Cited by 151Neuroinflammation and Neurodegeneration MechanismsPrion Diseases and Protein MisfoldingMicroRNA in disease regulation

The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index; 39 of the 55 sources its claims cite were checked for support.

MicroRNA 146a (miR-146a) Is Over-Expressed during Prion Disease and Modulates the Innate Immune Response and the Microglial Activation State

Open access

Abstract

Increasing evidence supports the involvement of microRNAs (miRNAs) in inflammatory and immune processes in prion neuropathogenesis. MiRNAs are small, non-coding RNA molecules which are emerging as key regulators of numerous cellular processes. We established miR-146a over-expression in prion-infected mouse brain tissues concurrent with the onset of prion deposition and appearance of activated microglia. Expression profiling of a variety of central nervous system derived cell-lines revealed that miR-146a is preferentially expressed in cells of microglial lineage. Prominent up-regulation of miR-146a was evident in the microglial cell lines BV-2 following TLR2 or TLR4 activation and also EOC 13.31 via TLR2 that reached a maximum 24-48 hours post-stimulation, concomitant with the return to basal levels of transcription of induced cytokines. Gain- and loss-of-function studies with miR-146a revealed a substantial deregulation of inflammatory response pathways in response to TLR2 stimulation. Significant transcriptional alterations in response to miR-146a perturbation included downstream mediators of the pro-inflammatory transcription factor, nuclear factor-kappa B (NF-κB) and the JAK-STAT signaling pathway. Microarray analysis also predicts a role for miR-146a regulation of morphological changes in microglial activation states as well as phagocytic mediators of the oxidative burst such as CYBA and NOS3. Based on our results, we propose a role for miR-146a as a potent modulator of microglial function by regulating the activation state during prion induced neurodegeneration.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

miR-146a is over-expressed in prion-infected mouse brain and is enriched in microglial cells, where TLR2/TLR4 stimulation induces it with delayed kinetics relative to cytokines. Gain- and loss-of-function studies indicate miR-146a broadly dampens microglial inflammatory and phagocytosis-related gene programs, suggesting it modulates the microglial activation state during prion disease.

Key findings

  • miR-146a was consistently up-regulated in prion-infected mouse brain: 3.3-fold in 22A whole brain, 8.3-fold in RML hippocampus, 16.3-fold in RML cerebellum, and 10.0-fold in BSE cerebellum versus age-matched mock-infected controls (Table 1).
  • miR-146a expression was enriched in microglial cell lines and induced by TLR2 or TLR4 agonists in BV-2 and EOC 13.31 cells, reaching a maximum at 24–48 hours and remaining elevated at 72 hours, while IL-6, CSF2/GM-CSF, and TNF transcripts peaked before 24 hours and returned to basal levels by 48 hours.
  • In EOC 13.31 cells, miR-146a over-expression altered 1,668 genes by ≥1.5-fold (FDR ≤2%) in resting cells; after TLR2/LPS stimulation, 977 genes were deregulated at 24 hours (778 down, 199 up), with enrichment in NF-κB, JNK, and MAPK signaling.
  • miR-146a over-expression significantly reduced IL-6 and GM-CSF protein after TLR2 stimulation (p<0.001), while anti-miR knock-down caused a small but significant increase in IL-6; predicted targets included IL1B, SMAD3, NOS2, QK1, and BCL2L1.

Methods

  • CD-1 mice were inoculated intracerebrally with 20 µl of 1% RML scrapie brain homogenate; at clinical symptoms, 6 mice per group were sacrificed and hippocampus or cerebellar tissue was used for RNA extraction, with equal numbers of age-matched mock-infected controls.
  • Murine microglial cell lines BV-2 and EOC 13.31 were stimulated with LPS or heat-killed Listeria monocytogenes (HKLM), with anti-TLR2 neutralization; miR-146a was over-expressed with 30 nM pre-miR mimic or knocked down with 50 nM anti-miR, followed by qRT-PCR (normalized to U6, 2−ΔΔCt) and IL-6/GM-CSF ELISA.
  • miRNA profiling used an in-house microarray; mRNA expression used Agilent whole mouse genome 4×44K arrays, analyzed with Feature Extraction, SAM (p=0.01), Ingenuity Pathway Analysis, and TargetScan 5.1; raw data deposited under GEO accession GSE17759.

Limitations

  • The paper states that in situ hybridization for miR-146a was inconclusive, that miR-146a may be expressed at low levels in other cell types including neurons, and that attempts to induce miR-146a in cultured microglia with recombinant PrP or PrP106–126 were unsuccessful.
  • The paper states that in vitro culture lacks multiple cell types, cell-to-cell signaling, normal cellular functions, and the long disease time course, and that TLR4 transcripts were below detection in their prion model; it also notes that MyD88 knockout data imply TLR2 signaling may not be essential in disease and that their model may not fully mimic disease processes.
  • Evident from the text: findings rely on mouse models and microglial cell lines rather than human tissue; direct miR-146a targets are largely inferred from microarray intersections and bioinformatic prediction, with limited validation; some in vivo miR-146a increases were not statistically significant (22A p=9.4×10−2; BSE p=7.6×10−2), and IL-10 up-regulation was not detectable by ELISA.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0030832

Cites

57 of 57 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Figure 1 Hierarchical cluster plot generated from miRNA expression profiling of a repertoire of a variety of CNS cell lineages (neuronal, microglia, astrocytes). A microglia specific cluster of miRNAs is indicated. Red indicates high levels of miRNA expression, green low levels and gray indicates expression that was undetected by the microarray used.
Figure 1 Hierarchical cluster plot generated from miRNA expression profiling of a repertoire of a variety of CNS cell lineages (neuronal, microglia, astrocytes). A microglia specific cluster of miRNAs is indicated. Red indicates high levels of miRNA expression, green low levels and gray indicates expression that was undetected by the microarray used.CC BY · PubMed Central
Figure 2 MiR-146a induction in microglia. A. LPS at concentrations ranging from 0.1–100 ng/ml was used to stimulate BV-2 cells. After 8 hours, RNA was collected and TaqMan® qRT-PCR was used to determine miR-146a expression relative to PBS treated (unstimulated) control cells. The experiment was performed in triplicate and the average fold induction is shown. B. EOC 13.31 cells were stimulated with 100 ng/ml semi-pure LPS, 100 ng ultra-pure LPS or PBS alone (unstimulated). RNA was collected after 8 hours and miR-146a expression was measured by TaqMan® qRT-PCR. Fold induction relative to untreated cells is shown. The experiment was performed in triplicate and the average fold change is shown. C. EOC 13.31 cells were incubated with increasing concentrations of an anti-TLR2 antibody for 30 minutes prior to stimulation with 100 ng/ml LPS. MiR-146a expression relative to mock-treated control cells was measured by TaqMan® qRT-PCR. Inhibition of miR-146a expression following anti-TLR2 antibody treatment was significant at all concentrations; 10 and 50 ng/ml * p<0.01, 100 ng/ml ** p<0.005. Treatment of BV-2 cells with 100 ng/ml anti-TLR-2 antibody prior to LPS stimulation failed to inhibit miR-146a induction. The experiment was performed in triplicate and the average fold change is shown. D. EOC 13.31 and BV-2 cells were stimulated with with 108 heat-killed Listeria monocytogenes (HKLM) cells/ml. RNA was collected at various time-points over 72 hours and miR-146a expression measured by TaqMan® qRT-PCR. Fold induction relative to unstimulated cells (US) is shown. The experiment was performed in triplicate and the average fold change is shown.
Figure 2 MiR-146a induction in microglia. A. LPS at concentrations ranging from 0.1–100 ng/ml was used to stimulate BV-2 cells. After 8 hours, RNA was collected and TaqMan® qRT-PCR was used to determine miR-146a expression relative to PBS treated (unstimulated) control cells. The experiment was performed in triplicate and the average fold induction is shown. B. EOC 13.31 cells were stimulated with 100 ng/ml semi-pure LPS, 100 ng ultra-pure LPS or PBS alone (unstimulated). RNA was collected after 8 hours and miR-146a expression was measured by TaqMan® qRT-PCR. Fold induction relative to untreated cells is shown. The experiment was performed in triplicate and the average fold change is shown. C. EOC 13.31 cells were incubated with increasing concentrations of an anti-TLR2 antibody for 30 minutes prior to stimulation with 100 ng/ml LPS. MiR-146a expression relative to mock-treated control cells was measured by TaqMan® qRT-PCR. Inhibition of miR-146a expression following anti-TLR2 antibody treatment was significant at all concentrations; 10 and 50 ng/ml * p<0.01, 100 ng/ml ** p<0.005. Treatment of BV-2 cells with 100 ng/ml anti-TLR-2 antibody prior to LPS stimulation failed to inhibit miR-146a induction. The experiment was performed in triplicate and the average fold change is shown. D. EOC 13.31 and BV-2 cells were stimulated with with 108 heat-killed Listeria monocytogenes (HKLM) cells/ml. RNA was collected at various time-points over 72 hours and miR-146a expression measured by TaqMan® qRT-PCR. Fold induction relative to unstimulated cells (US) is shown. The experiment was performed in triplicate and the average fold change is shown.CC BY · PubMed Central
Figure 3 EOC 13.31 cells were stimulated with 100 ng/ml semi-pure LPS and temporal changes in cytokine gene expression relative to mock-treated control were measured by microarray analysis. MiR-146a expression relative to mock-treated control was measured by TaqMan® qRT-PCR and expression is shown as grey bars.
Figure 3 EOC 13.31 cells were stimulated with 100 ng/ml semi-pure LPS and temporal changes in cytokine gene expression relative to mock-treated control were measured by microarray analysis. MiR-146a expression relative to mock-treated control was measured by TaqMan® qRT-PCR and expression is shown as grey bars.CC BY · PubMed Central
Figure 4 Altering the expression of miR-146a in microglia. A. MiR-146a over-expression as measured by TaqMan® qRT-PCR in microglia cells after 8, 24, and 48 hrs of treatment with 30 nM (previously optimized, data not shown) of transfected pre-miR-146a in comparison to 30 nM of transfected scrambled negative control miRNA. An average fold change and standard deviation were measured from triplicate experiments. B. MiR-146a knock-down as measured by TaqMan® qRT-PCR in microglia cells after 8, 24, and 48 hrs of treatment with 50 nM (previously optimized, data not shown) of transfected anti-miR-146a in comparison to 50 nM of transfected scrambled negative control miRNA. An average fold change and standard deviation were measured from triplicate experiments.
Figure 4 Altering the expression of miR-146a in microglia. A. MiR-146a over-expression as measured by TaqMan® qRT-PCR in microglia cells after 8, 24, and 48 hrs of treatment with 30 nM (previously optimized, data not shown) of transfected pre-miR-146a in comparison to 30 nM of transfected scrambled negative control miRNA. An average fold change and standard deviation were measured from triplicate experiments. B. MiR-146a knock-down as measured by TaqMan® qRT-PCR in microglia cells after 8, 24, and 48 hrs of treatment with 50 nM (previously optimized, data not shown) of transfected anti-miR-146a in comparison to 50 nM of transfected scrambled negative control miRNA. An average fold change and standard deviation were measured from triplicate experiments.CC BY · PubMed Central
Figure 5 Analysis of genes dysregulated by over-expression, or knock-down of miR-146a in resting EOC 13.31 cells using either miRNA mimics or anti-miRs. A. Venn diagram to show the intersection between genes down-regulated by miR-146a over-expression, up-regulated on miR-146a knock-down and those targets bioinformatically predicted using the TargetScan 5.1 program and IPA software. B. Networks showing the interactions between several predicted miR-146a target genes. Shaded grey are those genes also bioinformatically predicted using the TargetScan 5.1 program and IPA software.
Figure 5 Analysis of genes dysregulated by over-expression, or knock-down of miR-146a in resting EOC 13.31 cells using either miRNA mimics or anti-miRs. A. Venn diagram to show the intersection between genes down-regulated by miR-146a over-expression, up-regulated on miR-146a knock-down and those targets bioinformatically predicted using the TargetScan 5.1 program and IPA software. B. Networks showing the interactions between several predicted miR-146a target genes. Shaded grey are those genes also bioinformatically predicted using the TargetScan 5.1 program and IPA software.CC BY · PubMed Central
Figure 6 Analysis of genes dysregulated upon over-expression, or knock-down, of miR-146a in stimulated EOC 13.31 cells using either miRNA mimics or anti-miRs. A. Venn diagram to show the intersection between genes down-regulated in LPS stimulated EOC 13.31 cells by miR-146a over-expression, and those up-regulated upon miR-146a knock-down. Also shown are those targets bioinformatically predicted using the TargetScan 5.1 program and IPA software. B. Schematic showing alterations in expression in key inflammatory response-related genes in LPS stimulated EOC 13.31 cells following miR-146a over-expression. Colored green are those down-regulated genes, colored red are up-regulated genes, while those highlighted in blue are bioinformatically predicted targets of miR-146a using the TargetScan 5.1 program and IPA software.
Figure 6 Analysis of genes dysregulated upon over-expression, or knock-down, of miR-146a in stimulated EOC 13.31 cells using either miRNA mimics or anti-miRs. A. Venn diagram to show the intersection between genes down-regulated in LPS stimulated EOC 13.31 cells by miR-146a over-expression, and those up-regulated upon miR-146a knock-down. Also shown are those targets bioinformatically predicted using the TargetScan 5.1 program and IPA software. B. Schematic showing alterations in expression in key inflammatory response-related genes in LPS stimulated EOC 13.31 cells following miR-146a over-expression. Colored green are those down-regulated genes, colored red are up-regulated genes, while those highlighted in blue are bioinformatically predicted targets of miR-146a using the TargetScan 5.1 program and IPA software.CC BY · PubMed Central
Figure 7 EOC 13.31 cells were transfected with 30 nM of miR-146a mimic or anti-miR and 16 hrs later stimulated with 10 ng/ml LPS. At 24 hours post LPS stimulation, culture supernatant was collected and the levels of IL-6 and GM-CSF (coded for by the gene CSF2) were determined by ELISA; significance: ** p<0.001, * p<0.01.
Figure 7 EOC 13.31 cells were transfected with 30 nM of miR-146a mimic or anti-miR and 16 hrs later stimulated with 10 ng/ml LPS. At 24 hours post LPS stimulation, culture supernatant was collected and the levels of IL-6 and GM-CSF (coded for by the gene CSF2) were determined by ELISA; significance: ** p<0.001, * p<0.01.CC BY · PubMed Central
Figure 8 A summary showing key inflammatory response-related genes whose expression is modulated upon the over-expression of miR-146a.
Figure 8 A summary showing key inflammatory response-related genes whose expression is modulated upon the over-expression of miR-146a.CC BY · PubMed Central

Verification

Claims the paper makes

79 Own result · 18 Own interpretation · 16 Partly supported · 9 Supported · 8 No full text of the sources · 7 Own method · 4 Couldn’t confirm · 2 Not checked yet · 2 No basis given · 1 Supported so far · 1 Not supported · accuracy not yet measured

Verify all 2 references — free account

Show all 83 claims

  • Probably not a substantial claim. 31
  • It may state two separate claims as one. 42
  • The quote only partly states this claim. 4
64 of 64
  • The paper relies on this without support.

    PrPSc induces inflammatory responses by the brain's glial cells (astrocytes and microglia) by activating innate immunity pathways.

    “PrPSc induces inflammatory responses by the brain's glial cells (astrocytes and microglia) by activating innate immunity pathways.”
  • The paper relies on this without support.

    The microglial surface receptor that is engaged leading to activation during prion pathogenesis is unknown.

    “MiR-146a is reported to be up-regulated in LPS stimulated human macrophages, however, the microglial surface receptor that is engaged leading to activation during prion pathogenesis is unknown [16].”
  • The paper relies on this without support.

    The specific stimuli and signaling pathways that lead to modulations of microglial functions, and the mechanisms by which microglial activation influences chronic neurodegeneration, are as yet unknown.

    “The specific stimuli and signaling pathways that lead to these modulations of functions, and the mechanisms by which microglial activation influences chronic neurodegeneration, are as yet unknown.”
  • The paper relies on this without support.

    Whether activation of the innate immune response is beneficial or harmful in prion-like pathologies is still unknown.

    “Such an inflammatory milieu has been recognized in the prion infected brain for some time; however, whether the activation of this innate immune response is beneficial or harmful in prion-like pathologies is still unknown.”
  • The authors state this as an assumption.

    Most translational repression is accompanied by miRNA-mediated mRNA degradation.

    “It has been previously reported that most translational repression is accompanied by miRNA-mediated mRNA degradation, we therefore used this assumption to predict potential direct targets of miR-146a in this system [34], [35].”
  • The paper relies on this without support.

    Direct targets of miR-146a important in immune activation are likely to be those found at the intersection of genes up-regulated following knock-down and down-regulated after over-expression, provided they exhibit altered expression detectable at the mRNA level.

    “Direct targets of miR-146a important in immune activation are likely to be those found at the intersection of genes that are up-regulated following knock-down and down-regulated after over-expression, provided that they exhibit altered expression that is detectable at the mRNA level.”
  • The paper relies on this without support.

    Microglial cells respond to prion deposition by converting from a resting to an activated phenotype, but synthesize low levels of pro-inflammatory cytokines.

    “Microglial cells, the brain's resident immune effector cells, respond to prion deposition by the conversion of a resting phenotype into one that is ‘activated’. However, although they take on an activated phenotype they synthesize fairly low levels of pro-inflammatory cytokines”
  • The paper relies on this without support.

    Phenotypic changes in microglia are one of the earliest apparent alterations in tissue pathology detectable during prion disease.

    “However, it is clear that phenotypic changes in microglia are one of the earliest apparent alterations in tissue pathology detectable during disease.”
  • The paper relies on this without support.

    The in vivo transcriptional response likely represents the host's response to the process of neurodegeneration as much, if not more than, the response specifically to prions.

    “It is often speculated that the in vivo transcriptional response likely represents the host's response to the process of neurodegeneration as much, if not more than, the response specifically to prions, which may account for our inability to detect a robust miR-146a induction in the cultured microglia.”
  • The paper relies on this without support.

    Effector molecules downstream of multiple cell surface receptors, including TLR2 and TLR4 signals, are similar.

    “However, effector molecules downstream of multiple cell surface receptors, including TLR2 (and TLR4) signals, are similar”
  • The paper relies on this without support.

    A reduction in TLR2 expression is linked with an increase in phagocytosis, implying an inverse relation between TLR2 expression and phagocytic activity.

    “Studies also link a reduction in TLR2 expression with an increase in phagocytosis, implying an inverse relation between TLR2 expression and phagocytic activity.”
  • The paper relies on this without support.

    MyD88 is the main adaptor protein implicated in TLR signaling and is considered essential for the induction of inflammatory cytokines triggered by most TLRs, including TLR2.

    “MyD88 is the main adaptor protein implicated in TLR signaling and is considered essential for the induction of inflammatory cytokines triggered by most TLRs, including TLR2.”
12 of 12

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

4 of 4

Citations

Cites

Show all 57 references

Cited by

Sorted by citations

See all 151

Metadata

Authors
Saba, R., Gushue, S., Huzarewich, R. L. C. H., Manguiat, K., Medina, S., Robertson, C., & Booth, S. A.
Affiliations
Public Health Agency of Canada (CA)
Corresponding author
Booth, Stephanie A.
Venue
PLoS ONE
Published
2012-02-17
Volume
7
Issue
2
Pages
e30832
ISSN
1932-6203 (ISSN-L)
OpenAlex
W2084713640
Cited by
151
References
57
Citations by year
2026: 4 · 2025: 5 · 2024: 4 · 2023: 4 · 2022: 10 · 2021: 10 · 2020: 13 · 2019: 9 · 2018: 13 · 2017: 15 · 2016: 11 · 2015: 16 · 2014: 14 · 2013: 16 · 2012: 7
FWCI
8.04
Type
journal article
Language
en
Open access
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Public Health Agency of Canada
  • Public Health Agency
Topics
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Prion Diseases and Protein Misfolding
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
Keywords
miR-146a, prion disease, microglial activation, innate immune response, TLR2, TLR4, NF-κB signaling, JAK/STAT signaling, neuroinflammation, respiratory burst
MeSH terms
Animals, Brain, Cell Line, Cell Movement, Immunity, Innate, Kinetics, Lipopolysaccharides, Oxidative Phosphorylation, Prions, Time Factors, Transcription, Genetic, Protein Biosynthesis, Signal Transduction, Up-Regulation, Cluster Analysis, Cytokines, Prion Diseases, Microglia, Inflammation Mediators, Gene Expression Profiling, MicroRNAs, Toll-Like Receptor 2, Toll-Like Receptor 4, Mice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-11-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-11-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Cited sources are checked with a language model’s help (gpt-6-sol).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review