A computational model of cellular response to modulated radiation fields

Purpose:
To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies.

Materials and Methods:
A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields.

Results:
The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses.

Conclusions:
The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.

A Monte Carlo model of DNA double-strand break clustering and rejoining kinetics for the analysis of pulsed-field gel electrophoresis data

In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

Asymptotic layer-type model of high pressure direct current glow discharge in electronegative gases

Here a self-consistent one-dimensional continuum model is presented for a narrow gap plane-parallel dc glow discharge. The governing equations consist of continuity and momentum equations for positive and negative ions and electrons coupled with Poisson's equation. A singular perturbation method is developed for the analysis of high pressure dc glow discharge. The kinetic processes of the ionization, electron attachment, and ion-ion recombination are included in the model. Explicit results are obtained for the asymptotic limits: delta=(r(D)/L)(2)--> 0, omega=(r(S)/L)(2)--> 0, where r(D) is the Debye radius, r(S) is recombination length, and L is the gap length. The discharge gap divides naturally into four layers with multiple space scales: anode fall region, positive column, transitional region, cathode fall region and diffusion layer adjacent to the cathode surface, its formation is discussed. The effects of the gas pressure, gap spacing and dc voltage on the electrical properties of the layers and its dimension are investigated. (C) 2000 American Institute of Physics. [S0021-8979(00)00813-6].

Autophagy stimulation by rapamycin suppresses lung inflammation and infection by Burkholderia cenocepacia in a model of cystic fibrosis

Cystic fibrosis (CF) is the most common inherited lethal disease in Caucasians which results in multiorgan dysfunction. However, 85% of the deaths are due to pulmonary infections. Infection by Burkholderia cenocepacia (B. cepacia) is a particularly lethal threat to CF patients because it causes severe and persistent lung inflammation and is resistant to nearly all available antibiotics. In CFTR Delta F508 (Delta F508) mouse macrophages, B. cepacia persists in vacuoles that do not fuse with the lysosomes and mediates increased production of IL-1 beta. It is believed that intracellular bacterial survival contributes to the persistence of the bacterium. Here we show for the first time that in wild-type but not in Delta F508 macrophages, many B. cepacia reside in autophagosomes that fuse with lysosomes at later stages of infection. Accordingly, association and intracellular survival of B. cepacia are higher in CFTR-Delta F508 macrophages than in WT macrophages. An autophagosome is a compartment that engulfs nonfunctional organelles and parts of the cytoplasm then delivers them to the lysosome for degradation to produce nutrients during periods of starvation or stress. Furthermore, we show that B. cepacia downregulates autophagy genes in WT and Delta F508 macrophages. However, autophagy dysfunction is more pronounced in Delta F508 macrophages since they already have compromised autophagy activity. We demonstrate that the autophagy-stimulating agent, rapamycin markedly decreases B. cepacia infection in vitro by enhancing the clearance of B. cepacia via induced autophagy. In vivo, rapamycin decreases bacterial burden in the lungs of CF mice and drastically reduces signs of lung inflammation. Together, our studies reveal that if efficiently activated, autophagy can control B. cepacia infection and ameliorate the associated inflammation. Therefore, autophagy is a novel target for new drug development for CF patients to control B. cepacia infection and accompanying inflammation.

A two-tier model of polymyxin B resistance in Burkholderia cenocepacia

P>Burkholderia cenocepacia is an environmental bacterium causing serious human opportunistic infections and is extremely resistant to multiple antibiotics including antimicrobial peptides, such as polymyxin B (PmB). Extreme antibiotic resistance is attributed to outer membrane impermeability ('intrinsic' resistance). Previous work showed that production of full-length lipopolysaccharide (LPS) prevents surface binding of PmB. We hypothesized that two tiers of resistance mechanisms rendering different thresholds of PmB resistance exist in B. cenocepacia. To test this notion, candidate genes were mutated in two isogenic strains expressing full-length LPS or truncated LPS devoid of heptose ('heptoseless LPS') respectively. We uncovered various proteins required for PmB resistance only in the strain with heptoseless LPS. These proteins are not involved in preventing PmB binding to whole cells or permeabilization of the outer membrane. Our results support a two-tier model of PmB resistance in B. cenocepacia. One tier sets a very high threshold mediated by the LPS and the outer membrane permeability barrier. The second tier sets a lower threshold that may play a role in PmB resistance only when outer membrane permeability is compromised. This model may be of general applicability to understanding the high antimicrobial peptide resistance of environmental opportunistic pathogens.