High photon count rates improve the quality of super-resolution fluorescence fluctuation spectroscopy

Probing the diffusion of molecules has become a routine measurement across the life sciences, chemistry and physics. It provides valuable insights into reaction dynamics, oligomerisation, molecular (re-)organisation or cellular heterogeneities. Fluorescence correlation spectroscopy (FCS) is one of the widely applied techniques to determine diffusion dynamics in two and three dimensions. This technique relies on the temporal autocorrelation of intensity fluctuations but recording these fluctuations has thus far been limited by the detection electronics, which could not efficiently and accurately time-tag photons at high count rates. This has until now restricted the range of measurable dye concentrations, as well as the data quality of the FCS recordings, especially in combination with super-resolution stimulated emission depletion (STED) nanoscopy. Here, we investigate the applicability and reliability of (STED-)FCS at high photon count rates (average intensities of more than 1 MHz) using novel detection equipment, namely hybrid detectors and real-time gigahertz sampling of the photon streams implemented on a commercial microscope. By measuring the diffusion of fluorophores in solution and cytoplasm of live cells, as well as in model and cellular membranes, we show that accurate diffusion and concentration measurements are possible in these previously inaccessible high photon count regimes. Specifically, it offers much greater flexibility of experiments with biological samples with highly variable intensity, e.g. due to a wide range of expression levels of fluorescent proteins. In this context, we highlight the independence of diffusion properties of cytosolic GFP in a concentration range of approx. 0.01-1 µm. We further show that higher photon count rates also allow for much shorter acquisition times, and improved data quality. Finally, this approach also pronouncedly increases the robustness of challenging live cell STED-FCS measurements of nanoscale diffusion dynamics, which we testify by confirming a free diffusion pattern for a fluorescent lipid analogue on the apical membrane of adherent cells. © The Author(s). Published by IOP Publishing Ltd

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Data from: An analysis toolbox to explore mesenchymal migration heterogeneity reveals adaptive switching between distinct modes

Mesenchymal (lamellipodial) migration is heterogeneous, although whether this reflects progressive variability or discrete, 'switchable' migration modalities, remains unclear. We present an analytical toolbox, based on quantitative single-cell imaging data, to interrogate this heterogeneity. Integrating supervised behavioral classification with multivariate analyses of cell motion, membrane dynamics, cell-matrix adhesion status and F-actin organization, this toolbox here enables the detection and characterization of two quantitatively distinct mesenchymal migration modes, termed 'Continuous' and 'Discontinuous'. Quantitative mode comparisons reveal differences in cell motion, spatiotemporal coordination of membrane protrusion/retraction, and how cells within each mode reorganize with changed cell speed. These modes thus represent distinctive migratory strategies. Additional analyses illuminate the macromolecular- and cellular-scale effects of molecular targeting (fibronectin, talin, ROCK), including 'adaptive switching' between Continuous (favored at high adhesion/full contraction) and Discontinuous (low adhesion/inhibited contraction) modes. Overall, this analytical toolbox now facilitates the exploration of both spontaneous and adaptive heterogeneity in mesenchymal migration

Cell Adhesion and Migration Analysis Toolbox

This zip file contains code, data and documentation associated with the Cell Adhesion and Migration Analysis Toolbox. This Toolbox provides data analysis and organization tools for cell adhesion and migration data. To this end, this Toolbox provides a set of analysis features that can be combined to gain a coherent and comprehensive picture of the cell adhesion and migration systems. Some of the provided features may also be used in isolation to address alternate questions (i.e. complex processes other than cell adhesion/migration). The code is tailored to handle microscopy-derived multi-scale, multivariate time series data that can be image based or constitute extracted quantitative feature datasets from cell adhesion and migration experiments. This document describes the features listed in the table of contents and how the Cell adhesion and migration analysis Toolbox allows their implementation

Fibronectin_Modulation_Dataset

The associated .csv files constitute quantitative datasets underpinning the manuscript "Heterogeneity in mesenchymal motility reflects adaptive switching between two distinct migration modes", by Shafqat-Abbasi et al. Three datasets are presented with equivalent structures, reflecting data derived from multiscale, high resolution imaging of randomly migrating H1299-PL cells. These datasets focus on comparison of cells: attached on different concentrations of fibronectin (extracellular-matrix ligand, Fibronectin_Modulation_Dataset); following inhibition of Rho-associated kinase (ROCK, Y27632 inhibitor) or a control treatment (DMSO, ROCK_Modulation_Dataset); or following siRNA-mediated depletion of talin 1 protein levels compared to control siRNA treatment (Talin_Modulation_Dataset). Accordingly, each data set is divided into two conditions (denoted “1” or “2”), between which feature values are quantitatively compared throughout the manuscript. In each case, the values 1 and 2 in the “condition” column refer to: Fibronectin_Modulation_Dataset: 1 = 2.5 µg/ml FN (2580 observations), 2 = 10 µg/ml FN (7000 observations); ROCK_Modulation_Dataset: 1 = DMSO (2666 observations), 2 = 6 µM ROCK Inh (985 observations); Talin_Modulation_Dataset: 1 = Control siRNA (3154 observations), 2 = talin 1 siRNA (6263 observations). Column structure within the files is as follows. The first 6 columns are indexing columns, wherein the: experimental condition is defined (1 vs 2, as above); experimental date is define; individual cell identities are defined; the mesenchymal cell migration mode is defined (0 = undetermined, e.g. dead cells or cells in contact; 1 = Discontinuous migration mode; 2 = Continuous migration mode); cell centre of area (row), and; cell centre of area (column) are defined. The following 60 columns define quantitative features extracted based on image analyses. These include 5 Behavioral features and 55 Organizational features, as defined in Figure 3 – figure supplement 1

PAK4 suppresses RELB to prevent senescence-like growth arrest in breast cancer

Overcoming cellular growth restriction, including the evasion of cellular senescence, is a hallmark of cancer. We report that PAK4 is overexpressed in all human breast cancer subtypes and associated with poor patient outcome. In mice, MMTV-PAK4 overexpression promotes spontaneous mammary cancer, while PAK4 gene depletion delays MMTV-PyMT driven tumors. Importantly, PAK4 prevents senescence-like growth arrest in breast cancer cells in vitro, in vivo and ex vivo, but is not needed in non-immortalized cells, while PAK4 overexpression in untransformed human mammary epithelial cells abrogates H-RAS-V12-induced senescence. Mechanistically, a PAK4 – RELB - C/EBPβ axis controls the senescence-like growth arrest and a PAK4 phosphorylation residue (RELB-Ser151) is critical for RELB-DNA interaction, transcriptional activity and expression of the senescence regulator C/EBPβ. These findings establish PAK4 as a promoter of breast cancer that can overcome oncogene-induced senescence and reveal a selective vulnerability of cancer to PAK4 inhibition