Single-particle tracking is an important technique in the life sciences to understand the kinetics of biomolecules. Observed diffusion coefficients in vivo, for example, enable researchers to determine whether biomolecules are moving alone, as part of a larger complex or are bound to large cellular components such as the membrane or chromosomal DNA. A remaining challenge has been to retrieve quantitative kinetic models especially for molecules that rapidly interchange between different diffusional states. Here, we present analytic diffusion distribution analysis (anaDDA), a framework that allows extracting transition rates from distributions of observed diffusion coefficients. We show that theoretically predicted distributions accurately match simulated distributions and that anaDDA outperforms existing methods to retrieve kinetics especially in the fast regime of 0.1-10 transitions per imaging frame. AnaDDA does account for the effects of confinement and tracking window boundaries. Furthermore, we added the option to perform global fitting of data acquired at different frame times, to allow complex models with multiple states to be fitted confidently. Previously, we have started to develop anaDDA to investigate the target search of CRISPR-Cas complexes. In this work, we have optimized the algorithms and reanalysed experimental data of DNA polymerase I diffusing in live E. coli. We found that long-lived DNA interaction by DNA polymerase are more abundant upon DNA damage, suggesting roles in DNA repair. We further revealed and quantified fast DNA probing interactions that last shorter than 10 ms. AnaDDA pushes the boundaries of the timescale of interactions that can be probed with single-particle tracking and is a mathematically rigorous framework that can be further expanded to extract detailed information about the behaviour of biomolecules in living cells.
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 has 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 diffusional data indicated that the dense network regions have a characteristic diameter of ~1 µm and are itself mobile on the seconds-to-minutes timescale. sptFM provides an unprecedented view on spatiotemporal heterogeneity of hydrogel networks, which we believe bears general relevance for understanding transport and release of both low- and high molecular weight solutes.
The point spread function (PSF) of single molecule emitters can be engineered in the Fourier plane to encode three-dimensional localization information, creating double-helix, saddle-point or tetra-pod PSFs. Here, we describe and assess adaptations of the phasor-based single-molecule localization microscopy (pSMLM) algorithm to localize single molecules using these PSFs with sub-pixel accuracy. For double-helix, pSMLM identifies the two individual lobes and uses their relative rotation for obtaining z-resolved localizations, while for saddle-point or tetra-pod, a novel phasor-based deconvolution approach is used. The 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. pSMLM substantially improves the localization rate by a factor of 2 – 4x on a standard CPU, with 1-1.5·104 (double-helix) or 2.5·105 (saddle-point/tetra-pod) localizations/second.
With Mariska, the third PhD student in our NWO funded LocalBioFood project on super-resolution based localisation of biomolecules at food-related interfaces has started. Mariska started her PhD thesis in the Voets lab in Eindhoven and will relocate to our lab in early 2022.
Dani started his BSc thesis in the lab during Covid-19 times. He will look into improving our computational workflow for single-particle tracking in live cells.
Ezra just started his BSc thesis in a new project together with the Laboratory of Microbiology (Wen Wu & Dr. Raymond Staals). He will work on visualising CRISPR-Cas interactions in live bacteria using sptPALM.
CRISPR-Cas systems encode RNA-guided surveil-lance complexes to find and cleave invading DNA elements. While it is thought that invaders are neutralized minutes after cell entry, the mechanism andkinetics of target search and its impact on CRISPRprotection levels have remained unknown. Here, wevisualize 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 subunitCas8e, 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.
Fantastic news: Our miCube microscopy platform and the recent publication “Visualisation of dCas9 target search in vivo using an open-microscopy framework” [link] was featured in Nature Methods [link]. Thank you Dr. Strack!
47, 10788, 2019, [link]
, Nucleic Acid Research,
DNA-binding proteins utilise different recognition mechanisms to locate their DNA targets; some proteins recognise specific DNA sequences, while others interact with specific DNA structures. While sequence-specific DNA binding has been studied extensively, structure-specific recognition mechanisms remain unclear. Here, we study structure-specific DNA recognition by examining the structure and dynamics of DNA polymerase I Klenow Fragment (Pol) substrates both alone and in DNA–Pol complexes. Using a docking approach based on a network of 73 distances collected using single-molecule FRET, we determined a novel solution structure of the single-nucleotide-gapped DNA–Pol binary complex. The structure resembled existing crystal structures with regards to the downstream primer-template DNA substrate, and revealed a previously unobserved sharp bend (∼120°) in the DNA substrate; this pronounced bend was present in living cells. MD simulations and single-molecule assays also revealed that 4–5 nt of downstream gap-proximal DNA are unwound in the binary complex. Further, experiments and coarse-grained modelling showed the substrate alone frequently adopts bent conformations with 1–2 nt fraying around the gap, suggesting a mechanism wherein Pol recognises a pre-bent, partially-melted conformation of gapped DNA. We propose a general mechanism for substrate recognition by structure-specific enzymes driven by protein sensing of the conformational dynamics of their DNA substrates.
Šarūnė recently started her Erasmus+ internship in the group. She will characterise a variety of fluidic devices that we got our hands on including devices for high throughput smFRET screening, trapping of bacteria and establishing DNA curtains. Elmar started his MSc thesis and will utilise new DNA constructs for smFRET based studies of ARF transcription factor binding.