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Cited by 665Alzheimer's disease research and treatmentsGut microbiota and healthNeuroinflammation and Neurodegeneration Mechanisms

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Antibiotic-induced perturbations in gut microbial diversity influences neuro-inflammation and amyloidosis in a murine model of Alzheimer’s disease

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Minter, Myles R., Zhang, Can, Leone, Vanessa, Ringus, Daina L., Zhang, Xiaoqiong, Oyler-Castrillo, Paul, Musch, Mark W., Liao, Fan, Ward, Joseph F., Holtzman, David M., Chang, Eugene B., Tanzi, Rudolph E., Sisodia, Sangram S.·2016·Scientific Reports
DOI 10.1038/srep30028PMC PMC4956742
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Abstract

Severe amyloidosis and plaque-localized neuro-inflammation are key pathological features of Alzheimer’s disease (AD). In addition to astrocyte and microglial reactivity, emerging evidence suggests a role of gut microbiota in regulating innate immunity and influencing brain function. Here, we examine the role of the host microbiome in regulating amyloidosis in the APP SWE /PS1 ΔE9 mouse model of AD. We show that prolonged shifts in gut microbial composition and diversity induced by long-term broad-spectrum combinatorial antibiotic treatment regime decreases Aβ plaque deposition. We also show that levels of soluble Aβ are elevated and that levels of circulating cytokine and chemokine signatures are altered in this setting. Finally, we observe attenuated plaque-localised glial reactivity in these mice and significantly altered microglial morphology. These findings suggest the gut microbiota community diversity can regulate host innate immunity mechanisms that impact Aβ amyloidosis.

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Figure 1 Composition of the gastrointestinal microbiome is altered in ABX-treated APPSWE/PS1ΔE9 mice. (A) Q-PCR analysis of isolated DNA from cecal contents of 6 month old male APPSWE/PS1ΔE9 mice analysing 16s rRNA gene copy number (n = 9–10). (B) Q-PCR analysis of isolated DNA from fecal contents of 6 month old male APPSWE/PS1ΔE9 mice analysing 16s rRNA gene copy number (n = 9–10). To obtain a 16s rRNA gene copy number value, expression levels were normalized to both DNA concentration and an amplification standard curve of a 16s rRNA gene-containing plasmid with known copy number. Illumina® MiSeq based sequencing of the 16s rRNA gene from cecal and fecal contents of 6 month old male APPSWE/PS1ΔE9 mice was performed and a microbial (C) phylogenetic tree and (D) diversity histogram were generated based on quality-controlled OTU reads. Only families and genus’ with relative abundance >0.5% were included. (E) α-diversity analysis of the sequencing data using the Shannon index, reveals a significant decrease in microbial diversification in ABX-treated APPSWE/PS1ΔE9 mice (n = 9–10, *p = 0.0429, unpaired two-tailed Student’s t-test). Principal co-ordinate analysis of (F) un-weighted, accounting for presence of OTUs only, and (G) weighted β-diversity, accounting for both presence and relative abundance of OTUs, demonstrates distinct alterations in microbial diversity in ABX-treated APPSWE/PS1ΔE9 mice (n = 9–10 mice, each with cecal and fecal sequencing). The percentage of data variance explained by each IPCA is displayed. Data are displayed as X/Y scatter or mean ± SEM. See Supplementary Figure 2–3, statistical Table 1 and Supplementary table 2 for additional information.
Figure 1 Composition of the gastrointestinal microbiome is altered in ABX-treated APPSWE/PS1ΔE9 mice. (A) Q-PCR analysis of isolated DNA from cecal contents of 6 month old male APPSWE/PS1ΔE9 mice analysing 16s rRNA gene copy number (n = 9–10). (B) Q-PCR analysis of isolated DNA from fecal contents of 6 month old male APPSWE/PS1ΔE9 mice analysing 16s rRNA gene copy number (n = 9–10). To obtain a 16s rRNA gene copy number value, expression levels were normalized to both DNA concentration and an amplification standard curve of a 16s rRNA gene-containing plasmid with known copy number. Illumina® MiSeq based sequencing of the 16s rRNA gene from cecal and fecal contents of 6 month old male APPSWE/PS1ΔE9 mice was performed and a microbial (C) phylogenetic tree and (D) diversity histogram were generated based on quality-controlled OTU reads. Only families and genus’ with relative abundance >0.5% were included. (E) α-diversity analysis of the sequencing data using the Shannon index, reveals a significant decrease in microbial diversification in ABX-treated APPSWE/PS1ΔE9 mice (n = 9–10, *p = 0.0429, unpaired two-tailed Student’s t-test). Principal co-ordinate analysis of (F) un-weighted, accounting for presence of OTUs only, and (G) weighted β-diversity, accounting for both presence and relative abundance of OTUs, demonstrates distinct alterations in microbial diversity in ABX-treated APPSWE/PS1ΔE9 mice (n = 9–10 mice, each with cecal and fecal sequencing). The percentage of data variance explained by each IPCA is displayed. Data are displayed as X/Y scatter or mean ± SEM. See Supplementary Figure 2–3, statistical Table 1 and Supplementary table 2 for additional information.CC BY · PubMed Central
Figure 2 The circulating inflammatory mediator profile is altered in ABX-treated APPSWE/PS1ΔE9 mice. (A) Immunoblot-based array of inflammatory mediators in isolated serum from vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 10, pooled sera). (B) Densitometry of select inflammatory mediators from the aforementioned array. Expression levels in ABX-treated mice are expressed in arbitrary units relative to vehicle control (dashed line). Data are displayed as mean alone. See Supplementary Figures 4 and 5 for additional information.
Figure 2 The circulating inflammatory mediator profile is altered in ABX-treated APPSWE/PS1ΔE9 mice. (A) Immunoblot-based array of inflammatory mediators in isolated serum from vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 10, pooled sera). (B) Densitometry of select inflammatory mediators from the aforementioned array. Expression levels in ABX-treated mice are expressed in arbitrary units relative to vehicle control (dashed line). Data are displayed as mean alone. See Supplementary Figures 4 and 5 for additional information.CC BY · PubMed Central
Figure 3 Amyloidosis is altered in ABX-treated male APPSWE/PS1ΔE9 mice. (A) Representative immunohistochemical images of Aβ plaque deposition in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using anti-Aβ mAb 3D6. Each staining run was performed using sections from 12 month old APPSWE/PS1ΔE9 mice as a positive control and no primary antibody negative controls. (B) Plaque burden quantification in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using particle analysis of 3D6+ve immunofluorescence (n = 10, *p = 0.0169, unpaired two-tailed Student’s t-test). 3D6+ve area was averaged from 4 sections/mouse (240 μm apart) and expressed relative to total cortical and hippocampal area. (C) Representative x60 magnification z-stack maximum projection images of 3D6+ve Aβ plaques from vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. (D) Quantification of plaque area using threshold-limiting immunofluorescence detection (n = 10, *p = 0.02, unpaired two-tailed Student’s t-test). (E) MSD Mesoscale® analysis of TFA-soluble (TBS-insoluble) Aβ1-40 and Aβ1-42 levels in combined cortical and hippocampal tissue of vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using anti-Aβ mAb 4G8 (n = 10, *p = 0.0491, unpaired two-tailed Student’s t-test). (F) MSD Mesoscale® analysis of TBS-soluble Aβ1-40 and Aβ1-42 levels in combined cortical and hippocampal tissue of vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using anti-Aβ mAb 4G8 (n = 10, *p < 0.05, unpaired two-tailed Student’s t-test). (G) Quantification of the Aβ1-40:Aβ1-42 ratio from the TBS-soluble MSD Mesoscale® data in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 10, *p = 0.014, unpaired two-tailed Student’s t-test). Data are displayed as mean ± SEM. See Supplementary Figure 6–9 and statistical table 1 for additional information.
Figure 3 Amyloidosis is altered in ABX-treated male APPSWE/PS1ΔE9 mice. (A) Representative immunohistochemical images of Aβ plaque deposition in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using anti-Aβ mAb 3D6. Each staining run was performed using sections from 12 month old APPSWE/PS1ΔE9 mice as a positive control and no primary antibody negative controls. (B) Plaque burden quantification in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using particle analysis of 3D6+ve immunofluorescence (n = 10, *p = 0.0169, unpaired two-tailed Student’s t-test). 3D6+ve area was averaged from 4 sections/mouse (240 μm apart) and expressed relative to total cortical and hippocampal area. (C) Representative x60 magnification z-stack maximum projection images of 3D6+ve Aβ plaques from vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. (D) Quantification of plaque area using threshold-limiting immunofluorescence detection (n = 10, *p = 0.02, unpaired two-tailed Student’s t-test). (E) MSD Mesoscale® analysis of TFA-soluble (TBS-insoluble) Aβ1-40 and Aβ1-42 levels in combined cortical and hippocampal tissue of vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using anti-Aβ mAb 4G8 (n = 10, *p = 0.0491, unpaired two-tailed Student’s t-test). (F) MSD Mesoscale® analysis of TBS-soluble Aβ1-40 and Aβ1-42 levels in combined cortical and hippocampal tissue of vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice using anti-Aβ mAb 4G8 (n = 10, *p < 0.05, unpaired two-tailed Student’s t-test). (G) Quantification of the Aβ1-40:Aβ1-42 ratio from the TBS-soluble MSD Mesoscale® data in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 10, *p = 0.014, unpaired two-tailed Student’s t-test). Data are displayed as mean ± SEM. See Supplementary Figure 6–9 and statistical table 1 for additional information.CC BY · PubMed Central
Figure 4 Plaque-localized gliosis is influenced by ABX treatment in male APPSWE/PS1ΔE9 mice. (A) Representative x60 magnification z-stack maximum projection images of IBA-1+ve Aβ plaque-localized microglia, co-stained with DAPI, in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. (B) Quantification of plaque-localized IBA-1+ve microglial number in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8, ***p < 0.001, unpaired two-tailed Student’s t-test). (C) Plaque-localized IBA+ve microglial number expressed relative to 3D6+ve Aβ plaque area in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8). (D) Representative 3D IMARIS-based reconstructions of x60 magnification z-stack images (0.8 μm apart) depicting plaque-localized IBA-1+ve microglial morphology in in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. Microglial branching, terminal points and Aβ plaque surfaces can be seen. The (E) length and (F) number of microglial dendritic branches alongside (G) projection terminal points were quantified (n = 4, *p = 0.0237, **p < 0.01, unpaired two-tailed Student’s t-test). (H) Representative x60 magnification z-stack maximum projection images of GFAP+ve Aβ plaque-localized astrocytes, co-stained with DAPI, in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. (I) Quantification of plaque-localized GFAP+ve astrocyte number in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8, **p = 0.001, unpaired two-tailed Student’s t-test). (J) Plaque-localized GFAP+ve astrocyte number expressed relative to 3D6+ve Aβ plaque area in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8). Data are displayed as mean ± SEM. See statistical table 1 for additional information.
Figure 4 Plaque-localized gliosis is influenced by ABX treatment in male APPSWE/PS1ΔE9 mice. (A) Representative x60 magnification z-stack maximum projection images of IBA-1+ve Aβ plaque-localized microglia, co-stained with DAPI, in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. (B) Quantification of plaque-localized IBA-1+ve microglial number in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8, ***p < 0.001, unpaired two-tailed Student’s t-test). (C) Plaque-localized IBA+ve microglial number expressed relative to 3D6+ve Aβ plaque area in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8). (D) Representative 3D IMARIS-based reconstructions of x60 magnification z-stack images (0.8 μm apart) depicting plaque-localized IBA-1+ve microglial morphology in in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. Microglial branching, terminal points and Aβ plaque surfaces can be seen. The (E) length and (F) number of microglial dendritic branches alongside (G) projection terminal points were quantified (n = 4, *p = 0.0237, **p < 0.01, unpaired two-tailed Student’s t-test). (H) Representative x60 magnification z-stack maximum projection images of GFAP+ve Aβ plaque-localized astrocytes, co-stained with DAPI, in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice. (I) Quantification of plaque-localized GFAP+ve astrocyte number in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8, **p = 0.001, unpaired two-tailed Student’s t-test). (J) Plaque-localized GFAP+ve astrocyte number expressed relative to 3D6+ve Aβ plaque area in vehicle control and ABX-treated male 6 month old APPSWE/PS1ΔE9 mice (n = 8). Data are displayed as mean ± SEM. See statistical table 1 for additional information.CC BY · PubMed Central

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Metadata

Authors
Minter, M. R., Zhang, C., Leone, V., Ringus, D. L., Zhang, X., Oyler-Castrillo, P., Musch, M. W., Liao, F., Ward, J. F., Holtzman, D. M., Chang, E. B., Tanzi, R. E., & Sisodia, S. S.
Affiliations
  • University of Chicago (US)
  • Massachusetts General Hospital (US)
  • Washington University in St. Louis (US)
Corresponding author
Sisodia, Sangram S.
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2016-07-21
Volume
6
Issue
1
Pages
30028-30028
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/srep30028
PMC
PMC4956742
OpenAlex
W2479642761
Cited by
655
References
56
Citations by year
2026: 40 · 2025: 63 · 2024: 76 · 2023: 66 · 2022: 102 · 2021: 89 · 2020: 74 · 2019: 59 · 2018: 47 · 2017: 33 · 2016: 6
FWCI
38.90
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
Funders
  • University of Chicago (DK42086)
  • Cure Alzheimer's Fund
  • National Institute of Diabetes and Digestive and Kidney Diseases (DK42086, P30DK042086)
  • Argonne National Laboratory
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
Keywords
Alzheimer's disease, gut microbiota, antibiotic-induced dysbiosis, amyloid plaques, neuroinflammation, APPswe/PS1ΔE9 mice, soluble amyloid-beta, microglial morphology, glial activation, innate immunity, cytokines and chemokines, gut-brain axis
MeSH terms
Gastrointestinal Microbiome, Alzheimer Disease, Amyloidosis, Animals, Anti-Bacterial Agents, Disease Models, Animal, Immunity, Innate, Inflammation, Mice, Dysbiosis

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