158 research outputs found
Hybrid Epidemics - A Case Study on Computer Worm Conficker
Conficker is a computer worm that erupted on the Internet in 2008. It is
unique in combining three different spreading strategies: local probing,
neighbourhood probing, and global probing. We propose a mathematical model that
combines three modes of spreading, local, neighbourhood and global to capture
the worm's spreading behaviour. The parameters of the model are inferred
directly from network data obtained during the first day of the Conifcker
epidemic. The model is then used to explore the trade-off between spreading
modes in determining the worm's effectiveness. Our results show that the
Conficker epidemic is an example of a critically hybrid epidemic, in which the
different modes of spreading in isolation do not lead to successful epidemics.
Such hybrid spreading strategies may be used beneficially to provide the most
effective strategies for promulgating information across a large population.
When used maliciously, however, they can present a dangerous challenge to
current internet security protocols
Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection
HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free
infection following fluid-phase diffusion of virions and by highly-efficient
direct cell-to-cell transmission at immune cell contacts. The contribution of
this hybrid spreading mechanism, which is also a characteristic of some
important computer worm outbreaks, to HIV-1 progression in vivo remains
unknown. Here we present a new mathematical model that explicitly incorporates
the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the
consequences for HIV-1 pathogenenesis. The model captures the major phases of
the HIV-1 infection course of a cohort of treatment naive patients and also
accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at
Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading
is critical to seed and establish infection, and that cell-to-cell spread and
increased CD4+ T cell activation are important for HIV-1 progression. Notably,
the model predicts that cell-to-cell spread becomes increasingly effective as
infection progresses and thus may present a considerable treatment barrier.
Deriving predictions of various treatments' influence on HIV-1 progression
highlights the importance of earlier intervention and suggests that treatments
effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS.
This study suggests that hybrid spreading is a fundamental feature of HIV
infection, and provides the mathematical framework incorporating this feature
with which to evaluate future therapeutic strategies
Haematopoietic development and immunological function in the absence of cathepsin D
Background: Cathepsin D is a well-characterized aspartic protease expressed ubiquitously in lysosomes. Cathepsin D deficiency is associated with a spectrum of pathologies leading ultimately to death. Cathepsin D is expressed at high levels in many cells of the immune system, but its role in immune function is not well understood. This study examines the reconstitution and function of the immune system in the absence of cathepsin D, using bone marrow radiation chimaeras in which all haematopoietic cells are derived from cathepsin D deficient mice.Results: Cathepsin D deficient bone marrow cells fully reconstitute the major cellular components of both the adaptive and innate immune systems. Spleen cells from cathepsin D deficient chimaeric mice contained an increased number of autofluorescent granules characteristic of lipofuscin positive lysosomal storage diseases. Biochemical and ultrastructural changes in cathepsin D deficient spleen are consistent with increased autolysosomal activity. Chimaeric mice were immunised with either soluble (dinitrophenylated bovine gamma globulin) or particulate (sheep red blood cells) antigens. Both antigens induced equivalent immune responses in wild type or cathepsin D deficient chimaeras.Conclusion: All the parameters of haematopoietic reconstitution and adaptive immunity which were measured in this study were found to be normal in the absence of cathepsin D, even though cathepsin D deficiency leads to dysregulation of lysosomal function
Pseudomonas aeruginosa biofilm is a potent inducer of phagocyte hyperinflammation
Objective Pseudomonas aeruginosa effectively facilitate resistance to phagocyte killing by biofilm formation. However,b the
cross talk between biofilm components and phagocytes is still unclear. We hypothesize that a biofilm provides a concentrated
extracellular source of LPS, DNA and exopolysaccharides (EPS), which polarize neighbouring phagocytes into an adverse
hyperinflammatory state of activation.
Methods We measured the release of a panel of mediators produced in vitro by murine neutrophils and macrophages exposed
to various biofilm components of P. aeruginosa cultures.
Results We found that conditioned media from a high biofilm-producing strain of P. aeruginosa, PAR5, accumulated high
concentrations of extracellular bacterial LPS, DNA and EPS by 72 h. These conditioned media induced phagocytes to release
a hyperinflammatory pattern of mediators, with enhanced levels of , IL-6, IL12p40,
and NO. Moreover, the
phagocytes also upregulated COX-2 and iNOS with no influence on the expression of arginase-1.
Conclusions Phagocytes exposed to biofilm microenvironment, called by us biofilm-associated neutrophils/macrophages
(BANs/BAMs), display secretory properties similar to that of N1/M1-type phagocytes. These results suggest that in vivo
high concentrations of LPS and DNA, trapped in biofilm by EPS, might convert infiltrating phagocytes into cells responsible
for tissue injury without direct contact with bacteria and phagocytosis
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Error, reproducibility and sensitivity : a pipeline for data processing of Agilent oligonucleotide expression arrays
Background
Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples.
Results
We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2% of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log2 units ( 6% of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators.
Conclusions
This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells
Executable network of SARS-CoV-2-host interaction predicts drug combination treatments
The COVID-19 pandemic has pushed healthcare systems globally to a breaking point. The urgent need for effective and affordable COVID-19 treatments calls for repurposing combinations of approved drugs. The challenge is to identify which combinations are likely to be most effective and at what stages of the disease. Here, we present the first disease-stage executable signalling network model of SARS-CoV-2-host interactions used to predict effective repurposed drug combinations for treating early- and late stage severe disease. Using our executable model, we performed in silico screening of 9870 pairs of 140 potential targets and have identified nine new drug combinations. Camostat and Apilimod were predicted to be the most promising combination in effectively supressing viral replication in the early stages of severe disease and were validated experimentally in human Caco-2 cells. Our study further demonstrates the power of executable mechanistic modelling to enable rapid pre-clinical evaluation of combination therapies tailored to disease progression. It also presents a novel resource and expandable model system that can respond to further needs in the pandemic
Framework engineering to produce dominant T cell receptors with enhanced antigen-specific function
Immunobiology of allogeneic stem cell transplantation and immunotherapy of hematological disease
Role of DNA topology in uptake of polyplex molecules by dendritic cells.
Dendritic cells (DCs) are an attractive target for DNA vaccines as they are potent antigen presenting cells. This study demonstrated how non-viral gene delivery to DCs involving complexes of poly-l-lysine (PLL) and plasmid DNA (pDNA) (polyplexes) showed dependence on DNA vector topology. DNA topology is of importance from both production and regulatory viewpoints. In our previous study with CHO cells we demonstrated that polyplex uptake was dependent on DNA topology whereby complexes containing supercoiled (SC) pDNA were smaller, more resistant to nucleases and more effectively condensed by PLL than open circular (OC) and linear-pDNA complexes. In this study polyplex uptake in DCs was measured qualitatively and quantitatively by confocal microscopy along with gene expression studies and measurement of DC phenotype. PLL is known for its ability to condense DNA and serve as an effective gene delivery vehicle. Quantification studies revealed that by 1h following uptake 15% (±2.59% relative standard error [RSE]) of SC-pDNA polyplexes were identified to be associated (fluorescent co-localisation) with the nucleus, in comparison to no nuclear association identified for OC- and linear-pDNA complexes. By 48 h following uptake, 30% (±1.82% RSE) of SC-pDNA complexes associated with the nucleus in comparison to 16% (±4.40% RSE) and 12% (±6.97% RSE) of OC- and linear-pDNA polyplexes respectively. Confocal microscopy images showed how DNA and PLL remained associated following uptake by dual labelling. Polyplex (containing 20 μg pDNA) gene expression (plasmid encoded lacZ [β-galactosidase] reporter gene) in DCs was greatest for SC-pDNA polyplexes at 14.12% unlike that of OC- (9.59%) and linear-pDNA (7.43%). DCs express cell surface markers which contribute towards antigen presentation. Polyplex gene expression did not alter DC phenotype through surface marker expression. This may be due to the pDNA dose employed (20μg) as other studies have used doses as high as 200 μg pDNA to induce DC phenotypic changes. Although no change in DC phenotype occurred, this could be advantageous in terms of biocompatibility. Collectively these results indicate that DNA topology is an important parameter for DC vector design, particularly pDNA in the SC conformation in regards to DNA vaccination studies
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