Ciprofloxacin- and azithromycin-resistant bacteria in a wastewater treatment plant.

The occurrence of antibiotic-resistant bacteria (ARB) in wastewater treatment plants (WWTPs) has become an occupational and environmental concern. WWTPs are engineered systems that treat wastewater to meet public health standards before release into the environment. The residuals, as either effluent or solids, are then discharged or beneficially recycled into the environment. Since these wastes contain a diverse array of microorganisms, some of which are resistant to commonly used antibiotics, there is a potential for these organisms to spread in the environment via residual recycling and effluent discharge. Human infections with ARB are increasing, and it is not well known how the interaction between humans and the environment plays a role in this process. WWTP workers, who are on the front lines, may come into direct contact with materials containing these microbes. This study aimed to determine the number of ARB present in both air and sewage sludges in a WWTP using nonselective media supplemented with two antibiotics (ciprofloxacin and azithromycin). The densities of total heterotrophic bacteria, ciprofloxacin-resistant bacteria, and azithromycin-resistant bacteria were 7.82 × 105 - 4.7 × 109, 7.87 × 103 - 1.05 × 108, and 2.27 × 105 - 1.16 × 109 CFU/g, respectively. The prevalence [(concentration on medium with antibiotics/concentration on medium without antibiotics) × 100] of ciprofloxacin-resistant bacteria in treated sludge was twice as low as in digested sludge and approximately three times lower than in raw sludge. For azithromycin, the prevalence of resistant bacteria in treated sludge was about the same in digested and nearly twice lower than in raw sludge. Despite a marked reduction in the mean prevalence of resistant bacteria in dewatered treated sludge for both antibiotics, these differences were not significant. The highest prevalence of antibiotic resistance was observed for azithromycin. Similarly, the prevalence of airborne azithromycin-resistant bacteria inside the belt filter press room (BFPR) was nearly seven times higher than the prevalence of airborne ciprofloxacin-resistant bacteria. These concentrations of ARB were not negligible and may represent an exposure pathway for some workers in WWTPs.

Setting impurity limits for endogenous substances: Recommendations for a harmonized procedure and an example using fatty acids.

Endogenous substances, such as fatty, amino, and nucleic acids, are often purposefully used in parenterally pharmaceuticals, but may be present as impurities. Currently, no consensus guidance exists on setting impurity limits for these substances. Specific procedures are needed, as the amount and types of toxicity data available for endogenous substances are typically far less than those for other chemical impurities. Additionally, the parenteral route of administration of these substances is inherently non-physiological, resulting in potentially different or increased severity of toxicity. Risk Assessment Process Maps (RAPMAPs) are proposed as a model to facilitate the development of health-based exposure limits (HBELs) for endogenous substances. This yielded a framework that was applied to derive HBELs for several fatty acids commonly used in parenteral pharmaceuticals. This approach was used to derive HBELs with further vetting based on anticipated perturbations in physiological serum levels, impacts of dose-rate, and consideration of intermittent dosing. Parenteral HBELs of 100-500 mg/day were generated for several fatty acids, and a proposed class-based limit of 50 mg/day to be used in the absence of chemical-specific data. This default limit is consistent with the low toxicity of this chemical class and ICH Q3C value for Class 3 solvents.

Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data.

The Library of Integrated Network-based Cellular Signatures (LINCS) program is a national consortium funded by the NIH to generate a diverse and extensive reference library of cell-based perturbation-response signatures, along with novel data analytics tools to improve our understanding of human diseases at the systems level. In contrast to other large-scale data generation efforts, LINCS Data and Signature Generation Centers (DSGCs) employ a wide range of assay technologies cataloging diverse cellular responses. Integration of, and unified access to LINCS data has therefore been particularly challenging. The Big Data to Knowledge (BD2K) LINCS Data Coordination and Integration Center (DCIC) has developed data standards specifications, data processing pipelines, and a suite of end-user software tools to integrate and annotate LINCS-generated data, to make LINCS signatures searchable and usable for different types of users. Here, we describe the LINCS Data Portal (LDP) (http://lincsportal.ccs.miami.edu/), a unified web interface to access datasets generated by the LINCS DSGCs, and its underlying database, LINCS Data Registry (LDR). LINCS data served on the LDP contains extensive metadata and curated annotations. We highlight the features of the LDP user interface that is designed to enable search, browsing, exploration, download and analysis of LINCS data and related curated content.

Estimated dermal exposure to nebulized pharmaceuticals for a simulated home healthcare worker scenario.

The duties of home healthcare workers are extensive. One important task that is frequently performed by home healthcare workers is administration of nebulized medications, which may lead to significant dermal exposure. In this simulation study conducted in an aerosol exposure chamber, we administered a surrogate of nebulizer-delivered medications (dispersed sodium chloride, NaCl) to a patient mannequin. We measured the amount of NaCl deposited on the exposed surface of the home healthcare worker mannequin, which represented the exposed skin of a home healthcare worker. Factors such as distance and position of the home healthcare worker, room airflow rate and patient's inspiratory rate were varied to determine their effects on dermal exposure. There was a 2.78% reduction in dermal deposition for every centimeter the home healthcare worker moved away from the patient. Increasing the room's air exchange rate by one air change per hour increased dermal deposition by about 2.93%, possibly due to a decrease in near field particle settling. For every 10-degrees of arc the home healthcare worker is positioned from the left side of the patient toward the right and thus moving into the ventilation airflow direction, dermal deposition increased by about 4.61%. An increase in the patient's inspiratory rate from 15-30 L/min resulted in an average of 14.06% reduction in dermal deposition for the home healthcare worker, reflecting a relative increase in the aerosol fraction inhaled by the patient. The findings of this study elucidate the interactions among factors that contribute to dermal exposure to aerosolized pharmaceuticals administered by home healthcare workers. The results presented in this paper will help develop recommendations on mitigating the health risks related to dermal exposure of home healthcare workers.

Application of the Public Health Exposome Framework to Estimate Phenotypes of Resilience in a Model Ohio African-American Women's Cohort.

We report integration of the United States Environmental Protection Agency's (USEPA) United States Environmental Justice Screen (EJSCREEN) database with our Public Health Exposome dataset to interrogate 9232 census blocks to model the complexity of relationships among environmental and socio-demographic variables toward estimating adverse pregnancy outcomes [low birth weight (LBW) and pre-term birth (PTB)] in all Ohio counties. Using a hill-climbing algorithm in R software, we derived a Bayesian network that mapped all controlled associations among all variables available by applying a mapping algorithm. The results revealed 17 environmental and socio-demographic variables that were represented by nodes containing 69 links accounting for a network with 32.85% density and average degree of 9.2 showing the most connected nodes in the center of the model. The model predicts that the socio-economic variables low income, minority, and under age five populations are correlated and associated with the environmental variables; particulate matter (PM2.5) level in air, proximity to risk management facilities, and proximity to direct discharges in water are linked to PTB and LBW in 88 Ohio counties. The methodology used to derive significant associations of chemical and non-chemical stressors linked to PTB and LBW from indices of geo-coded environmental neighborhood deprivation serves as a proxy for design of an African-American women's cohort to be recruited in Ohio counties from federally qualified community health centers within the 9232 census blocks. The results have implications for the development of severity scores for endo-phenotypes of resilience based on associations and linkages for different chemical and non-chemical stressors that have been shown to moderate cardio-metabolic disease within a population health context.

An occupational exposure limit (OEL) approach to protect home healthcare workers exposed to common nebulized drugs.

Home healthcare is a growing area of employment. Assessment of occupational health risks to home health care workers (HHCWs) is important because in many cases the unique characteristics of the home environment do not facilitate the level of exposure control afforded to caregivers in hospitals and other fixed patient care sites. This assessment is focused on health risks to HHCWs from exposure to pharmaceutical drugs used to treat asthma and other respiratory diseases, which are commonly administered to patients in aerosolized form via nebulizers. We developed risk-based exposure limits for workers in the form of occupational exposure limits (OEL) values for exposure to nebulized forms of the three most common drugs administered by this method: albuterol, ipratropium, and budesonide. The derived OEL for albuterol was 2 µg/day, for ipratropium was 30 µg/day, and for budesonide was 11 µg/day. These OELs were derived based on human effect data and adjusted for pharmacokinetic variability and areas of uncertainty relevant to the underlying data (human and non-human) available for each drug. The resulting OEL values provide an input to the occupational risk assessment process to allow for comparisons to HHCW exposure that will guide risk management and exposure control decisions.

Update: Mode of action (MOA) for liver tumors induced by oral exposure to 1,4-dioxane.

Previous work has shown that the weight of evidence supports the hypothesis that 1,4-dioxane causes liver tumors in rodents through cytotoxicity and subsequent regenerative hyperplasia. Questions regarding a lack of concordant findings for this mode of action (MOA) in mice have not been resolved, however. In the current work, a reanalysis of data from two chronic mouse cancer bioassays on 1,4-dioxane, one 13-week mouse study, seven rat cancer bioassays, coupled with other data such as 1,4-dioxane's negative mutagenicity, its lack of up-regulated DNA repair, and the appearance of liver tumors with a high background incidence, support the conclusion that rodent liver tumors, including those in mice, are evoked by a regenerative hyperplasia MOA. The initiating event for this MOA is metabolic saturation of 1,4-dioxane. Above metabolic saturation, higher doses of the parent compound cause an ever increasing toxicity in the rodent liver as evidenced by higher blood levels of enzymes indicative of liver cell damage and associated histopathology that occurs in a dose and time related manner. Importantly, alternative modes of action can be excluded. The observed liver toxicity has a threshold in the dose scale at or below levels that saturate metabolism, and generally in the range of 9.6-42 mg/kg-day for rats and 57 to 66 mg/kg-day for mice. It follows that threshold approaches to the assessment of this chemical's toxicity are supported by the non-mutagenic, metabolic saturation kinetics, and cytotoxicity-generated regenerative repair information available for 1,4-dioxane promoted rodent liver tumors.

Toxicokinetic and toxicodynamic considerations when deriving health-based exposure limits for pharmaceuticals.

The purpose of this paper is to describe the use of toxicokinetic (TK) and toxicodynamic (TD) data in setting acceptable daily exposure (ADE) values and occupational exposure limits (OELs). Use of TK data can provide a more robust exposure limit based on a rigorous evaluation of systemic internal dose. Bioavailability data assist in extrapolating across different routes of exposure to be protective for route-based differences of exposure. Bioaccumulation data enable extrapolation to chronic exposures when the point of departure (PoD) is from a short-term critical study. Applied in the context of chemical-specific adjustment factors (CSAFs), TK data partially replace traditional default adjustment factors for interspecies extrapolation (extrapolation from studies conducted in animals to humans) and intraspecies variability (to account for human population variability). Default adjustments of 10-fold each for interspecies and intraspecies extrapolation are recommended in several guidelines, although some organization recommend other values. Such default factors may overestimate variability for many APIs, while not being sufficiently protective for variability with other APIs. For this reason, the use of chemical specific TK and TD data are preferred. Making full use of existing TK and TD data reduces underlying uncertainties, increases transparency, and ensures that resulting ADEs reflect the best available science.

Genome-wide signatures of transcription factor activity: connecting transcription factors, disease, and small molecules.

Identifying transcription factors (TF) involved in producing a genome-wide transcriptional profile is an essential step in building mechanistic model that can explain observed gene expression data. We developed a statistical framework for constructing genome-wide signatures of TF activity, and for using such signatures in the analysis of gene expression data produced by complex transcriptional regulatory programs. Our framework integrates ChIP-seq data and appropriately matched gene expression profiles to identify True REGulatory (TREG) TF-gene interactions. It provides genome-wide quantification of the likelihood of regulatory TF-gene interaction that can be used to either identify regulated genes, or as genome-wide signature of TF activity. To effectively use ChIP-seq data, we introduce a novel statistical model that integrates information from all binding "peaks" within 2 Mb window around a gene's transcription start site (TSS), and provides gene-level binding scores and probabilities of regulatory interaction. In the second step we integrate these binding scores and regulatory probabilities with gene expression data to assess the likelihood of True REGulatory (TREG) TF-gene interactions. We demonstrate the advantages of TREG framework in identifying genes regulated by two TFs with widely different distribution of functional binding events (ERα and E2f1). We also show that TREG signatures of TF activity vastly improve our ability to detect involvement of ERα in producing complex diseases-related transcriptional profiles. Through a large study of disease-related transcriptional signatures and transcriptional signatures of drug activity, we demonstrate that increase in statistical power associated with the use of TREG signatures makes the crucial difference in identifying key targets for treatment, and drugs to use for treatment. All methods are implemented in an open-source R package treg. The package also contains all data used in the analysis including 494 TREG binding profiles based on ENCODE ChIP-seq data. The treg package can be downloaded at http://GenomicsPortals.org.

Mode of action analysis for liver tumors from oral 1,4-dioxane exposures and evidence-based dose response assessment.

1,4-Dioxane is found in consumer products and is used as a solvent in manufacturing. Studies in rodents show liver tumors to be consistently reported after chronic oral exposure. However, there were differences in the reporting of non-neoplastic lesions in the livers of rats and mice. In order to clarify these differences, a reread of mouse liver slides from the 1978 NCI bioassay on 1,4-dioxane in drinking water was conducted. This reread clearly identified dose-related non-neoplastic changes in the liver; specifically, a dose-related increase in the hypertrophic response of hepatocytes, followed by necrosis, inflammation and hyperplastic hepatocellular foci. 1,4-Dioxane does not cause point mutations, DNA repair, or initiation. However, it appears to promote tumors and stimulate DNA synthesis. Using EPA Guidelines (2005), the weight of the evidence suggests that 1,4-dioxane causes liver tumors in rats and mice through cytotoxicity followed by regenerative hyperplasia. Specific key events in this mode of action are identified. A Reference Dose (RfD) of 0.05mg/kgday is proposed to protect against regenerative liver hyperplasia based on a benchmark dose (BMD) approach. Based on this RfD, a maximum contaminant level goal of 350µg/L is proposed using a default relative source contribution for water of 20%.

Selective Serotonin Reuptake Inhibitors and Other Treatment Modalities for Deep Space Missions.

INTRODUCTION: As humankind ventures further into the depths of space, planning is already underway for long-duration exploration missions that will test the bounds of human performance. Deep space travel will include added risk related to stressors from the isolated, confined, and extreme environment that lies outside the boundaries of low Earth orbit. Currently, selective serotonin reuptake inhibitors (SSRIs) are considered the standard of care for many mental health diagnoses, including anxiety and depression; however, SSRIs are also associated with several undesired side effects. The utility of nonpharmacological therapies for the management of behavioral health conditions has not yet been fully explored.METHODS: A comprehensive literature search was performed using PubMed. Relevant articles pertaining to the psychological impacts of isolated, confined, and extreme environments, use of SSRIs in spaceflight, side effects associated with SSRIs, and nonpharmacological treatments for anxiety and depression were reviewed. Over 70 studies were reviewed in total.RESULTS: Reduced bone mineral density, impaired hemostatic function, significant individual variability resulting from gene polymorphisms, and drug-drug interactions are well described adverse effects of SSRIs that may complicate their operational use in the deep space environment. Four alternative therapies for the treatment of anxiety and depression may show promise for long duration missions.DISCUSSION: Although SSRIs have long been considered standard of care treatment for many behavioral health conditions, we cannot trivialize the risk that prolonged pharmacological therapy may pose. The need to mitigate these risks by exploring alternative therapies has never been more relevant.El-Khoury BB, Ray KL, Altchuler SI, Reichard JF, Dukes CH. Selective serotonin reuptake inhibitors and other treatment modalities for deep space missions. Aerosp Med Hum Perform. 2023; 94(11):843-851.

Rapid Review of Dermal Penetration and Absorption of Inorganic Lead Compounds for Occupational Risk Assessment.

Lead (Pb) exposure continues to be a significant public health issue in both occupational and non-occupational settings. The vast majority of exposure and toxicological studies have focused on effects related to inhalation and gastrointestinal exposure routes. Exposure to inorganic Pb compounds through dermal absorption has been less well studied, perhaps due to the assumption that the dermal pathway is a minor contributor to aggregate exposures to Pb compounds. The aim of this rapid review was to identify and evaluate published literature on dermal exposures to support the estimation of key percutaneous absorption parameters (Kp, flux, diffusion rate) for use in occupational risk assessment. Eleven articles were identified containing information from both in vitro and in vivo systems relevant to percutaneous absorption kinetics. These articles provided 24 individual study summaries and information for seven inorganic Pb compounds. The vast majority of study summaries evaluated (n = 22, 92%) reported detectable amounts of dermal absorption of inorganic Pb. Data were identified for four Pb compounds (Pb acetate, Pb nitrate, Pb oxide, and Pb metal) that may be sufficient to use in evaluating physiologically based pharmacokinetic models. Average calculated diffusion rates for the pool of animal and human skin data ranged from 10-7 to 10-4 mg cm-2 h-1, and Kp values ranged from 10-7 to 10-5 cm h-1. Study design and documentation were highly variable, and only one of the studies identified was conducted using standard test guideline-compliant methodologies. Two studies provided quality estimates on the impacts of dermal absorption from water-insoluble Pb compounds on blood Pb levels. These two studies reported that exposures via dermal routes could elevate blood Pb by over 6 µg dl-1. This estimation could represent over 100% of 5 µg dl-1, the blood Pb associated with adverse health effects in adults. The utility of these estimates to occupational dermal exposures is limited, because the confidence in the estimates is not high. The literature, while of limited quality, overall strongly suggests inorganic Pb has the potential for dermal uptake in meaningful amounts associated with negative health outcomes based on upper bound diffusion rate estimates. Future standard test guideline-compliant studies are needed to provide high-confidence estimates of dermal uptake. Such data are needed to allow for improved evaluation of Pb exposures in an occupational risk assessment context.

Connecting omics signatures and revealing biological mechanisms with iLINCS.

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.

Bayesian hierarchical evaluation of dose-response for peanut allergy in clinical trial screening.

Risk-based labeling based on the minimal eliciting doses (EDs) in sensitized populations is a potential replacement for precautionary allergen labeling of food allergens. We estimated the dose-response distribution for peanut allergen using data from double-blind placebo-controlled food challenges (DBPCFCs) conducted in the US at multiple sites, testing a population believed to be similar to the general U.S. food allergic population. Our final (placebo-adjusted) dataset included 548 challenges of 481 subjects. Bayesian hierarchical analysis facilitated model fitting, and accounted for variability associated with various levels of data organization. The data are best described using a complex hierarchical structure that accounts for inter-individual variability and variability across study locations or substudies. Bayesian model averaging could simultaneously consider the fit of multiple models, but the Weibull model dominated so strongly that model averaging was not needed. The ED01 and ED05 (and 95% credible intervals) are 0.052 (0.021, 0.13) and 0.49 (0.22, 0.97) mg peanut protein, respectively. Accounting for challenges with severe reactions at the LOAEL, by using the dose prior to the LOAEL as the new LOAEL, the ED01 drops to 0.029 (0.014, 0.074) mg peanut protein. Our results could aid in establishing improved food labeling guidelines in the management of food allergies.

The Effects of Social, Personal, and Behavioral Risk Factors and PM2.5 on Cardio-Metabolic Disparities in a Cohort of Community Health Center Patients.

(1) Background: Cardio-metabolic diseases (CMD), including cardiovascular disease, stroke, and diabetes, have numerous common individual and environmental risk factors. Yet, few studies to date have considered how these multiple risk factors together affect CMD disparities between Blacks and Whites. (2) Methods: We linked daily fine particulate matter (PM2.5) measures with survey responses of participants in the Southern Community Cohort Study (SCCS). Generalized linear mixed modeling (GLMM) was used to estimate the relationship between CMD risk and social-demographic characteristics, behavioral and personal risk factors, and exposure levels of PM2.5. (3) Results: The study resulted in four key findings: (1) PM2.5 concentration level was significantly associated with reported CMD, with risk rising by 2.6% for each µg/m3 increase in PM2.5; (2) race did not predict CMD risk when clinical, lifestyle, and environmental risk factors were accounted for; (3) a significant variation of CMD risk was found among participants across states; and (4) multiple personal, clinical, and social-demographic and environmental risk factors played a role in predicting CMD occurrence. (4) Conclusions: Disparities in CMD risk among low social status populations reflect the complex interactions of exposures and cumulative risks for CMD contributed by different personal and environmental factors from natural, built, and social environments.

Heme oxygenase-1 induction by NRF2 requires inactivation of the transcriptional repressor BACH1.

Oxidative stress activates the transcription factor NRF2, which in turn binds cis-acting antioxidant response element (ARE) enhancers and induces expression of protective antioxidant genes. In contrast, the transcriptional repressor BACH1 binds ARE-like enhancers in cells naïve to oxidative stress and antagonizes NRF2 binding until it becomes inactivated by pro-oxidants. Here, we describe the dynamic roles of BACH1 and NRF2 in the transcription of the heme oxygenase-1 (HMOX1) gene. HMOX1 induction, elicited by arsenite-mediated oxidative stress, follows inactivation of BACH1 and precedes activation of NRF2. BACH1 repression is dominant over NRF2-mediated HMOX1 transcription and inactivation of BACH1 is a prerequisite for HMOX1 induction. In contrast, thioredoxin reductase 1 (TXNRD1) is regulated by NRF2 but not by BACH1. By comparing the expression levels of HMOX1 with TXNRD1, we show that nuclear accumulation of NRF2 is not necessary for HMOX1 induction; rather, BACH1 inactivation permits NRF2 already present in the nucleus at low basal levels to bind the HMOX1 promoter and elicit HMOX1 induction. Thus, BACH1 confers an additional level of regulation to ARE-dependent genes that reveals a new dimension to the oxidative stress response.

The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

Mode-of-action evaluation for the effect of trans fatty acids on low-density lipoprotein cholesterol.

The purpose of this work is to systematically consider the data relating to the mode of action (MOA) for the effects of industrially produced trans fatty acid (iTFA) on plasma low-density lipoprotein (LDL) levels. The hypothesized MOA is composed of two key events: increased LDL production and decreased LDL clearance. A substantial database supports this MOA, although the key events are likely to be interdependent, rather than sequential. Both key events are functions of nonlinear biological processes including rate-limited clearance, receptor-mediated transcription, and both positive and negative feedback regulation. Each key event was evaluated based on weight-of-evidence analysis and for human relevance. We conclude that the data are inadequate for a detailed dose-response analysis in the context of the evolved Bradford Hill considerations; however, the weight of evidence is strong and the overall shape of the dose-response curves for markers of the key events and the key determinants of those relationships is well understood in many cases and is nonlinear. Feedback controls are responsible for maintaining homeostasis of cholesterol and triglyceride levels and underlie both of the key events, resulting in a less-than-linear or thresholded relationship between TFA and LDL-C. The inconsistencies and gaps in the database are discussed.

Butylhydroquinone protects cells genetically deficient in glutathione biosynthesis from arsenite-induced apoptosis without significantly changing their prooxidant status.

Arsenic, first among the top environmentally hazardous substances, is associated with skin, lung, liver, kidney, prostate, and bladder cancer. Arsenic is also a cardiovascular and a central nervous system toxicant, and it has genotoxic and immunotoxic effects. Paradoxically, arsenic trioxide is used successfully in the treatment of acute promyelocytic leukemia and multiple myeloma. Arsenic induces oxidative stress, and its toxicity is decreased by free thiols and increased by glutathione depletion. To further characterize the role of glutathione and oxidative stress in the toxicity of arsenic, we have used fetal fibroblasts from Gclm(-/-) mice, which lack the modifier subunit of glutamate-cysteine ligase, the rate-limiting enzyme in glutathione biosynthesis. Gclm(-/-) mouse embryo fibroblasts (MEFs) are eight times more sensitive to arsenite-induced apoptotic death. Because of a dramatic decrease in glutathione levels, Gclm(-/-) MEFs have a high prooxidant status that is not significantly relieved by treatment with the phenolic antioxidant tBHQ; however, tBHQ blocks arsenite-induced apoptosis in both Gclm(+/+) and Gclm(-/-) cells, although it raises a significant antioxidant response only in Gclm(+/+) cells. Global gene expression profiles indicate that tBHQ is significantly effective in reversing arsenite-induced gene deregulation in Gclm(+/+) but not in Gclm(-/-) MEFs. This effect of tBHQ is evident in the expression of metalloproteases and chaperones, and in the expression of genes involved in DNA damage and repair, protein biosynthesis, cell growth and maintenance, apoptosis, and cell cycle regulation. These results suggest that regulation of glutathione levels by GCLM determines the sensitivity to arsenic-induced apoptosis by setting the overall ability of the cells to mount an effective antioxidant response.

Arsenic toxicology: translating between experimental models and human pathology.

BACKGROUND: Chronic arsenic exposure is a worldwide health problem. How arsenic exposure promotes a variety of diseases is poorly understood, and specific relationships between experimental and human exposures are not established. We propose phenotypic anchoring as a means to unify experimental observations and disease outcomes. OBJECTIVES: We examined the use of phenotypic anchors to translate experimental data to human pathology and investigated research needs for which phenotypic anchors need to be developed. METHODS: During a workshop, we discussed experimental systems investigating arsenic dose/exposure and phenotypic expression relationships and human disease responses to chronic arsenic exposure and identified knowledge gaps. In a literature review, we identified areas where data exist to support phenotypic anchoring of experimental results to pathologies from specific human exposures. DISCUSSION: Disease outcome is likely dependent on cell-type-specific responses and interaction with individual genetics, other toxicants, and infectious agents. Potential phenotypic anchors include target tissue dosimetry, gene expression and epigenetic profiles, and tissue biomarkers. CONCLUSIONS: Translation to human populations requires more extensive profiling of human samples along with high-quality dosimetry. Anchoring results by gene expression and epigenetic profiling has great promise for data unification. Genetic predisposition of individuals affects disease outcome. Interactions with infectious agents, particularly viruses, may explain some species-specific differences between human pathologies and experimental animal pathologies. Invertebrate systems amenable to genetic manipulation offer potential for elaborating impacts of specific biochemical pathways. Anchoring experimental results to specific human exposures will accelerate understanding of mechanisms of arsenic-induced human disease.