Fast live simultaneous multiwavelength four-dimensional optical microscopy

Department of Biochemistry and Biophysics, University of California, San Francisco, The Keck Center for Advanced Microscopy, CA 94158-2517, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 09/2010; 107(37):16016-22. DOI: 10.1073/pnas.1004037107
Source: PubMed

ABSTRACT Live fluorescence microscopy has the unique capability to probe dynamic processes, linking molecular components and their localization with function. A key goal of microscopy is to increase spatial and temporal resolution while simultaneously permitting identification of multiple specific components. We demonstrate a new microscope platform, OMX, that enables subsecond, multicolor four-dimensional data acquisition and also provides access to subdiffraction structured illumination imaging. Using this platform to image chromosome movement during a complete yeast cell cycle at one 3D image stack per second reveals an unexpected degree of photosensitivity of fluorophore-containing cells. To avoid perturbation of cell division, excitation levels had to be attenuated between 100 and 10,000× below the level normally used for imaging. We show that an image denoising algorithm that exploits redundancy in the image sequence over space and time allows recovery of biological information from the low light level noisy images while maintaining full cell viability with no fading.

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Available from: Charles Kervrann, Sep 28, 2015
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    • "One such situation is gravitational wave measurement, where kilometre-scale interferometric observatories operate with power near the damage threshold of their mirrors, yet still have not achieved the extreme precision required to directly observe a gravitational wave [3]. Biological measurements are another application area which has been discussed from the earliest days of quantum metrology [4] [5] [6] [7], since biological samples are often highly photosensitive and optical damage is a limiting factor in many biophysical experiments [8] [9] [10]. Although these applications were recognised in the 1980s, at that time the technology used for quantum metrology was in its infancy and unsuited to practical measurements. "
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    ABSTRACT: Quantum metrology provides a route to overcome practical limits in sensing devices. It holds particular relevance in biology, where sensitivity and resolution constraints restrict applications both in fundamental biophysics and in medicine. Here, we review quantum metrology from this biological context. The understanding of quantum mechanics developed over the past century has already enabled important applications in biology, including positron emission tomography (PET) with entangled photons, magnetic resonance imaging (MRI) using nuclear magnetic resonance, and bio-magnetic imaging with superconducting quantum interference devices (SQUIDs). With the birth of quantum information science came the realization that an even greater range of applications arise from the ability to not just understand, but to engineer coherence and correlations in systems at the quantum level. In quantum metrology, quantum coherence and quantum correlations are engineered to enable new approaches to sensing. This review focusses specifically on optical quantum metrology, where states of light that exhibit non-classical photon correlations are used to overcome practical and fundamental constraints, such as the shot-noise and diffraction limits. Recent experiments have demonstrated quantum enhanced sensing of biological systems, and established the potential for quantum metrology in biophysical research. These experiments have achieved capabilities that may be of significant practical benefit, including enhanced sensitivity and resolution, immunity to imaging artifacts, and characterisation of the biological response to light at the single-photon level. New quantum measurement techniques offer even greater promise, raising the prospect for improved multi-photon microscopy and magnetic imaging, among many other possible applications.
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    • "A major obstacle to filming cells at high resolution is phototoxicity (Carlton et al., 2010). We found that budding was delayed or blocked as light exposure was increased (Figure S1 available online). "
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    ABSTRACT: Many cells undergo symmetry-breaking polarization toward a randomly oriented "front" in the absence of spatial cues. In budding yeast, such polarization involves a positive feedback loop that enables amplification of stochastically arising clusters of polarity factors. Previous mathematical modeling suggested that, if more than one cluster were amplified, the clusters would compete for limiting resources and the largest would "win," explaining why yeast cells always make one and only one bud. Here, using imaging with improved spatiotemporal resolution, we show the transient coexistence of multiple clusters during polarity establishment, as predicted by the model. Unexpectedly, we also find that initial polarity factor clustering is oscillatory, revealing the presence of a negative feedback loop that disperses the factors. Mathematical modeling predicts that negative feedback would confer robustness to the polarity circuit and make the kinetics of competition between polarity factor clusters relatively insensitive to polarity factor concentration. These predictions are confirmed experimentally.
    Cell 04/2012; 149(2):322-33. DOI:10.1016/j.cell.2012.03.012 · 32.24 Impact Factor
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    • "Recent improvements to the NLM filter have focused on more accurate and faster computing of the Euclidean distances (intensity differences) between neighborhoods, used to estimate the coefficients for averaging (Brox et al., 2008; Mahmoudi and Sapiro, 2005; Tasdizen, 2008; Yang and Clausi, 2009). The patch-based filter (PBF) (Kervrann and Boulanger, 2008; Boulanger et al., 2008; Boulanger et al., 2010; Carlton et al., in press) is a state-of-the-art development of the non-local means filter in which the sizes of the searching windows are adaptively selected, so achieving a better balance between the accuracy of the point-wise estimator and stochastic error at each spatial position. It has demonstrated a great capability for restoration of natural images with minimal a priori knowledge. "
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    ABSTRACT: Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and particle detection. The commonly used non-local means filter is not optimal for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a particle feature probability image, which is based on Haar-like feature extraction. The particle probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this filter achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak particles when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means filter can reduce the threshold of imaging conditions required to obtain meaningful data.
    Journal of Structural Biology 12/2010; 172(3):233-43. DOI:10.1016/j.jsb.2010.06.019 · 3.23 Impact Factor
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