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Background: Development of new pan-genome analysis tools is important, as the pangenome of a microbial species has become an important method to define the diversity of a selected taxon, most commonly a species, in the last years. This enables comparison of strains from different ecological niches and can be used to define the functional potential in a bacterial population. It gives us a much better view of microbial genomics than can be gained from singular genomes which after all are just single representatives of a much more varied population. Results: We present Panakeia, a tool which strives to be easy to use and providing a detailed view of the pangenome structure which can efficiently be utilised for discovery, or further in-depth analysis, of features of interest. It analyses synteny and multiple structural patterns of the pangenome, giving insights into the biological diversity and evolution of the studied taxon. Panakeia hence provides both broad and detailed information on the structure of a pangenome, for diverse and highly clonal populations of bacteria. Conclusions: Previously published pangenome tools often reduce the information to a presence/absence matrix of unconnected genes or generate massive hard to interpret output graphs. However, Panakeia includes synteny and structural information and presents it in a way that can readily be used for further analysis. Panakeia can be downloaded at https://github.com/BioSina/Panakeiatogether with a detailed User Guide. [ABSTRACT FROM AUTHOR]

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: [ABSTRACT FROM AUTHOR]

Like many other Bacteroides species, Bacteroides vulgatus strain mpk, a mouse fecal isolate which was shown to promote intestinal homeostasis, utilizes a variety of mobile elements for genome evolution. Based on sequences collected by Pacific Biosciences SMRT sequencing technology, we discuss the challenges of assembling and studying a bacterial genome of high plasticity. Additionally, we conducted comparative genomics comparing this commensal strain with the B. vulgatus type strain ATCC 8482 as well as multiple other Bacteroides and Parabacteroides strains to reveal the most important differences and identify the unique features of B. vulgatus mpk. The genome of B. vulgatus mpk harbors a large and diverse set of mobile element proteins compared with other sequenced Bacteroides strains. We found evidence of a number of different horizontal gene transfer events and a genome landscape that has been extensively altered by different mobilization events. A CRISPR/Cas system could be identified that provides a possible mechanism for preventing the integration of invading external DNA. We propose that the high genome plasticity and the introduced genome instabilities of B. vulgatus mpk arising from the various mobilization events might play an important role not only in its adaptation to the challenging intestinal environment in general, but also in its ability to interact with the gut microbiota. [ABSTRACT FROM AUTHOR]

Escherichia coli represents a classical intestinal gram-negative commensal. Despite this commensalism, different E. coli strains can mediate disparate immunogenic properties in a given host. Symbiotic E. coli strains such as E. coli Nissle 1917 (EcN) are attributed beneficial properties, e.g., promotion of intestinal homeostasis. Therefore, we aimed to identify molecular features derived from symbiotic bacteria that might help to develop innovative therapeutic alternatives for the treatment of intestinal immune disorders. This study was performed using the dextran sodium sulphate (DSS)-induced colitis mouse model, which is routinely used to evaluate potential therapeutics for the treatment of Inflammatory Bowel Diseases (IBDs). We focused on the analysis of flagellin structures of different E. coli strains. EcN flagellin was found to harbor a substantially longer hypervariable region (HVR) compared to other commensal E. coli strains, and this longer HVR mediated symbiotic properties through stronger activation of Toll-like receptor (TLR)5, thereby resulting in interleukin (IL)-22–mediated protection of mice against DSS-induced colitis. Furthermore, using bone-marrow–chimeric mice (BMCM), CD11c+ cells of the colonic lamina propria (LP) were identified as the main mediators of these flagellin-induced symbiotic effects. We propose flagellin from symbiotic E. coli strains as a potential therapeutic to restore intestinal immune homeostasis, e.g., for the treatment of IBD patients. [ABSTRACT FROM AUTHOR]

Simple Summary: Computational modeling of bacterial infection is an attractive way to simulate infection scenarios. In the long-term, such models could be used to identify factors that make individuals more susceptible to infection, or how interference with bacterial growth influences the course of bacterial infection. This study used different mouse infection models (immunocompetent, lacking a microbiota, and immunodeficient models) to develop a basic mathematical model of a Yersinia enterocolitica gastrointestinal infection. We showed that our model can reflect our findings derived from mouse infections, and we demonstrated how crucial the exact knowledge about parameters influencing the population dynamics is. Still, we think that computational models will be of great value in the future; however, to foster the development of more complex models, we propose the broad implementation of the interdisciplinary training of mathematicians and biologists. The complex interplay of a pathogen with its virulence and fitness factors, the host's immune response, and the endogenous microbiome determine the course and outcome of gastrointestinal infection. The expansion of a pathogen within the gastrointestinal tract implies an increased risk of developing severe systemic infections, especially in dysbiotic or immunocompromised individuals. We developed a mechanistic computational model that calculates and simulates such scenarios, based on an ordinary differential equation system, to explain the bacterial population dynamics during gastrointestinal infection. For implementing the model and estimating its parameters, oral mouse infection experiments with the enteropathogen, Yersinia enterocolitica (Ye), were carried out. Our model accounts for specific pathogen characteristics and is intended to reflect scenarios where colonization resistance, mediated by the endogenous microbiome, is lacking, or where the immune response is partially impaired. Fitting our data from experimental mouse infections, we can justify our model setup and deduce cues for further model improvement. The model is freely available, in SBML format, from the BioModels Database under the accession number MODEL2002070001. [ABSTRACT FROM AUTHOR]