Imaging fluorescence (cross-) correlation spectroscopy in live cells and organisms.

Single-plane illumination (SPIM) or total internal reflection fluorescence (TIRF) microscopes can be combined with fast and single-molecule-sensitive cameras to allow spatially resolved fluorescence (cross-) correlation spectroscopy (FCS or FCCS, hereafter referred to FCS/FCCS). This creates a powerful quantitative bioimaging tool that can generate spatially resolved mobility and interaction maps with hundreds to thousands of pixels per sample. These massively parallel imaging schemes also cause less photodamage than conventional single-point confocal microscopy-based FCS/FCCS. Here we provide guidelines for imaging FCS/FCCS measurements on commercial and custom-built microscopes (including sample preparation, setup calibration, data acquisition and evaluation), as well as anticipated results for a variety of in vitro and in vivo samples. For a skilled user of an available SPIM or TIRF setup, sample preparation, microscope alignment, data acquisition and data fitting, as described in this protocol, will take ∼1 d, depending on the sample and the mode of imaging.

Dual-color fluorescence cross-correlation spectroscopy on a single plane illumination microscope (SPIM-FCCS).

Single plane illumination microscopy based fluorescence correlation spectroscopy (SPIM-FCS) is a new method for imaging FCS in 3D samples, providing diffusion coefficients, flow velocities and concentrations in an imaging mode. Here we extend this technique to two-color fluorescence cross-correlation spectroscopy (SPIM-FCCS), which allows to measure molecular interactions in an imaging mode. We present a theoretical framework for SPIM-FCCS fitting models, which is subsequently used to evaluate several test measurements of in-vitro (labeled microspheres, several DNAs and small unilamellar vesicles) and in-vivo samples (dimeric and monomeric dual-color fluorescent proteins, as well as membrane bound proteins). Our method yields the same quantitative results as the well-established confocal FCCS, but in addition provides unmatched statistics and true imaging capabilities.

Model based scattering correction in time-of-flight cameras.

In-camera light scattering is a systematic error of Time-of-Flight depth cameras that significantly reduces the accuracy of the systems. A completely new model is presented, based on raw data calibration and only one additional intrinsic camera parameter. It is shown that the approach effectively removes the errors of in-camera light scattering.

A strategy for identifying fluorescence intensity profiles of single rod-shaped cells.

The extraction of fluorescence intensity profiles of single cells from image data is a common challenge in cell biology. The manual segmentation of cells, the extraction of cell orientation and finally the extraction of intensity profiles are time-consuming tasks. This article proposes a routine for the segmentation of single rod-shaped cells (i.e. without neighboring cells in a distance of the cell length) from image data combined with an extraction of intensity distributions along the longitudinal cell axis under the aggravated conditions of (i) a low spatial resolution and (ii) lacking information on the imaging system i.e. the point spread function and signal-to-noise ratio. The algorithm named cipsa transfers a new approach from particle streak velocimetry to cell classification interpreting the rod-shaped as streak-like structures. An automatic reduction of systematic errors such as photobleaching and defocusing is included to guarantee robustness of the proposed approach under the described conditions and to the convenience of end-users unfamiliar with image processing. Performance of the algorithm has been tested on image sequences with high noise level produced by an overlay of different error sources. The developed algorithm provides a user-friendly, stand-alone procedure.

From chaos to split-ups--SHG microscopy reveals a specific remodelling mechanism in ageing dystrophic muscle.

Duchenne muscular dystrophy (DMD) is a common inherited muscle disease showing chronic inflammation and progressive muscle weakness. Absent dystrophin renders sarcolemma more Ca(2+) -permeable, disturbs signalling and triggers inflammation. Sustained degeneration/regeneration cycles render muscle cytoarchitecture susceptible to remodelling. Quantitative morphometry was introduced in living cells using second-harmonic generation (SHG) microscopy of myosin. As the time course of cellular remodelling is not known, we used SHG microscopy in mdx muscle fibres over a wide age range for three-dimensional (3D) rendering and detection of verniers and cosine angle sums (CASs). Wild-type (wt) and transgenic mini-dystrophin mice (MinD) were also studied. Vernier densities (VDs) declined in wt and MinD fibres until adulthood, while in mdx fibres, VDs remained significantly elevated during the life span. CAS values were close to unity in adult wt and MinD fibres, in agreement with tight regular myofibril orientation, while always smaller in mdx fibres. Using SHG 3D morphometry, we identified two types of altered ultrastructure: branched fibres and a novel, previously undetected 'chaotic' fibre type, both of which can be classified by distinct CAS and VD combinations. We present a novel model of tissue remodelling in dystrophic progression with age that involves the transition from normal to chaotic to branched fibres. Our model predicts a ~50% contribution of altered cytoarchitecture to progressive force loss with age. We also provide an improved automated image algorithm that is suitable for future ageing studies in human myopathies.

Automated multiscale morphometry of muscle disease from second harmonic generation microscopy using tensor-based image processing.

Practically, all chronic diseases are characterized by tissue remodeling that alters organ and cellular function through changes to normal organ architecture. Some morphometric alterations become irreversible and account for disease progression even on cellular levels. Early diagnostics to categorize tissue alterations, as well as monitoring progression or remission of disturbed cytoarchitecture upon treatment in the same individual, are a new emerging field. They strongly challenge spatial resolution and require advanced imaging techniques and strategies for detecting morphological changes. We use a combined second harmonic generation (SHG) microscopy and automated image processing approach to quantify morphology in an animal model of inherited Duchenne muscular dystrophy (mdx mouse) with age. Multiphoton XYZ image stacks from tissue slices reveal vast morphological deviation in muscles from old mdx mice at different scales of cytoskeleton architecture: cell calibers are irregular, myofibrils within cells are twisted, and sarcomere lattice disruptions (detected as "verniers") are larger in number compared to samples from healthy mice. In young mdx mice, such alterations are only minor. The boundary-tensor approach, adapted and optimized for SHG data, is a suitable approach to allow quick quantitative morphometry in whole tissue slices. The overall detection performance of the automated algorithm compares very well with manual "by eye" detection, the latter being time consuming and prone to subjective errors. Our algorithm outperfoms manual detection by time with similar reliability. This approach will be an important prerequisite for the implementation of a clinical image databases to diagnose and monitor specific morphological alterations in chronic (muscle) diseases.

Micro-flow analysis by molecular tagging velocimetry and planar Raman-scattering.

The two dimensional molecular tagging velocimetry (2D-MTV) has been used to measure velocity fields of the flow in a micro mixer. Instead of commonly used micro particles an optical tagging of the flow has been performed by using a caged dye. The pattern generation is done by imaging a mask for the first time. This allows to generate nearly any imaginable pattern. The flow induces a deformation of the optically written pattern that can be tracked by laser induced fluorescence. The series of raw images acquired in this way were analyzed quantitatively with a novel optical flow based technique. The reference measurements have been carried out allowing to draw conclusions about the accuracy of this procedure. A comparison to the standard technique of µPIV has also been conducted. Apart from measuring flow velocities in microfluidic mixing processes, the spatial distribution of concentration fields for different species has also been measured. To this end, a new technique has been developed that allows spatial measurements from Planar Spontaneous Raman Scattering (PSRS). The Raman stray light of the relevant species has been spectrally selected by a narrow bandpass filter and thus detected unaffectedly by the Raman stray light of other species. The successful operation of this measurement procedure in micro flows will be demonstrated exemplary for a mixing process of water and ethanol.