• 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.
    • 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. (2015-07)
      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.
    • 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 (2016-07-06)
      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.
    • 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; 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. (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 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. (2016-09)
      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.
    • "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. (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.
    • 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.
    • 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. (2014-10)
      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.
    • 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 (2015-07-28)
      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.
    • 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. (2016-01)
      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.
    • 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. (2016)
      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.
    • 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. (2017-01-31)
      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.
    • 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. (2016-11-21)
      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
    • 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. (2017)
      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.
    • How to Grow a Computational Biology Lab.

      McHardy, Alice Carolyn; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2015-09)
    • 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. (2016)
      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.
    • 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.
    • 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.
    • 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. (2017-05-10)
      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.