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14 Publications

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    Simpson Lab
    10/20/11 | Genetic manipulation of genes and cells in the nervous system of the fruit fly.
    Venken KJ, Simpson JH, Bellen HJ
    Neuron. 2011 Oct 20;72(2):202-30. doi: 10.1016/j.neuron.2011.09.021

    Research in the fruit fly Drosophila melanogaster has led to insights in neural development, axon guidance, ion channel function, synaptic transmission, learning and memory, diurnal rhythmicity, and neural disease that have had broad implications for neuroscience. Drosophila is currently the eukaryotic model organism that permits the most sophisticated in vivo manipulations to address the function of neurons and neuronally expressed genes. Here, we summarize many of the techniques that help assess the role of specific neurons by labeling, removing, or altering their activity. We also survey genetic manipulations to identify and characterize neural genes by mutation, overexpression, and protein labeling. Here, we attempt to acquaint the reader with available options and contexts to apply these methods.

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    10/14/11 | Cell biology. SevERing mitochondria.
    Rambold AS, Lippincott-Schwartz J
    Science (New York, N.Y.). 2011 Oct 14;334(6053):186-7. doi: 10.1126/science.1214059
    Gonen Lab
    10/12/11 | Advances in structural and functional analysis of membrane proteins by electron crystallography.
    Wisedchaisri G, Reichow SL, Gonen T
    Structure. 2011 Oct 12;19(10):1381-93. doi: 10.1016/j.str.2011.09.001

    Electron crystallography is a powerful technique for the study of membrane protein structure and function in the lipid environment. When well-ordered two-dimensional crystals are obtained the structure of both protein and lipid can be determined and lipid-protein interactions analyzed. Protons and ionic charges can be visualized by electron crystallography and the protein of interest can be captured for structural analysis in a variety of physiologically distinct states. This review highlights the strengths of electron crystallography and the momentum that is building up in automation and the development of high throughput tools and methods for structural and functional analysis of membrane proteins by electron crystallography.

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    10/12/11 | Perception of sniff phase in mouse olfaction.
    Smear M, Shusterman R, O’Connor R, Bozza T, Rinberg D
    Nature. 2011 Oct 12;14(7373):1039-44. doi: 10.1038/nature10521

    Olfactory systems encode odours by which neurons respond and by when they respond. In mammals, every sniff evokes a precise, odour-specific sequence of activity across olfactory neurons. Likewise, in a variety of neural systems, ranging from sensory periphery to cognitive centres, neuronal activity is timed relative to sampling behaviour and/or internally generated oscillations. As in these neural systems, relative timing of activity may represent information in the olfactory system. However, there is no evidence that mammalian olfactory systems read such cues. To test whether mice perceive the timing of olfactory activation relative to the sniff cycle (’sniff phase’), we used optogenetics in gene-targeted mice to generate spatially constant, temporally controllable olfactory input. Here we show that mice can behaviourally report the sniff phase of optogenetically driven activation of olfactory sensory neurons. Furthermore, mice can discriminate between light-evoked inputs that are shifted in the sniff cycle by as little as 10 milliseconds, which is similar to the temporal precision of olfactory bulb odour responses. Electrophysiological recordings in the olfactory bulb of awake mice show that individual cells encode the timing of photoactivation in relation to the sniff in both the timing and the amplitude of their responses. Our work provides evidence that the mammalian olfactory system can read temporal patterns, and suggests that timing of activity relative to sampling behaviour is a potent cue that may enable accurate olfactory percepts to form quickly.

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    Svoboda Lab
    10/06/11 | Long-range neuronal circuits underlying the interaction between sensory and motor cortex.
    Mao T, Kusefoglu D, Hooks BM, Huber D, Petreanu L, Svoboda K
    Neuron. 2011 Oct 6;72:111-23. doi: 10.1016/j.neuron.2011.07.029

    In the rodent vibrissal system, active sensation and sensorimotor integration are mediated in part by connections between barrel cortex and vibrissal motor cortex. Little is known about how these structures interact at the level of neurons. We used Channelrhodopsin-2 (ChR2) expression, combined with anterograde and retrograde labeling, to map connections between barrel cortex and pyramidal neurons in mouse motor cortex. Barrel cortex axons preferentially targeted upper layer (L2/3, L5A) neurons in motor cortex; input to neurons projecting back to barrel cortex was particularly strong. Barrel cortex input to deeper layers (L5B, L6) of motor cortex, including neurons projecting to the brainstem, was weak, despite pronounced geometric overlap of dendrites with axons from barrel cortex. Neurons in different layers received barrel cortex input within stereotyped dendritic domains. The cortico-cortical neurons in superficial layers of motor cortex thus couple motor and sensory signals and might mediate sensorimotor integration and motor learning.

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    10/06/11 | Sparse incomplete representations: a potential role of olfactory granule cells.
    Koulakov AA, Rinberg D
    Neuron. 2011 Oct 6;72(1):124-36. doi: 10.1016/j.neuron.2011.07.031

    Mitral/tufted cells of the olfactory bulb receive odorant information from receptor neurons and transmit this information to the cortex. Studies in awake behaving animals have found that sustained responses of mitral cells to odorants are rare, suggesting sparse combinatorial representation of the odorants. Careful alignment of mitral cell firing with the phase of the respiration cycle revealed brief transient activity in the larger population of mitral cells, which respond to odorants during a small fraction of the respiration cycle. Responses of these cells are therefore temporally sparse. Here, we propose a mathematical model for the olfactory bulb network that can reproduce both combinatorially and temporally sparse mitral cell codes. We argue that sparse codes emerge as a result of the balance between mitral cells’ excitatory inputs and inhibition provided by the granule cells. Our model suggests functional significance for the dendrodendritic synapses mediating interactions between mitral and granule cells.

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    10/05/11 | Alk is a transcriptional target of LMO4 and ERα that promotes cocaine sensitization and reward.
    Lasek AW, Gesch J, Giorgetti F, Kharazia V, Heberlein U
    The Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 2011 Oct 5;31(40):14134-41. doi: 10.1523/JNEUROSCI.3415-11.2011

    Previously, we showed that the mouse LIM-domain only 4 (Lmo4) gene, which encodes a protein containing two zinc-finger LIM domains that interact with various DNA-binding transcription factors, attenuates behavioral sensitivity to repeated cocaine administration. Here we show that transcription of anaplastic lymphoma kinase (Alk) is repressed by LMO4 in the striatum and that Alk promotes the development of cocaine sensitization and conditioned place preference, a measure of cocaine reward. Since LMO4 is known to interact with estrogen receptor α (ERα) at the promoters of target genes, we investigated whether Alk expression might be controlled by a similar mechanism. We found that LMO4 and ERα are associated with the Alk promoter by chromatin immunoprecipitation and that Alk is an estrogen-responsive gene in the striatum. Moreover, we show that ERα knock-out mice exhibit enhanced cocaine sensitization and conditioned place preference and an increase in Alk expression in the nucleus accumbens. These data define a novel regulatory network involved in behavioral responses to cocaine. Interestingly, sex differences in several behavioral responses to cocaine in humans and rodents have been described, and estrogen is thought to mediate some of these differences. Our data suggest that estrogen regulation of Alk may be one mechanism responsible for sexually dimorphic responses to cocaine.

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    10/01/11 | Accelerated profile HMM searches.
    Eddy SR
    PLoS Computational Biology. 2011 Oct;7(10):e1002195. doi: 10.1371/journal.pcbi.1002195

    Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.

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    Grigorieff Lab
    10/01/11 | An adaptation of the Wiener filter suitable for analyzing images of isolated single particles.
    Sindelar CV, Grigorieff N
    Journal of Structural Biology. 2011 Oct;176(1):60-74. doi: 10.1016/j.jsb.2011.06.010

    The Wiener filter is a standard means of optimizing the signal in sums of aligned, noisy images obtained by electron cryo-microscopy (cryo-EM). However, estimation of the resolution-dependent ("spectral") signal-to-noise ratio (SSNR) from the input data has remained problematic, and error reduction due to specific application of the SSNR term within a Wiener filter has not been reported. Here we describe an adjustment to the Wiener filter for optimal summation of images of isolated particles surrounded by large regions of featureless background, as is typically the case in single-particle cryo-EM applications. We show that the density within the particle area can be optimized, in the least-squares sense, by scaling the SSNR term found in the conventional Wiener filter by a factor that reflects the fraction of the image field occupied by the particle. We also give related expressions that allow the SSNR to be computed for application in this new filter, by incorporating a masking step into a Fourier Ring Correlation (FRC), a standard resolution measure. Furthermore, we show that this masked FRC estimation scheme substantially improves on the accuracy of conventional SSNR estimation methods. We demonstrate the validity of our new approach in numeric tests with simulated data corresponding to realistic cryo-EM imaging conditions. This variation of the Wiener filter and accompanying derivation should prove useful for a variety of single-particle cryo-EM applications, including 3D reconstruction.

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    10/01/11 | Anisotropic path searching for automatic neuron reconstruction.
    Xie J, Zhao T, Lee T, Myers E, Peng H
    Medical Image Analysis. 2011 Oct;15:680-9. doi: 10.1016/j.media.2011.05.013

    Full reconstruction of neuron morphology is of fundamental interest for the analysis and understanding of their functioning. We have developed a novel method capable of automatically tracing neurons in three-dimensional microscopy data. In contrast to template-based methods, the proposed approach makes no assumptions about the shape or appearance of neurite structure. Instead, an efficient seeding approach is applied to capture complex neuronal structures and the tracing problem is solved by computing the optimal reconstruction with a weighted graph. The optimality is determined by the cost function designed for the path between each pair of seeds and by topological constraints defining the component interrelations and completeness. In addition, an automated neuron comparison method is introduced for performance evaluation and structure analysis. The proposed algorithm is computationally efficient and has been validated using different types of microscopy data sets including Drosophila’s projection neurons and fly neurons with presynaptic sites. In all cases, the approach yielded promising results.

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