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Record W1960555797 · doi:10.18632/oncotarget.4402

Efferocytosis: Burying cell corpses to regulate tolerance and immunity

2015· editorial· en· W1960555797 on OpenAlexaff
Maziar Divangahi

Bibliographic record

VenueOncotarget · 2015
Typeeditorial
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsMcGill University Health CentreChristie (Canada)
Fundersnot available
KeywordsEfferocytosisImmunityMedicineCell mediated immunityImmunologyBiologyCell biologyImmune systemMacrophageGenetics

Abstract

fetched live from OpenAlex

It is remarkable that every second approximately one million of our cells die via apoptosis, yet the collateral damage incurred (e.g. onset of autoimmune disease) remains relatively rare [1]. Disposal of this massive number of cell corpses evolved to not only maintain homeostasis but also prevent dissemination of intracellular pathogens and promote host defense. For instance, during infection with Mycobacterium tuberculosis (Mtb), processing of infected apoptotic cells by macrophages [2] and dendritic cells (DC) [3] enhances anti-bacterial innate and adaptive immune responses. Uptake of apoptotic bodies by phagocytes to maintain or resume homeostatic conditions and prevent pathology is mediated through an elegant process called efferocytosis (Efferre in Latin means “to bury”). Recent studies have shown that efferocytosis differs from classical phagocytosis in several respects including the use of distinct receptors, bridging proteins and signaling pathways. Specifically, efferocytosis depends on three main steps: (1) a “find-me” signal or the release of soluble mediators from apoptotic cells that recruit phagocytes; (2) an “eat-me” signal including exposure of a unique set of engulfment ligands on the surface of apoptotic cells leading to their recognition by phagocytes; and (3) the formation of the efferosome (a specific phagosome) and its degradation [4]. The best characterized eat-me signal is the exposure of phosphatidylserine (PS) on the surface of apoptotic cells. However, PS alone is not sufficient in triggering engulfment and other eat-me signals are required for optimum efferocytosis. Annexin 1 is a member of the annexin family first shown to co-localize with PS on the surface of apoptotic cells promoting efficient efferocytosis under physiological conditions in Caenorhabditis elegans [5]. Consistently, we recently demonstrated that this pathway is also operational in mammalian cells and plays an essential role in immunity to Mtb. During Mtb infection, annexin 1 in DCs increased efferocytosis and enhanced the capacity of antigen-presenting machinery leading to more efficient cross-presentation of antigens to CD8 T cells. Considering that annexin 1 is an essential eat-me signal under both physiological and immunogenic conditions, how does the immune system distinguish between these settings to promote host defense and prevent autoimmunity? We envision that apoptotic cells expose two sets of “eat-me” signals on their plasma membrane. One set is common to both immunogenic and tolerogenic apoptotic cells facilitating recognition/internalization under both conditions (e.g. PS or annexin 1). The second set is more unique to immunogenic apoptotic cells that are undergoing death due to infection and potentially exposing differential levels of surface markers involved in anti-microbial immunity. For instance activation of pattern recognition receptors have been shown to be critical for induction of immunogenic apoptosis during mycobacterial infection [6]. Certainly, further experiments are needed to identify the molecular mechanisms involved in this process. In addition, the machinery of the immunogenic efferosome in macrophages versus DC may differ. For instance, Mtb-infected macrophages that die via apoptosis are rapidly efferocytosed by uninfected macrophages, which ultimately results in lysosome fusion and destruction of Mtb [2]. However, the mechanisms by which antigens derived from the efferosome are acquired by DC are still poorly understood. Our data suggest that annexin 1 is also involved in autophagy which may facilitate access to antigens for cross-presentation [3]. Future studies are necessary to assess the fate of efferosome in DC. As we have evolved with such a refined immune system, pathogens have also developed sophisticated mechanisms in-step to deal with our immunity including hijacking process involved in cell death. Although efferocytosis of apoptotic Mtb-infected macrophages by macrophages/DC is beneficial to the host, some other intracellular pathogens have evolved to subvert efferocytosis for their own survival. For instance, efferocytois of apoptotic Leishmania major-infected neutrophils by macrophages may promote infection as the bacteria appears to utilize efferocytosis as “Trojan Horse” for getting access into the macrophages for replication [7]. Thus the arms race between pathogens and hosts will persist indefinitely.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.010
GPT teacher head0.252
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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