@article {69542, title = {Neural circuit basis of placebo pain relief.}, journal = {Nature}, year = {2024}, month = {2024 Jul 24}, abstract = {

Placebo effects are striking demonstrations of mind-body interactions . During pain perception, in the absence of any treatment, an expectation of pain relief can reduce the experience of pain, a phenomenon known as placebo analgesia . However, despite the strength of placebo effects and their impact on everyday human experience and failure of clinical trials for new therapeutics , the neural circuit basis of placebo effects has remained elusive. Here, we show that analgesia from the expectation of pain relief is mediated by rostral anterior cingulate cortex (rACC) neurons that project to the pontine nucleus (rACC{\textrightarrow}Pn), a pre-cerebellar nucleus with no established function in pain. We created a behavioral assay that generates placebo-like anticipatory pain relief in mice. In vivo calcium imaging of neural activity and electrophysiological recordings in brain slices showed that expectations of pain relief boost the activity of rACC{\textrightarrow}Pn neurons and potentiate neurotransmission in this pathway. Transcriptomic studies of Pn neurons revealed an abundance of opioid receptors, further suggesting a role in pain modulation. Inhibition of the rACC{\textrightarrow}Pn pathway disrupted placebo analgesia and decreased pain thresholds, whereas activation elicited analgesia in the absence of placebo conditioning. Finally, Purkinje cells exhibited activity patterns resembling those of rACC{\textrightarrow}Pn neurons during pain relief expectation, providing cellular-level evidence of a role for the cerebellum in cognitive pain modulation. These findings open the possibility of targeting this prefrontal cortico-ponto-cerebellar pathway with drugs or neurostimulation to treat pain.

}, issn = {1476-4687}, doi = {10.1038/s41586-024-07816-z}, author = {Chen, Chong and Niehaus, Jesse K and Dinc, Fatih and Huang, Karen L and Barnette, Alexander L and Tassou, Adrien and Shuster, S Andrew and Wang, Lihua and Lemire, Andrew and Menon, Vilas and Ritola, Kimberly and Hantman, Adam and Zeng, Hongkui and Schnitzer, Mark J and Scherrer, Gr{\'e}gory} } @article {65798, title = {Behavioral state coding by molecularly defined paraventricular hypothalamic cell type ensembles.}, journal = {Science}, volume = {370}, year = {2020}, month = {2020 Oct 16}, abstract = {

Brains encode behaviors using neurons amenable to systematic classification by gene expression. The contribution of molecular identity to neural coding is not understood because of the challenges involved with measuring neural dynamics and molecular information from the same cells. We developed CaRMA (calcium and RNA multiplexed activity) imaging based on recording in vivo single-neuron calcium dynamics followed by gene expression analysis. We simultaneously monitored activity in hundreds of neurons in mouse paraventricular hypothalamus (PVH). Combinations of cell-type marker genes had predictive power for neuronal responses across 11 behavioral states. The PVH uses combinatorial assemblies of molecularly defined neuron populations for grouped-ensemble coding of survival behaviors. The neuropeptide receptor neuropeptide Y receptor type 1 (Npy1r) amalgamated multiple cell types with similar responses. Our results show that molecularly defined neurons are important processing units for brain function.

}, issn = {1095-9203}, doi = {10.1126/science.abb2494}, author = {Xu, Shengjin and Yang, Hui and Menon, Vilas and Lemire, Andrew L and Wang, Lihua and Henry, Fredrick E and Turaga, Srinivas C and Sternson, Scott M} } @article {65177, title = {Identification of cell types from single-cell transcriptomic data.}, journal = {Methods in Molecular Biology}, volume = {1935}, year = {2019}, month = {2019 Oct 16}, pages = {45-77}, abstract = {

Unprecedented technological advances in single-cell RNA-sequencing (scRNA-seq) technology have now made it possible to profile genome-wide expression in single cells at low cost and high throughput. There is substantial ongoing effort to use scRNA-seq measurements to identify the "cell types" that form components of a complex tissue, akin to taxonomizing species in ecology. Cell type classification from scRNA-seq data involves the application of computational tools rooted in dimensionality reduction and clustering, and statistical analysis to identify molecular signatures that are unique to each type. As datasets continue to grow in size and complexity, computational challenges abound, requiring analytical methods to be scalable, flexible, and robust. Moreover, careful consideration needs to be paid to experimental biases and statistical challenges that are unique to these measurements to avoid artifacts. This chapter introduces these topics in the context of cell-type identification, and outlines an instructive step-by-step example bioinformatic pipeline for researchers entering this field.

}, keywords = {Animals, Cluster Analysis, Computational Biology, Gene Expression Profiling, Genome, High-Throughput Nucleotide Sequencing, Humans, Mice, RNA, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome}, issn = {1940-6029}, doi = {10.1007/978-1-4939-9057-3_4}, author = {Shekhar, Karthik and Menon, Vilas} } @article {59911, title = {Molecular logic of spinocerebellar tract neuron diversity and connectivity.}, journal = {Cell Reports}, volume = {27}, year = {2019}, month = {2019 May 27}, pages = {2620-35}, abstract = {

Coordinated motor behaviors depend on feedback communication between peripheral sensory systems and central circuits in the brain and spinal cord. Relay of muscle and tendon-derived sensory information to the CNS is facilitated by functionally and anatomically diverse groups of spinocerebellar tract neurons (SCTNs), but the molecular logic by which SCTN diversity and connectivity is achieved is poorly understood. We used single cell RNA sequencing and genetic manipulations to define the mechanisms governing the molecular profile and organization of SCTN subtypes. We found that SCTNs relaying proprioceptive sensory information from limb and axial muscles are generated through segmentally-restricted actions of specific Hox genes. Loss of Hox function disrupts SCTN subtype-specific transcriptional programs, leading to defects in the connections between proprioceptive sensory neurons, SCTNs, and the cerebellum. These results indicate that Hox-dependent genetic programs play essential roles in the assembly of the neural circuits required for proprioception.

}, doi = {10.1016/j.celrep.2019.04.113}, author = {Baek, Myungin and Menon, Vilas and Jessell, Thomas M and Hantman, Adam W and Dasen, Jeremy} } @article {49118, title = {Continuous variation within cell types of the nervous system.}, journal = {Trends in Neurosciences}, volume = {41}, year = {2018}, month = {2018 Mar 22}, pages = {337-48}, abstract = {

The brain is an organ of immense complexity. Next-generation RNA sequencing (RNA-seq) is becoming increasingly popular in the deconstruction of this complexity into distinct classes of {\textquoteright}cell types{\textquoteright}. Notably, in addition to revealing the organization of this distinct cell-type landscape, the technology has also begun to illustrate that continuous variation can be found within narrowly defined cell types. Here we summarize the evidence for graded transcriptomic heterogeneity being present, widespread, and functionally relevant in the nervous system. We explain how these graded differences can map onto higher-order organizational features and how they may reframe existing interpretations of higher-order heterogeneity. Ultimately, a multimodal approach incorporating continuously variable cell types will facilitate an accurate reductionist interpretation of the nervous system.

}, issn = {1878-108X}, doi = {10.1016/j.tins.2018.02.010}, author = {Cembrowski, Mark S and Menon, Vilas} } @article {49496, title = {Distinct descending motor cortex pathways and their roles in movement.}, journal = {Nature}, volume = {563}, year = {2018}, month = {2018 Nov}, pages = {79-84}, abstract = {

Activity in the motor cortex predicts movements, seconds before they are initiated. This preparatory activity has been observed across cortical layers, including in descending pyramidal tract neurons in layer 5. A key question is how preparatory activity is maintained without causing movement, and is ultimately converted to a motor command to trigger appropriate movements. Here, using single-cell transcriptional profiling and axonal reconstructions, we identify two types of pyramidal tract neuron. Both types project to several targets in the basal ganglia and brainstem. One type projects to thalamic regions that connect back to motor cortex; populations of these neurons produced early preparatory activity that persisted until the movement was initiated. The second type projects to motor centres in the medulla and mainly\ produced late preparatory activity and motor commands. These results indicate that two types of motor cortex output neurons have specialized roles in motor control.

}, issn = {1476-4687}, doi = {10.1038/s41586-018-0642-9}, author = {Economo, Michael N and Viswanathan, Sarada and Tasic, Bosiljka and Bas, Erhan and Winnubst, Johan and Menon, Vilas and Graybuck, Lucas T and Nguyen, Thuc Nghi and Smith, Kimberly A and Yao, Zizhen and Wang, Lihua and Gerfen, Charles R and Chandrashekar, Jayaram and Zeng, Hongkui and Looger, Loren L and Svoboda, Karel} } @article {49495, title = {Shared and distinct transcriptomic cell types across neocortical areas.}, journal = {Nature}, volume = {563}, year = {2018}, month = {2018 Nov}, pages = {72-78}, abstract = {

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.

}, issn = {1476-4687}, doi = {10.1038/s41586-018-0654-5}, author = {Tasic, Bosiljka and Yao, Zizhen and Graybuck, Lucas T and Smith, Kimberly A and Nguyen, Thuc Nghi and Bertagnolli, Darren and Goldy, Jeff and Garren, Emma and Economo, Michael N and Viswanathan, Sarada and Penn, Osnat and Bakken, Trygve and Menon, Vilas and Miller, Jeremy and Fong, Olivia and Hirokawa, Karla E and Lathia, Kanan and Rimorin, Christine and Tieu, Michael and Larsen, Rachael and Casper, Tamara and Barkan, Eliza and Kroll, Matthew and Parry, Sheana and Shapovalova, Nadiya V and Hirschstein, Daniel and Pendergraft, Julie and Sullivan, Heather A and Kim, Tae Kyung and Szafer, Aaron and Dee, Nick and Groblewski, Peter and Wickersham, Ian and Cetin, Ali and Harris, Julie A and Levi, Boaz P and Sunkin, Susan M and Madisen, Linda and Daigle, Tanya L and Looger, Loren and Bernard, Amy and Phillips, John and Lein, Ed and Hawrylycz, Michael and Svoboda, Karel and Jones, Allan R and Koch, Christof and Zeng, Hongkui} } @article {48980, title = {Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data.}, journal = {Briefings in Functional Genomics}, volume = {17}, year = {2017}, month = {2017 Dec 11}, pages = {240-45}, abstract = {

Advances in single-cell RNA-sequencing technology have resulted in a wealth of studies aiming to identify transcriptomic cell types in various biological systems. There are multiple experimental approaches to isolate and profile single cells, which provide different levels of cellular and tissue coverage. In addition, multiple computational strategies have been proposed to identify putative cell types from single-cell data. From a data generation perspective, recent single-cell studies can be classified into two groups: those that distribute reads shallowly over large numbers of cells and those that distribute reads more deeply over a smaller cell population. Although there are advantages to both approaches in terms of cellular and tissue coverage, it is unclear whether different computational cell type identification methods are better suited to one or the other experimental paradigm. This study reviews three cell type clustering algorithms, each representing one of three broad approaches, and finds that PCA-based algorithms appear most suited to low read depth data sets, whereas gene clustering-based and biclustering algorithms perform better on high read depth data sets. In addition, highly related cell classes are better distinguished by higher-depth data, given the same total number of reads; however, simultaneous discovery of distinct and similar types is better served by lower-depth, higher cell number data. Overall, this study suggests that the depth of profiling should be determined by initial assumptions about the diversity of cells in the population, and that the selection of clustering algorithm(s) is subsequently based on the depth of profiling will allow for better identification of putative transcriptomic cell types.

}, issn = {2041-2657}, doi = {10.1093/bfgp/elx044}, author = {Menon, Vilas} } @article {47894, title = {Adult mouse cortical cell taxonomy revealed by single cell transcriptomics.}, journal = {Nature neuroscience}, volume = {19}, year = {2016}, month = {2016 Feb}, pages = {335-46}, abstract = {

Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. We constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing. We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types. We also analyzed cell type-specific mRNA processing and characterized genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we found that some of our transcriptomic cell types displayed specific and differential electrophysiological and axon projection properties, thereby confirming that the single-cell transcriptomic signatures can be associated with specific cellular properties.

}, keywords = {Animals, Cell Line, Cerebral Cortex, Classification, gamma-Aminobutyric Acid, Gene Library, Genetic Markers, Glutamic Acid, Interneurons, Male, Mice, Mice, Inbred C57BL, Mice, Transgenic, Neurons, RNA, Sequence Analysis, RNA, Transcriptome, Visual Cortex}, issn = {1546-1726}, doi = {10.1038/nn.4216}, author = {Tasic, Bosiljka and Menon, Vilas and Nguyen, Thuc Nghi and Kim, Tae Kyung and Jarsky, Tim and Yao, Zizhen and Levi, Boaz and Gray, Lucas T and Sorensen, Staci A and Dolbeare, Tim and Bertagnolli, Darren and Goldy, Jeff and Shapovalova, Nadiya and Parry, Sheana and Lee, Changkyu and Smith, Kimberly and Bernard, Amy and Madisen, Linda and Sunkin, Susan M and Hawrylycz, Michael and Koch, Christof and Zeng, Hongkui} } @article {47895, title = {Canonical genetic signatures of the adult human brain.}, journal = {Nature neuroscience}, volume = {18}, year = {2015}, month = {2015 Dec}, pages = {1832-44}, abstract = {

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure and function. We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations. Using genes with high differential stability, we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely patterned genes displayed marked shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.

}, keywords = {Adult, Animals, Brain, Gene Regulatory Networks, Humans, Mice, Nerve Net, Transcriptome}, issn = {1546-1726}, doi = {10.1038/nn.4171}, author = {Hawrylycz, Michael and Miller, Jeremy A and Menon, Vilas and Feng, David and Dolbeare, Tim and Guillozet-Bongaarts, Angela L and Jegga, Anil G and Aronow, Bruce J and Lee, Chang-Kyu and Bernard, Amy and Glasser, Matthew F and Dierker, Donna L and Menche, J{\"o}rg and Szafer, Aaron and Collman, Forrest and Grange, Pascal and Berman, Kenneth A and Mihalas, Stefan and Yao, Zizhen and Stewart, Lance and Barab{\'a}si, Albert-L{\'a}szl{\'o} and Schulkin, Jay and Phillips, John and Ng, Lydia and Dang, Chinh and Haynor, David R and Jones, Allan and Van Essen, David C and Koch, Christof and Lein, Ed} } @article {47901, title = {Correlated gene expression and target specificity demonstrate excitatory projection neuron diversity.}, journal = {Cerebral Cortex (New York, N.Y. : 1991)}, volume = {25}, year = {2015}, month = {2015 Feb}, pages = {433-49}, abstract = {

The neocortex contains diverse populations of excitatory neurons segregated by layer and further definable by their specific cortical and subcortical projection targets. The current study describes a systematic approach to identify molecular correlates of specific projection neuron classes in mouse primary somatosensory cortex (S1), using a combination of in situ hybridization (ISH) data mining, marker gene colocalization, and combined retrograde labeling with ISH for layer-specific marker genes. First, we identified a large set of genes with specificity for each cortical layer, and that display heterogeneous patterns within those layers. Using these genes as markers, we find extensive evidence for the covariation of gene expression and projection target specificity in layer 2/3, 5, and 6, with individual genes labeling neurons projecting to specific subsets of target structures. The combination of gene expression and target specificity imply a great diversity of projection neuron classes that is similar to or greater than that of GABAergic interneurons. The covariance of these 2 phenotypic modalities suggests that these classes are both discrete and genetically specified.

}, keywords = {Animals, Atlases as Topic, Data Mining, Gene Expression, In Situ Hybridization, Fluorescence, Male, Mice, Mice, Inbred C57BL, Neural Pathways, Neuronal Tract-Tracers, Neurons, Somatosensory Cortex}, issn = {1460-2199}, doi = {10.1093/cercor/bht243}, author = {Sorensen, Staci A and Bernard, Amy and Menon, Vilas and Royall, Joshua J and Glattfelder, Katie J and Desta, Tsega and Hirokawa, Karla and Mortrud, Marty and Miller, Jeremy A and Zeng, Hongkui and Hohmann, John G and Jones, Allan R and Lein, Ed S} } @article {47896, title = {Genome engineering of isogenic human ES cells to model autism disorders.}, journal = {Nucleic acids research}, volume = {43}, year = {2015}, month = {2015 May 26}, pages = {e65}, abstract = {

Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity.

}, keywords = {Autistic Disorder, Binding Sites, Cell Engineering, Cell Line, Child Development Disorders, Pervasive, Deoxyribonucleases, Embryonic Stem Cells, Gene Targeting, Genome, Human, Humans, Long QT Syndrome, Models, Genetic, Recombinational DNA Repair, Software, Syndactyly}, issn = {1362-4962}, doi = {10.1093/nar/gkv164}, author = {Martinez, Refugio A and Stein, Jason L and Krostag, Anne-Rachel F and Nelson, Angelique M and Marken, John S and Menon, Vilas and May, Ryan C and Yao, Zizhen and Kaykas, Ajamete and Geschwind, Daniel H and Grimley, Joshua S} } @article {47897, title = {A high-resolution spatiotemporal atlas of gene expression of the developing mouse brain.}, journal = {Neuron}, volume = {83}, year = {2014}, month = {2014 Jul 16}, pages = {309-23}, abstract = {

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for \~{}2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (http://developingmouse.brain-map.org).

}, keywords = {Animals, Brain, Brain Mapping, Gene Expression, Gene Expression Profiling, Gene Expression Regulation, Developmental, Mice}, issn = {1097-4199}, doi = {10.1016/j.neuron.2014.05.033}, author = {Thompson, Carol L and Ng, Lydia and Menon, Vilas and Martinez, Salvador and Lee, Chang-Kyu and Glattfelder, Katie and Sunkin, Susan M and Henry, Alex and Lau, Christopher and Dang, Chinh and Garcia-Lopez, Raquel and Martinez-Ferre, Almudena and Pombero, Ana and Rubenstein, John L R and Wakeman, Wayne B and Hohmann, John and Dee, Nick and Sodt, Andrew J and Young, Rob and Smith, Kimberly and Nguyen, Thuc-Nghi and Kidney, Jolene and Kuan, Leonard and Jeromin, Andreas and Kaykas, Ajamete and Miller, Jeremy and Page, Damon and Orta, Geri and Bernard, Amy and Riley, Zackery and Smith, Simon and Wohnoutka, Paul and Hawrylycz, Michael J and Puelles, Luis and Jones, Allan R} } @article {47898, title = {Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.}, journal = {BMC genomics}, volume = {15}, year = {2014}, month = {2014}, pages = {154}, abstract = {

BACKGROUND: High-throughput sequencing is gradually replacing microarrays as the preferred method for studying mRNA expression levels, providing nucleotide resolution and accurately measuring absolute expression levels of almost any transcript, known or novel. However, existing microarray data from clinical, pharmaceutical, and academic settings represent valuable and often underappreciated resources, and methods for assessing and improving the quality of these data are lacking.

RESULTS: To quantitatively assess the quality of microarray probes, we directly compare RNA-Seq to Agilent microarrays by processing 231 unique samples from the Allen Human Brain Atlas using RNA-Seq. Both techniques provide highly consistent, highly reproducible gene expression measurements in adult human brain, with RNA-Seq slightly outperforming microarray results overall. We show that RNA-Seq can be used as ground truth to assess the reliability of most microarray probes, remove probes with off-target effects, and scale probe intensities to match the expression levels identified by RNA-Seq. These sequencing scaled microarray intensities (SSMIs) provide more reliable, quantitative estimates of absolute expression levels for many genes when compared with unscaled intensities. Finally, we validate this result in two human cell lines, showing that linear scaling factors can be applied across experiments using the same microarray platform.

CONCLUSIONS: Microarrays provide consistent, reproducible gene expression measurements, which are improved using RNA-Seq as ground truth. We expect that our strategy could be used to improve probe quality for many data sets from major existing repositories.

}, keywords = {Brain, Cluster Analysis, Computational Biology, Gene Expression, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Humans, Neocortex, Oligonucleotide Array Sequence Analysis, Reproducibility of Results, Sequence Analysis, RNA, Transcriptome}, issn = {1471-2164}, doi = {10.1186/1471-2164-15-154}, author = {Miller, Jeremy A and Menon, Vilas and Goldy, Jeff and Kaykas, Ajamete and Lee, Chang-Kyu and Smith, Kimberly A and Shen, Elaine H and Phillips, John W and Lein, Ed S and Hawrylycz, Mike J} } @article {6715, title = {Balanced synaptic impact via distance-dependent synapse distribution and complementary expression of AMPARs and NMDARs in hippocampal dendrites.}, journal = {Neuron}, volume = {80}, year = {2013}, month = {2013 Dec 18}, pages = {1451-63}, abstract = {

Neuronal computation involves the integration of synaptic inputs that are often distributed over expansive dendritic trees, suggesting the need for compensatory mechanisms that enable spatially disparate synapses to influence neuronal output. In hippocampal CA1 pyramidal neurons, such mechanisms have indeed been reported, which normalize either the ability of distributed synapses to drive action potential initiation in the axon or their ability to drive dendritic spiking locally. Here we report that these mechanisms can coexist, through an elegant combination of distance-dependent regulation of synapse number and synaptic expression of AMPA and NMDA receptors. Together, these complementary gradients allow individual dendrites in both the apical and basal dendritic trees of hippocampal neurons to operate as facile computational subunits capable of supporting both global integration in the soma/axon and local integration in the dendrite.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2013.09.027}, author = {Menon, Vilas and Musial, Timothy F and Liu, Annie and Katz, Yael and Kath, William L and Spruston, Nelson and Nicholson, Daniel A} } @article {47900, title = {Dynamic Bayesian clustering.}, journal = {Journal of bioinformatics and computational biology}, volume = {11}, year = {2013}, month = {2013 Oct}, pages = {1342001}, abstract = {

Clusters of time series data may change location and memberships over time; in gene expression data, this occurs as groups of genes or samples respond differently to stimuli or experimental conditions at different times. In order to uncover this underlying temporal structure, we consider dynamic clusters with time-dependent parameters which split and merge over time, enabling cluster memberships to change. These interesting time-dependent structures are useful in understanding the development of organisms or complex organs, and could not be identified using traditional clustering methods. In cell cycle data, these time-dependent structure may provide links between genes and stages of the cell cycle, whilst in developmental data sets they may highlight key developmental transitions.

}, keywords = {Algorithms, Animals, Bayes Theorem, Brain, Cell Cycle, Cluster Analysis, Computational Biology, Databases, Genetic, Gene Expression Regulation, Developmental, Markov Chains, Mice, Models, Statistical, Monte Carlo Method}, issn = {1757-6334}, doi = {10.1142/S0219720013420018}, author = {Fowler, Anna and Menon, Vilas and Heard, Nicholas A} } @article {47899, title = {The influence of synaptic weight distribution on neuronal population dynamics.}, journal = {PLoS computational biology}, volume = {9}, year = {2013}, month = {2013 Oct}, pages = {e1003248}, abstract = {

The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations.

}, keywords = {Action Potentials, Computer Simulation, Models, Neurological, Neurons, Synapses}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1003248}, author = {Iyer, Ramakrishnan and Menon, Vilas and Buice, Michael and Koch, Christof and Mihalas, Stefan} } @article {47902, title = {Modeling proteins using a super-secondary structure library and NMR chemical shift information.}, journal = {Structure (London, England : 1993)}, volume = {21}, year = {2013}, month = {2013 Jun 4}, pages = {891-9}, abstract = {

A remaining challenge in protein modeling is to predict structures for sequences with no sequence similarity to any experimentally solved structure. Based on earlier observations, the library of protein backbone supersecondary structure motifs (Smotifs) saturated about a decade ago. Therefore, it should be possible to build any structure from a combination of existing Smotifs with the help of limited experimental data that are sufficient to relate the backbone conformations of Smotifs between target proteins and known structures. Here, we present a hybrid modeling algorithm that relies on an exhaustive Smotif library and on nuclear magnetic resonance chemical shift patterns without any input of primary sequence information. In a test of 102 proteins, the algorithm delivered 90 homology-model-quality models, among them 24 high-quality ones, and a topologically correct solution for almost all cases. The current approach opens a venue to address the modeling of larger protein structures for which chemical shifts are available.

}, keywords = {Algorithms, Models, Molecular, Nuclear Magnetic Resonance, Biomolecular, Protein Structure, Secondary, Proteins}, issn = {1878-4186}, doi = {10.1016/j.str.2013.04.012}, author = {Menon, Vilas and Vallat, Brinda K and Dybas, Joseph M and Fiser, Andras} } @article {47903, title = {Frozen tissue can provide reproducible proteomic results of subcellular fractionation.}, journal = {Analytical biochemistry}, volume = {418}, year = {2011}, month = {2011 Nov 1}, pages = {78-84}, abstract = {

Differential detergent fractionation (DDF) is frequently used to partition fresh cells and tissues into distinct compartments. We have tested whether DDF can reproducibly extract and fractionate cellular protein components from frozen tissues. Frozen kidneys were sequentially extracted with three different buffer systems. Analysis of the three fractions with liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified 1693 proteins, some of which were common to all fractions and others of which were unique to specific fractions. Normalized spectral index (SI(N)) values obtained from these data were compared to evaluate both the reproducibility of the method and the efficiency of enrichment. SI(N) values between replicate fractions demonstrated a high correlation, confirming the reproducibility of the method. Correlation coefficients across the three fractions were significantly lower than those for the replicates, supporting the capability of DDF to differentially fractionate proteins into separate compartments. Subcellular annotation of the proteins identified in each fraction demonstrated a significant enrichment of cytoplasmic, cell membrane, and nuclear proteins in the three respective buffer system fractions. We conclude that DDF can be applied to frozen tissue to generate reproducible proteome coverage discriminating subcellular compartments. This demonstrates the feasibility of analyzing cellular compartment-specific proteins in archived tissue samples with the simple DDF method.

}, keywords = {Animals, Cell Fractionation, Detergents, Freezing, Frozen Sections, Mice, Mice, Inbred C57BL, Proteome, Proteomics, Subcellular Fractions, Tandem Mass Spectrometry}, issn = {1096-0309}, doi = {10.1016/j.ab.2011.06.045}, author = {Lim, Jihyeon and Menon, Vilas and Bitzer, Markus and Miller, Leah M and Madrid-Aliste, Carlos and Weiss, Louis M and Fiser, Andras and Angeletti, Ruth H} } @article {47905, title = {Hallmarks of molecular action of microtubule stabilizing agents: effects of epothilone B, ixabepilone, peloruside A, and laulimalide on microtubule conformation.}, journal = {The Journal of biological chemistry}, volume = {286}, year = {2011}, month = {2011 Apr 1}, pages = {11765-78}, abstract = {

Microtubule stabilizing agents (MSAs) comprise a class of drugs that bind to microtubule (MT) polymers and stabilize them against disassembly. Several of these agents are currently in clinical use as anticancer drugs, whereas others are in various stages of development. Nonetheless, there is insufficient knowledge about the molecular modes of their action. Recent studies from our laboratory utilizing hydrogen-deuterium exchange in combination with mass spectrometry (MS) provide new information on the conformational effects of Taxol and discodermolide on microtubules isolated from chicken erythrocytes (CET). We report here a comprehensive analysis of the effects of epothilone B, ixabepilone (IXEMPRA(TM)), laulimalide, and peloruside A on CET conformation. The results of our comparative hydrogen-deuterium exchange MS studies indicate that all MSAs have significant conformational effects on the C-terminal H12 helix of α-tubulin, which is a likely molecular mechanism for the previously observed modulations of MT interactions with microtubule-associated and motor proteins. More importantly, the major mode of MT stabilization by MSAs is the tightening of the longitudinal interactions between two adjacent αβ-tubulin heterodimers at the interdimer interface. In contrast to previous observations reported with bovine brain tubulin, the lateral interactions between the adjacent protofilaments in CET are particularly strongly stabilized by peloruside A and laulimalide, drugs that bind outside the taxane site. This not only highlights the significance of tubulin isotype composition in modulating drug effects on MT conformation and stability but also provides a potential explanation for the synergy observed when combinations of taxane and alternative site binding drugs are used.

}, keywords = {Animals, Bicyclo Compounds, Heterocyclic, Binding Sites, Brain, Brain Chemistry, Cattle, Epothilones, Lactones, Macrolides, Mass Spectrometry, Microtubules, Nerve Tissue Proteins, Protein Structure, Secondary, Tubulin, Tubulin Modulators}, issn = {1083-351X}, doi = {10.1074/jbc.M110.162214}, author = {Khrapunovich-Baine, Marina and Menon, Vilas and Yang, Chia-Ping Huang and Northcote, Peter T and Miller, John H and Angeletti, Ruth Hogue and Fiser, Andras and Horwitz, Susan Band and Xiao, Hui} } @article {47904, title = {Multi-scale correlation structure of gene expression in the brain.}, journal = {Neural networks : the official journal of the International Neural Network Society}, volume = {24}, year = {2011}, month = {2011 Nov}, pages = {933-42}, abstract = {

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.

}, keywords = {Algorithms, Animals, Atlases as Topic, Brain, Brain Chemistry, Data Mining, Databases, Genetic, Gene Expression, Mice, Mice, Inbred C57BL, Nerve Tissue Proteins, Tryptophan Hydroxylase}, issn = {1879-2782}, doi = {10.1016/j.neunet.2011.06.012}, author = {Hawrylycz, Mike and Ng, Lydia and Page, Damon and Morris, John and Lau, Chris and Faber, Sky and Faber, Vance and Sunkin, Susan and Menon, Vilas and Lein, Ed and Jones, Allan} } @article {47906, title = {Distinct pose of discodermolide in taxol binding pocket drives a complementary mode of microtubule stabilization.}, journal = {Biochemistry}, volume = {48}, year = {2009}, month = {2009 Dec 15}, pages = {11664-77}, abstract = {

The microtubule cytoskeleton has proven to be an effective target for cancer therapeutics. One class of drugs, known as microtubule stabilizing agents (MSAs), binds to microtubule polymers and stabilizes them against depolymerization. The prototype of this group of drugs, Taxol, is an effective chemotherapeutic agent used extensively in the treatment of human ovarian, breast, and lung carcinomas. Although electron crystallography and photoaffinity labeling experiments determined that the binding site for Taxol is in a hydrophobic pocket in beta-tubulin, little was known about the effects of this drug on the conformation of the entire microtubule. A recent study from our laboratory utilizing hydrogen-deuterium exchange (HDX) in concert with various mass spectrometry (MS) techniques has provided new information on the structure of microtubules upon Taxol binding. In the current study we apply this technique to determine the binding mode and the conformational effects on chicken erythrocyte tubulin (CET) of another MSA, discodermolide, whose synthetic analogues may have potential use in the clinic. We confirmed that, like Taxol, discodermolide binds to the taxane binding pocket in beta-tubulin. However, as opposed to Taxol, which has major interactions with the M-loop, discodermolide orients itself away from this loop and toward the N-terminal H1-S2 loop. Additionally, discodermolide stabilizes microtubules mainly via its effects on interdimer contacts, specifically on the alpha-tubulin side, and to a lesser extent on interprotofilament contacts between adjacent beta-tubulin subunits. Also, our results indicate complementary stabilizing effects of Taxol and discodermolide on the microtubules, which may explain the synergy observed between the two drugs in vivo.

}, keywords = {Alkanes, Animals, Binding Sites, Carbamates, Cattle, Chickens, Deuterium Exchange Measurement, Dimerization, Drug Synergism, Lactones, Microtubules, Paclitaxel, Peptide Fragments, Protein Binding, Protein Isoforms, Protein Stability, Pyrones, Tubulin, Tubulin Modulators}, issn = {1520-4995}, doi = {10.1021/bi901351q}, author = {Khrapunovich-Baine, Marina and Menon, Vilas and Verdier-Pinard, Pascal and Smith, Amos B and Angeletti, Ruth Hogue and Fiser, Andras and Horwitz, Susan Band and Xiao, Hui} } @article {6783, title = {A state-mutating genetic algorithm to design ion-channel models.}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {106}, year = {2009}, month = {2009 Sep 29}, pages = {16829-34}, abstract = {

Realistic computational models of single neurons require component ion channels that reproduce experimental findings. Here, a topology-mutating genetic algorithm that searches for the best state diagram and transition-rate parameters to model macroscopic ion-channel behavior is described. Important features of the algorithm include a topology-altering strategy, automatic satisfaction of equilibrium constraints (microscopic reversibility), and multiple-protocol fitting using sequential goal programming rather than explicit weighting. Application of this genetic algorithm to design a sodium-channel model exhibiting both fast and prolonged inactivation yields a six-state model that produces realistic activity-dependent attenuation of action-potential backpropagation in current-clamp simulations of a CA1 pyramidal neuron.

}, keywords = {Algorithms, Cell Membrane, Ion Channels, Models, Mutation, Neurons, Sodium Channels, Theoretical}, issn = {1091-6490}, doi = {10.1073/pnas.0903766106}, author = {Menon, Vilas and Spruston, Nelson and Kath, William L} } @article {6784, title = {Synapse distribution suggests a two-stage model of dendritic integration in CA1 pyramidal neurons.}, journal = {Neuron}, volume = {63}, year = {2009}, month = {2009 Jul 30}, pages = {171-7}, abstract = {

Competing models have been proposed to explain how neurons integrate the thousands of inputs distributed throughout their dendritic trees. In a simple global integration model, inputs from all locations sum in the axon. In a two-stage integration model, inputs contribute directly to dendritic spikes, and outputs from multiple branches sum in the axon. These two models yield opposite predictions of how synapses at different dendritic locations should be scaled if they are to contribute equally to neuronal output. We used serial-section electron microscopy to reconstruct individual apical oblique dendritic branches of CA1 pyramidal neurons and observe a synapse distribution consistent with the two-stage integration model. Computational modeling suggests that the observed synapse distribution enhances the contribution of each dendritic branch to neuronal output.

}, keywords = {Animals, Dendrites, Electron, Hippocampus, Humans, Microscopy, Models, Neural Networks (Computer), Neural Pathways, Neurological, Neurons, Synapses}, issn = {1097-4199}, doi = {10.1016/j.neuron.2009.06.023}, author = {Katz, Yael and Menon, Vilas and Nicholson, Daniel A and Geinisman, Yuri and Kath, William L and Spruston, Nelson} }