Martha L. Bulyk

STAT3 Activation of miR-21 and miR-181b-1 via PTEN and CYLD Are Part of the Epigenetic Switch Linking Inflammation to Cancer

A transient inflammatory signal can initiate an epigenetic switch from nontransformed to cancer cells via a positive feedback loop involving NF-kappaB, Lin28, let-7, and IL-6. We identify differentially regulated microRNAs important for this switch and putative transcription factor binding sites in their promoters. STAT3, a transcription factor activated by IL-6, directly activates miR-21 and miR-181b-1. Remarkably, transient expression of either microRNA induces the epigenetic switch. MiR-21 and miR-181b-1, respectively, inhibit PTEN and CYLD tumor suppressors, leading to increased NF-kappaB activity required to maintain the transformed state. These STAT3-mediated regulatory circuits are required for the transformed state in diverse cell lines and tumor growth in xenografts, and their transcriptional signatures are observed in colon adenocarcinomas. Thus, STAT3 is not only a downstream target of IL-6 but, with miR-21, miR-181b-1, PTEN, and CYLD, is part of the positive feedback loop that underlies the epigenetic switch that links inflammation to cancer.

Variation in homeodomain DNA-binding revealed by high-resolution analysis of sequence preferences

Most homeodomains are unique within a genome, yet many are highly conserved across vast evolutionary distances, implying strong selection on their precise DNA-binding specificities. We determined the binding preferences of the majority (168) of mouse homeodomains to all possible 8-base sequences, revealing rich and complex patterns of sequence specificity and showing that there are at least 65 distinct homeodomain DNA-binding activities. We developed a computational system that successfully predicts binding sites for homeodomain proteins as distant from mouse as Drosophila and C. elegans, and we infer full 8-mer binding profiles for the majority of known animal homeodomains. Our results provide an unprecedented level of resolution in the analysis of this simple domain structure and suggest that variation in sequence recognition may be a factor in its functional diversity and evolutionary success.

Genome-wide analysis of ETS-family DNA-binding in vitro and in vivo

Members of the large ETS family of transcription factors (TFs) have highly similar DNA‐binding domains (DBDs)—yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA‐binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA‐binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high‐throughput microwell‐based TF DNA‐binding specificity assay, and protein‐binding microarrays (PBMs). Both approaches reveal that the ETS‐binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino‐acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP‐seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

UniPROBE: An Online Database of Protein Binding Microarray Data on Protein–DNA Interactions

The UniPROBE (Universal PBM Resource for Oligonucleotide Binding Evaluation) database hosts data generated by universal protein binding microarray (PBM) technology on the in vitro DNA-binding specificities of proteins. This initial release of the UniPROBE database provides a centralized resource for accessing comprehensive PBM data on the preferences of proteins for all possible sequence variants (‘words’) of length k (‘k-mers’), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. In total, the database hosts DNA-binding data for over 175 nonredundant proteins from a diverse collection of organisms, including the prokaryote Vibrio harveyi, the eukaryotic malarial parasite Plasmodium falciparum, the parasitic Apicomplexan Cryptosporidium parvum, the yeast Saccharomyces cerevisiae, the worm Caenorhabditis elegans, mouse and human. Current web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences. The UniPROBE database is available at http://thebrain.bwh.harvard.edu/uniprobe/.

Computational prediction of transcription-factor binding site locations

Identifying genomic locations of transcription-factor binding sites, particularly in higher eukaryotic genomes, has been an enormous challenge. Various experimental and computational approaches have been used to detect these sites; methods involving computational comparisons of related genomes have been particularly successful.

Exploring the DNA-binding specificities of zinc fingers with DNA microarrays

A key step in the regulation of networks that control gene expression is the sequence-specific binding of transcription factors to their DNA recognition sites. A more complete understanding of these DNA–protein interactions will permit a more comprehensive and quantitative mapping of the regulatory pathways within cells, as well as a deeper understanding of the potential functions of individual genes regulated by newly identified DNA-binding sites. Here we describe a DNA microarray-based method to characterize sequence-specific DNA recognition by zinc-finger proteins. A phage display library, prepared by randomizing critical amino acid residues in the second of three fingers of the mouse Zif268 domain, provided a rich source of zinc-finger proteins with variant DNA-binding specificities. Microarrays containing all possible 3-bp binding sites for the variable zinc fingers permitted the quantitation of the binding site preferences of the entire library, pools of zinc fingers corresponding to different rounds of selection from this library, as well as individual Zif268 variants that were isolated from the library by using specific DNA sequences. The results demonstrate the feasibility of using DNA microarrays for genome-wide identification of putative transcription factor-binding sites.

Quantifying DNA–protein interactions by double-stranded DNA arrays

We have created double-stranded oligonucleotide arrays to perform highly parallel investigations of DNA–protein interactions. Arrays of single-stranded DNA oligonucleotides, synthesized by a combination of photolithography and solid-state chemistry, have been used for a variety of applications, including large-scale mRNA expression monitoring, genotyping, and sequence-variation analysis. We converted a single-stranded to a double-stranded array by synthesizing a constant sequence at every position on an array and then annealing and enzymatically extending a complementary primer. The efficiency of second-strand synthesis was demonstrated by incorporation of fluorescently labeled dNTPs (2´-deoxyribonucleoside 5´-triphosphates) and by terminal transferase addition of a fluorescently labeled ddNTP. The accuracy of second-strand synthesis was demonstrated by digestion of the arrayed double-stranded DNA (dsDNA) on the array with sequence-specific restriction enzymes. We showed dam methylation of dsDNA arrays by digestion with DpnI, which cleaves when its recognition site is methylated. This digestion demonstrated that the dsDNA arrays can be further biochemically modified and that the DNA is accessible for interaction with DNA-binding proteins. This dsDNA array approach could be extended to explore the spectrum of sequence-specific protein binding sites in genomes.

A transcriptional signature and common gene networks link cancer with lipid metabolism and diverse human diseases

Transcriptional profiling of two isogenic models of transformation identifies a gene signature linking cancer with inflammatory and metabolic diseases. In accord with this common transcriptional program, many drugs used for treatment of diabetes and cardiovascular diseases inhibit transformation and tumor growth. Unexpectedly, lipid metabolism genes are important for transformation and are upregulated in cancer tissues. As in atherosclerosis, oxidized LDL and its receptor OLR1 activate the inflammatory pathway through NF-kappaB, leading to transformation. OLR1 is important for maintaining the transformed state in developmentally diverse cancer cell lines and for tumor growth, suggesting a molecular connection between cancer and atherosclerosis. We suggest that the interplay between this common transcriptional program and cell-type-specific factors gives rise to phenotypically disparate human diseases.

Specific DNA-binding by Apicomplexan AP2 transcription factors

Malaria remains one of the most prevalent infectious diseases worldwide, affecting more than half a billion people annually. Despite many years of research, the mechanisms underlying transcriptional regulation in the malaria-causing Plasmodium spp., and in Apicomplexan parasites generally, remain poorly understood. In Plasmodium, few regulatory elements sufficient to drive gene expression have been characterized, and their cognate DNA-binding proteins remain unknown. This study characterizes the DNA-binding specificities of two members of the recently identified Apicomplexan AP2 (ApiAP2) family of putative transcriptional regulators from Plasmodium falciparum. The ApiAP2 proteins contain AP2 domains homologous to the well characterized plant AP2 family of transcriptional regulators, which play key roles in development and environmental stress response pathways. We assayed ApiAP2 protein–DNA interactions using protein-binding microarrays and combined these results with computational predictions of coexpressed target genes to couple these putative trans factors to corresponding cis-regulatory motifs in Plasmodium. Furthermore, we show that protein–DNA sequence specificity is conserved in orthologous proteins between phylogenetically distant Apicomplexan species. The identification of the DNA-binding specificities for ApiAP2 proteins lays the foundation for the exploration of their role as transcriptional regulators during all stages of parasite development. Because of their origin in the plant lineage, ApiAP2 proteins have no homologues in the human host and may prove to be ideal antimalarial targets.

Evaluation of methods for modeling transcription factor sequence specificity

Genomic analyses often involve scanning for potential transcription factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a proteins DNA-binding specificity, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For nine TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from the in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices trained by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10% of the TFs examined here). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.