• 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. (Springer-Nature, 2019-04-18)
      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.
    • 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. (Springer Nature, 2019-03-05)
    • 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. (BioMedCentral, 2019-03-04)
      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 .
    • 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; et al. (BioMedCentral, 2019-02-08)
      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.
    • 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; et al. (Ferrata Storti Foundation, 2019-01-01)
      The homeobox gene
    • 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. (PLOS, 2019-01-01)
      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.
    • 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; et al. (Springer-Nature, 2019-01-01)
      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.
    • 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. (Nature publishing group, 2018-11-19)
      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.
    • 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. (Elsevier, 2018-07-11)
      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.
    • 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. (Oxford University Press, 2018-07-01)
      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.
    • 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. (2018-06-08)
      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).
    • 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; et al. (2018-05-14)
      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.
    • "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; et al. (2018-03-01)
      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.
    • 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; et al. (2018-02-01)
      Innate immune activation is essential to mount an effective antiviral response and to prime adaptive immunity. Although a crucial role of CD169
    • 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. (2018-01-10)
      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
    • 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. (2017-12-05)
      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.
    • EDEN: evolutionary dynamics within environments.

      Münch, Philipp C; Stecher, Bärbel; McHardy, Alice C; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Oxford Academic, 2017-10-15)
      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.
    • 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. (2017-10-09)
      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.
    • 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. (2017-06-12)
      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.
    • 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 (2017-05-22)
      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.