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1.
Bioinformatics. 2018 Aug 7. doi: 10.1093/bioinformatics/bty678. [Epub ahead of print]

Global importance of RNA secondary structures in protein coding sequences.

Author information

1
RNA Bioinformatics and High Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany.
2
European Virus Bioinformatics Center (EVBC), Jena, Germany.
3
Institute of Biochemistry, Faculty of Medicine, Justus-Liebig-University, Giessen, Germany.
4
German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.
5
FLI Leibniz Institute for Age Research, Jena, Germany.

Abstract

Motivation:

The protein-coding sequences of messenger RNAs are the linear template for translation of the gene sequence into protein. Nevertheless, the RNA can also form secondary structures by intramolecular base-pairing.

Results:

We show that the nucleotide distribution within codons is biased in all taxa of life on a global scale. Thereby, RNA secondary structures that require base-pairing between the position 1 of a codon with the position 1 of an opposing codon (here named RNA secondary structure class c1) are under-represented. We conclude that this bias may result from the co-evolution of codon sequence and mRNA secondary structure, suggesting that RNA secondary structures are generally important in protein coding regions of mRNAs. The above result also implies that codon position 2 has a smaller influence on the amino acid choice than codon position 1.

2.
Viruses. 2018 May 14;10(5). pii: E256. doi: 10.3390/v10050256.

Bioinformatics Meets Virology: The European Virus Bioinformatics Center's Second Annual Meeting.

Author information

1
European Virus Bioinformatics Center, 07743 Jena, Germany. bashar.ibrahim@uni-jena.de.
2
Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, 07743 Jena, Germany. bashar.ibrahim@uni-jena.de.
3
Theoretical Biology and Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands. arkhipova.a.ksenia@gmail.com.
4
European Virus Bioinformatics Center, 07743 Jena, Germany. a.andeweg@erasmusmc.nl.
5
Department of Viroscience, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands. a.andeweg@erasmusmc.nl.
6
Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland. susana.posada@bsse.ethz.ch.
7
SIB Swiss Institute of Bioinformatics, 4058 Basel, Switzerland. susana.posada@bsse.ethz.ch.
8
Université Clermont Auvergne, CNRS, LMGE, F-63000 Clermont-Ferrand, France. Francois.ENAULT@uca.fr.
9
Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, 05508-000 São Paulo, Brazil. argruber@usp.br.
10
National Center for Biotechnology Information, NLM, National Institutes of Health, Bethesda, MD 20894, USA. koonin@ncbi.nlm.nih.gov.
11
European Virus Bioinformatics Center, 07743 Jena, Germany. akupczok@ifam.uni-kiel.de.
12
Institute of General Microbiology, Kiel University, 24118 Kiel, Germany. akupczok@ifam.uni-kiel.de.
13
European Virus Bioinformatics Center, 07743 Jena, Germany. philippe.Lemey@rega.kuleuven.be.
14
Clinical and Epidemiological Virology, Rega Institute, KU Leuven, University of Leuven, 3000 Leuven, Belgium. philippe.Lemey@rega.kuleuven.be.
15
European Virus Bioinformatics Center, 07743 Jena, Germany. Alice.McHardy@helmholtz-hzi.de.
16
Department for Computational Biology of Infection Research, Helmholtz Center for Infection Research, 38124 Braunschweig, Germany. Alice.McHardy@helmholtz-hzi.de.
17
European Virus Bioinformatics Center, 07743 Jena, Germany. dino-peter.mcmahon@bam.de.
18
Institute of Biology, Free University Berlin, Schwendenerstr. 1, 14195 Berlin, Germany. dino-peter.mcmahon@bam.de.
19
Department for Materials and Environment, BAM Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205 Berlin, Germany. dino-peter.mcmahon@bam.de.
20
European Virus Bioinformatics Center, 07743 Jena, Germany. bpickett@jcvi.org.
21
J. Craig Venter Institute, Rockville, MD 20850, USA. bpickett@jcvi.org.
22
European Virus Bioinformatics Center, 07743 Jena, Germany. David.L.Robertson@glasgow.ac.uk.
23
MRC-University of Glasgow Centre for Virus Research, Garscube Campus, Glasgow G61 1QH, UK. David.L.Robertson@glasgow.ac.uk.
24
European Virus Bioinformatics Center, 07743 Jena, Germany. RScheuermann@jcvi.org.
25
J. Craig Venter Institute, La Jolla, CA 92037, USA. RScheuermann@jcvi.org.
26
Department of Genetics, University Medical Center Groningen, 9700 RB Groningen, The Netherlands. sashazhernakova@gmail.com.
27
Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), 6708 PB Wageningen, The Netherlands. m.zwart@nioo.knaw.nl.
28
European Virus Bioinformatics Center, 07743 Jena, Germany. A.Schoenhuth@cwi.nl.
29
Theoretical Biology and Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands. A.Schoenhuth@cwi.nl.
30
Centrum Wiskunde & Informatica, Science Park 123, 1098 XG Amsterdam, The Netherlands. A.Schoenhuth@cwi.nl.
31
European Virus Bioinformatics Center, 07743 Jena, Germany. bedutilh@gmail.com.
32
Theoretical Biology and Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands. bedutilh@gmail.com.
33
European Virus Bioinformatics Center, 07743 Jena, Germany. manja@uni-jena.de.
34
Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, 07743 Jena, Germany. manja@uni-jena.de.
35
Leibniz Institute for Age Research-Fritz Lipmann Institute, 07745 Jena, Germany. manja@uni-jena.de.

Abstract

The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.

KEYWORDS:

bioinformatics; software; virology; viruses

Conflict of interest statement

The authors declare no conflict of interest.

3.
Virus Res. 2018 Jun 2;251:86-90. doi: 10.1016/j.virusres.2018.05.009. Epub 2018 May 8.

A new era of virus bioinformatics.

Author information

1
European Virus Bioinformatics Center, Jena, Germany; RNA Bioinformatics and High Throughput Analysis Jena, Friedrich Schiller University Jena, Jena, Germany.
2
European Virus Bioinformatics Center, Jena, Germany; Host Parasite Evolution and Ecology, Institute of Biology, Free University of Berlin, Berlin, Germany; Department for Materials and Environment, BAM Federal Institute for Materials Research and Testing, Berlin, Germany.
3
European Virus Bioinformatics Center, Jena, Germany; Institute of Diagnostic Virology, Friedrich-Loeffler-Institute, Greifswald, Germany.
4
European Virus Bioinformatics Center, Jena, Germany; Institute of Virology, Helmholtz Zentrum Munich, Munich, Germany.
5
European Virus Bioinformatics Center, Jena, Germany; Swiss-Prot Group, SIB,CMU, University of Geneva Medical School, Geneva, Switzerland.
6
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
7
European Virus Bioinformatics Center, Jena, Germany; Federal Department of Home Affairs, Institute of Virology and Immunology, Bern and Mittelhausen, Switzerland; Department of Infectious Diseases and Pathobiology, University of Bern, Bern, Switzerland.
8
European Virus Bioinformatics Center, Jena, Germany; RNA Bioinformatics and High Throughput Analysis Jena, Friedrich Schiller University Jena, Jena, Germany. Electronic address: manja@uni-jena.de.

Abstract

Despite the recognized excellence of virology and bioinformatics, these two communities have interacted surprisingly sporadically, aside from some pioneering work on HIV-1 and influenza. Bringing together the expertise of bioinformaticians and virologists is crucial, since very specific but fundamental computational approaches are required for virus research, particularly in an era of big data. Collaboration between virologists and bioinformaticians is necessary to improve existing analytical tools, cloud-based systems, computational resources, data sharing approaches, new diagnostic tools, and bioinformatic training. Here, we highlight current progress and discuss potential avenues for future developments in this promising era of virus bioinformatics. We end by presenting an overview of current technologies, and by outlining some of the major challenges and advantages that bioinformatics will bring to the field of virology.

KEYWORDS:

Bioinformatics; Software; Virology; Viruses

Publication type

Publication type

4.
PLoS Pathog. 2018 Feb 8;14(2):e1006771. doi: 10.1371/journal.ppat.1006771. eCollection 2018 Feb.

Virologists-Heroes need weapons.

Hufsky F1,2, Ibrahim B1,2, Beer M1,3, Deng L1,4, Mercier PL1,5, McMahon DP1,6,7, Palmarini M1,8, Thiel V1,9,10, Marz M1,2.

Author information

1
European Virus Bioinformatics Center, Jena, Germany.
2
RNA Bioinformatics and High-Throughput Analysis Jena, Friedrich Schiller University Jena, Jena, Germany.
3
Institute of Diagnostic Virology, Friedrich-Loeffler-Institute, Greifswald, Germany.
4
Institute of Virology, Helmholtz Zentrum Munich, Munich, Germany.
5
Swiss-Prot group, SIB, CMU, University of Geneva Medical School, Geneva, Switzerland.
6
Host parasite evolution and ecology, Institute of Biology, Free University of Berlin, Berlin, Germany.
7
Department for Materials and Environment, BAM, Federal Institute for Materials Research and Testing, Berlin, Germany.
8
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
9
Federal Department of Home Affairs, Institute of Virology and Immunology, Bern and Mittelhäusern, Switzerland.
10
Department of Infectious Diseases and Pathobiology, University of Bern, Bern, Switzerland.
PMID:
29420617
PMCID:
PMC5805341
DOI:
10.1371/journal.ppat.1006771
[Indexed for MEDLINE]
Free PMC Article
Icon for Public Library of Science Icon for PubMed Central
5.
Genome Biol Evol. 2018 Feb 1;10(2):591-606. doi: 10.1093/gbe/evy011.

Multiple Roots of Fruiting Body Formation in Amoebozoa.

Author information

1
Junior Research Group Evolution of Microbial Interaction, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute (HKI), Jena, Germany.
2
Division of Cell and Developmental Biology, School of Life Sciences, University of Dundee, United Kingdom.
3
Bioinformatics/High Throughput Analysis, Friedrich Schiller University Jena, Germany.
4
CF DNA-Sequencing, Leibniz Institute on Aging Research, Jena, Germany.
5
Electron Microscopy Center, Jena University Hospital, Germany.
6
Pharmaceutical Biology, Institute of Pharmacy, Friedrich Schiller University Jena, Germany.
7
Institute of Biochemistry I, Medical Faculty, University of Cologne, Germany.

Abstract

Establishment of multicellularity represents a major transition in eukaryote evolution. A subgroup of Amoebozoa, the dictyosteliids, has evolved a relatively simple aggregative multicellular stage resulting in a fruiting body supported by a stalk. Protosteloid amoeba, which are scattered throughout the amoebozoan tree, differ by producing only one or few single stalked spores. Thus, one obvious difference in the developmental cycle of protosteliids and dictyosteliids seems to be the establishment of multicellularity. To separate spore development from multicellular interactions, we compared the genome and transcriptome of a Protostelium species (Protostelium aurantium var. fungivorum) with those of social and solitary members of the Amoebozoa. During fruiting body formation nearly 4,000 genes, corresponding to specific pathways required for differentiation processes, are upregulated. A comparison with genes involved in the development of dictyosteliids revealed conservation of >500 genes, but most of them are also present in Acanthamoeba castellanii for which fruiting bodies have not been documented. Moreover, expression regulation of those genes differs between P. aurantium and Dictyostelium discoideum. Within Amoebozoa differentiation to fruiting bodies is common, but our current genome analysis suggests that protosteliids and dictyosteliids used different routes to achieve this. Most remarkable is both the large repertoire and diversity between species in genes that mediate environmental sensing and signal processing. This likely reflects an immense adaptability of the single cell stage to varying environmental conditions. We surmise that this signaling repertoire provided sufficient building blocks to accommodate the relatively simple demands for cell-cell communication in the early multicellular forms.

KEYWORDS:

Amoebozoa; Dictyostelia; Protostelium; evolution of development; multicellular development; signaling; transcriptome

6.
J Biol Chem. 2018 Mar 2;293(9):3056-3072. doi: 10.1074/jbc.M117.812784. Epub 2018 Jan 12.

Effects of allelic variations in the human myxovirus resistance protein A on its antiviral activity.

Graf L1,2, Dick A3,4, Sendker F1, Barth E5, Marz M5,6,7, Daumke O8,4, Kochs G9,2,10.

Author information

1
From the Institute of Virology, Medical Center-University of Freiburg, Hermann-Herder-Strasse 11, 79104 Freiburg, Germany.
2
the Spemann Graduate School of Biology and Medicine, University of Freiburg, Albertstrasse 19a, 79104 Freiburg, Germany.
3
the Max-Delbrück Centrum for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany.
4
the Institute of Chemistry and Biochemistry, Free University Berlin, Takustrasse 6, 14195 Berlin, Germany.
5
the Bioinformatics/High Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.
6
the Leibniz Institute for Age Research-Fritz Lipmann Institute (FLI), Beutenbergstrasse 11, 07745 Jena, Germany.
7
the European Virus Bioinformatics Center, Leutragraben 1, 07743 Jena, Germany, and.
8
the Max-Delbrück Centrum for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany, oliver.daumke@mdc-berlin.de.
9
From the Institute of Virology, Medical Center-University of Freiburg, Hermann-Herder-Strasse 11, 79104 Freiburg, Germany, georg.kochs@uniklinik-freiburg.de.
10
the Faculty of Medicine, University of Freiburg, 79085 Freiburg, Germany.

Abstract

Only a minority of patients infected with seasonal influenza A viruses exhibit a severe or fatal outcome of infection, but the reasons for this inter-individual variability in influenza susceptibility are unclear. To gain further insights into the molecular mechanisms underlying this variability, we investigated naturally occurring allelic variations of the myxovirus resistance 1 (MX1) gene coding for the influenza restriction factor MxA. The interferon-induced dynamin-like GTPase consists of an N-terminal GTPase domain, a bundle signaling element, and a C-terminal stalk responsible for oligomerization and viral target recognition. We used online databases to search for variations in the MX1 gene. Deploying in vitro approaches, we found that non-synonymous variations in the GTPase domain cause the loss of antiviral and enzymatic activities. Furthermore, we showed that these amino acid substitutions disrupt the interface for GTPase domain dimerization required for the stimulation of GTP hydrolysis. Variations in the stalk were neutral or slightly enhanced or abolished MxA antiviral function. Remarkably, two other stalk variants altered MxA's antiviral specificity. Variations causing the loss of antiviral activity were found only in heterozygous carriers. Interestingly, the inactive stalk variants blocked the antiviral activity of WT MxA in a dominant-negative way, suggesting that heterozygotes are phenotypically MxA-negative. In contrast, the GTPase-deficient variants showed no dominant-negative effect, indicating that heterozygous carriers should remain unaffected. Our results demonstrate that naturally occurring mutations in the human MX1 gene can influence MxA function, which may explain individual variations in influenza virus susceptibility in the human population.

KEYWORDS:

Mx proteins; allelic variations; antiviral response; dynamin; genetic polymorphism; influenza virus; innate immunity; interferon

PMID:
29330299
PMCID:
PMC5836113
[Available on 2019-03-02]
DOI:
10.1074/jbc.M117.812784
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Secondary source ID

Secondary source ID

7.
Virology. 2018 Apr;517:44-55. doi: 10.1016/j.virol.2017.11.025. Epub 2017 Dec 6.

Structural and functional conservation of cis-acting RNA elements in coronavirus 5'-terminal genome regions.

Author information

1
Institute of Medical Virology, Justus Liebig University, Giessen, Germany.
2
Faculty of Mathematics and Computer Science, Friedrich Schiller University, Jena, Germany; European Virus Bioinformatics Center, Jena, Germany.
3
Faculty of Mathematics and Computer Science, Friedrich Schiller University, Jena, Germany; FLI Leibniz Institute for Age Research, Jena, Germany; European Virus Bioinformatics Center, Jena, Germany.
4
Institute of Medical Virology, Justus Liebig University, Giessen, Germany; European Virus Bioinformatics Center, Jena, Germany. Electronic address: john.ziebuhr@viro.med.uni-giessen.de.

Abstract

Structure predictions suggest a partial conservation of RNA structure elements in coronavirus terminal genome regions. Here, we determined the structures of stem-loops (SL) 1 and 2 of two alphacoronaviruses, human coronavirus (HCoV) 229E and NL63, by RNA structure probing and studied the functional relevance of these putative cis-acting elements. HCoV-229E SL1 and SL2 mutants generated by reverse genetics were used to study the effects on viral replication of single-nucleotide substitutions predicted to destabilize the SL1 and SL2 structures. The data provide conclusive evidence for the critical role of SL1 and SL2 in HCoV-229E replication and, in some cases, revealed parallels with previously characterized betacoronavirus SL1 and SL2 elements. Also, we were able to rescue viable HCoV-229E mutants carrying replacements of SL2 with equivalent betacoronavirus structural elements. The data obtained in this study reveal a remarkable degree of structural and functional conservation of 5'-terminal RNA structural elements across coronavirus genus boundaries.

KEYWORDS:

Coronavirus; Coronavirus phylogeny; RNA structure; Replication; Stem-loop; cis-acting RNA element

PMID:
29223446
DOI:
10.1016/j.virol.2017.11.025
[Indexed for MEDLINE]
Icon for Elsevier Science
8.
Adv Virus Res. 2017;99:233-257. doi: 10.1016/bs.aivir.2017.08.004. Epub 2017 Sep 28.

Software Dedicated to Virus Sequence Analysis "Bioinformatics Goes Viral".

Author information

1
RNA Bioinformatics and High Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, Germany; European Virus Bioinformatics Center (EVBC), Jena, Germany.
2
RNA Bioinformatics and High Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, Germany; European Virus Bioinformatics Center (EVBC), Jena, Germany; FLI Leibniz Institute for Age Research, Jena, Germany. Electronic address: manja@uni-jena.de.

Abstract

Computer-assisted technologies of the genomic structure, biological function, and evolution of viruses remain a largely neglected area of research. The attention of bioinformaticians to this challenging field is currently unsatisfying in respect to its medical and biological importance. The power of new genome sequencing technologies, associated with new tools to handle "big data", provides unprecedented opportunities to address fundamental questions in virology. Here, we present an overview of the current technologies, challenges, and advantages of Next-Generation Sequencing (NGS) in relation to the field of virology. We present how viral sequences can be detected de novo out of current short-read NGS data. Furthermore, we discuss the challenges and applications of viral quasispecies and how secondary structures, commonly shaped by RNA viruses, can be computationally predicted. The phylogenetic analysis of viruses, as another ubiquitous field in virology, forms an essential element of describing viral epidemics and challenges current algorithms. Recently, the first specialized virus-bioinformatic organizations have been established. We need to bring together virologists and bioinformaticians and provide a platform for the implementation of interdisciplinary collaborative projects at local and international scales. Above all, there is an urgent need for dedicated software tools to tackle various challenges in virology.

KEYWORDS:

Bioinformatics; Software; Virology; Virus sequence analysis

PMID:
29029728
DOI:
10.1016/bs.aivir.2017.08.004
[Indexed for MEDLINE]
Icon for Elsevier Science
9.
BMC Genomics. 2017 Sep 5;18(1):693. doi: 10.1186/s12864-017-3951-8.

A miRNA catalogue and ncRNA annotation of the short-living fish Nothobranchius furzeri.

Author information

1
Leibniz Institute for Age Research - Fritz Lipmann Institute (FLI), Beutenbergstraße 11, 07745, Jena, Germany.
2
Bioinformatics/High Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743, Jena, Germany.
3
Babraham Institute, Cambridge, England.
4
Dresden University of Technology, Dresden, Germany.
5
European Brain Research Institute (EBRI), Rome, Italy.
6
Leibniz Institute for Age Research - Fritz Lipmann Institute (FLI), Beutenbergstraße 11, 07745, Jena, Germany. manja@uni-jena.de.
7
Bioinformatics/High Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743, Jena, Germany. manja@uni-jena.de.
8
Leibniz Institute for Age Research - Fritz Lipmann Institute (FLI), Beutenbergstraße 11, 07745, Jena, Germany. alessandro.cellerino@sns.it.
9
Laboratory of Biology, Scuola Normale Superiore, 56126, Pisa, Italy. alessandro.cellerino@sns.it.

Abstract

BACKGROUND:

The short-lived fish Nothobranchius furzeri is the shortest-lived vertebrate that can be cultured in captivity and was recently established as a model organism for aging research. Small non-coding RNAs, especially miRNAs, are implicated in age dependent control of gene expression.

RESULTS:

Here, we present a comprehensive catalogue of miRNAs and several other non-coding RNA classes (ncRNAs) for Nothobranchius furzeri. Analyzing multiple small RNA-Seq libraries, we show most of these identified miRNAs are expressed in at least one of seven Nothobranchius species. Additionally, duplication and clustering of N. furzeri miRNAs was analyzed and compared to the four fish species Danio rerio, Oryzias latipes, Gasterosteus aculeatus and Takifugu rubripes. A peculiar characteristic of N. furzeri, as compared to other teleosts, was a duplication of the miR-29 cluster.

CONCLUSION:

The completeness of the catalogue we provide is comparable to that of the zebrafish. This catalogue represents a basis to investigate the role of miRNAs in aging and development in this species.

KEYWORDS:

Fish miRNA evolution; Nothobranchius furzeri; miRNome; ncRNA

PMID:
28874118
PMCID:
PMC5584509
DOI:
10.1186/s12864-017-3951-8
[Indexed for MEDLINE]
Free PMC Article
Icon for BioMed Central Icon for PubMed Central
10.
Genome Announc. 2017 Aug 24;5(34). pii: e00870-17. doi: 10.1128/genomeA.00870-17.

Complete Genome Sequence of JII-1961, a Bovine Mycobacterium avium subsp. paratuberculosis Field Isolate from Germany.

Author information

1
Institute of Molecular Pathogenesis, Friedrich-Loeffler-Institut (Federal Research Institute for Animal Health), Jena, Germany petra.moebius@fli.de.
2
Department of Genome Analysis, Helmholtz Centre for Infection Research, Braunschweig, Germany.
3
RNA Bioinformatics and High-Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich-Schiller-Universität, Jena, Germany.
4
Institute of Molecular Pathogenesis, Friedrich-Loeffler-Institut (Federal Research Institute for Animal Health), Jena, Germany.

Abstract

Mycobacterium avium subsp. paratuberculosis causes Johne's disease in ruminants and was also detected in nonruminant species, including human beings, and in milk products. We announce here the 4.829-Mb complete genome sequence of the cattle-type strain JII-1961 from Germany, which is very similar to cattle-type strains recovered from different continents.

11.
J Virol. 2017 Jul 12;91(15). pii: e00361-17. doi: 10.1128/JVI.00361-17. Print 2017 Aug 1.

Evolution and Antiviral Specificities of Interferon-Induced Mx Proteins of Bats against Ebola, Influenza, and Other RNA Viruses.

Author information

1
Institute of Virology, Medical Center, University of Freiburg, Freiburg, Germany.
2
Faculty of Medicine, University of Freiburg, Freiburg, Germany.
3
Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, Germany.
4
Institute for Virology, FB 10-Veterinary Medicine, Justus Liebig University Giessen, Giessen, Germany.
5
Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
6
Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, Montana, USA.
7
Institut für Virologie und Immunologie, Mittelhäusern, Switzerland.
8
FLI Leibniz Institute of Age Research, Jena, Germany.
9
Institute of Virology, University Medical Center Bonn, Bonn, Germany.
10
Institute of Virology, Medical Center, University of Freiburg, Freiburg, Germany georg.kochs@uniklinik-freiburg.de.

Abstract

Bats serve as a reservoir for various, often zoonotic viruses, including significant human pathogens such as Ebola and influenza viruses. However, for unknown reasons, viral infections rarely cause clinical symptoms in bats. A tight control of viral replication by the host innate immune defense might contribute to this phenomenon. Transcriptomic studies revealed the presence of the interferon-induced antiviral myxovirus resistance (Mx) proteins in bats, but detailed functional aspects have not been assessed. To provide evidence that bat Mx proteins might act as key factors to control viral replication we cloned Mx1 cDNAs from three bat families, Pteropodidae, Phyllostomidae, and Vespertilionidae. Phylogenetically these bat Mx1 genes cluster closely with their human ortholog MxA. Using transfected cell cultures, minireplicon systems, virus-like particles, and virus infections, we determined the antiviral potential of the bat Mx1 proteins. Bat Mx1 significantly reduced the polymerase activity of viruses circulating in bats, including Ebola and influenza A-like viruses. The related Thogoto virus, however, which is not known to infect bats, was not inhibited by bat Mx1. Further, we provide evidence for positive selection in bat Mx1 genes that might explain species-specific antiviral activities of these proteins. Together, our data suggest a role for Mx1 in controlling these viruses in their bat hosts.IMPORTANCE Bats are a natural reservoir for various viruses that rarely cause clinical symptoms in bats but are dangerous zoonotic pathogens, like Ebola or rabies virus. It has been hypothesized that the interferon system might play a key role in controlling viral replication in bats. We speculate that the interferon-induced Mx proteins might be key antiviral factors of bats and have coevolved with bat-borne viruses. This study evaluated for the first time a large set of bat Mx1 proteins spanning three major bat families for their antiviral potential, including activity against Ebola virus and bat influenza A-like virus, and we describe here their phylogenetic relationship, revealing patterns of positive selection that suggest a coevolution with viral pathogens. By understanding the molecular mechanisms of the innate resistance of bats against viral diseases, we might gain important insights into how to prevent and fight human zoonotic infections caused by bat-borne viruses.

KEYWORDS:

Ebola virus; Mx protein; bat; bunyavirus; influenza; interferons; orthomyxovirus; vesicular stomatitis virus

PMID:
28490593
PMCID:
PMC5512242
DOI:
10.1128/JVI.00361-17
[Indexed for MEDLINE]
Free PMC Article
Icon for PubMed Central
12.
Sci Rep. 2017 Jan 17;7:40598. doi: 10.1038/srep40598.

Massive Effect on LncRNAs in Human Monocytes During Fungal and Bacterial Infections and in Response to Vitamins A and D.

Author information

1
Friedrich Schiller University, Bioinformatics/High Throughput Analysis, Jena, 07743, Germany.
2
Jena University Hospital, Septomics Research Center, Jena, 07745, Germany.
3
FLI Leibniz Institute for Age Research, 07745 Jena, Germany.
4
Institute of Virology, Philipps-University Marburg, 35043 Marburg, Germany.
5
Chair of Bioinformatics, Friedrich-Schiller-University Jena, 07743 Jena, Germany.

Abstract

Mycoses induced by C.albicans or A.fumigatus can cause important host damage either by deficient or exaggerated immune response. Regulation of chemokine and cytokine signaling plays a crucial role for an adequate inflammation, which can be modulated by vitamins A and D. Non-coding RNAs (ncRNAs) as transcription factors or cis-acting antisense RNAs are known to be involved in gene regulation. However, the processes during fungal infections and treatment with vitamins in terms of therapeutic impact are unknown. We show that in monocytes both vitamins regulate ncRNAs involved in amino acid metabolism and immune system processes using comprehensive RNA-Seq analyses. Compared to protein-coding genes, fungi and bacteria induced an expression change in relatively few ncRNAs, but with massive fold changes of up to 4000. We defined the landscape of long-ncRNAs (lncRNAs) in response to pathogens and observed variation in the isoforms composition for several lncRNA following infection and vitamin treatment. Most of the involved antisense RNAs are regulated and positively correlated with their sense protein-coding genes. We investigated lncRNAs with stimulus specific immunomodulatory activity as potential marker genes: LINC00595, SBF2-AS1 (A.fumigatus) and RP11-588G21.2, RP11-394l13.1 (C.albicans) might be detectable in the early phase of infection and serve as therapeutic targets in the future.

13.
Sci Rep. 2017 Jan 17;7:40599. doi: 10.1038/srep40599.

Differential Effects of Vitamins A and D on the Transcriptional Landscape of Human Monocytes during Infection.

Author information

1
Jena University Hospital, Septomics Research Center, Jena, 07745, Germany.
2
Friedrich Schiller University, Bioinformatics/High Throughput Analysis, Jena, 07743, Germany.
3
Center for Sepsis Control and Care (CSCC), Jena University Hospital, Erlanger Allee 101, Jena, 07747, Germany.
4
Jena University Hospital, Institute of Transfusion Medicine, Jena, 07747, Germany.
5
Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Department of Infection Biology, Jena, 07745, Germany.

Abstract

Vitamin A and vitamin D are essential nutrients with a wide range of pleiotropic effects in humans. Beyond their well-documented roles in cellular differentiation, embryogenesis, tissue maintenance and bone/calcium homeostasis, both vitamins have attracted considerable attention due to their association with-immunological traits. Nevertheless, our knowledge of their immunomodulatory potential during infection is restricted to single gene-centric studies, which do not reflect the complexity of immune processes. In the present study, we performed a comprehensive RNA-seq-based approach to define the whole immunomodulatory role of vitamins A and D during infection. Using human monocytes as host cells, we characterized the differential role of both vitamins upon infection with three different pathogens: Aspergillus fumigatus, Candida albicans and Escherichia coli. Both vitamins showed an unexpected ability to counteract the pathogen-induced transcriptional responses. Upon infection, we identified 346 and 176 immune-relevant genes that were regulated by atRA and vitD, respectively. This immunomodulatory activity was dependent on the inflammatory stimulus, allowing us to distinguish regulatory patterns which were specific for each stimulatory setting. Moreover, we explored possible direct and indirect mechanisms of vitamin-mediated regulation of the immune response. Our findings highlight the importance of vitamin-monitoring in critically ill patients. Moreover, our results underpin the potential of atRA and vitD as therapeutic options for anti-inflammatory treatment.

16.
J Proteomics. 2017 Jan 30;152:153-160. doi: 10.1016/j.jprot.2016.11.003. Epub 2016 Nov 10.

Candidate Brocadiales dominates C, N and S cycling in anoxic groundwater of a pristine limestone-fracture aquifer.

Author information

1
Helmholtz-Centre for Environmental Research - UFZ, Department of Molecular Systems Biology, Leipzig, Germany.
2
Aquatic Geomicrobiology, Institute of Ecology, Friedrich Schiller University Jena, Germany; Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany.
3
Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany; FLI Leibniz Institute for Age Research, Jena, Germany.
4
Aquatic Geomicrobiology, Institute of Ecology, Friedrich Schiller University Jena, Germany; German Centre for integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany.
5
Department of Hydrogeology, Institute of Geosciences, Friedrich Schiller University of Jena, Germany.
6
Helmholtz-Centre for Environmental Research - UFZ, Department of Molecular Systems Biology, Leipzig, Germany; University of Leipzig, Faculty of Biosciences, Pharmacy and Psychology, Institute of Biochemistry, Leipzig, Germany; Aalborg University, Department of Chemistry and Bioscience, 9220 Aalborg, Denmark.
7
Helmholtz-Centre for Environmental Research - UFZ, Department of Molecular Systems Biology, Leipzig, Germany. Electronic address: nico.jehmlich@ufz.de.

Abstract

Groundwater-associated microorganisms are known to play an important role in the biogeochemical C, N and S cycling. Metaproteomics was applied to characterize the diversity and the activity of microbes to identify key species in major biogeochemical processes in the anoxic groundwater of a pristine karstic aquifer located in Hainich, central Germany. Sampling was achieved by pumping 1000L water from two sites of the upper aquifer assemblage and filtration on 0.3μm glass filters. In total, 3808 protein groups were identified. Interestingly, the two wells (H4/2 and H5/2) differed not only in microbial density but also in the prevalence of different C, N and S cycling pathways. The well H5/2 was dominated by the anaerobic ammonia-oxidizing (anammox) candidate Brocadiales (31%) while other orders such as Burkholderiales (2%) or Nitrospirales (3%) were less abundant. Otherwise, the well H4/2 featured only low biomass and remarkably fewer proteins (391 to 3631 at H5/2). Candidate Brocadiales was affiliated to all major carbon fixation strategies, and to the cycling of N and S implying a major role in biogeochemical processes of groundwater aquifers. The findings of our study support functions which can be linked to the ecosystem services provided by the microbial communities present in aquifers.

SIGNIFICANCE:

Subsurface environments especially the groundwater ecosystems represent a large habitat for microbial activity. Microbes are responsible for energy and nutrient cycling and are massively involved in the planet's sustainability. Microbial diversity is tremendous and the central question in current microbial ecology is "Who eats what, where and when?". In this study, we characterize a natural aquifer inhabiting microbial community to obtain evidence for the phylogenetic diversity and the metabolic activity by protein abundance and we highlight important biogeochemical cycling processes. The aquifer was dominated by Candidatus Brocadiales while other phylotypes such as Burkholderiales, Caulobacterales and Nitrospirales were less abundant. The candidate comprised all major carbon fixation strategies, ammonification, anammox and denitrification as well as assimilatory sulfate reduction. Our findings have broad implications for the understanding of microbial activities in this aquifer and consequently specific functions can be linked to the ecosystem services provided by the microbial communities present in aquifers.

KEYWORDS:

Biogeochemical cycling; Groundwater; Limestone aquifer; Metaproteomics

PMID:
27838466
DOI:
10.1016/j.jprot.2016.11.003
[Indexed for MEDLINE]
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17.
Brief Bioinform. 2018 Jan 1;19(1):118-135. doi: 10.1093/bib/bbw089.

Computational pan-genomics: status, promises and challenges.

Abstract

Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this article, we generalize existing definitions and understand a pan-genome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains.

KEYWORDS:

data structures; haplotypes; pan-genome; read mapping; sequence graph

18.
Sci Rep. 2016 Oct 7;6:34589. doi: 10.1038/srep34589.

Differential transcriptional responses to Ebola and Marburg virus infection in bat and human cells.

Author information

1
RNA Bioinformatics and High Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Leutragraben 1, 07743, Jena, Germany.
2
Institute of Virology, Philipps University Marburg, Hans-Meerwein-Str. 2, 35043 Marburg, Germany.
3
German Center for Infection Research (DZIF), partner site Gießen-Marburg-Langen, Hans-Meerwein Str. 2, 35043, Marburg, Germany.
4
Bioinformatics Group, Department of Computer Science, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Germany.
5
FLI Leibniz Institute for Age Research, Beutenbergstraße 11, 07745 Jena, Germany.
6
Transcriptome Bioinformatics, Junior Research Group, Leipzig Research Center for Civilization Diseases, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Germany.
7
Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870, Frederiksberg C, Denmark.
8
Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Grønnegårdsvej 3, 1870, Frederiksberg C, Denmark.
9
Theoretical Biochemistry Group, Institute of Theoretical Chemistry, University of Vienna, Währingerstraße 17, 1090, Vienna, Austria.
10
Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110, Freiburg, Germany.
11
Research Group Theoretical Systems Biology, Department of Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
12
Institute of Computer Science, Martin-Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120, Halle/Saale, Germany.
13
Department of Soil Ecology, UFZ - Helmholtz Centre for Environmental Research, Theodor-Lieser-Str. 4, 06120, Halle/Saale, Germany.
14
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany.
15
Biozentrum, University of Basel, Klingelbergstraße 50/70, CH-4056, Basel, Switzerland.
16
Chair of Bioinformatics, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
17
Junior Professorship for Computational EvoDevo, Bioinformatics, Department of Computer Science, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Germany.
18
TFome Research Group, Bioinformatics Group, Interdisciplinary Center of Bioinformatics, Department of Computer Science, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Germany.
19
Paul-Flechsig-Institute for Brain Research, University of Leipzig, Jahnallee 54, 04109, Leipzig, Germany.
20
Leibniz Institute for Natural Product Research and Infection Biology Hans Knöll Institute (HKI), Systems Biology and Bioinformatics, Beutenbergstraße 11a, 07745, Jena, Germany.
21
Department of Bioanalytical Ecotoxicology, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.
22
Doctoral School of Science and Technology, AZM Center for Biotechnology Research, Lebanese University, Tripoli, Lebanon.
23
TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University Mainz gGmbH, Mainz, Germany.
24
Institute of Aquaculture, University of Stirling, Stirling FK9 4LA, Scotland, U.K.
25
Medical University of Vienna, Center for Anatomy and Cell Biology, Währingerstraße 13, 1090, Vienna, Austria.
26
Centre for Biological Signalling Studies (BIOSS), University of Freiburg, Freiburg, Germany.
27
Research group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Währingerstraße 29, 1090, Vienna, Austria.
28
Research Group Medical Systems Biology, Institute for Experimental Medicine, Christian-Albrechts-University Kiel, Brunswiker Str. 10, 24105, Kiel, Germany.

Abstract

The unprecedented outbreak of Ebola in West Africa resulted in over 28,000 cases and 11,000 deaths, underlining the need for a better understanding of the biology of this highly pathogenic virus to develop specific counter strategies. Two filoviruses, the Ebola and Marburg viruses, result in a severe and often fatal infection in humans. However, bats are natural hosts and survive filovirus infections without obvious symptoms. The molecular basis of this striking difference in the response to filovirus infections is not well understood. We report a systematic overview of differentially expressed genes, activity motifs and pathways in human and bat cells infected with the Ebola and Marburg viruses, and we demonstrate that the replication of filoviruses is more rapid in human cells than in bat cells. We also found that the most strongly regulated genes upon filovirus infection are chemokine ligands and transcription factors. We observed a strong induction of the JAK/STAT pathway, of several genes encoding inhibitors of MAP kinases (DUSP genes) and of PPP1R15A, which is involved in ER stress-induced cell death. We used comparative transcriptomics to provide a data resource that can be used to identify cellular responses that might allow bats to survive filovirus infections.

PMID:
27713552
PMCID:
PMC5054393
DOI:
10.1038/srep34589
[Indexed for MEDLINE]
Free PMC Article
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19.
Nucleic Acids Res. 2016 Nov 16;44(20):9600-9610. Epub 2016 Sep 26.

Finding approximate gene clusters with Gecko 3.

Author information

1
Chair for Bioinformatics, Institute for Computer Science, Friedrich-Schiller-University Jena, Jena, Germany.
2
Genome Informatics, Faculty of Technology and Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.
3
Computational Biology Group, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
4
SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
5
RNA Bioinformatics and High Throughput Analysis, Institute for Computer Science, Friedrich-Schiller-University Jena, Jena, Germany.
6
Institute of Aquaculture, School of Natural Sciences, University of Stirling, Stirling, FK9LA, Scotland, UK.
7
Berlin-Brandenburg Center for Regenerative Therapies, Charité University Medicine Berlin, Berlin, Germany.
8
Leibniz Institute for Age Research-Fritz Lipmann Institute (FLI), Jena, Germany.
9
Chair for Bioinformatics, Institute for Computer Science, Friedrich-Schiller-University Jena, Jena, Germany sebastian.boecker@uni-jena.de.

Abstract

Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters. We present Gecko 3, an open-source software for finding gene clusters in hundreds of bacterial genomes, that comes with an easy-to-use graphical user interface. The underlying gene cluster model is intuitive, can cope with low degrees of conservation as well as misannotations and is complemented by a sound statistical evaluation. To evaluate the biological benefit of Gecko 3 and to exemplify our method, we search for gene clusters in a dataset of 678 bacterial genomes using Synechocystis sp. PCC 6803 as a reference. We confirm detected gene clusters reviewing the literature and comparing them to a database of operons; we detect two novel clusters, which were confirmed by publicly available experimental RNA-Seq data. The computational analysis is carried out on a laptop computer in <40 min.

PMID:
27679480
PMCID:
PMC5175365
DOI:
10.1093/nar/gkw843
[Indexed for MEDLINE]
Free PMC Article
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20.
Cell Mol Life Sci. 2017 Feb;74(4):747-760. doi: 10.1007/s00018-016-2377-9. Epub 2016 Sep 27.

microRNA-122 target sites in the hepatitis C virus RNA NS5B coding region and 3' untranslated region: function in replication and influence of RNA secondary structure.

Author information

1
Institute of Biochemistry, Faculty of Medicine, Justus-Liebig-University, Friedrichstrasse 24, 35392, Giessen, Germany.
2
Faculty of Mathematics and Computer Science, Friedrich-Schiller-University, 07743, Jena, Germany.
3
Institute for Theoretical Chemistry, University of Vienna, 1090, Vienna, Austria.
4
Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, 04107, Leipzig, Germany.
5
FLI Leibniz Institute for Age Research, 07743, Jena, Germany.
6
Institute of Biochemistry, Faculty of Medicine, Justus-Liebig-University, Friedrichstrasse 24, 35392, Giessen, Germany. michael.niepmann@biochemie.med.uni-giessen.de.

Abstract

We have analyzed the binding of the liver-specific microRNA-122 (miR-122) to three conserved target sites of hepatitis C virus (HCV) RNA, two in the non-structural protein 5B (NS5B) coding region and one in the 3' untranslated region (3'UTR). miR-122 binding efficiency strongly depends on target site accessibility under conditions when the range of flanking sequences available for the formation of local RNA secondary structures changes. Our results indicate that the particular sequence feature that contributes most to the correlation between target site accessibility and binding strength varies between different target sites. This suggests that the dynamics of miRNA/Ago2 binding not only depends on the target site itself but also on flanking sequence context to a considerable extent, in particular in a small viral genome in which strong selection constraints act on coding sequence and overlapping cis-signals and model the accessibility of cis-signals. In full-length genomes, single and combination mutations in the miR-122 target sites reveal that site 5B.2 is positively involved in regulating overall genome replication efficiency, whereas mutation of site 5B.3 showed a weaker effect. Mutation of the 3'UTR site and double or triple mutants showed no significant overall effect on genome replication, whereas in a translation reporter RNA, the 3'UTR target site inhibits translation directed by the HCV 5'UTR. Thus, the miR-122 target sites in the 3'-region of the HCV genome are involved in a complex interplay in regulating different steps of the HCV replication cycle.

KEYWORDS:

Accessibility; Ago2; Regulation; Translation; microRNA

PMID:
27677491
DOI:
10.1007/s00018-016-2377-9
[Indexed for MEDLINE]
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