Cell Cycle-Related Cyclin B1 Quantification

To obtain non-relative measures of cell proteins, purified preparations of the same proteins are used as standards in Western blots. We have previously quantified SV40 large T antigen expressed over a several fold range in different cell lines and correlated the average number of molecules to average fluorescence obtained by cytometry and determined cell cycle phase related expression by calculation from multi-parametric cytometry data. Using a modified approach, we report quantification of endogenous cyclin B1 and generation of the cell cycle time related expression profile.Recombinant cyclin B1 was purified from a baculovirus lysate using an antibody affinity column and concentrated. We created fixed cell preparations from nocodazole-treated (high cyclin B1) and serum starved (low cyclin B1) PC3 cells that were either lyophilized (for preservation) or solubilized. The lysates and purified cyclin B1 were subjected to Western blotting; the cell preparations were subjected to cytometry, and fluorescence was correlated to molecules. Three untreated cell lines (K562, HeLa, and RKO) were prepared for cytometry without lyophilization and also prepared for Western blotting. These were quantified by Western blotting and by cytometry using the standard cell preparations.The standard cell preparations had 1.5 x 10(5) to 2.5 x 10(6) molecules of cyclin B1 per cell on average (i.e., 16-fold range). The average coefficient of variation was 24%. Fluorescence varied 12-fold. The relationship between molecules/cell (Western blot) and immunofluorescence (cytometry) was linear (r(2) = 0.87). Average cyclin B1 levels for the three untreated cell lines determined by Western blotting and cytometry agreed within a factor of 2. The non-linear rise in cyclin B1 in S phase was quantified from correlated plots of cyclin B1 and DNA content. The peak levels achieved in G2 were similar despite differences in lineage, growth conditions, and rates of increase through the cell cycle (range: 1.6-2.2 x 10(6) molecules per cell).Net cyclin B1 expression begins in G1 in human somatic cells lines; increases non-linearly with variation in rates of accumulation, but peaks at similar peak values in different cell lines growing under different conditions. This suggests tight quantitative end point control

What we stand for: Reputation platforms in Scandinavian higher education

acceptedVersio

Influence of the different “patient global assessment” formulations on disease activity score by different indices in rheumatoid arthritis

© 2018, International League of Associations for Rheumatology (ILAR). Patient global assessment (PGA) is included in almost all rheumatoid arthritis (RA) composite disease activity indices and definitions of remission. However, different PGA formulations exist and are used interchangeably in research and clinical practice. We investigated how five different PGA formulations used in four disease indices affect the remission rates. This was an ancillary analysis of data from a cross-sectional study in patients with RA. The data comprised the following: 28-joint counts, C-reactive protein, and five PGA formulations. Remission rate variation was assessed using five PGA formulations in each index (ACR/EULAR Boolean, CDAI, SDAI, and DAS28-CRP). PGA agreement was assessed by the following: Pearson’s correlation; Bland-Altman plots; paired samples t test; and establishing the proportion of patients who scored (i) all formulations within an interval of 20mm and (ii) each formulation ≤ 10mm. This analysis included 191 patients. PGA formulations presented good correlations (≥ 0.65), but Bland-Altman plots showed clinically significant differences, which were statistically confirmed by comparison of means. Just over a half (51.8%) of patients scored all PGA formulations within a 20-mm interval. The proportion of those scoring ≤ 10mm varied from 11.5 to 16.2%. When different formulations of PGA were used in each index, remission differences of up to 4.7, 4.7, 6.3, and 5.2% were observed. When formulations were used in their respective indices, as validated, the remission rates were similar (13.1, 13.6, 14.1, and 18.3%). Using PGA formulations interchangeably may have implications in the assessment of disease activity and in the attainment of remission, and this can impact upon management decisions

Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process

Enhanced Enterovirus D68 Replication in Neuroblastoma Cells Is Associated with a Cell Culture-Adaptive Amino Acid Substitution in VP1

Since its emergence in the United States in 2014, enterovirus D68 (EV-D68) has been and is associated with severe respiratory diseases and acute flaccid myelitis. Even though EV-D68 has been shown to replicate in different neuronal cells in vitro, it is currently poorly understood which viral factors contribute to the ability to replicate efficiently in cells of the central nervous system and whether this feature is a clade-specific feature. Here, we determined the replication kinetics of clinical EV-D68 isolates from (sub)clades A, B1, B2, B3, and D1 in human neuroblastoma cells (SK-N-SH). Subsequently, we compared sequences to identify viral factors associated with increased viral replication. All clinical isolates replicated in SK-N-SH cells, although there was a large difference in efficiency. Efficient replication of clinical isolates was associated with an amino acid substitution at position 271 of VP1 (E271K), which was acquired during virus propagation in vitro. Recognition of heparan sulfate in addition to sialic acids was associated with increased attachment, infection, and replication. Removal of heparan sulfate resulted in a decrease in attachment, internalization, and replication of viruses with E271K. Taken together, our study suggests that the replication kinetics of EV-D68 isolates in SKN-SH cells is not a clade-specific feature. However, recognition of heparan sulfate as an additional receptor had a large effect on phenotypic characteristics in vitro. These observations emphasize the need to compare sequences from virus stocks with clinical isolates in order to retrieve phenotypic characteristics from original virus isolates. IMPORTANCE Enterovirus D68 (EV-D68) causes mild to severe respiratory disease and is associated with acute flaccid myelitis since 2014. Currently, the understanding of the ability of EV-D68 to replicate in the central nervous system (CNS), and whether it is associated with a specific clade of EV-D68 viruses or specific viral factors, is lacking. Comparing different EV-D68 clad

Acquisition of Human-Type Receptor Binding Specificity by New H5N1 Influenza Virus Sublineages during Their Emergence in Birds in Egypt

Highly pathogenic avian influenza A virus subtype H5N1 is currently widespread in Asia, Europe, and Africa, with 60% mortality in humans. In particular, since 2009 Egypt has unexpectedly had the highest number of human cases of H5N1 virus infection, with more than 50% of the cases worldwide, but the basis for this high incidence has not been elucidated. A change in receptor binding affinity of the viral hemagglutinin (HA) from α2,3- to α2,6-linked sialic acid (SA) is thought to be necessary for H5N1 virus to become pandemic. In this study, we conducted a phylogenetic analysis of H5N1 viruses isolated between 2006 and 2009 in Egypt. The phylogenetic results showed that recent human isolates clustered disproportionally into several new H5 sublineages suggesting that their HAs have changed their receptor specificity. Using reverse genetics, we found that these H5 sublineages have acquired an enhanced binding affinity for α2,6 SA in combination with residual affinity for α2,3 SA, and identified the amino acid mutations that produced this new receptor specificity. Recombinant H5N1 viruses with a single mutation at HA residue 192 or a double mutation at HA residues 129 and 151 had increased attachment to and infectivity in the human lower respiratory tract but not in the larynx. These findings correlated with enhanced virulence of the mutant viruses in mice. Interestingly, these H5 viruses, with increased affinity to α2,6 SA, emerged during viral diversification in bird populations and subsequently spread to humans. Our findings suggested that emergence of new H5 sublineages with α2,6 SA specificity caused a subsequent increase in human H5N1 influenza virus infections in Egypt, and provided data for understanding the virus's pandemic potential

A Computational and Experimental Study of the Regulatory Mechanisms of the Complement System

The complement system is key to innate immunity and its activation is necessary for the clearance of bacteria and apoptotic cells. However, insufficient or excessive complement activation will lead to immune-related diseases. It is so far unknown how the complement activity is up- or down- regulated and what the associated pathophysiological mechanisms are. To quantitatively understand the modulatory mechanisms of the complement system, we built a computational model involving the enhancement and suppression mechanisms that regulate complement activity. Our model consists of a large system of Ordinary Differential Equations (ODEs) accompanied by a dynamic Bayesian network as a probabilistic approximation of the ODE dynamics. Applying Bayesian inference techniques, this approximation was used to perform parameter estimation and sensitivity analysis. Our combined computational and experimental study showed that the antimicrobial response is sensitive to changes in pH and calcium levels, which determines the strength of the crosstalk between CRP and L-ficolin. Our study also revealed differential regulatory effects of C4BP. While C4BP delays but does not decrease the classical complement activation, it attenuates but does not significantly delay the lectin pathway activation. We also found that the major inhibitory role of C4BP is to facilitate the decay of C3 convertase. In summary, the present work elucidates the regulatory mechanisms of the complement system and demonstrates how the bio-pathway machinery maintains the balance between activation and inhibition. The insights we have gained could contribute to the development of therapies targeting the complement system.Singapore. Ministry of Education (Grant T208B3109)Singapore. Agency for Science, Technology and Research (BMRC 08/1/21/19/574)Singapore-MIT Alliance (Computational and Systems Biology Flagship Project)Swedish Research Counci

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering

<p>Abstract</p> <p>Background</p> <p>Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments.</p> <p>Results</p> <p>We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification.</p> <p>Conclusion</p> <p>We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich-data poor' paradox in Systems Biology.</p

Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

<p>Abstract</p> <p>Background</p> <p>In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme.</p> <p>Results</p> <p>The diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges.</p> <p>Conclusions</p> <p>The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.</p