scholarly journals Machine learning analysis identifies Drosophila Grunge/Atrophin as an important learning and memory gene required for memory retention and social learning

2017 ◽  
Author(s):  
Balint Z Kacsoh ◽  
Casey S. Greene ◽  
Giovanni Bosco
Keyword(s):  
Machine Learning ◽  
Learning And Memory ◽  
High Throughput ◽  
Mushroom Body ◽  
Neuronal Development ◽  
Active Role ◽  
Long Term Memory ◽  
Memory Retention ◽  
Genome Wide Data ◽  
High Throughput Experiments

ABSTRACTHigh throughput experiments are becoming increasingly common, and scientists must balance hypothesis driven experiments with genome wide data acquisition. We sought to predict novel genes involved in Drosophila learning and long-term memory from existing public high-throughput data. We performed an analysis using PILGRM, which analyzes public gene expression compendia using machine learning. We evaluated the top prediction alongside genes involved in learning and memory in IMP, an interface for functional relationship networks. We identified Grunge/Atrophin (Gug/Atro), a transcriptional repressor, histone deacetylase, as our top candidate. We find, through multiple, distinct assays, that Gug has an active role as a modulator of memory retention in the fly and its function is required in the adult mushroom body. Depletion of Gug specifically in neurons of the adult mushroom body, after cell division and neuronal development is complete, suggests that Gug function is important for memory retention through regulation of neuronal activity, and not by altering neurodevelopment. Our study provides a previously uncharacterized role for Gug as a possible regulator of neuronal plasticity at the interface of memory retention and memory extinction.

Molecular mechanism linking BDNF/TrkB signaling with the NMDA receptor in memory: the role of Girdin in the CNS

2016 ◽  
Vol 27 (5) ◽  
pp. 481-490 ◽  
Author(s):  
Norimichi Itoh ◽  
Atsushi Enomoto ◽  
Taku Nagai ◽  
Masahide Takahashi ◽  
Kiyofumi Yamada
Keyword(s):  
Synaptic Plasticity ◽  
Nmda Receptor ◽  
Learning And Memory ◽  
Molecular Mechanism ◽  
Neuronal Migration ◽  
Neuronal Development ◽  
Long Term Potentiation ◽  
Long Term Memory ◽  
Tropomyosin Related Kinase B

AbstractIt is well known that synaptic plasticity is the cellular mechanism underlying learning and memory. Activity-dependent synaptic changes in electrical properties and morphology, including synaptogenesis, lead to alterations of synaptic strength, which is associated with long-term potentiation (LTP). Brain-derived neurotrophic factor (BDNF)/tropomyosin-related kinase B (TrkB) signaling is involved in learning and memory formation by regulating synaptic plasticity. The phosphatidylinositol 3-kinase (PI3-K)/Akt pathway is one of the key signaling cascades downstream BDNF/TrkB and is believed to modulate N-methyl-d-aspartate (NMDA) receptor-mediated synaptic plasticity. However, the molecular mechanism underlying the connection between these two key players in synaptic plasticity remains largely unknown. Girders of actin filament (Girdin), an Akt substrate that directly binds to actin filaments, has been shown to play a role in neuronal migration and neuronal development. Recently, we identified Girdin as a key molecule involved in regulating long-term memory. It was demonstrated that phosphorylation of Girdin by Akt contributed to the maintenance of LTP by linking the BDNF/TrkB signaling pathway with NMDA receptor activity. These findings indicate that Girdin plays a pivotal role in a variety of processes in the CNS. Here, we review recent advances in our understanding about the roles of Girdin in the CNS and focus particularly on neuronal migration and memory.

scholarly journals On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Aaron Gilad Kusne ◽  
Tieren Gao ◽  
Apurva Mehta ◽  
Liqin Ke ◽  
Manh Cuong Nguyen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Rare Earth ◽  
High Throughput ◽  
Permanent Magnets ◽  
High Throughput Experiments

scholarly journals COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning

2020 ◽  
Author(s):  
◽  
Hagit Achdout ◽  
Anthony Aimon ◽  
Elad Bar-David ◽  
Haim Barr ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Throughput ◽  
Open Science ◽  
Viral Inhibition ◽  
Enzymatic Assays ◽  
Main Protease ◽  
Covalent Inhibitors ◽  
Ic50 Values ◽  
High Throughput Experiments ◽  
High Throughput Crystallography

AbstractHerein we provide a living summary of the data generated during the COVID Moonshot project focused on the development of SARS-CoV-2 main protease (Mpro) inhibitors. Our approach uniquely combines crowdsourced medicinal chemistry insights with high throughput crystallography, exascale computational chemistry infrastructure for simulations, and machine learning in triaging designs and predicting synthetic routes. This manuscript describes our methodologies leading to both covalent and non-covalent inhibitors displaying protease IC50 values under 150 nM and viral inhibition under 5 uM in multiple different viral replication assays. Furthermore, we provide over 200 crystal structures of fragment-like and lead-like molecules in complex with the main protease. Over 1000 synthesized and ordered compounds are also reported with the corresponding activity in Mpro enzymatic assays using two different experimental setups. The data referenced in this document will be continually updated to reflect the current experimental progress of the COVID Moonshot project, and serves as a citable reference for ensuing publications. All of the generated data is open to other researchers who may find it of use.

scholarly journals Increased abundance of nuclear HDAC4 impairs neuronal development and long-term memory

2021 ◽  
Author(s):  
Patrick Main ◽  
Wei Jun Tan ◽  
David Wheeler ◽  
Helen L Fitzsimons
Keyword(s):  
Subcellular Distribution ◽  
Mushroom Body ◽  
Neuronal Development ◽  
Eye Development ◽  
Critical Role ◽  
Long Term Memory ◽  
Term Memory ◽  
Neuronal Nuclei ◽  
Transcriptional Changes

AbstractDysregulation of the histone deacetylase HDAC4 is associated with both neurodevelopmental and neurodegenerative disorders, and a feature common to many of these disorders is impaired cognitive function. HDAC4 shuttles between the nucleus and cytoplasm in both vertebrates and invertebrates and alterations in the amounts of nuclear and/or cytoplasmic HDAC4 have been implicated in these diseases. In Drosophila, HDAC4 also plays a critical role in the regulation of memory however the mechanisms through which it acts are unknown. Nuclear and cytoplasmically-restricted HDAC4 mutants were expressed in the Drosophila brain to investigate a mechanistic link between HDAC4 subcellular distribution, transcriptional changes and neuronal dysfunction. Deficits in mushroom body morphogenesis, eye development and long-term memory correlated with increased abundance of nuclear HDAC4 but were associated with minimal transcriptional changes. Although HDAC4 sequesters MEF2 into punctate foci within neuronal nuclei, no alteration in MEF2 activity was observed on overexpression of HDAC4, and knockdown of MEF2 had no impact on long-term memory, indicating that HDAC4 is likely not acting through MEF2. Similarly, deletion of the MEF2 binding site also had no impact on HDAC4-induced impairments in eye development, however it did significantly reduce the mushroom body deficits, thus nuclear HDAC4 acts through MEF2 to disrupt mushroom body development. These data provide insight into the mechanisms through which dysregulation of HDAC4 subcellular distribution impairs neurological function and provides new avenues for further investigation.

scholarly journals Dendritic signal integration in a Drosophila Mushroom Body Output Neuron (MBON) essential for learning and memory

2020 ◽  
Author(s):  
Omar A. Hafez ◽  
Benjamin Escribano ◽  
Rouven L. Ziegler ◽  
Jan J. Hirtz ◽  
Ernst Niebur ◽  
...  
Keyword(s):  
Learning And Memory ◽  
Mushroom Body ◽  
Dendritic Tree ◽  
Memory Formation ◽  
Membrane Properties ◽  
Long Term Memory ◽  
Patch Clamp Recording ◽  
Electron Microscopic ◽  
Efficient Manner

AbstractThe ability to associate neutral stimuli with either positive or negative valence forms the basis for most forms of decision making. Long-term memory formation then enables manifestation of these associations to guide behavioral responses over prolonged periods of time. Despite recent advances in the understanding of the neuronal circuits and cellular mechanisms controlling memory formation, the computational principles at the level of individual information processing modules remain largely unknown. Here we use the Drosophila mushroom body (MB), the learning and memory center of the fly, as a model system to elucidate the cellular basis of memory computation. Recent studies resolved the precise synaptic connectome of the MB and identified the synaptic connections between Kenyon cells (KCs) and mushroom body output neurons (MBONs) as the sites of sensory association. We build a realistic computational model of the MBON-α3 neuron including precise synaptic connectivity to the 948 upstream KCs innervating the αβ MB lobes. To model membrane properties reflecting in vivo parameters we performed patch-clamp recording of MBON-α3. Based on the in vivo data we model synaptic input of individual cholinergic KC-MBON synapses by local conductance changes at the dendritic sections defined by the electron microscopic reconstruction. Modelling of activation of all individual synapses confirms prior results demonstrating that MBON-α3 is electrotonically compact. As a likely consequence of this compactness, activation pattern of individual KCs with identical numbers of synaptic connection but innervating different sections of the MBON-α3 dendritic tree result in highly similar depolarization voltages. Furthermore, we show that KC input patterns reflecting physiological activation by individual odors in vivo are sufficient to robustly drive MBON spiking. Our data suggest that the sparse innervation by KCs can control or modulate MBON activity in an efficient manner, with minimal requirements on the specificity of synaptic localization. This KC-MBON architecture therefore provides a suitable module to incorporate different olfactory associative memories based on stochastically encoded odor-specificity of KCs.

scholarly journals Characterization of the olfactory system in Apis dorsata, an Asian honey bee

2018 ◽  
Author(s):  
Sandhya Mogily ◽  
Meenakshi VijayKumar ◽  
Sunil Kumar Sethy ◽  
Joby Joseph
Keyword(s):  
Apis Mellifera ◽  
Learning And Memory ◽  
Honey Bee ◽  
Olfactory System ◽  
Mushroom Body ◽  
Antennal Lobe ◽  
Equivalent Model ◽  
Memory Retention ◽  
Apis Dorsata ◽  
Lateral Protocerebrum

AbstractThe European honeybee, Apis mellifera is the most common insect model system for studying learning and memory. We establish that the olfactory system of Apis dorsata, an Asian species of honeybee as an equivalent model to Apis mellifera to study physiology underlying learning and memory. We created an Atlas of the antennal lobe and counted the number of glomeruli in the antennal lobe of Apis dorsata to be around 165 which is similar to the number in the other honey bee species Apis mellifera and Apis florea. Apis dorsata was found to have five antenno-cerebral tracts namely mACT, lACT and 3 mlACTS which appear identical to Apis mellifera. Intracellular recording showed that the antennal lobe interneurons exhibit temporally patterned odor-cell specific responses. The neuritis of Kenyon cells with cell bodies located in a neighborhood in calyx retain their relative neighborhoods in the peduncle and alpha lobe forming a columnar organization in the mushroom body. Alpha lobe and the calyx of the mushroom body were innervated by extrinsic neurons with cell bodies in the lateral protocerebrum. A set of GABA positive cells in the lateral protocerebrum send their neurites towards alpha-lobe. Apis dorsata was amenable to olfactory conditioning and showed good learning and memory retention at 24 hours. They were amenable to massed and spaced conditioning and could distinguish trained odor from an untrained novel odor.

scholarly journals COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning

2020 ◽  
Author(s):  
The COVID Moonshot Consortium ◽  
John Chodera ◽  
Alpha Lee ◽  
Nir London ◽  
Frank von Delft
Keyword(s):  
Machine Learning ◽  
High Throughput ◽  
Open Science ◽  
Viral Inhibition ◽  
Enzymatic Assays ◽  
Main Protease ◽  
Covalent Inhibitors ◽  
Ic50 Values ◽  
High Throughput Experiments ◽  
High Throughput Crystallography

<div><div><div><p>Herein we provide a living summary of the data generated during the COVID Moonshot project focused on the development of SARS-CoV-2 main protease (Mpro) inhibitors. Our approach uniquely combines crowdsourced medicinal chemistry insights with high throughput crystallography, exascale computational chemistry infrastructure for simulations, and machine learning in triaging designs and predicting synthetic routes. This manuscript describes our methodologies leading to both covalent and non-covalent inhibitors displaying protease IC50 values under 150 nM and viral inhibition under 5 uM in multiple different viral replication assays. Furthermore, we provide over 200 crystal structures of fragment-like and lead-like molecules in complex with the main protease. Over 1000 synthesized and ordered compounds are also reported with the corresponding activity in Mpro enzymatic assays using two different experimental setups. The data referenced in this document will be continually updated to reflect the current experimental progress of the COVID Moonshot project, and serves as a citable reference for ensuing publications. All of the generated data is open to other researchers who may find it of use.<br></p></div></div></div>

scholarly journals Drosophila Graf regulates mushroom body β-axon extension and olfactory long-term memory

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Sungdae Kim ◽  
Joohyung Kim ◽  
Sunyoung Park ◽  
Joong-Jean Park ◽  
Seungbok Lee
Keyword(s):  
Mushroom Body ◽  
Neuronal Development ◽  
Growth Factor Receptor ◽  
Mapk Signaling ◽  
Mitogen Activated Protein Kinase ◽  
Long Term Memory ◽  
Loss Of Function ◽  
Specific Expression ◽  
Term Memory

AbstractLoss-of-function mutations in the humanoligophrenin-1(OPHN1) gene cause intellectual disability, a prevailing neurodevelopmental condition. However, the role OPHN1 plays during neuronal development is not well understood. We investigated the role of theDrosophilaOPHN1 ortholog Graf in the development of the mushroom body (MB), a key brain structure for learning and memory in insects. We show that loss of Graf causes abnormal crossing of the MB β lobe over the brain midline during metamorphosis. This defect inGrafmutants is rescued by MB-specific expression of Graf and OPHN1. Furthermore, MB α/β neuron-specific RNA interference experiments and mosaic analyses indicate that Graf acts via a cell-autonomous mechanism. Consistent with the negative regulation of epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) signaling by Graf, activation of this pathway is required for the β-lobe midline-crossing phenotype ofGrafmutants. Finally,Grafmutants have impaired olfactory long-term memory. Our findings reveal a role for Graf in MB axon development and suggest potential neurodevelopmental functions of human OPHN1.

scholarly journals Distinct dopamine neurons mediate reward signals for short- and long-term memories

2014 ◽  
Vol 112 (2) ◽  
pp. 578-583 ◽  
Author(s):  
Nobuhiro Yamagata ◽  
Toshiharu Ichinose ◽  
Yoshinori Aso ◽  
Pierre-Yves Plaçais ◽  
Anja B. Friedrich ◽  
...  
Keyword(s):  
Mushroom Body ◽  
Training Session ◽  
Dopamine Neurons ◽  
Single Type ◽  
Long Term Memory ◽  
Memory Retention ◽  
Term Memory ◽  
Neuronal Mechanisms ◽  
Short And Long Term

Drosophila melanogaster can acquire a stable appetitive olfactory memory when the presentation of a sugar reward and an odor are paired. However, the neuronal mechanisms by which a single training induces long-term memory are poorly understood. Here we show that two distinct subsets of dopamine neurons in the fly brain signal reward for short-term (STM) and long-term memories (LTM). One subset induces memory that decays within several hours, whereas the other induces memory that gradually develops after training. They convey reward signals to spatially segregated synaptic domains of the mushroom body (MB), a potential site for convergence. Furthermore, we identified a single type of dopamine neuron that conveys the reward signal to restricted subdomains of the mushroom body lobes and induces long-term memory. Constant appetitive memory retention after a single training session thus comprises two memory components triggered by distinct dopamine neurons.

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