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- ItemMultimodal Molecular Imaging and Identification of Bacterial Toxins Causing Mushroom Soft Rot and Cavity Disease(Weinheim : Wiley-VCH, 2021) Dose, Benjamin; Thongkongkaew, Tawatchai; Zopf, David; Kim, Hak Joong; Bratovanov, Evgeni V.; García-Altares, María; Scherlach, Kirstin; Kumpfmüller, Jana; Ross, Claudia; Hermenau, Ron; Niehs, Sarah; Silge, Anja; Hniopek, Julian; Schmitt, Michael; Popp, Jürgen; Hertweck, ChristianSoft rot disease of edible mushrooms leads to rapid degeneration of fungal tissue and thus severely affects farming productivity worldwide. The bacterial mushroom pathogen Burkholderia gladioli pv. agaricicola has been identified as the cause. Yet, little is known about the molecular basis of the infection, the spatial distribution and the biological role of antifungal agents and toxins involved in this infectious disease. We combine genome mining, metabolic profiling, MALDI-Imaging and UV Raman spectroscopy, to detect, identify and visualize a complex of chemical mediators and toxins produced by the pathogen during the infection process, including toxoflavin, caryoynencin, and sinapigladioside. Furthermore, targeted gene knockouts and in vitro assays link antifungal agents to prevalent symptoms of soft rot, mushroom browning, and impaired mycelium growth. Comparisons of related pathogenic, mutualistic and environmental Burkholderia spp. indicate that the arsenal of antifungal agents may have paved the way for ancestral bacteria to colonize niches where frequent, antagonistic interactions with fungi occur. Our findings not only demonstrate the power of label-free, in vivo detection of polyyne virulence factors by Raman imaging, but may also inspire new approaches to disease control. © 2021 The Authors. ChemBioChem published by Wiley-VCH GmbH
- ItemRaman imaging of changes in the polysaccharides distribution in the cell wall during apple fruit development and senescence(Berlin ; Heidelberg : Springer, 2016) Szymańska-Chargot, Monika; Chylińska, Monika; Pieczywek, Piotr M.; Rösch, Petra; Schmitt, Michael; Popp, Jürgen; Zdunek, ArturMain conclusion Du ring on-tree ripening, the pectin distribution changed from polydispersed in cell wall to cumulated in cell wall corners. During apple storage, the pectin distribution returned to evenly dispersed along the cell wall. The plant cell wall influences the texture properties of fruit tissue for example apples become softer during ripening and postharvest storage. This softening process is believed to be mainly connected with changes in the cell wall composition due to polysaccharides undergoing an enzymatic degradation. These changes in polysaccharides are currently mainly investigated via chemical analysis or monoclonal labeling. Here, we propose the application of Raman microscopy for evaluating the changes in the polysaccharide distribution in the cell wall of apples during both ripening and postharvest storage. The apples were harvested 1 month and 2 weeks before optimal harvest date as well as at the optimal harvest date. The apples harvested at optimal harvest date were stored for 3 months. The Raman maps, as well as the chemical analysis were obtained for each harvest date and after 1, 2 and 3 months of storage, respectively. The analysis of the Raman maps showed that the pectins in the middle lamella and primary cell wall undergo a degradation. The changes in cellulose and hemicellulose were less pronounced. These findings were confirmed by the chemical analysis results. During development changes of pectins from a polydispersed form in the cell walls to a cumulated form in cell wall corners could be observed. In contrast after 3 months of apple storage we could observe an substantial pectin decrease. The obtained results demonstrate that Raman chemical imaging might be a very useful tool for a first identification of compositional changes in plant tissue during their development. The great advantage Raman microspectroscopy offers is the simultaneous localization and identification of polysaccharides within the cell wall and plant tissue.
- ItemFLIM data analysis based on Laguerre polynomial decomposition and machine-learning(Bellingham, Wash. : SPIE, 2021) Guo, Shuxia; Silge, Anja; Bae, Hyeonsoo; Tolstik, Tatiana; Meyer, Tobias; Matziolis, Georg; Schmitt, Michael; Popp, Jürgen; Bocklitz, ThomasSignificance: The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis. Aim: We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML). Approach: The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker. Results: The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.
- ItemA polyyne toxin produced by an antagonistic bacterium blinds and lyses a Chlamydomonad alga(Washington, DC : National Acad. of Sciences, 2021) Hotter, Vivien; Zopf, David; Kim, Hak Joong; Silge, Anja; Schmitt, Michael; Aiyar, Prasad; Fleck, Johanna; Matthäus, Christian; Hniopek, Julian; Yan, Qing; Loper, Joyce; Sasso, Severin; Hertweck, Christian; Popp, Jürgen; Mittag, MariaAlgae are key contributors to global carbon fixation and form the basis of many food webs. In nature, their growth is often supported or suppressed by microorganisms. The bacterium Pseudomonas protegens Pf-5 arrests the growth of the green unicellular alga Chlamydomonas reinhardtii, deflagellates the alga by the cyclic lipopeptide orfamide A, and alters its morphology [P. Aiyar et al., Nat. Commun. 8, 1756 (2017)]. Using a combination of Raman microspectroscopy, genome mining, and mutational analysis, we discovered a polyyne toxin, protegencin, which is secreted by P. protegens, penetrates the algal cells, and causes destruction of the carotenoids of their primitive visual system, the eyespot. Together with secreted orfamide A, protegencin thus prevents the phototactic behavior of C. reinhardtii. A mutant of P. protegens deficient in protegencin production does not affect growth or eyespot carotenoids of C. reinhardtii. Protegencin acts in a direct and destructive way by lysing and killing the algal cells. The toxic effect of protegencin is also observed in an eyeless mutant and with the colony-forming Chlorophyte alga Gonium pectorale. These data reveal a two-pronged molecular strategy involving a cyclic lipopeptide and a conjugated tetrayne used by bacteria to attack select Chlamydomonad algae. In conjunction with the bloom-forming activity of several chlorophytes and the presence of the protegencin gene cluster in over 50 different Pseudomonas genomes [A. J. Mullins et al., bioRxiv [Preprint] (2021). https://www.biorxiv.org/content/10.1101/2021.03.05.433886v1 (Accessed 17 April 2021)], these data are highly relevant to ecological interactions between Chlorophyte algae and Pseudomonadales bacteria.
- ItemBessel beam CARS of axially structured samples([London] : Macmillan Publishers Limited, part of Springer Nature, 2015) Heuke, Sandro; Zheng, Juanjuan; Akimov, Denis; Heintzmann, Rainer; Schmitt, Michael; Popp, JürgenWe report about a Bessel beam CARS approach for axial profiling of multi-layer structures. This study presents an experimental implementation for the generation of CARS by Bessel beam excitation using only passive optical elements. Furthermore, an analytical expression is provided describing the generated anti-Stokes field by a homogeneous sample. Based on the concept of coherent transfer functions, the underling resolving power of axially structured geometries is investigated. It is found that through the non-linearity of the CARS process in combination with the folded illumination geometry continuous phase-matching is achieved starting from homogeneous samples up to spatial sample frequencies at twice of the pumping electric field wave. The experimental and analytical findings are modeled by the implementation of the Debye Integral and scalar Green function approach. Finally, the goal of reconstructing an axially layered sample is demonstrated on the basis of the numerically simulated modulus and phase of the anti-Stokes far-field radiation pattern.