Drift correction for single-molecule imaging by molecular constraint field, a distance minimum metric

The promise and peril of comparing fluorescence lifetime in biology revealed by simulations

Signaling dynamics are crucial in biological systems, and biosensor-based real-time imaging has revolutionized their analysis. Fluorescence lifetime imaging microscopy (FLIM) excels over the widely used fluorescence intensity imaging by allowing the measurement of absolute signal levels, independent of sensor concentration. This capability enables the comparison of signaling dynamics across different animals, body regions, and timeframes. However, FLIM's advantage can be compromised by factors like autofluorescence in biological experiments. To address this, we introduce FLiSimBA, a flexible computational framework for realistic F luorescence Li fetime Sim ulation for B iological A pplications. Through simulations, we analyze the signal-to-noise ratios of fluorescence lifetime data, determining measurement uncertainty and providing necessary error bars for lifetime measurements. Furthermore, we challenge the belief that fluorescence lifetime is unaffected by sensor expression and establish quantitative limits to this insensitivity in biological applications. Additionally, we propose innovations, notably multiplexed dynamic imaging that combines fluorescence intensity and lifetime measurements. This innovation can transform the number of signals that can be simultaneously monitored, thereby enabling a systems approach in studying signaling dynamics. Thus, by incorporating diverse factors into our simulation framework, we uncover surprises, identify limitations, and propose advancements for fluorescence lifetime imaging in biology. This quantitative framework supports rigorous experimental design, facilitates accurate data interpretation, and paves the way for technological advancements in fluorescence lifetime imaging.

Machine Learning for Single-Molecule Localization Microscopy: From Data Analysis to Quantification

Single-molecule localization microscopy (SMLM) is a versatile tool for realizing nanoscale imaging with visible light and providing unprecedented opportunities to observe bioprocesses. The integration of machine learning with SMLM enhances data analysis by improving efficiency and accuracy. This tutorial aims to provide a comprehensive overview of the data analysis process and theoretical aspects of SMLM, while also highlighting the typical applications of machine learning in this field. By leveraging advanced analytical techniques, SMLM is becoming a powerful quantitative analysis tool for biological research.

Robust, fiducial-free drift correction for super-resolution imaging

We describe a robust, fiducial-free method of drift correction for use in single molecule localization-based super-resolution methods. The method combines periodic 3D registration of the sample using brightfield images with a fast post-processing algorithm that corrects residual registration errors and drift between registration events. The method is robust to low numbers of collected localizations, requires no specialized hardware, and provides stability and drift correction for an indefinite time period.

A mean shift algorithm for drift correction in localization microscopy

Single-molecule localization microscopy techniques transcend the diffraction limit of visible light by localizing isolated emitters sampled stochastically. This time-lapse imaging necessitates long acquisition times, over which sample drift can become large relative to the localization precision. Here, we present an efficient and robust method for estimating drift, using a simple peak-finding algorithm based on mean shifts that is effective for single-molecule localization microscopy in two or three dimensions.

Real-time 3D single-molecule localization microscopy analysis using lookup tables

Herein, we present a new algorithm for real-time analysis of 3D single molecule localization microscopy images with a small impact on fitting accuracy using lookup-tables with discrete xyz-positions. The algorithm realizes real-time visualization during acquisition. We demonstrate its performance on simulated and measured data. Additionally, combining real-time fitting with a feedback loop controlling the activation laser pulse keeps the number of emitters per image frame constant.

Dual Channel Microfluidics for Mimicking the Blood-Brain Barrier

High-resolution imaging is essential for analysis of the steps and way stations of cargo transport in in vitro models of the endothelium. In this study, we demonstrate a microfluidic system consisting of two channels horizontally separated by a cell-growth-promoting membrane. Its design allows for high-resolution (down to single-molecule level) imaging using a high numerical aperture objective with a short working distance. To reduce optical aberrations and enable single-molecule-sensitive imaging, an observation window was constructed in the membrane via laser cutting with subsequent structuring using 3D multiphoton lithography for improved cell growth. The upper channel was loaded with endothelial cells under flow conditions, which showed polarization and junction formation. A coculture of human vascular endothelial cells with pericytes was developed that mimics the blood-brain barrier. Finally, this dual channel microfluidics system enabled 3D localization microscopy of the cytoskeleton and 3D single-molecule-sensitive tracing of lipoprotein particles.

Sample drift estimation method based on speckle patterns formed by backscattered laser light

Single molecule localization microscopy (SMLM) has been established to acquire images with unprecedented resolution down to several nanometers. A typical time scale for image acquisition is several minutes to hours. Yet it is difficult to avoid completely sample drift for long time measurements. To estimate drift, we present a method based on the evaluation of speckle patterns formed by backscattered laser light from the cells using a single molecule localization microscope setup. A z-stack of unique speckle patterns is recorded prior to the measurements as a three-dimensional position reference. During the experiment, images of scattered laser light were acquired, and correlated individually with each of the images of the speckle reference stack to estimate x, y and z drift. Our method shows highly comparable results with a fiducial marker approach, achieving a precision of several nanometers. This method allows for high precision three dimensional drift correction of microscope systems without any additional sample preparation.

Localization Microscopy of Actin Cytoskeleton in Human Platelets

Here, we measure the actin cytoskeleton arrangement of different morphological states of human platelets using a new protocol for photo-switching of rhodamine class fluorophores. A new medium composition was established for imaging the cytoskeleton using Alexa Fluor 488 conjugated to phalloidin. Morphological states of platelets bound to a glass substrate are visualized and quantified by two-dimensional localization microscopy at nanoscopic resolution. Marker-less drift correction yields localization of individual Alexa 488 conjugated to phalloidin with a positional accuracy of 12 nm.