| Literature DB >> 34899698 |
Yuying Ma1,2,3, Xiaohui Wang1,2,3, Weisheng Luo1,2,3, Ji Xiao1,2,3, Xiaowei Song1,2,3, Yifei Wang1,2,3, Hanlin Shuai4, Zhe Ren1,2,3, Yiliang Wang1,2,3,5.
Abstract
cGAS, a DNA sensor in mammalian cells, catalyzes the generation of 2'-3'-cyclic AMP-GMP (cGAMP) once activated by the binding of free DNA. cGAMP can bind to STING, activating downstream TBK1-IRF-3 signaling to initiate the expression of type I interferons. Although cGAS has been considered a traditional DNA-binding protein, several lines of evidence suggest that cGAS is a potential RNA-binding protein (RBP), which is mainly supported by its interactions with RNAs, RBP partners, RNA/cGAS-phase-separations as well as its structural similarity with the dsRNA recognition receptor 2'-5' oligoadenylate synthase. Moreover, two influential studies reported that the cGAS-like receptors (cGLRs) of fly Drosophila melanogaster sense RNA and control 3'-2'-cGAMP signaling. In this review, we summarize and discuss in depth recent studies that identified or implied cGAS as an RBP. We also comprehensively summarized current experimental methods and computational tools that can identify or predict RNAs that bind to cGAS. Based on these discussions, we appeal that the RNA-binding activity of cGAS cannot be ignored in the cGAS-mediated innate antiviral response. It will be important to identify RNAs that can bind and regulate the activity of cGAS in cells with or without virus infection. Our review provides novel insight into the regulation of cGAS by its RNA-binding activity and extends beyond its DNA-binding activity. Our review would be significant for understanding the precise modulation of cGAS activity, providing the foundation for the future development of drugs against cGAS-triggering autoimmune diseases such as Aicardi-Gourtières syndrome.Entities:
Keywords: RNA-binding activity; RNA-binding protein; cGAS; innate antiviral response; phase-separated condensates
Mesh:
Substances:
Year: 2021 PMID: 34899698 PMCID: PMC8660693 DOI: 10.3389/fimmu.2021.741599
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561
Figure 1The cytosolic DNA-activated cGAS-STING pathway. The recognition of free dsDNA in the cytoplasm by cGAS activates the production of 2’-3’-cGAMP, a natural ligand of ER-resident STING. The binding of 2’-3’-cGAMP to STING results in its translocation to the ER-Golgi intermediate compartment (ERGIC) and the Golgi apparatus. The relocated STING activates TBK1 and IKK. First, activated TBK1 phosphorylates STING, which consequently recruits and phosphorylates IRF3. The phosphorylated activated IRF3 dimerizes and enters the nucleus to initiate transcription of type I IFN. In addition, activated IKK results in the activation and nuclear transport of NF-κB to induce the expression of type I IFN and inflammatory cytokines such as TNF and IL-6. The interaction between cGAS and nucleosomes prevents the activation of cGAS. Notably, nuclear cGAS suppresses homologous recombination and promotes tumorigenesis.
Figure 2Binding of cGAS to RNA or RNA: DNA hybrids. (A, B) Binding of cGAS to tRNA as reported by a preprint server, which remains to be fully supported experimentally in cells. Cytoplasmic tRNA regulates cGAS activity by interfering with the formation of cGAS-containing aggregates. (A) In the context of low concentrations of DNA, cytoplasmic tRNA forms aggregates with cGAS, providing a platform for dsDNA-mediated cGAS activation. (B) In the context of a high concentration of DNA in the cytoplasm, DNA is sufficient to induce phase separation and activate cGAS. However, tRNA harbors a higher affinity than dsDNA for cGAS. Consequently, cGAS competes with dsDNA to bind cGAS and inhibit cGAS activity to avoid an excessive immune response. (C) Binding of cGAS to cia-cGAS. A circular RNA named cia-cGAS was highly expressed in the nucleus of LT-HSCs. Under homeostatic conditions, cia-cGAS binds cGAS in the nucleus to inhibit its binding to genomic DNA. As a consequence, cia-cGAS suppressed cGAS-mediated production of type I IFNs, thereby protecting dormant LT-HSCs from cGAS-mediated exhaustion. (D) RNA : DNA hybridization products can bind and activate cGAS.
Figure 3The RBP partners of cGAS. (A) The binding of TRIM56 to cGAS induces the Lys335 monoubiquitylation of cGAS, thereby increasing the dimerization and DNA-binding activity of cGAS. (B) ZCCHC3 acts as a co-sensor for the recognition of dsDNA by cGAS. Briefly, ZCCHC3 binds to dsDNA and interacts with cGAS in the cytoplasm, enhancing the binding of cGAS to dsDNA and the formation of a large cGAS complex. (C) PCBP1 is a critical regulator of DNA recognition by cGAS. PCBP1 was recruited to cGAS in a viral infection-dependent manner. PCBP1 bound to DNA and enhanced cGAS binding to dsDNA. (D) G3BP1 physically interacts with and primes cGAS for efficient activation. G3BP1 enhanced the DNA binding of cGAS by promoting the formation of large cGAS complexes. (E) The binding of cytosolic dsDNA to cGAS induces a robust phase transition to liquid-like droplets, which are considered as microreactors with concentrated RNA and RBPs, suggesting a potential link between cGAS and RBPs. (F) NONO is an essential sensor of the HIV capsid in the nucleus. NONO forms a complex with cGAS in the nucleus. Detection of the nuclear viral capsid by NONO promotes the recognition of DNA by cGAS.
Figure 4RNA-binding ability of murine-cGAS determined by catRAPID signature. (A) The propensity of murine cGAS for classical (0.5), putative (0.47), and nonclassical (0.41) RBPs. The overall interaction score (0.5) for murine cGAS as an RBP was also present. (B) The profile shows protein regions and their propensity to interact with RNA. All results were predicted by using catRAPID.
Figure 5RNA-binding ability of murine-2’-5’-OAS1 predicted by catRAPID signature. (A) The propensity of murine-2’-5’-OAS1 for the nonclassical (0.51), classical (0.43) and putative (0.35) RBPs. The overall interaction score (0.68) for murine-2’-5’-OAS1 as an RBP was also present. (B) The profile shows protein regions and their propensity to interact with RNA. The catRAPID signature correctly identifies the RNA binding domain of murine-2’-5’-OAS1, which carries the region of enzymatic activity between 320 and 344 at the extreme C-terminal end (122).
The RNA interactors of murine cGAS predicted by catRAPID omics (version 2.0).
| RNA ID | Gene Name | Interaction Propensity | Z-score | RBP Propensity | RNA-Binding Domains | RNA-Binding Motifs | Conserved Interactions | Ranking | |
|---|---|---|---|---|---|---|---|---|---|
| protein-coding RNAs | ENSMUST00000000080 | Kruppel-like Factor 6 (Klf6) | 88.83 | 1.73 | 0.5 | 1 | 0 | 0/0 | 0.405431 |
| ENSMUST00000000291 | max binding protein (Mnt) | 73.94 | 1.34 | 0.5 | 1 | 0 | 0/0 | 0.389061 | |
| ENSMUST00000000579 | sex determining region Y-box 9 (Sox9) | 56.82 | 0.89 | 0.5 | 1 | 0 | 0/0 | 0.37024 | |
| ENSMUST00000000619 | chloride channel, voltage-sensitive 4 (Clcn4) | 74.44 | 1.35 | 0.5 | 1 | 0 | 0/0 | 0.389611 | |
| ENSMUST00000000724 | K (lysine) acetyltransferase 2B (Kat2b) | 61.09 | 1 | 0.5 | 1 | 0 | 0/0 | 0.374934 | |
| long noncoding RNAs | ENSMUST00000047876 | Gm10710 | 45.58 | 0.59 | 0.5 | 1 | 0 | 0/0 | 0.357883 |
| ENSMUST00000052189 | B230317F23Rik | 49.89 | 0.7 | 0.5 | 1 | 0 | 0/0 | 0.362621 | |
| ENSMUST00000097612 | Gm10545 | 49.12 | 0.68 | 0.5 | 1 | 0 | 0/0 | 0.361774 | |
| ENSMUST00000098303 | Gm9934 | 42.98 | 0.52 | 0.5 | 1 | 0 | 0/0 | 0.355024 | |
| ENSMUST00000100713 | Gm10384 | 41.97 | 0.49 | 0.5 | 1 | 0 | 0/0 | 0.353914 | |
| small noncoding RNAs | ENSMUST00000082459 | Gm23627 | 25.98 | 0.07 | 0.49 | 1 | 0 | 0/0 | 0.333001 |
| ENSMUST00000082490 | Gm22749 | 28.99 | 0.15 | 0.49 | 1 | 0 | 0/0 | 0.33631 | |
| ENSMUST00000082508 | Gm26225 | 27.07 | 0.1 | 0.49 | 1 | 0 | 0/0 | 0.3342 | |
| ENSMUST00000082509 | Gm26226 | 36.2 | 0.34 | 0.49 | 1 | 0 | 0/0 | 0.344237 | |
| ENSMUST00000082534 | Gm25081 | 25.39 | 0.06 | 0.49 | 1 | 0 | 0/0 | 0.332353 |
Table summarization of the top 5 predicted coding-RNA interactors (RNA ID and Gene Name) of murine-cGAS by catRAPID omics (version 2.0). The table shows Z-scores (interaction propensity normalization relative to experimental cases), discriminative ability (relative to training sets), interaction strength (enrichment relative to random interactions), the presence of RNA-binding domains, and RNA motifs. RNAs were ranked by the score, which is the sum of three individual values: 1) catRAPID normalized propensity, 2) RBP propensity and 3) presence of known RNA-binding motifs. The full score is 1.
The RNA interactors of human cGAS predicted by catRAPID omics (version 2.0).
| RNA ID | Gene Name | Interaction Propensity | Z-score | RBP Propensity | RNA-Binding Domains | RNA-Binding Motifs | Conserved Interactions | Ranking | |
|---|---|---|---|---|---|---|---|---|---|
| protein-coding RNAs | ENST00000078429 | G protein subunit alpha 11 (GNA11) | 57.38 | 0.9 | 0.35 | 1 | 0 | 0/0 | 0.320855 |
| ENST00000169298 | ST6 beta-galactoside alpha-2,6-sialyltransferase 1 (ST6GAL1) | 56.82 | 0.89 | 0.35 | 1 | 0 | 0/0 | 0.32024 | |
| ENST00000170168 | RNA exonuclease 1 homolog (REXO1) | 59.47 | 0.96 | 0.35 | 1 | 0 | 0/0 | 0.323153 | |
| ENST00000174618 | MAX network transcriptional repressor (MNT) | 60.79 | 0.99 | 0.35 | 1 | 0 | 0/0 | 0.324604 | |
| ENST00000193322 | osteoclastogenesis associated transmembrane protein 1 (OSTM1) | 54.06 | 0.81 | 0.35 | 1 | 0 | 0/0 | 0.317205 | |
| long noncoding RNAs | ENST00000242109 | KIAA0087 | 24.68 | 0.04 | 0.35 | 1 | 0 | 0/0 | 0.284905 |
| ENST00000309874 | AC020659.1 | 19.83 | -0.09 | 0.35 | 1 | 0 | 0/0 | 0.279573 | |
| ENST00000316786 | C9orf106 | 21.42 | -0.05 | 0.35 | 1 | 0 | 0/0 | 0.281321 | |
| ENST00000325390 | AC018865.2 | 20.01 | -0.09 | 0.35 | 1 | 0 | 0/0 | 0.279771 | |
| ENST00000329618 | B3GALT5-AS1 | 20.99 | -0.06 | 0.35 | 1 | 0 | 0/0 | 0.280849 | |
| small noncoding RNAs | ENST00000347538 | MIR133A2 | 4.53 | -0.49 | 0.35 | 1 | 0 | 0/0 | 0.262753 |
| ENST00000362117 | MIR16-2 | 6.2 | -0.45 | 0.35 | 1 | 0 | 0/0 | 0.264589 | |
| ENST00000362317 | MIR365B | 7.6 | -0.41 | 0.35 | 1 | 0 | 0/0 | 0.266128 | |
| ENST00000362349 | RNU6-500P | 6.08 | -0.45 | 0.35 | 1 | 0 | 0/0 | 0.264457 | |
| ENST00000362356 | RNU6-50P | 5.19 | -0.48 | 0.35 | 1 | 0 | 0/0 | 0.263478 |
Table summarization of the top 5 predicted coding-RNA interactors (RNA ID and Gene Name) of murine-cGAS by catRAPID omics (version 2.0). The table shows Z-scores (interaction propensity normalization relative to experimental cases), discriminative ability (relative to training sets), interaction strength (enrichment relative to random interactions), the presence of RNA-binding domains, and RNA motifs. RNAs were ranked by the score, which is the sum of three individual values: 1) catRAPID normalized propensity, 2) RBP propensity and 3) presence of known RNA-binding motifs. The full score is 1.
Experimental methods for uncovering the interaction between proteins and RNAs.
| Classes | Methods | Advantages | Disadvantages | References |
|---|---|---|---|---|
| In the test tube | EMSA | Separation of numerous types of complexes, such as monomer and dimer; Works well with crude cell extracts. | Low-throughput; Failure of detecting binding sites. | ( |
| RNA pull-down | A simple protocol; Enrichment of low-abundance RBPs. | Failure of confirming direct or indirect interaction; Failure of forming RNA-protein interactions that only occur in vitro under non-physiological conditions. | ( | |
| SELEX | Direct interaction of the oligonucleotides with the target is closely application-oriented; Independence of in-depth knowledge regarding the respective target for aptamer selection. | No standardized aptamer selection protocol for target. | ( | |
| RNAcompete | Accurate estimation of the relative preference for a large numbers of individual sequences; Querying preferences are available for structured RNA; Time-saving. | Limited size of the current RNA pool for the represented combinations of sequence and structure. | ( | |
| RBNS | Accurate estimation of dissociation constants of RBP-RNA complex; A more reliable prediction of RNA folding and a better identification of the binding structural determinants than RNAcompete. | N/A | ( | |
| In cells | RIP Assay | A simple and standard protocol; Preserves the intracellular native complexes. | Failure of confirmation of direct or indirect interaction between RNA and protein; Failure of determination of the precise site within the RNA interacting protein; Poor resolution; Antibody-consuming. | ( |
| CLIP | A sensitive determination of binding sites. | Low abundance of RNA-ribonucleoprotein complexes; Potentially inefficient library preparation; Large amounts of raw material required. | ( | |
| PIP-seq | A simultaneous view of the global landscapes of both RNA secondary structure and RNA-protein interactions. | High concentrations of structure-specific RNases. | ( |
EMSA, Electrophoretic Mobility Shift Assay; SELEX, Systematic Evolution of Ligands by Exponential Enrichment; RBNS; RNA Bind-n-Seq; RIP, RNA Immunoprecipitation; CLIP, Cross-linked Immunoprecipitation; PIP-seq, Protein Interaction Profile Sequencing; N/A, not applicable.
Computational tools for the prediction of RNA-protein interactions.
| Methods | Advantages | Disadvantages | Links | References |
|---|---|---|---|---|
| catRAPID | Outperforms other algorithms in the identification of RBPs and detection of non-classical RNA-binding regions. | Spurious binding may occur. |
| ( |
| lncPro | Time-saving. | Limited ability of computational prediction of RNA secondary structure for lncRNAs. |
| ( |
| RNAcontext | A more accurate elucidation of RBP-specific sequence and structural preferences. | Misleading results will be produced for those RBPs with non-trivial structural preferences. |
| ( |
| RPI-Pred | A comprehensive understanding of PRIs based on the sequence features and the high-order structures of both proteins and RNAs. | Limited to prediction of ncRNA-Protein interaction. |
| ( |
| PRIPU | Employs SVM for predicting PRIs using only positive and unlabeled examples based on proposing a new performance measure called EPR; Outperforms existing methods and predicts unknown PRIs. | N/A |
| ( |
| RPISeq | Reliable prediction based on sequence. | Requirement for larger and more diverse experimental datasets. | RNA-Protein Interaction Prediction (RPISeq) (iastate.edu) | ( |
RBPs, RNA-binding proteins; SVM, biased-support vector machine; lncRNA, long noncoding RNA; PRIS, Protein-RNA interactions; EPR, explicit positive recall; N/A, not applicable.