Cited by 238Gut microbiota and healthAlzheimer's disease research and treatmentsOral microbiology and periodontitis research

Shifts in gut microbiota composition in an APP/PSS1 transgenic mouse model of Alzheimer’s disease during lifespan

Bäuerl, C., Collado, M.C., Diaz Cuevas, A., Viña, J., Pérez Martínez, G.·2018·Letters in Applied Microbiology

Abstract

Alzheimer's disease (AD) is the most common form of dementia and one of the major causes of disability and dependency in older people. Accumulating evidences link gut microbiota with different diseases and its relationship with neurodegenerative diseases is becoming most intriguing. This study was aimed to compare the gut microbiota of transgenic APP/PS1 (TG) mice, a well-established deterministic mouse model of AD, with their C57BL/6 wild-type (WT) littermates. Faecal samples were collected from 3-, 6- and 24-month-old mice and analysed by pyrosequencing of the V1-V3 region of the bacterial 16S rRNA genes. Bacterial profiles were similar in all young mice (3 months old), and started to diverge so that 6-month-old WT and TG mice had different and more diverse microbiota. During ageing, Turicibacteriaceae (typical mice bacterial group) and Rikenellaceae increased in all groups, although total Bacteroidetes remained stable. TG mice were characterized by an increase in Proteobacteria after 6 months, particularly the genus Sutterella (Betaproteobacteria), interestingly also increased in autism disorder. Also, the inflammation related family Erysipelotrichaceae was more abundant in TG mice at 24 months compared to wild-type control. In summary, AD pathology in mice shifts the gut microbiota towards profiles that share features with autism and inflammatory disorders. SIGNIFICANCE AND IMPACT OF THE STUDY: Alzheimer's disease is a neurodegenerative disease and neuroinflammation in the central nervous system appears to have a pivotal role. Using the transgenic APP/PS1 (TG) mouse model, we successfully characterized how AD pathology shifted gut microbiota composition during ageing towards an inflammation related bacterial profile related to Proteobacteria and Erysipelotrichaceae and suggest that these changes could contribute to disease progression and severity. Microbiota-targeted interventions could therefore represent a strategy to postpone disease symptoms.

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Crossref · 10.1111/lam.12882

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Authors
Bäuerl, C., Collado, M. C., Diaz Cuevas, A., Viña, J., & Pérez Martínez, G.
Affiliations
  • Consejo Superior de Investigaciones Científicas (ES)
  • Central Research Unit-INCLIVA Faculty of Medicine University of Valencia Valencia Spain
  • Universitat de València (ES)
  • Department of Biotechnology Institute of Agrochemistry and Food Technology Consejo Superior de Investigaciones Científicas (Spanish National Research Council) Valencia Spain
Venue
Letters in Applied Microbiology
Published
2018-06-01
Volume
66
Issue
6
Pages
464-471
ISSN
  • 0266-8254 (ISSN-L)
  • 1472-765X
OpenAlex
W2791853645
Cited by
238
References
41
Citations by year
2026: 12 · 2025: 21 · 2024: 30 · 2023: 28 · 2022: 45 · 2021: 36 · 2020: 29 · 2019: 30 · 2018: 7
FWCI
9.06
Type
journal article
Language
en
Open access
closed
Locations
  • Letters in Applied Microbiology (publishedVersion)
  • PubMed (publishedVersion)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
Funders
Spanish Ministerio de Economia y Competitividad (AGL2015-70487-P)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
Keywords
Alzheimer's disease, gut microbiota, APP/PS1 mice, aging, neuroinflammation, Proteobacteria, Sutterella, Erysipelotrichaceae, Bacteroidetes, autism spectrum disorder, microbiota-targeted interventions, gut-brain axis
MeSH terms
Bacillota, Gastrointestinal Microbiome, Aging, Alzheimer Disease, Animals, Disease Models, Animal, Humans, Male, Mice, Inbred C57BL, Mice, Transgenic, RNA, Ribosomal, 16S, Proteobacteria, Bacteroidetes, Mice

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