward, new avenues of research will open up as biologists take advantage of the power to see more.

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