PubMed Health⌕ Search

Biomedical subjects

James W Tung

Publications and source records attributed to James W Tung.

7 recordsLinked to original sources
PubMed2006

CD72 down-modulates BCR-induced signal transduction and diminishes survival in primary mature B lymphocytes.

CD72, a 45-kDa type II transmembrane glycoprotein carrying an ITIM motif, is believed to be an inhibitory coreceptor of the BCR. Mature B cells lacking CD72 show enhanced Ca(2+) mobilization and are hyperproliferative in response to BCR ligation. However, the signal transduction pathways downstream of BCR signaling that transmit the inhibitory effect of CD72 in mature B cells remain unknown. To address this question, we used hen egg lysozyme-specific BCR transgenic mice to elucidate the differential cell signaling between wild-type and CD72-deficient B cells in response to hen egg lysozyme Ag stimulation. Our results demonstrate that CD72 predominantly down-regulates the major signal transduction pathways downstream of the BCR, including NF-AT, NF-kappaB, ERK, JNK, p38-MAPK, and PI3K/Akt in mature B cells. CD72 ligation with anti-CD72 Ab (K10.6), which mimics the binding of CD100 (a natural ligand for CD72) to release the inhibitory function of CD72, augments cell proliferation, Ca(2+) flux, IkappaBalpha activation, and ERK MAPK activity upon Ag stimulation in wild-type B cells. In addition, we show direct evidence that CD72 promotes cell cycle arrest and apoptosis after Ag stimulation in mature B cells. Taken together, our findings conclude that CD72 plays a dominant role as a negative regulator of BCR signaling in primary mature B lymphocytes.

Animals↗
PubMed2006

Phenotypically distinct B cell development pathways map to the three B cell lineages in the mouse.

A recent article by Montecino-Rodriguez et al. [Montecino-Rodriguez, E., Leathers, H. & Dorshkind, K. (2006) Nat. Immunol.7, 293-301] has distinguished the early progenitors for B-1 cells, which principally develop in neonates, from early progenitors for B-2 cells, which principally develop in adult bone marrow. Here we introduce syndecan-1 (CD138) and MHC class II (I-A) as markers of early B cell development [Hardy, R. R., Carmack, C. E., Shinton, S. A., Kemp, J. D. & Hayakawa, K. (1991) J. Exp. Med. 173, 1213-1225; Hardy fractions B-D] and show that the expression of these markers distinguishes the predominant B cell development pathway in neonates from the corresponding predominant pathway in adults (both progenitors are present but differently represented in each case). We show that pre-B cells (Hardy fraction D) in the predominant adult pathway express high levels of CD138 and intermediate levels of I-A, whereas the corresponding pre-B cells in the pathway that predominates in neonates do not express either of these markers. As expected, because most of the pre-B cells in adults express CD138, we find that sorted CD138+ adult pre-B cells differentiate to IgM+ B cells in vitro. Sorted CD138- pre-B cells from neonates, the majority subset at this age, also mature to IgM+ cells (without passing through a CD138+ stage). Importantly, our studies here confirm the differential representation of adult and neonatal progenitor populations and further demonstrate that CD138 expression subdivides the adult CD19+, B220-6B2-/low population shown to contain B-1 progenitors in a way consistent with the predominance of B-1b progenitors in adults. Thus, CD138 expression provides a key route to distinguishing early B cell development pathway for what now are clearly three B cell lineages.

Animals↗
PubMed2005

Inherent specificities in natural antibodies: a key to immune defense against pathogen invasion.

Natural antibodies are produced at tightly regulated levels in the complete absence of external antigenic stimulation. They provide immediate, early and broad protection against pathogens, making them a crucial non-redundant component of the humoral immune system. These antibodies are produced mainly, if not exclusively, by a subset of long-lived, self-replenishing B cells termed B-1 cells. We argue here that the unique developmental pattern of these B-1 cells, which rests on positive selection by self antigens, ensures production of natural antibodies expressing evolutionarily important specificities that are required for the initial defense against invading pathogens. Positive selection for reactivity with self antigens could also result in the production of detrimental anti-self antibodies. However, B-1 cells have evolved a unique response pattern that minimizes the risk of autoimmunity. Although these cells respond rapidly and strongly to host-derived innate signals, such as cytokines, and to pathogen-encoded signals, such as lipopolysaccharide and phosphorylcholine, they respond very poorly to receptor-mediated activation. In addition, they rarely enter germinal centers and undergo affinity maturation. Thus, their potential for producing high-affinity antibodies with harmful anti-self specificity is highly restricted. The positive selection of B-1 cells occurs during the neonatal period, during which the long-lived self-renewing B-1 population is constituted. Many of these cells (B-1a) express CD5, although a smaller subset (B-1b) does not express this surface marker. Importantly, B-1a cells should not be confused with short-lived anergic B-2 cells, which originate in the bone marrow in adults and initiate CD5 expression and programmed cell death following self-antigen recognition. In summary, we argue here that the mechanisms that enable natural antibody production by B-1 cells reflect the humoral immune system, which has evolved in layers whose distinct developmental mechanisms generate complementary repertoires that collectively operate to maximize flexibility in responses to invading pathogens. B-2 cells, present in what may be the most highly evolved layer(s), express a repertoire that is explicitly selected against self recognition and directed towards the generation of high-affinity antibody response to external antigenic stimuli. B-1 cells, whose repertoire is selected by recognition of self antigen, belong to what may be earlier layer(s) and inherently maintain production of evolutionarily important antibody specificities that respond to pathogen-related, rather then antigen-specific signals.

Animals↗
PubMed2004

The E47 transcription factor negatively regulates CD5 expression during thymocyte development.

The expression of CD5 increases progressively as thymocytes mature. We have shown that CD5 expression is controlled by a tissue-specific regulatory promoter located upstream of the CD5 translation start sites. Deletion of this regulatory promoter, which contains three potential transcription factor binding sites (CCAAT, kappa E2, and ets) reduces the promoter activity to basal level. Of these sites, only ets proved essential for CD5 expression in T cell lines. Here, we introduce a role for the E47 transcription factor and the CD5 promoter kappa E2 site in regulating CD5 expression during thymocyte development. Using T cell lines, we show that (i) mutation of the kappa E2 site in the CD5 regulatory promoter results in a significant elevation of CD5 promoter activity; (ii) the E47 transcription factor binds to the kappa E2 site; and (iii) overexpression of E47 inhibits CD5 expression. We then show, in high-dimensional fluorescence-activated cell sorting studies with primary thymocytes at successive developmental stages, that (i) intracellular E47 levels decrease as surface CD5 expression increases; (ii) E47 expression is down-regulated and CD5 expression is correspondingly up-regulated in DN3 thymocytes in RAG-2-deficient mice injected with anti-CD3 to mimic pre-T cell receptor stimulation; and (iii) E47 expression is down-regulated and CD5 expression is up-regulated when double positive thymocytes are stimulated in vitro with anti-CD3. Based on these data, we propose that E47 negatively regulates CD5 expression by interacting with the kappa E2 site in the CD5 regulatory promoter and that decreases in E47 in response to developmental signals are critical to the progressive increase in CD5 expression as thymocytes mature.

Animals↗
PubMed2004

New approaches to fluorescence compensation and visualization of FACS data.

The Fluorescence Activated Cell Sorter (FACS) is an invaluable tool for clinicians and researchers alike in phenotyping and sorting individual cells. With the advances in FACS methodology, notably intracellular staining for cytokines, transcription factors and phosphoproteins, and with increases in the number of fluorescence detection channels, researchers now have the opportunity to study individual cells in far greater detail than previously possible. In this chapter, we discuss High-Definition (Hi-D) FACS methods that can improve analysis of lymphocyte subsets in mouse and man. We focus on the reasons why fluorescence compensation, which is necessary to correct for spectral overlap between two or more fluorochromes used in the same staining combination, is best done as a computed transformation rather than using the analog circuitry available on many flow cytometers. In addition, we introduce a new data visualization method that scales the axes on histograms and two-dimensional contour (or dot) plots to enable visualization of signals from all cells, including those that have minimal fluorescence values and are not properly represented with traditional logarithmic axes. This "Logicle" visualization method, we show, provides superior representations of compensated data and makes correctly compensated data look correct. Finally, we discuss controls that facilitate recognition of boundaries between positive and negative subsets.

Animals↗
PubMed2004

Identification of B-cell subsets: an exposition of 11-color (Hi-D) FACS methods.

In the last few years, the effectiveness of developmental and functional studies of individual subsets of cells has increased dramatically owing to the identification of additional subset markers and the extension of fluorescence-activated cell sorter (FACS) capabilities to simultaneously measure the expression of more markers on individual cells. For example, introduction of a 6-8 multiparameter FACS instrument resulted in significant advances in understanding B-cell development. In this chapter, we describe 11-color high-dimensional (Hi-D) FACS staining and data analysis methods that provide greater clarity in identifying the B-cell subsets in bone marrow, spleen, and peritoneal cavity. Further, we show how a single Hi-D FACS antibody reagent combination is sufficient to unambiguously identify most of the currently defined B-cell developmental subsets in the bone marrow (Hardy fractions A-F) and the functional B-cell subsets (B-1a, B-1b, B-2, and marginal zone [MZ] B cells) in the periphery. Although we focus on murine B-cell subsets, the methods we discuss are relevant to FACS studies conducted with all types of cells and other FACS instruments. We introduce a new method for scaling axes for histograms or contour plots of FACS data. This method, which we refer to as Logicle visualization, is particularly useful in promoting correct interpretations of fluorescence-compensated FACS data and visual confirmation of correct compensation values. In addition, it facilitates discrimination of valid subsets. Application of Logicle visualization tools in the Hi-D FACS studies discussed here creates a strong new base for in-depth analysis of B-cell development and function.

Animals↗