S-adenosyl-l-methionine protection of acetaminophen mediated oxidative stress and identification of hepatic 4-hydroxynonenal protein adducts by mass spectrometry.

Acetaminophen (APAP) hepatotoxicity is protected by S-adenosyl-l-methionine (SAMe) treatment 1hour (h) after APAP in C57/Bl6 mice. This study examined protein carbonylation as well as mitochondrial and cytosolic protein adduction by 4-hydroxynonenal (4-HNE) using mass spectrometry (MS) analysis. Additional studies investigated the leakage of mitochondrial proteins and 4-HNE adduction of these proteins. Male C57/Bl6 mice (n=5/group) were divided into the following groups and treated as indicated: Veh (15ml/kg water, ip), SAMe (1.25mmol/kg, ip), APAP (250mg/kg), and SAMe given 1h after APAP (S+A). APAP toxicity was confirmed by an increase (p<0.05) in plasma ALT (U/l) and liver weight/10g body weight relative to the Veh, SAMe and S+A groups 4h following APAP treatment. SAMe administered 1h post-APAP partially corrected APAP hepatotoxicity as ALT and liver weight/10g body weights were lower in the S+A group compared the APAP group. APAP induced leakage of the mitochondrial protein, carbamoyl phosphate synthase-1 (CPS-1) into the cytosol and which was reduced in the S+A group. SAMe further reduced the extent of APAP mediated 4-HNE adduction of CPS-1. MS analysis of hepatic and mitochondrial subcellular fractions identified proteins from APAP treated mice. Site specific 4-HNE adducts were identified on mitochondrial proteins sarcosine dehydrogenase and carbamoyl phosphate synthase-1 (CPS-1). In summary, APAP is associated with 4-HNE adduction of proteins as identified by MS analysis and that CPS-1 leakage was greater in APAP treated mice. SAMe reduced the extent of 4-HNE adduction of proteins as well as leakage of CPS-1.

Interdependent genotoxic mechanisms of monomethylarsonous acid: role of ROS-induced DNA damage and poly(ADP-ribose) polymerase-1 inhibition in the malignant transformation of urothelial cells.

Exposure of human bladder urothelial cells (UROtsa) to 50 nM of the arsenic metabolite, monomethylarsonous acid (MMA(III)), for 12 weeks results in irreversible malignant transformation. The ability of continuous, low-level MMA(III) exposure to cause an increase in genotoxic potential by inhibiting repair processes necessary to maintain genomic stability is unknown. Following genomic insult within cellular systems poly(ADP-ribose) polymerase-1 (PARP-1), a zinc finger protein, is rapidly activated and recruited to sites of DNA strand breaks. When UROtsa cells are continuously exposed to 50 nM MMA(III), PARP-1 activity does not increase despite the increase in MMA(III)-induced DNA single-strand breaks through 12 weeks of exposure. When UROtsa cells are removed from continuous MMA(III) exposure (2 weeks), PARP-1 activity increases coinciding with a subsequent decrease in DNA damage levels. Paradoxically, PARP-1 mRNA expression and protein levels are elevated in the presence of continuous MMA(III) indicating a possible mechanism to compensate for the inhibition of PARP-1 activity in the presence of MMA(III). The zinc finger domains of PARP-1 contain vicinal sulfhydryl groups which may act as a potential site for MMA(III) to bind, displace zinc ion, and render PARP-1 inactive. Mass spectrometry analysis demonstrates the ability of MMA(III) to bind a synthetic peptide representing the zinc-finger domain of PARP-1, and displace zinc from the peptide in a dose-dependent manner. In the presence of continuous MMA(III) exposure, continuous 4-week zinc supplementation restored PARP-1 activity levels and reduced the genotoxicity associated with MMA(III). Zinc supplementation did not produce an overall increase in PARP-1 protein levels, decrease the levels of MMA(III)-induced reactive oxygen species, or alter Cu-Zn superoxide dismutase levels. Overall, these results present two potential interdependent mechanisms in which MMA(III) may increase the susceptibility of UROtsa cells to genotoxic insult and/or malignant transformation: elevated levels of MMA(III)-induced DNA damage through the production of reactive oxygen species, and the direct MMA(III)-induced inhibition of PARP-1.

Disparities in spread and control of influenza in slums of Delhi: findings from an agent-based modelling study.

OBJECTIVES: This research studies the role of slums in the spread and control of infectious diseases in the National Capital Territory of India, Delhi, using detailed social contact networks of its residents. METHODS: We use an agent-based model to study the spread of influenza in Delhi through person-to-person contact. Two different networks are used: one in which slum and non-slum regions are treated the same, and the other in which 298 slum zones are identified. In the second network, slum-specific demographics and activities are assigned to the individuals whose homes reside inside these zones. The main effects of integrating slums are that the network has more home-related contacts due to larger family sizes and more outside contacts due to more daily activities outside home. Various vaccination and social distancing interventions are applied to control the spread of influenza. RESULTS: Simulation-based results show that when slum attributes are ignored, the effectiveness of vaccination can be overestimated by 30%-55%, in terms of reducing the peak number of infections and the size of the epidemic, and in delaying the time to peak infection. The slum population sustains greater infection rates under all intervention scenarios in the network that treats slums differently. Vaccination strategy performs better than social distancing strategies in slums. CONCLUSIONS: Unique characteristics of slums play a significant role in the spread of infectious diseases. Modelling slums and estimating their impact on epidemics will help policy makers and regulators more accurately prioritise allocation of scarce medical resources and implement public health policies.

Effect of modelling slum populations on influenza spread in Delhi.

OBJECTIVES: This research studies the impact of influenza epidemic in the slum and non-slum areas of Delhi, the National Capital Territory of India, by taking proper account of slum demographics and residents' activities, using a highly resolved social contact network of the 13.8 million residents of Delhi. METHODS: An SEIR model is used to simulate the spread of influenza on two different synthetic social contact networks of Delhi, one where slums and non-slums are treated the same in terms of their demographics and daily sets of activities and the other, where slum and non-slum regions have different attributes. RESULTS: Differences between the epidemic outcomes on the two networks are large. Time-to-peak infection is overestimated by several weeks, and the cumulative infection rate and peak infection rate are underestimated by 10-50%, when slum attributes are ignored. CONCLUSIONS: Slum populations have a significant effect on influenza transmission in urban areas. Improper specification of slums in large urban regions results in underestimation of infections in the entire population and hence will lead to misguided interventions by policy planners.

Role of hydroquinone-thiol conjugates in benzene-mediated toxicity.

Hydroquinone (HQ) is a metabolite of benzene, and in combination with phenol (PHE), reproduces benzene myelotoxicity. HQ readily oxidizes to 1,4-benzoquinone (1,4-BQ) followed by the reductive addition of glutathione (GSH). Subsequent cycles of oxidation and GSH addition give rise to a variety of mono-, and multi-GSH substituted conjugates. Following administration of PHE/HQ (1.1 mmol/kg/0.9 mmol/kg, ip) to male Sprague-Dawley (SD) rats, 2-(glutathion-S-yl)HQ [GS-HQ], 2,5-bis-(glutathion-S-yl)HQ [2,5-GS-HQ], 2,6-bis-(glutathion-S-yl)HQ [2,6-GS-HQ], and 2,3,5-tris-(glutathion-S-yl)HQ [2,3,5-GS-HQ] were all identified in bone marrow. 2-(Cystein-S-ylglycine)HQ [2-(CysGly)HQ], 2-(cystein-S-yl)HQ [2-(Cys)HQ], and 2-(N-acetylcystein-S-yl)HQ [2-(NACys)HQ] were also found in the bone marrow of PHE/HQ and benzene treated rats and mice, indicating the presence of an active mercapturic acid pathway within bone marrow. Moreover, 2,6-GS-HQ and 2,3,5-GS-HQ were hematotoxic when administered to rats. All of the HQ-GSH conjugates retain the ability to redox cycle and generate reactive oxygen species (ROS), and to arylate target proteins. Recent in vitro and in vivo studies in our laboratory revealed lysine and arginine residues as primary targets of 1,4-BQ, GS-HQ and 2-(NACys)HQ adduction. In contrast 1,4-BQ-adduction of cysteine residues may be a transient interaction, where physiological conditions dictate adduct stability. The generation of ROS and alkylation of proteins may both contribute to benzene-mediated myelotoxicity, and the two processes may be inter-dependent. However, the precise molecular mechanism by which benzene and HQ-GSH conjugates induce hematotoxicity remains to be determined. Within 18h of administration of PHE/HQ to SD rats a significant decrease in blood lymphocyte count was observed. At this early time point, erythrocyte counts and hemoglobin concentrations remained within the normal range. Concomitant with the decrease in lymphocyte count, western blot analysis of bone marrow lysate, using HQ-GSH and 4-hydroxy-2-nonenal (4HNE) specific antibodies, revealed the presence of HQ-GSH- and 4HNE-derived protein adducts. Identification of these adducts is required before the functional significance of such protein modifications can be determined.

Detail in network models of epidemiology: are we there yet?

Network models of infectious disease epidemiology can potentially provide insight into how to tailor control strategies for specific regions, but only if the network adequately reflects the structure of the region's contact network. Typically, the network is produced by models that incorporate details about human interactions. Each detail added renders the models more complicated and more difficult to calibrate, but also more faithful to the actual contact network structure. We propose a statistical test to determine when sufficient detail has been added to the models and demonstrate its application to the models used to create a synthetic population and contact network for the USA.