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Hurwitz I, Tam S, Jing J, Chiel HJ, Susswein AJ. Repeated stimulation of feeding mechanoafferents in Aplysia generates responses consistent with the release of food. Learn Mem 2024; 31:a053880. [PMID: 38950976 PMCID: PMC11261209 DOI: 10.1101/lm.053880.123] [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: 09/04/2023] [Accepted: 04/19/2024] [Indexed: 07/03/2024]
Abstract
How does repeated stimulation of mechanoafferents affect feeding motor neurons? Monosynaptic connections from a mechanoafferent population in the Aplysia buccal ganglia to five motor followers with different functions were examined during repeated stimulus trains. The mechanoafferents produced both fast and slow synaptic outputs, which could be excitatory or inhibitory. In contrast, other Aplysia mechanoafferents produce only fast excitation on their followers. In addition, patterns of synaptic connections were different to the different motor followers. Some followers received both fast excitation and fast inhibition, whereas others received exclusively fast excitation. All followers showed strong decreases in fast postsynaptic potential (PSP) amplitude within a stimulus train. Fast and slow synaptic connections were of net opposite signs in some followers but not in others. For one follower, synaptic contacts were not uniform from all subareas of the mechanoafferent cluster. Differences in properties of the buccal ganglia mechanoafferents and other Aplysia mechanoafferents may arise because the buccal ganglia neurons innervate the interior of the feeding apparatus, rather than an external surface, and connect to motor neurons for muscles with different motor functions. Fast connection patterns suggest that these synapses may be activated when food slips, biasing the musculature to release food. The largest slow inhibitory synaptic PSPs may contribute to a delay in the onset of the next behavior. Additional functions are also possible.
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Affiliation(s)
- Itay Hurwitz
- Gonda (Goldschmied) Brain Res Center and Goodman Faculty of Life Science, Bar Ilan University, Ramat Gan 52900, Israel
| | - Shlomit Tam
- Gonda (Goldschmied) Brain Res Center and Goodman Faculty of Life Science, Bar Ilan University, Ramat Gan 52900, Israel
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, School Life Sciences, Nanjing University, Jiangsu 210023, China
| | - Hillel J Chiel
- Departments of Biology, Neurosciences, and Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106-7080, USA
| | - Abraham J Susswein
- Gonda (Goldschmied) Brain Res Center and Goodman Faculty of Life Science, Bar Ilan University, Ramat Gan 52900, Israel
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2
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Hurwitz I, Tam S, Jing J, Chiel HJ, Gill J, Susswein AJ. Multiple changes in connectivity between buccal ganglia mechanoafferents and motor neurons with different functions after learning that food is inedible in Aplysia. Learn Mem 2024; 31:a053882. [PMID: 38950977 PMCID: PMC11261210 DOI: 10.1101/lm.053882.123] [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: 09/04/2023] [Accepted: 04/19/2024] [Indexed: 07/03/2024]
Abstract
Changes caused by learning that a food is inedible in Aplysia were examined for fast and slow synaptic connections from the buccal ganglia S1 cluster of mechanoafferents to five followers, in response to repeated stimulus trains. Learning affected only fast connections. For these, unique patterns of change were present in each follower, indicating that learning differentially affects the different branches of the mechanoafferents to their followers. In some followers, there were increases in either excitatory or inhibitory connections, and in others, there were decreases. Changes in connectivity resulted from changes in the amplitude of excitation or inhibition, or as a result of the number of connections, or of both. Some followers also exhibited changes in either within or between stimulus train plasticity as a result of learning. In one follower, changes differed from the different areas of the S1 cluster. The patterns of changes in connectivity were consistent with the behavioral changes produced by learning, in that they would produce an increase in the bias to reject or to release food, and a decrease in the likelihood to respond to food.
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Affiliation(s)
- Itay Hurwitz
- Gonda (Goldschmied) Brain Res Center and Goodman Faculty of Life Science, Bar Ilan University, Ramat Gan 52900, Israel
| | - Shlomit Tam
- Gonda (Goldschmied) Brain Res Center and Goodman Faculty of Life Science, Bar Ilan University, Ramat Gan 52900, Israel
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, School Life Sciences, Nanjing University, Jiangsu 210023, China
| | - Hillel J Chiel
- Departments of Biology, Case Western Reserve University, Cleveland, Ohio 44106-7080, USA
- Neurosciences, Case Western Reserve University, Cleveland, Ohio 44106-7080, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106-7080, USA
| | - Jeffrey Gill
- Departments of Biology, Case Western Reserve University, Cleveland, Ohio 44106-7080, USA
| | - Abraham J Susswein
- Gonda (Goldschmied) Brain Res Center and Goodman Faculty of Life Science, Bar Ilan University, Ramat Gan 52900, Israel
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Evans CG, Barry MA, Perkins MH, Jing J, Weiss KR, Cropper EC. Variable task switching in the feeding network of Aplysia is a function of differential command input. J Neurophysiol 2023; 130:941-952. [PMID: 37671445 PMCID: PMC10648941 DOI: 10.1152/jn.00190.2023] [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: 05/11/2023] [Revised: 08/09/2023] [Accepted: 08/31/2023] [Indexed: 09/07/2023] Open
Abstract
Command systems integrate sensory information and then activate the interneurons and motor neurons that mediate behavior. Much research has established that the higher-order projection neurons that constitute these systems can play a key role in specifying the nature of the motor activity induced, or determining its parametric features. To a large extent, these insights have been obtained by contrasting activity induced by stimulating one neuron (or set of neurons) to activity induced by stimulating a different neuron (or set of neurons). The focus of our work differs. We study one type of motor program, ingestive feeding in the mollusc Aplysia californica, which can either be triggered when a single projection neuron (CBI-2) is repeatedly stimulated or can be triggered by projection neuron coactivation (e.g., activation of CBI-2 and CBI-3). We ask why this might be an advantageous arrangement. The cellular/molecular mechanisms that configure motor activity are different in the two situations because the released neurotransmitters differ. We focus on an important consequence of this arrangement, the fact that a persistent state can be induced with repeated CBI-2 stimulation that is not necessarily induced by CBI-2/3 coactivation. We show that this difference can have consequences for the ability of the system to switch from one type of activity to another.NEW & NOTEWORTHY We study a type of motor program that can be induced either by stimulating a higher-order projection neuron that induces a persistent state, or by coactivating projection neurons that configure activity but do not produce a state change. We show that when an activity is configured without a state change, it is possible to immediately return to an intermediate state that subsequently can be converted to any type of motor program.
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Affiliation(s)
- Colin G Evans
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Michael A Barry
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Matthew H Perkins
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Jian Jing
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chemistry and Biomedicine Innovation Center, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, China
| | - Klaudiusz R Weiss
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Elizabeth C Cropper
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
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4
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Fu P, Mei YS, Liu WJ, Chen P, Jin QC, Guo SQ, Wang HY, Xu JP, Zhang YCF, Ding XY, Liu CP, Liu CY, Mao RT, Zhang G, Jing J. Identification of three elevenin receptors and roles of elevenin disulfide bond and residues in receptor activation in Aplysia californica. Sci Rep 2023; 13:7662. [PMID: 37169790 PMCID: PMC10175484 DOI: 10.1038/s41598-023-34596-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 05/04/2023] [Indexed: 05/13/2023] Open
Abstract
Neuropeptides are ubiquitous intercellular signaling molecules in the CNS and play diverse roles in modulating physiological functions by acting on specific G-protein coupled receptors (GPCRs). Among them, the elevenin signaling system is now believed to be present primarily in protostomes. Although elevenin was first identified from the L11 neuron of the abdominal ganglion in mollusc Aplysia californica, no receptors have been described in Aplysia, nor in any other molluscs. Here, using two elevenin receptors in annelid Platynereis dumerilii, we found three putative elevenin GPCRs in Aplysia. We cloned the three receptors and tentatively named them apElevR1, apElevR2, and apElevR3. Using an inositol monophosphate (IP1) accumulation assay, we demonstrated that Aplysia elevenin with the disulfide bond activated the three putative receptors with low EC50 values (ranging from 1.2 to 25 nM), supporting that they are true receptors for elevenin. In contrast, elevenin without the disulfide bond could not activate the receptors, indicating that the disulfide bond is required for receptor activity. Using alanine substitution of individual conserved residues other than the two cysteines, we showed that these residues appear to be critical to receptor activity, and the three different receptors had different sensitivities to the single residue substitution. Finally, we examined the roles of those residues outside the disulfide bond ring by removing these residues and found that they also appeared to be important to receptor activity. Thus, our study provides an important basis for further study of the functions of elevenin and its receptors in Aplysia and other molluscs.
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Affiliation(s)
- Ping Fu
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Yu-Shuo Mei
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Wei-Jia Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ping Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Qing-Chun Jin
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Shi-Qi Guo
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Hui-Ying Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ju-Ping Xu
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Yan-Chu-Fei Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Xue-Ying Ding
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Cui-Ping Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Cheng-Yi Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Rui-Ting Mao
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Guo Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China.
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Medical Psychology and Neurology, Nanjing Drum Tower Hospital, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China.
- Peng Cheng Laboratory, Shenzhen, 518000, China.
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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5
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Xu JP, Ding XY, Guo SQ, Wang HY, Liu WJ, Jiang HM, Li YD, Fu P, Chen P, Mei YS, Zhang G, Zhou HB, Jing J. Characterization of an Aplysia vasotocin signaling system and actions of posttranslational modifications and individual residues of the ligand on receptor activity. Front Pharmacol 2023; 14:1132066. [PMID: 37021048 PMCID: PMC10067623 DOI: 10.3389/fphar.2023.1132066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 03/06/2023] [Indexed: 04/07/2023] Open
Abstract
The vasopressin/oxytocin signaling system is present in both protostomes and deuterostomes and plays various physiological roles. Although there were reports for both vasopressin-like peptides and receptors in mollusc Lymnaea and Octopus, no precursor or receptors have been described in mollusc Aplysia. Here, through bioinformatics, molecular and cellular biology, we identified both the precursor and two receptors for Aplysia vasopressin-like peptide, which we named Aplysia vasotocin (apVT). The precursor provides evidence for the exact sequence of apVT, which is identical to conopressin G from cone snail venom, and contains 9 amino acids, with two cysteines at position 1 and 6, similar to nearly all vasopressin-like peptides. Through inositol monophosphate (IP1) accumulation assay, we demonstrated that two of the three putative receptors we cloned from Aplysia cDNA are true receptors for apVT. We named the two receptors as apVTR1 and apVTR2. We then determined the roles of post-translational modifications (PTMs) of apVT, i.e., the disulfide bond between two cysteines and the C-terminal amidation on receptor activity. Both the disulfide bond and amidation were critical for the activation of the two receptors. Cross-activity with conopressin S, annetocin from an annelid, and vertebrate oxytocin showed that although all three ligands can activate both receptors, the potency of these peptides differed depending on their residue variations from apVT. We, therefore, tested the roles of each residue through alanine substitution and found that each substitution could reduce the potency of the peptide analog, and substitution of the residues within the disulfide bond tended to have a larger impact on receptor activity than the substitution of those outside the bond. Moreover, the two receptors had different sensitivities to the PTMs and single residue substitutions. Thus, we have characterized the Aplysia vasotocin signaling system and showed how the PTMs and individual residues in the ligand contributed to receptor activity.
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Affiliation(s)
- Ju-Ping Xu
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Xue-Ying Ding
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Shi-Qi Guo
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Hui-Ying Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Wei-Jia Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Hui-Min Jiang
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Ya-Dong Li
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Ping Fu
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Ping Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Yu-Shuo Mei
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Guo Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
| | - Hai-Bo Zhou
- School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, China
- Peng Cheng Laboratory, Shenzhen, China
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Chemistry and Biomedicine Innovation Center, Institute for Brain Sciences, Advanced Institute for Life Sciences, School of Life Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Nanjing University, Nanjing, Jiangsu, China
- Peng Cheng Laboratory, Shenzhen, China
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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6
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Wang HY, Yu K, Yang Z, Zhang G, Guo SQ, Wang T, Liu DD, Jia RN, Zheng YT, Su YN, Lou Y, Weiss KR, Zhou HB, Liu F, Cropper EC, Yu Q, Jing J. A Single Central Pattern Generator for the Control of a Locomotor Rolling Wave in Mollusc Aplysia. RESEARCH (WASHINGTON, D.C.) 2023; 6:0060. [PMID: 36930762 PMCID: PMC10013812 DOI: 10.34133/research.0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/09/2023] [Indexed: 01/21/2023]
Abstract
Locomotion in mollusc Aplysia is implemented by a pedal rolling wave, a type of axial locomotion. Well-studied examples of axial locomotion (pedal waves in Drosophila larvae and body waves in leech, lamprey, and fish) are generated in a segmented nervous system via activation of multiple coupled central pattern generators (CPGs). Pedal waves in molluscs, however, are generated by a single pedal ganglion, and it is unknown whether there are single or multiple CPGs that generate rhythmic activity and phase shifts between different body parts. During locomotion in intact Aplysia, bursting activity in the parapedal commissural nerve (PPCN) was found to occur during tail contraction. A cluster of 20 to 30 P1 root neurons (P1Ns) on the ventral surface of the pedal ganglion, active during the pedal wave, were identified. Computational cluster analysis revealed that there are 2 phases to the motor program: phase I (centered around 168°) and phase II (centered around 357°). PPCN activity occurs during phase II. The majority of P1Ns are motoneurons. Coactive P1Ns tend to be electrically coupled. Two classes of pedal interneurons (PIs) were characterized. Class 1 (PI1 and PI2) is active during phase I. Their axons make a loop within the pedal ganglion and contribute to locomotor pattern generation. They are electrically coupled to P1Ns that fire during phase I. Class 2 (PI3) is active during phase II and innervates the contralateral pedal ganglion. PI3 may contribute to bilateral coordination. Overall, our findings support the idea that Aplysia pedal waves are generated by a single CPG.
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Affiliation(s)
- Hui-Ying Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ke Yu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Zhe Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Guo Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Shi-Qi Guo
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Tao Wang
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Dan-Dan Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ruo-Nan Jia
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Yu-Tong Zheng
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Yan-Nan Su
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Yi Lou
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Klaudiusz R. Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hai-Bo Zhou
- School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu 210023, China
- Peng Cheng Laboratory, Shenzhen 518000, China
| | - Feng Liu
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Elizabeth C. Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Quan Yu
- Peng Cheng Laboratory, Shenzhen 518000, China
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Peng Cheng Laboratory, Shenzhen 518000, China
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AI protein structure prediction-based modeling and mutagenesis of a protostome receptor and peptide ligands reveal key residues for their interaction. J Biol Chem 2022; 298:102440. [PMID: 36049520 PMCID: PMC9562341 DOI: 10.1016/j.jbc.2022.102440] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 11/24/2022] Open
Abstract
The protostome leucokinin (LK) signaling system, including LK peptides and their G protein-coupled receptors, has been characterized in several species. Despite progress in this area, molecular mechanisms governing LK peptide-receptor interactions remain to be elucidated. Previously, we identified a precursor protein for Aplysia leucokinin-like peptides (ALKs) that contains the greatest number of amidated peptides among LK precursors in all species identified so far. Here, we identified the first ALK receptor from Aplysia, ALKR. We used cell-based IP1 activation assays to demonstrate that the two ALK peptides with the most copies, ALK1 and ALK2, activated ALKR with high potencies. Other endogenous ALK-derived peptides bearing the FXXWX-amide motif also activated ALKR to various degrees. Our examination of cross-species activity of ALKs with the Anopheles LKR was consistent with a critical role for the FXXWX-amide motif in receptor activity. Furthermore, we showed, through alanine substitution of ALK1, the highly conserved phenylalanine (F), tryptophan (W), and C-terminal amidation were each essential for receptor activation. Finally, we used an AI-based protein structure prediction server (Robetta) and Autodock Vina to predict the ligand-bound conformation of ALKR. Our model predicted several interactions (i.e., hydrophobic interactions, hydrogen bonds, and amide-pi stacking) between ALK peptides and ALKR, and several of our substitution and mutagenesis experiments were consistent with the predicted model. In conclusion, our results provide important information defining the possible interactions between ALK peptides and their receptors. The workflow utilized here may be useful for studying other ligand-receptor interactions for a neuropeptide signaling system, particularly in protostomes.
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8
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Momohara Y, Neveu CL, Chen HM, Baxter DA, Byrne JH. Specific Plasticity Loci and Their Synergism Mediate Operant Conditioning. J Neurosci 2022; 42:1211-1223. [PMID: 34992131 PMCID: PMC8883845 DOI: 10.1523/jneurosci.1722-21.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 09/26/2021] [Accepted: 12/03/2021] [Indexed: 11/21/2022] Open
Abstract
Despite numerous studies examining the mechanisms of operant conditioning (OC), the diversity of OC plasticity loci and their synergism have not been examined sufficiently. In the well-characterized feeding neural circuit of Aplysia, in vivo and in vitro appetitive OC increases neuronal excitability and electrical coupling among several neurons leading to an increase in expression of ingestive behavior. Here, we used the in vitro analog of OC to investigate whether OC reduces the excitability of a neuron, B4, whose inhibitory connections decrease expression of ingestive behavior. We found OC decreased the excitability of B4. This change appeared intrinsic to B4 because it could be replicated with an analog of OC in isolated cultures of B4 neurons. In addition to changes in B4 excitability, OC decreased the strength of B4's inhibitory connection to a key decision-making neuron, B51. The OC-induced changes were specific without affecting the excitability of another neuron critical for feeding behavior, B8, or the B4-to-B8 inhibitory connection. A conductance-based circuit model indicated that reducing the B4-to-B51 synapse, or increasing B51 excitability, mediated the OC phenotype more effectively than did decreasing B4 excitability. We combined these modifications to examine whether they could act synergistically. Combinations including B51 synergistically enhanced feeding. Taken together, these results suggest modifications of diverse loci work synergistically to mediate OC and that some neurons are well suited to work synergistically with plasticity in other loci.SIGNIFICANCE STATEMENT The ways in which synergism of diverse plasticity loci mediate the change in motor patterns in operant conditioning (OC) are poorly understood. Here, we found that OC was in part mediated by decreasing the intrinsic excitability of a critical neuron of Aplysia feeding behavior, and specifically reducing the strength of one of its inhibitory connections that targets a key decision-making neuron. A conductance-based computational model indicated that the known plasticity loci showed a surprising level of synergism to mediate the behavioral changes associated with OC. These results highlight the importance of understanding the diversity, specificity and synergy among different types of plasticity that encode memory. Also, because OC in Aplysia is mediated by dopamine (DA), the present study provides insights into specific and synergistic mechanisms of DA-mediated reinforcement of behaviors.
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Affiliation(s)
- Yuto Momohara
- Department of Neurobiology and Anatomy, W.M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the, University of Texas Health Science Center, Houston, Texas 77030
| | - Curtis L Neveu
- Department of Neurobiology and Anatomy, W.M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the, University of Texas Health Science Center, Houston, Texas 77030
| | - Hsin-Mei Chen
- Department of Neurobiology and Anatomy, W.M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the, University of Texas Health Science Center, Houston, Texas 77030
- Center for Nursing Research, Education and Practice, Houston Methodist Academic Institute, Houston, Texas 77030
| | - Douglas A Baxter
- Department of Neurobiology and Anatomy, W.M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the, University of Texas Health Science Center, Houston, Texas 77030
- Engineering Medicine (ENMED), Texas A&M University College of Medicine, Houston, Texas 77030
| | - John H Byrne
- Department of Neurobiology and Anatomy, W.M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the, University of Texas Health Science Center, Houston, Texas 77030
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9
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Jiang HM, Yang Z, Xue YY, Wang HY, Guo SQ, Xu JP, Li YD, Fu P, Ding XY, Yu K, Liu WJ, Zhang G, Wang J, Zhou HB, Susswein AJ, Jing J. Identification of an allatostatin C signaling system in mollusc Aplysia. Sci Rep 2022; 12:1213. [PMID: 35075137 PMCID: PMC8786951 DOI: 10.1038/s41598-022-05071-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 01/06/2022] [Indexed: 02/06/2023] Open
Abstract
Neuropeptides, as pervasive intercellular signaling molecules in the CNS, modulate a variety of behavioral systems in both protostomes and deuterostomes. Allatostatins are neuropeptides in arthropods that inhibit the biosynthesis of juvenile hormones. Based on amino acid sequences, they are divided into three different types in arthropods: allatostatin A, allatostatin B, allatostatin C. Allatostatin C (AstC) was first isolated from Manduca sexta, and it has an important conserved feature of a disulfide bridge formed by two cysteine residues. Moreover, AstC appears to be the ortholog of mammalian somatostatin, and it has functions in common with somatostatin, such as modulating feeding behaviors. The AstC signaling system has been widely studied in arthropods, but minimally studied in molluscs. In this study, we seek to identify the AstC signaling system in the marine mollusc Aplysia californica. We cloned the AstC precursor from the cDNA of Aplysia. We predicted a 15-amino acid peptide with a disulfide bridge, i.e., AstC, using NeuroPred. We then cloned two putative allatostatin C-like receptors and through NCBI Conserved Domain Search we found that they belonged to the G protein-coupled receptor (GPCR) family. In addition, using an inositol monophosphate 1 (IP1) accumulation assay, we showed that Aplysia AstC could activate one of the putative receptors, i.e., the AstC-R, at the lowest EC50, and AstC without the disulfide bridge (AstC') activated AstC-R with the highest EC50. Moreover, four molluscan AstCs with variations of sequences from Aplysia AstC but with the disulfide bridge activated AstC-R at intermediate EC50. In summary, our successful identification of the Aplysia AstC precursor and its receptor (AstC-R) represents the first example in molluscs, and provides an important basis for further studies of the AstC signaling system in Aplysia and other molluscs.
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Affiliation(s)
- Hui-Min Jiang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Zhe Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ying-Yu Xue
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Hui-Ying Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Shi-Qi Guo
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ju-Ping Xu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ya-Dong Li
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ping Fu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Xue-Ying Ding
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Ke Yu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Wei-Jia Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China
| | - Guo Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China.
| | - Jian Wang
- School of Electronic Science and Engineering, Nanjing University, Nanjing, 210023, Jiangsu, China.
- Peng Cheng Laboratory, Shenzhen, 518000, China.
| | - Hai-Bo Zhou
- School of Electronic Science and Engineering, Nanjing University, Nanjing, 210023, Jiangsu, China.
- Peng Cheng Laboratory, Shenzhen, 518000, China.
| | - Abraham J Susswein
- The Mina and Everard Goodman Faculty of Life Sciences, The Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center, Bar Ilan University, 52900, Ramat Gan, Israel
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, 210023, Jiangsu, China.
- Peng Cheng Laboratory, Shenzhen, 518000, China.
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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10
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Zhang G, Yu K, Wang T, Chen TT, Yuan WD, Yang F, Le ZW, Guo SQ, Xue YY, Chen SA, Yang Z, Liu F, Cropper EC, Weiss KR, Jing J. Synaptic mechanisms for motor variability in a feedforward network. SCIENCE ADVANCES 2020; 6:6/25/eaba4856. [PMID: 32937495 PMCID: PMC7458462 DOI: 10.1126/sciadv.aba4856] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 05/07/2020] [Indexed: 05/26/2023]
Abstract
Behavioral variability often arises from variable activity in the behavior-generating neural network. The synaptic mechanisms underlying this variability are poorly understood. We show that synaptic noise, in conjunction with weak feedforward excitation, generates variable motor output in the Aplysia feeding system. A command-like neuron (CBI-10) triggers rhythmic motor programs more variable than programs triggered by CBI-2. CBI-10 weakly excites a pivotal pattern-generating interneuron (B34) strongly activated by CBI-2. The activation properties of B34 substantially account for the degree of program variability. CBI-10- and CBI-2-induced EPSPs in B34 vary in amplitude across trials, suggesting that there is synaptic noise. Computational studies show that synaptic noise is required for program variability. Further, at network state transition points when synaptic conductance is low, maximum program variability is promoted by moderate noise levels. Thus, synaptic strength and noise act together in a nonlinear manner to determine the degree of variability within a feedforward network.
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Affiliation(s)
- Guo Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ke Yu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Tao Wang
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Ting-Ting Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Wang-Ding Yuan
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Fan Yang
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Zi-Wei Le
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Shi-Qi Guo
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ying-Yu Xue
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Song-An Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Zhe Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Feng Liu
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China.
| | - Elizabeth C Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Klaudiusz R Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China.
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Peng Cheng Laboratory, Shenzhen 518000, China
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11
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Costa RM, Baxter DA, Byrne JH. Computational model of the distributed representation of operant reward memory: combinatoric engagement of intrinsic and synaptic plasticity mechanisms. ACTA ACUST UNITED AC 2020; 27:236-249. [PMID: 32414941 PMCID: PMC7233148 DOI: 10.1101/lm.051367.120] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 02/13/2020] [Indexed: 01/15/2023]
Abstract
Operant reward learning of feeding behavior in Aplysia increases the frequency and regularity of biting, as well as biases buccal motor patterns (BMPs) toward ingestion-like BMPs (iBMPs). The engram underlying this memory comprises cells that are part of a central pattern generating (CPG) circuit and includes increases in the intrinsic excitability of identified cells B30, B51, B63, and B65, and increases in B63-B30 and B63-B65 electrical synaptic coupling. To examine the ways in which sites of plasticity (individually and in combination) contribute to memory expression, a model of the CPG was developed. The model included conductance-based descriptions of cells CBI-2, B4, B8, B20, B30, B31, B34, B40, B51, B52, B63, B64, and B65, and their synaptic connections. The model generated patterned activity that resembled physiological BMPs, and implementation of the engram reproduced increases in frequency, regularity, and bias. Combined enhancement of B30, B63, and B65 excitabilities increased BMP frequency and regularity, but not bias toward iBMPs. Individually, B30 increased regularity and bias, B51 increased bias, B63 increased frequency, and B65 decreased all three BMP features. Combined synaptic plasticity contributed primarily to regularity, but also to frequency and bias. B63-B30 coupling contributed to regularity and bias, and B63-B65 coupling contributed to all BMP features. Each site of plasticity altered multiple BMP features simultaneously. Moreover, plasticity loci exhibited mutual dependence and synergism. These results indicate that the memory for operant reward learning emerged from the combinatoric engagement of multiple sites of plasticity.
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Affiliation(s)
- Renan M Costa
- Keck Center for the Neurobiology of Learning and Memory, Department of Neurobiology and Anatomy, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.,MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, Texas 77030, USA
| | - Douglas A Baxter
- Keck Center for the Neurobiology of Learning and Memory, Department of Neurobiology and Anatomy, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.,Engineering in Medicine (EnMed), Texas A&M Health Science Center-Houston, Houston, Texas 77030, USA
| | - John H Byrne
- Keck Center for the Neurobiology of Learning and Memory, Department of Neurobiology and Anatomy, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.,MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, Texas 77030, USA
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12
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Multiple Local Synaptic Modifications at Specific Sensorimotor Connections after Learning Are Associated with Behavioral Adaptations That Are Components of a Global Response Change. J Neurosci 2020; 40:4363-4371. [PMID: 32366723 DOI: 10.1523/jneurosci.2647-19.2020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 02/24/2020] [Accepted: 02/25/2020] [Indexed: 11/21/2022] Open
Abstract
Learning causes local changes in synaptic connectivity and coordinated, global changes affecting many aspects of behavior. How do local synaptic changes produce global behavioral changes? In the hermaphroditic mollusc Aplysia, after learning that food is inedible, memory is expressed as bias to reject a food and to reduce responses to that food. We now show that memory is also expressed as an increased bias to reject even a nonfood object. The increased bias to rejection is partially explained by changes in synaptic connections from primary mechanoafferents to five follower neurons with well defined roles in producing different feeding behaviors. Previously, these mechanoafferents had been shown to play a role in memory consolidation. Connectivity changes differed for each follower neuron: the probability that cells were connected changed; excitation changed to inhibition and vice versa; and connection amplitude changed. Thus, multiple neural changes at different sites underlie specific aspects of a coordinated behavioral change. Changes in the connectivity between mechanoafferents and their followers cannot account for all of the behavioral changes expressed after learning, indicating that additional synaptic sites are also changed. Access to the circuit controlling feeding can help determine the logic and cellular mechanisms by which multiple local synaptic changes produce an integrated, global change in behavior.SIGNIFICANCE STATEMENT How do local changes in synapses affect global behavior? Studies on invertebrate preparations usually examine synaptic changes at specific neural sites, producing a specific behavioral change. However, memory may be expressed by multiple behavioral changes. We report that a change in behavior after learning in Aplysia is accomplished, in part, by regulating connections between mechanoafferents and their synaptic followers. For some followers, the connection probabilities change; for others, the connection signs are reversed; in others, the connection strength is modified. Thus, learning produces changes in connectivity at multiple sites, via multiple synaptic mechanisms that are consistent with the observed behavioral change.
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13
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Abstract
The neurotransmitter gamma-aminobutyric acid (GABA) is widely distributed in the mammalian central nervous system, where it acts as a major mediator of synaptic inhibition. GABA also serves as a neurotransmitter in a range of invertebrate phyla, including arthropods, echinoderms, annelids, nematodes, and platyhelminthes. This article reviews evidence supporting the neurotransmitter role of GABA in gastropod molluscs, with an emphasis on its presence in identified neurons and well-characterized neural circuits. The collective findings indicate that GABAergic signaling participates in the selection and specification of motor programs, as well as the bilateral coordination of motor circuits. While relatively few in number, GABAergic neurons can influence neural circuits via inhibitory, excitatory, and modulatory synaptic actions. GABA's colocalization with peptidergic and classical neurotransmitters can broaden its integrative capacity. The functional properties of GABAergic neurons in simpler gastropod systems may provide insight into the role of this neurotransmitter phenotype in more complex brains.
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Key Words
- BCI, buccal-cerebral interneuron
- CBC, cerebral-buccal connective
- CBI, cerebral-buccal interneuron
- CNS, central nervous system
- CPG, central pattern generator
- Cr-Aint, cerebral A interneuron
- DA, dopamine
- EPSP, excitatory postsynaptic potential
- FCAP, feeding circuit activating peptide
- GABA, gamma-aminobutyric acid
- GABAli, GABA-like immunoreactivity
- IPSP, inhibitory postsynaptic potential
- PKC, protein kinase C
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Affiliation(s)
- MARK W. MILLER
- Institute of Neurobiology and Department of Anatomy and Neurobiology, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico 00901
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14
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Cropper EC, Jing J, Vilim FS, Barry MA, Weiss KR. Multifaceted Expression of Peptidergic Modulation in the Feeding System of Aplysia. ACS Chem Neurosci 2018; 9:1917-1927. [PMID: 29309115 DOI: 10.1021/acschemneuro.7b00447] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Neuropeptides are present in species throughout the animal kingdom and generally exert actions that are distinct from those of small molecule transmitters. It has, therefore, been of interest to define the unique behavioral role of this class of substances. Progress in this regard has been made in experimentally advantageous invertebrate preparations. We focus on one such system, the feeding circuit in the mollusc Aplysia. We review research conducted over several decades that played an important role in establishing that peptide cotransmitters are released under behaviorally relevant conditions. We describe how this was accomplished. For example, we describe techniques developed to purify novel peptides, localize them to identified neurons, and detect endogenous peptide release. We also describe physiological experiments that demonstrated that peptides are bioactive under behaviorally relevant conditions. The feeding system is like others in that peptides exert effects that are both convergent and divergent. Work in the feeding system clearly illustrates how this creates potential for behavioral flexibility. Finally, we discuss experiments that determined physiological consequences of one of the hallmark features of peptidergic modulation, its persistence. Research in the feeding system demonstrated that this persistence can change network state and play an important role in determining network output.
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Affiliation(s)
- Elizabeth C. Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York 10029, United States
| | - Jian Jing
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York 10029, United States
- State Key Laboratory of Pharmaceutical Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Ferdinand S. Vilim
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York 10029, United States
| | - Michael A. Barry
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York 10029, United States
| | - Klaudiusz R. Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York 10029, United States
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15
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Zhang G, Vilim FS, Liu DD, Romanova EV, Yu K, Yuan WD, Xiao H, Hummon AB, Chen TT, Alexeeva V, Yin SY, Chen SA, Cropper EC, Sweedler JV, Weiss KR, Jing J. Discovery of leucokinin-like neuropeptides that modulate a specific parameter of feeding motor programs in the molluscan model, Aplysia. J Biol Chem 2017; 292:18775-18789. [PMID: 28924050 DOI: 10.1074/jbc.m117.795450] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 08/31/2017] [Indexed: 12/12/2022] Open
Abstract
A better understanding of neuromodulation in a behavioral system requires identification of active modulatory transmitters. Here, we used identifiable neurons in a neurobiological model system, the mollusc Aplysia, to study neuropeptides, a diverse class of neuromodulators. We took advantage of two types of feeding neurons, B48 and B1/B2, in the Aplysia buccal ganglion that might contain different neuropeptides. We performed a representational difference analysis (RDA) by subtraction of mRNAs in B48 versus mRNAs in B1/B2. The RDA identified an unusually long (2025 amino acids) peptide precursor encoding Aplysia leucokinin-like peptides (ALKs; e.g. ALK-1 and ALK-2). Northern blot analysis revealed that, compared with other ganglia (e.g. the pedal-pleural ganglion), ALK mRNA is predominantly present in the buccal ganglion, which controls feeding behavior. We then used in situ hybridization and immunohistochemistry to localize ALKs to specific neurons, including B48. MALDI-TOF MS on single buccal neurons revealed expression of 40 ALK precursor-derived peptides. Among these, ALK-1 and ALK-2 are active in the feeding network; they shortened the radula protraction phase of feeding motor programs triggered by a command-like neuron. We also found that this effect may be mediated by the ALK-stimulated enhancement of activity of an interneuron, which has previously been shown to terminate protraction. We conclude that our multipronged approach is effective for determining the structure and defining the diverse functions of leucokinin-like peptides. Notably, the ALK precursor is the first verified nonarthropod precursor for leucokinin-like peptides with a novel, marked modulatory effect on a specific parameter (protraction duration) of feeding motor programs.
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Affiliation(s)
- Guo Zhang
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ferdinand S Vilim
- the Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, and
| | - Dan-Dan Liu
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Elena V Romanova
- the Beckman Institute for Advanced Science and Technology and Department of Chemistry, University of Illinois, Urbana, Illinois 61801
| | - Ke Yu
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Wang-Ding Yuan
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Hui Xiao
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Amanda B Hummon
- the Beckman Institute for Advanced Science and Technology and Department of Chemistry, University of Illinois, Urbana, Illinois 61801
| | - Ting-Ting Chen
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Vera Alexeeva
- the Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, and
| | - Si-Yuan Yin
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Song-An Chen
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Elizabeth C Cropper
- the Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, and
| | - Jonathan V Sweedler
- the Beckman Institute for Advanced Science and Technology and Department of Chemistry, University of Illinois, Urbana, Illinois 61801
| | - Klaudiusz R Weiss
- the Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, and
| | - Jian Jing
- From the State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China, .,the Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, and
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16
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Neveu CL, Costa RM, Homma R, Nagayama S, Baxter DA, Byrne JH. Unique Configurations of Compression and Truncation of Neuronal Activity Underlie l-DOPA-Induced Selection of Motor Patterns in Aplysia. eNeuro 2017; 4:ENEURO.0206-17.2017. [PMID: 29071298 PMCID: PMC5654236 DOI: 10.1523/eneuro.0206-17.2017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 09/05/2017] [Accepted: 09/28/2017] [Indexed: 12/29/2022] Open
Abstract
A key issue in neuroscience is understanding the ways in which neuromodulators such as dopamine modify neuronal activity to mediate selection of distinct motor patterns. We addressed this issue by applying either low or high concentrations of l-DOPA (40 or 250 μM) and then monitoring activity of up to 130 neurons simultaneously in the feeding circuitry of Aplysia using a voltage-sensitive dye (RH-155). l-DOPA selected one of two distinct buccal motor patterns (BMPs): intermediate (low l-DOPA) or bite (high l-DOPA) patterns. The selection of intermediate BMPs was associated with shortening of the second phase of the BMP (retraction), whereas the selection of bite BMPs was associated with shortening of both phases of the BMP (protraction and retraction). Selection of intermediate BMPs was also associated with truncation of individual neuron spike activity (decreased burst duration but no change in spike frequency or burst latency) in neurons active during retraction. In contrast, selection of bite BMPs was associated with compression of spike activity (decreased burst latency and duration and increased spike frequency) in neurons projecting through specific nerves, as well as increased spike frequency of protraction neurons. Finally, large-scale voltage-sensitive dye recordings delineated the spatial distribution of neurons active during BMPs and the modification of that distribution by the two concentrations of l-DOPA.
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Affiliation(s)
- Curtis L Neveu
- Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX 77030
| | - Renan M Costa
- Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX 77030
| | - Ryota Homma
- Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX 77030
| | - Shin Nagayama
- Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX 77030
| | - Douglas A Baxter
- Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX 77030
| | - John H Byrne
- Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX 77030
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17
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Cropper EC, Jing J, Perkins MH, Weiss KR. Use of the Aplysia feeding network to study repetition priming of an episodic behavior. J Neurophysiol 2017; 118:1861-1870. [PMID: 28679841 DOI: 10.1152/jn.00373.2017] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 06/21/2017] [Accepted: 06/21/2017] [Indexed: 02/06/2023] Open
Abstract
Many central pattern generator (CPG)-mediated behaviors are episodic, meaning that they are not continuously ongoing; instead, there are pauses between bouts of activity. This raises an interesting possibility, that the neural networks that mediate these behaviors are not operating under "steady-state" conditions; i.e., there could be dynamic changes in motor activity as it stops and starts. Research in the feeding system of the mollusk Aplysia californica has demonstrated that this can be the case. After a pause, initial food grasping responses are relatively weak. With repetition, however, responses strengthen. In this review we describe experiments that have characterized cellular/molecular mechanisms that produce these changes in motor activity. In particular, we focus on cumulative effects of modulatory neuropeptides. Furthermore, we relate Aplysia research to work in other systems and species, and develop a hypothesis that postulates that changes in response magnitude are a reflection of an efficient feeding strategy.
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Affiliation(s)
- Elizabeth C Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; and
| | - Jian Jing
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; and.,State Key Laboratory of Pharmaceutical Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Matthew H Perkins
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; and
| | - Klaudiusz R Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York; and
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18
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Siniscalchi MJ, Cropper EC, Jing J, Weiss KR. Repetition priming of motor activity mediated by a central pattern generator: the importance of extrinsic vs. intrinsic program initiators. J Neurophysiol 2016; 116:1821-1830. [PMID: 27466134 DOI: 10.1152/jn.00365.2016] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 07/23/2016] [Indexed: 12/28/2022] Open
Abstract
Repetition priming is characterized by increased performance as a behavior is repeated. Although this phenomenon is ubiquitous, mediating mechanisms are poorly understood. We address this issue in a model system, the feeding network of Aplysia This network generates both ingestive and egestive motor programs. Previous data suggest a chemical coding model: ingestive and egestive inputs to the feeding central pattern generator (CPG) release different modulators, which act via different second messengers to prime motor activity in different ways. The ingestive input to the CPG (neuron CBI-2) releases the peptides feeding circuit activating peptide and cerebral peptide 2, which produce an ingestive pattern of activity. The egestive input to the CPG (the esophageal nerve) releases the peptide small cardioactive peptide. This model is based on research that focused on a single aspect of motor control (radula opening). Here we ask whether repetition priming is observed if activity is triggered with a neuron within the core CPG itself and demonstrate that it is not. Moreover, previous studies demonstrated that effects of modulatory neurotransmitters that induce repetition priming persist. This suggests that it should be possible to "prime" motor programs triggered from within the CPG by first stimulating extrinsic modulatory inputs. We demonstrate that programs triggered after ingestive input activation are ingestive and programs triggered after egestive input activation are egestive. We ask where this priming occurs and demonstrate modifications within the CPG itself. This arrangement is likely to have important consequences for "task" switching, i.e., the cessation of one type of motor activity and the initiation of another.
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Affiliation(s)
- Michael J Siniscalchi
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Elizabeth C Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jian Jing
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Klaudiusz R Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
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19
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Yang CY, Yu K, Wang Y, Chen SA, Liu DD, Wang ZY, Su YN, Yang SZ, Chen TT, Livnat I, Vilim FS, Cropper EC, Weiss KR, Sweedler JV, Jing J. Aplysia Locomotion: Network and Behavioral Actions of GdFFD, a D-Amino Acid-Containing Neuropeptide. PLoS One 2016; 11:e0147335. [PMID: 26796097 PMCID: PMC4721866 DOI: 10.1371/journal.pone.0147335] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2015] [Accepted: 01/01/2016] [Indexed: 12/02/2022] Open
Abstract
One emerging principle is that neuromodulators, such as neuropeptides, regulate multiple behaviors, particularly motivated behaviors, e.g., feeding and locomotion. However, how neuromodulators act on multiple neural networks to exert their actions remains poorly understood. These actions depend on the chemical form of the peptide, e.g., an alternation of L- to D- form of an amino acid can endow the peptide with bioactivity, as is the case for the Aplysia peptide GdFFD (where dF indicates D-phenylalanine). GdFFD has been shown to act as an extrinsic neuromodulator in the feeding network, while the all L-amino acid form, GFFD, was not bioactive. Given that both GdFFD/GFFD are also present in pedal neurons that mediate locomotion, we sought to determine whether they impact locomotion. We first examined effects of both peptides on isolated ganglia, and monitored fictive programs using the parapedal commissural nerve (PPCN). Indeed, GdFFD was bioactive and GFFD was not. GdFFD increased the frequency with which neural activity was observed in the PPCN. In part, there was an increase in bursting spiking activity that resembled fictive locomotion. Additionally, there was significant activity between bursts. To determine how the peptide-induced activity in the isolated CNS is translated into behavior, we recorded animal movements, and developed a computer program to automatically track the animal and calculate the path of movement and velocity of locomotion. We found that GdFFD significantly reduced locomotion and induced a foot curl. These data suggest that the increase in PPCN activity observed in the isolated CNS during GdFFD application corresponds to a reduction, rather than an increase, in locomotion. In contrast, GFFD had no effect. Thus, our study suggests that GdFFD may act as an intrinsic neuromodulator in the Aplysia locomotor network. More generally, our study indicates that physiological and behavioral analyses should be combined to evaluate peptide actions.
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Affiliation(s)
- Chao-Yu Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Ke Yu
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Ye Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Song-An Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Dan-Dan Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Zheng-Yang Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Yan-Nan Su
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Shao-Zhong Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Ting-Ting Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
| | - Itamar Livnat
- Beckman Institute for Advanced Science and Technology and Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Ferdinand S. Vilim
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Elizabeth C. Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Klaudiusz R. Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Jonathan V. Sweedler
- Beckman Institute for Advanced Science and Technology and Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Collaborative Innovation Center of Chemistry for Life Sciences, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- * E-mail:
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20
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Abstract
We investigate stimulus specificity of repetition priming in a tractable model system; the feeding network of Aplysia. Previous studies primarily focused on an aspect of behavior that is altered during ingestive priming, radula opening. Priming of radula opening occurs when two modulatory peptides [feeding circuit activating peptide (FCAP) and cerebral peptide-2 (CP-2)] are released from the cholinergic command-like neuron cerebral buccal interneuron 2. Effects of FCAP/CP-2 on radula opening motor neurons are cAMP mediated. The present experiments sought to determine whether FCAP/CP-2 and cAMP are also involved in the priming of radula opening during an incompatible activity, i.e., during egestive motor programs. Egestive priming is induced when motor programs are triggered by afferents with processes in the esophageal nerve. We demonstrate that egestive priming is not FCAP/CP-2 mediated. Instead, it is induced by an unrelated peptide (small cardioactive peptide), which exerts PKC-mediated effects. Our data, therefore, suggest that different feeding motor programs are primed via actions of different sets of intercellular and intracellular substances. We suggest that this accounts for the stimulus specificity that can be characteristic of repetition priming. Different stimuli activate different central pattern generator inputs. These inputs release different modulators, which induce functionally distinct motor programs.
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21
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Sakurai A, Gunaratne CA, Katz PS. Two interconnected kernels of reciprocally inhibitory interneurons underlie alternating left-right swim motor pattern generation in the mollusk Melibe leonina. J Neurophysiol 2014; 112:1317-28. [PMID: 24920032 DOI: 10.1152/jn.00261.2014] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The central pattern generator (CPG) underlying the rhythmic swimming behavior of the nudibranch Melibe leonina (Mollusca, Gastropoda, Heterobranchia) has been described as a simple half-center oscillator consisting of two reciprocally inhibitory pairs of interneurons called swim interneuron 1 (Si1) and swim interneuron 2 (Si2). In this study, we identified two additional pairs of interneurons that are part of the swim CPG: swim interneuron 3 (Si3) and swim interneuron 4 (Si4). The somata of Si3 and Si4 were both located in the pedal ganglion, near that of Si2, and both had axons that projected through the pedal commissure to the contralateral pedal ganglion. These neurons fulfilled the criteria for inclusion as members of the swim CPG: 1) they fired at a fixed phase in relation to Si1 and Si2, 2) brief changes in their activity reset the motor pattern, 3) prolonged changes in their activity altered the periodicity of the motor pattern, 4) they had monosynaptic connections with each other and with Si1 and Si2, and 5) their synaptic actions helped explain the phasing of the motor pattern. The results of this study show that the motor pattern has more complex internal dynamics than a simple left/right alternation of firing; the CPG circuit appears to be composed of two kernels of reciprocally inhibitory neurons, one consisting of Si1, Si2, and the contralateral Si4 and the other consisting of Si3. These two kernels interact with each other to produce a stable rhythmic motor pattern.
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Affiliation(s)
- Akira Sakurai
- Neuroscience Institute, Georgia State University, Atlanta, Georgia
| | | | - Paul S Katz
- Neuroscience Institute, Georgia State University, Atlanta, Georgia
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22
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Sakurai A, Tamvacakis AN, Katz PS. Hidden synaptic differences in a neural circuit underlie differential behavioral susceptibility to a neural injury. eLife 2014; 3. [PMID: 24920390 PMCID: PMC4084405 DOI: 10.7554/elife.02598] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Accepted: 06/09/2014] [Indexed: 12/19/2022] Open
Abstract
Individuals vary in their responses to stroke and trauma, hampering predictions of outcomes. One reason might be that neural circuits contain hidden variability that becomes relevant only when those individuals are challenged by injury. We found that in the mollusc, Tritonia diomedea, subtle differences between animals within the neural circuit underlying swimming behavior had no behavioral relevance under normal conditions but caused differential vulnerability of the behavior to a particular brain lesion. The extent of motor impairment correlated with the site of spike initiation in a specific neuron in the neural circuit, which was determined by the strength of an inhibitory synapse onto this neuron. Artificially increasing or decreasing this inhibitory synaptic conductance with dynamic clamp correspondingly altered the extent of motor impairment by the lesion without affecting normal operation. The results suggest that neural circuit differences could serve as hidden phenotypes for predicting the behavioral outcome of neural damage.
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Affiliation(s)
- Akira Sakurai
- Neuroscience Institute, Georgia State University, Atlanta, United States
| | | | - Paul S Katz
- Neuroscience Institute, Georgia State University, Atlanta, United States
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23
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Wu JS, Wang N, Siniscalchi MJ, Perkins MH, Zheng YT, Yu W, Chen SA, Jia RN, Gu JW, Qian YQ, Ye Y, Vilim FS, Cropper EC, Weiss KR, Jing J. Complementary interactions between command-like interneurons that function to activate and specify motor programs. J Neurosci 2014; 34:6510-6521. [PMID: 24806677 PMCID: PMC4012310 DOI: 10.1523/jneurosci.5094-13.2014] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2013] [Revised: 03/13/2014] [Accepted: 03/31/2014] [Indexed: 11/21/2022] Open
Abstract
Motor activity is often initiated by a population of command-like interneurons. Command-like interneurons that reliably drive programs have received the most attention, so little is known about how less reliable command-like interneurons may contribute to program generation. We study two electrically coupled interneurons, cerebral-buccal interneuron-2 (CBI-2) and CBI-11, which activate feeding motor programs in the mollusk Aplysia californica. Earlier work indicated that, in rested preparations, CBI-2, a powerful activator of programs, can trigger ingestive and egestive programs. CBI-2 reliably generated ingestive patterns only when it was repeatedly stimulated. The ability of CBI-2 to trigger motor activity has been attributed to the two program-promoting peptides it contains, FCAP and CP2. Here, we show that CBI-11 differs from CBI-2 in that it contains FCAP but not CP2. Furthermore, it is weak in its ability to drive programs. On its own, CBI-11 is therefore less effective as a program activator. When it is successful, however, CBI-11 is an effective specifier of motor activity; that is, it drives mostly ingestive programs. Importantly, we found that CBI-2 and CBI-11 complement each other's actions. First, prestimulation of CBI-2 enhanced the ability of CBI-11 to drive programs. This effect appears to be partly mediated by CP2. Second, coactivation of CBI-11 with CBI-2 makes CBI-2 programs immediately ingestive. This effect may be mediated by specific actions that CBI-11 exerts on pattern-generating interneurons. Therefore, different classes of command-like neurons in a motor network may make distinct, but potentially complementary, contributions as either activators or specifiers of motor activity.
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Affiliation(s)
- Jin-Sheng Wu
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
| | - Nan Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Michael J. Siniscalchi
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
| | - Matthew H. Perkins
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
| | - Yu-Tong Zheng
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Wei Yu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Song-an Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Ruo-nan Jia
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Jia-Wei Gu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Yi-Qing Qian
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Yang Ye
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
| | - Ferdinand S. Vilim
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
| | - Elizabeth C. Cropper
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
| | - Klaudiusz R. Weiss
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
| | - Jian Jing
- Department of Neuroscience and Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York 10029, and
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Jiangsu 210093, China
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24
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Premotor spinal network with balanced excitation and inhibition during motor patterns has high resilience to structural division. J Neurosci 2014; 34:2774-84. [PMID: 24553920 DOI: 10.1523/jneurosci.3349-13.2014] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Direct measurements of synaptic inhibition (I) and excitation (E) to spinal motoneurons can provide an important insight into the organization of premotor networks. Such measurements of flexor motoneurons participating in motor patterns in turtles have recently demonstrated strong concurrent E and I as well as stochastic membrane potentials and irregular spiking in the adult turtle spinal cord. These findings represent a departure from the widespread acceptance of feedforward reciprocal rate models for spinal motor function. The apparent discrepancy has been reviewed as an experimental artifact caused by the distortion of local networks in the transected turtle spinal cord. We tested this assumption in the current study by performing experiments to assess the integrity of motor functions in the intact spinal cord and the cord transected at segments D9/D10. Excitatory and inhibitory synaptic inputs to motoneurons were estimated during rhythmic motor activity and demonstrated primarily intense inputs that consisted of qualitatively similar mixed E/I before and after the transection. To understand this high functional resilience, we used mathematical modeling of networks with recurrent connectivity that could potentially explain the balanced E/I. Both experimental and modeling data support the concept of a locally balanced premotor network consisting of recurrent E/I connectivity, in addition to the well known reciprocal network activity. The multifaceted synaptic connections provide spinal networks with a remarkable ability to remain functional after structural divisions.
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Berg RW, Ditlevsen S. Synaptic inhibition and excitation estimated via the time constant of membrane potential fluctuations. J Neurophysiol 2013; 110:1021-34. [DOI: 10.1152/jn.00006.2013] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
When recording the membrane potential, V, of a neuron it is desirable to be able to extract the synaptic input. Critically, the synaptic input is stochastic and nonreproducible so one is therefore often restricted to single-trial data. Here, we introduce means of estimating the inhibition and excitation and their confidence limits from single sweep trials. The estimates are based on the mean membrane potential, V̄, and the membrane time constant, τ. The time constant provides the total conductance ( G = capacitance/τ) and is extracted from the autocorrelation of V. The synaptic conductances can then be inferred from V̄ when approximating the neuron as a single compartment. We further employ a stochastic model to establish limits of confidence. The method is verified on models and experimental data, where the synaptic input is manipulated pharmacologically or estimated by an alternative method. The method gives best results if the synaptic input is large compared with other conductances, the intrinsic conductances have little or no time dependence or are comparably small, the ligand-gated kinetics is faster than the membrane time constant, and the majority of synaptic contacts are electrotonically close to soma (recording site). Although our data are in current clamp, the method also works in V-clamp recordings, with some minor adaptations. All custom made procedures are provided in Matlab.
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Affiliation(s)
- Rune W. Berg
- Faculty of Health Sciences, Department of Neuroscience and Pharmacology, University of Copenhagen, Denmark; and
| | - Susanne Ditlevsen
- Department of Mathematical Sciences, University of Copenhagen, Denmark
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26
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Removal of default state-associated inhibition during repetition priming improves response articulation. J Neurosci 2013; 32:17740-52. [PMID: 23223294 DOI: 10.1523/jneurosci.4137-12.2012] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Behavior is a product of both the stimuli encountered and the current internal state. At the level of the nervous system, the internal state alters the biophysical properties of, and connections between, neurons establishing a "network state." To establish a network state, the nervous system must be altered from an initial default/resting state, but what remains unclear is the extent to which this process represents induction from a passive default state or the removal of suppression by an active default state. We use repetition priming (a history-dependent improvement of behavioral responses to repeatedly encountered stimuli) to determine the cellular mechanisms underlying the transition from the default to the primed network state. We demonstrate that both removal of active suppression and induction of neuron excitability changes each contribute separately to the production of a primed state. The feeding system of Aplysia californica displays repetition priming via an increase in the activity of the radula closure neuron B8, which results in increased bite strength with each motor program. We found that during priming, B8 received progressively less inhibitory input from the multifunctional neurons B4/5. Additionally, priming enhanced the excitability of B8, but the rate at which B8 activity increased as a result of these changes was regulated by the progressive removal of inhibitory input. Thus, the establishment of the network state involves the induction of processes from a rested state, yet the consequences of these processes are conditional upon critical gating mechanisms actively enforced by the default state.
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Functional differentiation of a population of electrically coupled heterogeneous elements in a microcircuit. J Neurosci 2013; 33:93-105. [PMID: 23283325 DOI: 10.1523/jneurosci.3841-12.2013] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Although electrical coupling is present in many microcircuits, the extent to which it will determine neuronal firing patterns and network activity remains poorly understood. This is particularly true when the coupling is present in a population of heterogeneous, or intrinsically distinct, circuit elements. We examine this question in the Aplysia californica feeding motor network in five electrically coupled identified cells, B64, B4/5, B70, B51, and a newly identified interneuron B71. These neurons exhibit distinct activity patterns during the radula retraction phase of motor programs. In a subset of motor programs, retraction can be flexibly extended by adding a phase of network activity (hyper-retraction). This is manifested most prominently as an additional burst in the radula closure motoneuron B8. Two neurons that excite B8 (B51 and B71) and one that inhibits it (B70) are active during hyper-retraction. Consistent with their near synchronous firing, B51 and B71 showed one of the strongest coupling ratios in this group of neurons. Nonetheless, by manipulating their activity, we found that B51 preferentially acted as a driver of B64/B71 activity, whereas B71 played a larger role in driving B8 activity. In contrast, B70 was weakly coupled to other neurons and its inhibition of B8 counteracted the excitatory drive to B8. Finally, the distinct firing patterns of the electrically coupled neurons were fine-tuned by their intrinsic properties and the largely chemical cross-inhibition between some of them. Thus, the small microcircuit of the Aplysia feeding network is advantageous in understanding how a population of electrically coupled heterogeneous neurons may fulfill specific network functions.
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Dacks AM, Weiss KR. Release of a single neurotransmitter from an identified interneuron coherently affects motor output on multiple time scales. J Neurophysiol 2013; 109:2327-34. [PMID: 23407357 DOI: 10.1152/jn.01079.2012] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Neurotransmitters can have diverse effects that occur over multiple time scales often making the consequences of neurotransmission difficult to predict. To explore the consequences of this diversity, we used the buccal ganglion of Aplysia to examine the effects of GABA release by a single interneuron, B40, on the intrinsic properties and motor output of the radula closure neuron B8. B40 induces a picrotoxin-sensitive fast IPSP lasting milliseconds in B8 and a slow EPSP lasting seconds. We found that the excitatory effects of this slow EPSP are also mediated by GABA. Together, these two GABAergic actions structure B8 firing in a pattern characteristic of ingestive programs. Furthermore, we found that repeated B40 stimulation induces a persistent increase in B8 excitability that was occluded in the presence of the GABA B receptor agonist baclofen, suggesting that GABA affects B8 excitability over multiple time scales. The phasing of B8 activity during the feeding motor programs determines the nature of the behavior elicited during that motor program. The persistent increase in B8 excitability induced by B40 biased the activity of B8 during feeding motor programs causing the motor programs to become more ingestive in nature. Thus, a single transmitter released from a single interneuron can have consequences for motor output that are expressed over multiple time scales. Importantly, despite the differences in their signs and temporal characteristics, the three actions of B40 are coherent in that they promote B8 firing patterns that are characteristic of ingestive motor outputs.
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Affiliation(s)
- Andrew M Dacks
- Department of Neuroscience, Mount Sinai School of Medicine, New York, NY, USA.
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29
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Romanova EV, Sasaki K, Alexeeva V, Vilim FS, Jing J, Richmond TA, Weiss KR, Sweedler JV. Urotensin II in invertebrates: from structure to function in Aplysia californica. PLoS One 2012; 7:e48764. [PMID: 23144960 PMCID: PMC3493602 DOI: 10.1371/journal.pone.0048764] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2012] [Accepted: 10/05/2012] [Indexed: 02/07/2023] Open
Abstract
Neuropeptides are ancient signaling molecules that are involved in many aspects of organism homeostasis and function. Urotensin II (UII), a peptide with a range of hormonal functions, previously has been reported exclusively in vertebrates. Here, we provide the first direct evidence that UII-like peptides are also present in an invertebrate, specifically, the marine mollusk Aplysia californica. The presence of UII in the central nervous system (CNS) of Aplysia implies a more ancient gene lineage than vertebrates. Using representational difference analysis, we identified an mRNA of a protein precursor that encodes a predicted neuropeptide, we named Aplysia urotensin II (apUII), with a sequence and structural similarity to vertebrate UII. With in-situ hybridization and immunohistochemistry, we mapped the expression of apUII mRNA and its prohormone in the CNS and localized apUII-like immunoreactivity to buccal sensory neurons and cerebral A-cluster neurons. Mass spectrometry performed on individual isolated neurons, and tandem mass spectrometry on fractionated peptide extracts, allowed us to define the posttranslational processing of the apUII neuropeptide precursor and confirm the highly conserved cyclic nature of the mature neuropeptide apUII. Electrophysiological analysis of the central effects of a synthetic apUII suggests it plays a role in satiety and/or aversive signaling in feeding behaviors. Finding the homologue of vertebrate UII in the numerically small CNS of an invertebrate animal model is important for gaining insights into the molecular mechanisms and pathways mediating the bioactivity of UII in the higher metazoan.
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Affiliation(s)
- Elena V. Romanova
- Beckman Institute for Advanced Science and Technology and the Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Kosei Sasaki
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Vera Alexeeva
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Ferdinand S. Vilim
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Jian Jing
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Timothy A. Richmond
- Beckman Institute for Advanced Science and Technology and the Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Klaudiusz R. Weiss
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Jonathan V. Sweedler
- Beckman Institute for Advanced Science and Technology and the Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- * E-mail:
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30
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Nargeot R, Simmers J. Functional organization and adaptability of a decision-making network in aplysia. Front Neurosci 2012; 6:113. [PMID: 22855670 PMCID: PMC3405415 DOI: 10.3389/fnins.2012.00113] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2012] [Accepted: 07/08/2012] [Indexed: 12/31/2022] Open
Abstract
Whereas major insights into the neuronal basis of adaptive behavior have been gained from the study of automatic behaviors, including reflexive and rhythmic motor acts, the neural substrates for goal-directed behaviors in which decision-making about action selection and initiation are crucial, remain poorly understood. However, the mollusk Aplysia is proving to be increasingly relevant to redressing this issue. The functional properties of the central circuits that govern this animal’s goal-directed feeding behavior and particularly the neural processes underlying the selection and initiation of specific feeding actions are becoming understood. In addition to relying on the intrinsic operation of central networks, goal-directed behaviors depend on external sensory inputs that through associative learning are able to shape decision-making strategies. Here, we will review recent findings on the functional design of the central network that generates Aplysia’s feeding-related movements and the sensory-derived plasticity that through learning can modify the selection and initiation of appropriate action. The animal’s feeding behavior and the implications of decision-making will be briefly described. The functional design of the underlying buccal network will then be used to illustrate how cellular diversity and the coordination of neuronal burst activity provide substrates for decision-making. The contribution of specific synaptic and neuronal membrane properties within the buccal circuit will also be discussed in terms of their role in motor pattern selection and initiation. The ability of learning to “rigidify” these synaptic and cellular properties so as to regularize network operation and lead to the expression of stereotyped rhythmic behavior will then be described. Finally, these aspects will be drawn into a conceptual framework of how Aplysia’s goal-directed circuitry compares to the central pattern generating networks for invertebrate rhythmic behaviors.
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Affiliation(s)
- Romuald Nargeot
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Université Bordeaux, UMR 5287 Bordeaux, France
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31
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Coordination of distinct motor structures through remote axonal coupling of projection interneurons. J Neurosci 2011; 31:15438-49. [PMID: 22031890 DOI: 10.1523/jneurosci.3741-11.2011] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Complex behaviors often require coordinated movements of dissimilar motor structures. The underlying neural mechanisms are poorly understood. We investigated cycle-by-cycle coordination of two dissimilar feeding structures in Aplysia californica: the external lips and the internal radula. During feeding, the lips open while the radula protracts. Lip and radula motoneurons are located in the cerebral and buccal ganglia, respectively, and radula motoneurons are controlled by a well characterized buccal central pattern generator (CPG). Here, we examined whether the three electrically coupled lip motoneurons C15/16/17 are controlled by the buccal CPG or by a previously postulated cerebral CPG. Two buccal-cerebral projection interneurons, B34 and B63, which are part of the buccal CPG and mediate radula protraction, monosynaptically excite C15/16/17. Recordings from the B34 axon in the cerebral ganglion demonstrate its direct electrical coupling with C15/16/17, eliminating the need for a cerebral CPG. Moreover, when the multifunctional buccal CPG generates multiple forms of motor programs due to the activation of two inputs, the command-like neuron CBI-2 and the esophageal nerve (EN), C15/16 exhibit activity patterns that are distinct from C17. These distinct activity patterns result from combined activity of B34 and B63 and their differential excitation of C15/16 versus C17. In more general terms, we identified neuronal mechanisms that allow a single CPG to coordinate the phasing and activity of remotely located motoneurons innervating distinct structures that participate in the production of different motor outputs. We also demonstrated that axodendritic electrical coupling by projection interneurons plays a pivotal role in coordinating activity of these remotely located neurons.
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Abstract
Rhythmically active motor circuits can generate different activity patterns in response to different inputs. In most systems, however, it is not known whether the same neurons generate the underlying rhythm for each different pattern. Thus far, information regarding the degree of conservation of rhythm generator neurons is limited to a few pacemaker-driven circuits, in most of which the core rhythm generator is unchanged across different output patterns. We are addressing this issue in the network-driven, gastric mill (chewing) circuit in the crab stomatogastric nervous system. We first establish that distinct gastric mill motor patterns are triggered by separate stimulation of two extrinsic input pathways, the ventral cardiac neurons (VCNs) and postoesophageal commissure (POC) neurons. A prominent feature that distinguishes these gastric mill motor patterns is the LG (lateral gastric) protractor motor neuron activity pattern, which is tonic during the VCN rhythm and exhibits fast rhythmic bursting during the POC rhythm. These two motor patterns also differed in their cycle period and some motor neuron phase relationships, duty cycles, and burst durations. Despite the POC and VCN motor patterns being distinct, rhythm generation during each motor pattern required the activity of the same two, reciprocally inhibitory gastric mill neurons [LG, Int1 (interneuron 1)]. Specifically, reversibly hyperpolarizing LG or Int1, but no other gastric mill neuron, delayed the start of the next gastric mill cycle until after the imposed hyperpolarization. Thus, the same circuit neurons can comprise the core rhythm generator during different versions of a network-driven rhythmic motor pattern.
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Abstract
Noise and variability are fundamental companions to ion channels and synapses and thus inescapable elements of brain function. The overriding unresolved issue is to what extent noise distorts and limits signaling on one hand and at the same time constitutes a crucial and fundamental enrichment that allows and facilitates complex adaptive behavior in an unpredictable world. Here we review the growing experimental evidence that functional network activity is associated with intense fluctuations in membrane potential and spike timing. We trace origins and consequences of noise and variability. Finally, we discuss noise-free neuronal signaling and detrimental and beneficial forms of noise in large-scale functional neural networks. Evidence that noise and variability in some cases go hand in hand with behavioral variability and increase behavioral choice, richness, and adaptability opens new avenues for future studies.
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Affiliation(s)
- Yosef Yarom
- Department of Neurobiology, Life Science Institute, The Edmond & Liliy Safra Centre for Brain Sciences, Hebrew University, Jerusalem, Israel
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34
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Feedforward compensation mediated by the central and peripheral actions of a single neuropeptide discovered using representational difference analysis. J Neurosci 2011; 30:16545-58. [PMID: 21147994 DOI: 10.1523/jneurosci.4264-10.2010] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Compensatory mechanisms are often used to achieve stability by reducing variance, which can be accomplished via negative feedback during homeostatic regulation. In principle, compensation can also be implemented through feedforward mechanisms where a regulator acts to offset the anticipated output variation; however, few such neural mechanisms have been demonstrated. We provide evidence that an Aplysia neuropeptide, identified using an enhanced representational difference analysis procedure, implements feedforward compensation within the feeding network. We named the novel peptide "allatotropin-related peptide" (ATRP) because of its similarity to insect allatotropin. Mass spectrometry confirmed the peptide's identity, and in situ hybridization and immunostaining mapped its distribution in the Aplysia CNS. ATRP is present in the higher-order cerebral-buccal interneuron (CBI) CBI-4, but not in CBI-2. Previous work showed that CBI-4-elicited motor programs have a shorter protraction duration than those elicited by CBI-2. Here we show that ATRP shortens protraction duration of CBI-2-elicited ingestive programs, suggesting a contribution of ATRP to the parametric differences between CBI-4-evoked and CBI-2-evoked programs. Importantly, because Aplysia muscle contractions are a graded function of motoneuronal activity, one consequence of the shortening of protraction is that it can weaken protraction movements. However, this potential weakening is offset by feedforward compensatory actions exerted by ATRP. Centrally, ATRP increases the activity of protraction motoneurons. Moreover, ATRP is present in peripheral varicosities of protraction motoneurons and enhances peripheral motoneuron-elicited protraction muscle contractions. Therefore, feedforward compensatory mechanisms mediated by ATRP make it possible to generate a faster movement with an amplitude that is not greatly reduced, thereby producing stability.
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Repetition priming of motoneuronal activity in a small motor network: intercellular and intracellular signaling. J Neurosci 2010; 30:8906-19. [PMID: 20592213 DOI: 10.1523/jneurosci.1287-10.2010] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The characteristics of central pattern generator (CPG) outputs are subject to extensive modulation. Previous studies of neuromodulation largely focused on immediate actions of neuromodulators, i.e., actions that were exerted at the time when either neuromodulators were present or neuromodulatory inputs to the CPG were active. However, neuromodulatory actions are known to persist when neuromodulators are no longer present. In Aplysia, stimulation of cerebral-buccal interneuron-2 (CBI-2), which activates the feeding CPG, produces a repetition priming of motor programs. This priming is reflected in an increase of firing of motoneurons. As CBI-2 contains two neuromodulatory peptides, FCAP (feeding circuit-activating peptide) and CP2 (cerebral peptide 2), we hypothesized that repetition priming may involve persistent peptidergic neuromodulation. We find that these peptides produce priming-like effects, i.e., they increase the firing of radula-opening (B48) and radula-closing (B8) motoneurons during motor programs. Proekt et al. (2004, 2007) showed that repetition priming of neuron B8 is implemented by modulatory inputs that B8 receives from the CPG. In contrast, our current findings indicate that priming of B48 may be implemented by a direct peptidergic modulation of its intrinsic characteristics via a pathway that activates cAMP. We suggest that the direct versus indirect, i.e., CPG-dependent, repetition priming may be related to the type of input that individual motoneurons receive from the CPG. We suggest that in motoneurons that are driven by concurrent excitation-inhibition, repetition priming is indirect as it is preferentially implemented via modulation of the output of CPGs. In contrast, in motoneurons that are driven by alternating excitation-inhibition, direct modulation of motoneurons may be preferentially used.
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Abstract
In a variety of vertebrates, including turtle, many classical and contemporary studies of spinal cord neuronal networks generating rhythmic motor behaviors emphasize a Reciprocal Model with alternation of agonists and antagonists, alternation of excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs), and reciprocal inhibition. Some studies of spinal cord neuronal networks, including some in turtle during scratch motor rhythms, describe a Balanced Model with concurrent EPSPs and IPSPs. The present report reviews turtle spinal cord studies and concludes that there is support for a Combined Model with both alternating and concurrent excitation and inhibition, that is, characteristics of both the Reciprocal and the Balanced Models, in the same spinal cord neuronal network for scratch reflex in turtle. Studies of spinal cord neuronal networks for locomotion in a variety of vertebrates also support a Combined Model.
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Affiliation(s)
- Paul S G Stein
- Biology Department, Washington University, St. Louis, Missouri, USA.
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Jing J, Gillette R, Weiss KR. Evolving concepts of arousal: insights from simple model systems. Rev Neurosci 2010; 20:405-27. [PMID: 20397622 DOI: 10.1515/revneuro.2009.20.5-6.405] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Arousal states strongly influence behavioral decisions. In general, arousal promotes activity and enhances responsiveness to sensory stimuli. Earlier work has emphasized general, or nonspecific, effects of arousal on multiple classes of behaviors. However, contemporary work indicates that arousal has quite specific effects on behavior. Here we review studies of arousal-related circuitry in molluscan model systems. Neural substrates for both general and specific effects of arousal have been identified. Based on the scope of their actions, we can distinguish two major classes of arousal elements: localized versus general. Actions of localized arousal elements are often limited to one class of behavior, and may thereby mediate specific effects of arousal. In contrast, general arousal elements may influence multiple classes of behaviors, and mediate both specific and nonspecific effects of arousal. One common way in which general arousal elements influence multiple behaviors is by acting on localized arousal elements of distinct networks. Often, effects on distinct networks have different time courses that may facilitate formation of specific behavioral sequences. This review highlights prominent roles of serotonergic systems in arousal that are conserved in gastropod molluscs despite extreme diversification of body forms, diet and ecological niches. The studies also indicate that the serotonergic elements can act as either localized or general arousal elements. We discuss the implications of these findings across animals.
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Affiliation(s)
- Jian Jing
- Department of Neuroscience, Mount Sinai School of Medicine, New York, NY 10029, USA.
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Wu JS, Vilim FS, Hatcher NG, Due MR, Sweedler JV, Weiss KR, Jing J. Composite modulatory feedforward loop contributes to the establishment of a network state. J Neurophysiol 2010; 103:2174-84. [PMID: 20181731 DOI: 10.1152/jn.01054.2009] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Feedforward loops (FFLs) are one of many network motifs identified in a variety of complex networks, but their functional role in neural networks is not well understood. We provide evidence that combinatorial actions of multiple modulators may be organized as FFLs to promote a specific network state in the Aplysia feeding motor network. The Aplysia feeding central pattern generator (CPG) receives two distinct inputs-a higher-order interneuron cerebral-buccal interneuron-2 (CBI-2) and the esophageal nerve (EN)-that promote ingestive and egestive motor programs, respectively. EN stimulation elicits a persistent egestive network state, which enables the network to temporarily express egestive programs following a switch of input from the EN to CBI-2. Previous work showed that a modulatory CPG element, B65, is specifically activated by the EN and participates in establishing the egestive state by enhancing activity of egestion-promoting B20 interneurons while suppressing activity and synaptic outputs of ingestion-promoting B40 interneurons. Here a peptidergic contribution is mediated by small cardioactive peptide (SCP). Immunostaining and mass spectrometry show that SCP is present in the EN and is released on EN stimulation. Importantly, SCP directly enhances activity and synaptic outputs of B20 and suppresses activity and synaptic outputs of B40. Moreover, SCP promotes B65 activity. Thus the direct and indirect (through B65) pathways to B20 and B40 from SCPergic neurons constitute two FFLs with one functioning to promote egestive output and the other to suppress ingestive output. This composite FFL consisting of the two combined FFLs appears to be an effective means to co-regulate activity of two competing elements that do not inhibit each other, thereby contributing to establish specific network states.
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Affiliation(s)
- Jin-Sheng Wu
- Dept. of Neuroscience, Mount Sinai School of Medicine, New York, NY 10029, USA
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