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Roggenbuck EC, Hall EA, Hanson IB, Roby AA, Zhang KK, Alkatib KA, Carter JA, Clewner JE, Gelfius AL, Gong S, Gordon FR, Iseler JN, Kotapati S, Li M, Maysun A, McCormick EO, Rastogi G, Sengupta S, Uzoma CU, Wolkov MA, Clowney EJ. Let's talk about sex: Mechanisms of neural sexual differentiation in Bilateria. WIREs Mech Dis 2024; 16:e1636. [PMID: 38185860 DOI: 10.1002/wsbm.1636] [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: 05/09/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 01/09/2024]
Abstract
In multicellular organisms, sexed gonads have evolved that facilitate release of sperm versus eggs, and bilaterian animals purposefully combine their gametes via mating behaviors. Distinct neural circuits have evolved that control these physically different mating events for animals producing eggs from ovaries versus sperm from testis. In this review, we will describe the developmental mechanisms that sexually differentiate neural circuits across three major clades of bilaterian animals-Ecdysozoa, Deuterosomia, and Lophotrochozoa. While many of the mechanisms inducing somatic and neuronal sex differentiation across these diverse organisms are clade-specific rather than evolutionarily conserved, we develop a common framework for considering the developmental logic of these events and the types of neuronal differences that produce sex-differentiated behaviors. This article is categorized under: Congenital Diseases > Stem Cells and Development Neurological Diseases > Stem Cells and Development.
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Affiliation(s)
- Emma C Roggenbuck
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Elijah A Hall
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Isabel B Hanson
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Alyssa A Roby
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Katherine K Zhang
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Kyle A Alkatib
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Joseph A Carter
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jarred E Clewner
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Anna L Gelfius
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Shiyuan Gong
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Finley R Gordon
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jolene N Iseler
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Samhita Kotapati
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Marilyn Li
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Areeba Maysun
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Elise O McCormick
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Geetanjali Rastogi
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Srijani Sengupta
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Chantal U Uzoma
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - Madison A Wolkov
- MCDB 464 - Cellular Diversity: Sex Differentiation of the Brain, University of Michigan, Ann Arbor, Michigan, USA
| | - E Josephine Clowney
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan, USA
- Michigan Neuroscience Institute Affiliate, University of Michigan, Ann Arbor, Michigan, USA
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2
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Cronin EM, Schneider AC, Nadim F, Bucher D. Modulation by Neuropeptides with Overlapping Targets Results in Functional Overlap in Oscillatory Circuit Activation. J Neurosci 2024; 44:e1201232023. [PMID: 37968117 PMCID: PMC10851686 DOI: 10.1523/jneurosci.1201-23.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 10/18/2023] [Accepted: 10/24/2023] [Indexed: 11/17/2023] Open
Abstract
Neuromodulation lends flexibility to neural circuit operation but the general notion that different neuromodulators sculpt neural circuit activity into distinct and characteristic patterns is complicated by interindividual variability. In addition, some neuromodulators converge onto the same signaling pathways, with similar effects on neurons and synapses. We compared the effects of three neuropeptides on the rhythmic pyloric circuit in the stomatogastric ganglion of male crabs, Cancer borealis Proctolin (PROC), crustacean cardioactive peptide (CCAP), and red pigment concentrating hormone (RPCH) activate the same modulatory inward current, I MI, and have convergent actions on synapses. However, while PROC targets all four neuron types in the core pyloric circuit, CCAP and RPCH target the same subset of only two neurons. After removal of spontaneous neuromodulator release, none of the neuropeptides restored the control cycle frequency, but all restored the relative timing between neuron types. Consequently, differences between neuropeptide effects were mainly found in the spiking activity of different neuron types. We performed statistical comparisons using the Euclidean distance in the multidimensional space of normalized output attributes to obtain a single measure of difference between modulatory states. Across preparations, the circuit output in PROC was distinguishable from CCAP and RPCH, but CCAP and RPCH were not distinguishable from each other. However, we argue that even between PROC and the other two neuropeptides, population data overlapped enough to prevent reliable identification of individual output patterns as characteristic for a specific neuropeptide. We confirmed this notion by showing that blind classifications by machine learning algorithms were only moderately successful.Significance Statement It is commonly assumed that distinct behaviors or circuit activities can be elicited by different neuromodulators. Yet it is unknown to what extent these characteristic actions remain distinct across individuals. We use a well-studied circuit model of neuromodulation to examine the effects of three neuropeptides, each known to produce a distinct activity pattern in controlled studies. We find that, when compared across individuals, the three peptides elicit activity patterns that are either statistically indistinguishable or show too much overlap to be labeled characteristic. We ascribe this to interindividual variability and overlapping subcellular actions of the modulators. Because both factors are common in all neural circuits, these findings have broad significance for understanding chemical neuromodulatory actions while considering interindividual variability.
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Affiliation(s)
- Elizabeth M Cronin
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey 07102
| | - Anna C Schneider
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey 07102
| | - Farzan Nadim
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey 07102
| | - Dirk Bucher
- Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey 07102
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3
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Dong K, Liu WC, Su Y, Lyu Y, Huang H, Zheng N, Rogers JA, Nan K. Scalable Electrophysiology of Millimeter-Scale Animals with Electrode Devices. BME FRONTIERS 2023; 4:0034. [PMID: 38435343 PMCID: PMC10907027 DOI: 10.34133/bmef.0034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/08/2023] [Indexed: 03/05/2024] Open
Abstract
Millimeter-scale animals such as Caenorhabditis elegans, Drosophila larvae, zebrafish, and bees serve as powerful model organisms in the fields of neurobiology and neuroethology. Various methods exist for recording large-scale electrophysiological signals from these animals. Existing approaches often lack, however, real-time, uninterrupted investigations due to their rigid constructs, geometric constraints, and mechanical mismatch in integration with soft organisms. The recent research establishes the foundations for 3-dimensional flexible bioelectronic interfaces that incorporate microfabricated components and nanoelectronic function with adjustable mechanical properties and multidimensional variability, offering unique capabilities for chronic, stable interrogation and stimulation of millimeter-scale animals and miniature tissue constructs. This review summarizes the most advanced technologies for electrophysiological studies, based on methods of 3-dimensional flexible bioelectronics. A concluding section addresses the challenges of these devices in achieving freestanding, robust, and multifunctional biointerfaces.
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Affiliation(s)
- Kairu Dong
- College of Pharmaceutical Sciences,
Zhejiang University, Hangzhou 310058, China
- National Key Laboratory of Advanced Drug Delivery and Release Systems,
Zhejiang University, Hangzhou 310058, China
- College of Biomedical Engineering & Instrument Science,
Zhejiang University, Hangzhou, 310027, China
| | - Wen-Che Liu
- College of Pharmaceutical Sciences,
Zhejiang University, Hangzhou 310058, China
- National Key Laboratory of Advanced Drug Delivery and Release Systems,
Zhejiang University, Hangzhou 310058, China
| | - Yuyan Su
- College of Pharmaceutical Sciences,
Zhejiang University, Hangzhou 310058, China
- Department of Gastroenterology, Brigham and Women’s Hospital,
Harvard Medical School, Boston, MA 02115, USA
| | - Yidan Lyu
- College of Pharmaceutical Sciences,
Zhejiang University, Hangzhou 310058, China
| | - Hao Huang
- College of Pharmaceutical Sciences,
Zhejiang University, Hangzhou 310058, China
- College of Chemical and Biological Engineering,
Zhejiang University, Hangzhou 310058, China
| | - Nenggan Zheng
- Qiushi Academy for Advanced Studies,
Zhejiang University, Hangzhou 310027, China
- College of Computer Science and Technology,
Zhejiang University, Hangzhou 310027, China
- State Key Lab of Brain-Machine Intelligence,
Zhejiang University, Hangzhou 310058, China
- CCAI by MOE and Zhejiang Provincial Government (ZJU), Hangzhou 310027, China
| | - John A. Rogers
- Querrey Simpson Institute for Bioelectronics,
Northwestern University, Evanston, IL 60208, USA
- Department of Biomedical Engineering,
Northwestern University, Evanston, IL 60208, USA
- Department of Materials Science and Engineering,
Northwestern University, Evanston, IL 60208, USA
- Department of Mechanical Engineering,
Northwestern University, Evanston, IL 60208, USA
| | - Kewang Nan
- College of Pharmaceutical Sciences,
Zhejiang University, Hangzhou 310058, China
- National Key Laboratory of Advanced Drug Delivery and Release Systems,
Zhejiang University, Hangzhou 310058, China
- Jinhua Institute of Zhejiang University, Jinhua 321299, China
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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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Schneider AC, Itani O, Cronin E, Daur N, Bucher D, Nadim F. Comodulation reduces interindividual variability of circuit output. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.03.543573. [PMID: 37383946 PMCID: PMC10298844 DOI: 10.1101/2023.06.03.543573] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
Ionic current levels of identified neurons vary substantially across individual animals. Yet, under similar conditions, neural circuit output can be remarkably similar, as evidenced in many motor systems. All neural circuits are influenced by multiple neuromodulators which provide flexibility to their output. These neuromodulators often overlap in their actions by modulating the same channel type or synapse, yet have neuron-specific actions resulting from distinct receptor expression. Because of this different receptor expression pattern, in the presence of multiple convergent neuromodulators, a common downstream target would be activated more uniformly in circuit neurons across individuals. We therefore propose that a baseline tonic (non-saturating) level of comodulation by convergent neuromodulators can reduce interindividual variability of circuit output. We tested this hypothesis in the pyloric circuit of the crab, Cancer borealis. Multiple excitatory neuropeptides converge to activate the same voltage-gated current in this circuit, but different subsets of pyloric neurons have receptors for each peptide. We quantified the interindividual variability of the unmodulated pyloric circuit output by measuring the activity phases, cycle frequency and intraburst spike number and frequency. We then examined the variability in the presence of different combinations and concentrations of three neuropeptides. We found that at mid-level concentration (30 nM) but not at near-threshold (1 nM) or saturating (1 μM) concentrations, comodulation by multiple neuropeptides reduced the circuit output variability. Notably, the interindividual variability of response properties of an isolated neuron was not reduced by comodulation, suggesting that the reduction of output variability may emerge as a network effect.
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Cronin EM, Schneider AC, Nadim F, Bucher D. Modulation by neuropeptides with overlapping targets results in functional overlap in oscillatory circuit activation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.05.543756. [PMID: 37333253 PMCID: PMC10274681 DOI: 10.1101/2023.06.05.543756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Neuromodulation lends flexibility to neural circuit operation but the general notion that different neuromodulators sculpt neural circuit activity into distinct and characteristic patterns is complicated by interindividual variability. In addition, some neuromodulators converge onto the same signaling pathways, with similar effects on neurons and synapses. We compared the effects of three neuropeptides on the rhythmic pyloric circuit in the crab Cancer borealis stomatogastric nervous system. Proctolin (PROC), crustacean cardioactive peptide (CCAP), and red pigment concentrating hormone (RPCH) all activate the same modulatory inward current, IMI, and have convergent actions on synapses. However, while PROC targets all four neuron types in the core pyloric circuit, CCAP and RPCH target the same subset of only two neurons. After removal of spontaneous neuromodulator release, none of the neuropeptides restored the control cycle frequency, but all restored the relative timing between neuron types. Consequently, differences between neuropeptide effects were mainly found in the spiking activity of different neuron types. We performed statistical comparisons using the Euclidean distance in the multidimensional space of normalized output attributes to obtain a single measure of difference between modulatory states. Across preparations, circuit output in PROC was distinguishable from CCAP and RPCH, but CCAP and RPCH were not distinguishable from each other. However, we argue that even between PROC and the other two neuropeptides, population data overlapped enough to prevent reliable identification of individual output patterns as characteristic for a specific neuropeptide. We confirmed this notion by showing that blind classifications by machine learning algorithms were only moderately successful.
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