Jieun Jeong

Comparison of glioma stem cells to neural stem cells from the adult human brain identifies dysregulated Wnt- signaling and a fingerprint associated with clinical outcome

Glioblastoma is the most common brain tumor. Median survival in unselected patients is <10 months. The tumor harbors stem-like cells that self-renew and propagate upon serial transplantation in mice, although the clinical relevance of these cells has not been well documented. We have performed the first genome-wide analysis that directly relates the gene expression profile of nine enriched populations of glioblastoma stem cells (GSCs) to five identically isolated and cultivated populations of stem cells from the normal adult human brain. Although the two cell types share common stem- and lineage-related markers, GSCs show a more heterogeneous gene expression. We identified a number of pathways that are dysregulated in GSCs. A subset of these pathways has previously been identified in leukemic stem cells, suggesting that cancer stem cells of different origin may have common features. Genes upregulated in GSCs were also highly expressed in embryonic and induced pluripotent stem cells. We found that canonical Wnt-signaling plays an important role in GSCs, but not in adult human neural stem cells. As well we identified a 30-gene signature highly overexpressed in GSCs. The expression of these signature genes correlates with clinical outcome and demonstrates the clinical relevance of GSCs.

Nucleoporin Nup98 Associates with Trx/MLL and NSL Histone-Modifying Complexes and Regulates Hox Gene Expression

The nuclear pore complex is a transport channel embedded in the nuclear envelope and made up of 30 different components termed nucleoporins (Nups). In addition to their classical role in transport, a subset of Nups has a conserved role in the regulation of transcription via direct binding to chromatin. The molecular details of this function remain obscure, and it is unknown how metazoan Nups are recruited to their chromatin locations or what transcription steps they regulate. Here, we demonstrate genome-wide and physical association between Nup98 and histone-modifying complexes MBD-R2/NSL [corrected] and Trx/MLL. Importantly, we identify a requirement for MBD-R2 in recruitment of Nup98 to many of its genomic target sites. Consistent with its interaction with the Trx/MLL complex, Nup98 is shown to be necessary for Hox gene expression in developing fly tissues. These findings introduce roles of Nup98 in epigenetic regulation that may underlie the basis of oncogenicity of Nup98 fusions in leukemia.

A direct fate exclusion mechanism by Sonic hedgehog-regulated transcriptional repressors.

Sonic hedgehog (Shh) signaling patterns the vertebrate spinal cord by activating a group of transcriptional repressors in distinct neural progenitors of somatic motor neuron and interneuron subtypes. To identify the action of this network, we performed a genome-wide analysis of the regulatory actions of three key ventral determinants in mammalian neural tube patterning: Nkx2.2, Nkx6.1 and Olig2. Previous studies have demonstrated that each factor acts predominantly as a transcriptional repressor, at least in part, to inhibit alternative progenitor fate choices. Here, we reveal broad and direct repression of multiple alternative fates as a general mechanism of repressor action. Additionally, the repressor network targets multiple Shh signaling components providing negative feedback to ongoing Shh signaling. Analysis of chromatin organization around Nkx2.2-, Nkx6.1- and Olig2-bound regions, together with co-analysis of engagement of the transcriptional activator Sox2, indicate that repressors bind to, and probably modulate the action of, neural enhancers. Together, the data suggest a model for neural progenitor specification downstream of Shh signaling, in which Nkx2.2 and Olig2 direct repression of alternative neural progenitor fate determinants, an action augmented by the overlapping activity of Nkx6.1 in each cell type. Integration of repressor and activator inputs, notably activator inputs mediated by Sox2, is probably a key mechanism in achieving cell type-specific transcriptional outcomes in mammalian neural progenitor fate specification. Summary: Unbiased functional genomics approaches reveal that Nkx2.2, Nkx6.1 and Olig2 directly repress multiple alternative fates during mammalian neural progenitor fate specification.

Packing to angles and sectors

Motivated by the widespread proliferation of wireless networks employing directional antennas, we study some capacitated covering problems arising in these networks. Geometrically, the area covered by a directional antenna with parameters α,ρ,r is a set of points with polar coordinates (r,θ) such that r ≤ r and α ≤ θ ≤ α + ρ. Given a set of customers, their positions on the plane and their bandwidth demands, the capacitated covering problem considered here is to cover all the customers with the minimum number of directional antennas such that the demands of customers assigned to an antenna stays within a bound. We consider two settings of this capacitated cover problem arising in wireless networks. In the first setting where the antennas have variable angular range, we present an approximation algorithm with ratio 3. In the setting where the angular range of antennas is fixed, we improve this approximation ratio to 1.5. These results also apply for a related problem of bin packing with deadlines. In this problem we are are given a set of items, each with a weight, arrival time and deadline, and we want to pack each item into a bin after it arrives but before its deadline. The objective is to minimize the number of bins used. We present a 3-approximation algorithm for this problem, and 1.5-approximation algorithm for the special case when each difference between a deadline and the corresponding arrival time is the same.

The Sequence-Specific Transcription Factor c-Jun Targets Cockayne Syndrome Protein B to Regulate Transcription and Chromatin Structure

Cockayne syndrome is an inherited premature aging disease associated with numerous developmental and neurological defects, and mutations in the gene encoding the CSB protein account for the majority of Cockayne syndrome cases. Accumulating evidence suggests that CSB functions in transcription regulation, in addition to its roles in DNA repair, and those defects in this transcriptional activity might contribute to the clinical features of Cockayne syndrome. Transcription profiling studies have so far uncovered CSB-dependent effects on gene expression; however, the direct targets of CSBs transcriptional activity remain largely unknown. In this paper, we report the first comprehensive analysis of CSB genomic occupancy during replicative cell growth. We found that CSB occupancy sites display a high correlation to regions with epigenetic features of promoters and enhancers. Furthermore, we found that CSB occupancy is enriched at sites containing the TPA-response element. Consistent with this binding site preference, we show that CSB and the transcription factor c-Jun can be found in the same protein-DNA complex, suggesting that c-Jun can target CSB to specific genomic regions. In support of this notion, we observed decreased CSB occupancy of TPA-response elements when c-Jun levels were diminished. By modulating CSB abundance, we found that CSB can influence the expression of nearby genes and impact nucleosome positioning in the vicinity of its binding site. These results indicate that CSB can be targeted to specific genomic loci by sequence-specific transcription factors to regulate transcription and local chromatin structure. Additionally, comparison of CSB occupancy sites with the MSigDB Pathways database suggests that CSB might function in peroxisome proliferation, EGF receptor transactivation, G protein signaling and NF-κB activation, shedding new light on the possible causes and mechanisms of Cockayne syndrome.

Improving Strand Pairing Prediction through Exploring Folding Cooperativity

The topology of beta-sheets is defined by the pattern of hydrogen-bonded strand pairing. Therefore, predicting hydrogen bonded strand partners is a fundamental step towards predicting beta-sheet topology. At the same time, finding the correct partners is very difficult due to long range interactions involved in strand pairing. Additionally, patterns of aminoacids involved, in beta-sheet formations are very general and therefore difficult to use for computational recognition of specific contacts between strands. In this work, we report a new strand pairing algorithm. To address above mentioned difficulties, our algorithm attempts to mimic elements of the folding process. Namely, in addition to ensuring that the predicted hydrogen bonded strand pairs satisfy basic global consistency constraints, it takes into account hypothetical folding pathways. Consistently with this view, introducing hydrogen bonds between a pair of strands changes the probabilities of forming hydrogen bonds between other pairs of strand. We demonstrate that this approach provides an improvement over previously proposed algorithms. We also compare the performance of this method to that of a global optimization algorithm that poses the problem as integer linear programming optimization problem and solves it using ILOG CPLEX package.

Bringing folding pathways into strand pairing prediction

The topology of β-sheets is defined by the pattern of hydrogen-bonded strand pairing. Therefore, predicting hydrogen bonded strand partners is a fundamental step towards predicting β-sheet topology. In this work we report a new strand pairing algorithm. Our algorithm attempts to mimic elements of the folding process. Namely, in addition to ensuring that the predicted hydrogen bonded strand pairs satisfy basic global consistency constraints, it takes into account hypothetical folding pathways. Consistently with this view, introducing hydrogen bonds between a pair of strands changes the probabilities of forming other strand pairs. We demonstrate that this approach provides an improvement over previously proposed algorithms.

Fold classification based on secondary structure – how much is gained by including loop topology?

BackgroundIt has been proposed that secondary structure information can be used to classify (to some extend) protein folds. Since this method utilizes very limited information about the protein structure, it is not surprising that it has a higher error rate than the approaches that use full 3D fold description. On the other hand, the comparing of 3D protein structures is computing intensive. This raises the question to what extend the error rate can be decreased with each new source of information, especially if the new information can still be used with simple alignment algorithms.We consider the question whether the information about closed loops can improve the accuracy of this approach. While the answer appears to be obvious, we had to overcome two challenges. First, how to code and to compare topological information in such a way that local alignment of strings will properly identify similar structures. Second, how to properly measure the effect of new information in a large data sample.We investigate alternative ways of computing and presenting this information.ResultsWe used the set of beta proteins with at most 30% pairwise identity to test the approach; local alignment scores were used to build a tree of clusters which was evaluated using a new log-odd cluster scoring function. In particular, we derive a closed formula for the probability of obtaining a given score by chance.Parameters of local alignment function were optimized using a genetic algorithm.Of 81 folds that had more than one representative in our data set, log-odds scores registered significantly better clustering in 27 cases and significantly worse in 6 cases, and small differences in the remaining cases. Various notions of the significant change or average change were considered and tried, and the results were all pointing in the same direction.ConclusionWe found that, on average, properly presented information about the loop topology improves noticeably the accuracy of the method but the benefits vary between fold families as measured by log-odds cluster score.

Consistent Sets of Secondary Structures in Proteins

Abstract Ab initio predictions of secondary structures in proteins have to combine local predictions, based on short fragments of the protein sequence, with consistency restrictions, as not all locally plausible predictions may be simultaneously true. We use the fact that secondary structures are patterns of hydrogen bonds and that a single residue can participate in hydrogen bonds of at most one secondary structure. Consistency of fixed-sized pieces of secondary structures is the easiest to approximate and we formalize it as 1-2 matching problem. Consistency of entire secondary structures is a version of set packing. We also investigate how to form a simple problem if we add the requirement that the secondary structure and the loops that connect them fit together in a metric space. Every problem that we investigated is MAX-SNP hard and it has a constant factor approximation. Computational experience suggests that in biological instances, we can find nearly optimal solutions using heuristics.

The role of Cockayne Syndrome Protein B in transcription regulation.

We investigated the question if CSB (Cockayne Syndrome complementation B) protein actively regulates gene transcription and how mutations in CSB gene affect that regulatory role. Here we describe how we processed and interpreted ChIP-seq data (deposited in Gene Expression Omnibus with accession number GSE50171) obtained during an investigation of that question, and how this analysis assisted in the generation of hypothesis that were subsequently validated using other types of experiment.