Accepted abstracts for poster presentations

1. Fredrik Boulund (1), Anna Johnning (2), Joakim Larsson (2), Erik Kristiansson (1)
   1. Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg
   2. Department of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg
   Exploring antibiotic resistance genes in the human intestinal microbiome
   Modern health care is heavily reliant on antibiotics and several common procedures such as abdominal surgery would not be possible without them. However, antibiotic resistance of pathogenic bacteria is a growing global issue, and there are several types of bacteria that regularly infect humans that are increasingly hard to treat. Millions of bacterial cells inhabit the human body, for example on the skin and in the intestine. The antibiotic resistance profile — the resistome — of environmental bacteria is well known but the resistome of the human intestinal bacterial communities has not yet been thoroughly investigated. With the recently published large amounts of high-throughput DNA sequencing data, it is now possible to start determining the size of the antibiotic resistome of the human intestinal microbiota. In this project, we develop a bioinformatics framwork for quantitative characterisation of the resistome in the human gut microbiome. Using efficient high-throughput sequence alignment algorithms, more than five billion short Illumina reads (75bp) were matched on peptide level to a reference database of antibiotic resistance genes. A workflow for parallel read mapping was created and applied using Chalmers Centre for Computational Science and Engineering's (C3SE) supercomputer systems. The results showed an extensive resistome present in the microbiome of the human intestine and we identified several genes conferring resistance to a number of classes of antibiotic compounds. Moreover, significant differences in the abundances of several resistance genes were identified when geographically separated groups were compared. In conclusion, this work shows that there is a large antibiotic resistome in the intestinal microbial communities of the human gut. Understanding its composition and interplay with potential pathogens might benefit future health care.
2. Johan Bengtsson, K. Martin Eriksson, Martin Hartmann, Zheng Wang, Belle D. Shenoy, Gwen-Aelle Grelet, Kessy Abarenkov, Anna Petri, Magnus Alm Rosenblad, R. Henrik Nilsson
   Dept. of Neuroscience and Physiology, University of Gothenburg
   Metaxa: Automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts
   The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. However, the gene is not only present in the nuclear genome of eukaryotes and the core genome of prokaryotes, but also in the mitochondria and chloroplasts of eukaryotes. The SSU genes in the core genome, mitochondria and chloroplast are conceptually paralogous and should in most situations not be aligned and analyzed jointly, e.g. when estimating species diversity. Identifying the origin of SSU sequences in complex sequence datasets is a time-consuming and largely manual undertaking. To ease this situation, we have created Metaxa, an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Metaxa very efficiently detects SSU sequences from fragments as short as 200 base pairs, and correctly classifies 97% of the identified genes at read lengths typically obtained from pyrosequencing. In addition, Metaxa shows a false positive rate of 0.00012% when run on random DNA fragments, showing the robustness of the method. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.
3. Yasser Gaber
   Biotechnology, Lund University
   Molecular Modeling as a Rational Design Tool of an Esterase
   Rational design of enzymes is an approach to modify enzyme properties based on mechanistic and structural knowledge of the enzyme. It has been greatly enhanced by the availability of molecular simulation software. We have used YASARA molecular modelling software to design mutants of an esterase (PLE) in order to enhance its enzyme activity and enantioselectivity toward a racemic compound (clopidogrel). Molecular modelling of the R and S enantiomers inside the active site of PLE model was performed to understand the possible geometric hindrances for formation of the enzyme-substrate tetrahedral intermediate. Glu203 in the vicinity of the active site was found to form hydrogen bonds with the catalytic His449 and GGG(X) motif residues. The hydrogen bonding of these residues should be available for the stabilization of the tetrahedral intermediate (Fig.1). Hence, Glu203 would be a potential site for a site directed mutation in the PLE gene expressed in Escherichia coli.
4. Robert Lizatovic
   Biochemistry and Structural Biology, Lund University
   Design of functional amyloid-like fibrils
   Many severe neurodegenerative diseases are caused by the deposition of normally soluble proteins in the form of insoluble amyloid fibrils. The yeast prion protein Sup35 has the ability to form amyloid-like fibrils of the cross-β spine structure. The spine is composed of two stacked β-sheets whose residues interdigitate extensively in order to form an anhydrous interface, called “the steric zipper. By using the sequence GNNQQNY, which is responsible for fibril formation in the Sup35 protein, as a template during modeling, a novel amyloid-like fibril was designed using Rosetta. The building block of this designed fibril was named the 2.14.2 peptide (31 residues), and it is composed of two parallel β-strands, connected vie a helix, with short loop segments in between. The external helices and loops can be used as scaffolds for further functionalization, which would facilitate the use of these fibrils as valuable biomaterials.
   A method for recombinant production of the 2.14.2 peptide was developed and tests were performed on both the synthetic and recombinant 2.14.2.
5. Andreas Tjärnberg (1), Torbjörn Nordling (2), Erik Sonnhammer (3)
   1. Biochemistry and Biophysics, Stockholm University
   2. Royal Institute of Technology Stockholm, Sweden
   3. Stockholm Bioinformatics Center, Stockholm University
   Network inference benchmarking
   Understanding biological complexity and the emergence of properties in these systems is essential for understanding diseases and predicting, for example, drug targets and how genes interact on a larger scale when exposed to external stress.
   Several methods for inferring protein interaction networks have been developed, but an objective and realistic comparative assessment of their performance is still missing.
   We here compare and benchmark a selection of methods published during the last decade to evaluate their performance on both artificial networks with varying properties, and synthetic biological networks such as the yeast network IRMA. The properties of the artificial networks have to mimic real biological networks as closely as possible to be able to accurately evaluate a method; therefore we create a number of different networks where each property is well defined and modeled to create as "realistic" a network as possible.
   Moreover, most network inference methods rely on a regularization parameter that has to be tuned for optimal performance, yet no objective principles existed to estimated it. We therefore developed a method to predict the parameter best suited for the data at hand.
   We evaluated each method based on a range of performance measures of how good the predicted network model is.
6. Tejashwari Meerupati, Karl-Magnus Andersson, Anders Tunlid, Dag Ahren
   Department of Biology, Section of Microbial Ecology, Lund University
   Whole genome sequencing and analysis of the nematode - trapping fungus Monacrosporium haptotylum
   The nematode trapping fungi can grow both as saprophyte and as parasite by forming special hyphal structures called traps. The traps are induced by signals from the environment, including peptides and other compounds secreted by the host nematode. The nematode trapping fungi are cosmopolitan in distribution and form a monophyletic clade within ascomycetes. We have sequenced the genome of a nematode trapping fungus, Monacrosporium haptotylum using pyrosequencing. The draft genome is of high quality with 28x coverage and of 40 M basepairs. We have identified 11,694 protein coding genes, which includes a large number of subtilisin like serine proteases. These are the most expanded protein families with 62 genes in Monacrosporium haptotylum and have previously been shown to be involved in the infection of the nematodes. In addition, several other genes such as CFEM and Cerato-platanin genes have been identified. Candidates including genes encoding subtiltisins and fungal effector genes have been selected for heterologous expression in the yeast Pichia pastoris.
   Keywords: Nematode trapping fungi, Monacrosporium haptotylum, High throughput sequencing, Bioinformatics
7. Kemal Sanli, Fredrik Karlsson, Intawat Nookaew, Jens Nielsen
   Systems Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology
   FANTOM: Functional and Taxonomical Analysis of Metagenomes
   Development of culture independent molecular techniques was invaluable for microbial research since the majority of microorganisms are recalcitrant to culturing in the laboratory. Application of the emerging high-throughput shotgun sequencing techniques have provided global views of the microbial communities not obtainable by 16S rRNA sequencing and gave birth to a new discipline called metagenomics. Metagenomics revolutionized the functional and taxonomical analysis of uncultured microorganisms along with an explosion of sequence data. This project aims to provide a software tool accessed throuh a graphical user interface (GUI) that can handle bioinformatic tasks including taxonomical and functional comparisons of metagenomic samples. Biological databases NCBI taxonomy, KEGG and COG are also integrated within the software for the statistical analysis of annotated sequence data to make biological inferences. In addition to software development, metagenomic content of the microorganisms harbored in human gut is investigated as a case study with special interest in its relation to obesity and inflammatory bowel disease. Key findings of the case study include the drastic reduction in relative abundance of the methanogenic archaeon Methanobrevibacter smithii in Crohn's Disease patients which is known be metabolizing the end products of fermenting bacteria in the gut as well as the increased relative abundance of Prevotella genus in obese individuals which suggests a possible relationship between the enterotype and disease.
8. Daniel Edsgärd, Olof Emanuelsson
   Science for Life Laboratory, KTH
   TargetP 2.0: Improved subcellular localization prediction
   Determining the subcellular localization of a protein is an important first step toward understanding its function. The translocation of a protein within the cell is governed by intrinsic signals of the proteins, and bioinformatics has become an important tool for the characterization and prediction of these protein-encoded sorting signals. TargetP is a neural-network based subcellular localization tool which provides prediction of chloroplast, mitochondrial and secretory pathway translocation, based on N-terminal sequence motifs. It can be applied to newly identified proteins and to characterize the proteome-wide localization patterns of a species protein content. Here we report a comprehensive update of TargetP with regard to two major aspects. First, TargetP is extended to supply specific predictions for three phyla; plant, fungi and metazoa; rather than only for plants and non-plants. Second, new protein compartments are added. TargetP is currently available as a web-server at http://www.cbs.dtu.dk/services/TargetP, where also the new version will be released.