LymphTF Database A DATABASE OF TRANSCRIPTION FACTOR ACTIVITY IN LYMPHOCYTE DEVELOPMENT

LymphTF Database A DATABASE OF TRANSCRIPTION FACTOR ACTIVITY IN LYMPHOCYTE DEVELOPMENT PAUL CHILDRESS Submitted to the faculty of the Bioinformatics Graduate Program in partial fulfillment of the requirements for the degree Master of Science in the School of Informatics, Indiana University September 2005 i Accepted by the Bioinformatics Program Graduate Faculty, Indiana University, in partial fulfillment of the requirements for the degree of Master of Science in Bioinformatics Master’s Committee _ Narayanan B Perumal, PhD _ Malika Mahoui, PhD _ Mark H Kaplan, PhD ii Dedication This thesis and indeed my entire graduate education are dedicated to Mason and Joshua Childress They are wonderful sons and a continuing source for inspiration and motivation iii Acknowledgments This project is due in large part to my advisor, Dr Narayanan Perumal His advice, patience and encouragement along the way have made this possible Thank You! Mr Charles Moad provided me with some very helpful hints in the design of the database and I would like to thank him very much Bhanu Potugari helped with PHP coding advice and hints for website design without which this project would have been very difficult Finally, I would like to thank Dr Mark Kaplan and Dr Malika Mahoui for serving on my advisory committee iv Abstract Study of the transcriptional regulation of lymphocyte development has advanced greatly in the past 15 years Owing to improved techniques and intense interest in the topic, a great many interactions between transcription factors and their target genes have been described For these B and T cells, a more clear picture is beginning to emerge of how they start with a common progenitor cell, and progressively restrict potential to give many different types of terminally differentiated cells As B and T cells develop they both follow a roughly similar path that involves early stepwise progression to later stages where multiple developmental options are available To progress in the developmental regime they share requirements for proper anatomical location and successful rearrangements of the germ line DNA to give the plethora of antibodies and T cell receptors seen in the immune system Because the amount of information is quickly becoming more than can be assimilated by researchers, a knowledge gap has opened between what is known about the transcription factor activities during this process and what any one individual can recall To help fill this gap, we have created the LymphTF Database This database holds interactions between individual transcription factors and their specific targets at a given developmental time It is our hope that storing the interactions in developmental time will allow for elucidation of regulatory networks which guide the process Work for this project also included construction of a custom data entry web page that automates many tasks associated with populating the database tables These tables have also been related in multiple ways to allow for storage of incomplete information on transcription factor activity This is done without having to replace existing records as details become available The LymphTF DB is a relational MySQL database which can be accessed freely on the web at http://www.iupui.edu/~tfinterx/ v Table of Contents Introduction _ 1-13 Lymphocyte development 1-10 B cell development 2-5 T cell development _5-10 Lymphocyte stages 10-13 Importance 14-22 Developmental model system 14-16 Clinical importance 16-17 Genetic control model system 18-20 Transcriptional regulatory networks _20-22 Knowledge Gap _23-28 Transcriptional regulatory networks _23-24 Gene expression 24-26 Related research 26-28 The Database 28 Materials and Methods 29-44 Definitions and general comments 29-31 Article selection 31-32 Database design 32-44 PHP code: data entry and retrieval 43 Data entry _43-45 Results/Discussion 46-51 Database contents _46-47 Interesting observations 47-48 Searches 48-51 Final comments/Future Possibilities _52-53 References _54-57 Literature 54-56 Websites _57 Appendix 58-65 vi Introduction Immune system development is an area of active research which holds the potential to develop knowledge about disease processes, serve as a model system for study of stem cell differentiation and provide insights into the broader understanding of control of genetic expression Much advancement in technique and the accumulation of a large amount of information have also allowed for the development of rudimentary transcriptional regulatory networks (TRNs) both from automated means and manual creation These networks are in the nascent stages, and rely on a dependable base of information to assemble Such a base exists within peer-reviewed literature B and T cells occupy this unique position in biological study due to several factors These cells arise from a continuously regenerating supply of hematopoietic stem cell precursors (Busslinger, 2004), collection of samples is comparatively easy, animal models exist which mimics human immune cell biology closely, and this is a particularly well-studied area of science which has yielded an enormous amount of information (Siu, 2002) Lymphocyte development B and T lymphocyte development patterns bear many similarities in development and their cooperation in immune system functions combines to give natural companions for study Both populations are derived from the same precursor cells (see following two sections for details) and then proceed in a step-wise fashion through various stages of development These stages are characterized by appearance (or disappearance) of cell surface markers, genomic rearrangements and progressive loss of developmental potential This process begins in the embryo and persists throughout life (Bommhardt U et al, 2004) Each cell type will be discussed independently and a discussion of their cooperative function follows B cell development Mammalian B cells originate within the liver of embryos or the bone marrow of adults The common lymphoid progenitor (CLP) is widely recognized as the stem cell (multipotential cell) that displays the first commitment to a lymphoid cell fate This is a progression from the less restricted hematopoietic stem cell (HSC) which has the ability to become any type of blood cell and the similar multipotent progenitor (MPP) which cannot self-renew its population Figure1 highlights B cell development showing the staging scheme used in the database design (see Materials and Methods) Figure This figure shows the stages of B cell development used in the LymphTF Database, indicates anatomical location of developing cells, and arrows describe pathway(s) of progression of developing cells The action of the receptor tyrosine kinase Flk2/Flk3 separates a subset of MPPs from the others to give a population of cells that are directed to a lymphoid cell fate This means that they can no longer assume the myeloid lineage cell types (Singh et al, 2005) The action of this kinase results in the earliest recognized committed B cell progenitor, the pre-pro B cell This population does not yet contain rearranged immunoglobulin µ (Igµ) heavy chain genes Cells at this stage show the B cell surface markers, AA4+, B220+ and interleukin-7 receptor α-chain (IL-7Rα+), but still show plasticity to develop into non-B cell types under certain conditions Rearrangement of the Igµ heavy chain diversity (DH) region and joining (JH) region genes signals the early pro-B cell stage Recombination of these genes is mediated by RAG1 and RAG2 enzymes Next, the variable (VH) gene is rearranged to combine with the D-JH genes to form the IgH complex, which is displayed on the cell surface Cells that successfully rearrange the heavy chains are then able to associate IgH with the surrogate light chain gene products of the VpreB and λ5 genes The Igα and Igβ signaling molecules are associated with the developing complex (IgH, VpreB and λ5) to create the pre B cell receptor (preBCR) At this point, the cells are referred to as large preB cells and signal transduction activity of the preBCR constitutes a major checkpoint in B cell development (Mathias and Rolink, 2005) Autoreactive cells are removed from the population by apoptosis (programmed cell death) or anergy if their reaction to self antigens is of sufficient strength and cannot be attenuated by a process known as receptor editing (a second rearrangement event) Anergy is a functional silencing of autoreactive B cells which confers tolerance to these cells and predisposes them to an apoptotic fate (Loder et al, 2001) Signaling through the preBCR is also important for allelic exclusion of one of the IgH locus genes Because of the diploid complement, exclusion is necessary so that cells express only one allele for the heavy chain genes The end result is developing B cells that have recombined successfully at the IgH locus, and have subsequently restricted expression of one allele at that locus Signals from the pre-BCR serve to induce an expansion of the developing population (Mathias and Rolink, 2005) The expression of the surrogate light chains is then downregulated, leading to resting, smaller pre-B cells that begin to rearrange the kappa light chain gene locus If this proves unproductive, the lambda chain begins rearrangement B cells at this stage of development are referred to as immature B cells (Melchers et al, 2000) These cells can then leave the marrow (or fetal liver) and enter the spleen to await further developmental progress that is dependent on interacting with an antigen (Siebenlist et al, 2005) At this point in development, the B cells are also known as transitional B cells, and their eventual fate is dependent on their location within the spleen and the concentration of BCR complexes on the cell surface At least two transitional stages, T1 and T2, are required for B cell development into a mature B cell (termed lymphoblast in this project’s database) Given their location in the marginal zone of the spleen, these B cells are the first cells to encounter foreign antigens and thus constitute the first line of defense in the humoral response to antigenic challenge A process known as repertoire selection promotes proliferation of these marginal zone B cells based on their reactivity to T cell-independent epitopes After this selection, a portion of the cells leave the spleen to become circulating plasmablasts which no longer express immunoglobulin as part of their cell surface Table Unique list of all factors active or present in the pre-pro-B stage Just as important as identifying all the players at a particular stage is all the factors acting on a particular target The web interface allows for this searching functionality in a similar, straightforward manner Table shows sample results for the T cell marker gene, CD4 Seven genes have been shown to participate in this gene’s expression This represents the most transcription factors participating in any one single target gene’s expression, which speaks to this gene product’s importance in T cell development CD4 has been shown to undergo a complex regulation pattern from the single positive stage all the way to terminal differentiation, and its role as a cell surface receptor is well established in the functionality of an operating T cell Table Unique list of all factors active or present on the T cell marker CD4 51 Final Comments / Future Possibilities The study of lymphocyte development has experienced an explosion of detail in the last decade This is especially true with respect to the number and identities of transcription factors involved in the process However, looming questions of the target genes and exact phenotypes (i.e developmental stages and restricted potential) of developing lymphocytes remain behind (Hardy 2003) Still, the available data has allowed for modeling of this developmental program The work by Singh and coworkers has attempted to model the B cell developmental program by assembling transcriptional circuits into a contingency network which is dynamic enough to account for the known plasticity and progressive restrictions placed on the developing cells Their network is a beginning point, but does not include all the possible players that have been identified in the literature (see ‘B cell Development’) It remains to be seen whether or not the transcription factors not included in their model are important Anderson et al looked at two transcription factors that are important in T cell development: PU.1 and Gata-3 This interesting perspective examined the effects of perturbing each transcription factor as a function of developmental time The investigators manually designed a regulatory network encompassing at least eleven transcription factors and thirteen targets (some of which are TFs themselves) This type of individually created network has only recently been able to model processes as complex as stem cell differentiation, owing to the recent deluge of information regarding transcription factor activity and targets As these networks are redefined and improved, 52 our database should serve as a reservoir of information that contributes to the understanding of this complicated and important process The LymphTF database strives to organize genetic interaction information in the field of immunology The database can grow as new interactions, transcription factors and target genes are identified Future plans for this project include a visualization tool to display interaction information in a more meaningful way Also, the web site has a submission section so that the interested community can contribute to the completeness and timely inclusion of data in this expanding scientific effort 53 References Literature Åkerblad P., Rosberg M., Leanderson T., Sigvardsson M The B29 (immunoglobulin beta-chain) gene is a genetic target for early B-cell factor Mol Cell Biol 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Mutschler B, Ray RJ, Paige CJ, Sideras P, Torres R, Lamers MC, Carsetti R Anergy and not clonal ignorance determines the fate of B cells that recognize a physiological autoantigen The Journal of Immunology 2001 66(5): pp 31943200 O’Riordan M and Grosschedl R Coordinate Regulation of B Cell Differentiation by the Transcription Factors EBF and E2A Immunity 1999 11: pp 21-31 Rajaiya J., Hatfield M Nixon J.C., Rawlings D.J., Webb C.F Bruton's tyrosine kinase regulates immunoglobulin promoter activation in association with the transcription factor Bright Mol Cell Biol 2005 25(6): pp 2073-2084 Romanow W.J., Langerak A.W., Goebel P., Wolvers-Tettero I.L., van Dongen J.J., Feeney A.J., Murre C E2A and EBF act in synergy with the V(D)J recombinase to generate a diverse immunoglobulin repertoire in nonlymphoid cells Molecular Cell 2000 5(2): pp 343-53 Sabbattini P., Lundgren M Georgiou A Chow C., Warnes G Dillon N Binding of Ikaros to the lambda5 promoter silences transcription through a mechanism that does not require heterochromatin formation EMBO Journal 2001 20(11): pp 28122822 Siebenlist U., Brown K., Claudio E Control of Lymphocyte Development by Nuclear Factor-κB Nature Reviews Immunology 2005 5: pp 435-445 55 Singh H., Medina K., Pongubala J M R Contingent gene regulatory networks and B cell fate specification PNAS 102(14): pp 4949-4953 Singh M Birshtein B.K NF-HB (BSAP) is a repressor of the murine immunoglobulin heavy-chain 3' alpha enhancer at early stages of B-cell differentiation Mol Cell Biol 1993 13(6): pp 3611-3622 Siu G Controlling CD4 gene expression during T cell lineage commitment Seminars in Immunology 2002 14: pp 441-451/ Smith E.M., Gisler R., Sigvardsson M Cloning and characterization of a promoter flanking the early B cell factor (EBF) gene indicates roles for E-proteins andautoregulation in the control of EBF expression Journal of Immunology 2002 169(1): pp 261-270 Song S., Cooperman J., Letting D.L., Blobel G.A., Choi J.K Identification of Cyclin D3 as a Direct Target of E2A Using DamID Mol Cell Biol 2004 24(19): pp 87908802 Thelander E.F., Walsh S.H., Thorsélius M., Laurell A., Landgren O Larsson C., Rosenquist R., Lagercrantz S Mantle cell lymphomas with clonal immunoglobulin VH3-21 gene rearrangements exhibit fewer genomic imbalances than mantle cell lymphomas utilizing other immunoglobulin VH genes Modern Pathology 2005 18: pp 331-339 Trinh L.A., Ferrini R., Cobb B.S., Weinmann A.S., Hahm K., Ernst P., Garraway I.P., Merkenschlager M., Smale S.T Down-regulation of TDT transcription in CD4(+)CD8(+) thymocytes by Ikaros proteins in direct competition with an Ets activator Genes and Development 2001 15(14): pp 1817-1832 van Baarle D., Kostense S., van Oers M H., Miedema F Failing immune control as a result of impaired CD8+ T-cell maturation: CD27 might provide a clue Trends in Immunology 2002 12: pp 586-591 Warren L A., Rothenberg E V Regulatory coding of lymphoid choice by hematopoietic transcription factors Current Opinion in Immunology 2003 15: pp 166-175 Yeo W., Gautier J Early neural cell death: dying to become neurons Developmental biology 2004 274(2): pp 233-244 56 Web sites http://www.nf-kb.org/ http://www.ncbi.nih.gov/entrez/query.fcgi?db=cancerchromosomes http://bioinformatics.med.ohio-state.edu/HemoPDB/ http://www.cifn.unam.mx/Computational_Genomics/regulondb/ http://www.flybase.org/ http://www.ncbi.nih.gov/entrez/query.fcgi?db=PubMed http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene 57 Appendix A – representative code for data entry of B cell information Color code: Blue, Red, Black– php Orange – SQL Green – Comments 63 Appendix C – Representative code used for searching database