Studies of Single-Molecule Dynamics in Microorganisms

Fluorescence microscopy is one of the most extensively used techniques in the life sciences. Considering the non-invasive sample preparation, enabling live-cell compliant imaging, and the specific fluorescence labeling, allowing for a specific visualization of virtually any cellular compound, it is possible to localize even a single molecule in living cells. This makes modern fluorescence microscopy a powerful toolbox. In the recent decades, the development of new, "super-resolution" fluorescence microscopy techniques, which surpass the diffraction limit, revolutionized the field. Single-Molecule Localization Microscopy (SMLM) is a class of super-resolution microscopy methods and it enables resolution of down to tens of nanometers. SMLM methods like Photoactivated Localization Microscopy (PALM), (direct) Stochastic Optical Reconstruction Microscopy ((d)STORM), Ground-State Depletion followed by Individual Molecule Return (GSDIM) and Point Accumulation for Imaging in Nanoscale Topography (PAINT) have allowed to investigate both, the intracellular spatial organization of proteins and to observe their real-time dynamics at the single-molecule level in live cells. The focus of this thesis was the development of novel tools and strategies for live-cell SingleParticle Tracking PALM (sptPALM) imaging and implementing them for biological research. In the first part of this thesis, I describe the development of new Photoconvertible Fluorescent Proteins (pcFPs) which are optimized for sptPALM lowering the phototoxic damage caused by the imaging procedure. Furthermore, we show that we can utilize them together with Photoactivatable Fluorescent Proteins (paFPs) to enable multi-target labeling and read-out in a single color channel, which significantly simplifies the sample preparation and imaging routines as well as data analysis of multi-color PALM imaging of live cells. In parallel to developing new fluorescent proteins, I developed a high throughput data analysis pipeline. I have implemented this pipeline in my second project, described in the second part of this thesis, where I have investigated the protein organization and dynamics of the CRISPR-Cas antiviral defense mechanism of bacteria in vivo at a high spatiotemporal level with the sptPALM approach. I was successful to show the differences in the target search dynamics of the CRISPR effector complexes as well as of single Cas proteins for different target complementarities. I have also first data describing longer-lasting bound-times between effector complex and their potential targets in vivo, for which only in vitro data has been available till today. In summary, this thesis is a significant contribution for both, the advances of current sptPALM imaging methods, as well as for the understanding of the native behavior of CRISPR-Cas systems in vivo

Automatic Hotspots Detection for Intracellular Calcium Analysis in Fluorescence Microscopic Videos

In recent years, life-cell imaging techniques and their software applications have become powerful tools to investigate complex biological mechanisms such as calcium signalling. In this paper, we propose an automated framework to detect areas inside cells that show changes in their calcium concentration i.e. the regions of interests or hotspots, based on videos taken after loading living mouse cardiomyocytes with fluorescent calcium reporter dyes. The proposed system allows an objective and efficient analysis through the following four key stages: (1) Pre-processing to enhance video quality, (2) First level segmentation to detect candidate hotspots based on adaptive thresholding on the frame level, (3) Second-level segmentation to fuse and identify the best hotspots from the entire video by proposing the concept of calcium fluorescence hit-ratio, and (4) Extraction of the changes of calcium fluorescence over time per hotspot. From the extracted signals, different measurements are calculated such as maximum peak amplitude, area under the curve, peak frequency, and inter-spike interval of calcium changes. The system was tested using calcium imaging data collected from Heart muscle cells. The paper argues that the automated proposal offers biologists a tool to speed up the processing time and mitigate the consequences of inter-intra observer variability

SEM analyses of minerals from Allchar deposite - Republic of Macedonia

The Allchar Sb-As-Tl-Au volcanogenic hydrothermal deposit is situated at the northwestern margins of Kožuf Mts. (Republic of Macedonia), close to the border between Republic of Macedonia and Greece. From the geotectonic point of view, ore mineralization is related to a Pliocene volcano-intrusive complex located between the rigid Pellagonian block in the west, and the labile Vardar zone in the east. From the metallogenic point of view, the Allchar deposit belongs to the Kožuf ore district as part of the Serbo-Macedonian metallogenetic province.The locality is one of the Unique deposits in the world not because of its size but because of its mineral composition and diversity, including an abundance of particularly rare thallium sulfosalts

Gotta trace ‘em all: A mini-review on tools and procedures for segmenting single neurons toward deciphering the structural connectome

Decoding the morphology and physical connections of all the neurons populating a brain is necessary for predicting and studying the relationships between its form and function, as well as for documenting structural abnormalities in neuropathies. Digitizing a complete and high-fidelity map of the mammalian brain at the micro-scale will allow neuroscientists to understand disease, consciousness, and ultimately what it is that makes us humans. The critical obstacle for reaching this goal is the lack of robust and accurate tools able to deal with 3D datasets representing dense-packed cells in their native arrangement within the brain. This obliges neuroscientist to manually identify the neurons populating an acquired digital image stack, a notably time-consuming procedure prone to human bias. Here we review the automatic and semi-automatic algorithms and software for neuron segmentation available in the literature, as well as the metrics purposely designed for their validation, highlighting their strengths and limitations. In this direction, we also briefly introduce the recent advances in tissue clarification that enable significant improvements in both optical access of neural tissue and image stack quality, and which could enable more efficient segmentation approaches. Finally, we discuss new methods and tools for processing tissues and acquiring images at sub-cellular scales, which will require new robust algorithms for identifying neurons and their sub-structures (e.g., spines, thin neurites). This will lead to a more detailed structural map of the brain, taking twenty-first century cellular neuroscience to the next level, i.e., the Structural Connectome

Sample Chapter Cell and Molecular Biology 5e: What We Know and How We Found Out

https://dc.uwm.edu/biosci_facbooks_bergtrom/1016/thumbnail.jp