A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells.

We propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatio-temporal gene expression in intact networks of cells. The model describes the oscillating time evolution of molecular mRNA counts through a negative transcriptional-translational feedback loop encoded in a chemical Langevin equation with a probabilistic delay distribution. The model is extended spatially by means of a multiplicative random effects model with a first order Markov random field prior distribution. Our methodology effectively separates intrinsic molecular noise, measurement noise, and extrinsic noise and phenotypic variation driving cell heterogeneity, while being amenable to parameter identification and inference. Based on the single-cell model we propose a novel computational stability analysis that allows us to infer two key characteristics, namely the robustness of the oscillations, i.e. whether the reaction network exhibits sustained or damped oscillations, and the profile of the regulation, i.e. whether the inhibition occurs over time in a more distributed versus a more direct manner, which affects the cells' ability to phase-shift to new schedules. We show how insight into the spatio-temporal characteristics of the circadian feedback loop in the suprachiasmatic nucleus (SCN) can be gained by applying the methodology to bioluminescence-reported expression of the circadian core clock gene Cry1 across mouse SCN tissue. We find that while (almost) all SCN neurons exhibit robust cell-autonomous oscillations, the parameters that are associated with the regulatory transcription profile give rise to a spatial division of the tissue between the central region whose oscillations are resilient to perturbation in the sense that they maintain a high degree of synchronicity, and the dorsal region which appears to phase shift in a more diversified way as a response to large perturbations and thus could be more amenable to entrainment.

Microtubule organization within mitotic spindles revealed by serial block face scanning electron microscopy and image analysis.

Serial block face scanning electron microscopy (SBF-SEM) is a powerful method to analyze cells in 3D. Here, working at the resolution limit of the method, we describe a correlative light-SBF-SEM workflow to resolve microtubules of the mitotic spindle in human cells. We present four examples of uses for this workflow that are not practical by light microscopy and/or transmission electron microscopy. First, distinguishing closely associated microtubules within K-fibers; second, resolving bridging fibers in the mitotic spindle; third, visualizing membranes in mitotic cells, relative to the spindle apparatus; and fourth, volumetric analysis of kinetochores. Our workflow also includes new computational tools for exploring the spatial arrangement of microtubules within the mitotic spindle. We use these tools to show that microtubule order in mitotic spindles is sensitive to the level of TACC3 on the spindle.

Osmium Atoms and Os2 Molecules Move Faster on Selenium-Doped Compared to Sulfur-Doped Boronic Graphenic Surfaces.

We deposited Os atoms on S- and Se-doped boronic graphenic surfaces by electron bombardment of micelles containing 16e complexes [Os(p-cymene)(1,2-dicarba-closo-dodecarborane-1,2-diselenate/dithiolate)] encapsulated in a triblock copolymer. The surfaces were characterized by energy-dispersive X-ray (EDX) analysis and electron energy loss spectroscopy of energy filtered TEM (EFTEM). Os atoms moved ca. 26× faster on the B/Se surface compared to the B/S surface (233 ± 34 pm·s(-1) versus 8.9 ± 1.9 pm·s(-1)). Os atoms formed dimers with an average Os-Os distance of 0.284 ± 0.077 nm on the B/Se surface and 0.243 ± 0.059 nm on B/S, close to that in metallic Os. The Os2 molecules moved 0.83× and 0.65× more slowly than single Os atoms on B/S and B/Se surfaces, respectively, and again markedly faster (ca. 20×) on the B/Se surface (151 ± 45 pm·s(-1) versus 7.4 ± 2.8 pm·s(-1)). Os atom motion did not follow Brownian motion and appears to involve anchoring sites, probably S and Se atoms. The ability to control the atomic motion of metal atoms and molecules on surfaces has potential for exploitation in nanodevices of the future.

Single-molecule level analysis of the subunit composition of the T cell receptor on live T cells.

The T cell receptor (TCR) expressed on most T cells is a protein complex consisting of TCRalphabeta heterodimers that bind antigen and cluster of differentiation (CD) 3epsilondelta, epsilongamma, and zetazeta dimers that initiate signaling. A long-standing controversy concerns whether there is one, or more than one, alphabeta heterodimer per complex. We used a form of single-molecule spectroscopy to investigate this question on live T cell hybridomas. The method relies on detecting coincident fluorescence from single molecules labeled with two different fluorophores, as the molecules diffuse through a confocal volume. The fraction of events that are coincident above the statistical background is defined as the "association quotient," Q. In control experiments, Q was significantly higher for cells incubated with wheat germ agglutinin dual-labeled with Alexa488 and Alexa647 than for cells incubated with singly labeled wheat germ agglutinin. Similarly, cells expressing the homodimer, CD28, gave larger values of Q than cells expressing the monomer, CD86, when incubated with mixtures of Alexa488- and Alexa647-labeled antibody Fab fragments. T cell hybridomas incubated with mixtures of anti-TCRbeta Fab fragments labeled with each fluorophore gave a Q value indistinguishable from the Q value for CD86, indicating that the dominant form of the TCR comprises single alphabeta heterodimers. The values of Q obtained for CD86 and the TCR were low but nonzero, suggesting that there is transient or nonrandom confinement, or diffuse clustering of molecules at the T cell surface. This general method for analyzing the subunit composition of protein complexes could be extended to other cell surface or intracellular complexes, and other living cells.