No serum miRNA was regulated exclusively in aUC compared with iUC patients. Four miRNAs were higher and three miRNAs

were lower in the mucosa of aCD than iCD. Two miRNAs were higher and three miRNAs were lower in the mucosa of aUC than iUC. No serum miRNAs coincided with tissue miRNAs in aCD and aUC patients. Our results suggest Tyrosine Kinase Inhibitor Library the existence of specific miRNA expression patterns associated with IBD and their different stages and support the utility of miRNA as possible biomarkers. This pilot study needs to be validated in a large prospective cohort. Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), is a chronic inflammatory gastrointestinal disorder, the pathophysiology of which remains unclear. The theory accepted most commonly is that IBD

and the associated gastrointestinal inflammation are likely to be the result of the interaction between a defective immune response to a luminal factor (probably intestinal flora), epigenetic and environmental factors (e.g. smoking) and its influence in genetically predisposed subjects [1-3]. Genetic factors involved in inflammation and immune functions are known to play a very important role in IBD physiopathology. Micro-RNAs (miRNAs) are a class of small non-coding RNAs, involved in the control of gene expression at the post-transcriptional level [4]. Following the discovery of miRNAs, the number of publications regarding their biogenesis and functions has been increasing exponentially and the miRNA sequence database, miRBase, is growing continuously [5, 6].

Smoothened Agonist mw MiRNAs are involved in the regulation of many biological processes such as the cell cycle, differentiation, Methane monooxygenase proliferation, apoptosis, fibrosis and immune function [7]. Emerging evidence has demonstrated that miRNAs can also play an important role in the development of cancer as well as in the induction of chronic inflammatory and autoimmune diseases [8, 9]. miRNAs have been found in tissues, serum, plasma and other body fluids. It has been demonstrated that the levels of miRNAs in serum are stable, reproducible and consistent among individuals of the same species [10]; for this reason, such levels are now being used as a non-invasive biomarker for different pathologies (i.e. cancer, autoimmune disease, inflammation) [10, 11]. Previous studies, focused particularly on cancer, have discovered that circulating miRNA profiles can be correlated with tissue miRNA profiles [12, 13]. In most cases, those changes in circulating miRNA profiles can precede the standard blood biomarkers and possess prognostic value [12, 14, 15]. These properties mean that miRNAs are attractive, blood-based, non-invasive biomarkers. Recently, several papers have focused investigation on the altered expression of miRNAs in IBD and their important role as regulators and possible diagnostic biomarkers in IBD [8, 16-18].

0101 and rPer a 1.0104 on these cytokine secretion check details from P815 cells. The results showed that rPer a 1.0101 and rPer a 1.0104 provoked a dose-dependent

increase in IL-4 and IL-13 release following 16-h incubation period. They also induced increase in IL-4 (Fig. 4A) or IL-13 (Fig. 4B) release at 6 h following incubation. rPer a 1.0101- and rPer a 1.0104-induced IL-4 and IL-13 release were significantly blocked by specific antibody against rPer a 1.01. At the concentrations tested, rPer a 1.0101 and rPer a 1.0104 failed to induce IL-10 and IL-12 release from P815 cells following 6-h and 16-h incubation periods (data not shown). ET-28a is a powerful prokaryotic expression vector capable of producing reasonable quantities of foreign proteins in E. coli when induced by IPTG [18]. The BugBuster Protein Extraction Reagent can solubilize cell components, thereby release cellular proteins without denaturation and remain greater activity. Our results showed that the target proteins retain their unique molecule sequences and immunological activity as assessed by LC-ESI-MS/MS and Western blot analyses. Using the same expression system, Wu et al [3] showed recombinant Per a 1.0104 can react with specific IgE

from serum of allergic buy Luminespib patients, indicating the protein possesses biological activity. Lack of cysteine residue and potential N-glycosylation site in Per a 1 molecule also supports that the E. coli expression system employed in the present study is suitable for producing functional Per a 1 proteins. To our surprise, sera from 80% of cockroach allergy Isotretinoin patients react to rPer a 1.0101 protein, which is a much higher incident rate than that reported by Wu et al [3] (∼50%). It is rather difficult to explain the reason for the discrimination,

but nevertheless, it confirms that Per a 1.0101 is a major allergen of American cockroach. Sera from 73.3% of cockroach allergy patients react to rPer a 1.0104 protein is agreed well with a previous report which showed that 77.3% cockroach-sensitive atopic patients reacted to per a 1.0104 during skin prick [19]. The very similar reactivity of specific IgE to rPer a 1.0101 and rPer a 1.0104 implicates that allergenicity of these two molecules is similar, and the epitopes of allergenicity are likely located in the identical parts of the two molecules. As little is known of functions of Per a 1 allergens, we demonstrate for the first time that recombinant Per a 1.0101 and Per a 1.0104 are able to induce enhanced expression of PAR-1 protein. Induction of upregulated PAR-2 and PAR-4 expression by rPer a 1.0101 and rPer a 1.0104, respectively, indicates that these two Per a 1 isoallergens can act differently on the expression of PARs even if they share nearly 80% identity in their protein sequence. Like rPer a 7 [8], as much as 1 μg/ml of rPer a 1.0101 and rPer a 1.

In addition to changes at the mRNA level, master transcription factors drive epigenetic modifications of many Th effector genes that reinforce the dominant phenotype [61, 62]. These epigenetic patterns are passed on to the cell’s progeny, creating a single Th

clone with similar epigenetic imprinting, that is, a Th-cell phenotype. Cytokine production by Th cells typically requires a few days of differentiation following the initial activation [41, 42], but phenotype induction at the transcriptional level already occurs within a few hours [63-65]. Over the last decade, Th-cell feedback mechanisms have been studied extensively using mathematical modelling. Whereas older studies focused on Th1/Th2 differentiation [66-68], more recent studies have included www.selleckchem.com/products/BKM-120.html Treg and the novel Th-cell phenotypes [69-73]. Most of these mathematical models incorporate positive feedback and cross-inhibition. These models are typically parameterized in such manner that only single master transcription factors can be expressed, but co-expression can occur with other parameter regimes [71]. Interestingly, models have been formulated both at the inter- and intracellular level, and models at either level are capable of explaining Th differentiation

in response to outside signals, showing that there is redundancy in the system. Some studies have attempted to incorporate feedbacks at the genetic and epigenetic levels into models [56, 73], although only a single feedback loop is sufficient to explain Th-cell phenotypes. Modelling has also illustrated that mTOR inhibitor master regulator heterodimer formation Vasopressin Receptor is sufficient for explaining mutual inhibition [71]. In addition to make the inducible phenotypes mathematically tractable as

alternative ‘steady states’ or ‘attractors’ of a dynamical system, these models provide insight into the development of Th-cell phenotypes over time, that is, the time series of changes that these cells undergo. These models show that early skewing leads to progressive differentiation into Th-cell phenotype as seen by experimental studies [43, 65]. In addition to traditional approaches, Th-cell differentiation has been studied intensively using high-throughput techniques. The targets of many important Th transcription factors have been mapped [9, 13, 14, 63, 74], and expression profiling has been performed by a number of groups [8, 63, 65, 75]. We and others have advocated a time series approach to Th-cell differentiation, because the Th-cell transcriptome is very dynamic in time. Indeed, we have shown that the mRNA signature of Th cells changes rapidly after the cognate priming and that genes can be classified into a ‘core’ and ‘turnover’ groups, and these also differ when different phenotypes are induced [65].

This work was supported by Shandong Natural Science Foundation grant JQ200908 and the State Key Basic Research of China grant number 2009CB526506 to Y.W. The authors declare no financial or commercial conflict of interest. As a service to our authors and readers, this journal provides

supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should Roscovitine cell line be addressed to the authors. Table S1 Table S2 Figure S1 Figure S2 Figure S3 Figure S4 Figure S5 Figure S6 “
“Cell survival transcription factor FOXO3 has been recently implicated in moderating pro-inflammatory cytokine production by dendritic cells (DCs), but the molecular mechanisms are unclear. It was suggested that FOXO3 could antagonize NF-κB activity, while IKK-β was demonstrated to inactivate FOXO3, suggesting a cross-talk between the two pathways. Therefore, FOXO3 activity must be tightly regulated to allow for an appropriate inflammatory response. Here, we show that in human monocyte-derived DCs (MDDCs), FOXO3 is able to antagonize signaling intermediates downstream of the Toll-like receptor (TLR) 4, such as NF-κB

and interferon regulatory factors (IRFs), resulting in inhibition of interferon (IFN)-β expression. We also demonstrate that the activity of FOXO3 itself is regulated by IKK-ε, a kinase involved LEE011 datasheet in IFN-β production, which phosphorylates and inactivates FOXO3 in response to TLR4 agonists. Thus, we identify FOXO3 as a new IKK-ε-controlled check-point of IRF activation and regulation of IFN-β expression, providing new insight into the role of FOXO3 in immune response control. The FOXO transcription factors (FOXO1, FOXO3, FOXO4, and FOXO6) are involved in a wide range of cellular processes including cell-cycle arrest, apoptosis, oxidative stress detoxification, and cellular homeostasis [[1-3]]. Given their importance

in such critical cellular functions, their activity is tightly regulated by posttrans-lational modifications, Ponatinib mainly via the phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway [[4]]. In response to growth factors or cytokines, FOXO proteins are phosphorylated by AKT at three conserved serine/threonine residues (Thr32, Ser253, and Ser315 of FOXO3) resulting in the protein inactivation via nuclear exclusion and subsequent degradation [[5, 6]]. More recently, FOXO factors have been shown to play a role in immunity and inflammation [[7-11]]. In addition to their critical role in homeostasis of immune-relevant cells including B and T cells [[7-9]], FOXOs are associated with inflammatory diseases [[12, 13]]. Moreover, FOXO3 was identified as a key factor in regulation of the innate immune response [[10]].

A study conducted with murine splenic B cells showed an association between IRE1-dependent induction of XBP-1s and increased levels of the GRP78 and GRP94 mRNAs during terminal differentiation of B cells [53]. The chaperone BiP mediates one proposed

model of regulation of the UPR pathway. Under non-stressful conditions, BiP remains bound to the luminal domains of IRE1, PERK, and ATF6, functioning as a negative regulator [54]. Early experiments showed that IRE1 interacts with BiP in resting cells, from which it dissociates during ER stress [55]. A second model proposes that unfolded/misfolded proteins bind to the luminal selleckchem domain of IRE1, promoting its dimerization and activation of cytoplasmic effectors domains [56]. Finally, a third model integrates the previous models suggesting that dissociation of BiP from IRE1 triggers its oligomerization, Pictilisib mouse followed by binding of misfolded/unfolded proteins to sub-regions II and IV (core stress-sensing region, CSSR) of IRE1 luminal domain. The CSSR would then activate the effectors functions of IRE1. The ability of CSSR to inhibit aggregation of denaturated proteins

in vitro led to the observation of its ability to bind unfolded proteins [56]. More recently, a study showed that HSP72, a member of the HSP70 family whose expression is triggered by ER stress, might regulate the UPR pathway. The study showed that physical interaction between the kinase domain of IRE1 with the ATPase domain from HSP72 causes a delay in the termination of IRE1 endonuclease functions (XBP-1 splicing), enhancing the signalling by the IRE1/XBP-1 axis, which ultimately results in cytoprotection [57]. Viruses appear to regulate the UPR in order to benefit from it, but at the same time, inhibit those Non-specific serine/threonine protein kinase aspects that are detrimental to the regulation of

viral replication. PERK is activated in cells infected with herpes virus, while eIF2α remains dephosphorylated, so that viral protein synthesis is undisturbed [58]. In the early stages of cytomegalovirus infection, PERK is not phosphorylated, but as infection progresses, a slight increase in PERK phosphorylation is observed, along with phosphorylation of eIF2α. Still, there is no attenuation of protein translation. A significant increase of the ATF4 mRNA levels is also observed. ATF4 is responsible for transcription activation of several genes related to cellular metabolism. Altogether, these effects of cytomegalovirus appear to be important for maintenance of viral infection [59]. The earlier evidences of intersection between the UPR pathway and the inflammatory response were found in studies that showed a connection between ER stress and activation of the transcription factor NF-κB and the kinase stress-activated protein kinase/c-Jun-terminal kinase (SAPK/JNK) [60–63].

During IFN-α signaling, the activated STAT1 dimer and ISGF3 (STAT1:STAT2:p48) complex each acquires exposed nuclear localization signals. Importin-α/β complex recognizes these signals and induces translocation of the STAT complexes into the nucleus 35, 38, 39. However, no mechanisms governing the nuclear localization www.selleckchem.com/products/AZD6244.html of STAT6 have been identified

yet, except that the translocation of STAT6 depends on its phosphorylation on Y641 39. In this regard, we have noted that the cytoplasmic retention complex containing pY-STAT6 did not interact with importin-α (Supporting Information Fig. S3, left panel). Interestingly, with increased association of pY-STAT6 with pY-STAT2 and p48 during IFN-α treatment from 0.5 to 4 h, there is a decreased interaction of pY-STAT1 with pY-STAT2 and p48 (Supporting this website Information Fig. S3, right panel). The observation raises a possibility that by the action of IFN-α-induced factors during 4 h treatment, pY-STAT1 gradually dissociates from the ISGF3 complex, which is then replaced with IL-4-activated pY-STAT6. This would result in the sequestration of STAT6 from the translocatable STAT6 homodimer to form the putative pY-STAT6:pY-STAT2:p48 complex incapable of importin binding and nuclear translocation, which is then retained in the cytosol. On the other hand,

it is also possible that pY-STAT6 is accumulated in the cytoplasm upon the inhibition of translocation mediated by IFN-α-induced factors, which then interacts with pY-STAT2 and p48. Several post-translational modifications other than tyrosine phosphorylation may be involved in the formation of the STAT complex retained in the cytosol, since STAT6 and/or STAT2 are thought to undergo serine/threonine

phosphorylation, acetylation, and sumoylation. Yet, in our experimental system, we have observed no STK38 detectable changes in these modifications on STAT6 or STAT2 by IFN-α and IL-4, which suggests that such post-translational modifications may not play a role in the molecular interaction and cytosolic accumulation of the STAT complex. As shown by the inhibition of the IL-4-induced CD23 expression and the IFN-α-induced IRF7 expression, a novel feature of the IFN-α and IL-4-induced cross-signaling found in the present study is the cytoplasmic co-retention of activated STATs (Figs. 3, and 4). By coimmunoprecipitation experiments, we have verified the molecular interaction among pY-STAT6, pY-STAT2, and p48 induced in cells upon treatment with IL-4 and IFN-α (Fig. 5A), which strongly suggests a possibility that these proteins are present in a molecular complex. To further examine the possibility that the inhibition by IFN-α and IL-4 is mediated via the formation and cytoplasmic retention of the pY-STAT6:pY-STAT2:p48, the effect of STAT over-expression was analyzed.

Thus, with the exception of this latter group, the antibody isotype patterns suggest that a mixed Th1/Th2 type immune response had been elicited against recNcPDI. Serological reactivity against the Nc. extract showed the following characteristics (Figure 4): (i) total IgG (as well as IgG1 and IgG2a) levels taken prior to challenge were generally low in all groups; (ii) PXD101 in vivo following Neospora challenge, all mice elicited a significantly increased (P < 0·05) total IgG response against the Nc. extract antigens; (iii) after challenge infection, most groups responded with a significant increase in both IgG1 and IgG2a levels, the exception being the group vaccinated intranasally with recNcPDI

associated with chitosan/alginate

nanoparticles (1PDI-Alg-CT), with which IgG2a selleck chemical levels did not increase significantly (Figure 4b). Overall, these results were once again showing evidence for a mixed Th1/Th2 type immune response in the majority of animals. Cytokine transcript levels in spleen of all mice were assessed by real-time PCR at the time-point of euthanasia (Figure 5). This analysis demonstrated that in the control group 1 (SAP) and the experimental groups 2–6 vaccinated i.p., IL-4 and interferon-gamma (IFN-γ) transcription occurred at similar levels. There was a slight reduction in the IL-4 transcripts found in the two groups receiving only nanogels with SAP (Alg-SAP and Man-SAP) compared to the SAP alone control (SAP). In contrast to the IL-4 and IFN-γ, IL-10 and IL-12 transcription was increased in all vaccinated groups compared to the SAP controls. In the groups vaccinated i.n., all groups, including the cholera toxin control group (CT), showed an IL-10 and IL-12 transcription, which was higher than that obtained with the SAP control group receiving saponin intraperitoneally. Interestingly, it was noted that the IL-10 : IL-12 ratios tended to favour the IL-10

transcripts Neratinib nmr in the groups receiving CT alone and recNcPDI antigen plus CT. With the antigen formulated in nanogels, this ratio was closer to equivalence or favoured IL-12, especially when the mannosylated nanogels were employed. The latter modification of the IL-10 : IL-12 ratio appeared to be dependent on the nanogels, considering that the nanogels without antigen showed a similar profile to the nanogels carrying the recNcPDI antigen. As for the IL-4 transcripts, these were notably reduced in all mice vaccinated with nanogel formulations, particularly the mannosylated nanogels, compared to the CT control group and the group receiving the lower dose of recNcPDI antigen. An efficient vaccine against neosporosis in cattle should sufficiently stimulate humoral and cell-mediated immune responses to prevent tachyzoite proliferation, tissue cyst formation, recrudescence and transplacental transmission to the foetus (10,13).

The Krüppel-like factors (KLFs) are a family of transcriptional regulators with a highly conserved DNA-binding domain that consists of three C2H2-type zinc fingers capable of binding to a CACCC element or GC box consensus sequences [17, MG-132 order 18]. KLFs play different

roles in biology through their divergent non-DNA-binding regions that function as trans-activation or trans-repression domains. A total of 17 members of mammalian KLFs have been identified thus far [19], some are found to play important roles in immune and hematopoietic cell biology by regulating gene transcription. For example, Klf1 (erythroid Krüppel-like factor) regulates β-globin expression during erythrocyte development [20, 21] and also affects IL-12p40 production in human macrophages [22]. Klf4 has been reported as a key regulator in monocyte differentiation and macrophage activation [23-25]. Recent studies further demonstrated Klf4 as a novel regulator in M2 macrophage polarization [5]. Klf10 belongs to the KLF family and was initially identified in human osteoblasts as a TGF-β responsive gene [26]. Thus, Klf10 is also called TGF-β inducible early gene 1 (TIEG1) [26]. Osteoblasts from Klf10-deficient mice have been reported as defective in mineralization and in supporting osteoclast differentiation

in vitro [27]. Subsequent studies demonstrated that Klf10 is also essential in T-cell biology. Klf10 cooperates with Itch to regulate Foxp3 expression [28] and also regulates CD4+CD25− T cells and Treg cells by

targeting TGF-β [29]. TGF-β inhibits several LPS-induced inflammatory cytokines in ICG-001 macrophages [30] and contributes to resolve inflammation. Recent studies revealed that TGF-β also contributes to M2 macrophage polarization [2]. However, as a TGF-β-induced gene, the function of Klf10 in innate immune cells such as macrophages has not been studied thus far. Here, we demonstrate the role of Klf10 in regulating the production of inflammatory cytokines in M-BMMs. We found that Klf10 expression was downregulated upon TLR activation. The forced expression and loss function assay of Klf10 in M-BMMs revealed a repressive effect on IL-12p40. Moreover, we also observed a similar role for Klf11 as that of Klf10 in regulating Fenbendazole IL-12p40 expression. Studies on this mechanism demonstrated that Klf10 inhibits the production of IL-12p40 by binding to the IL-12p40 promoter. Therefore, our observations support the importance of Klf10 as a key transcriptional repressor of inflammatory cytokines in M-CSF-induced macrophages. Quantitative PCR (qPCR) analysis for the expression of the KLF family members in M-BMMs was conducted to determine whether the KLF family members can control the inflammatory factors in M-BMMs. The result shows that Klf3, Klf4, Klf6, Klf10, Klf11, and Klf13 have high mRNA level among all family members (Fig. 1A).

All the culture-positive cases of EHEC infection, irrespective of the serogroups isolated, are reported to the National Institute of Infectious Diseases. At present, the most dominant serotype is O157:[H7], followed by O26:[H11] and O111:H-. These three serotypes account for more than 95% of the EHEC isolated in Japan (5). Recent advances in microbial genome sequencing have enabled the establishment of new methods for subtyping bacterial isolates. Among these, MLVA is one of the most widely accepted and useful methods (6). MLVA was successfully used to elucidate selleck screening library the molecular epidemiology of EHEC O157:[H7], and an MLVA system

involving nine genomic loci was established for this serogroup (7). However, see more this system has not yet been

applied for EHEC serogroups other than O157. In the present study, we first investigated whether the MLVA system for O157 can be applied to EHEC O26 and O111 and found that it cannot. Therefore, on the basis of the genome sequences of EHEC O26 and O111 (8), we developed an expanded MLVA system that is applicable not only to the O157 serogroup but also to the O26 and O111 serogroups. Furthermore, our study revealed that cluster analysis based on the MLVA profiles is comparable to that based on PFGE profiles in outbreak investigations. A total of 641 EHEC isolates (153 O157:H7/-, 355 O26:H11/-, and 133 O111:H- isolates) were examined in the present study. All these isolates were collected by the staff of local public health institutes between 2005 and 2007. Among these, 145 O26 and 39 O111 isolates had been collected during nine and three outbreaks, respectively, and were used to evaluate the efficacy of our new MLVA system in detecting outbreak-related strains. A strain set comprising 469 isolates (153 2-hydroxyphytanoyl-CoA lyase O157, 219 O26, and 97 O111 isolates, referred to as ‘representative isolates’) was used to evaluate the discriminatory power of the MLVA system. This included isolates from apparently independent

sporadic cases and those representing each outbreak (one isolate from one outbreak). MLVA was carried out as described in our previous study (9). The genome sequences of four EHEC strains (two O157, one O26, and one O111 strain) were searched for tandem repeats in silico (8, 10, 11). Finally, 18 loci, including the nine loci used in the current MLVA system for O157, were used to analyze the isolates in the present study. The primers were designed so that amplification reactions could be carried out in two multiplex mixtures. The primers used in this study are shown in Table 1. The O157-9 reverse primer for O26 and O111 was different from the original primer for O157, because the sequence corresponding to the primer in O26 and O111 differed from that in O157, as described below. One primer of each primer pair was labeled at its 5′ end with 6-FAM, NED, VIC, or PET (Applied BioSystems, Foster City, CA).

Thus, 4–1BBL on radioresistant cells contributes to the recovery of CD8+ memory T cells after adoptive transfer in vivo, with smaller effects from 4–1BBL on radiosensitive cells. We next used immunohistochemistry to identify

the cells that are the nearest neighbors of CD8+ memory T cells in the BM. To this end, we generated Red fluorescent OT-I memory T cells by crossing OT-I mice with ACTB-DsRed transgenic mice. This transgene leads to expression of Red fluorescent protein under control of the β-actin promoter. Although Red fluorescent protein is a foreign protein in mice, initial experiments showed similar recovery of in vitro generated CD45.1 OT-I memory T cells or Red fluorescent CD8+ memory T cells for at least 6 days post transfer (data not shown). We transferred 6 million OT-I-DsRed CD8+ memory T cells into WT mice and 1 day later analyzed their location by immunofluorescence microscopy. This time point Selleck Cobimetinib was chosen based on initial kinetic experiments showing the highest numbers of Red OT-I T cells in the BM at 1 day post transfer followed by a gradual decline. This is the same time frame analyzed by previous investigators to identify find more interactions of CD4 memory

T cells in the BM [5]. The transferred memory T cells were found randomly scattered in the BM, with no obvious overall distribution pattern at low magnification (Fig. 6A). To gain insight into their local environment, we used costaining with other markers to assess which Florfenicol cell types were in close proximity to the transferred memory T cells. More than 70% of OT-I-DsRed memory T cells were found in close contact with VCAM-1+ cells in contrast to <5% in contact with CD31+ endothelial cells or 13% with CD11c+ cells (Fig. 6B). VCAM-1 can be found on inflamed endothelial cells [37] as well as on stromal cells [38]. However, the finding that there was minimal association of the CD8+ memory cells with CD31+ cells argues that the VCAM-1-positive stromal cell is the most abundant cell to be found in close proximity to the transferred red memory T cells.

The second most abundant interaction of the memory T cells was with Gr1+ cells (50% of CD8+ memory T cells and this was not significantly different from the number found in proximity to VCAM-1+ cells). B220+ cells were found in close proximity with 35% of memory T cells and this was significantly lower than the number associated with VCAM-1+ cells. F4/80-positive cells were associated with 25% of the CD8+ memory T cells. We also showed that the Gr1+ and B220+ cells located in proximity to the OT-I-DsRed memory T cells did not coexpress the Gr1 and B220 markers (Supporting Information Fig. 5). Thus, these cells are not plasmacytoid DCs (which coexpress Gr1 and B220), but myeloid cells or granulocytes (Gr1+) and B cells.