Biophysical reports最新文献

Förster resonance energy transfer (FRET) microscopy is used in numerous biophysical and biomedical applications to monitor inter- and intramolecular interactions and conformational changes in the 2-10 nm range. FRET is currently being extended to in vivo optical imaging, its main application being in quantifying drug-target engagement or drug release in animal models of cancer using organic dye or nanoparticle-labeled probes. Herein, we compared FRET quantification using intensity-based FRET (sensitized emission FRET analysis with the three-cube approach using an IVIS imager) and macroscopic fluorescence lifetime (MFLI) FRET using a custom system using a time-gated-intensified charge-coupled device, for small animal optical in vivo imaging. The analytical expressions and experimental protocols required to quantify the product $f_{D}E$ of the FRET efficiency E and the fraction of donor molecules involved in FRET, $f_D$, are described in detail for both methodologies. Dynamic in vivo FRET quantification of transferrin receptor-transferrin binding was acquired in live intact nude mice upon intravenous injection of a near-infrared-labeled transferrin FRET pair and benchmarked against in vitro FRET using hybridized oligonucleotides. Even though both in vivo imaging techniques provided similar dynamic trends for receptor-ligand engagement, we demonstrate that MFLI-FRET has significant advantages. Whereas the sensitized emission FRET approach using the IVIS imager required nine measurements (six of which are used for calibration) acquired from three mice, MFLI-FRET needed only one measurement collected from a single mouse, although a control mouse might be needed in a more general situation. Based on our study, MFLI therefore represents the method of choice for longitudinal preclinical FRET studies such as that of targeted drug delivery in intact, live mice.

Ca²⁺ imaging provides insight into biological processes ranging from subcellular dynamics to neural network activity. Two-photon microscopy has assumed a dominant role in Ca²⁺ imaging. The longer wavelength infra-red illumination undergoes less scattering, and absorption is confined to the focal plane. Two-photon imaging can thus penetrate thick tissue ∼10-fold more deeply than single-photon visible imaging to make two-photon microscopy an exceptionally powerful method for probing function in intact brain. However, two-photon excitation produces photobleaching and photodamage that increase very steeply with light intensity, limiting how strongly one can illuminate. In thin samples, illumination intensity can assume a dominant role in determining signal quality, raising the possibility that single-photon microscopy may be preferable. We therefore tested laser scanning single-photon and two-photon microscopy side by side with Ca²⁺ imaging in neuronal compartments at the surface of a brain slice. We optimized illumination intensity for each light source to obtain the brightest signal without photobleaching. Intracellular Ca²⁺ rises elicited by one action potential had twice the signal/noise ratio with confocal as with two-photon imaging in axons, were 31% higher in dendrites, and about the same in cell bodies. The superior performance of confocal imaging in finer neuronal processes likely reflects the dominance of shot noise when fluorescence is dim. Thus, when out-of-focus absorption and scattering are not issues, single-photon confocal imaging can yield better quality signals than two-photon microscopy.

Magnetic resonance imaging (MRI) is a highly significant imaging platform for a variety of medical and research applications. However, the low spatiotemporal resolution of conventional MRI limits its applicability toward rapid acquisition of ultrahigh-resolution scans. Current aims at high-resolution MRI focus on increasing the accuracy of tissue delineation, assessments of structural integrity, and early identification of malignancies. Unfortunately, high-resolution imaging often leads to decreased signal/noise (SNR) and contrast/noise (CNR) ratios and increased time cost, which are unfeasible in many clinical and academic settings, offsetting any potential benefits. In this study, we apply and assess the efficacy of super-resolution reconstruction (SRR) through iterative back-projection utilizing through-plane voxel offsets. SRR allows for high-resolution imaging in condensed time frames. Rat skulls and archerfish samples, typical models in academic settings, were used to demonstrate the impact of SRR on varying sample sizes and applicability for translational and comparative neuroscience. The SNR and CNR increased in samples that did not fully occupy the imaging probe and in instances where the low-resolution data were acquired in three dimensions, while the CNR was found to increase with both 3D and 2D low-resolution data reconstructions when compared with directly acquired high-resolution images. Limitations to the applied SRR algorithm were investigated to determine the maximum ratios between low-resolution inputs and high-resolution reconstructions and the overall cost effectivity of the strategy. Overall, the study revealed that SRR could be used to decrease image acquisition time, increase the CNR in nearly all instances, and increase the SNR in small samples.

Cryogenic electron microscopy (cryo-EM) is among the most powerful tools available for interrogating nanoscale structure of biological materials. We recently showed that cryo-EM can be used to measure the bilayer thickness of lipid vesicles and biological membranes with subangstrom precision, resulting in the direct visualization of nanoscopic domains of different thickness in multicomponent lipid mixtures and giant plasma membrane vesicles. Despite the great potential of cryo-EM for revealing the lateral organization of biomembranes, a large parameter space of experimental conditions remains to be optimized. Here, we systematically investigate the influence of instrument parameters and image postprocessing steps on the ability to accurately measure bilayer thickness and discriminate regions of different thickness within unilamellar liposomes. This unique application of cryo-EM places particular demands on image acquisition optimization and analysis due to the facts that 1) each vesicle is a different size with different curvature, 2) the domains in each vesicle can be heterogenous in size, and 3) the random orientation of vesicles amplifies the variability of domain size in projected images. We also demonstrate a spatial autocorrelation analysis to extract additional information about lateral heterogeneity.

Neutrophils are key players of the immune system and possess an arsenal of effector functions, including the ability to form and expel neutrophil extracellular traps (NETs) in a process termed NETosis. During NETosis, the nuclear DNA/chromatin expands until it fills the whole cell and is released into the extracellular space. NETs are composed of DNA decorated with histones, proteins, or peptides, and NETosis is implicated in many diseases. Resolving the structure of the nucleus in great detail is essential to understand the underlying processes, but so far, superresolution methods have not been applied. Here, we developed an expansion-microscopy-based method and determined the spatial distribution of chromatin/DNA, histone H1, and nucleophosmin with an over fourfold improved resolution (<40-50 nm) and increased information content. It allowed us to identify the punctate localization of nucleophosmin in the nucleus and histone-rich domains in NETotic cells with a size of 54-66 nm. The technique could also be applied to components of the nuclear envelope (lamins B1 and B2) and myeloperoxidase, providing a complete picture of nuclear composition and structure. In conclusion, expansion microscopy enables superresolved imaging of the highly dynamic structure of nuclei in immune cells.

Single-cell RNA sequencing data can be modeled using Markov chains to yield genome-wide insights into transcriptional physics. However, quantitative inference with such data requires careful assessment of noise sources. We find that long pre-mRNA transcripts are over-represented in sequencing data. To explain this trend, we propose a length-based model of capture bias, which may produce false-positive observations. We solve this model and use it to find concordant parameter trends as well as systematic, mechanistically interpretable technical and biological differences in paired data sets.

The thermodynamics of molecular recognition by proteins is a central determinant of complex biochemistry. For over a half-century, detailed cryogenic structures have provided deep insight into the energetic contributions to ligand binding by proteins. More recently, a dynamical proxy based on NMR-relaxation methods has revealed an unexpected richness in the contributions of conformational entropy to the thermodynamics of ligand binding. Here, we report the pressure dependence of fast internal motion within the ribonuclease barnase and its complex with the protein barstar. In what we believe is a first example, we find that protein dynamics are conserved along the pressure-binding thermodynamic cycle. The femtomolar affinity of the barnase-barstar complex exists despite a penalty by -TΔS_conf of +11.7 kJ/mol at ambient pressure. At high pressure, however, the overall change in side-chain dynamics is zero, and binding occurs with no conformational entropy penalty, suggesting an important role of conformational dynamics in the adaptation of protein function to extreme environments. Distinctive clustering of the pressure sensitivity is observed in response to both pressure and binding, indicating the presence of conformational heterogeneity involving less efficiently packed alternative conformation(s). The structural segregation of dynamics observed in barnase is striking and shows how changes in both the magnitude and the sign of regional contributions of conformational entropy to the thermodynamics of protein function are possible.

Human aquaporin 1 (hAQP1) forms homotetrameric channels that facilitate fluxes of water and small solutes across cell membranes. In addition to water channel activity, hAQP1 displays non-selective monovalent cation-channel activity gated by intracellular cyclic GMP. Dual water and ion-channel activity of hAQP1, thought to regulate cell shape and volume, could offer a target for novel therapeutics relevant to controlling cancer cell invasiveness. This study probed properties of hAQP1 ion channels using proteoliposomes, which, unlike conventional cell-based systems such as Xenopus laevis oocytes, are relatively free of background ion channels. Histidine-tagged recombinant hAQP1 protein was synthesized and purified from the methylotrophic yeast, Pichia pastoris, and reconstituted into proteoliposomes for biophysical analyses. Osmotic water channel activity confirmed correct folding and channel assembly. Ion-channel activity of hAQP1-Myc-His₆ was recorded by patch-clamp electrophysiology with excised patches. In symmetrical potassium, the hAQP1-Myc-His₆ channels displayed coordinated gating, a single-channel conductance of approximately 75 pS, and multiple subconductance states. Applicability of this method for structure-function analyses was tested using hAQP1-Myc-His₆ ^D48A/D185A channels modified by site-directed mutations of charged Asp residues estimated to be adjacent to the central ion-conducting pore of the tetramer. No differences in conductance were detected between mutant and wild-type constructs, suggesting the open-state conformation could differ substantially from expectations based on crystal structures. Nonetheless, the method pioneered here for AQP1 demonstrates feasibility for future work defining structure-function relationships, screening pharmacological inhibitors, and testing other classes in the broad family of aquaporins for previously undiscovered ion-conducting capabilities.

Cell-matrix and cell-cell adhesion play important roles in a wide variety of physiological processes, from the single-cell level to the large scale, multicellular organization of tissues. Cells actively apply forces to their environment, either extracellular matrix or neighboring cells, as well as sense its biophysical properties. The fluctuations associated with these active processes occur on an energy scale much larger than that of ordinary thermal equilibrium fluctuations, yet their statistical properties and characteristic scales are not fully understood. Here, we compare measurements of the energy scale of active cellular fluctuations-an effective cellular temperature-in four different biophysical settings, involving both single-cell and cell-aggregate experiments under various control conditions, different cell types, and various biophysical observables. The results indicate that a similar energy scale of active fluctuations might characterize the same cell type in different settings, though it may vary among different cell types, being approximately six to eight orders of magnitude larger than the ordinary thermal energy at room temperature. These findings call for extracting the energy scale of active fluctuations over a broader range of cell types, experimental settings, and biophysical observables and for understanding the biophysical origin and significance of such cellular energy scales.

A central endeavor in bioengineering concerns the construction of multistrain microbial consortia with desired properties. Typically, a gene network is partitioned between strains, and strains communicate via quorum sensing, allowing for complex behaviors. Yet a fundamental question of how emergent spatiotemporal patterning in multistrain microbial consortia affects consortial dynamics is not understood well. Here, we propose a computationally tractable and straightforward modeling framework that explicitly allows linking spatiotemporal patterning to consortial dynamics. We validate our model against previously published results and make predictions of how spatial heterogeneity impacts interstrain communication. By enabling the investigation of spatial patterns effects on microbial dynamics, our modeling framework informs experimentalists, helps advance the understanding of complex microbial systems, and supports the development of applications involving them.