Decision by committee: new light on the CD4/CD8-lineage choice

Understanding transcriptional regulatory networks using computational models

Transcriptional regulatory networks (TRNs) encode instructions for animal development and physiological responses. Recent advances in genomic technologies and computational modeling have revolutionized our ability to construct models of TRNs. Here, we survey current computational methods for inferring TRN models using genome-scale data. We discuss their advantages and limitations. We summarize representative TRNs constructed using genome-scale data in both normal and disease development. We discuss lessons learned about the structure/function relationship of TRNs, based on examining various large-scale TRN models. Finally, we outline some open questions regarding TRNs, including how to improve model accuracy by integrating complementary data types, how to infer condition-specific TRNs, and how to compare TRNs across conditions and species in order to understand their structure/function relationship.

TCF-1 and LEF-1 act upstream of Th-POK to promote the CD4(+) T cell fate and interact with Runx3 to silence Cd4 in CD8(+) T cells

The transcription factors TCF-1 and LEF-1 are essential for early T cell development, but their roles beyond the CD4(+)CD8(+) double-positive (DP) stage are unknown. By specific ablation of these factors in DP thymocytes, we demonstrated that deficiency in TCF-1 and LEF-1 diminished the output of CD4(+) T cells and redirected CD4(+) T cells to a CD8(+) T cell fate. The role of TCF-1 and LEF-1 in the CD4-versus-CD8 lineage 'choice' was mediated in part by direct positive regulation of the transcription factor Th-POK. Furthermore, loss of TCF-1 and LEF-1 unexpectedly caused derepression of CD4 expression in T cells committed to the CD8(+) lineage without affecting the expression of Runx transcription factors. Instead, TCF-1 physically interacted with Runx3 to cooperatively silence Cd4. Thus, TCF-1 and LEF-1 adopted distinct genetic 'wiring' to promote the CD4(+) T cell fate and establish CD8(+) T cell identity.

Emerging properties of animal gene regulatory networks

Gene regulatory networks (GRNs) provide system level explanations of developmental and physiological functions in the terms of the genomic regulatory code. Depending on their developmental functions, GRNs differ in their degree of hierarchy, and also in the types of modular sub-circuit of which they are composed, although there is a commonly employed sub-circuit repertoire. Mathematical modelling of some types of GRN sub-circuit has deepened biological understanding of the functions they mediate. The structural organization of various kinds of GRN reflects their roles in the life process, and causally illuminates both developmental and evolutionary process.

A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis

Background

Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls.

Methodology/Principal Findings

We have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expressed (or differentially co-expressed) in cases and controls (e.g., V$KROX_Q6, p-value <3.31E-6; V$CREBP1_Q2, p-value <9.93E-6, V$YY1_02, p-value <1.65E-5).

Conclusions/Significance

Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. The most significant transcription factor motifs were for the Early Growth Response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families. These transcription factors are involved in early T-lymphocyte specification and commitment as well as in oligodendrocyte dedifferentiation and development, both pathways that have significant biological plausibility in MS causation.

Bcl11b represses a mature T-cell gene expression program in immature CD4(+)CD8(+) thymocytes

Bcl11b is a transcription factor that, within the hematopoietic system, is expressed specifically in T cells. Although Bcl11b is required for T-cell differentiation in newborn Bcl11b-null mice, and for positive selection in the adult thymus of mice bearing a T-cell-targeted deletion, the gene network regulated by Bcl11b in T cells is unclear. We report herein that Bcl11b is a bifunctional transcriptional regulator, which is required for the correct expression of approximately 1000 genes in CD4(+)CD8(+)CD3(lo) double-positive (DP) thymocytes. Bcl11b-deficient DP cells displayed a gene expression program associated with mature CD4(+)CD8(-) and CD4(-)CD8(+) single-positive (SP) thymocytes, including upregulation of key transcriptional regulators, such as Zbtb7b and Runx3. Bcl11b interacted with regulatory regions of many dysregulated genes, suggesting a direct role in the transcriptional regulation of these genes. However, inappropriate expression of lineage-associated genes did not result in enhanced differentiation, as deletion of Bcl11b in DP cells prevented development of SP thymocytes, and that of canonical NKT cells. These data establish Bcl11b as a crucial transcriptional regulator in thymocytes, in which Bcl11b functions to prevent the premature expression of genes fundamental to the SP and NKT cell differentiation programs.

Itk derived signals regulate the expression of Th-POK and controls the development of CD4 T cells

T cell development is critically dependent on both the environment and signals delivered by the T cell Receptor (TCR). The Tec family kinase Itk has been suggested to be an amplifier of signals emanating from the TCR and the loss of Itk partially affects most stages of thymopoiesis. Loss of Itk also differentially affects the development of conventional vs. non-conventional or innate memory phenotype T cells. Here, we examine whether these lineage choices are affected by a combination of TCR affinity and Itk by analyzing mice lacking Itk and carrying two TCR transgenes with differing affinities, OT-II and DO11.10. Our results show that developing thymocytes receive a gradient of signals, DO11.10>OT-II>DO11.10/Itk(-/-)>OT-II/Itk(-/-). We also show that the development of CD4(+) T cells is controlled by TCR signaling via Itk, which regulates the expression of the transcription factor, Th-POK, an enforcement factor for CD4 commitment. This results in a reduction in CD4(+) T cell development, and an increase in the development of MHC class II restricted TCR transgenic CD8(+) T cells that resemble non-conventional or innate memory phenotype CD8 T cells. This alteration accompanies increased expression of Runx3 and its target genes Eomesodermin, Granzyme B and Perforin in Itk null OT-II CD4(+) thymocytes. All together, these data suggest that Itk plays an important role in CD4/CD8 commitment by regulating signal thresholds for the lineage commitment. Our data also suggest that the lower level of TCR signaling that occurs with a low affinity TCR in the absence of Itk can redirect some MHC class II restricted CD4(+) T cell to class II-restricted CD8(+) innate memory phenotype T cells.