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

In single-particle tracking, 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 single-particle tracking: temporal analysis of relative distances (TARDIS). In TARDIS, an all-to-all distance analysis between localizations is performed with increasing temporal shifts. These pairwise distances represent either intraparticle distances originating from the same particle, or interparticle distances originating from unrelated particles, and are fitted analytically to obtain quantitative measures on particle dynamics. We showcase that TARDIS outperforms tracking algorithms, benchmarked on simulated and experimental data of varying complexity. We further show that TARDIS performs accurately in complex conditions characterized by high particle density, strong emitter blinking or false-positive localizations, and is in fact limited by the capabilities of localization algorithms. TARDIS' robustness enables fivefold shorter measurements without loss of information.

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

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.

Addressing spatiotemporal signal variations in pair correlation function analysis.

Fluorescence correlation spectroscopy (FCS) is a cornerstone technique in optical microscopy to measure, for example, the concentration and diffusivity of fluorescent emitters and biomolecules in solution. The application of FCS to complex biological systems, however, is fraught with inherent intricacies that impair the interpretation of correlation patterns. Critical among these intricacies are temporal variations beyond diffusion in the quantity, intensity, and spatial distribution of fluorescent emitters. These variations introduce distortions into correlated intensity data, thus compromising the accuracy and reproducibility of the analysis. This issue is accentuated in imaging-based approaches such as pair correlation function (pCF) analysis due to their broader regions of interest compared with point-detector-based approaches. Despite ongoing developments in FCS, attention to systems characterized by a spatiotemporal-dependent probability distribution function (ST-PDF) has been lacking. To address this knowledge gap, we developed a new analytical framework for ST-PDF systems that introduces a dual-timescale model function within the conventional pCF analysis. Our approach selectively differentiates the signals associated with rapid processes, such as particle diffusion, from signals stemming from spatiotemporal variations in the distribution of fluorescent emitters occurring at extended delay timescales. To corroborate our approach, we conducted proof-of-concept experiments on an ST-PDF system, wherein the, initially, uniform distribution of fluorescent microspheres within a microfluidic channel changes into a localized accumulation of microspheres over time. Our framework is offering a comprehensive solution for investigating various phenomena such as biomolecular binding, sedimentation, and particle accumulation.

Droplet size dependency and spatial heterogeneity of lipid oxidation in whey protein isolate-stabilized emulsions.

Spatiotemporal assessment of lipid and protein oxidation is key for understanding quality deterioration in emulsified food products containing polyunsaturated fatty acids. In this work, we first mechanistically validated the use of the lipid oxidation-sensitive fluorophore BODIPY 665/676 as a semi-quantitative marker for local peroxyl radical formation. Next, we assessed the impact of microfluidic and colloid mill emulsification (respectively producing mono- and polydisperse droplets) on local protein and lipid oxidation kinetics in whey protein isolate (WPI)-stabilized emulsions. We further used BODIPY 581/591 C11 and CAMPO-AFDye 647 as colocalisation markers for lipid and protein oxidation. The polydisperse emulsions showed an inverse relation between droplet size and lipid oxidation rate. Further, we observed less protein and lipid oxidation occurring in similar sized droplets in monodisperse emulsions. This observation was linked to more heterogeneous protein packing at the droplet surface during colloid mill emulsification, resulting in larger inter-droplet heterogeneity in both protein and lipid oxidation. Our findings indicate the critical roles of emulsification methods and droplet sizes in understanding and managing lipid oxidation.