Hfsp Journal最新文献

Spatiotemporal control of gene expression is fundamental to multicellular life. Despite prodigious efforts, the encoding of gene expression regulation in eukaryotes is not understood. Gene expression analyses nourish the hope to reverse engineer effector-target gene networks using inference techniques. Inference from noisy and circumstantial data relies on using robust models with few parameters for the underlying mechanisms. However, a systematic path to gene regulatory network reverse engineering from functional genomics data is still impeded by fundamental problems. Recently, Johannes Berg from the Theoretical Physics Institute of Cologne University has made two remarkable contributions that significantly advance the gene regulatory network inference problem. Berg, who uses gene expression data from yeast, has demonstrated a nonequilibrium regime for mRNA concentration dynamics and was able to map the gene regulatory process upon simple stochastic systems driven out of equilibrium. The impact of his demonstration is twofold, affecting both the understanding of the operational constraints under which transcription occurs and the capacity to extract relevant information from highly time-resolved expression data. Berg has used his observation to predict target genes of selected transcription factors, and thereby, in principle, demonstrated applicability of his out of equilibrium statistical mechanics approach to the gene network inference problem.

Intracellular transport along microtubules is often bidirectional, employing multiple plus- and minus-end directed motors. How cells regulate such transport in time and space is a fundamental but unsolved question in cell biology. A recent paper presents a new modeling approach to predict how much of transport can be understood just from our knowledge of the motors involved. The model can generate strikingly complex patterns of motion, mimicking key aspects of cargo transport in vivo. Previous studies had inferred that plus-end motors on bidirectional cargoes are usually turned off when the minus-end motors are engaged (and vice versa). In the model, such motor coordination can arise from motors competing in a tug-of-war, without help from additional regulators. This new theoretical framework should stimulate much research that will help unravel whether regulation of intracellular transport is dominated by higher-order control mechanisms or is achieved simply by tuning basic properties of the motors themselves.

Dorsal closure in Drosophila is a model system for cell sheet morphogenesis and wound healing. During closure two sheets of lateral epidermis move dorsally to close over the amnioserosa and form a continuous epidermis. Forces from the amnioserosa and actomyosin-rich, supracellular purse strings at the leading edges of these lateral epidermal sheets drive closure. Purse strings generate the largest force for closure and occur during development and wound healing throughout phylogeny. We use laser microsurgery to remove some or all of the purse strings from developing embryos. Free edges produced by surgery undergo characteristic responses as follows. Intact cells in the free edges, which previously had no purse string, recoil away from the incision and rapidly assemble new, secondary purse strings. Next, recoil slows, then pauses at a turning point. Following a brief delay, closure resumes and is powered to completion by the secondary purse strings. We confirm that the assembly of the secondary purse strings requires RhoA. We show that alpha-actinin alternates with nonmuscle myosin II along purse strings and requires nonmuscle myosin II for its localization. Together our data demonstrate that purse strings are renewable resources that contribute to the robust and resilient nature of closure.

Over the past century the resolution of far-field optical microscopes, which rely on propagating optical modes, was widely believed to be limited because of diffraction to a value on the order of a half-wavelength lambda2 of the light used. Although immersion microscopes had slightly improved resolution on the order of lambda2n, the increased resolution was limited by the small range of refractive indices, n, of available transparent materials. We are experiencing quick demolition of the diffraction limit in optical microscopy. Over the past few years numerous nonlinear optical microscopy techniques based on photoswitching and saturation of fluorescence demonstrated far-field resolution of 20 to 30 nm. The latest exciting example of these techniques has been demonstrated by Huang et al. [Science 319, 810-813 (2008)]. Moreover, recent progress in metamaterials indicates that artificial optical media can be created, which do not exhibit the diffraction limit. Resolution of linear "immersion" microscopes based on such metamaterials appears limited only by losses, which can be compensated by gain media. Thus, optical microscopy is quickly moving towards the 10 nm resolution scale, which should bring about numerous revolutionary advances in biomedical imaging.

Gene activation in eukaryotes involves the concerted action of histone tail modifiers, chromatin remodelers, and transcription factors, whose precise coordination is currently unknown. We demonstrate that the experimentally observed interactions of the molecules are in accord with a kinetic proofreading scheme. Our finding could provide a basis for the development of quantitative models for gene regulation in eukaryotes based on the combinatorical interactions of chromatin modifiers.

Neuromorphic analog metal-oxide-silicon (MOS) transistor circuits promise compact, low-power, and high-speed emulations of iono-neuronal dynamics orders-of-magnitude faster than digital simulation. However, their inherently limited input voltage dynamic range vs power consumption and silicon die area tradeoffs makes them highly sensitive to transistor mismatch due to fabrication inaccuracy, device noise, and other nonidealities. This limitation precludes robust analog very-large-scale-integration (aVLSI) circuits implementation of emergent iono-neuronal dynamics computations beyond simple spiking with limited ion channel dynamics. Here we present versatile neuromorphic analog building-block circuits that afford near-maximum voltage dynamic range operating within the low-power MOS transistor weak-inversion regime which is ideal for aVLSI implementation or implantable biomimetic device applications. The fabricated microchip allowed robust realization of dynamic iono-neuronal computations such as coincidence detection of presynaptic spikes or pre- and postsynaptic activities. As a critical performance benchmark, the high-speed and highly interactive iono-neuronal simulation capability on-chip enabled our prompt discovery of a minimal model of chaotic pacemaker bursting, an emergent iono-neuronal behavior of fundamental biological significance which has hitherto defied experimental testing or computational exploration via conventional digital or analog simulations. These compact and power-efficient transistor analogs of emergent iono-neuronal dynamics open new avenues for next-generation neuromorphic, neuroprosthetic, and brain-machine interface applications.

In January 2008, Duke University and the Japan Science and Technology Agency (JST) publicized their successful control of a brain-machine interface for a humanoid robot by a monkey brain across the Pacific Ocean. The activities of a few hundred neurons were recorded from a monkey's motor cortex in Miguel Nicolelis's lab at Duke University, and the kinematic features of monkey locomotion on a treadmill were decoded from neural firing rates in real time. The decoded information was sent to a humanoid robot, CB-i, in ATR Computational Neuroscience Laboratories located in Kyoto, Japan. This robot was developed by the JST International Collaborative Research Project (ICORP) as the "Computational Brain Project." CB-i's locomotion-like movement was video-recorded and projected on a screen in front of the monkey. Although the bidirectional communication used a conventional Internet connection, its delay was suppressed below one over several seconds, partly due to a video-streaming technique, and this encouraged the monkey's voluntary locomotion and influenced its brain activity. This commentary introduces the background and future directions of the brain-controlled robot.

Live imaging has gained a pivotal role in developmental biology since it increasingly allows real-time observation of cell behavior in intact organisms. Microscopes that can capture the dynamics of ever-faster biological events, fluorescent markers optimal for in vivo imaging, and, finally, adapted reconstruction and analysis programs to complete data flow all contribute to this success. Focusing on temporal resolution, we discuss how fast imaging can be achieved with minimal prejudice to spatial resolution, photon count, or to reliably and automatically analyze images. In particular, we show how integrated approaches to imaging that combine bright fluorescent probes, fast microscopes, and custom post-processing techniques can address the kinetics of biological systems at multiple scales. Finally, we discuss remaining challenges and opportunities for further advances in this field.