Bacterial phototaxis was first recognized over a century ago, but the method by
which such small cells can sense the direction of illumination has remained
puzzling. The unicellular cyanobacterium Synechocystis sp. PCC
6803 moves with Type IV pili and measures light intensity and color with a range
of photoreceptors. Here, we show that individual Synechocystis
cells do not respond to a spatiotemporal gradient in light intensity, but rather
they directly and accurately sense the position of a light source. We show that
directional light sensing is possible because Synechocystis
cells act as spherical microlenses, allowing the cell to see a light source and
move towards it. A high-resolution image of the light source is focused on the
edge of the cell opposite to the source, triggering movement away from the
focused spot. Spherical cyanobacteria are probably the world’s smallest
and oldest example of a camera eye.
DOI:
http://dx.doi.org/10.7554/eLife.12620.001
We propose an algorithm for 3-D multiview deblurring using spatially variant point spread functions (PSFs). The algorithm is applied to multiview reconstruction of volumetric microscopy images. It includes registration and estimation of the PSFs using irregularly placed point markers (beads). We formulate multiview deblurring as an energy minimization problem subject to L1-regularization. Optimization is based on the regularized Lucy-Richardson algorithm, which we extend to deal with our more general model. The model parameters are chosen in a profound way by optimizing them on a realistic training set. We quantitatively and qualitatively compare with existing methods and show that our method provides better signal-to-noise ratio and increases the resolution of the reconstructed images.
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With volumetric data from widefield fluorescence microscopy, many emerging questions in biological and biomedical research are being investigated. Data can be recorded with high temporal resolution while the specimen is only exposed to a low amount of phototoxicity. These advantages come at the cost of strong recording blur caused by the infinitely extended point spread function (PSF). For widefield microscopy, its magnitude only decays with the square of the distance to the focal point and consists of an airy bessel pattern which is intricate to describe in the spatial domain. However, the Fourier transform of the incoherent PSF (denoted as Optical Transfer Function (OTF)) is well localized and smooth. In this paper, we present a blind deconvolution method that improves results of state-of-theart deconvolution methods on widefield data by exploiting the properties of the widefield OTF.
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