Using claudin-2 to mark mossy fibers in the mouse hippocampus

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

The purpose of the present study was to test the possibility of identifying hippocampal mossy fiber projections by staining mouse brain sections with antibodies to the claudin-2 protein.

Material and methods: the subjects of the study were 9 male wild mice. Serial frontal sections of the brain were prepared using a cryostat. In order to identify hippocampal mossy fiber projections, sections were immunohistochemically stained with polyclonal antibodies to the claudin-2 protein and analyzed under a fluorescence microscope. The resulting images were processed in ZEN and ImageJ software, then the morphometric parameters were compared with literature data on staining of mossy fibers with antibodies to the zinc transporter ZNT3.

Results: Our results suggest that claudin-2 can be used as a marker of hippocampal mossy fibers in mice. The staining pattern obtained with antibodies to claudin-2 replicates that obtained with Timm staining of mossy fibers or with antibodies to the zinc transporter ZNT3: intense staining of the hilus of the dentate gyrus, with a clear pattern of infra- and suprapyramidal mossy fibers, including in the area of the stratum lucidum. The total area of dorsal hippocampal mossy fibers identified by claudin-2 antibodies was not statistically significantly different from the area measured by ZNT3 staining.

Conclusion: Immunohistochemical staining of mouse brain sections for claudin-2 can be used to identify hippocampal mossy fibers.

Full Text

Restricted Access

About the authors

Ainazik Ismailova

Immanuel Kant Baltic Federal University

Author for correspondence.
Email: aiismailova@stud.kantiana.ru
ORCID iD: 0009-0002-5162-3884

student, Educational and scientific cluster “Institute of Medicine and Life Sciences (MEDBIO)”, High School of life sciences, Laboratory for Synthetic biology

Russian Federation, ul. Universitetskaya, 2, Kaliningrad, 236041

Ksenia Vladimirovna Ichetkina

Immanuel Kant Baltic Federal University

Email: ksenya.ichetkina@gmail.com
ORCID iD: 0009-0004-8519-3354

student, Educational and scientific cluster “Institute of Medicine and Life Sciences (MEDBIO)”, High School of life sciences, Laboratory for Synthetic biology

Russian Federation, ul. Universitetskaya, 2, Kaliningrad, 236041, Russian Federation

Ekaterina Alexandrovna Kurilova

Immanuel Kant Baltic Federal University

Email: ekaterinakuuurilova@gmail.com
ORCID iD: 0000-0003-0031-116X

PhD student of High School of life sciences, Institute of Medicine and Life Sciences (MEDBIO), Laboratory for Synthetic biology

Russian Federation, ul. Universitetskaya, 2, Kaliningrad, 236041, Russian Federation

Oksana Pavlovna Tuchina

Immanuel Kant Baltic Federal University

Email: otuchina@kantiana.ru
ORCID iD: 0000-0003-1480-1311

head of laboratory for Synthetic biology, Educational and scientific cluster “Institute of Medicine and Life Sciences (MEDBIO)”, High School of life sciences, Laboratory for Synthetic biology, Candidate of Biological Sciences, Associate Professor 

Russian Federation, ul. Universitetskaya, 2, Kaliningrad, 236041

References

  1. Global nutrition targets 2025: childhood overweight policy brief. https://www.who.int/publications-detail-redirect/WHO-NMH-NHD-14.6. Accessed 26 May 2024/
  2. Ley R.E., Turnbaugh P.J., Klein S., Gordon J.I. Human gut microbes associated with obesity. Nature. 2006; 444: 1022–23. https://doi.org/10.1038/4441022a.
  3. Santacruz A., Collado M.C., GarcIa-Valdés L., Segura M.T., MartIn-Lagos J.A., Anjos T., MartI-Romero M., Lopez R.M., Florido J., Campoy C., Sanz Y. Gut microbiota composition is associated with body weight, weight gain and biochemical parameters in pregnant women. Br. J. Nutr. 2010; 104: 83–92. https://doi.org/10.1017/S0007114510000176.
  4. Turnbaugh P.J., Ley R.E., Mahowald M.A., Magrini V., Mardis E.R., Gordon J.I. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006; 444: 1027–31. https://doi.org/10.1038/nature05414.
  5. Sanchez-Alcoholado L., Castellano-Castillo D., Jordán-MartInez L., Moreno-Indias I., Cardila-Cruz P., Elena D., Muñoz-Garcia A.J., Queipo-Ortuño M.I., Jimenez-Navarro M. Role of Gut Microbiota on Cardio-Metabolic Parameters and Immunity in Coronary Artery Disease Patients with and without Type-2 Diabetes Mellitus. Front Microbiol. 2017; 8: 1936. https://doi.org/10.3389/fmicb.2017.01936.
  6. Корниенко Е.А. Современные представления о взаимосвязи ожирения и кишечной микробиоты. Педиатр. 2013; 4 (3): 3–14. https://doi.org/10.24412/FHG3C-ZTKP8. [Kornienko E.A. Sovremennye predstavleniya o vzaimosvyazi ozhireniya i kishechnoj mikrobioty. Pediatr. 2013; 4 (3): 3–14. https://doi.org/10.24412/FHG3C-ZTKP8 (in Russian)].
  7. Blacher E., Levy M., Tatirovsky E., Elinav E. Microbiome-Modulated Metabolites at the Interface of Host Immunity. J. Immunol. 2017; 198: 572–80. https://doi.org/10.4049/jimmunol.1601247.
  8. Rakoff-Nahoum S., Paglino J., Eslami-Varzaneh F., Edberg S., Medzhitov R. Recognition of Commensal Microflora by Toll-Like Receptors Is Required for Intestinal Homeostasis. Cell. 2004; 118: 229–41. https://doi.org/10.1016/j.cell.2004.07.002.
  9. Шестопалов А.В., Дворников А.С., Борисенко О.В., Тутельян А.В. Трефоиловые факторы-новые маркеры мукозального барьера желудочно-кишечного тракта. Российский Журнал Инфекция и Иммунитет. 2019; 9: 39–46. https://doi.org/10.15789/2220-7619-2019-1-39-46. [Shestopalov A.V., Dvornikov A.S., Borisenko O.V., Tutelyan A.V. Trefoil factors – new markers of gastrointestinal mucosal barrier. Russian Journal of Infection and Immunity. 2019; 9 (1): 39–46. https://doi.org/10.15789/2220-7619-2019-1-39-46 (in Russian)].
  10. Шестопалов А.В., Колесникова И.М., Савчук Д.В., Теплякова Е.Д., Шин В.А., Григорьева Т.В., Набока Ю.Л., Гапонов А.М., Румянцев С.А. Влияние вида вскармливания на таксономический состав кишечного микробиома и уровни трефоиловых факторов у детей и подростков. Российский Физиологический Журнал им. И.М. Сеченова. 2023; 109: 656–72. https://doi.org/10.31857/S0869813923050096. [Shestopalov A.V., Kolesnikova I.M., Savchuk D.V., Teplyakova E.D., Shin V.A., Grigoryeva T.V., Naboka Y.L., Gaponov A.M., Roumiantsev S.A. Influence of the Infant Feeding on the Taxonomy of the Gut Microbiome and the Trefoil Factors Level in Children and Adolescents. Rossijskij fiziologiceskij zhurnal im. I.M. Sechenova. 2023; 109 (5): 656–72. https://doi.org/10.31857/S0869813923050096 (in Russian)].
  11. Kolesnikova I.M., Ganenko L.A., Vasilyev I.Yu., Grigoryeva T.V., Volkova N.I., Roumiantsev S.A., Shestopalov A.V. Metabolic Profile of Gut Microbiota and Levels of Trefoil Factors in Adults with Different Metabolic Phenotypes of Obesity. Mol Biol. 2024; 58: 728–44. https://doi.org/10.1134/S0026893324700316.
  12. Скворцова О.В., Мигачева Н.Б., Михайлова Е.Г. Иммунометаболические аспекты хронического неспецифического воспаления на фоне ожирения. Медицинский Совет. 2023; 75–82. https://doi.org/10.21518/ms2023-187. [Skvortsova O.V., Migacheva N.B., Mikhailova E.G. Immunometabolic aspects of chronic nonspecific inflammation in obesity. Meditsinskiy Sovet. 2023; 75–82. https://doi.org/10.21518/ms2023-187 (in Russian)].
  13. Schwartz C., Schmidt V., Deinzer A., Hawerkamp H.C., Hams E., Bayerlein J., Röger O., Bailer M., Krautz C., El Gendy A., Elshafei M., Heneghan H.M., Hogan A.E., O’Shea D., Fallon P.G. Innate PD-L1 limits T cell–mediated adipose tissue inflammation and ameliorates diet-induced obesity. Sci Transl Med. 2022; 14: 6879. https://doi.org/10.1126/scitranslmed.abj6879.
  14. Teijeiro A., Garrido A., Ferre A., Perna C., Djouder N. Inhibition of the IL-17A axis in adipocytes suppresses diet-induced obesity and metabolic disorders in mice. Nat Metab. 2021; 3: 496–12. https://doi.org/10.1038/s42255-021-00371-1.
  15. Douzandeh-Mobarrez B., Kariminik A. Gut Microbiota and IL-17A: Physiological and Pathological Responses. Probiotics Antimicrob Proteins. 2019; 11: 1–10. https://doi.org/10.1007/s12602-017-9329-z.
  16. Кирилина И.В., Шестопалов А.В., Гапонов А.М., Камальдинова Д.Р., Хуснутдинова Д.Р., Григорьева Т.В., Теплякова Е.Д., Юдин С.М., Макаров В.В., Румянцев А.Г., Борисенко О.В., Румянцев С.А. Особенности микробиома крови у детей с ожирением. Педиатрия имени Г.Н. Сперанского. 2022; 101 (5): 15–22. https://doi.org/10.24110/0031-403X-2022-101-5-15-22. [Kirilina I.V., Shestopalov A.V., Gaponov A.M., Kamaldinova D.R., Khusnutdinova D.R., Grigorieva T.V., Teplyakova E.D., Yudin S.M., Makarov V.V., Rumyantsev A.G., Borisenko O.V., Rumyantsev S.A. Features of the blood microbiome in obese children. Pediatria n.a. G.N. Speransky. 2022; 101 (5): 15–22. https://doi.org/10.24110/0031-403X-2022-101-5-15-22 (in Russian)].
  17. Murthy KGK., Deb A., Goonesekera S., SzabóC., Salzman A.L. Identification of Conserved Domains in Salmonella muenchen Flagellin That Are Essential for Its Ability to Activate TLR5 and to Induce an Inflammatory Response in Vitro. J. Biol. Chem. 2004; 279: 5667–75. https://doi.org/10.1074/jbc.M307759200.
  18. Bambou J-C., Giraud A., Menard S., Begue B., Rakotobe S., Heyman M., Taddei F., Cerf-Bensussan N., Gaboriau-Routhiau V. In Vitro and ex Vivo Activation of the TLR5 Signaling Pathway in Intestinal Epithelial Cells by a Commensal Escherichia coli Strain. J. Biol. Chem. 2004; 279: 42984–92. https://doi.org/10.1074/jbc.M405410200.
  19. Wu Z., Pan D., Guo Y., Sun Y., Zeng X. Peptidoglycan diversity and anti-inflammatory capacity in Lactobacillus strains. Carbohydr Polym. 2015; 128: 130–37. https://doi.org/10.1016/j.carbpol.2015.04.026.
  20. Wu Z., Pan D., Guo Y., Zeng X. Structure and anti-inflammatory capacity of peptidoglycan from Lactobacillus acidophilus in RAW-264.7 cells. Carbohydr Polym. 2013; 96: 466–73. https://doi.org/10.1016/j.carbpol.2013.04.028.
  21. Kwan JMC, Liang Y., Ng EWL., Sviriaeva E., Li C., Zhao Y., Zhang X-L., Liu X-W., Wong S.H., Qiao Y. In silico MS/MS prediction for peptidoglycan profiling uncovers novel anti-inflammatory peptidoglycan fragments of the gut microbiota. Chem Sci. 2024; 15 (5): 1846–59. https://doi.org/ 10.1039/d3sc05819k.
  22. Grangette C., Macho-Fernandez E., Pot B. Anti-inflammatory capacity of lactobacilli peptidoglycan: mucosal and systemic routes of administration promote similar effects – The Authors’ reply. Gut. 2012; 61: 784. https://doi.org/10.1136/gutjnl-2011-301194.
  23. Rhee S.H., Im E., Riegler M., Kokkotou E., O’Brien M., Pothoulakis C. Pathophysiological role of Toll-like receptor 5 engagement by bacterial flagellin in colonic inflammation. Proc Natl Acad Sci. 2005; 102 (38): 13610–5. https://doi.org/10.1073/pnas.0502174102.
  24. Yoon S., Kurnasov O., Natarajan V., Hong M., Gudkov A.V., Osterman A.L., Wilson I.A. Structural Basis of TLR5-Flagellin Recognition and Signaling. Science. 2012; 335: 859–64. https://doi.org/10.1126/science.1215584.
  25. Vijay-Kumar M., Gewirtz A.T. Flagellin: key target of mucosal innate immunity. Mucosal Immunol. 2009; 2: 197–205. https://doi.org/10.1038/mi.2009.9.
  26. Feng S., Zhang C. Chen S. He R., Chao G, Zhang S. TLR5 Signaling in the Regulation of Intestinal Mucosal Immunity. J. Inflamm Res. 2023; (16): 2491–01. https://doi.org/10.2147/JIR.S407521.
  27. Kukhtina N.B., Arefieva T.I., Ruleva N.Yu., Sidorova M.V., Azmuko A.A., Bespalova Zh.D., Krasnikova T.L. Peptide fragments of the fractalkine chemokine domain: Influence on migration of human monocytes. Russ J. Bioorganic Chem. 2012; (38): 584–89. https://doi.org/10.1134/S1068162012060088.
  28. McGinley A.M., Sutton C.E., Edwards S.C., Leane C.M., DeCourcey J., Teijeiro A., Hamilton J.A., Boon L., Djouder N., Mills KHG. Interleukin-17A Serves a Priming Role in Autoimmunity by Recruiting IL-1β-Producing Myeloid Cells that Promote Pathogenic T Cells. Immunity. 2020; (52): 342–56. https://doi.org/10.1016/j.immuni.2020.01.002.
  29. Ishigame H., Kakuta S., Nagai T., Kadoki M., Nambu A., Komiyama Y., Fujikado N., Tanahashi Y., Akitsu A., Kotaki H., Sudo K., Nakae S. Sasakawa C., Iwakura Y. Differential Roles of Interleukin-17A and -17F in Host Defense against Mucoepithelial Bacterial Infection and Allergic Responses. Immunity. 2009; 30: 108–19. https://doi.org/10.1016/j.immuni.2008.11.009.
  30. Kumar P., Chen K., Kolls J.K. Th17 cell based vaccines in mucosal immunity. Curr Opin Immunol. 2013; 25: 373–80. https://doi.org/10.1016/j.coi.2013.03.011.
  31. Mills KHG. Induction, function and regulation of IL-17-producing T cells. Eur J Immunol. 2008; 38: 2636–49. https://doi.org/10.1002/eji.200838535.
  32. Beenen A.C., Sauerer T., Schaft N., Dörrie J. Beyond Cancer: Regulation and Function of PD-L1 in Health and Immune-Related Diseases. Int. J. Mol. Sci. 2022; 23: 8599. https://doi.org/10.3390/ijms23158599.
  33. Kawamura N., Katsuura G., Yamada-Goto N., Nakama R., Kambe Y., Miyata A., Furuyashiki T., Narumiya S., Ogawa Y., Inui A. Brain fractalkine-CX3CR1 signalling is anti-obesity system as anorexigenic and anti-inflammatory actions in diet-induced obese mice. Sci Rep. 2022; 12: 12604. https://doi.org/10.1038/s41598-022-16944-3.
  34. PolyákÁ., Ferenczi S., DénesÁ., Winkler Z., Kriszt R., Pintér-Kübler B., Kovács K.J. The fractalkine/Cx3CR1 system is implicated in the development of metabolic visceral adipose tissue inflammation in obesity. Brain Behav Immun. 2014; 38: 25–35. https://doi.org/10.1016/j.bbi.2014.01.010.
  35. Hoffmann W. Trefoil Factor Family (TFF) Peptides and Their Diverse Molecular Functions in Mucus Barrier Protection and More: Changing the Paradigm. Int. J. Mol. Sci. 2020; 21: 4535. https://doi.org/10.3390/ijms21124535.

Supplementary files

Supplementary Files
Action
1. JATS XML
2. Fig. 1.Identification of hippocampal mossy fibers using antibodies to claudin-2. А–И micrographs of the mouse brain hippocampal frontal slices, in a rostral-caudal orientation Note.CA1, CA2, CA3 – cornu Ammonis 1, 2, 3 hippocampal regions; DG – gyrus dentatus, dentate gyrus; DG-po, DG-mo, DG-gs – polymorphic, molecular and granular layers of the dentate gyrus; Fi – fimbria hippocampi, fimbria of hippocampus; TH – thalamus, thalamus.

Download (358KB)
3. Fig. 2.Identification of hippocampal mossy fibers using antibodies to claudin-2. А – И micrographs of the mouse brain hippocampal frontal slices, in a rostral-caudal orientation Note.CA1, CA2, CA3 – cornu Ammonis 1, 2, 3 hippocampal regions; DG – gyrus dentatus, dentate gyrus; Fi – fimbria hippocampi, fimbria of hippocampus. H – hilus, polymorphic layer of the dentate gyrus; SP – suprapyramidal mossy fibers; IP – infrapyramidal mossy fibers; the solid line indicates measurable total area of the mossy fibers of the dorsal hippocampus, the dotted line indicates the measurement of the length of supra- and infrapyramidal fibers.

Download (149KB)
4. Fig. 3.Distribution pattern of hippocampal mossy fibers and CA3 pyramidal neurons. А – micrograph of the hippocampus on a frontal section of a mouse brain stained with antibodies to claudin-2 and a schematic representation of granule neurons, mossy fibers and pyramidal neurons of the CA3 region. Б – scheme of the proposed location and interactions of claudin-2 with other synaptic contact proteins Note.CA3 – cornu Ammonis 3 hippocampal region; DG – gyrus dentatus, dentate gyrus; DG-po, DG-mo, DG-gs – polymorphic, molecular and granular layers of the dentate gyrus; sl – stratum lucidum CA3; the arrow shows the contact en passant, the double arrow shows large buds with filopodia; AMPAR, NMDAR – glutamate receptors, Glu – glutamate, ZnT3 – zinc transporter, Claudin-2 – claudin-2, EphrinB-EphB2 – ephrins.

Download (154KB)
5. Comparison of morphometric parameters when staining dorsal hippocampal mossy fibers for claudin-2 and zinc transporter ZNT3

Download (90KB)

Copyright (c) 2025 Russkiy Vrach Publishing House