s2fieldsofstudy: Biology Medicine

text:
Involvement of dendritic cells in autoimmune diseases in children

Dendritic cells (DCs) are professional antigen-presenting cells that are specialized in the uptake of antigens and their transport from peripheral tissues to the lymphoid organs. Over the last decades, the properties of DCs have been intensely studied and much knowledge has been gained about the role of DCs in various diseases and health conditions where the immune system is involved, particularly in cancer and autoimmune disorders. Emerging clues in autoimmune diseases, suggest that dendritic cell dysregulation might be involved in the development of various autoimmune disorders in both adults and children. However, studies investigating a possible contribution of DCs in autoimmune diseases in the pediatric population alone are scanty. The purpose of this review is to give a general overview of the current literature on the relevance of dendritic cells in the most common autoimmune conditions of childhood.

Background
Autoimmune disorders are chronic disabling disorders in which underlying defects in the immune response resulting in an inappropriate response to self-tissues. Collectively, autoimmune diseases are thought to affect approximately 14-22 million people in the United States, according to the American Autoimmune Related Diseases Association (AARDA) representing greater than 80 unique disorders [1], which affect preferentially women.
Autoimmune disorders in children are less common but important to diagnosis, as immunomodulating therapy can prevent considerable mobility and mortality, and improve the survival of many of these patients. Autoimmune diseases are characterized by the loss of tolerance against self-determinants, activation of autoreactive lymphocytes and/or autoantibodies, with pathological damage that is organ specific or systemic.
A clear understanding of the mechanisms by which autoimmune responses are triggered leading to the activation and/or induction of autoreactive lymphocytes and to the breakdown of immunological self-tolerance are not yet fully understood. Currently, multiple lines of evidence indicate that DCs may also participate in the onset of autoimmune diseases. [2][3][4][5]. Animal models show the transfer of DCs isolated from donors with acute autoimmune disease or propagated in vitro under conditions that induce maturation, generates a strong T helper (Th)-1 response, eventually culminating in autoimmune disease [6]. For instance, one of the hallmarks of systemic autoimmune diseases, such as systemic lupus erythematosus (SLE), is the immune response to nuclear autoantigens. Several studies have proposed that DCs may acquire the nuclear autoantigens from the apoptotic cells to initiate the systemic autoimmune responses [7,8]. On the other hand, experimental models of diabetes in mice suggest that DCs may trigger autoimmunity by initiating a local or systemic response to an infective agent [9]. Increased numbers of DCs have been described in chronic arthritis synovial membrane and fluids [10][11][12]. However, there have been a limited number of studies investigating the role of DCs in the immunopathogenesis of autoimmune disorders in childhood.
We think that, a better understanding of unique pathogenic involvement of DCs in autoimmune diseases will hopefully lead to the development of better, more targeted and less toxic therapies and could contribute to improve their outcome. Therefore, targeted modulation of DC function may open new treatment options aiming at alleviating DC-driven autoimmune responses. In this review, an attempt has been made to summarize recent data on DCs physiology in autoimmune diseases in the pediatric population.

Dendritic cells: key cells in autoimmune diseases?
Briefly, DCs are a population of bone marrow-derived leukocytes that efficiently link the innate and adaptive immune systems and play a crucial part in initiating, amplifying and controlling the immune response to pathogenic microorganisms [13]. DCs reside in and traffic through non-lymphoid peripheral tissues where they develop to a stage referred to as immature DCs, continuously surveying the environment for invading microorganisms. These immature DCs (iDCs) are characterized by high capability for antigen capture and processing, but low antigen presentation and T cell stimulatory capabilities. DCs in the periphery are triggered by exposure to microbial agents such as lypopolysaccharide (LPS) or inflammatory mediators such as tumor necrosis factor (TNF-α) and interleukin-1 (IL-1) are induced to enter in a maturation process [14,15].
During their conversion from immature to mature cells, DCs undergo a number of phenotypic and functional changes. They lose their ability to capture antigen and transform into efficient antigen presenting cells (APCs). The process of DC maturation is characterized by an increased surface expression of major histocompatibility complex (MHC) class I and class II, up-regulation of T-cell costimulatory molecules such as CD80, CD86 and CD40, secretion of chemokines and cytokines, surface expression of adhesion molecules and chemokines receptors [16]. Chemokine receptors promote DC migration out of nonlymphoid tissues into the blood or afferent lymphoid vessels, as well as enhanced T cells stimulation. These migratory cells reach secondary lymphoid organs where they home to the T cell areas, and interact with, stimulate and direct primary T-and B-lymphocytes responses. Maturation of DCs modifies expression of chemokines receptors and adhesion molecules, causing migration from the periphery to the T cell zone of secondary organs. [17,18] The types of T cell-mediated immune responses induced can vary depending on the specific DC lineage (myeloid vs. lymphoid) and maturation stage in addition to the activation signals received from the surrounding microenvironment. During the primary immune responses, the DC subset is a critical determinant for polarizing naive T cells into Th1 or Th2 cells [19]. Studies over the last decade have demonstrated that the distinct subsets of human DCs (myeloid and plasmacytoid DCs a form of lymphoid DC) induce the different profiles of T cells responses [13,15,20]. For example, studies have shown that myeloid DCs (mDCs) produce a large amount of IL-12 and preferentially induce Th1 development, whereas plasmacytoid DC (pDCs) secrete lower amounts of IL-12 and primarily elicit Th2 development [21][22][23][24]. On the other hand, other studies have suggested that functional differences between DCs in guiding T cell responses might depend on not only their lineage but also the microenvironment of cytokines and/or inflammatory mediators in the primary immune response [22,24].

Role of dendritic cells in children autoimmune diseases Dendritic cells in children lupus
Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by polyclonal B-cell activation, the production of antinuclear antibodies (ANAs) and systemic inflammatory injury of multiple organs. SLE constitutes up to 10 percent of the new diagnosis of systemic rheumatic diseases in childhood [25]. The pathogenesis of SLE is correlated with both genetic predisposition and environmental influences. The contribution of these two factors may differ between individuals, but the resulting malfunctions in the immune system and the production of autoantibodies plays a pivotal role in the pathogenesis of SLE; however, the mechanisms of how this occurs in SLE pathogenesis remains unclear. Lupus has been considered mainly as B-cell disease resulting from altered Tcell and B-cell interactions [26,27]. The immune system abnormalities seen in patients with lupus are diverse and include CD4+ autoreactive T cells that are specific for ubiquitous self-peptides and provide pathogenic B cell help, ANA-producing autoreactive B cells, alterations in Th1 and/or Th2 lymphocyte functions resulting in production of cytokines that up-regulate autoantibody production by B cell, promote immune complex formation which determine different subsets of the disease [26,28,29].
The mechanisms by which an autoimmune response is triggered and activation of autoreactive lymphocytes is initiated and maintained in SLE are not fully understood. Different groups have proposed that T cell abnormalities in SLE could be induced or promoted, at least in part, by alterations in DCs phenotype and function, because these are key regulators of the immune system [30][31][32]. Naïve T lymphocytes circulate through the blood and secondary lymph organs (SLOs), where they scan for antigen-histocompatibility complex molecule displayed on dendritic cells. If accompanied by appropriate co-signals, naïve T cell-DC interaction induces T cell clonal expansion and promotes migration either to B cell area to assist in antibody production or out of the lymphoid tissue to sites of inflammation [33]. Moreover, DCs appear to be the only class of antigen presenting cells that have the capacity to stimulate the expansion of naïve T cells and thereby initiate primary immune responses [15,34,35]. DCs can also generate regulatory T cells that suppress activated T cells, a function of probable importance in autoimmunity [36].
Type I interferons (IFNs) are produced in response to viral and non-viral infections and may be induced during T cell-DC interactions in the absence of infecting agents [37]. Type I IFNs have been shown to act as a maturation factor for DCs and to increase DC maturation [38,39]. Patients with SLE have increased blood levels of IFN-α, which correlate to disease activity [32,[40][41][42]. In addition, drug-induced lupus has been reported in hepatitis C or cancer patients treated with recombinant IFN-α [43]. This evidence suggests a significant role to the pDCs, the major source of IFN-α in the blood, in the immunopathogenesis of SLE. Palucka et al. [44] have been the first group to identify how the interaction between lymphoid and myeloid DCs might play an important role initiating the immune response in SLE patients. They linked a hyperactivated secretion of IFN-α by DCs to the immunological dysfunction observed in children with SLE. In brief, serum from children with SLE induced monocytes to differentiate into DCs. Furthermore, they found that DCs are stimulated to proliferate when peripheral mononuclear cells (PBMCs) from normal donors were cultured with the serum of pediatric lupus patients. IFN-α was identified as the cytokine responsible for this effect and, as seen in other reports, pDCs were the major source of interferon in the blood of these patients. From these findings, they have formulated a hypothesis that explains the activation and pivotal action of the type I IFN system in the development of SLE. It is based on the activation of immature myeloid dendritic cells through type I IFNα/β. IFN-matured mDCs are proposed to efficiently capture autoantigens (apoptotic cells and nuclesomes) and then present the antigens to CD4+ T cells which initiate the expansion of autoreactive T cells. The mDCs together with pDCs could help to expand autoreactive B cells, followed subsequently by autoantibody production. This abnormal immune reaction could finally lead the immune system of lupus patients to attack their own tissues with the subsequent injury to various organ systems, including skin, kidney and central nervous system [44][45][46]. Ronnblom et al. implicated pDCs and IFN-α in adults with SLE [42,47]. Interesting others investigators have demonstrated in SLE subjects that circulating immune complexes ((ICs), in addition to INF-α, activates DCs and can induce cytokines and chemokines implicated in SLE pathogenesis. For instance, the local production of the chemokines IL-8, MCP-1, and RANTES has been noted in inflamed joints of SLE patients, and serum levels of MCP-1 and IP-10 are higher in SLE patients than in controls [48,49]. Means et al. demonstrated that anti-DNA autoantibody ICs were able to activate DCs through a cooperative interaction between Toll-like receptor 9 (TLR9) and FcγRIIa (CD32) [50].
These findings may provide a framework for developing better lupus therapies that the currently available, however more research is needed to clarify the exact role of DCs in lupus pathogenesis.

DCs in Juvenile Dermatomyositis
Juvenile DM is the most common of the idiopathic inflammatory myopathies in children. It is considered an autoimmune disease of etiology and pathogenesis relatively unknown. The inflammatory lesions consist of perivascular, perifasicular and intradermal lymphocytes infiltrates. The perivascular infiltrates are composed mainly of CD4+ T lymphocytes, B lymphocytes, macrophages [51]. While the exact triggers of the immune response in children with juvenile DM have not been identified, recent studies have attempted to elucidate the targets of such abnormal immune responses. The presence of T cells indicates an ongoing immune response requiring the presence of APCs. Emerging data suggest that DCs, the most potent APCs, may be involved in the immunopathogenesis of the idiopathic inflammatory myopathies (IIM). Mature DCs have been detected in dermatomyositis and polymyositis muscle tissue, predominantly located in perivascular infiltrates and surrounded muscle fibers [52]. Recently, our laboratory demonstrated that pDCs populate muscle lesions of patients with new-onset Juvenile DM [53]. We compared samples of muscle tissue from children with Juvenile DM to patients with non-inflammatory muscle disorders using triple immunofluorescence analysis (Figure 1). We found that pDCs populate muscle lesions of patients with new onset JDM, the majorities of these pDCs were mature as indicated by high CD83 expression and they were localized in close proximity to T cells and B cells in the perimysium and perivascular areas (Figure 2). Since such cellular infiltrates contained a large proportion of T cells, presence of mature pDCs is consistent with the idea that these infiltrates are foci of inflammation. Furthermore, we also found that DC-derived chemokines CCL21, CCL19 and CXCL12 ("lymphoid" chemokines), which have been demonstrated to be up regulated in ectopic secondary lymphoid organs at sites of chronic inflammation [54][55][56], were over-expressed within organized infiltrates in Juvenile DM muscle lesions. The simultaneous presence of DCs, T-and B-cells and the chemokine profile found in the inflamed muscle tissue of these patients suggests that interactions among these cells types might be instrumental in the local induction and maintenance of neo-lymphoid genesis in JDM muscle.
Recent advances in the study of patterns of gene expression with the use of microarray technology, has provide new insights into the study of role of pDCs in the immunopathogenesis of adult and Juvenile DM. A gene expression profile identified by microarray analysis and consistent with IFN-mediated gene transcription in inflammatory myositis was first reported by Tezak and colleagues in a study of muscle biopsies from JDM and age-matched controls [57]. They compared the gene expression profile data from children with untreated Juvenile DM, positive for the DQA1*0501 allele, with data from children with Duchene muscular dystrophy and healthy pediatric controls, as well as profiles reflective of intracellular antiviral response by using Affymetrix HuFL Gene Chips. They found profound dysregulation in muscle biopsies from children with Juvenile DM, most of the dysregulated genes being interferon-inducible genes. This pattern of gene expression found was consistent with an of IFN α/β transcription cascade seen in an in vitro viral resistance model. These findings gave additional support to the hypothesis that the pathogenesis of Juvenile DM is a response to an infection agent, particularly since transcription of IFN-inducible genes is a hallmark of the host defense mechanism against infection. From this profiling data, the authors hypothesized a model of disease pathogenesis that involves a repetitive cycle of muscle injury in which both INF-α/β and INF-γ cascades lead to muscle ischemia and increased production of TNF-α and nitric oxide, which in turn, interact with the immune response cascades in the endothelium and with infiltrating T and pDCs, thus exacerbating the IFN-induced processes. In a recent work from our laboratory [58], we investigated patterns of gene expression profiling of peripheral blood cells from adult and Juvenile DM and healthy controls by using as well microarray analysis. We studied the expression levels of 314 IFN-inducible genes between adult and Juvenile DM and healthy controls. We found that in the most of DM patients 93 out of 314 genes examined were overexpressed in DM patients, which correlated with disease activity. The particular interest, we noted the increased expression of a number of genes involved in muscle function, mitochondrial/oxidative phosphorylation and immune function. Many genes previously demonstrated by other investigators as overexpressed in other autoimmune diseases such as SLE [59,60], Sjögren's syndrome [61] and inflammatory myopathies [62] were similarly increased in our data. Together, our findings suggested that pDCs are an important source of IFN-α/β in adult and childhood DM and may therefore be of pathogenic importance, and even more relevant the IFN-profile found could points towards the type I IFN-α/β pathway as a candidate pathway for DM susceptibility genes.

DCs in Juvenile Inflammatory Arthritis
Juvenile arthritis is a group of chronic inflammatory diseases in children collectively known as Juvenile Idiopathic Architecture and cellular composition of inflammatory infil-trates in JDM muscle Arthritis (JIA). It is the most common chronic autoimmune arthropathies of childhood and an important cause of disability. JIA is characterized by a persistent inflammatory infiltrate within the synovial layer of the joints. The findings of T cells and chronic synovial inflammation have indicated a possible cellular-mediated immune response. However, the presences of immune complexes, complement, and inflammation in JIA have indicated a possible B cells hyperreactivity [63]. T cells within the hypertrophied synovium are activated, oligoclonal, and has a bias towards a T helper (Th1) phenotype in oligoarticular and polyarticular JIA. The immune response identified by the induction of Th1/Th2 cells may play an important role in the immunopathogenesis of JIA [64,65]. However, it is unclear what causes clonal inflammatory lymphocytes within the joints of these patients. One mechanism could be through signals received from APCs such as DCs. DCs may contribute to the synovitis by homing T cells as well as by the induction of cytokines belonging to both Th1/Th2 cells. Varsani et al [66] have recently found an increased number of cells with DC morphology, in the joint of children with JIA. Specifically, they examined the expression of the receptor activator of NF-κB (RANK), a TNF receptor-like surface protein derived from DCs, and its ligand (RANKL). The RANK/RANKL pathway is critical in bone erosion in conditions such as rheumatoid arthritis [67] and is involved in DC-T cell interactions. They investigated the expression of RANK/RANKL in paired samples of peripheral blood (PB) and synovial fluid (SF) from JIA patients, as well as in monocytederived dendritic cells by the reverse transcriptasepolymerase chain reaction and flow cytometry. They determined that RANK and RANKL were overexpressed in cells from both PB and SF compartments of children with JIA as compared to controls. Interesting, a large number of RANK+ synovial cells had the phenotype of mature myeloid dendritic cells. Mature DC may play a central role in the presentation of antigens to T cells and the production of inflammatory cytokines. These RANK+ cells also expressed the DC-specific adhesion receptor DC-SIGN (CD209), which supports rolling of DC-SIGN+ cells on the vascular ligand ICAM-2 under shear flow, a prerequisite for DC emigration from the blood into the peripheral tissues. Another novel finding of this study was that the majority of RANK+ DC-SIGN+ cells also expressed high levels of the costimulatory molecule CD86; the binding of this protein with CD28 antigen at the cell surface of T cells could be a costimulatory signal for activation of the T-cell in JIA synovium. Taken together, these findings suggest that RANK+ DCs in children with JIA might contribute to persistence and expansion of particular T cell subset within inflamed joint of JIA patients.
Similarly, Palucka et al. [68] implicated INF-α production by pDCs in the immunopathogenesis of JIA. They have proposed that the induction of autoimmunity to nuclear antigens during anti-TFN-α therapy appears to be induced by IFN-α. They found that children with systemic onset JIA (SoJIA) who did received anti-TNF therapy displayed over-expression levels of IFN-α-regulated genes in their blood leukocytes compared with patients without anti-TNF therapy. In addition, they found that the IFN-α production by pDCs generated from CD34+ hematopoietic progenitors exposed to influenza virus was inhibited by TNF. These findings led them to propose that the neutralization of endogenous INF during anti-TNF therapy might further switch the TNF/INF-α balance to a sustained IFNα secretion by pDCs with a well-known pathogenic effect, and therefore a possible explanation to the lupus-like symptoms develop during TNF blockade.

Role of dendritic cells in vasculities
Recent studies have investigated the participation of DCs in the pathogenesis of various vascular inflammatory diseases such as Giant Cell Arteritis (GCA) [69], Takayasu's Arteritis [70] and atherosclerosis, which is now emerging as an inflammatory syndrome [71]. Weyand et al [69,72] have intensely investigated the mechanisms involved in the persistence and expansion of DCs in the vessel wall of medium-sized arteries from patients affected by GCA, the most common form of systemic vasculities in human. They found a number increased of mature (activated) DCs positioned in the adventitia-media border of these vessels (adventitial DCs), which were equipped molecularly to contribute to vascular lesion. Moreover, these DCs might be influenced by antigen-specific signaling from T cells, which may extend and amplify DC antigen capabilities, especially for the stimulation of cytotoxic responses.
The involvement of DCs in the immunopathogenesis of Kawasaki disease, a multisystem vasculities associated with cardiac complications in children, has been suggested by Yilmaz and Colleagues [73]. They studied the participation of DCs in the immunological abnormalities seen in the coronary lesions of Kawasaki's patients. They found an increased number of mature myeloid DCs (S100+, Fascin+, HLA-DR+, CD83+) in the adventitia of coronary arteries. Interesting, they observed mature DCs with high HLA-DR expression in close proximity to T cells evoking DC-T cell immunological synapse formation, which suggested that mature arterial myeloid DCs might be activating T cells in situ and may be a significant factor in the pathogenesis of coronary arteritis in KD.
Aberrant DC function has also been implicated in other, less prevalent autoimmune diseases in childhood such as cutaneous scleroderma [74]. In addition, the pathogenic role of DCs in the pathogenesis of Type I Diabetes has been recently suggested in several studies [75,76]; how-ever the analysis of impact of DC malfunction in this disease has not been considered in this review.

Conclusion
Based on the evidence obtained from various autoimmune diseases described here, it is highly suggestive that local or recruited DCs play a fundamental role in both induction and maintenance of these disorders. Moreover, direct analysis of DC phenotypes and DC-T cell interactions is several autoimmune diseases bring light on the pathogenesis of these autoimmune disorders. We must take into account the delicate balance between immunity and autoimmunity and the pivotal role DCs play in this equilibrium. Future therapeutic regimes used to fight autoimmune disease need to consider therapeutic options based on specific modulation of pathogenic DCs that induce and sustain autoimmune inflammation, which could be curative or be able to induce long term remissions.


extfieldsofstudy: Biology Medicine

text:
Dynamic resolution of functionally related gene sets in response to acute heat stress

Background Using a gene clustering strategy we determined intracellular pathway relationships within skeletal myotubes in response to an acute heat stress stimuli. Following heat shock, the transcriptome was analyzed by microarray in a temporal fashion to characterize the dynamic relationship of signaling pathways. Results Bioinformatics analyses exposed coordination of functionally-related gene sets, depicting mechanism-based responses to heat shock. Protein turnover-related pathways were significantly affected including protein folding, pre-mRNA processing, mRNA splicing, proteolysis and proteasome-related pathways. Many responses were transient, tending to normalize within 24 hours. Conclusion In summary, we show that the transcriptional response to acute cell stress is largely transient and proteosome-centric.

Background
Damaged skeletal muscle tissue retains the capacity to self-repair through activation, expansion and fusion of resident satellite, progenitor cells [1][2][3]. However, the signaling mechanisms required to trigger satellite cell activation remain unclear in this context. Emerging pathways involved in the injury-response profile of skeletal muscle include Notch [4], Akt/Foxo [5] and NFκB [6,7], which appear to play distinct roles in regeneration, hypertrophy and atrophy. Although these signaling pathways are well established, there remains a dearth of molecular detail, including the transcriptional consequence of atrophic stimuli, and this aspect forms the focus of the current study.
We hypothesized that subtle variance in gene expression may underlie significant functional events within the cell. Consistently, previous studies have addressed the transcriptional profile of recovering muscle tissue following acute injury [8]. However, such studies rely on the analysis of individual genes, which is limiting from both statistical and biological perspectives. Here, we performed a study with the tenet that mechanistic data may be more readily revealed in the context of pathway-related gene clustering [9,10]. We employed Gene Set Enrichment Analysis (GSEA), a bioinformatics approach conceived to exploit functional regulation at the pathway level. The study focused on the dynamic expression profile of acutely stressed skeletal muscle cells, and the resultant data revealed major transcriptional adjustments in a wide range of functional categories. These findings may underscore a coordinated pathway-centric response, and reveal rational strategies for target discovery in atrophic muscle diseases.

Results
In the present study, we exposed C2C12 skeletal myotubes to heat shock-induced damage in order to identify coordinate patterns of transcriptional regulation. To initially authenticate this cell-based injury model, we identified several stress-related biomarkers and regulatory patterns to confirm bona fide damage response in the cells. Following heat shock treatment, cells recovered in growth medium at 37°C, and gene expression profiles were generated at 0, 1, 2, 4, 8 and 24 hours post-treatment. ATF3 and c-jun are critically regulated in the neuronal response to damage and during degeneration. Furthermore, these genes may play an anti-apoptotic role in the survival response of neuronal cells [11][12][13]. Here, both ATF3 and c-jun transcript levels were upregulated in response to heat-shock, consistent with their reported coordinate role in cell damage response ( Figure 1A). A transient peak in expression of both genes occurred at 8 hours and attenuated at 24 h post-damage induction, indicating a regulated damage-induced response.
Vimentin, an intermediate filament protein that plays a role in wound healing [14] and response to thermal stress [15,16], was augmented immediately following heat shock, and peaked at 2 hours. This rapid response to cell stress was consistent with the role of vimentin in protection against cytotoxic effects ( Figure 1B). Also, the membrane type 1matrix metalloproteases MMP14 and MMP2, which are functional partners during skeletal development [17] and stress response in the context of vascular injury [18], were robustly co-regulated at the transcriptional level in response to heat shock of C2C12 skeletal myotubes. Their expression level rose within 2-4 hours of insult, followed by a repression of expression levels at 8 and 24 hours (Figure 1C).
Atrogin-1 is expressed specifically in skeletal and cardiac muscle, and has been shown to regulate muscle atrophy [19,20]. In response to heat shock, Atrogin-1 (Fbxo32) was upregulated after 8 hours, and this level of expression was maintained for at least 15 hours ( Figure 1D). This dynamic profile is consistent with previous reports of C2C12 cells recover from heat shock with a characteristic profile of injury response Figure 1 C2C12 cells recover from heat shock with a characteristic profile of injury response. Temporal gene expression profiles of heat shocked C2C12 myotubes (47°C for 30 minutes). Heat shock treatment was abated at 0 hours and cells were restored to growth conditions. mRNA was isolated at 1, 2, 4, 8 and 24 hours post-heat shock. (A-D) Transcriptional activity of the indicated genes was measured using Affymetrix GeneChips and data was analyzed using GeneSpring bioinformatics software. Data points represent the mean of three independent studies (± S.D). (E-G) C2C12 cells stably expressing Foxo3a-GFP were differentiated into myotubes (E), heat shocked and recovered for 3 hours (F) or treated with 20 μM LY294002 for 3 hours (G). Cells were then viewed under fluorescent light to observe localization of the protein.
muscle injury response, whereby the expression of atrogin-1 was concomitant with atrophy and recovery [21]. Atrogin-1 is regulated by Foxo transcription factors, via nuclear localization of Foxo in response to various stimuli that inhibit PI3K/Akt signaling and subsequently drive atrophy [5,22].

Transient profiles of gene expression
Of the approximately 46,000 probes arrayed on the gene chips, the most variable and dynamically regulated were characterized by basic clustering methodology ( Figure 2). The most actively regulated group of genes immediately following treatment (ie. 1 hour post heat shock) unsurprisingly comprised a number of heat-shock proteins. hsp1a, hsp1b and hsp8 were among the most significantly upregulated transcripts at this time point (Figure 2A). Gene sets that clustered at 2, 4, 8 and 24 hours following heat shock are displayed in Figure 2 and are partially represented in Table 1. The 8 hour gene set was the largest group that displayed a significant upregulation, and is likely comprised of genes that were regulated downstream of immediate early genes. Therefore, this cluster may represent an important set of genes that functionally dictate the coordinated response of myogenic cells to stress or injury.

Gene set enrichment analysis
We employed a the gene set enrichment analysis strategy [10] to cluster functionally related genes in order to consider shifts in pathway activity. Individual gene sets were mined from various publicly and privately available data sources, and methodologies for the curation of functional pathways varied between sources. In all, a total of 789 gene sets made up the collection that was employed in this study, and the approach was employed to facilitate potential mechanistic insight to the myogenic cell response to injury [10]. As a control, we looked at the gene set for stress response at the 8 hour time point ( Figure 3A). This probe set was significantly upregulated (p < 1.0e -36 ), relative to the basal expression distribution (Figure 3-3A). Furthermore, a subsidence in the stress response could be observed between 8 and 24 hours post-heat shock treatment as the gene set underwent a significant downregulation (p = 1.4e -8 ) that may reflect a normalization of the cell's condition ( Figure 3B). These data clearly demonstrate the statistical strength of pathway analysis in the context of the heat shock response.
To gain better insight into the dynamic nature of regulated functional pathways, we traced the expression pattern of specific gene sets within the time course, such as the extracellular matrix protein-mediated signaling (EMP-M) (Figure 4, see Additional file 1). The analysis revealed a pattern of regulation that reflected an initial increase in pathway activity at 1, 2, and 4 hours, followed by a timedependent decrease in expression through 8 and 24 hours post treatment. Therefore, the overall response in the EMP-M pathway to heat shock reflected an augmentation immediately following treatment, followed by a subsidence and eventual decrease in functional pathway expression after 24 hours. The transient nature of the pathway response was clearly defined with this bioinformatics approach, and is presented in Figure 4F.
A similar analysis was carried out on the BMP signaling pathway (see Additional file 1). When traced as a function of time over the 24 hour period, the BMP signaling pathway was initially decreased at 1, 2 and 4 hours at the transcriptional level, and recovered through 8 and 24 hours post treatment ( Figure 5). This result was consistent with the established role of BMP signaling in antagonizing myogenic specification during development, and in regenerating adult muscle tissue [23]. Furthermore, along with the stress response pathway and the EMP-M pathway expression traces, it appears that much of the initial response to heat shock was reversed within 24 hours of recovery.
Temporal gene clusters during response to heat shock of C2C12 myotubes Figure 2 Temporal gene clusters during response to heat shock of C2C12 myotubes. Temporally upregulated genes were clustered by selection of probes that coregulated with a specific peak time between 1 and 24 hours post-heat shock, as determined from the normalized expression profile data. Expression profiles of each gene within clusters are represented for the entire 24 hour timecourse to reflect the transient nature of expression.
Analysis of the most active gene sets through the entirety of the time-course revealed a notable phenomenon, typified by the dynamic profile of the protein biosynthesis pathway gene set. In response to heat shock treatment, the genes in this pathway underwent a significant and immediate upregulation, which gradually declined over the next 24 hours (Figure 6). The trend for this particular functional pathway suggested that protein turnover was highly regulated in the response to heat shock-induced stress, and this hypothesis was further supported by the apparent upregulation of several related pathways involved in the expression and degradation of proteins.
After 8 hours recovery from heat shock, a selection of gene sets related to core gene expression machinery and protein turnover, were significantly upregulated ( Table 2). This general increase in protein metabolism pathways as an immediate response to injury may reflect the clearance and replacement (turnover) of the protein complement of the cell.

Discussion and Conclusion
This study was conducted to explore changes in gene expression following acute injury of C2C12 myotubes, and to reveal regulation of pathways during initial recovery. 866 individual transcripts represented on the microarray varied more than 2 fold over the course of the study, and the data revealed significant transcriptional changes in a wide variety of functional classes following heat shock damage to the cells. We devised the current study with two distinct dimensions. Firstly, to trace the timecourse of recovery over a 24 hour period, and secondly, to analyze in a pathway-centric manner in order to extract hypotheses of coordinated molecular mechanisms that Stress response gene set is bi-directional during response to heat shock in C2C12 cell Figure 3 Stress response gene set is bi-directional during response to heat shock in C2C12 cell. Distribution in stress response-related gene sets during response to heat shock of C2C12 myotubes. All probes representing the stress response gene set are presented as an expression ratio of time a against time b. Frequency (y-axis) represents the number of probes in each gene set with the corresponding expression ratio (x-axis). The statistical significance of the mean expression variance ratio for the gene set relative to all other probesets is indicated. Variance between 0 -8 hours (A) and 8 -24 hours (B) post-heat shock are depicted in the figure. Dotplot representations of GSEA as a function of C2C12 response to heat shock is also presented. The x-axis of each plot represents expression levels at time a, and the y-axis represents expression at time b. Each dot represents a single probe on the GeneChip. The total probe set (grey dots) and the specific gene set (blue dots) are presented on the same plot to give direct perspective of gene set regulation. The stress response probe set is represented by 122 gene probes, previously annotated as related to the stress response. The list is attached in Additional file 1.
occur during cellular stress and recovery. Two notable pathways significantly modulated during recovery were the BMP signaling pathway, and the extracellular matrixprotein mediated signaling pathway, both of which are known to function in myogenesis, either by directing lineage specification (BMP) or structural/regenerative signaling (ECM-M). Additionally, the muscle-specific E3 ligase gene, Atrogin-1 was upregulated significantly, consistent with its reported role in mediating muscle atrophy in response to catabolic signals [19], and this in turn was coincident with our observation of nuclear translocation of Foxo3a following heat shock [5,22]. This reconstruction of a well documented atrophic pathway served to validate the heat shock treatment paradigm as a useful model of acute muscle stress.
The experimental approach carried out in this study demonstrated the value of characterizing cellular responses in a temporal fashion, as transcriptional regulation was commonly found to be non-static between contiguous time points within the first 24 hours of treatment, and often presented transient regulation that required a time-course dimension to clarify.
A notable trend that emerged from the data was an apparent increase in protein turnover apparatus-related gene sets. The most significantly upregulated gene sets included those for both transcriptional activity, translational activity and protein modification, as well as the proteolysis and proteosome pathways. This suggests that a primary response of skeletal myotubes to heat shock treatment is to renew the protein complement of the cell, presumably as a defense mechanism against proteomic damage, and potential aberrant consequences in the function or integrity of the cell. The data also show that much of this response is transient, and appears to normalize within 24 hours of the acute insult at the transcriptional level.
In summary, the data presented in this report demonstrate a dynamic resolution of gene expression in response to Dynamic regulation of the EMP-M gene set following heat shock acute stress that implicates waves of pathway activity in the cell's metabolic recovery. Further validation of these data are required, however, in order to demonstrate clearly the practical nature of these pathways as part of the functional stress response profile.

Methods
Cell culture and treatment C2C12 mouse skeletal myoblasts were cultured in DMEM high glucose with 10% FBS and 1% penicillin/streptomycin (Gibco), and maintained at 37°C and 5% CO 2 . Cells were grown to confluence and then differentiated for seven days in media containing 3% fetal bovine serum.  determined not to be cytotoxic, as continued culture in normal growth conditions was sufficient for full recovery of the cells (data not shown).

Bioinformatics
Raw intensity files were imported into GeneSpring ® v.6.2 (Silicon Genetics, US) and filtered such that genes with a raw expression level of less than 100 were excluded from any future analyses. The resulting gene list was filtered to identify genes with a fold change increase or decrease of 2 or greater. Statistically significant genes were found using one-way ANOVA with time as variable and no multiple testing correction.
An in-house implementation of the Gene Set Enrichment Analysis method [10] was used to analyze microarray data. As input, GSEA requires microarray data from two conditions to be compared (e.g. myoblasts vs myotubes). Genes with expression levels below 100 on more than 75% of the Genechips were discarded. Then, the relative expression level under condition 1 and condition 2 was computed as an expression ratio r i where μ i,j is the average expression value for gene i under condition j . Genes were then sorted according to their expression ratios. Next, the collection of available gene sets were projected onto the sorted gene list. In essence, this step applies a priori biological knowledge to the experimental data to identify functionally related genes that are expressed in a coordinated fashion. Gene sets were processed individually and used to partition the genes into two groups: those gene in a pathway, and all other genes measured on the Genechip. A two-tailed Wilcoxon ranksum test was then calculated to determine if the genes in each gene set were enriched at either the top or bottom of the sorted list. The Wilcoxon p-values were then transformed into false discovery rate q-values [24,25] as a means of multiple hypothesis testing correction.  Dynamic response of the protein biosynthesis pathway following heat shock Figure 6 Dynamic response of the protein biosynthesis pathway following heat shock. (A) Overview depiction of the dynamic response of the protein biosynthesis pathway gene set following heat shock over 24 hours. Data is represented as for Figure 5. (B) Dotplot diagram showing the upregulation in expression of the same gene set after 1 hour post-heat shock.


extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy: Biology Chemistry

text:
Bacterial Expression, NMR, and Electrophysiology Analysis of Chimeric Short/Long-chain α-Neurotoxins Acting on Neuronal Nicotinic Receptors*

Different snake venom neurotoxins block distinct subtypes of nicotinic acetylcholine receptors (nAChR). Short-chain α-neurotoxins preferentially inhibit muscle-type nAChRs, whereas long-chain α-neurotoxins block both muscle-type and α7 homooligomeric neuronal nAChRs. An additional disulfide in the central loop of α- and κ-neurotoxins is essential for their action on the α7 and α3β2 nAChRs, respectively. Design of novel toxins may help to better understand their subtype specificity. To address this problem, two chimeric toxins were produced by bacterial expression, a short-chain neurotoxin II Naja oxiana with the grafted disulfide-containing loop from long-chain neurotoxin I from N. oxiana, while a second chimera contained an additional A29K mutation, the most pronounced difference in the central loop tip between long-chain α-neurotoxins and κ-neurotoxins. The correct folding and structural stability for both chimeras were shown by 1H and 1H-15N NMR spectroscopy. Electrophysiology experiments on the nAChRs expressed in Xenopus oocytes revealed that the first chimera and neurotoxin I blockα7 nAChRs with similar potency (IC50 6.1 and 34 nm, respectively). Therefore, the disulfide-confined loop endows neurotoxin II with full activity of long-chain α-neurotoxin and the C-terminal tail in neurotoxin I is not essential for binding. The A29K mutation of the chimera considerably diminished the affinity for α7 nAChR (IC50 126 nm) but did not convey activity at α3β2 nAChRs. Docking of both chimeras toα7 andα3β2 nAChRs was possible, but complexes with the latter were not stable at molecular dynamics simulations. Apparently, some other residues and dimeric organization of κ-neurotoxins underlie their selectivity for α3β2 nAChRs.

1
H-15 N NMR spectroscopy. Electrophysiology experiments on the nAChRs expressed in Xenopus oocytes revealed that the first chimera and neurotoxin I block ␣7 nAChRs with similar potency (IC 50 6.1 and 34 nM, respectively). Therefore, the disulfide-confined loop endows neurotoxin II with full activity of long-chain ␣-neurotoxin and the C-terminal tail in neurotoxin I is not essential for binding. The A29K mutation of the chimera considerably diminished the affinity for ␣7 nAChR (IC 50 126 nM) but did not convey activity at ␣3␤2 nAChRs. Docking of both chimeras to ␣7 and ␣3␤2 nAChRs was possible, but complexes with the latter were not stable at molecular dynamics simulations. Apparently, some other residues and dimeric organization of -neurotoxins underlie their selectivity for ␣3␤2 nAChRs.
Nicotinic acetylcholine receptors (nAChRs) 2 belong to the class of ligand-gated ion channels (1)(2)(3). All nAChRs are com-posed of five homologous subunits, which span the plasma membrane to form a transmembrane ion-conducting pore. The muscle-type receptors are composed of four types of subunits, ␣2␤␥␦ in the fetal and ␣2␤⑀␦ in the mature receptor. The best studied nAChR of this type is the receptor from electric organ of ray Torpedo marmorata (4). Neuronal receptors consist of two types of subunits, ␣ (␣2-␣10) and ␤ (␤2-␤4), and can have homooligomeric (for example, ␣7-type nAChR) or heterooligomeric (for example, ␣3␤2-type receptor) composition. Neuronal nAChRs are widely expressed both pre-and postsynaptically, and presynaptic receptors modulate synaptic activity and the release of different neurotransmitters. Neuronal nAChRs are found also in non-neuronal tissues, such as keratinocytes and pulmonary and other tissues (5)(6)(7)(8).
Because of their role in cellular communication, nAChRs play important roles in the normal functioning of the organism. Dysfunctions of these receptors have been proposed to contribute to a number of disorders of the central and peripheral nervous systems such as schizophrenia, epilepsy, depression, nicotine and alcohol dependence, Alzheimer disease, Parkinson disease, and autism (9 -17). Distinct nAChR subtypes are involved in different disorders, and proper treatment of such diseases requires new therapeutic agents that are specific for a defined receptor subtype.
␣-Neurotoxins from snake venoms are natural potent inhibitors of nAChRs. These toxins are small proteins with a "threefingered" structure formed by three ␤-structural loops stabilized by disulfide bonds (18 -20). ␣-Neurotoxins can be subdivided into several classes according to their biological and structural properties. Short-chain ␣-neurotoxins (4 disulfide bonds, 60 -62 amino acid residues) selectively inhibit only muscle-type nAChRs, whereas long-chain ␣-neurotoxins (5 disulfide bonds, 66 -75 amino acid residues) with an additional disulfide bond in the tip of the central loop can inhibit both muscle and neuronal ␣7 nAChRs (19,20). There are -neurotoxins (5 disulfide bonds, 66 amino acid residues) that also contain an additional disulfide bond in the central loop and block neuronal ␣3␤2 nAChR (21).
Site-directed mutagenesis (22,23), chemical modification studies (24 -26), and investigation of synthetic chimeric short/ long-chain ␣-neurotoxins (27) indicate that the central loop fragment with fifth disulfide bond is essential for interaction of *This work was supported by the Russian Academy of Sciences (program on molecular and cellular biology) and the Russian Foundation for Basic Research (Projects 05-04-48918, 05-04-48932). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. 1 To whom correspondence should be addressed. ␣and -neurotoxins with neuronal ␣7 and ␣3␤2 receptors, respectively. Recently the structural basis of interaction between the central loop of a toxin and nAChR was revealed by x-ray investigation of a crystallized complex of long-chain ␣-cobratoxin from Naja kaouthia with the acetylcholine-binding protein from Lymnaea stagnalis (AChBP) (28). (AChBP is a natural water-soluble homopentameric protein that is an excellent model of the ligand-binding domain of the nAChR) (29,30). Direct intermolecular contacts between the fifth disulfide of the neurotoxin, Cys-27-Cys-31 (numbers are given for neurotoxin I), and the residues on the surface of the adjacent subunit of the AChBP were observed in this complex. The structure of ␣-cobratoxin-AChBP complex explains common principles of interaction between ␣-neurotoxins and nAChRs. However, the exact structural features that determine the selectivity between different nAChR subtypes remain unclear. Design of chimeric molecules bearing features of toxins from different groups can shed light on this problem.
In the present communication we describe heterologous expression in Escherichia coli of chimeric short/long-chain ␣-neurotoxins. We demonstrate using electrophysiology on human ␣7 nAChR expressed in Xenopus oocytes that grafting the disulfide-confined tip of the neurotoxin I N. oxiana on a short-chain neurotoxin II from the same venom makes the latter as active as neurotoxin I itself. An additional mutation, A29K, has been done in this chimera to test the hypothesis of Bourne et al. (28) that the Lys-29 is the major factor underlying the difference in specificity between the long-chain ␣-neurotoxins and -neurotoxins toward ␣7 and ␣3␤2 nAChRs, respectively. This mutation considerably decreased the activity against ␣7 nAChRs but showed no inhibition of human ␣3␤2 nAChRs.
Expression of NTII Gene in E. coli-A synthetic NTII gene (32) was joined to a sequence encoding the signal peptide of E. coli heat-stable enterotoxin II (STII) (NCBI accession number M35729). This fusion gene was placed under the control of the T7 promoter in an expression vector pET-22b (Novagen) between the NdeI and HindIII sites. The resultant plasmid was named pET22b/STII/NTII.
Engineering of the Mutant Neurotoxins-The fragment of the NTI central loop was introduced into the NTII molecule using the QuikChange TM site-directed mutagenesis kit (Stratagene) on the basis of pET22b/STII/NTII. Primer 5Ј-CTACAAAAAG-TGGTGGTGCGACGCGTGGTGCGGTTCCCGTGGTACC-ATCATC-3Ј, coding the disulfide-containing fragment of central loop of NTI, was used as direct primer. Primer 5Ј-GATGATG-GTACCACGGGAACCGCACCACTTGTCGCACCACCAC-TTTTTGTAG-3, partly complementary to the direct primer sequence, coding the disulfide-containing fragment of the central loop of NTI with substitution Ala/Lys, was used as reverse primer. Amplification was performed on the Mastercycler Personal PCR amplifier (Eppendorf, Germany).

Bacterial Expression, Isolation, and Purification of Recombinant Neurotoxins-BL21(DE3) E. coli cells were transformed with the recombinant vectors and plated onto Petri dishes with
Luria Bertani agar containing ampicillin (100 g/ml). Several colonies were then inoculated with minimal mineral M9 medium (0.4% glycerol, 3 g/liter KH 2 PO 4 , 6 g/liter Na 2 HPO 4 , 0.5 g/liter NaCl, 0.24 g/liter MgSO 4 , 0.01 g/liter CaCl 2 , 2 g/liter NH 4 Cl, 1% thiamine chloride, 0.2% yeast extract) containing ampicillin (100 g/ml). The cells were cultivated at 37°C and moderate mixing (250 rpm) until optical density of the bacterial culture had reached 0.6 optical units at 600 nm wavelength. After that, gene expression was induced by adding isopropyl-1-thio-␤-D-galactopyranoside to a final concentration of 0.05 mM. After 15 h of cultivation the cell culture was centrifuged (14,000 ϫ g, 30 min, 4°C). Growth medium was acidified to pH 4.5, heated at 70°C during 30 min, and centrifuged once more (14000 ϫ g, 30 min, 4°C). The supernatant was diluted 2-fold with Milli-Q deionized water (Millipore). The first step of purification was made using cation exchange SP-Sepharose Fast Flow resin (GE Healthcare), equilibrated in 10 mM CH 3 COONa, pH 5.0. Protein fractions were eluted in the linear gradient of NaCl (from 0 mM to 1 M), and fractions containing modified neurotoxins were collected at 0.25 mM NaCl. The mutant toxins were additionally purified on a MonoS HR5/5 column (GE Healthcare), equilibrated with 10 mM CH 3 COONa, pH 5.0, and eluted from the column with 0.4 M NaCl. The buffer of protein samples was changed to 0.2 M CH 3 COOH using Sephadex TM G-25 NAP TM -5 and NAP TM -10 columns (GE Healthcare). Finally, protein solutions were lyophilized overnight on an Alpha I-5 freeze dryer (Martin Christ Gefriertrocknungsanlagen GmbH). Protocol for production and purification of 15 N-labeled NTII and NTII/I chimera was the same as in the case of non-labeled toxins, with the exception of using 15 NHCl as a sole source of nitrogen ( 15 N Ͼ 99%; Martek Biosciences).
Analysis of Recombinant Toxins-All the steps of protein production, isolation, and purification were controlled by 12% Tris/Tricine-SDS-PAGE (33). The N-terminal amino acid sequence of the obtained proteins was determined on the Applied Biosystems 470A gas-phase sequenator. Recombinant neurotoxins were analyzed by mass spectrometry using a matrix-assisted laser desorption ionization Daltonics Ultraflex II TOF/TOF (time-of-flight) instrument (Bruker) equipped with nitrogen laser and time-of-flight mass analyzer. All NMR experiments were performed on a 500-MHz DRX-500 spectrometer (Bruker). One-dimensional 1 H and two-dimensional 1 H-15 N HSQC spectra were measured for 1 mM protein solu- Electrophysiology-Expression and electrophysiological recording from nAChRs was carried out as described previously (34). Briefly, oocytes were injected intranuclearly with 2 ng of cDNA that coded for either the human ␣7 or ␣3␤2 receptors (cDNAs were a gift from J. P. Changeux). All recordings were performed in OR2 medium that contained 82.5 mM NaCl, 2.5 mM KCl, 5 mM HEPES, 2.5 mM CaCl 2 , 1 mM MgCl adjusted to pH 7.4 with NaOH. Acetylcholine and toxins were dissolved in the OR2 medium just prior to use. Recordings were carried out at Ϫ100 mV. Oocyte loading, penetration, and voltage clamping were carried out by an automated system based around a liquidhandling robot controlled by in-house software. Solution exchanges were automated and carried out by the same liquid handler. Control responses were recorded before toxin exposure and toxin incubation was carried out in the recording chamber during 3 min using a static bath technique. Peak current amplitude was plotted as a function of the toxin concentration on a semilog scale. Dose-response curves for toxin inhibition were fit with the equation y ϭ 1/1 ([toxin]/(IC 50 ) n ), where y is the normalized response, [toxin] is the toxin concentration, and n is the Hill coefficient. ACh concentration was close to the EC 50 for receptor activation, and toxin incubation time was determined by testing receptor responses after increasing toxin incubation times. Equilibrium was assumed to be reached when no further inhibition of the response was seen.
Modeling of Chimeras and Their nAChR Complexes-The models of the chimeric toxins were built using homology modeling technique under MODELLER with further molecular dynamics refinement in CHARMM'27 and stochastic dynamics under GROMACS. Further relaxation was done with Minimization routine in CHARMM'27 force field under TINKER program. 3-ns trajectories were calculated at the temperature 300 K and dielectric permittivity e ϭ 1.
The models of the nAChR subunits and their assemblies were built similarly as described in Ref. 35 for Torpedo californica nAChR subunits; the structure of the ␣-cobratoxin complex with AChBP (PDB code 1YI5) was additionally used as a template. Visual analysis was carried out with SPDBViewer version 3.7 sp5 program.
Docking simulations were performed with both AutoDock 3.05 and HEX 4.5 programs. The solutions of the complexes were relaxed and underwent molecular dynamics simulation with GROMACS for 100 -200-ps trajectories.

Construction of Short/Long-chain ␣-Neurotoxin Chimeras-
The chimeric toxins were built on the scaffold of the shortchain NTII chosen for several reasons. First, NTII has low activity against neuronal nAChRs (IC 50 Ͼ 1 M), thus providing reliable reference for detection of even subtle changes in affinity. Second, high level bacterial expression systems for this toxin had previously been developed (32,36) and could be adapted for production of chimeras.
To find the most appropriate donor for the disulfide-confined fragment of the central loop, we compared, in terms of atomic pair-wise root mean square deviation, the spatial structures of several long-chain neurotoxins (neurotoxin I, ␣-bungarotoxin, ␣-cobratoxin, toxin B, -bungarotoxin) with the three-dimensional structure of NTII. The molecules were superimposed by fitting atomic coordinates for C␣ atoms from four conserved disulfides and from two ␤-strands that form the central loop (residues 3, 14, 21-26, 37-42, 46, 57, 58, 63, numbers are given for NTI). The minimal value of pair-wise root mean square deviation with NTII for this group of atoms (0.89 Å) was found for NTI from N. oxiana (NTI), and this long-chain ␣-neurotoxin was chosen as donor, ensuring less structural perturbation during "transplantation." To this end, Ser-29, Asp-30, and His-31 of NTII were replaced by Cys-27, Asp-28, Ala-29, Trp-30, Cys-31, Gly-32, and Ser-33 of NTI (Fig. 1).
Bacterial Expression, Isolation, and Purification of Recombinant Toxins-Recombinant neurotoxins were produced in E. coli BL21(DE3) strain under the transcriptional control of a T7 promoter. After induction with isopropyl-1-thio-␤-D-galactopyranoside, toxins began to accumulate in periplasm and growth medium and were processed accurately during the secretion process. Chimeras were isolated from growth medium in two steps by separation on cation exchange SP-Sepharose Fast Flow resin and MonoS HR5/5 column (GE Healthcare). The toxin purity was checked by reversed phase HPLC (Fig. 2). It is seen that the elution times for chimeric toxins are between those for NTII and NTI. The substitution of alanine residue by lysine in NTII/I[A29K] resulted in decreased hydrophobicity manifested in shorter retention time on reversed phase HPLC.
The final yield of the mutant toxins containing five disulfide bonds was ϳ1 mg/liter of bacterial culture in the case of NTII/I chimera and 5 mg for NTII/I[A29K], which is several times lower than yield of NTII (ϳ20 mg/l) in this system. The yields of 15 N-labeled NTII and NTII/I chimera were similar to the yields of non-labeled proteins. The lower yields of chimeric toxins can be explained by the presence of an additional disulfide bond. Nevertheless, the obtained quantities of chimeras were sufficient for structural and electrophysiological investigations.
The N-terminal analysis using Edman's degradation showed that the obtained recombinant toxins had N-terminal sequences identical to that of the wild-type NTII. Thus, mutant neurotoxins were secreted into periplasm and the signal peptide STII was properly cleaved. Mass spectral analysis of natural NTII and mutant neurotoxins revealed very good correlation between the determined masses and expected calculated values (8020 Da versus 8021, 6878 versus 6877, 7257 versus 7258, and 7314 versus 7315 for NTI, NTII, NTII/I and NTII/I[A29K], respectively).
Structural Analysis of Recombinant Chimeras-The fragments grafted to NTII consist of 7 residues and include additional disulfide bond. Introduction of these fragments might affect the stability and spatial structure of chimeric toxins. We used NMR spectroscopy to estimate possible changes in spatial structure of chimeras.
The one-dimensional 1 H NMR spectra for recombinant NTII/I and NTII/I[A29K] displayed narrow NMR lines and a large dispersion of signals in amide and aliphatic regions. Comparison with the one-dimensional 1 H spectrum of NTII revealed almost coinciding envelope for all three one-dimensional spectra, with intact position of several characteristic non-overlapping resonances and with additional signals in the case of chimeras (data not shown). The 1 H-15 N HSQC spectra for recombinant 15 N-labeled NTII and NTII/I (Fig. 3, A and B) revealed almost complete correspondence of 1 H and 15 N resonance frequencies for common residues in both toxins. The detailed analysis of these spectra allowed us to make resonance assignment for the NTII/I chimera. Comparison of the onedimensional 1 H spectrum of NTII/I[A29K] with the HSQC spectrum of NTII/I (Fig. 3C) indicated that point mutation A29K does not change the spatial structure of chimeric toxin. Thus, recombinant chimeras share a common, relatively rigid spatial structure with neurotoxin II. This conclusion was also supported by CD spectroscopy data (not shown).
Electrophysiological Analysis of Chimeras-The biological activity of modified neurotoxins was tested in vitro by measuring the ability to inhibit acetylcholine-induced currents at neuronal ␣7 and ␣3␤2 nAChRs expressed in Xenopus laevis oocytes. The capacity of neurotoxins NTI and NTII to inhibit ACh-evoked currents at the human ␣7 nAChR was first examined. Fig. 4A shows that NTI blocked the human ␣7 nAChR with an IC 50 of 34 nM, whereas the short-chain NTII had no effect. Then the effects of the NTII/I and NTII/I[A29K] chimeras at the human ␣7 nAChR were assessed. The inclusion of the central loop tip containing the additional disulfide in NTII conveyed activity at ␣7 nAChRs to NTII/I chimera (IC 50 of 6.1 nM) (Fig. 4B). The second chimera, NTII/I[A29K], also inhibited ACh-evoked currents; however, the A29K substitution in the tip considerably decreased the activity at the ␣7 nAChR (IC 50 126 nM, Fig. 4C). Neither the native toxins NTI and NTII nor the chimeras NTII/I and NTII/I[A29K] inhibited currents at human ␣3␤2 nAChRs at concentrations up to 1 M (data not shown).

Modeling of Spatial Structures for Chimeric Toxins and Their
Complexes with nAChRs-The spatial structures of the chimeric toxins were constructed using homology modeling on the basis of three-dimensional structures of NTI, NTII, and ␣-cobratoxin. The introduction of the insert from the longchain neurotoxin and subsequent A29K replacement did not affect the stability of the general fold of the molecule and did not influence the flexibility of the disulfide-fixed core taken from NTII.
Constructed models of the nAChR subunits and their assemblies (␣7 and ␣3␤2) were similar to those built previously (35,37). The control docking of NTII and NTI to ␣7 and ␣3␤2 nAChRs gave stable complex only in the case of NTI/-␣7 (similar to 1YI5) (28). Docking of NTII/I chimera was possible both  to ␣7 and ␣3␤2, but only NTII/I-␣7 complex was stable during subsequent molecular dynamics simulation. The main interactions were with the C-loop of the nAChR principal site, similar to ␣-cobratoxin complex (28). However, the position of the whole chimera molecule resembled NTII bound to the ␣/␥ interface of Torpedo nAChR (35).
Docking studies suggest that the A29K substitution in the NTII/I[A29K] chimera should not influence the position of the chimeric toxin on the receptor interface. However, the affinity of NTII/I[A29K] chimera to the ␣7 nAChR subtype was higher than to ␣3␤2 nAChR (estimated energies of interaction are 1400 KJ/mol/binding site and 340 KJ/mol/binding site, respectively). Moreover, the chimera complex with ␣3␤2 nAChR was unstable under MD simulation.

DISCUSSION
Until recently, information on the mode of interaction of diverse snake toxins with various nAChRs was based mainly on mutations of toxins and/or receptors, pair-wise mutagenesis, and cross-linking (20). Such approaches revealed, for example, some differences between short-chain and long-chain ␣-neurotoxins in the involvement of their three loops in the interaction with muscle-type nAChRs (38 -41). It was also shown that a number of residues of the muscle-type receptors participate in the interaction with the toxins of both groups, whereas some residues are important for binding with only short-chain neurotoxins and others with long-chain neurotoxins (42).
Determination of the crystal structure for the acetylcholinebinding proteins (AChBPs) (29,43), their complexes with different agonists (44), and antagonists such as ␣-cobratoxin and ␣-conotoxins (28,37,45,46) has provided a basis for detailed analysis of the nAChR interaction with snake neurotoxins. This model can help to better understand the topography of their binding surfaces and choose new mutations that in principle can give novel toxins of higher affinity and better selectivity for a particular nAChR subtype.
As mentioned in the Introduction, the action of snake toxins on neuronal ␣7 or ␣3␤2 nAChRs requires the presence of an intact disulfide bond in the central loop of the toxin molecule (22)(23)(24)(25)(26). The x-ray analysis of the ␣-cobratoxin complex with L. stagnalis AChBP revealed direct contacts between this disulfide bond and residues in the binding site (28). This analysis also detected contacts of 10 ␣-cobratoxin residues whose involvement in binding to ␣7 nAChRs has been previously suggested from mutagenesis studies (22,23,25). Although the AChBP is considered a model for all types of nAChRs, the available data do not answer the question why, for example, long-chain ␣-neurotoxins have a high affinity for ␣7 nAChRs whereas -neurotoxins target ␣3␤2 nAChRs. Because the disulfide-confined tip of the central loop is a prerequisite for binding to both these nAChRs, one could assume that the differences in specificity might stem from the amino acid differences in this fragment. (It should be kept in mind that -neurotoxins exist as dimers, which could also affect their nAChR selectivity (47,48). The most obvious difference is the presence of Lys-29 in -neurotoxins whereas the homologous position in ␣-neurotoxins is occupied by Ala-29 (Fig. 1). Bourne et al. (28) suggested that this substitution may be one of the major factors determining specificity to a particular nAChR subtype. To test this hypothesis, we designed the chimera with A29K substitution.
Mutagenesis (22,23), NMR, and x-ray structures of longchain ␣-neurotoxin complexes with nAChR fragments or combinatorial peptides (49 -52), as well as the crystal structure for the AChBP complex with ␣-cobratoxin (28), showed that some residues of the ␣-neurotoxin C-terminal tail may participate in binding with the ␣7 nAChR. Because the C-terminal tail is absent in -neurotoxins acting on ␣3␤2 nAChRs (Fig. 1) and in short-chain ␣-neurotoxins, we used short-chain neurotoxin II N. oxiana as a scaffold for chimeras. Chimeras were constructed on the basis of this toxin by inserting a disulfide-confined fragment from the central loop of long-chain ␣-neurotoxin, namely neurotoxin I N. oxiana. Analysis of the three-dimensional structures of NTII and a number of long-chain ␣-neurotoxins indicated that the introduction of the loop fragment from neurotoxin I might lead only to small perturbations of the NTII central loop conformation. Indeed, NMR and modeling data confirmed these expectations. Because NTII itself practically does not interact with neuronal nAChRs (IC 50 Ͼ 1 M), the chimeras allowed evaluation of the role of the introduced fragment in the interactions with ␣7 and ␣3␤2 nAChRs.
Chimeras were produced by bacterial expression, which was quite successful in the case of NTII and its 15 N-13 C-labeled analogue (36). Introduction of the fifth disulfide into the neurotoxin molecule resulted in a lower yield of the target protein. However, the conditions were found that gave sufficient amounts of the products and allowed us to obtain one of the chimeras (NTII/I) in 15 N-labeled form for detailed structural study (Fig. 3).
The electrophysiology experiments on ␣7 nAChRs expressed in X. laevis oocytes revealed that the chimera NTII/I had a comparable activity (IC 50 ϭ 6.1 nM) to the naturally occurring neurotoxin I (IC 50 ϭ 34 nM). This finding indicates that the C-terminal tail of NTI is not essential for binding to ␣7 nAChR.
It should be noted that Mourier et al. (27), who were the first to make a chimera of long-and short-chain ␣-neurotox-ins, with the aid of peptide synthesis prepared ␣-toxin Naja nigricollis containing the central loop tip from ␣-bungarotoxin. This chimera bound to ␣7 nAChR, with K d 100 nM, being 100-fold less active than native ␣-bungarotoxin.
The A29K substitution in the tip of the chimera NTII/I[A29K] markedly decreased the activity at ␣7 nAChR. However, neither NTI itself nor the chimeras showed activity toward ␣3␤2 nAChRs. Thus, our results indicate that introduction of a positive charge (Lys-29) to the disulfide-confined tip of the central loop does not shift the specificity of ␣-neurotoxin from the ␣7 to ␣3␤2 nAChRs.
Our results are in agreement with the available literature data showing that the interaction of snake venom neurotoxins with nAChRs depends on numerous points of contacts. The overall toxin affinity for the receptor is most likely the sum of several contributions, some from the residues of the central loop, others may include the N-terminal loop or C terminus. The involvement of the N-terminal loop and the C terminus in binding appears to vary among different ␣-neurotoxins (23,53). Although a single mutation of ␣-neurotoxins can cause pronounced changes in the affinity for a given receptor subtype, no shifts in the nAChR subtype specificity were registered.
In this respect ␣-neurotoxins differ from ␣-conotoxins, small subtype-selective nAChR antagonists from cone snails. For these peptides, single amino acid substitutions may be sufficient not only to enhance the affinity at a particular nAChR but also to change the specificity. For example, the A10L substitution in ␣-conotoxin PnIA induced a shift in the specificity from ␣3␤2 to ␣7 nAChR (54). An additional substitution (D14K) in PnIA gave a "double mutant" with a slightly increased affinity for ␣7 nAChR and a 10-fold enhancement of affinity for L. stagnalis AChBP. The crystal structure of this double mutant complex with AChBP provided an explanation why the affinity was increased toward L. stagnalis AChBP, but not to Aplysia californica AChBP (37). Interestingly, in complexes with AChBP (37,45,46) ␣-conotoxins occupy approximately the same site as the tip of the central loop of ␣-cobratoxin (28).
Simulation of binding of both chimeras to ␣7 nAChR revealed that the Lys-29 residue could not make any specific interaction with the ␣7 nAChR residues and was exposed to the solvent, being repulsed by Lys-192-positive charge (numbering by human ␣7 nAChR), see Fig. 5. On the contrary, Ala-29 had weak hydrophobic contacts with the main chain C-loop residues. This distinction could explain the decreased affinity of NTII/I[A29K] to ␣7 nAChR. On the other hand, modeling suggests that Lys-29 of NTII/I[A29K] can make a contact with Glu-190 of ␣3 subunit in the ␣3␤2 nAChR. Despite that, the complex NTII/I[A29K]-␣3␤2 was unstable during MD simulation. It seems that some other interactions, including those due to a dimeric structure, are the basis of the known specificity of -neurotoxins to the ␣3␤2 nAChR.
In summary, bacterial expression gave us chimeras combining structural features of short-and long-chain snake venom neurotoxins. Their individuality and chemical structure were confirmed by analytical HPLC and mass spectrometry, and spatial structure was characterized by NMR and computer modeling. Electrophysiology experiments showed that incorporation of a disulfide-confined tip makes a short-chain neurotoxin fully active against ␣7 nAChR. Modeling of the chimera complexes with ␣7 and ␣3␤2 nAChRs in general agrees with the electrophysiology data, but deeper understanding of toxin specificity toward a particular nAChR subtype will require a larger series of mutants and refined computational approaches.


text:
Thymic emigration revisited

Conventional αβ T cell precursors undergo positive selection in the thymic cortex. When this is successful, they migrate to the medulla and are exposed to tissue-specific antigens (TSA) for purposes of central tolerance, and they undergo maturation to become functionally responsive T cells. It is commonly understood that thymocytes spend up to 2 wk in the medulla undergoing these final maturation steps before emigrating to peripheral lymphoid tissues. In addition, emigration is thought to occur via a stochastic mechanism whereby some progenitors leave early and others leave late—a so-called “lucky dip” process. However, recent research has revealed that medullary thymocytes are a heterogeneous mix of naive αβ T cell precursors, memory T cells, natural killer T cells, and regulatory T cells. Given this, we revisited the question of how long it takes naive αβ T cell precursors to emigrate. We combined the following three approaches to study this question: BrdU labeling, intrathymic injection of a cellular tag, and RAG2p-GFP reporter mice. We established that, on average, naive αβ T cell precursors emigrate only 4–5 d after becoming single-positive (SP) thymocytes. Furthermore, emigration occurs via a strict “conveyor belt” mechanism, where the oldest thymocytes leave first.

Positive selection occurs in the thymic cortex. This signaling event causes up-regulation of CCR7 and migration of the progenitor to the thymic medulla ( 1 ). During medullary residency, thymocytes are exposed to tissue-specifi c antigens (TSAs) expressed by medullary thymic epithelial cells (mTECs). They also undergo receptor tuning and fi nal diff erentiation to become a functional naive T cell. Ultimately, such cells emigrate from the thymus via a mechanism that requires KLF2-mediated up-regulation of the sphingosine-1 phosphate receptor (S1P 1 ) ( 2,3 ). This entire process is commonly believed to take ف 14 d ( 4 ).
The time course of medullary residency and emigration have been primarily examined using either single-dose administration of BrdU to track a cohort of cells, or continuous labeling using either BrdU or tritiated thymidine ( 5 -8 ). Recent thymic emigrants (RTEs) were detected after only 2 d of continuous BrdU administration ( 5 ). However, continuous labeling studies showed that complete labeling of the mature single-positive (SP) thymocyte pool took up to 20 d ( 7 ). An asynchronous, or " lucky dip, " mechanism was proposed to reconcile these data, and because RTEs were felt to be of various ages based on their expression of heat-stable antigen (HSA) and Qa-2 ( 9 ). A lengthy medullary residency period has been speculated to be important in allowing thymic progenitors suffi cient time to survey the TSAs displayed by mTECs, as individual antigens are often expressed only in a small fraction of total mTECs ( 10 ).
Since these studies were published, it has be come apparent that the medulla is also important for the generation of various antigenexperienced populations: NKT cells, T reg cells, and CD8 ␣ ␣ T cells ( 11 ). Although such populations may be selected in the cortex, their fi nal maturation requires mTECs and is disrupted in mouse strains that lack a normal mTEC compartment ( 12 ). Furthermore, it is not clear if all NKT cells, T reg cells, and CD8 ␣ ␣ T cells present in the thymus were newly developed because NK1.1 pos NKT cells have been shown to be retained in the thymus long term ( 13 ), and T reg cells have been shown to be capable of reentering the thymus ( 14 ). Indeed, activated memory T cells have also been shown to be able to recirculate back to the thymus ( 15,16 ), as can naive T cells during various periods of life ( 17,18 ). Given this heterogeneity of SP thymocytes, we decided to revisit the question of how long it takes a naive ␣ ␤ T cell progenitor to exit the thymus.
An important tool that was not previously available is the RAG2p-GFP (also called NG-BAC) mouse. This mouse carries a bacterial artifi cial chromosome transgene encoding a modifi ed RAG1/2 locus, where GFP is inserted after the RAG2 promoter ( 19 ). The RAG genes are highly expressed in double-positive (DP) progenitors, but then are rapidly suppressed after selection. However, the half-life of GFP is such that it lingers long after RAG gene expression is terminated ( 20 ). Because of this, GFP expression in such mice has the potential to act as a " molecular timer " of thymocyte maturation. Using this tool and careful exclusion of nonconventional ␣ ␤ T cells, as well as antigen-experienced T cells, by phenotypic gating, we were able to determine the kinetics of thymic emigration of naive ␣ ␤ T cells. Surprisingly, we found that naive SP thymocytes emigrate only 4 -5 d after entering the SP pool, via a highly ordered process where only the oldest and most mature cells exit the thymus.

RESULTS AND DISCUSSION SP thymocytes are a heterogeneous mixture of various cell types
For the following studies, we used RAG2p-GFP mice where GFP expression is initiated coincidentally with RAG2. However, the GFP protein lingers after RAG expression is terminated during positive selection at the DP stage, creating a situation where the level of GFP can indicate how much time has passed since positive selection. Thus, DP thymocytes express a uniformly high level of GFP, whereas SP thymocytes show a reduced level ( Fig. 1 A ) ( 20 ). In fact, the level of GFP expressed on CD4 SP thymocytes is hetero ge neous, with a prominent population of GFP-negative cells (10.8 Ϯ 3.2%; Fig. 1 A ). This is consistent with heterogeneity in the " age " of SP thymocytes relative to their diff erentiation from DP precursors, and would suggest that some SP thymocytes are retained long-term in the thymus. However, the CD4 SP thymocyte pool includes not only bona fi de naive ␣ ␤ thymocytes, but also NKT cells, T reg cells, ␥ ␦ T cells, and recirculating memory cells. In total, these nonconventional thymocyte populations account for 13.5 Ϯ 1.3% of the total CD4 SP pool (unpublished data), which is in agreement with published data ( 21,22 ). We used a " dump " strategy (NK1.1, GL3, and CD25), along with CD44, to exclude NKT cells, ␥ ␦ T cells, T reg cells, and memory T cells, respectively, and found that the majority (80.9 Ϯ 3.2%) of the GFP neg cells were CD44 hi and/or dump pos , whereas the GFP pos thymocytes were primarily (91.9 Ϯ 1.4%) a CD44/dump neg phenotype (henceforth called " naive " ; Fig. 1 B ). When NKT cells were specifi cally gated, >95% were GFP neg ( Fig. 1 C ), and T reg cells were ف 60% GFP neg ( Fig. 1 D ). This low GFP level indicates that the majority of NKT cells and T reg cells have either: (a) recirculated from the periphery, (b) divided extensively, or (c) been retained for long periods in the thymus. Thymic reentry has been reported for T reg cells ( 14 ), and long retention periods have been reported for NKT cells ( 13 ). However, it has also been shown that the NKT cells that emigrate from the thymus are NK1.1 neg immature cells ( 23,24 ). When we gated on NK1.1 neg CD1d/ ␣ GalCer teteramer pos cells, we found that their GFP profi le more closely resem bled conventional naive ␣ ␤ T cells (unpublished data).

BRIEF DEFINITIVE REPORT
the periphery, and was essentially below the limit of detection by day 8 ( Fig. 2 B ). These kinetics are similar to those previously published ( 6 ). We also examined the mean fl uorescent intensity (MFI) of GFP in BrdU pos CD4 SPs at various time points, and found that it declined progressively with time, demonstrating that GFP acts as a molecular timer for diff erentiation in these mice ( Fig. 2 C ). Furthermore, based on the decrease in GFP intensity over this time period, we estimated that the half-life of GFP is ف 56 h in vivo (unpublished data).

Emigration occurs via a synchronous mechanism
We next sought to determine which cells emigrate from the thymus, and if emigration occurs via a lucky dip mechanism or if it functions more similarly to a conveyor belt. To do this, we divided the naive GFP pos CD4 SP thymocytes into three equal bins, which we called GFP hi , GFP mid , and GFP lo ( Fig. 3 A ). We then examined the three GFP subsets for their expression of molecules known to be changed after positive selection. As expected, some molecules, such as Alk-1 and CD127 (IL-7R ␣ ), were up-regulated after positive selec tion and maintained throughout the lifespan of CD4 SP thymocytes ( Fig. 3 A ). However, several molecules known to correlate with thymocyte maturity were changed most dramatically only in the oldest, GFP lo thymocytes. Specifi cally, HSA was down-regulated the most in GFP lo thymocytes, as was CD69. Likewise, CD62L and Qa-2 were expressed most highly in GFP lo thymocytes ( Fig. 3 A ). TCR ␤ pos CD8 SPs were also ex amined, and similar results were obtained, with the exception that GFP, CD69, HSA, and Qa-2 expression indicated that the cells were older and more mature, confi rming that CD8 SPs take longer to transition from the DP stage (Fig. S1, avai lable at http://www.jem.org/cgi/content/ full/jem.20070601/DC1). Using multicolor cell sorting and Although our approach does not distinguish between cell division, long thymic residency, and thymic reentry in these NKT cells and T reg cells, we emphasize that their presence in previous experiments would certainly have complicated interpretation of the results. For future fl ow cytometry experiments, we used a dump channel consisting of NK1.1, GL3, and CD25, along with CD44, to remove these cell populations from our analyses.
Using this dump strategy, we found that the majority of naive CD4 SPs (98.5%) were uniformly GFP pos . The very small GFP neg population (1.5 ± 0.4%) could theoretically represent thymocytes that were retained in the organ for a long time. Alternatively, they could represent NK1.1 neg NKT cells or, more likely, naive peripheral T cells that recirculated back to the thymus from the periphery during the neonatal period, as naive T cells were shown to recirculate to the thymus in neonatal and old mice ( 17,18 ).

GFP intensity acts as a " molecular timer " to follow development
We fi rst sought to confi rm that declining GFP levels in SP thymocytes correlated with increasing age. To do this, we performed a BrdU pulse-chase time course. 2 mg BrdU was injected into RAG2p-GFP mice at the indicated times before harvest, after which, BrdU pos cells were analyzed by fl ow cytometry. Shortly after BrdU administration (2 h to 1 d), cells were still transitioning from the DN to DP pool and there were very few BrdU pos cells present in the SP compartments ( Fig. 2 A ). By day 3, a notable population of labeled CD4 SPs began to appear. The absolute number of BrdU pos CD4 SP thymocytes reached a maximum at 3 -4 d after BrdU injection ( Fig. 2 B ). The number of BrdU pos CD4 SPs began to decrease after day 4, which was presumably caused by a combination of medullary negative selection and emigration to the molecules necessary to leave the thymus and are represented among the recently emigrated cells.

Emigration of naive T cells occurs after only 4 -5 d
To estimate how long it takes an SP thymocyte to emi grate, we sought to measure the decay of GFP between the GFP hi SPs present in the thymus, and RTE in the periphery. To translate this into time we determined the half-life of GFP in RAG2p-GFP SP thymocytes cultured in vitro, and found it to be 54 h (see Materials and methods and Fig. S3, available at http://www.jem.org/cgi/content/full/jem.20070601/DC1). This is similar to the half-life we estimated in vivo (56 h). Thus, we compared the mean fl uorescence of GFP in GFP hi SP thymocytes (those just entering the medullary SP thymocyte pool) to that seen in RTEs 0 -12 h after emigration ( Fig. 4 B ). From this, we calculated that RTEs are only 4.4 (CD4) or 4.6 d (CD8) older than GFP hi thymocytes on average. Interestingly, CD8 SP thymocytes have a lower GFP intensity than CD4 SPs, again suggesting that they take longer to transition from the DP stage. However, the diff erence in GFP intensity was the same when comparing both GFP hi CD4 or CD8 SP thymocytes and their respective population of RTEs, indicating that medullary residency time is equal for CD4 and CD8 SPs. This timeframe for emigration is also in agreement with the BrdU pulse-chase data, where the majority (85%) of BrdU pos CD4 SPs were gone by 4 d after their peak ( Fig. 2 B ).
quantitative RT-PCR, we examined the mRNA expression of KLF2 and S1P 1 , which are two molecules that are required for emigration from the thymus ( 2, 3 ). We saw that these molecules were most highly up-regulated in GFP lo thymocytes ( Fig. 3 B ). Collectively, these data suggest that GFP lo thymocytes bear the most mature phenotype, and that these cells have an " exit " phenotype.
To study emigrants directly, we performed intrathymic injection of a biotinylating agent, which allowed us to track RTEs in the periphery ( Fig. 4 ). Examination of the SA pos CD4 and CD8 SPs showed that the majority of RTEs are uniformly GFP pos , but a considerable population of GFP neg cells could also be seen, especially in CD4 SPs ( Fig. 4 A ). However, when we examined these GFP neg cells further, they were found to be mostly CD44 and/or dump pos (not depicted), which was similar to the thymus ( Fig. 1 B ). This provides further evidence that the CD4 SP pool is heterogeneous and that not all T cells emigrating from the thymus are bona fi de, naive ␣ ␤ T cells. When we compared the GFP intensity of naive RTEs to that of the SP thymocytes, we saw a distinct shift ( Fig. 4 B ), and the majority of RTEs fell within the GFP lo bin. Furthermore, the ex pression of HSA and Qa-2 on naive phenotype RTEs was uni form and correlated with the GFP lo thymocytes (Fig. S2, avail able at http://www.jem .org/cgi/content/full/jem.20070601/DC1). These data confi rm that emigration from the thymus occurs via a conveyor belt mechanism, where only the oldest thymocytes express Figure 3. GFP lo CD4 SPs are the most mature and have an " exit " phenotype. (A) Naive CD4 SP thymocytes were divided into three equal bins based on GFP intensity. The three bins, along with DP thymocytes, were then analyzed for their expression of the indicated surface molecule. Representative data from 4 -5 experiments is shown. (B) Dump neg cells from the indicated subset were FACS-sorted, RNA was isolated and used for cDNA synthesis, and quantitative RT-PCR was performed for KLF2 and S1P 1 . Data represent the mean fold change Ϯ the SD from two independent sorts relative to CD69 neg DPs and normalized using primers for ␤ -catenin. GFP mid CD4 SPs were only sorted once.

BRIEF DEFINITIVE REPORT
Our data are in agreement with Lucas et al., who showed similar kinetics for thymic development ( 6 ), and also Tough and Sprent, who showed a linear accumulation of labeled cells in the periphery after only a few days ( 5 ). In this study, we have extended those results by making use of RAG2p-GFP mice and 10-parameter fl ow cytometry to reexamine thymic emigration in more precise detail. Our data are in apparent opposition to results obtained by Egerton et al. who showed, with continuous 3 H labeling, that complete labeling of the CD4 SP pool required 20 d ( 7 ), and that RTEs were of various stages of maturity ( 9 ). To reconcile these data, Scollay and Godfrey proposed a " lucky dip " model where the average residency time of SP thymocytes is ف 14 d ( 25 ), which has long remained dogma. However, at that time the degree of heterogeneity in the CD4 SP pool was not appreciated. Their analysis of CD4 pos CD8 neg CD3 pos cells would have included T reg cells, NKT cells, ␥ ␦ cells, and mature recirculating cells. In an attempt to reconcile these fi ndings, we performed continuous BrdU labeling studies and found that naive CD4 and CD8 SPs approached complete labeling after only 8 -9 d, which was just 4 d after TCR ␤ pos DPs were completely labeled ( Fig. 5 ). However, CD44/dump pos cells had only reached ف 50% BrdU pos in this timeframe, and when specifi cally gated, T reg cells, ␥ ␦ T cells, NKT cells, and memory T cells all had a large fraction of BrdU neg cells, even at day 11.
It has also been observed by several groups that mature SPs can undergo a minimal amount of proliferation ( 26 -29 ). Our analysis of the few cycling SPs defi ned at 1 h after BrdU injection confi rmed that most of these are naive ␣ ␤ thymocytes and that more proliferation is seen in CD8 SPs, compared with CD4 SPs (Fig. S4, available at http://www.jem .org/cgi/content/full/jem.20070601/DC1). This diff erence between CD4 and CD8 SPs likely accounts for the slightly diff erent labeling kinetics observed in continuous labeling experiments ( Fig. 5 B ). Furthermore, we note that the BrdU pos SP thymocytes do not represent any specifi c maturation state based on GFP expression (Fig. S4, top) or any other maturation marker, e.g., Qa-2 or HSA (not depicted). Neither our estimation of medullary residency time based on the GFP intensity of RTEs compared with SP thymocytes nor previous estimates based on BrdU 3 H incorporation take into account this putative division of SPs after positive selection. However, we note that because cell division would further dilute GFP, our data is, if anything, an overestimate of medullary residency time, and emigration may happen even more quickly. In summary, our data show that naive ␣ ␤ T cells emigrate quickly and synchronously. They further suggest that the T cells that " emigrate " late are mostly a heterogeneous mix of NKT cells, ␥ ␦ T cells, T reg cells, and memory T cells. In fact, it is probable that these cells, or a substantial The expression of GFP in naive CD4 and CD8 RTEs compared with naive CD4 and CD8 SP thymocytes, respectively. Gates were drawn on naive CD4 and CD8 SP thymocytes, as seen in Fig. 3 . The MFI for the indicated subsets is shown below the histogram. The CV values were as follows: CD4 SP, 57.59; CD4 RTE, 59.29; CD8 SP, 73.44; and CD8 RTE, 74.68. For comparison, DP thymocytes were 34.52. The MFI values were used to estimate the average difference in age between the youngest (GFP hi ) SP thymocyte and a RTE, as described in the Materials and methods (shown on right, in days).

Mice.
RAG2p-GFP mice have been previously described ( 19 ), and they were provided by P. Fink (University of Washington, Seattle, WA). All animals were maintained and treated in accordance with federal guidelines approved by the University of Minnesota Institutional Animal Care Committee.
Antibodies and fl ow cytometry. All fl uorochrome-conjugated and biotinylated antibodies were purchased from BD Biosciences, eBioscience, Invitrogen, or BioLegend, except for biotinylated mCD1d/ ␣ GalCer monomers, which were obtained from the National Institutes of Health Tetramer Facility (Atlanta, GA). Tetramers were formed by mixing monomers with streptavidin PE at a molar ratio of 1:6. Anti-BrdU (PRB-1) was purchased from Phoenix Flow Systems. Conventional surface staining was performed by staining cells with antibody for 30 min on ice in FACS buff er (PBS, 1% FCS, and 0.02% azide, pH 7.2) and washing two times in FACS buff er after each antibody incubation. Intracellular Foxp3 staining was performed using the Mouse Regulatory T Cell Staining kit (eBioscience). Cell events were collected using an LSR-II cytometer (BD Biosciences) and analyzed with FlowJo software (Tree Star, Inc.).
BrdU labeling. BrdU pulse-chase time courses were performed as previously described ( 6 ). 100 l of 10 mg/ml BrdU (Sigma-Aldrich; B5002) was injected intraperitoneally twice at 4-h intervals for a total of 2 mg/mouse at the indicated time point before harvest. Thymi were harvested and surface stained as described in the previous paragraph, followed by intracellular staining for BrdU using the APC BrdU fl ow kit (BD Biosciences), with the substitution of the anti-BrdU antibody mentioned in the previous paragraph. Continuous BrdU labeling was performed similarly with the following exceptions, as previously described ( 37 ). Groups of 3 mice were injected intraperitoneally with 1 mg BrdU at the indicated time point before harvest, and then continuously given 0.8 mg/ml BrdU in sterile drinking water that was changed daily until harvest.
Cell sorting and quantitative RT-PCR. Thymocyte subsets were purifi ed by FACS-sorting on a FACSVantage (Becton Dickinson). RNA was isolated from sorted populations by oligo(dT) and random hexamer priming using the RNeasy kit (Qiagen), and cDNA was produced using the Super-ScriptIII Platinum Two-Step qRT-PCR kit (Invitrogen). qRT-PCR was proportion of them, are recirculating, as opposed to emigrating late.
Given our fi nding that medullary residency is much shorter than previously thought, a pertinent question is asked -is this a problem for central tolerance? Not only do SP thymocytes require interaction with the medulla to tune their TCR and lose responsiveness to self-ligands ( 30 ), but they also undergo negative selection to TSA in the medulla. Furthermore, SP thymocytes are only competent to undergo clonal deletion at the semimature stage (HSA hi and Qa-2 neg ), which is roughly the fi rst two thirds of their residency time (unpublished data). Given that some TSAs are expressed only by rare mTECs ( 10 ), and that loss of tolerance to just one TSA is capable of causing autoimmunity ( 31 ), a short medullary residency time might be a point of weakness in the central tolerance arsenal. A comprehensive understanding of TCR tuning and medullar deletion (including AIRE-mediated), must take into account this kinetic aspect.
Lastly, the means by which thymocytes leave the organ is poorly understood. Selected thymocytes migrate to the medulla in a CCR7-dependent manner. Thus, it would stand to reason that emigration occurs via an exit route from the medulla. However, CCR7-defi cient mice appear to have normal thymic emigration, even though they show poor accumulation of SP thymocytes in the medulla ( 1,32 ). This suggests that migration to the medulla is not a prerequisite for emigration, and that exit routes from the thymus are present in both the cortex and the medulla. It is possible that emigration occurs either through the lymphatic system, or through blood vessels ( 33 -35 ). Perivascular spaces were proposed as a site for emigration, but this has not been proven ( 35,36 ). It is our hope that this study of the kinetics and phenotype of emigrating thymocytes will lead to greater understanding of this process in the future.