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Nilsson, Patric
Publications (10 of 22) Show all publications
Jansson, A., Pernestig, A.-K., Nilsson, P., Jirstrand, M. & Hornquist, E. H. (2013). Toward Quantifying the Thymic Dysfunctional State in Mouse Models of Inflammatory Bowel Disease. Inflammatory Bowel Diseases, 19(4), 881-888
Open this publication in new window or tab >>Toward Quantifying the Thymic Dysfunctional State in Mouse Models of Inflammatory Bowel Disease
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2013 (English)In: Inflammatory Bowel Diseases, ISSN 1078-0998, E-ISSN 1536-4844, Vol. 19, no 4, p. 881-888Article, review/survey (Refereed) Published
Abstract [en]

Inflammatory bowel disease is characterized by a number of immunological alterations, not the least in the T-cell compartment. Numerous animal models of colitis have revealed aberrant thymocyte dynamics associated with skewed thymocyte development. The recent advancements in quantitative methods have proposed critical kinetic alterations in the thymocyte development during the progression of colitis. This review focuses on the aberrant thymocyte dynamics in G alpha i2-deficient mice as this mouse model provides most quantitative data of the thymocyte development associated with colitis. Herein, we discuss several dynamic changes during the progression of colitis and propose a hypothesis for the underlying causes for the skewed proportions of the thymocyte populations seen in the G alpha i2-deficient mice and in other mouse models of colitis. (Inflamm Bowel Dis 2013; 19: 881-888)

Place, publisher, year, edition, pages
Lippincott Williams & Wilkins, 2013
Keywords
kinetics, thymocyte, thymus, IBD, colitis
National Category
Natural Sciences
Research subject
Natural sciences
Identifiers
urn:nbn:se:his:diva-8399 (URN)10.1097/MIB.0b013e3182802c58 (DOI)000316451600037 ()23448795 (PubMedID)2-s2.0-84884651875 (Scopus ID)
Available from: 2013-08-13 Created: 2013-08-13 Last updated: 2017-12-06Bibliographically approved
Fagerlind, M. G., Webb, J. S., Barraud, N., McDougald, D., Jansson, A., Nilsson, P., . . . Rice, S. A. (2012). Dynamic modelling of cell death during biofilm development. Journal of Theoretical Biology, 295, 23-36
Open this publication in new window or tab >>Dynamic modelling of cell death during biofilm development
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2012 (English)In: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 295, p. 23-36Article in journal (Refereed) Published
Abstract [en]

Biofilms are currently recognised as the predominant bacterial life-style and it has been suggested that biofilm development is influenced by a number of different processes such as adhesion, detachment, mass transport, quorum sensing, cell death and active dispersal. One of the least understood processes and its effects on biofilm development is cell death. However, experimental studies suggest that bacterial death is an important process during biofilm development and many studies show a relationship between cell death and dispersal in microbial biofilms. We present a model of the process of cell death during biofilm development, with a particular focus on the spatial localisation of cell death or cell damage. Three rules governing cell death or cell damage were evaluated which compared the effects of starvation, damage accumulation, and viability during biofilm development and were also used to design laboratory based experiments to test the model. Results from model simulations show that actively growing biofilms develop steep nutrient gradients within the interior of the biofilm that affect neighbouring microcolonies resulting in cell death and detachment. Two of the rules indicated that high substrate concentrations lead to accelerated cell death, in contrast to the third rule, based on the accumulation of damage, which predicted earlier cell death for biofilms grown with low substrate concentrations. Comparison of the modelling results with experimental results suggests that cell death is favoured under low nutrient conditions and that the accumulation of damage may be the main cause of cell death during biofilm development. (C) 2011 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
Academic Press, 2012
Keywords
Biofilm, Individual based CA, Cell death
National Category
Natural Sciences
Research subject
Natural sciences
Identifiers
urn:nbn:se:his:diva-5452 (URN)10.1016/j.jtbi.2011.10.007 (DOI)000299408500003 ()2-s2.0-82255169356 (Scopus ID)
Available from: 2012-02-23 Created: 2012-02-22 Last updated: 2017-12-07Bibliographically approved
James, J. R., McColl, J., Oliveira, M. I., Dunne, P. D., Huang, E., Jansson, A., . . . Davis, S. J. (2011). The T Cell Receptor Triggering Apparatus Is Composed of Monovalent or Monomeric Proteins. Journal of Biological Chemistry, 286(37), 31993-32001
Open this publication in new window or tab >>The T Cell Receptor Triggering Apparatus Is Composed of Monovalent or Monomeric Proteins
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2011 (English)In: Journal of Biological Chemistry, ISSN 0021-9258, E-ISSN 1083-351X, Vol. 286, no 37, p. 31993-32001Article in journal (Refereed) Published
Abstract [en]

Understanding the component stoichiometry of the T cell antigen receptor (TCR) triggering apparatus is essential for building realistic models of signal initiation. Recent studies suggesting that the TCR and other signaling-associated proteins are preclustered on resting T cells relied on measurements of the behavior of membrane proteins at interfaces with functionalized glass surfaces. Using fluorescence recovery after photo-bleaching, we show that, compared with the apical surface, the mobility of TCRs is significantly reduced at Jurkat T cell/glass interfaces, in a signaling-sensitive manner. Using two biophysical approaches that mitigate these effects, bioluminescence resonance energy transfer and two-color coincidence detection microscopy, we show that, within the uncertainty of the methods, the membrane components of the TCR triggering apparatus, i.e. the TCR complex, MHC molecules, CD4/Lck and CD45, are exclusively monovalent or monomeric in human T cell lines, implying that TCR triggering depends only on the kinetics of TCR/pMHC interactions. These analyses also showed that constraining proteins to two dimensions at the cell surface greatly enhances random interactions versus those between the membrane and the cytoplasm. Simulations of TCR-pMHC complex formation based on these findings suggest how unclustered TCR triggering-associated proteins might nevertheless be capable of generating complex signaling outputs via the differential recruitment of cytosolic effectors to the cell membrane.

Place, publisher, year, edition, pages
American Society for Biochemistry and Molecular Biology, 2011
National Category
Biochemistry and Molecular Biology
Research subject
Natural sciences
Identifiers
urn:nbn:se:his:diva-5519 (URN)10.1074/jbc.M111.219212 (DOI)000294726800008 ()2-s2.0-80052730531 (Scopus ID)
Available from: 2012-03-23 Created: 2012-03-01 Last updated: 2017-12-07Bibliographically approved
Gustafsson, E., Jacobsson, G., Nilsson, P., Enroth, H., Beronius, M. K., Andersson, R. & Arvidson, S. (2009). Invasive Staphylococcus aureus strains are highly variable in PFGE patterns, agr group and exoprotein production. Scandinavian Journal of Infectious Diseases, 41(8), 577-583
Open this publication in new window or tab >>Invasive Staphylococcus aureus strains are highly variable in PFGE patterns, agr group and exoprotein production
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2009 (English)In: Scandinavian Journal of Infectious Diseases, ISSN 0036-5548, E-ISSN 1651-1980, Vol. 41, no 8, p. 577-583Article in journal (Refereed) Published
Abstract [en]

In the present study, we have investigated 37 invasive Staphylococcus aureus strains (collected between 1997 and 2005) from 33 human episodes of septicaemia causing either endocarditis or vertebral osteomyelitis. All S. aureus strains were typed using pulsed field gel electrophoresis (PFGE), and most strains belonged to any of 4 different PFGE clusters. There was no correlation between any of the PFGE clusters with site of infection. All strains showed highly different expression patterns of extracellular proteins, i.e. we found a vast variation in the number of proteins and amount of individual proteins expressed by the different strains. There was no correlation between any cluster of exoprotein patterns with endocarditis or with vertebral osteomyelitis. We did not find any correlation between agr group and endocarditis, as previously reported. On the other hand, a correlation between some of the PFGE clusters with a certain agr group was found. Known risk factors for S. aureus infections were observed in a majority of the patients.

Place, publisher, year, edition, pages
Informa Healthcare, 2009
National Category
Natural Sciences
Research subject
Natural sciences
Identifiers
urn:nbn:se:his:diva-3512 (URN)10.1080/00365540903030314 (DOI)000268933400005 ()19513937 (PubMedID)2-s2.0-70849088373 (Scopus ID)
Available from: 2009-12-01 Created: 2009-12-01 Last updated: 2017-12-12Bibliographically approved
Gustafsson, E., Karlsson, S., Oscarsson, J., Sögård, P., Nilsson, P. & Arvidson, S. (2009). Mathematical modelling of the regulation of spa (protein A) transcription in Staphylococcus aureus. International Journal of Medical Microbiology, 299(1), 65-74
Open this publication in new window or tab >>Mathematical modelling of the regulation of spa (protein A) transcription in Staphylococcus aureus
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2009 (English)In: International Journal of Medical Microbiology, ISSN 1438-4221, E-ISSN 1618-0607, Vol. 299, no 1, p. 65-74Article in journal (Refereed) Published
Abstract [en]

In the present work a general systems biology approach has been used to study the complex regulatory network controlling the transcription of the spa gene, encoding protein A, a major surface protein and an important virulence factor of Staphylococcus aureus. A valid mathematical model could be formulated using parameter values, which were fitted to quantitative Northern blot data from various S. aureus regulatory mutants using a gradient search method. The model could correctly predict spa expression levels in 4 different regulatory mutants not included in the parameter value search, and in 2 other S. aureus strains, SH 1000 and UAMS-1. The mathematical model revealed that sarA and sarS seem to balance each other in a way that when the activating impact of sarS is small, e.g. in the wild-type, the repressive impact of sarA is small, while in an agr-deficient background, when the impact of sarS is maximal, the repressive impact of sarA is close to its maximum. Furthermore, the model revealed that Rot and SarS act synergistically to stimulate spa expression, something that was not obvious from experimental data. We believe that this mathematical model can be used to evaluate the significance of other putative interactions in the regulatory network governing spa transcription. (C) 2008 Elsevier GmbH. All rights reserved.

Place, publisher, year, edition, pages
Elsevier, 2009
Identifiers
urn:nbn:se:his:diva-7832 (URN)10.1016/j.ijmm.2008.05.011 (DOI)000263074400007 ()18657473 (PubMedID)2-s2.0-56949084305 (Scopus ID)
Available from: 2013-03-28 Created: 2013-03-21 Last updated: 2017-12-06Bibliographically approved
Karlsson, D., Jansson, A., Normark, B. H. & Nilsson, P. (2008). An individual-based network model to evaluate interventions for controlling pneumococcal transmission. BMC Infectious Diseases, 8, 83
Open this publication in new window or tab >>An individual-based network model to evaluate interventions for controlling pneumococcal transmission
2008 (English)In: BMC Infectious Diseases, ISSN 1471-2334, E-ISSN 1471-2334, Vol. 8, p. 83-Article in journal (Refereed) Published
Abstract [en]

Background: Streptococcus pneumoniae is a major cause of morbidity and mortality worldwide, but also a common colonizer of the upper respiratory tract. The emergence and spread of antibiotic resistant pneumococcal strains has threatened effective therapy. The long-term effects of measures aiming to limit pneumococcal spread are poorly understood. Computational modeling makes it possible to conduct virtual experiments that are impractical to perform in real life and thereby allows a more full understanding of pneumococcal epidemiology and control efforts. Methods: We have developed a contact network model to evaluate the efficacy of interventions aiming to control pneumococcal transmission. Demographic data from Sweden during the mid-2000s were employed. Analyses of the model's parameters were conducted to elucidate key determinants of pneumococcal spread. Also, scenario simulations were performed to assess candidate control measures. Results: The model made good predictions of previous findings where a correlation has been found between age and pneumococcal carriage. Of the parameters tested, group size in day-care centers was shown to be one of the most important factors for pneumococcal transmission. Consistent results were generated from the scenario simulations. Conclusion: We recommend, based on the model predictions, that strategies to control pneumococcal disease and organism transmission should include reducing the group size in day-care centers.

Identifiers
urn:nbn:se:his:diva-6868 (URN)10.1186/1471-2334-8-83 (DOI)000257399500002 ()18559109 (PubMedID)2-s2.0-47349104286 (Scopus ID)
Available from: 2012-11-29 Created: 2012-11-29 Last updated: 2017-12-07Bibliographically approved
Synnergren, J., Adak, S., Englund, M., Giesler, T., Noaksson, K., Lindahl, A., . . . Sartipy, P. (2008). Cardiomyogenic gene expression profiling of differentiating human embryonic stem cells. Journal of Biotechnology, 134(1-2), 162-170
Open this publication in new window or tab >>Cardiomyogenic gene expression profiling of differentiating human embryonic stem cells
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2008 (English)In: Journal of Biotechnology, ISSN 0168-1656, E-ISSN 1873-4863, Vol. 134, no 1-2, p. 162-170Article in journal (Refereed) Published
Abstract [en]

Human embryonic stem cells (hESCs) can differentiate into a variety of specialized cell types. Thus, they provide a model system for embryonic development to investigate the molecular processes of cell differentiation and lineage commitment. The development of the cardiac lineage is easily detected in mixed cultures by the appearance of spontaneously contracting areas of cells. We performed gene expression profiling of undifferentiated and differentiating hESCs and monitored 468 genes expressed during cardiac development and/or in cardiac tissue. Their transcription during early differentiation of hESCs through embryoid bodies (EBs) was investigated and compared with spontaneously differentiating hESCs maintained on feeders in culture without passaging (high-density (HD) protocol). We observed a larger variation in the gene expression between cells from a single cell line that were differentiated using two different protocols than in cells from different cell lines that were cultured according to the same protocol. Notably, the EB protocol resulted in more reproducible transcription profiles than the HD protocol. The results presented here provide new information about gene regulation during early differentiation of hESCs with emphasis on the cardiomyogenic program. In addition, we also identified regulatory elements that could prove critical for the development of the cardiomyocyte lineage.

Place, publisher, year, edition, pages
Elsevier, 2008
Keywords
Differentiation, Human embryonic stem cell, Cardiomyocyte, Gene expression
National Category
Bioinformatics and Systems Biology
Research subject
Natural sciences
Identifiers
urn:nbn:se:his:diva-2759 (URN)10.1016/j.jbiotec.2007.11.011 (DOI)000254681000020 ()18241947 (PubMedID)2-s2.0-39649111081 (Scopus ID)
Available from: 2009-02-18 Created: 2009-02-18 Last updated: 2017-12-13Bibliographically approved
Jansson, A., Harlén, M., Karlsson, S., Nilsson, P. & Cooley, M. (2007). 3D computation modelling of the influence of cytokine secretion on Th-cell development suggests that negative selection (inhibition of Th1 cells) is more effective than positive selection by IL-4 for Th2 cell dominance. Immunology and Cell Biology, 85(3), 189-196
Open this publication in new window or tab >>3D computation modelling of the influence of cytokine secretion on Th-cell development suggests that negative selection (inhibition of Th1 cells) is more effective than positive selection by IL-4 for Th2 cell dominance
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2007 (English)In: Immunology and Cell Biology, ISSN 0818-9641, E-ISSN 1440-1711, Vol. 85, no 3, p. 189-196Article in journal (Refereed) Published
Abstract [en]

Th-cell development has been suggested to include selective mechanisms in which certain cytokines select either Th1 or Th2 cells to proliferate and grow. The selective theory is based on the observation that Th2 cells secrete IL-4, a cytokine that promotes Th2 development, whereas Th1 cells secrete interferon-gamma (IFN-italic gamma) that favours Th1 development, and both positive and negative selective influences have been suggested to operate. In this study, we investigate the role of autocrine secretion and utilization of IL-4 by Th2 cells and address the question of whether an activated Th2 cell can be positively selected by IL-4 secreted from other Th2 cells. We present a spatial three dimensional (3D) modelling approach to simulate the interaction between the IL-4 ligand and its IL-4 receptors expressed on discrete IL-4 secreting cells. The simulations, based on existing experimental data on the IL-4 receptor–ligand system, illustrate how Th-cell development is highly dependent on the distance between cells that are communicating. The model suggests that a single Th2 cell is likely to communicate with possible target cells within a range of approximately 100 mum and that an activated Th2 cell manages to fill most of its own IL-4 receptors, even at a low secretion rate. The predictions made by the model suggest that negative selection against Th1 cells is more effective than positive selection by IL-4 for promoting Th2 dominance.

Place, publisher, year, edition, pages
Nature Publishing Group, 2007
Keywords
simulation, IL-4, diffusion, differentiation
Identifiers
urn:nbn:se:his:diva-2034 (URN)10.1038/sj.icb.7100023 (DOI)000246427900005 ()17199110 (PubMedID)2-s2.0-34247868910 (Scopus ID)
Available from: 2008-05-07 Created: 2008-05-07 Last updated: 2017-12-12Bibliographically approved
Synnergren, J., Giesler, T. L., Adak, S., Tandon, R., Noaksson, K., Lindahl, A., . . . Sartipy, P. (2007). Differentiating human embryonic stem cells express a unique housekeeping gene signature. Stem Cells, 25(2), 473-480
Open this publication in new window or tab >>Differentiating human embryonic stem cells express a unique housekeeping gene signature
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2007 (English)In: Stem Cells, ISSN 1066-5099, E-ISSN 1549-4918, Vol. 25, no 2, p. 473-480Article in journal (Refereed) Published
Abstract [en]

Housekeeping genes (HKGs) are involved in basic functions needed for the sustenance of the cell and are assumed to be constitutively expressed at a constant level. Based on these features, HKGs are frequently used for normalization of gene expression data. In the present study, we used the CodeLink Gene Expression Bioarray system to interrogate changes in gene expression occurring during differentiation of human ESCs (hESCs). Notably, in the three hESC lines used for the study, we observed that the RNA levels of 56 frequently used HKGs varied to a degree that rendered them inappropriate as reference genes. Therefore, we defined a novel set of HKGs specifically for hESCs. Here we present a comprehensive list of 292 genes that are stably expressed (coefficient of variation <20%) in differentiating hESCs. These genes were further grouped into high-, medium-, and low-expressed genes. The expression patterns of these novel HKGs show very little overlap with results obtained from somatic cells and tissues. We further explored the stability of this novel set of HKGs in independent, publicly available gene expression data from hESCs and observed substantial similarities with our results. Gene expression was confirmed by real-time quantitative polymerase chain reaction analysis. Taken together, these results suggest that differentiating hESCs have a unique HKG signature and underscore the necessity to validate the expression profiles of putative HKGs. In addition, this novel set of HKGs can preferentially be used as controls in gene expression analyses of differentiating hESCs.

Place, publisher, year, edition, pages
AlphaMed Press & Wiley-Blackwell, 2007
Keywords
Gene expression, Microarray, In vitro differentiation, Human embryonic stem cells, Housekeeping gene Normalization
Identifiers
urn:nbn:se:his:diva-2004 (URN)10.1634/stemcells.2006-0247 (DOI)000244070600026 ()17284652 (PubMedID)2-s2.0-33846928928 (Scopus ID)
Available from: 2008-04-25 Created: 2008-04-25 Last updated: 2017-12-12Bibliographically approved
Laurio, K., Svensson, T., Jirstrand, M., Nilsson, P., Gamalielsson, J. & Olsson, B. (2007). Evolutionary search for improved path diagrams. In: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 5th European Conference. LNCS 4447 (pp. 114-121). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Evolutionary search for improved path diagrams
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2007 (English)In: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 5th European Conference. LNCS 4447, Springer Berlin/Heidelberg, 2007, p. 114-121Conference paper, Published paper (Refereed)
Abstract [en]

A path diagram relates observed, pairwise, variable correlations to a functional structure which describes the hypothesized causal relations between the variables. Here we combine path diagrams, heuristics and evolutionary search into a system which seeks to improve existing gene regulatory models. Our evaluation shows that once a correct model has been identified it receives a lower prediction error compared to incorrect models, indicating the overall feasibility of this approach. However, with smaller samples the observed correlations gradually become more misleading, and the evolutionary search increasingly converges on suboptimal models. Future work will incorporate publicly available sources of experimentally verified biological facts to computationally suggest model modifications which might improve the model’s fitness.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2007
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 1611-3349 ; 4447 LNCS
Identifiers
urn:nbn:se:his:diva-2124 (URN)10.1007/978-3-540-71783-6_11 (DOI)000246102100011 ()2-s2.0-38049047606 (Scopus ID)978-3-540-71782-9 (ISBN)
Available from: 2008-06-03 Created: 2008-06-03 Last updated: 2017-11-27
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