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  • 1.
    Alneberg, Johannes
    et al.
    KTH Royal Institute of Technology, Sweden.
    Sundh, John
    Stockholm University, Sweden.
    Bennke, Christin
    Leibniz Inst Balt Sea Res Warnemunde, Germany.
    Beier, Sara
    Leibniz Inst Balt Sea Res Warnemunde, Germany.
    Lundin, Daniel
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Hugerth, Luisa W.
    KTH Royal Institute of Technology, Sweden.
    Pinhassi, Jarone
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Kisand, Veljo
    Univ Tartu, Estonia.
    Riemann, Lasse
    Univ Copenhagen, Denmark.
    Juergens, Klaus
    Leibniz Inst Balt Sea Res Warnemunde, Germany.
    Labrenz, Matthias
    Leibniz Inst Balt Sea Res Warnemunde, Germany.
    Andersson, Anders F.
    KTH Royal Institute of Technology, Sweden.
    BARM and BalticMicrobeDB, a reference metagenome and interface to meta-omic data for the Baltic Sea2018In: Scientific Data, E-ISSN 2052-4463, Vol. 5, article id 180146Article in journal (Refereed)
    Abstract [en]

    The Baltic Sea is one of the world's largest brackish water bodies and is characterised by pronounced physicochemical gradients where microbes are the main biogeochemical catalysts. Meta-omic methods provide rich information on the composition of, and activities within, microbial ecosystems, but are computationally heavy to perform. We here present the Baltic Sea Reference Metagenome (BARM), complete with annotated genes to facilitate further studies with much less computational effort. The assembly is constructed using 2.6 billion metagenomic reads from 81 water samples, spanning both spatial and temporal dimensions, and contains 6.8 million genes that have been annotated for function and taxonomy. The assembly is useful as a reference, facilitating taxonomic and functional annotation of additional samples by simply mapping their reads against the assembly. This capability is demonstrated by the successful mapping and annotation of 24 external samples. In addition, we present a public web interface, BalticMicrobeDB, for interactive exploratory analysis of the dataset. [GRAPHICS] .

  • 2.
    Amnebrink, Dennis
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Transcriptomic profiling of marine bacteria between development and senescence phases of a phytoplankton bloom2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Bacterioplankton provide important ecosystem functions by carrying out biogeochemical cycling of organic matter. Playing an important role in the microbial loop they help remineralize carbon and nutrients. Bacteria also interact with phytoplankton during phytoplankton blooms. However, fundamental understanding on the underlying molecular mechanisms involved in the degradation of phytoplankton-derived organic matter is still in its infancy. Therefore, we analysed data from a mesocosm experiment following a natural phytoplankton-bloom from an upwelling system in the North- East Atlantic Ocean. The purpose was to contribute a mechanistic understanding based on functional gene expression analysis of natural microbial assemblages. Our results show the difference in functional gene expression within a bacterial metacommunity and how this functional response drastically switches between bloom build up and senescence. Transcripts showed a broad change in gene expression involving major SEED categories, with the bloom senescence phase exhibiting a higher relative abundance in major categories such as Carbohydrates, Protein Metabolism and Amino Acids and Derivatives. Within these categories genes connected to carbon utilization and transport systems (Ton and Tol) as well as chemotaxis showed a higher abundance during bloom senescence. The change in functionality based on transcripts showed a different bacterial community composition appearing over a very short time. We thus conclude that the bacterial functional gene expression response between build-up and degradation bloom phases is remarkably different and associated with a change in the identity of bacteria with active expression. Our findings highlight the importance of bacterial substrate specialists with different functional roles during different time points of phytoplankton blooms.

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  • 3.
    Arikumar, K. S.
    et al.
    St. Joseph’s Institute of Technology, India.
    Prathiba, Sahaya Beni
    Anna University, India.
    Alazab, Mamoun
    Charles Darwin University, Australia.
    Gadekallu, Thippa Reddy
    Vellore Institute of Technology, India.
    Pandya, Sharnil
    Symbiosis International (Deemed) University, India.
    Khan, Javed Masood
    King Saud University, Saudi Arabia.
    Moorthy, Rajalakshmi Shenbaga
    Sri Ramachandra Institute of Higher Education and Research, India.
    FL-PMI: Federated Learning-Based Person Movement Identification through Wearable Devices in Smart Healthcare Systems2022In: Sensors, E-ISSN 1424-8220, Vol. 22, no 4, article id 1377Article in journal (Refereed)
    Abstract [en]

    Recent technological developments, such as the Internet of Things (IoT), artificial intelligence, edge, and cloud computing, have paved the way in transforming traditional healthcare systems into smart healthcare (SHC) systems. SHC escalates healthcare management with increased efficiency, convenience, and personalization, via use of wearable devices and connectivity, to access information with rapid responses. Wearable devices are equipped with multiple sensors to identify a person's movements. The unlabeled data acquired from these sensors are directly trained in the cloud servers, which require vast memory and high computational costs. To overcome this limitation in SHC, we propose a federated learning-based person movement identification (FL-PMI). The deep reinforcement learning (DRL) framework is leveraged in FL-PMI for auto-labeling the unlabeled data. The data are then trained using federated learning (FL), in which the edge servers allow the parameters alone to pass on the cloud, rather than passing vast amounts of sensor data. Finally, the bidirectional long short-term memory (BiLSTM) in FL-PMI classifies the data for various processes associated with the SHC. The simulation results proved the efficiency of FL-PMI, with 99.67% accuracy scores, minimized memory usage and computational costs, and reduced transmission data by 36.73%.

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  • 4.
    Awais, Muhammad
    et al.
    Fudan University, China.
    Ghayvat, Hemant
    University of Denmark, Denmark.
    Krishnan Pandarathodiyil, Anitha
    SEGi University, Malaysia.
    Nabillah Ghani, Wan Maria
    University of Malaya, Malaysia.
    Ramanathan, Anand
    University of Malaya, Malaysia.
    Pandya, Sharnil
    Symbiosis International (Deemed) University, India.
    Walter, Nicolas
    Universiti Teknologi PETRONAS, Malaysia.
    Saad, Mohamad Naufal
    Universiti Teknologi PETRONAS, Malaysia.
    Zain, Rosnah Binti
    University of Malaya, Malaysia; MAHSA University, Malaysia.
    Faye, Ibrahima
    Universiti Teknologi PETRONAS, Malaysia.
    Healthcare Professional in the Loop (HPIL): Classification of Standard and Oral Cancer-Causing Anomalous Regions of Oral Cavity Using Textural Analysis Technique in Autofluorescence Imaging2020In: Sensors, E-ISSN 1424-8220, Vol. 20, no 20, article id 5780Article in journal (Refereed)
    Abstract [en]

    Oral mucosal lesions (OML) and oral potentially malignant disorders (OPMDs) have been identified as having the potential to transform into oral squamous cell carcinoma (OSCC). This research focuses on the human-in-the-loop-system named Healthcare Professionals in the Loop (HPIL) to support diagnosis through an advanced machine learning procedure. HPIL is a novel system approach based on the textural pattern of OML and OPMDs (anomalous regions) to differentiate them from standard regions of the oral cavity by using autofluorescence imaging. An innovative method based on pre-processing, e.g., the Deriche–Canny edge detector and circular Hough transform (CHT); a post-processing textural analysis approach using the gray-level co-occurrence matrix (GLCM); and a feature selection algorithm (linear discriminant analysis (LDA)), followed by k-nearest neighbor (KNN) to classify OPMDs and the standard region, is proposed in this paper. The accuracy, sensitivity, and specificity in differentiating between standard and anomalous regions of the oral cavity are 83%, 85%, and 84%, respectively. The performance evaluation was plotted through the receiver operating characteristics of periodontist diagnosis with the HPIL system and without the system. This method of classifying OML and OPMD areas may help the dental specialist to identify anomalous regions for performing their biopsies more efficiently to predict the histological diagnosis of epithelial dysplasia.

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  • 5.
    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, E-ISSN 1944-3277, Vol. 10, article id 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.

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  • 6.
    Buetti-Dinh, Antoine
    USI, Switzerland .
    Gene Regulation by Numbers: Steady-State and Equilibrium Binding Applied to Gene Regulation Systems.2012Doctoral thesis, monograph (Other academic)
  • 7.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Dethlefsen, Olga
    Stockholm University.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Dopson, Mark
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Transcriptomic analysis reveals how a lack of potassium ions increases Sulfolobus acidocaldarius sensitivity to pH changes2016In: Microbiology, ISSN 1350-0872, E-ISSN 1465-2080, Vol. 162, no 8, p. 1422-1434Article in journal (Refereed)
    Abstract [en]

    Extremely acidophilic microorganisms (optimum growth pH of ≤3) maintain a near neutral cytoplasmic pH via several homeostatic mechanisms, including an inside positive membrane potential created by potassium ions. Transcriptomic responses to pH stress in the thermoacidophilic archaeon, Sulfolobus acidocaldarius were investigated by growing cells without added sodium and/or potassium ions at both optimal and sub-optimal pH. Culturing the cells in the absence of added sodium or potassium ions resulted in a reduced growth rate compared to full-salt conditions as well as 43 and 75 significantly different RNA transcript ratios, respectively. Differentially expressed RNA transcripts during growth in the absence of added sodium ions included genes coding for permeases, a sodium/proline transporter and electron transport proteins. In contrast, culturing without added potassium ions resulted in higher RNA transcripts for similar genes as a lack of sodium ions plus genes related to spermidine that has a general role in response to stress and a decarboxylase that potentially consumes protons. The greatest RNA transcript response occurred when S. acidocaldarius cells were grown in the absence of potassium and/or sodium at a sub-optimal pH. These adaptations included those listed above plus osmoregulated glucans and mechanosensitive channels that have previously been shown to respond to osmotic stress. In addition, data analyses revealed two co-expressed IclR family transcriptional regulator genes with a previously unknown role in the S. acidocaldarius pH stress response. Our study provides additional evidence towards the importance of potassium in acidophile growth at acidic pH.

  • 8.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Università della Svizzera Italiana, Italy;Swiss Institute of Bioinformatics, Switzerland.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Computer simulations of the signalling network in FLT3+-acute myeloid leukaemia: indications for an optimal dosage of inhibitors against FLT3 and CDK62018In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 19, p. 1-13, article id 155Article in journal (Refereed)
    Abstract [en]

    Background

    Mutations in the FMS-like tyrosine kinase 3 (FLT3) are associated with uncontrolled cellular functions that contribute to the development of acute myeloid leukaemia (AML). We performed computer simulations of the FLT3-dependent signalling network in order to study the pathways that are involved in AML development and resistance to targeted therapies.

    Results

    Analysis of the simulations revealed the presence of alternative pathways through phosphoinositide 3 kinase (PI3K) and SH2-containing sequence proteins (SHC), that could overcome inhibition of FLT3. Inhibition of cyclin dependent kinase 6 (CDK6), a related molecular target, was also tested in the simulation but was not found to yield sufficient benefits alone.

    Conclusions

    The PI3K pathway provided a basis for resistance to treatments. Alternative signalling pathways could not, however, restore cancer growth signals (proliferation and loss of apoptosis) to the same levels as prior to treatment, which may explain why FLT3 resistance mutations are the most common resistance mechanism. Finally, sensitivity analysis suggested the existence of optimal doses of FLT3 and CDK6 inhibitors in terms of efficacy and toxicity.

  • 9.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Università della Svizzera italiana, Switzerland;Swiss Institute of Bioinformatics, Switzerland.
    Herold, Malte
    University of Luxembourg, Luxembourg.
    Christel, Stephan
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    El Hajjami, Mohamed
    QNLM, China.
    Delogu, Francesco
    Norwegian University of Life Sciences, Norway.
    Ilie, Olga
    Università della Svizzera italiana, Switzerland;Swiss Institute of Bioinformatics, Switzerland.
    Bellenberg, Sören
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Wilmes, Paul
    University of Luxembourg, Luxembourg.
    Poetsch, Ansgar
    Ruhr University Bochum, Germany;QNLM, China;Ocean University of China, China.
    Sand, Wolfgang
    University Duisburg-Essen, Germany;Donghua University, China;Mining Academy and Technical University Freiberg, Germany.
    Vera, Mario
    Pontificia Universidad Católica de Chile, Chile.
    Pivkin, Igor V.
    Università della Svizzera italiana, Switzerland;Swiss Institute of Bioinformatics, Switzerland.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Linnaeus University, Linnaeus Knowledge Environments, Water.
    Dopson, Mark
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations2020In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 21, no 1, p. 1-15, article id 23Article in journal (Refereed)
    Abstract [en]

    Background: Network inference is an important aim of systems biology. It enables the transformation of OMICs datasets into biological knowledge. It consists of reverse engineering gene regulatory networks from OMICs data, such as RNAseq or mass spectrometry-based proteomics data, through computational methods. This approach allows to identify signalling pathways involved in specific biological functions. The ability to infer causality in gene regulatory networks, in addition to correlation, is crucial for several modelling approaches and allows targeted control in biotechnology applications. Methods: We performed simulations according to the approximate Bayesian computation method, where the core model consisted of a steady-state simulation algorithm used to study gene regulatory networks in systems for which a limited level of details is available. The simulations outcome was compared to experimentally measured transcriptomics and proteomics data through approximate Bayesian computation. Results: The structure of small gene regulatory networks responsible for the regulation of biological functions involved in biomining were inferred from multi OMICs data of mixed bacterial cultures. Several causal inter- and intraspecies interactions were inferred between genes coding for proteins involved in the biomining process, such as heavy metal transport, DNA damage, replication and repair, and membrane biogenesis. The method also provided indications for the role of several uncharacterized proteins by the inferred connection in their network context. Conclusions: The combination of fast algorithms with high-performance computing allowed the simulation of a multitude of gene regulatory networks and their comparison to experimentally measured OMICs data through approximate Bayesian computation, enabling the probabilistic inference of causality in gene regulatory networks of a multispecies bacterial system involved in biomining without need of single-cell or multiple perturbation experiments. This information can be used to influence biological functions and control specific processes in biotechnology applications.

  • 10.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Univ Svizzera Italiana, Switzerland;Swiss Inst Bioinformat, Switzerland.
    Jensen, Rebecca
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Univ Svizzera Italiana, Switzerland;Swiss Inst Bioinformat, Switzerland.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy2018In: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 18, no 1, p. 1-8, article id 569Article in journal (Refereed)
    Abstract [en]

    Background: The smoothened (SMO) receptor is an essential component of the Sonic hedgehog (SHH) signalling, which is associated with the development of skin basal cell carcinoma (BCC). SMO inhibitors are indicated for BCC patients when surgical treatment or radiation therapy are not possible. Unfortunately, SMO inhibitors are not always well tolerated due to severe side effects, and their therapeutical success is limited by resistance mutations. Methods: We investigated how common are resistance-causing mutations in two genomic databases which are not linked to BCC or other cancers, namely 1000 Genomes and ExAC. To examine the potential for combination therapy or other treatments, we further performed knowledge-based simulations of SHH signalling, in the presence or absence of SMO and PI3K/Akt inhibitors. Results: The database analysis revealed that of 18 known mutations associated with Vismodegib-resistance, three were identified in the databases. Treatment of individuals carrying such mutations is thus liable to fail a priori. Analysis of the simulations suggested that a combined inhibition of SMO and the PI3K/Akt signalling pathway may provide an effective reduction in tumour proliferation. However, the inhibition dosage of SMO and PI3K/Akt depended on the activity of phosphodiesterases (PDEs). Under high PDEs activities, SMO became the most important control node of the network. By applying PDEs inhibition, the control potential of SMO decreased and P13K appeared as a significant factor in controlling tumour proliferation. Conclusions: Our systems biology approach employs knowledge-based computer simulations to help interpret the large amount of data available in public databases, and provides application-oriented solutions for improved cancer resistance treatments.

  • 11.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Univ Svizzera Italiana, Switzerland;Swiss Inst Bioinformat, Switzerland.
    O'Hare, Thomas
    Univ Utah, USA;Huntsman Canc Inst, USA.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Sensitivity Analysis of the NPM-ALK Signalling Network Reveals Important Pathways for Anaplastic Large Cell Lymphoma Combination Therapy2016In: PLOS ONE, E-ISSN 1932-6203, Vol. 11, no 9, article id e0163011Article in journal (Refereed)
    Abstract [en]

    A large subset of anaplastic large cell lymphoma (ALCL) patients harbour a somatic aberration in which anaplastic lymphoma kinase (ALK) is fused to nucleophosmin (NPM) resulting in a constitutively active signalling fusion protein, NPM-ALK. We computationally simulated the signalling network which mediates pathological cell survival and proliferation through NPM-ALK to identify therapeutically targetable nodes through which it may be possible to regain control of the tumourigenic process. The simulations reveal the predominant role of the VAV1-CDC42 (cell division control protein 42) pathway in NPM-ALK-driven cellular proliferation and of the Ras / mitogen-activated ERK kinase (MEK) / extracellular signal-regulated kinase (ERK) cascade in controlling cell survival. Our results also highlight the importance of a group of interleukins together with the Janus kinase 3 (JAK3) / signal transducer and activator of transcription 3 (STAT3) signalling in the development of NPM-ALK derived ALCL. Depending on the activity of JAK3 and STAT3, the system may also be sensitive to activation of protein tyrosine phosphatase-1 (SHP1), which has an inhibitory effect on cell survival and proliferation. The identification of signalling pathways active in tumourigenic processes is of fundamental importance for effective therapies. The prediction of alternative pathways that circumvent classical therapeutic targets opens the way to preventive approaches for countering the emergence of cancer resistance.

  • 12.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Univ Svizzera Italiana, Switzerland.
    Pivkin, Igor
    Univ Svizzera Italiana, Switzerland ;Swiss Inst Bioinformat, Switzerland.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    S100A4 and its role in metastasis – computational integration of data on biological networks2015In: Molecular Biosystems, ISSN 1742-206X, E-ISSN 1742-2051, Vol. 11, p. 2238-2246Article in journal (Refereed)
    Abstract [en]

    Characterising signal transduction networks is fundamental to our understanding of biology. However, redundancy and different types of feedback mechanisms make it difficult to understand how variations of the network components contribute to a biological process. In silico modelling of signalling interactions therefore becomes increasingly useful for the development of successful therapeutic approaches. Unfortunately, quantitative information cannot be obtained for all of the proteins or complexes that comprise the network, which limits the usability of computational models. We developed a flexible computational framework for the analysis of biological signalling networks. We demonstrate our approach by studying the mechanism of metastasis promotion by the S100A4 protein, and suggest therapeutic strategies. The advantage of the proposed method is that only limited information (interaction type between species) is required to set up a steady-state network model. This permits a straightforward integration of experimental information where the lack of details are compensated by efficient sampling of the parameter space. We investigated regulatory properties of the S100A4 network and the role of different key components. The results show that S100A4 enhances the activity of matrix metalloproteinases (MMPs), causing higher cell dissociation. Moreover, it leads to an increased stability of the pathological state. Thus, avoiding metastasis in S100A4-expressing tumours requires multiple target inhibition. Moreover, the analysis could explain the previous failure of MMP inhibitors in clinical trials. Finally, our method is applicable to a wide range of biological questions that can be represented as directional networks.

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  • 13.
    Buetti-Dinh, Antoine
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. Univ Svizzera Italiana, Switzerland.
    Pivkin, Igor V.
    Univ Svizzera Italiana, Switzerland ; Swiss Inst Bioinformat, Switzerland.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    S100A4 and its role in metastasis: simulations of knockout and amplification of epithelial growth factor receptor and matrix metalloproteinases2015In: Molecular Biosystems, ISSN 1742-206X, E-ISSN 1742-2051, Vol. 11, no 8, p. 2247-2254Article in journal (Refereed)
    Abstract [en]

    The calcium-binding signalling protein S100A4 enhances metastasis in a variety of cancers. Despite a wealth of data available, the molecular mechanism by which S100A4 drives metastasis is unknown. Integration of the current knowledge defies straightforward intuitive interpretation and requires computer-aided approaches to represent the complexity emerging from cross-regulating species. Here we carried out a systematic sensitivity analysis of the S100A4 signalling network in order to identify key control parameters for efficient therapeutic intervention. Our approach only requires limited details of the molecular interactions and permits a straightforward integration of the available experimental information. By integrating the available knowledge, we investigated the effects of combined inhibition of signalling pathways. Through selective knockout or inhibition of the network components, we show that the interaction between epidermal growth factor receptor (EGFR) and S100A4 modulates the sensitivity of angiogenesis development to matrix metalloproteinases (MMPs) activity. We also show that, in cells that express high EGFR, MMP inhibitors are not expected to be useful in tumours if high activity of S100A4 is present.

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  • 14.
    Buetti-Dinh, Antoine
    et al.
    University of Zurich, Switzerland.
    Ungricht, Rosemarie
    University of Zurich, Switzerland.
    Kelemen, János Z.
    University of Zurich, Switzerland.
    Shetty, Chetak
    University of Zurich, Switzerland.
    Ratna, Prasuna
    University of Zurich, Switzerland.
    Becskei, Attila
    University of Zurich, Switzerland.
    Control and signal processing by transcriptional interference2009In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 5, p. Article ID: 300-Article in journal (Refereed)
    Abstract [en]

    A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears the hallmarks of competitive inhibition, whereas a downstream activator inhibits gene expression non-competitively. When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation. Equilibrium and non-equilibrium models of transcription shed light on the mechanism by which interference converts signals, and reveals that self-antagonism of activators imitates the behavior of feed-forward loops. Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal. The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.

  • 15.
    Capo, Eric
    et al.
    CSIC, Spain;Swedish University of Agricultural Sciences, Sweden.
    Peterson, Benjamin D.
    Univ Wisconsin, USA.
    Kim, Minjae
    Colorado State Univ, USA.
    Jones, Daniel S.
    New Mexico Inst Min & Technol, USA;Natl Cave & Karst Res Inst, USA.
    Acinas, Silvia G.
    CSIC, Spain.
    Amyot, Marc
    Univ Montreal, Canada.
    Bertilsson, Stefan
    Swedish University of Agricultural Sciences, Sweden.
    Bjoern, Erik
    Umeå University, Sweden.
    Buck, Moritz
    Swedish University of Agricultural Sciences, Sweden.
    Cosio, Claudia
    Univ Reims, France.
    Elias, Dwayne A.
    Elias Consulting LLC, USA.
    Gilmour, Cynthia
    Smithsonian Environm Res Ctr, USA.
    Goni-Urriza, Marisol
    Univ Pau & Pays Adour, France.
    Gu, Baohua
    Oak Ridge Natl Lab, USA.
    Lin, Heyu
    Univ Melbourne, Australia.
    Liu, Yu-Rong
    Huazhong Agr Univ, China.
    McMahon, Katherine
    Univ Wisconsin, USA.
    Moreau, John W.
    Univ Glasgow, UK.
    Pinhassi, Jarone
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Linnaeus University, Linnaeus Knowledge Environments, Water.
    Podar, Mircea
    Oak Ridge Natl Lab, USA.
    Puente-Sanchez, Fernando
    Swedish University of Agricultural Sciences, Sweden.
    Sanchez, Pablo
    CSIC, Spain.
    Storck, Veronika
    Univ Montreal, Canada.
    Tada, Yuya
    Natl Inst Minamata Dis, Japan.
    Vigneron, Adrien
    Univ Pau & Pays Adour, France.
    Walsh, David A.
    Concordia Univ, Canada.
    Vandewalle-Capo, Marine
    Swedish University of Agricultural Sciences, Sweden.
    Bravo, Andrea G.
    CSIC, Spain.
    Gionfriddo, Caitlin M.
    Smithsonian Environm Res Ctr, USA.
    A consensus protocol for the recovery of mercury methylation genes from metagenomes2023In: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 23, no 1, p. 190-204Article in journal (Refereed)
    Abstract [en]

    Mercury (Hg) methylation genes (hgcAB) mediate the formation of the toxic methylmercury and have been identified from diverse environments, including freshwater and marine ecosystems, Arctic permafrost, forest and paddy soils, coal-ash amended sediments, chlor-alkali plants discharges and geothermal springs. Here we present the first attempt at a standardized protocol for the detection, identification and quantification of hgc genes from metagenomes. Our Hg-cycling microorganisms in aquatic and terrestrial ecosystems (Hg-MATE) database, a catalogue of hgc genes, provides the most accurate information to date on the taxonomic identity and functional/metabolic attributes of microorganisms responsible for Hg methylation in the environment. Furthermore, we introduce "marky-coco", a ready-to-use bioinformatic pipeline based on de novo single-metagenome assembly, for easy and accurate characterization of hgc genes from environmental samples. We compared the recovery of hgc genes from environmental metagenomes using the marky-coco pipeline with an approach based on coassembly of multiple metagenomes. Our data show similar efficiency in both approaches for most environments except those with high diversity (i.e., paddy soils) for which a coassembly approach was preferred. Finally, we discuss the definition of true hgc genes and methods to normalize hgc gene counts from metagenomes.

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  • 16.
    Chavan, Swapnil
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Towards new computational tools for predicting toxicity2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The toxicological screening of the numerous chemicals that we are exposed to requires significant cost and the use of animals. Accordingly, more efficient methods for the evaluation of toxicity are required to reduce cost and the number of animals used. Computational strategies have the potential to reduce both the cost and the use of animal testing in toxicity screening. The ultimate goal of this thesis is to develop computational models for the prediction of toxicological endpoints that can serve as an alternative to animal testing. In Paper I, an attempt was made to construct a global quantitative structure-activity relationship (QSAR)model for the acute toxicity endpoint (LD50 values) using the Munro database that represents a broad chemical landscape. Such a model could be used for acute toxicity screening of chemicals of diverse structures. Paper II focuses on the use of acute toxicity data to support the prediction of chronic toxicity. The results of this study suggest that for related chemicals having acute toxicities within a similar range, their lowest observed effect levels (LOELs) can be used in read-across strategies to fill gaps in chronic toxicity data. In Paper III a k-nearest neighbor (k-NN) classification model was developed to predict human ether-a-go-go related gene (hERG)-derived toxicity. The results suggest that the model has potential for use in identifying compounds with hERG-liabilities, e.g. in drug development.

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    Swapnil Chavan, Doctoral Thesis (Kappa)
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  • 17.
    Chieh, Hsu
    et al.
    University of Basel, Switzerland.
    Scherrer, S
    University of Basel, Switzerland.
    Buetti-Dinh, Antoine
    University of Basel, Switzerland.
    Ratna, P
    University of Basel, Switzerland.
    Pizzolato, J
    University of Basel, Switzerland.
    Jaquet, V
    University of Basel, Switzerland.
    Becskei, A
    University of Basel, Switzerland.
    Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution.2012In: Nature Communications, E-ISSN 2041-1723, Vol. 3, p. Article ID: 682-Article in journal (Refereed)
    Abstract [en]

    During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit.

  • 18.
    Friedman, Ran
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Boye, Kjetil
    Flatmark, Kjersti
    Molecular modelling and simulations in cancer research2013In: Biochimica et Biophysica Acta. CR. Reviews on Cancer, ISSN 0304-419X, E-ISSN 1879-2561, Vol. 1836, no 1, p. 1-14Article, review/survey (Refereed)
    Abstract [en]

    The complexity of cancer and the vast amount of experimental data available have made computer-aided approaches necessary. Biomolecular modelling techniques are becoming increasingly easier to use, whereas hardware and software are becoming better and cheaper. Cross-talk between theoretical and experimental scientists dealing with cancer-research from a molecular approach, however, is still uncommon. This is in contrast to other fields, such as amyloid-related diseases, where molecular modelling studies are widely acknowledged. The aim of this review paper is therefore to expose some of the more common approaches in molecular modelling to cancer scientists in simple terms, illustrating success stories while also revealing the limitations of computational studies at the molecular level.

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  • 19.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Aleksakhin, Vladyslav
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Schreiber, Falk
    Martin-Luther University.
    Visualization of Mappings between the Gene Ontology and Cluster Trees2012In: Proceedings of the SPIE 2012 Conference on Visualization and Data Analysis (VDA '12) / [ed] Pak Chung Wong, David L. Kao, Ming C. Hao, Chaomei Chen, Robert Kosara, Mark A. Livingston, Jinah Park, and Ian Roberts, SPIE - International Society for Optical Engineering, 2012Conference paper (Refereed)
    Abstract [en]

    Ontologies and hierarchical clustering are both important tools in biology and medicine to study high-throughput data such as transcriptomics and metabolomics data. Enrichment of ontology terms in the data is used to identify statistically overrepresented ontology terms, giving insight into relevant biological processes or functional modules. Hierarchical clustering is a standard method to analyze and visualize data to find relatively homogeneous clusters of experimental data points. Both methods support the analysis of the same data set, but are usually considered independently. However, often a combined view is desired: visualizing a large data set in the context of an ontology under consideration of a clustering of the data. This paper proposes a new visualization method for this task.

  • 20.
    Kerren, Andreas
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Schreiber, Falk
    Martin Luther University .
    Network Visualization for Integrative Bioinformatics2014In: Approaches in Integrative Bioinformatics: Towards the Virtual Cell / [ed] Ming Chen and Ralf Hofestädt, Berlin Heidelberg: Springer, 2014, p. 173-202Chapter in book (Refereed)
    Abstract [en]

    Approaches to investigate biological processes have been of strong interest in the past few years and are the focus of several research areas like systems biology. Biological networks as representations of such processes are crucial for an extensive understanding of living beings. Due to their size and complexity, their growth and continuous change, as well as their compilation from databases on demand, researchers very often request novel network visualization, interaction and exploration techniques. In this chapter, we first provide background information that is needed for the interactive visual analysis of various biological networks. Fields such as (information) visualization, visual analytics and automatic layout of networks are highlighted and illustrated by a number of examples. Then, the state of the art in network visualization for the life sciences is presented together with a discussion of standards for the graphical representation of cellular networks and biological processes.

  • 21.
    Kerren, Andreas
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Schreiber, Falk
    Monash Univ, Australia.
    Why Integrate InfoVis and SciVis?: An Example from Systems Biology2014In: IEEE Computer Graphics and Applications, ISSN 0272-1716, E-ISSN 1558-1756, Vol. 34, no 6, p. 69-73Article in journal (Other academic)
    Abstract [en]

    The more-or-less artificial barrier between information visualization and scientific visualization hinders knowledge discovery. Having an integrated view of many aspects of the target data, including a seamlessly interwoven visual display of structural abstract data and 3D spatial information, could lead to new discoveries, insights, and scientific questions. Such a view also could reduce the user’s cognitive load—that is, reduce the effort the user expends when comparing views.

  • 22.
    Kirdok, Emrah
    et al.
    Mersin Univ, Turkiye.
    Kashuba, Natalija
    Uppsala University, Sweden.
    Damlien, Hege
    Univ Oslo, Norway.
    Manninen, Mikael A.
    Univ Helsinki, Finland.
    Nordqvist, Bengt
    Foundation War-Booty Site Finnestorp, Sweden.
    Kjellström, Anna
    Stockholm University, Sweden.
    Jakobsson, Mattias
    Uppsala University, Sweden.
    Lindberg, A. Michael
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Storå, Jan
    Stockholm University, Sweden.
    Persson, Per
    Univ Oslo, Norway.
    Andersson, Björn
    Karolinska Insitutet, Sweden.
    Aravena, Andres
    Istanbul Univ, Turkiye.
    Götherström, Anders
    Centre for Palaeogenetics, Sweden;Stockholm University, Sweden.
    Metagenomic analysis of Mesolithic chewed pitch reveals poor oral health among stone age individuals2024In: Scientific Reports, E-ISSN 2045-2322, Vol. 13, no 1, article id 22125Article in journal (Refereed)
    Abstract [en]

    Prehistoric chewed pitch has proven to be a useful source of ancient DNA, both from humans and their microbiomes. Here we present the metagenomic analysis of three pieces of chewed pitch from Huseby Klev, Sweden, that were dated to 9,890-9,540 before present. The metagenomic profile exposes a Mesolithic oral microbiome that includes opportunistic oral pathogens. We compared the data with healthy and dysbiotic microbiome datasets and we identified increased abundance of periodontitis-associated microbes. In addition, trained machine learning models predicted dysbiosis with 70-80% probability. Moreover, we identified DNA sequences from eukaryotic species such as red fox, hazelnut, red deer and apple. Our results indicate a case of poor oral health during the Scandinavian Mesolithic, and show that pitch pieces have the potential to provide information on material use, diet and oral health.

  • 23.
    Lindström, Jonathan
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Modelling the evolution of treatment-induced resistance in Ph+ leukaemias2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Targeted therapies are a mainstay of modern cancer treatments. Rather than harming rapidly dividing cells in general, targeted therapies work by directly interfering with oncogenic molecular pathways present in a tumour. Consequently, a targeted therapy typically has less severe side effects. However, specificity comes at a price as comparatively small changes to the target can render the treatment ineffective. Much like the natural selection among plants and animals, individual cancer cells compete with one another for space and resources. Hence, if a single cancer cell acquires a resistance adaptation, the forces of evolution can turn that advantage in a single cell into an untreatable resistant cancer.

    This thesis is principally concerned with chronic myeloid leukaemia (CML), characterized by a chromosomal translocation called the Philadelphia chromosome which creates the constitutively active tyrosine kinase Bcr-Abl1. The discovery of tyrosine kinase inhibitors (TKIs) targeting Bcr-Abl1 greatly improved treatment outcomes. Eventually however, resistance emerges. An important mechanism in CML is mutations in the kinase domain of Bcr-Abl1 that affect how well the drugs bind. A number of drugs have been developed that target the mutated kinase to varying degrees, but it is still desirable to prevent drug resistance from occurring in the first place, as the accumulation of multiple mutations is almost certain to create untreatable resistance.

    The fitness effects of a drug resistance adaptation depend on the drug treatment, so it may be possible to alter the fitness landscape by modifying the treatment. This work examines different approaches, mainly in CML, to delay or prevent the onset of resistance through modifying the treatment protocol.

    Periodically switching between different TKIs, i.e. drug rotations, was shown through modelling to increase the expected time to resistance and seems to have some protective benefits in vitro. Also apparently promising were drug combinations involving a novel inhibitor asciminib, currently in phase III trials, which can reduce overall drug burden while also being seemingly effective against known resistance mutations. Finally, a model of the interaction between resistance mutations and less potent alternate resistance mechanisms revealed how a drug holiday may have resensitizing, or even beneficial effects.

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    Doctoral Dissertation (Comprehensive Summary)
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  • 24.
    Lindström, Jonathan
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    de Wijn, Astrid S.
    Norwegian University of Science and Technology, Norway.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Modelling resistance in leukaemia mediated by mutations and alternate mechanisms – their interactions and treatment-free periods (drug holidays).Manuscript (preprint) (Other academic)
  • 25.
    Lindström, Jonathan
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    de Wijn, Astrid S.
    Norwegian University of Science and Technology, Norway.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Stochastic modelling of tyrosine kinase inhibitor rotation therapy in chronic myeloid leukaemia2019In: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 19, p. 1-13, article id 508Article in journal (Refereed)
    Abstract [en]

    BackgroundResistance towards targeted cancer treatments caused by single nucleotide variations is a major issue in many malignancies. Currently, there are a number of available drugs for chronic myeloid leukaemia (CML), which are overcome by different sets of mutations. The main aim of this study was to explore if it can be possible to exploit this and create a treatment protocol that outperforms each drug on its own.MethodsWe present a computer program to test different treatment protocols against CML, based on available resistance mutation growth data. The evolution of a relatively stable pool of cancer stem cells is modelled as a stochastic process, with the growth of cells expressing a tumourigenic protein (here, Abl1) and any emerging mutants determined principally by the drugs used in the therapy.ResultsThere can be some benefit to Bosutinib-Ponatinib rotation therapy even if the mutation status is unknown, whereas Imatinib-Nilotinib rotation is unlikely to improve the outcomes. Furthermore, an interplay between growth inhibition and selection effects generates a non-linear relationship between drug doses and the risk of developing resistance.ConclusionsDrug rotation therapy might be able to delay the onset of resistance in CML patients without costly ongoing observation of mutation status. Moreover, the simulations give credence to the suggestion that lower drug concentrations may achieve better results following major molecular response in CML.

  • 26.
    Lindström, Jonathan
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Inferring time-dependent growth rates in cell cultures undergoing adaptationManuscript (preprint) (Other academic)
  • 27.
    Lindström, Jonathan
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Friedman, Ran
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    The effects of combination treatments on drug resistance in chronic myeloid leukaemia: an evaluation of the tyrosine kinase inhibitors axitinib and asciminib2020In: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 20, no 1, article id 397Article in journal (Refereed)
    Abstract [en]

    Background: Chronic myeloid leukaemia is in principle a treatable malignancy but drug resistance is lowering survival. Recent drug discoveries have opened up new options for drug combinations, which is a concept used in other areas for preventing drug resistance. Two of these are (I) Axitinib, which inhibits the T315I mutation of BCR-ABL1, a main source of drug resistance, and (II) Asciminib, which has been developed as an allosteric BCR-ABL1 inhibitor, targeting an entirely different binding site, and as such does not compete for binding with other drugs. These drugs offer new treatment options. Methods: We measured the proliferation of KCL-22 cells exposed to imatinib–dasatinib, imatinib–asciminib and dasatinib–asciminib combinations and calculated combination index graphs for each case. Moreover, using the median–effect equation we calculated how much axitinib can reduce the growth advantage of T315I mutant clones in combination with available drugs. In addition, we calculated how much the total drug burden could be reduced by combinations using asciminib and other drugs, and evaluated which mutations such combinations might be sensitive to. Results: Asciminib had synergistic interactions with imatinib or dasatinib in KCL-22 cells at high degrees of inhibition. Interestingly, some antagonism between asciminib and the other drugs was present at lower degrees on inhibition. Simulations revealed that asciminib may allow for dose reductions, and its complementary resistance profile could reduce the risk of mutation based resistance. Axitinib, however, had only a minor effect on T315I growth advantage. Conclusions: Given how asciminib combinations were synergistic in vitro, our modelling suggests that drug combinations involving asciminib should allow for lower total drug doses, and may result in a reduced spectrum of observed resistance mutations. On the other hand, a combination involving axitinib was not shown to be useful in countering drug resistance.

  • 28.
    Nilsson, R. Henrik
    et al.
    University of Gothenburg, Sweden.
    Andersson, Anders F.
    KTH Royal instute of technology, Sweden.
    Bissett, Andrew
    CSIRO O&A, Australia.
    Finstad, Anders G.
    Norwegian University of Science and Technology, Norway.
    Fossøy, Frode
    Norwegian institute for nature research (NINA), Norway.
    Grosjean, Marie
    Global Biodiversity Information Facility (GBIF), Denmark.
    Hope, Michael
    CSIRO National Collections & Marine Infrastructure, Australia.
    Jeppesen, Thomas S.
    Global Biodiversity Information Facility (GBIF), Denmark.
    Kõljalg, Urmas
    University of Tartu, Estonia.
    Lundin, Daniel
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Prager, Maria
    Stockholm University, Sweden, Karolinska Institutet, Sweden.
    Suominen, Saara
    UNESCO Intergovernmental Oceanographic Commission (IOC), Belgium.
    Svenningsen, Cecilie S.
    University of Copenhagen, Denmark.
    Schigel, Dmitry
    Global Biodiversity Information Facility (GBIF), Denmark.
    Introducing guidelines for publishing DNA-derived occurrence data through biodiversity data platforms2022In: Metabarcoding and Metagenomics, E-ISSN 2534-9708, Vol. 6, p. 239-244Article in journal (Refereed)
    Abstract [en]

    DNA sequencing efforts of environmental and other biological samples disclose unprecedented and largely untapped opportunities for advances in the taxonomy, ecology, and geographical distributions of our living world. To realise this potential, DNA-derived occurrence data (notably sequences with dates and coordinates) – much like traditional specimens and observations – need to be discoverable and interpretable through biodiversity data platforms. The Global Biodiversity Information Facility (GBIF) recently headed a community effort to assemble a set of guidelines for publishing DNA-derived data. These guidelines target the principles and approaches of exposing DNA-derived occurrence data in the context of broader biodiversity data. They cover a choice of terms using a controlled vocabulary, common pitfalls, and good practices, without going into platform-specific details. Our hope is that they will benefit anyone interested in better exposure of DNA-derived occurrence data through general biodiversity data platforms, including national biodiversity portals. This paper provides a brief rationale and an overview of the guidelines, an up-to-date version of which is maintained at https://doi.org/10.35035/doc-vf1a-nr22. User feedback and interaction are encouraged as new techniques and best practices emerge.

  • 29.
    Orozovic, Goran
    Linnaeus University, Faculty of Science and Engineering, School of Natural Sciences.
    Resistance to neuraminidase inhibitors in influenza A virus isolated from mallards2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Influenza A virus belongs to the Orothomyxoviridae family of viruses and is one of the most common pathogens that cause infections of the respiratory tract. The aim of this thesis was to investigate if neuraminidase inhibitor (NAI) Tamiflu® (oseltamivir, OC) and Relenza® (zanamivir, ZA) - related resistance mutations exist in the neuraminidase (NA) gene of viruses collected from wild birds.

    A new set of degenerate primers was designed for the sequencing procedure, which resulted in a protocol that reduced time and costs of NA sequencing. This protocol was employed for subtyping of 120 NA genes (i.e. influenza viruses). Altogether, 230 NA sequences from avian influenza viruses originating from wild mallards (Ottenby, Sweden) were scanned for NAI-related mutations together with 5,490 avian, 379 swine and 122 environmental NA sequences from the NCBI dataset. The screening showed a distinction between the numbers of mutants found in avian virus sequences derived from NCBI (2.4%) as compared to virus sequences form mallards (6.5%). This is the first report of NAI resistance mutations in viruses isolated from wild birds.

    The mutants carrying NAI resistance-related and resistance-unrelated mutations were screened using NA inhibition assay (NAIA) with ZA and OC inhibitors. The majority of mutations assayed showed IC50 values indicating an inhibitor sensitive phenotype. One H12N3 mutant showed a cross-resistant phenotype, i.e. insensitive to both ZA and OC treatment. Protein structure homology-modeling indicated that this cross-resistance might be associated to a D151K mutation, possibly supported by changes in NA residue 149, 150, 152 and 153. In addition, an OC resistance-related emergence of H274Y mutants was revealed in an experimental set up where mallard ducks, subjected to different concentrations of OC ( 0.28, 3.5 and 280 nM)  in their water pool, were infected with avian H1N1 virus.

    In conclusion, this thesis provides new insights into the field of NAI resistance in avian influenza virus as well as indicating the evolutionary forces modern drug design has to confront. This thesis also emphasizes the importance of a continuous search for new means of protecting the human population from this potentially devastating pathogen. 

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  • 30.
    Palma, Daniela
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Analysis of metatranscriptomes from an acidophilic electricity generating community treating acidic mining wastewaters2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Human ́s constant need for metals requires unsustainable mining and refining of metalore. As a result, highly contaminated wastewaters are discharged in the environmentcompromising the nearby habitat together with all its life forms. Microbial fuel cells arebioelectrochemical systems (BES’s) that use microorganisms to convert organic andinorganic matter, producing electricity as the final product. This technology has shownto have great potential for application for bioremediation of wastewaters. This thesisdescribes the gene expression and the taxonomical abundance of an acidophilic,electricity generating community that was used to treat mining wastewaters in amicrobial fuel cell. A complete metatranscriptomics analysis has been performed onduplicate MFC anode acidophilic microbial community generating electricity frominorganic sulfur compounds (ISC) oxidation at extremely low pH. The analysis showsthat the most expressed genus is Ferroplasma-like, the genus Acidithiobacillus-like isfollowing along with Sulfobacillus-like and Thermoplasma-like. Some of the generaexpressed show behaviours never described before suggesting that potentially, newspecies have been selected. The reactions of the sulfur pathway are regulated mostly bytwo genera: Acidithiobacillus-like during the disproportionation of tetrathionate, andFerroplasma-like by expressing the hdr gene that catalyses the reaction from elementalsulfur to sulfite, the sulfite is then converted to sulfate. The hdr gene has not previouslybeen found in F. acidarmanus-like suggesting that the specie might have been selectedfor this trait. Acidithiobacillus-like genus has a bigger role for the energy conservationand the electron transport in the sample, however the data are not sufficient to point outwhich gene has the major role in the process. The CO2 fixation in the chamber wasconsiderably low as a result from a significant carboxysomes production, bacterialcompartiments involved in the carbon dioxide fixation. The transcripts abundanceregarding the metal resistance genes have shown low expression suggesting that thecells were not under stress. This result is indicated by the synthesis of a transcriptionalrepressor protein that had prevented a significant production of metal resistanceenzymes. Likewise, the pH homeostasis plot does not show vast transcripts abundances,indicating that the cells were thriving under conditions not far from the optimum.

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  • 31.
    Sachpazidou, Varvara
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Microbial community and activity during re-oxygenation of Baltic Sea “dead zone” sediments2017Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
  • 32.
    Salgado, Marco G.
    et al.
    Stockholm University, Sweden.
    van Velzen, Robin
    Wageningen Univ, Netherlands.
    Nguyen, Thanh Van
    Stockholm University, Sweden.
    Battenberg, Kai
    Univ Calif Davis, USA.
    Berry, Alison M.
    Univ Calif Davis, USA.
    Lundin, Daniel
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Stockholm University, Sweden.
    Pawlowski, Katharina
    Stockholm University, Sweden.
    Comparative Analysis of the Nodule Transcriptomes of Ceanothus thyrsiflorus (Rhamnaceae, Rosales) and Datisca glomerate (Datiscaceae, Cucurbitales)2018In: Frontiers in Plant Science, E-ISSN 1664-462X, Vol. 9, article id 1629Article in journal (Refereed)
    Abstract [en]

    Two types of nitrogen-fixing root nodule symbioses are known, rhizobial and actinorhizal symbioses. The latter involve plants of three orders, Fagales, Rosales, and Cucurbitales. To understand the diversity of plant symbiotic adaptation, we compared the nodule transcriptomes of Datisca glomerate (Datiscaceae, Cucurbitales) and Ceanothus thyrsiflorus (Rhamnaceae, Rosales); both species are nodulated by members of the uncultured Frankia Glade, cluster II. The analysis focused on various features. In both species, the expression of orthologs of legume Nod factor receptor genes was elevated in nodules compared to roots. Since arginine has been postulated as export form of fixed nitrogen from symbiotic Frankia in nodules of D. glomerate, the question was whether the nitrogen metabolism was similar in nodules of C. thyrsiflorus. Analysis of the expression levels of key genes encoding enzymes involved in arginine metabolism revealed up-regulation of arginine catabolism, but no up-regulation of arginine biosynthesis, in nodules compared to roots of D. glomerate, while arginine degradation was not upregulated in nodules of C. thyrsiflorus. This new information corroborated an arginine-based metabolic exchange between host and microsymbiont for D. glomerate, but not for C. thyrsiflorus. Oxygen protection systems for nitrogenase differ dramatically between both species. Analysis of the antioxidant system suggested that the system in the nodules of D. glomerate leads to greater oxidative stress than the one in the nodules of C. thyrsiflorus, while no differences were found for the defense against nitrosative stress. However, induction of nitrite reductase in nodules of C. thyrsiflorus indicated that here, nitrite produced from nitric oxide had to be detoxified. Additional shared features were identified: genes encoding enzymes involved in thiamine biosynthesis were found to be upregulated in the nodules of both species. Orthologous nodule-specific subtilisin-like proteases that have been linked to the infection process in actinorhizal Fagales, were also upregulated in the nodules of D. glomerate and C. thyrsiflorus. Nodule-specific defensin genes known from actinorhizal Fagales and Cucurbitales, were also found in C. thyrsiflorus. In summary, the results underline the variability of nodule metabolism in different groups of symbiotic plants while pointing at conserved features involved in the infection process.

  • 33.
    Seidel, Laura
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Broman, Elias
    Stockholm University, Sweden.
    Nilsson, Emelie
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Ståhle, Magnus
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Ketzer, João Marcelo
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Pérez Martínez, Clara
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Turner, Stephanie
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Hylander, Samuel
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Pinhassi, Jarone
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Forsman, Anders
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Dopson, Mark
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Climate change-related warming reduces thermal sensitivity and modifies metabolic activity of coastal benthic bacterial communities2023In: The ISME Journal, ISSN 1751-7362, E-ISSN 1751-7370, Vol. 17, p. 855-869Article in journal (Refereed)
    Abstract [en]

    Besides long-term average temperature increases, climate change is projected to result in a higher frequency of marine heatwaves. Coastal zones are some of the most productive and vulnerable ecosystems, with many stretches already under anthropogenic pressure. Microorganisms in coastal areas are central to marine energy and nutrient cycling and therefore, it is important to understand how climate change will alter these ecosystems. Using a long-term heated bay (warmed for 50 years) in comparison with an unaffected adjacent control bay and an experimental short-term thermal (9 days at 6–35 °C) incubation experiment, this study provides new insights into how coastal benthic water and surface sediment bacterial communities respond to temperature change. Benthic bacterial communities in the two bays reacted differently to temperature increases with productivity in the heated bay having a broader thermal tolerance compared with that in the control bay. Furthermore, the transcriptional analysis showed that the heated bay benthic bacteria had higher transcript numbers related to energy metabolism and stress compared to the control bay, while short-term elevated temperatures in the control bay incubation experiment induced a transcript response resembling that observed in the heated bay field conditions. In contrast, a reciprocal response was not observed for the heated bay community RNA transcripts exposed to lower temperatures indicating a potential tipping point in community response may have been reached. In summary, long-term warming modulates the performance, productivity, and resilience of bacterial communities in response to warming.

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  • 34.
    Seidel, Laura
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Broman, Elias
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Stockholm University, Sweden.
    Ståhle, Magnus
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Nilsson, Emelie
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Turner, Stephanie
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Hendrycks, Wouter
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Sachpazidou, Varvara
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Forsman, Anders
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Linnaeus University, Linnaeus Knowledge Environments, Water.
    Hylander, Samuel
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Linnaeus University, Linnaeus Knowledge Environments, Water.
    Dopson, Mark
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Linnaeus University, Linnaeus Knowledge Environments, Water.
    Long-term warming of Baltic Sea coastal waters affects bacterial communities in bottom water and sediments differently2022In: Frontiers in Microbiology, E-ISSN 1664-302X, Vol. 13, article id 873281Article in journal (Refereed)
    Abstract [en]

    Coastal marine ecosystems are some of the most diverse natural habitats while being highly vulnerable in the face of climate change. The combination of anthropogenic influence from land and ongoing climate change will likely have severe effects on the environment, but the precise response remains uncertain. This study compared an unaffected “control” Baltic Sea bay to a “heated” bay that has undergone artificial warming from cooling water release from a nuclear power plant for ~50 years. This heated the water in a similar degree to IPCC SSP5-8.5 predictions by 2100 as natural systems to study temperature-related climate change effects. Bottom water and surface sediment bacterial communities and their biogeochemical processes were investigated to test how future coastal water warming alters microbial communities; shifts seasonal patterns, such as increased algae blooming; and influences nutrient and energy cycling, including elevated respiration rates. 16S rRNA gene amplicon sequencing and geochemical parameters demonstrated that heated bay bottom water bacterial communities were influenced by increased average temperatures across changing seasons, resulting in an overall Shannon's H diversity loss and shifts in relative abundances. In contrast, Shannon's diversity increased in the heated surface sediments. The results also suggested a trend toward smaller-sized microorganisms within the heated bay bottom waters, with a 30% increased relative abundance of small size picocyanobacteria in the summer (June). Furthermore, bacterial communities in the heated bay surface sediment displayed little seasonal variability but did show potential changes of long-term increased average temperature in the interplay with related effects on bottom waters. Finally, heated bay metabolic gene predictions from the 16S rRNA gene sequences suggested raised anaerobic processes closer to the sediment-water interface. In conclusion, climate change will likely alter microbial seasonality and diversity, leading to prolonged and increased algae blooming and elevated respiration rates within coastal waters.

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  • 35.
    Soudan, Rahaf
    Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences.
    Bestämning av myosin ATPas med NADH-kopplade mätsystem jämfört med in vitro motilitet med isolerat myosin och aktin2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    SammanfattningSyftet med denna studie var att jämföra NADH-kopplade mätsystem och in vitro motilitets-analys (IVMA) för att bestämma aktiviteten hos isolerat myosin. Från NADH-kopplade analysmätningar bestämdes tre parameter: den maximala hastigheten med vilken myosin hydrolyserar ATP i frånvaro av F-aktin (V0), den maximala ATPas-hastigheten för myosin i närvaro av mättande aktin (kcat) och den koncentration av aktin som behövs för att nå halv maximal aktivering av myosin ATPas-aktivitet (KATPas). Från in vitro-motilitets-analys (IVMA) bestämdes två parametrar: fraktion av rörliga filament (FMF) och totala antalet rörliga filament (TMF). Från detta kunde vi uppskatta den fraktion av aktiva huvuden i myosinpreparationer som behövs för en lyckad IVMA.Myosin är ett protein som tillsammans med aktin är ansvarigt för muskelkontraktionen. I denna studie används två myosin preparationer (HMM-fragment) som vi betecknade ”bra HMM” och ”dåligt HMM” på grund av deras kvalitet för aktin motilitet. Först mättes ATPas-aktiviteten hos myosinmotorer med hjälp av ett NADH-kopplat mätsystem som bygger på övervakning av förändringen i absorbans av NADH. Därefter bestämdes V0, kcat, och KATPas för aktin-beroende av myosin-ATPast genom att mäta myosinaktivitet vid olika aktinkoncentrationer, följt av anpassning av data till Michaelis-Menten ekvationen.Parallellt utfördes IVMA-studier genom att HMM immobiliserades på ett objektglas som derivatiserats med trimetylklorsilan. Sedan observerades när HMM flyttar fram fluorescensmärkta aktinfilament i närvaro av ATP. Under samma förhållanden gav resultaten för basalt myosin ATPas aktivitet V0 värden som var ~0,03 ATP s-1 myosinhuvud -1for både dåligt och bra HMM. I en jämförelse mellan de två HMM vid olika F-aktin-koncentrationer var hastighet i ATP-förbrukningen högre för bra än för dåligt HMM. Anpassning av data till Michaelis-Menten-ekvationen gav kcat på 7,18 ATP s-1myosinhuvud-1för dåligt HMM jämfört med 11,21 ATP s-1 myosinhuvud-1för bra HMM (35 % högre). KATPas (Km) för dåligt HMM var lite högre jämfört med den för bra HMM. Vid IVMA-studierna var FMF och TMF 80 % respektive 98 % lägre för dåligt än bra HMM. Slutsatsen var att de två metoderna karakteriserar HMM-funktionen på olika sätt och med olika känslighet. Om man antar att bra HMM har nästan 100 % aktiva huvuden och eftersom man vet att uppmätt kcat är direkt proportionellt mot antalet aktiva myosinhuvuden ser man från dessa mätningar att mycket mer än 65 % av totalt myosin måste vara aktivt för att ge god aktinmotilitet i en IVMA.

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  • 36.
    Westmeijer, George
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Microbial life deep underground: From anaerobic cultures to reconstructed genomes2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The deep biosphere refers to the vast ecosystem of life beneath the Earth’s surface, residing in the fractured bedrock and pores of rocks, largely isolated from solar energy. These fractures enclose an important reservoir of groundwater that contains microorganisms active in processes such as the uptake of inorganic carbon, sulfur cycling, or the degradation of organic matter. However, there is still much knowledge to be gained on the diversity and function of these subsurface microorganisms, and how the surface influences subsurface life. In this work, I explored interactions among subsurface microorganisms, studied subsurface microbial diversity in the light of surface recharge, and characterized microbial populations residing in biofilms.

    Potential interactions among microorganisms were explored with anaerobic cultures using groundwaters from the Äspö Hard Rock Laboratory. By removal of larger cells (> 0.45 𝜇m in diameter), an inoculum enriched in ultra-small bacteria (nanobacteria) was obtained. Despite the presence of various sources of energy and nutrients, these nanobacteria did not grow over prolonged incubation times up to four months. Reconstructed genomes confirmed this group of bacteria to have a low metabolic potential, indicative of a symbiotic lifestyle.

    Characterization of microbial communities in subsurface groundwaters and overlying environments on Äspö island revealed that a substantial proportion of the subsurface community was also detected in soil-hosted groundwaters. Considering the unidirectional water flow, this showed that part of the subsurface diversity between 70 and 460 m depth could originate from surface recharge, especially for the shallower groundwaters. In contrast to the high microbial diversity observed in Äspö groundwaters, characterization of a fracture fluid at 975 m depth in central Sweden revealed a microbial community dominated by a single population, adapted to the energy-limited conditions in the deep subsurface, namely the bacterium Candidatus Desulforudis audaxviator.

    Furthermore, the activity (based on RNA transcripts) of attached microbial populations was measured using flow-cells that facilitated biofilm formation. An elevated number of genes involved in the transition from a planktonic to an attached lifestyle was observed. Interestingly, comparing the microbial activity in the biofilm to the planktonic community revealed Thiobacillus denitrificans to have a principal role in the biofilm formation. Combined, these findings help understand the magnitude of microbial diversity in the continental subsurface as well as how these microorganisms are adapted to cope with the energy limitations in this subsurface ecosystem.

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