SOFI Simulation Tool: A Software Package for Simulating and Testing Super-Resolution Optical Fluctuation Imaging

Super-resolution optical fluctuation imaging (SOFI) allows one to perform sub-diffraction fluorescence microscopy of living cells. By analyzing the acquired image sequence with an advanced correlation method, i.e. a high-order cross-cumulant analysis, super-resolution in all three spatial dimensions can be achieved. Here we introduce a software tool for a simple qualitative comparison of SOFI images under simulated conditions considering parameters of the microscope setup and essential properties of the biological sample. This tool incorporates SOFI and STORM algorithms, displays and describes the SOFI image processing steps in a tutorial-like fashion. Fast testing of various parameters simplifies the parameter optimization prior to experimental work. The performance of the simulation tool is demonstrated by comparing simulated results with experimentally acquired data

Informal interorganizational relations and dynamic capabilities : an analysis of microfoundations

Alors que les relations formelles entre organisations comme les alliances ont été largement étudiées, les relations inter-organisationnelles informelles demandent à être mieux comprises. Comment l'organisation gère-t-elle ses relations inter-organisationnelles informelles ? Quels sont les effets de ces relations sur l'entreprise ? Comment peut-on essayer d'organiser d'une façon consciente des actions d'influence de l'environnement au travers de ces relations ? Pour aborder ces questions, nous avons choisi d'utiliser le cadre de la théorie des capacités dynamiques, qui accorde une place importante aux relations entre l'entreprise et son environnement. Les capacités dynamiques de l'entreprise peuvent être définies comme la capacité à détecter et façonner des opportunités et des menaces, à saisir des opportunités, et à reconfigurer les ressources de la firme. Répondant à l'appel des chercheurs sur les capacités dynamiques, cette thèse analyse les micro-fondations de ces capacités. Notre étude s'appuie sur une analyse des individus "passeurs de frontières" qui participent aux relations inter-organisationnelles informelles au nom de leur entreprise. Nos travaux pointent les contributions des passeurs de frontières aux capacités dynamiques de l'entreprise et conceptualisent la capacité à gérer des relations inter-organisationnelles informelles comme capacité dynamiqueWhereas formal relations such as alliances have been well-studied, informal inter-organizational relations still need to be analyzed. This gap in the literature leads to the following research questions: How do organizations manage their informal inter-organizational relations? What are the effects of such relations? How can firms organize influencing activities based on these relations? The theory of dynamic capabilities addresses relations between the firm and its environment. The dynamic capabilities of the firm can be defined as the capacity of the firm to sense and shape opportunities and threats, to seize opportunities and to reconfigure assets. They permit the organization to adapt to and to shape its environment. This work contributes to answering the call from researchers to analyze the microfoundations of dynamic capabilities. It studies the role played by boundary spanners, individuals playing an interfacing role between the firm and its environment, in the dynamic capabilities of the firm. Further, this research leads to the conceptualization of the capacity to manage informal interorganizational relations as a dynamic capability allowing the firm to develop its absorptive capacity, legitimacy and influence on its environmen

Sub-second, super-resolved imaging of biological systems using parallel EO-STED

We present a parallel stimulated emission depletion (STED) nanoscope with no mechanical moving parts and sub-millisecond pixel dwell times, relying on electro-optical (EO) phase modulators. The nanoscope offers 1225-fold parallelization over single-doughnut-scanning STED and achieves a spatial resolution of 35 nm. We imaged immunostained nuclear pore complexes of zebrafish within their natural biological environment, demonstrating spatial and temporal resolutions of 56 nm and 0.2 s, respectively. Furthermore, we show parallel EO-STED sub-second imaging of microtubules inside living cells. Finally, we reveal the nanodomain organization of a eukaryotic initiation factor within the processing bodies of fixed cells. The potential of parallel EO-STED to offer microsecond pixel dwell times over large fields of view promises millisecond STED imaging.</jats:p

Simulation of single-protein nanopore sensing shows feasibility for whole-proteome identification

Single-molecule techniques for protein sequencing are making headway towards single-cell proteomics and are projected to propel our understanding of cellular biology and disease. Yet, single cell proteomics presents a substantial unmet challenge due to the unavailability of protein amplification techniques, and the vast dynamic-range of protein expression in cells. Here, we describe and computationally investigate the feasibility of a novel approach for single-protein identification using tri-color fluorescence and plasmonic-nanopore devices. Comprehensive computer simulations of denatured protein translocation processes through the nanopores show that the tri-color fluorescence time-traces retain sufficient information to permit pattern-recognition algorithms to correctly identify the vast majority of proteins in the human proteome. Importantly, even when taking into account realistic experimental conditions, which restrict the spatial and temporal resolutions as well as the labeling efficiency, and add substantial noise, a deep-learning protein classifier achieves 97% whole-proteome accuracies. Applying our approach for protein datasets of clinical relevancy, such as the plasma proteome or cytokine panels, we obtain ~98% correct protein identification. This study suggests the feasibility of a method for accurate and high-throughput protein identification, which is highly versatile and applicable.</div

Simulation of the fluorescence signals generated during the translocation of the SDS-denatured PH and SEC7 domain-containing (PSD) protein.

(a) The nanopore diameter and height were set to 3 and 5 nm, respectively, and the plasmonic architecture deposited on its ‘top-side’ produced a confined excitation profile (14–20 nm axial full-width half maximum) whose color map displayed on the left indicates the excitation near field enhancement at a wavelength of 640 nm (modeled using FDTD, see S1 Note). Two snapshots of the translocation process are shown and denoted by the timepoints t0 and t1 at which they were respectively taken. Energy transfer, photo-bleaching, incomplete labeling and non-specific labeling are indicated by dotted yellow lines, solid grey, purple and green arrows, respectively. (b) Zoomed in region of the polypeptide in which Forster resonance energy transfer (FRET) is shown in greater details. In this configuration, energy was transferred from lysine fluorophores to cysteine and methionine emitters, and from cysteine to methionine fluorophores. (c) The fluorescence emission rate of each labeled amino-acid was modeled as either a two-state or three-state system (see online methods for further details and in which kF+ and kF- refer to kFRET,+ and kFRET,-, respectively). kexc denotes the absorption rate, kisc the inter-system crossing rate and kT1 the triplet state relaxation rate. Fluorophores are depicted in a color which denote the excitation wavelength with which they are excited or the channel to which they belong. (d) Schematics of the nanopore chip and optical system, which includes a high NA water immersion objective lens, three excitation laser lines and corresponding APDs. The nanopore chip is made of four consecutive layers: silicon (grey), silicon nitride (green) in which the nanopore is drilled, titanium oxide (grey blue) and gold (orange).</p

Measurements of SDS-denatured human serum albumin translocations through solid-state nanopores.

(a) Electrical events of albumin translocating through a 4 nm-wide nanopore measured at 300 mV. (b) Scatter plot of the fractional blockade current IB versus the translocation time t, with its corresponding density map. The number of translocations events displayed amounts to 900. The inset shows the dwell-time histogram, fitted to an exponential decay with characteristic time of 94.3±7.2 μs.</p

Simulation of single-protein nanopore sensing shows feasibility for whole-proteome identification - Fig 6

CNN-based classification results of: a) whole proteome, b) plasma proteome, and c) a cytokine panel. The fractions of the correctly-identified translocation events from whole-proteome classifications repeated five times are shown in a) and b) left panels. Each classification consisted of five separate training-and-testing of a CNN using 100 translocation events per protein (a total of ~107 events), whose resulting correct identifications were averaged. These experiments and analyses were performed under four different spatial resolutions (20, 30, 50 and 100 nm) and labelling efficiencies (60, 70, 80 and 90%). Right-hand panels show the fraction of the proteome correctly identified with probability p when considering a spatial resolution of 30 nm for different labeling efficiencies. The bin size was set to 1%. The insets display the degree of randomness in misclassification. The bin height is given by the fraction of mis-identified proteins R (i.e. proteins that had at least 10% of their events misclassified) at different ri (fraction of identical mismatch) intervals: ri = maxjnij/Ni for each protein i, where nij is the number of translocation events misidentified to protein j and Ni the total number of misclassified translocation events. The bin width–ri interval size–was set to 10%. Other experimental conditions are provided in supporting information file. c) Cytokines panel identification using the same proteins as in the ELISA set “CytokineMAP A”. The heat-map represents the correct ID of each cytokine under the specified labelling efficiency and resolution. The average correct ID is provided in the right-hand column.</p

Simulated optical traces of epidermal growth factor (EGF) precursor protein and its receptor EGFR produced under different conditions.

The C, K and M amino-acids were labeled using three different fluorophores as indicated. (a) Optical signals simulated using a spatial resolution of 0.5 nm and a labelling efficiency of 100%. (b) optical signals simulated using three distinct spatial resolutions: 10, 30 and 50 nm (from left to right).</p

Analyzing Blood Cells of High-Risk Myelodysplastic Syndrome Patients Using Interferometric Phase Microscopy and Fluorescent Flow Cytometry

Myelodysplastic syndromes (MDSs) are a group of potentially deadly diseases that affect the morphology and function of neutrophils. Rapid diagnosis of MDS is crucial for the initiation of treatment that can vastly improve disease outcome. In this work, we present a new approach for detecting morphological differences between neutrophils isolated from blood samples of high-risk MDS patients and blood bank donors (BBDs). Using fluorescent flow cytometry, neutrophils were stained with 2′,7′-dichlorofluorescin diacetate (DCF), which reacts with reactive oxygen species (ROS), and Hoechst, which binds to DNA. We observed that BBDs possessed two cell clusters (designated H and L), whereas MDS patients possessed a single cluster (L). Later, we used FACS to sort the H and the L cells and used interferometric phase microscopy (IPM) to image the cells without utilizing cell staining. IPM images showed that H cells are characterized by low optical path delay (OPD) in the nucleus relative to the cytoplasm, especially in cell vesicles containing ROS, whereas L cells are characterized by low OPD in the cytoplasm relative to the nucleus and no ROS-containing vesicles. Moreover, L cells present a higher average OPD and dry mass compared to H cells. When examining neutrophils from MDS patients and BBDs by IPM during flow, we identified ~20% of cells as H cells in BBDs in contrast to ~4% in MDS patients. These results indicate that IPM can be utilized for the diagnosis of complex hematological pathologies such as MDS