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I am Koen J.A. Martens, a postdoc in the lab of Ulrike Endesfelder. Currently, I am at Carnegie Mellon University, Physics department, in Pittsburgh, USA, and from sept 1st 2021, I will be positioned at Bonn University, Institute for Microbiology and Biotechnology in Bonn, Germany.

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Phasor based single-molecule localization microscopy in 3D (pSMLM-3D): An algorithm for MHz localization rates using standard CPUs

Abstract

We present a fast and model-free 2D and 3D single-molecule localization algorithm that allows more than 3 × 106 localizations per second to be calculated on a standard multi-core central processing unit with localization accuracies in line with the most accurate algorithms currently available. Our algorithm converts the region of interest around a point spread function to two phase vectors (phasors) by calculating the first Fourier coefficients in both the x- and y-direction. The angles of these phasors are used to localize the center of the single fluorescent emitter, and the ratio of the magnitudes of the two phasors is a measure for astigmatism, which can be used to obtain depth information (z-direction). Our approach can be used both as a stand-alone algorithm for maximizing localization speed and as a first estimator for more time consuming iterative algorithms.

Published in Journal of Chemical Physics, 2017

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Quantitative Structural Analysis of Fat Crystal Networks by Means of Raman Confocal Imaging

Abstract

The techniques that are currently available to assess fat crystal networks are compromised with respect to invasive sample preparation and ability to quantify compositional and structural features. Raman confocal hyperspectral imaging coupled to analysis with multivariate curve resolution can address these bottlenecks, as it provides label-free, noninvasive chemical information in three dimensions (3D). We demonstrate the ability to acquire compositional maps of dispersions of micronized fat crystals (MFC) in oil, which contain local concentrations of liquid oil and solid fat with submicron spatial resolution and with acquisition times in the order of 10 min. From the compositional maps, we can derive quantitative information on the size and porosity of fat crystal flocs, as well as the solid fat content of the embedding continuous phase. Furthermore, the fractal dimension of the fat crystal network could be determined from the compositional maps via the box-counting method and via the porosities of the crystal flocs. This makes it feasible to assess the validity of the weak-link network theory under industrial relevant conditions. The confocal imaging mode allows for straightforward acquisition of 3D compositional cubes by recording a stack of two-dimensional (2D) images. The box-counting fractal dimension analysis performed on 2D maps can be extended to 3D cubes, which allows for straightforward verification that MFC networks are self‐similar rather than self-affine.

Published in Journal of the American Oil Chemists' Society, 2018

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Manipulation of Recrystallization and Network Formation of Oil-Dispersed Micronized Fat Crystals

Abstract

A detailed investigation was carried out on the modulation of the coupling between network formation and the recrystallization of oil-dispersed micronized fat crystal (MFC) nanoplatelets by varying oil composition, shear, and temperature. Sunflower (SF) and bean (BO) oils were used as dispersing media for MFC nanoplatelets. During MFC dispersion production at high shear, a significant increase in the average crystal thickness (ACT) could be observed, pointing to recrystallization of the MFC nanoplatelets. More rapid recrystallization of MFC occurred in the SF dispersion than in the BO dispersion, which is attributed to higher solubility of MFC in the SF oil. When the dispersions were maintained under low shear in narrow gap Couette geometry, we witnessed two stages of recrystallization (measured via rheo-SAXD) and the development of a local yield stress (measured via rheo-MRI). In the first stage, shear-enabled mass transfer induces rapid recrystallization of randomly distributed MFC nanoplatelets, which is reflected in a rapid increase in ACT (rheo-SAXD). The formation of a space-filling weak-link MFC network explains the increase in yield stress (assessed in real time by rheo-MRI). In this second stage, recrystallization slows down and yield stress decreases as a result of the formation of MFC aggregates in the weak link network, as observed by confocal Raman imaging. The high fractal dimension of the weak-link network indicates that aggregation takes place via a particle-cluster mechanism. The effects of oil type and shear on the recrystallization rate and network strength could be reproduced in a stirred bowl with a heterogeneous shear stress field, which opens perspectives for the rational manipulation of MFC thickness and network strength under industrial processing conditions.

Published in Langmuir, 2019

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Evaluating single-particle tracking by photo-activation localization microscopy (sptPALM) in Lactococcus lactis

Abstract

Lactic acid bacteria (LAB) are frequently used in food fermentation and are invaluable for the taste and nutritional value of the fermentation end-product. To gain a better understanding of underlying biochemical and microbiological mechanisms and cell-to-cell variability in LABs, single-molecule techniques such as single-particle tracking photo-activation localization microscopy (sptPALM) hold great promises but are not yet employed due to the lack of detailed protocols and suitable assays.

Published in Physical Biology, 2019

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Visualisation of dCas9 target search in vivo using an open-microscopy framework

Abstract

CRISPR-Cas9 is widely used in genomic editing, but the kinetics of target search and its relation to the cellular concentration of Cas9 have remained elusive. Effective target search requires constant screening of the protospacer adjacent motif (PAM) and a 30 ms upper limit for screening was recently found. To further quantify the rapid switching between DNA-bound and freely-diffusing states of dCas9, we developed an open-microscopy framework, the miCube, and introduce Monte-Carlo diffusion distribution analysis (MC-DDA). Our analysis reveals that dCas9 is screening PAMs 40% of the time in Gram-positive Lactoccous lactis, averaging 17 ± 4 ms per binding event. Using heterogeneous dCas9 expression, we determine the number of cellular target-containing plasmids and derive the copy number dependent Cas9 cleavage. Furthermore, we show that dCas9 is not irreversibly bound to target sites but can still interfere with plasmid replication. Taken together, our quantitative data facilitates further optimization of the CRISPR-Cas toolbox.

Published in Nature Communications, 2019

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Direct Visualization of Native CRISPR Target Search in Live Bacteria Reveals Cascade DNA Surveillance Mechanism

Abstract

CRISPR-Cas systems encode RNA-guided surveillance complexes to find and cleave invading DNA elements. While it is thought that invaders are neutralized minutes after cell entry, the mechanism and kinetics of target search and its impact on CRISPR protection levels have remained unknown. Here, we visualize individual Cascade complexes in a native type I CRISPR-Cas system. We uncover an exponential relation between Cascade copy number and CRISPR interference levels, pointing to a time-driven arms race between invader replication and target search, in which 20 Cascade complexes provide 50% protection. Driven by PAM-interacting subunit Cas8e, Cascade spends half its search time rapidly probing DNA (∼30 ms) in the nucleoid. We further demonstrate that target DNA transcription and CRISPR arrays affect the integrity of Cascade and affect CRISPR interference. Our work establishes the mechanism of cellular DNA surveillance by Cascade that allows the timely detection of invading DNA in a crowded, DNA-packed environment.

Published in Molecular Cell, 2020

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Spatiotemporal Heterogeneity of κ-Carrageenan Gels Investigated via Single-Particle-Tracking Fluorescence Microscopy

Abstract

Hydrogels made of the polysaccharide κ-carrageenan are widely used in the food and personal care industry as thickeners or gelling agents. These hydrogels feature dense regions embedded in a coarser bulk network, but the characteristic size and behavior of these regions have remained elusive. Here, we use single-particle-tracking fluorescence microscopy (sptFM) to quantitatively describe κ-carrageenan gels. Infusing fluorescent probes into fully gelated κ-carrageenan hydrogels resulted in two distinct diffusional behaviors. Obstructed self-diffusion of the probes revealed that the coarse network consists of κ-carrageenan strands with a typical diameter of 3.2 ± 0.3 nm leading to a nanoprobe diffusion coefficient of ∼1–5 × 10–12 m2/s. In the dense network regions, we found a fraction with a largely decreased diffusion coefficient of ∼1 × 10–13 m2/s. We also observed dynamic exchange between these states. The computation of spatial mobility maps from the diffusional data indicated that the dense network regions have a characteristic diameter of ∼1 μm and show mobility on the second-to-minute timescale. sptFM provides an unprecedented view of spatiotemporal heterogeneity of hydrogel networks, which we believe bears general relevance for understanding transport and release of both low- and high-molecular weight solutes.

Published in Langmuir, 2020

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Integrating engineered point spread functions into the phasor-based single-molecule localization microscopy framework

Abstract

In single-molecule localization microscopy (SMLM), the use of engineered point spread functions (PSFs) provides access to three-dimensional localization information. The conventional approach of fitting PSFs with a single 2-dimensional Gaussian profile, however, often falls short in analyzing complex PSFs created by placing phase masks, deformable mirrors or spatial light modulators in the optical detection pathway. Here, we describe the integration of PSF modalities known as double-helix, saddle-point or tetra-pod into the phasor-based SMLM (pSMLM) framework enabling fast CPU based localization of single-molecule emitters with sub-pixel accuracy in three dimensions. For the double-helix PSF, pSMLM identifies the two individual lobes and uses their relative rotation for obtaining z-resolved localizations. For the analysis of saddle-point or tetra-pod PSFs, we present a novel phasor-based deconvolution approach entitled circular-tangent pSMLM. Saddle-point PSFs were experimentally realized by placing a deformable mirror in the Fourier plane and modulating the incoming wavefront with specific Zernike modes. Our pSMLM software package delivers similar precision and recall rates to the best-in-class software package (SMAP) at signal-to-noise ratios typical for organic fluorophores and achieves localization rates of up to 15 kHz (double-helix) and 250 kHz (saddle-point/tetra-pod) on a standard CPU. We further integrated pSMLM into an existing software package (SMALL-LABS) suitable for single-particle imaging and tracking in environments with obscuring backgrounds. Taken together, we provide a powerful hardware and software environment for advanced single-molecule studies.

Published in Methods, 2020

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Raw data to results: a hands-on introduction and overview of computational analysis for single-molecule localization microscopy

Abstract

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (~5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a ‘black box’ for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Published in Frontiers in Bioinformatics, 2021

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Enabling Spectrally Resolved Single-Molecule Localization Microscopy at High Emitter Densities

Abstract

Single-molecule localization microscopy (SMLM) is a powerful super-resolution technique for elucidating structure and dynamics in the life- and material sciences. Simultaneously acquiring spectral information (spectrally resolved SMLM, sSMLM) has been hampered by several challenges: an increased complexity of the optical detection pathway, lower accessible emitter densities, and compromised spatio-spectral resolution. Here we present a single-component, low-cost implementation of sSMLM that addresses these challenges. Using a low-dispersion transmission grating positioned close to the image plane, the +1st diffraction order is minimally elongated and is analyzed using existing single-molecule localization algorithms. The distance between the 0th and 1st order provides accurate information on the spectral properties of individual emitters. This method enables a 5-fold higher emitter density while discriminating between fluorophores whose peak emissions are less than 15 nm apart. Our approach can find widespread use in single-molecule applications that rely on distinguishing spectrally different fluorophores under low photon conditions.

Published in Nano Letters, 2022

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Temporal analysis of relative distances (TARDIS) is a robust, parameter-free alternative to single-particle tracking

Abstract

In single-particle tracking (spt), individual particles are localized and tracked over time to probe their diffusion and molecular interactions. Temporal crossing of trajectories, blinking particles, and false-positive localizations present computational challenges that have remained difficult to overcome. Here, we introduce a robust, parameter-free alternative to spt: TARDIS. In TARDIS, an all-to-all distance analysis between localizations is performed with increasing temporal shifts. These pairwise distances fall in two categories: inter-particle distances not originating from the same particle, and intra-particle distances originating from the same particle. Since the distribution of inter-particle distances is unaffected by temporal shifts, the distribution of particle jump distances can be analytically fitted by analysing multiple temporal shifts. TARDIS outperforms existing tracking algorithms especially in complex conditions, and is even robust in scenarios that exceed the capabilities of current localization algorithms. Using TARDIS, we further show that measurements can be five-fold shorter without loss of information.

Published in Nature Methods, 2024

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Live-cell imaging reveals the trade-off between target search flexibility and efficiency for Cas9 and Cas12a

Abstract

CRISPR-Cas systems have widely been adopted as genome editing tools, with two frequently employed Cas nucleases being SpyCas9 and LbCas12a. Although both nucleases use RNA guides to find and cleave target DNA sites, the two enzymes differ in terms of protospacer-adjacent motif (PAM) requirements, guide architecture and cleavage mechanism. In the last years, rational engineering led to the creation of PAM-relaxed variants SpRYCas9 and impLbCas12a to broaden the targetable DNA space. By employing their catalytically inactive variants (dCas9/dCas12a), we quantified how the protein-specific characteristics impact the target search process. To allow quantification, we fused these nucleases to the photoactivatable fluorescent protein PAmCherry2.1 and performed single-particle tracking in cells of Escherichia coli. From our tracking analysis, we derived kinetic parameters for each nuclease with a non-targeting RNA guide, strongly suggesting that interrogation of DNA by LbdCas12a variants proceeds faster than that of SpydCas9. In the presence of a targeting RNA guide, both simulations and imaging of cells confirmed that LbdCas12a variants are faster and more efficient in finding a specific target site. Our work demonstrates the trade-off of relaxing PAM requirements in SpydCas9 and LbdCas12a using a powerful framework, which can be applied to other nucleases to quantify their DNA target search.

Published in Nucleic Acid Research, 2024

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EVE is an open modular data analysis software for event-based localization microscopy

Abstract

Event-based sensors (EBS), or neuromorphic vision sensors, offer a novel approach to imaging by recording light intensity changes asynchronously, unlike conventional cameras that capture light over fixed exposure times. This capability results in high temporal resolution, reduced data redundancy, and a wide dynamic range. This makes EBS ideal for Single-Molecule Localization Microscopy (SMLM) as SMLM relies on the sequential imaging of sparse, blinking fluorescent emitters to achieve super-resolution. Recent studies have shown that EBS can effectively capture these emitters, achieving spatial resolution comparable to traditional cameras. However, existing analyses of event-based SMLM (eveSMLM) data have relied on converting event lists into image frames for conventional analysis, limiting the full potential of the technology.

To overcome this limitation, we developed EVE, a specialized software for analyzing eveSMLM data. EVE offers an integrated platform for detection, localization, and post-processing, with various algorithmic options tailored for the unique structure of eveSMLM data. EVE is user-friendly and features an open, modular infrastructure that supports ongoing development and optimization. EVE is the first dedicated tool for event-based SMLM, transforming the analysis process to fully utilize the spatiotemporal data generated by EBS. This allows researchers to explore the full potential of eveSMLM and encourages the development of new analytical methods and experimental improvements.

Published in bioRxiv, 2024

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