Peroxiredoxin 3 Is a Redox-Dependent Target of Thiostrepton in Malignant Mesothelioma Cells

Thiostrepton (TS) is a thiazole antibiotic that inhibits expression of FOXM1, an oncogenic transcription factor required for cell cycle progression and resistance to oncogene-induced oxidative stress. The mechanism of action of TS is unclear and strategies that enhance TS activity will improve its therapeutic potential. Analysis of human tumor specimens showed FOXM1 is broadly expressed in malignant mesothelioma (MM), an intractable tumor associated with asbestos exposure. The mechanism of action of TS was investigated in a cell culture model of human MM. As for other tumor cell types, TS inhibited expression of FOXM1 in MM cells in a dose-dependent manner. Suppression of FOXM1 expression and coincidental activation of ERK1/2 by TS were abrogated by pre-incubation of cells with the antioxidant N-acetyl-L-cysteine (NAC), indicating its mechanism of action in MM cells is redox-dependent. Examination of the mitochondrial thioredoxin reductase 2 (TR2)-thioredoxin 2 (TRX2)-peroxiredoxin 3 (PRX3) antioxidant network revealed that TS modifies the electrophoretic mobility of PRX3. Incubation of recombinant human PRX3 with TS in vitro also resulted in PRX3 with altered electrophoretic mobility. The cellular and recombinant species of modified PRX3 were resistant to dithiothreitol and SDS and suppressed by NAC, indicating that TS covalently adducts cysteine residues in PRX3. Reduction of endogenous mitochondrial TRX2 levels by the cationic triphenylmethane gentian violet (GV) promoted modification of PRX3 by TS and significantly enhanced its cytotoxic activity. Our results indicate TS covalently adducts PRX3, thereby disabling a major mitochondrial antioxidant network that counters chronic mitochondrial oxidative stress. Redox-active compounds like GV that modify the TR2/TRX2 network may significantly enhance the efficacy of TS, thereby providing a combinatorial approach for exploiting redox-dependent perturbations in mitochondrial function as a therapeutic approach in mesothelioma

Adenovirus-associated health risks for recreational activities in a multi-use coastal watershed based on site-specific quantitative microbial risk assessment

We used site-specific quantitative microbial risk assessment (QMRA) to assess the probability of adenovirus illness for three groups of swimmers: adults with primary contact, children with primary contact, and secondary contact regardless of age. Human enteroviruses and adenoviruses were monitored by qPCR in a multi-use watershed and Adenovirus type 40/41 was detected in 11% of 73 samples, ranging from 147 to 4117 genomes per liter. Enterovirus was detected only once (32 genomes per liter). Seven of eight virus detections occurred when E. coli concentrations were below the single sample maximum water quality criterion for contact recreation, and five of eight virus detections occurred when fecal coliforms were below the corresponding criterion. We employed dose-harmonization to convert viral genome measurements to TCID50 values needed for dose–response curves. The three scenarios considered different amounts of water ingestion and Monte Carlo simulation was used to account for the variability associated with the doses. The mean illness risk in children based on adenovirus measurements obtained over 11 months was estimated to be 3.5%, which is below the 3.6% risk considered tolerable by the current United States EPA recreational criteria for gastrointestinal illnesses (GI). The mean risks of GI illness for adults and secondary contact were 1.9% and 1.0%, respectively. These risks changed appreciably when different distributions were fitted to the data as determined by Monte Carlo simulations. In general, risk was at a maximum for the log-logistic distribution and lowest for the hockey stick distribution in all three selected scenarios. Also, under default assumptions, the risk was lowered considerably when assuming that only a small proportion of Adenovirus 40/41 (3%) was as infectious as Adenovirus type 4, compared to the assumption that all genomes were Adenovirus 4. In conclusion, site-specific QMRA on water-borne adenoviruses in this watershed provided a similar level of protection against public health risks as would be obtained by enumeration of fecal indicator bacteria under the new U.S. EPA guidelines

Quantitative microbial risk assessment to estimate the risk of diarrheal diseases from fresh produce consumption in India

This study estimates illness (diarrhea) risks from fecal pathogens that can be transmitted via fecal-contaminated fresh produce. To do this, a quantitative microbial risk assessment (QMRA) framework was developed in National Capital Region, India based on bacterial indicator and pathogen data from fresh produce wash samples collected at local markets. Produce wash samples were analyzed for fecal indicator bacteria (Escherichia coli, total Bacteroidales) and pathogens (Salmonella, Shiga-toxin producing E. coli (STEC), enterohemorrhagic E. coli (EHEC)). Based on the E. coli data and on literature values for Cryptosporidium and norovirus, the annual mean diarrhea risk posed by ingestion of fresh produce ranged from 18% in cucumbers to 59% in cilantro for E. coli O157:H7, and was <0.0001% for Cryptosporidium; for norovirus the risk was 11% for cucumbers and up to 46% for cilantro. The risks were drastically reduced, from 59% to 4% for E. coli O157:H7, and from 46% to 2% for norovirus for cilantro in post-harvest washing and disinfection scenario. The present QMRA study revealed the potential hazards of eating raw produce and how post-harvest practices can reduce the risk of illness. The results may lead to better food safety surveillance systems and use of hygienic practices pre- and post-harvest

Drinking Water Safety: Role of Hand Hygiene, Sanitation Facility, and Water System in Semi-Urban Areas of India.

Poor drinking water quality is one of the main causes of acute diarrheal disease in developing countries. The study investigated the relationship between fecal contamination of hands, stored drinking water, and source waters in India. We further evaluated the environmental and behavioral factors associated with recontamination of water between collection and consumption. The bacterial contamination, that is, Escherichia coli (log10 most probable number per two hands), found on mothers' hands (mean = 1.11, standard deviation [SD] = 1.2, N = 152) was substantially higher than that on their children younger than 5 years (mean = 0.64, SD = 1.0, and N = 152). We found a low level of E. coli (&lt; 1 per 100 mL) in the source water samples; however, E. coli contamination in stored drinking water was above the recommended guidelines of the World Health Organization. The study also found that E. coli on hands was significantly associated with E. coli in the stored drinking water (P &lt; 0.001). Moreover, E. coli was positively associated with gastrointestinal symptoms (odds ratio 1.42, P &lt; 0.05). In the households with elevated levels (&gt; 100 E. coli/100 mL) of fecal contamination, we found that 43.5% had unimproved sanitation facilities, poor water handling practices, and higher diarrheal incidences. The water quality deterioration from the source to the point of consumption is significant. This necessitates effective interventions in collection, transport, storage, and extraction practices when hand-water contact is likely to occur. These findings support the role of hands in the contamination of stored drinking water and suggest that clean source water does not guarantee safe water at the point of consumption

Data fitting approach more critical than exposure scenarios and treatment of censored data for quantitative microbial risk assessment

Recreational waters are a source of many diseases caused by human viral pathogens, including norovirus genogroup II (NoV GII) and enterovirus (EV). Water samples from the Arenales river in Salta, Argentina, were concentrated by ultrafiltration and analyzed for the concentrations of NoV GII and EV by quantitative PCR. Out of 65 samples, 61 and 59 were non-detects (below the Sample Limit of Detection limit, SLOD) for EV and NoV GII, respectively. We hypothesized that a finite number of environmental samples would lead to different conclusions regarding human health risks based on how data were treated and fitted to existing distribution functions. A quantitative microbial risk assessment (QMRA) was performed and the risk of infection was calculated using: (a) two methodological approaches to find the distributions that best fit the data sets (methods H and R), (b) four different exposure scenarios (primary contact for children and adults and secondary contact by spray inhalation/ingestion and hand-to-mouth contact), and (c) five alternatives for treating censored data. The risk of infection for NoV GII was much higher (and exceeded in most cases the acceptable value established by the USEPA) than for EV (in almost all the scenarios within the recommended limit), mainly due to the low infectious dose of NoV. The type of methodology used to fit the monitoring data was critical for these datasets with numerous non-detects, leading to very different estimates of risk. Method R resulted in higher projected risks than Method H. Regarding the alternatives for treating censored data, replacing non-detects by a unique value like the average or median SLOD to simplify the calculations led to the loss of information about the particular characteristics of each sample. In addition, the average SLOD was highly impacted by extreme values (due to events such as precipitations or point source contamination). Instead, using the SLOD or half- SLOD captured the uniqueness of each sample since they account for the history of the sample including the concentration procedure and the detection method used. Finally, substitution of non-detects by Zero is not realistic since a negative result would be associated with a SLOD that can change by developing more efficient and sensitive methodology; hence this approach would lead to an underestimation of the health risk. Our findings suggest that in most cases the use of the half-SLOD approach is appropriate for QMRA modeling.Fil: Poma, Hugo Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; ArgentinaFil: Kundu, Arti. University of California; Estados UnidosFil: Wuertz, Stefan. University of California; Estados Unidos. Nanyang Technological University.; SingapurFil: Rajal, Verónica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina. Nanyang Technological University.; Singapu