Nanoimaging - Heintzmann Group

Chair of Physical Chemistry I (Nanobiophotonics)

The group is concerned with the development of new techniques for measuring multidimensional information in small biological objects such as cells, cell organelles, molecules or other biologically relevant structures. We want to elucidate how molecules interact in living cells at certain locations (e.g. in cell organelles) and at certain times (e.g. after stimulation by another molecule). To achieve this goal, we use molecules that can be switched between different fluorescent states by excitation with light of different wavelengths. If associated state transitions are saturated, the resulting nonlinear dependencies can be used to achieve theoretically unlimited resolution, for example by structured illumination (SI).

Further information on the working group can be found hereExternal link.

Contact

Rainer Heintzmann, Univ.-Prof. Dr
Chair of Physical Chemsitry I
Prof. Dr. Rainer Heintzmann
Image: Prof. Dr. Rainer Heintzmann
Room E016
Helmholtzweg 4
07743 Jena Google Maps site planExternal link

Staff

  1. Ali, Maryam Abdulla Jasim Habib PhD student Chair of Physical Chemistry I (Nanobiophotonics)

    Albert-Einstein-Straße 9
    07745 Jena

  2. Bergner, Georg, Dr Chair of Physical Chemistry I (Nanobiophotonics)
  3. Cheng, Shangjun PhD student Chair of Physical Chemistry I (Nanobiophotonics)

    Room K012
    Helmholtzweg 4
    07743 Jena

  4. Heintzmann, Rainer, Univ.-Prof. Dr Chair of Physical Chemistry I (Nanobiophotonics)
    Prof. Dr. Rainer Heintzmann
    Image: Prof. Dr. Rainer Heintzmann
  5. Kretschmer, Robert Chair of Physical Chemistry I (Nanobiophotonics)

    Room HG184
    Albert-Einstein-Straße 9
    07745 Jena

  6. Täuber, Daniela, Dr PostDoc Chair of Physical Chemistry I (Nanobiophotonics)
  7. Zarei Oshtolagh, Hossein PhD student Chair of Physical Chemistry I (Nanobiophotonics)

35 Publikationen filtern

Die Publikationen filtern
  1. Resolution in super-resolution microscopy - facts, artifacts, technological advancements and biological applications

    Year of publicationStatusReview pendingPublished 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
  2. Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours

    Year of publicationStatusReview pendingPublished 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.
    University Bibliography Jena:
    fsu_mods_00023219External link
  3. Spectral Analysis of Human Retinal Pigment Epithelium Cells in Healthy and AMD Eyes

    Year of publicationPublished 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.
    University Bibliography Jena:
    fsu_mods_00009883External link
  4. Selective-plane-activation structured illumination microscopy

    Year of publicationPublished 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
  5. Universal inverse modeling of point spread functions for SMLM localization and microscope characterization

    Year of publicationPublished 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
  6. Experimental validation of numerical point spread function calculation including aberration estimation

    Year of publicationPublished 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%.
    University Bibliography Jena:
    fsu_mods_00013604External link
  7. Resolution in super-resolution microscopy: definition, trade-offs and perspectives

    Year of publicationPublished 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
  8. Deep learning-enhanced automated mitochondrial segmentation in FIB-SEM images using an entropy-weighted ensemble approach

    Year of publicationPublished 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.
    University Bibliography Jena:
    fsu_mods_00018454External link
  9. Structured illumination microscopy with extreme ultraviolet pulses

    Year of publicationPublished in:Optics Express R. Mincigrucci, E. Paltanin, J. Pelli-Cresi, F. Gala, E. Pontecorvo, L. Foglia, D. Angelis, D. Fainozzi, A. Gessini, D. Molina, O. Stranik, F. Wechsler, R. Heintzmann, J. Rothhardt, L. Loetgering, G. Ruocco, F. Bencivenga, C. Masciovecchio
  10. Nanoscale chemical characterization of secondary protein structure of F-Actin using mid-infrared photoinduced force microscopy (PiF-IR)

    Year of publicationPublished in:Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy J. Joseph, L. Spantzel, M. Ali, D. Moonnukandathil Joseph, S. Unger, K. Reglinski, C. Krafft, A. Müller, C. Eggeling, R. Heintzmann, M. Börsch, A. Press, D. Täuber
    The recently developed photoinduced force microscopy for mid-infrared (PiF-IR) offers high spectral resolution in combination with surface sensitivity and a spatial resolution in the range of a few nanometers. Although PiF-IR has primarily been applied to polymer materials, this technology presents significant potential for the chemical characterization of cellular structures approaching single-molecule sensitivity. We applied PiF-IR to differently polymerized F-Actin samples finding general agreement with FTIR spectra from the same samples. Single PiF-IR spectra of F-Actin show variations in the amide I band spectral region, which is related to secondary protein structure. Local variations are also seen in PiF-IR hyperspectra in this region. Such high sensitivity is a necessary requirement for discriminating Actin organization into bundles and other networks in cells and tissue. We applied PiF-IR to mouse liver tissue ex vivo. Single-frequency PiF-IR scans at three different IR frequencies show significant variations in local contrast. However, the presence of other proteins and the unique spatial resolution of PiF-IR pose a challenge to interpreting and validating such data. Careful design of model systems and further theoretical understanding of PiF-IR data far from bulk averages are needed to fully unfold the potential of PiF-IR for high-resolution chemical investigation in the Life Sciences.
    University Bibliography Jena:
    fsu_mods_00008945External link
  11. Inverse modelling of point spread function for single-molecule localization microscopy

    Year of publicationPublished in:Biophysical journal S. Liu, J. Hellgoth, J. Chen, L. Müller, B. Ferdman, K. Lidke, Y. Shechtman, R. Heintzmann, Y. Li, J. Ries
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