Effects of Chronic Secondhand Smoke (SHS) Exposure on Cognitive Performance and Metabolic Pathways in the Hippocampus of Wild-Type and Human Tau Mice
2021; National Institute of Environmental Health Sciences; Volume: 129; Issue: 5 Linguagem: Inglês
10.1289/ehp8428
ISSN1552-9924
AutoresJacob Raber, Ruby Perez, Eileen Ruth S. Torres, Destine Krenik, Sydney Weber Boutros, Esha Patel, Anna C. Chlebowski, Estefania Ramos Torres, Zakia Perveen, Arthur Penn, Daniel B. Paulsen, Michael G. Bartlett, Enze Jia, Sarah Holden, Reed Hall, Jeffrey T. Morré, Carmen P. Wong, Emily Ho, Jaewoo Choi, Jan F. Stevens, Alexandra Noël, Gerd Bobe, Glen E. Kisby,
Tópico(s)Biochemical effects in animals
ResumoVol. 129, No. 5 ResearchOpen AccessEffects of Chronic Secondhand Smoke (SHS) Exposure on Cognitive Performance and Metabolic Pathways in the Hippocampus of Wild-Type and Human Tau Mice Jacob Raber, Ruby Perez, Eileen Ruth S. Torres, Destine Krenik, Sydney Boutros, Esha Patel, Anna C. Chlebowski, Estefania Ramos Torres, Zakia Perveen, Arthur Penn, Daniel B. Paulsen, Michael G. Bartlett, Enze Jia, Sarah Holden, Reed Hall, Jeffrey Morré, Carmen Wong, Emily Ho, Jaewoo Choi, Jan Frederik Stevens, Alexandra Noël, Gerd Bobe, and Glen Kisby Jacob Raber Address correspondence to Jacob Raber, Department of Behavioral Neuroscience, L470, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239 USA. Telephone: (503) 494-1524; Fax: (503) 494-6877. Email: E-mail Address: [email protected] Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA Departments of Neurology, Psychiatry, and Radiation Medicine, Division of Neuroscience ONPRC, Oregon Health & Science University, Portland, Oregon, USA College of Pharmacy, Oregon State University, Corvallis, Oregon, USA , Ruby Perez Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Eileen Ruth S. Torres Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Destine Krenik Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Sydney Boutros Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Esha Patel Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Anna C. Chlebowski Department of Basic Medical Sciences, Western University of Health Sciences, College of Osteopathic Medicine of the Pacific Northwest, Lebanon, Oregon, USA , Estefania Ramos Torres Department of Basic Medical Sciences, Western University of Health Sciences, College of Osteopathic Medicine of the Pacific Northwest, Lebanon, Oregon, USA , Zakia Perveen Department of Comparative Biomedical Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA , Arthur Penn Department of Comparative Biomedical Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA , Daniel B. Paulsen Department of Pathobiological Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA , Michael G. Bartlett University of Georgia, College of Pharmacy, Athens, Georgia, USA , Enze Jia University of Georgia, College of Pharmacy, Athens, Georgia, USA , Sarah Holden Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Reed Hall Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA , Jeffrey Morré Mass Spectrometry Core, Oregon State University, Corvallis, Oregon, USA , Carmen Wong Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA Department of Animal Sciences, Oregon State University, Corvallis, Oregon, USA , Emily Ho Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA , Jaewoo Choi Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA , Jan Frederik Stevens College of Pharmacy, Oregon State University, Corvallis, Oregon, USA Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA , Alexandra Noël Department of Comparative Biomedical Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA , Gerd Bobe Mass Spectrometry Core, Oregon State University, Corvallis, Oregon, USA Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA , and Glen Kisby Department of Basic Medical Sciences, Western University of Health Sciences, College of Osteopathic Medicine of the Pacific Northwest, Lebanon, Oregon, USA Published:19 May 2021CID: 057009https://doi.org/10.1289/EHP8428AboutSectionsPDF Supplemental Materials ToolsDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditEmail AbstractBackground:Exposure to secondhand smoke (SHS) is a risk factor for developing sporadic forms of sporadic dementia. A human tau (htau) mouse model is available that exhibits age-dependent tau dysregulation, neurofibrillary tangles, neuronal loss, neuroinflammation, and oxidative stress starting at an early age (3–4 months) and in which tau dysregulation and neuronal loss correlate with synaptic dysfunction and cognitive decline.Objective:The goal of this study was to assess the effects of chronic SHS exposure (10 months' exposure to ∼30 mg/m3) on behavioral and cognitive function, metabolism, and neuropathology in mice.Methods:Wild-type (WT) and htau female and male mice were exposed to SHS (90% side stream, 10% main stream) using the SCIREQ® inExpose™ system or air control for 168 min per day, for 312 d, 7 d per week. The exposures continued during the days of behavioral and cognitive testing. In addition to behavioral and cognitive performance and neuropathology, the lungs of mice were examined for pathology and alterations in gene expression.Results:Mice exposed to chronic SHS exposure showed the following genotype-dependent responses: a) lower body weights in WT, but not htau, mice; b) less spontaneous alternation in WT, but not htau, mice in the Y maze; c) faster swim speeds of WT, but not htau, mice in the water maze; d) lower activity levels of WT and htau mice in the open field; e) lower expression of brain PHF1, TTCM1, IGF1β, and HSP90 protein levels in WT male, but not female, mice; and f) more profound effects on hippocampal metabolic pathways in WT male than female mice and more profound effects in WT than htau mice.Discussion:The brain of WT mice, in particular WT male mice, might be especially susceptible to the effects of chronic SHS exposure. In WT males, independent pathways involving ascorbate, flavin adenine dinucleotide, or palmitoleic acid might contribute to the hippocampal injury following chronic SHS exposure. https://doi.org/10.1289/EHP8428IntroductionSeveral studies have shown detrimental effects of SHS on the adult brain (Akhtar et al. 2013; Heffernan and O'Neill 2013a, 2013b). Nonsmokers exposed to SHS have an increased risk of developing mild cognitive impairment (MCI) (Akhtar et al. 2013; Barnes et al. 2010; Llewellyn et al. 2009; Orsitto et al. 2012). Most MCI patients eventually develop dementia (Langa and Levine 2014). SHS also doubles the risk for dementia among individuals who never smoked (Cataldo et al. 2010; Chen 2012; Schick and Glantz 2005).In Alzheimer's disease (AD), a common form of dementia, the spread of neurofibrillary tangles (NFTs), which are made up of hyperphosphorylated tau aggregates, is associated with disease severity in individuals with AD. Tau seeding activity in cell- and animal-based studies was correlated with disease severity (Dujardin et al. 2020), and there is evidence that spread of tau pathology throughout the brain is correlated with progressive cognitive decline in AD and other forms of dementia (Mufson et al. 2014; Ossenkoppele et al. 2020; Vogel et al. 2020; Brier et al. 2016; Malpetti et al. 2020). The formation of tau oligomers is considered an early event that triggers the subsequent hyperphosphorylation and aggregation of tau in NFTs (Takeda 2019). Recent advances in tau oligomer research have increased our understanding about tau dysregulation in cognitive disorders (Mufson et al. 2014; Ossenkoppele et al. 2020; Vogel et al. 2020; Brier et al. 2016; Malpetti et al. 2020), but whether SHS induces dysregulation of wild-type (WT) human tau is unknown. In addition, although much is known about the influence of mutant human tau, less is known about the dysregulation of endogenous tau on brain integrity and function in animal models of dementia. A nonmutant human tau (htau) mouse model is available that exhibits age-dependent tau dysregulation, neurofibrillary tangles, neuronal loss, neuroinflammation, and oxidative stress starting at an early age (3–4 months) and in which tau dysregulation and neuronal loss correlate with synaptic dysfunction and cognitive decline (Polydoro et al. 2009).MCI is characterized by a dysfunction in brain glucose metabolism (Chami et al. 2016; Willette et al. 2015a, 2015b) and other metabolic pathways are perturbed in neurodegenerative diseases (González-Domínguez et al. 2015; Liu et al. 2014; Trushina et al. 2013). SHS might increase the risk of MCI or dementia by perturbing brain metabolism (i.e., insulin signaling, oxidative stress) and the accumulation of pathological proteins (i.e., tau, amyloid).Consistent with the human data, brain insulin signaling was impaired and the accumulation of pathological proteins induced following short-term exposure of 2-month old mice (6h/d×5d/wk×4wk or 8wk) to a mixture of sidestream/mainstream cigarette smoke (Deochand et al. 2015). Lipid peroxides, DNA damage, and tau dysregulation (tau isomers, phosphotau) in the brain were induced following shorter durations of exposure of neonatal mice to mainstream/sidestream smoke (1h/d×1 month) (La Maestra et al. 2011), features frequently observed in MCI and dementia patients (Bradley-Whitman et al. 2013; Lovell and Markesbery 2007; Wirz et al. 2013). Longer exposures of 2-month-old WT rats or 3-month-old APP/PS1 transgenic mice to sidestream cigarette smoke (1h/d×5d/wk×2 or 4 months) resulted in tau and amyloid pathology like that reported in patients with MCI or dementia (Ho et al. 2012; Moreno-Gonzalez et al. 2013). The duration of SHS exposure in these studies (Avila-Tang et al. 2013) was much shorter in comparison with human studies that showed a strong correlation between the duration of SHS exposure (>25y) and impaired cognitive function (Barnes et al. 2010; Llewellyn et al. 2009; Orsitto et al. 2012). To more closely replicate human SHS exposure, in the present study we assessed the effects of daily SHS exposure, for 10 months and starting at 5–9 wk of age, on behavioral and cognitive performance and neuropathology of WT and htau mice. In addition, the lungs of these mice were examined for pathology and alterations in gene expression. Because women are at increased risk of developing MCI and AD (Au et al. 2017; Barnes et al. 2003; Farrer et al. 1997) and one study showed that cognitive decline was greater in women than men (Sohn et al. 2018), we included female and male mice in these studies.Animals, Exposures, Materials, and MethodsAnimals and ExposuresSixty four 5- to 9-wk-old htau mice on a C57BL/6J background and C57BL6/J WT mice (n=16 mice/genotype/sex) were purchased from the Jackson Laboratory. Mice were group housed at 4 mice per cage. Food (PicoLab Laboratory Rodent Diet 5L0D) and water were available ad libitum except during the SHS or control exposures. Lights in the housing room were set to 12 h light:12 h dark cycle. All behavioral tests and procedures took place within the light cycle. For each group of 16 mice per genotype and sex, 8 were randomly assigned to SHS and 8 to air control (Sham) exposures. For the Sham exposures, the mice were put in the same pie-shaped holders and exposed to ambient air. The SHS and Sham exposure groups were offset by 1 month (Sham exposures started 1 month after SHS exposures) to allow for enough time for behavioral and cognitive testing. One male htau mouse and one male WT mouse died during the 10-month exposure window (312 d, 7 d per week). Mice were exposed to SHS (90% sidestream, 10% mainstream) using the SCIREQ® inExpose™ system or to air control (Sham) for 168 min per day. The exposures continued during the days of behavioral and cognitive testing. Each day, (24) 3R4F certified cigarettes (University of Kentucky, Lexington, KY, USA) were lit using a cigarette-smoking robot (CSR) and CSR lighter (SCIREQ®), with one puff taken per minute and a flow rate of 2L/min. The amount of particulate matter was analyzed monthly by gravimetric analysis as described in Noël et al. (2017). Off-line determination of total mass concentration was measured gravimetrically by sampling and collecting the SHS particulate on glass fiber filters (MilliporeSigma) placed inside a cassette. The filters were weighed, before and after sampling, on a Mettler-Toledo balance (AG285). All mice were weighed every other week. After exposure for 4 and 8 months, blood was collected (submandibular) in tubes containing 5μL of a 0.5M EDTA solution and following centrifugation at 5,000×g for 10 min, and the supernatant was stored at −80°C for analysis of steady-state plasma cotinine levels. Procedures were performed according to the National Institutes of Health (NIH) Guide for the Care and Use of Laboratory Animals, with approval from the Oregon Health & Science University (OHSU) Institutional Animal Care and Use Committee (IACUC) and consistent with the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines.Plasma Cotinine LevelsFor the analysis of plasma cotinine and its metabolites in the mice, a hydrophilic interaction liquid chromatography–tandem mass spectrometry (HILIC-MS) method adapted from Li et al. (2012) was used; (–)-Cotinine (COT) was purchased from Sigma-Aldrich. (R,S)-norcotinine (NCOT), trans-3′-hydroxcotinine (OHCOT) and (S)-cotinine-N-oxide were obtained from Toronto Research Chemicals. Stable isotope labeled internal standard (IS) (±)-cotinine-D3 (COT-d3) solution (1mg/mL in methanol) was obtained from Sigma-Aldrich. (R,S)-norcotinine-d4 (NCOT-d4), trans-3′-hydroxycotinine-d3 (OHCOT-d3) and (R,S)-cotinine-N-oxide-d3 (COTNO-d3) were also obtained from Toronto Research Chemical. Stock solutions of all analytes and internal standards were prepared by dissolving 1.0mg of each compound in 1.0mL of methanol to obtain drug concentrations of 1.0mg/mL, with the exception of COT-d3, which was prepared as a 1.0-mg/mL methanol solution. Serial dilution of each compound with 90% acetonitrile (ACN)/water (v/v, 9/1) was used to obtain combined working solutions at concentrations of 10.0, 20.0, 50.0, 100.0, 200.0, 500.0, and 1,000.0 ng/mL. Quality control (QC) working solutions were 10.0, 30.0, 300.0, and 750.0 ng/mL. IS working solutions containing COT-d3, NCOT-d4, OHCOT-d3, and COTNO-d3 were prepared at a single concentration of 500.0 ng/mL in 90% ACN/water (v/v, 9/1).Liquid Chromatography–Mass Spectrometry (LC-MS/MS) Conditions for Plasma Cotinine LevelsAn Agilent 1100 binary pump high-performance liquid chromatography (HPLC) system was interfaced to a Waters Micromass Quattro micro™ triple quadrupole mass spectrometer. The analytes were separated on a Phenomenex Kinetex® HILIC ultra-high-performance liquid chromatography (UHPLC) column (50×2.1mm ID, 2.6μm) coupled with a SecurityGuard™ ULTRA HILIC guard column. The mobile phase A was a 10 mM ammonium formate aqueous buffer with 0.1% formic acid. The mobile phase B was acetonitrile; 10μL of samples were injected onto the column. The analytes were separated with the following gradient (time in minutes, % mobile phase B): (0, 95), (8, 50), (8.1, 95), (15, 95) at a flow rate of 0.3mL/min and a column temperature of 25°C. The LC system was interfaced by a six-port divert valve to the mass spectrometer, introducing eluents from 1.0 to 6.0 min to the ion source. After each injection, the autosampler needle was washed with methanol.The mass spectrometer was run in positive ion electrospray mode, with nitrogen as the desolvation gas at a flow rate of 500L/h and a temperature of 500°C. The cone gas flow was set to 0L/h. Argon was used as the collision gas. The collision cell pressure was 3.5×10−3 mbar. The source temperature was 120°C, and the capillary voltage was set at 3.0 kV. For the quantification of analytes, multiple reaction monitoring (MRM) functions were used: cotinine, norcotinine, cotinine-N-oxide, and trans-3′-hydroxy-cotinine. The cone voltage was 20 V, and collision energy was 26 eV. Ion transitions monitored for analytes were 177→80 for COT, 163→80 for NCOT, 193→80 for OHCOT, and 193→96 for COTNO. Ion transitions for IS were 180→80 for COT-d3, 167→84 for NCOT-d4, 196→80 for d3-OHCOT and 196→96 for d3-COTNO.Plasma Cotinine StandardsBlank plasma with sodium EDTA was purchased from Bioreclamation. In addition, 10μL of standard or QC working solution was spiked into 100μL of blank plasma to generate standard/QC samples. For the calibration standards, the final concentrations were 1.0, 2.0, 5.0, 10.0, 20.0, 50.0, and 100.0 ng/mL in plasma.Sample Preparation for Assessment of Plasma Cotinine LevelsThe mouse plasma samples were subjected to protein precipitation and solid phase extraction (SPE). To remove plasma proteins, 10μL of the IS working solution (500 ng/mL) was added to 100μL of plasma, 800μL of water, and 100μL of 25% (wt/vol) trichloroacetic acid (TCA), and the mixture vortexed for 10 min. For SPE, the supernatant from protein precipitation was loaded onto an OASIS MCX SPE cartridge (Waters Corporation), which was preconditioned with 1mL of methanol and equilibrated with 1mL of water and allowed to flow by gravity. The cartridge was washed twice with 1mL of 5% methanol, 5% formic acid in water (v/v), followed by vacuum drying for 5 min. Analytes were eluted with 1mL of fresh 20% methanol, 5% ammonia in water (v/v). The eluent was evaporated to complete dryness in a centrifuge evaporator at 50°C. The lyophilized sample was reconstituted with 100μL of 95% ACN/water (v/v, 9/1) with 2% formic acid prior to injection.Calibration Curve Plasma Cotinine LevelsTo generate calibration curves for cotinine and its metabolites, a 1/x-weighted linear regression was used. The response was reported from peak area ratios between the analyte and the internal standard. For all analytes, the calibration curves exhibited good linearity (R2>0.99) within the range of 1 to 100 ng/mL.Behavioral and Cognitive TestingY maze.Mice were tested for hippocampus-dependent spontaneous alternation in the Y maze, exploratory behavioral and measures of anxiety, and object recognition in week 1. Performance in the Y maze was described using the mazes from O'Hara as described in Saito et al. (2014). The Y-shaped maze was purchased from O' Hara & Co., Ltd. It has raised sides (3.8cm bottom width, 12.55cm top width, 12.55cm height) with plastic, opaque gray arms (37.98cm length) at a 120° angle from each other. At the beginning of a 6-min trial, mice were placed in the center of the maze. To isolate mice from the surrounding room as well as from the experimenter, the mazes were surrounded with a white curtain. The mazes were cleaned with 0.5% acetic acid between trials. Performance of the mice was tracked during testing with Ethovision XT v14 software (Wageningen). To measure the number of arm entries and to calculate the percent spontaneous alternations, the videos were analyzed. The criterion for an arm entry was when all four limbs were within the arm. The spontaneous alternation percentage was calculated by dividing the number of 3-arm alternations by the number of possible 3-arm alternations and multiplying the value by 100.Open field and object recognition.Exploratory activity and measures of anxiety were assessed in the open field test, as described (Benice et al. 2006). The open field consisted of a well-lit square (L 40.6×W 40.6×H 40.6cm) with a central light intensity of 100 lux. On each of 2 subsequent days, mice were allowed to explore the open field for 5 min. Object recognition was assessed as described (McGinnis et al. 2017), with the following modifications. On day 3, the open field contained two identical objects, and the mice were exposed to the open field with the objects for a 10-min trial. The objects were placed 10cm apart and 15cm from the adjacent walls of the arena. On day 4, one object was replaced with a novel object, and mice were allowed to explore for 10 min. During object recognition trials, the objects were affixed with masking tape to the floor of the arena. Physical interaction with the object in the form of sniffing within a 2-cm proximity was coded as object exploration. The enclosures were cleaned with 0.5% acetic acid between trials. Performance of the mice during all trials was analyzed using Ethovision XT software (version 7.0). Time spent in the center of the open field was analyzed to assess measures of anxiety. Videos were later hand scored to measure object exploration. The percent time exploring the novel object out of the total time spent exploring both objects on day 4 was calculated.Water maze.The mice were tested for spatial learning and memory in the water maze in week 2, with a 72-h probe trial on the following Monday. The maze was 140cm in diameter and was filled with opaque water containing nontoxic, white chalk. Large visual cues surrounded the maze to make this a hippocampus-dependent task. An escape platform was submerged 1cm below the water surface. First, the mice were trained to locate a visible platform over 2 d, each consisting of three trials. During each training trial, mice were dropped off in counterbalanced locations and allowed to explore the water maze. When mice located the escape platform and remained on it for 3 s, the trial ended. Mice that did not find the platform within the 60-s trial time were gently led to the platform by the experimenter. Following visible platform training, the mice were trained to locate a hidden platform over 3 d, each consisting of three trials. To assess spatial memory retention, there was a probe (no platform) before starting the third day of hidden platform training. Following the third day of hidden-platform training, there was a second probe trial 72 h later. For the visible and hidden platform learning curves, time to reach the platform (latency), distance moved, and swim speeds were analyzed using Ethovision XT v14 software. Percent time spent in the quadrant that contained the target location during the hidden platform training trial (target quadrant) and the three non-target quadrants and cumulative distance to the target (since there is no platform in the probe trial) location were used as performance measures for analyzing performance in the probe trials.Contextual fear conditioning.Mice were tested for hippocampus-dependent contextual fear learning and memory in week 3. Contextual fear conditioning was assessed over the 2 consecutive days using a Med Associates mouse fear conditioning system (PMED-VFC-NIR-M; Med Associates, Inc.) and Med Associates VideoFreeze® automated scoring system. Mice were placed inside the fear conditioning chamber. The chamber lights were turned on at the beginning of the trial. Following a 120-s baseline habituation period, four 30-s tones (80 dB) were presented which coterminated for the last 2 s of each tone with a 0.50 mA foot shock. Twenty-four hours later the mice were placed in the same chamber as during training (acquisition) for a 5-min trial. The chamber lights were on, but no tones or shocks were presented. Between trials, the enclosures were cleaned with 0.5% acetic acid. Motion during the baseline (prior to the first tone on the training day) and percent freezing during the tones and between the tone-shock pairings on the training day and during the contextual fear memory test were analyzed using VideoFreeze® software.Histopathological Analysis of the LungsMice were killed by cervical dislocation the day after the last SHS or sham exposure, and the lungs were examined for histopathology. The lungs that were excised were not previously lavaged, and therefore the histopathology is representative of intact lungs. No mice in this study were used to collect broncho-alveolar lavage (BAL). After euthanasia, the lungs of mice were excised and either fixed or processed for RNA extraction. The left lung of each mouse (n=8 mice per group) was fixed with buffered formalin (10%) for 24–48 h. Subsequently, standard histological processing, sectioning and hematoxylin-eosin (H&E) staining were conducted as previously described (Noël et al. 2020). Slides containing three sections (5μm) of lung lobes were coded randomly. The stained sections were then evaluated by a board-certified veterinary pathologist with expertise in pulmonary pathology and blinded to treatments. Lung tissues were evaluated for a) hyperplasia of bronchus-associated lymphoid tissue (BALT); b) bronchial, peribronchial, and perivascular infiltration of lymphocytes and plasma cells; c) bronchial, peribronchial, and perivascular infiltration of neutrophils; d) bronchial, peribronchial, and perivascular infiltration of eosinophils; e) bronchial goblet cell hyperplasia; and f) alveolar inflammation. Ten to 20 random sections were evaluated to determine the spectrum of lesions in the study from the least to most affected for each parameter. On that basis, the least affected ones were considered to be normal, and the spectrum of changes was used to determine the range of changes from normal to severe (if applicable). The lungs were scored for each of the six aforementioned parameters on a 0–4 scale, with 0=normal, 1=minimal increase, 2=mild increase, 3=moderate increase, and 4=severe increase.Lung mRNA ExtractionHalf of the right lung of each mouse (n=8 mice per group) was harvested and placed in RNA later and stored at −80∘C. Prior to mRNA extraction from these lung samples, RNA was purified from the aqueous phase of the lung homogenate using a RNeasy Mini Kit (Qiagen) that included a RNase-free DNase treatment, according to the manufacturer's instructions. A NanoDrop™ ND-1000 Spectrophotometer (Nano-Drop Technologies) was used to assess the quantity and purity of the RNA samples, as previously described (Noël et al. 2017, 2020).Gene Expression Analysis via RT2 profiler Polymerase Chain Reaction (PCR) ArrayThe expression of 84 genes included in the Molecular Toxicology Pathway Finder RT2 PCR array (PAMM-401Z, Qiagen) was analyzed in the lungs of mice (n=4 mice per group) following the manufacturer's instructions. As previously described in Noël et al. (2020), after DNase treatment of lung tissues, total RNA (0.5μg) was reverse transcribed using the RT2 First Strand Kit (Cat. No. 330401; Qiagen). The cDNA was diluted with RNase-free water and mixed with RT2 SYBR Green qPCR Master mix (Cat No. 330503; Qiagen). Equal aliquots (25μL) were added to the corresponding wells of a PCR Array plate. The PCR was performed according to the cycling conditions of an Applied Biosystems model 7300 real-time cycler. Gene expression and fold-change compared with the respective air control group were calculated using the 2−ΔΔCt method. ΔCt data for male mice were calculated using the average arithmetic means of Actb, B2m, Gapdh, Gusb, and Hsp90ab1 to normalize the raw data, whereas ΔCt data for female mice were calculated using the geometric means of Actb and Gapdh as the normalization factor. The fold changes were calculated with the Qiagen web-based PCR Array data analysis software. Gene expression results were considered significant with fold-changes >±1.5 compared with the respective air control group.Ingenuity Pathway AnalysisGene expression data obtained from the RT2 PCR array were analyzed with Ingenuity Pathway Analysis (IPA; version 60467501; Qiagen Ingenuity Systems), as previously described (Noël et al. 2020; Rouse et al. 2008). The Ingenuity Analysis Knowledge Database was used to identify gene networks and canonical pathways from our gene expression datasets.Dot Blot AnalysisThe hippocampus, cortex, and cerebellum were obtained from the left hemispheres of 4–5 mice per exposure/genotype/sex, immediately snap frozen in liquid N2 prior to storage at −80∘C. The left hemisphere was used for dot blotting and metabolomics analysis, whereas the right hemispheres were immersion fixed in 4% buffered paraformaldehyde and used for immunohistochemistry. Protein extracts were prepared from freshly frozen brain regions of mice and immunoprobed for 21 molecular markers (see Table 1 for details of primary antibodies) by dot blot with near-infrared imaging as previously described (Chlebowski and Kisby 2020). The hippocampus, cerebral cortex and cerebellum of mice were sonicated in extraction buffer [Tris HCl, 10 mM, pH 7.8; dithiothreitol, 0.5 mM; MgCl2, 5 mM; adenosine triphosphate, 30.8mg/10mL; cOmplete Mini Protease inhibitor, EDTA-free (1 tablet/10mL); double-distilled water, 7.8mL/10mL solution]. All buffer components were from Millipore-Sigma. The tissue homogenates were centrifuged at 15,000×g for 90 min at 4°C, and the supernatants were examined for protein concentration by the Bradford assay (BioRad Laboratories, Inc.). The supernatants were diluted with TBS for dot blot analysis and stored at −80°C until use. Diluted samples (1μg protein/well) were first applied on a 0.45μM nitrocellulose membrane in a dot blot apparatus (BioRad). The membranes were then treated with the Revert® total protein stain kit (LiCor) before imaging on an Odyssey® CLx imager (LiCor Biosciences) to determine protein loading. Membranes were then blocked with LiCor Intercept® (TBS) blocking buffer, and the primary and secondary antibodies (see Table 1 for the list of primary antibodies) were diluted in 50:50 Intercept® Blocking Buffer:TBS with 0.01% Tween-20. The membranes were incubated with the primary antibodies overnight at 4°C with gentle rocking. Subsequently, the membranes were washed 3 × 10 min in TBS+0.1% TWEEN-20 (TBST) before incubation with secondary antibodies for 1 h at 20–22°C in the dark (the wash container was wrapped in foil). All secondary antibodies were from LiCor and used at a 1:10,000 dilution. The secondary antibodies used were 926-32210,
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