Matthew R. Huska

DNA methylation protects hematopoietic stem cell multipotency from myeloerythroid restriction

DNA methylation is a dynamic epigenetic mark that undergoes extensive changes during differentiation of self-renewing stem cells. However, whether these changes are the cause or consequence of stem cell fate remains unknown. Here, we show that alternative functional programs of hematopoietic stem cells (HSCs) are governed by gradual differences in methylation levels. Constitutive methylation is essential for HSC self-renewal but dispensable for homing, cell cycle control and suppression of apoptosis. Notably, HSCs from mice with reduced DNA methyltransferase 1 activity cannot suppress key myeloerythroid regulators and thus can differentiate into myeloerythroid, but not lymphoid, progeny. A similar methylation dosage effect controls stem cell function in leukemia. These data identify DNA methylation as an essential epigenetic mechanism to protect stem cells from premature activation of predominant differentiation programs and suggest that methylation dynamics determine stem cell functions in tissue homeostasis and cancer.

MedlineRanker: flexible ranking of biomedical literature

The biomedical literature is represented by millions of abstracts available in the Medline database. These abstracts can be queried with the PubMed interface, which provides a keyword-based Boolean search engine. This approach shows limitations in the retrieval of abstracts related to very specific topics, as it is difficult for a non-expert user to find all of the most relevant keywords related to a biomedical topic. Additionally, when searching for more general topics, the same approach may return hundreds of unranked references. To address these issues, text mining tools have been developed to help scientists focus on relevant abstracts. We have implemented the MedlineRanker webserver, which allows a flexible ranking of Medline for a topic of interest without expert knowledge. Given some abstracts related to a topic, the program deduces automatically the most discriminative words in comparison to a random selection. These words are used to score other abstracts, including those from not yet annotated recent publications, which can be then ranked by relevance. We show that our tool can be highly accurate and that it is able to process millions of abstracts in a practical amount of time. MedlineRanker is free for use and is available at http://cbdm.mdc-berlin.de/tools/medlineranker.

Study of stem cell function using microarray experiments

DNA Microarrays are used to simultaneously measure the levels of thousands of mRNAs in a sample. We illustrate here that a collection of such measurements in different cell types and states is a sound source of functional predictions, provided the microarray experiments are analogous and the cell samples are appropriately diverse. We have used this approach to study stem cells, whose identity and mechanisms of control are not well understood, generating Affymetrix microarray data from more than 200 samples, including stem cells and their derivatives, from human and mouse. The data can be accessed online (StemBase; http://www.scgp.ca:8080/StemBase/).

PROmiRNA: a new miRNA promoter recognition method uncovers the complex regulation of intronic miRNAs

The regulation of intragenic miRNAs by their own intronic promoters is one of the open problems of miRNA biogenesis. Here, we describe PROmiRNA, a new approach for miRNA promoter annotation based on a semi-supervised statistical model trained on deepCAGE data and sequence features. We validate our results with existing annotation, PolII occupancy data and read coverage from RNA-seq data. Compared to previous methods PROmiRNA increases the detection rate of intronic promoters by 30%, allowing us to perform a large-scale analysis of their genomic features, as well as elucidate their contribution to tissue-specific regulation. PROmiRNA can be downloaded from http://promirna.molgen.mpg.de.

Detection of Alpha-Rod Protein Repeats Using a Neural Network and Application to Huntingtin

A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (<10%). We identify alpha-rod repeats in approximately 0.4% of proteins in eukaryotic genomes. We then investigate the results for all human proteins, identifying alpha-rod repeats for the first time in six protein families, including proteins STAG1-3, SERAC1, and PSMD1-2 & 5. We also characterize a short version of these repeats in eight protein families of Archaeal, Bacterial, and Fungal species. Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntingtons disease. Using yeast two hybrid analysis and an immunoprecipitation technique, we show that the huntingtin fragments containing alpha-rods associate with each other. This is the first definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments.

The soluble intracellular domain of megalin does not affect renal proximal tubular function in vivo.

Megalin-mediated endocytic uptake constitutes the main pathway for clearance of plasma proteins from the glomerular filtrate in proximal tubules. Little is known, however, about mechanisms that control megalin expression and activity in the kidney. A widely discussed hypothesis states that upon ligand binding a regulated intramembrane proteolysis releases the cytosolic domain of megalin and this fragment subsequently modulates megalin gene transcription. Here, we tested this by generating a mouse model that co-expressed both the soluble intracellular domain and full-length megalin. Despite pronounced synthesis in the proximal tubules, the soluble intracellular domain failed to exert distinct effects on renal proximal tubular function, including megalin expression, endocytic retrieval of proteins, or global renal gene transcription. Hence, our study argues that the soluble intracellular domain does not have a role in regulating the activity of megalin in the kidney.

Recent developments in StemBase: a tool to study gene expression in human and murine stem cells

BackgroundCurrently one of the largest online repositories for human and mouse stem cell gene expression data, StemBase was first designed as a simple web-interface to DNA microarray data generated by the Canadian Stem Cell Network to facilitate the discovery of gene functions relevant to stem cell control and differentiation.FindingsSince its creation, StemBase has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. As of September 1, 2008, StemBase contains gene expression data (microarray and Serial Analysis of Gene Expression) from 210 stem cell samples in 60 different experiments.ConclusionStemBase can be used to study gene expression in human and murine stem cells and is available at http://www.stembase.ca.

SPON2, a newly identified target gene of MACC1, drives colorectal cancer metastasis in mice and is prognostic for colorectal cancer patient survival.

MACC1 (metastasis associated in colon cancer 1) is a prognostic biomarker for tumor progression, metastasis and survival of a variety of solid cancers including colorectal cancer (CRC). Here we aimed to identify the MACC1-induced transcriptome and key players mediating the MACC1-induced effects in CRC. We performed microarray analyses using CRC cells ectopically overexpressing MACC1. We identified more than 1300 genes at least twofold differentially expressed, including the gene SPON2 (Spondin 2) as 90-fold upregulated transcriptional target of MACC1. MACC1-dependent SPON2 expression regulation was validated on mRNA and protein levels in MACC1 high (endogenously or ectopically) and low (endogenously or by knockdown) expressing cells. Chromatin immunoprecipitation analysis demonstrated the binding of MACC1 to the gene promoter of SPON2. In cell culture, ectopic SPON2 overexpression induced cell viability, migration, invasion and colony formation in endogenously MACC1 and SPON2 low expressing cells, whereas SPON2 knockdown reduced proliferative, migratory and invasive abilities in CRC cells with high endogenous MACC1 and SPON2 expression. In intrasplenically transplanted NOD/SCID mice, metastasis induction was analyzed with control or SPON2-overexpressing CRC cells. Tumors with SPON2 overexpression induced liver metastasis (vs control animals without any metastases, P=0.0036). In CRC patients, SPON2 expression was determined in primary tumors (stages I–III), and survival time was analyzed by Kaplan–Meier method. CRC patients with high SPON2 expressing primary tumors demonstrated 8 months shorter metastasis-free survival (MFS) compared with patients with low SPON2 levels (P=0.053). Combining high levels of SPON2 and MACC1 improved the identification of high-risk patients with a 20-month shorter MFS vs patients with low biomarker expression. In summary, SPON2 is a transcriptional target of the metastasis gene MACC1. SPON2 induces cell motility in vitro and CRC metastasis in mice. In patients, SPON2 serves as prognostic indicator for CRC metastasis and survival, and might represent a promising target for therapeutic approaches.

BiasViz: visualization of amino acid biased regions in protein alignments

About a third of all protein sequences have at least one composition biased region (CBR). Such regions might act as linkers between protein domains but often confer specific binding to various molecules; therefore, their characterization in terms of their boundaries and over-represented residues is important. Analysis of CBRs in a particular sequence can be time consuming if several types of biases have to be explored and their position visualized. Assessment of the significance of the detected CBRs can be approached by comparison to homologous protein sequences. To assist this procedure, we have developed BiasViz, a tool that allows to graphically studying local amino acid composition in protein sequences of a multiple sequence alignment.

Role of the chromatin landscape and sequence in determining cell type-specific genomic glucocorticoid receptor binding and gene regulation

Abstract The genomic loci bound by the glucocorticoid receptor (GR), a hormone-activated transcription factor, show little overlap between cell types. To study the role of chromatin and sequence in specifying where GR binds, we used Bayesian modeling within the universe of accessible chromatin. Taken together, our results uncovered that although GR preferentially binds accessible chromatin, its binding is biased against accessible chromatin located at promoter regions. This bias can only be explained partially by the presence of fewer GR recognition sequences, arguing for the existence of additional mechanisms that interfere with GR binding at promoters. Therefore, we tested the role of H3K9ac, the chromatin feature with the strongest negative association with GR binding, but found that this correlation does not reflect a causative link. Finally, we find a higher percentage of promoter–proximal GR binding for genes regulated by GR across cell types than for cell type-specific target genes. Given that GR almost exclusively binds accessible chromatin, we propose that cell type-specific regulation by GR preferentially occurs via distal enhancers, whose chromatin accessibility is typically cell type-specific, whereas ubiquitous target gene regulation is more likely to result from binding to promoter regions, which are often accessible regardless of cell type examined.