Sami Koho

Palladin promotes assembly of non-contractile dorsal stress fibers through VASP recruitment.

ABSTRACT Stress fibers are major contractile actin structures in non-muscle cells where they have an important role in adhesion, morphogenesis and mechanotransduction. Palladin is a multidomain protein, which associates with stress fibers in a variety of cell types. However, the exact role of palladin in stress fiber assembly and maintenance has remained obscure, and whether it functions as an actin filament crosslinker or scaffolding protein was unknown. We demonstrate that palladin is specifically required for the assembly of non-contractile dorsal stress fibers, and is, consequently, essential for the generation of stress fiber networks and the regulation of cell morphogenesis in osteosarcoma cells migrating in a three-dimensional collagen matrix. Importantly, we reveal that palladin is necessary for the recruitment of vasodilator stimulated phosphoprotein (VASP) to dorsal stress fibers and that it promotes stress fiber assembly through VASP. Both palladin and VASP display similar rapid dynamics at dorsal stress fibers, suggesting that they associate with stress fibers as a complex. Thus, palladin functions as a dynamic scaffolding protein that promotes the assembly of dorsal stress fibers by recruiting VASP to these structures.

Image Quality Ranking Method for Microscopy.

Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics.

STED-TEM Correlative Microscopy Leveraging Nanodiamonds as Intracellular Dual-Contrast Markers

Development of fluorescent and electron dense markers is essential for the implementation of correlative light and electron microscopy, as dual-contrast landmarks are required to match the details in the multimodal images. Here, a novel method for correlative microscopy that utilizes fluorescent nanodiamonds (FNDs) as dual-contrast probes is reported. It is demonstrated how the FNDs can be used as dual-contrast labels-and together with automatic image registration tool SuperTomo, for precise image correlation-in high-resolution stimulated emission depletion (STED)/confocal and transmission electron microscopy (TEM) correlative microscopy experiments. It is shown how FNDs can be employed in experiments with both live and fixed cells as well as simple test samples. The fluorescence imaging can be performed either before TEM imaging or after, as the robust FNDs survive the TEM sample preparation and can be imaged with STED and other fluorescence microscopes directly on the TEM grids.

Tomographic STED microscopy to study bone resorption

We present a tomographic Stimulated Emission Depletion (STED) microscopy method with three-dimensional superresolution, and its application to osteoclast bone resorption study. In order to improve axial resolution in standard STED system by tomography, two axial projections were obtained by imaging a sample at two different angles; one conventionally from below and another from the side. The second observation was acquired via a metal-coated silicon mirror, positioned above the region of interest by a custom-built micro-positioner. The acquired two sets of 3D stacks were computationally registered and fused, with our own in-house-developed software, to produce a 3D tomogram with three-dimensional super-resolution. With the presented tomographic super-resolution method we optically investigated actin cytoskeleton through thin and smooth bone layer, particularly at ruffled boarders (RB), which are directly associated with active bone resorption in osteoclasts. Tomographic STED microscopy at RB of osteoclast, cultured on thin bone layer, demonstrated axial resolution of approx. 210 nm, revealing fine axial structures of actin cytoskeleton at RB. Further investigation of the cytoskeleton at RB in relation with associated proteins would provide understanding in the protein roles during the bone resorption.

A software tool for STED-AFM correlative super-resolution microscopy

Multi-modal correlative microscopy allows combining the strengths of several imaging techniques to provide unique contrast. However it is not always straightforward to setup instruments for such customized experiments, as most microscope manufacturers use their own proprietary software, with limited or no capability to interface with other instruments - this makes correlation of the multi-modal data extremely challenging. We introduce a new software tool for simultaneous use of a STimulated Emission Depletion (STED) microscope with an Atomic Force Microscope (AFM). In our experiments, a Leica TCS STED commercial super-resolution microscope, together with an Agilent 5500ilm AFM microscope was used. With our software, it is possible to synchronize the data acquisition between the STED and AFM instruments, as well as to perform automatic registration of the AFM images with the super-resolution STED images. The software was realized in LabVIEW; the registration part was also implemented as an ImageJ script. The synchronization was realized by controlling simple trigger signals, also available in the commercial STED microscope, with a low-cost National Instruments USB-6501 digital I/O card. The registration was based on detecting the positions of the AFM tip inside the STED fieldof-view, which were then used as registration landmarks. The registration should work on any STED and tip-scanning AFM microscope combination, at nanometer-scale precision. Our STED-AFM correlation method has been tested with a variety of nanoparticle and fixed cell samples. The software will be released under BSD open-source license.

A software tool for tomographic axial superresolution in STED microscopy

A method for generating three‐dimensional tomograms from multiple three‐dimensional axial projections in STimulated Emission Depletion (STED) superresolution microscopy is introduced. Our STED< method, based on the use of a micromirror placed on top of a standard microscopic sample, is used to record a three‐dimensional projection at an oblique angle in relation to the main optical axis. Combining the STED< projection with the regular STED image into a single view by tomographic reconstruction, is shown to result in a tomogram with three‐to‐four‐fold improved apparent axial resolution. Registration of the different projections is based on the use of a mutual‐information histogram similarity metric. Fusion of the projections into a single view is based on Richardson‐Lucy iterative deconvolution algorithm, modified to work with multiple projections. Our tomographic reconstruction method is demonstrated to work with real biological STED superresolution images, including a data set with a limited signal‐to‐noise ratio (SNR); the reconstruction software (SuperTomo) and its source code will be released under BSD open‐source license.

Image Scanning Microscopy with Single-Photon Detector Array

Image scanning microscopy (ISM) improves the spatial resolution of conventional confocal laser-scanning microscopy (CLSM), but current implementations reduce versatility and restrict its combination with fluorescence spectroscopy techniques, such as fluorescence lifetime. Here, we describe a natural design of ISM based on a fast single-photon detector array, which allows straightforward upgrade of an existing confocal microscope, without compromising any of its functionalities. In contrast to all-optical ISM implementations, our approach provides access to the raw scanned images, opening the way to adaptive reconstruction methods, capable of considering different imaging conditions and distortions. We demonstrate its utility in the context of fluorescence lifetime, deep, multicolor and live-cell imaging. This implementation will pave the way for a transparent and massive transition from conventional CLSM to ISM. confocal microscopy | time-resolved spectroscopy | image scanning microscopy | single-photon detector array

Photo-induced ultrasound microscopy for photo-acoustic imaging of non-absorbing specimens

Photo-Acoustic Microscopy (PAM) has raised high interest in in-vivo imaging due to its ability to preserve the near-diffraction limited spatial resolution of optical microscopes, whilst extending the penetration depth to the mm-range. Another advantage of PAM is that it is a label-free technique – any substance that absorbs PAM excitation laser light can be viewed. However, not all sample structures desired to be observed absorb sufficiently to provide contrast for imaging. This work describes a novel imaging method that makes it possible to visualize optically transparent samples that lack intrinsic photo-acoustic contrast, without the addition of contrast agents. A thin, strongly light absorbing layer next to sample is used to generate a strong ultrasonic signal. This signal, when recorded from opposite side, contains ultrasonic transmission information of the sample and thus the method can be used to obtain an ultrasound transmission image on any PAM.

Erratum: Image Quality Ranking Method for Microscopy.

Scientific Reports 6: Article number: 28962; published online: 01 July 2016; updated: 19 August 2016. In this Article, the PyImageQualityRanking software source code has been omitted from the Methods section under subheading ‘Image Quality Ranking Software’. It should read: “The PyImageQualityRanking software’s source code can be downloaded from https://bitbucket.