Cold-adapted arsenite oxidase from a psychrotolerant Polaromonas species.

Polaromonas sp. str. GM1 is an aerobic, psychrotolerant, heterotrophic member of the Betaproteobacteria and is the only isolate capable of oxidising arsenite at temperatures below 10 °C. Sequencing of the aio gene cluster in GM1 revealed the presence of the aioB and aioA genes, which encode the arsenite oxidase but the regulatory genes typically found upstream of aioB in other members of the Proteobacteria were absent. The GM1 Aio was purified to homogeneity and was found to be a heterodimer. The enzyme contained Mo and Fe as cofactors and had, using the artificial electron acceptor 2,6-dichlorophenolindophenol, a Km for arsenite of 111.70 ± 0.88 μM and a Vmax of 12.16 ± 0.30 U mg(-1), which is the highest reported specific activity for any known Aio. The temperature-activity profiles of the arsenite oxidases from GM1 and the mesophilic betaproteobacterium Alcaligenes faecalis were compared and showed that the GM1 Aio was more active at low temperatures than that of A. faecalis. A homology model of the GM1 Aio was made using the X-ray crystal structure of the Aio from A. faecalis as the template. Structural changes that account for cold adaptation were identified and it was found that these resulted in increased enzyme flexibility and a reduction in the hydrophobicity of the core

A computational model of invasive aspergillosis in the lung and the role of iron

BACKGROUND: Invasive aspergillosis is a severe infection of immunocompromised hosts, caused by the inhalation of the spores of the ubiquitous environmental molds of the Aspergillus genus. The innate immune response in this infection entails a series of complex and inter-related interactions between multiple recruited and resident cell populations with each other and with the fungal cell; in particular, iron is critical for fungal growth. RESULTS: A computational model of invasive aspergillosis is presented here; the model can be used as a rational hypothesis-generating tool to investigate host responses to this infection. Using a combination of laboratory data and published literature, an in silico model of a section of lung tissue was generated that includes an alveolar duct, adjacent capillaries, and surrounding lung parenchyma. The three-dimensional agent-based model integrates temporal events in fungal cells, epithelial cells, monocytes, and neutrophils after inhalation of spores with cellular dynamics at the tissue level, comprising part of the innate immune response. Iron levels in the blood and tissue play a key role in the fungus’ ability to grow, and the model includes iron recruitment and consumption by the different types of cells included. Parameter sensitivity analysis suggests the model is robust with respect to unvalidated parameters, and thus is a viable tool for an in silico investigation of invasive aspergillosis. CONCLUSIONS: Using laboratory data from a mouse model of invasive aspergillosis in the context of transient neutropenia as validation, the model predicted qualitatively similar time course changes in fungal burden, monocyte and neutrophil populations, and tissue iron levels. This model lays the groundwork for a multi-scale dynamic mathematical model of the immune response to Aspergillus species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0275-2) contains supplementary material, which is available to authorized users

A computational model of invasive aspergillosis in the lung and the role of iron.

BACKGROUND: Invasive aspergillosis is a severe infection of immunocompromised hosts, caused by the inhalation of the spores of the ubiquitous environmental molds of the Aspergillus genus. The innate immune response in this infection entails a series of complex and inter-related interactions between multiple recruited and resident cell populations with each other and with the fungal cell; in particular, iron is critical for fungal growth. RESULTS: A computational model of invasive aspergillosis is presented here; the model can be used as a rational hypothesis-generating tool to investigate host responses to this infection. Using a combination of laboratory data and published literature, an in silico model of a section of lung tissue was generated that includes an alveolar duct, adjacent capillaries, and surrounding lung parenchyma. The three-dimensional agent-based model integrates temporal events in fungal cells, epithelial cells, monocytes, and neutrophils after inhalation of spores with cellular dynamics at the tissue level, comprising part of the innate immune response. Iron levels in the blood and tissue play a key role in the fungus\u27 ability to grow, and the model includes iron recruitment and consumption by the different types of cells included. Parameter sensitivity analysis suggests the model is robust with respect to unvalidated parameters, and thus is a viable tool for an in silico investigation of invasive aspergillosis. CONCLUSIONS: Using laboratory data from a mouse model of invasive aspergillosis in the context of transient neutropenia as validation, the model predicted qualitatively similar time course changes in fungal burden, monocyte and neutrophil populations, and tissue iron levels. This model lays the groundwork for a multi-scale dynamic mathematical model of the immune response to Aspergillus species. BMC Syst Biol 2016 Apr 21; 10(1):3

Additional file 3 of A computational model of invasive aspergillosis in the lung and the role of iron

Experimental design and results of parameter sensitivity analysis. Parameters not validated by literature are altered to 10 %, 50 %, and 200 % of baseline values in order to determine the effect of each (one at a time). Relevant model dynamics are presented under both normal and neutropenic conditions (in.pdf format). (PDF 186 kb

Additional file 1 of A computational model of invasive aspergillosis in the lung and the role of iron

Overview, Design Concepts, and Details (ODD) protocol for the agent-based model. A complete description of the agent-based model, including process ordering, state variable values, and algorithm pseudocode (in.pdf format). (PDF 145 kb

Additional file 2 of A computational model of invasive aspergillosis in the lung and the role of iron

State variables for the agent-based model. Descriptions and values for all state variable values, organized by cell type (with global variables indicated as such). N(μ,σ)indicates values taken from a normal distribution with mean μ and standard deviation σ (in.pdf format). (PDF 985 kb