Interleukin 2 transcription factors as molecular targets of cAMP inhibition: delayed inhibition kinetics and combinatorial transcription roles

Elevation of cAMP can cause gene-specific inhibition of interleukin 2 (IL-2) expression. To investigate the mechanism of this effect, we have combined electrophoretic mobility shift assays and in vivo genomic footprinting to assess both the availability of putative IL-2 transcription factors in forskolin-treated cells and the functional capacity of these factors to engage their sites in vivo. All observed effects of forskolin depended upon protein kinase A, for they were blocked by introduction of a dominant negative mutant subunit of protein kinase A. In the EL4.E1 cell line, we report specific inhibitory effects of cAMP elevation both on NF-κB/Rel family factors binding at -200 bp, and on a novel, biochemically distinct "TGGGC" factor binding at -225 bp with respect to the IL-2 transcriptional start site. Neither NF-AT nor AP-1 binding activities are detectably inhibited in gel mobility shift assays. Elevation of cAMP inhibits NF-κB activity with delayed kinetics in association with a delayed inhibition of IL-2 RNA accumulation. Activation of cells in the presence of forskolin prevents the maintenance of stable protein-DNA interactions in vivo, not only at the NF-κB and TGGGC sites of the IL-2 enhancer, but also at the NF-AT, AP-1, and other sites. This result, and similar results in cyclosporin A-treated cells, imply that individual IL-2 transcription factors cannot stably bind their target sequences in vivo without coengagement of all other distinct factors at neighboring sites. It is proposed that nonhierarchical, cooperative enhancement of binding is a structural basis of combinatorial transcription factor action at the IL-2 locus

GATA-3 locks the door to the B-cell option

T-cell early developmental stages and alternative options: GATA-3 is depicted as an intrathymically induced, specific inhibitor of access to the B-lineage pathway. Recognized stages in early intrathymic T-cell development are shown, along with the degrees of access to the B-cell program and other alternative programs that the cells can demonstrate at these stages if the extrinsic barrier of Notch/Dll4 signaling (red line) is removed. Red bricks represent GATA-3 when expressed at critical levels, and purple bricks represent other T-lineage commitment factors (eg, Bcl11b) that are activated later. Not shown are the positive roles of GATA-3 that permit the efficient generation of DN2 cells. Full commitment is complete by the DN2b stage

T Cell Lineage Commitment: Identity and Renunciation

Precursors undertaking T cell development shed their access to other pathways in a sequential process that begins before entry into the thymus and continues through many cell cycles afterward. This process involves three levels of regulatory change, in which the cells' intrinsic transcriptional regulatory factors, expression of signaling receptors (e.g., Notch1), and expression of distinct homing receptors separately contribute to confirmation of T cell identity. Each alternative potential has a different underlying molecular basis that is neutralized and then permanently silenced through different mechanisms in early T cell precursors. This regulatory mosaic has notable implications for the hierarchy of relationships linking T lymphocytes to other hematopoietic fates

Fitting structure to function in gene regulatory networks

Cascades of transcriptional regulation are the common source of the forward drive in all developmental systems. Increases in complexity and specificity of gene expression at successive stages are based on the collaboration of varied combinations of transcription factors already expressed in the cells to turn on new genes, and the logical relationships between the transcription factors acting and becoming newly expressed from stage to stage are best visualized as gene regulatory networks. However, gene regulatory networks used in different developmental contexts underlie processes that actually operate through different sets of rules, which affect the kinetics, synchronicity, and logical properties of individual network nodes. Contrasting early embryonic development in flies and sea urchins with adult mammalian hematopoietic development from stem cells, major differences are seen in transcription factor dosage dependence, the silencing or damping impacts of repression, and the impact of cellular regulatory history on the parts of the genome that are accessible to transcription factor action in a given cell type. These different features not only affect the kinds of models that can illuminate developmental mechanisms in the respective biological systems, but also reflect the evolutionary needs of these biological systems to optimize different aspects of development

Immune Cell Identity: Perspective from a Palimpsest

The immune system in mammals is composed of multiple different immune cell types that migrate through the body and are made continuously throughout life. Lymphocytes and myeloid cells interact with each other and depend upon each other, but each are highly diverse and specialized for different roles. Lymphocytes uniquely require developmentally programmed mutational changes in the genome itself for their maturation. Despite profound differences between their mechanisms of threat recognition and threat response, however, the developmental origins of lymphocytes and myeloid cells are interlinked, and important aspects of their response mechanisms remain shared. It is notable that the chain of logic toward our current understanding of the immune defense system over the past 50 years has been driven by strongly posited models that have led to crucial discoveries, even though these models ended up being partly wrong. The predictive strength of these models and their success as guides to incisive experimental research have illuminated the limits of each model’s explanatory scope, beyond which another model needed to assume the lead. This brief review describes how a succession of distinct paradigms has helped to clarify a sophisticated picture of immune cell generation and control

Lineage determination in the immune system

Underlying all immune responses are the developmental programs that give immune cells their identities. Developmental controls determine the kinds of effector mechanisms that are available to different classes of cells, the degree of amplification that they can achieve through clonal expansion, the signals that they will respond to, and the limits that will be set on their abilities to alter function in different environmental conditions. As all these cell types are ultimately derived from common hematopoietic precursors, they each become distinct from other cell types at developmental choice points that define a time course of branching lineage relationships. This volume showcases striking new advances that illuminate the mechanisms governing several particularly interesting choice points where divergent immune cell identities are established

Eric Davidson: Steps to A Gene Regulatory Network for Development

Eric Harris Davidson was a unique and creative intellectual force who grappled with the diversity of developmental processes used by animal embryos and wrestled them into an intelligible set of principles, then spent his life translating these process elements into molecularly definable terms through the architecture of gene regulatory networks. He took speculative risks in his theoretical writing but ran a highly organized, rigorous experimental program that yielded an unprecedentedly full characterization of a developing organism. His writings created logical order and a framework for mechanism from the complex phenomena at the heart of advanced multicellular organism development. This is a reminiscence of intellectual currents in his work as observed by the author through the last 30-35 years of Davidson's life

Transcriptional Control of Early T and B Cell Developmental Choices

T and B cells share a common somatic gene rearrangement mechanism for assembling the genes that code for their antigen receptors; they also have developmental pathways with many parallels. Shared usage of basic helixloop- helix E proteins as transcriptional drivers underlies these common features. However, the transcription factor networks in which these E proteins are embedded are different both in membership and in architecture for T and B cell gene regulatory programs. These differences permit lineage commitment decisions to be made in different hierarchical orders. Furthermore, in contrast to B cell gene networks, the T cell gene network architecture for effector differentiation is sufficiently modular so that E protein inputs can be removed. Complete T cell–like effector differentiation can proceed without T cell receptor rearrangement or selection when E proteins are neutralized, yielding natural killer and other innate lymphoid cells

Spontaneous Expression of Interleukin-2 In Vivo in Specific Tissues of Young Mice

In situ hybridization and immunohistochemistry were used to determine the spectrum of tissues in which interleukin-2 (IL-2) mRNA and protein are found in healthy, normal young mice. In neonatal animals, IL-2 is expressed specifically by distinct, isolated cells at three major sites: the thymus, skin, and gut. Based on morphology and distribution, the IL-2-expressing cells resemble CD3ε + T cells that are also present in all these locations. Within the thymus of postweanling animals, both TcRαβ and TcRγδ lineage cells secrete "haloes" of the cytokine that diffuse over many cell diameters. Within the skin, isolated cells expressing IL-2 are seen at birth in the mesenchyme, and large numbers of IL-2-expressing cells are localized around hair follicles in the epidermis in 3-week-old animals. At this age, a substantial subset of CD3ε + cells is similarly localized in the skin. Significantly, by 5 weeks of age and later when the CD3ε + cells are evenly distributed throughout the epidermis, IL-2 RNA and protein expression are no longer detectable. Finally, within the intestine, IL-2 protein is first detected in association with a few discrete, isolated cells at day 16 of gestation and the number of IL-2 reactive cells increases in frequency through El9 and remains abundant in adult life. In postnatal animals, the frequency of IL- 2-positive cells in villi exceeds by greater than fivefold that found in mesenteric lymph node or Peyer's patches. Overall, these temporal and spatial patterns of expression provide insight into the regulation of IL-2 in vivo and suggest a role for IL-2 expression distinct from immunological responses to antigen

Encounters across networks: Windows into principles of genomic regulation

Gene regulatory networks account for the ability of the genome to program development in complex multi-cellular organisms. Such networks are based on principles of gene regulation by combinations of transcription factors that bind to specific cis-regulatory DNA sites to activate transcription. These cis-regulatory regions mediate logic processing at each network node, enabling progressive increases in organismal complexity with development. Gene regulatory network explanations of development have been shown to account for patterning and cell type diversification in fly and sea urchin embryonic systems, where networks are characterized by fast coupling between transcriptional inputs and changes in target gene transcription rates, and crucial cis-regulatory elements are concentrated relatively close to the protein coding sequences of the target genes, thus facilitating their identification. Stem cell-based development in post-embryonic mammalian systems also depends on gene networks, but differs from the fly and sea urchin systems. First, the number of regulatory elements per gene and the distances between regulatory elements and the genes they control are considerably larger, forcing searches via genome-wide transcription factor binding surveys rather than functional assays. Second, the intrinsic timing of network state transitions can be slowed considerably by the need to undo stem-cell chromatin configurations, which presumably add stability to stem-cell states but retard responses to transcription factor changes during differentiation. The dispersed, partially redundant cis-regulatory systems controlling gene expression and the slow state transition kinetics in these systems already reveal new insights and opportunities to extend understanding of the repertoire of gene networks and regulatory system logic