11 Aug 2018

Finicky by nature, microglia have earned a rep for adopting a myriad of gene-expression patterns at the drop of a hat. How physiological are such responses? According to a paper published in the Journal of Experimental Medicine on August 6, some are likely artifacts of the tools used to study the cells. Microglia respond consistently in the face of aging, Aβ accumulation, and tauopathy, report researchers led by John Fryer at the Mayo Clinic in Jacksonville, Florida. They used a relatively new transcriptional profiling method to find that microglia ramp up expression of a common set of genes in all three conditions, and that ApoE is the master regulator. What’s more, the signature was stronger in microglia from female mice than it was in those from males.

The unique aspect of the study was the use of RiboTag, a technique that isolates ribosome-bound mRNA from specific cell types without the need for extensive tissue processing or cell sorting (Sanz et al., 2009). This avoids setting off highly reactive microglia prior to analysis, an issue that has plagued other microglial profiling studies. And because RiboTag isolates mRNAs undergoing active translation, this so-called “translatome” may better reflect the proteome than the more commonly used transcriptome.

“This is an innovative study using the RiboTag technology to capture transcripts while they are being translated, potentially avoiding unwanted bias when microglia are isolated for profiling,” noted Guojun Bu of the Mayo Clinic in Jacksonville, Florida. “The authors have generated publically accessible translational profiling data in models of amyloidosis, tauopathy, and aging.”

Marco Colonna of Washington University in St. Louis added that the technique could expose some flaws in previous findings. “Comparison of RNA profiles obtained from FACS-sorted cells versus RiboTagged RNA suggests that sorting of microglia results in considerable cell activation, which may bias the characterization of a ‘homeostatic’ profile.”

First author Silvia Kang and colleagues sought to compare how microglia change in response to aging, Aβ accumulation, and tau pathology. Concerned about microglial responses to cell sorting, Kang decided to try RiboTag. Researchers had recently used the technique to reveal that sorting markedly activated cells (Haimon et al., 2018). In Kang’s version, transgenic mice expressed an HA-tagged ribosomal subunit, Rpl22, under control of the microglial-specific promoter for the gene CX3CR1. Following rapid extraction and lysing of the brain tissue, she used the HA tag to pull out microglial ribosomes, along with their associated mRNAs.

Kang compared those translatomes with microglial transcriptomes obtained by isolating cells from the RiboTagged mice using traditional cell-sorting methods. The results surprised Fryer: a principal component analysis revealed that the cell isolation procedure had a far more profound effect on microglial gene expression than did treating the mice with lipopolysaccharide (LPS), an inflammatory toxin. Further, a comparison of the sorted and unsorted cells after LPS found sparse overlap between the 25 most highly induced genes in each. For some genes, the increase in RiboTag transcripts elicited by LPS was dwarfed by the massive elevation induced by cell sorting. For others, the effects of cell sorting and LPS were additive.

To avoid such cell-sorting confounds, the researchers decided to use RiboTag analysis to compare microglial gene expression in aging and disease models. Kang used 24-month-old RiboTag mice to reflect aging, and nine- to 10-month-old RiboTag mice on the APP/PS1 or AAV-Tau-P301L backgrounds as models of amyloidosis and tauopathy, respectively. They dissected out the animals’ forebrains, quickly sonicated them in the presence of the protein translation inhibitor cycloheximide to lock translating mRNAs to the labeled ribosomes, purified the latter with HA-affinity beads, and sequenced the associated mRNAs. Using three-month-old RiboTag mice as a control, they found a striking overlap among the gene-expression changes in aged, amyloidosis, and tauopathy mice. More than 75 of the 100 most highly elevated transcripts were shared among the three conditions. The common genes fell into eight biological pathways, including inflammatory responses, cell adhesion, and neutrophil chemotaxis. Upregulated genes included ApoE and others previously linked to AD pathology, including Cst7, Lgals3, Itgax, Spp1, Clec7a, Lpl, and Gpnmb (Jun 2017 news; Sep 2017 news; Oct 2017 news on Mathys et al., 2017). In addition, genes not previously linked to pathology, notably Ccl3 and Ccl4, emerged among the commonly elevated transcripts. The researchers also treated RiboTag mice with LPS or Poly(I:C) to induce acute inflammation, and found virtually no overlap between the top 100 transcripts upregulated by these insults and those induced by amyloidosis or tauopathy. However, they did find some commonalities between genes induced by aging and acute inflammation. This suggested that aging encompasses some aspects of both chronic and acute inflammatory insults, they contend.

Colonna found the commonalities among the aged mice and disease models striking. He suggested that this supports the idea that AD-like pathology accelerates an inflammatory process already ongoing in normal aging.

Cst7 emerged as the top hit in Kang’s analysis, although it had not been singled out as one of the most strongly induced genes in previous studies. Fryer thinks this gene has been discounted in the past because its expression ramps up dramatically in response to cell sorting. Differences between healthy and disease states would have been masked, he suggested. Indeed, when the researchers knocked down Cst7 in cultured microglia, they found a significant boost in phagocytic activity, suggesting that a rise in Cst7 could thwart phagocytosis during aging and AD. Chemoattractants Ccl3 and Ccl4 were also strongly induced by cell sorting. These chemoattractants recruit into the brain peripheral cells such as neutrophils, which reportedly worsen pathology and cognition in AD mouse models.

The Buck Stops Here. A network analysis places many of the transcripts that were commonly elevated in aging, amyloidosis, and tauopathy models into an ApoE-driven network. [Courtesy of Kang et al., JEM, 2018.]

ApoE in Charge
Microglial ApoE expression also rose in response to aging, amyloidosis, and tauopathy. Notably, co-expression analysis revealed that many of the genes included in the common signature were part of an ApoE-driven network, which converged on Ccl3 and Ccl4.

Jason Ulrich of Washington University in St. Louis was intrigued by this, noting that he and colleagues had also observed an ApoE-dependent induction of Ccl3 and Ccl4 expression in APP/PS1 mice, but had not nailed down in which cells the pathway was active.

Though ApoE expression was strongly induced by aging and disease, the gene also had a remarkably high expression under basal conditions. In three-month-old RiboTag mice, ApoE transcripts were among the top 1 percent of all transcripts expressed in microglia. In fact, only Tyrobp, a classic microglial gene, was expressed at higher levels in the young, healthy animals. This surprised Fryer, because astrocytes are commonly thought to be the major source of ApoE in the healthy brain.

Bu found this result important. “Such observations suggest that ApoE may have a primary role in microglia under both physiological and pathological conditions,” he wrote in a comment to Alzforum. “This also opens up a whole new possibility of exploring whether ApoE function in microglia contributes to its risk effects on AD, a topic that has received increasing attention in recent scientific meetings.”

Finally, the researchers investigated whether sex played a role in microglial profiles during aging and disease. They compared microglial gene expression in three-, 12-, and 24-month-old female and male mice. Differences between the sexes increased with age, and 37 transcripts were differentially abundant in 24-month-old males and females. Strikingly, seven of these transcripts—Spp1, Gpnmb, Lgals3, ApoES, Ccl3, Clec7a, and Ccl4—were part of the ApoE-driven network, and were expressed more with age in females than in males. The researchers think this signature could relate to women having a higher risk for AD than do men.

Li-Huei Tsai of the Massachusetts Institute of Technology in Cambridge wondered the same thing. “Together, these findings inform about a sexual dimorphism in a cell type that is known to play an important role in many neurodegenerative disorders,” she wrote in a comment to Alzforum. Tsai recently uncovered differences in gene-expression patterns between the sexes in other cell types of the brain, including excitatory neurons and oligodendrocytes (Jul 2018 conference news). 

Fryer’s RiboTag data set is publically available for researchers to peruse. He hopes other researchers will do functional studies on some of the transcripts identified in the data set, and perhaps compare data from this and other microglial profiling studies that used cell sorting. This might help raise some transcripts that were less highly induced in previous studies, such as Cst7, to the top of the hit list, he said.

Ulrich agreed that the data set will be useful resource. “It will be interesting to dig deeper into this and other data sets to understand the differences in microglial transcriptomic states between amyloid and tau pathology, and to identify potential pathways that drive neurodegeneration in the context of neuronal tau aggregation,” he wrote.—Jessica Shugart

Comments

1. • Guojun Bu
     Hong Kong University of Science & Technology
   • Posted: 11 Aug 2018

   This is an innovative study using the RiboTag technology to capture transcripts while they are being translated, potentially avoiding unwanted bias when microglia are isolated for profiling. The authors have generated publically accessible translational profiling data in models of amyloidosis, tauopathy, and aging. More interesting, they found that although ApoE is known to be an astrocytic gene in the brain, the absolute abundance of ApoE under basal conditions is among the top 1 percent of all transcripts expressed in microglia, while further upregulated in aging, amyloidosis, and tauopathy. Such observations suggest that ApoE may have a primary role in microglia under both physiological and pathological conditions. This also opens up a whole new possibility of exploring whether ApoE function in microglia contributes to its risk effects on AD, a topic that has received increasing attention in recent scientific meetings.

   View all comments by Guojun Bu
2. • Li-Huei Tsai
     Picower Institute of MIT
   • Posted: 11 Aug 2018

   I think the RiboTag system is an elegant approach to profile ribosome-associated transcripts in a minimally invasive fashion as demonstrated by Kang et al. and other labs who have successfully applied the approach to study diverse microglia phenotypes (Ayata et al., 2018; Haimon et al., 2018).

   The difference in the response of male and female microglia to challenge reported by Kang et al. is in line with previous studies reporting that gender may markedly affect the phenotype of microglia (Thion et al., 2018; Rahimian et al., 2018). Kang et al. also find that aging, a well-known risk factor for AD, increases the expression of APOE in microglia more so in female than in male mice. It would be interesting to know if this has any implication in the higher incidence of AD in women than in men. Together, these findings inform about a sexual dimorphism in a cell type that is known to play an important role in many neurodegenerative disorders.

   References:

   Ayata P, Badimon A, Strasburger HJ, Duff MK, Montgomery SE, Loh YE, Ebert A, Pimenova AA, Ramirez BR, Chan AT, Sullivan JM, Purushothaman I, Scarpa JR, Goate AM, Busslinger M, Shen L, Losic B, Schaefer A. Epigenetic regulation of brain region-specific microglia clearance activity. Nat Neurosci. 2018 Aug;21(8):1049-1060. Epub 2018 Jul 23 PubMed.

   Haimon Z, Volaski A, Orthgiess J, Boura-Halfon S, Varol D, Shemer A, Yona S, Zuckerman B, David E, Chappell-Maor L, Bechmann I, Gericke M, Ulitsky I, Jung S. Re-evaluating microglia expression profiles using RiboTag and cell isolation strategies. Nat Immunol. 2018 Jun;19(6):636-644. Epub 2018 May 18 PubMed.

   Thion MS, Low D, Silvin A, Chen J, Grisel P, Schulte-Schrepping J, Blecher R, Ulas T, Squarzoni P, Hoeffel G, Coulpier F, Siopi E, David FS, Scholz C, Shihui F, Lum J, Amoyo AA, Larbi A, Poidinger M, Buttgereit A, Lledo PM, Greter M, Chan JK, Amit I, Beyer M, Schultze JL, Schlitzer A, Pettersson S, Ginhoux F, Garel S. Microbiome Influences Prenatal and Adult Microglia in a Sex-Specific Manner. Cell. 2018 Jan 25;172(3):500-516.e16. Epub 2017 Dec 21 PubMed.

   Rahimian R, Cordeau P Jr, Kriz J. Brain Response to Injuries: When Microglia Go Sexist. Neuroscience. 2018 Mar 8; PubMed.

   View all comments by Li-Huei Tsai

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References

Research Models Citations

1. APPPS1

News Citations

1. Hot DAM: Specific Microglia Engulf Plaques 9 Jun 2017
2. ApoE and Trem2 Flip a Microglial Switch in Neurodegenerative Disease 24 Sep 2017
3. Changing With the Times: Disease Stage Alters TREM2 Effect on Tau 14 Oct 2017
4. A Delicate Frontier: Human Microglia Focus of Attention at Keystone 13 Jul 2018

Paper Citations

1. Sanz E, Yang L, Su T, Morris DR, McKnight GS, Amieux PS. Cell-type-specific isolation of ribosome-associated mRNA from complex tissues. Proc Natl Acad Sci U S A. 2009 Aug 18;106(33):13939-44. Epub 2009 Aug 4 PubMed.
2. Haimon Z, Volaski A, Orthgiess J, Boura-Halfon S, Varol D, Shemer A, Yona S, Zuckerman B, David E, Chappell-Maor L, Bechmann I, Gericke M, Ulitsky I, Jung S. Re-evaluating microglia expression profiles using RiboTag and cell isolation strategies. Nat Immunol. 2018 Jun;19(6):636-644. Epub 2018 May 18 PubMed.
3. Mathys H, Adaikkan C, Gao F, Young JZ, Manet E, Hemberg M, De Jager PL, Ransohoff RM, Regev A, Tsai LH. Temporal Tracking of Microglia Activation in Neurodegeneration at Single-Cell Resolution. Cell Rep. 2017 Oct 10;21(2):366-380. PubMed.

External Citations

1. RiboTag data set

Further Reading

News

1. Microglia—Who Are You Really? New Clues Emerge 24 Apr 2015
2. Nature Versus Nurture: What Gives Microglia Their Identity? 19 Feb 2015
3. Has ApoE’s Time Come as a Therapeutic Target? 23 May 2014
4. Human ApoE Antibody Nips Mouse Amyloid in the Bud 5 Apr 2018
5. ApoE and Tau: Unholy Alliance Spawns Neurodegeneration 15 Apr 2017
6. ApoE and Tau: Unholy Alliance Spawns Neurodegeneration 15 Apr 2017