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Created January 26, 2013 05:05
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Publications for testing bibliography sorting in Cell
Raw
cell-bib-sort.rdf
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<foaf:Person>
<foaf:surname>Del Giorgio</foaf:surname>
<foaf:givenname>Paul A.</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Gasol</foaf:surname>
<foaf:givenname>Josep M.</foaf:givenname>
</foaf:Person>
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<link:link rdf:resource="#item_36"/>
<dc:title>A comparative study of the cytometric characteristics of High and Low nucleic-acid bacterioplankton cells from different aquatic ecosystems</dc:title>
<dcterms:abstract>Flow cytometry has revealed the existence of two distinct fractions of bacterioplankton cells, characterized by high and low nucleic acid contents (HNA and LNA cells). Although these fractions seem ubiquitous in aquatic systems, little is known concerning the variation in the cytometric parameters used to characterize them. We have performed cytometric analyses of samples from a wide range of aquatic systems to determine the magnitude and variability in the cytometric characteristics of HNA/LNA. We show that neither group is associated to a fixed level of fluorescence and of light scatter. Rather, the relative position of HNA and LNA in the fluorescence versus side scatter cytograms varies greatly, both within and among ecosystems. Although the cytometric parameters of both groups tend to covary, there is often uncoupling between the two, particularly in light scatter. Our results show that, although the basic HNA/LNA configuration is present in most samples, its cytometric expression changes greatly in different ecosystems and along productivity gradients. The patterns in cytometric parameters do not support the simple, dichotomous view of HNA and LNA as active and inactive cells, or the notion of two distinct and independent communities, but rather suggest that there may be cells that are intrinsic to each fraction, as well as others that may exchange between fractions.</dcterms:abstract>
<bib:pages>2050–2066</bib:pages>
<dc:date>2007</dc:date>
<z:language>en</z:language>
<dc:identifier>
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<dcterms:dateSubmitted>2013-01-25 22:28:33</dcterms:dateSubmitted>
<z:libraryCatalog>Wiley Online Library</z:libraryCatalog>
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<bib:Journal rdf:about="urn:issn:1462-2920">
<dc:title>Environmental Microbiology</dc:title>
<prism:volume>9</prism:volume>
<prism:number>8</prism:number>
<dc:identifier>DOI 10.1111/j.1462-2920.2007.01321.x</dc:identifier>
<dc:identifier>ISSN 1462-2920</dc:identifier>
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<foaf:Person>
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<foaf:givenname>Thierry</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Maurice</foaf:surname>
<foaf:givenname>Corinne F.</foaf:givenname>
</foaf:Person>
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<link:link rdf:resource="#item_33"/>
<link:link rdf:resource="#item_34"/>
<dc:subject>
<z:AutomaticTag><rdf:value>Ecology</rdf:value></z:AutomaticTag>
</dc:subject>
<dc:subject>
<z:AutomaticTag>
<rdf:value>Geoecology/Natural Processes</rdf:value>
</z:AutomaticTag>
</dc:subject>
<dc:subject>
<z:AutomaticTag>
<rdf:value>Microbial Ecology</rdf:value>
</z:AutomaticTag>
</dc:subject>
<dc:subject>
<z:AutomaticTag><rdf:value>Microbiology</rdf:value></z:AutomaticTag>
</dc:subject>
<dc:subject>
<z:AutomaticTag>
<rdf:value>Nature Conservation</rdf:value>
</z:AutomaticTag>
</dc:subject>
<dc:title>A Single-Cell Analysis of Virioplankton Adsorption, Infection, and Intracellular Abundance in Different Bacterioplankton Physiologic Categories</dc:title>
<dcterms:abstract>Culture studies of phage–host systems have shown that phage proliferation strongly depends on the physiological state of the host, but it is still unclear to what extent this holds true within aquatic ecosystems. We used a combination of flow sorting and electron microscopy to explore how the frequency of bacterial cells with attached viruses (FCAV), of visibly infected cells, and the number of intracellular viruses are distributed within five physiologic categories: cells with high (HNA) and low (LNA) nucleic acid content, with a compromised membrane, in division, and with an intact-looking morphology. FCAV was not different between the cellular physiologic categories, suggesting low influence of host physiology on viral adsorption. Infected cells were found within all the physiologic categories, besides the dividing cells, but showed different levels of new virion production, with the abundance of intracellular viruses ranked as follows: HNA > intact-looking cells > LNA > compromised membrane cells. These results favor the physiological control hypothesis of viral progeny production. The calculation of viral production rate of the HNA and LNA cells show that viral infection of HNA cells likely accounts for the majority of viral production. It also show that cells considered as less active can still act as resources for phages, although they contain much less intracellular phage particles.</dcterms:abstract>
<bib:pages>669-678</bib:pages>
<dc:date>2011/10/01</dc:date>
<z:language>en</z:language>
<dc:identifier>
<dcterms:URI>
<rdf:value>http://link.springer.com/article/10.1007/s00248-011-9862-3</rdf:value>
</dcterms:URI>
</dc:identifier>
<dcterms:dateSubmitted>2013-01-25 22:20:57</dcterms:dateSubmitted>
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<dc:title>Microbial Ecology</dc:title>
<prism:volume>62</prism:volume>
<prism:number>3</prism:number>
<dcterms:alternative>Microb Ecol</dcterms:alternative>
<dc:identifier>DOI 10.1007/s00248-011-9862-3</dc:identifier>
<dc:identifier>ISSN 0095-3628, 1432-184X</dc:identifier>
</bib:Journal>
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<z:itemType>journalArticle</z:itemType>
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<rdf:Seq>
<rdf:li>
<foaf:Person>
<foaf:surname>Crow</foaf:surname>
<foaf:givenname>Yanick J.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Hayward</foaf:surname>
<foaf:givenname>Bruce E.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Parmar</foaf:surname>
<foaf:givenname>Rekha</foaf:givenname>
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<rdf:li>
<foaf:Person>
<foaf:surname>Robins</foaf:surname>
<foaf:givenname>Peter</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Leitch</foaf:surname>
<foaf:givenname>Andrea</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Ali</foaf:surname>
<foaf:givenname>Manir</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Black</foaf:surname>
<foaf:givenname>Deborah N.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>van Bokhoven</foaf:surname>
<foaf:givenname>Hans</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Brunner</foaf:surname>
<foaf:givenname>Han G.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Hamel</foaf:surname>
<foaf:givenname>Ben C.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Corry</foaf:surname>
<foaf:givenname>Peter C.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Cowan</foaf:surname>
<foaf:givenname>Frances M.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Frints</foaf:surname>
<foaf:givenname>Suzanne G.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Klepper</foaf:surname>
<foaf:givenname>Joerg</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Livingston</foaf:surname>
<foaf:givenname>John H.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Lynch</foaf:surname>
<foaf:givenname>Sally Ann</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Massey</foaf:surname>
<foaf:givenname>Roger F.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Meritet</foaf:surname>
<foaf:givenname>Jean François</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Michaud</foaf:surname>
<foaf:givenname>Jacques L.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Ponsot</foaf:surname>
<foaf:givenname>Gerard</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Voit</foaf:surname>
<foaf:givenname>Thomas</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Lebon</foaf:surname>
<foaf:givenname>Pierre</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Bonthron</foaf:surname>
<foaf:givenname>David T.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Jackson</foaf:surname>
<foaf:givenname>Andrew P.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Barnes</foaf:surname>
<foaf:givenname>Deborah E.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Lindahl</foaf:surname>
<foaf:givenname>Tomas</foaf:givenname>
</foaf:Person>
</rdf:li>
</rdf:Seq>
</bib:authors>
<link:link rdf:resource="#item_52"/>
<link:link rdf:resource="#item_51"/>
<dc:title>Mutations in the gene encoding the 3′-5′ DNA exonuclease TREX1 cause Aicardi-Goutières syndrome at the AGS1 locus</dc:title>
<dcterms:abstract>Aicardi-Goutières syndrome (AGS) presents as a severe neurological brain disease and is a genetic mimic of the sequelae of transplacentally acquired viral infection1, 2. Evidence exists for a perturbation of innate immunity as a primary pathogenic event in the disease phenotype3. Here, we show that TREX1, encoding the major mammalian 3' 5' DNA exonuclease4, is the AGS1 gene, and AGS-causing mutations result in abrogation of TREX1 enzyme activity. Similar loss of function in the Trex1 -/- mouse leads to an inflammatory phenotype5. Our findings suggest an unanticipated role for TREX1 in processing or clearing anomalous DNA structures, failure of which results in the triggering of an abnormal innate immune response.</dcterms:abstract>
<bib:pages>917-920</bib:pages>
<dc:date>August 2006</dc:date>
<z:language>en</z:language>
<dc:identifier>
<dcterms:URI>
<rdf:value>http://www.nature.com/ng/journal/v38/n8/abs/ng1845.html</rdf:value>
</dcterms:URI>
</dc:identifier>
<dcterms:dateSubmitted>2013-01-26 03:16:39</dcterms:dateSubmitted>
<z:libraryCatalog>www.nature.com</z:libraryCatalog>
<dc:rights>© 2006 Nature Publishing Group</dc:rights>
</bib:Article>
<bib:Journal rdf:about="urn:issn:1061-4036">
<dc:title>Nature Genetics</dc:title>
<prism:volume>38</prism:volume>
<prism:number>8</prism:number>
<dcterms:alternative>Nat Genet</dcterms:alternative>
<dc:identifier>DOI 10.1038/ng1845</dc:identifier>
<dc:identifier>ISSN 1061-4036</dc:identifier>
</bib:Journal>
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<dc:title>Nature Genetics</dc:title>
<prism:volume>38</prism:volume>
<prism:number>8</prism:number>
<dcterms:alternative>Nat Genet</dcterms:alternative>
<dc:identifier>DOI 10.1038/ng1842</dc:identifier>
<dc:identifier>ISSN 1061-4036</dc:identifier>
</bib:Journal>
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<rdf:Seq>
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<foaf:Person>
<foaf:surname>Crow</foaf:surname>
<foaf:givenname>Yanick J.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Leitch</foaf:surname>
<foaf:givenname>Andrea</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Hayward</foaf:surname>
<foaf:givenname>Bruce E.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Garner</foaf:surname>
<foaf:givenname>Anna</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Parmar</foaf:surname>
<foaf:givenname>Rekha</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Griffith</foaf:surname>
<foaf:givenname>Elen</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Ali</foaf:surname>
<foaf:givenname>Manir</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Semple</foaf:surname>
<foaf:givenname>Colin</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Aicardi</foaf:surname>
<foaf:givenname>Jean</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Babul-Hirji</foaf:surname>
<foaf:givenname>Riyana</foaf:givenname>
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<rdf:li>
<foaf:Person>
<foaf:surname>Baumann</foaf:surname>
<foaf:givenname>Clarisse</foaf:givenname>
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<foaf:Person>
<foaf:surname>Baxter</foaf:surname>
<foaf:givenname>Peter</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Bertini</foaf:surname>
<foaf:givenname>Enrico</foaf:givenname>
</foaf:Person>
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<foaf:Person>
<foaf:surname>Chandler</foaf:surname>
<foaf:givenname>Kate E.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Chitayat</foaf:surname>
<foaf:givenname>David</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Cau</foaf:surname>
<foaf:givenname>Daniel</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Déry</foaf:surname>
<foaf:givenname>Catherine</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Fazzi</foaf:surname>
<foaf:givenname>Elisa</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Goizet</foaf:surname>
<foaf:givenname>Cyril</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>King</foaf:surname>
<foaf:givenname>Mary D.</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Klepper</foaf:surname>
<foaf:givenname>Joerg</foaf:givenname>
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<rdf:li>
<foaf:Person>
<foaf:surname>Lacombe</foaf:surname>
<foaf:givenname>Didier</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Lanzi</foaf:surname>
<foaf:givenname>Giovanni</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Lyall</foaf:surname>
<foaf:givenname>Hermione</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Martínez-Frías</foaf:surname>
<foaf:givenname>María Luisa</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
<foaf:Person>
<foaf:surname>Mathieu</foaf:surname>
<foaf:givenname>Michèle</foaf:givenname>
</foaf:Person>
</rdf:li>
<rdf:li>
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<foaf:surname>McKeown</foaf:surname>
<foaf:givenname>Carole</foaf:givenname>
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<foaf:surname>Monier</foaf:surname>
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</foaf:Person>
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<foaf:Person>
<foaf:surname>Oade</foaf:surname>
<foaf:givenname>Yvette</foaf:givenname>
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<foaf:Person>
<foaf:surname>Quarrell</foaf:surname>
<foaf:givenname>Oliver W.</foaf:givenname>
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<foaf:Person>
<foaf:surname>Rittey</foaf:surname>
<foaf:givenname>Christopher D.</foaf:givenname>
</foaf:Person>
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<foaf:Person>
<foaf:surname>Rogers</foaf:surname>
<foaf:givenname>R. Curtis</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Sanchis</foaf:surname>
<foaf:givenname>Amparo</foaf:givenname>
</foaf:Person>
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<foaf:Person>
<foaf:surname>Stephenson</foaf:surname>
<foaf:givenname>John B. P.</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Tacke</foaf:surname>
<foaf:givenname>Uta</foaf:givenname>
</foaf:Person>
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<rdf:li>
<foaf:Person>
<foaf:surname>Till</foaf:surname>
<foaf:givenname>Marianne</foaf:givenname>
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<foaf:givenname>Thomas</foaf:givenname>
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<foaf:Person>
<foaf:surname>Weschke</foaf:surname>
<foaf:givenname>Bernhard</foaf:givenname>
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<foaf:surname>Woods</foaf:surname>
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<foaf:surname>Ponting</foaf:surname>
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<foaf:surname>Jackson</foaf:surname>
<foaf:givenname>Andrew P.</foaf:givenname>
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<link:link rdf:resource="#item_54"/>
<dc:title>Mutations in genes encoding ribonuclease H2 subunits cause Aicardi-Goutières syndrome and mimic congenital viral brain infection</dc:title>
<dcterms:abstract>Aicardi-Goutières syndrome (AGS) is an autosomal recessive neurological disorder, the clinical and immunological features of which parallel those of congenital viral infection. Here we define the composition of the human ribonuclease H2 enzyme complex and show that AGS can result from mutations in the genes encoding any one of its three subunits. Our findings demonstrate a role for ribonuclease H in human neurological disease and suggest an unanticipated relationship between ribonuclease H2 and the antiviral immune response that warrants further investigation.</dcterms:abstract>
<bib:pages>910-916</bib:pages>
<dc:date>August 2006</dc:date>
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<dcterms:dateSubmitted>2013-01-26 03:17:45</dcterms:dateSubmitted>
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<dc:title>Structure of the SAM-II riboswitch bound to S-adenosylmethionine</dc:title>
<dcterms:abstract>In bacteria, numerous genes harbor regulatory elements in the 5' untranslated regions of their mRNA, termed riboswitches, which control gene expression by binding small-molecule metabolites. These sequences influence the secondary and tertiary structure of the RNA in a ligand-dependent manner, thereby directing its transcription or translation. The crystal structure of an S-adenosylmethionine–responsive riboswitch found predominantly in proteobacteria, SAM-II, has been solved to reveal a second means by which RNA interacts with this important cellular metabolite. Notably, this is the first structure of a complete riboswitch containing all sequences associated with both the ligand binding aptamer domain and the regulatory expression platform. Chemical probing of this RNA in the absence and presence of ligand shows how the structure changes in response to S-adenosylmethionine to sequester the ribosomal binding site and affect translational gene regulation.</dcterms:abstract>
<bib:pages>177-182</bib:pages>
<dc:date>February 2008</dc:date>
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<dc:rights>© 2008 Nature Publishing Group</dc:rights>
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<dc:title>Nature Structural &amp; Molecular Biology</dc:title>
<prism:volume>15</prism:volume>
<prism:number>2</prism:number>
<dcterms:alternative>Nat Struct Mol Biol</dcterms:alternative>
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<link:link rdf:resource="#item_18"/>
<dc:title>Origin of life: The RNA world</dc:title>
<bib:pages>618-618</bib:pages>
<dc:date>February 20, 1986</dc:date>
<z:language>en</z:language>
<z:shortTitle>Origin of life</z:shortTitle>
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<dc:title>Long-range pseudoknot interactions dictate the regulatory response in the tetrahydrofolate riboswitch</dc:title>
<dcterms:abstract>Tetrahydrofolate (THF), a biologically active form of the vitamin folate (B9), is an essential cofactor in one-carbon transfer reactions. In bacteria, expression of folate-related genes is controlled by feedback modulation in response to specific binding of THF and related compounds to a riboswitch. Here, we present the X-ray structures of the THF-sensing domain from the Eubacterium siraeum riboswitch in the ligand-bound and unbound states. The structure reveals an “inverted” three-way junctional architecture, most unusual for riboswitches, with the junction located far from the regulatory helix P1 and not directly participating in helix P1 formation. Instead, the three-way junction, stabilized by binding to the ligand, aligns the riboswitch stems for long-range tertiary pseudoknot interactions that contribute to the organization of helix P1 and therefore stipulate the regulatory response of the riboswitch. The pterin moiety of the ligand docks in a semiopen pocket adjacent to the junction, where it forms specific hydrogen bonds with two moderately conserved pyrimidines. The aminobenzoate moiety stacks on a guanine base, whereas the glutamate moiety does not appear to make strong interactions with the RNA. In contrast to other riboswitches, these findings demonstrate that the THF riboswitch uses a limited number of available determinants for ligand recognition. Given that modern antibiotics target folate metabolism, the THF riboswitch structure provides insights on mechanistic aspects of riboswitch function and may help in manipulating THF levels in pathogenic bacteria.</dcterms:abstract>
<bib:pages>14801-14806</bib:pages>
<dc:date>09/06/2011</dc:date>
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<dc:title>Proceedings of the National Academy of Sciences</dc:title>
<prism:volume>108</prism:volume>
<prism:number>36</prism:number>
<dcterms:alternative>PNAS</dcterms:alternative>
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<foaf:givenname>Alexander</foaf:givenname>
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<foaf:surname>Patel</foaf:surname>
<foaf:givenname>Dinshaw J.</foaf:givenname>
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<dc:title>Structural Insights into Ligand Recognition by a Sensing Domain of the Cooperative Glycine Riboswitch</dc:title>
<dcterms:abstract>Summary
Glycine riboswitches regulate gene expression by feedback modulation in response to cooperative binding to glycine. Here, we report on crystal structures of the second glycine-sensing domain from the Vibrio cholerae riboswitch in the ligand-bound and unbound states. This domain adopts a three-helical fold that centers on a three-way junction and accommodates glycine within a bulge-containing binding pocket above the junction. Glycine recognition is facilitated by a pair of bound Mg2+ cations and governed by specific interactions and shape complementarity with the pocket. A conserved adenine extrudes from the binding pocket and intercalates into the junction implying that glycine binding in the context of the complete riboswitch could impact on gene expression by stabilizing the riboswitch junction and regulatory P1 helix. Analysis of riboswitch interactions in the crystal and footprinting experiments indicates that adjacent glycine-sensing modules of the riboswitch could form specific interdomain interactions, thereby potentially contributing to the cooperative response.</dcterms:abstract>
<bib:pages>774-786</bib:pages>
<dc:date>December 10, 2010</dc:date>
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<bib:Journal rdf:about="urn:issn:1097-2765">
<dc:title>Molecular Cell</dc:title>
<prism:volume>40</prism:volume>
<prism:number>5</prism:number>
<dcterms:alternative>Molecular Cell</dcterms:alternative>
<dc:identifier>DOI 10.1016/j.molcel.2010.11.026</dc:identifier>
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<foaf:surname>Lee</foaf:surname>
<foaf:givenname>Elaine R.</foaf:givenname>
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<foaf:surname>Weinberg</foaf:surname>
<foaf:givenname>Zasha</foaf:givenname>
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<foaf:surname>Sudarsan</foaf:surname>
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<link:link rdf:resource="#item_30"/>
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<dc:title>An Allosteric Self-Splicing Ribozyme Triggered by a Bacterial Second Messenger</dc:title>
<dcterms:abstract>Group I self-splicing ribozymes commonly function as components of selfish mobile genetic elements. We identified an allosteric group I ribozyme, wherein self-splicing is regulated by a distinct riboswitch class that senses the bacterial second messenger c-di-GMP. The tandem RNA sensory system resides in the 5′ untranslated region of the messenger RNA for a putative virulence gene in the pathogenic bacterium Clostridium difficile. c-di-GMP binding by the riboswitch induces folding changes at atypical splice site junctions to modulate alternative RNA processing. Our findings indicate that some self-splicing ribozymes are not selfish elements but are harnessed by cells as metabolite sensors and genetic regulators.</dcterms:abstract>
<bib:pages>845-848</bib:pages>
<dc:date>08/13/2010</dc:date>
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<dc:title>Science</dc:title>
<prism:volume>329</prism:volume>
<prism:number>5993</prism:number>
<dcterms:alternative>Science</dcterms:alternative>
<dc:identifier>DOI 10.1126/science.1190713</dc:identifier>
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<foaf:givenname>Eun-Jin</foaf:givenname>
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<foaf:surname>Groisman</foaf:surname>
<foaf:givenname>Eduardo A.</foaf:givenname>
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<link:link rdf:resource="#item_28"/>
<link:link rdf:resource="#item_27"/>
<dc:subject>
<z:AutomaticTag><rdf:value>genetics</rdf:value></z:AutomaticTag>
</dc:subject>
<dc:subject>
<z:AutomaticTag><rdf:value>Genomics</rdf:value></z:AutomaticTag>
</dc:subject>
<dc:subject>
<z:AutomaticTag><rdf:value>Microbiology</rdf:value></z:AutomaticTag>
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<rdf:value>molecular biology</rdf:value>
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<dc:title>Control of a Salmonella virulence locus by an ATP-sensing leader messenger RNA</dc:title>
<dcterms:abstract>The facultative intracellular pathogen Salmonella enterica resides within a membrane-bound compartment inside macrophages. This compartment must be acidified for Salmonella to survive within macrophages, possibly because acidic pH promotes expression of Salmonella virulence proteins. We reasoned that Salmonella might sense its surroundings have turned acidic not only upon protonation of the extracytoplasmic domain of a protein sensor but also by an increase in cytosolic ATP levels, because conditions that enhance the proton gradient across the bacterial inner membrane stimulate ATP synthesis. Here we report that an increase in cytosolic ATP promotes transcription of the coding region for the virulence gene mgtC, which is the most highly induced horizontally acquired gene when Salmonella is inside macrophages. This transcript is induced both upon media acidification and by physiological conditions that increase ATP levels independently of acidification. ATP is sensed by the coupling/uncoupling of transcription of the unusually long mgtC leader messenger RNA and translation of a short open reading frame located in this region. A mutation in the mgtC leader messenger RNA that eliminates the response to ATP hinders mgtC expression inside macrophages and attenuates Salmonella virulence in mice. Our results define a singular example of an ATP-sensing leader messenger RNA. Moreover, they indicate that pathogens can interpret extracellular cues by the impact they have on cellular metabolites.</dcterms:abstract>
<bib:pages>271-275</bib:pages>
<dc:date>June 14, 2012</dc:date>
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<dc:rights>© 2012 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.</dc:rights>
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<dc:title>Nature</dc:title>
<prism:volume>486</prism:volume>
<prism:number>7402</prism:number>
<dcterms:alternative>Nature</dcterms:alternative>
<dc:identifier>DOI 10.1038/nature11090</dc:identifier>
<dc:identifier>ISSN 0028-0836</dc:identifier>
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<foaf:surname>Manley</foaf:surname>
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<dc:title>Inactivation of the SR Protein Splicing Factor ASF/SF2 Results in Genomic Instability</dc:title>
<bib:pages>365-378</bib:pages>
<dc:date>August 12 2005</dc:date>
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<dc:title>Cell</dc:title>
<prism:volume>122</prism:volume>
<prism:number>3</prism:number>
<dc:identifier>DOI 10.1016/j.cell.2005.06.008</dc:identifier>
<dc:identifier>ISSN 0092-8674</dc:identifier>
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<foaf:givenname>Yingfu</foaf:givenname>
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<foaf:givenname>Ronald R.</foaf:givenname>
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<dc:title>Kinetics of RNA Degradation by Specific Base Catalysis of Transesterification Involving the 2‘-Hydroxyl Group</dc:title>
<dcterms:abstract>A detailed understanding of the susceptibility of RNA phosphodiesters to specific base-catalyzed cleavage is necessary to approximate the stability of RNA under various conditions. In addition, quantifying the rate enhancements that can be produced exclusively by this common cleavage mechanism is needed to fully interpret the mechanisms employed by ribonucleases and by RNA-cleaving ribozymes. Chimeric DNA/RNA oligonucleotides were used to examine the rates of hydroxide-dependent degradation of RNA phosphodiesters under reaction conditions that simulate those of biological systems. Under neutral or alkaline pH conditions, the dominant pathway for RNA degradation is an internal phosphoester transfer reaction that is promoted by specific base catalysis. As expected, increasing the concentration of hydroxide ion, increasing the concentration of divalent magnesium, or raising the temperature accelerates strand scission. In most instances, the identities of the nucleotide bases that flank the target RNA linkage have a negligible effect on the pKa of the nucleophilic 2?-hydroxyl group, and only have a minor effect on the maximum rate constant for the transesterification reaction. Under representative physiological conditions, specific base catalysis of RNA cleavage generates a maximum rate enhancement of ?100?000-fold over the background rate of RNA transesterification. The kinetic parameters reported herein provide theoretical limits for the stability of RNA polymers and for the proficiency of RNA-cleaving enzymes and enzyme mimics that exclusively employ a mechanism of general base catalysis.</dcterms:abstract>
<bib:pages>5364-5372</bib:pages>
<dc:date>June 1, 1999</dc:date>
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<dc:title>Journal of the American Chemical Society</dc:title>
<prism:volume>121</prism:volume>
<prism:number>23</prism:number>
<dcterms:alternative>J. Am. Chem. Soc.</dcterms:alternative>
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<foaf:givenname>Kim</foaf:givenname>
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<dc:title>Cohesin: a catenase with separate entry and exit gates?</dc:title>
<dcterms:abstract>Cohesin confers both intrachromatid and interchromatid cohesion through formation of a tripartite ring within which DNA is thought to be entrapped. Here, I discuss what is known about the four stages of the cohesin ring cycle using the ring model as an intellectual framework. I postulate that cohesin loading onto chromosomes, catalysed by a separate complex called kollerin, is mediated by the entry of DNA into cohesin rings, whereas dissociation, catalysed by Wapl and several other cohesin subunits (an activity that will be called releasin here), is mediated by the subsequent exit of DNA. I suggest that the ring's entry and exit gates may be separate, with the former and latter taking place at Smc1–Smc3 and Smc3–kleisin interfaces, respectively. Establishment of cohesion during S phase involves neutralization of releasin through acetylation of Smc3 at a site close to the putative exit gate of DNA, which locks rings shut until opened irreversibly by kleisin cleavage through the action of separase, an event that triggers the metaphase to anaphase transition.</dcterms:abstract>
<bib:pages>1170-1177</bib:pages>
<dc:date>October 2011</dc:date>
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<dc:rights>© 2011 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.</dc:rights>
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<dc:title>Nature Cell Biology</dc:title>
<prism:volume>13</prism:volume>
<prism:number>10</prism:number>
<dcterms:alternative>Nat Cell Biol</dcterms:alternative>
<dc:identifier>DOI 10.1038/ncb2349</dc:identifier>
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<foaf:givenname>Kim</foaf:givenname>
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<foaf:surname>Schleiffer</foaf:surname>
<foaf:givenname>Alexander</foaf:givenname>
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<link:link rdf:resource="#item_60"/>
<dc:title>From a single double helix to paired double helices and back.</dc:title>
<dcterms:abstract>The propagation of our genomes during cell proliferation depends on the movement of sister DNA molecules produced by DNA replication to opposite sides of the cell before it divides. This feat is achieved by microtubules in eukaryotic cells but it has long remained a mystery how cells ensure that sister DNAs attach to microtubules with opposite orientations, known as amphitelic attachment. It is currently thought that sister chromatid cohesion has a crucial role. By resisting the forces exerted by microtubules, sister chromatid cohesion gives rise to tension that is thought essential for stabilizing kinetochore-microtubule attachments. Efficient amphitelic attachment is therefore achieved by an error correction mechanism that selectively eliminates connections that do not give rise to tension. Cohesion between sister chromatids is mediated by a multisubunit complex called cohesin which forms a gigantic ring structure. It has been proposed that sister DNAs are held together owing to their becoming entrapped within a single cohesin ring. Cohesion between sister chromatids is destroyed at the metaphase to anaphase transition by proteolytic cleavage of cohesin's Scc1 subunit by a thiol protease called separase, which severs the ring and thereby releases sister DNAs.</dcterms:abstract>
<bib:pages>99-108</bib:pages>
<dc:date>2004-1-29</dc:date>
<dc:identifier>
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<dc:title>Absolute quantification of microbial proteomes at different states by directed mass spectrometry</dc:title>
<dcterms:abstract>The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.,
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.
The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.
The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.
This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
, Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput., In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified () and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome ()., To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria ()., The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology., Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.</dcterms:abstract>
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<prism:volume>7</prism:volume>
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<dcterms:abstract>The fission yeast Schizosaccharomyces pombe is a widely used model organism to study basic mechanisms of eukaryotic biology, but unlike other model organisms, its proteome remains largely uncharacterized. Using a shotgun proteomics approach based on multidimensional prefractionation and tandem mass spectrometry, we have detected 30% of the theoretical fission yeast proteome. Applying statistical modelling to normalize spectral counts to the number of predicted tryptic peptides, we have performed label-free quantification of 1465 proteins. The fission yeast protein data showed considerable correlations with mRNA levels and with the abundance of orthologous proteins in budding yeast. Functional pathway analysis indicated that the mRNA–protein correlation is strong for proteins involved in signalling and metabolic processes, but increasingly discordant for components of protein complexes, which clustered in groups with similar mRNA–protein ratios. Self-organizing map clustering of large-scale protein and mRNA data from fission and budding yeast revealed coordinate but not always concordant expression of components of functional pathways and protein complexes. This finding reaffirms at the protein level the considerable divergence in gene expression patterns of the two model organisms that was noticed in previous transcriptomic studies.</dcterms:abstract>
<dc:date>February 13, 2007</dc:date>
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