
www.nature.com/scientificreports OPEN Understanding complex dynamics of behavioral, neurochemical and transcriptomic changes induced by prolonged chronic unpredictable stress in zebrafsh Konstantin A. Demin1,2*, Anton M. Lakstygal1, Nataliya A. Krotova1,2, Alexey Masharsky3, Natsuki Tagawa4, Maria V. Chernysh1, Nikita P. Ilyin1, Alexander S. Taranov1, David S. Galstyan1,5, Ksenia A. Derzhavina2, Nataliia A. Levchenko1, Tatiana O. Kolesnikova1, Mikael S. Mor1, Marina L. Vasyutina2, Evgeniya V. Efmova1, Nataliia Katolikova1,7, Andrey D. Prjibelski8, Raul R. Gainetdinov1, Murilo S. de Abreu9, Tamara G. Amstislavskaya10,11, Tatyana Strekalova12,13,14 & Allan V. Kaluef6,15,16* Stress-related neuropsychiatric disorders are widespread, debilitating and often treatment-resistant illnesses that represent an urgent unmet biomedical problem. Animal models of these disorders are widely used to study stress pathogenesis. A more recent and historically less utilized model organism, the zebrafsh (Danio rerio), is a valuable tool in stress neuroscience research. Utilizing the 5-week chronic unpredictable stress (CUS) model, here we examined brain transcriptomic profles and complex dynamic behavioral stress responses, as well as neurochemical alterations in adult zebrafsh and their correction by chronic antidepressant, fuoxetine, treatment. Overall, CUS induced complex neurochemical and behavioral alterations in zebrafsh, including stable anxiety-like behaviors and serotonin metabolism defcits. Chronic fuoxetine (0.1 mg/L for 11 days) rescued most of the observed behavioral and neurochemical responses. Finally, whole-genome brain transcriptomic analyses revealed altered expression of various CNS genes (partially rescued by chronic fuoxetine), including infammation-, ubiquitin- and arrestin-related genes. Collectively, this supports zebrafsh as a valuable translational tool to study stress-related pathogenesis, whose anxiety and serotonergic defcits parallel rodent and clinical studies, and genomic analyses implicate neuroinfammation, structural neuronal remodeling and arrestin/ubiquitin pathways in both stress pathogenesis and its potential therapy. 1Institute of Translational Biomedicine, St. Petersburg State University, University Emb. 7-9, Saint-Petersburg, Russia. 2Institute of Experimental Medicine, Almazov National Medical Research Centre, Ministry of Healthcare of Russian Federation, Saint-Petersburg, Russia. 3Core Facility Centre for Molecular and Cell Technologies, St. Petersburg State University, Saint-Petersburg, Russia. 4Department of Biophysics and Biochemistry, Graduate School of Science, University of Tokyo, Tokyo, Japan. 5Laboratory of Preclinical Bioscreening, Granov Russian Research Center of Radiology and Surgical Technologies, Ministry of Healthcare of Russian Federation, Pesochny, Russia. 6School of Pharmacy, Southwest University, Chongqing, China. 7Institute of Cytology RAS, Saint-Petersburg, Russia. 8Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, Saint-Petersburg, Russia. 9University of Passo Fundo, Passo Fundo, Brazil. 10Laboratory of Biopsychiatry, Scientifc Research Institute of Physiology and Basic Medicine, Novosibirsk, Russia. 11School of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia. 12Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands. 13Laboratory of Psychiatric Neurobiology, Institute of Molecular Medicine, I.M. Sechenov First Moscow State Medical University, Moscow, Russia. 14Division of Molecular Psychiatry, Centre of Mental Health, University of Würzburg, Würzburg, Germany. 15Ural Federal University, Ekaterinburg, Russia. 16Laboratory of Cell and Molecular Biology and Neurobiology, Moscow Institute of Physics and Technology, Dolgoprudny, Russia. *email: deminkasci@ gmail.com; [email protected] Scientifc Reports | (2020) 10:19981 | https://doi.org/10.1038/s41598-020-75855-3 1 Vol.:(0123456789) www.nature.com/scientificreports/ Figure 1. A brief diagram outlining the study experimental design, including the chronic unpredictable stress (CUS) protocol and behavioral testing (see Table 1 for details of CUS stressors applied in the present study). NTT the novel tank test, LDT the light–dark test, SH shoaling test, ZTI the zebrafsh tail immobilization test, HPLC high-performance liquid chromatography, RNASeq RNA sequencing. Stress evokes multiple behavioral and physiological responses1,2, including neuroendocrine and immune defcits3–7, that may trigger common afective illnesses, such as anxiety, depression and post-traumatic stress disorder (PTSD)8–11. Widespread, debilitating and ofen treatment-resistant, these neuropsychiatric disorders represent an urgent unmet biomedical problem12–14, complicated by their multiple overlapping genetic and environmental determinants, and poor understanding of their mechanisms and risk factors 15,16. Animal models, especially employing rodents, are widely used to study stress biology and pathogenesis 17–19. Commonly utilizing various chronic unpredictable stress (CUS) protocols 20–24, such models typically expose rodents to continuous exposure to varying stressors for several weeks22,24–27, to evoke anxiety- and/or depression-like states28–30 and physiological alterations that resemble those observed clinically 31. A more recently recognized and historically less utilized model organism, the zebrafsh (Danio rerio) is rapidly becoming a critical species for translational neuroscience research, complementing rodent studies 32,33. For exam- ple zebrafsh demonstrate high genetic and physiological similarity to humans34,35, and possess major, evolutionar- ily conserved neurotransmitter systems 36,37 and shared central nervous system (CNS) morphology 38,39. Zebrafsh are also widely used in stress research40–42, ofen based on various aquatic CUS protocols adapted from rodent models43–47. Here, we utilize a rigorous 5-week CUS protocol, already established in our laboratory48, to examine brain transcriptomic changes and weekly dynamics of behavioral and neurochemical stress responses in adult zebrafsh (Fig. 1, Table 1), as well as their potential correction by fuoxetine, a common, clinically efcient and most prescribed selective serotonin reuptake inhibitor (SSRI) antidepressant. Results Te generalized linear models 1 (GZLM1) analyses were used in the present study to compare CUS and con- trol zebrafsh groups in the novel tank test (NTT) across all 5 weeks of stress, revealing signifcant Wald test efects for week, group for distance traveled, as well as the time spent in top, with signifcant within-week diferences between control and stressed fsh in all fve experimental weeks (Table 2, Supplementary Tables S2–S4). Tere were also signifcant group, week and week × group efects for time spent not moving, where the post-hoc Tukey’s test revealed only the signifcant diference within week group (control vs. stress) for week 2, but not other weeks (Table 2, Supplementary Tables S2–S4). We also found signifcant week and interaction, but not group, efects for the number of top entries, as Tukey’s test for week groups revealed signifcant diferences vs. control only at week 1 (Table 2, Supplementary Tables S2–S4). Finally, signifcant week, group and interaction efects were found for the latency to enter the top, whose post-hoc pairwise week comparisons revealed signifcant diferences from controls in weeks 2, 3 and 5 (Table 2, Supplementary Tables S2–S4). Generalized linear models 2 (GZLM2) analyses of CUS, fuoxetine and control groups at week 5 revealed signifcant NTT group efect for distance travelled, with signifcant diferences between stress vs. both control and fuoxetine by post-hoc Tukey’s test (Table 3). Tere was also signifcant group efect for time spent in top, with signifcant diferences in control vs. stress and vs. fuoxetine (Table 3). Finally, signifcant group efect was found for the latency to enter the top, yielding signifcant stress vs. control and vs. fuoxetine diferences, as assessed by the post-hoc Tukey’s test (Table 3). Applying GZLM1 analyses to the light–dark test (LDT), showed signifcant group and week × group efects for time spent in light. Post-hoc Tukey’s test comparison of the weeks revealed signifcant diferences between stress and control groups at weeks 1–3, but not other weeks of CUS (Table 2, Supplementary Tables S2–S4). In contrast, there were no signifcant efects for any predictor studied for the number of light entries (Table 2), and no group efects were observed in GZLM2 using the Wald test for the LDT endpoints (Table 3). Scientifc Reports | (2020) 10:19981 | https://doi.org/10.1038/s41598-020-75855-3 2 Vol:.(1234567890) www.nature.com/scientificreports/ Behavioral tests and CUS days Specifc CUS stress procedures sampling 1 Tank change → local hypothermia* 2 Net chasing (10 min) → novel objects added to the hometank **(6 h) 3 Crowding (2 h) → Air exposure *** 4 Darkness (24 h) 5 Food deprivation (24 h) 6 Water change → noise exposure in unfamiliar tank **** (4 h) 7 Alarm pheromone ***** → remixing cohorts Week 1 NTT/LDT 8 Bright light (4 h) → novel objects (8 h) ST 9 Crowding (2 h) + remixing cohorts → net chasing (15 min) ZTI 10 Noise exposure in unfamiliar tank **** (5 h) → water change Euthanasia, sampling 11 Darkness (24 h) 12 Food deprivation (24 h) 13 Air exposure → local hypothermia 14 Bright light (6 h) → alarm pheromone Week 2 NTT/LDT 15 Noise exposure in an unfamiliar tank (6 h) → remixing cohorts ST 16 Novel
Details
-
File Typepdf
-
Upload Time-
-
Content LanguagesEnglish
-
Upload UserAnonymous/Not logged-in
-
File Pages20 Page
-
File Size-