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161 Publications
Showing 151-160 of 161 resultsThe secondary neurons generated in the thoracic central nervous system of Drosophila arise from a hemisegmental set of 25 neuronal stem cells, the neuroblasts (NBs). Each NB undergoes repeated asymmetric divisions to produce a series of smaller ganglion mother cells (GMCs), which typically divide once to form two daughter neurons. We find that the two daughters of the GMC consistently have distinct fates. Using both loss-of-function and gain-of-function approaches, we examined the role of Notch signaling in establishing neuronal fates within all of the thoracic secondary lineages. In all cases, the ’A’ (Notch(ON)) sibling assumes one fate and the ’B’ (Notch(OFF)) sibling assumes another, and this relationship holds throughout the neurogenic period, resulting in two major neuronal classes: the A and B hemilineages. Apparent monotypic lineages typically result from the death of one sibling throughout the lineage, resulting in a single, surviving hemilineage. Projection neurons are predominantly from the B hemilineages, whereas local interneurons are typically from A hemilineages. Although sibling fate is dependent on Notch signaling, it is not necessarily dependent on numb, a gene classically involved in biasing Notch activation. When Numb was removed at the start of larval neurogenesis, both A and B hemilineages were still generated, but by the start of the third larval instar, the removal of Numb resulted in all neurons assuming the A fate. The need for Numb to direct Notch signaling correlated with a decrease in NB cell cycle time and may be a means for coping with multiple sibling pairs simultaneously undergoing fate decisions.
It is well known that light-sheet illumination can enable optically sectioned wide-field imaging of macroscopic samples. However, the optical sectioning capacity of a light-sheet macroscope is undermined by sample-induced scattering or aberrations that broaden the thickness of the sheet illumination. We present a technique to enhance the optical sectioning capacity of a scanning light-sheet microscope by out-of-focus background rejection. The technique, called HiLo microscopy, makes use of two images sequentially acquired with uniform and structured sheet illumination. An optically sectioned image is then synthesized by fusing high and low spatial frequency information from both images. The benefits of combining light-sheet macroscopy and HiLo background rejection are demonstrated in optically cleared whole mouse brain samples, using both green fluorescent protein (GFP)-fluorescence and dark-field scattered light contrast.
Recent developments in single-molecule localization techniques using photoactivatable fluorescent proteins have allowed the probing of single-molecule motion in a living cell with high specificity, millisecond time resolution, and nanometer spatial resolution. Analyzing the dynamics of individual molecules at high densities in this manner promises to provide new insights into the mechanisms of many biological processes, including protein heterogeneity in the plasma membrane, the dynamics of cytoskeletal flow, and clustering of receptor complexes in response to signaling cues. Here we describe the method of single-molecule tracking photoactivated localization microscopy (sptPALM) and discuss how its use can contribute to a quantitative understanding of fundamental cellular processes.
Superresolution imaging is a rapidly emerging new field of microscopy that dramatically improves the spatial resolution of light microscopy by over an order of magnitude (approximately 10-20-nm resolution), allowing biological processes to be described at the molecular scale. Here, we discuss a form of superresolution microscopy based on the controlled activation and sampling of sparse subsets of photoconvertible fluorescent molecules. In this single-molecule-based imaging approach, a wide variety of probes have proved valuable, ranging from genetically encodable photoactivatable fluorescent proteins to photoswitchable cyanine dyes. These have been used in diverse applications of superresolution imaging: from three-dimensional, multicolor molecule localization to tracking of nanometric structures and molecules in living cells. Single-molecule-based superresolution imaging thus offers exciting possibilities for obtaining molecular-scale information on biological events occurring at variable timescales.
BACKGROUND: Previous studies suggest that mechanical feedback could coordinate morphogenetic events in embryos. Furthermore, embryonic tissues have complex structure and composition and undergo large deformations during morphogenesis. Hence we expect highly non-linear and loading-rate dependent tissue mechanical properties in embryos. METHODOLOGY/PRINCIPAL FINDINGS: We used micro-aspiration to test whether a simple linear viscoelastic model was sufficient to describe the mechanical behavior of gastrula stage Xenopus laevis embryonic tissue in vivo. We tested whether these embryonic tissues change their mechanical properties in response to mechanical stimuli but found no evidence of changes in the viscoelastic properties of the tissue in response to stress or stress application rate. We used this model to test hypotheses about the pattern of force generation during electrically induced tissue contractions. The dependence of contractions on suction pressure was most consistent with apical tension, and was inconsistent with isotropic contraction. Finally, stiffer clutches generated stronger contractions, suggesting that force generation and stiffness may be coupled in the embryo. CONCLUSIONS/SIGNIFICANCE: The mechanical behavior of a complex, active embryonic tissue can be surprisingly well described by a simple linear viscoelastic model with power law creep compliance, even at high deformations. We found no evidence of mechanical feedback in this system. Together these results show that very simple mechanical models can be useful in describing embryo mechanics.
BACKGROUND: Conditional gene activation is an efficient strategy for studying gene function in genetically modified animals. Among the presently available gene switches, the tetracycline-regulated system has attracted considerable interest because of its unique potential for reversible and adjustable gene regulation. RESULTS: To investigate whether the ubiquitously expressed Gt(ROSA)26Sor locus enables uniform DOX-controlled gene expression, we inserted the improved tetracycline-regulated transcription activator iM2 together with an iM2 dependent GFP gene into the Gt(ROSA)26Sor locus, using gene targeting to generate ROSA26-iM2-GFP (R26t1Δ) mice. Despite the presence of ROSA26 promoter driven iM2, R26t1Δ mice showed very sparse DOX-activated expression of different iM2-responsive reporter genes in the brain, mosaic expression in peripheral tissues and more prominent expression in erythroid, myeloid and lymphoid lineages, in hematopoietic stem and progenitor cells and in olfactory neurons. CONCLUSIONS: The finding that gene regulation by the DOX-activated transcriptional factor iM2 in the Gt(ROSA)26Sor locus has its limitations is of importance for future experimental strategies involving transgene activation from the endogenous ROSA26 promoter. Furthermore, our ROSA26-iM2 knock-in mouse model (R26t1Δ) represents a useful tool for implementing gene function in vivo especially under circumstances requiring the side-by-side comparison of gene manipulated and wild type cells. Since the ROSA26-iM2 mouse allows mosaic gene activation in peripheral tissues and haematopoietic cells, this model will be very useful for uncovering previously unknown or unsuspected phenotypes.
The genome of the severe acute respiratory syndrome-associated coronavirus (SARS-CoV) contains eight open reading frames (ORFs) that encode novel proteins. These accessory proteins are dispensable for in vitro and in vivo replication and thus may be important for other aspects of virus-host interactions. We investigated the functions of the largest of the accessory proteins, the ORF 3a protein, using a 3a-deficient strain of SARS-CoV. Cell death of Vero cells after infection with SARS-CoV was reduced upon deletion of ORF 3a. Electron microscopy of infected cells revealed a role for ORF 3a in SARS-CoV induced vesicle formation, a prominent feature of cells from SARS patients. In addition, we report that ORF 3a is both necessary and sufficient for SARS-CoV-induced Golgi fragmentation and that the 3a protein accumulates and localizes to vesicles containing markers for late endosomes. Finally, overexpression of ADP-ribosylation factor 1 (Arf1), a small GTPase essential for the maintenance of the Golgi apparatus, restored Golgi morphology during infection. These results establish an important role for ORF 3a in SARS-CoV-induced cell death, Golgi fragmentation, and the accumulation of intracellular vesicles.
Pfam is a widely used database of protein families and domains. This article describes a set of major updates that we have implemented in the latest release (version 24.0). The most important change is that we now use HMMER3, the latest version of the popular profile hidden Markov model package. This software is approximately 100 times faster than HMMER2 and is more sensitive due to the routine use of the forward algorithm. The move to HMMER3 has necessitated numerous changes to Pfam that are described in detail. Pfam release 24.0 contains 11,912 families, of which a large number have been significantly updated during the past two years. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/).
High-throughput screening (HTS) using model organisms is a promising method to identify a small number of genes or drugs potentially relevant to human biology or disease. In HTS experiments, robots and computers do a significant portion of the experimental work. However, one remaining major bottleneck is the manual analysis of experimental results, which is commonly in the form of microscopy images. This manual inspection is labor intensive, slow and subjective. Here we report our progress towards applying computer vision and machine learning methods to analyze HTS experiments that use Caenorhabditis elegans (C. elegans) worms grown on agar. Our main contribution is a robust segmentation algorithm for separating the worms from the background using brightfield images. We also show that by combining the output of this segmentation algorithm with an algorithm to detect the fluorescent dye, Nile Red, we can reliably distinguish different fluorescence-based phenotypes even though the visual differences are subtle. The accuracy of our method is similar to that of expert human analysts. This new capability is a significant step towards fully automated HTS experiments using C. elegans.