Publications by authors named "Xuejian Xiong"

20 Publications

  • Page 1 of 1

Analyzing Metabolic Pathways in Microbiomes.

Methods Mol Biol 2018 ;1849:291-307

Program in Molecular Medicine, The Hospital for Sick Children, Toronto, ON, Canada.

Understanding the metabolic activity of a microbial community, at both the level of the individual microbe and the whole microbiome, provides fundamental biological, biochemical, and clinical insights into the nature of the microbial community and interactions with their hosts in health and disease. Here, we discuss a method to examine the expression of metabolic pathways in microbial communities using data from metatranscriptomic next-generation sequencing data. The methodology described here encompasses enzyme function annotation, differential enzyme expression and pathway enrichment analyses, and visualization of metabolic networks with differential enzyme expression levels.
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http://dx.doi.org/10.1007/978-1-4939-8728-3_18DOI Listing
July 2019

A Map of Human Mitochondrial Protein Interactions Linked to Neurodegeneration Reveals New Mechanisms of Redox Homeostasis and NF-κB Signaling.

Cell Syst 2017 12 8;5(6):564-577.e12. Epub 2017 Nov 8.

Department of Biochemistry, University of Regina, Regina, SK S4S 0A2, Canada. Electronic address:

Mitochondrial protein (MP) dysfunction has been linked to neurodegenerative disorders (NDs); however, the discovery of the molecular mechanisms underlying NDs has been impeded by the limited characterization of interactions governing MP function. Here, using mass spectrometry (MS)-based analysis of 210 affinity-purified mitochondrial (mt) fractions isolated from 27 epitope-tagged human ND-linked MPs in HEK293 cells, we report a high-confidence MP network including 1,964 interactions among 772 proteins (>90% previously unreported). Nearly three-fourths of these interactions were confirmed in mouse brain and multiple human differentiated neuronal cell lines by primary antibody immunoprecipitation and MS, with many linked to NDs and autism. We show that the SOD1-PRDX5 interaction, critical for mt redox homeostasis, can be perturbed by amyotrophic lateral sclerosis-linked SOD1 allelic variants and establish a functional role for ND-linked factors coupled with IκBɛ in NF-κB activation. Our results identify mechanisms for ND-linked MPs and expand the human mt interaction landscape.
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http://dx.doi.org/10.1016/j.cels.2017.10.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5746455PMC
December 2017

Perilipin-2 modulates dietary fat-induced microbial global gene expression profiles in the mouse intestine.

Microbiome 2017 09 6;5(1):117. Epub 2017 Sep 6.

Molecular Medicine, Hospital for Sick Children, 686 Bay Street, Toronto, M5G 0A4, ON, Canada.

Background: Intestinal microbiota are critical determinants of obesity and metabolic disease risk. In previous work, we showed that deletion of the cytoplasmic lipid droplet (CLD) protein perilipin-2 (Plin2) modulates gut microbial community structure and abrogates long-term deleterious effects of a high-fat (HF) diet in mice. However, the impact of Plin2 on microbiome function is unknown.

Results: Here, we used metatranscriptomics to identify differences in microbiome transcript expression in WT and Plin2-null mice following acute exposure to high-fat/low-carbohydrate (HF) or low-fat/high-carbohydrate (LF) diets. Consistent with previous studies, dietary changes resulted in significant taxonomic shifts. Unexpectedly, when fed a HF diet, the microbiota of Plin2-null and WT mice exhibited dramatic shifts in transcript expression despite no discernible shift in community structure. For Plin2-null mice, these changes included the coordinated upregulation of metabolic enzymes directing flux towards the production of growth metabolites such as fatty acids, nucleotides, and amino acids. In contrast, the LF diet did not appear to induce the same dramatic changes in transcript or pathway expression between the two genotypes.

Conclusions: Our data shows that a host genotype can modulate microbiome function without impacting community structure and identify Plin2 as a specific host determinant of diet effects on microbial function. Along with uncovering potential mechanisms for integrating how diet modulates host and microbial metabolism, our findings demonstrate the limits of 16S rRNA surveys to inform on community functional activities and the need to prioritize metatranscriptomic studies to gain more meaningful insights into microbiome function.
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http://dx.doi.org/10.1186/s40168-017-0327-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5588750PMC
September 2017

PhyloPro2.0: a database for the dynamic exploration of phylogenetically conserved proteins and their domain architectures across the Eukarya.

Database (Oxford) 2016 15;2016. Epub 2016 Mar 15.

Program in Molecular Structure and Function, Hospital for Sick Children, 21-9830 PGCRL, 686 Bay Street, Toronto, ON M5G 0A4, Canada and Departments of Biochemistry, Computer Science and Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada

PhyloPro is a database and accompanying web-based application for the construction and exploration of phylogenetic profiles across the Eukarya. In this update article, we present six major new developments in PhyloPro: (i) integration of Pfam-A domain predictions for all proteins; (ii) new summary heatmaps and detailed level views of domain conservation; (iii) an interactive, network-based visualization tool for exploration of domain architectures and their conservation; (iv) ability to browse based on protein functional categories (GOSlim); (v) improvements to the web interface to enhance drill down capability from the heatmap view; and (vi) improved coverage including 164 eukaryotes and 12 reference species. In addition, we provide improved support for downloading data and images in a variety of formats. Among the existing tools available for phylogenetic profiles, PhyloPro provides several innovative domain-based features including a novel domain adjacency visualization tool. These are designed to allow the user to identify and compare proteins with similar domain architectures across species and thus develop hypotheses about the evolution of lineage-specific trajectories. Database URL: http://www.compsysbio.org/phylopro/.
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http://dx.doi.org/10.1093/database/baw013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792532PMC
October 2016

Proteome-wide dataset supporting the study of ancient metazoan macromolecular complexes.

Data Brief 2016 Mar 12;6:715-21. Epub 2015 Dec 12.

Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.

Our analysis examines the conservation of multiprotein complexes among metazoa through use of high resolution biochemical fractionation and precision mass spectrometry applied to soluble cell extracts from 5 representative model organisms Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Strongylocentrotus purpuratus, and Homo sapiens. The interaction network obtained from the data was validated globally in 4 distant species (Xenopus laevis, Nematostella vectensis, Dictyostelium discoideum, Saccharomyces cerevisiae) and locally by targeted affinity-purification experiments. Here we provide details of our massive set of supporting biochemical fractionation data available via ProteomeXchange (PXD002319-PXD002328), PPIs via BioGRID (185267); and interaction network projections via (http://metazoa.med.utoronto.ca) made fully accessible to allow further exploration. The datasets here are related to the research article on metazoan macromolecular complexes in Nature [1].
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http://dx.doi.org/10.1016/j.dib.2015.11.062DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4738005PMC
March 2016

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

Microbiome 2016 Jan 12;4. Epub 2016 Jan 12.

Program in Molecular Structure and Function, The Hospital for Sick Children, Peter Gilgan Center for Research and Learning, 686 Bay Street, Toronto, ON, M5G 0A4, Canada.

Background: Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function.

Results: Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions.

Conclusions: The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome .
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http://dx.doi.org/10.1186/s40168-015-0146-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710996PMC
January 2016

Panorama of ancient metazoan macromolecular complexes.

Nature 2015 Sep 7;525(7569):339-44. Epub 2015 Sep 7.

Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.

Macromolecular complexes are essential to conserved biological processes, but their prevalence across animals is unclear. By combining extensive biochemical fractionation with quantitative mass spectrometry, here we directly examined the composition of soluble multiprotein complexes among diverse metazoan models. Using an integrative approach, we generated a draft conservation map consisting of more than one million putative high-confidence co-complex interactions for species with fully sequenced genomes that encompasses functional modules present broadly across all extant animals. Clustering reveals a spectrum of conservation, ranging from ancient eukaryotic assemblies that have probably served cellular housekeeping roles for at least one billion years, ancestral complexes that have accrued contemporary components, and rarer metazoan innovations linked to multicellularity. We validated these projections by independent co-fractionation experiments in evolutionarily distant species, affinity purification and functional analyses. The comprehensiveness, centrality and modularity of these reconstructed interactomes reflect their fundamental mechanistic importance and adaptive value to animal cell systems.
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http://dx.doi.org/10.1038/nature14877DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5036527PMC
September 2015

Identification of Candidate Adherent-Invasive E. coli Signature Transcripts by Genomic/Transcriptomic Analysis.

PLoS One 2015 30;10(6):e0130902. Epub 2015 Jun 30.

Department of Pediatrics, Stony Brook University, Stony Brook, New York, United States of America.

Adherent-invasive Escherichia coli (AIEC) strains are detected more frequently within mucosal lesions of patients with Crohn's disease (CD). The AIEC phenotype consists of adherence and invasion of intestinal epithelial cells and survival within macrophages of these bacteria in vitro. Our aim was to identify candidate transcripts that distinguish AIEC from non-invasive E. coli (NIEC) strains and might be useful for rapid and accurate identification of AIEC by culture-independent technology. We performed comparative RNA-Sequence (RNASeq) analysis using AIEC strain LF82 and NIEC strain HS during exponential and stationary growth. Differential expression analysis of coding sequences (CDS) homologous to both strains demonstrated 224 and 241 genes with increased and decreased expression, respectively, in LF82 relative to HS. Transition metal transport and siderophore metabolism related pathway genes were up-regulated, while glycogen metabolic and oxidation-reduction related pathway genes were down-regulated, in LF82. Chemotaxis related transcripts were up-regulated in LF82 during the exponential phase, but flagellum-dependent motility pathway genes were down-regulated in LF82 during the stationary phase. CDS that mapped only to the LF82 genome accounted for 747 genes. We applied an in silico subtractive genomics approach to identify CDS specific to AIEC by incorporating the genomes of 10 other previously phenotyped NIEC. From this analysis, 166 CDS mapped to the LF82 genome and lacked homology to any of the 11 human NIEC strains. We compared these CDS across 13 AIEC, but none were homologous in each. Four LF82 gene loci belonging to clustered regularly interspaced short palindromic repeats region (CRISPR)--CRISPR-associated (Cas) genes were identified in 4 to 6 AIEC and absent from all non-pathogenic bacteria. As previously reported, AIEC strains were enriched for pdu operon genes. One CDS, encoding an excisionase, was shared by 9 AIEC strains. Reverse transcription quantitative polymerase chain reaction assays for 6 genes were conducted on fecal and ileal RNA samples from 22 inflammatory bowel disease (IBD), and 32 patients without IBD (non-IBD). The expression of Cas loci was detected in a higher proportion of CD than non-IBD fecal and ileal RNA samples (p <0.05). These results support a comparative genomic/transcriptomic approach towards identifying candidate AIEC signature transcripts.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130902PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4509574PMC
April 2016

New tricks for "old" domains: how novel architectures and promiscuous hubs contributed to the organization and evolution of the ECM.

Genome Biol Evol 2014 Oct 15;6(10):2897-917. Epub 2014 Oct 15.

Program in Molecular Structure and Function, Hospital for Sick Children, Toronto, Ontario, Canada Department of Molecular Genetics, University of Toronto, Ontario, Canada Department of Biochemistry, University of Toronto, Ontario, Canada

The extracellular matrix (ECM) is a defining characteristic of metazoans and consists of a meshwork of self-assembling, fibrous proteins, and their functionally related neighbours. Previous studies, focusing on a limited number of gene families, suggest that vertebrate complexity predominantly arose through the duplication and subsequent modification of retained, preexisting ECM genes. These genes provided the structural underpinnings to support a variety of specialized tissues, as well as a platform for the organization of spatio-temporal signaling and cell migration. However, the relative contributions of ancient versus novel domains to ECM evolution have not been quantified across the full range of ECM proteins. Here, utilizing a high quality list comprising 324 ECM genes, we reveal general and clade-specific domain combinations, identifying domains of eukaryotic and metazoan origin recruited into new roles in approximately two-third of the ECM proteins in humans representing novel vertebrate proteins. We show that, rather than acquiring new domains, sampling of new domain combinations has been key to the innovation of paralogous ECM genes during vertebrate evolution. Applying a novel framework for identifying potentially important, noncontiguous, conserved arrangements of domains, we find that the distinct biological characteristics of the ECM have arisen through unique evolutionary processes. These include the preferential recruitment of novel domains to existing architectures and the utilization of high promiscuity domains in organizing the ECM network around a connected array of structural hubs. Our focus on ECM proteins reveals that distinct types of proteins and/or the biological systems in which they operate have influenced the types of evolutionary forces that drive protein innovation. This emphasizes the need for rigorously defined systems to address questions of evolution that focus on specific systems of interacting proteins.
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http://dx.doi.org/10.1093/gbe/evu228DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224354PMC
October 2014

Identification of a functional connectome for long-term fear memory in mice.

PLoS Comput Biol 2013 3;9(1):e1002853. Epub 2013 Jan 3.

Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada.

Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression.
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http://dx.doi.org/10.1371/journal.pcbi.1002853DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3536620PMC
June 2013

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing.

PLoS One 2012 27;7(4):e36009. Epub 2012 Apr 27.

Program in Molecular Structure and Function, The Hospital for Sick Children, Toronto, Canada.

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0036009PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3338770PMC
September 2012

Toward a systems level view of the ECM and related proteins: a framework for the systematic definition and analysis of biological systems.

Proteins 2012 Jun 13;80(6):1522-44. Epub 2012 Feb 13.

Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.

Advances in high throughput 'omic technologies are starting to provide unprecedented insights into how components of biological systems are organized and interact. Key to exploiting these datasets is the definition of the components that comprise the system of interest. Although a variety of knowledge bases exist that capture such information, a major challenge is determining how these resources may be best utilized. Here we present a systematic curation strategy to define a systems-level view of the human extracellular matrix (ECM)--a three-dimensional meshwork of proteins and polysaccharides that impart structure and mechanical stability to tissues. Employing our curation strategy we define a set of 357 proteins that represent core components of the ECM, together with an additional 524 genes that mediate related functional roles, and construct a map of their physical interactions. Topological properties help identify modules of functionally related proteins, including those involved in cell adhesion, bone formation and blood clotting. Because of its major role in cell adhesion, proliferation and morphogenesis, defects in the ECM have been implicated in cancer, atherosclerosis, asthma, fibrosis, and arthritis. We use MeSH annotations to identify modules enriched for specific disease terms that aid to strengthen existing as well as predict novel gene-disease associations. Mapping expression and conservation data onto the network reveal modules evolved in parallel to convey tissue-specific functionality on otherwise broadly expressed units. In addition to demonstrating an effective workflow for defining biological systems, this study crystallizes our current knowledge surrounding the organization of the ECM.
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http://dx.doi.org/10.1002/prot.24036DOI Listing
June 2012

Genetic interaction maps in Escherichia coli reveal functional crosstalk among cell envelope biogenesis pathways.

PLoS Genet 2011 Nov 17;7(11):e1002377. Epub 2011 Nov 17.

Banting and Best Department of Medical Research, Donnelly Centre, University of Toronto, Toronto, Canada.

As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among > 235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.
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http://dx.doi.org/10.1371/journal.pgen.1002377DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219608PMC
November 2011

PhyloPro: a web-based tool for the generation and visualization of phylogenetic profiles across Eukarya.

Bioinformatics 2011 Mar 19;27(6):877-8. Epub 2011 Jan 19.

Program in Molecular Structure and Function, Hospital for Sick Children, Canada.

Summary: With increasing numbers of eukaryotic genome sequences, phylogenetic profiles of eukaryotic genes are becoming increasingly informative. Here, we introduce a new web-tool Phylopro (http://compsysbio.org/phylopro/), which uses the 120 available eukaryotic genome sequences to visualize the evolutionary trajectories of user-defined subsets of model organism genes. Applied to pathways or complexes, PhyloPro allows the user to rapidly identify core conserved elements of biological processes together with those that may represent lineage-specific innovations. PhyloPro thus provides a valuable resource for the evolutionary and comparative studies of biological systems.
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http://dx.doi.org/10.1093/bioinformatics/btr023DOI Listing
March 2011

Expanding the landscape of chromatin modification (CM)-related functional domains and genes in human.

PLoS One 2010 Nov 29;5(11):e14122. Epub 2010 Nov 29.

Program in Molecular Structure & Function, Hospital for Sick Children, Toronto, Canada.

Chromatin modification (CM) plays a key role in regulating transcription, DNA replication, repair and recombination. However, our knowledge of these processes in humans remains very limited. Here we use computational approaches to study proteins and functional domains involved in CM in humans. We analyze the abundance and the pair-wise domain-domain co-occurrences of 25 well-documented CM domains in 5 model organisms: yeast, worm, fly, mouse and human. Results show that domains involved in histone methylation, DNA methylation, and histone variants are remarkably expanded in metazoan, reflecting the increased demand for cell type-specific gene regulation. We find that CM domains tend to co-occur with a limited number of partner domains and are hence not promiscuous. This property is exploited to identify 47 potentially novel CM domains, including 24 DNA-binding domains, whose role in CM has received little attention so far. Lastly, we use a consensus Machine Learning approach to predict 379 novel CM genes (coding for 329 proteins) in humans based on domain compositions. Several of these predictions are supported by very recent experimental studies and others are slated for experimental verification. Identification of novel CM genes and domains in humans will aid our understanding of fundamental epigenetic processes that are important for stem cell differentiation and cancer biology. Information on all the candidate CM domains and genes reported here is publicly available.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0014122PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2993927PMC
November 2010

DAnCER: disease-annotated chromatin epigenetics resource.

Nucleic Acids Res 2011 Jan 28;39(Database issue):D889-94. Epub 2010 Sep 28.

Hospital for Sick Children, Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada.

Chromatin modification (CM) is a set of epigenetic processes that govern many aspects of DNA replication, transcription and repair. CM is carried out by groups of physically interacting proteins, and their disruption has been linked to a number of complex human diseases. CM remains largely unexplored, however, especially in higher eukaryotes such as human. Here we present the DAnCER resource, which integrates information on genes with CM function from five model organisms, including human. Currently integrated are gene functional annotations, Pfam domain architecture, protein interaction networks and associated human diseases. Additional supporting evidence includes orthology relationships across organisms, membership in protein complexes, and information on protein 3D structure. These data are available for 962 experimentally confirmed and manually curated CM genes and for over 5000 genes with predicted CM function on the basis of orthology and domain composition. DAnCER allows visual explorations of the integrated data and flexible query capabilities using a variety of data filters. In particular, disease information and functional annotations are mapped onto the protein interaction networks, enabling the user to formulate new hypotheses on the function and disease associations of a given gene based on those of its interaction partners. DAnCER is freely available at http://wodaklab.org/dancer/.
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http://dx.doi.org/10.1093/nar/gkq857DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013761PMC
January 2011

The evolutionary landscape of the chromatin modification machinery reveals lineage specific gains, expansions, and losses.

Proteins 2010 Jul;78(9):2075-89

Program in Molecular Structure and Function, Hospital for Sick Children, Toronto, Ontario, Canada.

Model organisms such as yeast, fly, and worm have played a defining role in the study of many biological systems. A significant challenge remains in translating this information to humans. Of critical importance is the ability to differentiate those components where knowledge of function and interactions may be reliably inferred from those that represent lineage-specific innovations. To address this challenge, we use chromatin modification (CM) as a model system for exploring the evolutionary properties of their components in the context of their known functions and interactions. Collating previously identified components of CM from yeast, worm, fly, and human, we identified a "core" set of 50 CM genes displaying consistent orthologous relationships that likely retain their interactions and functions across taxa. In addition, we catalog many components that demonstrate lineage specific expansions and losses, highlighting much duplication within vertebrates that may reflect an expanded repertoire of regulatory mechanisms. Placed in the context of a high-quality protein-protein interaction network, we find, contrary to existing views of evolutionary modularity, that CM complex components display a mosaic of evolutionary histories: a core set of highly conserved genes, together with sets displaying lineage specific innovations. Although focused on CM, this study provides a template for differentiating those genes which are likely to retain their functions and interactions across species. As such, in addition to informing on the evolution of CM as a system, this study provides a set of comparative genomic approaches that can be generally applied to any biological systems.
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http://dx.doi.org/10.1002/prot.22723DOI Listing
July 2010

Comparison of substrate specificity of the ubiquitin ligases Nedd4 and Nedd4-2 using proteome arrays.

Mol Syst Biol 2009 1;5:333. Epub 2009 Dec 1.

Programs in Cell Biology and Molecular Structure and Function, The Hospital for Sick Children, Toronto, Ontario, Canada.

Target recognition by the ubiquitin system is mediated by E3 ubiquitin ligases. Nedd4 family members are E3 ligases comprised of a C2 domain, 2-4 WW domains that bind PY motifs (L/PPxY) and a ubiquitin ligase HECT domain. The nine Nedd4 family proteins in mammals include two close relatives: Nedd4 (Nedd4-1) and Nedd4L (Nedd4-2), but their global substrate recognition or differences in substrate specificity are unknown. We performed in vitro ubiquitylation and binding assays of human Nedd4-1 and Nedd4-2, and rat-Nedd4-1, using protein microarrays spotted with approximately 8200 human proteins. Top hits (substrates) for the ubiquitylation and binding assays mostly contain PY motifs. Although several substrates were recognized by both Nedd4-1 and Nedd4-2, others were specific to only one, with several Tyr kinases preferred by Nedd4-1 and some ion channels by Nedd4-2; this was subsequently validated in vivo. Accordingly, Nedd4-1 knockdown or knockout in cells led to sustained signalling via some of its substrate Tyr kinases (e.g. FGFR), suggesting Nedd4-1 suppresses their signalling. These results demonstrate the feasibility of identifying substrates and deciphering substrate specificity of mammalian E3 ligases.
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http://dx.doi.org/10.1038/msb.2009.85DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2824488PMC
April 2010

The Modular Organization of Protein Interactions in Escherichia coli.

PLoS Comput Biol 2009 Oct 2;5(10):e1000523. Epub 2009 Oct 2.

Program in Molecular Structure and Function, Hospital for Sick Children, Toronto, Ontario, Canada.

Escherichia coli serves as an excellent model for the study of fundamental cellular processes such as metabolism, signalling and gene expression. Understanding the function and organization of proteins within these processes is an important step towards a 'systems' view of E. coli. Integrating experimental and computational interaction data, we present a reliable network of 3,989 functional interactions between 1,941 E. coli proteins ( approximately 45% of its proteome). These were combined with a recently generated set of 3,888 high-quality physical interactions between 918 proteins and clustered to reveal 316 discrete modules. In addition to known protein complexes (e.g., RNA and DNA polymerases), we identified modules that represent biochemical pathways (e.g., nitrate regulation and cell wall biosynthesis) as well as batteries of functionally and evolutionarily related processes. To aid the interpretation of modular relationships, several case examples are presented, including both well characterized and novel biochemical systems. Together these data provide a global view of the modular organization of the E. coli proteome and yield unique insights into structural and evolutionary relationships in bacterial networks.
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http://dx.doi.org/10.1371/journal.pcbi.1000523DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2739439PMC
October 2009
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