MicroRNA-223-5p and -3p Cooperatively Suppress Necroptosis in Ischemic/Reperfused Hearts
Bibliographic record
Abstract
Recent studies have shown that myocardial ischemia/reperfusion (I/R)-induced necrosis can be controlled by multiple genes.In this study, we observed that both strands (5p and 3p) of miR-223 were remarkably dysregulated in mouse hearts upon I/R.Precursor miR-223 (pre-miR-223) transgenic mouse hearts exhibited better recovery of contractile performance over reperfusion period and lesser degree of myocardial necrosis than wild type hearts upon ex vivo and in vivo myocardial ischemia.Conversely, pre-miR-223 knock-out (KO) mouse hearts displayed opposite effects.Furthermore, we found that the RIP1/ RIP3/MLKL necroptotic pathway and inflammatory response were suppressed in transgenic hearts, whereas they were activated in pre-miR-223 KO hearts upon I/R compared with wild type controls.Accordingly, treatment of pre-miR-223 KO mice with necrostatin-1s, a potent necroptosis inhibitor, significantly decreased I/R-triggered cardiac necroptosis, infarction size, and dysfunction.Mechanistically, we identified two critical cell death receptors, TNFR1 and DR6, as direct targets of miR-223-5p, whereas miR-223-3p directly suppressed the expression of NLRP3 and IB kinase ␣, two important mediators known to be involved in I/R-induced inflammation and cell necroptosis.Our findings indicate that miR-223-5p/-3p duplex works together and cooperatively inhibits I/R-induced cardiac necroptosis at multiple layers.Thus, pre-miR-223 may constitute a new therapeutic agent for the treatment of ischemic heart disease.Reperfusion of ischemic hearts by percutaneous coronary intervention, cardiac surgery, or thrombolytic therapy is commonly used in patients with myocardial infarction (1).However, it is well recognized that reperfusion could induce excessive oxidative stress and inflammation, leading to myocyte death (apoptosis and necrosis) (2).Over the past decades, tremendous efforts have been made to dissect mechanisms under-lying the gene-regulated apoptosis in ischemia/reperfusion (I/R)1 3 -induced cardiac injury, whereas gene-controlled necrosis has received less attention.In recent years, it has become clear that I/R-triggered cardiac necrosis can be regulated by multiple genes/mediators, such as cyclophilin D (CypD), NLRP3, receptor-interacting protein kinase 3 (RIP3) and its partners RIP1, mixed lineage kinase-like (MLKL), and Ca 2ϩcalmodulin-dependent protein kinase (CaMKII) (3-7).Currently, the best characterized form of regulated necrosis (also referred to as necroptosis) is mediated by tumor necrosis factor-␣ (TNF-␣)/TNFR1-induced protein complex RIP1-RIP3 (necrosome) (8).Importantly, several recent studies have demonstrated that inhibition of necroptosis by necrostatin-1, a small molecule capable of suppressing RIP1 kinase activity, alleviated reperfusion injury following acute myocardial infarction in mice, rats, and pigs (9 -12).Nevertheless, given that I/R activates multiple necrosis-associated signals (5, 7, 13), making several necrotic pathways highly intertwined, blocking only one road to cell death may be unlikely to yield the desired outcome in a clinical setting.Therefore, it would be very significant to explore novel strategies aiming to target multiple cell death pathways in I/R hearts.MicroRNAs (miRs; miRNAs), a highly conserved group of small non-protein-coding RNAs, possess the capacity to finetune expression of hundreds of genes (14).Our previous work and that of others have revealed that miRNAs are dysregulated in I/R hearts and actively involved in the modulation of cardiac cell death during I/R (14 -19).Nonetheless, how such miRNAs regulate cell necrosis in I/R hearts remains poorly understood.Along this line, miR-223 has garnered special attention (20).Previously, only the 3Ј-arm of precursor miR-223 (pre-miR-223) (designated as miR-223 or the guide strand) was considered to maturate and become functional, whereas the complementary 5Ј-arm (referred as miR-223* or passenger strand) was destined to be degraded (20).However, we recently discovered that both arms of pre-miR-223 were co-expressed differently in * This work was supported in part by National Institutes of Health Grants HL-087861 and GM-112930 (to G.-C. F.).The authors declare that they have no conflicts of interest with the contents of this article.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".