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Enregistrement W2317027602 · doi:10.1038/icb.2011.28

Regulators of T‐cell memory generation: TCR signals versus CD4<sup>+</sup> help?

2011· article· en· W2317027602 sur OpenAlexaff
Channakeshava Sokke Umeshappa, Jim Xiang

Notice bibliographique

RevueImmunology and Cell Biology · 2011
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueT-cell and B-cell Immunology
Établissements canadiensSaskatchewan Cancer AgencyUniversity of Saskatchewan
Organismes subventionnairesnon disponible
Mots-clésT-cell receptorMemory cellT cellComputer scienceComputational biologyBiologyPhysicsGeneticsImmune system

Résumé

récupéré en direct d'OpenAlex

In the event of pathogen entry, antigen (Ag)-specific naive CD8+ T cells undergo activation and rapid clonal expansion that results in the generation of millions of effector CD8+ cytotoxic T lymphocytes (CTLs), and subsequently, a small cohort of memory cells. This dynamic event is largely controlled by signaling provided by the immunological synapse, proinflammatory cytokines and CD4+ T cells.1,2 However, how these signals contribute to the generation of heterogeneous populations of effector and memory cells from a relatively homogeneous and rare naive CD8+ T-cell population is still not clearly understood. Two recent reports in Blood from Smith-Garvin et al.3 and Wiehagen et al.4 now show that altered T-cell receptor (TCR) signals can affect differentiation, heterogeneity, and the functions of effector and memory cells, supporting growing evidence that the strength of TCR signals, at least in part, determines the fate of CD8+ T-cell lineage choices. To verify whether altered TCR signals impact effector and memory CD8+ T-cell differentiation fates, Smith-Garvin et al. use genomic knock-in mice that express tyrosine to phenylalanine mutations in SH2 domain-containing leukocyte phosphorylation of 76 kDa (SLP-76), and a well-defined infectious model, Armstrong strain of lymphocytic choriomeningitis virus (LCMV). On the other hand, Wiehagen et al.4 used conditional knockout mice where they ablated the SLP-76 gene by administering estrogen analog, tamoxifen. As SLP-76 mediates initial TCR-induced phosphorylation signals to various downstream effector molecules, mutation in its tyrosine residues or its conditional deletion results in defective phosphorylation of critical molecules that propagate TCR signals.3,4 Thus, this elegant approach allowed the study of how TCR signal strengths determine memory differentiation fates. On the basis of temporal expression of CD62L, a central memory (Tcm) marker, Smith-Garvin et al.3 showed an increased rate of effector memory (Tem) to Tcm conversion in LCMV-infected SLP-76-knock-in mice. Similarly, when SLP-76 expression was abolished during the contraction or memory phase, Wiehagen et al.4 also observed an increased rate of Tem to Tcm conversion. In line with these results, Sarkar et al.5 showed that this rate of conversion is largely influenced by priming signals, such as Ag strength (strong versus subdominant epitopes), and/or duration of infection. Fousteri et al.2 showed that, during later stage of viral infection, naive CD8+ T cells receiving weaker TCR signals due to reduced Ag concentration convert into memory cells efficiently. Similarly, the preferential development of Tcm from latecomer CD8+ T cells that received weaker stimuli following infection by intracellular pathogens was also reported.6,7 Notably, inducing short-term transgene expression following adenovirus serotype-5 or plasmid DNA immunization also produced higher levels of Tcm and a more robust secondary response compared with more sustained expression, in which persistence and predominance of effector CTLs and Tem are observed.8,9 Smith-Garvin et al.3 and Wiehagen et al.4 attempt to address the functional characteristics of memory cells by re-challenging the mice with potent immunostimulants. Interestingly, although Tcm exhibited a mature memory phenotype expressing CXCR3, CD27, CD44, CD127, CD122 or CD62L, they observed partial or complete loss of interferon-γ-secreting and proliferative responses to re-challenge by LCMV-specific peptide(s) and Listeria monocytogenes3 or LCMV clone-13,4 respectively (Figure 1a). However, stimulation with phorbol myristate acetate/ionomycin, which circumvents proximal TCR signaling, showed that these Tcm can secrete cytokines similar to wild-type cells, suggesting they are not terminally differentiated following TCR stimulation. As phorbol myristate acetate/ionomycin provides very potent, nonspecific stimulation, its signaling is possibly strong enough to drive cytokine secretion from these Tcm even if they are poorly functional. Thus, although their studies provide compelling evidence of a role for TCR signals in Tcm generation, they are unable to assess the requirements for fully functional Tcm during secondary responses. One possible explanation for the poorly functional Tcm described in these two papers is that the strength of recall stimulus might determine memory response10 (Figure 1a). Alternatively, it is possible that defective Tcm generation occurs because of the reduced or lack of TCR signals during priming or contraction. Supporting this notion, Teixeiro et al.,1 by directly introducing point mutation into the TCR-β-transmembrane domain, showed that reduced TCR signals leading to poor TCR polarization and a severe decrease in nuclear translocation and DNA binding of nuclear factor-κB, resulted in defective memory, but normal primary, responses. Furthermore, a study by Gett et al.11 suggested that stronger TCR signals increase the fitness of T cells by enhancing survival and cytokine responsiveness, whereas weaker signals result in T-cell death because of the poor responsiveness to cytokines, interleukin (IL)-7 and IL-15. These results suggest that differential TCR signals induce memory cells with separable fates, exhibiting altered functions. From these observations, it seems that the functional memory cells observed in infected or immunized wild-type mice2,5,6,7,11,12 are different from defective memory cells observed in infected, genetically mutated mice1,3,4 (Figure 1). Hence, to assess Tcm functions in the latter reports, future studies should focus on temporarily halting or reducing TCR signals at different stages of CTL responses so that, during recall phase, Tcm receive normal TCR signals. CD4+ T-cell help during priming has been implicated in the generation of functional memory CD8+ T cells in both infectious and non-infectious diseases.12,13,14,15 In addition, during the contraction and memory phases, nonspecific signaling from naive, polyclonal CD4+ T cells is known to enhance the size and the health of memory cells pool.16 In the Smith-Garvin et al.3 study, cognate CD4+ T cells with mutated SLP-76 differentiate properly but failed to produce cytokines and exhibit effector functions.3 Similarly, in the Wiehagen et al.4 study, ablating the SLP-76 gene perturbed naive and possibly activated CD4+ T-cell repertoires (Maltzman JS, personal communication). Altered TCR signaling within the CD4+ T-cell population may also alter the differentiation of T-helper subsets including those that are responsible for cellular (Th1), humoral (Th2 and follicular Th cells) and regulatory (T regulatory cells (Tregs)) responses. Consequently, in these mice with altered SLP-76 function CD4+ T cells may not participate efficiently in providing help for both memory development and recall responses (Figure 1a) or the inflammatory environment may be changed. Furthermore, as regulatory mechanisms have crucial roles in suppressing excessive immune responses and memory generation after peak effector responses,17 depletion of Treg cells could result in enhanced generation of memory cells. Thus, in their studies, altered CD4+ T-cell repertoire or their responses could have profound effects not only on the rate of Tem to Tcm conversion, but also on the functionality of Tcm generated (Figure 1a). Indeed, many studies,2,6,7,18 including ours,13,12 showed the generation of functional Tcm by providing weaker TCR signals in the presence of CD4+ helper factors, such as CD40L and IL-2 signaling (Figure 1b). Hence, future studies to dissect the contribution of TCR versus CD4+ helper signals are required, perhaps by transferring physiological levels of TCR-transgenic CD8+ T cells with mutated SLP-76 background to congenic wild-type mice with a normal or depleted CD4+ T-cell environment before challenging with the pathogen. In this way, one could track effector and memory CD8+ T cells that have received weaker TCR signals but completely normal or no CD4+ helper signals. While Smith-Garvin et al.3 and Wiehagen et al.4 studies highlight the importance of altered TCR signals in CD8+ T-cell differentiation fates, there remains to be determined the relative degrees of threshold TCR signal strengths, and CD4+ T helper factors that shape hallmark features of Tcm, such as cytokine secretion and rapid proliferation. Further expanding these studies not only help in effective vaccine development, but also help in resolving why memory cells in certain chronic infections, and cancers, which often provide weaker antigenic TCR signals and exhibit defective CD4+ T-cell responses, are less functional compared with those in other diseases. The authors declare no conflict of interest. A proposed model for memory differentiation under differential TCR signals and CD4+ T-cell help. (a) Primed CD8+ CTLs receiving reduced or lack of TCR signals during priming or contraction phase, perhaps without CD4+ T-cell help, bias towards Tcm differentiation. During pathogen re-entry, these Tcm fail to secrete cytokines and proliferate efficiently,1,3,4 possibly because of the lack of sufficient TCR signal strength and/or CD4+ T-cell help. (b) In contrast, primed CD8+ CTLs receiving both reduced or lack of TCR signals and CD4+ T-cell help during priming or contraction phase may bias toward functional Tcm differentiation.2,5,6,7,11,12 During pathogen re-entry, these Tcm could respond swiftly by enhanced proliferation and cytokine secretion if they receive normal TCR signals and CD4+ T-cell help.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,043
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,002
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,215
Écart entre enseignants0,193 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations13
Publié2011
Routes d'admission1
Résumé présentoui

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