2024-03-29T05:24:41Zhttp://repository.helmholtz-hzi.de/oai/requestoai:repository.helmholtz-hzi.de:10033/3371822019-08-30T11:24:31Zcom_10033_620597col_10033_620598
Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods.
Dröge, J
Gregor, I
McHardy, A C
Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany.
Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.
2014-12-15T15:33:28Z
2014-12-15T15:33:28Z
2014-11-10
Article
Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods. 2014: Bioinformatics
1367-4811
25388150
10.1093/bioinformatics/btu745
http://hdl.handle.net/10033/337182
Bioinformatics (Oxford, England)
oai:repository.helmholtz-hzi.de:10033/3470452019-08-30T11:28:23Zcom_10033_620597col_10033_620598
Computational prediction of vaccine strains for human influenza A (H3N2) viruses.
Steinbrück, L
Klingen, T R
McHardy, A C
Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.
Human influenza A viruses are rapidly evolving pathogens that cause substantial morbidity and mortality in seasonal epidemics around the globe. To ensure continued protection, the strains used for the production of the seasonal influenza vaccine have to be regularly updated, which involves data collection and analysis by numerous experts worldwide. Computer-guided analysis is becoming increasingly important in this problem due to the vast amounts of generated data. We here describe a computational method for selecting a suitable strain for production of the human influenza A virus vaccine. It interprets available antigenic and genomic sequence data based on measures of antigenic novelty and rate of propagation of the viral strains throughout the population. For viral isolates sampled between 2002 and 2007, we used this method to predict the antigenic evolution of the H3N2 viruses in retrospective testing scenarios. When seasons were scored as true or false predictions, our method returned six true positives, three false negatives, eight true negatives, and one false positive, or 78% accuracy overall. In comparison to the recommendations by the WHO, we identified the correct antigenic variant once at the same time and twice one season ahead. Even though it cannot be ruled out that practical reasons such as lack of a sufficiently well-growing candidate strain may in some cases have prevented recommendation of the best-matching strain by the WHO, our computational decision procedure allows quantitative interpretation of the growing amounts of data and may help to match the vaccine better to predominating strains in seasonal influenza epidemics. Importance: Human influenza A viruses continuously change antigenically to circumvent the immune protection evoked by vaccination or previously circulating viral strains. To maintain vaccine protection and thereby reduce the mortality and morbidity caused by infections, regular updates of the vaccine strains are required. We have developed a data-driven framework for vaccine strain prediction which facilitates the computational analysis of genetic and antigenic data and does not rely on explicit evolutionary models. Our computational decision procedure generated good matches of the vaccine strain to the circulating predominant strain for most seasons and could be used to support the expert-guided prediction made by the WHO; it thus may allow an increase in vaccine efficacy.
2015-03-24T13:03:14Z
2015-03-24T13:03:14Z
2014-10
Article
Computational prediction of vaccine strains for human influenza A (H3N2) viruses. 2014, 88 (20):12123-32 J. Virol.
1098-5514
25122778
10.1128/JVI.01861-14
http://hdl.handle.net/10033/347045
Journal of virology
en
oai:repository.helmholtz-hzi.de:10033/5768652019-08-30T11:24:31Zcom_10033_620597col_10033_620598
Adaptive Mutations That Occurred during Circulation in Humans of H1N1 Influenza Virus in the 2009 Pandemic Enhance Virulence in Mice.
Otte, A
Sauter, M
Daxer, M A
McHardy, A C
Klingel, K
Gabriel, G
Helmholtz Centre for infection research, Inhoffenstr. 7, D-38124 Braunschweig, Germany.
During the 2009 H1N1 influenza pandemic, infection attack rates were particularly high among young individuals who suffered from pneumonia with occasional death. Moreover, previously reported determinants of mammalian adaptation and pathogenicity were not present in 2009 pandemic H1N1 influenza A viruses. Thus, it was proposed that unknown viral factors might have contributed to disease severity in humans. In this study, we performed a comparative analysis of two clinical 2009 pandemic H1N1 strains that belong to the very early and later phases of the pandemic. We identified mutations in the viral hemagglutinin (HA) and the nucleoprotein (NP) that occurred during pandemic progression and mediate increased virulence in mice. Lethal disease outcome correlated with elevated viral replication in the alveolar epithelium, increased proinflammatory cytokine and chemokine responses, pneumonia, and lymphopenia in mice. These findings show that viral mutations that have occurred during pandemic circulation among humans are associated with severe disease in mice.
2015-09-07T12:57:46Z
2015-09-07T12:57:46Z
2015-07
Article
Adaptive Mutations That Occurred during Circulation in Humans of H1N1 Influenza Virus in the 2009 Pandemic Enhance Virulence in Mice. 2015, 89 (14):7329-37 J. Virol.
1098-5514
25948752
10.1128/JVI.00665-15
http://hdl.handle.net/10033/576865
Journal of virology
en
oai:repository.helmholtz-hzi.de:10033/5769242019-08-30T11:30:58Zcom_10033_620597col_10033_620598
Coupling of diversification and pH adaptation during the evolution of terrestrial Thaumarchaeota.
Gubry-Rangin, Cécile
Kratsch, Christina
Williams, Tom A
McHardy, Alice C
Embley, T Martin
Prosser, James I
Macqueen, Daniel J
Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen AB24 2TZ, United Kingdom
The Thaumarchaeota is an abundant and ubiquitous phylum of archaea that plays a major role in the global nitrogen cycle. Previous analyses of the ammonia monooxygenase gene amoA suggest that pH is an important driver of niche specialization in these organisms. Although the ecological distribution and ecophysiology of extant Thaumarchaeota have been studied extensively, the evolutionary rise of these prokaryotes to ecological dominance in many habitats remains poorly understood. To characterize processes leading to their diversification, we investigated coevolutionary relationships between amoA, a conserved marker gene for Thaumarchaeota, and soil characteristics, by using deep sequencing and comprehensive environmental data in Bayesian comparative phylogenetics. These analyses reveal a large and rapid increase in diversification rates during early thaumarchaeotal evolution; this finding was verified by independent analyses of 16S rRNA. Our findings suggest that the entire Thaumarchaeota diversification regime was strikingly coupled to pH adaptation but less clearly correlated with several other tested environmental factors. Interestingly, the early radiation event coincided with a period of pH adaptation that enabled the terrestrial Thaumarchaeota ancestor to initially move from neutral to more acidic and alkaline conditions. In contrast to classic evolutionary models, whereby niches become rapidly filled after adaptive radiation, global diversification rates have remained stably high in Thaumarchaeota during the past 400-700 million years, suggesting an ongoing high rate of niche formation or switching for these microbes. Our study highlights the enduring importance of environmental adaptation during thaumarchaeotal evolution and, to our knowledge, is the first to link evolutionary diversification to environmental adaptation in a prokaryotic phylum.
2015-09-08T11:59:44Z
2015-09-08T11:59:44Z
2015-07-28
Article
Coupling of diversification and pH adaptation during the evolution of terrestrial Thaumarchaeota. 2015, 112 (30):9370-5 Proc. Natl. Acad. Sci. U.S.A.
1091-6490
26170282
10.1073/pnas.1419329112
http://hdl.handle.net/10033/576924
Proceedings of the National Academy of Sciences of the United States of America
en
oai:repository.helmholtz-hzi.de:10033/5969302019-08-30T11:31:23Zcom_10033_620597col_10033_620598
PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes.
Gregor, Ivan
Dröge, Johannes
Schirmer, Melanie
Quince, Christopher
McHardy, Alice C
Helmholtz Centre for infection research, Inhoffenstr. 7, D-38124 Braunschweig, Germany.
Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into 'bins' representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies 'training' sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.
2016-02-22T15:15:41Z
2016-02-22T15:15:41Z
2016
Article
PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes. 2016, 4:e1603 PeerJ
2167-8359
26870609
10.7717/peerj.1603
http://hdl.handle.net/10033/596930
PeerJ
en
oai:repository.helmholtz-hzi.de:10033/6046242019-08-30T11:34:19Zcom_10033_620597col_10033_620598
How to Grow a Computational Biology Lab.
McHardy, Alice Carolyn
Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.
2016-04-06T09:47:56Z
2016-04-06T09:47:56Z
2015-09
Article
How to Grow a Computational Biology Lab. 2015, 11 (9):e1004397 PLoS Comput. Biol.
1553-7358
26402619
10.1371/journal.pcbi.1004397
http://hdl.handle.net/10033/604624
PLoS computational biology
en
oai:repository.helmholtz-hzi.de:10033/6158042019-08-30T11:26:42Zcom_10033_620597col_10033_620598
Improved metagenome assemblies and taxonomic binning using long-read circular consensus sequence data.
Frank, J A
Pan, Y
Tooming-Klunderud, A
Eijsink, V G H
McHardy, A C
Nederbragt, A J
Pope, P B
Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, 1432 Norway.
DNA assembly is a core methodological step in metagenomic pipelines used to study the structure and function within microbial communities. Here we investigate the utility of Pacific Biosciences long and high accuracy circular consensus sequencing (CCS) reads for metagenomic projects. We compared the application and performance of both PacBio CCS and Illumina HiSeq data with assembly and taxonomic binning algorithms using metagenomic samples representing a complex microbial community. Eight SMRT cells produced approximately 94 Mb of CCS reads from a biogas reactor microbiome sample that averaged 1319 nt in length and 99.7% accuracy. CCS data assembly generated a comparative number of large contigs greater than 1 kb, to those assembled from a ~190x larger HiSeq dataset (~18 Gb) produced from the same sample (i.e approximately 62% of total contigs). Hybrid assemblies using PacBio CCS and HiSeq contigs produced improvements in assembly statistics, including an increase in the average contig length and number of large contigs. The incorporation of CCS data produced significant enhancements in taxonomic binning and genome reconstruction of two dominant phylotypes, which assembled and binned poorly using HiSeq data alone. Collectively these results illustrate the value of PacBio CCS reads in certain metagenomics applications.
2016-07-08T08:44:39Z
2016-07-08T08:44:39Z
2016
Article
Improved metagenome assemblies and taxonomic binning using long-read circular consensus sequence data. 2016, 6:25373 Sci Rep
2045-2322
27156482
10.1038/srep25373
http://hdl.handle.net/10033/615804
Scientific reports
en
info:eu-repo/grantAgreement/EC/FP7/336355
http://creativecommons.org/licenses/by-nc-sa/4.0/
openAccess
oai:repository.helmholtz-hzi.de:10033/6172682019-08-30T11:30:58Zcom_10033_620597col_10033_620598
Evolution of 2009 H1N1 influenza viruses during the pandemic correlates with increased viral pathogenicity and transmissibility in the ferret model.
Otte, Anna
Marriott, Anthony C
Dreier, Carola
Dove, Brian
Mooren, Kyra
Klingen, Thorsten R
Sauter, Martina
Thompson, Katy-Anne
Bennett, Allan
Klingel, Karin
van Riel, Debby
McHardy, Alice C
Carroll, Miles W
Gabriel, Gülsah
Viral Zoonoses and Adaptation, Heinrich Pette Institute, Leibniz Institute for Experimental Virology, Hamburg, Germany.
There is increasing evidence that 2009 pandemic H1N1 influenza viruses have evolved after pandemic onset giving rise to severe epidemics in subsequent waves. However, it still remains unclear which viral determinants might have contributed to disease severity after pandemic initiation. Here, we show that distinct mutations in the 2009 pandemic H1N1 virus genome have occurred with increased frequency after pandemic declaration. Among those, a mutation in the viral hemagglutinin was identified that increases 2009 pandemic H1N1 virus binding to human-like α2,6-linked sialic acids. Moreover, these mutations conferred increased viral replication in the respiratory tract and elevated respiratory droplet transmission between ferrets. Thus, our data show that 2009 H1N1 influenza viruses have evolved after pandemic onset giving rise to novel virus variants that enhance viral replicative fitness and respiratory droplet transmission in a mammalian animal model. These findings might help to improve surveillance efforts to assess the pandemic risk by emerging influenza viruses.
2016-07-20T14:57:59Z
2016-07-20T14:57:59Z
2016
Article
Evolution of 2009 H1N1 influenza viruses during the pandemic correlates with increased viral pathogenicity and transmissibility in the ferret model. 2016, 6:28583 Sci Rep
2045-2322
27339001
10.1038/srep28583
http://hdl.handle.net/10033/617268
Scientific reports
en
oai:repository.helmholtz-hzi.de:10033/6173142019-08-30T11:33:05Zcom_10033_620597col_10033_620598
Alterations of miRNAs and miRNA-regulated mRNA expression in GC B cell lymphomas determined by integrative sequencing analysis.
Hezaveh, Kebria
Kloetgen, Andreas
Bernhart, Stephan H
Mahapatra, Kunal Das
Lenze, Dido
Richter, Julia
Haake, Andrea
Bergmann, Anke K
Brors, Benedikt
Burkhardt, Birgit
Claviez, Alexander
Drexler, Hans G
Eils, Roland
Haas, Siegfried
Hoffmann, Steve
Karsch, Dennis
Klapper, Wolfram
Kleinheinz, Kortine
Korbel, Jan
Kretzmer, Helene
Kreuz, Markus
Küppers, Ralf
Lawerenz, Chris
Leich, Ellen
Loeffler, Markus
Mantovani-Loeffler, Luisa
López, Cristina
McHardy, Alice C
Möller, Peter
Rohde, Marius
Rosenstiel, Philip
Rosenwald, Andreas
Schilhabel, Markus
Schlesner, Matthias
Scholz, Ingrid
Stadler, Peter F
Stilgenbauer, Stephan
Sungalee, Séphanie
Szczepanowski, Monika
Trümper, Lorenz
Weniger, Marc A
Siebert, Reiner
Borkhardt, Arndt
Hummel, Michael
Hoell, Jessica I
Heinrich-Heine-University Duesseldorf, Medical Faculty, Department of Pediatric Oncology
MicroRNAs are well-established players in posttranscriptional gene regulation. However, information on the effects of microRNA deregulation mainly relies on bioinformatic prediction of potential targets, whereas proof of the direct physical microRNAs/target mRNAs interaction is mostly lacking. Within the International Cancer Genome Consortium Project Determining Molecular Mechanisms in Malignant Lymphoma by Sequencing (ICGC MMML-Seq), we performed miRnome sequencing from 16 Burkitt lymphomas, 19 diffuse large B-cell lymphomas, and 21 follicular lymphomas. Twenty-two miRNAs separated Burkitt lymphomas from diffuse large B-cell lymphomas/follicular lymphomas, of which 13 have shown regulation by MYC. Moreover, we show expression of three hitherto unreported microRNAs. Additionally, we detect recurrent mutations of hsa-miR-142 in diffuse large B-cell lymphomas and follicular lymphomas, and editing of the hsa-miR-376 cluster, providing evidence for microRNA editing in lymphomagenesis. To interrogate the direct physical interactions of microRNAs with mRNAs, we performed Argonaute-2 photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation experiments. MicroRNAs directly targeted 208 mRNAs in the Burkitt lymphomas and 328 mRNAs in the non-Burkitt lymphoma models. This integrative analysis discovered several regulatory pathways of relevance in lymphomagenesis including Ras, PI3K-Akt and MAPK signaling pathways, also recurrently deregulated in lymphomas by mutations. Our dataset uncovers in detail the mRNA deregulation through microRNAs as a highly relevant mechanism in lymphomagenesis.
2016-07-21T10:51:35Z
2016-07-21T10:51:35Z
2016-07-06
Article
Alterations of miRNAs and miRNA-regulated mRNA expression in GC B cell lymphomas determined by integrative sequencing analysis. 2016: Haematologica
1592-8721
27390358
10.3324/haematol.2016.143891
http://hdl.handle.net/10033/617314
Haematologica
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6205812019-08-30T11:35:39Zcom_10033_620597col_10033_620598
Snowball: strain aware gene assembly of metagenomes.
Gregor, I
Schönhuth, A
McHardy, A C
[BRICS] Braunschweiger Zentrum für Systembiology, Rebenring 56, 38106 Braunschweig, Germany.
Gene assembly is an important step in functional analysis of shotgun metagenomic data. Nonetheless, strain aware assembly remains a challenging task, as current assembly tools often fail to distinguish among strain variants or require closely related reference genomes of the studied species to be available.
2016-11-16T14:29:58Z
2016-11-16T14:29:58Z
2016-09-01
Article
Meetings and Proceedings
Snowball: strain aware gene assembly of metagenomes. 2016, 32 (17):i649-i657 Bioinformatics
1367-4811
27587685
10.1093/bioinformatics/btw426
http://hdl.handle.net/10033/620581
Bioinformatics (Oxford, England)
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6206692019-08-30T11:36:32Zcom_10033_620597col_10033_620598
The PARA-suite: PAR-CLIP specific sequence read simulation and processing.
Kloetgen, Andreas
Borkhardt, Arndt
Hoell, Jessica I
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Next-generation sequencing technologies have profoundly impacted biology over recent years. Experimental protocols, such as photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP), which identifies protein-RNA interactions on a genome-wide scale, commonly employ deep sequencing. With PAR-CLIP, the incorporation of photoactivatable nucleosides into nascent transcripts leads to high rates of specific nucleotide conversions during reverse transcription. So far, the specific properties of PAR-CLIP-derived sequencing reads have not been assessed in depth. [Source code of the PARA-suite toolkit and the PARA-suite aligner (BWA PARA) are available at https://github.com/akloetgen/PARA-suite and https://github.com/akloetgen/PARA-suite_aligner , respectively, under the GNU GPLv3 license.]
2016-12-15T15:06:07Z
2016-12-15T15:06:07Z
2016 (Source code of the PARA-suite toolkit and the PARA-suite aligner (BWA PARA) are available at https://github.com/akloetgen/PARA-suite and https://github.com/akloetgen/PARA-suite_aligner , respectively, under the GNU GPLv3 license.)
Article
The PARA-suite: PAR-CLIP specific sequence read simulation and processing. 2016, 4:e2619 PeerJ
27812418
10.7717/peerj.2619
http://hdl.handle.net/10033/620669
PeerJ
en
Source code of the PARA-suite toolkit and the PARA-suite aligner (BWA PARA) are available at https://github.com/akloetgen/PARA-suite and https://github.com/akloetgen/PARA-suite_aligner , respectively, under the GNU GPLv3 license.
https://github.com/akloetgen/PARA-suite
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6207972019-08-30T11:32:17Zcom_10033_620597col_10033_620598
From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer.
Weimann, Aaron
Mooren, Kyra
Frank, Jeremy
Pope, Phillip B
Bremges, Andreas
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar. IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.
2017-01-31T10:32:09Z
2017-01-31T10:32:09Z
2017-01-31
Article
From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer., 1 (6) mSystems
28066816
10.1128/mSystems.00101-16
http://hdl.handle.net/10033/620797
mSystems
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6209092019-08-30T11:29:47Zcom_10033_620597col_10033_620598
Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi.
Hacquard, Stéphane
Kracher, Barbara
Hiruma, Kei
Münch, Philipp C
Garrido-Oter, Ruben
Thon, Michael R
Weimann, Aaron
Damm, Ulrike
Dallery, Jean-Félix
Hainaut, Matthieu
Henrissat, Bernard
Lespinet, Olivier
Sacristán, Soledad
Ver Loren van Themaat, Emiel
Kemen, Eric
McHardy, Alice Carolyn
Schulze-Lefert, Paul
O'Connell, Richard J
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
The sessile nature of plants forced them to evolve mechanisms to prioritize their responses to simultaneous stresses, including colonization by microbes or nutrient starvation. Here, we compare the genomes of a beneficial root endophyte, Colletotrichum tofieldiae and its pathogenic relative C. incanum, and examine the transcriptomes of both fungi and their plant host Arabidopsis during phosphate starvation. Although the two species diverged only 8.8 million years ago and have similar gene arsenals, we identify genomic signatures indicative of an evolutionary transition from pathogenic to beneficial lifestyles, including a narrowed repertoire of secreted effector proteins, expanded families of chitin-binding and secondary metabolism-related proteins, and limited activation of pathogenicity-related genes in planta. We show that beneficial responses are prioritized in C. tofieldiae-colonized roots under phosphate-deficient conditions, whereas defense responses are activated under phosphate-sufficient conditions. These immune responses are retained in phosphate-starved roots colonized by pathogenic C. incanum, illustrating the ability of plants to maximize survival in response to conflicting stresses.
2017-05-05T09:02:33Z
2017-05-05T09:02:33Z
2016-05-06
Article
Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi. 2016, 7:11362 Nat Commun
2041-1723
27150427
10.1038/ncomms11362
http://hdl.handle.net/10033/620909
Nature communications
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6209142019-08-30T11:33:57Zcom_10033_620597col_10033_620598
Determination of antigenicity-altering patches on the major surface protein of human influenza A/H3N2 viruses.
Kratsch, Christina
Klingen, Thorsten R
Mümken, Linda
Steinbrück, Lars
McHardy, Alice Carolyn
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Human influenza viruses are rapidly evolving RNA viruses that cause short-term respiratory infections with substantial morbidity and mortality in annual epidemics. Uncovering the general principles of viral coevolution with human hosts is important for pathogen surveillance and vaccine design. Protein regions are an appropriate model for the interactions between two macromolecules, but the currently used epitope definition for the major antigen of influenza viruses, namely hemagglutinin, is very broad. Here, we combined genetic, evolutionary, antigenic, and structural information to determine the most relevant regions of the hemagglutinin of human influenza A/H3N2 viruses for interaction with human immunoglobulins. We estimated the antigenic weights of amino acid changes at individual sites from hemagglutination inhibition data using antigenic tree inference followed by spatial clustering of antigenicity-altering protein sites on the protein structure. This approach determined six relevant areas (patches) for antigenic variation that had a key role in the past antigenic evolution of the viruses. Previous transitions between successive predominating antigenic types of H3N2 viruses always included amino acid changes in either the first or second antigenic patch. Interestingly, there was only partial overlap between the antigenic patches and the patches under strong positive selection. Therefore, besides alterations of antigenicity, other interactions with the host may shape the evolution of human influenza A/H3N2 viruses.
2017-05-09T14:07:16Z
2017-05-09T14:07:16Z
2016-01
Article
Determination of antigenicity-altering patches on the major surface protein of human influenza A/H3N2 viruses. 2016, 2 (1):vev025 Virus Evol
27774294
10.1093/ve/vev025
http://hdl.handle.net/10033/620914
Virus evolution
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6209162019-08-30T11:29:47Zcom_10033_620597col_10033_620598
Novel Syntrophic Populations Dominate an Ammonia-Tolerant Methanogenic Microbiome.
Frank, J A
Arntzen, M Ø
Sun, L
Hagen, L H
McHardy, A C
Horn, S J
Eijsink, V G H
Schnürer, A
Pope, P B
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Biogas reactors operating with protein-rich substrates have high methane potential and industrial value; however, they are highly susceptible to process failure because of the accumulation of ammonia. High ammonia levels cause a decline in acetate-utilizing methanogens and instead promote the conversion of acetate via a two-step mechanism involving syntrophic acetate oxidation (SAO) to H2 and CO2, followed by hydrogenotrophic methanogenesis. Despite the key role of syntrophic acetate-oxidizing bacteria (SAOB), only a few culturable representatives have been characterized. Here we show that the microbiome of a commercial, ammonia-tolerant biogas reactor harbors a deeply branched, uncultured phylotype (unFirm_1) accounting for approximately 5% of the 16S rRNA gene inventory and sharing 88% 16S rRNA gene identity with its closest characterized relative. Reconstructed genome and quantitative metaproteomic analyses imply unFirm_1's metabolic dominance and SAO capabilities, whereby the key enzymes required for acetate oxidation are among the most highly detected in the reactor microbiome. While culturable SAOB were identified in genomic analyses of the reactor, their limited proteomic representation suggests that unFirm_1 plays an important role in channeling acetate toward methane. Notably, unFirm_1-like populations were found in other high-ammonia biogas installations, conjecturing a broader importance for this novel clade of SAOB in anaerobic fermentations. IMPORTANCE The microbial production of methane or "biogas" is an attractive renewable energy technology that can recycle organic waste into biofuel. Biogas reactors operating with protein-rich substrates such as household municipal or agricultural wastes have significant industrial and societal value; however, they are highly unstable and frequently collapse due to the accumulation of ammonia. We report the discovery of a novel uncultured phylotype (unFirm_1) that is highly detectable in metaproteomic data generated from an ammonia-tolerant commercial reactor. Importantly, unFirm_1 is proposed to perform a key metabolic step in biogas microbiomes, whereby it syntrophically oxidizes acetate to hydrogen and carbon dioxide, which methanogens then covert to methane. Only very few culturable syntrophic acetate-oxidizing bacteria have been described, and all were detected at low in situ levels compared to unFirm_1. Broader comparisons produced the hypothesis that unFirm_1 is a key mediator toward the successful long-term stable operation of biogas production using protein-rich substrates.
2017-05-10T13:24:04Z
2017-05-10T13:24:04Z
2017-05-10
Article
Novel Syntrophic Populations Dominate an Ammonia-Tolerant Methanogenic Microbiome., 1 (5) mSystems
27822555
10.1128/mSystems.00092-16
http://hdl.handle.net/10033/620916
mSystems
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6210272019-08-30T11:34:22Zcom_10033_620597col_10033_620598
Characterisation of a stable laboratory co-culture of acidophilic nanoorganisms.
Krause, Susanne
Bremges, Andreas
Münch, Philipp C
McHardy, Alice C
Gescher, Johannes
Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.
This study describes the laboratory cultivation of ARMAN (Archaeal Richmond Mine Acidophilic Nanoorganisms). After 2.5 years of successive transfers in an anoxic medium containing ferric sulfate as an electron acceptor, a consortium was attained that is comprised of two members of the order Thermoplasmatales, a member of a proposed ARMAN group, as well as a fungus. The 16S rRNA identity of one archaeon is only 91.6% compared to the most closely related isolate Thermogymnomonas acidicola. Hence, this organism is the first member of a new genus. The enrichment culture is dominated by this microorganism and the ARMAN. The third archaeon in the community seems to be present in minor quantities and has a 100% 16S rRNA identity to the recently isolated Cuniculiplasma divulgatum. The enriched ARMAN species is most probably incapable of sugar metabolism because the key genes for sugar catabolism and anabolism could not be identified in the metagenome. Metatranscriptomic analysis suggests that the TCA cycle funneled with amino acids is the main metabolic pathway used by the archaea of the community. Microscopic analysis revealed that growth of the ARMAN is supported by the formation of cell aggregates. These might enable feeding of the ARMAN by or on other community members.
2017-08-01T13:55:16Z
2017-08-01T13:55:16Z
2017-06-12
Article
Characterisation of a stable laboratory co-culture of acidophilic nanoorganisms. 2017, 7 (1):3289 Sci Rep
2045-2322
28607432
10.1038/s41598-017-03315-6
http://hdl.handle.net/10033/621027
Scientific reports
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6211402019-08-30T11:26:12Zcom_10033_620597col_10033_620598
A probabilistic model to recover individual genomes from metagenomes
Dröge, Johannes
Schönhuth, Alexander
McHardy, Alice Carolyn
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany
Shotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs.
2017-10-20T14:38:56Z
2017-10-20T14:38:56Z
2017-05-22
Article
A probabilistic model to recover individual genomes from metagenomes 2017, 3:e117 PeerJ Computer Science
2376-5992
10.7717/peerj-cs.117
http://hdl.handle.net/10033/621140
PeerJ Computer Science
https://peerj.com/articles/cs-117
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6211792019-08-30T11:35:13Zcom_10033_620597col_10033_620598
In Silico Vaccine Strain Prediction for Human Influenza Viruses.
Klingen, Thorsten R
Reimering, Susanne
Guzmán, Carlos A
McHardy, Alice C
Braunschweiger Zentrum für Systembiology, Rebenring 56,38108 Braunschweig, Germany.
Vaccines preventing seasonal influenza infections save many lives every year; however, due to rapid viral evolution, they have to be updated frequently to remain effective. To identify appropriate vaccine strains, the World Health Organization (WHO) operates a global program that continually generates and interprets surveillance data. Over the past decade, sophisticated computational techniques, drawing from multiple theoretical disciplines, have been developed that predict viral lineages rising to predominance, assess their suitability as vaccine strains, link genetic to antigenic alterations, as well as integrate and visualize genetic, epidemiological, structural, and antigenic data. These could form the basis of an objective and reproducible vaccine strain-selection procedure utilizing the complex, large-scale data types from surveillance. To this end, computational techniques should already be incorporated into the vaccine-selection process in an independent, parallel track, and their performance continuously evaluated.
2017-11-20T11:53:09Z
2017-11-20T11:53:09Z
2017-10-09
Article
In Silico Vaccine Strain Prediction for Human Influenza Viruses. 2017 Trends Microbiol.
1878-4380
29032900
10.1016/j.tim.2017.09.001
http://hdl.handle.net/10033/621179
Trends in microbiology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6212072019-08-30T11:30:58Zcom_10033_620597col_10033_620598
Genomics and prevalence of bacterial and archaeal isolates from biogas-producing microbiomes.
Maus, Irena
Bremges, Andreas
Stolze, Yvonne
Hahnke, Sarah
Cibis, Katharina G
Koeck, Daniela E
Kim, Yong S
Kreubel, Jana
Hassa, Julia
Wibberg, Daniel
Weimann, Aaron
Off, Sandra
Stantscheff, Robbin
Zverlov, Vladimir V
Schwarz, Wolfgang H
König, Helmut
Liebl, Wolfgang
Scherer, Paul
McHardy, A C
Sczyrba, Alexander
Klocke, Michael
Pühler, Alfred
Schlüter, Andreas
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
To elucidate biogas microbial communities and processes, the application of high-throughput DNA analysis approaches is becoming increasingly important. Unfortunately, generated data can only partialy be interpreted rudimentary since databases lack reference sequences.
2017-12-14T13:21:15Z
2017-12-14T13:21:15Z
2017
Article
Genomics and prevalence of bacterial and archaeal isolates from biogas-producing microbiomes. 2017, 10:264 Biotechnol Biofuels
1754-6834
29158776
10.1186/s13068-017-0947-1
http://hdl.handle.net/10033/621207
Biotechnology for biofuels
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6212452019-08-30T11:34:22Zcom_10033_620597col_10033_620598
Investigation of different nitrogen reduction routes and their key microbial players in wood chip-driven denitrification beds.
Grießmeier, Victoria
Bremges, Andreas
McHardy, Alice Carolyn
Gescher, Johannes
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Field denitrification beds containing polymeric plant material are increasingly used to eliminate nitrate from agricultural drainage water. They mirror a number of anoxic ecosystems. However, knowledge of the microbial composition, the interaction of microbial species, and the carbon degradation processes within these denitrification systems is sparse. This study revealed several new aspects of the carbon and nitrogen cycle, and these findings can be correlated with the dynamics of the microbial community composition and the activity of key species. Members of the order Pseudomonadales seem to be important players in denitrification at low nitrate concentrations, while a switch to higher nitrate concentrations seems to select for members of the orders Rhodocyclales and Rhizobiales. We observed that high nitrate loading rates lead to an unpredictable transition of the community's activity from denitrification to dissimilatory reduction of nitrate to ammonium (DNRA). This transition is mirrored by an increase in transcripts of the nitrite reductase gene nrfAH and the increase correlates with the activity of members of the order Ignavibacteriales. Denitrification reactors sustained the development of an archaeal community consisting of members of the Bathyarchaeota and methanogens belonging to the Euryarchaeota. Unexpectedly, the activity of the methanogens positively correlated with the nitrate loading rates.
2018-01-22T08:48:14Z
2018-01-22T08:48:14Z
2017-12-05
Article
Investigation of different nitrogen reduction routes and their key microbial players in wood chip-driven denitrification beds. 2017, 7 (1):17028 Sci Rep
2045-2322
29208961
10.1038/s41598-017-17312-2
http://hdl.handle.net/10033/621245
Scientific reports
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6212592018-06-12T17:31:49Zcom_10033_620597col_10033_620598
Tumor Necrosis Factor-Mediated Survival of CD169+ Cells Promotes Immune Activation during Vesicular Stomatitis Virus Infection.
Shinde, Prashant V
Xu, Haifeng C
Maney, Sathish Kumar
Kloetgen, Andreas
Namineni, Sukumar
Zhuang, Yuan
Honke, Nadine
Shaabani, Namir
Bellora, Nicolas
Doerrenberg, Mareike
Trilling, Mirko
Pozdeev, Vitaly I
van Rooijen, Nico
Scheu, Stefanie
Pfeffer, Klaus
Crocker, Paul R
Tanaka, Masato
Duggimpudi, Sujitha
Knolle, Percy
Heikenwalder, Mathias
Ruland, Jürgen
Mak, Tak W
Brenner, Dirk
Pandyra, Aleksandra A
Hoell, Jessica I
Borkhardt, Arndt
Häussinger, Dieter
Lang, Karl S
Lang, Philipp A
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Innate immune activation is essential to mount an effective antiviral response and to prime adaptive immunity. Although a crucial role of CD169+ cells during vesicular stomatitis virus (VSV) infections is increasingly recognized, factors regulating CD169+ cells during viral infections remain unclear. Here, we show that tumor necrosis factor is produced by CD11b+ Ly6C+ Ly6G+ cells following infection with VSV. The absence of TNF or TNF receptor 1 (TNFR1) resulted in reduced numbers of CD169+ cells and in reduced type I interferon (IFN-I) production during VSV infection, with a severe disease outcome. Specifically, TNF triggered RelA translocation into the nuclei of CD169+ cells; this translocation was inhibited when the paracaspase MALT-1 was absent. Consequently, MALT1 deficiency resulted in reduced VSV replication, defective innate immune activation, and development of severe disease. These findings indicate that TNF mediates the maintenance of CD169+ cells and innate and adaptive immune activation during VSV infection.IMPORTANCE Over the last decade, strategically placed CD169+ metallophilic macrophages in the marginal zone of the murine spleen and lymph nodes (LN) have been shown to play a very important role in host defense against viral pathogens. CD169+ macrophages have been shown to activate innate and adaptive immunity via "enforced virus replication," a controlled amplification of virus particles. However, the factors regulating the CD169+ macrophages remain to be studied. In this paper, we show that after vesicular stomatitis virus infection, phagocytes produce tumor necrosis factor (TNF), which signals via TNFR1, and promote enforced virus replication in CD169+ macrophages. Consequently, lack of TNF or TNFR1 resulted in defective immune activation and VSV clearance.
2018-01-30T11:43:10Z
2018-01-30T11:43:10Z
2018-02-01
Article
Tumor Necrosis Factor-Mediated Survival of CD169+ Cells Promotes Immune Activation during Vesicular Stomatitis Virus Infection. 2018, 92 (3) J. Virol.
1098-5514
29142134
10.1128/JVI.01637-17
http://hdl.handle.net/10033/621259
Journal of virology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6212942019-08-30T11:31:23Zcom_10033_620597col_10033_620598
Reconstructing metabolic pathways of a member of the genus Pelotomaculum suggesting its potential to oxidize benzene to carbon dioxide with direct reduction of sulfate.
Dong, Xiyang
Dröge, Johannes
von Toerne, Christine
Marozava, Sviatlana
McHardy, Alice C
Meckenstock, Rainer U
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
The enrichment culture BPL is able to degrade benzene with sulfate as electron acceptor and is dominated by an organism of the genus Pelotomaculum. Members of Pelotomaculum are usually known to be fermenters, undergoing syntrophy with anaerobic respiring microorganisms or methanogens. By using a metagenomic approach, we reconstructed a high-quality genome (∼2.97 Mbp, 99% completeness) for Pelotomaculum candidate BPL. The proteogenomic data suggested that (1) anaerobic benzene degradation was activated by a yet unknown mechanism for conversion of benzene to benzoyl-CoA; (2) the central benzoyl-CoA degradation pathway involved reductive dearomatization by a class II benzoyl-CoA reductase followed by hydrolytic ring cleavage and modified β-oxidation; (3) the oxidative acetyl-CoA pathway was utilized for complete oxidation to CO2. Interestingly, the genome of Pelotomaculum candidate BPL has all the genes for a complete sulfate reduction pathway including a similar electron transfer mechanism for dissimilatory sulfate reduction as in other Gram-positive sulfate-reducing bacteria. The proteome analysis revealed that the essential enzymes for sulfate reduction were all formed during growth with benzene. Thus, our data indicated that, besides its potential to anaerobically degrade benzene, Pelotomaculum candidate BPL is the first member of the genus that can perform sulfate reduction.
2018-02-23T11:43:46Z
2018-02-23T11:43:46Z
2017
Article
Reconstructing metabolic pathways of a member of the genus Pelotomaculum suggesting its potential to oxidize benzene to carbon dioxide with direct reduction of sulfate. 2017, 93 (3) FEMS Microbiol. Ecol.
1574-6941
28011598
10.1093/femsec/fiw254
http://hdl.handle.net/10033/621294
FEMS microbiology ecology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6213122019-08-30T11:30:57Zcom_10033_620597com_10033_311308col_10033_620721col_10033_620598
Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses.
Klingen, Thorsten R
Reimering, Susanne
Loers, Jens
Mooren, Kyra
Klawonn, Frank
Krey, Thomas
Gabriel, Gülsah
McHardy, Alice Carolyn
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Monitoring changes in influenza A virus genomes is crucial to understand its rapid evolution and adaptation to changing conditions e.g. establishment within novel host species. Selective sweeps represent a rapid mode of adaptation and are typically observed in human influenza A viruses. We describe Sweep Dynamics (SD) plots, a computational method combining phylogenetic algorithms with statistical techniques to characterize the molecular adaptation of rapidly evolving viruses from longitudinal sequence data. SD plots facilitate the identification of selective sweeps, the time periods in which these occurred and associated changes providing a selective advantage to the virus. We studied the past genome-wide adaptation of the 2009 pandemic H1N1 influenza A (pH1N1) and seasonal H3N2 influenza A (sH3N2) viruses. The pH1N1 influenza virus showed simultaneous amino acid changes in various proteins, particularly in seasons of high pH1N1 activity. Partially, these changes resulted in functional alterations facilitating sustained human-to-human transmission. In the evolution of sH3N2 influenza viruses, we detected changes characterizing vaccine strains, which were occasionally revealed in selective sweeps one season prior to the WHO recommendation. Taken together, SD plots allow monitoring and characterizing the adaptive evolution of influenza A viruses by identifying selective sweeps and their associated signatures. - - all data is published on GitHub: https://github.com/hzi-bifo/SDplots/tree/v1.0.0
2018-03-07T15:17:04Z
2018-03-07T15:17:04Z
2018-01-10
Article
Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses. 2018, 8 (1):373 Sci Rep
2045-2322
29321538
10.1038/s41598-017-18791-z
http://hdl.handle.net/10033/621312
Scientific reports
https://github.com/hzi-bifo/SDplots/tree/v1.0.0
en
https://github.com/hzi-bifo/SDplots/tree/v1.0.0
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6213142019-08-30T11:28:51Zcom_10033_620597col_10033_620598
'Candidatus Adiutrix intracellularis', an endosymbiont of termite gut flagellates, is the first representative of a deep-branching clade of Deltaproteobacteria and a putative homoacetogen.
Ikeda-Ohtsubo, Wakako
Strassert, Jürgen F H
Köhler, Tim
Mikaelyan, Aram
Gregor, Ivan
McHardy, Alice C
Tringe, Susannah Green
Hugenholtz, Phil
Radek, Renate
Brune, Andreas
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Termite gut flagellates are typically colonized by specific bacterial symbionts. Here we describe the phylogeny, ultrastructure and subcellular location of 'Candidatus Adiutrix intracellularis', an intracellular symbiont of Trichonympha collaris in the termite Zootermopsis nevadensis. It represents a novel, deep-branching clade of uncultured Deltaproteobacteria widely distributed in intestinal tracts of termites and cockroaches. Fluorescence in situ hybridization and transmission electron microscopy localized the endosymbiont near hydrogenosomes in the posterior part and near the ectosymbiont 'Candidatus Desulfovibrio trichonymphae' in the anterior part of the host cell. The draft genome of 'Ca. Adiutrix intracellularis' obtained from a metagenomic library revealed the presence of a complete gene set encoding the Wood-Ljungdahl pathway, including two homologs of fdhF encoding hydrogenase-linked formate dehydrogenases (FDHH ) and all other components of the recently described hydrogen-dependent carbon dioxide reductase (HDCR) complex, which substantiates previous claims that the symbiont is capable of reductive acetogenesis from CO2 and H2 . The close phylogenetic relationship between the HDCR components and their homologs in homoacetogenic Firmicutes and Spirochaetes suggests that the deltaproteobacterium acquired the capacity for homoacetogenesis via lateral gene transfer. The presence of genes for nitrogen fixation and the biosynthesis of amino acids and cofactors indicate the nutritional nature of the symbiosis.
2018-03-08T09:15:48Z
2018-03-08T09:15:48Z
2016-09
Article
'Candidatus Adiutrix intracellularis', an endosymbiont of termite gut flagellates, is the first representative of a deep-branching clade of Deltaproteobacteria and a putative homoacetogen. 2016, 18 (8):2548-64 Environ. Microbiol.
1462-2920
26914459
10.1111/1462-2920.13234
http://hdl.handle.net/10033/621314
Environmental microbiology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6213392019-08-30T11:25:11Zcom_10033_620597col_10033_620598
"Candidatus Paraporphyromonas polyenzymogenes" encodes multi-modular cellulases linked to the type IX secretion system.
Naas, A E
Solden, L M
Norbeck, A D
Brewer, H
Hagen, L H
Heggenes, I M
McHardy, A C
Mackie, R I
Paša-Tolić, L
Arntzen, M Ø
Eijsink, V G H
Koropatkin, N M
Hess, M
Wrighton, K C
Pope, P B
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
In nature, obligate herbivorous ruminants have a close symbiotic relationship with their gastrointestinal microbiome, which proficiently deconstructs plant biomass. Despite decades of research, lignocellulose degradation in the rumen has thus far been attributed to a limited number of culturable microorganisms. Here, we combine meta-omics and enzymology to identify and describe a novel Bacteroidetes family ("Candidatus MH11") composed entirely of uncultivated strains that are predominant in ruminants and only distantly related to previously characterized taxa.
2018-04-06T13:43:12Z
2018-04-06T13:43:12Z
2018-03-01
Article
"Candidatus Paraporphyromonas polyenzymogenes" encodes multi-modular cellulases linked to the type IX secretion system. 2018, 6 (1):44 Microbiome
2049-2618
29490697
10.1186/s40168-018-0421-8
http://hdl.handle.net/10033/621339
Microbiome
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
oai:repository.helmholtz-hzi.de:10033/6213812019-08-30T11:30:53Zcom_10033_620597col_10033_620598
Bioinformatics Meets Virology: The European Virus Bioinformatics Center's Second Annual Meeting.
Ibrahim, Bashar
Arkhipova, Ksenia
Andeweg, Arno C
Posada-Céspedes, Susana
Enault, François
Gruber, Arthur
Koonin, Eugene V
Kupczok, Anne
Lemey, Philippe
McHardy, Alice C
McMahon, Dino P
Pickett, Brett E
Robertson, David L
Scheuermann, Richard H
Zhernakova, Alexandra
Zwart, Mark P
Schönhuth, Alexander
Dutilh, Bas E
Marz, Manja
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
bioinformatics
software
virology
viruses
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.
2018-05-30T10:57:05Z
2018-05-30T10:57:05Z
2018-05-14
Article
29757994
http://hdl.handle.net/10033/621381
http://creativecommons.org/licenses/by-nc-sa/3.0/us/
Attribution-NonCommercial-ShareAlike 3.0 United States
oai:repository.helmholtz-hzi.de:10033/6214102019-08-30T11:32:37Zcom_10033_620597col_10033_620598
AMBER: Assessment of Metagenome BinnERs.
Meyer, Fernando
Hofmann, Peter
Belmann, Peter
Garrido-Oter, Ruben
Fritz, Adrian
Sczyrba, Alexander
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Reconstructing the genomes of microbial community members is key to the interpretation of shotgun metagenome samples. Genome binning programs deconvolute reads or assembled contigs of such samples into individual bins, but assessing their quality is difficult due to the lack of evaluation software and standardized metrics. We present AMBER, an evaluation package for the comparative assessment of genome reconstructions from metagenome benchmark data sets. It calculates the performance metrics and comparative visualizations used in the first benchmarking challenge of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). As an application, we show the outputs of AMBER for eleven different binning programs on two CAMI benchmark data sets. AMBER is implemented in Python and available under the Apache 2.0 license on GitHub (https://github.com/CAMI-challenge/AMBER).
2018-06-25T14:30:30Z
2018-06-25T14:30:30Z
2018-06-08
Article
2047-217X
29893851
10.1093/gigascience/giy069
http://hdl.handle.net/10033/621410
http://creativecommons.org/licenses/by-nc-sa/3.0/us/
Attribution-NonCommercial-ShareAlike 3.0 United States
GigaScience
oai:repository.helmholtz-hzi.de:10033/6214302019-08-22T12:38:18Zcom_10033_620597col_10033_620598
Seqenv: Linking sequences to environments through text mining
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Understanding the distribution of taxa and associated traits across different environments is one of the central questions in microbial ecology. High-throughput sequencing (HTS) studies are presently generating huge volumes of data to address this biogeographical topic. However, these studies are often focused on specific environment types or processes leading to the production of individual, unconnected datasets. The large amounts of legacy sequence data with associated metadata that exist can be harnessed to better place the genetic information found in these surveys into a wider environmental context. Here we introduce a software program, seqenv, to carry out precisely such a task. It automatically performs similarity searches of short sequences against the ``nt'' nucleotide database provided by NCBI and, out of every hit, extracts-if it is available-the textual metadata field. After collecting all the isolation sources from all the search results, we run a text mining algorithm to identify and parse words that are associated with the Environmental Ontology (EnvO) controlled vocabulary. This, in turn, enables us to determine both in which environments individual sequences or taxa have previously been observed and, by weighted summation of those results, to summarize complete samples. We present two demonstrative applications of seqenv to a survey of ammonia oxidizing archaea as well as to a plankton paleome dataset from the Black Sea. These demonstrate the ability of the tool to reveal novel patterns in HTS and its utility in the fields of environmental source tracking, paleontology, and studies of microbial biogeography. To install seqenv, go to: https://github.com/xapple/seqenv. (c) 2016 Sinclair et al
2018-07-24T12:39:35Z
2018-07-24T12:39:35Z
Article
http://hdl.handle.net/10033/621430
http://creativecommons.org/licenses/by-nc-sa/3.0/us/
Attribution-NonCommercial-ShareAlike 3.0 United States
oai:repository.helmholtz-hzi.de:10033/6214452019-08-30T11:29:13Zcom_10033_620597col_10033_620598
Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium.
Brugiroux, Sandrine
Beutler, Markus
Pfann, Carina
Garzetti, Debora
Ruscheweyh, Hans-Joachim
Ring, Diana
Diehl, Manuel
Herp, Simone
Lötscher, Yvonne
Hussain, Saib
Bunk, Boyke
Pukall, Rüdiger
Huson, Daniel H
Münch, Philipp C
McHardy, Alice C
McCoy, Kathy D
Macpherson, Andrew J
Loy, Alexander
Clavel, Thomas
Berry, David
Stecher, Bärbel
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Protection against enteric infections, also termed colonization resistance, results from mutualistic interactions of the host and its indigenous microbes. The gut microbiota of humans and mice is highly diverse and it is therefore challenging to assign specific properties to its individual members. Here, we have used a collection of murine bacterial strains and a modular design approach to create a minimal bacterial community that, once established in germ-free mice, provided colonization resistance against the human enteric pathogen Salmonella enterica serovar Typhimurium (S. Tm). Initially, a community of 12 strains, termed Oligo-Mouse-Microbiota (Oligo-MM
2018-08-09T08:29:56Z
2018-08-09T08:29:56Z
2016-11-21
Article
2058-5276
27869789
10.1038/nmicrobiol.2016.215
http://hdl.handle.net/10033/621445
http://creativecommons.org/licenses/by-nc-sa/3.0/us/
Attribution-NonCommercial-ShareAlike 3.0 United States
Nature microbiology
oai:repository.helmholtz-hzi.de:10033/6214732019-08-30T11:27:44Zcom_10033_620597col_10033_620598
Tumor Necrosis Factor-Mediated Survival of CD169 Cells Promotes Immune Activation during Vesicular Stomatitis Virus Infection.
Shinde, Prashant V
Xu, Haifeng C
Maney, Sathish Kumar
Kloetgen, Andreas
Namineni, Sukumar
Zhuang, Yuan
Honke, Nadine
Shaabani, Namir
Bellora, Nicolas
Doerrenberg, Mareike
Trilling, Mirko
Pozdeev, Vitaly I
van Rooijen, Nico
Scheu, Stefanie
Pfeffer, Klaus
Crocker, Paul R
Tanaka, Masato
Duggimpudi, Sujitha
Knolle, Percy
Heikenwalder, Mathias
Ruland, Jürgen
Mak, Tak W
Brenner, Dirk
Pandyra, Aleksandra A
Hoell, Jessica I
Borkhardt, Arndt
Häussinger, Dieter
Lang, Karl S
Lang, Philipp A
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
MALT1
NF-κB
TNF
innate immunity
interferon
interferons
tumor necrosis factor
Innate immune activation is essential to mount an effective antiviral response and to prime adaptive immunity. Although a crucial role of CD169
2018-09-10T13:36:54Z
2018-09-10T13:36:54Z
2018-02-01
Article
1098-5514
29142134
10.1128/JVI.01637-17
http://hdl.handle.net/10033/621473
http://creativecommons.org/licenses/by-nc-sa/3.0/us/
Attribution-NonCommercial-ShareAlike 3.0 United States
Journal of virology
oai:repository.helmholtz-hzi.de:10033/6216232019-08-30T11:32:37Zcom_10033_620597col_10033_620598
A Fréchet tree distance measure to compare phylogeographic spread paths across trees.
Reimering, Susanne
Muñoz, Sebastian
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Phylogeographic methods reconstruct the origin and spread of taxa by inferring locations for internal nodes of the phylogenetic tree from sampling locations of genetic sequences. This is commonly applied to study pathogen outbreaks and spread. To evaluate such reconstructions, the inferred spread paths from root to leaf nodes should be compared to other methods or references. Usually, ancestral state reconstructions are evaluated by node-wise comparisons, therefore requiring the same tree topology, which is usually unknown. Here, we present a method for comparing phylogeographies across different trees inferred from the same taxa. We compare paths of locations by calculating discrete Fréchet distances. By correcting the distances by the number of paths going through a node, we define the Fréchet tree distance as a distance measure between phylogeographies. As an application, we compare phylogeographic spread patterns on trees inferred with different methods from hemagglutinin sequences of H5N1 influenza viruses, finding that both tree inference and ancestral reconstruction cause variation in phylogeographic spread that is not directly reflected by topological differences. The method is suitable for comparing phylogeographies inferred with different tree or phylogeographic inference methods to each other or to a known ground truth, thus enabling a quality assessment of such techniques.
2018-12-19T14:08:01Z
2018-12-19T14:08:01Z
2018-11-19
Article
2045-2322
30451977
10.1038/s41598-018-35421-4
http://hdl.handle.net/10033/621623
PMC6242967
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Nature publishing group
Scientific reports
oai:repository.helmholtz-hzi.de:10033/6216392019-08-30T11:35:10Zcom_10033_620597col_10033_620598
MicroPheno: predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples.
Asgari, Ehsaneddin
Garakani, Kiavash
McHardy, Alice C
Mofrad, Mohammad R K
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Microbial communities play important roles in the function and maintenance of various biosystems, ranging from the human body to the environment. A major challenge in microbiome research is the classification of microbial communities of different environments or host phenotypes. The most common and cost-effective approach for such studies to date is 16S rRNA gene sequencing. Recent falls in sequencing costs have increased the demand for simple, efficient and accurate methods for rapid detection or diagnosis with proved applications in medicine, agriculture and forensic science. We describe a reference- and alignment-free approach for predicting environments and host phenotypes from 16S rRNA gene sequencing based on k-mer representations that benefits from a bootstrapping framework for investigating the sufficiency of shallow sub-samples. Deep learning methods as well as classical approaches were explored for predicting environments and host phenotypes. A k-mer distribution of shallow sub-samples outperformed Operational Taxonomic Unit (OTU) features in the tasks of body-site identification and Crohn's disease prediction. Aside from being more accurate, using k-mer features in shallow sub-samples allows (i) skipping computationally costly sequence alignments required in OTU-picking and (ii) provided a proof of concept for the sufficiency of shallow and short-length 16S rRNA sequencing for phenotype prediction. In addition, k-mer features predicted representative 16S rRNA gene sequences of 18 ecological environments, and 5 organismal environments with high macro-F1 scores of 0.88 and 0.87. For large datasets, deep learning outperformed classical methods such as Random Forest and Support Vector Machine. The software and datasets are available at https://llp.berkeley.edu/micropheno. Supplementary data are available at Bioinformatics online.
2019-01-10T09:24:03Z
2019-01-10T09:24:03Z
2018-07-01
Article
Bioinformatics. 2018 Jul 1;34(13):i32-i42. doi: 10.1093/bioinformatics/bty296.
1367-4811
29950008
10.1093/bioinformatics/bty296
http://hdl.handle.net/10033/621639
https://llp.berkeley. edu/micropheno
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Oxford University Press
Bioinformatics (Oxford, England)
oai:repository.helmholtz-hzi.de:10033/6216722019-08-30T11:30:30Zcom_10033_620597col_10033_620598
The homeobox transcription factor HB9 induces senescence and blocks differentiation in hematopoietic stem and progenitor cells.
Ingenhag, Deborah
Reister, Sven
Auer, Franziska
Bhatia, Sanil
Wildenhain, Sarah
Picard, Daniel
Remke, Marc
Hoell, Jessica I
Kloetgen, Andreas
Sohn, Dennis
Jänicke, Reiner U
Koegler, Gesine
Borkhardt, Arndt
Hauer, Julia
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.; HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.
The homeobox gene
2019-01-29T15:09:03Z
2019-01-29T15:09:03Z
2019-01-01
Article
Haematologica. 2019 Jan;104(1):35-46. doi: 10.3324/haematol.2018.189407. Epub 2018 Aug 9.
1592-8721
30093397
10.3324/haematol.2018.189407
http://hdl.handle.net/10033/621672
Haematologica
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Ferrata Storti Foundation
Haematologica
oai:repository.helmholtz-hzi.de:10033/6217022019-08-30T11:32:40Zcom_10033_620597col_10033_620598
CAMISIM: simulating metagenomes and microbial communities.
Fritz, Adrian
Hofmann, Peter
Majda, Stephan
Dahms, Eik
Dröge, Johannes
Fiedler, Jessika
Lesker, Till R
Belmann, Peter
DeMaere, Matthew Z
Darling, Aaron E
Sczyrba, Alexander
Bremges, Andreas
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Benchmarking
CAMI
Genome binning
Metagenome assembly
Metagenomics software
Microbial community
Simulation
Taxonomic binning
Taxonomic profiling
Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required. We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM. CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.
2019-02-25T14:01:35Z
2019-02-25T14:01:35Z
2019-02-08
Article
Microbiome. 2019 Feb 8;7(1):17. doi: 10.1186/s40168-019-0633-6.
2049-2618
30736849
10.1186/s40168-019-0633-6
http://hdl.handle.net/10033/621702
Microbiome
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
BioMedCentral
Microbiome
oai:repository.helmholtz-hzi.de:10033/6217342019-08-30T11:32:59Zcom_10033_620597col_10033_620598
Probabilistic variable-length segmentation of protein sequences for discriminative motif discovery (DiMotif) and sequence embedding (ProtVecX).
Asgari, Ehsaneddin
McHardy, Alice C
Mofrad, Mohammad R K
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
2019-03-28T15:01:48Z
2019-03-28T15:01:48Z
2019-03-05
Article
2045-2322
30837494
10.1038/s41598-019-38746-w
http://hdl.handle.net/10033/621734
Scientific Reports
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Springer Nature
Scientific reports
oai:repository.helmholtz-hzi.de:10033/6217512019-08-30T11:32:11Zcom_10033_620597col_10033_620598
Modular Traits of the Rhizobiales Root Microbiota and Their Evolutionary Relationship with Symbiotic Rhizobia.
Garrido-Oter, Ruben
Nakano, Ryohei Thomas
Dombrowski, Nina
Ma, Ka-Wai
McHardy, Alice C
Schulze-Lefert, Paul
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
commensalism
microbiota
phylogenomics
plant immunity
rhizobiales
symbiosis
Animal-microbe facultative symbioses play a fundamental role in ecosystem and organismal health. Yet, due to the flexible nature of their association, the selection pressures that act on animals and their facultative symbionts remain elusive. Here we apply experimental evolution to Drosophila melanogaster associated with its growth-promoting symbiont Lactobacillus plantarum, representing a well-established model of facultative symbiosis. We find that the diet of the host, rather than the host itself, is a predominant driving force in the evolution of this symbiosis. Furthermore, we identify a mechanism resulting from the bacterium's adaptation to the diet, which confers growth benefits to the colonized host. Our study reveals that bacterial adaptation to the host's diet may be the foremost step in determining the evolutionary course of a facultative animal-microbe symbiosis.
2019-04-16T13:42:48Z
2019-04-16T13:42:48Z
2018-07-11
Article
Cell Host Microbe. 2018 Jul 11;24(1):155-167.e5. doi: 10.1016/j.chom.2018.06.006
1934-6069
30001518
10.1016/j.chom.2018.06.006
http://hdl.handle.net/10033/621751
Cell Host and Microbe
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Elsevier
Cell host & microbe
oai:repository.helmholtz-hzi.de:10033/6217592019-08-30T11:32:36Zcom_10033_620597col_10033_620598
Assessing taxonomic metagenome profilers with OPAL.
Meyer, Fernando
Bremges, Andreas
Belmann, Peter
Janssen, Stefan
McHardy, Alice C
Koslicki, David
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Bioboxes
Metagenomics
Performance metrics
Taxonomic profiling
The explosive growth in taxonomic metagenome profiling methods over the past years has created a need for systematic comparisons using relevant performance criteria. The Open-community Profiling Assessment tooL (OPAL) implements commonly used performance metrics, including those of the first challenge of the initiative for the Critical Assessment of Metagenome Interpretation (CAMI), together with convenient visualizations. In addition, we perform in-depth performance comparisons with seven profilers on datasets of CAMI and the Human Microbiome Project. OPAL is freely available at https://github.com/CAMI-challenge/OPAL .
2019-04-30T08:51:25Z
2019-04-30T08:51:25Z
2019-03-04
Article
Genome Biol. 2019 Mar 4;20(1):51. doi: 10.1186/s13059-019-1646-y.
1474-760X
30832730
10.1186/s13059-019-1646-y
http://hdl.handle.net/10033/621759
Genome Biology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
BioMedCentral
Genome biology
oai:repository.helmholtz-hzi.de:10033/6217652019-08-30T11:35:08Zcom_10033_620597col_10033_620598
EDEN: evolutionary dynamics within environments.
Münch, Philipp C
Stecher, Bärbel
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Metagenomics revolutionized the field of microbial ecology, giving access to Gb-sized datasets of microbial communities under natural conditions. This enables fine-grained analyses of the functions of community members, studies of their association with phenotypes and environments, as well as of their microevolution and adaptation to changing environmental conditions. However, phylogenetic methods for studying adaptation and evolutionary dynamics are not able to cope with big data. EDEN is the first software for the rapid detection of protein families and regions under positive selection, as well as their associated biological processes, from meta- and pangenome data. It provides an interactive result visualization for detailed comparative analyses.
Availability and implementation:
EDEN is available as a Docker installation under the GPL 3.0 license, allowing its use on common operating systems, at http://www.github.com/hzi-bifo/eden.
2019-05-09T09:01:54Z
2019-05-09T09:01:54Z
2017-10-15
Article
Bioinformatics. 2017 Oct 15;33(20):3292-3295. doi: 10.1093/bioinformatics/btx394.
1367-4811
28637301
10.1093/bioinformatics/btx394
http://hdl.handle.net/10033/621765
Bioinformatics
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Oxford Academic
Bioinformatics (Oxford, England)
oai:repository.helmholtz-hzi.de:10033/6217692019-08-30T11:35:09Zcom_10033_620597col_10033_620598
Evolutionary model for the unequal segregation of high copy plasmids.
Münch, Karin
Münch, Richard
Biedendieck, Rebekka
Jahn, Dieter
Müller, Johannes
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Plasmids are extrachromosomal DNA elements of microorganisms encoding beneficial genetic information. They were thought to be equally distributed to daughter cells during cell division. Here we use mathematical modeling to investigate the evolutionary stability of plasmid segregation for high-copy plasmids—plasmids that are present in up to several hundred copies per cell—carrying antibiotic resistance genes. Evolutionary stable strategies (ESS) are determined by numerical analysis of a plasmid-load structured population model. The theory predicts that the evolutionary stable segregation strategy of a cell depends on the plasmid copy number: For low and medium plasmid load, both daughters receive in average an equal share of plasmids, while in case of high plasmid load, one daughter obtains distinctively and systematically more plasmids. These findings are in good agreement with recent experimental results. We discuss the interpretation and practical consequences.
2019-05-10T13:10:31Z
2019-05-10T13:10:31Z
2019-01-01
Article
PLoS Comput Biol. 2019 Mar 5;15(3):e1006724. doi: 10.1371/journal.pcbi.1006724 eCollection 2019 Mar.
1553-7358
30835726
10.1371/journal.pcbi.1006724
http://hdl.handle.net/10033/621769
PLoS computational biology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
PLOS
PLoS computational biology
oai:repository.helmholtz-hzi.de:10033/6217812019-08-30T11:33:53Zcom_10033_620597col_10033_620598
Structures and functions linked to genome-wide adaptation of human influenza A viruses.
Klingen, Thorsten R
Loers, Jens
Stanelle-Bertram, Stephanie
Gabriel, Gülsah
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Human influenza A viruses elicit short-term respiratory infections with considerable mortality and morbidity. While H3N2 viruses circulate for more than 50 years, the recent introduction of pH1N1 viruses presents an excellent opportunity for a comparative analysis of the genome-wide evolutionary forces acting on both subtypes. Here, we inferred patches of sites relevant for adaptation, i.e. being under positive selection, on eleven viral protein structures, from all available data since 1968 and correlated these with known functional properties. Overall, pH1N1 have more patches than H3N2 viruses, especially in the viral polymerase complex, while antigenic evolution is more apparent for H3N2 viruses. In both subtypes, NS1 has the highest patch and patch site frequency, indicating that NS1-mediated viral attenuation of host inflammatory responses is a continuously intensifying process, elevated even in the longtime-circulating subtype H3N2. We confirmed the resistance-causing effects of two pH1N1 changes against oseltamivir in NA activity assays, demonstrating the value of the resource for discovering functionally relevant changes. Our results represent an atlas of protein regions and sites with links to host adaptation, antiviral drug resistance and immune evasion for both subtypes for further study.
2019-05-16T13:36:00Z
2019-05-16T13:36:00Z
2019-04-18
Article
Sci Rep. 2019 Apr 18;9(1):6267. doi: 10.1038/s41598-019-42614-y.
2045-2322
31000776
10.1038/s41598-019-42614-y
http://hdl.handle.net/10033/621781
Scientific Reports
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Springer-Nature
Scientific reports
oai:repository.helmholtz-hzi.de:10033/6219772019-10-16T01:34:57Zcom_10033_620597col_10033_620598
Genomic variation and strain-specific functional adaptation in the human gut microbiome during early life.
Vatanen, Tommi
Plichta, Damian R
Somani, Juhi
Münch, Philipp C
Arthur, Timothy D
Hall, Andrew Brantley
Rudolf, Sabine
Oakeley, Edward J
Ke, Xiaobo
Young, Rachel A
Haiser, Henry J
Kolde, Raivo
Yassour, Moran
Luopajärvi, Kristiina
Siljander, Heli
Virtanen, Suvi M
Ilonen, Jorma
Uibo, Raivo
Tillmann, Vallo
Mokurov, Sergei
Dorshakova, Natalya
Porter, Jeffrey A
McHardy, Alice C
Lähdesmäki, Harri
Vlamakis, Hera
Huttenhower, Curtis
Knip, Mikael
Xavier, Ramnik J
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
The human gut microbiome matures towards the adult composition during the first years of life and is implicated in early immune development. Here, we investigate the effects of microbial genomic diversity on gut microbiome development using integrated early childhood data sets collected in the DIABIMMUNE study in Finland, Estonia and Russian Karelia. We show that gut microbial diversity is associated with household location and linear growth of children. Single nucleotide polymorphism- and metagenomic assembly-based strain tracking revealed large and highly dynamic microbial pangenomes, especially in the genus Bacteroides, in which we identified evidence of variability deriving from Bacteroides-targeting bacteriophages. Our analyses revealed functional consequences of strain diversity; only 10% of Finnish infants harboured Bifidobacterium longum subsp. infantis, a subspecies specialized in human milk metabolism, whereas Russian infants commonly maintained a probiotic Bifidobacterium bifidum strain in infancy. Groups of bacteria contributing to diverse, characterized metabolic pathways converged to highly subject-specific configurations over the first two years of life. This longitudinal study extends the current view of early gut microbial community assembly based on strain-level genomic variation.
2019-10-15T12:05:01Z
2019-10-15T12:05:01Z
2019-01-01
Article
Nat Microbiol. 2019 Mar;4(3):470-479. doi: 10.1038/s41564-018-0321-5. Epub 2018 Dec 17.
2058-5276
30559407
10.1038/s41564-018-0321-5
http://hdl.handle.net/10033/621977
Nature Microbiology
PMC6384140
en
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384140/
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Springer-Nature
Nature microbiology
oai:repository.helmholtz-hzi.de:10033/6220062019-11-07T01:59:28Zcom_10033_620597col_10033_620598
Pediatric ALL relapses after allo-SCT show high individuality, clonal dynamics, selective pressure, and druggable targets.
Hoell, Jessica I
Ginzel, Sebastian
Kuhlen, Michaela
Kloetgen, Andreas
Gombert, Michael
Fischer, Ute
Hein, Daniel
Demir, Salih
Stanulla, Martin
Schrappe, Martin
Zur Stadt, Udo
Bader, Peter
Babor, Florian
Schuster, Friedhelm
Strahm, Brigitte
Alten, Julia
Moericke, Anja
Escherich, Gabriele
von Stackelberg, Arend
Thiele, Ralf
McHardy, Alice C
Peters, Christina
Bornhauser, Beat
Bourquin, Jean-Pierre
Krause, Stefan
Enczmann, Juergen
Meyer, Lüder Hinrich
Eckert, Cornelia
Borkhardt, Arndt
Meisel, Roland
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Survival of patients with pediatric acute lymphoblastic leukemia (ALL) after allogeneic hematopoietic stem cell transplantation (allo-SCT) is mainly compromised by leukemia relapse, carrying dismal prognosis. As novel individualized therapeutic approaches are urgently needed, we performed whole-exome sequencing of leukemic blasts of 10 children with post-allo-SCT relapses with the aim of thoroughly characterizing the mutational landscape and identifying druggable mutations. We found that post-allo-SCT ALL relapses display highly diverse and mostly patient-individual genetic lesions. Moreover, mutational cluster analysis showed substantial clonal dynamics during leukemia progression from initial diagnosis to relapse after allo-SCT. Only very few alterations stayed constant over time. This dynamic clonality was exemplified by the detection of thiopurine resistance-mediating mutations in the nucleotidase NT5C2 in 3 patients' first relapses, which disappeared in the post-allo-SCT relapses on relief of selective pressure of maintenance chemotherapy. Moreover, we identified TP53 mutations in 4 of 10 patients after allo-SCT, reflecting acquired chemoresistance associated with selective pressure of prior antineoplastic treatment. Finally, in 9 of 10 children's post-allo-SCT relapse, we found alterations in genes for which targeted therapies with novel agents are readily available. We could show efficient targeting of leukemic blasts by APR-246 in 2 patients carrying TP53 mutations. Our findings shed light on the genetic basis of post-allo-SCT relapse and may pave the way for unraveling novel therapeutic strategies in this challenging situation.
2019-11-06T14:49:29Z
2019-11-06T14:49:29Z
2019-10-22
Article
Blood Adv. 2019 Oct 22;3(20):3143-3156. doi: 10.1182/bloodadvances.2019000051.
2473-9537
31648313
10.1182/bloodadvances.2019000051
http://hdl.handle.net/10033/622006
Blood Advances
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
American Society of Haematology
Blood advances
oai:repository.helmholtz-hzi.de:10033/6220382019-12-05T02:03:43Zcom_10033_620597col_10033_620598
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens.
Zhou, Naihui
Jiang, Yuxiang
Bergquist, Timothy R
Lee, Alexandra J
Kacsoh, Balint Z
Crocker, Alex W
Lewis, Kimberley A
Georghiou, George
Nguyen, Huy N
Hamid, Md Nafiz
Davis, Larry
Dogan, Tunca
Atalay, Volkan
Rifaioglu, Ahmet S
Dalkıran, Alperen
Cetin Atalay, Rengul
Zhang, Chengxin
Hurto, Rebecca L
Freddolino, Peter L
Zhang, Yang
Bhat, Prajwal
Supek, Fran
Fernández, José M
Gemovic, Branislava
Perovic, Vladimir R
Davidović, Radoslav S
Sumonja, Neven
Veljkovic, Nevena
Asgari, Ehsaneddin
Mofrad, Mohammad R K
Profiti, Giuseppe
Savojardo, Castrense
Martelli, Pier Luigi
Casadio, Rita
Boecker, Florian
Schoof, Heiko
Kahanda, Indika
Thurlby, Natalie
McHardy, Alice C
Renaux, Alexandre
Saidi, Rabie
Gough, Julian
Freitas, Alex A
Antczak, Magdalena
Fabris, Fabio
Wass, Mark N
Hou, Jie
Cheng, Jianlin
Wang, Zheng
Romero, Alfonso E
Paccanaro, Alberto
Yang, Haixuan
Goldberg, Tatyana
Zhao, Chenguang
Holm, Liisa
Törönen, Petri
Medlar, Alan J
Zosa, Elaine
Borukhov, Itamar
Novikov, Ilya
Wilkins, Angela
Lichtarge, Olivier
Chi, Po-Han
Tseng, Wei-Cheng
Linial, Michal
Rose, Peter W
Dessimoz, Christophe
Vidulin, Vedrana
Dzeroski, Saso
Sillitoe, Ian
Das, Sayoni
Lees, Jonathan Gill
Jones, David T
Wan, Cen
Cozzetto, Domenico
Fa, Rui
Torres, Mateo
Warwick Vesztrocy, Alex
Rodriguez, Jose Manuel
Tress, Michael L
Frasca, Marco
Notaro, Marco
Grossi, Giuliano
Petrini, Alessandro
Re, Matteo
Valentini, Giorgio
Mesiti, Marco
Roche, Daniel B
Reeb, Jonas
Ritchie, David W
Aridhi, Sabeur
Alborzi, Seyed Ziaeddin
Devignes, Marie-Dominique
Koo, Da Chen Emily
Bonneau, Richard
Gligorijević, Vladimir
Barot, Meet
Fang, Hai
Toppo, Stefano
Lavezzo, Enrico
Falda, Marco
Berselli, Michele
Tosatto, Silvio C E
Carraro, Marco
Piovesan, Damiano
Ur Rehman, Hafeez
Mao, Qizhong
Zhang, Shanshan
Vucetic, Slobodan
Black, Gage S
Jo, Dane
Suh, Erica
Dayton, Jonathan B
Larsen, Dallas J
Omdahl, Ashton R
McGuffin, Liam J
Brackenridge, Danielle A
Babbitt, Patricia C
Yunes, Jeffrey M
Fontana, Paolo
Zhang, Feng
Zhu, Shanfeng
You, Ronghui
Zhang, Zihan
Dai, Suyang
Yao, Shuwei
Tian, Weidong
Cao, Renzhi
Chandler, Caleb
Amezola, Miguel
Johnson, Devon
Chang, Jia-Ming
Liao, Wen-Hung
Liu, Yi-Wei
Pascarelli, Stefano
Frank, Yotam
Hoehndorf, Robert
Kulmanov, Maxat
Boudellioua, Imane
Politano, Gianfranco
Di Carlo, Stefano
Benso, Alfredo
Hakala, Kai
Ginter, Filip
Mehryary, Farrokh
Kaewphan, Suwisa
Björne, Jari
Moen, Hans
Tolvanen, Martti E E
Salakoski, Tapio
Kihara, Daisuke
Jain, Aashish
Šmuc, Tomislav
Altenhoff, Adrian
Ben-Hur, Asa
Rost, Burkhard
Brenner, Steven E
Orengo, Christine A
Jeffery, Constance J
Bosco, Giovanni
Hogan, Deborah A
Martin, Maria J
O'Donovan, Claire
Mooney, Sean D
Greene, Casey S
Radivojac, Predrag
Friedberg, Iddo
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Biofilm
Community challenge
Critical assessment
Long-term memory
Protein function prediction
BACKGROUND:
The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.
RESULTS:
Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.
CONCLUSION:
We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.
2019-12-04T13:00:45Z
2019-12-04T13:00:45Z
2019-11-19
Article
Genome Biol. 2019 Nov 19;20(1):244. doi: 10.1186/s13059-019-1835-8.
1474-760X
31744546
10.1186/s13059-019-1835-8
http://hdl.handle.net/10033/622038
Genome Biology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
BMC
Genome biology
oai:repository.helmholtz-hzi.de:10033/6220862020-01-17T02:05:48Zcom_10033_620597col_10033_620598
CAMITAX: Taxon labels for microbial genomes.
Bremges, Andreas
Fritz, Adrian
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
CAMI
Docker
Genome Taxonomy
Nextflow
Phylogenetic Placement
Reproducible Research
BACKGROUND: The number of microbial genome sequences is increasing exponentially, especially thanks to recent advances in recovering complete or near-complete genomes from metagenomes and single cells. Assigning reliable taxon labels to genomes is key and often a prerequisite for downstream analyses.
FINDINGS: We introduce CAMITAX, a scalable and reproducible workflow for the taxonomic labelling of microbial genomes recovered from isolates, single cells, and metagenomes. CAMITAX combines genome distance-, 16S ribosomal RNA gene-, and gene homology-based taxonomic assignments with phylogenetic placement. It uses Nextflow to orchestrate reference databases and software containers and thus combines ease of installation and use with computational reproducibility. We evaluated the method on several hundred metagenome-assembled genomes with high-quality taxonomic annotations from the TARA Oceans project, and we show that the ensemble classification method in CAMITAX improved on all individual methods across tested ranks.
CONCLUSIONS: While we initially developed CAMITAX to aid the Critical Assessment of Metagenome Interpretation (CAMI) initiative, it evolved into a comprehensive software package to reliably assign taxon labels to microbial genomes. CAMITAX is available under Apache License 2.0 at https://github.com/CAMI-challenge/CAMITAX.
2020-01-16T13:40:58Z
2020-01-16T13:40:58Z
2020-01-01
Article
Gigascience. 2020 Jan 1;9(1). pii: 5698015. doi: 10.1093/gigascience/giz154.
2047-217X
31909794
10.1093/gigascience/giz154
http://hdl.handle.net/10033/622086
Gigascience
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Oxford Academic
GigaScience
oai:repository.helmholtz-hzi.de:10033/6221392020-03-12T03:27:22Zcom_10033_620597col_10033_620598
Reproducible Colonization of Germ-Free Mice With the Oligo-Mouse-Microbiota in Different Animal Facilities.
Eberl, Claudia
Ring, Diana
Münch, Philipp C
Beutler, Markus
Basic, Marijana
Slack, Emma Caroline
Schwarzer, Martin
Srutkova, Dagmar
Lange, Anna
Frick, Julia S
Bleich, André
Stecher, Bärbel
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
3R
Oligo-MM12
defined bacterial consortia
gnotobiology
isobiotic mice
minimal microbiome
sDMDMm2
syncom
The Oligo-Mouse-Microbiota (OMM12) is a recently developed synthetic bacterial community for functional microbiome research in mouse models (Brugiroux et al., 2016). To date, the OMM12 model has been established in several germ-free mouse facilities world-wide and is employed to address a growing variety of research questions related to infection biology, mucosal immunology, microbial ecology and host-microbiome metabolic cross-talk. The OMM12 consists of 12 sequenced and publically available strains isolated from mice, representing five bacterial phyla that are naturally abundant in the murine gastrointestinal tract (Lagkouvardos et al., 2016). Under germ-free conditions, the OMM12 colonizes mice stably over multiple generations. Here, we investigated whether stably colonized OMM12 mouse lines could be reproducibly established in different animal facilities. Germ-free C57Bl/6J mice were inoculated with a frozen mixture of the OMM12 strains. Within 2 weeks after application, the OMM12 community reached the same stable composition in all facilities, as determined by fecal microbiome analysis. We show that a second application of the OMM12 strains after 72 h leads to a more stable community composition than a single application. The availability of such protocols for reliable de novo generation of gnotobiotic rodents will certainly contribute to increasing experimental reproducibility in biomedical research.
2020-02-17T09:47:34Z
2020-02-17T09:47:34Z
2019-01-01
Article
Front Microbiol. 2020 Jan 10;10:2999. doi: 10.3389/fmicb.2019.02999. eCollection 2019.
1664-302X
31998276
10.3389/fmicb.2019.02999
http://hdl.handle.net/10033/622139
Frontiers in Microbiology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Frontiers
Frontiers in microbiology
oai:repository.helmholtz-hzi.de:10033/6221742020-03-12T03:28:51Zcom_10033_620597col_10033_620598
Phylogeographic reconstruction using air transportation data and its application to the 2009 H1N1 influenza A pandemic.
Reimering, Susanne
Muñoz, Sebastian
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Influenza A viruses cause seasonal epidemics and occasional pandemics in the human population. While the worldwide circulation of seasonal influenza is at least partly understood, the exact migration patterns between countries, states or cities are not well studied. Here, we use the Sankoff algorithm for parsimonious phylogeographic reconstruction together with effective distances based on a worldwide air transportation network. By first simulating geographic spread and then phylogenetic trees and genetic sequences, we confirmed that reconstructions with effective distances inferred phylogeographic spread more accurately than reconstructions with geographic distances and Bayesian reconstructions with BEAST that do not use any distance information, and led to comparable results to the Bayesian reconstruction using distance information via a generalized linear model. Our method extends Bayesian methods that estimate rates from the data by using fine-grained locations like airports and inferring intermediate locations not observed among sampled isolates. When applied to sequence data of the pandemic H1N1 influenza A virus in 2009, our approach correctly inferred the origin and proposed airports mainly involved in the spread of the virus. In case of a novel outbreak, this approach allows to rapidly analyze sequence data and infer origin and spread routes to improve disease surveillance and control.
2020-02-26T10:12:49Z
2020-02-26T10:12:49Z
2020-02-01
Article
PLoS Comput Biol. 2020 Feb 7;16(2):e1007101. doi: 10.1371/journal.pcbi.1007101. eCollection 2020 Feb.
1553-7358
32032362
10.1371/journal.pcbi.1007101
http://hdl.handle.net/10033/622174
PLOS computational biology
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
PLOS
PLoS computational biology
oai:repository.helmholtz-hzi.de:10033/6221752020-03-12T03:28:58Zcom_10033_620968com_10033_620597col_10033_620970col_10033_620598
Eleven grand challenges in single-cell data science.
Lähnemann, David
Köster, Johannes
Szczurek, Ewa
McCarthy, Davis J
Hicks, Stephanie C
Robinson, Mark D
Vallejos, Catalina A
Campbell, Kieran R
Beerenwinkel, Niko
Mahfouz, Ahmed
Pinello, Luca
Skums, Pavel
Stamatakis, Alexandros
Attolini, Camille Stephan-Otto
Aparicio, Samuel
Baaijens, Jasmijn
Balvert, Marleen
Barbanson, Buys de
Cappuccio, Antonio
Corleone, Giacomo
Dutilh, Bas E
Florescu, Maria
Guryev, Victor
Holmer, Rens
Jahn, Katharina
Lobo, Thamar Jessurun
Keizer, Emma M
Khatri, Indu
Kielbasa, Szymon M
Korbel, Jan O
Kozlov, Alexey M
Kuo, Tzu-Hao
Lelieveldt, Boudewijn P F
Mandoiu, Ion I
Marioni, John C
Marschall, Tobias
Mölder, Felix
Niknejad, Amir
Raczkowski, Lukasz
Reinders, Marcel
Ridder, Jeroen de
Saliba, Antoine-Emmanuel
Somarakis, Antonios
Stegle, Oliver
Theis, Fabian J
Yang, Huan
Zelikovsky, Alex
McHardy, Alice C
Raphael, Benjamin J
Shah, Sohrab P
Schönhuth, Alexander
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.;HIRI, Helmholtz-Institut für RNA-basierte Infektionsforschung, Josef-Shneider Strasse 2, 97080 Würzburg, Germany.
The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
2020-02-26T10:38:33Z
2020-02-26T10:38:33Z
2020-02-07
Article
Genome Biol. 2020 Feb 7;21(1):31. doi: 10.1186/s13059-020-1926-6.
1474-760X
32033589
10.1186/s13059-020-1926-6
http://hdl.handle.net/10033/622175
Genome Biology
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
BMC
Genome biology
oai:repository.helmholtz-hzi.de:10033/6221872020-03-06T04:09:53Zcom_10033_620597col_10033_620598
Toward unrestricted use of public genomic data.
Amann, Rudolf I
Baichoo, Shakuntala
Blencowe, Benjamin J
Bork, Peer
Borodovsky, Mark
Brooksbank, Cath
Chain, Patrick S G
Colwell, Rita R
Daffonchio, Daniele G
Danchin, Antoine
de Lorenzo, Victor
Dorrestein, Pieter C
Finn, Robert D
Fraser, Claire M
Gilbert, Jack A
Hallam, Steven J
Hugenholtz, Philip
Ioannidis, John P A
Jansson, Janet K
Kim, Jihyun F
Klenk, Hans-Peter
Klotz, Martin G
Knight, Rob
Konstantinidis, Konstantinos T
Kyrpides, Nikos C
Mason, Christopher E
McHardy, Alice C
Meyer, Folker
Ouzounis, Christos A
Patrinos, Aristides A N
Podar, Mircea
Pollard, Katherine S
Ravel, Jacques
Muñoz, Alejandro Reyes
Roberts, Richard J
Rosselló-Móra, Ramon
Sansone, Susanna-Assunta
Schloss, Patrick D
Schriml, Lynn M
Setubal, João C
Sorek, Rotem
Stevens, Rick L
Tiedje, James M
Turjanski, Adrian
Tyson, Gene W
Ussery, David W
Weinstock, George M
White, Owen
Whitman, William B
Xenarios, Ioannis
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Despite some notable progress in data sharing policies and practices, restrictions are still often placed on the open and unconditional use of various genomic data after they have received official approval for release to the public domain or to public databases. These restrictions, which often conflict with the terms and conditions of the funding bodies who supported the release of those data for the benefit of the scientific community and society, are perpetuated by the lack of clear guiding rules for data usage. Existing guidelines for data released to the public domain recognize but fail to resolve tensions between the importance of free and unconditional use of these data and the “right” of the data producers to the first publication. This self-contradiction has resulted in a loophole that allows different interpretations and a continuous debate between data producers and data users on the use of public data. We argue that the publicly available data should be treated as open data, a shared resource with unrestricted use for analysis, interpretation, and publication.
2020-03-05T10:25:01Z
2020-03-05T10:25:01Z
2019-01-25
Article
Science. 2019 Jan 25;363(6425):350-352. doi: 10.1126/science.aaw1280.
1095-9203
30679363
10.1126/science.aaw1280
http://hdl.handle.net/10033/622187
Science
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
AAAS
Science (New York, N.Y.)
oai:repository.helmholtz-hzi.de:10033/6221922020-04-07T05:15:15Zcom_10033_620597col_10033_620598
Functional omics analyses reveal only minor effects of microRNAs on human somatic stem cell differentiation.
Schira-Heinen, Jessica
Czapla, Agathe
Hendricks, Marion
Kloetgen, Andreas
Wruck, Wasco
Adjaye, James
Kögler, Gesine
Werner Müller, Hans
Stühler, Kai
Trompeter, Hans-Ingo
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
The contribution of microRNA-mediated posttranscriptional regulation on the final proteome in differentiating cells remains elusive. Here, we evaluated the impact of microRNAs (miRNAs) on the proteome of human umbilical cord blood-derived unrestricted somatic stem cells (USSC) during retinoic acid (RA) differentiation by a systemic approach using next generation sequencing analysing mRNA and miRNA expression and quantitative mass spectrometry-based proteome analyses. Interestingly, regulation of mRNAs and their dedicated proteins highly correlated during RA-incubation. Additionally, RA-induced USSC demonstrated a clear separation from native USSC thereby shifting from a proliferating to a metabolic phenotype. Bioinformatic integration of up- and downregulated miRNAs and proteins initially implied a strong impact of the miRNome on the XXL-USSC proteome. However, quantitative proteome analysis of the miRNA contribution on the final proteome after ectopic overexpression of downregulated miR-27a-5p and miR-221-5p or inhibition of upregulated miR-34a-5p, respectively, followed by RA-induction revealed only minor proportions of differentially abundant proteins. In addition, only small overlaps of these regulated proteins with inversely abundant proteins in non-transfected RA-treated USSC were observed. Hence, mRNA transcription rather than miRNA-mediated regulation is the driving force for protein regulation upon RA-incubation, strongly suggesting that miRNAs are fine-tuning regulators rather than active primary switches during RA-induction of USSC.
2020-03-06T15:16:57Z
2020-03-06T15:16:57Z
2020-02-24
Article
Sci Rep. 2020 Feb 24;10(1):3284. doi: 10.1038/s41598-020-60065-8.
2045-2322
32094412
10.1038/s41598-020-60065-8
http://hdl.handle.net/10033/622192
Syientific reports
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
NPG
Scientific reports
oai:repository.helmholtz-hzi.de:10033/6222162020-03-25T02:02:50Zcom_10033_620597com_10033_621723col_10033_621724col_10033_620598
An Integrated Metagenome Catalog Reveals New Insights into the Murine Gut Microbiome.
Lesker, Till R
Durairaj, Abilash C
Gálvez, Eric J C
Lagkouvardos, Ilias
Baines, John F
Clavel, Thomas
Sczyrba, Alexander
McHardy, Alice C
Strowig, Till
HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.
gene catalog
metagenome assembled genome
microbiome
mouse gut microbiota
The complexity of host-associated microbial ecosystems requires host-specific reference catalogs to survey the functions and diversity of these communities. We generate a comprehensive resource, the integrated mouse gut metagenome catalog (iMGMC), comprising 4.6 million unique genes and 660 metagenome-assembled genomes (MAGs), many (485 MAGs, 73%) of which are linked to reconstructed full-length 16S rRNA gene sequences. iMGMC enables unprecedented coverage and taxonomic resolution of the mouse gut microbiota; i.e., more than 92% of MAGs lack species-level representatives in public repositories (<95% ANI match). The integration of MAGs and 16S rRNA gene data allows more accurate prediction of functional profiles of communities than predictions based on 16S rRNA amplicons alone. Accompanying iMGMC, we provide a set of MAGs representing 1,296 gut bacteria obtained through complementary assembly strategies. We envision that integrated resources such as iMGMC, together with MAG collections, will enhance the resolution of numerous existing and future sequencing-based studies.
2020-03-24T10:33:33Z
2020-03-24T10:33:33Z
Article
Cell Rep. 2020 Mar 3;30(9):2909-2922.e6. doi: 10.1016/j.celrep.2020.02.036.
32130896
10.1016/j.celrep.2020.02.036
http://hdl.handle.net/10033/622216
2211-1247
Cell reports
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Elsevier/Cell Press
30
9
2909
2922.e6
Cell reports
United States
oai:repository.helmholtz-hzi.de:10033/6222592020-05-13T01:29:40Zcom_10033_620597col_10033_620598
Cellular Importin-α3 Expression Dynamics in the Lung Regulate Antiviral Response Pathways against Influenza A Virus Infection.
Thiele, Swantje
Stanelle-Bertram, Stephanie
Beck, Sebastian
Kouassi, Nancy Mounogou
Zickler, Martin
Müller, Martin
Tuku, Berfin
Resa-Infante, Patricia
van Riel, Debby
Alawi, Malik
Günther, Thomas
Rother, Franziska
Hügel, Stefanie
Reimering, Susanne
McHardy, Alice
Grundhoff, Adam
Brune, Wolfram
Osterhaus, Albert
Bader, Michael
Hartmann, Enno
Gabriel, Gülsah
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
cytokine storm
immune sensor
influenza
lung
pneumonia
Importin-α adaptor proteins orchestrate dynamic nuclear transport processes involved in cellular homeostasis. Here, we show that importin-α3, one of the main NF-κB transporters, is the most abundantly expressed classical nuclear transport factor in the mammalian respiratory tract. Importin-α3 promoter activity is regulated by TNF-α-induced NF-κB in a concentration-dependent manner. High-level TNF-α-inducing highly pathogenic avian influenza A viruses (HPAIVs) isolated from fatal human cases harboring human-type polymerase signatures (PB2 627K, 701N) significantly downregulate importin-α3 mRNA expression in primary lung cells. Importin-α3 depletion is restored upon back-mutating the HPAIV polymerase into an avian-type signature (PB2 627E, 701D) that can no longer induce high TNF-α levels. Importin-α3-deficient mice show reduced NF-κB-activated antiviral gene expression and increased influenza lethality. Thus, importin-α3 plays a key role in antiviral immunity against influenza. Lifting the bottleneck in importin-α3 availability in the lung might provide a new strategy to combat respiratory virus infections.
2020-05-12T10:19:46Z
2020-05-12T10:19:46Z
Article
Cell Rep. 2020 Apr 21;31(3):107549. doi: 10.1016/j.celrep.2020.107549.
32320654
10.1016/j.celrep.2020.107549
http://hdl.handle.net/10033/622259
2211-1247
Cell reports
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Elsevier(Cell Press)
31
3
107549
Cell reports
United States
oai:repository.helmholtz-hzi.de:10033/6222972020-06-13T01:32:58Zcom_10033_620597col_10033_620598
Temporally feathered intensity-modulated radiation therapy: A planning technique to reduce normal tissue toxicity.
López Alfonso, Juan Carlos
Parsai, Shireen
Joshi, Nikhil
Godley, Andrew
Shah, Chirag
Koyfman, Shlomo A
Caudell, Jimmy J
Fuller, Clifton D
Enderling, Heiko
Scott, Jacob G
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
dosimetry planning
normal tissue complication probability
normal tissue toxicity reduction
temporally feathered radiation therapy
therapeutic ratio
Purpose: Intensity-modulated radiation therapy (IMRT) has allowed optimization of three-dimensional spatial radiation dose distributions permitting target coverage while reducing normal tissue toxicity. However, radiation-induced normal tissue toxicity is a major contributor to patients' quality of life and often a dose-limiting factor in the definitive treatment of cancer with radiation therapy. We propose the next logical step in the evolution of IMRT using canonical radiobiological principles, optimizing the temporal dimension through which radiation therapy is delivered to further reduce radiation-induced toxicity by increased time for normal tissue recovery. We term this novel treatment planning strategy "temporally feathered radiation therapy" (TFRT).
Methods: Temporally feathered radiotherapy plans were generated as a composite of five simulated treatment plans each with altered constraints on particular hypothetical organs at risk (OARs) to be delivered sequentially. For each of these TFRT plans, OARs chosen for feathering receive higher doses while the remaining OARs receive lower doses than the standard fractional dose delivered in a conventional fractionated IMRT plan. Each TFRT plan is delivered a specific weekday, which in effect leads to a higher dose once weekly followed by four lower fractional doses to each temporally feathered OAR. We compared normal tissue toxicity between TFRT and conventional fractionated IMRT plans by using a dynamical mathematical model to describe radiation-induced tissue damage and repair over time.
Results: Model-based simulations of TFRT demonstrated potential for reduced normal tissue toxicity compared to conventionally planned IMRT. The sequencing of high and low fractional doses delivered to OARs by TFRT plans suggested increased normal tissue recovery, and hence less overall radiation-induced toxicity, despite higher total doses delivered to OARs compared to conventional fractionated IMRT plans. The magnitude of toxicity reduction by TFRT planning was found to depend on the corresponding standard fractional dose of IMRT and organ-specific recovery rate of sublethal radiation-induced damage.
Conclusions: TFRT is a novel technique for treatment planning and optimization of therapeutic radiotherapy that considers the nonlinear aspects of normal tissue repair to optimize toxicity profiles. Model-based simulations of TFRT to carefully conceptualized clinical cases have demonstrated potential for radiation-induced toxicity reduction in a previously described dynamical model of normal tissue complication probability (NTCP).
2020-06-12T09:42:31Z
2020-06-12T09:42:31Z
2018-06-08
Article
Med Phys. 2018;45(7):3466‐3474. doi:10.1002/mp.12988.
29786861
10.1002/mp.12988
http://hdl.handle.net/10033/622297
2473-4209
Medical physics
PMC6041138
en
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6041138/
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Wiley
45
7
3466
3474
Medical physics
United States
United States
United States
United States
United States
United States
United States
United States
oai:repository.helmholtz-hzi.de:10033/6223892020-08-06T02:29:33Zcom_10033_620597col_10033_620598
YBX1 Indirectly Targets Heterochromatin-Repressed Inflammatory Response-Related Apoptosis Genes through Regulating CBX5 mRNA.
Kloetgen, Andreas
Duggimpudi, Sujitha
Schuschel, Konstantin
Hezaveh, Kebria
Picard, Daniel
Schaal, Heiner
Remke, Marc
Klusmann, Jan-Henning
Borkhardt, Arndt
McHardy, Alice C
Hoell, Jessica I
HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.
PAR-CLIP
RNA-Seq
Y-box binding protein 1
medulloblastoma
post-transcriptional gene regulation
Medulloblastomas arise from undifferentiated precursor cells in the cerebellum and account for about 20% of all solid brain tumors during childhood; standard therapies include radiation and chemotherapy, which oftentimes come with severe impairment of the cognitive development of the young patients. Here, we show that the posttranscriptional regulator Y-box binding protein 1 (YBX1), a DNA- and RNA-binding protein, acts as an oncogene in medulloblastomas by regulating cellular survival and apoptosis. We observed different cellular responses upon YBX1 knockdown in several medulloblastoma cell lines, with significantly altered transcription and subsequent apoptosis rates. Mechanistically, PAR-CLIP for YBX1 and integration with RNA-Seq data uncovered direct posttranscriptional control of the heterochromatin-associated gene CBX5; upon YBX1 knockdown and subsequent CBX5 mRNA instability, heterochromatin-regulated genes involved in inflammatory response, apoptosis and death receptor signaling were de-repressed. Thus, YBX1 acts as an oncogene in medulloblastoma through indirect transcriptional regulation of inflammatory genes regulating apoptosis and represents a promising novel therapeutic target in this tumor entity.
2020-08-05T14:27:31Z
2020-08-05T14:27:31Z
2020-06-23
Article
Int J Mol Sci. 2020;21(12):4453. Published 2020 Jun 23. doi:10.3390/ijms21124453.
32585856
10.3390/ijms21124453
http://hdl.handle.net/10033/622389
1422-0067
International journal of molecular sciences
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
MDPI
21
12
International journal of molecular sciences
International
Switzerland
oai:repository.helmholtz-hzi.de:10033/6224002020-08-12T02:30:19Zcom_10033_620597col_10033_620598
Transcriptome-wide analysis uncovers the targets of the RNA-binding protein MSI2 and effects of MSI2's RNA-binding activity on IL-6 signaling.
Duggimpudi, Sujitha
Kloetgen, Andreas
Maney, Sathish Kumar
Münch, Philipp C
Hezaveh, Kebria
Shaykhalishahi, Hamed
Hoyer, Wolfgang
McHardy, Alice C
Lang, Philipp A
Borkhardt, Arndt
Hoell, Jessica I
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Janus kinase (JAK)
Janus kinase (JAK)/STAT signaling
Musashi 2
PAR-CLIP
RNA-binding protein
cancer
cancer and Musashi2
interleukin 6 (IL-6)
leukemia
mitogen-activated protein kinase (MAPK)
mitogen-activated protein kinase (MAPK) signaling
phosphorylation
post-transcriptional regulation
The RNA-binding protein Musashi 2 (MSI2) has emerged as an important regulator in cancer initiation, progression, and drug resistance. Translocations and deregulation of the MSI2 gene are diagnostic of certain cancers, including chronic myeloid leukemia (CML) with translocation t(7;17), acute myeloid leukemia (AML) with translocation t(10;17), and some cases of B-precursor acute lymphoblastic leukemia (pB-ALL). To better understand the function of MSI2 in leukemia, the mRNA targets that are bound and regulated by MSI2 and their MSI2-binding motifs need to be identified. To this end, using photoactivatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) and the multiple EM for motif elicitation (MEME) analysis tool, here we identified MSI2's mRNA targets and the consensus RNA-recognition element (RRE) motif recognized by MSI2 (UUAG). Of note, MSI2 knockdown altered the expression of several genes with roles in eukaryotic initiation factor 2 (eIF2), hepatocyte growth factor (HGF), and epidermal growth factor (EGF) signaling pathways. We also show that MSI2 regulates classic interleukin-6 (IL-6) signaling by promoting the degradation of the mRNA of IL-6 signal transducer (IL6ST or GP130), which, in turn, affected the phosphorylation statuses of signal transducer and activator of transcription 3 (STAT3) and the mitogen-activated protein kinase ERK. In summary, we have identified multiple MSI2-regulated mRNAs and provided evidence that MSI2 controls IL6ST activity that control oncogenic signaling networks. Our findings may help inform strategies for unraveling the role of MSI2 in leukemia to pave the way for the development of targeted therapies.
2020-08-11T13:09:47Z
2020-08-11T13:09:47Z
2018-08-20
Article
Other
J Biol Chem. 2018;293(40):15359-15369. doi:10.1074/jbc.RA118.002243.
30126842
10.1074/jbc.RA118.002243
http://hdl.handle.net/10033/622400
1083-351X
The Journal of biological chemistry
PMC6177596
en
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6177596/
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
American Society for Biochemistry and Molecular Biology
293
40
15359
15369
The Journal of biological chemistry
United States
oai:repository.helmholtz-hzi.de:10033/6225032020-10-09T01:34:23Zcom_10033_620597com_10033_621852com_10033_620968com_10033_620636col_10033_621853col_10033_620970col_10033_620969col_10033_620598col_10033_620638
Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment.
Schulte-Schrepping, Jonas
Reusch, Nico
Paclik, Daniela
Baßler, Kevin
Schlickeiser, Stephan
Zhang, Bowen
Krämer, Benjamin
Krammer, Tobias
Brumhard, Sophia
Bonaguro, Lorenzo
De Domenico, Elena
Wendisch, Daniel
Grasshoff, Martin
Kapellos, Theodore S
Beckstette, Michael
Pecht, Tal
Saglam, Adem
Dietrich, Oliver
Mei, Henrik E
Schulz, Axel R
Conrad, Claudia
Kunkel, Désirée
Vafadarnejad, Ehsan
Xu, Cheng-Jian
Horne, Arik
Herbert, Miriam
Drews, Anna
Thibeault, Charlotte
Pfeiffer, Moritz
Hippenstiel, Stefan
Hocke, Andreas
Müller-Redetzky, Holger
Heim, Katrin-Moira
Machleidt, Felix
Uhrig, Alexander
Bosquillon de Jarcy, Laure
Jürgens, Linda
Stegemann, Miriam
Glösenkamp, Christoph R
Volk, Hans-Dieter
Goffinet, Christine
Landthaler, Markus
Wyler, Emanuel
Georg, Philipp
Schneider, Maria
Dang-Heine, Chantip
Neuwinger, Nick
Kappert, Kai
Tauber, Rudolf
Corman, Victor
Raabe, Jan
Kaiser, Kim Melanie
Vinh, Michael To
Rieke, Gereon
Meisel, Christian
Ulas, Thomas
Becker, Matthias
Geffers, Robert
Witzenrath, Martin
Drosten, Christian
Suttorp, Norbert
von Kalle, Christof
Kurth, Florian
Händler, Kristian
Schultze, Joachim L
Aschenbrenner, Anna C
Li, Yang
Nattermann, Jacob
Sawitzki, Birgit
Saliba, Antoine-Emmanuel
Sander, Leif Erik
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.; HIRI, Helmholtz-Institut für RNA-basierte Infektionsforschung, Josef-Shneider Strasse 2, 97080 Würzburg, Germany.; CiiM, Zentrum für individualisierte Infektionsmedizin, Feodor-Lynen-Str.7, 30625 Hannover.; HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.
COVID-19
SARS-CoV-2
dysfunctional neutrophils
emergency myelopoiesis
immune profiling
mass cytometry
monocytes
neutrophils
scRNA-seq
Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.
2020-10-08T14:17:42Z
2020-10-08T14:17:42Z
2020-08-05
Article
Other
Cell. 2020 Sep 17;182(6):1419-1440.e23. doi: 10.1016/j.cell.2020.08.001.
32810438
10.1016/j.cell.2020.08.001
http://hdl.handle.net/10033/622503
1097-4172
Cell
en
info:eu-repo/grantAgreement/EC/H2020/733100
http://creativecommons.org/licenses/by-nc-sa/4.0/
openAccess
Attribution-NonCommercial-ShareAlike 4.0 International
Elsevier /Cell Press)
182
6
1419
1440.e23
Cell
United States
oai:repository.helmholtz-hzi.de:10033/6225292020-10-30T01:36:04Zcom_10033_620597col_10033_620598
Evolutionary Stabilization of Cooperative Toxin Production through a Bacterium-Plasmid-Phage Interplay.
Spriewald, Stefanie
Stadler, Eva
Hense, Burkhard A
Münch, Philipp C
McHardy, Alice C
Weiss, Anna S
Obeng, Nancy
Müller, Johannes
Stecher, Bärbel
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
adaptive dynamics
bacteriocin
bacteriophage
bistability
cheater
colicin
evolution
evolutionary stable strategy
gastrointestinal infection
heterogeneity
lysogen
phenotypic noise
regulation
spiteful interaction
toxin
virus
Colicins are toxins produced and released by Enterobacteriaceae to kill competitors in the gut. While group A colicins employ a division of labor strategy to liberate the toxin into the environment via colicin-specific lysis, group B colicin systems lack cognate lysis genes. In Salmonella enterica serovar Typhimurium (S. Tm), the group B colicin Ib (ColIb) is released by temperate phage-mediated bacteriolysis. Phage-mediated ColIb release promotes S. Tm fitness against competing Escherichia coli It remained unclear how prophage-mediated lysis is realized in a clonal population of ColIb producers and if prophages contribute to evolutionary stability of toxin release in S. Tm. Here, we show that prophage-mediated lysis occurs in an S. Tm subpopulation only, thereby introducing phenotypic heterogeneity to the system. We established a mathematical model to study the dynamic interplay of S. Tm, ColIb, and a temperate phage in the presence of a competing species. Using this model, we studied long-term evolution of phage lysis rates in a fluctuating infection scenario. This revealed that phage lysis evolves as bet-hedging strategy that maximizes phage spread, regardless of whether colicin is present or not. We conclude that the ColIb system, lacking its own lysis gene, is making use of the evolutionary stable phage strategy to be released. Prophage lysis genes are highly prevalent in nontyphoidal Salmonella genomes. This suggests that the release of ColIb by temperate phages is widespread. In conclusion, our findings shed new light on the evolution and ecology of group B colicin systems.IMPORTANCE Bacteria are excellent model organisms to study mechanisms of social evolution. The production of public goods, e.g., toxin release by cell lysis in clonal bacterial populations, is a frequently studied example of cooperative behavior. Here, we analyze evolutionary stabilization of toxin release by the enteric pathogen Salmonella The release of colicin Ib (ColIb), which is used by Salmonella to gain an edge against competing microbiota following infection, is coupled to bacterial lysis mediated by temperate phages. Here, we show that phage-dependent lysis and subsequent release of colicin and phage particles occurs only in part of the ColIb-expressing Salmonella population. This phenotypic heterogeneity in lysis, which represents an essential step in the temperate phage life cycle, has evolved as a bet-hedging strategy under fluctuating environments such as the gastrointestinal tract. Our findings suggest that prophages can thereby evolutionarily stabilize costly toxin release in bacterial populations.
2020-10-22T12:52:33Z
2020-10-22T12:52:33Z
2020-07-21
Article
mBio. 2020 Jul 21;11(4):e00912-20. doi: 10.1128/mBio.00912-20.
32694140
10.1128/mBio.00912-20
http://hdl.handle.net/10033/622529
2150-7511
mBio
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
ASM
11
4
mBio
United States
oai:repository.helmholtz-hzi.de:10033/6226072020-12-02T01:41:13Zcom_10033_620597col_10033_620598
Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.
Hufsky, Franziska
Lamkiewicz, Kevin
Almeida, Alexandre
Aouacheria, Abdel
Arighi, Cecilia
Bateman, Alex
Baumbach, Jan
Beerenwinkel, Niko
Brandt, Christian
Cacciabue, Marco
Chuguransky, Sara
Drechsel, Oliver
Finn, Robert D
Fritz, Adrian
Fuchs, Stephan
Hattab, Georges
Hauschild, Anne-Christin
Heider, Dominik
Hoffmann, Marie
Hölzer, Martin
Hoops, Stefan
Kaderali, Lars
Kalvari, Ioanna
von Kleist, Max
Kmiecinski, Renó
Kühnert, Denise
Lasso, Gorka
Libin, Pieter
List, Markus
Löchel, Hannah F
Martin, Maria J
Martin, Roman
Matschinske, Julian
McHardy, Alice C
Mendes, Pedro
Mistry, Jaina
Navratil, Vincent
Nawrocki, Eric P
O'Toole, Áine Niamh
Ontiveros-Palacios, Nancy
Petrov, Anton I
Rangel-Pineros, Guillermo
Redaschi, Nicole
Reimering, Susanne
Reinert, Knut
Reyes, Alejandro
Richardson, Lorna
Robertson, David L
Sadegh, Sepideh
Singer, Joshua B
Theys, Kristof
Upton, Chris
Welzel, Marius
Williams, Lowri
Marz, Manja
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
SARS-CoV-2
drug design
epidemiology
sequencing
tools
virus bioinformatics
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories.
2020-11-24T12:50:51Z
2020-11-24T12:50:51Z
2020-11-04
Article
Brief Bioinform. 2020 Nov 4:bbaa232. doi: 10.1093/bib/bbaa232. Epub ahead of print.
33147627
10.1093/bib/bbaa232
http://hdl.handle.net/10033/622607
1477-4054
Briefings in bioinformatics
en
http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
Oxford Academic
Briefings in bioinformatics
England
oai:repository.helmholtz-hzi.de:10033/6226822021-01-15T01:53:48Zcom_10033_620597com_10033_620589col_10033_620598col_10033_620590
Hepatitis C reference viruses highlight potent antibody responses and diverse viral functional interactions with neutralising antibodies.
Bankwitz, Dorothea
Bahai, Akash
Labuhn, Maurice
Doepke, Mandy
Ginkel, Corinne
Khera, Tanvi
Todt, Daniel
Ströh, Luisa J
Dold, Leona
Klein, Florian
Klawonn, Frank
Krey, Thomas
Behrendt, Patrick
Cornberg, Markus
McHardy, Alice C
Pietschmann, Thomas
TWINCORE, Zentrum für experimentelle und klinische Infektionsforschung GmbH,Feodor-Lynen Str. 7, 30625 Hannover, Germany.; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
HCV
genotype
hepatitis C
immunology in hepatology
liver
Community-acquired pneumonia by primary or superinfections with Streptococcus pneumoniae can lead to acute respiratory distress requiring mechanical ventilation. The pore-forming toxin pneumolysin alters the alveolar-capillary barrier and causes extravasation of protein-rich fluid into the interstitial pulmonary tissue, which impairs gas exchange. Platelets usually prevent endothelial leakage in inflamed pulmonary tissue by sealing inflammation-induced endothelial gaps. We not only confirm that S pneumoniae induces CD62P expression in platelets, but we also show that, in the presence of pneumolysin, CD62P expression is not associated with platelet activation. Pneumolysin induces pores in the platelet membrane, which allow anti-CD62P antibodies to stain the intracellular CD62P without platelet activation. Pneumolysin treatment also results in calcium efflux, increase in light transmission by platelet lysis (not aggregation), loss of platelet thrombus formation in the flow chamber, and loss of pore-sealing capacity of platelets in the Boyden chamber. Specific anti-pneumolysin monoclonal and polyclonal antibodies inhibit these effects of pneumolysin on platelets as do polyvalent human immunoglobulins. In a post hoc analysis of the prospective randomized phase 2 CIGMA trial, we show that administration of a polyvalent immunoglobulin preparation was associated with a nominally higher platelet count and nominally improved survival in patients with severe S pneumoniae-related community-acquired pneumonia. Although, due to the low number of patients, no definitive conclusion can be made, our findings provide a rationale for investigation of pharmacologic immunoglobulin preparations to target pneumolysin by polyvalent immunoglobulin preparations in severe community-acquired pneumococcal pneumonia, to counteract the risk of these patients becoming ventilation dependent. This trial was registered at www.clinicaltrials.gov as #NCT01420744.
2021-01-14T15:18:35Z
2021-01-14T15:18:35Z
2020-12-15
Article
Gut. 2020 Dec 15:gutjnl-2020-321190. doi: 10.1136/gutjnl-2020-321190. Epub ahead of print.
33323394
10.1136/gutjnl-2020-321190
http://hdl.handle.net/10033/622682
1468-3288
Gut
en
http://creativecommons.org/licenses/BY/NC//4.0/
Attribution 4.0 International
BMJ Publisher. Group
Gut
England
oai:repository.helmholtz-hzi.de:10033/6227862022-03-24T13:19:46Zcom_10033_620597col_10033_620598
Evaluating assembly and variant calling software for strain-resolved analysis of large DNA viruses
Deng, Zhi-Luo
Dhingra, Akshay
Fritz, Adrian
Götting, Jasper
Münch, Philipp C
Steinbrück, Lars
Schulz, Thomas F
Ganzenmüller, Tina
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Molecular Biology
Information Systems
Infection with human cytomegalovirus (HCMV) can cause severe complications in immunocompromised individuals and congenitally infected children. Characterizing heterogeneous viral populations and their evolution by high-throughput sequencing of clinical specimens requires the accurate assembly of individual strains or sequence variants and suitable variant calling methods. However, the performance of most methods has not been assessed for populations composed of low divergent viral strains with large genomes, such as HCMV. In an extensive benchmarking study, we evaluated 15 assemblers and 6 variant callers on 10 lab-generated benchmark data sets created with two different library preparation protocols, to identify best practices and challenges for analyzing such data. Most assemblers, especially metaSPAdes and IVA, performed well across a range of metrics in recovering abundant strains. However, only one, Savage, recovered low abundant strains and in a highly fragmented manner. Two variant callers, LoFreq and VarScan2, excelled across all strain abundances. Both shared a large fraction of false positive variant calls, which were strongly enriched in T to G changes in a ‘G.G’ context. The magnitude of this context-dependent systematic error is linked to the experimental protocol. We provide all benchmarking data, results and the entire benchmarking workflow named QuasiModo, Quasispecies Metric determination on omics, under the GNU General Public License v3.0 (https://github.com/hzi-bifo/Quasimodo), to enable full reproducibility and further benchmarking on these and other data.
2021-03-23T12:39:07Z
2021-03-23T12:39:07Z
2020-07-07
Problem solving protocol
Briefings in Bioinformatics, 2020;, bbaa123, https://doi.org/10.1093/bib/bbaa123.
10.1093/bib/bbaa123
http://hdl.handle.net/10033/622786
1477-4054
Briefings in Bioinformatics
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Oxford University Press (OUP)
Briefings in Bioinformatics
oai:repository.helmholtz-hzi.de:10033/6228342021-04-21T01:31:18Zcom_10033_620597col_10033_620598
Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit.
Meyer, Fernando
Lesker, Till-Robin
Koslicki, David
Fritz, Adrian
Gurevich, Alexey
Darling, Aaron E
Sczyrba, Alexander
Bremges, Andreas
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.
2021-04-20T12:29:37Z
2021-04-20T12:29:37Z
2021-03-01
Review
Nat Protoc. 2021 Apr;16(4):1785-1801. doi: 10.1038/s41596-020-00480-3. Epub 2021 Mar 1.
33649565
10.1038/s41596-020-00480-3
http://hdl.handle.net/10033/622834
1750-2799
Nature protocols
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Nature Research
Nature protocols
England
oai:repository.helmholtz-hzi.de:10033/6228542021-05-06T01:46:08Zcom_10033_620597com_10033_620968col_10033_620970col_10033_620969col_10033_620598
Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.
Bernardes, Joana P
Mishra, Neha
Tran, Florian
Bahmer, Thomas
Best, Lena
Blase, Johanna I
Bordoni, Dora
Franzenburg, Jeanette
Geisen, Ulf
Josephs-Spaulding, Jonathan
Köhler, Philipp
Künstner, Axel
Rosati, Elisa
Aschenbrenner, Anna C
Bacher, Petra
Baran, Nathan
Boysen, Teide
Brandt, Burkhard
Bruse, Niklas
Dörr, Jonathan
Dräger, Andreas
Elke, Gunnar
Ellinghaus, David
Fischer, Julia
Forster, Michael
Franke, Andre
Franzenburg, Sören
Frey, Norbert
Friedrichs, Anette
Fuß, Janina
Glück, Andreas
Hamm, Jacob
Hinrichsen, Finn
Hoeppner, Marc P
Imm, Simon
Junker, Ralf
Kaiser, Sina
Kan, Ying H
Knoll, Rainer
Lange, Christoph
Laue, Georg
Lier, Clemens
Lindner, Matthias
Marinos, Georgios
Markewitz, Robert
Nattermann, Jacob
Noth, Rainer
Pickkers, Peter
Rabe, Klaus F
Renz, Alina
Röcken, Christoph
Rupp, Jan
Schaffarzyk, Annika
Scheffold, Alexander
Schulte-Schrepping, Jonas
Schunk, Domagoj
Skowasch, Dirk
Ulas, Thomas
Wandinger, Klaus-Peter
Wittig, Michael
Zimmermann, Johannes
Busch, Hauke
Hoyer, Bimba F
Kaleta, Christoph
Heyckendorf, Jan
Kox, Matthijs
Rybniker, Jan
Schreiber, Stefan
Schultze, Joachim L
Rosenstiel, Philip
Deutsche COVID-19 Omics Initiative (DeCOI)
HIRI, Helmholtz-Institut für RNA-basierte Infektionsforschung, Josef-Shneider Strasse 2, 97080 Würzburg, Germany.; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
COVID-19
RNA-seq
acute respiratory distress
blood
disease trajectory
immune response
infectious disease
methylation
scRNA-seq
virus
Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.
2021-05-05T11:04:51Z
2021-05-05T11:04:51Z
2020-11-26
Article
mmunity. 2020 Dec 15;53(6):1296-1314.e9. doi: 10.1016/j.immuni.2020.11.017. Epub 2020 Nov 26.
33296687
10.1016/j.immuni.2020.11.017
http://hdl.handle.net/10033/622854
1097-4180
Immunity
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Elsevier (Cell Press)
53
6
1296
1314.e9
Immunity
United States
oai:repository.helmholtz-hzi.de:10033/6229352021-07-13T01:41:45Zcom_10033_620597com_10033_211390col_10033_211409col_10033_620598
Needs for an Integration of Specific Data Sources and Items - First Insights of a National Survey Within the German Center for Infection Research.
Jakob, Carolin E M
Stecher, Melanie
Fuhrmann, Sandra
Wingen-Heimann, Sebastian
Heinen, Stephanie
Anton, Gabriele
Behnke, Michael
Behrends, Uta
Boeker, Martin
Castell, Stefanie
Demski, Hans
Diefenbach, Maximilian
Falgenhauer, Jane C
Fritzenwanker, Moritz
Gastmeier, Petra
Gerhard, Markus
Glöckner, Stephan
Golubovic, Mira
Gunsenheimer Bartmeyer, Barbara
Ingenerf, Josef
Kaiser, Rolf
Körner, Marie-Luise
Loag, Wibke
Mchardy, Alice
Molitor, Ernst
Nübel, Ulrich
Pritsch, Michael
Ramharter, Michael
Rieg, Sigbert R
Rupp, Jan
Schindler, Daniela
Schwudke, Dominik
Spinner, Christoph
Stottmeier, Benjamin
Vehreschild, Maria
Willmann, Matthias
Vehreschild, Jörg J
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Data integration
infectious diseases
minimum data requirement
survey
State-subsidized programs develop medical data integration centers in Germany. To get infection disease (ID) researchers involved in the process of data sharing, common interests and minimum data requirements were prioritized. In 06/2019 we have initiated the German Infectious Disease Data Exchange (iDEx) project. We have developed and performed an online survey to determine prioritization of requests for data integration and exchange in ID research. The survey was designed with three sub-surveys, including a ranking of 15 data categories and 184 specific data items and a query of available 51 data collecting systems. A total of 84 researchers from 17 fields of ID research participated in the survey (predominant research fields: gastrointestinal infections n=11, healthcare-associated and antibiotic-resistant infections n=10, hepatitis n=10). 48% (40/84) of participants had experience as medical doctor. The three top ranked data categories were microbiology and parasitology, experimental data, and medication (53%, 52%, and 47% of maximal points, respectively). The most relevant data items for these categories were bloodstream infections, availability of biomaterial, and medication (88%, 87%, and 94% of maximal points, respectively). The ranking of requests of data integration and exchange is diverse and depends on the chosen measure. However, there is need to promote discipline-related digitalization and data exchange.
2021-07-12T13:50:13Z
2021-07-12T13:50:13Z
2021-05-24
Article
Stud Health Technol Inform. 2021 May 24;278:237-244. doi: 10.3233/SHTI210075.
34042900
10.3233/SHTI210075
http://hdl.handle.net/10033/622935
1879-8365
Studies in health technology and informatics
en
http://creativecommons.org/licenses/by-nc/4.0/
Attribution-NonCommercial 4.0 International
IOS Press
278
237
244
Studies in health technology and informatics
Netherlands
oai:repository.helmholtz-hzi.de:10033/6229642021-07-29T01:53:54Zcom_10033_620597com_10033_6839com_10033_621852col_10033_621853col_10033_620598col_10033_621495
Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease.
Chu, Xiaojing
Jaeger, Martin
Beumer, Joep
Bakker, Olivier B
Aguirre-Gamboa, Raul
Oosting, Marije
Smeekens, Sanne P
Moorlag, Simone
Mourits, Vera P
Koeken, Valerie A C M
de Bree, Charlotte
Jansen, Trees
Mathews, Ian T
Dao, Khoi
Najhawan, Mahan
Watrous, Jeramie D
Joosten, Irma
Sharma, Sonia
Koenen, Hans J P M
Withoff, Sebo
Jonkers, Iris H
Netea-Maier, Romana T
Xavier, Ramnik J
Franke, Lude
Xu, Cheng-Jian
Joosten, Leo A B
Sanna, Serena
Jain, Mohit
Kumar, Vinod
Clevers, Hans
Wijmenga, Cisca
Netea, Mihai G
Li, Yang
CiiM, Zentrum für individualisierte Infektionsmedizin, Feodor-Lynen-Str.7, 30625 Hannover.; TWINCORE, Zentrum für experimentelle und klinische Infektionsforschung GmbH,Feodor-Lynen Str. 7, 30625 Hannover, Germany.; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Genomics
Immune phenotypes
Integrative analysis
Metabolomics
Background: Recent studies highlight the role of metabolites in immune diseases, but it remains unknown how much of this effect is driven by genetic and non-genetic host factors.
Result: We systematically investigate circulating metabolites in a cohort of 500 healthy subjects (500FG) in whom immune function and activity are deeply measured and whose genetics are profiled. Our data reveal that several major metabolic pathways, including the alanine/glutamate pathway and the arachidonic acid pathway, have a strong impact on cytokine production in response to ex vivo stimulation. We also examine the genetic regulation of metabolites associated with immune phenotypes through genome-wide association analysis and identify 29 significant loci, including eight novel independent loci. Of these, one locus (rs174584-FADS2) associated with arachidonic acid metabolism is causally associated with Crohn's disease, suggesting it is a potential therapeutic target.
Conclusion: This study provides a comprehensive map of the integration between the blood metabolome and immune phenotypes, reveals novel genetic factors that regulate blood metabolite concentrations, and proposes an integrative approach for identifying new disease treatment targets.
2021-07-28T13:30:46Z
2021-07-28T13:30:46Z
2021-07-06
Article
Genome Biol. 2021 Jul 6;22(1):198. doi: 10.1186/s13059-021-02413-z.
34229738
10.1186/s13059-021-02413-z
http://hdl.handle.net/10033/622964
1474-760X
Genome biology
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
BMC
22
1
198
Genome biology
United States
United States
United States
United States
United States
United States
International
International
International
England
oai:repository.helmholtz-hzi.de:10033/6229882021-08-17T01:50:52Zcom_10033_620597col_10033_620598
Understanding and Engineering the Stereoselectivity of Humulene Synthase.
Schotte, Carsten
Lukat, Peer
Deuschmann, Adrian
Blankenfeldt, Wulf
Cox, Russell J
HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.
biosynthesis
enzyme engineering
humulene
meroterpenoid
tropolone sesquiterpenoid
The non-canonical terpene cyclase AsR6 is responsible for the formation of 2E,6E,9E-humulene during the biosynthesis of the tropolone sesquiterpenoid (TS) xenovulene A. The structures of unliganded AsR6 and of AsR6 in complex with an in crystallo cyclized reaction product and thiolodiphosphate reveal a new farnesyl diphosphate binding motif that comprises a unique binuclear Mg2+ -cluster and an essential K289 residue that is conserved in all humulene synthases involved in TS formation. Structure-based site-directed mutagenesis of AsR6 and its homologue EupR3 identify a single residue, L285/M261, that controls the production of either 2E,6E,9E- or 2Z,6E,9E-humulene. A possible mechanism for the observed stereoselectivity was investigated using different isoprenoid precursors and results demonstrate that M261 has gatekeeping control over product formation.
2021-08-16T12:05:27Z
2021-08-16T12:05:27Z
2021-06-28
communication
Angew Chem Int Ed Engl. 2021 Jun 28. doi: 10.1002/anie.202106718. Epub ahead of print.
34180566
10.1002/anie.202106718
http://hdl.handle.net/10033/622988
1521-3773
Angewandte Chemie (International ed. in English)
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Wiley-VCH
Angewandte Chemie (International ed. in English)
Germany
oai:repository.helmholtz-hzi.de:10033/6229892021-08-17T01:50:59Zcom_10033_620597col_10033_620598
EpitopeVec: Linear Epitope Prediction Using Deep Protein Sequence Embeddings.
Bahai, Akash
Asgari, Ehsaneddin
Mofrad, Mohammad R K
Kloetgen, Andreas
McHardy, Alice C
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Motivation: B-cell epitopes (BCEs) play a pivotal role in the development of peptide vaccines, immuno-diagnostic reagents, and antibody production, and thus in infectious disease prevention and diagnostics in general. Experimental methods used to determine BCEs are costly and time-consuming. Therefore, it is essential to develop computational methods for the rapid identification of BCEs. Although several computational methods have been developed for this task, generalizability is still a major concern, where cross-testing of the classifiers trained and tested on different datasets has revealed accuracies of 51-53.
Results: We describe a new method called EpitopeVec, which uses a combination of residue properties, modified antigenicity scales, and protein language model-based representations (protein vectors) as features of peptides for linear BCE predictions. Extensive benchmarking of EpitopeVec and other state-of-the-art methods for linear BCE prediction on several large and small datasets, as well as cross-testing, demonstrated an improvement in the performance of EpitopeVec over other methods in terms of accuracy and area under the curve (AUC). As the predictive performance depended on the species origin of the respective antigens (viral, bacterial, eukaryotic), we also trained our method on a large viral dataset to create a dedicated linear viral BCE predictor with improved cross-testing
2021-08-16T12:47:14Z
2021-08-16T12:47:14Z
2021-06-28
Article
Bioinformatics. 2021 Jun 28:btab467. doi: 10.1093/bioinformatics/btab467. Epub ahead of print.
34180989
10.1093/bioinformatics/btab467
http://hdl.handle.net/10033/622989
1367-4811
Bioinformatics (Oxford, England)
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Oxford University Press
Bioinformatics (Oxford, England)
England
oai:repository.helmholtz-hzi.de:10033/6230072021-09-01T01:53:59Zcom_10033_620597col_10033_620598
Offspring born to influenza A virus infected pregnant mice have increased susceptibility to viral and bacterial infections in early life.
Jacobsen, Henning
Walendy-Gnirß, Kerstin
Tekin-Bubenheim, Nilgün
Kouassi, Nancy Mounogou
Ben-Batalla, Isabel
Berenbrok, Nikolaus
Wolff, Martin
Dos Reis, Vinicius Pinho
Zickler, Martin
Scholl, Lucas
Gries, Annette
Jania, Hanna
Kloetgen, Andreas
Düsedau, Arne
Pilnitz-Stolze, Gundula
Jeridi, Aicha
Yildirim, Ali Önder
Fuchs, Helmut
Gailus-Durner, Valerie
Stoeger, Claudia
de Angelis, Martin Hrabe
Manuylova, Tatjana
Klingel, Karin
Culley, Fiona J
Behrends, Jochen
Loges, Sonja
Schneider, Bianca
Krauss-Etschmann, Susanne
Openshaw, Peter
Gabriel, Gülsah
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Influenza during pregnancy can affect the health of offspring in later life, among which neurocognitive disorders are among the best described. Here, we investigate whether maternal influenza infection has adverse effects on immune responses in offspring. We establish a two-hit mouse model to study the effect of maternal influenza A virus infection (first hit) on vulnerability of offspring to heterologous infections (second hit) in later life. Offspring born to influenza A virus infected mothers are stunted in growth and more vulnerable to heterologous infections (influenza B virus and MRSA) than those born to PBS- or poly(I:C)-treated mothers. Enhanced vulnerability to infection in neonates is associated with reduced haematopoetic development and immune responses. In particular, alveolar macrophages of offspring exposed to maternal influenza have reduced capacity to clear second hit pathogens. This impaired pathogen clearance is partially reversed by adoptive transfer of alveolar macrophages from healthy offspring born to uninfected dams. These findings suggest that maternal influenza infection may impair immune ontogeny and increase susceptibility to early life infections of offspring.
2021-08-31T12:17:58Z
2021-08-31T12:17:58Z
2021-08-16
Article
Nat Commun. 2021 Aug 16;12(1):4957. doi: 10.1038/s41467-021-25220-3.
34400653
10.1038/s41467-021-25220-3
http://hdl.handle.net/10033/623007
2041-1723
Nature communications
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Springer Nature
12
1
4957
Nature communications
United Kingdom
United Kingdom
England
oai:repository.helmholtz-hzi.de:10033/6230972021-11-17T02:45:53Zcom_10033_620597col_10033_620598
Cohesin Core Complex Gene Dosage Contributes to Germinal Center Derived Lymphoma Phenotypes and Outcomes.
Rivas, Martin A
Durmaz, Ceyda
Kloetgen, Andreas
Chin, Cristopher R
Chen, Zhengming
Bhinder, Bhavneet
Koren, Amnon
Viny, Aaron D
Scharer, Christopher D
Boss, Jeremy M
Elemento, Olivier
Mason, Christopher E
Melnick, Ari M
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
B-cell
GCB-subtype DLBCL
Hi-C
Tet2 gene
chromosomal architecture
cohesin
lymphoma
The cohesin complex plays critical roles in genomic stability and gene expression through effects on 3D architecture. Cohesin core subunit genes are mutated across a wide cross-section of cancers, but not in germinal center (GC) derived lymphomas. In spite of this, haploinsufficiency of cohesin ATPase subunit Smc3 was shown to contribute to malignant transformation of GC B-cells in mice. Herein we explored potential mechanisms and clinical relevance of Smc3 deficiency in GC lymphomagenesis. Transcriptional profiling of Smc3 haploinsufficient murine lymphomas revealed downregulation of genes repressed by loss of epigenetic tumor suppressors Tet2 and Kmt2d. Profiling 3D chromosomal interactions in lymphomas revealed impaired enhancer-promoter interactions affecting genes like Tet2, which was aberrantly downregulated in Smc3 deficient lymphomas. Tet2 plays important roles in B-cell exit from the GC reaction, and single cell RNA-seq profiles and phenotypic trajectory analysis in Smc3 mutant mice revealed a specific defect in commitment to the final steps of plasma cell differentiation. Although Smc3 deficiency resulted in structural abnormalities in GC B-cells, there was no increase of somatic mutations or structural variants in Smc3 haploinsufficient lymphomas, suggesting that cohesin deficiency largely induces lymphomas through disruption of enhancer-promoter interactions of terminal differentiation and tumor suppressor genes. Strikingly, the presence of the Smc3 haploinsufficient GC B-cell transcriptional signature in human patients with GC-derived diffuse large B-cell lymphoma (DLBCL) was linked to inferior clinical outcome and low expression of cohesin core subunits. Reciprocally, reduced expression of cohesin subunits was an independent risk factor for worse survival int DLBCL patient cohorts. Collectively, the data suggest that Smc3 functions as a bona fide tumor suppressor for lymphomas through non-genetic mechanisms, and drives disease by disrupting the commitment of GC B-cells to the plasma cell fate.
2021-11-16T14:55:51Z
2021-11-16T14:55:51Z
2021-09-21
Article
Front Immunol. 2021 Sep 21;12:688493. doi: 10.3389/fimmu.2021.688493.
34621263
10.3389/fimmu.2021.688493
http://hdl.handle.net/10033/623097
1664-3224
Frontiers in immunology
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
Frontiers
12
688493
Frontiers in immunology
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
Switzerland
oai:repository.helmholtz-hzi.de:10033/6231132021-12-08T01:53:08Zcom_10033_620597col_10033_620598
A bipartite element with allele-specific functions safeguards DNA methylation imprints at the Dlk1-Dio3 locus.
Aronson, Boaz E
Scourzic, Laurianne
Shah, Veevek
Swanzey, Emily
Kloetgen, Andreas
Polyzos, Alexander
Sinha, Abhishek
Azziz, Annabel
Caspi, Inbal
Li, Jiexi
Pelham-Webb, Bobbie
Glenn, Rachel A
Vierbuchen, Thomas
Wichterle, Hynek
Tsirigos, Aristotelis
Dawlaty, Meelad M
Stadtfeld, Matthias
Apostolou, Effie
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
DNA methylation
Dlk1-Dio3
Dnmt3
IG-DMR
Tet enzymes
bipartite element
enhancer
epigenome editing
genomic imprinting
pluripotent stem cells
Loss of imprinting (LOI) results in severe developmental defects, but the mechanisms preventing LOI remain incompletely understood. Here, we dissect the functional components of the imprinting control region of the essential Dlk1-Dio3 locus (called IG-DMR) in pluripotent stem cells. We demonstrate that the IG-DMR consists of two antagonistic elements: a paternally methylated CpG island that prevents recruitment of TET dioxygenases and a maternally unmethylated non-canonical enhancer that ensures expression of the Gtl2 lncRNA by counteracting de novo DNA methyltransferases. Genetic or epigenetic editing of these elements leads to distinct LOI phenotypes with characteristic alternations of allele-specific gene expression, DNA methylation, and 3D chromatin topology. Although repression of the Gtl2 promoter results in dysregulated imprinting, the stability of LOI phenotypes depends on the IG-DMR, suggesting a functional hierarchy. These findings establish the IG-DMR as a bipartite control element that maintains imprinting by allele-specific restriction of the DNA (de)methylation machinery.
2021-12-07T10:22:28Z
2021-12-07T10:22:28Z
2021-10-27
Article
jDev Cell. 2021 Nov 22;56(22):3052-3065.e5. doi: 10.1016/j.devcel.2021.10.004. Epub 2021 Oct 27.
34710357
10.1016/j.devcel.2021.10.004
http://hdl.handle.net/10033/623113
1878-1551
Developmental cell
en
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 International
Elsevier (Cell Press)
56
22
3052
3065.e5
Developmental cell
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
oai:repository.helmholtz-hzi.de:10033/6231422022-01-14T03:20:07Zcom_10033_620597col_10033_620598
Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo.
Lähnemann, David
Köster, Johannes
Fischer, Ute
Borkhardt, Arndt
McHardy, Alice C
Schönhuth, Alexander
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.
Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable-because computationally efficient-manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo.
2022-01-13T12:46:09Z
2022-01-13T12:46:09Z
2021-11-18
Article
Nat Commun. 2021 Nov 18;12(1):6744. doi: 10.1038/s41467-021-26938-w.
34795237
10.1038/s41467-021-26938-w
http://hdl.handle.net/10033/623142
2041-1723
Nature communications
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
NPG
12
1
6744
Nature communications
England
oai:repository.helmholtz-hzi.de:10033/6231452022-01-18T03:43:27Zcom_10033_620597col_10033_620598
In vitro interaction network of a synthetic gut bacterial community.
Weiss, Anna S
Burrichter, Anna G
Durai Raj, Abilash Chakravarthy
von Strempel, Alexandra
Meng, Chen
Kleigrewe, Karin
Münch, Philipp C
Rössler, Luis
Huber, Claudia
Eisenreich, Wolfgang
Jochum, Lara M
Göing, Stephanie
Jung, Kirsten
Lincetto, Chiara
Hübner, Johannes
Marinos, Georgios
Zimmermann, Johannes
Kaleta, Christoph
Sanchez, Alvaro
Stecher, Bärbel
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM12) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM12 interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, Enterococcus faecalis KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM12 interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.
2022-01-17T09:17:55Z
2022-01-17T09:17:55Z
2021-12-02
Article
ISME J. 2021 Dec 2. doi: 10.1038/s41396-021-01153-z. Epub ahead of print.
34857933
10.1038/s41396-021-01153-z
http://hdl.handle.net/10033/623145
1751-7370
The ISME journal
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
NPG
The ISME journal
England
oai:repository.helmholtz-hzi.de:10033/6231882022-05-07T01:56:59Zcom_10033_620597col_10033_620598
MIAMI--a tool for non-targeted detection of metabolic flux changes for mode of action identification.
Dudek, Christian-Alexander
Reuse, Carsten
Fuchs, Regine
Hendriks, Janneke
Starck, Veronique
Hiller, Karsten
2022-05-06T13:41:48Z
2022-05-06T13:41:48Z
2022-05-06
Article
32324861
10.1093/bioinformatics/btaa251
http://hdl.handle.net/10033/623188
1367-4811
Bioinformatics (Oxford, England)
en
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
36
12
3925
3926
Bioinformatics (Oxford, England)
England