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Stojkovic M, Petrovic M, Capovilla M, Milojevic S, Makevic V, Budimirovic DB, Corscadden L, He S, Protic D. Using a Combination of Novel Research Tools to Understand Social Interaction in the Drosophila melanogaster Model for Fragile X Syndrome. BIOLOGY 2024; 13:432. [PMID: 38927312 PMCID: PMC11200401 DOI: 10.3390/biology13060432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/31/2024] [Accepted: 06/06/2024] [Indexed: 06/28/2024]
Abstract
Fragile X syndrome (FXS), the most common monogenic cause of inherited intellectual disability and autism spectrum disorder, is caused by a full mutation (>200 CGG repeats) in the Fragile X Messenger Ribonucleoprotein 1 (FMR1) gene. Individuals with FXS experience various challenges related to social interaction (SI). Animal models, such as the Drosophila melanogaster model for FXS where the only ortholog of human FMR1 (dFMR1) is mutated, have played a crucial role in the understanding of FXS. The aim of this study was to investigate SI in the dFMR1B55 mutants (the groups of flies of both sexes simultaneously) using the novel Drosophila Shallow Chamber and a Python data processing pipeline based on social network analysis (SNA). In comparison with wild-type flies (w1118), SNA analysis in dFMR1B55 mutants revealed hypoactivity, fewer connections in their networks, longer interaction duration, a lower ability to transmit information efficiently, fewer alternative pathways for information transmission, a higher variability in the number of interactions they achieved, and flies tended to stay near the boundaries of the testing chamber. These observed alterations indicate the presence of characteristic strain-dependent social networks in dFMR1B55 flies, commonly referred to as the group phenotype. Finally, combining novel research tools is a valuable method for SI research in fruit flies.
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Affiliation(s)
- Maja Stojkovic
- Department of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia; (M.S.); (S.M.)
| | - Milan Petrovic
- Department of Informatics, University of Rijeka, 51000 Rijeka, Croatia;
- Center for Artificial Intelligence and Cybersecurity, University of Rijeka, 51000 Rijeka, Croatia
| | - Maria Capovilla
- UMR7275 CNRS-UCA, Institut de Pharmacologie Moléculaire et Cellulaire, 06560 Valbonne Sophia Antipolis, France;
| | - Sara Milojevic
- Department of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia; (M.S.); (S.M.)
| | - Vedrana Makevic
- Department of Pathophysiology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia;
| | - Dejan B. Budimirovic
- Department of Psychiatry, Fragile X Clinic, Kennedy Krieger Institute, Baltimore, MD 21205, USA;
- Department of Psychiatry & Behavioral Sciences-Child Psychiatry, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | | | - Shuhan He
- Lab of Computer Science, Department of Internal Medicine, Harvard Medical School, Boston, MA 02115, USA;
| | - Dragana Protic
- Department of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia; (M.S.); (S.M.)
- Fragile X Clinic, Special Hospital for Cerebral Palsy and Developmental Neurology, 11000 Belgrade, Serbia
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2
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Peng D, Zheng L, Liu D, Han C, Wang X, Yang Y, Song L, Zhao M, Wei Y, Li J, Ye X, Wei Y, Feng Z, Huang X, Chen M, Gou Y, Xue Y, Zhang L. Large-language models facilitate discovery of the molecular signatures regulating sleep and activity. Nat Commun 2024; 15:3685. [PMID: 38693116 PMCID: PMC11063160 DOI: 10.1038/s41467-024-48005-w] [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: 05/17/2023] [Accepted: 04/17/2024] [Indexed: 05/03/2024] Open
Abstract
Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained transformer (GPT) 3.5, which interprets 10.2-13.8% of Drosophila genes known to regulate the 3 behaviors. We develop an instrument for simultaneous video tracking of multiple moving objects, and conduct a genome-wide screen. We have identified 758 fly genes that regulate sleep and activities, including mre11 which regulates sleep only in the presence of conspecifics, and NELF-B which regulates sleep regardless of whether conspecifics are present. Based on LLM-reasoning, an educated signal web is modeled for understanding of potential relationships between its components, presenting comprehensive molecular signatures that control sleep, locomotor and social activities. This LLM-aided strategy may also be helpful for addressing other complex scientific questions.
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Affiliation(s)
- Di Peng
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Liubin Zheng
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Dan Liu
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Cheng Han
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Xin Wang
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Yan Yang
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Li Song
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Miaoying Zhao
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Yanfeng Wei
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Jiayi Li
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Xiaoxue Ye
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Yuxiang Wei
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Zihao Feng
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Xinhe Huang
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Miaomiao Chen
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Yujie Gou
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Yu Xue
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Nanjing University Institute of Artificial Intelligence Biomedicine, Nanjing, Jiangsu, 210031, China.
| | - Luoying Zhang
- Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration, Wuhan, Hubei, 430022, China.
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3
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Sokolowski DJ, Vasquez OE, Wilson MD, Sokolowski MB, Anreiter I. Transcriptomic effects of the foraging gene shed light on pathways of pleiotropy and plasticity. Ann N Y Acad Sci 2023; 1526:99-113. [PMID: 37350250 DOI: 10.1111/nyas.15015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2023]
Abstract
Genes are often pleiotropic and plastic in their expression, features which increase and diversify the functionality of the genome. The foraging (for) gene in Drosophila melanogaster is highly pleiotropic and a long-standing model for studying individual differences in behavior and plasticity from ethological, evolutionary, and genetic perspectives. Its pleiotropy is known to be linked to its complex molecular structure; however, the downstream pathways and interactors remain mostly elusive. To uncover these pathways and interactors and gain a better understanding of how pleiotropy and plasticity are achieved at the molecular level, we explore the effects of different for alleles on gene expression at baseline and in response to 4 h of food deprivation, using RNA sequencing analysis in different Drosophila larval tissues. The results show tissue-specific transcriptomic dynamics influenced by for allelic variation and food deprivation, as well as genotype by treatment interactions. Differentially expressed genes yielded pathways linked to previously described for phenotypes and several potentially novel phenotypes. Together, these findings provide putative genes and pathways through which for might regulate its varied phenotypes in a pleiotropic, plastic, and gene-structure-dependent manner.
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Affiliation(s)
- Dustin J Sokolowski
- Genetics and Genome Biology, SickKids Research Institute, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Oscar E Vasquez
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - Michael D Wilson
- Genetics and Genome Biology, SickKids Research Institute, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Marla B Sokolowski
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
- Program in Child and Brain Development, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
| | - Ina Anreiter
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
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4
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Gallot A, Desouhant E, Lhuillier V, Lepetit D, El Filali A, Mouton L, Vieira-Heddi C, Amat I. The for gene as one of the drivers of foraging variations in a parasitic wasp. Mol Ecol 2022; 32:1760-1776. [PMID: 36571434 DOI: 10.1111/mec.16834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/08/2022] [Accepted: 12/22/2022] [Indexed: 12/27/2022]
Abstract
Foraging behaviours encompass strategies to locate resources and to exploit them. In many taxa, these behaviours are driven by a major gene called for, but the mechanisms of gene regulation vary between species. In the parasitoid wasp Venturia canescens, sexual and asexual populations coexist in sympatry but differ in life-history traits, physiology and behaviours, which could impact their foraging strategies. Here, we explored the molecular bases underpinning divergence in behaviours by testing two mutually nonexclusive hypotheses: first, the divergence in the for gene correlates with differences in foraging strategies, and second, the latter rely on a divergence in whole-genome expression. Using comparative genomics, we showed that the for gene was conserved across insects considering both sequence and gene model complexity. Polymorphism analysis did not support the occurrence of two allelic variants diverging across the two populations, yet the asexual population exhibited less polymorphism than the sexual population. Sexual and asexual transcriptomes split sharply, with 10.9% differentially expressed genes, but these were not enriched in behaviour-related genes. We showed that the for gene was more highly expressed in asexual female heads than in sexual heads and that those differences correlate with divergence in foraging behaviours in our experiment given that asexuals explored the environment more and exploited more host patches. Overall, these results suggested that fine tuning of for gene expression between populations may have led to distinct foraging behaviours. We hypothesized that reproductive polymorphism and coexistence in sympatry of sexual and asexual populations specialized to different ecological niches via divergent optima on phenotypic traits could imply adaptation through different expression patterns of the for gene and at many other loci throughout the genome.
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Affiliation(s)
- Aurore Gallot
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - Emmanuel Desouhant
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - Vincent Lhuillier
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - David Lepetit
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - Adil El Filali
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - Laurence Mouton
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - Cristina Vieira-Heddi
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
| | - Isabelle Amat
- LBBE - Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université de Lyon, Université Lyon1, Villeurbanne, France
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5
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Jezovit JA, Alwash N, Levine JD. Using Flies to Understand Social Networks. Front Neural Circuits 2021; 15:755093. [PMID: 34924963 PMCID: PMC8683092 DOI: 10.3389/fncir.2021.755093] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 11/08/2021] [Indexed: 12/21/2022] Open
Abstract
Many animals live in groups and interact with each other, creating an organized collective structure. Social network analysis (SNA) is a statistical tool that aids in revealing and understanding the organized patterns of shared social connections between individuals in groups. Surprisingly, the application of SNA revealed that Drosophila melanogaster, previously considered a solitary organism, displays group dynamics and that the structure of group life is inherited. Although the number of studies investigating Drosophila social networks is currently limited, they address a wide array of questions that have only begun to capture the details of group level behavior in this insect. Here, we aim to review these studies, comparing their respective scopes and the methods used, to draw parallels between them and the broader body of knowledge available. For example, we highlight how despite methodological differences, there are similarities across studies investigating the effects of social isolation on social network dynamics. Finally, this review aims to generate hypotheses and predictions that inspire future research in the emerging field of Drosophila social networks.
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Affiliation(s)
- Jacob A Jezovit
- Department of Cell and Systems Biology, University of Toronto Mississauga, Mississauga, ON, Canada
| | - Nawar Alwash
- Department of Cell and Systems Biology, University of Toronto Mississauga, Mississauga, ON, Canada
| | - Joel D Levine
- Department of Cell and Systems Biology, University of Toronto Mississauga, Mississauga, ON, Canada.,Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.,International Research Centre for Neurointelligence, University of Tokyo, Tokyo, Japan
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6
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Allen AM, B Sokolowski M. Expression of the foraging gene in adult Drosophila melanogaster. J Neurogenet 2021; 35:192-212. [PMID: 34382904 PMCID: PMC8846931 DOI: 10.1080/01677063.2021.1941946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
The foraging gene in Drosophila melanogaster, which encodes a cGMP-dependent protein kinase, is a highly conserved, complex gene with multiple pleiotropic behavioral and physiological functions in both the larval and adult fly. Adult foraging expression is less well characterized than in the larva. We characterized foraging expression in the brain, gastric system, and reproductive systems using a T2A-Gal4 gene-trap allele. In the brain, foraging expression appears to be restricted to multiple sub-types of glia. This glial-specific cellular localization of foraging was supported by single-cell transcriptomic atlases of the adult brain. foraging is extensively expressed in most cell types in the gastric and reproductive systems. We then mapped multiple cis-regulatory elements responsible for parts of the observed expression patterns by a nested cloned promoter-Gal4 analysis. The mapped cis-regulatory elements were consistently modular when comparing the larval and adult expression patterns. These new data using the T2A-Gal4 gene-trap and cloned foraging promoter fusion GAL4's are discussed with respect to previous work using an anti-FOR antibody, which we show here to be non-specific. Future studies of foraging's function will consider roles for glial subtypes and peripheral tissues (gastric and reproductive systems) in foraging's pleiotropic behavioral and physiological effects.
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Affiliation(s)
- Aaron M Allen
- Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.,Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
| | - Marla B Sokolowski
- Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.,Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada.,Child and Brain Development Program, Canadian Institute for Advanced Research (CIFAR), Toronto, Canada
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7
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Lucas C, Ben-Shahar Y. The foraging gene as a modulator of division of labour in social insects. J Neurogenet 2021; 35:168-178. [PMID: 34151702 DOI: 10.1080/01677063.2021.1940173] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
The social ants, bees, wasps, and termites include some of the most ecologically-successful groups of animal species. Their dominance in most terrestrial environments is attributed to their social lifestyle, which enable their colonies to exploit environmental resources with remarkable efficiency. One key attribute of social insect colonies is the division of labour that emerges among the sterile workers, which represent the majority of colony members. Studies of the mechanisms that drive division of labour systems across diverse social species have provided fundamental insights into the developmental, physiological, molecular, and genomic processes that regulate sociality, and the possible genetic routes that may have led to its evolution from a solitary ancestor. Here we specifically discuss the conserved role of the foraging gene, which encodes a cGMP-dependent protein kinase (PKG). Originally identified as a behaviourally polymorphic gene that drives alternative foraging strategies in the fruit fly Drosophila melanogaster, changes in foraging expression and kinase activity were later shown to play a key role in the division of labour in diverse social insect species as well. In particular, foraging appears to regulate worker transitions between behavioural tasks and specific behavioural traits associated with morphological castes. Although the specific neuroethological role of foraging in the insect brain remains mostly unknown, studies in genetically tractable insect species indicate that PKG signalling plays a conserved role in the neuronal plasticity of sensory, cognitive and motor functions, which underlie behaviours relevant to division of labour, including appetitive learning, aggression, stress response, phototaxis, and the response to pheromones.
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Affiliation(s)
- Christophe Lucas
- Institut de Recherche sur la Biologie de l'Insecte (UMR7261), CNRS - University of Tours, Tours, France
| | - Yehuda Ben-Shahar
- Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
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