Adsorption of HSA, IgG and laminin-1 on model titania surfaces--effects of glow discharge treatment on competitively adsorbed film composition

This study investigated the effect of glow discharge treatment of titania surfaces on plasma protein adsorption, by means of ellipsometry and mechanically assisted SDS elution. The adsorption and film elution of three plasma proteins, viz. human serum albumin (HSA), human immunoglobulin G (IgG) and laminin-1, as well as competitive adsorption from a mixture of the three proteins, showed that the adsorbed amount of the individual proteins after 1 h increased in the order HSA 相似文献   

Peroxisome reintroduction in Hansenula polymorpha requires Pex25 and Rho1

We identified two proteins, Pex25 and Rho1, which are involved in reintroduction of peroxisomes in peroxisome-deficient yeast cells. These are, together with Pex3, the first proteins identified as essential for this process. Of the three members of the Hansenula polymorpha Pex11 protein family-Pex11, Pex25, and Pex11C-only Pex25 was required for reintroduction of peroxisomes into a peroxisome-deficient mutant strain. In peroxisome-deficient pex3 cells, Pex25 localized to structures adjacent to the ER, whereas in wild-type cells it localized to peroxisomes. Pex25 cells were not themselves peroxisome deficient but instead contained a slightly increased number of peroxisomes. Interestingly, pex11 pex25 double deletion cells, in which both peroxisome fission (due to the deletion of PEX11) and reintroduction (due to deletion of PEX25) was blocked, did display a peroxisome-deficient phenotype. Peroxisomes reappeared in pex11 pex25 cells upon synthesis of Pex25, but not of Pex11. Reintroduction in the presence of Pex25 required the function of the GTPase Rho1. These data therefore provide new and detailed insight into factors important for de novo peroxisome formation in yeast.     

Affecting Pseudomonas aeruginosa Phenotypic Plasticity by Quorum Sensing Dysregulation Hampers Pathogenicity in Murine Chronic Lung Infection

In Pseudomonas aeruginosa quorum sensing (QS) activates the production of virulence factors, playing a critical role in pathogenesis. Multiple negative regulators modulate the timing and the extent of the QS response either in the pre-quorum or post-quorum phases of growth. This regulation likely increases P. aeruginosa phenotypic plasticity and population fitness, facilitating colonization of challenging environments such as higher organisms. Accordingly, in addition to the factors required for QS signals synthesis and response, also QS regulators have been proposed as targets for anti-virulence therapies. However, while it is known that P. aeruginosa mutants impaired in QS are attenuated in their pathogenic potential, the effect of mutations causing a dysregulated timing and/or magnitude of the QS response has been poorly investigated so far in animal models of infection. In order to investigate the impact of QS dysregulation on P. aeruginosa pathogenesis in a murine model of lung infection, the QteE and RsaL proteins have been selected as representatives of negative regulators controlling P. aeruginosa QS in the pre- and post-quorum periods, respectively. Results showed that the qteE mutation does not affect P. aeruginosa lethality and ability to establish chronic infection in mice, despite causing a premature QS response and enhanced virulence factors production in test tube cultures compared to the wild type. Conversely, the post-quorum dysregulation caused by the rsaL mutation hampers the establishment of P. aeruginosa chronic lung infection in mice without affecting the mortality rate. On the whole, this study contributes to a better understanding of the impact of QS regulation on P. aeruginosa phenotypic plasticity during the infection process. Possible fallouts of these findings in the anti-virulence therapy field are also discussed.     

Submicronic Fungal Bioaerosols: High-Resolution Microscopic Characterization and Quantification

Submicronic particles released from fungal cultures have been suggested to be additional sources of personal exposure in mold-contaminated buildings. In vitro generation of these particles has been studied with particle counters, eventually supplemented by autofluorescence, that recognize fragments by size and discriminate biotic from abiotic particles. However, the fungal origin of submicronic particles remains unclear. In this study, submicronic fungal particles derived from Aspergillus fumigatus, A. versicolor, and Penicillium chrysogenum cultures grown on agar and gypsum board were aerosolized and enumerated using field emission scanning electron microscopy (FESEM). A novel bioaerosol generator and a fungal spores source strength tester were compared at 12 and 20 liters min⁻¹ airflow. The overall median numbers of aerosolized submicronic particles were 2 × 10⁵ cm⁻², 2.6 × 10³ cm⁻², and 0.9 × 10³ cm⁻² for A. fumigatus, A. versicolor, and P. chrysogenum, respectively. A. fumigatus released significantly (P < 0.001) more particles than A. versicolor and P. chrysogenum. The ratios of submicronic fragments to larger particles, regardless of media type, were 1:3, 5:1, and 1:2 for A. fumigatus, A. versicolor, and P. chrysogenum, respectively. Spore fragments identified by the presence of rodlets amounted to 13%, 2%, and 0% of the submicronic particles released from A. fumigatus, A. versicolor, and P. chrysogenum, respectively. Submicronic particles with and without rodlets were also aerosolized from cultures grown on cellophane-covered media, indirectly confirming their fungal origin. Both hyphae and conidia could fragment into submicronic particles and aerosolize in vitro. These findings further highlight the potential contribution of fungal fragments to personal fungal exposure.     

Embedding mRNA stability in correlation analysis of time-series gene expression data

Current methods for the identification of putatively co-regulated genes directly from gene expression time profiles are based on the similarity of the time profile. Such association metrics, despite their central role in gene network inference and machine learning, have largely ignored the impact of dynamics or variation in mRNA stability. Here we introduce a simple, but powerful, new similarity metric called lead-lag R(2) that successfully accounts for the properties of gene dynamics, including varying mRNA degradation and delays. Using yeast cell-cycle time-series gene expression data, we demonstrate that the predictive power of lead-lag R(2) for the identification of co-regulated genes is significantly higher than that of standard similarity measures, thus allowing the selection of a large number of entirely new putatively co-regulated genes. Furthermore, the lead-lag metric can also be used to uncover the relationship between gene expression time-series and the dynamics of formation of multiple protein complexes. Remarkably, we found a high lead-lag R(2) value among genes coding for a transient complex.