HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hedges, J. F. Articles by Jutila, M. A. Search for Related Content PubMed PubMed Citation Articles by Hedges, J. F. Articles by Jutila, M. A.

Transcriptional Profiling of T Cells ¹

Veterinary Molecular Biology, Montana State University, Bozeman, MT 59718

	Introduction

Top Introduction Genomic approaches used in... Preliminary studies on specific... Future genomic analyses of... Summary References

 
Evolutionarily well-conserved, T cells may have been precursors to modern B and T cells (1). T cells are distinct from T cells, in part, by the genes that encode their TCRs, their ability to recognize Ag in the absence of classical MHC Ag presentation, and their role in maintaining the integrity of epithelial tissue (2). T cells represent a small percentage of the circulating T cells in adult humans and mice, but make up a majority of the intraepithelial lymphocyte (IEL) ³ population in the gut and other epithelial mucosa. Conversely, T cells are a major subset in adult ruminants and make up a majority (up to 70%) of circulating lymphocytes in neonatal calves (3). They are the first T cells to develop and are recruited, and expand in response, to various infections in humans, rodents, and other animals (4). Evidence suggests that T cells play an important role in innate immunity at mucosal surfaces (5) and may contribute to immunity in neonates (2).

Although there is considerable evidence from work in humans, rodents, and ruminants that T cells participate in a variety of responses, their overall importance and the similarities of T cells between species are still unclear. A number of variables complicate the analyses of these cells in these different systems. First, distinct functional subsets of T cells, some of which have opposing activities, confound the interpretation of the role of T cells as a whole. These subsets can be distinguished by their TCR (6, 7, 8, 9), tissue localization (10, 11, 12), and/or coexpression of lineage-specific differentiation molecules (10, 11, 12). T cell subsets in some systems selectively migrate to sites of inflammation, exacerbate inflammatory reactions, and contribute to antimicrobial responses, whereas other subsets suppress inflammatory and/or immune responses (8, 12, 13). Unfortunately, these subsets are not equally represented nor are their phenotypes the same in all species. For example, in adult human blood, the major proportion of the circulating pool of T cells express the same TCR (V9/V2 (also termed V2/V2)) and selectively respond to phosphoantigens of various pathogens, such as Mycobacterium tuberculosis (6). Microbial responsive T cell subsets exist in mice as well, but their TCR gene usage and the Ags they recognize are different (7, 8, 9). However, a subset distinguished by low expression of either the or dimer form of CD8 is common to all species, and compromises a major portion of the IELs in rodents and ruminants (10, 11, 12). Second, experimental variables associated with animal age, environment (microbial/allergen/toxin exposure), and tissue source (blood, lymph, tissues) also complicate development of a consensus about the functional importance of T cells (2, 4, 11, 14, 15, 16, 17, 18, 19). Even within the TCR gene deletion mouse model, the precise and likely highly diverse roles of T cells in immunity remain enigmatic, as their function appears to be specific to infectious agent or assault (2). Besides the inability to study individual T cell subsets in TCR gene knockout mice, compensatory mechanisms likely develop due to the redundancy of the immune system, thus potentially cloaking a vast array of T cell functions.

One approach to minimize the impact of the aforementioned variables is to perform global gene expression analyses of T cells to identify trends conserved between species, to distinguish T cells from other T cells, and to differentiate between subsets of T cells. Advances in genomic technology now provide the means of rapidly comparing global transcriptional differences between rare cell populations. These approaches have been used extensively in many biological settings, including analysis of T cell subsets. Recently, four studies using genomic approaches to analyze transcription profiles of tissue and blood T cells have been published. The intent of this review is to compare the results from these genomic reports and to elucidate general transcriptional trends for T cells that emerge despite several variables between studies. In addition, we briefly summarize some key findings and emphasize new research directions suggested by these studies.

	Genomic approaches used in the analysis of T cells

Top Introduction Genomic approaches used in... Preliminary studies on specific... Future genomic analyses of... Summary References

 
There are many excellent studies of gene transcription in T cells, including the analysis of T cells, using techniques such as Northern blot, RNase protection assays, RT-PCR, and quantitative RT-PCR, which have provided tremendous insight into our understanding of immunology. However, we will focus on two genomic approaches (Fig. 1) that have been used in the study of T cells: microarray technology, including cDNA and oligonucleotide arrays, and serial analysis of gene expression (SAGE). Arrays are highly sensitive and uncomplicated. Analysis of microarray data is simplified by prior annotation of the genes, the ability to select specific genes to spot on the array, and by the increasing number of bioinformatics tools available for analysis. Arrays are the most widely used functional genomics tool in immunology (20) and have been used to compare CD4⁺ and CD8⁺ type 1 and type 2 T cells (21), to examine the activation of T cells (22), and to characterize Th cell development (23). SAGE is technically more challenging and sequencing costs can be high, but offers some advantages over microarrays, as the genes that are identified are not predetermined, thus the data are unbiased and comprehensive (24). After normalization, SAGE libraries are also comparable to all other SAGE libraries, irrelevant of the time or place of their construction. Long SAGE can be used to isolate longer (21 bp) tags and is ideal for new gene discovery (25). Finally, confidence in the quantification of low abundance transcripts and the reliability of SAGE-predicted gene regulation can be increased by simply sequencing additional tags from the same SAGE library. In summary, both microarray and SAGE techniques are valuable new methods for analysis of transcriptional trends in specific cell populations.

View larger version (26K): [in this window] [in a new window]   FIGURE 1. Genomics tools used to study immune cell function. A, Microarray technology involves hybridization of fluorescently labeled total mRNA to a microchip spotted with oligonucleotides or cDNAs representing thousands of genes. Differently labeled mRNA from two different cell populations or treatments can be applied, and essentially compete for hybridization to spots on the array, thus, the differential expression levels of mRNA between the two samples is measured. B, SAGE is used to isolate 14-bp sequence "tags" derived from the 3' end of every mRNA present in a cell population. This sequence is sufficient to identify the mRNA from which it is derived. The tags are sequenced and identified by comparison to sequence databases. L, linker; B, biotin; S, streptavidin-conjugated to magnetic beads.

A similar study identified an "activated yet resting," cytolytic and immunoregulatory phenotype for intestinal IELs by applying SAGE to analyze gene expression in adult mouse and IELs (27). This is the first study that directly compared and T cells from the same anatomical location. Although the expression of several effector genes was high in both populations, the expression of conventional cytokines and cytokine receptors was low. The expression profiles of known genes did not clearly differentiate from IELs. This underscores the potential importance of signals in the tissue microenvironment in directing resting IELs, regardless of T cell type, into conformance and/or the impact of the isolation procedure in artificially reducing differentially expressed transcripts. A majority of the mRNAs that were differentially expressed between and IELs were unknown genes, whose eventual characterization may provide exciting new insight into differences in and IELs.

Both of these mouse studies analyzed IELs as one group and presented a phenotype for IELs that was both activated and resting. Two recent analyses from our laboratory suggest one possible reason for this mixed and seemingly opposing state of the IELs. We have analyzed circulating bovine T cells subsets, defined predominantly by expression of CD8, using cDNA microarrays and SAGE (28, 29). After high-speed cell sorting, both subsets were globally activated with either Con A and IL-2 (for array analysis) or PMA and ionomycin (for SAGE analysis) for 3–4 h prior to RNA extraction to re-establish mRNAs that were potentially down-regulated during the sorting process. The overriding conclusion from these studies was that the transcriptional activities of these two T cell subsets were very different, almost polar. The analyses of bovine T cell subsets indicated that while CD8^- T cells were activated, proliferative, and inflammatory, the CD8⁺ subset expressed genes consistent with quiescence, trafficking to the mucosa, and immune suppression. Both of these investigations also identified genes consistent with a proapoptotic trend in the CD8⁺ T cells and a resistance to apoptosis in the CD8^- T cells. The tendency of CD8⁺ T cells toward apoptosis and quiescence is consistent with a tissue-specific, anti-inflammatory "immune sentinel" phenotype, whereas resistance to apoptosis is consistent with the inflammatory nature of CD8^- T cells (30). Further, the microarray analysis of bovine T cell subsets (28) indicated that CD8⁺ T cells were sensitive to IFN and expressed lymphoid chemokines. The SAGE analysis of bovine T cell subsets (29) underscored their relationship to myeloid cells by their expression of genes such as CD14, CD68, scavenger receptor 1, and B lymphocyte-induced maturation protein (BLIMP-1). BLIMP-1 is a master regulator of B and myeloid cell differentiation that was also detected in the murine microarray analysis (26).

The obvious disadvantage of the studies with bovine cells is that the bovine genome is not completely sequenced. Thus, we relied on cross-reactivity in human cDNA arrays in the microarray analysis and incomplete identification of tags in the case of the SAGE investigation (28, 29). Genes that were not identified in these analyses may have been missed because of the lack of cross-reactivity or genomic sequence. Despite this disadvantage, not only were several of the same genes and trends identified in both of the bovine analyses, each study also revealed unique, differentially expressed genes, some of which were also identified in the murine studies.

Table I shows several genes that were identified in more than one of the recent genomic analyses of T cells and their relative expression levels within the various studies. Gene expression trends for these examples correlated well, despite different approaches and skepticism about reproducibility of genomics studies between laboratories. The bovine studies show that T cell subsets in circulation express many of the same genes as IELs in murine tissue. Specifically, there is overlap between the various studies in the expression of chemokines (RANTES) and macrophage inflammatory protein (MIP)1, cytokines (lymphotoxin), adhesion molecules (₇ integrin), cytokine receptors (IL-2R and CXCR4), signaling molecules (regulator of G protein signaling-1 and PIM-1), and transcription factors (BLIMP-1 and JunB), among other genes (Table I). Because the bovine cells were isolated from the blood whereas the mouse cells were isolated from the gut mucosa, this suggests that the tissue microenvironment may only be partially responsible for these gene expression profiles of the IELs.

View this table: [in this window] [in a new window]   Table I. Expression values for specific genes identified in more than one of the recent genomic investigations of T cellsa

	Preliminary studies on specific genes and gene expression patterns identified in or suggested by the genomic studies

Top Introduction Genomic approaches used in... Preliminary studies on specific... Future genomic analyses of... Summary References

 
A major goal of such genomic studies should be to suggest avenues for further detailed investigations. This includes careful analysis of the factors that control gene expression and the precise functional pathway of a given expressed protein in the context of the surrounding tissues and cells. One unexpected specific gene product of interest was the transcription factor BLIMP-1, which has previously been shown to be involved in B and myeloid cell differentiation (31, 32). BLIMP-1 was shown by two genomic studies to be expressed in T cells, in mouse IELs in the microarray analysis by Fahrer et al. (26) and in bovine CD8^- T cells by SAGE (29). In the investigation by Meissner et al. (29), BLIMP-1 expression in T cells was confirmed by quantitative real-time RT-PCR and RNase protection assays. BLIMP-1 expression in T cells is very intriguing. BLIMP-1 is known to suppress expression of c-Myc, MHC class II, and inhibitor of differentiation 3 (Id3) in B and myeloid cells (31). The expression of BLIMP-1 in CD8^- T cells is consistent with a higher level of MHC class II and Id3 expression in CD8⁺ T cells as compared to CD8^- T cells (28). The extensive functional activities of BLIMP-1, its role in driving B and myeloid cell differentiation, and its selective expression in a subset of T cells provide compelling reasons to study the potential role of this unique transcription factor in T cell differentiation.

A number of genes normally associated with myeloid cells were expressed in circulating T cells, including pathogen-associated molecular pattern (PAMP) receptors, such as CD14, scavenger receptor, and mannose-binding receptor (28, 29). This, combined with previous studies showing that T cells respond to microbial products, such as alkylamines and phosphoantigens (33), prompted us to extend these analyses to other PAMP receptors, most notably Toll-like receptors (TLRs). TLRs are the receptors for PAMPs, such as LPS and peptidoglycan, and are expressed on dendritic, myeloid, epithelial, and endothelial cells (34). The mRNAs encoding TLRs 2 and 4 have been demonstrated in murine T cells (35). We have now amplified TLR 2, 3, 4, and 5 transcripts from bovine T cell subsets by real-time RT-PCR and are studying the functions of these PAMP receptors. Thus, a general trend identified by genomic analyses has spurred a new course of investigation.

	Future genomic analyses of T cells

Top Introduction Genomic approaches used in... Preliminary studies on specific... Future genomic analyses of... Summary References

 
Though not intended to be comprehensive, below we outline three suggested areas of investigation using specific examples where additional genomic analyses might be useful in furthering our understanding of T cell biology. Comparisons of and T cells as well as different T cell subsets could be done in each of these settings.

Studies on the effect of activation on gene expression in T cells.

Activation states can alter the transcriptional profiles of immune cells. Although the issue of artifactual activation was a major concern in the two mouse studies, the probability that transcripts were down-regulated during tissue processing and cell isolation was not addressed. To overcome this potential problem, both subsets in the bovine studies were globally activated with either Con A/IL-2 or PMA and ionomycin prior to RNA extraction. Clearly, neither approach is an ideal reflection of the in vivo situation. We have preliminary evidence suggesting that mitogen activation affects various splenic T cell types differently. Our results suggest that upon global activation of both populations isolated from the bovine spleen, T cells become more dissimilar from T cells. Specifically, based on the analysis of >80,000 initial SAGE tags from resting and 6-h Con A/IL-2-activated splenic and T cells, the resting cells shared 81% of expressed genes whereas the activated and T cells shared only 66%. This difference was primarily based on a greater increase in T cell-specific genes (J. C. Graff and M. A. Jutila, manuscript in preparation). These preliminary studies suggest that understanding the progression of gene expression profiles during in vitro and, more importantly, in vivo activation of T cells derived from various anatomical sites will reveal novel signaling pathways and downstream responses unique to these cells.

Studies in infectious challenge models.

Further genomic comparisons of T cell transcriptional profiles during responses against relevant infectious agents are clearly necessary. To date, a majority of such "infectomics" studies has been performed on cultured T cells. Given the complexity of the tissue microenvironment in which T cells are frequently found, and the clear influence the microenvironment has on T cells, it is critical that these cells not be taken out of context, and that infection studies be conducted in vivo or directly ex vivo whenever possible. Subsets of T cells can contribute to protective immunity against a wide range of pathogens, including those that cause malaria and tuberculosis (36). T cells have also been shown to expand in the peripheral blood of human patients infected with many different pathogens, including salmonella, toxoplasma, and HIV (4). In cases where T cells decrease in peripheral blood, such as in Bordetella pertussis infection in children, they may traffic to the sites of infection and have an important role upon arrival (37). Many of these diseases are also of veterinary health relevance, such as salmonellosis, for which the ruminant is an excellent model, both from the perspective of the disease and in the availability of T cells. When genomics techniques are applied to various infection models, it is likely the distinct immunological functions of T cells or T cell subsets will begin to emerge.

Studies in noninfectious disease of the lung.

Although it is known that T cell populations can be altered in various situations of lung pathology, their precise function in asthma and other airway diseases is only now beginning to be revealed (38). T cells can prevent murine airway hyperresponsiveness by maintaining homeostasis in airway mucosa during inflammatory challenge (39). Conversely, distinct T cell subsets may actually promote allergic pulmonary inflammation (40, 41). T cells additionally have a clear importance in recovery from airway epithelial damage after ozone assault (42). The application of genomics techniques to T cells in studies of airway inflammation will likely provide many answers as to their precise mechanisms of protection. An excellent model for lung pathology (43) and a good source of T cells is the ovine model, which has likely been underutilized due to lack of specific reagents. However, we have recently demonstrated that use of ruminants is not an obstacle to the application of genomics techniques (28, 29). Regardless of species, genomics studies of lung T cells may provide new insight into their elusive roles in respiratory pathology and protection.

	Summary

Top Introduction Genomic approaches used in... Preliminary studies on specific... Future genomic analyses of... Summary References

 
It has been repeatedly shown that the functions of and T cells are not completely redundant, and given the strong evolutionary conservation of T cells, their function is surely unique. These distinctions will likely emerge through genomic investigations following specific stimuli, such as infection, that are likely to influence T cell subsets differently. Furthermore, expression of individual genes analyzed using less comprehensive techniques are likely to be less conserved than are the more global patterns and trends discerned from genomic analyses, as the investigations discussed herein have demonstrated. A major argument against genomics techniques is that the approach is not hypothesis-driven. However, for a rare, ancient, and functionally elusive cell population such as T cells, there is insufficient data to begin to make assumptions about their transcriptional profiles in various situations. Indeed, much of the genomics data uncover novel and unexpected genes and pathways. Thus, genomics techniques are ideal tools that result in more focused and directed hypotheses with which to approach T cells in various anatomical sites and infection models.

	Acknowledgments

 
We thank Drs. Willi Born and Mark Quinn for critical review and several helpful suggestions.

	Footnotes

 
¹ This work was supported by U.S. Department of Agriculture Initiative for Future Agriculture and Food Systems Grant 2000-04446.

² Address correspondence and reprint requests to Dr. Mark A. Jutila, Veterinary Molecular Biology, Montana State University, Bozeman, MT 59718. E-mail address: uvsmj{at}montana.edu

³ Abbreviations used in this paper: IEL, intraepithelial lymphocyte; SAGE, serial analysis of gene expression; BLIMP-1, B lymphocyte-induced maturation protein; PAMP, pathogen-associated molecular pattern; TLR, Toll-like receptor.

Received for publication May 30, 2003. Accepted for publication August 8, 2003.

	References

Top Introduction Genomic approaches used in... Preliminary studies on specific... Future genomic analyses of... Summary References

 

1. Richards, M. H., J. L. Nelson. 2000. The evolution of vertebrate antigen receptors: a phylogenetic approach. Mol. Biol. Evol. 17:146.[Abstract/Free Full Text]
2. Hayday, A. C.. 2000. Cells: a right time and a right place for a conserved third way of protection. Annu. Rev. Immunol. 18:975.[Medline]
3. Hein, W. R., C. R. Mackay. 1991. Prominence of T cells in the ruminant immune system. Immunol. Today 12:30.[Medline]
4. Bukowski, J. F., C. T. Morita, M. B. Brenner. 1999. Human T cells recognize alkylamines derived from microbes, edible plants, and tea: implications for innate immunity. Immunity 11:57.[Medline]
5. Ferrick, D. A., D. P. King, K. A. Jackson, R. K. Braun, S. Tam, D. M. Hyde, B. L. Beaman. 2000. Intraepithelial T lymphocytes: sentinel cells at mucosal barriers. Springer Semin. Immunopathol. 22:283.[Medline]
6. Constant, P., F. Davodeau, M. A. Peyrat, Y. Poquet, G. Puzo, M. Bonneville, J. J. Fournie. 1994. Stimulation of human T cells by nonpeptide mycobacterial ligands. Science 264:267.[Abstract/Free Full Text]
7. O’Brien, R. L., X. Yin, S. A. Huber, K. Ikuta, W. K. Born. 2000. Depletion of a T cell subset can increase host resistance to a bacterial infection. J. Immunol. 165:6472.[Abstract/Free Full Text]
8. O’Brien, R. L., M. Lahn, W. K. Born, S. A. Huber. 2001. T cell receptor and function cosegregate in T cell subsets. Chem. Immunol. 79:1.[Medline]
9. Huber, S. A., D. Graveline, M. K. Newell, W. K. Born, R. L. O’Brien. 2000. V1⁺ T cells suppress and V4⁺ T cells promote susceptibility to coxsackievirus B3-induced myocarditis in mice. J. Immunol. 165:4174.[Abstract/Free Full Text]
10. Wilson, E., B. Walcheck, W. C. Davis, M. A. Jutila. 1998. Preferential tissue localization of bovine T cell subsets defined by anti-T cell receptor for antigen antibodies. Immunol. Lett. 64:39.[Medline]
11. Rocha, B., P. Vassalli, D. Guy-Grand. 1994. Thymic and extrathymic origins of gut intraepithelial lymphocyte populations in mice. J. Exp. Med. 180:681.[Abstract/Free Full Text]
12. Wilson, E., M. K. Aydintug, M. A. Jutila. 1999. A circulating bovine T cell subset, which is found in large numbers in the spleen, accumulates inefficiently in an artificial site of inflammation: correlation with lack of expression of E-selectin ligands and L-selectin. J. Immunol. 162:4914.[Abstract/Free Full Text]
13. Gerber, D. J., V. Azuara, J. P. Levraud, S. Y. Huang, M. P. Lembezat, P. Pereira. 1999. IL-4-producing T cells that express a very restricted TCR repertoire are preferentially localized in liver and spleen. J. Immunol. 163:3076.[Abstract/Free Full Text]
14. Lefrancois, L.. 1991. Phenotypic complexity of intraepithelial lymphocytes of the small intestine. J. Immunol. 147:1746.[Abstract]
15. Wilson, E., J. F. Hedges, E. C. Butcher, M. A. Jutila. 2002. Bovine T cell subsets express different patterns of chemokine responsiveness and adhesion molecules: a mechanism for tissue specific T cell subset accumulation. J. Immunol. 169:4970.[Abstract/Free Full Text]
16. Abrahamsen, M. S., C. A. Lancto, B. Walcheck, W. Layton, M. A. Jutila. 1997. Localization of and T lymphocytes in Cryptosporidium parvum-infected tissues in naive and immune calves. Infect. Immun. 65:2428.[Abstract]
17. Lahn, M., A. Kanehiro, K. Takeda, J. Terry, Y. S. Hahn, M. K. Aydintug, A. Konowal, K. Ikuta, R. L. O’Brien, E. W. Gelfand, W. K. Born. 2002. MHC class I-dependent V4⁺ pulmonary T cells regulate T cell-independent airway response. Proc. Natl. Acad. Sci. USA 99:8850.[Abstract/Free Full Text]
18. Wang, H., H. K. Lee, J. F. Bukowski, H. Li, R. A. Mariuzza, Z. W. Chen, K. H. Nam, C. T. Morita. 2003. Conservation of nonpeptide antigen recognition by rhesus monkey V2V2 T cells. J. Immunol. 170:3696.[Abstract/Free Full Text]
19. Hayday, A., E. Theodoridis, E. Ramsburg, J. Shires. 2001. Intraepithelial lymphocytes: exploring the Third Way in immunology. Nat. Immunol. 2:997.[Medline]
20. Aujame, L., N. Burdin, M. Vicari. 2002. How microarrays can improve our understanding of immune responses and vaccine development. Ann. NY Acad. Sci. 975:1.[Medline]
21. Chtanova, T., R. A. Kemp, A. P. Sutherland, F. Ronchese, C. R. Mackay. 2001. Gene microarrays reveal extensive differential gene expression in both CD4⁺ and CD8⁺ type 1 and type 2 T cells. J. Immunol. 167:3057.[Abstract/Free Full Text]
22. Teague, T. K., D. Hildeman, R. M. Kedl, T. Mitchell, W. Rees, B. C. Shaefer, J. Bender, J. Kappler, P. Marrack. 1999. Activation changes the spectrum but not the diversity of genes expressed by T cells. Proc. Natl. Acad. Sci. USA 96:12691.[Abstract/Free Full Text]
23. Rogge, L., E. Bianchi, M. Biffi, E. Bono, S. Y. P. Chang, H. Alexander, C. Santini, G. Ferrari, L. Sinigaglia, M. Seiler, et al 2000. Transcript imaging of the development of human T helper cells using oligonucleotide arrays. Nat. Genet. 25:96.[Medline]
24. Velculescu, V. E., L. Zhang, B. Vogelstein, K. W. Kinzler. 1995. Serial analysis of gene expression. Science 270:484.[Abstract/Free Full Text]
25. Saha, S., A. B. Sparks, C. Rago, V. Akmaev, C. J. Wang, B. Vogelstein, K. W. Kinzler, V. E. Velculescu. 2002. Using the transcriptome to annotate the genome. Nat. Biotechnol. 20:508.[Medline]
26. Fahrer, A. M., Y. Konigshofer, E. M. Kerr, G. Ghandour, D. H. Mack, M. M. Davis, Y. H. Chien. 2001. Attributes of intraepithelial lymphocytes as suggested by their transcriptional profile. Proc. Natl. Acad. Sci. USA 98:10261.[Abstract/Free Full Text]
27. Shires, J., E. Theodoridis, A. C. Hayday. 2001. Biological insights into TCR⁺ and TCR⁺ intraepithelial lymphocytes provided by serial analysis of gene expression (SAGE). Immunity 15:419.[Medline]
28. Hedges, J. F., D. Cockrell, L. Jackiw, N. Meissner, M. A. Jutila. 2003. Differential mRNA expression in circulating T lymphocyte subsets defines unique tissue-specific functions. J. Leukocyte Biol. 73:306.[Abstract/Free Full Text]
29. Meissner, N., J. Radke, J. F. Hedges, M. White, M. Behnke, S. Bertolino, M. S. Abrahamsen, M. A. Jutila. 2003. Comparative gene expression analysis in circulating T-cell subsets defines distinct immunoregulatory phenotypes and reveals their relationship to myeloid cells. J. Immunol. 170:356.[Abstract/Free Full Text]
30. Neurath, M. F., S. Finotto, I. Fuss, M. Boirivant, P. R. Galle, W. Strober. 2001. Regulation of T-cell apoptosis in inflammatory bowel disease: to die or not to die, that is the mucosal question. Trends Immunol. 22:21.[Medline]
31. Shaffer, A. L., K. I. Lin, T. C. Kuo, X. Yu, E. M. Hurt, A. Rosenwald, J. M. Giltnane, L. Yang, H. Zhao, K. Calame, L. M. Staudt. 2002. Blimp-1 orchestrates plasma cell differentiation by extinguishing the mature B cell gene expression program. Immunity 17:51.[Medline]
32. Chang, D. H., C. Angelin-Duclos, K. Calame. 2000. BLIMP-1: trigger for differentiation of myeloid lineage. Nat. Immunol. 1:169.[Medline]
33. Sireci, G., E. Espinosa, C. Di Sano, F. Dieli, J. J. Fournie, A. Salerno. 2001. Differential activation of human cells by nonpeptide phosphoantigens. Eur. J. Immunol. 31:1628.[Medline]
34. Muzio, M., N. Polentarutti, D. Bosisio, M. K. P. Prahlanan, A. Mantovani. 2000. Toll-like receptors: a growing family of immune receptors that are differentially expressed and regulated by different leukocytes. J. Leukocyte Biol. 67:450.[Abstract]
35. Mokuno, Y., T. Matsuguchi, M. Takano, H. Nishimura, J. Washizu, T. Ogawa, O. Takeuchi, S. Akira, Y. Nimura, Y. Yoshikai. 2000. Expression of Toll-like receptor 2 on T cells bearing invariant V 6/V 1 induced by Escherichia coli infection in mice. J. Immunol. 165:931.[Abstract/Free Full Text]
36. Dieli, F., M. Troye-Blomberg, S. E. Farouk, G. Sireci, A. Salerno. 2001. Biology of T cells in tuberculosis and malaria. Curr. Mol. Med. 4:446.
37. Bertotto, A., F. De Benedictis, C. Vagliasindi, M. Radicioni, F. Spinozzi, G. M. Fabietti, G. Castellucci, L. Ferraro, R. Cozzali, A. Niccoli, R. Vaccaro. 1997. T cells are decreased in the blood of children with Bordetella pertussis infection. Acta Paediatr. 86:114.[Medline]
38. Lahn, M.. 2000. The role of T cells in the airways. J. Mol. Med. 78:409.[Medline]
39. Lahn, M., A. Kanehiro, K. Takeda, A. Joetham, J. Schwarze, G. Kohler, R. O’Brien, E. W. Gelfand, W. Born. 1999. Negative regulation of airway responsiveness that is dependent on T cells and independent of T cells. Nat. Med. 5:1150.[Medline]
40. Zuany-Amorim, C., C. Ruffie, S. Haile, B. B. Vargaftig, P. Pereira, M. Pretolani. 1998. Requirement for T cells in allergic airway inflammation. Science 280:1265.[Abstract/Free Full Text]
41. Svensson, L., B. Lilliehöök, R. Larsson, A. Ucht. 2003. T cells contribute to the systemic immunoglobulin E response and local B-cell reactivity in allergic eosinophilic airway inflammation. Immunology 108:98.[Medline]
42. King, D. P., D. M. Hyde, K. A. Jackson, D. M. Novosad, T. N. Ellis, L. Putney, M. Y. Stovall, L. S. Van Winkle, B. L. Beaman, D. A. Ferrick. 1999. Cutting edge: protective response to pulmonary injury requires T lymphocytes. J. Immunol. 162:5033.[Abstract/Free Full Text]
43. Harris, A.. 1997. Towards an ovine model of cystic fibrosis. Hum. Mol. Genet. 6:2191.[Free Full Text]

This article has been cited by other articles:

				J. C. Graff, M. Behnke, J. Radke, M. White, and M. A. Jutila A comprehensive SAGE database for the analysis of {gamma}{delta} T cells Int. Immunol., April 1, 2006; 18(4): 613 - 626. [Abstract] [Full Text] [PDF]

This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hedges, J. F. Articles by Jutila, M. A. Search for Related Content PubMed PubMed Citation Articles by Hedges, J. F. Articles by Jutila, M. A.