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Pribbenow C, Owald D. Skewing information flow through pre- and postsynaptic plasticity in the mushroom bodies of Drosophila. Learn Mem 2024; 31:a053919. [PMID: 38876487 PMCID: PMC11199954 DOI: 10.1101/lm.053919.124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/26/2024] [Indexed: 06/16/2024]
Abstract
Animal brains need to store information to construct a representation of their environment. Knowledge of what happened in the past allows both vertebrates and invertebrates to predict future outcomes by recalling previous experience. Although invertebrate and vertebrate brains share common principles at the molecular, cellular, and circuit-architectural levels, there are also obvious differences as exemplified by the use of acetylcholine versus glutamate as the considered main excitatory neurotransmitters in the respective central nervous systems. Nonetheless, across central nervous systems, synaptic plasticity is thought to be a main substrate for memory storage. Therefore, how brain circuits and synaptic contacts change following learning is of fundamental interest for understanding brain computations tied to behavior in any animal. Recent progress has been made in understanding such plastic changes following olfactory associative learning in the mushroom bodies (MBs) of Drosophila A current framework of memory-guided behavioral selection is based on the MB skew model, in which antagonistic synaptic pathways are selectively changed in strength. Here, we review insights into plasticity at dedicated Drosophila MB output pathways and update what is known about the plasticity of both pre- and postsynaptic compartments of Drosophila MB neurons.
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Affiliation(s)
- Carlotta Pribbenow
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - David Owald
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Einstein Center for Neurosciences Berlin, 10117 Berlin, Germany
- NeuroCure, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
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2
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Parnas M, Manoim JE, Lin AC. Sensory encoding and memory in the mushroom body: signals, noise, and variability. Learn Mem 2024; 31:a053825. [PMID: 38862174 PMCID: PMC11199953 DOI: 10.1101/lm.053825.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 11/21/2023] [Indexed: 06/13/2024]
Abstract
To survive in changing environments, animals need to learn to associate specific sensory stimuli with positive or negative valence. How do they form stimulus-specific memories to distinguish between positively/negatively associated stimuli and other irrelevant stimuli? Solving this task is one of the functions of the mushroom body, the associative memory center in insect brains. Here we summarize recent work on sensory encoding and memory in the Drosophila mushroom body, highlighting general principles such as pattern separation, sparse coding, noise and variability, coincidence detection, and spatially localized neuromodulation, and placing the mushroom body in comparative perspective with mammalian memory systems.
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Affiliation(s)
- Moshe Parnas
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
| | - Julia E Manoim
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Andrew C Lin
- School of Biosciences, University of Sheffield, Sheffield S10 2TN, United Kingdom
- Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, United Kingdom
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3
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Takagi S, Sancer G, Abuin L, Stupski SD, Arguello JR, Prieto-Godino LL, Stern DL, Cruchet S, Alvarez-Ocana R, Wienecke CFR, van Breugel F, Jeanne JM, Auer TO, Benton R. Sensory neuron population expansion enhances odor tracking without sensitizing projection neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.15.556782. [PMID: 37745467 PMCID: PMC10515935 DOI: 10.1101/2023.09.15.556782] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The evolutionary expansion of sensory neuron populations detecting important environmental cues is widespread, but functionally enigmatic. We investigated this phenomenon through comparison of homologous neural pathways of Drosophila melanogaster and its close relative Drosophila sechellia , an extreme specialist for Morinda citrifolia noni fruit. D. sechellia has evolved species-specific expansions in select, noni-detecting olfactory sensory neuron (OSN) populations, through multigenic changes. Activation and inhibition of defined proportions of neurons demonstrate that OSN population increases contribute to stronger, more persistent, noni-odor tracking behavior. These sensory neuron expansions result in increased synaptic connections with their projection neuron (PN) partners, which are conserved in number between species. Surprisingly, having more OSNs does not lead to greater odor-evoked PN sensitivity or reliability. Rather, pathways with increased sensory pooling exhibit reduced PN adaptation, likely through weakened lateral inhibition. Our work reveals an unexpected functional impact of sensory neuron expansions to explain ecologically-relevant, species-specific behavior.
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4
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Zhu L, Mangan M, Webb B. Neuromorphic sequence learning with an event camera on routes through vegetation. Sci Robot 2023; 8:eadg3679. [PMID: 37756384 DOI: 10.1126/scirobotics.adg3679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 08/29/2023] [Indexed: 09/29/2023]
Abstract
For many robotics applications, it is desirable to have relatively low-power and efficient onboard solutions. We took inspiration from insects, such as ants, that are capable of learning and following routes in complex natural environments using relatively constrained sensory and neural systems. Such capabilities are particularly relevant to applications such as agricultural robotics, where visual navigation through dense vegetation remains a challenging task. In this scenario, a route is likely to have high self-similarity and be subject to changing lighting conditions and motion over uneven terrain, and the effects of wind on leaves increase the variability of the input. We used a bioinspired event camera on a terrestrial robot to collect visual sequences along routes in natural outdoor environments and applied a neural algorithm for spatiotemporal memory that is closely based on a known neural circuit in the insect brain. We show that this method is plausible to support route recognition for visual navigation and more robust than SeqSLAM when evaluated on repeated runs on the same route or routes with small lateral offsets. By encoding memory in a spiking neural network running on a neuromorphic computer, our model can evaluate visual familiarity in real time from event camera footage.
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Affiliation(s)
- Le Zhu
- School of Informatics, University of Edinburgh, EH8 9AB Edinburgh, UK
| | - Michael Mangan
- Sheffield Robotics, Department of Computer Science, University of Sheffield, S1 4DP Sheffield, UK
| | - Barbara Webb
- School of Informatics, University of Edinburgh, EH8 9AB Edinburgh, UK
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5
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Lin AC, Prieto-Godino L. Neuroscience: Hacking development to understand sensory discrimination. Curr Biol 2023; 33:R822-R825. [PMID: 37552952 DOI: 10.1016/j.cub.2023.06.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2023]
Abstract
Fine sensory discrimination abilities are enabled by specific neural circuit architectures. A new study reveals how manipulating particular network parameters in the fly's memory centre, the mushroom body, alters sensory coding and discrimination.
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Affiliation(s)
- Andrew C Lin
- School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK. andrew.lin,@,sheffield.ac.uk
| | - Lucia Prieto-Godino
- The Francis Crick Institute, London NW1 1BF, UK. lucia.prietogodino,@,crick.ac.uk
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6
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Schlegel P, Yin Y, Bates AS, Dorkenwald S, Eichler K, Brooks P, Han DS, Gkantia M, Dos Santos M, Munnelly EJ, Badalamente G, Capdevila LS, Sane VA, Pleijzier MW, Tamimi IFM, Dunne CR, Salgarella I, Javier A, Fang S, Perlman E, Kazimiers T, Jagannathan SR, Matsliah A, Sterling AR, Yu SC, McKellar CE, Costa M, Seung HS, Murthy M, Hartenstein V, Bock DD, Jefferis GSXE. Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.27.546055. [PMID: 37425808 PMCID: PMC10327018 DOI: 10.1101/2023.06.27.546055] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.
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Ahmed M, Rajagopalan AE, Pan Y, Li Y, Williams DL, Pedersen EA, Thakral M, Previero A, Close KC, Christoforou CP, Cai D, Turner GC, Clowney EJ. Input density tunes Kenyon cell sensory responses in the Drosophila mushroom body. Curr Biol 2023; 33:2742-2760.e12. [PMID: 37348501 PMCID: PMC10529417 DOI: 10.1016/j.cub.2023.05.064] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 05/02/2023] [Accepted: 05/26/2023] [Indexed: 06/24/2023]
Abstract
The ability to discriminate sensory stimuli with overlapping features is thought to arise in brain structures called expansion layers, where neurons carrying information about sensory features make combinatorial connections onto a much larger set of cells. For 50 years, expansion coding has been a prime topic of theoretical neuroscience, which seeks to explain how quantitative parameters of the expansion circuit influence sensory sensitivity, discrimination, and generalization. Here, we investigate the developmental events that produce the quantitative parameters of the arthropod expansion layer, called the mushroom body. Using Drosophila melanogaster as a model, we employ genetic and chemical tools to engineer changes to circuit development. These allow us to produce living animals with hypothesis-driven variations on natural expansion layer wiring parameters. We then test the functional and behavioral consequences. By altering the number of expansion layer neurons (Kenyon cells) and their dendritic complexity, we find that input density, but not cell number, tunes neuronal odor selectivity. Simple odor discrimination behavior is maintained when the Kenyon cell number is reduced and augmented by Kenyon cell number expansion. Animals with increased input density to each Kenyon cell show increased overlap in Kenyon cell odor responses and become worse at odor discrimination tasks.
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Affiliation(s)
- Maria Ahmed
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Adithya E Rajagopalan
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA; The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Yijie Pan
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Ye Li
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48104, USA
| | - Donnell L Williams
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Erik A Pedersen
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Manav Thakral
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Angelica Previero
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kari C Close
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | | | - Dawen Cai
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48104, USA; Biophysics LS&A, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Neuroscience Institute Affiliate, University of Michigan, Ann Arbor, MI 48109, USA
| | - Glenn C Turner
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | - E Josephine Clowney
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Neuroscience Institute Affiliate, University of Michigan, Ann Arbor, MI 48109, USA.
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Sekar A, Leiblich A, Wainwright SM, Mendes CC, Sarma D, Hellberg JEEU, Gandy C, Goberdhan DCI, Hamdy FC, Wilson C. Rbf/E2F1 control growth and endoreplication via steroid-independent Ecdysone Receptor signalling in Drosophila prostate-like secondary cells. PLoS Genet 2023; 19:e1010815. [PMID: 37363926 PMCID: PMC10328346 DOI: 10.1371/journal.pgen.1010815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 07/07/2023] [Accepted: 06/06/2023] [Indexed: 06/28/2023] Open
Abstract
In prostate cancer, loss of the tumour suppressor gene, Retinoblastoma (Rb), and consequent activation of transcription factor E2F1 typically occurs at a late-stage of tumour progression. It appears to regulate a switch to an androgen-independent form of cancer, castration-resistant prostate cancer (CRPC), which frequently still requires androgen receptor (AR) signalling. We have previously shown that upon mating, binucleate secondary cells (SCs) of the Drosophila melanogaster male accessory gland (AG), which share some similarities with prostate epithelial cells, switch their growth regulation from a steroid-dependent to a steroid-independent form of Ecdysone Receptor (EcR) control. This physiological change induces genome endoreplication and allows SCs to rapidly replenish their secretory compartments, even when ecdysone levels are low because the male has not previously been exposed to females. Here, we test whether the Drosophila Rb homologue, Rbf, and E2F1 regulate this switch. Surprisingly, we find that excess Rbf activity reversibly suppresses binucleation in adult SCs. We also demonstrate that Rbf, E2F1 and the cell cycle regulators, Cyclin D (CycD) and Cyclin E (CycE), are key regulators of mating-dependent SC endoreplication, as well as SC growth in both virgin and mated males. Importantly, we show that the CycD/Rbf/E2F1 axis requires the EcR, but not ecdysone, to trigger CycE-dependent endoreplication and endoreplication-associated growth in SCs, mirroring changes seen in CRPC. Furthermore, Bone Morphogenetic Protein (BMP) signalling, mediated by the BMP ligand Decapentaplegic (Dpp), intersects with CycD/Rbf/E2F1 signalling to drive endoreplication in these fly cells. Overall, our work reveals a signalling switch, which permits rapid growth of SCs and increased secretion after mating, independently of previous exposure to females. The changes observed share mechanistic parallels with the pathological switch to hormone-independent AR signalling seen in CRPC, suggesting that the latter may reflect the dysregulation of a currently unidentified physiological process.
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Affiliation(s)
- Aashika Sekar
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Aaron Leiblich
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - S. Mark Wainwright
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Cláudia C. Mendes
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Dhruv Sarma
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Carina Gandy
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Deborah C. I. Goberdhan
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Freddie C. Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Clive Wilson
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
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9
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Ahmed M, Rajagopalan AE, Pan Y, Li Y, Williams DL, Pedersen EA, Thakral M, Previero A, Close KC, Christoforou CP, Cai D, Turner GC, Clowney EJ. Hacking brain development to test models of sensory coding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525425. [PMID: 36747712 PMCID: PMC9900841 DOI: 10.1101/2023.01.25.525425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Animals can discriminate myriad sensory stimuli but can also generalize from learned experience. You can probably distinguish the favorite teas of your colleagues while still recognizing that all tea pales in comparison to coffee. Tradeoffs between detection, discrimination, and generalization are inherent at every layer of sensory processing. During development, specific quantitative parameters are wired into perceptual circuits and set the playing field on which plasticity mechanisms play out. A primary goal of systems neuroscience is to understand how material properties of a circuit define the logical operations-computations--that it makes, and what good these computations are for survival. A cardinal method in biology-and the mechanism of evolution--is to change a unit or variable within a system and ask how this affects organismal function. Here, we make use of our knowledge of developmental wiring mechanisms to modify hard-wired circuit parameters in the Drosophila melanogaster mushroom body and assess the functional and behavioral consequences. By altering the number of expansion layer neurons (Kenyon cells) and their dendritic complexity, we find that input number, but not cell number, tunes odor selectivity. Simple odor discrimination performance is maintained when Kenyon cell number is reduced and augmented by Kenyon cell expansion.
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Affiliation(s)
- Maria Ahmed
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Adithya E. Rajagopalan
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Yijie Pan
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Ye Li
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48104, USA
| | - Donnell L. Williams
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Erik A. Pedersen
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Manav Thakral
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Angelica Previero
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kari C. Close
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | | | - Dawen Cai
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48104, USA
- Biophysics LS&A, University of Michigan, Ann Arbor, MI 48109, United States
- Michigan Neuroscience Institute Affiliate
| | - Glenn C. Turner
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | - E. Josephine Clowney
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
- Michigan Neuroscience Institute Affiliate
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10
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Pardo-Garcia TR, Gu K, Woerner RKR, Dus M. Food memory circuits regulate eating and energy balance. Curr Biol 2023; 33:215-227.e3. [PMID: 36528025 PMCID: PMC9877168 DOI: 10.1016/j.cub.2022.11.039] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 09/16/2022] [Accepted: 11/17/2022] [Indexed: 12/23/2022]
Abstract
In mammals, learning circuits play an essential role in energy balance by creating associations between sensory cues and the rewarding qualities of food. This process is altered by diet-induced obesity, but the causes and mechanisms are poorly understood. Here, we exploited the relative simplicity and wealth of knowledge about the D. melanogaster reinforcement learning network, the mushroom body, in order to study the relationship between the dietary environment, dopamine-induced plasticity, and food associations. We show flies that are fed a high-sugar diet cannot make associations between sensory cues and the rewarding properties of sugar. This deficit was caused by diet exposure, not fat accumulation, and specifically by lower dopamine-induced plasticity onto mushroom body output neurons (MBONs) during learning. Importantly, food memories dynamically tune the output of MBONs during eating, which instead remains fixed in sugar-diet animals. Interestingly, manipulating the activity of MBONs influenced eating and fat mass, depending on the diet. Altogether, this work advances our fundamental understanding of the mechanisms, causes, and consequences of the dietary environment on reinforcement learning and ingestive behavior.
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Affiliation(s)
- Thibaut R Pardo-Garcia
- The Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA; The Department of Molecular, Cellular, and Developmental Biology, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kathleen Gu
- The Undergraduate Program in Neuroscience, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI 48109, USA
| | - Riley K R Woerner
- The Department of Molecular, Cellular, and Developmental Biology, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI 48109, USA
| | - Monica Dus
- The Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA; The Department of Molecular, Cellular, and Developmental Biology, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI 48109, USA; The Undergraduate Program in Neuroscience, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI 48109, USA.
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11
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Hayashi TT, MacKenzie AJ, Ganguly I, Ellis KE, Smihula HM, Jacob MS, Litwin-Kumar A, Caron SJC. Mushroom body input connections form independently of sensory activity in Drosophila melanogaster. Curr Biol 2022; 32:4000-4012.e5. [PMID: 35977547 PMCID: PMC9533768 DOI: 10.1016/j.cub.2022.07.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 05/04/2022] [Accepted: 07/21/2022] [Indexed: 11/19/2022]
Abstract
Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons-namely those activated by a few ethologically meaningful odors-connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in partially anosmic flies-flies lacking the obligate odorant co-receptor Orco-and in wild-type flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. This finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.
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Affiliation(s)
- Tatsuya Tatz Hayashi
- School of Biological Sciences, University of Utah, Aline Skaggs Wilmot Biology Building, 257 South 1400 East, Salt Lake City, UT 84112, USA; Neuroscience Program, University of Utah, Salt Lake City, UT 84112, USA
| | - Alexander John MacKenzie
- School of Biological Sciences, University of Utah, Aline Skaggs Wilmot Biology Building, 257 South 1400 East, Salt Lake City, UT 84112, USA; Neuroscience Program, University of Utah, Salt Lake City, UT 84112, USA
| | - Ishani Ganguly
- Center for Theoretical Neuroscience, Columbia University, Jerome L Greene Science Center, 3227 Broadway, New York, NY 10027, USA
| | - Kaitlyn Elizabeth Ellis
- School of Biological Sciences, University of Utah, Aline Skaggs Wilmot Biology Building, 257 South 1400 East, Salt Lake City, UT 84112, USA
| | - Hayley Marie Smihula
- School of Biological Sciences, University of Utah, Aline Skaggs Wilmot Biology Building, 257 South 1400 East, Salt Lake City, UT 84112, USA
| | - Miles Solomon Jacob
- School of Biological Sciences, University of Utah, Aline Skaggs Wilmot Biology Building, 257 South 1400 East, Salt Lake City, UT 84112, USA
| | - Ashok Litwin-Kumar
- Center for Theoretical Neuroscience, Columbia University, Jerome L Greene Science Center, 3227 Broadway, New York, NY 10027, USA
| | - Sophie Jeanne Cécile Caron
- School of Biological Sciences, University of Utah, Aline Skaggs Wilmot Biology Building, 257 South 1400 East, Salt Lake City, UT 84112, USA; Neuroscience Program, University of Utah, Salt Lake City, UT 84112, USA.
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12
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Duhart JC, Mosca TJ. Genetic regulation of central synapse formation and organization in Drosophila melanogaster. Genetics 2022; 221:6597078. [PMID: 35652253 DOI: 10.1093/genetics/iyac078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/29/2022] [Indexed: 01/04/2023] Open
Abstract
A goal of modern neuroscience involves understanding how connections in the brain form and function. Such a knowledge is essential to inform how defects in the exquisite complexity of nervous system growth influence neurological disease. Studies of the nervous system in the fruit fly Drosophila melanogaster enabled the discovery of a wealth of molecular and genetic mechanisms underlying development of synapses-the specialized cell-to-cell connections that comprise the essential substrate for information flow and processing in the nervous system. For years, the major driver of knowledge was the neuromuscular junction due to its ease of examination. Analogous studies in the central nervous system lagged due to a lack of genetic accessibility of specific neuron classes, synaptic labels compatible with cell-type-specific access, and high resolution, quantitative imaging strategies. However, understanding how central synapses form remains a prerequisite to understanding brain development. In the last decade, a host of new tools and techniques extended genetic studies of synapse organization into central circuits to enhance our understanding of synapse formation, organization, and maturation. In this review, we consider the current state-of-the-field. We first discuss the tools, technologies, and strategies developed to visualize and quantify synapses in vivo in genetically identifiable neurons of the Drosophila central nervous system. Second, we explore how these tools enabled a clearer understanding of synaptic development and organization in the fly brain and the underlying molecular mechanisms of synapse formation. These studies establish the fly as a powerful in vivo genetic model that offers novel insights into neural development.
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Affiliation(s)
- Juan Carlos Duhart
- Department of Neuroscience, Vickie and Jack Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Timothy J Mosca
- Department of Neuroscience, Vickie and Jack Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA
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13
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Endo K, Kazama H. Central organization of a high-dimensional odor space. Curr Opin Neurobiol 2022; 73:102528. [DOI: 10.1016/j.conb.2022.102528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 02/17/2022] [Accepted: 02/24/2022] [Indexed: 11/03/2022]
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14
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Yang K, Liu T, Wang Z, Liu J, Shen Y, Pan X, Wen R, Xie H, Ruan Z, Tan Z, Chen Y, Guo A, Liu H, Han H, Di Z, Zhang K. Classifying Drosophila Olfactory Projection Neuron Boutons by Quantitative Analysis of Electron Microscopic Reconstruction. iScience 2022; 25:104180. [PMID: 35494235 PMCID: PMC9038572 DOI: 10.1016/j.isci.2022.104180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 01/25/2022] [Accepted: 03/29/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Kai Yang
- School of Basic Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, China
- BNU-BUCM Hengqin Innovation Institute of Science and Technology, Zhuhai, Guangdong 518057, China
| | - Tong Liu
- International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Ze Wang
- International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Jing Liu
- Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yuxinyao Shen
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Xinyi Pan
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Ruyi Wen
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Haotian Xie
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Zhaoxuan Ruan
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Zixiao Tan
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Yingying Chen
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Aike Guo
- International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
- Huitong College, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
- School of Life Sciences, Shanghai University, Shanghai 200444, China
| | - He Liu
- International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Hua Han
- Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Zengru Di
- International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
| | - Ke Zhang
- International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, Guangdong 519087, China
- Corresponding author
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15
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Xie Q, Brbic M, Horns F, Kolluru SS, Jones RC, Li J, Reddy AR, Xie A, Kohani S, Li Z, McLaughlin CN, Li T, Xu C, Vacek D, Luginbuhl DJ, Leskovec J, Quake SR, Luo L, Li H. Temporal evolution of single-cell transcriptomes of Drosophila olfactory projection neurons. eLife 2021; 10:e63450. [PMID: 33427646 PMCID: PMC7870145 DOI: 10.7554/elife.63450] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 01/05/2021] [Indexed: 12/18/2022] Open
Abstract
Neurons undergo substantial morphological and functional changes during development to form precise synaptic connections and acquire specific physiological properties. What are the underlying transcriptomic bases? Here, we obtained the single-cell transcriptomes of Drosophila olfactory projection neurons (PNs) at four developmental stages. We decoded the identity of 21 transcriptomic clusters corresponding to 20 PN types and developed methods to match transcriptomic clusters representing the same PN type across development. We discovered that PN transcriptomes reflect unique biological processes unfolding at each stage-neurite growth and pruning during metamorphosis at an early pupal stage; peaked transcriptomic diversity during olfactory circuit assembly at mid-pupal stages; and neuronal signaling in adults. At early developmental stages, PN types with adjacent birth order share similar transcriptomes. Together, our work reveals principles of cellular diversity during brain development and provides a resource for future studies of neural development in PNs and other neuronal types.
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Affiliation(s)
- Qijing Xie
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
- Neurosciences Graduate Program, Stanford UniversityStanfordUnited States
| | - Maria Brbic
- Department of Computer Science, Stanford UniversityStanfordUnited States
| | - Felix Horns
- Department of Bioengineering, Stanford UniversityStanfordUnited States
- Biophysics Graduate Program, Stanford UniversityStanfordUnited States
| | | | - Robert C Jones
- Department of Bioengineering, Stanford UniversityStanfordUnited States
| | - Jiefu Li
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Anay R Reddy
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Anthony Xie
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Sayeh Kohani
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Zhuoran Li
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Colleen N McLaughlin
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Tongchao Li
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Chuanyun Xu
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - David Vacek
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - David J Luginbuhl
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Jure Leskovec
- Department of Computer Science, Stanford UniversityStanfordUnited States
| | - Stephen R Quake
- Department of Bioengineering, Stanford UniversityStanfordUnited States
- Department of Applied Physics, Stanford UniversityStanfordUnited States
- Chan Zuckerberg BiohubStanfordUnited States
| | - Liqun Luo
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Hongjie Li
- Department of Biology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
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16
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Puñal VM, Ahmed M, Thornton-Kolbe EM, Clowney EJ. Untangling the wires: development of sparse, distributed connectivity in the mushroom body calyx. Cell Tissue Res 2021; 383:91-112. [PMID: 33404837 PMCID: PMC9835099 DOI: 10.1007/s00441-020-03386-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 12/07/2020] [Indexed: 01/16/2023]
Abstract
Appropriate perception and representation of sensory stimuli pose an everyday challenge to the brain. In order to represent the wide and unpredictable array of environmental stimuli, principle neurons of associative learning regions receive sparse, combinatorial sensory inputs. Despite the broad role of such networks in sensory neural circuits, the developmental mechanisms underlying their emergence are not well understood. As mammalian sensory coding regions are numerically complex and lack the accessibility of simpler invertebrate systems, we chose to focus this review on the numerically simpler, yet functionally similar, Drosophila mushroom body calyx. We bring together current knowledge about the cellular and molecular mechanisms orchestrating calyx development, in addition to drawing insights from literature regarding construction of sparse wiring in the mammalian cerebellum. From this, we formulate hypotheses to guide our future understanding of the development of this critical perceptual center.
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Affiliation(s)
- Vanessa M. Puñal
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA,Department of Molecular & Integrative Physiology, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Maria Ahmed
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Emma M. Thornton-Kolbe
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA,Neuroscience Graduate Program, The University of Michigan, Ann Arbor, MI 48109, USA
| | - E. Josephine Clowney
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA
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17
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Li F, Lindsey JW, Marin EC, Otto N, Dreher M, Dempsey G, Stark I, Bates AS, Pleijzier MW, Schlegel P, Nern A, Takemura SY, Eckstein N, Yang T, Francis A, Braun A, Parekh R, Costa M, Scheffer LK, Aso Y, Jefferis GSXE, Abbott LF, Litwin-Kumar A, Waddell S, Rubin GM. The connectome of the adult Drosophila mushroom body provides insights into function. eLife 2020; 9:e62576. [PMID: 33315010 PMCID: PMC7909955 DOI: 10.7554/elife.62576] [Citation(s) in RCA: 157] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 12/11/2020] [Indexed: 12/12/2022] Open
Abstract
Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory, and activity regulation. Here, we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.
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Affiliation(s)
- Feng Li
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Jack W Lindsey
- Department of Neuroscience, Columbia University, Zuckerman InstituteNew YorkUnited States
| | - Elizabeth C Marin
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Nils Otto
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
- Centre for Neural Circuits & Behaviour, University of OxfordOxfordUnited Kingdom
| | - Marisa Dreher
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Georgia Dempsey
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Ildiko Stark
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Alexander S Bates
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | | | - Philipp Schlegel
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Shin-ya Takemura
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Nils Eckstein
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Tansy Yang
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Audrey Francis
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Amalia Braun
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Ruchi Parekh
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Louis K Scheffer
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Yoshinori Aso
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gregory SXE Jefferis
- Drosophila Connectomics Group, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
- Neurobiology Division, MRC Laboratory of Molecular BiologyCambridgeUnited Kingdom
| | - Larry F Abbott
- Department of Neuroscience, Columbia University, Zuckerman InstituteNew YorkUnited States
| | - Ashok Litwin-Kumar
- Department of Neuroscience, Columbia University, Zuckerman InstituteNew YorkUnited States
| | - Scott Waddell
- Centre for Neural Circuits & Behaviour, University of OxfordOxfordUnited Kingdom
| | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
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