Although nervous system sexual dimorphisms are known in many species, relatively little is understood about the molecular mechanisms generating these dimorphisms. Recent findings in Drosophila provide the tools for dissecting how neurogenesis and neuronal differentiation are modulated by the Drosophila sex-determination regulatory genes to produce nervous system sexual dimorphisms. Here we report studies aimed at illuminating the basis of the sexual dimorphic axonal projection patterns of foreleg gustatory receptor neurons (GRNs): only in males do GRN axons project across the midline of the ventral nerve cord. We show that the sex determination genes fruitless (fru) and doublesex (dsx) both contribute to establishing this sexual dimorphism. Male-specific Fru (Fru(M)) acts in foreleg GRNs to promote midline crossing by their axons, whereas midline crossing is repressed in females by female-specific Dsx (Dsx(F)). In addition, midline crossing by these neurons might be promoted in males by male-specific Dsx (Dsx(M)). Finally, we (1) demonstrate that the roundabout (robo) paralogs also regulate midline crossing by these neurons, and (2) provide evidence that Fru(M) exerts its effect on midline crossing by directly or indirectly regulating Robo signaling.

Since the demonstration that the sequence of a protein encodes its structure, the prediction of structure from sequence remains an outstanding problem that impacts numerous scientific disciplines, including many genome projects. By iteratively fixing secondary structure assignments of residues during Monte Carlo simulations of folding, our coarse-grained model without information concerning homology or explicit side chains can outperform current homology-based secondary structure prediction methods for many proteins. The computationally rapid algorithm using only single (phi,psi) dihedral angle moves also generates tertiary structures of accuracy comparable with existing all-atom methods for many small proteins, particularly those with low homology. Hence, given appropriate search strategies and scoring functions, reduced representations can be used for accurately predicting secondary structure and providing 3D structures, thereby increasing the size of proteins approachable by homology-free methods and the accuracy of template methods that depend on a high-quality input secondary structure.

The use of chronically implanted electrodes for neural recordings in small, freely behaving animals poses several unique technical challenges. Because of the need for an extremely lightweight apparatus, chronic recording technology has been limited to manually operated microdrives, despite the advantage of motorized manipulators for positioning electrodes. Here we describe a motorized, miniature chronically implantable microdrive for independently positioning three electrodes in the brain. The electrodes are controlled remotely, avoiding the need to disturb the animal during electrode positioning. The microdrive is approximately 6 mm in diameter, 17 mm high and weighs only 1.5 g, including the headstage preamplifier. Use of the motorized microdrive has produced a ten-fold increase in our data yield compared to those experiments done using a manually operated drive. In addition, we are able to record from multiple single neurons in the behaving animal with signal quality comparable to that seen in a head-fixed anesthetized animal. We also describe a motorized commutator that actively tracks animal rotation based on a measurement of torque in the tether.

The ability to image neurons anywhere in the mammalian brain is a major goal of optical microscopy. Here we describe a minimally invasive microendoscopy system for studying the morphology and function of neurons at depth. Utilizing a guide cannula with an ultrathin wall, we demonstrated in vivo two-photon fluorescence imaging of deeply buried nuclei such as the striatum (2.5 mm depth), substantia nigra (4.4 mm depth) and lateral hypothalamus (5.0 mm depth) in mouse brain. We reported, for the first time, the observation of neuronal activity with subcellular resolution in the lateral hypothalamus and substantia nigra of head-fixed awake mice.

The ability to automatically segment an image into distinct regions is a critical aspect in many visual processing applications. Because inaccuracies often exist in automatic segmentation, manual segmentation is necessary in some application domains to correct mistakes, such as required in the reconstruction of neuronal processes from microscopic images. The goal of the automated segmentation tool is traditionally to produce the highest-quality segmentation, where quality is measured by the similarity to actual ground truth, so as to minimize the volume of manual correction necessary. Manual correction is generally orders-of-magnitude more time consuming than automated segmentation, often making handling large images intractable. Therefore, we propose a more relevant goal: minimizing the turn-around time of automated/manual segmentation while attaining a level of similarity with ground truth. It is not always necessary to inspect every aspect of an image to generate a useful segmentation. As such, we propose a strategy to guide manual segmentation to the most uncertain parts of segmentation. Our contributions include 1) a probabilistic measure that evaluates segmentation without ground truth and 2) a methodology that leverages these probabilistic measures to significantly reduce manual correction while maintaining segmentation quality.

How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes. Widely used methods typically rank genes according to their differential expressions among phenotypes and pick the top-ranked genes. We observe that feature sets so obtained have certain redundancy and study methods to minimize it. We propose a minimum redundancy - maximum relevance (MRMR) feature selection framework. Genes selected via MRMR provide a more balanced coverage of the space and capture broader characteristics of phenotypes. They lead to significantly improved class predictions in extensive experiments on 6 gene expression data sets: NCI, Lymphoma, Lung, Child Leukemia, Leukemia, and Colon. Improvements are observed consistently among 4 classification methods: Naive Bayes, Linear discriminant analysis, Logistic regression, and Support vector machines. SUPPLIMENTARY: The top 60 MRMR genes for each of the datasets are listed in http://crd.lbl.gov/ cding/MRMR/. More information related to MRMR methods can be found at http://www.hpeng.net/.

An important open question in biophysics is to understand how mechanical forces shape membrane-bounded cells and their organelles. A general solution to this problem is to calculate the bending energy of an arbitrarily shaped membrane surface, which can include both lipids and cytoskeletal proteins, and minimize the energy subject to all mechanical constraints. However, the calculations are difficult to perform, especially for shapes that do not possess axial symmetry. We show that the spherical harmonics parameterization (SHP) provides an analytic description of shape that can be used to quickly and reliably calculate minimum energy shapes of both symmetric and asymmetric surfaces. Using this method, we probe the entire set of shapes predicted by the bilayer couple model, unifying work based on different computational approaches, and providing additional details of the transitions between different shape classes. In addition, we present new minimum-energy morphologies based on non-linear models of membrane skeletal elasticity that closely mimic extreme shapes of red blood cells. The SHP thus provides a versatile shape description that can be used to investigate forces that shape cells.

Starvation-induced autophagosomes engulf cytosol and/or organelles and deliver them to lysosomes for degradation, thereby resupplying depleted nutrients. Despite advances in understanding the molecular basis of this process, the membrane origin of autophagosomes remains unclear. Here, we demonstrate that, in starved cells, the outer membrane of mitochondria participates in autophagosome biogenesis. The early autophagosomal marker, Atg5, transiently localizes to punctae on mitochondria, followed by the late autophagosomal marker, LC3. The tail-anchor of an outer mitochondrial membrane protein also labels autophagosomes and is sufficient to deliver another outer mitochondrial membrane protein, Fis1, to autophagosomes. The fluorescent lipid NBD-PS (converted to NBD-phosphotidylethanolamine in mitochondria) transfers from mitochondria to autophagosomes. Photobleaching reveals membranes of mitochondria and autophagosomes are transiently shared. Disruption of mitochondria/ER connections by mitofusin2 depletion dramatically impairs starvation-induced autophagy. Mitochondria thus play a central role in starvation-induced autophagy, contributing membrane to autophagosomes.

Healthy mitochondria are critical for reproduction. During aging, both reproductive fitness and mitochondrial homeostasis decline. Mitochondrial metabolism and dynamics are key factors in supporting mitochondrial homeostasis. However, how they are coupled to control reproductive health remains unclear. We report that mitochondrial GTP (mtGTP) metabolism acts through mitochondrial dynamics factors to regulate reproductive aging. We discovered that germline-only inactivation of GTP- but not ATP-specific succinyl-CoA synthetase (SCS) promotes reproductive longevity in Caenorhabditis elegans. We further identified an age-associated increase in mitochondrial clustering surrounding oocyte nuclei, which is attenuated by GTP-specific SCS inactivation. Germline-only induction of mitochondrial fission factors sufficiently promotes mitochondrial dispersion and reproductive longevity. Moreover, we discovered that bacterial inputs affect mtGTP levels and dynamics factors to modulate reproductive aging. These results demonstrate the significance of mtGTP metabolism in regulating oocyte mitochondrial homeostasis and reproductive longevity and identify mitochondrial fission induction as an effective strategy to improve reproductive health.

Healthy mitochondria are critical for reproduction. During aging, both reproductive fitness and mitochondrial homeostasis decline. Mitochondrial metabolism and dynamics are key factors in supporting mitochondrial homeostasis. However, how they are coupled to control reproductive health remains unclear. We report that mitochondrial GTP (mtGTP) metabolism acts through mitochondrial dynamics factors to regulate reproductive aging. We discovered that germline-only inactivation of GTP- but not ATP-specific succinyl-CoA synthetase (SCS) promotes reproductive longevity in Caenorhabditis elegans. We further identified an age-associated increase in mitochondrial clustering surrounding oocyte nuclei, which is attenuated by GTP-specific SCS inactivation. Germline-only induction of mitochondrial fission factors sufficiently promotes mitochondrial dispersion and reproductive longevity. Moreover, we discovered that bacterial inputs affect mtGTP levels and dynamics factors to modulate reproductive aging. These results demonstrate the significance of mtGTP metabolism in regulating oocyte mitochondrial homeostasis and reproductive longevity and identify mitochondrial fission induction as an effective strategy to improve reproductive health.