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PERSPECTIVES OPI N ION-DECIS ION MAK I NG I N TH E I MMU N E SYSTE M Cellular identity and lineage choice Amanda G. Fisher In multicellular organisms, cells usually respond to signals that they encounter in a manner that depends on their particular lineage ‘identity’. In other words, cells that have identical genomes can respond in markedly different ways to the same stimulus, with the outcome being determined largely by the previous developmental history of the cell. This general observation implies that individual somatic cells retain a ‘working memory’ of their ancestry and that this epigenetic information can be passed through successive rounds of DNA replication and cell division. Here, I discuss whether recent advances in our knowledge of chromatin biology and gene silencing can provide new insights into how cell fate is chosen and maintained during development. The formation of blood cells from haematopoietic stem cells (HSCs) has been studied intensively and remains a model for understanding cell commitment. Although standard texts illustrate a hierarchical relationship between HSCs and common myeloid and common lymphoid precursors, other haematopoietic ‘fate-maps’ have been proposed also. Each model is supported by different types of evidence and each offers a different interpretation of the precursor–product relationships between haematopoietic cells. For example, in the hierachical model (FIG. 1a), the first step proposes the generation of a progenitor that gives rise to megakaryocytes, erythrocytes, granulocytes and monocytes (a common myeloid precursor, CMP), as well as a precursor for T and B cells (a common lymphoid precursor, CLP). Evidence for this model comes from early demonstrations that chromosome-marked bone marrow can repopulate the myeloid or lymphoid compartments of transplant recipients1,2. The subsequent identification of progenitors that have the functional and phenotypic characteristics of CMPs3 and of CLPs4, and a comparison of their transcriptional profiles5, have added weight to the argument that myeloid versus lymphoid choice is a primary decision. In the second scheme (FIG. 1b), the commitment decision of haematopoietic precursors is considered to be stochastic — that is, at any one time, the choice is essentially random, with success being determined only later by the availability of essential growth and survival factors (a stochastic–selective model). Some support for this model can be taken from studies showing the co-expression of several distinct lineage-affiliated programmes by multipotent haematopoietic stem cells and progenitor cells6,7. In addition, assuming that cellular identity is determined ultimately at the level of many individual genes, there is growing evidence that gene activation has a stochastic basis, from which ‘all or nothing’ outcomes of gene expression can result. Examples of this include the expression of globin genes in developing erythroblasts8 and genetic studies of the mechanisms that underlie position-effect variegation (discussed in REF. 9). A third, radically different, model was put forward by Brown and colleagues in 1985 (REF. 10). The sequential lineage-determination model proposed that there is a predetermined (or prescribed) order of developmental choices (FIG. 1c). This model was based on experimental data showing the common origins and shared NATURE REVIEWS | IMMUNOLOGY features of different haematopoietic cells. The model proposes that HSCs undergo an intrinsic programme of decisions to generate cells that can differentiate along one or, at most, two discrete pathways. Support for the model was provided by quantitative studies of the rate of production of various haematopoietic cells11 and, more interestingly, by detailed analysis of the cell types that are absent from mice lacking key transcriptional regulators12. To illustrate the fundamental differences between these three models, it is perhaps worth using as an analogy the selection of careers by students during their secondary (high-school) education. According to the first model, students would be encouraged to make a fundamental decision early on, either to study arts or sciences. Within these disciplines, different career options are then offered (for example, medicine or fine art), as well as similar ones that differ only in their particular speciality (for example, to become a teacher). According to the second model, career choice is mainly vocational, the outcome depending on the individual student and whether there is a large enough job market for the skills on offer. The third model proposes a progressive education, in which candidates are offered career options in a defined order. If the offer is declined, then students continue their education (according to a defined syllabus) until they are qualified for the next round of recruitment. However, when reviewing these contrasting descriptions of lineage (or career) choice, it is important to understand that alternative schemes should be considered13 and that hierarchical models could also involve stochastic events or a sequential requirement for transcription factors. According to the career-choice analogy, one could imagine that a chance encounter with an exceptionally charismatic art or chemistry teacher might determine the career choice of a student, which is an example of randomness of choice in a prescribed educational structure. VOLUME 2 | DECEMBER 2002 | 9 7 7 © 2002 Nature Publishing Group PERSPECTIVES differentiation. These protein complexes are postulated to undergo successive changes in composition, a feature that might allow them to acquire and carry out new functions Transcription and cell identity During haematopoiesis, transcription factors are involved in many protein–protein interactions that define lineage and stage of a Stem cell CLP T cell CMP B cell Monocyte Neutrophil Erythrocytes Megakaryocyte b T cell B cell Monocyte Stem cell c Stem cell Megakaryocyte Neutrophil Me E Erythrocytes Megakaryocyte G Erythrocytes M Neutrophil B Monocyte T B cell T cell Figure 1 | Contrasting models of haematopoiesis. Three alternative schemes describing the generation of blood cells from primitive haematopoietic stem cells are shown. a | In the hierachical model, the first decision is to become a progenitor committed to either a lymphoid fate (a common lymphoid progenitor; CLP) or a myeloid fate (a common myeloid progenitor; CMP). Thereafter, CLPs generate T or B cells, whereas CMPs give rise to a range of other cell types, including monocytes, neutrophils, erythrocytes and megakaryocytes. b | The stochastic–selective model proposes that cell fate is chosen randomly, with success being determined by the availability of appropriate survival and differentiation factors. c | In the sequential-determination model, the order of developmental decisions is pre-determined, with cells making successive choices to differentiate along one or, at most, two discrete pathways. Precursors derived from haematopoietic stem cells progressively express the potential for megakaryocyte (Me), erythrocyte (E), granulocyte (G), monocyte (M), B-cell and T-cell development. At each developmental stage, a decision is made to either execute the differentiation programme that is on offer or proceed to the next cell-fate option. 978 | DECEMBER 2002 | VOLUME 2 (discussed in REF. 14). One of the best-characterized examples of this is the interaction of the transcription factor GATA1 with many partners, including FOG1 (friend of GATA1), EKLF (erythroid Kruppel-like factor), SP1, CBP (CREB-binding protein)/p300 and PU.1 (REF. 15). There is compelling evidence that by manipulating the composition of transcription-factor complexes experimentally, different lineage outcomes can be favoured. This is shown most convincingly by examples of the re-specification of lineage fate induced by transcriptional regulators. For example, Heyworth, Enver and colleagues16 showed recently that in response to ectopic expression of GATA1, neutrophil/monocyte precursors are reprogrammed to take on erythroid, eosinophil and basophil-like cell fates. This demonstration of the re-specification of primary cells was based on early studies showing the antagonistic roles of PU.1 and GATA1 in myeloid and erythroid differentiation17,18,19, and the ability of GATA1 to reprogram avian myelomonocytic precursors20. Classical studies have shown also that single transcription factors, such as MyoD (myogenic differentiation)21, can specify cell lineage actively. In these experiments, the expression of MyoD was shown to be sufficient to generate muscle cells from a range of cell types, including fibroblasts and pigmented epithelial cells of the retina21,22. The importance of single transcription factors for dictating lineage fate is also clear from studies of the transcriptional regulator PAX5 (paired box gene 5)23. In this case, PAX5 functions not only by activation of the B-cell programme, but also by repression of other lineage fates — a fact that is evident at the molecular level by the activation or repression of the respective lineage-specific genes. For example, PAX5 is required for B-cell differentiation as its removal favours the development of alternative haematopoietic cells from haematopoietic precursors24. Attempts to restore B-cell development by supplying exogenous PAX5 to genetically deficient cells have indicated that PAX5 is required more or less continuously to maintain B-cell identity25,26. PAX5 can function as both a conventional activator of transcription (for example, in the case of the CD19 gene27) and a potent transcriptional repressor (through interaction with Groucho-like co-repressor proteins28). Together, these data highlight the importance of transcriptional activators and repressors for regulating lineage decisions, and they might indicate that commitment to a particular lineage is more flexible than was thought previously. www.nature.com/reviews/immunol © 2002 Nature Publishing Group PERSPECTIVES Stable gene silencing • • • • HAT activity Active gene transcription HDAC activity Chromatin compaction Locus repositioning CpG methylation Polycomb-group recruitment HMT activity SUV39H E(z)–Esc SUV39H Ac Ac Ac P P P Me Me P P Me HP1 Me P Priming Active euchromatin E(z)–Esc Me Me PC Me Neutral or permissive chromatin Repressed chromatin Figure 2 | A chromatin-based model of gene activation and silencing. DNA complexed with core histones and other chromosomal proteins forms chromatin. Gene activation and silencing are associated with characteristic changes in chromatin structure, which include specific modifications to core histone tails — such as acetylation (Ac), phosphorylation (P), methylation (Me) and ubiquitylation (not shown) — as well as changes in the degree of condensation of nucleosome fibres. In this example, an actively transcribed (euchromatic) locus is shown, in which the nucleosome fibre is accessible and acetylated (by histone acetyltransferases, HATs). This state might be stabilized further by interaction with Trithorax-group proteins and the selective methylation of, for example, histone 3 at lysine-4 (H3-K4; not shown). Gene silencing is shown as a sequential multi-step process, in which the degree of acetylation is reduced by histone deacetylases (HDACs) and site-specific methylation is achieved by recruitment of various histone methyltransferases (HMTs), including SUV39H (which methylates H3-K9) and the extra sex combs (Esc)–enhancer of Zeste (E(z)) complex (which methylates H3-K9 and H3-K27). Methyl-docking partners, such as heterochromatin protein 1 (HP1) and Polycomb (PC), that recognize these specific modifications, stabilize heterochromatin structure and condensation, and reduce accessibility. Silencing or ‘marking’ of an inactive locus might be enhanced further by the recruitment of additional PC-group proteins, CpG DNA methylation and locus repositioning in the nucleus. SUV39H, suppressor of variegation 3-9 homologue. Conventionally, cellular identity has been described in positive terms — that is, in terms of the set of expressed genes that give a cell its distinguishing character. It is worth pointing out that an equally valid, if less intuitive, description of identity could be based on the extent of the genome that is not expressed or is actively silenced. In fact, this ‘negative’ description of cell identity pre-dates much of our present fascination with molecular signatures of gene expression (discussed in REF. 29). The idea that lineage-specific transcription factors function not only by activating gene expression, but also by repressing inappropriate genes, has several important precedents, particularly with regard to functional studies of the transcription factors MAFB (musculoaponeurotic fibrosarcoma oncogene homologue B)30, PU.1 (REF. 31) and GATA1 (REF. 32). Despite accumulating evidence that gene repression is crucial for determining haematopoietic and neural cell fates33,34, less attention has been focused on gene silencing that on gene activation. Access to accurate gene-expression profiles for HSCs, lineage-committed precursors35,36, neural stem cells and embryonic stem (ES) cells might allow us to distinguish overlapping sets of genes that are likely to be concerned with, for example, stem-cell identity (self renewal and differentiation). Recently, Ivanova and Lemischka37 identified a group of genes that are enriched in HSCs, ES cells and neural stem cells, and they showed that these genes encode several transcription factors that were known previously to sustain the activity of HSCs (such as early developmental regulator 1, EDR1) and epidermal stem cells (such as transcription factor 3, TCF3), and to regulate the proliferation of neural stem cells (such as ephrin-B2, EFNB2; and hairy and enhancer of split 1, HES1). This kind of analysis, although in its infancy, offers some promise. If it can be applied to mammalian cells with the same success as has been achieved for Saccharomyces cerevisiae (a simple eukaryote), then we will have an ‘information framework’ with which to begin to define the ‘molecular circuitry’ of haematopoietic cells during differentiation. The complexity of this task should not be underestimated (discussed in REF. 38), and complementary approaches are likely to be required to advance our understanding of haematopoiesis in the interim. Chromatin and lineage restriction Gene expression is determined not only by the availability of combinations of transcription factors, but also by chromatin context. The interactions between transcription factors that occur during haematopoietic differentiation have been likened to a cocktail party, in which the introduction of new guests (and exit of old guests) encourages new topics for discussion14. According to this NATURE REVIEWS | IMMUNOLOGY analogy, chromatin structure can be thought of as the venue for the cocktail party. Just as one might anticipate that at a gentlemen’s club (to which women are not admitted) or at a venue where alcohol is prohibited, the topics of conversation might be more restricted (and less cosmopolitan), so the chromatin context of specific genes might restrict or encourage particular transcriptional outcomes. Formal proof that gene expression is not dictated by transcription factors alone is provided by several well-characterized examples of imprinted genes, for which expression of a single allele is predetermined according to the parent of origin39. It is probable also that chromatin-based self-templating mechanisms are involved in conveying transcriptional states through the cell cycle. This might be particularly important for maintaining lineage identity in haematopoietic cells, such as HSCs and lymphocytes, for which proliferation is an essential part of the function of each cell type. Several epigenetic modifications that are associated with active and inactive chromatin states have provided clues as to how such selfpropagating mechanisms might operate. For example, DNA methylation — which is important for the transcriptional repression of imprinted genes, as well as genes on the inactive X-chromosome and candidate tissuespecific genes40 — is mediated by specific DNA methyltransferases (DNMTs). In the case of DNMT1, this enzyme is recruited to VOLUME 2 | DECEMBER 2002 | 9 7 9 © 2002 Nature Publishing Group PERSPECTIVES replication forks at S-phase41, where it establishes symmetrical CpG methylation of hemimethylated substrates, effectively duplicating DNA-methylation patterns on newly synthesized DNA strands. This property, together with the action of methyl-CpG-bindingdomain proteins (such as MECP2), acts to repress transcription and recruit histone deacetylases, providing a possible mechanism to propagate transcriptionally inactive states42,43. Other features of active and inactive chromatin that might be relevant to understanding how transcriptional states are effectively ‘locked-in’ in differentiated cells include the covalent modification of histone tails44 and the spatial restriction of loci to certain nuclear domains (reviewed in REF. 45). It is an interesting consideration how specific genes are targeted for this type of regulation. It is assumed that sequence-specific DNA-binding factors that activate or repress transcription either can recruit protein partners that are capable of further chromatin modifications and locus recruitment, or can carry out such functions themselves (discussed in REFS 45, 46). On the basis of several recent reports, it is possible to construct a hierarchy of interrelated epigenetic changes that provide a plausible mechanistic bridge between transcriptionally active, permissive, repressive and permanently silent chromatin states. Although the scheme that is illustrated in FIG. 2 is far from complete, these new studies provide three important clues to understanding chromatin-based transcriptional regulation. First, histone methylation at specific residues can recruit additional components that further stabilize a repressive chromatin state. For example, the methylation of lysine-9 of histone 3 (H3) by SUV39H (suppressor of variegation 3-9 homologue) recruits the structural heterochromatin protein HP1 (REFS 47,48). Similarly, the methylation of H3 lysine-9 and lysine-27 by extra sex combs (Esc) and enhancer of Zeste (E(z)) is postulated to recruit Polycomb (Pc), a component of the Polycomb repressor complex 1 (PRC1), thereby enhancing repression and permanently ‘marking’ the silent state49,50. Second, it has been shown that histone methylation and DNA methylation are inter-dependent51, which provides a mechanism by which protein and DNA modifications can ‘converse’52. Third, recent studies highlight an increasingly important role for intergenic and sterile (non-coding transcripts) transcription for the recruitment of chromatin modifiers (in particular, histone acetyltransferases) before bona fide gene transcription53,54. 980 Pro-T cell IgH locus Constitutive heterochromatin comprising 'clusters' of centromeric DNA and associated proteins ES cell Relocation Locus Pro-B cell compaction Gene rearrangement Immunoglobulin alleles are peripheral Mature B cell Allelic choice Immunoglobulin alleles are poised and central Monoallelic expression Immunoglobulin alleles are non-equivalent Figure 3 | Repositioning of immunoglobulin alleles in developing B cells. Immunoglobulin heavychain (IgH) and light-chain (IgL) loci undergo large-scale changes in their sub-nuclear position and compaction during B-cell development. In embryonic stem (ES) cells and T-cell progenitors (pro-T cells), immunoglobulin alleles (red circles) are located adjacent to the nuclear periphery and away from clusters of centromeric heterochromatin (shown in grey). In pro-B cells, before the onset of IgH rearrangement, IgH alleles are repositioned in the interior of the nucleus and undergo locus compaction. After immunoglobulin gene rearrangement and allelic choice, a single productively rearranged and transcribed IgH allele (and a single IgL allele) is positioned away from heterochromatin clusters. Unrearranged and non-productively rearranged immunoglobulin alleles are recruited close to centromeric heterochromatin domains in the nucleus of mature B cells. Interestingly, the low levels of transcription of lineage-affiliated genes that are seen in HSCs, CLPs and MLPs4,16 might be owing to the selective ‘opening-up’ of chromatin (or priming) in precursor populations. An alternative interpretation of these observations is that the apparently ‘promiscuous’ transcription indicates that changes from permissive to repressive chromatin states occur in committed progenitors once a particular fate or option has been excluded. These contrasting possibilities illustrate differing viewpoints on the probable contribution of sequential gene activation versus progressive gene silencing to commitment and lineage restriction29. An additional feature of the multi-layered model of chromatin events that promote either gene activation or heritable silencing (FIG. 2) is that it might offer some clues about cell plasticity. According to such a model, it might be relatively easy to reprogram cells that retain a permissive chromatin configuration, but more difficult to re-specify cells that have already shut down expression of key genes. | DECEMBER 2002 | VOLUME 2 Chromatin and nuclear location The combined role of chromatin-based mechanisms and transcription factors in controlling lineage fate is exemplified by the development of T helper (TH)-cell subsets. Naive CD4+ progenitors can be induced by different stimuli to differentiate to two functionally different types of cell that express either interferon-γ (IFN-γ; TH1 cells) or interleukin-4 (IL-4; TH2 cells). Differentiation results in modifications to the chromatin structure of the effector-cytokine genes55, including changes in DNA demethylation and methylation56, histone acetylation and accessibility to NFAT1 (nuclear factor of activated T cells 1) at locus-regulatory regions57. These modifications, which are progressive, help to polarize the developing cells, so that expression of IL-4 and IFN-γ is mutually exclusive. The silencing of expression of IL-4 or IFN-γ might be stabilized further by the large-scale recruitment of these loci to specific heterochromatin domains in the nucleus 58. Interestingly, with successive www.nature.com/reviews/immunol © 2002 Nature Publishing Group PERSPECTIVES division, progeny cells loose the ability to revert to the alternative lineage, an observation that is consistent with lineage restriction being underpinned by progressive gene silencing. Although the role of nuclear ‘architecture’ in regulating cellular gene expression is not well understood, there are specific and compelling examples in which gene recruitment to heterochromatin can cause silencing59 and gene movement away from heterochromatin (or from chromosome territories) is a feature of expression60–62. In this respect, several socalled ‘nuclear compartments’ have been described, and two of these — the nuclear periphery and centromeric heterochromatin — seem to be important for propagating or restricting expression of certain genes in haematopoietic cells. One example, which is shown in FIG. 3, is the relocation of immunoglobulin alleles in developing B cells. Kosak et al.63 showed recently that in ES cells, multipotent bone-marrow precursors and pro-T cells, immunoglobulin heavy-chain (IgH) and immunoglobulin κ-light-chain (Igκ) alleles occupy perinuclear positions close to the nuclear lamina. In committed pro-B cells, these loci are selectively repositioned away from this compartment immediately before immunoglobulin-gene rearrangement — an observation that indicates that relocation might regulate the lineage- and stage-specific accessibility of immunoglobulin loci to chromatin modifiers and the recombination machinery. Later, after the productive rearrangement of single immunoglobulin heavy- and light-chain genes, Skok and colleagues64 showed that individual immunoglobulin alleles that are ‘selected against’ (germline or non-productive rearrangements) are repositioned close to repressive heterochromatin clusters, resulting in expression from a single IgH and Igκ (or Igλ) locus. Amanda G. Fisher is at the Lymphocyte Development Group, Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College of Science, Technology and Medicine, Hammersmith Campus, Du Cane Road, London W12 0NN, UK. e-mail: [email protected] doi:10.1038/nri958 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Concluding remarks Our knowledge of the relationship between chromatin structure, chromosome movement and cell-fate choice is still fragmentary. 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Nonequivalent nuclear location of immunoglobulin alleles in B lymphocytes. Nature Immunol. 2, 848–854 (2002). Acknowledgements I would like to thank my colleagues, in particular members of the Lymphocyte Development Group, for helpful discussions. Online links DATABASES The following terms in this article are linked online to: LocusLink: http://www.ncbi.nlm.nih.gov/LocusLink/ CBP | CD19 | DNMT1 | EDR1 | EFNB2 | EKLF | FOG1 | GATA1 | H3 | HES1 | IFN-γ | IL-4 | MAFB | MECP2 | MyoD | NFAT1 | p300 | PAX5 | PRC1 | PU.1 | SP1 | SUV39H | TCF3 Access to this interactive links box is free online. OPI N ION-DECIS ION MAK I NG I N TH E I MMU N E SYSTE M Progressive differentiation and selection of the fittest in the immune response Antonio Lanzavecchia and Federica Sallusto T cells are stimulated by stochastic exposure to antigen-presenting cells and cytokines. We review evidence that the level of signal that is accumulated determines progression through hierarchical thresholds for proliferation and differentiation, leading to the generation of various intermediates and effector T cells. These cells are then selected to enter the memory pool according to their fitness — that is, their capacity to access and use survival signals. We suggest that the intermediates that are generated by antigenic stimulation of T and B cells persist as central memory cells, which can mount secondary responses to antigen and maintain appropriate levels of effector cells and antibodies throughout the lifetime of an individual. Antigenic stimulation can lead to divergent responses that range from the deletion of antigen-specific lymphocytes and tolerance to the generation of a large number of effector cells, followed by establishment of immunological memory. The mechanisms that account for these divergent responses remain uncertain. In this article, we elaborate further on a 982 progressive-differentiation model that we have proposed previously for T cells1, and we discuss this model in the context of present experiments and competing models. The progressive-differentiation model (BOX 1) proposes that, as a function of the level of signal that is accumulated, T cells progress through hierarchical thresholds for proliferation and DIFFERENTIATION. Stochastic exposure to antigenpresenting cells (APCs) and cytokines, owing to random encounters of variable duration, results in the generation of different fates that are then selected on the basis of their capacity to survive, in the absence of antigen, as distinct populations of memory T cells. This model, which can be extended to B-cell differentiation, proposes that the INTERMEDIATES of the differentiation process form a pool of CENTRALMEMORY CELLS with stem-cell-like properties. Signal strength and T-cell fate The amount of signal (SIGNAL STRENGTH) that T cells receive by interacting with APCs is determined by three factors: the concentration of peptide–MHC complexes, which determines the rate of T-cell receptor (TCR) triggering2; the concentrations of co-stimulatory | DECEMBER 2002 | VOLUME 2 molecules, which determine the extent of signal amplification3; and the duration of the interaction between T cells and APCs, which determines for how long signal is accumulated. The amount of signal that T cells receive can vary over several orders of magnitude. The number of peptide–MHC complexes displayed by an APC can vary by a factor of 103, and the degree of signal amplification provided by co-stimulation can vary by a factor of 102 (REFS 3,4). In addition, T cells can engage APCs in single or multiple contacts of variable duration5,6. The concept of signal accumulation is supported by the finding that the commitment of naive T cells to proliferation can be reached in ~6 hours if T cells are stimulated by a high dose of antigen plus costimulation, but requires as long as 40 hours if T cells are exposed to low doses of antigen and co-stimulation7. T-cell differentiation involves the regulation of transcriptional programmes that control the cell cycle, response to cytokines, migratory capacity, effector function and susceptibility to activation-induced cell death (AICD)8–11. In general, T-cell differentiation is a slow and progressive process that is mediated by EPIGENETIC changes12. After primary stimulation, effector function is acquired by only a fraction of the proliferating T cells, and this fraction increases after subsequent restimulations. The main hypothesis on which the progressive-differentiation model is based is that some transcriptional programmes are activated at a low strength of stimulation, whereas others require a higher strength of stimulation, as well as additional signals delivered by cytokines. By exposing CD4+ T cells to plastic-bound TCR ligands and co-stimulatory antibodies for different periods of time, it has been possible to determine a precise relationship between signal strength and T-cell fate. Hierarchical thresholds of stimulation have been defined for cell proliferation, differentiation and death7,13–15 (FIG. 1a). At low signal strength, naive T cells proliferate but do not acquire effector function, and they retain lymph-node-homing capacity. By contrast, at high signal strength and in the presence of cytokines that polarize differentiation to T helper 1 (TH1) or TH2 effector cells, CD4+ T cells lose lymph-node-homing capacity, but acquire effector function and the capacity to migrate to inflamed peripheral tissues. Finally, at even higher levels of stimulation, T cells are deleted through AICD. The role of cytokines. Cytokines are the prototypical external cues that determine the quality of T-cell responses. Interleukin-12 (IL-12) and IL-4, which are produced by APCs and www.nature.com/reviews/immunol © 2002 Nature Publishing Group