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Tianle C, Yunhan F, Delong L, Haitao X, Lanting M, Xueqing S, Liuxu Y, Yu H, Guizhi W. Transcriptomic analysis to elucidate the response of Apis mellifera ligustica brain tissue to fluvalinate exposure. Anim Biotechnol 2023; 34:4175-4186. [PMID: 35436166 DOI: 10.1080/10495398.2022.2061506] [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: 11/01/2022]
Abstract
As a commonly used acaricide in apiculture, fluvalinate is used to kill Varroa mites, while it also damages the nervous system of honeybees. To date, the transcriptomic characteristics associated with fluvalinate-induced neuronal injury in the bee brain have not been reported. Here, we performed transcriptome sequencing on Apis mellifera ligustica (A. mellifera ligustica) brain tissues collected before and after fluvalinate treatment. A total of 546 differentially expressed genes (DEGs) were detected, and these DEGs mainly showed 4 different expression patterns. Further analysis revealed that DEGs with different expression patterns were mainly involved in lipid metabolism, amino acid metabolism, visual transduction, and neural response-related GO terms and KEGG pathways. Moreover, protein-protein interaction network analysis revealed five protein-coding DEGs as key genes, which may play important roles in the resistance to fluvalinate-induced honeybee brain nerve tissue damage. In summary, this study is the first to perform a detailed characterization and functional analysis of genes related to fluvalinate stimulation in honeybee brains.
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Affiliation(s)
- Chao Tianle
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
| | - Fan Yunhan
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
| | - Lou Delong
- Comprehensive Testing and Inspection Center, Shandong Provincial Animal Husbandry and Veterinary Bureau, Jinan, Shandong, China
| | - Xia Haitao
- Animal Husbandry Development Center of Linqu County, Weifang, Shandong, China
| | - Ma Lanting
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
| | - Shan Xueqing
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
| | - Yang Liuxu
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
| | - He Yu
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
| | - Wang Guizhi
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, Shandong, China
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Duan W, Zhang Y, Zhang X, Yang J, Shan H, Liu L, Wei H. A Visual Pathway into Central Complex for High-Frequency Motion-Defined Bars in Drosophila. J Neurosci 2023; 43:4821-4836. [PMID: 37290936 PMCID: PMC10312062 DOI: 10.1523/jneurosci.0128-23.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/10/2023] Open
Abstract
Relative motion breaks a camouflaged target from a same-textured background, thus eliciting discrimination of a motion-defined object. Ring (R) neurons are critical components in the Drosophila central complex, which has been implicated in multiple visually guided behaviors. Using two-photon calcium imaging with female flies, we demonstrated that a specific population of R neurons that innervate the superior domain of bulb neuropil, termed superior R neurons, encoded a motion-defined bar with high spatial frequency contents. Upstream superior tuberculo-bulbar (TuBu) neurons transmitted visual signals by releasing acetylcholine within synapses connected with superior R neurons. Blocking TuBu or R neurons impaired tracking performance of the bar, which reveals their importance in motion-defined feature encoding. Additionally, the presentation of a low spatial frequency luminance-defined bar evoked consistent excitation in R neurons of the superior bulb, whereas either excited or inhibited responses were evoked in the inferior bulb. The distinct properties of the responses to the two bar stimuli indicate there is a functional division between the bulb subdomains. Moreover, physiological and behavioral tests with restricted lines suggest that R4d neurons play a vital role in tracking motion-defined bars. We conclude that the central complex receives the motion-defined features via a visual pathway from superior TuBu to R neurons and might encode different visual features via distinct response patterns at the population level, thereby driving visually guided behaviors.SIGNIFICANCE STATEMENT Animals could discriminate a motion-defined object that is indistinguishable with a same-textured background until it moves, but little is known about the underlying neural mechanisms. In this study, we identified that R neurons and their upstream partners, TuBu neurons, innervating the superior bulb of Drosophila central brain are involved in the discrimination of high-frequency motion-defined bars. Our study provides new evidence that R neurons receive multiple visual inputs from distinct upstream neurons, indicating a population coding mechanism for the fly central brain to discriminate diverse visual features. These results build progress in unraveling neural substrates for visually guided behaviors.
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Affiliation(s)
- Wenlan Duan
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing 100039, China
| | - Yihao Zhang
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing 100039, China
| | - Xin Zhang
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing 100039, China
| | - Jihua Yang
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing 100039, China
| | - Heying Shan
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Li Liu
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing 100039, China
- Chinese Academy of Sciences Key Laboratory of Mental Health, Beijing 100101, China
| | - Hongying Wei
- State Key Laboratory of Brain and Cognitive Science, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of the Chinese Academy of Sciences, Beijing 100039, China
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3
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Zhao Y, Ke S, Cheng G, Lv X, Chang J, Zhou W. Direction Selectivity of TmY Neurites in Drosophila. Neurosci Bull 2023; 39:759-773. [PMID: 36399278 PMCID: PMC10169962 DOI: 10.1007/s12264-022-00966-y] [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: 04/29/2022] [Accepted: 06/29/2022] [Indexed: 11/19/2022] Open
Abstract
The perception of motion is an important function of vision. Neural wiring diagrams for extracting directional information have been obtained by connectome reconstruction. Direction selectivity in Drosophila is thought to originate in T4/T5 neurons through integrating inputs with different temporal filtering properties. Through genetic screening based on synaptic distribution, we isolated a new type of TmY neuron, termed TmY-ds, that form reciprocal synaptic connections with T4/T5 neurons. Its neurites responded to grating motion along the four cardinal directions and showed a variety of direction selectivity. Intriguingly, its direction selectivity originated from temporal filtering neurons rather than T4/T5. Genetic silencing and activation experiments showed that TmY-ds neurons are functionally upstream of T4/T5. Our results suggest that direction selectivity is generated in a tripartite circuit formed among these three neurons-temporal filtering, TmY-ds, and T4/T5 neurons, in which TmY-ds plays a role in the enhancement of direction selectivity in T4/T5 neurons.
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Affiliation(s)
- Yinyin Zhao
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Shanshan Ke
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Guo Cheng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Xiaohua Lv
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jin Chang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
| | - Wei Zhou
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
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Städele C, Keleş MF, Mongeau JM, Frye MA. Non-canonical Receptive Field Properties and Neuromodulation of Feature-Detecting Neurons in Flies. Curr Biol 2020; 30:2508-2519.e6. [PMID: 32442460 PMCID: PMC7343589 DOI: 10.1016/j.cub.2020.04.069] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 03/10/2020] [Accepted: 04/24/2020] [Indexed: 10/24/2022]
Abstract
Several fundamental aspects of motion vision circuitry are prevalent across flies and mice. Both taxa segregate ON and OFF signals. For any given spatial pattern, motion detectors in both taxa are tuned to speed, selective for one of four cardinal directions, and modulated by catecholamine neurotransmitters. These similarities represent conserved, canonical properties of the functional circuits and computational algorithms for motion vision. Less is known about feature detectors, including how receptive field properties differ from the motion pathway or whether they are under neuromodulatory control to impart functional plasticity for the detection of salient objects from a moving background. Here, we investigated 19 types of putative feature selective lobula columnar (LC) neurons in the optic lobe of the fruit fly Drosophila melanogaster to characterize divergent properties of feature selection. We identified LC12 and LC15 as feature detectors. LC15 encodes moving bars, whereas LC12 is selective for the motion of discrete objects, mostly independent of size. Neither is selective for contrast polarity, speed, or direction, highlighting key differences in the underlying algorithms for feature detection and motion vision. We show that the onset of background motion suppresses object responses by LC12 and LC15. Surprisingly, the application of octopamine, which is released during flight, reverses the suppressive influence of background motion, rendering both LCs able to track moving objects superimposed against background motion. Our results provide a comparative framework for the function and modulation of feature detectors and new insights into the underlying neuronal mechanisms involved in visual feature detection.
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Affiliation(s)
- Carola Städele
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA
| | - Mehmet F Keleş
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA
| | - Jean-Michel Mongeau
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA
| | - Mark A Frye
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA.
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5
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Yuan D, Ji X, Hao S, Gestrich JY, Duan W, Wang X, Xiang Y, Yang J, Hu P, Xu M, Liu L, Wei H. Lamina feedback neurons regulate the bandpass property of the flicker-induced orientation response in Drosophila. J Neurochem 2020; 156:59-75. [PMID: 32383496 DOI: 10.1111/jnc.15036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 04/28/2020] [Accepted: 04/30/2020] [Indexed: 11/28/2022]
Abstract
Natural scenes contain complex visual cues with specific features, including color, motion, flicker, and position. It is critical to understand how different visual features are processed at the early stages of visual perception to elicit appropriate cellular responses, and even behavioral output. Here, we studied the visual orientation response induced by flickering stripes in a novel behavioral paradigm in Drosophila melanogaster. We found that free walking flies exhibited bandpass orientation response to flickering stripes of different frequencies. The most sensitive frequency spectrum was confined to low frequencies of 2-4 Hz. Through genetic silencing, we showed that lamina L1 and L2 neurons, which receive visual inputs from R1 to R6 neurons, were the main components in mediating flicker-induced orientation behavior. Moreover, specific blocking of different types of lamina feedback neurons Lawf1, Lawf2, C2, C3, and T1 modulated orientation responses to flickering stripes of particular frequencies, suggesting that bandpass orientation response was generated through cooperative modulation of lamina feedback neurons. Furthermore, we found that lamina feedback neurons Lawf1 were glutamatergic. Thermal activation of Lawf1 neurons could suppress neural activities in L1 and L2 neurons, which could be blocked by the glutamate-gated chloride channel inhibitor picrotoxin (PTX). In summary, lamina monopolar neurons L1 and L2 are the primary components in mediating flicker-induced orientation response. Meanwhile, lamina feedback neurons cooperatively modulate the orientation response in a frequency-dependent way, which might be achieved through modulating neural activities of L1 and L2 neurons.
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Affiliation(s)
- Deliang Yuan
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Xiaoxiao Ji
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Shun Hao
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Julia Yvonne Gestrich
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China
| | - Wenlan Duan
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Xinwei Wang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Yuanhang Xiang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Jihua Yang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Pengbo Hu
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
| | - Mengbo Xu
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China
| | - Li Liu
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China.,CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Hongying Wei
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R. China.,College of Life Sciences, University of the Chinese Academy of Sciences, Beijing, P. R. China
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