Detection of cellular responses to toxicants by dielectrophoresis

The dielectrophoretic (DEP) crossover method has been applied to the detection of cell responses to toxicants. Time and dose responses of the human cultured leukemia (HL-60) line were measured for paraquat, styrene oxide (SO), N-nitroso-N-methylurea (NMU) and puromycin. These toxicants were chosen because of their different predominant mechanisms of action, namely membrane free radical attack, simultaneous membrane and nucleic acid attack, nucleic acid alkylation, and protein synthesis inhibition, respectively. For all treatments, the specific membrane capacitance (C_mem) of the cells decreased while the specific membrane conductance (G_mem) increased in dose- and time-dependent manners. The DEP responses correlated sensitively with alterations in cell surface morphology, especially folds, microvilli, and blebs, observed by scanning electron microscopy. The DEP method was more sensitive to agents that had a direct action on the membrane than to agents for which membrane alterations were secondary. The responses to paraquat and SO, which directly damaged the cell membrane, could be detected 15 min after exposure, while those for puromycin and NMU, which acted on intracellular targets, could be detected after 30 min. The detection times and dose sensitivity results showed that the DEP method is much faster and more sensitive than conventional cell and higher organism viability testing techniques. The feasibility of producing small instruments for toxicity detection and screening based on cellular dielectric responses is discussed.     

Online Respondent-Driven Sampling for Studying Contact Patterns Relevant for the Spread of Close-Contact Pathogens: A Pilot Study in Thailand

Background

Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens.

Materials and Methods

We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks.

Results

We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts.

Conclusions

Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks.     

CometChip: A High-throughput 96-Well Platform for Measuring DNA Damage in Microarrayed Human Cells

DNA damaging agents can promote aging, disease and cancer and they are ubiquitous in the environment and produced within human cells as normal cellular metabolites. Ironically, at high doses DNA damaging agents are also used to treat cancer. The ability to quantify DNA damage responses is thus critical in the public health, pharmaceutical and clinical domains. Here, we describe a novel platform that exploits microfabrication techniques to pattern cells in a fixed microarray. The ‘CometChip’ is based upon the well-established single cell gel electrophoresis assay (a.k.a. the comet assay), which estimates the level of DNA damage by evaluating the extent of DNA migration through a matrix in an electrical field. The type of damage measured by this assay includes abasic sites, crosslinks, and strand breaks. Instead of being randomly dispersed in agarose in the traditional assay, cells are captured into an agarose microwell array by gravity. The platform also expands from the size of a standard microscope slide to a 96-well format, enabling parallel processing. Here we describe the protocols of using the chip to evaluate DNA damage caused by known genotoxic agents and the cellular repair response followed after exposure. Through the integration of biological and engineering principles, this method potentiates robust and sensitive measurements of DNA damage in human cells and provides the necessary throughput for genotoxicity testing, drug development, epidemiological studies and clinical assays.     

NSIT: Novel Sequence Identification Tool

Novel sequences are DNA sequences present in an individual''s genome but absent in the human reference assembly. They are predicted to be biologically important, both individual and population specific, and consistent with the known human migration paths. Recent works have shown that an average person harbors 2–5 Mb of such sequences and estimated that the human pan-genome contains as high as 19–40 Mb of novel sequences. To identify them in a de novo genome assembly, some existing sequence aligners have been used but no computational method has been specifically proposed for this task. In this work, we developed NSIT (Novel Sequence Identification Tool), a software that can accurately and efficiently identify novel sequences in an individual''s de novo whole genome assembly. We identified and characterized 1.1 Mb, 1.2 Mb, and 1.0 Mb of novel sequences in NA18507 (African), YH (Asian), and NA12878 (European) de novo genome assemblies, respectively. Our results show very high concordance with the previous work using the respective reference assembly. In addition, our results using the latest human reference assembly suggest that the amount of novel sequences per individual may not be as high as previously reported. We additionally developed a graphical viewer for comparisons of novel sequence contents. The viewer also helped in identifying sequence contamination; we found 130 kb of Epstein-Barr virus sequence in the previously published NA18507 novel sequences as well as 287 kb of zebrafish repeats in NA12878 de novo assembly. NSIT requires 2GB of RAM and 1.5–2 hrs on a commodity desktop. The program is applicable to input assemblies with varying contig/scaffold sizes, ranging from 100 bp to as high as 50 Mb. It works in both 32-bit and 64-bit systems and outperforms, by large margins, other fast sequence aligners previously applied to this task. To our knowledge, NSIT is the first software designed specifically for novel sequence identification in a de novo human genome assembly.     

Oxidative DNA damage and influence of genetic polymorphisms among urban and rural schoolchildren exposed to benzene

Traffic related urban air pollution is a major environmental health problem in many large cities. Children living in urban areas are exposed to benzene and other toxic pollutants simultaneously on a regular basis. Assessment of benzene exposure and oxidative DNA damage in schoolchildren in Bangkok compared with the rural schoolchildren was studied through the use of biomarkers.Benzene levels in ambient air at the roadside adjacent to Bangkok schools was 3.95-fold greater than that of rural school areas. Personal exposure to benzene in Bangkok schoolchildren was 3.04-fold higher than that in the rural schoolchildren. Blood benzene, urinary benzene and urinary muconic acid (MA) levels were significantly higher in the Bangkok schoolchildren. A significantly higher level of 8-hydroxy-2′-deoxyguanosine (8-OHdG) in leukocytes and in urine was found in Bangkok children than in the rural children. There was a significant correlation between individual benzene exposure level and blood benzene (r_s = 0.193, P < 0.05), urinary benzene (r_s = 0.298, P < 0.05), urinary MA (r_s = 0.348, P < 0.01), and 8-OHdG in leukocyte (r_s = 0.130, P < 0.05). In addition, a significant correlation between urinary MA and 8-OHdG in leukocytes (r_s = 0.241, P < 0.05) was also found. Polymorphisms of various xenobiotic metabolizing genes responsible for susceptibility to benzene toxicity have been studied; however only the GSTM1 genotypes had a significant effect on urinary MA excretion.Our data indicates that children living in the areas of high traffic density are exposed to a higher level of benzene than those living in rural areas. Exposure to higher level of benzene in urban children may contribute to oxidative DNA damage, suggesting an increased health risk from traffic benzene emission.     

Potential health effects of exposure to carcinogenic compounds in incense smoke in temple workers

Incense smoke is a potential hazard to human health due to various airborne carcinogens emitted from incense burning. This study aimed to evaluate the potential health effects of exposure to benzene, 1,3-butadiene, and polycyclic aromatic hydrocarbons (PAHs) emitted from incense smoke in temple workers. Exposure and health risks were assessed through the measurement of ambient exposure as well as through the use of biomarkers of exposure and early biological effects. Ambient air measurement showed that incense burning generates significantly higher levels of airborne benzene (P<0.01), 1,3-butadiene (P<0.001) and total PAHs (P<0.01) inside the temples, compared to those of the control workplace. Temple workers were exposed to relatively high levels of benzene (45.90 microg/m(3)) 1,3-butadiene (11.29 microg/m(3)) and PAHs (19.56 ng/m(3)), which were significantly higher than those of control workers (P<0.001). The most abundant PAHs were chrysene, B[ghi]P, B[a]P, B[a]F and fluoranthene. Concentrations of B[a]P and B[a]P equivalents in air samples to which temple workers were exposed were 63- and 16-fold, higher, respectively, than those to which control subjects were exposed (P<0.001). Biomarkers of exposure to benzene (blood benzene and the urinary metabolites trans,trans-muconic acid and S-phenylmercapturic acid), 1,3-butadiene (urinary monohydroxy-butenyl mercapturic acid) and PAHs (1-hydroxypyrene) were all significantly higher in temple workers than those in control workers. DNA damage and DNA repair capacity were measured as biomarkers of early biological effects. Temple workers had a significant increase in DNA damage observed as a 2-fold increase in the levels of leukocyte 8-hydroxy-2'-deoxguanosine (8-OHdG) and DNA strand breaks (P<0.001). A significant reduction of DNA repair capacity in temple workers determined by the radiation challenge assay was also observed. These results indicate that exposure to carcinogens emitted from incense burning may increase health risk for the development of cancer in temple workers.     

Exposure assessment of benzene in Thai workers, DNA-repair capacity and influence of genetic polymorphisms

Exposure to benzene can cause DNA damage and the subsequent development of cancer. In this study, study subjects were 31 laboratory workers at a petrochemical factory and 31 gasoline service attendants. Control subjects were 34 workers from a mail sorting service center. Occupational exposures to benzene were assessed using biomarkers of exposure in blood and urine. Induction of DNA-repair capacity was assessed as a biomarker of early effect. The effects of polymorphisms in a metabolizing gene (CYP2E1), in detoxification genes (NQO1 and GSTT1), and in a DNA-repair gene (XRCC1, codon 399) on biomarker levels were evaluated. The mean individual benzene exposure of laboratory workers (24.40+/-5.82 ppb) and that of gasoline service attendants (112.41+/-13.92 ppb) were significantly higher than in controls (1.39+/-0.17 ppb, p<0.001). Blood benzene levels of laboratory workers (169.12+/-30.60 ppt) and gasoline service attendants (483.46+/-59.62 ppt) were significantly higher than those of the controls (43.30+/-4.89 ppt, p<0.001). Trans,trans-muconic acid levels in post-shift urine samples collected from laboratory workers (0.14+/-0.02 mg/g creatinine) and gasoline service attendants (0.20+/-0.02 mg/g creatinine) were significantly higher than in urine samples of controls (0.04+/-0.01 mg/g creatinine, p<0.001). The level of benzene exposure was correlated with blood benzene levels (R2=0.65, p<0.01) and post-shift urinary trans,trans-muconic acid concentrations (R2=0.49, p<0.01). As a biomarker of early effect, DNA-repair capacity was assessed by use of the cytogenetic challenge assay, i.e., chromosomal aberrations in peripheral lymphocytes were assessed after challenging blood cultures with 1 Gy gamma radiation. A significantly lower DNA-repair capacity--determined as dicentrics in laboratory workers (0.17 per metaphase cell) and in gasoline service attendants (0.19 per metaphase cell) compared with controls (0.12 per metaphase cell, p<0.001)--was observed. The frequency of deletions in laboratory workers (0.22 per metaphase cell) and gasoline service attendants (0.39 per metaphase cell) were significantly higher than in control workers (0.16 per metaphase cell, p<0.01 and p<0.001, respectively). An increase in radiation-induced dicentrics and deletions indicate a lower DNA-repair capacity in benzene-exposed workers. The influence of genetic polymorphisms on the biomarkers was assessed. Benzene-exposed workers who carried CYP2E1*1/*5 or *5/*5 genotypes excreted slightly higher levels of trans,trans-muconic acid than workers who carried the CYP2E1*1/*1 genotype. In this study, NQO1 and GSTT1 genotypes did not have any effect on the levels of trans,trans-muconic acid. In the case of XRCC1, laboratory workers with 399Arg/Gln or Gln/Gln had a lower DNA-repair capacity--measured as radiation-induced frequency of dicentrics and deletions--than those with the 399Arg/Arg genotype (p<0.01). Our results show that biomarkers of internal dose and early biological effect in people occupationally exposed to benzene are influenced by genetic polymorphisms in susceptibility genes.     

The Spatial Dynamics of Dengue Virus in Kamphaeng Phet,Thailand

Background

Dengue is endemic to the rural province of Kamphaeng Phet, Northern Thailand. A decade of prospective cohort studies has provided important insights into the dengue viruses and their generated disease. However, as elsewhere, spatial dynamics of the pathogen remain poorly understood. In particular, the spatial scale of transmission and the scale of clustering are poorly characterized. This information is critical for effective deployment of spatially targeted interventions and for understanding the mechanisms that drive the dispersal of the virus.

Methodology/Principal Findings

We geocoded the home locations of 4,768 confirmed dengue cases admitted to the main hospital in Kamphaeng Phet province between 1994 and 2008. We used the phi clustering statistic to characterize short-term spatial dependence between cases. Further, to see if clustering of cases led to similar temporal patterns of disease across villages, we calculated the correlation in the long-term epidemic curves between communities. We found that cases were 2.9 times (95% confidence interval 2.7–3.2) more likely to live in the same village and be infected within the same month than expected given the underlying spatial and temporal distribution of cases. This fell to 1.4 times (1.2–1.7) for individuals living in villages 1 km apart. Significant clustering was observed up to 5 km. We found a steadily decreasing trend in the correlation in epidemics curves by distance: communities separated by up to 5 km had a mean correlation of 0.28 falling to 0.16 for communities separated between 20 km and 25 km. A potential explanation for these patterns is a role for human movement in spreading the pathogen between communities. Gravity style models, which attempt to capture population movement, outperformed competing models in describing the observed correlations.

Conclusions

There exists significant short-term clustering of cases within individual villages. Effective spatially and temporally targeted interventions deployed within villages may target ongoing transmission and reduce infection risk.