Martin Enge

Small molecule RITA binds to p53, blocks p53–HDM-2 interaction and activates p53 function in tumors

In tumors that retain wild-type p53, its tumor-suppressor function is often impaired as a result of the deregulation of HDM-2, which binds to p53 and targets it for proteasomal degradation. We have screened a chemical library and identified a small molecule named RITA (reactivation of p53 and induction of tumor cell apoptosis), which bound to p53 and induced its accumulation in tumor cells. RITA prevented p53–HDM-2 interaction in vitro and in vivo and affected p53 interaction with several negative regulators. RITA induced expression of p53 target genes and massive apoptosis in various tumor cells lines expressing wild-type p53. RITA suppressed the growth of human fibroblasts and lymphoblasts only upon oncogene expression and showed substantial p53-dependent antitumor effect in vivo. RITA may serve as a lead compound for the development of an anticancer drug that targets tumors with wild-type p53.

DNA-binding specificities of human transcription factors.

Although the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

Counting absolute numbers of molecules using unique molecular identifiers

Counting individual RNA or DNA molecules is difficult because they are hard to copy quantitatively for detection. To overcome this limitation, we applied unique molecular identifiers (UMIs), which make each molecule in a population distinct, to genome-scale human karyotyping and mRNA sequencing in Drosophila melanogaster. Use of this method can improve accuracy of almost any next-generation sequencing method, including chromatin immunoprecipitation–sequencing, genome assembly, diagnostics and manufacturing-process control and monitoring.

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.

MED12, the Mediator Complex Subunit 12 Gene, Is Mutated at High Frequency in Uterine Leiomyomas

Uterine fibroids frequently harbor mutations in a specific gene that has been implicated in transcriptional regulation. Uterine leiomyomas, or fibroids, are benign tumors that affect millions of women worldwide and that can cause considerable morbidity. To study the genetic basis of this tumor type, we examined 18 uterine leiomyomas derived from 17 different patients by exome sequencing and identified tumor-specific mutations in the mediator complex subunit 12 (MED12) gene in 10. Through analysis of 207 additional tumors, we determined that MED12 is altered in 70% (159 of 225) of tumors from a total of 80 patients. The Mediator complex is a 26-subunit transcriptional regulator that bridges DNA regulatory sequences to the RNA polymerase II initiation complex. All mutations resided in exon 2, suggesting that aberrant function of this region of MED12 contributes to tumorigenesis.

A survey of human brain transcriptome diversity at the single cell level

Significance The brain comprises an immense number of cells and cellular connections. We describe the first, to our knowledge, single cell whole transcriptome analysis of human adult cortical samples. We have established an experimental and analytical framework with which the complexity of the human brain can be dissected on the single cell level. Using this approach, we were able to identify all major cell types of the brain and characterize subtypes of neuronal cells. We observed changes in neurons from early developmental to late differentiated stages in the adult. We found a subset of adult neurons which express major histocompatibility complex class I genes and thus are not immune privileged. The human brain is a tissue of vast complexity in terms of the cell types it comprises. Conventional approaches to classifying cell types in the human brain at single cell resolution have been limited to exploring relatively few markers and therefore have provided a limited molecular characterization of any given cell type. We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers. We then used single cell RNA sequencing on fetal human cortical neurons to identify genes that are differentially expressed between fetal and adult neurons and those genes that display an expression gradient that reflects the transition between replicating and quiescent fetal neuronal populations. Finally, we observed the expression of major histocompatibility complex type I genes in a subset of adult neurons, but not fetal neurons. The work presented here demonstrates the applicability of single cell RNA sequencing on the study of the adult human brain and constitutes a first step toward a comprehensive cellular atlas of the human brain.

Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities

The genetic code-the binding specificity of all transfer-RNAs--defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the approximately 1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.

Transcription Factor Binding in Human Cells Occurs in Dense Clusters Formed around Cohesin Anchor Sites

During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M phase. These results suggest that cohesin-binding functions as a cellular memory that promotes re-establishment of TF clusters after DNA replication and chromatin condensation.

Mice lacking a Myc enhancer that includes human SNP rs6983267 are resistant to intestinal tumors.

From Man to Mouse Genome-wide association studies of humans have identified single-nucleotide polymorphisms (SNPs) that increase an individuals risk of developing common diseases like cancer. Most of these SNPs have only a modest effect on risk, and many map to noncoding regions of the genome. Sur et al. (p. 1360, published online 1 November; see the Perspective by Lewis and Tomlinson) used a mouse model to study the functional impact of a particular SNP that resides 300 kilobases upstream of the MYC oncogene on human chromosome 8q24 and has been linked to cancer risk in humans. When a sequence encompassing this SNP was deleted in mice that were predisposed to develop intestinal tumors, the mice displayed fewer tumors than control mice. This SNP may thus play a causal role in human cancer, presumably through altered regulation of MYC. A human genetic variant, identified in genome-wide association studies as increasing cancer risk, alters tumorigenesis in mice. Multiple cancer-associated single-nucleotide polymorphisms (SNPs) have been mapped to conserved sequences within a 500-kilobase region upstream of the MYC oncogene on human chromosome 8q24. These SNPs may affect cancer development through altered regulation of MYC expression, but this hypothesis has been difficult to confirm. We generated mice deficient in Myc-335, a putative MYC regulatory element that contains rs6983267, a SNP accounting for more human cancer-related morbidity than any other genetic variant or mutation. In Myc-335 null mice, Myc transcripts were expressed in the intestinal crypts in a pattern similar to that in wild-type mice but at modestly reduced levels. The mutant mice displayed no overt phenotype but were markedly resistant to intestinal tumorigenesis induced by the APCmin mutation. These results establish that a cancer-associated SNP identified in human genome-wide association studies has a functional effect in vivo.

DNA-dependent formation of transcription factor pairs alters their binding specificity.

Gene expression is regulated by transcription factors (TFs), proteins that recognize short DNA sequence motifs. Such sequences are very common in the human genome, and an important determinant of the specificity of gene expression is the cooperative binding of multiple TFs to closely located motifs. However, interactions between DNA-bound TFs have not been systematically characterized. To identify TF pairs that bind cooperatively to DNA, and to characterize their spacing and orientation preferences, we have performed consecutive affinity-purification systematic evolution of ligands by exponential enrichment (CAP-SELEX) analysis of 9,400 TF–TF–DNA interactions. This analysis revealed 315 TF–TF interactions recognizing 618 heterodimeric motifs, most of which have not been previously described. The observed cooperativity occurred promiscuously between TFs from diverse structural families. Structural analysis of the TF pairs, including a novel crystal structure of MEIS1 and DLX3 bound to their identified recognition site, revealed that the interactions between the TFs were predominantly mediated by DNA. Most TF pair sites identified involved a large overlap between individual TF recognition motifs, and resulted in recognition of composite sites that were markedly different from the individual TF’s motifs. Together, our results indicate that the DNA molecule commonly plays an active role in cooperative interactions that define the gene regulatory lexicon.