Changing the data representation from the classical time delay histogram to the phasor representation provides a global view of the fluorescence decay at each pixel of an image. In the phasor representation we can easily recognize the presence of different molecular species in a pixel or the occurrence of fluorescence resonance energy transfer. The analysis of the fluorescence lifetime imaging microscopy (FLIM) data in the phasor space is done observing clustering of pixels values in specific regions of the phasor plot rather than by fitting the fluorescence decay using exponentials. The analysis is instantaneous since is not based on calculations or nonlinear fitting. The phasor approach has the potential to simplify the way data are analyzed in FLIM, paving the way for the analysis of large data sets and, in general, making the FLIM technique accessible to the nonexpert in spectroscopy and data analysis.

We describe a technique based on moment-analysis for the measurement of the average number of molecules and brightness in each pixel in fluorescence microscopy images. The average brightness of the particle is obtained from the ratio of the variance to the average intensity at each pixel. To obtain the average number of fluctuating particles, we divide the average intensity at one pixel by the brightness. This analysis can be used in a wide range of concentrations. In cells, the intensity at any given pixel may be due to bright immobile structures, dim fast diffusing particles, and to autofluorescence or scattering. The total variance is given by the variance of each of the above components in addition to the variance due to detector noise. Assuming that all sources of variance are independent, the total variance is the sum of the variances of the individual components. The variance due to the particles fluctuating in the observation volume is proportional to the square of the particle brightness while the variance of the immobile fraction, the autofluorescence, scattering, and that of the detector is proportional to the intensity of these components. Only the fluctuations that depend on the square of the brightness (the mobile particles) will have a ratio of the variance to the intensity >1. Furthermore, changing the fluorescence intensity by increasing the illumination power, distinguishes between these possible contributions. We show maps of molecular brightness and number of cell migration proteins obtained using a two-photon scanning microscope operating with a photon-counting detector. These brightness maps reveal binding dynamics at the focal adhesions with pixel resolution and provide a picture of the binding and unbinding process in which dim molecules attach to the adhesions or large molecular aggregates dissociate from adhesion.

We describe a label-free imaging method to monitor stem-cell metabolism that discriminates different states of stem cells as they differentiate in living tissues. In this method we use intrinsic fluorescence biomarkers and the phasor approach to fluorescence lifetime imaging microscopy in conjunction with image segmentation, which we use to introduce the concept of the cell phasor. In live tissues we are able to identify intrinsic fluorophores, such as collagen, retinol, retinoic acid, porphyrin, flavins, and free and bound NADH. We have exploited the cell phasor approach to detect a trend in metabolite concentrations along the main axis of the Caenorhabditis elegans germ line. This trend is consistent with known changes in metabolic states during differentiation. The cell phasor approach to lifetime imaging provides a label-free, fit-free, and sensitive method to identify different metabolic states of cells during differentiation, to sense small changes in the redox state of cells, and may identify symmetric and asymmetric divisions and predict cell fate. Our method is a promising noninvasive optical tool for monitoring metabolic pathways during differentiation or disease progression, and for cell sorting in unlabeled tissues.phasor analysis | single cell metabolism T he hallmark of stem cells is their ability to produce a new stem cell by self-renewing, as they generate daughter cells that are committed to differentiation and form specialized tissues (1). The modulation of the balance between self-renewing divisions and differentiation is a central mechanism for stem cells during embryo development, adult tissue regeneration, and homeostasis. Stem-cell differentiation is a complex process mediated both by intrinsic molecular mechanisms and extrinsic signaling. Intrinsic cell polarity, subcellular localization mechanism, asymmetric centrosome and spindles, as well as cell-cycle regulators can establish self-renewing asymmetry during stem-cell division (2, 3). The influence of external chemical and physical stimuli, such as molecular gradients, extracellular matrix remodeling, and niche signaling is crucial for stem-cell plasticity and tissue development (4-6). Extrinsic signals can be propagated through intracellular signal-transduction pathways that converge to genetic networks that control pluripotency. Many different signaling and transcriptional pathways, which are important for development and cell-cycle regulation, converge on regulation of the redox state of stem cells (5,7,8). In turn, histone posttranscriptional modifications and epigenetic mechanisms, such as phosphorylation, acetylation, and methylation, sense cellular metabolism and the variation of metabolites levels (9). Hence, redox balance plays an important role in the maintenance and modulation of stem cell self-renewal and differentiation (10-12).In stem-cell research there is a high demand for noninvasive techniques to investigate self-renewal and differentiation. Methods, such as immunohistochemistry, metabolic assays, and PCR are currently...

Single-point fluorescence correlation spectroscopy (FCS) allows measurements of fast diffusion and dynamic processes in the microsecond-to-millisecond time range. For measurements on living cells, image correlation spectroscopy (ICS) and temporal ICS extend the FCS approach to diffusion times as long as seconds to minutes and simultaneously provide spatially resolved dynamic information. However, ICS is limited to very slow dynamics due to the frame acquisition rate. Here we develop novel extensions to ICS that probe spatial correlations in previously inaccessible temporal windows. We show that using standard laser confocal imaging techniques (raster-scan mode) not only can we reach the temporal scales of single-point FCS, but also have the advantages of ICS in providing spatial information. This novel method, called raster image correlation spectroscopy (RICS), rapidly measures during the scan many focal points within the cell providing the same concentration and dynamic information of FCS as well as information on the spatial correlation between points along the scanning path. Longer time dynamics are recovered from the information in successive lines and frames. We exploit the hidden time structure of the scan method in which adjacent pixels are a few microseconds apart thereby accurately measuring dynamic processes such as molecular diffusion in the microseconds-to-seconds timescale. In conjunction with simulated data, we show that a wide range of diffusion coefficients and concentrations can be measured by RICS. We used RICS to determine for the first time spatially resolved diffusions of paxillin-EGFP stably expressed in CHOK1 cells. This new type of data analysis has a broad application in biology and it provides a powerful tool for measuring fast as well as slower dynamic processes in cellular systems using any standard laser confocal microscope.

The delivery of therapeutics to the central nervous system (CNS) remains a major challenge in part due to the presence of the blood-brain barrier (BBB). Recently, cell-derived vesicles, particularly exosomes, have emerged as an attractive vehicle for targeting drugs to the brain, but whether or how they cross the BBB remains unclear. Here, we investigated the interactions between exosomes and brain microvascular endothelial cells (BMECs) in vitro under conditions that mimic the healthy and inflamed BBB in vivo. Transwell assays revealed that luciferase-carrying exosomes can cross a BMEC monolayer under stroke-like, inflamed conditions (TNF-α activated) but not under normal conditions. Confocal microscopy showed that exosomes are internalized by BMECs through endocytosis, co-localize with endosomes, in effect primarily utilizing the transcellular route of crossing. Together, these results indicate that cell-derived exosomes can cross the BBB model under stroke-like conditions in vitro. This study encourages further development of engineered exosomes as drug delivery vehicles or tracking tools for treating or monitoring neurological diseases.

SummaryRaster image correlation spectroscopy (RICS) is a new and novel technique for measuring molecular dynamics and concentrations from fluorescence confocal images. The RICS technique extracts information about molecular dynamics and concentrations from images of living cells taken on commercial confocal systems. Here we develop guidelines for performing the RICS analysis on an analogue commercial laser scanning confocal microscope. Guidelines for typical instrument settings, image acquisition settings and analogue detector characterization are presented. Using appropriate instrument/acquisition parameters, diffusion coefficients and concentrations can be determined, even for highly dynamic dye molecules in solution. Standard curves presented herein demonstrate the ability to detect protein concentrations as low as ∼ 2 nM. Additionally, cellular measurements give accurate values for the diffusion of paxillin-enhanced-green fluorescent protein (EGFP), an adhesion adaptor molecule, in the cytosol of the cell and also show slower paxillin dynamics near adhesions where paxillin interacts with immobile adhesion components. Methods are presented to account for bright immobile structures within the cell that dominate spatial correlation functions; allowing the extraction of fast protein dynamics within and near these structures. A running average algorithm is also presented to address slow cellular movement or movement of cellular features such as adhesions. Finally, methods to determine protein concentration in the presence

Blood stream infection or sepsis is a major health problem worldwide, with extremely high mortality, which is partly due to the inability to rapidly detect and identify bacteria in the early stages of infection. Here we present a new technology termed ‘Integrated Comprehensive Droplet Digital Detection’ (IC 3D) that can selectively detect bacteria directly from milliliters of diluted blood at single-cell sensitivity in a one-step, culture- and amplification-free process within 1.5–4 h. The IC 3D integrates real-time, DNAzyme-based sensors, droplet microencapsulation and a high-throughput 3D particle counter system. Using Escherichia coli as a target, we demonstrate that the IC 3D can provide absolute quantification of both stock and clinical isolates of E. coli in spiked blood within a broad range of extremely low concentration from 1 to 10,000 bacteria per ml with exceptional robustness and limit of detection in the single digit regime.

The regulatory domains of conventional and novel protein kinases C (PKC) have two C1 domains (C1A and C1B) that have been identified as the interaction site for diacylglycerol (DAG) and phorbol ester. It has been reported that C1A and C1B domains of individual PKC isoforms play different roles in their membrane binding and activation; however, DAG affinity of individual C1 domains has not been quantitatively determined. In this study, we measured the affinity of isolated C1A and C1B domains of two conventional PKCs, PKC␣ and PKC␥, for soluble and membrane-incorporated DAG and phorbol ester by isothermal calorimetry and surface plasmon resonance. The C1A and C1B domains of PKC␣ have opposite affinities for DAG and phorbol ester; i.e. the C1A domain with high affinity for DAG and the C1B domain with high affinity for phorbol ester. In contrast, the C1A and C1b domains of PKC␥ have comparably high affinities for both DAG and phorbol ester. Consistent with these results, mutational studies of full-length proteins showed that the C1A domain is critical for the DAG-induced activation of PKC␣, whereas both C1A and C1B domains are involved in the DAG-induced activation of PKC␥. Further mutational studies in conjunction with in vitro activity assay and monolayer penetration analysis indicated that, unlike the C1A domain of PKC␣, neither the C1A nor the C1B domain of PKC␥ is conformationally restricted. Cell studies with enhanced green fluorescent protein-tagged PKCs showed that PKC␣ did not translocate to the plasma membrane in response to DAG at a basal intracellular calcium concentration due to the inaccessibility of its C1A domain, whereas PKC␥ rapidly translocated to the plasma membrane under the same conditions. These data suggest that differential activation mechanisms of PKC isoforms are determined by the DAG affinity and conformational flexibility of their C1 domains. Protein kinase C (PKC)1 are a family of serine/threonine kinases that mediate numerous cellular processes (1, 2). All PKCs contain an amino-terminal regulatory domain and a carboxyl-terminal catalytic domain. Based on structural differences in the regulatory domain, PKCs are generally classified into three groups: conventional PKC (␣, ␤I, ␤II, and ␥ subtypes), novel PKC (␦, ⑀, , and subtypes), and atypical PKC ( and / subtypes). Regulatory domains of both conventional and novel PKCs contain tandem C1 (C1A and C1B) domains and a C2 domain. The C1 domain (ϳ50 residues) is a cysteine-rich compact structure that contains five short ␤ strands, a short helix, and two zinc ions (3-7), whereas the C2 domain (ϳ130 residues) is composed of eight-stranded antiparallel ␤ strands (5, 8 -10) and interconnecting loops some of which are involved in Ca 2ϩ -dependent membrane binding. The C1 domain was first identified as the interaction site for diacylglycerol (DAG) and phorbol ester in PKCs (11), but it was subsequently found in other proteins with diverse functions, including protein kinase D (PKD/PKC), chimaerin, Ras-GRP, DAG kinases, and Raf-1 kinase (4, 6, 7). ...