Lehrstuhl für Physikalische Chemie I (Prof. Dr. Rainer Heintzmann)
Die Arbeitsgruppe befasst sich mit der Entwicklung neuer Techniken zur Messung multidimensionaler Informationen in kleinen biologischen Objekten wie Zellen, Zellorganellen, Molekülen oder anderen biologisch relevanten Strukturen. Wir wollen aufklären, wie Moleküle in lebenden Zellen an bestimmten Orten (z. B. in Zellorganellen) und zu bestimmten Zeiten (z. B. nach Anregung durch ein anderes Molekül) interagieren. Um dieses Ziel zu erreichen, verwenden wir Moleküle, die durch Anregung mit Licht verschiedener Wellenlängen zwischen verschiedenen fluoreszierenden Zuständen geschaltet werden können. Werden zugehörige Zustandsübergänge gesättigt, können die daraus resultierenden nichtlinearen Abhängigkeiten genutzt werden, um zum Beispiel durch strukturierte Beleuchtung (SI) eine theoretisch unbegrenzt hohe Auflösung zu erreichen.
Weitere Informationen zur Arbeitsgruppe finden Sie hierExterner Link.
Reconstruction of subcellular structures from resolution-limited volume electron microscopy
Erscheinungsjahr
L. Heinrich
Volume electron microscopy (vEM) of biological samples achieves high resolution with generic contrast, providing access to the intricate 3D organization of tissues and cells. It has been used extensively for connectomics—the reconstruction of biological nervous systems —but also serves as a powerful tool for the life sciences more broadly. However, the size and complexity of these data make information extraction a significant image analysis challenge. In this PhD work, I developed deep learning (DL) methods for three such problems. Serial-section vEM produces data with highly anisotropic resolution. We show that high isotropic resolution can be reliably reconstructed if adequate training data is available. Since such data can only be simulated, we developed self-supervised training strategies that eliminate the need for isotropic ground truth, with promising early results. Connectome reconstruction depends on accurately segmenting neurons and detecting all synapses. We developed a method to systematically adapt a successful DL architecture to anisotropic data and reformulated segmentation as a regression on a distance map. This significantly improved state-of-the-art performance, and we used it to generate a synaptic cleft segmentation of the entire Drosophila brain—a valuable resource for neuroscience. We further extended the method to encode synaptic partners at each cleft, enabling assignment of synaptic connections to neurons. Most automated vEM tools focus on neurons and synapses, leaving much of the rich subcellular information untapped. Standard EM staining reveals organelles and other structures distinguishable by morphology and texture. The third project in this thesis makes this information accessible using DL to segment such structures. We manually annotated up to 36 organelle classes across diverse high-resolution datasets and trained networks that generalize across 4 nm and 8 nm data, demonstrating their utility in deriving new biological insights.
Resolution in super-resolution microscopy - facts, artifacts, technological advancements and biological applications
ErscheinungsjahrErschienen in:Journal of cell science: publ. for the Company of Biologists Limited
K. Prakash, D. Baddeley, C. Eggeling, R. Fiolka, R. Heintzmann, S. Manley, A. Radenovic, H. Shroff, C. Smith, L. Schermelleh
Combining image scanning and stimulated emission depletion microscopy to achieve isotropic resolution
Erscheinungsjahr
M. Goswami
Biologists are always interested in the molecular structures inside living cells, for example, mitochondria. But most of the time, these fine subcellular structures are randomly oriented in X, Y, and Z direction. For faithful image reconstruction, it is always desired to have an isotropic resolution improvement. But the resolution, in general, is not isotropic. In fact, it is three times worse along the axial direction than the lateral, making it challenging to study 3D structures inside the cells. Although existing techniques like 4pi and STED microscopy have been used to achieve isotropic resolution improvements, the setups are highly complex and high intensities used in the STED beam cause photobleaching and phototoxicity-induced artifacts, especially in the case of live-cell imaging. Therefore, it is crucial to develop novel microscopy approaches that simultaneously optimize both lateral and axial resolution potentially using low excitation powers. In this thesis, we realize a new combination of image scanning microscopy and π-step phase modulated depletion STED beam. The basic idea behind this is that image scanning microscopy will improve the resolution in the lateral direction and the resolution in the axial direction will be improved simultaneously by the depletion STED beam. The depletion STED beam used here is a π-step phase modulated that will deplete the fluorescence originating from the areas above and below the image plane but the fluorescence in the image plane is never quenched by the STED laser beam. Thus, their photobleaching by the STED beam can be avoided. We therefore expect much higher photon counting rates than with conventional 3D STED.
ErscheinungsjahrStatusPrüfung ausstehendErschienen in:Light: Science and Applications
K. Tsuji, M. Yamanaka, Y. Kumamoto, S. Tamura, W. Miyamura, T. Kubo, K. Mizushima, K. Kono, H. Hirano, M. Shiozaki, X. Zhao, H. Xi, K. Sugiura, S. Fukushima, T. Kunimoto, Y. Tanabe, K. Nishida, K. Mochizuki, Y. Harada, N. Smith, R. Heintzmann, Z. Yu, M. Wang, T. Nagai, H. Tanaka, K. Fujita
Fluorescence microscopy enables the visualization of cellular morphology, molecular distribution, ion distribution, and their dynamic behaviors during biological processes. Enhancing the signal-to-noise ratio (SNR) in fluorescence imaging improves the quantification accuracy and spatial resolution; however, achieving high SNR at fast image acquisition rates, which is often required to observe cellular dynamics, still remains a challenge. In this study, we developed a technique to rapidly freeze biological cells in milliseconds during optical microscopy observation. Compared to chemical fixation, rapid freezing provides rapid immobilization of samples while more effectively preserving the morphology and conditions of cells. This technique combines the advantages of both live-cell and cryofixation microscopy, i.e., temporal dynamics and high SNR snapshots of selected moments, and is demonstrated by fluorescence and Raman microscopy with high spatial resolution and quantification under low temperature conditions. Furthermore, we also demonstrated that intracellular calcium dynamics can be frozen rapidly and visualized using fluorescent ion indicators, suggesting that ion distribution and conformation of the probe molecules can be fixed both spatially and temporally. These results confirmed that our technique can time-deterministically suspend and visualize cellular dynamics while preserving molecular and ionic states, indicating the potential to provide detailed insights into sample dynamics with improved spatial resolution and temporal accuracy in observations.
Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours
ErscheinungsjahrStatusPrüfung ausstehendErschienen in:Communications Engineering
H. Wang, P. Brown, J. Ullom, D. Shepherd, R. Heintzmann, B. Diederich
In biological imaging, there is a demand for cost-effective, high-resolution techniques to study dynamic intracellular processes. Structured illumination microscopy (SIM) is ideal for achieving high axial and lateral resolution in live samples due to its optical sectioning and low phototoxicity. However, conventional SIM systems remain expensive and complex. We introduce openSIMMO, an open-source, fully-automated SIM module compatible with commercial microscopes, supporting dual-color excitation. Our design uses affordable single-mode fiber-coupled lasers and a digital micromirror device (DMD), integrated with the open-source ImSwitch software for real-time super-resolution imaging. This setup offers up to 1.55-fold improvement in lateral resolution over wide-field microscopy. To optimize DMD diffraction, we developed a model for tilt and roll pixel configurations, enabling use with various low-cost projectors in SIM setups. Our goal is to democratize SIM-based super-resolution microscopy by providing open-source documentation and a flexible software framework adaptable to various hardware (e.g., cameras, stages) and reconstruction algorithms, enabling more widespread super-resolution upgrades across devices.
PRIAMOS: A technique for mixing embedding media for freely adjusting pH value and refractive index (RI) for optical clearing (OC) of whole tissue samples
ErscheinungsjahrStatusPrüfung ausstehendErschienen in:Journal of microscopy / The Royal Microscopical Society
U. Leischner, M. Reifarth, M. Brill, F. Schmitt, S. Hoeppener, D. Unnersjö Jess, H. Brismar, U. Schubert, R. Heintzmann
Spectral Analysis of Human Retinal Pigment Epithelium Cells in Healthy and AMD Eyes
ErscheinungsjahrErschienen in:Investigative ophthalmology & visual science: official publication of the Association for Research in Vision and Ophthalmology
L. Bourauel, M. Vaisband, L. von der Emde, K. Bermond, I. Tarau, R. Heintzmann, F. Holz, C. Curcio, J. Hasenauer, T. Ach
Purpose: Retinal pigment epithelium (RPE) cells show strong autofluorescence (AF). Here, we characterize the AF spectra of individual RPE cells in healthy eyes and those affected by age-related macular degeneration (AMD) and investigate associations between AF spectral response and the number of intracellular AF granules per cell. Methods: RPE-Bruch's membrane flatmounts of 22 human donor eyes, including seven AMD-affected eyes (early AMD, three; geographic atrophy, one; neovascular, three) and 15 unaffected macula (<51 years, eight; >80 years, seven), were imaged at the fovea, perifovea, and near-periphery using confocal AF microscopy (excitation 488 nm), and emission spectra were recorded (500-710 nm). RPE cells were manually segmented with computer assistance and stratified by disease status, and emission spectra were analyzed using cubic spline transforms. Intracellular granules were manually counted and classified. Linear mixed models were used to investigate associations between spectra and the number of intracellular granules. Results: Spectra of 5549 RPE cells were recorded. The spectra of RPE cells in healthy eyes showed similar emission curves that peaked at 580 nm for fovea and perifovea and at 575 and 580 nm for near-periphery. RPE spectral curves in AMD eyes differed significantly, being blue shifted by 10 nm toward shorter wavelengths. No significant association coefficients were found between wavelengths and granule counts. Conclusions: This large series of RPE cell emission spectra at precisely predefined retinal locations showed a hypsochromic spectral shift in AMD. Combining different microscopy techniques, our work has identified cellular RPE spectral AF and subcellular granule properties that will inform future in vivo investigations using single-cell imaging.
ErscheinungsjahrErschienen in:Nature methods: techniques for life scientists and chemists
K. Temma, R. Oketani, T. Kubo, K. Bando, S. Maeda, K. Sugiura, T. Matsuda, R. Heintzmann, T. Kaminishi, K. Fukuda, M. Hamasaki, T. Nagai, K. Fujita
Universal inverse modeling of point spread functions for SMLM localization and microscope characterization
ErscheinungsjahrErschienen in:Nature methods: techniques for life scientists and chemists
S. Liu, J. Chen, J. Hellgoth, L. Müller, B. Ferdman, C. Karras, D. Xiao, K. Lidke, R. Heintzmann, Y. Shechtman, Y. Li, J. Ries
Resolution in super-resolution microscopy: definition, trade-offs and perspectives
ErscheinungsjahrErschienen in:Nature Reviews Molecular Cell Biology
K. Prakash, D. Baddeley, C. Eggeling, R. Fiolka, R. Heintzmann, S. Manley, A. Radenovic, C. Smith, H. Shroff, L. Schermelleh
Experimental validation of numerical point spread function calculation including aberration estimation
ErscheinungsjahrErschienen in:Optics Express
R. Miora, M. Senftleben, S. Abrahamsson, E. Rohwer, R. Heintzmann, G. Bosman, R. Holinirina Dina Miora
Image reconstruction in fluorescence microscopy is highly sensitive to the accuracy of the impulse response, defined as the point spread function (PSF), of the optical system under which the image to reconstruct was acquired. In our previous work, we developed a MATLAB toolbox for accurately calculating realistic vector Fourier-based PSF accounting for any type of aberrations [arXiv, arXiv:2301.13515 (2023)10.48550/arXiv.2301.13515]. In this work, we present a fundamental experimental validation of these numerical methods. The simulated results are found to fit experimental data under different image acquisition conditions at an accuracy higher than 0.97 in normalized cross-correlation. These methods enable a relative contrast of up to 95%.
Deep learning-enhanced automated mitochondrial segmentation in FIB-SEM images using an entropy-weighted ensemble approach
ErscheinungsjahrErschienen in:PLoS ONE
Y. Gupta, R. Heintzmann, C. Costa, R. Jesus, E. Pinho
Mitochondria are intracellular organelles that act as powerhouses by breaking down nutrition molecules to produce adenosine triphosphate (ATP) as cellular fuel. They have their own genetic material called mitochondrial DNA. Alterations in mitochondrial DNA can result in primary mitochondrial diseases, including neurodegenerative disorders. Early detection of these abnormalities is crucial in slowing disease progression. With recent advances in data acquisition techniques such as focused ion beam scanning electron microscopy, it has become feasible to capture large intracellular organelle volumes at data rates reaching 4Tb/ minute, each containing numerous cells. However, manually segmenting large data volumes (gigapixels) can be time-consuming for pathologists. Therefore, there is an urgent need for automated tools that can efficiently segment mitochondria with minimal user intervention. Our article proposes an ensemble of two automatic segmentation pipelines to predict regions of interest specific to mitochondria. This architecture combines the predicted outputs from both pipelines using an ensemble learning-based entropy-weighted fusion technique. The methodology minimizes the impact of individual predictions and enhances the overall segmentation results. The performance of the segmentation task is evaluated using various metrics, ensuring the reliability of our results. We used four publicly available datasets to evaluate our proposed method’s effectiveness. Our proposed fusion method has achieved a high score in terms of the mean Jaccard index and dice coefficient for all four datasets. For instance, in the UroCell dataset, our proposed fusion method achieved scores of 0.9644 for the mean Jaccard index and 0.9749 for the Dice coefficient. The mean error rate and pixel accuracy were 0.0062 and 0.9938, respectively. Later, we compared it with state-of-the-art methods like 2D and 3D CNN algorithms. Our ensemble approach shows promising segmentation efficiency with minimal intervention and can potentially aid in the early detection and mitigation of mitochondrial diseases.
