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Abstract Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic pathogen. Its RNA genome consists of two negative-sense segments (L and M) with one gene each, and one ambisense segment (S) with two opposing genes separated by the noncoding “intergenic region” (IGR). These vRNAs and the complementary cRNAs are encapsidated by nucleoprotein (N). Using iCLIP2 (individual-nucleotide resolution UV crosslinking and immunoprecipitation) to map all N-vRNA and N-cRNA interactions, we detect N coverage along the L and M segments. However, the S segment vRNA and cRNA each contain approximately 100 non-encapsidated nucleotides stretching from the IGR into the 5’-adjacent reading frame. These exposed regions are RNase-sensitive and predicted to form stem-loop structures with the mRNA transcription termination motif positioned near the top. Moreover, optimal S segment transcription and replication requires the entire exposed region rather than only the IGR. Thus, the RVFV S segment contains a central, non-encapsidated RNA region with a functional role.

Abstract Even though high-throughput transcriptome sequencing is routinely performed in many laboratories, computational analysis of such data remains a cumbersome process often executed manually, hence error-prone and lacking reproducibility. For corresponding data processing, we introduce Curare, an easy-to-use yet versatile workflow builder for analyzing high-throughput RNA-Seq data focusing on differential gene expression experiments. Data analysis with Curare is customizable and subdivided into preprocessing, quality control, mapping, and downstream analysis stages, providing multiple options for each step while ensuring the reproducibility of the workflow. For a fast and straightforward exploration and visualization of differential gene expression results, we provide the gene expression visualizer software GenExVis. GenExVis can create various charts and tables from simple gene expression tables and DESeq2 results without the requirement to upload data or install software packages. In combination, Curare and GenExVis provide a comprehensive software environment that supports the entire data analysis process, from the initial handling of raw RNA-Seq data to the final DGE analyses and result visualizations, thereby significantly easing data processing and subsequent interpretation.

Increasing landscape transformations and urbanisation affect insectivorous bird populations in various ways such as food availability, breeding phenology, or reproductive success. Especially during the breeding season, many passerine birds rely on the availability of caterpillars as the main prey for their nestlings. Previous studies suggested that similar diet preferences of sympatric species may result in interspecific competition, as demonstrated for Blue and Great Tits in forest habitats. However, nestling diet and prey preferences in other habitats are not fully understood. Prey availability, especially caterpillars, is lower in cities than in forests, thus influencing prey choice and interspecific competition. Here we used faecal DNA metabarcoding to investigate if nestling diet composition of the two sympatric species Blue Cyanistes caeruleus and Great Tits Parus major varied among species and different habitats (forest, traditional orchards, and urban parks). Furthermore, we examined food availability by DNA barcoding of the arboreal arthropod communities among habitats and compared them to the nestling diet to infer parental prey selectivity. The study was carried out in central Germany from 2018 to 2019. Blue and Great Tits showed a diverse diet which was dominated by Lepidoptera in all habitats. Lepidopteran diet components were most similar between forest and orchard sites, as were the components with other arthropods between orchard and urban sites. Both tit species showed selectivity for the lepidopteran families Geometridae and Tortricidae in all habitats, and for Noctuidae (Lepidoptera), Tenthredinidae and Braconidae (Hymenoptera) in forest and orchard sites. As the tits showed preferences for mainly families of Lepidoptera, and Hymenoptera, our approach provides a baseline to support monitoring of these groups.

Microbes – bacteria, archaea, unicellular eukaryotes, and viruses – play an important role in human and environmental health. Growing awareness of this fact has led to a huge increase in microbiological research and applications in a variety of fields. Driven by technological advances that allow high-throughput molecular characterization of microbial species and communities, microbiological research now offers unparalleled opportunities to address current and emerging needs. As well as helping to address global health threats such as antimicrobial resistance and viral pandemics, it also has a key role to play in areas such as agriculture, waste management, water treatment, ecosystems remediation, and the diagnosis, treatment and prevention of various diseases. Reflecting this broad potential, billions of euros have been invested in microbiota research programs worldwide. Though run independently, many of these projects are closely related. However, Germany currently has no infrastructure to connect such projects or even compare their results. Thus, the potential synergy of data and expertise is being squandered. The goal of the NFDI4Microbiota consortium is to serve and connect this broad and heterogeneous research community by elevating the availability and quality of research results through dedicated training, and by facilitating the generation, management, interpretation, sharing, and reuse of microbial data. In doing so, we will also foster interdisciplinary interactions between researchers. NFDI4Microbiota will achieve this by creating a German microbial research network through training and community-building activities, and by creating a cloud-based system that will make the storage, integration and analysis of microbial data, especially omics data, consistent, reproducible, and accessible across all areas of life sciences. In addition to increasing the quality of microbial research in Germany, our training program will support widespread and proper usage of these services. Through this dual emphasis on education and services, NFDI4Microbiota will ensure that microbial research in Germany is synergistic and efficient, and thus excellent. By creating a central resource for German microbial research, NDFDI4Microbiota will establish a connecting hub for all NFDI consortia that work with microbiological data, including GHGA, NFDI4Biodiversity, NFDI4Agri and several others. NFDI4Microbiota will provide non-microbial specialists from these consortia with direct and easy access to the necessary expertise and infrastructure in microbial research in order to facilitate their daily work and enhance their research. The links forged through NFDI4Microbiota will not only increase the synergy between NFDI consortia, but also elevate the overall quality and relevance of microbial research in Germany.

The construction of complex synthetic gene circuits with predetermined and reliable output depends on orthogonal regulatory parts that do not inadvertently interfere with the host machinery or with other circuit components. Previously, extracytoplasmic function sigma factors (ECFs), a diverse group of alternative sigma factors with distinct promoter specificities, were shown to have great potential as context-independent regulators, but so far, they have only been used in a few model species. Here, we show that the alphaproteobacterium Sinorhizobium meliloti, which has been proposed as a plant-associated bacterial chassis for synthetic biology, has a similar phylogenetic ECF acceptance range as the gammaproteobacterium Escherichia coli. A common set of orthogonal ECF-based regulators that can be used in both bacterial hosts was identified and used to create 2-step delay circuits. The genetic circuits were implemented in single copy in E. coli by chromosomal integration using an established method that utilizes bacteriophage integrases. In S. meliloti, we demonstrated the usability of single-copy pABC plasmids as equivalent carriers of the synthetic circuits. The circuits were either implemented on a single pABC or modularly distributed on 3 such plasmids. In addition, we provide a toolbox containing pABC plasmids compatible with the Golden Gate (MoClo) cloning standard and a library of basic parts that enable the construction of ECF-based circuits in S. meliloti and in E. coli. This work contributes to building a context-independent and species-overarching ECF-based toolbox for synthetic biology applications.

The hemiparasitic flowering plant Viscum album (European mistletoe) is known for its very special life cycle, extraordinary biochemical properties, and extremely large genome. The size of its genome is estimated to be 30 times larger than the human genome and 600 times larger than the genome of the model plant Arabidopsis thaliana. To achieve insights into the Gene Space of the genome, which is defined as the space including and surrounding protein-coding regions, a transcriptome project based on PacBio sequencing has recently been conducted. A database resulting from this project contains sequences of 39,092 different open reading frames encoding 32,064 distinct proteins. Based on ‘Benchmarking Universal Single-Copy Orthologs’ (BUSCO) analysis, the completeness of the database was estimated to be in the range of 78%. To further develop this database, we performed a transcriptome project of V. album organs harvested in summer and winter based on Illumina sequencing. Data from both sequencing strategies were combined. The new V. album Gene Space database II (VaGs II) contains 90,039 sequences and has a completeness of 93% as revealed by BUSCO analysis. Sequences from other organisms, particularly fungi, which are known to colonize mistletoe leaves, have been removed. To evaluate the quality of the new database, proteome data of a mitochondrial fraction of V. album were re-analyzed. Compared to the original evaluation published five years ago, nearly 1000 additional proteins could be identified in the mitochondrial fraction, providing new insights into the Oxidative Phosphorylation System of V. album. The VaGs II database is available at https://viscumalbum.pflanzenproteomik.de/. Furthermore, all V. album sequences have been uploaded at the European Nucleotide Archive (ENA).

Natural circular RNAs have been found to sequester microRNAs and suppress their function. We have used this principle as a molecular tool and produced artificial circular RNA sponges in a cell-free system by in vitro transcription and ligation. Formerly, we were able to inhibit hepatitis C virus propagation by applying a circular RNA decoy strategy against microRNA-122, which is essential for the viral life cycle. In another proof-of-principle study, we used circular RNAs to sequester microRNA-21, an oncogenic and pro-proliferative microRNA. This strategy slowed tumor growth in a 3D cell culture model system, as well as in xenograft mice upon systemic delivery. In the wake of the global use of an in vitro transcribed RNA in coronavirus disease 2019 (COVID-19) vaccines, the question arose whether therapeutic circular RNAs trigger cellular antiviral defense mechanisms when delivered systemically. In this study, we present data on the cellular innate immune response as a consequence of liposome-based transfection of the circular RNA sponges we previously used to inhibit microRNA function. We find that circular RNAs produced by the presented methodology do not trigger the antiviral response and do not activate innate immune-signaling pathways.

Antimicrobial resistance (AMR) is a global health and development threat. In particular, multi-drug resistance (MDR) is increasingly common in pathogenic bacteria. It has become a serious problem to public health, as MDR can lead to the failure of treatment of patients. MDR is typically the result of mutations and the accumulation of multiple resistance genes within a single cell. Machine learning methods have a wide range of applications for AMR prediction. However, these approaches typically focus on single drug resistance prediction and do not incorporate information on accumulating antimicrobial resistance traits over time. Thus, identifying multi-drug resistance simultaneously and rapidly remains an open challenge. In our study, we could demonstrate that multi-label classification (MLC) methods can be used to model multi-drug resistance in pathogens. Importantly, we found the ensemble of classifier chains (ECC) model achieves accurate MDR prediction and outperforms other MLC methods. Thus, our study extends the available tools for MDR prediction and paves the way for improving diagnostics of infections in patients. Furthermore, the MLC methods we introduced here would contribute to reducing the threat of antimicrobial resistance and related deaths in the future by improving the speed and accuracy of the identification of pathogens and resistance.

Abstract Background Mutualistic interactions with microbes can help insects adapt to extreme environments and unusual diets. An intriguing example is the burying beetle Nicrophorus vespilloides, which feeds and reproduces on small vertebrate carcasses. Its fungal microbiome is dominated by yeasts that potentially facilitate carcass utilization by producing digestive enzymes, eliminating cadaver-associated toxic volatiles (that would otherwise attract competitors), and releasing antimicrobials to sanitize the microenvironment. Some of these yeasts are closely related to the biotechnologically important species Yarrowia lipolytica. Results To investigate the roles of these Yarrowia-like yeast (YLY) strains in more detail, we selected five strains from two different phylogenetic clades for third-generation sequencing and genome analysis. The first clade, represented by strain B02, has a 20-Mb genome containing ~ 6400 predicted protein-coding genes. The second clade, represented by strain C11, has a 25-Mb genome containing ~ 6300 predicted protein-coding genes, and extensive intraspecific variability within the ITS–D1/D2 rDNA region commonly used for species assignments. Phenotypic microarray analysis revealed that both YLY strains were able to utilize a diverse range of carbon and nitrogen sources (including microbial metabolites associated with putrefaction), and can grow in environments with extreme pH and salt concentrations. Conclusions The genomic characterization of five yeast strains isolated from N. vespilloides resulted in the identification of strains potentially representing new YLY species. Given their abundance in the beetle hindgut, and dominant growth on beetle-prepared carcasses, the analysis of these strains has revealed the genetic basis of a potential symbiotic relationship between yeasts and burying beetles that facilitates carcass digestion and preservation.

Abstract Background Energy landscapes provide an approach to the mechanistic basis of spatial ecology and decision-making in animals. This is based on the quantification of the variation in the energy costs of movements through a given environment, as well as how these costs vary in time and for different animal populations. Organisms as diverse as fish, mammals, and birds will move in areas of the energy landscape that result in minimised costs and maximised energy gain. Recently, energy landscapes have been used to link energy gain and variable energy costs of foraging to breeding success, revealing their potential use for understanding demographic changes. Methods Using GPS-temperature-depth and tri-axial accelerometer loggers, stable isotope and molecular analyses of the diet, and leucocyte counts, we studied the response of gentoo (Pygoscelis papua) and chinstrap (Pygoscelis antarcticus) penguins to different energy landscapes and resources. We compared species and gentoo penguin populations with contrasting population trends. Results Between populations, gentoo penguins from Livingston Island (Antarctica), a site with positive population trends, foraged in energy landscape sectors that implied lower foraging costs per energy gained compared with those around New Island (Falkland/Malvinas Islands; sub-Antarctic), a breeding site with fluctuating energy costs of foraging, breeding success and populations. Between species, chinstrap penguins foraged in sectors of the energy landscape with lower foraging costs per bottom time, a proxy for energy gain. They also showed lower physiological stress, as revealed by leucocyte counts, and higher breeding success than gentoo penguins. In terms of diet, we found a flexible foraging ecology in gentoo penguins but a narrow foraging niche for chinstraps. Conclusions The lower foraging costs incurred by the gentoo penguins from Livingston, may favour a higher breeding success that would explain the species’ positive population trend in the Antarctic Peninsula. The lower foraging costs in chinstrap penguins may also explain their higher breeding success, compared to gentoos from Antarctica but not their negative population trend. Altogether, our results suggest a link between energy landscapes and breeding success mediated by the physiological condition.

Nosocomial pathogens of the Acinetobacter calcoaceticus-baumannii (ACB) complex are a cautionary example for the world-wide spread of multi- and pan-drug resistant bacteria. Aiding the urgent demand for novel therapeutic targets, comparative genomics studies between pathogens and their apathogenic relatives shed light on the genetic basis of human-pathogen interaction. Yet, existing studies are limited in taxonomic scope, sensing of the phylogenetic signal, and resolution by largely analyzing genes independent of their organization in functional gene clusters. Here, we explored more than 3,000 Acinetobacter genomes in a phylogenomic framework integrating orthology-based phylogenetic profiling and microsynteny conservation analyses. We delineate gene clusters in the type strain A. baumannii ATCC 19606 whose evolutionary conservation indicates a functional integration of the subsumed genes. These evolutionarily stable gene clusters (ESGCs) reveal metabolic pathways, transcriptional regulators residing next to their targets but also tie together sub-clusters with distinct functions to form higher-order functional modules. We shortlisted 150 ESGCs that either co-emerged with the pathogenic ACB clade or are preferentially found therein. They provide a high-resolution picture of genetic and functional changes that coincide with the manifestation of the pathogenic phenotype in the ACB clade. Key innovations are the remodeling of the regulatory-effector cascade connecting LuxR/LuxI quorum sensing via an intermediate messenger to biofilm formation, the extension of micronutrient scavenging systems, and the increase of metabolic flexibility by exploiting carbon sources that are provided by the human host. We could show experimentally that only members of the ACB clade use kynurenine as a sole carbon and energy source, a substance produced by humans to fine-tune the antimicrobial innate immune response. In summary, this study provides a rich and unbiased set of novel testable hypotheses on how pathogenic Acinetobacter interact with and ultimately infect their human host. It is a comprehensive resource for future research into novel therapeutic strategies. Author summary The spread of multi- and pan-drug resistant bacterial pathogens is a worldwide threat to human health. Understanding the genetics of host colonization and infection can substantially help in devising novel ways of treatment. Acinetobacter baumannii, a nosocomial pathogen ranked top by the World Health Organization in the list of bacteria for which novel therapeutic approaches are needed, is a prime example. Here, we have carved out the genetic make-up that distinguishes A. baumannii and its pathogenic next relatives from other and mostly apathogenic Acinetobacter species. We found a rich spectrum of pathways and regulatory modules that reveal how the pathogens have modified biofilm formation, iron scavenging, and their carbohydrate metabolism to adapt to their human host. Among these, the capability to metabolize kynurenine is particularly intriguing. Humans produce this substance to contain bacterial invaders and to fine-tune the innate immune response. But A. baumannii and closely related pathogens found a way to feed on kynurenine. This suggests that the pathogens might be able to dysregulate the human immune response. In summary, our study substantially deepens the understanding of how a highly critical pathogen interacts with its host, which substantially eases the identification of novel targets for innovative therapeutic strategies.

Abstract Background The technology of single cell RNA sequencing (scRNA-seq) has gained massively in popularity as it allows unprecedented insights into cellular heterogeneity as well as identification and characterization of (sub-)cellular populations. Furthermore, scRNA-seq is almost ubiquitously applicable in medical and biological research. However, these new opportunities are accompanied by additional challenges for researchers regarding data analysis, as advanced technical expertise is required in using bioinformatic software. Results Here we present WASP, a software for the processing of Drop-Seq-based scRNA-Seq data. Our software facilitates the initial processing of raw reads generated with the ddSEQ or 10x protocol and generates demultiplexed gene expression matrices including quality metrics. The processing pipeline is realized as a Snakemake workflow, while an R Shiny application is provided for interactive result visualization. WASP supports comprehensive analysis of gene expression matrices, including detection of differentially expressed genes, clustering of cellular populations and interactive graphical visualization of the results. The R Shiny application can be used with gene expression matrices generated by the WASP pipeline, as well as with externally provided data from other sources. Conclusions With WASP we provide an intuitive and easy-to-use tool to process and explore scRNA-seq data. To the best of our knowledge, it is currently the only freely available software package that combines pre- and post-processing of ddSEQ- and 10x-based data. Due to its modular design, it is possible to use any gene expression matrix with WASP’s post-processing R Shiny application. To simplify usage, WASP is provided as a Docker container. Alternatively, pre-processing can be accomplished via Conda, and a standalone version for Windows is available for post-processing, requiring only a web browser.

Abstract Bacteria occupy all major ecosystems and maintain an intensive relationship to the eukaryotes, developing together into complex biomes (i.e., phycosphere and rhizosphere). Interactions between eukaryotes and bacteria range from cooperative to competitive, with the associated microorganisms affecting their host`s development, growth and health. Since the advent of non-culture dependent analytical techniques such as metagenome sequencing, consortia have been described at the phylogenetic level but rarely functionally. Multifaceted analysis of the microbial consortium of the ancient phytoplankton Botryococcus as an attractive model food web revealed that its all abundant bacterial members belong to a niche of biotin auxotrophs, essentially depending on the microalga. In addition, hydrocarbonoclastic bacteria without vitamin auxotrophies seem adversely to affect the algal cell morphology. Synthetic rearrangement of a minimal community consisting of an alga, a mutualistic and a parasitic bacteria underpins the model of a eukaryote that maintains its own mutualistic microbial community to control its surrounding biosphere. This model of coexistence, potentially useful for defense against invaders by a eukaryotic host could represent ecologically relevant interactions that cross species boundaries. Metabolic and system reconstruction is an opportunity to unravel the relationships within the consortia and provide a blueprint for the construction of mutually beneficial synthetic ecosystems.

Abstract Background The archaeal exosome is an exoribonucleolytic multiprotein complex, which degrades single-stranded RNA in 3′ to 5′ direction phosphorolytically. In a reverse reaction, it can add A-rich tails to the 3′-end of RNA. The catalytic center of the exosome is in the aRrp41 subunit of its hexameric core. Its RNA-binding subunits aRrp4 and aDnaG confer poly(A) preference to the complex. The archaeal exosome was intensely characterized in vitro, but still little is known about its interaction with natural substrates in the cell, particularly because analysis of the transcriptome-wide interaction of an exoribonuclease with RNA is challenging. Results To determine binding sites of the exosome to RNA on a global scale, we performed individual-nucleotide resolution UV crosslinking and immunoprecipitation (iCLIP) analysis with antibodies directed against aRrp4 and aRrp41 of the chrenarchaeon Sulfolobus solfataricus. A relatively high proportion (17–19%) of the obtained cDNA reads could not be mapped to the genome. Instead, they corresponded to adenine-rich RNA tails, which are post-transcriptionally synthesized by the exosome, and to circular RNAs (circRNAs). We identified novel circRNAs corresponding to 5′ parts of two homologous, transposase-related mRNAs. To detect preferred substrates of the exosome, the iCLIP reads were compared to the transcript abundance using RNA-Seq data. Among the strongly enriched exosome substrates were RNAs antisense to tRNAs, overlapping 3′-UTRs and RNAs containing poly(A) stretches. The majority of the read counts and crosslink sites mapped in mRNAs. Furthermore, unexpected crosslink sites clustering at 5′-ends of RNAs was detected. Conclusions In this study, RNA targets of an exoribonuclease were analyzed by iCLIP. The data documents the role of the archaeal exosome as an exoribonuclease and RNA-tailing enzyme interacting with all RNA classes, and underlines its role in mRNA turnover, which is important for adaptation of prokaryotic cells to changing environmental conditions. The clustering of crosslink sites near 5′-ends of genes suggests simultaneous binding of both RNA ends by the S. solfataricus exosome. This may serve to prevent translation of mRNAs dedicated to degradation in 3′-5′ direction.

ABSTRACT Myxococcus xanthus has a nutrient-regulated biphasic life cycle forming predatory swarms in the presence of nutrients and spore-filled fruiting bodies in the absence of nutrients. The second messenger 3′-5′, 3′-5 cyclic di-GMP (c-di-GMP) is essential during both stages of the life cycle; however, different enzymes involved in c-di-GMP synthesis and degradation as well as several c-di-GMP receptors are important during distinct life cycle stages. To address this stage specificity, we determined transcript levels using transcriptome sequencing (RNA-seq) and transcription start sites using Cappable sequencing (Cappable-seq) during growth and development genome wide. All 70 genes encoding c-di-GMP-associated proteins were expressed, with 28 upregulated and 10 downregulated during development. Specifically, the three genes encoding enzymatically active proteins with a stage-specific function were expressed stage specifically. By combining operon mapping with published chromatin immunoprecipitation sequencing (ChIP-seq) data for MrpC (M. Robinson, B. Son, D. Kroos, L. Kroos, BMC Genomics 15:1123, 2014, http://dx.doi.org/10.1186/1471-2164-15-1123), the cAMP receptor protein (CRP)-like master regulator of development, we identified nine developmentally regulated genes as regulated by MrpC. In particular, MrpC directly represses the expression of dmxB, which encodes the diguanylate cyclase DmxB that is essential for development and responsible for the c-di-GMP increase during development. Moreover, MrpC directly activates the transcription of pmxA, which encodes a bifunctional phosphodiesterase that degrades c-di-GMP and 3′,3′-cGAMP in vitro and is essential for development. Thereby, MrpC regulates and curbs the cellular pools of c-di-GMP and 3′,3′-cGAMP during development. We conclude that temporal regulation of the synthesis of proteins involved in c-di-GMP metabolism contributes to c-di-GMP signaling specificity. MrpC is important for this regulation, thereby being a key regulator of developmental cyclic di-nucleotide metabolism in M. xanthus. IMPORTANCE The second messenger c-di-GMP is important during both stages of the nutrient-regulated biphasic life cycle of Myxococcus xanthus with the formation of predatory swarms in the presence of nutrients and spore-filled fruiting bodies in the absence of nutrients. However, different enzymes involved in c-di-GMP synthesis and degradation are important during distinct life cycle stages. Here, we show that the three genes encoding enzymatically active proteins with a stage-specific function are expressed stage specifically. Moreover, we find that the master transcriptional regulator of development MrpC directly regulates the expression of dmxB, which encodes the diguanylate cyclase DmxB that is essential for development, and of pmxA, which encodes a bifunctional phosphodiesterase that degrades c-di-GMP and 3′,3′-cGAMP in vitro and is essential for development. We conclude that temporal regulation of the synthesis of proteins involved in c-di-GMP metabolism contributes to c-di-GMP signaling specificity and that MrpC plays an important role in this regulation.

Antimicrobial resistance (AMR) has become one of the serious global health problems, threatening the effective treatment of a growing number of infections. Machine learning and deep learning show great potential in rapid and accurate AMR predictions. However, a large number of samples for the training of these models is essential. In particular, for novel antibiotics, limited training samples and data imbalance hinder the models’ generalization performance and overall accuracy. We propose a deep transfer learning model that can improve model performance for AMR prediction on small, imbalanced datasets. As our approach relies on transfer learning and secondary mutations, it is also applicable to novel antibiotics and emerging resistances in the future and enables quick diagnostics and personalized treatments.

One should assume that in silico experiments in systems biology are less susceptible to reproducibility issues than their wet-lab counterparts, because they are free from natural biological variations and their environment can be fully controlled. However, recent studies show that only half of the published mathematical models of biological systems can be reproduced without substantial effort. In this article we examine the potential causes for failed or cumbersome reproductions in a case study of a one-dimensional mathematical model of the atrioventricular node, which took us four months to reproduce. The model demonstrates that even otherwise rigorous studies can be hard to reproduce due to missing information, errors in equations and parameters, a lack in available data files, non-executable code, missing or incomplete experiment protocols, and missing rationales behind equations. Many of these issues seem similar to problems that have been solved in software engineering using techniques such as unit testing, regression tests, continuous integration, version control, archival services, and a thorough modular design with extensive documentation. Applying these techniques, we reimplement the examined model using the modeling language Modelica. The resulting workflow is independent of the model and can be translated to SBML, CellML, and other languages. It guarantees methods reproducibility by executing automated tests in a virtual machine on a server that is physically separated from the development environment. Additionally, it facilitates results reproducibility, because the model is more understandable and because the complete model code, experiment protocols, and simulation data are published and can be accessed in the exact version that was used in this article. We found the additional design and documentation effort well justified, even just considering the immediate benefits during development such as easier and faster debugging, increased understandability of equations, and a reduced requirement for looking up details from the literature.

Whole genome sequencing of bacteria has become daily routine in many fields. Advances in DNA sequencing technologies and continuously dropping costs have resulted in a tremendous increase in the amounts of available sequence data. However, comprehensive in-depth analysis of the resulting data remains an arduous and time-consuming task. In order to keep pace with these promising but challenging developments and to transform raw data into valuable information, standardized analyses and scalable software tools are needed. Here, we introduce ASA3P, a fully automatic, locally executable and scalable assembly, annotation and analysis pipeline for bacterial genomes. The pipeline automatically executes necessary data processing steps, i.e. quality clipping and assembly of raw sequencing reads, scaffolding of contigs and annotation of the resulting genome sequences. Furthermore, ASA3P conducts comprehensive genome characterizations and analyses, e.g. taxonomic classification, detection of antibiotic resistance genes and identification of virulence factors. All results are presented via an HTML5 user interface providing aggregated information, interactive visualizations and access to intermediate results in standard bioinformatics file formats. We distribute ASA3P in two versions: a locally executable Docker container for small-to-medium-scale projects and an OpenStack based cloud computing version able to automatically create and manage self-scaling compute clusters. Thus, automatic and standardized analysis of hundreds of bacterial genomes becomes feasible within hours. The software and further information is available at: asap.computational.bio.

Abstract Background The characterization of microbial communities based on sequencing and analysis of their genetic information has become a popular approach also referred to as metagenomics; in particular, the recent advances in sequencing technologies have enabled researchers to study even the most complex communities. Metagenome analysis, the assignment of sequences to taxonomic and functional entities, however, remains a tedious task: large amounts of data need to be processed. There are a number of approaches addressing particular aspects, but scientific questions are often too specific to be answered by a general-purpose method. Results We present MGX, a flexible and extensible client/server-framework for the management and analysis of metagenomic datasets; MGX features a comprehensive set of adaptable workflows required for taxonomic and functional metagenome analysis, combined with an intuitive and easy-to-use graphical user interface offering customizable result visualizations. At the same time, MGX allows to include own data sources and devise custom analysis pipelines, thus enabling researchers to perform basic as well as highly specific analyses within a single application. Conclusions With MGX, we provide a novel metagenome analysis platform giving researchers access to the most recent analysis tools. MGX covers taxonomic and functional metagenome analysis, statistical evaluation, and a wide range of visualizations easing data interpretation. Its default taxonomic classification pipeline provides equivalent or superior results in comparison to existing tools.

Rhizoctonia solani AG1-IB of the phylum Basidiomycota is known as phytopathogenic fungus affecting various economically important crops, such as bean, rice, soybean, figs, cabbage and lettuce. The isolates 1/2/21 and O8/2 of the anastomosis group AG1-IB originating from lettuce plants with bottom rot symptoms represent two less aggressive R. solani isolates, as confirmed in a pathogenicity test on lettuce. They were deeply sequenced on the Illumina MiSeq system applying the mate-pair and paired-end mode to establish their genome sequences. Assemblies of obtained sequences resulted in 2092 and 1492 scaffolds, respectively, for isolate 1/2/21 and O8/2, amounting to a size of approximately 43 Mb for each isolate. Gene prediction by applying AUGUSTUS (v. 3.2.1.) yielded 12,827 and 12,973 identified genes, respectively. Based on automatic functional annotation, genes potentially encoding cellulases and enzymes involved in secondary metabolite synthesis were identified in the AG1-IB genomes. The annotated genome sequences of the less aggressive AG1-IB isolates were compared with the isolate 7/3/14, which is highly aggressive on lettuce and other vegetable crops such as bean, cabbage and carrot. This analysis revealed the first insights into core genes of AG1-IB isolates and unique determinants of each genome that may explain the different aggressiveness levels of the strains.

Extracellular vesicles (EVs) can transfer diverse RNA cargo for intercellular communication. EV-associated RNAs have been found in diverse fungi and were proposed to be relevant for pathogenesis in animal hosts. In plant-pathogen interactions, small RNAs are exchanged in a cross-kingdom RNAi warfare and EVs were considered to be a delivery mechanism. To extend the search for EV-associated molecules involved in plant-pathogen communication, we have characterised the repertoire of EV-associated mRNAs secreted by the maize smut pathogen, Ustilago maydis. For this initial survey, we examined EV-enriched fractions from axenic filamentous cultures that mimic infectious hyphae. EV-associated RNAs were resistant to degradation by RNases and the presence of intact mRNAs was evident. The set of mRNAs enriched inside EVs relative to the fungal cells are functionally distinct from those that are depleted from EVs. mRNAs encoding metabolic enzymes are particularly enriched. Intriguingly, mRNAs of some known effectors and other proteins linked to virulence were also found in EVs. Furthermore, several mRNAs enriched in EVs are also upregulated during infection, suggesting that EV-associated mRNAs may participate in plant-pathogen interactions.

Abstract Background Oleaginous microalgae are promising production hosts for the sustainable generation of lipid-based bioproducts and as bioenergy carriers such as biodiesel. Transcriptomics of the lipid accumulation phase, triggered efficiently by nitrogen starvation, is a valuable approach for the identification of gene targets for metabolic engineering. Results An explorative analysis of the detailed transcriptional response to different stages of nitrogen availability was performed in the oleaginous green alga Monoraphidium neglectum. Transcript data were correlated with metabolic data for cellular contents of starch and of different lipid fractions. A pronounced transcriptional down-regulation of photosynthesis became apparent in response to nitrogen starvation, whereas glucose catabolism was found to be up-regulated. An in-depth reconstruction and analysis of the pathways for glycerolipid, central carbon, and starch metabolism revealed that distinct transcriptional changes were generally found only for specific steps within a metabolic pathway. In addition to pathway analyses, the transcript data were also used to refine the current genome annotation. The transcriptome data were integrated into a database and complemented with data for other microalgae which were also subjected to nitrogen starvation. It is available at https://tdbmn.cebitec.uni-bielefeld.de . Conclusions Based on the transcriptional responses to different stages of nitrogen availability, a model for triacylglycerol and lipid hyperaccumulation is proposed, which involves transcriptional induction of thioesterases, differential regulation of lipases, and a re-routing of the central carbon metabolism. Over-expression of distinct thioesterases was identified to be a potential strategy to increase the oleaginous phenotype of M. neglectum, and furthermore specific lipases were identified as potential targets for future metabolic engineering approaches.

Abstract Ferroplasmaceae represent ubiquitous iron-oxidising extreme acidophiles with a number of unique physiological traits. In a genome-based study of Ferroplasma acidiphilum YT, the only species of the genus Ferroplasma with a validly published name, we assessed its central metabolism and genome stability during a long-term cultivation experiment. Consistently with physiology, the genome analysis points to F. acidiphilum YT having an obligate peptidolytic oligotrophic lifestyle alongside with anaplerotic carbon assimilation. This narrow trophic specialisation abridges the sugar uptake, although all genes for glycolysis and gluconeogenesis, including bifunctional unidirectional fructose 1,6-bisphosphate aldolase/phosphatase, have been identified. Pyruvate and 2-oxoglutarate dehydrogenases are substituted by ‘ancient’ CoA-dependent pyruvate and alpha-ketoglutarate ferredoxin oxidoreductases. In the lab culture, after ~550 generations, the strain exhibited the mutation rate of ≥1.3 × 10−8 single nucleotide substitutions per site per generation, which is among the highest values recorded for unicellular organisms. All but one base substitutions were G:C to A:T, their distribution between coding and non-coding regions and synonymous-to-non-synonymous mutation ratios suggest the neutral drift being a prevalent mode in genome evolution in the lab culture. Mutations in nature seem to occur with lower frequencies, as suggested by a remarkable genomic conservation in F. acidiphilum YT variants from geographically distant populations.

Abstract Background Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.

Strain E19T described as Hartmannibacter diazotrophicus gen. nov. sp. nov. was isolated from the rhizosphere of Plantago winteri from a natural salt meadow in a nature protection area. Strain E19T is a plant growth-promoting rhizobacterium able to colonize the rhizosphere of barley and to promote its growth only under salt stress conditions. To gain insights into the genetic bases of plant growth promotion and its lifestyle at the rhizosphere under salty conditions, we determined the complete genome sequence using two complementary sequencing platforms (Ilumina MiSeq and PacBio RSII). The E19T genome comprises one circular chromosome and one plasmid containing several genes involved in salt adaptation and genes related to plant growth-promoting traits under salt stress. Based on previous experiments, ACC deaminase activity was identified as a main mechanism of E19T to promote plant growth under salt stress. Interestingly, no genes classically reported to encode for ACC deaminase activity are present. In general, the E19T genome provides information to confirm, discover, and better understand many of its previously evaluated traits involved in plant growth promotion under salt stress. Furthermore, the complete E19T genome sequence helps to define its previously reported unclear 16S rRNA gene-based phylogenetic affiliation. Hartmannibacter forms a distinct subcluster with genera Methylobrevis, Pleomorphomonas, Oharaeibacter, and Mongoliimonas subclustered with genera belonging to Rhizobiales.

Details about the members of the Indian Listeria Consortium are provided in the Supplementary Data.Emerging Microbes and Infections (2016) 5, e55; doi:10.1038/emi.2016.55; published online 8 June 2016

The majority of soil organic nitrogen (N) is bound in protein-like compounds and therefore its proteolysis in peptides and amino acids is considered the initial and rate limiting step of N mineralization. Proteolysis of N bound in organic fertilizer and subsequent provisioning for crops is a central element in agro-ecological intensification. Long-term farming system effects on N provisioning from organic fertilizer to crops and its underlying functional microbial communities were analyzed in experiments conducted in soils from the “DOK” system comparison trial (bio-Dynamic, bio-Organic, and “Konventionell”) subjected to optimal and future projected drought scenarios. A plant nutrition experiment using 15N labeled lupine as a fertilizer (green manure) identified 30% higher amounts of N derived from fertilizer in ryegrass grown on organically compared to conventionally managed soil, but only when subjected to dry conditions. A second experiment, also amended with lupine green manure, assessed the effect of farming system and drought stress on N cycling microbes with a focus on alkaline (apr) and neutral (npr) metallopeptidase encoding microbial communities. apr encoding microbial communities were more strongly affected by farming system and water treatment than npr encoding communities. Differences in structure and diversity of apr encoding microbial communities showed concomitant patterns with distinct N provisioning from organic fertilizer in the plant nutrition experiment. It is suggested that conventionally managed systems are less capable in maintaining diversity and initial structure of apr encoding microbial communities when subjected to drought scenarios. Overall, we demonstrated organically managed soils to provide a more stable N provisioning potential from organic fertilizer under future drought scenarios, likely facilitated by a distinct and more adaptive proteolytic microbial community. This work contributes to an in-depth comprehension of yet poorly studied fundamental soil processes and helps developing strategies to maintain a versatile and functioning microbial community in a rapidly changing environment.

microRNAs (miRNAs) coordinate several physiological and pathological processes by regulating the fate of mRNAs. Studies conducted in vitro indicate a role of microRNAs in the control of host-microbe interactions. However, there is limited understanding of miRNA functions in in vivo models of bacterial infections. In this study, we systematically explored changes in miRNA expression levels of Galleria mellonella larvae (greater-wax moth), a model system that recapitulates the vertebrate innate immunity, following infection with L. monocytogenes. Using an insect-specific miRNA microarray with more than 2000 probes, we found differential expression of 90 miRNAs (39 upregulated and 51 downregulated) in response to infection with L. monocytogenes. We validated the expression of a subset of miRNAs which have mammalian homologs of known or predicted function. In contrast, non-pathogenic L. innocua failed to induce these miRNAs, indicating a virulence-dependent miRNA deregulation. To predict miRNA targets using established algorithms, we generated a publically available G. mellonella transcriptome database. We identified miRNA targets involved in innate immunity, signal transduction and autophagy, including spätzle, MAP kinase, and optineurin, respectively, which exhibited a virulence-specific differential expression. Finally, in silico estimation of minimum free energy of miRNA-mRNA duplexes of validated microRNAs and target transcripts revealed a regulatory network of the host immune response to L. monocytogenes. In conclusion, this study provides evidence for a role of miRNAs in the regulation of the innate immune response following bacterial infection in a simple, rapid and scalable in vivo model that may predict host-microbe interactions in higher vertebrates.

Sinorhizobium fredii HH103 is a fast-growing rhizobial strain infecting a broad range of legumes including both American and Asiatic soybeans. In this work, we present the sequencing and annotation of the HH103 genome (7.25 Mb), consisting of one chromosome and six plasmids and representing the structurally most complex sinorhizobial genome sequenced so far. Comparative genomic analyses of S. fredii HH103 with strains USDA257 and NGR234 showed that the core genome of these three strains contains 4,212 genes (61.7% of the HH103 genes). Synteny plot analysis revealed that the much larger chromosome of USDA257 (6.48 Mb) is colinear to the HH103 (4.3 Mb) and NGR324 chromosomes (3.9 Mb). An additional region of the USDA257 chromosome of about 2 Mb displays similarity to plasmid pSfHH103e. Remarkable differences exist between HH103 and NGR234 concerning nod genes, flavonoid effect on surface polysaccharide production, and quorum-sensing systems. Furthermore a number of protein secretion systems have been found. Two genes coding for putative type III–secreted effectors not previously described in S. fredii, nopI and gunA, have been located on the HH103 genome. These differences could be important to understand the different symbiotic behavior of S. fredii strains HH103, USDA257, and NGR234 with soybean.

Streptococcus pneumoniae is a major pathogen that causes different invasive pneumococcal diseases (IPD). The pneumococcal polysaccharide capsule is a main virulence factor. More than 94 capsule types have been described, but only a limited number of capsule types accounted for the majority of IPD cases before the introduction of pneumococcal vaccines. After the introduction of the conjugated pneumococcal vaccine PCV7, which covered the seven most frequent serotypes in IPD in the USA, an increase in IPD caused by non-vaccine serotypes was observed, and serotype 19A, which belongs to sequence type (ST) 199, was among the most prevalent STs. After the introduction of the extended vaccine PCV13, which includes serotype 19A, serogroup 15B/C increased in IPD. Therefore, whole genome sequences of 39 isolates of ST199 from Germany (collected between 1998 and 2011) with serotype 19A (n = 24) and serogroup 15B/C (n = 15) were obtained using an Illumina platform and were analysed to identify capsular switches within ST199. Two 19A to 15B/C serotype switch events were identified. Both events occurred before the introduction of PCV7, which indicates that a capsular switch from 19A to 15B among ST199 isolates is not unusual and is not directly linked to the vaccination. The observed serotype replacement appears to be the result of a vacant niche due to the displacement of vaccine serotypes that is now successfully occupied by ST199 clones.

Some members of the physiological human microbiome occasionally cause life-threatening disease even in immunocompetent individuals. A prime example of such a commensal pathogen is Neisseria meningitidis, which normally resides in the human nasopharynx but is also a leading cause of sepsis and epidemic meningitis. Using N. meningitidis as model organism, we tested the hypothesis that virulence of commensal pathogens is a consequence of within host evolution and selection of invasive variants due to mutations at contingency genes, a mechanism called phase variation. In line with the hypothesis that phase variation evolved as an adaptation to colonize diverse hosts, computational comparisons of all 27 to date completely sequenced and annotated meningococcal genomes retrieved from public databases showed that contingency genes are indeed enriched for genes involved in host interactions. To assess within-host genetic changes in meningococci, we further used ultra-deep whole-genome sequencing of throat-blood strain pairs isolated from four patients suffering from invasive meningococcal disease. We detected up to three mutations per strain pair, affecting predominantly contingency genes involved in type IV pilus biogenesis. However, there was not a single (set) of mutation(s) that could invariably be found in all four pairs of strains. Phenotypic assays further showed that these genetic changes were generally not associated with increased serum resistance, higher fitness in human blood ex vivo or differences in the interaction with human epithelial and endothelial cells in vitro. In conclusion, we hypothesize that virulence of meningococci results from accidental emergence of invasive variants during carriage and without within host evolution of invasive phenotypes during disease progression in vivo.

Background: Hepatitis C virus (HCV) infects human liver hepatocytes, often leading to liver cirrhosis and hepatocellular carcinoma (HCC). It is believed that chronic infection alters host gene expression and favors HCC development. In particular, HCV replication in Endoplasmic Reticulum (ER) derived membranes induces chronic ER stress. How HCV replication affects host mRNA translation and transcription at a genome wide level is not yet known. Methods: We used Riboseq (Ribosome Profiling) to analyze transcriptome and translatome changes in the Huh-7.5 hepatocarcinoma cell line replicating HCV for 6 days. Results: Established viral replication does not cause global changes in host gene expression—only around 30 genes are significantly differentially expressed. Upregulated genes are related to ER stress and HCV replication, and several regulated genes are known to be involved in HCC development. Some mRNAs (PPP1R15A/GADD34, DDIT3/CHOP, and TRIB3) may be subject to upstream open reading frame (uORF) mediated translation control. Transcriptional downregulation mainly affects mitochondrial respiratory chain complex core subunit genes. Conclusion: After establishing HCV replication, the lack of global changes in cellular gene expression indicates an adaptation to chronic infection, while the downregulation of mitochondrial respiratory chain genes indicates how a virus may further contribute to cancer cell-like metabolic reprogramming (“Warburg effect”) even in the hepatocellular carcinoma cells used here.

Meeting the increasing food and energy demands of a growing population will require the development of ground-breaking strategies that promote sustainable plant production. Host-induced gene silencing has shown great potential for controlling pest and diseases in crop plants. However, while delivery of inhibitory noncoding double-stranded (ds)RNA by transgenic expression is a promising concept, it requires the generation of transgenic crop plants which may cause substantial delay for application strategies depending on the transformability and genetic stability of the crop plant species. Using the agronomically important barley-Fusarium graminearum pathosystem, we alternatively demonstrate that a spray application of a long noncoding dsRNA (791 nt CYP3-dsRNA), which targets the three fungal cytochrome P450 lanosterol C-14α-demethylases, required for biosynthesis of fungal ergosterol, inhibits fungal growth in the directly sprayed (local) as well as the non-sprayed (distal) parts of detached leaves. Unexpectedly, efficient spray-induced control of fungal infections in the distal tissue involved passage of CYP3-dsRNA via the plant vascular system and processing into small interfering (si)RNAs by fungal DICER-LIKE 1 (FgDCL-1) after uptake by the pathogen. We discuss important consequences of this new finding on future RNA-based disease control strategies. Given the ease of design, high specificity, and applicability to diverse pathogens, the use of target-specific dsRNA as an anti-fungal agent offers unprecedented potential as a new plant protection strategy.

The natural restoration of soils polluted by aromatic hydrocarbons such as benzene, toluene, ethylbenzene and m- and p-xylene (BTEX) may be accelerated by inoculation of specific biodegraders (bioaugmentation). Bioaugmentation mainly involves introducing bacteria that deploy their metabolic properties and adaptation potential to survive and propagate in the contaminated environment by degrading the pollutant. In order to better understand the adaptive response of cells during a transition to contaminated material, we analyzed here the genome and short-term (1 h) changes in genome-wide gene expression of the BTEX-degrading bacterium Pseudomonas veronii 1YdBTEX2 in non-sterile soil and liquid medium, both in presence or absence of toluene. We obtained a gapless genome sequence of P. veronii 1YdBTEX2 covering three individual replicons with a total size of 8 Mb, two of which are largely unrelated to current known bacterial replicons. One-hour exposure to toluene, both in soil and liquid, triggered massive transcription (up to 208-fold induction) of multiple gene clusters, such as toluene degradation pathway(s), chemotaxis and toluene efflux pumps. This clearly underlines their key role in the adaptive response to toluene. In comparison to liquid medium, cells in soil drastically changed expression of genes involved in membrane functioning (e.g., lipid composition, lipid metabolism, cell fatty acid synthesis), osmotic stress response (e.g., polyamine or trehalose synthesis, uptake of potassium) and putrescine metabolism, highlighting the immediate response mechanisms of P. veronii 1YdBTEX2 for successful establishment in polluted soil.

Fire blight, caused by the enterobacterium Erwinia amylovora, is a devastating disease of rosaceous plants that has global economic importance for apple and pear production and trade. The complete genome of E. amylovora CFBP 1430 was sequenced, annotated, and compared with the genomes of other Erwinia spp. Several singleton and shared features of the E. amylovora CFBP 1430 genome were identified that offer a first view into evolutionary aspects within the genus Erwinia. Comparative genomics identified or clarified virulence and fitness determinants and secretion systems. Novel insights revealed in the genome of E. amylovora CFBP 1430 hold potential for exploitation to improve the design of more effective fire blight control strategies.

ABSTRACT Here we present an extensive genomic and genetic analysis of Escherichia coli strains of serotype O78 that represent the major cause of avian colisepticemia, an invasive infection caused by avian pathogenic Escherichia coli (APEC) strains. It is associated with high mortality and morbidity, resulting in significant economic consequences for the poultry industry. To understand the genetic basis of the virulence of avian septicemic E. coli, we sequenced the entire genome of a clinical isolate of serotype O78—O78:H19 ST88 isolate 789 (O78-9)—and compared it with three publicly available APEC O78 sequences and one complete genome of APEC serotype O1 strain. Although there was a large variability in genome content between the APEC strains, several genes were conserved, which are potentially critical for colisepticemia. Some of these genes are present in multiple copies per genome or code for gene products with overlapping function, signifying their importance. A systematic deletion of each of these virulence-related genes identified three systems that are conserved in all septicemic strains examined and are critical for serum survival, a prerequisite for septicemia. These are the plasmid-encoded protein, the defective ETT2 (E. coli type 3 secretion system 2) type 3 secretion system ETT2sepsis, and iron uptake systems. Strain O78-9 is the only APEC O78 strain that also carried the regulon coding for yersiniabactin, the iron binding system of the Yersinia high-pathogenicity island. Interestingly, this system is the only one that cannot be complemented by other iron uptake systems under iron limitation and in serum. IMPORTANCE Avian colisepticemia is a severe systemic disease of birds causing high morbidity and mortality and resulting in severe economic losses. The bacteria associated with avian colisepticemia are highly antibiotic resistant, making antibiotic treatment ineffective, and there is no effective vaccine due to the multitude of serotypes involved. To understand the disease and work out strategies to combat it, we performed an extensive genomic and genetic analysis of Escherichia coli strains of serotype O78, the major cause of the disease. We identified several potential virulence factors, conserved in all the colisepticemic strains examined, and determined their contribution to growth in serum, an absolute requirement for septicemia. These findings raise the possibility that specific vaccines or drugs can be developed against these critical virulence factors to help combat this economically important disease.

Rhizoctonia solani, a soil-born plant pathogenic basidiomycetous fungus, affects various economically important agricultural and horticultural crops. The draft genome sequence for the R. solani AG1-IB isolate 7/3/14 as well as a corresponding transcriptome dataset (Expressed Sequence Tags--ESTs) were established previously. Development of a specific R. solani AG1-IB gene model based on GMAP transcript mapping within the eukaryotic gene prediction platform AUGUSTUS allowed detection of new genes and provided insights into the gene structure of this fungus. In total, 12,616 genes were recognized in the genome of the AG1-IB isolate. Analysis of predicted genes by means of different bioinformatics tools revealed new genes whose products potentially are involved in degradation of plant cell wall components, melanin formation and synthesis of secondary metabolites. Comparative genome analyses between members of different R. solani anastomosis groups, namely AG1-IA, AG3 and AG8 and the newly annotated R. solani AG1-IB genome were performed within the comparative genomics platform EDGAR. It appeared that only 21 to 28% of all genes encoded in the draft genomes of the different strains were identified as core genes. Based on Average Nucleotide Identity (ANI) and Average Amino-acid Identity (AAI) analyses, considerable sequence differences between isolates representing different anastomosis groups were identified. However, R. solani isolates form a distinct cluster in relation to other fungi of the phylum Basidiomycota. The isolate representing AG1-IB encodes significant more genes featuring predictable functions in secondary metabolite production compared to other completely sequenced R. solani strains. The newly established R. solani AG1-IB 7/3/14 gene layout now provides a reliable basis for post-genomics studies.

Chinese hamster ovary (CHO) cell lines represent the most commonly used mammalian expression system for the production of therapeutic proteins. In this context, detailed knowledge of the CHO cell transcriptome might help to improve biotechnological processes conducted by specific cell lines. Nevertheless, very few assembled cDNA sequences of CHO cells were publicly released until recently, which puts a severe limitation on biotechnological research. Two extended annotation systems and web-based tools, one for browsing eukaryotic genomes (GenDBE) and one for viewing eukaryotic transcriptomes (SAMS), were established as the first step towards a publicly usable CHO cell genome/transcriptome analysis platform. This is complemented by the development of a new strategy to assemble the ca. 100 million reads, sequenced from a broad range of diverse transcripts, to a high quality CHO cell transcript set. The cDNA libraries were constructed from different CHO cell lines grown under various culture conditions and sequenced using Roche/454 and Illumina sequencing technologies in addition to sequencing reads from a previous study. Two pipelines to extend and improve the CHO cell line transcripts were established. First, de novo assemblies were carried out with the Trinity and Oases assemblers, using varying k-mer sizes. The resulting contigs were screened for potential CDS using ESTScan. Redundant contigs were filtered out using cd-hit-est. The remaining CDS contigs were re-assembled with CAP3. Second, a reference-based assembly with the TopHat/Cufflinks pipeline was performed, using the recently published draft genome sequence of CHO-K1 as reference. Additionally, the de novo contigs were mapped to the reference genome using GMAP and merged with the Cufflinks assembly using the cuffmerge software. With this approach 28,874 transcripts located on 16,492 gene loci could be assembled. Combining the results of both approaches, 65,561 transcripts were identified for CHO cell lines, which could be clustered by sequence identity into 17,598 gene clusters.

Adduct formation, fragmentation events and matrix effects impose special challenges to the identification and quantitation of metabolites in LC-ESI-MS datasets. An important step in compound identification is the deconvolution of mass signals. During this processing step, peaks representing adducts, fragments, and isotopologues of the same analyte are allocated to a distinct group, in order to separate peaks from coeluting compounds. From these peak groups, neutral masses and pseudo spectra are derived and used for metabolite identification via mass decomposition and database matching. Quantitation of metabolites is hampered by matrix effects and nonlinear responses in LC-ESI-MS measurements. A common approach to correct for these effects is the addition of a U-13C-labeled internal standard and the calculation of mass isotopomer ratios for each metabolite. Here we present a new web-platform for the analysis of LC-ESI-MS experiments. ALLocator covers the workflow from raw data processing to metabolite identification and mass isotopomer ratio analysis. The integrated processing pipeline for spectra deconvolution "ALLocatorSD" generates pseudo spectra and automatically identifies peaks emerging from the U-13C-labeled internal standard. Information from the latter improves mass decomposition and annotation of neutral losses. ALLocator provides an interactive and dynamic interface to explore and enhance the results in depth. Pseudo spectra of identified metabolites can be stored in user- and method-specific reference lists that can be applied on succeeding datasets. The potential of the software is exemplified in an experiment, in which abundance fold-changes of metabolites of the l-arginine biosynthesis in C. glutamicum type strain ATCC 13032 and l-arginine producing strain ATCC 21831 are compared. Furthermore, the capability for detection and annotation of uncommon large neutral losses is shown by the identification of (γ-)glutamyl dipeptides in the same strains. ALLocator is available online at: https://allocator.cebitec.uni-bielefeld.de. A login is required, but freely available.

De novo genome assembly is the process of reconstructing a complete genomic sequence from countless small sequencing reads. Due to the complexity of this task, numerous genome assemblers have been developed to cope with different requirements and the different kinds of data provided by sequencers within the fast evolving field of next-generation sequencing technologies. In particular, the recently introduced generation of benchtop sequencers, like Illumina's MiSeq and Ion Torrent's Personal Genome Machine (PGM), popularized the easy, fast, and cheap sequencing of bacterial organisms to a broad range of academic and clinical institutions. With a strong pragmatic focus, here, we give a novel insight into the line of assembly evaluation surveys as we benchmark popular de novo genome assemblers based on bacterial data generated by benchtop sequencers. Therefore, single-library assemblies were generated, assembled, and compared to each other by metrics describing assembly contiguity and accuracy, and also by practice-oriented criteria as for instance computing time. In addition, we extensively analyzed the effect of the depth of coverage on the genome assemblies within reasonable ranges and the k-mer optimization problem of de Bruijn Graph assemblers. Our results show that, although both MiSeq and PGM allow for good genome assemblies, they require different approaches. They not only pair with different assembler types, but also affect assemblies differently regarding the depth of coverage where oversampling can become problematic. Assemblies vary greatly with respect to contiguity and accuracy but also by the requirement on the computing power. Consequently, no assembler can be rated best for all preconditions. Instead, the given kind of data, the demands on assembly quality, and the available computing infrastructure determines which assembler suits best. The data sets, scripts and all additional information needed to replicate our results are freely available at ftp://ftp.cebitec.uni-bielefeld.de/pub/GABenchToB.

Proteorhodopsin (PR) photoheterotrophy in the marine flavobacterium Dokdonia sp. PRO95 has previously been investigated, showing no growth stimulation in the light at intermediate carbon concentrations. Here we report the genome sequence of strain PRO95 and compare it to two other PR encoding Dokdonia genomes: that of strain 4H-3-7-5 which shows the most similar genome, and that of strain MED134 which grows better in the light under oligotrophic conditions. Our genome analysis revealed that the PRO95 genome as well as the 4H-3-7-5 genome encode a protein related to xanthorhodopsins. The genomic environment and phylogenetic distribution of this gene suggest that it may have frequently been recruited by lateral gene transfer. Expression analyses by RT-PCR and direct mRNA-sequencing showed that both rhodopsins and the complete β-carotene pathway necessary for retinal production are transcribed in PRO95. Proton translocation measurements showed enhanced proton pump activity in response to light, supporting that one or both rhodopsins are functional. Genomic information and carbon source respiration data were used to develop a defined cultivation medium for PRO95, but reproducible growth always required small amounts of yeast extract. Although PRO95 contains and expresses two rhodopsin genes, light did not stimulate its growth as determined by cell numbers in a nutrient poor seawater medium that mimics its natural environment, confirming previous experiments at intermediate carbon concentrations. Starvation or stress conditions might be needed to observe the physiological effect of light induced energy acquisition.

The plant pathogen Erwinia amylovora can be divided into two host-specific groupings; strains infecting a broad range of hosts within the Rosaceae subfamily Spiraeoideae (e.g., Malus, Pyrus, Crataegus, Sorbus) and strains infecting Rubus (raspberries and blackberries). Comparative genomic analysis of 12 strains representing distinct populations (e.g., geographic, temporal, host origin) of E. amylovora was used to describe the pan-genome of this major pathogen. The pan-genome contains 5751 coding sequences and is highly conserved relative to other phytopathogenic bacteria comprising on average 89% conserved, core genes. The chromosomes of Spiraeoideae-infecting strains were highly homogeneous, while greater genetic diversity was observed between Spiraeoideae- and Rubus-infecting strains (and among individual Rubus-infecting strains), the majority of which was attributed to variable genomic islands. Based on genomic distance scores and phylogenetic analysis, the Rubus-infecting strain ATCC BAA-2158 was genetically more closely related to the Spiraeoideae-infecting strains of E. amylovora than it was to the other Rubus-infecting strains. Analysis of the accessory genomes of Spiraeoideae- and Rubus-infecting strains has identified putative host-specific determinants including variation in the effector protein HopX1(Ea) and a putative secondary metabolite pathway only present in Rubus-infecting strains.

Escherichia coli G3/10 is a component of the probiotic drug Symbioflor 2. In an in vitro assay with human intestinal epithelial cells, E. coli G3/10 is capable of suppressing adherence of enteropathogenic E. coli E2348/69. In this study, we demonstrate that a completely novel class II microcin, produced by probiotic E. coli G3/10, is responsible for this behavior. We named this antibacterial peptide microcin S (MccS). Microcin S is coded on a 50.6 kb megaplasmid of E. coli G3/10, which we have completely sequenced and annotated. The microcin S operon is about 4.7 kb in size and is comprised of four genes. Subcloning of the genes and gene fragments followed by gene expression experiments enabled us to functionally characterize all members of this operon, and to clearly identify the nucleotide sequences encoding the microcin itself (mcsS), its transport apparatus and the gene mcsI conferring self immunity against microcin S. Overexpression of cloned mcsI antagonizes MccS activity, thus protecting indicator strain E. coli E2348/69 in the in vitro adherence assay. Moreover, growth of E. coli transformed with a plasmid containing mcsS under control of an araC PBAD activator-promoter is inhibited upon mcsS induction. Our data provide further mechanistic insight into the probiotic behavior of E. coli G3/10.

Periodontitis, one of the most common diseases in the world, is caused by a mixture of pathogenic bacteria and inflammatory host responses and often treated by antimicrobials as an adjunct to scaling and root planing (SRP). Our study aims to elucidate explorative and descriptive temporal shifts in bacterial communities between patients treated by SRP alone versus SRP plus antibiotics. This is the first metagenomic study using an Ion Torrent Personal Genome Machine (PGM). Eight subgingival plaque samples from four patients with chronic periodontitis, taken before and two months after intervention were analyzed. Amplicons from the V6 hypervariable region of the 16S rRNA gene were generated and sequenced each on a 314 chip. Sequencing reads were clustered into operational taxonomic units (OTUs, 3% distance), described by community metrics, and taxonomically classified. Reads ranging from 599,933 to 650,416 per sample were clustered into 1,648 to 2,659 non-singleton OTUs, respectively. Increased diversity (Shannon and Simpson) in all samples after therapy was observed regardless of the treatment type whereas richness (ACE) showed no correlation. Taxonomic analysis revealed different microbial shifts between both therapy approaches at all taxonomic levels. Most remarkably, the genera Porphyromonas, Tannerella, Treponema, and Filifactor all harboring periodontal pathogenic species were removed almost only in the group treated with SPR and antibiotics. For the species T. forsythia and P. gingivalis results were corroborated by real-time PCR analysis. In the future, hypothesis free metagenomic analysis could be the key in understanding polymicrobial diseases and be used for therapy monitoring. Therefore, as read length continues to increase and cost to decrease, rapid benchtop sequencers like the PGM might finally be used in routine diagnostic.

BackgroundNeisseria meningitidis is a naturally transformable, facultative pathogen colonizing the human nasopharynx. Here, we analyze on a genome-wide level the impact of recombination on gene-complement diversity and virulence evolution in N. meningitidis. We combined comparative genome hybridization using microarrays (mCGH) and multilocus sequence typing (MLST) of 29 meningococcal isolates with computational comparison of a subset of seven meningococcal genome sequences.Principal findingsWe found that lateral gene transfer of minimal mobile elements as well as prophages are major forces shaping meningococcal population structure. Extensive gene content comparison revealed novel associations of virulence with genetic elements besides the recently discovered meningococcal disease associated (MDA) island. In particular, we identified an association of virulence with a recently described canonical genomic island termed IHT-E and a differential distribution of genes encoding RTX toxin- and two-partner secretion systems among hyperinvasive and non-hyperinvasive lineages. By computationally screening also the core genome for signs of recombination, we provided evidence that about 40% of the meningococcal core genes are affected by recombination primarily within metabolic genes as well as genes involved in DNA replication and repair. By comparison with the results of previous mCGH studies, our data indicated that genetic structuring as revealed by mCGH is stable over time and highly similar for isolates from different geographic origins.ConclusionsRecombination comprising lateral transfer of entire genes as well as homologous intragenic recombination has a profound impact on meningococcal population structure and genome composition. Our data support the hypothesis that meningococcal virulence is polygenic in nature and that differences in metabolism might contribute to virulence.

Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus bourgensis. While rarefaction analyses still indicate incomplete coverage, examination of the GS FLX Titanium dataset resulted in the identification of additional genera and functional elements, providing a far more complete coverage of the community involved in anaerobic fermentative pathways leading to methane formation.

Fungal laccases have been used in various fields ranging from processes in wood and paper industries to environmental applications. Although a few bacterial laccases have been characterized in recent years, prokaryotes have largely been neglected as a source of novel enzymes, in part due to the lack of knowledge about the diversity and distribution of laccases within Bacteria. In this work genes for laccase-like enzymes were searched for in over 2,200 complete and draft bacterial genomes and four metagenomic datasets, using the custom profile Hidden Markov Models for two- and three-domain laccases. More than 1,200 putative genes for laccase-like enzymes were retrieved from chromosomes and plasmids of diverse bacteria. In 76% of the genes, signal peptides were predicted, indicating that these bacterial laccases may be exported from the cytoplasm, which contrasts with the current belief. Moreover, several examples of putatively horizontally transferred bacterial laccase genes were described. Many metagenomic sequences encoding fragments of laccase-like enzymes could not be phylogenetically assigned, indicating considerable novelty. Laccase-like genes were also found in anaerobic bacteria, autotrophs and alkaliphiles, thus opening new hypotheses regarding their ecological functions. Bacteria identified as carrying laccase genes represent potential sources for future biotechnological applications.

BackgroundPantoea vagans is a commercialized biological control agent used against the pome fruit bacterial disease fire blight, caused by Erwinia amylovora. Compared to other biocontrol agents, relatively little is currently known regarding Pantoea genetics. Better understanding of antagonist mechanisms of action and ecological fitness is critical to improving efficacy.Principal findingsGenome analysis indicated two major factors Contribute to biocontrol activity: competition for limiting substrates and antibacterial metabolite production. Pathways for utilization of a broad diversity of sugars and acquisition of iron were identified. Metabolism of sorbitol by P. vagans C9-1 may be a major metabolic feature in biocontrol of fire blight. Biosynthetic genes for the antibacterial peptide pantocin A were found on a chromosomal 28-kb genomic island, and for dapdiamide E on the plasmid pPag2. There was no evidence of potential virulence factors that could enable an animal or phytopathogenic lifestyle and no indication of any genetic-based biosafety risk in the antagonist.ConclusionsIdentifying key determinants contributing to disease suppression allows the development of procedures to follow their expression in planta and the genome sequence contributes to rationale risk assessment regarding the use of the biocontrol strain in agricultural systems.