It has long been puzzling how a relatively small number of transcription factors (TFs) can precisely control expression of ~21,000 ORFs and probably 10-fold more non-coding RNAs in humans. Another major gap in the transcription field is a lack of a simple set of rules that explain the specificity of protein-DNA interactions. These gaps represent a major problem because, until they are filled, understanding of the transcription circuitry and its underlining principles will remain highly incomplete. The long-term goals are to characterize the human protein-DNA interaction (PDI) network and elucidate the underlining molecular mechanisms of transcriptional regulation using the combined force of protein microarray technologies and bioinformatics. The objectives of this particular application are to identify a comprehensive list of sequence-specific unconventional DNA-binding proteins (uDBPs) and to better define rules that specify TF-DNA interactions. The central hypothesis is that unbiased, high-throughput profiling of PDIs will reveal rules and organization of transcriptional regulatory networks and pathways. This hypothesis has been formulated on the basis of preliminary data produced in the applicants

Public Health Relevance

The propose research is relevant to public health because generation of a comprehensive list of participants in human transcriptional control and regulation and characterization of the rules that define DNA-binding specificity is ultimately expected to increase understanding of diseases that result from defects in transcription factor function. The proposed research is thus relevant to part of the NIH's mission as this advance in fundamental biological knowledge will help identify better therapeutics for a broad range of human diseases.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-GGG-F (02))
Program Officer
Sledjeski, Darren D
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Johns Hopkins University
Schools of Medicine
United States
Zip Code
Guo, Junjie U; Su, Yijing; Shin, Joo Heon et al. (2014) Distribution, recognition and regulation of non-CpG methylation in the adult mammalian brain. Nat Neurosci 17:215-22
Fan, Baochang; Lu, Kuan-Yi; Reymond Sutandy, F X et al. (2014) A human proteome microarray identifies that the heterogeneous nuclear ribonucleoprotein K (hnRNP K) recognizes the 5' terminal sequence of the hepatitis C virus RNA. Mol Cell Proteomics 13:84-92
Hu, Jianfei; Rho, Hee-Sool; Newman, Robert H et al. (2014) Global analysis of phosphorylation networks in humans. Biochim Biophys Acta 1844:224-31
Lee, Yun-Il; Giovinazzo, Daniel; Kang, Ho Chul et al. (2014) Protein microarray characterization of the S-nitrosoproteome. Mol Cell Proteomics 13:63-72
Hu, Jianfei; Rho, Hee-Sool; Newman, Robert H et al. (2014) PhosphoNetworks: a database for human phosphorylation networks. Bioinformatics 30:141-2
Uzoma, Ijeoma; Zhu, Heng (2013) Interactome mapping: using protein microarray technology to reconstruct diverse protein networks. Genomics Proteomics Bioinformatics 11:18-28
Hu, Shaohui; Feng, Yingzhu; Henson, Brandon et al. (2013) VirD: a virion display array for profiling functional membrane proteins. Anal Chem 85:8046-54
Sutandy, F X Reymond; Qian, Jiang; Chen, Chien-Sheng et al. (2013) Overview of protein microarrays. Curr Protoc Protein Sci Chapter 27:Unit 27.1
Shamay, Meir; Liu, Jianyong; Li, Renfeng et al. (2012) A protein array screen for Kaposi's sarcoma-associated herpesvirus LANA interactors links LANA to TIP60, PP2A activity, and telomere shortening. J Virol 86:5179-91
Hu, Shaohui; Xie, Zhi; Blackshaw, Seth et al. (2011) Characterization of protein-DNA interactions using protein microarrays. Cold Spring Harb Protoc 2011:pdb.prot5614

Showing the most recent 10 out of 20 publications