Anatomy of large biological specimens is often reconstructed from serially sectioned volumes imaged by high-resolution microscopy. We developed a method to reassemble a continuous volume from such large section series that explicitly minimizes artificial deformation by applying a global elastic constraint. We demonstrate our method on a series of transmission electron microscopy sections covering the entire 558-cell Caenorhabditis elegans embryo and a segment of the Drosophila melanogaster larval ventral nerve cord.

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

The visual system of Drosophila is an excellent model for determining the interactions that direct the differentiation of the nervous system’s many unique cell types. Glia are essential not only in the development of the nervous system, but also in the function of those neurons with which they become associated in the adult. Given their role in visual system development and adult function we need to both accurately and reliably identify the different subtypes of glia, and to relate the glial subtypes in the larval brain to those previously described for the adult. We viewed driver expression in subsets of larval eye disc glia through the earliest stages of pupal development to reveal the counterparts of these cells in the adult. Two populations of glia exist in the lamina, the first neuropil of the adult optic lobe: those that arise from precursors in the eye-disc/optic stalk and those that arise from precursors in the brain. In both cases, a single larval source gives rise to at least three different types of adult glia. Furthermore, analysis of glial cell types in the second neuropil, the medulla, has identified at least four types of astrocyte-like (reticular) glia. Our clarification of the lamina’s adult glia and identification of their larval origins, particularly the respective eye disc and larval brain contributions, begin to define developmental interactions which establish the different subtypes of glia.

Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options.

Females of many animal species emit chemical signals that attract and arouse males for mating. For example, the major aphrodisiac pheromone of Drosophila melanogaster females, 7,11-heptacosadiene (7,11-HD), is a potent inducer of male-specific courtship and copulatory behaviors. Here, we demonstrate that a set of gustatory sensory neurons on the male foreleg, defined by expression of the ppk23 marker, respond to 7,11-HD. Activity of these neurons is required for males to robustly court females or to court males perfumed with 7,11-HD. Artificial activation of these ppk23(+) neurons stimulates male-male courtship even without 7,11-HD perfuming. These data identify the ppk23(+) sensory neurons as the primary targets for female sex pheromones in Drosophila.

The functional state of a cell is largely determined by the spatiotemporal organization of its proteome. Technologies exist for measuring particular aspects of protein turnover and localization, but comprehensive analysis of protein dynamics across different scales is possible only by combining several methods. Here we describe tandem fluorescent protein timers (tFTs), fusions of two single-color fluorescent proteins that mature with different kinetics, which we use to analyze protein turnover and mobility in living cells. We fuse tFTs to proteins in yeast to study the longevity, segregation and inheritance of cellular components and the mobility of proteins between subcellular compartments; to measure protein degradation kinetics without the need for time-course measurements; and to conduct high-throughput screens for regulators of protein turnover. Our experiments reveal the stable nature and asymmetric inheritance of nuclear pore complexes and identify regulators of N-end rule–mediated protein degradation.

No abstract available.

An important role of visual systems is to detect nearby predators, prey, and potential mates [1], which may be distinguished in part by their motion. When an animal is at rest, an object moving in any direction may easily be detected by motion-sensitive visual circuits [2, 3]. During locomotion, however, this strategy is compromised because the observer must detect a moving object within the pattern of optic flow created by its own motion through the stationary background. However, objects that move creating back-to-front (regressive) motion may be unambiguously distinguished from stationary objects because forward locomotion creates only front-to-back (progressive) optic flow. Thus, moving animals should exhibit an enhanced sensitivity to regressively moving objects. We explicitly tested this hypothesis by constructing a simple fly-sized robot that was programmed to interact with a real fly. Our measurements indicate that whereas walking female flies freeze in response to a regressively moving object, they ignore a progressively moving one. Regressive motion salience also explains observations of behaviors exhibited by pairs of walking flies. Because the assumptions underlying the regressive motion salience hypothesis are general, we suspect that the behavior we have observed in Drosophila may be widespread among eyed, motile organisms.

Imaging mRNA with single-molecule sensitivity in live cells has become an indispensable tool for quantitatively studying RNA biology. The MS2 system has been extensively used due to its unique simplicity and sensitivity. However, the levels of the coat protein needed for consistent labeling of mRNAs limits the sensitivity and quantitation of this technology. Here, we applied fluorescence fluctuation spectroscopy to quantitatively characterize and enhance the MS2 system. Surprisingly, we found that a high fluorescence background resulted from inefficient dimerization of fluorescent protein (FP)-labeled MS2 coat protein (MCP). To mitigate this problem, we used a single-chain tandem dimer of MCP (tdMCP) that significantly increased the uniformity and sensitivity of mRNA labeling. Furthermore, we characterized the PP7 coat protein and the binding to its respective RNA stem loop. We conclude that the PP7 system performs better for RNA labeling. Finally, we used these improvements to study endogenous β-actin mRNA, which has 24xMS2 binding sites inserted into the 3' untranslated region. The tdMCP-FP allowed uniform RNA labeling and provided quantitative measurements of endogenous mRNA concentration and diffusion. This work provides a foundation for quantitative spectroscopy and imaging of single mRNAs directly in live cells.

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.