A fundamental objective in molecular biology is to understand how DNA is organized in concert with various proteins, RNA, and biological membranes. Mitochondria maintain and express their own DNA (mtDNA), which is arranged within structures called nucleoids. Their functions, dimensions, composition, and precise locations relative to other mitochondrial structures are poorly defined. Superresolution fluorescence microscopy techniques that exceed the previous limits of imaging within the small and highly compartmentalized mitochondria have been recently developed. We have improved and employed both two- and three-dimensional applications of photoactivated localization microscopy (PALM and iPALM, respectively) to visualize the core dimensions and relative locations of mitochondrial nucleoids at an unprecedented resolution. PALM reveals that nucleoids differ greatly in size and shape. Three-dimensional volumetric analysis indicates that, on average, the mtDNA within ellipsoidal nucleoids is extraordinarily condensed. Two-color PALM shows that the freely diffusible mitochondrial matrix protein is largely excluded from the nucleoid. In contrast, nucleoids are closely associated with the inner membrane and often appear to be wrapped around cristae or crista-like inner membrane invaginations. Determinations revealing high packing density, separation from the matrix, and tight association with the inner membrane underscore the role of mechanisms that regulate access to mtDNA and that remain largely unknown.

Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement.

The mammalian brain is best understood as a multi-scale hierarchical neural system, in the sense that connection and function occur on multiple scales from micro to macro. Modern genomic-scale expression profiling can provide insight into methodologies that elucidate this architecture. We present a methodology for understanding the relationship of gene expression and neuroanatomy based on correlation between gene expression profiles across tissue samples. A resulting tool, NeuroBlast, can identify networks of genes co-expressed within or across neuroanatomic structures. The method applies to any data modality that can be mapped with sufficient spatial resolution, and provides a computation technique to elucidate neuroanatomy via patterns of gene expression on spatial and temporal scales. In addition, from the perspective of spatial location, we discuss a complementary technique that identifies gene classes that contribute to defining anatomic patterns.

The paradigm that the secretory pathway consists of a stable endoplasmic reticulum and Golgi apparatus, using discrete transport vesicles to exchange their contents, gained important support from groundbreaking biochemical and genetic studies during the 1980s. However, the subsequent development of new imaging technologies with green fluorescent protein introduced data on dynamic processes not fully accounted for by the paradigm. As a result, we may be seeing an example of how a paradigm is evolving to account for the results of new technologies and their new ways of describing cellular processes.

Despite the apparent simplicity of the xanthene fluorophores, the preparation of caged derivatives with free carboxy groups remains a synthetic challenge. A straightforward and flexible strategy for preparing rhodamine and fluorescein derivatives was developed using reduced, “leuco” intermediates.

MOTIVATION: Homology search for RNAs can use secondary structure information to increase power by modeling base pairs, as in covariance models, but the resulting computational costs are high. Typical acceleration strategies rely on at least one filtering stage using sequence-only search. RESULTS: Here we present the multi-segment CYK (MSCYK) filter, which implements a heuristic of ungapped structural alignment for RNA homology search. Compared to gapped alignment, this approximation has lower computation time requirements (O(N⁴) reduced to O(N³), and space requirements (O(N³) reduced to O(N²). A vector-parallel implementation of this method gives up to 100-fold speed-up; vector-parallel implementations of standard gapped alignment at two levels of precision give 3- and 6-fold speed-ups. These approaches are combined to create a filtering pipeline that scores RNA secondary structure at all stages, with results that are synergistic with existing methods.

The comparison of a pair of electron microscope images recorded at different specimen tilt angles provides a powerful approach for evaluating the quality of images, image-processing procedures, or three-dimensional structures. Here, we analyze tilt-pair images recorded from a range of specimens with different symmetries and molecular masses and show how the analysis can produce valuable information not easily obtained otherwise. We show that the accuracy of orientation determination of individual single particles depends on molecular mass, as expected theoretically since the information in each particle image increases with molecular mass. The angular uncertainty is less than 1° for particles of high molecular mass ( 50 MDa), several degrees for particles in the range 1-5 MDa, and tens of degrees for particles below 1 MDa. Orientational uncertainty may be the major contributor to the effective temperature factor (B-factor) describing contrast loss and therefore the maximum resolution of a structure determination. We also made two unexpected observations. Single particles that are known to be flexible showed a wider spread in orientation accuracy, and the orientations of the largest particles examined changed by several degrees during typical low-dose exposures. Smaller particles presumably also reorient during the exposure; hence, specimen movement is a second major factor that limits resolution. Tilt pairs thus enable assessment of orientation accuracy, map quality, specimen motion, and conformational heterogeneity. A convincing tilt-pair parameter plot, where 60% of the particles show a single cluster around the expected tilt axis and tilt angle, provides confidence in a structure determined using electron cryomicroscopy.

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain’s computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Receptor-regulated cellular signaling often is mediated by formation of transient, heterogeneous protein complexes of undefined structure. We used single and two-color photoactivated localization microscopy to study complexes downstream of the T cell antigen receptor (TCR) in single-molecule detail at the plasma membrane of intact T cells. The kinase ZAP-70 distributed completely with the TCRζ chain and both partially mixed with the adaptor LAT in activated cells, thus showing localized activation of LAT by TCR-coupled ZAP-70. In resting and activated cells, LAT primarily resided in nanoscale clusters as small as dimers whose formation depended on protein-protein and protein-lipid interactions. Surprisingly, the adaptor SLP-76 localized to the periphery of LAT clusters. This nanoscale structure depended on polymerized actin and its disruption affected TCR-dependent cell function. These results extend our understanding of the mechanism of T cell activation and the formation and organization of TCR-mediated signaling complexes, findings also relevant to other receptor systems.

A crucial issue in studies of morphogen gradients relates to their range: the distance over which they can act as direct regulators of cell signaling, gene expression and cell differentiation. To address this, we present a straightforward statistical framework that can be used in multiple developmental systems. We illustrate the developed approach by providing a point estimate and confidence interval for the spatial range of the graded distribution of nuclear Dorsal, a transcription factor that controls the dorsoventral pattern of the Drosophila embryo.