Andrew Paul Hutchins

Oct4 switches partnering from Sox2 to Sox17 to reinterpret the enhancer code and specify endoderm.

How regulatory information is encoded in the genome is poorly understood and poses a challenge when studying biological processes. We demonstrate here that genomic redistribution of Oct4 by alternative partnering with Sox2 and Sox17 is a fundamental regulatory event of endodermal specification. We show that Sox17 partners with Oct4 and binds to a unique ‘compressed’ Sox/Oct motif that earmarks endodermal genes. This is in contrast to the pluripotent state where Oct4 selectively partners with Sox2 at ‘canonical’ binding sites. The distinct selection of binding sites by alternative Sox/Oct partnering is underscored by our demonstration that rationally point‐mutated Sox17 partners with Oct4 on pluripotency genes earmarked by the canonical Sox/Oct motif. In an endodermal differentiation assay, we demonstrate that the compressed motif is required for proper expression of endodermal genes. Evidently, Oct4 drives alternative developmental programs by switching Sox partners that affects enhancer selection, leading to either an endodermal or pluripotent cell fate. This work provides insights in understanding cell fate transcriptional regulation by highlighting the direct link between the DNA sequence of an enhancer and a developmental outcome.

The IL-10/STAT3-mediated anti-inflammatory response: recent developments and future challenges

Inflammation is a fundamental response of the immune system whose successful termination involves the elimination of the invading pathogens, the resolution of inflammation and the repair of the local damaged tissue. In this context, the interleukin 10 (IL-10)-mediated anti-inflammatory response (AIR) represents an essential homeostatic mechanism that controls the degree and duration of inflammation. Here, we review recent work on the mechanistic characterization of the IL-10-mediated AIR on multiple levels: from the cataloguing of the in vivo genomic targets of STAT3 (the transcription factor downstream of IL-10) to the identification of specific co-factors that endow STAT3 with genomic-binding specificity, and how genomic and computational methods are being used to elucidate the regulatory mechanisms of this essential physiological response in macrophages.

The p53-induced lincRNA-p21 derails somatic cell reprogramming by sustaining H3K9me3 and CpG methylation at pluripotency gene promoters.

Recent studies have boosted our understanding of long noncoding RNAs (lncRNAs) in numerous biological processes, but few have examined their roles in somatic cell reprogramming. Through expression profiling and functional screening, we have identified that the large intergenic noncoding RNA p21 (lincRNA-p21) impairs reprogramming. Notably, lincRNA-p21 is induced by p53 but does not promote apoptosis or cell senescence in reprogramming. Instead, lincRNA-p21 associates with the H3K9 methyltransferase SETDB1 and the maintenance DNA methyltransferase DNMT1, which is facilitated by the RNA-binding protein HNRNPK. Consequently, lincRNA-p21 prevents reprogramming by sustaining H3K9me3 and/or CpG methylation at pluripotency gene promoters. Our results provide insight into the role of lncRNAs in reprogramming and establish a novel link between p53 and heterochromatin regulation.

Genome-wide analysis of STAT3 binding in vivo predicts effectors of the anti-inflammatory response in macrophages

Inflammation is a powerful response of the immune system against invading pathogens, and must be cancelled when unneeded or otherwise death inevitably follows. In macrophages, the anti-inflammatory response (AIR) is driven by STAT3 upon IL-10 signaling. The role of STAT3 is to stimulate the expression of specific genes that in-turn suppress the transcription of proinflammatory genes. Here we describe a systematic approach to identify the elusive STAT3-controlled effectors of the AIR. In vivo STAT3-binding sites were identified by ChIP-seq, coupled to expression analysis by RNA-seq, both in resting and IL-10-treated peritoneal macrophages. We report the genomic targets of STAT3 and show that STAT3s transcriptional program during the AIR is highly specific to IL-10-stimulated macrophages, that STAT3 is a positive transcriptional regulator, and we predict severalputative AIR factors that merit further investigation. This is the first in-depth study of the AIR by next-generation sequencing and provides an unprecedented degree of detail into this fundamental physiologic response.

Conversion of Sox17 into a pluripotency reprogramming factor by reengineering its association with Oct4 on DNA.

Very few proteins are capable to induce pluripotent stem (iPS) cells and their biochemical uniqueness remains unexplained. For example, Sox2 cooperates with other transcription factors to generate iPS cells, but Sox17, despite binding to similar DNA sequences, cannot. Here, we show that Sox2 and Sox17 exhibit inverse heterodimerization preferences with Oct4 on the canonical versus a newly identified compressed sox/oct motif. We can swap the cooperativity profiles of Sox2 and Sox17 by exchanging single amino acids at the Oct4 interaction interface resulting in Sox2KE and Sox17EK proteins. The reengineered Sox17EK now promotes reprogramming of somatic cells to iPS, whereas Sox2KE has lost this potential. Consistently, when Sox2KE is overexpressed in embryonic stem cells it forces endoderm differentiation similar to wild‐type Sox17. Together, we demonstrate that strategic point mutations that facilitate Sox/Oct4 dimer formation on variant DNA motifs lead to a dramatic swap of the bioactivities of Sox2 and Sox17. STEM CELLS 2011;29:940–951

Distinct transcriptional regulatory modules underlie STAT3’s cell type-independent and cell type-specific functions

Transcription factors (TFs) regulate gene expression by binding to short DNA sequence motifs, yet their binding specificities alone cannot explain how certain TFs drive a diversity of biological processes. In order to investigate the factors that control the functions of the pleiotropic TF STAT3, we studied its genome-wide binding patterns in four different cell types: embryonic stem cells, CD4+ T cells, macrophages and AtT-20 cells. We describe for the first time two distinct modes of STAT3 binding. First, a small cell type-independent mode represented by a set of 35 evolutionarily conserved STAT3-binding sites that collectively regulate STAT3’s own functions and cell growth. We show that STAT3 is recruited to sites with E2F1 already pre-bound before STAT3 activation. Second, a series of different transcriptional regulatory modules (TRMs) assemble around STAT3 to drive distinct transcriptional programs in the four cell types. These modules recognize cell type-specific binding sites and are associated with factors particular to each cell type. Our study illustrates the versatility of STAT3 to regulate both universal- and cell type-specific functions by means of distinct TRMs, a mechanism that might be common to other pleiotropic TFs.

The oncogene c-Jun impedes somatic cell reprogramming

Oncogenic transcription factors are known to mediate the conversion of somatic cells to tumour or induced pluripotent stem cells (iPSCs). Here we report c-Jun as a barrier for iPSC formation. c-Jun is expressed by and required for the proliferation of mouse embryonic fibroblasts (MEFs), but not mouse embryonic stem cells (mESCs). Consistently, c-Jun is induced during mESC differentiation, drives mESCs towards the endoderm lineage and completely blocks the generation of iPSCs from MEFs. Mechanistically, c-Jun activates mesenchymal-related genes, broadly suppresses the pluripotent ones, and derails the obligatory mesenchymal to epithelial transition during reprogramming. Furthermore, inhibition of c-Jun by shRNA, dominant-negative c-Jun or Jdp2 enhances reprogramming and replaces Oct4 among the Yamanaka factors. Finally, Jdp2 anchors 5 non-Yamanaka factors (Id1, Jhdm1b, Lrh1, Sall4 and Glis1) to reprogram MEFs into iPSCs. Our studies reveal c-Jun as a guardian of somatic cell fate and its suppression opens the gate to pluripotency.

The Repertoires of Ubiquitinating and Deubiquitinating Enzymes in Eukaryotic Genomes

Reversible protein ubiquitination regulates virtually all known cellular activities. Here, we present a quantitatively evaluated and broadly applicable method to predict eukaryotic ubiquitinating enzymes (UBE) and deubiquitinating enzymes (DUB) and its application to 50 distinct genomes belonging to four of the five major phylogenetic supergroups of eukaryotes: unikonts (including metazoans, fungi, choanozoa, and amoebozoa), excavates, chromalveolates, and plants. Our method relies on a collection of profile hidden Markov models, and we demonstrate its superior performance (coverage and classification accuracy >99%) by identifying approximately 25% and approximately 35% additional UBE and DUB genes in yeast and human, which had not been reported before. In yeast, we predict 85 UBE and 24 DUB genes, for 814 UBE and 107 DUB genes in the human genome. Most UBE and DUB families are present in all eukaryotic lineages, with plants and animals harboring massively enlarged repertoires of ubiquitin ligases. Unicellular organisms, on the other hand, typically harbor less than 300 UBEs and less than 40 DUBs per genome. Ninety-one UBE/DUB genes are orthologous across all four eukaryotic supergroups, and these likely represent a primordial core of enzymes of the ubiquitination system probably dating back to the first eukaryotes approximately 2 billion years ago. Our genome-wide predictions are available through the Database of Ubiquitinating and Deubiquitinating Enzymes (www.DUDE-db.org), where users can also perform advanced sequence and phylogenetic analyses and submit their own predictions.

Transcriptional Pause Release Is a Rate-Limiting Step for Somatic Cell Reprogramming

Reactivation of the pluripotency network during somatic cell reprogramming by exogenous transcription factors involves chromatin remodeling and the recruitment of RNA polymerase II (Pol II) to target loci. Here, we report that Pol II is engaged at pluripotency promoters in reprogramming but remains paused and inefficiently released. We also show that bromodomain-containing protein 4 (BRD4) stimulates productive transcriptional elongation of pluripotency genes by dissociating the pause release factor P-TEFb from an inactive complex containing HEXIM1. Consequently, BRD4 overexpression enhances reprogramming efficiency and HEXIM1 suppresses it, whereas Brd4 and Hexim1 knockdown do the opposite. We further demonstrate that the reprogramming factor KLF4 helps recruit P-TEFb to pluripotency promoters. Our work thus provides a mechanism for explaining the reactivation of pluripotency genes in reprogramming and unveils an unanticipated role for KLF4 in transcriptional pause release.

glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data

Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.