Development of a protein secretion system with the application of sec-dependent protein secretion components

In order to induce high levels of protein secretion, we have constructed a recombinant plasmid, designated pBP244, into which was incorporated key components of the type-II Sec-dependent secretion system, including LepB (signal peptidase), SecA (ATPase), and SecB (chaperone). The biological activities of the LepB, SecA, and SecB components expressed from genes harbored by pBP244 appeared to play their normal roles. In order to evaluate the protein secretion, a pspA (Streptococcus pneumoniae surface protein A) gene was cloned into pBP244, resulting in pBP438. S. typhimurium harboring pBP438 grown until the stationary phase, secreted a higher level of PspA into the culture supernatants than did the strain harboring pYA3494. The strain harboring pBP438 secreted a supernatant amount 1.71-fold, a periplasmic space amount 1.47-fold, and an outer membrane amount 1.49-fold higher than that of pYA3494. S. typhimurium chi8554 kept the Asd+ plasmid pBP244 and pBP438 for 60 generations in LB broth harboring DAP, thereby indicating that pBP244 and pBP438 were quite stable in the Salmonella strain.     

Optimal conditions for cryopreservation of primary chicken embryo kidney cells with dimethyl sulfoxide

Conditions were evaluated for optimum cryopreservation of primary chicken embryo kidney (CEK) cells. The recovery of viable CEK cells was best (50.8% viability) when the concentration of dimethyl sulfoxide (DMSO) in the freezing medium was 20% (v/v). The viability of primary CEK cells was not influenced by the concentration of calf serum in the freezing medium, the duration of storage at −70°C before storage in liquid nitrogen, cell concentration, or the method of addition or dilution of DMSO. Thawed cells recovered and grew in complete growth medium similarly to cells freshly isolated from kidney, and influenza viruses produced plaques in the monolayer. The cryopreservation procedures described here may facilitate maintenance of a standard stock of primary CEK cells for laboratories where preparation of primary CEK cells is not an option.     

Rho activation is required for transforming growth factor-beta-induced epithelial-mesenchymal transition in lens epithelial cells

Lens epithelial cells undergo epithelial-mesenchymal transition (EMT) after injury as in cataract extraction, leading to fibrosis of the lens capsule. We have recently shown that TGF-beta-induced EMT in lens epithelial cells depends on PI3 kinase/Akt signal pathway. In this report, we suggest Smad3 is necessary for TGF-beta-induced EMT by showing that the expression of dominant-negative Smad3 blocks the expression of alpha-smooth muscle actin (alpha-SMA) and morphological changes. We also show that TGF-beta induces a biphasic change in Rho activity, and that Y27632, a selective inhibitor of Rho effector ROCK, inhibits TGF-beta-induced EMT in vitro and in vivo. We finally show that Smad3 activation and Rho signal activation is independent each other. All of these findings suggest that Rho/ROCK activation together with Smad3 is necessary for TGF-beta-induced EMT in lens epithelial cells.     

Anaerobic treatment of highly concentrated aniline wastewater using packed-bed biofilm reactor

The performance of packed-bed biofilm reactor (PBBR) with self-floating bio-carriers was investigated to treat highly concentrated organic nitrogenous aniline wastewater with a COD value as high as 24,000 mg/L. With 45 vol% of carrier charge inside the reactor, the aniline wastewater can be effectively treated with 94% of COD removal efficiency at a low organic loading rate (OLR) of 0.9 kg COD/(m³ d). The removal efficiency decreased gradually down to 75% when OLR increased to 12.27 kg COD/(m³ d) that corresponded to 1 day of HRT. Separate tests with biofilm alone showed that the conversion contribution of the biofilm was about half of the overall COD conversion by the biofilm plus sludge system at the same OLRs of 3–4 kg COD/(m³ d), and that the biofilm had higher activity than suspended sludge. Ammonium released from decomposed aniline was increased gradually from 500 to 1700 mg/L with the OLR increase from 0.9 to 12.27 kg COD/(m³ d), which resulted in inhibitory effect to the microorganism due to the toxicity of free ammonia. Batch anaerobic toxicity tests showed that the biofilm was less sensitive to toxic compounds than suspended sludge and could tolerate higher concentration of free ammonia.     

SOCS-1 is a central mediator of steroid-increased thymocyte apoptosis and decreased survival following sepsis

Suppressor of Cytokine Signaling (SOCS) proteins are recently identified inhibitors/regulators of cytokine/growth factor signaling pathways. We have previously shown that SOCS-3 is upregulated in mice after sepsis induced by cecal ligation and puncture; however, the contribution of SOCS-1 to septic morbidity and mortality is unclear. In the present study, we characterized SOCS-1 expression in different tissues and delineated putative mechanisms effecting SOCS-1 expression in thymus from septic mice. We observed no difference in SOCS-1 expression in blood, peritoneal leukocytes, lung, and spleen taken from sham or septic animals at 24 h after surgery. In contrast, SOCS-1 expression in thymus declined significantly after sepsis and this down-regulation of SOCS-1 was associated with increased thymocyte apoptosis as well as augmented Bax recruitment to the mitochondria. Administration of RU-38486, a steroid receptor antagonist, reversed the above effects in the septic thymus. Furthermore, SOCS-1+/− mice showed a significant higher mortality when compared to SOCS-1+/+ mice after sepsis. Together, these results show that sepsis increases steroid-induced thymic lymphoid cell apoptosis, which is associated with reduced SOCS-1 expression and increased Bax translocation to mitochondria. Survival data suggests that SOCS-1 protein may play an important role in sepsis.     

Log-linear model-based multifactor dimensionality reduction method to detect gene gene interactions

MOTIVATION: The identification and characterization of susceptibility genes that influence the risk of common and complex diseases remains a statistical and computational challenge in genetic association studies. This is partly because the effect of any single genetic variant for a common and complex disease may be dependent on other genetic variants (gene-gene interaction) and environmental factors (gene-environment interaction). To address this problem, the multifactor dimensionality reduction (MDR) method has been proposed by Ritchie et al. to detect gene-gene interactions or gene-environment interactions. The MDR method identifies polymorphism combinations associated with the common and complex multifactorial diseases by collapsing high-dimensional genetic factors into a single dimension. That is, the MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups based on a comparison of the ratios of the numbers of cases and controls. When a high-order interaction model is considered with multi-dimensional factors, however, there may be many sparse or empty cells in the contingency tables. The MDR method cannot classify an empty cell as high risk or low risk and leaves it as undetermined. RESULTS: In this article, we propose the log-linear model-based multifactor dimensionality reduction (LM MDR) method to improve the MDR in classifying sparse or empty cells. The LM MDR method estimates frequencies for empty cells from a parsimonious log-linear model so that they can be assigned to high-and low-risk groups. In addition, LM MDR includes MDR as a special case when the saturated log-linear model is fitted. Simulation studies show that the LM MDR method has greater power and smaller error rates than the MDR method. The LM MDR method is also compared with the MDR method using as an example sporadic Alzheimer's disease.     

Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions

MOTIVATION: The identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases is a challenging task in genetic association studies. The multifactor dimensionality reduction (MDR) method has been proposed and implemented by Ritchie et al. (2001) to identify the combinations of multilocus genotypes and discrete environmental factors that are associated with a particular disease. However, the original MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups in an ad hoc manner based on a simple comparison of the ratios of the number of cases and controls. Hence, the MDR approach is prone to false positive and negative errors when the ratio of the number of cases and controls in a combination of genotypes is similar to that in the entire data, or when both the number of cases and controls is small. Hence, we propose the odds ratio based multifactor dimensionality reduction (OR MDR) method that uses the odds ratio as a new quantitative measure of disease risk. RESULTS: While the original MDR method provides a simple binary measure of risk, the OR MDR method provides not only the odds ratio as a quantitative measure of risk but also the ordering of the multilocus combinations from the highest risk to lowest risk groups. Furthermore, the OR MDR method provides a confidence interval for the odds ratio for each multilocus combination, which is extremely informative in judging its importance as a risk factor. The proposed OR MDR method is illustrated using the dataset obtained from the CDC Chronic Fatigue Syndrome Research Group. AVAILABILITY: The program written in R is available.     

PowerCore: a program applying the advanced M strategy with a heuristic search for establishing core sets

MOTIVATION: Core sets are necessary to ensure that access to useful alleles or characteristics retained in genebanks is guaranteed. We have successfully developed a computational tool named 'PowerCore' that aims to support the development of core sets by reducing the redundancy of useful alleles and thus enhancing their richness. RESULTS: The program, using a new approach completely different from any other previous methodologies, selects entries of core sets by the advanced M (maximization) strategy implemented through a modified heuristic algorithm. The developed core set has been validated to retain all characteristics for qualitative traits and all classes for quantitative ones. PowerCore effectively selected the accessions with higher diversity representing the entire coverage of variables and gave a 100% reproducible list of entries whenever repeated. AVAILABILITY: PowerCore software uses the .NET Framework Version 1.1 environment which is freely available for the MS Windows platform. The files can be downloaded from http://genebank.rda.go.kr/powercore/. The distribution of the package includes executable programs, sample data and a user manual.