Поведенческий профиль и состав кишечной микробиоты у крыс с различной возбудимостью нервной системы

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Предыдущие исследования показали, что две линии крыс, селектированные по порогу возбудимости нервной системы в ответ на длительное эмоционально-болевое стрессирование, проявляют различия как на поведенческом, так и на нейробиологическом и молекулярно-генетическом уровнях, а также специфические изменения выявляются и в составе кишечного микробиома. Это указывает на потенциальную связь между генетическими факторами, микробиотой и нарушениями поведения. Целью данного исследования являлся анализ кишечной микробиоты и поведенческих профилей интактных крыс линий с высоким (ВП) и низким (НП) порогами возбудимости нервной системы для выявления ключевых различий, обусловленных их генетическими особенностями. Поведение интактных крыс двух линий было проанализировано в тестах “Открытое поле” и “Приподнятый крестообразный лабиринт”, анализ микробиоты в образцах стула проведен с использованием ампликонного секвенирования гена 16S рРНК. Поведенческий анализ показал, что высоковозбудимые крысы (линия НП) демонстрировали более высокую активность и менее выраженное замирание в приподнятом крестообразном лабиринте по сравнению с низковозбудимыми крысами (линия ВП). Показатели альфа-разнообразия микробиоты кишечника не различались между линиями, но анализ бета-разнообразия показал значимые различия в микробных профилях между линиями ВП и НП. Крысы линии НП имеют значимо более высокую по сравнению с линией ВП представленность родов Lactobacillus и Faecalibacterium, в то время как у крыс линии ВП выше относительная представленность родов Romboutsia, Eubacterium и Turicibacter. Интеграция данных о поведении и микробиоте выявляет потенциальную взаимосвязь между генетическими факторами, профилями кишечного микробиома и уникальными физиологическими и поведенческими характеристиками линий крыс, селектированных по порогу возбудимости нервной системы.

Об авторах

И. Г. Шалагинова

Балтийский федеральный университет им. Иммануила Канта; Институт физиологии им. И.П. Павлова РАН

Email: shalaginova_i@mail.ru
Калининград, Россия; Санкт-Петербург, Россия

Д. С. Кацеров

Балтийский федеральный университет им. Иммануила Канта

Калининград, Россия

К. О. Энш

Балтийский федеральный университет им. Иммануила Канта

Калининград, Россия

Е. А. Буденкова

Балтийский федеральный университет им. Иммануила Канта

Калининград, Россия

А. К. Прибышина

Институт физиологии им. И.П. Павлова РАН

Санкт-Петербург, Россия

Н. А. Дюжикова

Институт физиологии им. И.П. Павлова РАН

Санкт-Петербург, Россия

Список литературы

  1. Vaido AI, Shiryaeva NV, Pavlova MB, Levina AS, Khlebaeva DA, Lyubashina OA, Dyuzhikova NA (2018) Selected rat strains Ht, Lt as a model for the study of dysadaptation states dependent on the level of excitability of the nervous system. Lab Animals for Sci 3. https://doi.org/10.29296/2618723X-2018-03-02
  2. Shiryaeva NV, Vshivtseva VV, Mal’tsev NA, Sukhorukov VN, Vaido AI (2008) Neuron density in the hippocampus in rat strains with contrasting nervous system excitability after prolonged emotional-pain stress. Neurosci Behav Physiol 38: 355–357. https://doi.org/10.1007/S11055-008-0049-4
  3. Shalaginova IG, Tuchina OP, Sidorova MV, Levina AS, Khlebaeva DA, Vaido AI, Dyuzhikova NA (2021) Effects of psychogenic stress on some peripheral and central inflammatory markers in rats with the different level of excitability of the nervous system. PLoS One 16: e0255380. https://doi.org/10.1371/journal.pone.0255380
  4. Shevchenko A, Shalaginova I, Katserov D, Matskova L, Shiryaeva N, Dyuzhikova N (2023) Post-stress changes in the gut microbiome composition in rats with different levels of nervous system excitability. PLoS One 18: e0295709. https://doi.org/10.1371/journal.pone.0295709
  5. Shalaginova IG, Tuchina OP, Turkin AV, Vylegzhanina AE, Nagumanova AN, Zachepilo TG, Dyuzhikova NA (2023) The effect of long-term emotional and painful stress on the expression of proinflammatory cytokine genes in rats with high and low excitability of the nervous system. Russ J Physiol 109(4): 545–558 (In Russ). https://doi.org/ 10.31857/S0869813923040088
  6. Shcherbinina V, Pavlova M, Daev E, Dyuzhikova N (2024) Rats selected for different nervous excitability: long-term emotional-painful stress affects the dynamics of DNA damage in cells of several brain areas. Int J Mol Sci 25: 994. https://doi.org/10.3390/ijms25020994
  7. Van averbeke V, Berkell M, Mysara M, Rodriguez-Ruiz JP, Xavier BB, De Winter FHR, Jongers B‘, Jairam RK, Hotterbeekx A, Goossens H, Cohen ES, Malhotra-Kumar S and Kumar-Singh S (2022) Host Immunity Influences the Composition of Murine Gut Microbiota. Front Immunol 13: 828016. https://doi.org/10.3389/fimmu.2022.828016
  8. Paone P, Cani PD (2020) Mucus barrier, mucins and gut microbiota: the expected slimy partners? Gut 69: 2232–2243. https://doi.org/10.1136/gutjnl-2020-322260
  9. Dzierozynski L, Queen J, Sears CL (2023) Subtle, persistent shaping of the gut microbiome by host genes: A critical determinant of host biology. Cell Host Microb 31(10): 1569–1573. https://doi.org/10.1016/j.chom.2023.09.007
  10. Clarke G, Grenham S, Scully P, Fitzgerald P, Moloney RD, Shanahan F, Dinan TG, Cryan JF (2013) The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Mol Psychiatry 18: 666–673. https://doi.org/10.1038/mp.2012.77
  11. Sorboni SG, Moghaddam HS, Jafarzadeh-Esfehani R, Soleimanpour S (2022) A comprehensive review on the role of the gut microbiome in human neurological disorders. Clin Microbiol Rev 35: e00338-20. https://doi.org/10.1128/CMR.00338-20
  12. Lof J, Smits K, Melotte V, Kuil LE (2022) The health effect of probiotics on high-fat diet-induced cognitive impairment, depression and anxiety: a cross-species systematic review. Neurosci Biobehav Rev 136: 104634. https://doi.org/10.1016/j.neubiorev.2022.104634
  13. Laukens D, Brinkman BM, Raes J, De Vos M, Vandenabeele P (2016) Heterogeneity of the gut microbiome in mice: guidelines for optimizing experimental design. FEMS Microbiol Rev 40: 117–132. https://doi.org/10.1093/femsre/fuv036
  14. Toshchakov SV, Izotova AO, Vinogradova EN, Kachmazov GS, Tuaeva AY, Abaev VT (2021) Culture-independent survey of thermophilic microbial communities of the North Caucasus. Biology 10: 1352. https://doi.org/10.3390/biology10121352
  15. Gohl DM, Vangay P, Garbe J, MacLean A, Hauge A, Becker A (2016) Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies. Nat Biotechnol 34: 942–949. https://doi.org/10.1038/nbt.3656
  16. Fox J, Weisberg S, Adler D, Bates D, Baud-Bovy G, Ellison S, Heiberger R (2012) Package ‘car’. Vienna: R Found Stat Comput 16: 332–333.
  17. Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, Suggests MASS (2007) The vegan package. Commun ecol package 10: 631–637.
  18. Wickham H (2016) Programming with ggplot2. Ggplot2: elegant graphics for data analysis 241–253.
  19. Renaud G, Stenzel U, Maricic T, Wiebe V, Kelso J (2015) deML: robust demultiplexing of Illumina sequences using a likelihood-based approach. Bioinformatics 31: 770–772. https://doi.org/10.1093/bioinformatics/btu719
  20. Bolyen E, Rideout JR, Dillon MR (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37: 852–857. https://doi.org/10.1038/s41587-019-0209-9
  21. Lu Y, Zhou G, Ewald J, Pang Z, Shiri T, Xia J (2023) MicrobiomeAnalyst 2.0: comprehensive statistical, functional and integrative analysis of microbiome data. Nucleic Acids Res 51. https://doi.org/10.1093/nar/gkad407
  22. De Marco P, Henriques AC, Azevedo R, Sá SI, Cardoso A, Fonseca B, Barbosa J, Leal S (2021) Gut microbiome composition and metabolic status are differently affected by early exposure to unhealthy diets in a rat model. Nutrients 13: 3236. https://doi.org/10.3390/nu13093236
  23. Grigor’eva IN (2020) Gallstone disease, obesity and the firmicutes/bacteroidetes ratio as a possible biomarker of gut dysbiosis. J Pers Med 11: 13. https://doi.org/10.3390/jpm11010013
  24. Stojanov S, Berlec A, Štrukelj B (2020) The influence of probiotics on the firmicutes/bacteroidetes ratio in the treatment of obesity and inflammatory bowel disease. Microorganisms 8: 1715. https://doi.org/10.3390/microorganisms8111715
  25. Xu Z (2022) Gut microbiota in patients with obesity and metabolic disorders – A systematic review. Genes Nutr 17: 2. https://doi.org/10.1007/s12263-021-00693-y
  26. Hantsoo L, Zemel BS (2021) Stress gets into the belly: early life stress and the gut microbiome. Behav Brain Res 414: 113474. https://doi.org/10.1016/j.bbr.2021.113474
  27. Magne F, Gotteland M, Gauthier L, Zazueta A, Pesoa S, Navarrete P, Balamurugan R (2020) The firmicutes/bacteroidetes ratio: a relevant marker of gut dysbiosis in obese patients? Nutrients 12: 1474. https://doi.org/10.3390/nu12051474
  28. Dong Y, Han M, Fei T (2024) Utilization of diverse oligosaccharides for growth by Bifidobacterium and Lactobacillus species and their in vitro co-cultivation characteristics. Int Microbiol 27: 941–952. https://doi.org/10.1007/s10123-023-00446-x
  29. Fusco W, Lorenzo MB, Cintoni M (2023) Short-chain fatty-acid-producing bacteria: key components of the human gut microbiota. Nutrients 15: 2211. https://doi.org/10.3390/nu1509221
  30. Zhang K (2019) Abnormal composition of gut microbiota is associated with resilience versus susceptibility to inescapable electric stress. Transl Psychiatry 9: 231. https://doi.org/10.1038/s41398-019-0571-x
  31. Mindus C (2021) Lactobacillus-based probiotics reduce the adverse effects of stress in rodents: a meta-analysis. Front Behav Neurosci 15: 642757. https://doi.org/10.3389/fnbeh.2021.642757
  32. Caporaso JG, Lauber CL, Costello EK (2011) Moving pictures of the human microbiome. Genome Biol 12: R50. https://doi.org/10.1186/gb-2011-12-5-r50
  33. Claesson M, Jeffery I, Conde S (2012) Gut microbiota composition correlates with diet and health in the elderly. Nature 488: 178–184. https://doi.org/10.1038/nature11319
  34. Meng C, Feng S, Hao Z, Dong C, Liu H (2020) Changes in gut microbiota composition with age and correlations with gut inflammation in rats. PLoS One 17: e0265430. https://doi.org/10.1371/journal.pone.0265430
  35. Neu AT, Allen EE, Roy K (2021) Defining and quantifying the core microbiome: challenges and prospects. Proc Natl Acad Sci U S A 118: e2104429118. https://doi.org/10.1073/pnas.2104429118
  36. Mukherjee A, Lordan C, Ross RP, Cotter PD (2020) Gut microbes from the phylogenetically diverse genus Eubacterium and their various contributions to gut health. Gut Microbes 12: 1802866. https://doi.org/10.1080/19490976.2020.1802866
  37. Yassour M, Lim MY, Yun HS (2016) Sub-clinical detection of gut microbial biomarkers of obesity and type 2 diabetes. Genome Med 8: 17. https://doi.org/10.1186/s13073-016-0271-6
  38. Liu G, Qiao Y, Zhang Y, Leng C, Chen H, Sun J, Fan X, Li A, Feng Z (2020) Metabolic profiles of carbohydrates in Streptococcus thermophilus during pH-controlled batch fermentation. Front Microbiol 11: 1131. https://doi.org/10.3389/fmicb.2020.01131
  39. Gerritsen J, Hornung B, Renckens B, van Hijum SAFT, Martins dos Santos V, Rijkers GT, Schaap PJ, de Vos WM, Smidt H (2017) Genomic and functional analysis of Romboutsia ilealis CRIBT reveals adaptation to the small intestine. Peer J 5: e3698. https://doi.org/10.7717/peerj.3698
  40. Rampanelli E, Romp N, Troise AD, Ananthasabesan J, Wu H, Gül IS, Bui TPN (2025) Gut bacterium Intestinimonas butyriciproducens improves host metabolic health: Evidence from cohort and animal intervention studies. Microbiome 13: 15.
  41. Seegers J, Bui T, de Vos WM (2021) Remarkable metabolic versatility of the commensal bacteria Eubacterium hallii and Intestinimonas butyriciproducens: potential next-generation therapeutic microbes. In: Mojgani N, Dadar M (eds) Probiotic bacteria and postbiotic metabolites: role in animal and human health. Microorganisms for Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-16-0223-8_5
  42. La Reau AJ, Suen G (2018) The Ruminococci: key symbionts of the gut ecosystem. J Microbiol 56: 199–208. https://doi.org/10.1007/s12275-018-8024-4
  43. Cao Q, Sun X, Rajesh K, Chalasani N, Gelow K, Katz B, Shah VH, Sanyal AJ, Smirnova E (2021) Effects of rare microbiome taxa filtering on statistical analysis. Front Microbiol 11: 607325. https://doi.org/10.3389/fmicb.2020.607325
  44. Lynch JB, Gonzalez EL, Choy K (2023) Gut microbiota Turicibacter strains differentially modify bile acids and host lipids. Nat Commun 14: 3669. https://doi.org/10.1038/s41467-023-39403-7
  45. Hoek KL, McClanahan KG, Latour YL, Shealy N, Piazuelo MB, Vallance BA, Byndloss MX, Wilson KT, Olivares-Villagómez D (2023) Turicibacterales protect mice from severe Citrobacter rodentium infection. Infect Immun 91: e00322-23. https://doi.org/10.1128/IAI.00322-23
  46. Zhang L, Jing J, Han L, Wang J, Zhang W, Liu Z (2021) Characterization of gut microbiota, metabolism and cytokines in benzene-induced hematopoietic damage. Ecotoxicol Environ Saf 228: 112956. https://doi.org/10.1016/j.ecoenv.2021.112956
  47. Misiak B, Pawlak E, Rembacz K, Kotas M, Żebrowska-Różańska P, Kujawa D (2024) Associations of gut microbiota alterations with clinical, metabolic, and immune-inflammatory characteristics of chronic schizophrenia. J Psychiatr Res 171: 152–160. https://doi.org/10.1016/j.jpsychires.2024.01.036
  48. Oñate FP, Chamignon C, Burz SD (2023) Adlercreutzia equolifaciens is an anti-inflammatory commensal bacterium with decreased abundance in gut microbiota of patients with metabolic liver disease. Int J Mol Sci 24: 12232. https://doi.org/10.3390/ijms241512232
  49. Wu X, Chen J, Xu M, Zhu D, Wang X, Chen Y, Yu L (2017) 16S rDNA analysis of periodontal plaque in chronic obstructive pulmonary disease and periodontitis patients. J Oral Microbiol 9: 1324725. https://doi.org/10.1080/20002297.2017.1324725
  50. Vacca M, Celano G, Calabrese FM (2020) The controversial role of human gut Lachnospiraceae. Microorganisms 8: 573. https://doi.org/10.3390/microorganisms8040573
  51. Hexun Z, Miyake T, Maekawa T (2023) High abundance of Lachnospiraceae in the human gut microbiome is related to high immunoscores in advanced colorectal cancer. Cancer Immunol Immunother 72: 315–326. https://doi.org/10.1007/s00262-022-03256-8
  52. McGaughey KD (2019) Relative abundance of Akkermansia spp. and other bacterial phylotypes correlates with anxiety- and depressive-like behavior following social defeat in mice. Sci Rep 9: 3281. https://doi.org/10.1038/s41598-019-40140-5
  53. Hao Z (2019) Faecalibacterium prausnitzii (ATCC 27766) has preventive and therapeutic effects on chronic unpredictable mild stress-induced depression-like and anxiety-like behavior in rats. Psychoneuroendocrinology 104: 132–142. https://doi.org/10.1016/j.psyneuen.2019.02.025
  54. Martín R, Miquel S, Chain F (2015) Faecalibacterium prausnitzii prevents physiological damages in a chronic low-grade inflammation murine model. BMC Microbiol 15: 67. https://doi.org/10.1186/s12866-015-0400-1
  55. Li LF, Zou HW, Song BL, Wang Y, Jiang Y, Li ZL, Niu QH, Liu YJ (2023) Increased Lactobacillus Abundance Contributes to Stress Resilience in Mice Exposed to Chronic Social Defeat Stress. Neuroendocrinology 113(5): 563–576. https://doi.org/10.1159/000528876
  56. Yano JM, Yu K, Donaldson GP, Shastri GG, Ann P, Ma L, Nagler CR, Ismagilov RF, Mazmanian SK, Hsiao EY (2015) Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161: 264–276. https://doi.org/10.1016/j.cell.2015.02.047
  57. Mansuy-Aubert V, Ravussin Y (2023) Short chain fatty acids: the messengers from down below. Front Neurosci 17: 1197759. https://doi.org/10.3389/fnins.2023.1197759
  58. Bonaz B, Bazin T and Pellissier S (2018) The Vagus Nerve at the Interface of the Microbiota-Gut-Brain Axis. Front Neurosci 12: 49. https://doi.org/10.3389/fnins.2018.00049
  59. Colombo AV, Sadler RK, Llovera G, Singh V, Roth S, Heindl S, Sebastian Monasor L, Verhoeven A, Peters F, Parhizkar S, Kamp F, Gomez de Aguero M, MacPherson AJ, Winkler E, Herms J, Benakis C, Dichgans M, Steiner H, Giera M, Haass C, Tahirovic S, Liesz A (2021) Microbiota-derived short chain fatty acids modulate microglia and promote Aβ plaque deposition. Elife 10: e59826. https://doi.org/.7554/eLife.59826
  60. Terry N, Margolis KG (2017) Serotonergic Mechanisms Regulating the GI Tract: Experimental Evidence and Therapeutic Relevance. Handb Exp Pharmacol 239: 319–342. https://doi.org/10.1007/164_2016_103
  61. Clarke G, Grenham S, Scully P, Fitzgerald P, Moloney RD, Shanahan F, Dinan TG, Cryan J (2013) The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Mol Psychiatry 18: 666–673. https://doi.org/10.1038/mp.2012.77
  62. Strandwitz P, Kim KH, Terekhova D, Liu JK, Sharma A, Levering J, McDonald D, Dietrich D, Ramadhar T, Lekbua A, Mroue N, Liston C, Stewart EG, Dubin MJ, Zengler K, Knight R, Gilbert JA, Clardy J, Lewis K (2019) GABA-modulating bacteria of the human gut microbiota. Nature Microbiol 4(3): 396–403. https://doi.org/10.1038/s41564-018-0307-3
  63. Wang Y, Tong Q, Ma SR, Zhao ZX, Pan LB, Cong L, Han P, Peng R, Yu H, Lin Y, Gao T, Shou Y, Li X, Zhang X, Zhang Z, Fu J, Wen B, Yu J, Cao X, Jiang JD (2021) Oral berberine improves brain dopa/dopamine levels to ameliorate Parkinson’s disease by regulating gut microbiota. Signal Transduct Targ Therapy 6(1): 77.
  64. Zheng D, Liwinski T, Elinav E (2020) Interaction between microbiota and immunity in health and disease. Cell Res 30: 492–506. https://doi.org/10.1038/s41422-020-0332-7
  65. Dąbrowska K, Witkiewicz W (2016) Correlations of Host Genetics and Gut Microbiome Composition. Front Microbiol 7: 1357. https://doi.org/10.3389/fmicb.2016.01357
  66. Korach-Rechtman H, Freilich S, Gerassy-Vainberg S, Buhnik-Rosenblau K, Danin-Poleg Y, Bar H, Kashi Y (2019) Murine Genetic Background Has a Stronger Impact on the Composition of the Gut Microbiota than Maternal Inoculation or Exposure to Unlike Exogenous Microbiota. Appl Environ Microbiol 85(18): e00826-19. https://doi.org/10.1128/AEM.00826-19

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