The composition of cellular structures on the nanoscale is a key determinant of macroscopic functions in cell biology and beyond. Different fluorescence single-molecule techniques have proven ideally suited for measuring protein copy numbers of cellular structures in intact biological samples. Of these, photobleaching step analysis poses minimal demands on the microscope and its counting range has significantly improved with more sophisticated algorithms for step detection, albeit at an increasing computational cost. Here, we present a comprehensive framework for photobleaching step analysis, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labelling strategies with respect to their molecular brightness and photostability. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we benchmark the framework with experimental data acquired on DNA origami labeled with defined fluorophore numbers to demonstrate counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis for robust protein counting by counting labelled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated fashion.
Core Ideas Our aim was to test whether mucilage promotes diffusion of nutrients in dry soil. Mucilage favors transport of nutrients in drying soil and their uptake by plant. Mucilage increases the soil moisture in the rhizosphere as soil dries. Mucilage maintains the connectivity of liquid phase in the rhizosphere as soil dries. Despite detailed investigations of its distinct biochemical properties and their effects on the availability of nutrients for plants, the biophysical aspects of the rhizosphere, particularly the effect of mucilage on the transport of water and nutrients, are poorly understood. The aim of this study was to investigate the effect of mucilage on the diffusion of nutrients and consequently their transport through the rhizosphere into the plant roots. Phosphor imaging technique determined the temporospatial distribution of 137Cs in a model rhizosphere (a sandy soil mixed with chia seed (Salvia hispanica L) mucilage. The observed profiles of activities were used to estimate the diffusion coefficient of K in soils. A diffusion–convection equation was numerically solved to predict the transport of K and its uptake by a single plant root in drying soil. The results suggest that mucilage (i) keeps the rhizosphere wet and (ii) maintains the connectivity of the liquid phase in drying soil. In these ways, mucilage moderates the drop in diffusive transport. The modeling results showed that the presence of mucilage in the rhizosphere (i) prevents depletion of nutrients in soils with a low nutrient concentration in the soil solution and (ii) delays the risk of nutrient and/or salt accumulation in the vicinity of the root in soils with a high concentration nutrient and/or salt the soil solution. In conclusion, mucilage appears to mitigate the risk of nutrient deficiency and salinity stress as it enhances the diffusive transport in drying soil. In this way, mucilage may favor the transport of nutrients within the rhizosphere and their uptake by plant roots in drying soil.
The counting of discrete photobleaching steps in fluorescence microscopy is ideally suited to study protein complex stoichiometry in situ. The counting range of photobleaching step analysis has significantly improved with more sophisticated algorithms for step detection, albeit at an increasing computational cost and with the necessity for high data quality. Here, we address concerns regarding robustness, automation, and experimental validation, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labelling strategies with respect to their molecular brightness, photostability, and photoblinking. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we validate the developed methods with experimental data acquired on DNA origami labeled with defined fluorophore numbers, demonstrating counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis by counting labeled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated fashion.
The hepatitis C virus (HCV) is capable of spreading within a host by two different transmission modes: cell-free and cell-to-cell. However, the contribution of each of these transmission mechanisms to HCV spread is unknown. To dissect the contribution of these different transmission modes to HCV spread, we measured HCV lifecycle kinetics and used an in vitro spread assay to monitor HCV spread kinetics after a low multiplicity of infection in the absence and presence of a neutralizing antibody that blocks cell-free spread. By analyzing these data with a spatially explicit mathematical model that describes viral spread on a single-cell level, we quantified the contribution of cell-free, and cell-to-cell spread to the overall infection dynamics and show that both transmission modes act synergistically to enhance the spread of infection. Thus, the simultaneous occurrence of both transmission modes represents an advantage for HCV that may contribute to viral persistence. Notably, the relative contribution of each viral transmission mode appeared to vary dependent on different experimental conditions and suggests that viral spread is optimized according to the environment. Together, our analyses provide insight into the spread dynamics of HCV and reveal how different transmission modes impact each other.
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