Cellular RNA is chemically modified by exposure to air pollution mixtures.

http://informahealthcare.com/iht ISSN: 0895-8378 (print), 1091-7691 (electronic) Inhal Toxicol, 2015; 27(1): 74–82 ! 2015 Informa Healthcare USA, Inc. DOI: 10.3109/08958378.2014.987361

RESEARCH ARTICLE

Cellular RNA is chemically modified by exposure to air pollution mixtures Kevin C. Baldridge1, Jose Zavala2, Jason Surratt2, Kenneth G. Sexton2, and Lydia M. Contreras1 McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin TX, USA and 2Gillings School of Global Public Health, Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

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1

Abstract

Keywords

RNAs are more susceptible to modifications than DNA, and chemical modifications in RNA have an effect on their structure and function. This study aimed to characterize chemical effects on total RNA in human A549 lung cells after exposure to elevated levels of major secondary air pollutants commonly found in urban locations, including ozone (O3), acrolein (ACR) and methacrolein (MACR). Enzyme-linked immunosorbent assays (ELISA) were used to measure levels of interleukin (IL)-8 in the growth media and 8-oxoguanine (8OG) levels in total cellular RNA, and lactate dehydrogenase (LDH) in the growth media was measured by a coupled enzymatic assay. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to measure levels of microRNA 10b (miR-10b). The study found that 1-h exposure to all tested pollutant mixtures consistently caused significant increases in the levels of 8OG in total RNA. In the case of 4 ppm O3 exposures, measured levels of IL-8, LDH and miR-10b each showed consistent trends between two independent trials, but varied among these three targets. After 1-h exposures to an ACR+MACR mixture, measured levels of IL-8, LDH and miR-10b showed variable results. For mixtures of O3+ACR+MACR, IL-8 measurements showed no change; miR-10b and LDH showed variable results. The results indicate that short-term highconcentration exposures to air pollution can cause RNA chemical modifications. Chemical modifications in RNAs could represent more consistent markers of cellular stress relative to other inflammation markers, such as IL-8 and LDH, and provide a new biomarker endpoint for mechanistic studies in toxicity of air pollution exposure.

8-oxoguanine, air pollution exposure, exposure biomarker, human lung, ozone, RNA oxidation, toxicity endpoint, volatile organic compound

Introduction With continued growth of developing nations and increased transportation needs of the growing world population, air quality continues to decrease in highly populated areas. While regulatory efforts in USA have been somewhat successful in reducing pollution emissions, the global levels of several pollutants still exceed the exposure levels recommended by the World Health Organization (WHO) (World Health Organization, 2005). Numerous studies have shown high levels of known toxic pollutants, including ozone (O3) and a wide variety of volatile organic compounds (VOCs) (Chiang et al., 2007; Crounse et al., 2012; Jacob & Winner, 2009; Mao et al., 2010; Meng et al., 1997; Rager et al., 2011a). Among those pollutants exceeding recommended levels, O3 is of particular importance in its effects on health. Its strong reactivity and tendency to generate free radicals, such as hydroxyl (OH) radicals and reactive odd nitrogen species (NOy), cause damage to a wide range of cellular components (Byvoet et al., 1995; Cataldo, 2006a; Jorge et al., 2002; Address for correspondence: Dr Lydia M. Contreras, McKetta Department of Chemical Engineering, The University of Texas at Austin, 200 E. Dean Keeton St., Stop C0400, Austin, TX 78712, USA. Tel: +512-471-2453. E-mail: [email protected]

History Received 30 June 2014 Revised 25 October 2014 Accepted 10 November 2014 Published online 20 January 2015

Weschler et al., 1992). Furthermore, O3 is created as a byproduct of VOC photolysis and oxidation, degradation of chlorine and nitrogen compounds, and surface reactions on particulate matter (PM) (Crounse et al., 2012; Doyle et al., 2004; Ebersviller et al., 2012; Faxon & Allen, 2013; Meng et al., 1997; Weschler et al., 1992). In addition, it is wellknown that photochemical reactions in air pollution mixtures generate higher levels of O3 and secondary oxidative compounds (Doyle et al., 2007), an effect which may increase with global climate change (Jacob & Winner, 2009). Other VOC components, such as acrolein (ACR), produced from the atmospheric oxidation of primarily emitted VOCs have also been shown to have direct effects on human health in micromolar aqueous solutions (Tang et al., 2011). The known carcinogenic effect of outdoor air pollution and PM (Loomis et al., 2013) indicates a strong need for studies focusing on the impacts of air quality on human health. Many studies of pollution in cellular contexts have used A549 human alveolar adenocarcinoma cells, an immortalized cell line commonly used as a model for lung studies. Most studies in this and other cell lines have focused on biomarkers of oxidative stress, ranging from oxidized DNA nucleotides to inflammatory protein signals (de Zwart et al., 1999) to measure the impact of exposure to various environmental


DOI: 10.3109/08958378.2014.987361

toxins to human health. Several studies have implicated inflammation and cell death protein signals with exposure to a variety of environmentally relevant levels of VOC air pollutants in A549 cells (Doyle et al., 2004; Dumler et al., 1994; Sexton et al., 2004), and another study has shown regulatory changes at the microRNA (miRNA) level in the same cell line following exposures to 1 parts per million (ppm) formaldehyde, a carbonyl-containing VOC (Rager et al., 2011b). Since the lungs are the main point of exposure to air pollution in humans, the model lung A549 cells are the logical choice for our studies; while other studies have focused on using primary cells, this more ideal scenario was impractical for this study, especially given the higher abundance of data that has been collected with A549 cells. Reactive oxygen species (ROS) are generated as a byproduct of normal metabolism and play an important role in signaling (Martin & Barrett, 2002); it is therefore plausible that the introduction of exogenous ROS can disrupt this signaling balance and cause a cascade of dysfunctional reactions and disease (Poulsen et al., 2012). Given the slow timescale for transcriptional and translational responses (102– 104 units added per second) relative to oxidation reactions in RNA (104–106 oxidized bases per second) (Milo et al., 2010; Theruvathu et al., 2001), it is interesting to consider what the chemical effects of exposure are to biological molecules in addition to differentially expressed transcriptional and translational responses. Since DNA has a much longer half-life than RNA, (Milo et al., 2010), more studies have focused on pollution-induced modifications to DNA. For instance, DNA has been shown to be oxidized by O3 in mouse models (1–2 ppm) and during epidemiological studies in humans [300–400 ppb (parts per billion)] (Bornholdt et al., 2002; Palli et al., 2009). In vitro, DNA has been shown to be oxidized by exposure to O3 at levels as low as 80 ppb (Cheng et al., 2003) and numerous mechanistic studies have focused on reactions of nucleic acids and nucleotides with O3 and its radical degradation products (Biondi et al., 1997; Cataldo, 2006b; Ito et al., 2005; Jorge et al., 2002; Theruvathu et al., 2001). Although not many studies of oxidative modifications in RNA with direct air pollution exposures have been conducted, accumulating evidence indicates that chemical modifications and strand breaks on RNA can have significant impact on regulatory events in the cell. In fact, it is now understood that non-coding RNAs are key players in coordinating cellular responses by adjusting levels of coding RNA transcripts, producing alternative splicing variants and guiding post-transcriptional modification of other functional RNAs (Huang et al., 2013; Kaczanowska & Ryde´n-Aulin, 2007; Will & Lu¨hrmann, 2001). At the nucleotide level, base modifications are known to affect base pairing and base stacking interactions, which are important determinants of secondary and tertiary structure [reviewed in (Carell et al., 2012)]. It is widely believed that non-coding RNAs depend strongly on structure to enact its functions (Erdmann et al., 2001; Mattick & Makunin, 2006). These observations of the strong structure/function relationship in RNA led us to study RNA modifications, as a likely determinant of dysfunction in non-coding RNAs. In our study, we tested the effects of O3, ACR+MACR (methacrolein) and O3+ACR+MACR (Table 1) on formation

Characterizing O3 and VOC exposure in A549 lung cells

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Table 1. Exposure conditions tested in vitro with A549 lung cells in gas in vitro exposure system (Ebersviller et al., 2012).

Component

Target concentration

Exposure time (h)

O3 O3 ACR MACR O3 ACR MACR

0.4 ppm 4 ppm 872 ppb 698 ppb 4 ppm 872 ppb 698 ppb

4 1 1

1

of 8-oxoguanosine (8OG) in total RNA of A549 lung cells exposed at an air–liquid interface (Figure 1). We measured levels of 8OG as a marker of chemical modification in RNA, and we compared the results to other biomarkers that have been previously used to measure cellular stress responses. Specifically, we measured the level of microRNA-10b (miR10b) in total cellular RNA as a signature of post-transcriptional regulation, interleukin-8 (IL-8) protein secretion in growth media as a marker of inflammation and lactate dehydrogenase (LDH) secretion in growth media as a marker of cytotoxicity. We focus on O3 and a mixture of ACR and MACR as a model for total ROS and VOCs, which have been observed in automobile exhaust (Chiang et al., 2007). We choose to focus on O3 and carbonyl VOCs given that these have been shown to have a direct effect on nucleic acids, proteins and lipids (Cataldo, 2006a; Stevens & Maier, 2008). We use the detection of 8OG as a marker of oxidation due to its higher susceptibility to oxidation relative to any other standard ribonucleobase (Biondi et al., 1997; Theruvathu et al., 2001). It is worth noting that RNA reacts with ROS more quickly than DNA (Biondi et al., 1997; Hofer et al., 2005).

Methods Cell culture and exposure In vitro exposures were performed using the GIVES (gas in vitro exposure system) as previously described (Doyle et al., 2007; Ebersviller et al., 2012; Rager et al., 2011a; Sexton et al., 2004). Briefly, cells were grown on 30 mm Millicell membranes (EMD Millipore Corp., Billerica, MA) in F12-K media with 10% fetal bovine serum (FBS) plus 0.01% penicillin/streptomycin at a density of 850 000 cells/ membrane, 28 h prior to exposure as described (Jaspers et al., 1997; Zavala et al., 2014). Four hours before exposure, when cells reached 80% confluency, FBS-containing media was replaced with serum-free media (F12-K media + 1.5 mg/ml bovine serum albumin + 0.01% penicillin/streptomycin). Immediately before exposures, the serum-free media was replaced with fresh serum-free media added to the basolateral side only to allow air–liquid exposure. Immediately after exposure, basolateral media was collected for protein measurements, and cells were dissolved in TRIzol directly from membrane cultures. These TRIzol (Life Technologies, Carlsbad, CA) dissolved samples were frozen immediately at 80 C and shipped in dry ice from UNC for analysis at The University of Texas at Austin (UT).

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K. C. Baldridge et al.

Inhal Toxicol, 2015; 27(1): 74–82

H O

O

N N

8-oxoguanosine ELISA

N

H

N

H

N

H

8-oxoguanine (8OG)

Unexposed controls Incubator controls

Extract total RNA

A549 on membranes


Growth Media

Secreted IL-8 and LDH measured in basolateral media

A549 on membranes

quantitative real time PCR 8-oxoguanosine ELISA

Exposed test cases Extract total RNA

A549 on membranes Growth Media

Secreted IL-8 and LDH measured in basolateral media

quantitative real time PCR

Figure 1. Schematic representation of experimental workflow. Cells were cultured to 80% confluence, then separated into two groups (each N ¼ 6 or greater) for exposures, with control groups remaining unexposed in the incubator. Immediately after exposure, cells were lysed using TRIzol and frozen immediately at 80 C for later RNA extraction and analysis (including miR-10b quantification and 8OG measurements). Samples of basolateral media were collected from each group and tested for inflammation and cytotoxicity signals (IL-8 and LDH, respectively).

The O3 and carbonyls (ACR and MACR) were injected into a 120-m3 (triangular cross-section; 7.4 6.0 5.4 m high) environmental irradiation chamber enclosed in Teflon film walls located on the rooftop of the Gillings School of Global Public Health at UNC. This environmental irradiation chamber facility has been previously described in detail (Ebersviller et al., 2012; Lichtveld et al., 2012). From this chamber, the air pollutant source was sampled over A549 cells, where direct pollutant–cell interaction occurred. For each experiment, A549 cells were exposed to O3, carbonyls (ACR and MACR) or a mix of O3 and carbonyls for 1 h in the GIVES at a flow rate of 1.6 L/min. Ozone was generated from oxidized air using an O3 generator (model OL80A; Ozone Services, Yanco Industries Ltd, Burton, British Columbia, Canada) and injected directly into the rooftop chamber. ACR and MACR were injected using microliter syringes as liquid into the rooftop chamber, where they quickly evaporated into the gas phase. In all experiments, chamber injections were made near sunset to minimize possible photochemical transformations. To generate the mix of O3 and carbonyls, O3 was first injected into the chamber until the target concentration was achieved. Immediately after, ACR and MACR were injected independently next to the mixing fans located inside the chamber. The

chamber contents were allowed to mix for 10 min and the exposures were started. It is worth noting that the composition of the ACR+MACR and O3+ACR+MACR mixtures after 1 h may have changed slightly due to photo-initiated gas-phase reactions, despite our attempts to minimize sun exposure and secondary products; however, this work aimed at characterizing toxicity endpoints rather than the toxic effects of specific pollution components. A set of unexposed A549 cells remained in an incubator and served as controls for each exposure condition presented in this study. Use of unexposed A549 cells as controls has previously been shown to be equivalent to exposing cells to clean background chamber air (Ebersviller et al., 2012). The exposure conditions tested and the average target concentrations for each experiment are shown in Table 1. The GIVES system used in this work has previously been shown to yield reasonable IL-8 measurements with exposures of comparable concentrations and durations (Rager et al., 2011a). The chamber concentrations used in the exposure conditions presented here are not observed in typical ambient environments; however, our goal is to demonstrate the proof of concept for the application of 8OG as a toxicity endpoint. Therefore, we chose to use elevated levels and relatively short time exposure times to ensure a relevant dose to the cells and

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to ensure signals above the detection limits for reasonable comparison of the various endpoints measured. Furthermore, given the fast reaction rate of O3 with RNA, shorter exposures are of interest; on longer timescales, measurements of RNA chemistry may be skewed by repair mechanisms which are expressed in response to exposure stress. In this study, we achieved a similar dosage by decreasing time and elevating concentrations further in order to capture the more rapid chemical changes we expected to see in 8OG levels.


RNA extraction RNA was extracted by the suggested protocol in the TRIzol product manual, with the following exceptions: (i) centrifugations were performed for twice the recommended time to ensure adequate yields and (ii) after air drying of ethanol, samples were reconstituted with 30 ml degassed ultrapure water and placed under vacuum for 5 min to ensure adequate ethanol removal. In general, practical steps were taken to minimize artificial oxidation of samples during workup, which has been shown to contribute a significant level of oxidative damage in the absence of precautions (Helbock et al., 1998; Ravanat et al., 2002). For example, all solutions (except for TRIzol and chloroform) used in the extraction of RNAs were purged for at least 30 min by bubbling with oxygen-free nitrogen (Matheson Tri-gas, Basking Ridge, NJ). RNA samples were also stored on ice during experiments, and stored at 80 C for long-term storage to reduce oxidation reaction rates during handling. Quantification of total RNA extracted was performed using a NanoDrop spectrophotometer (Thermo Scientific, Waltham, MA). The concentrations and quality (lack of degradation) of RNA samples were checked by denaturing polyacrylamide gel electrophoresis (PAGE). 8OG measurements A competitive enzyme-linked immunosorbent assay, ELISA, (DNA/RNA Oxidative Damage EIA kit from Cayman Chemical, Ann Arbor, MI) was used to measure the concentration of 8OG in total RNA samples. To prepare samples for 8OG measurements, each sample was aliquoted in two dilutions, adequate for triplicate 50 ml samples of 1 and 0.5 mg/well each. Each aliquot was then digested to nucleotides by nuclease P1 (Sigma-Aldrich, St. Louis, MO) in a 20 mM sodium acetate (Sigma) buffer for 2 h at 37 C. Following digestion, each sample was dephosphorylated using calf intestinal alkaline phosphatase (CIP) from New England Biolabs (NEB, Ipswich, MA) in a 100 mM TRIS buffer (JT Baker, Center Valley, PA) for 1 h at 37 C. After digestion, 50 ml of each aliquot were loaded into triplicate wells and the 8OG ELISA assay was carried out as recommended by the manufacturer. Absorbance values were measured using a SoftMax plate reader (SoftMax, Molecular Devices, Sunnyvale, CA), and concentrations were calculated according to manufacturer instructions. Protein measurements For each cell exposure conducted, the basolateral supernatants were collected immediately after exposure and frozen at 20 C until toxicological analysis was conducted. IL-8, a


77

marker of inflammation in the supernatant, was measured via ELISA (BD Biosciences, San Diego, CA) following the manufacturer protocol. Cellular membrane damage was measured via levels of LDH in the collected basolateral supernatant using a coupled enzymatic assay (LDH Cytotoxicity Detection Kit; Takara Bio Inc., Otsu, Japan). miRNA measurements Before measuring miRNA levels, RNA samples were subjected to digestion with DNase I (Thermo Scientific) in a 10 mM TRIS buffer (with 2.5 mM Mg2+ and 0.5 mM Ca2+, pH 7.5). To analyze miRNA expression, two individual cultures were chosen randomly from samples that yielded adequate quantities of RNA after DNase I digestion. Following digestion, samples were extracted once again with TRIzol to remove DNase contamination. The samples were then reverse transcribed using the NCode miRNA cDNA synthesis kit (Life Technologies, Carlsbad, CA), which adds a polyA tail to all RNAs and creates cDNAs using a universal oligodT primer. Quantitative real-time polymerase chain reaction (qRT-PCR) was then performed to measure the expression level of one targeted miRNA (i.e. miRNA-10b) which was previously shown to be down-regulated after 1 mM formaldehyde exposure (Rager et al., 2011b). qRT-PCR was performed using the Power SYBR Green Master Mix (Life Technologies) in the Applied Biosystems Viia7 Real-Time PCR System (Foster City, CA) in the Core DNA facility in the Institute for Cellular and Molecular Biology at the University of Texas at Austin. Statistical analysis Data are represented as a mean with positive and negative (±) standard error of the mean. All hypothesis testing was performed in JMP 9 (SAS Institute Inc., 2010). The significance between groups was determined by Student’s t-test. A probability level of p50.05 was considered significant.

Results Short, high-concentration (4 ppm for 1 h), but not longer exposures at lower concentration (0.4 ppm for 4 h) O3 exposures increase 8OG levels in cellular RNAs O3 was the first model pollutant we chose to study, and cells were exposed to: (i) 0.4 ppm for 4 h and (ii) 4 ppm for 1 h. After exposing A549 human lung cells to 0.4 ppm O3, we first confirmed the exposures were conducted in a consistent manner to previously reported experiments (Jaspers et al., 1997) by measuring levels of IL-8 and LDH. After validating previously observed trends in IL-8 and LDH, we next measured levels of 8OG in extracted total RNA via an ELISA assay. 8OG levels were found to be virtually identical in control and test groups following exposure to 0.4 ppm O3 for 4 h. Next, we increased O3 concentrations to 4 ppm for 1 h exposures. Since the goal of this work was to evaluate the potential of 8OG measurement as a consistent marker of exposure and we expect RNA chemistry to change relatively quickly, we chose to increase the concentration to approximate a similar dose in a shorter time frame. Upon exposures to 4 ppm of O3 for 1 h, levels of 8OG increased relative to the incubator control group (Figure 2A) for both independent

K. C. Baldridge et al. (A) 1200

(B) 0.14

*

p=0.0001 p=0.181

0.12 LDH - Measured absorbance (a.u.)

1000 Measured 8OG (pg/mL)

Figure 2. Changes after short ozone exposure. Incubator controls (unfilled bars/white bars) and exposed test samples (filled bars/black bars) are shown. Significance levels are indicated over bracket showing comparison groups; error bars represent standard error of mean (SEM). (A) For Trial 1, 8OG was increased (insignificantly) in the exposed compared to in the control group. In Trial 2, the level of 8OG in the exposed group was significantly higher than in the control group. (B) In both trials, the level of LDH secreted was significantly higher in the exposed group compared to the control group. (C) In both trials, the secretions of IL-8 were significantly decreased after exposure. (D) In both trials, the quantity of miR-10b was decreased, but only Trial 2 was significantly different after exposure. In these cases, p values shown are from comparison of DCt values instead of directly measured Ct values.

Inhal Toxicol, 2015; 27(1): 74–82

800

600

400

200

Trial 1 (C)

0.1 0.08 0.06

p=0.0006

* p=0.0008

0.04

*

0.02 0

0

Trial 2

Trial 1 (D)

600

Trial 2

2 1.8

500

1.6 miR-10b Relative quantity

Measured IL-8 secreon (pg/mL)


78

400

300

200

100

*

p=0.011

p=0.0001

*

1.4 1.2

p=0.0566

p=0.0368

Trial 1

Trial 2

*

1 0.8 0.6 0.4 0.2 0

0 Trial 1

exposure trials, although significance could not be confirmed in Trial 1. In both independent trials following 4 ppm levels of O3 for 1 h, LDH release was significantly increased in the exposed group (Figure 2B), while IL-8 secretion was significantly decreased in the exposed group as compared to the control group (Figure 2C). Given that miR-10 b levels have been found to change following formaldehyde exposures, we also tested the effect of 4 ppm of O3 exposure for 1 h on this particular miRNA, previously implicated in the inflammation response and cancer (Rager et al., 2011b). Quantities of miR-10b were decreased in both trials, albeit significance in Trial 1 was not confirmed (Figure 2D); this was the same trend observed in previous studies of 1 ppm formaldehyde exposures (Rager et al., 2011b), where intracellular levels of this particular miRNA were shown to decrease. 8OG levels in cellular RNAs increase following exposures to ACR mixtures After confirming changes in 8OG accumulation in RNAs of A549 cells exposed to 4 ppm O3, we wanted to understand how these same modifications accumulated in RNAs of A549 cells exposed to similar levels of ACR (872 ppb, 2 mg/m3) and MACR (698 ppb, 2 mg/m3) mixtures. We therefore

Trial 2

examined the effect on 8OG accumulation after exposure to a mixture of model unsaturated carbonyls (ACR and MACR) which are commonly observed in air pollution. As shown in Figure 3(A), 8OG levels in RNAs of exposed A549 cells were significantly increased above the control group in two independent exposure trials. Interestingly, the other measured signals were remarkably inconsistent; LDH secretion was virtually identical between control and exposed groups in the first trial, while the measured levels were significantly decreased in the exposed group for the second trial (Figure 3B). Moreover, the levels of IL-8 also varied greatly between trials, with a significant IL-8 increase in exposed samples (relative to unexposed controls) for the first trial and a significant IL-8 decrease in exposed samples (relative to unexposed controls) for the second trial (Figure 3C). A mild trend of increasing miR-10b levels following exposures was also observed for both trials, but the increase was not statistically significant in either trial (Figure 3D). 8OG levels in cellular RNAs increase following more complex exposures to O3/ACR mixtures During the last exposures of this study, we wanted to test potential changes in 8OG levels in cellular RNAs, following


(A) 1200

79

(B) 0.14 p=0.0094

*

*

p=0.039

*

p=0.0069

800

600

400

200

LDH - Measured absorbance (a.u.)

0.12


Figure 3. Changes after short exposure to ACR (872 ppb) and MACR (698 ppb). Incubator controls (unfilled bars/white bars) and exposed test samples (filled bars/black bars) are shown. Significance levels are indicated over the bracket showing comparison groups; error bars represent SEM. (A) The level of 8OG was significantly increased after exposure to carbonyl alkenes in both trials. (B) In Trial 1, there was no observable change in LDH secretion, but in Trial 2 it decreased significantly. (C) Measures of IL-8 were interesting, as the two trials showed opposite trends; in Trial 1, there was a small but significant increase and in Trial 2 there was a strong significant decrease in IL-8 secretion. (D) The quantity of miR-10b appeared to increase in both trials, but neither was statistically significant. In these cases, p values shown are from comparison of DCt values instead of directly measured Ct values.

0

0.1 0.08 0.06 0.04

p=0.829

0.02 0

Trial 1 (C) 600

Trial 2 p=0.0472

*

Trial 1 (D)

2

Trial 2 p=0.8986

1.8 500




DOI: 10.3109/08958378.2014.987361

400

300

200

p=0.0128

*

100

1.4

p=0.4605

1.2 1 0.8 0.6 0.4 0.2 0

0 Trial 1

exposure to a more complex mixture involving 4 ppm O3, 872 ppb ACR and 698 ppb MACR. Based on the increased generation of radicals in more complex reactive mixtures, we hypothesized an even more drastic increase in 8OG levels in cellular RNAs in combined O3 and unsaturated carbonyl mixtures. As shown in Figure 4(A), under this mixed condition, we observed a significant increase in 8OG that appeared consistent with a linear response based on combined effects of each component. Likewise, LDH secretion was increased in exposed groups, but only the first trial was seen as statistically significant (Figure 4B). IL-8 levels exhibited very little observable change in either experiment (Figure 4C); the relative quantities of miR-10b were reduced in the exposed group for both experiments, but the differences were not statistically significant (Figure 4D).

Discussion In this study, we characterized several toxicity marker endpoints using single-pollutant (O3) and multi-pollutant

Trial 2

Trial 1

Trial 2

mixtures (ACR+MACR and O3+ACR+MACR) to gain understanding of the effects of concentration and exposure time on the accumulation of chemical modifications (8OG) in intracellular RNAs as a novel endpoint for gauging exposure stress. Following a 4-h exposure to 0.4 ppm ozone, the fact that we did not observe any changes in 8OG levels (Table 2) is not surprising since numerous cellular barriers (membranes, repair mechanisms and anti-oxidant proteins) are working to prevent RNA damage (Davies, 2000). However, we expected that a stronger exposure on a shorter time scale might overwhelm cellular defenses and exhibit a more linear response in 8OG levels. Indeed, we observed an increased level of 8OG following a higher concentration exposure (4 ppm per 1 h). In addition, a significant increase of 8OG levels was observed in all independent trials following exposures using ACR/MACR and more complex O3/ACR/ MACR mixtures. Especially in the latter case, both trials were both found to be significant (to a level of p50.0001), indicating a very clear increase in exposed groups. As for LDH, following 1-h O3 exposures, we observed consistent increases in measured levels relative to unexposed

K. C. Baldridge et al. (A) 1200

(B)

p=0.0001

*

0.14 0.12

p=0.0001

*

800 600 400 200

LDH - Measured absorbance (a.u.)


Figure 4. Changes after short exposure to O3 (4 ppm), ACR (872 ppb) and MACR (698 ppb). Incubator controls (unfilled bars/ white bars) and exposed test samples (filled bars/black bars) are shown. Significance levels are indicated over bracket showing comparison groups; error bars represent SEM. (A) A very clear increase in 8OG levels was observed after short, high-concentration exposure to the complex mixture. Trends in both experiments are significant and quite consistent, with 50% increase above control. (B) Levels of LDH appear to be increased in both trials, but the difference was only significant in Trial 1. (C) In both experiments, the levels of IL-8 secretion were virtually the same in both groups. (D) In both trials, a small decrease in miR-10b levels was observed, but neither was found significant. In these cases, p values shown are from comparison of DCt values instead of directly measured Ct values.

Inhal Toxicol, 2015; 27(1): 74–82

0

0.1 0.08 p=0.0001

0.06

* p=0.0876

0.04 0.02 0

Trial 1 (C)

600


500

Trial 2

Trial 1 (D)

Trial 2

2 1.8

p=0.4999



80

400 300 200 100 p=0.5279

p=0.0634

Trial 1

Trial 2

1.4

p=0.6607

1.2 1 0.8 0.6 0.4 0.2 0

0

Trial 1

Trial 2

Table 2. Measurements of 8OG for each exposure condition. Trial 1

0.4 ppm ozone 4 ppm ozonea 2 mg/m3 unsaturated carbonylsa 4 ppm ozone and 2 mg/m3 unsaturated carbonylsa

Trial 2

Control group mean measured 8OG (pg/mL)

Exposed group mean measured 8OG (pg/mL)

Control group mean measured 8OG (pg/mL)

Exposed group mean measured 8OG (pg/mL)

1321.1 ± 26.3 776.3 ± 73.8 717.6 ± 33.7 576.3 ± 59.9

1355.3 ± 36.4 910.5 ± 56.5 802.6 ± 20.5 871.1 ± 25.4

1392.1 ± 29.5 742.1 ± 43.5 602.6 ± 59.6 586.8 ± 18.3

1418.4 ± 46.8 1018.4 ± 45.4 815.8 ± 45.2 865.8 ± 19

Presented values are calculated directly from the ELISA assay, where the quantities of RNA used in the assay were normalized for each sample. Values represent mean of group ± SEM. Exposed group and incubator control group means are shown for each trial. aFor a visual representation with significance levels, see Figures 2(A), 3(A) and 4(A).

controls. This increase in LDH is consistent with LDH trends observed in the literature following lower level O3 exposures (Doyle et al., 2007). However, the observed LDH trends in this experiment (not reported before under the conditions tested here) were not as clear with the other mixtures tested. The levels of miR-10b appeared to decrease with 1 h O3 exposures; while this miRNA has not been studied with O3

exposures, the observed trends were consistent with other types of exposure experiments in the literature (Rager et al., 2011b), and the decrease in Trial 2 appear statistically significant. However, similar to LDH levels, IL-8 and miR10b measurements do not show clear trends following exposures involving unsaturated carbonyls and more complex mixtures of O3 in this study.


DOI: 10.3109/08958378.2014.987361

The non-linear responses of the LDH, IL-8 and miRNA levels are not surprising, since chemistry changes in pollutant mixtures from gas-phase reactions initiated by sunlight (which unavoidably varies slightly between experiments) are known to produce at least 20 other gaseous VOCs, making each experiment slightly different. Since our focus was not to characterize the specific cellular response to O3, ACR and MACR, air chemistry variations across experiments were not of great concern. Although the inconsistent responses seen in the measurement of IL-8 and miR-10b complicate our goal of comparing the various toxicity marker endpoints that were measured, LDH measurements viewed in combination with the IL-8 and miR-10b measurements are informative, since LDH release is indicative of cell death. In each case where LDH increased significantly (i.e. significant cell death occurred), IL-8 and miR-10b measurements either did not change significantly or decreased. This is not surprising, since significant cell death can reduce the measurable levels of transcriptional and translational signals, and since downstream signals like IL-8 and miR-10b can take several hours after exposure to change significantly (Doyle et al., 2007; Rager et al., 2011a; Zavala et al., 2014). In stark contrast, trends in measured levels of 8OG were highly consistent, even as reflected by the linear additive effect in 8OG accumulation resulting from combining O3 and unsaturated carbonyls. While the likelihood of increased cell permeability prior to death may allow pollutants to interfere with IL-8 and miR-10b production, it seems that 8OG levels are less influenced by cell death effects. Likewise, 8OG measurements seemed consistent despite the possibility of variable composition of the pollutant mixture.

Conclusions Overall, our findings suggest that chemical changes in RNA appear to be a more consistent endpoint measurement than the other stress markers commonly measured for in vitro exposure studies. In all 1-h exposure conditions, the level of oxidation in total RNA appeared to consistently increase, in a way that was determined to be significant (in all but one trial). We also observed a trend that RNA oxidation (as measured by 8OG) further increased with complexity of the mixture used for cellular exposure. This trend is not surprising, since the total pollutant content was higher than the other exposures; furthermore, it has previously been shown that complex pollutant mixtures generate more radical species, leading to more oxidation. Importantly, while this work does not investigate potential downstream health effects of RNA modifications directly, our results suggest that chemical modifications in cellular RNAs may be a more sensitive and consistent marker with a clear linear response for gauging cellular stress immediately after exposure to environmental stimuli relative to the non-linear responses of miRNA, inflammation and cell death markers traditionally measured, although this trend should be further tested at ambient pollutant concentrations in future work. An additional advantage to using 8OG is the ability to obtain an indicator of compositional effects of air pollution mixture variation with an hourly resolution, which is consistent with atmospheric chemical timescales. We therefore conclude that


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chemical changes in RNAs should be included in future exposure studies as a more reliable measurement of cellular stress.

Acknowledgements We would like to thank Dr. Lea Hildebrandt at the University of Texas at Austin for the generous use of laboratory space. We also thank Dr. Isaac Sanchez for his mentorship and support to K.C.B.

Declaration of interest This work was funded by the Welch Foundation (F-1756) and funding to K.C.B. from the National Defense Science and Engineering Graduate Fellowship.

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