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Rosa ME, Oliveira RS, de Faria Barbosa R, Hyslop S, Dal Belo CA. Recent advances on the influence of fipronil on insect behavior. CURRENT OPINION IN INSECT SCIENCE 2024; 65:101251. [PMID: 39147324 DOI: 10.1016/j.cois.2024.101251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 07/31/2024] [Accepted: 08/08/2024] [Indexed: 08/17/2024]
Abstract
Fipronil, a pesticide widely used to control agricultural and household insect pests, blocks insect GABAA and glutamate (GluCl) ionotropic receptors, resulting in uncontrolled hyperexcitation and paralysis that eventually leads to death. The use of fipronil is controversial because unintentional exposure to this compound may contribute to the ongoing global decline of insect pollinator populations. Although the sublethal effects of fipronil have been linked to aberrant behavior and impaired olfactory learning in insects, the precise mechanisms involved in these responses remain unclear. In this article, we highlight recent studies that have investigated the interaction among different pathways involved in the ability of fipronil to modulate insect behavior, with particular emphasis on the role of GABAergic neurotransmission in fine-tuning the integration of sensorial responses and insect behavior. Recent findings suggest that fipronil can also cause functional alterations that affect synaptic organization and the availability of metal ions in the brain.
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Affiliation(s)
- Maria E Rosa
- Laboratório de Neurobiologia e Toxinologia (LANETOX), Centro Interdisciplinar de Pesquisas em Biotecnologia (CIPBiotec), Universidade Federal do Pampa (UNIPAMPA), Campus São Gabriel, Rua Aluízio Barros Macedo, S/N, BR 290, Km 423, 97307-020, São Gabriel, RS, Brazil
| | - Raquel S Oliveira
- Departamento de Medicina Translacional (Área de Farmacologia), Universidade Estadual de Campinas (UNICAMP), Faculdade de Ciências Médicas, Rua Vital Brazil, 80, Cidade Universitária Zeferino Vaz, 13083-888, Campinas, SP, Brazil
| | - Renata de Faria Barbosa
- Departamento Multidisciplinar, Escola Paulista de Política, Economia e Negócios (EPPEN), Universidade Federal de São Paulo (UNIFESP), Rua General Newton Estilac Leal, 932, Pestana, 06190-170, Osasco, SP, Brazil
| | - Stephen Hyslop
- Departamento de Medicina Translacional (Área de Farmacologia), Universidade Estadual de Campinas (UNICAMP), Faculdade de Ciências Médicas, Rua Vital Brazil, 80, Cidade Universitária Zeferino Vaz, 13083-888, Campinas, SP, Brazil
| | - Cháriston A Dal Belo
- Laboratório de Neurobiologia e Toxinologia (LANETOX), Centro Interdisciplinar de Pesquisas em Biotecnologia (CIPBiotec), Universidade Federal do Pampa (UNIPAMPA), Campus São Gabriel, Rua Aluízio Barros Macedo, S/N, BR 290, Km 423, 97307-020, São Gabriel, RS, Brazil; Programa de Pós-Graduação em Ciências Biológicas: Bioquímica Toxicológica (PPGBtox), Universidade Federal de Santa Maria (UFSM), Centro de Ciências Naturais e Exatas, Prédio 18, Cidade Universitária, Bairro Camobi, 97105-900, Santa Maria, RS, Brazil; Departamento Multidisciplinar, Escola Paulista de Política, Economia e Negócios (EPPEN), Universidade Federal de São Paulo (UNIFESP), Rua General Newton Estilac Leal, 932, Pestana, 06190-170, Osasco, SP, Brazil.
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Traniello IM, Kocher SD. Integrating computer vision and molecular neurobiology to bridge the gap between behavior and the brain. CURRENT OPINION IN INSECT SCIENCE 2024; 66:101259. [PMID: 39244088 DOI: 10.1016/j.cois.2024.101259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 07/23/2024] [Accepted: 09/02/2024] [Indexed: 09/09/2024]
Abstract
The past decade of social insect research has seen rapid development in automated behavioral tracking and molecular profiling of the nervous system, two distinct but complementary lines of inquiry into phenotypic variation across individuals, colonies, populations, and species. These experimental strategies have developed largely in parallel, as automated tracking generates a continuous stream of behavioral data, while, in contrast, 'omics-based profiling provides a single 'snapshot' of the brain. Better integration of these approaches applied to studying variation in social behavior will reveal the underlying genetic and neurobiological mechanisms that shape the evolution and diversification of social life. In this review, we discuss relevant advances in both fields and propose new strategies to better elucidate the molecular and behavioral innovations that generate social life.
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Affiliation(s)
- Ian M Traniello
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
| | - Sarah D Kocher
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
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Lafon G, Geng H, Avarguès-Weber A, Buatois A, Massou I, Giurfa M. The Neural Signature of Visual Learning Under Restrictive Virtual-Reality Conditions. Front Behav Neurosci 2022; 16:846076. [PMID: 35250505 PMCID: PMC8888666 DOI: 10.3389/fnbeh.2022.846076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 01/21/2022] [Indexed: 11/22/2022] Open
Abstract
Honey bees are reputed for their remarkable visual learning and navigation capabilities. These capacities can be studied in virtual reality (VR) environments, which allow studying performances of tethered animals in stationary flight or walk under full control of the sensory environment. Here, we used a 2D VR setup in which a tethered bee walking stationary under restrictive closed-loop conditions learned to discriminate vertical rectangles differing in color and reinforcing outcome. Closed-loop conditions restricted stimulus control to lateral displacements. Consistently with prior VR analyses, bees learned to discriminate the trained stimuli. Ex vivo analyses on the brains of learners and non-learners showed that successful learning led to a downregulation of three immediate early genes in the main regions of the visual circuit, the optic lobes (OLs) and the calyces of the mushroom bodies (MBs). While Egr1 was downregulated in the OLs, Hr38 and kakusei were coincidently downregulated in the calyces of the MBs. Our work thus reveals that color discrimination learning induced a neural signature distributed along the sequential pathway of color processing that is consistent with an inhibitory trace. This trace may relate to the motor patterns required to solve the discrimination task, which are different from those underlying pathfinding in 3D VR scenarios allowing for navigation and exploratory learning and which lead to IEG upregulation.
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Affiliation(s)
- Gregory Lafon
- Research Center on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
| | - Haiyang Geng
- Research Center on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
- College of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou, China
| | - Aurore Avarguès-Weber
- Research Center on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
| | - Alexis Buatois
- Research Center on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
| | - Isabelle Massou
- Research Center on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
| | - Martin Giurfa
- Research Center on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France
- College of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou, China
- Institut Universitaire de France, Paris, France
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