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TFTag: A novel library of tagged transcription factors in Drosophila

Reference	BB/W018780/1
Principal Investigator / Supervisor	Dr Korneel Hens
Co-Investigators / Co-Supervisors	Dr Sebastian Kittelmann, Dr Jack Sunter
Institution	Oxford Brookes University
Department	Faculty of Health and Life Sciences
Funding type	Research
Value (£)	1,144,262
Status	Current
Type	Research Grant
Start date	01/12/2022
End date	30/11/2027
Duration	60 months

Abstract

Gene regulation is largely controlled at the transcriptional level, where transcription factors (TFs) interact with regulatory elements in the DNA to repress or enhance activity of RNA polymerase II. The study of TFs involves analysis of expression patterns, genomic binding sites, and interaction partners, all of which rely on the use of specific antibodies. However, the production of antibodies is expensive, time-consuming, and ethically questionable. In Drosophila melanogaster, one of the prime model organisms for the analysis of basic biological processes, a common solution is the use of tagged versions of TFs. Tags encode small peptides, fluorescent proteins, or enzymatic domains and allow for various downstream applications. Fly strain libraries allowing for analysis of tagged proteins have been created in recent years but they only cover a small and largely already well-studied subset of the 753 known or predicted Drosophila TFs. Here, we propose to create a biological and bioinformatic resource to greatly advance the analysis of TFs in Drosophila and beyond. This resource will consist of three parts: 1) a library of plasmids for the CRISPR-mediated tagging of all Drosophila TFs; 2) a collection of fly lines in which the tags have been introduced at endogenous loci; 3) a database with basic information about the plasmids and tagged lines, as well as expression and binding data for a subset of previously unstudied TFs. We plan to tag TFs at every annotated N and C-terminus. This will alleviate problems that might arise from interference of the tag with one terminus and at the same time allow analysis of all TF variants with different termini. Moreover, the primary sfGFP will be easily exchangeable by crossing to a donor line for any other tag that might be desired. This will allow any downstream analysis imaginable and substantially broaden the user base. Furthermore, our database will allow researchers to easily select candidate TFs to study in more detail.

Summary

Every multicellular organism consists of dozens or even hundreds of different cell types that are defined by their different protein repertoires. The building plans for the proteins are encoded in the form of genes in the DNA, as are the instructions of where and when to make them. This process, referred to as gene expression, is highly dynamic and is constantly adjusted during development or in response to, e.g., environmental changes. Each cell type has its characteristic pattern of gene expression, and mis-regulation is associated with various diseases, including cancer. Therefore, gene expression must be tightly regulated to ensure that each cell has the correct protein content. This is largely done by a specific class of proteins, the transcription factors (TFs), which can bind to DNA and cooperate with each other to influence which genes are transcribed in what quantities. This in turn determines which proteins are present in which cells and in which amount. TFs are, accordingly, studied by a wide range of scientists in the life and medical sciences. Research on TFs mainly seeks to uncover information about their expression level, localisation, binding sites in the genome, interaction partners, and effects of a loss of function. Most of these analyses rely heavily on the use of antibodies, the production of which is costly, difficult, and ethically questionable. Moreover, methods involving antibodies are geared towards fixed biological materials, which makes the recapitulation of dynamic processes challenging. A common solution is the use of genetic tricks to express a version of the TF that is fused to another protein, which can, in turn, be readily detected and is, accordingly, called a tag. However, tags are often suitable for only a single or few methods or otherwise are large and might interfere with the function of the TF. Moreover, the additional expression of the tagged TF can induce artefacts. Also, tools for the expression of such tagged constructs are only available for a subset of TFs. The fruit fly, Drosophila melanogaster, has long served as one of the prime model organisms to study basic biological processes. It benefits from a large, well-connected worldwide community of researchers and the availability of vast genetic and molecular resources. Importantly, it allows investigations in vivo, and the creation of transgenic lines for the generation of novel tools is straightforward. Here we propose to create a biological and bioinformatic resource consisting of a library of transgenic fly lines in which all Drosophila TF genes have been tagged at their native genomic locus. We will also establish a database with basic data on the expression and DNA binding of a subset of TFs that have not previously been studied. Our resources will alleviate many of the shortcomings of previous libraries of tagged proteins: 1) Our tagging strategy allows for the easy exchange of the tag, making each TF accessible for various downstream applications; 2) We will create individual transgenic lines in which either end of a TF has been tagged, which reduces the risk of an interference of the tag with protein function; 3) For TFs that are expressed with alternative ends, we will create a line for each end, allowing the study of different versions of each TF. We will distribute the fly lines free of charge to members of the research community, and the database will, likewise, be free to use. These resources will open the possibility to study any Drosophila TF with the methods of choice in any biological process imaginable and allow scientists to easily identify potential candidates among the many unstudied TFs. We expect that our resource will greatly advance research in the field of gene regulation.

Committee	Research Committee C (Genes, development and STEM approaches to biology)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Bioinformatics and Biological Resources Fund (BBR) [2007-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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