Comparison of Proliferation and Genomic Instability Responses to WRN Silencing in Hematopoietic HL60 and TK6 Cells

BACKGROUND: Werner syndrome (WS) results from defects in the RecQ helicase (WRN) and is characterized by premature aging and accelerated tumorigenesis. Contradictorily, WRN deficient human fibroblasts derived from WS patients show a characteristically slower cell proliferation rate, as do primary fibroblasts and human cancer cell lines with WRN depletion. Previous studies reported that WRN silencing in combination with deficiency in other genes led to significantly accelerated cellular proliferation and tumorigenesis. The aim of the present study was to examine the effects of silencing WRN in p53 deficient HL60 and p53 wild-type TK6 hematopoietic cells, in order to further the understanding of WRN-associated tumorigenesis. METHODOLOGY/PRINCIPAL FINDINGS: We found that silencing WRN accelerated the proliferation of HL60 cells and decreased the cell growth rate of TK6 cells. Loss of WRN increased DNA damage in both cell types as measured by COMET assay, but elicited different responses in each cell line. In HL60 cells, but not in TK6 cells, the loss of WRN led to significant increases in levels of phosphorylated RB and numbers of cells progressing from G1 phase to S phase as shown by cell cycle analysis. Moreover, WRN depletion in HL60 cells led to the hyper-activation of homologous recombination repair via up-regulation of RAD51 and BLM protein levels. This resulted in DNA damage disrepair, apparent by the increased frequencies of both spontaneous and chemically induced structural chromosomal aberrations and sister chromatid exchanges. CONCLUSIONS/SIGNIFICANCE: Together, our data suggest that the effects of WRN silencing on cell proliferation and genomic instability are modulated probably by other genetic factors, including p53, which might play a role in the carcinogenesis induced by WRN deficiency

A probabilistic Risk Forecast of Accidental Oil Spills from Vessels in Luoyuan Bay, Fujian Province, PRC

Marine environment and resources have always been and continue to be an important support for human existence and development. However, the increasing interferences by various types of human activities have made marine and coastal ecosystem under heavier pressure. With the rapid development of shipping industry, especially ship transportation of petroleum, accidental oil spills have been one example of the human pressure and constituted one of the biggest threats to marine ecosystem. Marine oil spill accidents have also brought huge economic losses to local fishery, aquaculture, tourism and etc. Therefore, it is important to forecast and cut the risk of marine accidental oil spills. This paper focuses on the probability for potential future oil spill accidents in Luoyuan Bay. Based on the predicted number of vessels in Luoyuan Bay in the future, we estimate the foundational probability of shipping accident and then forecast the probabilistic risk of oil spill accidents using methodologies of probability and mathematical statistics. By calculating the probability of oil spills from oil tankers of different tonnages, we also predict the spilled oil quantity at one time and its diffusion area. The results indicate that the foundational probability is 0.361x10(-4)/S in the next S years, and the probability of oil spills from vessels is 0.0925, implying that the oil spill accidents may occur almost once every 10 years. The possible spilled oil quantity at one time is 57.3 tons and the oil diffusion area may reach 0.64km(2) after one tidal cycle. Finally, we put forward some relevant measures for the risk prevention of oil spill accidents in Luoyuan Bay. (C) 2010 Published by Elsevier Ltd

Characterization of changes in gene expression and biochemical pathways at low levels of benzene exposure.

Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from <1 ppm to >10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and CYP2E1. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings

Characterization of changes in gene expression and biochemical pathways at low levels of benzene exposure

Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from 10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and CYP2E1. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings

Characterization of Changes in Gene Expression and Biochemical Pathways at Low Levels of Benzene Exposure

<div><p>Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from <1 ppm to >10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and <i>CYP2E1</i>. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings.</p></div

Median and 95% confidence interval (CI) estimates of the rate of change of marginal effect of benzene exposure below 1 ppm (/ – see equations (9) and (12)) and above 1 ppm (/ - see equations (10) and (13)) and the change in absolute rate of change of the marginal effects from below 1 ppm to above 1 ppm (/ – see equations (11) and (14)) for the first two principal components of the Acute Myeloid Leukemia pathway and six chosen genes of interest.

<p>Median and 95% confidence interval (CI) estimates of the rate of change of marginal effect of benzene exposure below 1 ppm (/ – see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091828#pone.0091828.e050" target="_blank">equations (9</a>) and (12)) and above 1 ppm (/ - see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091828#pone.0091828.e051" target="_blank">equations (10</a>) and (13)) and the change in absolute rate of change of the marginal effects from below 1 ppm to above 1 ppm (/ – see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091828#pone.0091828.e055" target="_blank">equations (11</a>) and (14)) for the first two principal components of the Acute Myeloid Leukemia pathway and six chosen genes of interest.</p

Responses of selected genes associated with the leukemia disease process.

<p>Non-parametric model fits to the expression response of the probes corresponding to six genes known to be associated with AML, with air-benzene concentrations in parts per million. Note the responses here are log fold-changes in expression. The dot-dashed horizontal line at a log fold change value equal to zero indicates the no-effect response. The gene names along with the corresponding probe id number on the microarray in parentheses are provided for each gene. The small vertical ticks on the x-axis denote doses to which one or more subjects in the study were exposed and consequently the doses for which data for all covariates under consideration were available. The three red ‘x’s above these ticks indicate the doses that there used to compare the rate of change of the marginal effect of benzene exposure from 0.001 to 1 ppm air benzene to the corresponding rate from 1 to 10 ppm air benzene.</p