Project description:Spatial grain of studies of communities is often based on arbitrary convention. Few studies have examined how spatial scaling of grain size affects estimates of compositional change over time, despite its broad implications.Fish assemblage structure was compared between 1974 and 2014 at 33 sampling locations in the Muddy Boggy River drainage, USA. The two main objectives for this comparison were to quantify change in assemblage structure and to test for a relationship between compositional change and spatial scale. Spatial scale was manipulated by pooling assemblage data into a continuous range of groups, which increased in size from K = 33 pairs (i.e., local scale) to K = 1 pair (i.e., global scale), via clustering algorithm based on pair-wise fluvial distance.Local assemblages (stream reaches) varied in the degree of assemblage change over time (range = 0.10-0.99 dissimilarity; mean = 0.66). The global assemblage (drainage), however, remained relatively similar. A discontinuity in the relationship between compositional change and spatial scale occurred at K = 15 (mean dissimilarity = 0.56; p = .062), and this grouping is roughly the size of the headwater/tributary drainages (i.e., stream order ? 3) in the study system.Spatial scale can impact estimates of biodiversity change over time. These results suggest assemblages are more dynamic at individual stream reaches than at the scale of the entire drainage. The decline in assemblage change at the spatial scale of K = 15 deserves further attention given the marginal significance, despite a small sample size (n = 15). This pattern could suggest regional and meta-community processes become more important in shaping assemblage dynamics at the scale of headwater drainages, whereas the factors responsible for driving individual stream reach dynamics (e.g., stochasticity) become less important. Defining assemblages at a larger scale will result in different estimates of species persistence. Biodiversity monitoring efforts must take the effect of spatial scaling into consideration.
Project description:Multicellular organisms rely on intercellular communication to regulate important cellular processes critical to life. To further our understanding of those processes there is a need to scrutinize dynamical signaling events and their functions in both cells and organisms. Here, we report a method and provide MATLAB code that analyzes time-lapse microscopy recordings to identify and characterize network structures within large cell populations, such as interconnected neurons. The approach is demonstrated using intracellular calcium (Ca(2+)) recordings in neural progenitors and cardiac myocytes, but could be applied to a wide variety of biosensors employed in diverse cell types and organisms. In this method, network structures are analyzed by applying cross-correlation signal processing and graph theory to single-cell recordings. The goal of the analysis is to determine if the single cell activity constitutes a network of interconnected cells and to decipher the properties of this network. The method can be applied in many fields of biology in which biosensors are used to monitor signaling events in living cells. Analyzing intercellular communication in cell ensembles can reveal essential network structures that provide important biological insights.
Project description:Cells elongate on a surface with nanogrooved (NG) patterns and align along that pattern. Although various models have been proposed for how this occurs, much remains to be clarified. Studies with fixed cells do not lend themselves to answering some of these open questions. In this study, the dynamic behaviours of living mesenchymal stem cells on an NG substrate with a 200 nm groove depth, an 870 nm ridge width and a 670 nm groove width were observed using time-lapse microscopes. We found that filopodia moved as if they were probing the surroundings of the cell protrusion, and then some cell protrusions invaded the probed areas. Cell protrusions that extended perpendicular to the NG direction tended to retract more rapidly than those parallel to the grooves. From these facts, we think that the retracting phase of cell protrusions play a rule in cell alignment along the NG patterns.
Project description:Contemporary models of psychosis suggest that a continuum of severity of psychotic symptoms exists, with subthreshold psychotic experiences (PEs) potentially reflecting some genetic and environmental risk factors shared with clinical psychosis. Thus, identifying abnormalities in brain activity that manifest across this continuum can shed new light on the pathophysiology of psychosis. Here, we investigated the moment-to-moment engagement of brain networks ("states") in individuals with schizophrenia (SCZ) and PEs and identified features of these states that are associated with psychosis-spectrum symptoms. Transient brain states were defined by clustering "single snapshots" of blood oxygen level-dependent images, based on spatial similarity of the images. We found that individuals with SCZ (n = 35) demonstrated reduced recruitment of three brain states compared to demographically matched healthy controls (n = 35). Of these three illness-related states, one specific state, involving primarily the visual and salience networks, also occurred at a lower rate in individuals with persistent PEs (n = 22), compared to demographically matched healthy youth (n = 22). Moreover, the occurrence rate of this marker brain state was negatively correlated with the severity of PEs (r = -0.26, p = 0.003, n = 130). In contrast, the spatial map of this state appeared to be unaffected in the SCZ or PE groups. Thus, reduced engagement of a brain state involving the visual and salience networks was demonstrated across the psychosis continuum, suggesting that early disruptions of perceptual and affective function may underlie some of the core symptoms of the illness.
Project description:We present a 3D time-lapse imaging method for monitoring mitochondrial dynamics in living HeLa cells based on photothermal optical coherence microscopy and using novel surface functionalization of gold nanoparticles. The biocompatible protein-based biopolymer coating contains multiple functional groups which impart better cellular uptake and mitochondria targeting efficiency. The high stability of the gold nanoparticles allows continuous imaging over an extended time up to 3000 seconds without significant cell damage. By combining temporal autocorrelation analysis with a classical diffusion model, we quantify mitochondrial dynamics and cast these results into 3D maps showing the heterogeneity of diffusion parameters across the whole cell volume.
Project description:Under a warmer future climate, thermal refuges could facilitate the persistence of species relying on cold-water habitat. Often these refuges are small and easily missed or smoothed out by averaging in models. Thermal infrared (TIR) imagery can provide empirical water surface temperatures that capture these features at a high spatial resolution (<1 m) and over tens of kilometers. Our study examined how TIR data could be used along with spatial stream network (SSN) models to characterize thermal regimes spatially in the Middle Fork John Day (MFJD) River mainstem (Oregon, USA). We characterized thermal variation in seven TIR longitudinal temperature profiles along the MFJD mainstem and compared them with SSN model predictions of stream temperature (for the same time periods as the TIR profiles). TIR profiles identified reaches of the MFJD mainstem with consistently cooler temperatures across years that were not consistently captured by the SSN prediction models. SSN predictions along the mainstem identified ~80% of the 1-km reach scale temperature warming or cooling trends observed in the TIR profiles. We assessed whether landscape features (e.g., tributary junctions, valley confinement, geomorphic reach classifications) could explain the fine-scale thermal heterogeneity in the TIR profiles (after accounting for the reach-scale temperature variability predicted by the SSN model) by fitting SSN models using the TIR profile observation points. Only the distance to the nearest upstream tributary was identified as a statistically significant landscape feature for explaining some of the thermal variability in the TIR profile data. When combined, TIR data and SSN models provide a data-rich evaluation of stream temperature captured in TIR imagery and a spatially extensive prediction of the network thermal diversity from the outlet to the headwaters.
Project description:Nitric oxide (NO) is a gaseous signaling molecule that plays an important role in neurovascular coupling. NO produced by neurons diffuses into the smooth muscle surrounding cerebral arterioles, driving vasodilation. However, the rate of NO degradation in hemoglobin is orders of magnitude higher than in brain tissue, though how this might impact NO signaling dynamics is not completely understood. We used simulations to investigate how the spatial and temporal patterns of NO generation and degradation impacted dilation of a penetrating arteriole in cortex. We found that the spatial location of NO production and the size of the vessel both played an important role in determining its responsiveness to NO. The much higher rate of NO degradation and scavenging of NO in the blood relative to the tissue drove emergent vascular dynamics. Large vasodilation events could be followed by post-stimulus constrictions driven by the increased degradation of NO by the blood, and vasomotion-like 0.1-0.3 Hz oscillations could also be generated. We found that these dynamics could be enhanced by elevation of free hemoglobin in the plasma, which occurs in diseases such as malaria and sickle cell anemia, or following blood transfusions. Finally, we show that changes in blood flow during hypoxia or hyperoxia could be explained by altered NO degradation in the parenchyma. Our simulations suggest that many common vascular dynamics may be emergent phenomena generated by NO degradation by the blood or parenchyma.
Project description:Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors' discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the computational models were experimentally confirmed by a series of video-microscopy acquisitions of co-cultures of unlabelled human cancer and immune cells embedded in 3D collagen gels within microfluidic devices. We argue that the experimental protocol of acquisition should be adapted to the specific kind of analysis involved and to the chosen descriptors in order to derive reliable conclusions and avoid biasing the interpretation of results.
Project description:An understanding of the mechanisms regulating cellular responses has recently been augmented by innovations enabling the observation of phenotypes at high spatio-temporal resolution. Technologies such as microfluidics have sought to expand the throughput of these methods, although assimilation with advanced imaging strategies has been limited. Here, we describe the pairing of high resolution time-lapse imaging with microfluidic multiplexing for the analysis of cellular dynamics, utilizing a design selected for facile fabrication and operation, and integration with microscopy instrumentation. This modular, medium-throughput platform enables the long-term imaging of living cells at high numerical aperture (via oil immersion) by using a conserved 96-well, approximately 6 x 5 mm(2) imaging area with a variable input/output channel design chosen for the number of cell types and microenvironments under investigation. In the validation of this system, we examined fundamental features of cell cycle progression, including mitotic kinetics and spindle orientation dynamics, through the high-resolution parallel analysis of model cell lines subjected to anti-mitotic agents. We additionally explored the self-renewal kinetics of mouse embryonic stem cells, and demonstrate the ability to dynamically assess and manipulate stem cell proliferation, detect rare cell events, and measure extended time-scale correlations. We achieved an experimental throughput of >900 cells/experiment, each observed at >40x magnification for up to 120 h. Overall, these studies illustrate the capacity to probe cellular functions and yield dynamic information in time and space through the integration of a simple, modular, microfluidics-based imaging platform.
Project description:The dynamics of chromatin provides the access to DNA within nucleosomes, and therefore, this process is critically involved in the regulation of chromatin function. However, our knowledge of the large-range dynamics of nucleosomes is limited. Answers to the questions, such as the range of opening of the nucleosome and the mechanism via which the opening occurs and propagates, remain unknown. Here we applied single-molecule time-lapse atomic force microscopy (AFM) imaging to directly visualize the dynamics of nucleosomes and identify the mechanism of the large range DNA exposure. With this technique, we are able to observe the process of unwrapping of nucleosomes. The unwrapping of nucleosomes proceeds from the ends of the particles, allowing for the unwrapping of DNA regions as large as dozens of base pairs. This process may lead to a complete unfolding of nucleosomes and dissociation of the histone core from the complex. The unwrapping occurs in the absence of proteins involved in the chromatin remodeling that require ATP hydrolysis for their function, suggesting that the inherent dynamics of nucleosomes can contribute to the chromatin unwrapping process. These findings shed a new light on molecular mechanisms of nucleosome dynamics and provide novel hypotheses about the understanding of the action of remodeling proteins as well as other intracellular systems in chromatin dynamics.