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  • 1. Adhikari, P. R.
    et al.
    Upadhyaya, B. B.
    Meng, Chen
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Hollmén, J.
    Gene selection in time-series gene expression data2011In: 6th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2011, 2011, 145-156 p.Conference paper (Refereed)
    Abstract [en]

    The dimensionality of biological data is often very high. Feature selection can be used to tackle the problem of high dimensionality. However, majority of the work in feature selection consists of supervised feature selection methods which require class labels. The problem further escalates when the data is time-series gene expression measurements that measure the effect of external stimuli on biological system. In this paper we propose an unsupervised method for gene selection from time-series gene expression data founded on statistical significance testing and swap randomization. We perform experiments with a publicly available mouse gene expression dataset and also a human gene expression dataset describing the exposure to asbestos. The results in both datasets show a considerable decrease in number of genes.

  • 2.
    Ahlinder, Jon
    et al.
    Totalförsvarets Forskningsinstitut, FOI, Stockholm, Sweden.
    Nordgaard, Anders
    Swedish National Forensic Centre (NFC), Linköping, Sweden.
    Wiklund Lindström, Susanne
    Totalförsvarets Forskningsinstitut, FOI, Stockholm, Sweden.
    Chemometrics comes to court: evidence evaluation of chem–bio threat agent attacks2015In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 29, no 5, 267-276 p.Article in journal (Refereed)
    Abstract [en]

    Forensic statistics is a well-established scientific field whose purpose is to statistically analyze evidence in order to support legal decisions. It traditionally relies on methods that assume small numbers of independent variables and multiple samples. Unfortunately, such methods are less applicable when dealing with highly correlated multivariate data sets such as those generated by emerging high throughput analytical technologies. Chemometrics is a field that has a wealth of methods for the analysis of such complex data sets, so it would be desirable to combine the two fields in order to identify best practices for forensic statistics in the future. This paper provides a brief introduction to forensic statistics and describes how chemometrics could be integrated with its established methods to improve the evaluation of evidence in court.

    The paper describes how statistics and chemometrics can be integrated, by analyzing a previous know forensic data set composed of bacterial communities from fingerprints. The presented strategy can be applied in cases where chemical and biological threat agents have been illegally disposed.

  • 3.
    Ahrné, Karin
    et al.
    SLU.
    Bengtsson, Bengt Åke
    Björklund, Jan-Olof
    Cederberg, Björn
    Eliasson, Claes
    Hydén, Nils
    Jonasson, Jan
    Lindeborg, Mats
    Lst Kalmar Län.
    Ohlsson, Anders
    Palmqvist, Göran
    Ryrholm, Nils
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences.
    Rödlista över fjärilar Lepidoptera2015In: Rödlistade arter i Sverige 2015 / [ed] Westling, Anna, Uppsala: ArtDatabanken SLU , 2015, 98-112 p.Chapter in book (Other academic)
  • 4.
    Ajawatanawong, Pravech
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology.
    Mine the Gaps: Evolution of Eukaryotic Protein Indels and their Application for Testing Deep Phylogeny2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Insertions/deletions (indels) are potentially powerful evolutionary markers, but little is known about their evolution and few tools exist to effectively study them. To address this, I developed SeqFIRE, a tool for automated identification and extraction of indels from protein multiple sequence alignments. The program also extracts conserved alignment blocks, thus covering all major steps in preparing multiple sequence alignments for phylogenetic analysis.

    I then used SeqFIRE to build an indel database, using 299 single copy proteins from a broad taxonomic sampling of mainly multicellular eukaryotes. A total of 4,707 indels were extracted, of which 901 are simple (one genetic event) and 3,806 are complex (multiple events). The most abundant indels are single amino acid simple indels. Indel frequency decreases exponentially with length and shows a linear relationship with host protein size. Singleton indels reveal a strong bias towards insertions (2.31 x deletions on average). These analyses also identify 43 indels marking major clades in Plantae and Fungi (clade defining indels or CDIs), but none for Metazoa.

    In order to study the 3806 complex indels they were first classified by number of states. Analysis of the 2-state complex and simple indels combined (“bi-state indels”) confirms that insertions are over 2.5 times as frequent as deletions. Three-quarters of the complex indels had three-nine states (“slightly complex indels”). A tree-assisted search method was developed allowing me to identify 1,010 potential CDIs supporting all examined major branches of Plantae and Fungi.

    Forty-two proteins were also found to host complex indel CDIs for the deepest branches of Metazoa. After expanding the taxon set for these proteins, I identified a total of 49 non-bilaterian specific CDIs. Parsimony analysis of these indels places Ctenophora as sister taxon to all other Metazoa including Porifera. Six CDIs were also found placing Placozoa as sister to Bilateria. I conclude that slightly complex indels are a rich source of CDIs, and my tree-assisted search strategy could be automated and implemented in the program SeqFIRE to facilitate their discovery. This will have important implications for mining the phylogenomic content of the vast resource of protist genome data soon to become available.

  • 5.
    Ajawatanawong, Pravech
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology.
    Atkinson, Gemma C.
    Watson-Haigh, Nathan S.
    MacKenzie, Bryony
    Baldauf, Sandra L.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology.
    SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments2012In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 40, no W1, W340-W347 p.Article in journal (Refereed)
    Abstract [en]

    Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

  • 6. Alexeyenko, Andrey
    et al.
    Schmitt, Thomas
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Tjärnberg, Andreas
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Guala, Dmitri
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Frings, Oliver
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Sonnhammer, Erik L. L.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Comparative interactomics with Funcoup 2.02012In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 40, no D1, D821-D828 p.Article in journal (Refereed)
    Abstract [en]

    FunCoup (http://FunCoup.sbc.su.se) is a database that maintains and visualizes global gene/protein networks of functional coupling that have been constructed by Bayesian integration of diverse high-throughput data. FunCoup achieves high coverage by orthology-based integration of data sources from different model organisms and from different platforms. We here present release 2.0 in which the data sources have been updated and the methodology has been refined. It contains a new data type Genetic Interaction, and three new species: chicken, dog and zebra fish. As FunCoup extensively transfers functional coupling information between species, the new input datasets have considerably improved both coverage and quality of the networks. The number of high-confidence network links has increased dramatically. For instance, the human network has more than eight times as many links above confidence 0.5 as the previous release. FunCoup provides facilities for analysing the conservation of subnetworks in multiple species. We here explain how to do comparative interactomics on the FunCoup website.

  • 7.
    Alexiou, Athanasios
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Sets of Genes Predict Survival of Glioblastoma Patients2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 8.
    Alexsson, Andrei
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics .
    Unsupervised hidden Markov model for automatic analysis of expressed sequence tags2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis provides an in-depth analyze of expressed sequence tags (EST) that represent pieces of eukaryotic mRNA by using unsupervised hidden Markov model (HMM). ESTs are short nucleotide sequences that are used primarily for rapid identificationof new genes with potential coding regions (CDS). ESTs are made by sequencing on double-stranded cDNA and the synthesizedESTs are stored in digital form, usually in FASTA format. Since sequencing is often randomized and that parts of mRNA contain non-coding regions, some ESTs will not represent CDS.It is desired to remove these unwanted ESTs if the purpose is to identifygenes associated with CDS. Application of stochastic HMM allow identification of region contents in a EST. Softwares like ESTScanuse HMM in which a training of the HMM is done by supervised learning with annotated data. However, because there are not always annotated data at hand this thesis focus on the ability to train an HMM with unsupervised learning on data containing ESTs, both with and without CDS. But the data used for training is not annotated, i.e. the regions that an EST consists of are unknown. In this thesis a new HMM is introduced where the parameters of the HMM are in focus so that they are reasonablyconsistent with biologically important regionsof an mRNA such as the Kozak sequence, poly(A)-signals and poly(A)-tails to guide the training and decoding correctly with ESTs to proper statesin the HMM. Transition probabilities in the HMMhas been adapted so that it represents the mean length and distribution of the different regions in mRNA. Testing of the HMM's specificity and sensitivityhave been performed via BLAST by blasting each EST and compare the BLAST results with the HMM prediction results.A regression analysis test shows that the length of ESTs used when training the HMM is significantly important, the longer the better. The final resultsshows that it is possible to train an HMM with unsupervised machine learning but to be comparable to supervised machine learning as ESTScan, further expansion of the HMM is necessary such as frame-shift correction of ESTs byimproving the HMM's ability to choose correctly positioned start codons or nucleotides. Usually the false positive results are because of incorrectly positioned start codons leadingto too short CDS lengths. Since no frame-shift correction is implemented, short predicted CDS lengths are not acceptable and is hence not counted as coding regionsduring prediction. However, when there is a lack of supervised models then unsupervised HMM is a potential replacement with stable performance and able to be adapted forany eukaryotic organism.

  • 9.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Arvestad, Lars
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Burnin estimation and convergence assessment in Bayesian phylogenetic inferenceManuscript (preprint) (Other academic)
    Abstract [en]

     Convergence assessment and burnin estimation are central concepts in Markov chain Monte Carlo algorithms. Studies on eects, statistical properties, and comparisons between dierent convergence assessment methods have been conducted during the past few decades. However, not much work has been done on the eect of convergence diagnostic on posterior distribution of tree parameters and which method should be used by researchers in Bayesian phylogenetics inference. In this study, we propose and evaluate two novel burnin estimation methods that estimate burnin using all parameters jointly. We also consider some other popular convergence diagnostics, evaluate them in light of parallel chains and quantify the eect of burnin estimates from various convergence diagnostics on the posterior distribution of trees. We motivate the use of convergence diagnostics to assess convergence and estimate burnin in Bayesian phylogenetics inference and found out that it is better to employ convergence diagnostics rather than remove a xed percentage as burnin. We concluded that the last burnin estimator using eective sample size appears to estimate burnin better than all other convergence diagnostics.

  • 10.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Bark, Mikael
    KTH, School of Information and Communication Technology (ICT).
    Miro, Jorge
    KTH, School of Information and Communication Technology (ICT).
    Muhammad, Sayyed Auwn
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Sjöstrand, Joel
    Stockholm University.
    Zubair, Syed Muhammad
    KTH, School of Electrical Engineering (EES), Communication Networks. University of Balochistan, Pakistan.
    Abbas, Raja Manzar
    Arvestad, Lars
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo tracesManuscript (preprint) (Other academic)
    Abstract [en]

    Motivation: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical diculties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters.

    Results: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines.

    Availability: VMCMC is available for Java SE 6+ under the New BSD License. Executable jar les, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/.

  • 11.
    Ali, Raja Hashim
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Muhammad, Sayyed Auwn
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Arvestad, Lars
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    GenFamClust: An accurate, synteny-aware and reliable homology inference algorithm2016In: BMC EVOLUTIONARY BIOLOGY, ISSN 1471-2148, Vol. 16Article in journal (Other academic)
    Abstract [en]

    Background: Homology inference is pivotal to evolutionary biology and is primarily based on significant sequence similarity, which, in general, is a good indicator of homology. Algorithms have also been designed to utilize conservation in gene order as an indication of homologous regions. We have developed GenFamClust, a method based on quantification of both gene order conservation and sequence similarity. Results: In this study, we validate GenFamClust by comparing it to well known homology inference algorithms on a synthetic dataset. We applied several popular clustering algorithms on homologs inferred by GenFamClust and other algorithms on a metazoan dataset and studied the outcomes. Accuracy, similarity, dependence, and other characteristics were investigated for gene families yielded by the clustering algorithms. GenFamClust was also applied to genes from a set of complete fungal genomes and gene families were inferred using clustering. The resulting gene families were compared with a manually curated gold standard of pillars from the Yeast Gene Order Browser. We found that the gene-order component of GenFamClust is simple, yet biologically realistic, and captures local synteny information for homologs. Conclusions: The study shows that GenFamClust is a more accurate, informed, and comprehensive pipeline to infer homologs and gene families than other commonly used homology and gene-family inference methods.

  • 12.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Pinidiyaarachchi, Amalka
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Robust signal detection in 3D fluorescence microscopy2010In: Cytometry. Part A, ISSN 1552-4922, Vol. 77A, no 1, 86-96 p.Article in journal (Refereed)
    Abstract [en]

    Robust detection and localization of biomolecules inside cells is of great importance to better understand the functions related to them. Fluorescence microscopy and specific staining methods make biomolecules appear as point-like signals on image data, often acquired in 3D. Visual detection of such point-like signals can be time consuming and problematic if the 3D images are large, containing many, sometimes overlapping, signals. This sets a demand for robust automated methods for accurate detection of signals in 3D fluorescence microscopy. We propose a new 3D point-source signal detection method that is based on Fourier series. The method consists of two parts, a detector, which is a cosine filter to enhance the point-like signals, and a verifier, which is a sine filter to validate the result from the detector. Compared to conventional methods, our method shows better robustness to noise and good ability to resolve signals that are spatially close. Tests on image data show that the method has equivalent accuracy in signal detection in comparison to Visual detection by experts. The proposed method can be used as an efficient point-like signal detection tool for various types of biological 3D image data.

  • 13.
    Alvarsson, Jonathan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Ligand-based Methods for Data Management and Modelling2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Drug discovery is a complicated and expensive process in the billion dollar range. One way of making the drug development process more efficient is better information handling, modelling and visualisation. The majority of todays drugs are small molecules, which interact with drug targets to cause an effect. Since the 1980s large amounts of compounds have been systematically tested by robots in so called high-throughput screening. Ligand-based drug discovery is based on modelling drug molecules. In the field known as Quantitative Structure–Activity Relationship (QSAR) molecules are described by molecular descriptors which are used for building mathematical models. Based on these models molecular properties can be predicted and using the molecular descriptors molecules can be compared for, e.g., similarity. Bioclipse is a workbench for the life sciences which provides ligand-based tools through a point and click interface. 

    The aims of this thesis were to research, and develop new or improved ligand-based methods and open source software, and to work towards making these tools available for users through the Bioclipse workbench. To this end, a series of molecular signature studies was done and various Bioclipse plugins were developed.

    An introduction to the field is provided in the thesis summary which is followed by five research papers. Paper I describes the Bioclipse 2 software and the Bioclipse scripting language. In Paper II the laboratory information system Brunn for supporting work with dose-response studies on microtiter plates is described. In Paper III the creation of a molecular fingerprint based on the molecular signature descriptor is presented and the new fingerprints are evaluated for target prediction and found to perform on par with industrial standard commercial molecular fingerprints. In Paper IV the effect of different parameter choices when using the signature fingerprint together with support vector machines (SVM) using the radial basis function (RBF) kernel is explored and reasonable default values are found. In Paper V the performance of SVM based QSAR using large datasets with the molecular signature descriptor is studied, and a QSAR model based on 1.2 million substances is created and made available from the Bioclipse workbench.

  • 14. Anders, Gerd
    et al.
    Mackowiak, Sebastian D
    Jens, Marvin
    Maaskola, Jonas
    Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems Biology, Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany.
    Kuntzagk, Andreas
    Rajewsky, Nikolaus
    Landthaler, Markus
    Dieterich, Christoph
    doRiNA: a database of RNA interactions in post-transcriptional regulation.2012In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 40, no Database issueArticle in journal (Refereed)
    Abstract [en]

    In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.

  • 15.
    Andersson, Christoffer
    University of Skövde, School of Humanities and Informatics.
    PELICAN: a PipELIne, including a novel redundancy-eliminating algorithm, to Create and maintain a topicAl family-specific Non-redundant protein database2005Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    The increasing number of biological databases today requires that users are able to search more efficiently among as well as in individual databases. One of the most widespread problems is redundancy, i.e. the problem of duplicated information in sets of data. This thesis aims at implementing an algorithm that distinguishes from other related attempts by using the genomic positions of sequences, instead of similarity based sequence comparisons, when making a sequence data set non-redundant. In an automatic updating procedure the algorithm drastically increases the possibility to update and to maintain the topicality of a non-redundant database. The procedure creates a biologically sound non-redundant data set with accuracy comparable to other algorithms focusing on making data sets non-redundant

  • 16.
    Andersson, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Decoding the Structural Layer of Transcriptional Regulation: Computational Analyses of Chromatin and Chromosomal Aberrations2010Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Gene activity is regulated at two separate layers. Through structural and chemical properties of DNA – the primary layer of encoding – local signatures may enable, or disable, the binding of proteins or complexes of them with regulatory potential to the DNA. At a higher level – the structural layer of encoding – gene activity is regulated through the properties of higher order DNA structure, chromatin, and chromosome organization. Cells with abnormal chromosome compaction or organization, e.g. cancer cells, may thus have perturbed regulatory activities resulting in abnormal gene activity.

    Hence, there is a great need to decode the transcriptional regulation encoded in both layers to further our understanding of the factors that control activity and life of a cell and, ultimately, an organism. Modern genome-wide studies with those aims rely on data-intense experiments requiring sophisticated computational and statistical methods for data handling and analyses. This thesis describes recent advances of analyzing experimental data from quantitative biological studies to decipher the structural layer of encoding in human cells.

    Adopting an integrative approach when possible, combining multiple sources of data, allowed us to study the influences of chromatin (Papers I and II) and chromosomal aberrations (Paper IV) on transcription. Combining chromatin data with chromosomal aberration data allowed us to identify putative driver oncogenes and tumor-suppressor genes in cancer (Paper IV).

    Bayesian approaches enabling the incorporation of background information in the models and the adaptability of such models to data have been very useful. Their usages yielded accurate and narrow detection of chromosomal breakpoints in cancer (Papers III and IV) and reliable positioning of nucleosomes and their dynamics during transcriptional regulation at functionally relevant regulatory elements (Paper II).

    Using massively parallel sequencing data, we explored the chromatin landscapes of human cells (Papers I and II) and concluded that there is a preferential and evolutionary conserved positioning at internal exons nearly unaffected by the transcriptional level. We also observed a strong association between certain histone modifications and the inclusion or exclusion of an exon in the mature gene transcript, suggesting a functional role in splicing.

  • 17. Andorf, Sandra
    et al.
    Altmann, T
    Witucka-Wall, H
    Selbig, Joachim
    Repsilber, Dirk
    Institute of Genetics and Biometry, Bioinformatics and Biomathematics Unit, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Molecular network structures in heterozygotes: A systems-biology approach to heterosis2009Conference paper (Refereed)
  • 18.
    Andorf, Sandra
    et al.
    Bioinformatics and Biomathematics Group, Genetics and Biometry Unit, Research Institute for the Biology of Farm Animals (FBN), Dummersdorf, Germany.
    Gärtner, Tanja
    Institute for Biochemistry and Biology, University of Potsdam, Potsdam-Golm, Germany.
    Steinfath, Matthias
    Institute for Biochemistry and Biology, University of Potsdam, Potsdam-Golm, Germany.
    Witucka-Wall, Hanna
    Institute for Genetics, University of Potsdam, Potsdam-Golm, Germany.
    Altmann, Thomas
    Institute for Genetics, University of Potsdam, Potsdam-Golm, Germany.
    Repsilber, Dirk
    Bioinformatics and Biomathematics Group, Genetics and Biometry Unit, Research Institute for the Biology of Farm Animals (FBN), Dummersdorf, Germany.
    Towards systems biology of heterosis: a hypothesis about molecular network structure applied for the Arabidopsis metabolome2009In: EURASIP Journal on Bioinformatics and Systems Biology, ISSN 1687-4145, E-ISSN 1687-4153, 147157Article in journal (Refereed)
    Abstract [en]

    We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity--a known phenomenon in the literature.

  • 19.
    Andorf, Sandra
    et al.
    Department Genetics and Biometry, Bioinformatics and Biomathematics Group, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany; Department of Medicine, Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany.
    Meyer, Rhonda C
    Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
    Selbig, Joachim
    Bioinformatics Chair, Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany.
    Altmann, Thomas
    Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
    Repsilber, Dirk
    Department Genetics and Biometry, Bioinformatics and Biomathematics Group, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Integration of a systems biological network analysis and QTL results for biomass heterosis in Arabidopsis thaliana2012In: PLoS ONE, ISSN 1932-6203, Vol. 7, no 11, e49951Article in journal (Refereed)
    Abstract [en]

    To contribute to a further insight into heterosis we applied an integrative analysis to a systems biological network approach and a quantitative genetics analysis towards biomass heterosis in early Arabidopsis thaliana development. The study was performed on the parental accessions C24 and Col-0 and the reciprocal crosses. In an over-representation analysis it was tested if the overlap between the resulting gene lists of the two approaches is significantly larger than expected by chance. Top ranked genes in the results list of the systems biological analysis were significantly over-represented in the heterotic QTL candidate regions for either hybrid as well as regarding mid-parent and best-parent heterosis. This suggests that not only a few but rather several genes that influence biomass heterosis are located within each heterotic QTL region. Furthermore, the overlapping resulting genes of the two integrated approaches were particularly enriched in biomass related pathways. A chromosome-wise over-representation analysis gave rise to the hypothesis that chromosomes number 2 and 4 probably carry a majority of the genes involved in biomass heterosis in the early development of Arabidopsis thaliana.

  • 20. Andorf, Sandra
    et al.
    Repsilber, Dirk
    Institute of Genetics and Biometry, Bioinformatics and Biomathematics Unit, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
    Molecular network structures in heterozygotes: A systems biological approach to heterosis2009In: Neue Methoden der Biometrie: 55. Biometrisches Kolloquium / [ed] R. Foraita, T. Gerds, L. A. Hothorn, M. Kieser, O. Kuß, U. Munzel, R. Vonk, A. Ziegler, 2009Conference paper (Refereed)
  • 21.
    Andorf, Sandra
    et al.
    Leibniz Institute for Farm Animal Biology, Dummerstorf, Gremany.
    Selbig, Joachim
    University of Potsdam, Potsdam-Golm, Germany.
    Altmann, T
    Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany.
    Witucka-Wall, H
    University of Potsdam, Potsdam-Golm, Germany.
    Repsilber, Dirk
    Leibniz Institute for Farm Animal Biology, Dummerstorf, Gremany.
    Heterosis in Arabidopsis thaliana: A metabolite network structure approach2010In: 11th Day of the Doktoral Student: abstract; 19 May 2010, Dummerstorf, Dummerstorf, Germany: FBN , 2010, 7-10 p.Conference paper (Refereed)
  • 22.
    Andorf, Sandra
    et al.
    Research Institute for the Biology of Farm Animals (FBN), Dummerstorf, Germany.
    Selbig, Joachim
    Research Institute for the Biology of Farm Animals (FBN), Dummerstorf, Germany.
    Altmann, Thomas
    Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
    Poos, Kathrin
    University of Applied Sciences Gelsenkirchen, Site Recklinghausen, Recklinghausen, Germany .
    Witucka-Wall, Hanna
    Research Institute for the Biology of Farm Animals (FBN), Dummerstorf, Germany.
    Repsilber, Dirk
    Research Institute for the Biology of Farm Animals (FBN), Dummerstorf, Germany.
    Enriched partial correlations in genome-wide gene expression profiles of hybrids (A. thaliana): a systems biological approach towards the molecular basis of heterosis2010In: Theoretical and Applied Genetics, ISSN 0040-5752, E-ISSN 1432-2242, Vol. 120, no 2, 249-59 p.Article in journal (Refereed)
    Abstract [en]

    Heterosis is a well-known phenomenon but the underlying molecular mechanisms are not yet established. To contribute to the understanding of heterosis at the molecular level, we analyzed genome-wide gene expression profile data of Arabidopsis thaliana in a systems biological approach. We used partial correlations to estimate the global interaction structure of regulatory networks. Our hypothesis states that heterosis comes with an increased number of partial correlations which we interpret as increased numbers of regulatory interactions leading to enlarged adaptability of the hybrids. This hypothesis is true for mid-parent heterosis for our dataset of gene expression in two homozygous parental lines and their reciprocal crosses. For the case of best-parent heterosis just one hybrid is significant regarding our hypothesis based on a resampling analysis. Summarizing, both metabolome and gene expression level of our illustrative dataset support our proposal of a systems biological approach towards a molecular basis of heterosis.

  • 23. Andorf, Sandra
    et al.
    Selbig, Joachim
    Meyer, Rhonda
    Altmann, Thomas
    Repsilber, Dirk
    Integrating a molecular network hypothesis and QTL results for heterosis in Arabidopsis thaliana2010In: Statistical Computings 2010: Abstracts der 42. Arbeitstagung, 2010, Vol. 5Conference paper (Refereed)
  • 24.
    Andrade, Jorge
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Andersen, Malin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Sillén, Anna
    Graff, Caroline
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    The use of grid computing to drive data-intensive genetic research2007In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 15, no 6, 694-702 p.Article in journal (Refereed)
    Abstract [en]

    In genetics, with increasing data sizes and more advanced algorithms for mining complex data, a point is reached where increased computational capacity or alternative solutions becomes unavoidable. Most contemporary methods for linkage analysis are based on the Lander-Green hidden Markov model (HMM), which scales exponentially with the number of pedigree members. In whole genome linkage analysis, genotype simulations become prohibitively time consuming to perform on single computers. We have developed 'Grid-Allegro', a Grid aware implementation of the Allegro software, by which several thousands of genotype simulations can be performed in parallel in short time. With temporary installations of the Allegro executable and datasets on remote nodes at submission, the need of predefined Grid run-time environments is circumvented. We evaluated the performance, efficiency and scalability of this implementation in a genome scan on Swedish multiplex Alzheimer's disease families. We demonstrate that 'Grid-Allegro' allows for the full exploitation of the features available in Allegro for genome-wide linkage. The implementation of existing bioinformatics applications on Grids (Distributed Computing) represent a cost-effective alternative for addressing highly resource-demanding and data-intensive bioinformatics task, compared to acquiring and setting up clusters of computational hardware in house (Parallel Computing), a resource not available to most geneticists today.

  • 25.
    Anyango, Stephen Omondi Otieno
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre. Uppsala University.
    VisuNet: Visualizing Networks of feature interactions in rule-based classifiers2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 26.
    Apostolov, Rossen
    et al.
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.
    Yonezawa, Yasushige
    Standley, Daron M
    Kikugawa, Gota
    Takano, Yu
    Nakamura, Haruki
    Membrane attachment facilitates ligand access to the active site in monoamine oxidase A2009In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 48, no 25, 5864-5873 p.Article in journal (Refereed)
    Abstract [en]

    Monoamine oxidase membrane enzymes are responsible for the catalytic breakdown of extra- and intracellular neurotransmitters and are targets for the development of central nervous system drugs. We analyzed the dynamics of rat MAOA by performing multiple independent molecular dynamics simulations of membrane-bound and membrane-free forms to clarify the relationship between the mechanics of the enzyme and its function, with particular emphasis on the significance of membrane attachment. Principal component analysis of the simulation trajectories as well as correlations in the fluctuations of the residues pointed to the existence of three domains that define the global dynamics of the protein. Interdomain anticorrelated movements in the membrane-bound system facilitated the relaxation of interactions between residues surrounding the substrate cavity and induced conformational changes which expanded the active site cavity and opened putative pathways for substrate uptake and product release. Such events were less pronounced in the membrane-free system due to differences in the nature of the dominant modes of motion. The presence of the lipid environment is suggested to assist in decoupling the interdomain motions, consistent with the observed reduction in enzyme activity under membrane-free conditions. Our results are also in accordance with mutational analysis which shows that modifications of interdomain hinge residues decrease the activity of rat MAOA in solution.

  • 27. Ardelius, John
    et al.
    Aurell, Erik
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Krishnamurthy, Supriya
    KTH, School of Information and Communication Technology (ICT).
    Clustering of solutions in hard satisfiability problems2007In: Journal of Statistical Mechanics: Theory and Experiment, ISSN 1742-5468, no 10, P10012- p.Article in journal (Refereed)
    Abstract [en]

    We study numerically the solution space structure of random 3-SAT problems close to the SAT/UNSAT transition. This is done by considering chains of satisfiability problems, where clauses are added sequentially to a problem instance. Using the overlap measure of similarity between different solutions found on the same problem instance, we examine geometrical changes as a function of α. In each chain, the overlap distribution is first smooth, but then develops a tiered structure, indicating that the solutions are found in well separated clusters. On chains of not too large instances, all remaining solutions are eventually observed to be found in only one small cluster before vanishing. This condensation transition point is estimated by finite size scaling to be αc = 4.26 with an apparent critical exponent of about 1.7. The average overlap value is also observed to increase with α up to the transition, indicating a reduction in solutions space size, in accordance with theoretical predictions. The solutions are generated by a local heuristic, ASAT, and compared to those found by the Survey Propagation algorithm up to αc.

  • 28.
    Ardell, David H.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Andersson, Siv G. E.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    TFAM detects co-evolution of tRNA identity rules with lateral transfer of histidyl-tRNA sythetase2006In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 34, no 3, 893-904 p.Article in journal (Refereed)
    Abstract [en]

    We present TFAM, an automated, statistical method to classify the identity of tRNAs. TFAM, currently optimized for bacteria, classifies initiator tRNAs and predicts the charging identity of both typical and atypical tRNAs such as suppressors with high confidence. We show statistical evidence for extensive variation in tRNA identity determinants among bacterial genomes due to variation in overall tDNA base content. With TFAM we have detected the first case of eukaryotic-like tRNA identity rules in bacteria. An alpha-proteobacterial clade encompassing Rhizobiales, Caulobacter crescentus and Silicibacter pomeroyi, unlike a sister clade containing the Rickettsiales, Zymomonas mobilis and Gluconobacter oxydans, uses the eukaryotic identity element A73 instead of the highly conserved prokaryotic element C73. We confirm divergence of bacterial histidylation rules by demonstrating perfect covariation of alpha-proteobacterial tRNA(His) acceptor stems and residues in the motif IIb tRNA-binding pocket of their histidyl-tRNA synthetases (HisRS). Phylogenomic analysis supports lateral transfer of a eukaryotic-like HisRS into the alpha-proteobacteria followed by in situ adaptation of the bacterial tDNA(His) and identity rule divergence. Our results demonstrate that TFAM is an effective tool for the bioinformatics, comparative genomics and evolutionary study of tRNA identity.

  • 29.
    Aspeborg, Henrik
    et al.
    KTH, School of Biotechnology (BIO), Glycoscience.
    Coutinho, Pedro M.
    Wang, Yang
    KTH, School of Biotechnology (BIO), Glycoscience.
    Brumer, Harry
    KTH, School of Biotechnology (BIO), Glycoscience.
    Henrissat, Bernard
    Evolution, substrate specificity and subfamily classification of glycoside hydrolase family 5 (GH5)2012In: BMC Evolutionary Biology, ISSN 1471-2148, Vol. 12, no 1, 186- p.Article in journal (Refereed)
    Abstract [en]

    Background: The large Glycoside Hydrolase family 5 (GH5) groups together a wide range of enzymes acting on beta-linked oligo- and polysaccharides, and glycoconjugates from a large spectrum of organisms. The long and complex evolution of this family of enzymes and its broad sequence diversity limits functional prediction. With the objective of improving the differentiation of enzyme specificities in a knowledge-based context, and to obtain new evolutionary insights, we present here a new, robust subfamily classification of family GH5. Results: About 80% of the current sequences were assigned into 51 subfamilies in a global analysis of all publicly available GH5 sequences and associated biochemical data. Examination of subfamilies with catalytically-active members revealed that one third are monospecific (containing a single enzyme activity), although new functions may be discovered with biochemical characterization in the future. Furthermore, twenty subfamilies presently have no characterization whatsoever and many others have only limited structural and biochemical data. Mapping of functional knowledge onto the GH5 phylogenetic tree revealed that the sequence space of this historical and industrially important family is far from well dispersed, highlighting targets in need of further study. The analysis also uncovered a number of GH5 proteins which have lost their catalytic machinery, indicating evolution towards novel functions. Conclusion: Overall, the subfamily division of GH5 provides an actively curated resource for large-scale protein sequence annotation for glycogenomics; the subfamily assignments are openly accessible via the Carbohydrate-Active Enzyme database at http://www.cazy.org/GH5.html.

  • 30.
    Attwood, Misty
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    The gene repertoire and functional characterization of membrane bound proteins: with focus on three- and four-transmembrane regions2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 31.
    Avican, Kemal
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS).
    Persistent infection by Yersinia pseudotuberculosis2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Enteropathogenic Yersinia species can infect many mammalian organs such as the small intestine, cecum, Peyer’s patches, liver, spleen, and lung and cause diseases that resemble a typhoid-like syndrome, as seen for other enteropathogens. We found that sublethal infection doses of Y. pseudotuberculosis gave rise to asymptomatic persistent infection in mice and identified the cecal lymphoid follicles as the primary site for colonization during persistence. Persistent Y. pseudotuberculosis is localized in the dome area, often in inflammatory lesions, as foci or as single cells, and also in neutrophil exudates in the cecal lumen. This new mouse model for bacterial persistence in cecum has potential as an investigative tool for deeper understanding of bacterial adaptation and host immune defense mechanisms during persistent infection. Here, we investigated the nature of the persistent infection established by Y. pseudotuberculosis in mouse cecal tissue using in vivo RNA-seq of bacteria during early and persistent stages of infection. Comparative analysis of the bacterial transcriptomes revealed that Y. pseudotuberculosis undergoes transcriptional reprogramming with drastic down-regulation of T3SS virulence genes during persistence in the cecum. At the persistent stage, the expression pattern in many respects resembles the pattern seen in vitro at 26°C. Genes that are up-regulated during persistence are genes involved in anaerobiosis, chemotaxis, and protection against oxidative and acidic stress, which indicates the influence of different environmental cues. We found that the Crp/CsrA/RovA regulatory cascades influence the pattern of bacterial gene expression during persistence. Furthermore, we show that ArcA, Fnr, FrdA, WrbA, RovA, and RfaH play critical roles in persistence. An extended investigation of the transcriptional regulator rfaH employing mouse infection studies, phenotypic characterizations, and RNA-seq transcriptomics analyses indicated that this gene product contributes to establishment of infection and confirmed that it regulates O-antigen biosynthesis genes in Y. pseudotuberculosis. The RNA-seq results also suggest that rfaH has a relatively global effect. Furthermore, we also found that the dynamics of the cecal tissue organization and microbial composition shows changes during different stages of the infection. Taken together, based on our findings, we speculate that this enteropathogen initiates infection by using its virulence factors in meeting the innate immune response in the cecal tissue. Later on, these factors lead to dysbiosis in the local microbiota and altered tissue organization. At later stages of the infection, the pathogen adapts to the environment in the cecum by reprogramming its transcriptome from a highly virulent mode to a more environmentally adaptable mode for survival and shedding. The in vivo transcriptomic analyses for essential genes during infections present strong candidates for novel targets for antimicrobials.

  • 32.
    Avican, Kemal
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Fahlgren, Anna
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR).
    Huss, Mikael
    Heroven, Ann Kathrin
    Beckstette, Michael
    Dersch, Petra
    Fällman, Maria
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS).
    Reprogramming of Yersinia from Virulent to Persistent Mode Revealed by Complex In Vivo RNA-seq Analysis2015In: PLoS Pathogens, ISSN 1553-7366, E-ISSN 1553-7374, Vol. 11, no 1, e1004600Article in journal (Refereed)
    Abstract [en]

    We recently found that Yersinia pseudotuberculosis can be used as a model of persistent bacterial infections. We performed in vivo RNA-seq of bacteria in small cecal tissue biopsies at early and persistent stages of infection to determine strategies associated with persistence. Comprehensive analysis of mixed RNA populations from infected tissues revealed that Y. pseudotuberculosis undergoes transcriptional reprogramming with drastic down-regulation of T3SS virulence genes during persistence when the pathogen resides within the cecum. At the persistent stage, the expression pattern in many respects resembles the pattern seen in vitro at 26oC, with for example, up-regulation of flagellar genes and invA. These findings are expected to have impact on future rationales to identify suitable bacterial targets for new antibiotics. Other genes that are up-regulated during persistence are genes involved in anaerobiosis, chemotaxis, and protection against oxidative and acidic stress, which indicates the influence of different environmental cues. We found that the Crp/CsrA/RovA regulatory cascades influence the pattern of bacterial gene expression during persistence. Furthermore, arcA, fnr, frdA, and wrbA play critical roles in persistence. Our findings suggest a model for the life cycle of this enteropathogen with reprogramming from a virulent to an adapted phenotype capable of persisting and spreading by fecal shedding.

  • 33.
    Avican, Ummehan
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology).
    Twin-arginine translocation in Yersinia: the substrates and their role in virulence2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Pathogenic Yersinia cause a manifold of diseases in humans ranging from mild gastroenteritis (Y. pseudotuberculosis and Y. enterocolitica) to pneumonic and bubonic plague (Y. pestis), while all three have a common virulence strategy that relies on a well-studied type III secretion system and its effector proteins to colonize the host and evade immune responses. However, the role of other protein secretion and/or translocation systems in virulence of Yersinia species is not well known. In this thesis, we sought to investigate the contribution of twin-arginine translocation (Tat) pathway and its secreted substrates to the physiology and virulence of Y. pseudotuberculosis. Tat pathway uniquely exports folded proteins including virulence factors across the cytoplasmic membranes of bacteria. The proteins exported by Tat pathway contain a highly conserved twin-arginine motif in the N-terminal signal peptide. We found that the loss of Tat pathway causes a drastic change of the transcriptome of Y. pseudotuberculosis in stationary phase at environmental temperature with differential regulation of genes involved in virulence, carbon metabolism and stress responses. Phenotypic analysis revealed novel phenotypes of the Tat-deficient strain with defects in iron acquisition, acid resistance, copper oxidation and envelope integrity, which we were partly able to associate with the related Tat substrates. Moreover, increased glucose consumption and accumulation of intracellular fumarate were observed in response to inactivation of Tat pathway implicating a generic effect in cellular physiology. We evaluated the direct role of 22 in silico predicted Tat substrate mutants in the mouse infection model and found only one strain, ΔsufI, exhibited a similar degree of attenuation as Tat-deficient strain. Comparative in vivo characterization studies demonstrated a minor defect for ΔsufI in colonization of intestinal tissues compared to the Tat-deficient strain during early infection, whereas both SufI and TatC were required for dissemination from mesenteric lymph nodes and further systemic spread during late infection. This verifies that SufI has a major role in attenuation seen for the Tat deficient strain both during late infection and initial colonization. It is possible that other Tat substrates such as those involved in iron acquisition and copper resistance also has a role in establishing infection. Further phenotypic analysis indicated that SufI function is required for cell division and stress-survival. Transcriptomic analysis revealed that the highest number of differentially regulated genes in response to loss of Tat and SufI were involved in metabolism and transport. Taken together, this thesis presents a thorough analysis of the involvement of Tat pathway in the overall physiology and virulence strategies of Y. pseudotuberculosis. Finally, we propose that strong effects in virulence render TatC and SufI as potential targets for development of novel antimicrobial compounds

  • 34.
    Avican, Ummehan
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology).
    Avican, Kemal
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Fällman, Maria
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Forsberg, Åke
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Transcriptomic and phenotypic analysis of sufI and tatC mutants of Yersinia pseudotuberculosisManuscript (preprint) (Other academic)
  • 35.
    Avican, Ummehan
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology).
    Beckstette, Michael
    Heroven, Ann Kathrin
    Lavander, Moa
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology).
    Dersch, Petra
    Forsberg, Åke
    Umeå University, Faculty of Medicine, Umeå Centre for Microbial Research (UCMR). Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Transcriptomic and phenotypic analysis reveals new functions for the Tat pathway in Yersinia pseudotuberculosis2016In: Journal of Bacteriology, ISSN 0021-9193, E-ISSN 1098-5530, Vol. 198, no 20, 2876-2886 p.Article in journal (Refereed)
    Abstract [en]

    The Twin-arginine translocation (Tat) system mediates secretion of folded proteins that in bacteria, plants and archaea are identified via an N-terminal signal peptide. Tat systems are associated with virulence in many bacterial pathogens and our previous studies revealed that Tat deficient Yersinia pseudotuberculosis was severely attenuated for virulence. Aiming to identify Tat-dependent pathways and phenotypes of relevance for in vivo infection, we analysed the global transcriptome of parental and ∆tatC mutant strains of Y. pseudotuberculosis during exponential and stationary growth at 26oC and 37oC. The most significant changes in the transcriptome of the ∆tatC mutant were seen at 26oC during stationary phase growth and these included the altered expression of genes related to virulence, stress responses and metabolism. Subsequent phenotypic analysis based on these transcriptome changes revealed several novel Tat-dependent phenotypes including decreased YadA expression, impaired growth under iron-limiting and high copper conditions as well as acidic pH and SDS. Several functionally related Tat substrates were also verified to contribute to these phenotypes. Interestingly, the phenotypic defects observed in the Tat-deficient strain were generally more pronounced than in mutants lacking the Tat substrate predicted to contribute to that specific function. Altogether, this provides new insight into the impact of Tat deficiency on in vivo fitness and survival/replication of Y. pseudotuberculosis during infection.

  • 36.
    Baichoo, Shakuntala
    et al.
    University of Mauritius, Mauritius.
    Botha, Gerrit
    University of Cape Town, South Africa.
    Jaufeerally-Fakim, Yasmina
    University of Mauritius, Mauritius.
    Mungloo-Dilmohamud, Zahra
    University of Mauritius, Mauritius.
    Lundin, Daniel
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Stockholm University.
    Mulder, Nicola
    University of Cape Town, South Africa.
    Promponas, Vasilis J.
    University of Cyprus, Cyprus.
    Ouzounis, Christos A.
    Centre for Research & Technology (CERTH), Greece.
    H3ABioNet computational metagenomics workshop in Mauritius: training to analyse microbial diversity for Africa2015In: Standards in Genomic Sciences, ISSN 1944-3277, E-ISSN 1944-3277, Vol. 10, 115Article in journal (Refereed)
    Abstract [en]

    In the context of recent international initiatives to bolster genomics research for Africa, and more specifically to develop bioinformatics expertise and networks across the continent, a workshop on computational metagenomics was organized during the end of 2014 at the University of Mauritius. The workshop offered background on various aspects of computational biology, including databases and algorithms, sequence analysis fundamentals, metagenomics concepts and tools, practical exercises, journal club activities and research seminars. We have discovered a strong interest in metagenomics research across Africa, to advance practical applications both for human health and the environment. We have also realized the great potential to develop genomics and bioinformatics through collaborative efforts across the continent, and the need for further reinforcing the untapped human potential and exploring the natural resources for stronger engagement of local scientific communities, with a view to contributing towards the improvement of human health and well-being for the citizens of Africa.

  • 37. Banerjee, M.
    et al.
    Zhang, Lai
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Stabilizing Role of Nonlocal Interaction on Spatio-temporal Pattern Formation2016In: Mathematical Modelling of Natural Phenomena, ISSN 0973-5348, E-ISSN 1760-6101, Vol. 11, no 5, 103-118 p.Article in journal (Refereed)
    Abstract [en]

    Here we study a spatio-temporal prey-predator model with ratio-dependent functional response and nonlocal interaction term in the prey growth. For a clear understanding of the effect of nonlocal interaction on the resulting stationary and non-stationary patterns, we consider the nonlocal interaction term in prey growth only to describe the nonlocal intra-specific competition due to limited resources for the prey. First we obtain the patterns exhibited by the basic model in the absence of nonlocal interaction and then explore the effect of nonlocal interaction on the resulting patterns. We demonstrate the stabilizing role of nonlocal interaction as it induces stationary pattern from periodic and chaotic regimes with an increase in the range of nonlocal interaction. The existence of multiple branches of stationary solutions, bifurcating from homogeneous steady-state as well as non-stationary patterns, is illustrated with the help of numerical continuation technique.

  • 38.
    Bartoszek, Krzysztof
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
    Phylogenetic effective sample size2016In: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 407, 371-386 p.Article in journal (Refereed)
    Abstract [en]

    In this paper I address the question—how large is a phylogenetic sample? I propose a definition of a phylogenetic effective sample size for Brownian motion and Ornstein-Uhlenbeck processes-the regression effective sample size. I discuss how mutual information can be used to define an effective sample size in the non-normal process case and compare these two definitions to an already present concept of effective sample size (the mean effective sample size). Through a simulation study I find that the AICc is robust if one corrects for the number of species or effective number of species. Lastly I discuss how the concept of the phylogenetic effective sample size can be useful for biodiversity quantification, identification of interesting clades and deciding on the importance of phylogenetic correlations.

  • 39.
    Baxter, Charles J
    et al.
    Department of Plant Sciences, University of Oxford, Oxford, United Kingdom.
    Redestig, Henning
    Max-Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Schauer, Nicolas
    Max-Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Repsilber, Dirk
    ax-Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Patil, Kiran R
    Center for Microbial Biotechnology, BioCentrum Technical University of Denmark, Kongens Lyngby, Denmark.
    Nielsen, Jens
    Max-Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Selbig, Joachim
    Max-Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Liu, Junli
    Genetics Programme, Scottish Crop Research Institute, Dundee, United Kingdom .
    Fernie, Alisdair R
    Max-Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
    Sweetlove, Lee J
    Department of Plant Sciences, University of Oxford, Oxford, United Kingdom.
    The metabolic response of heterotrophic Arabidopsis cells to oxidative stress2007In: Plant Physiology, ISSN 0032-0889, E-ISSN 1532-2548, Vol. 143, no 1, 312-25 p.Article in journal (Refereed)
    Abstract [en]

    To cope with oxidative stress, the metabolic network of plant cells must be reconfigured either to bypass damaged enzymes or to support adaptive responses. To characterize the dynamics of metabolic change during oxidative stress, heterotrophic Arabidopsis (Arabidopsis thaliana) cells were treated with menadione and changes in metabolite abundance and (13)C-labeling kinetics were quantified in a time series of samples taken over a 6 h period. Oxidative stress had a profound effect on the central metabolic pathways with extensive metabolic inhibition radiating from the tricarboxylic acid cycle and including large sectors of amino acid metabolism. Sequential accumulation of metabolites in specific pathways indicated a subsequent backing up of glycolysis and a diversion of carbon into the oxidative pentose phosphate pathway. Microarray analysis revealed a coordinated transcriptomic response that represents an emergency coping strategy allowing the cell to survive the metabolic hiatus. Rather than attempt to replace inhibited enzymes, transcripts encoding these enzymes are in fact down-regulated while an antioxidant defense response is mounted. In addition, a major switch from anabolic to catabolic metabolism is signaled. Metabolism is also reconfigured to bypass damaged steps (e.g. induction of an external NADH dehydrogenase of the mitochondrial respiratory chain). The overall metabolic response of Arabidopsis cells to oxidative stress is remarkably similar to the superoxide and hydrogen peroxide stimulons of bacteria and yeast (Saccharomyces cerevisiae), suggesting that the stress regulatory and signaling pathways of plants and microbes may share common elements.

  • 40.
    Benediktsson, Elís Ingi
    University of Skövde, School of Humanities and Informatics.
    Detection and analysis of megasatellites in the human genome using in silico methods2005Independent thesis Advanced level (degree of Master (One Year))Student thesis
    Abstract [en]

    Megasatellites are polymorphic tandem repetitive sequences with repeat-units longer than or equal to 1000 base pairs. The novel algorithm Megasatfinder predicts megasatellites in the human genome. A structured method of analysing the algorithm is developed and conducted. The analysis method consists of six test scenarios. Scripts are created, which execute the algorithm using various parameter settings. Three nucleotide sequences are applied; a real sequence extracted from the human genome and two random sequences, generated using different base probabilities. Usability and accuracy are investigated, providing the user with confidence in the algorithm and its output. The results indicate that Megasatfinder is an excellent tool for the detection of megasatellites and that the generated results are highly reliable. The results of the complete analysis suggest alterations in the default parameter settings, presented as user guidelines, and state that artificially generated sequences are not applicable as models for real DNA in computational simulations.

  • 41.
    Bergenholm, Linnéa
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.
    Modeling as a Tool to Support Self-Management of Type 1 Diabetes2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Type 1 diabetes (T1D) is an auto-immune disease characterized by insulin-deficiency. Insulin is a metabolic hormone that is involved in lowering blood glucose (BG) levels in order to control BG level to a tight range. In T1D this glycemic control is lost, causing chronic hyperglycemia (excess glucose in blood stream). Chronic hyperglycemia damages vital tissues. Therefore, glycemic control must be restored.

    A common therapy for restoring glycemic control is intensive insulin therapy, where the missing insulin is replaced with regular insulin injections. When dosing this compensatory insulin many factors that affect glucose metabolism must be considered. Linkura is a company that has developed tools for monitoring the most important factors, which are meals and exercise. In the Linkura meal and exercise tools, the nutrition content in meals and the calorie consumption during exercise are estimated. Another tool designed to aid control of BG is the bolus calculator. Bolus calculators use input of BG level, carbohydrate intake, and insulin history to estimate insulin need. The accuracy of these insulin bolus calculations suffer from two problems. First, errors occur when users inaccurately estimate the carbohydrate content in meals. Second, exercise is not included in bolus calculations. To reduce these problems, it was suggested that the Linkura web tools could be utilized in combination with a bolus calculator.

    For this purpose, a bolus calculator was developed. The bolus calculator was based on existing models that utilize clinical parameters to relate changes in BG levels to meals, insulin, and exercise stimulations. The bolus calculator was evaluated using data collected from Linkura's web tools. The collected data showed some inconsistencies which cannot be explained by any model.  The performance of the bolus calculator in predicting BG levels using general equations to derive the clinical parameters was inadequate. Performance was increased by adopting an update-algorithm where the clinical parameters were updated daily using previous data. Still, better model performance is prefered for use in a bolus calculator.  

    The results show potential in developing bolus calculator tools combined with the Linkura tools. For such bolus calculator, further evaluation on modeling long-term exercise and additional safety features minimizing risk of hypoglycemia are required.

  • 42. Berglund, Ann-Charlotte
    et al.
    Sjölund, Erik
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Östlund, Gabriel
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Sonnhammer, Erik L. L.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    InParanoid 6: eukaryotic ortholog clusters with inparalogs2008In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 36, D263-D266 p.Article in journal (Refereed)
    Abstract [en]

    The InParanoid eukaryotic ortholog database (http://InParanoid.sbc.su.se/) has been updated to version 6 and is now based on 35 species. We collected all available 'complete' eukaryotic proteomes and Escherichia coli, and calculated ortholog groups for all 595 species pairs using the InParanoid program. This resulted in 2 642 187 pairwise ortholog groups in total. The orthology-based species relations are presented in an orthophylogram. InParanoid clusters contain one or more orthologs from each of the two species. Multiple orthologs in the same species, i.e. inparalogs, result from gene duplications after the species divergence. A new InParanoid website has been developed which is optimized for speed both for users and for updating the system. The XML output format has been improved for efficient processing of the InParanoid ortholog clusters.

  • 43.
    Berglund, Eva Caroline
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Genome Evolution and Host Adaptation in Bartonella2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Bacteria of the genus Bartonella infect the red blood cells of a wide range of wild and domestic mammals and are transmitted between hosts by blood-sucking insects. Although most Bartonella infections are asymptomatic, the genus contains several human pathogens. In this work, host adaptation and host switches in Bartonella have been studied from a genomic perspective, with special focus on the acquisition and evolution of genes involved in host interactions.

    As part of this study, the complete genome of B. grahamii isolated from a Swedish wood mouse was sequenced. A genus-wide comparison revealed that rodent-associated Bartonella species, which have rarely been associated with human disease, have the largest genomes and the largest number of host-adaptability genes. Analysis of known and putative genes for host interactions identified several families of autotransporters as horizontally transferred to the Bartonella ancestor, with a possible role both during early host adaptation and subsequent host shifts.

    In B. grahamii, the association of a gene transfer agent (GTA) and phage-derived run-off replication of a large genomic segment was demonstrated for the first time. Among all acquisitions to the Bartonella ancestor, the only well conserved gene clusters are those that encode the GTA and contain the origin of the run-off replication. This conservation, along with a high density of host-adaptability genes in the amplified region suggest that the GTA provides a strong selective advantage, possibly by increasing recombination frequencies of host-adaptability genes, thereby facilitating evasion of the host immune system and colonization of new hosts.

    B. grahamii displays stronger geographic pattern and higher recombination frequencies than the cat-associated B. henselae, probably caused by different lifestyles and/or population sizes of the hosts. The genomic diversity of B. grahamii is markedly lower in Europe and North America than in Asia, possibly an effect of reduced host variability in these areas following the latest ice age.

  • 44.
    Bergman, Julia
    et al.
    Uppsala University.
    Botling, Johan
    Uppsala University.
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    M Hallström, Björn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Djureinovic, Dijana
    Uppsala University.
    Pontén, Fredrik
    Uppsala University.
    Mathias, Uhlén
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    The human adrenal gland proteome defined by transcriptomics and antibody-based profiling.2017In: Endocrinology, ISSN 0013-7227, E-ISSN 1945-7170, Vol. 158, no 2, 239-251 p.Article in journal (Refereed)
    Abstract [en]

    The adrenal gland is a composite endocrine organ with vital functions that include the synthesis and release of glucocorticoids and catecholamines. To define the molecular landscape that underlies the specific functions of the adrenal gland, we combined a genome-wide transcriptomics approach using messenger RNA sequencing of human tissues with immunohistochemistry-based protein profiling on tissue microarrays. Approximately two-thirds of all putative protein coding genes were expressed in the adrenal gland, and the analysis identified 253 genes with an elevated pattern of expression in the adrenal gland, with only 37 genes showing a markedly greater expression level (more than fivefold) in the adrenal gland compared with 31 other normal human tissue types analyzed. The analyses allowed for an assessment of the relative expression levels for well-known proteins involved in adrenal gland function but also identified previously poorly characterized proteins in the adrenal cortex, such as the FERM (4.1 protein, ezrin, radixin, moesin) domain containing 5 and the nephroblastoma overexpressed (NOV) protein homolog. We have provided a global analysis of the adrenal gland transcriptome and proteome, with a comprehensive list of genes with elevated expression in the adrenal gland and spatial information with examples of protein expression patterns for corresponding proteins. These genes and proteins constitute important starting points for an improved understanding of the normal function and pathophysiology of the adrenal glands.

  • 45.
    Bergman Laurila, Jonas
    Linköping University. Linköping University, Department of Computer and Information Science.
    Ontology Slice Generation and Alignment for Enhanced Life Science Literature Search2009Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Query composition is an often complicated and cumbersome task for persons performing a literature search. This thesis is part of a project which aims to present possible queries to the user in form of natural language expressions. The thesis presents methods of ontology slice generation. Slices are parts of ontologies connecting two concepts along all possible paths between them. Those slices hence represent all relevant queries connecting the concepts and the paths can in a later step be translated into natural language expressions. Methods of slice alignment, connecting slices that originate from different ontologies, are also presented. The thesis concludes with some example scenarios and comparisons to related work.

  • 46.
    Bernsel, Andreas
    et al.
    Stockholm University.
    Viklund, Håkan
    Stockholm University.
    Falk, Jenny
    Stockholm University.
    Lindahl, Erik
    Stockholm University.
    von Heijne, Gunnar
    Stockholm University.
    Elofsson, Arne
    Stockholm University.
    Prediction of membrane-protein topology from first principles2008In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 105, no 20, 7177-7781 p.Article in journal (Refereed)
    Abstract [en]

    The current best membrane-protein topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among protein, lipids and water, it should be possible to predict topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based topology predictors. This result suggests that prediction of membrane-protein topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.

  • 47.
    Bertaccini, Edward J.
    et al.
    Stanford University.
    Lindahl, Erik
    Stockholm University.
    Sixma, Titia
    Netherlands Cancer Institute.
    Trudell, James R.
    Stanford University.
    Effect of cobratoxin binding on the normal mode vibration within acetylcholine binding protein2008In: Journal of chemical information and modeling, ISSN 1549-9596, Vol. 48, no 4, 855-860 p.Article in journal (Refereed)
    Abstract [en]

    Recent crystal structures of the acetylcholine binding protein (AChBP) have revealed surprisingly small structural alterations upon ligand binding. Here we investigate the extent to which ligand binding may affect receptor dynamics. AChBP is a homologue of the extracellular component of ligand-gated ion channels (LGICs). We have previously used an elastic network normal-mode analysis to propose a gating mechanism for the LGICs and to suggest the effects of various ligands on such motions. However, the difficulties with elastic network methods lie in their inability to account for the modest effects of a small ligand or mutation on ion channel motion. Here, we report the successful application of an elastic network normal mode technique to measure the effects of large ligand binding on receptor dynamics. The present calculations demonstrate a clear alteration in the native symmetric motions of a protein due to the presence of large protein cobratoxin ligands. In particular, normal-mode analysis revealed that cobratoxin binding to this protein significantly dampened the axially symmetric motion of the AChBP that may be associated with channel gating in the full nAChR. The results suggest that alterations in receptor dynamics could be a general feature of ligand binding.

  • 48.
    Bertaccini, Edward J
    et al.
    Stanford University.
    Lindahl, Erik
    Stanford University.
    Titia, Sixma
    Netherlands Cancer Institute.
    Trudell, James R
    Stanford University.
    Toxin Binding Serves as an Initial Model for Studying the Effects of Anesthetics on Ion Channels2007Conference paper (Refereed)
    Abstract [en]

    Introduction: We have previously used molecular modeling techniques combined with experimental data to visualize a plausible model of an anesthetic binding site within a LGIC complex.We have also previously shown a computational mechanism by which these ion channels may open and close and postulated how this motion may be affected by the presence of anesthetics.2 The difficulties with these methods, however, lay in their inability to account for the modest effects of a separate anesthetic ligand or small mutation on ion channel motion. Here we show the successful application of an elastic network calculation on a homologue of the extracellular component of LGIC's, the acetycholine binding protein (AChBP), in the presence and absence of large cobratoxin ligands. These calculations demonstrate a clear alteration in the native symmetric motion of a protein due to the presence of multiple ligands, as may occur with anesthetics and muscle relaxants.

    Methods: Coordinates of the AChBP with (1YI5)3 and without (1I9B)4 cobratoxin were obtained from the Research Collaboratory for Structural Biology (RCSB). Hydrogens were added using DSViewer 5.0 (Accelrys, San Diego, CA). Normal mode analysis was performed using an all atom elastic network model developed by Lindahl. Root-mean-square deviations (RMSD) of each residue were produced from the application of the RMSD analysis utility within the GROMACS software suite to the coordinate trajectory output files. The RMSD data was then imported into Microsoft Excel for plotting and further comparison of protein backbone motions between the two different normal mode trajectories.

    Results: Normal mode analysis reveals that ligand binding to this protein alters its natural harmonic vibration. In this case, the axially symmetric motion of the AChBP, that may be associated with channel gating in the full nAChR, is highly dampened by the presence of bound cobratoxin. A large proportion of the kinetic energy within this mode seems to be absorbed by the cobratoxin, leaving the channel motion significantly decreased.

    Conclusions: This is among the first descriptions of the effect of bound ligand on large scale protein dynamics, especially as it relates to ion channel gating. This analysis was possible using an elastic network approximation due to the large protein nature of the cobratoxin ligand. For nonpeptide drugs such as anesthetics which contain far fewer atoms, using the effects of bound ligand on protein motion as additional criteria for future drug design may require a more robust molecular mechanics treatment of the ligand-receptor complex.

  • 49.
    Bertaccini, Edward J.
    et al.
    Stanford University.
    Trudell, James R.
    Stanford University.
    Lindahl, Erik
    Stockholm University.
    Normal-mode analysis of the glycine alpha1 receptor by three separate methods2007In: Journal of Chemical Information and Modeling, ISSN 1549-9596, Vol. 47, no 4, 1572-1579 p.Article in journal (Refereed)
    Abstract [en]

    Predicting collective dynamics and structural changes in biological macromolecules is pivotal toward a better understanding of many biological processes. Limitations due to large system sizes and inaccessible time scales have prompted the development of alternative techniques for the calculation of such motions. In this work, we present the results of a normal-mode analysis technique based on molecular mechanics that enables the calculation of accurate force-field based vibrations of extremely large molecules and compare it with two elastic network approximate models. When applied to the glycine alpha1 receptor, all three normal-mode analysis algorithms demonstrate an "iris-like" gating motion. Such gating motions have implications for understanding the effects of anesthetic and other ligand binding sites and for the means of transducing agonist binding into ion channel opening. Unlike the more approximate methods, molecular mechanics based analyses can also reveal approximate vibrational frequencies. Such analyses may someday allow the use of protein dynamics elucidated via normal-mode calculations as additional endpoints for future drug design.

  • 50.
    Bertaccini, Edward J
    et al.
    Stanford University.
    Trudell, James R
    Stanford University.
    Lindahl, Erik
    Stockholm University.
    Understanding Effects of Anesthetics on Ligand-Gated Ion Channels (LGIC) in Lipid Membranes2008Conference paper (Refereed)
    Abstract [en]

    Introduction: We have previously used molecular modeling combined with experimental data to visualize a plausible model of an anesthetic binding site within a LGIC.1 We have also previously shown a computational mechanism by which these LGICs may gate and postulated how this motion may be affected by the presence of anesthetics.2 The initial difficulty with these calculations concerns the 26000 atoms present in the receptor and the computing capabilities required to perform vibrational analyses on such a large construct. Here we show the successful application of an elastic network calculation on our previously published model of a glycine alpha one receptor (GlyRa1), now suspended in a fully hydrated lipid bilayer. Despite the presence of over 100,000 atoms , these calculations continue to demonstrate a symmetric motion of the ion channel protein that is consistent with the gating motion demonstrated in previous in vacuo work by us and others. Methods: Coordinates of the GlyRa1 model were obtained from our previous work. A 100x100A lipid bilayer matrix was constructed from POPC and then hydrated on both surfaces with water molecules using the VMD 1.86 software package (NCSA, Urbana, Ill.). Discovery Studio 1.7 (Accelrys, San Diego, CA) molecular modeling software was used to insert our GlyRa1 model into the lipid bilayer such that the known interfacial residue GLY 221 was at the POPC-water interface. All waters within 3.8A of the protein were removed as were all lipid molecules within 2A of the protein. Hydrogens were added followed by energy minimization of the entire system to remove energetically unfavorable contacts. The system was subsequently further hydrated within the GROMACS software suite and subjected to further energy equilibration via molecular dynamics simulation with periodic boundary conditions. Subsequent normal mode analysis was performed using an all atom elastic network model developed by Lindahl which takes advantage of a sparse matrix implementation for computational efficiency. Results: Despite the large size of the system, the introduction of water and lipid did not grossly distort the overall gating motion of the glyRa1 noted in previous works. Normal mode analysis revealed that the GlyRa1 in a fully hydrated bilayer environment continues to demonstrate an iris-like gating motion as a low frequency, high amplitude natural harmonic vibration. Furthermore, the introduction of periodic boundary conditions allowed simultaneous harmonic vibrations of lipid in sync with the protein gating motion that are compatible with reasonable lipid bilayer perturbations. Conclusions: This is among the first description of a normal mode calculation describing large-scale protein dynamics and ion channel gating in the presence of a fully hydrated lipid bilayer complex. This analysis was only possible on such a large system due to the computational efficiencies of the elastic network approximation. This model will hopefully provide a more accurate means of introducing anesthetics and alcohols into protein and lipid bilayer systems and allow us to discern their effects on LGIC gating. 1Bertaccini EJ, Shapiro J, Brutlag DL, Trudell JR: J Chem Inf Model 2005; 45: 128-35; 2Bertaccini EJ, Trudell JR, Lindahl E:J Chem Inf Model 2007; 47: 1572-9.

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