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Materials and Methods Top

Neuronal and astrocyte cell cultures

We prepared primary mouse granule and astrocyte cell cultures from the cerebella of 6- to 8-day-old neonatal C57BL/6 (Charles River Laboratories, Wilmington, MA) mice by placing the tissues in ice-cold Hibernate/B27 cell culture media (Invitrogen Corp., Carlsbad, CA) and dissociating the tissue in balanced salt solution with 0.1% trypsin as previously described (Kisby et al. 2000, 2004; Meira et al. 2001). The cell suspension was placed in poly-D-lysine coated (Biocoat; BD Biosciences, Bedford, MA) 48-well plates (viability studies), 8-well chamber slides [terminal deoxynucleotidyl transferase-mediated biotinylated-UTP nick end-labeling (TUNEL)], or 6-well plates (DNA damage) at a density of 0.07 × 10⁶/well (8-well chamber slides and 48-well plates) or 1 × 10⁶ cells/well (6-well plates), respectively. We fed cell cultures weekly by adding fresh culture media to the wells and maintained the cells for 7 days (neurons) or 3–4 weeks (astrocytes) before treatment with 10–1,000 μM MAM or 0.1–20 μM mechlorethamine hydrochloride (HN2). All animals used in these studies were treated humanely and with regard to the alleviation of suffering according to protocols approved by the Oregon Health & Science University Institutional Animal Care and Use Committee.

Cell viability

Mouse neuronal and astrocyte cell cultures treated with control media or media supplemented with various concentrations of MAM or HN2 were examined for cell viability using the fluorochrome acetoxymethyl ester, as previously described (Kisby et al. 2004; Meira et al. 2001). The fluorochrome-containing media was aspirated, the cultures washed once with control media, and cell survival examined on a fluorescence microplate reader (GeminiXS; Molecular Devices, Sunnyvale, CA) with well-scan capabilities. Values were expressed as the mean percent surviving of control cells ± SE (n = 6/treatment group × 3–5 separate experiments).

DNA damage

N 7-Alkylguanine levels.

We isolated and purified DNA from MAM- or HN2-treated cerebellar neuronal cell cultures by extracting the tissue with Tri-Reagent (Molecular Research Corp., Cincinnati, OH) according to the manufacturer’s instructions. DNA concentration ranged between 20 and 30 μg/1 × 10⁶ cells, and the purity was checked by measuring 260/280 ratios (range 1.7–2.0). An alkylated DNA standard was prepared by treating calf thymus DNA (CT-DNA) with 1 mM MAM in buffer [300 mM MOPS, 2 mM EDTA (pH 7.5)] for 1 hr at 37°C. DNA samples and alkylated CT-DNA were depurinated by incubating in 0.1 N HCl for 17 hr at 37°C. The depurinated samples and standards were neutralized with 1.0 N NaOH, passed through a C₁₈ SepPak cartridge (Millipore Corp., Bedford, MA), and taken to dryness in a speed-vac. The lyophylized samples and alkylated DNA were analyzed for N 7-methylguanine (N7-mG) or N 7-alkylguanine [i.e, N-(2-hydroxyethyl)-N-(2-(7-guaninyl)ethyl)-methylamine (GMOH)] DNA lesions by HPLC with electrochemical detection as previously described by Eizirik and Kisby (1995), Esclaire et al. (1999), and Kisby et al. (2000). Alkylated DNA was used to determine recovery (> 90%) of N7-mG and GMOH from the extraction process. N7-mG and GMOH levels were determined in samples and from a standard curve (r = 0.99) of CT-DNA alkylated with MAM or HN2, respectively. Values are expressed as fmoles N7-mG or GMOH per microgram DNA.

TUNEL labeling.

Primary cerebellar neuronal cultures treated for 24 hr with MAM or HN2 were examined for DNA fragmentation using TUNEL with the NeuroTacs staining kit according to the manufacturer’s instructions (Trevigen, Gaithersburg, MD). After toxin treatment, the cells were fixed with 4% buffered paraformaldehyde, and the incorporation of biotinylated nucleotides was visualized by incubating the cells with NovaRed (Vector Labs, Inc, Burlingame, CA). Slides were lightly counterstained with methyl green and the cells examined by light microscopy as previously described (Kisby et al. 2004).

Microarrays

We purchased 27,648 sequence-verified mouse cDNA clones from Research Genetics [Brain Molecular Anatomy Project (BMAP) clones; Invitrogen Corp.] and The National Institute of Aging (NIA clones; Bethesda, MD) as frozen bacterial stocks were used to create two individual arrays (13,824 genes/array) spanning nearly the entire mouse genome. Universal forward and reverse primers were amino modified with a 5′ C₁₂ spacer. Polymerase chain reaction (PCR) products were purified using Telechem PCR clean-up plates, dried down, and resuspended in 20 μL Telechem spotting solution and printed on TeleChem SuperAldehyde substrates using a Cartesian Pixsys printer with quill pins from TeleChem International (Sunnyvale, CA).

RNA preparation.

We isolated RNA from cerebellar neuronal cultures treated for 24 hr with 100 μM MAM or 1.0 μM HN2 using Tri-Reagent (Molecular Research Corp.) according to the manufacturer’s protocol. Because RNA concentrations were low (10–15 μg/well for 6-well plate), two wells were combined, and each combined sample (n = 3) was analyzed for gene expression using mouse cDNA microarrays. We used bromochloropropane for the initial phase separation. RNA was dissolved in water that had been treated with diethyl pyrocarbonate to ensure that it was RNAse free and quantitated based on optical density (OD)₂₆₀.

Gene arrays processing.

RNA (10 μg) was reverse transcribed using 2 μg of oligo dT primer (24mer) in the presence of 200 mM dNTP mixture (dATP, dGTP, dCTP), 100 mM dTTP, 100 mM 5-(3-aminoallyl)-2′-deoxyuridine-5′-trip​hosphate (Sigma Chemical Corp., St. Louis, MO) and 300 U of Superscript II (Invitrogen, Carlsbad, CA) to generate aminoallyl-modified cDNA probes. After hydrolysis of the original RNA, we used a Qiagen PCR cleanup kit (Qiagen, Valencia, CA) with a modified protocol to purify the cDNA product. The cDNA probe was then dried down and resuspended in 0.1 M NaCO₂ buffer (pH 9.0) and coupled to N-hydroxysuccinimide ester cyanine 5 dye (GE Healthcare, Piscataway, NJ) in the presence of dimethylsulfoxide. The uncoupled dye was removed using a Qiagen PCR cleanup kit according to the the manufacturer’s protocol. The purified cDNA probe was lyophilized and resuspended in 70 μL of Ribohybe (Ventana, Tucson, AZ). Probe was added to the microarray using a lifterslip (Erie Scientific, Portsmouth, NH) and allowed to hybridize in a humidity chamber for 16 hr at 50°C. Each sample was hybridized separately to two arrays with distinct sets of cDNA probes (one set from the BMAP clones and one from the NIA clone set). The combined data from the two probe sets explore the variation in gene expression with 27,265 unique clones. Microarrays were washed with 2 × SSC [300 mM NaCl, 30 mM sodium citrate (pH 7.0)] on a rocker 2 × 10 min at room temperature followed by two washes for 10 min each in 0.2 × SSC at 50°C to remove unbound probe. Microarrays were dried by centrifugation. Tagged image file format (.tif) images were collected using a SA5000 fluorescence scanner (PerkinElmer, Wellesley, MA) and the data collected and analyzed with QuantArray data collection software (PerkinElmer). Signal extraction protocols exported the mean pixel intensity of the upper 65% of signal pixels and the mean pixel intensity of the lower 65% of background pixels.

Data analysis

We adjusted mean signal intensity for local background by subtracting the mean background intensity. Data for each array set were exported to Arraystat statistical software (Imaging Research, version 1.0, revision 2.0; GE Healthcare). The Arraystat normalization parameters used were “proportional model with offsets, no outlier exclusion,” which log transforms the data (log₁₀) and globally centers the transformed data within conditions by subtracting the array mean for all genes present on all arrays in the condition and adding the condition mean for all arrays in the condition. Condition means were globally centered by subtracting the median of the mean signal intensities for the condition and adding the median of the mean signal intensities across all conditions. Modified analysis of variance (ANOVA) (Arraystat F* tests) and significance of differences between means (z-tests) were determined using a pooled error model. Centered expression values and test results were exported to Microsoft Excel (Microsoft Corp., Redmond, WA). We converted normalized means and differences between means from log₁₀ to log₂ for ease of comparison with the literature. Data sets were merged and adjustment for multiple testing was conducted on the p-values of the statistical tests in the merged data set using the false discovery rate correction with the level of acceptable false positives set at 0.05 for each statistical test (Benjamini and Hochberg 1995). The full set of MAM- and HN2-targeted genes can be found online in Supplemental Material (http://www.ehponline.org/docs/2006/9073/​suppl.pdf ).

Results Top

Viability and DNA damage in immature neurons

In the present study, our goal was to determine the relationship between the sensitivity of immature postmitotic neurons to MAM or HN2 and their ability to damage DNA. For these studies, we treated neuronal cell cultures from the cerebellum of neonatal mice with various concentrations of MAM or HN2 for 24 hr and examined them for cell survival (Figure 1A,B). We also similarly treated astrocytes with MAM and HN2 to compare the vulnerability of different CNS cell types to genotoxicants. Survival of cerebellar neurons was significantly reduced with increasing concentrations of MAM (> 100 μM) or HN2 (> 5.0 μM). In contrast, astrocytes derived from the same set of animals were significantly less sensitive (p < 0.01) to MAM or HN2. These studies demonstrate that immature neurons are more sensitive to MAM or HN2 than astrocytes, which suggests that this CNS cell type would be preferentially targeted in vivo by these genotoxicants.

Additional studies were conducted to determine if the increased sensitivity of neurons to MAM and HN2 was due to their genotoxic (i.e., DNA damaging) properties. DNA damage was assessed by measuring the level of N7-mG or GMOH, the two major DNA lesions formed by MAM and HN2 (Nagata and Matsumoto 1969; Osborne et al. 1995), or strand breaks (TUNEL labeling). There was a good correlation between the increased sensitivity of neurons to these genotoxicants and TUNEL labeling (Figure 2A) or the level of N7-mG and GMOH DNA lesions (Figure 2B,C). These studies demonstrate that the major DNA lesions formed by MAM or HN2 accumulate in immature neurons and that these cells are particularly inefficient at repairing these types of DNA lesions. Thus, N7-mG and GMOH are likely responsible for the neurotoxic effects of these genotoxicants observed in Figure 1. These findings are also consistent with previous in vitro and in vivo studies, demonstrating that the increased sensitivity of rat cerebellar neurons or differentiated human SY5Y neuroblastoma cell cultures to HN2 correlated with GMOH levels (Kisby et al. 2000) and N7-mG levels were elevated in the dystrophic cerebellum of neonatal or fetal mice injected with MAM (Kisby et al. 1999, 2005) or other alkylating agents (Buecheler and Kleihues 1977; Kleihues and Bucheler 1977).

Genotoxicant-induced gene expression changes

Collectively, the studies described above and the previous work with these genotoxicants (Dacre and Goldman 1996; Matsumoto et al. 1972; Somani and Babu 1989) indicate that neuronal DNA is a sensitive intracellular target. Failure to repair these DNA lesions would be expected to interfere with transcription and translation (Scicchitano and Mellon 1997; Scicchitano et al. 2004), resulting in perturbed cell function and eventual death via an apoptotic or necrotic mechanism (Dabrowska et al. 1996; Hur et al. 1998; Meier and Millard 1998; Sun et al. 1999). To identify the specific molecular networks targeted by MAM or HN2, we examined genotoxicant-treated neurons for genomewide expression using high-density mouse cDNA microarrays (Figure 3). Our objective here was to determine if these genotoxicants induce a distinct pattern of gene expression at concentrations that are sublethal (Figure 1) and that induce DNA damage (Figure 2B,C). Using these criteria, we treated cerebellar neuronal cultures with 100 μM MAM or 1.0 μM HN2 for 24 hr and examined total RNA for gene expression changes using high-density microarrays. We then compared the gene expression profiles of MAM- and HN2-treated neurons to characterize the response of immature neurons to the two different genotoxicants.

We first used hierarchical clustering (Euclidean distance measure and centroid linkage) to group genes with similar expression levels. Several of these clusters are also specifically enriched with genes of known function. As shown in the heatmap (Figure 3A), we observed distinct clusters for MAM and HN2. The number of genes uniquely regulated by each genotoxicant and their overlap is shown in Figure 3B. The global expression patterns were analyzed further by functional classes of molecules such as DNA repair, cell signaling, proteasome degradation, apoptosis to find correlations among genes and gene-regulatory networks (Figure 3C,D). The global gene expression changes we observed after MAM (606 genes, 2.19%) and HN2 (617 genes, 2.23%) treatment were comparable. Of these global changes, 397 unique genes (64%) were altered by MAM, whereas a similar amount of unique genes (408 genes, 66%) were altered by HN2. Although comparable numbers of unique genes were up-regulated by either MAM or HN2, approximately 3 times as many were down-regulated by HN2 as by MAM (Figure 3B). Among the down-regulated genes, those involved in apoptosis (9.5%) and protein synthesis (4.8%) were targeted by HN2 (n = 21), whereas MAM (n = 10) primarily targeted those involved in signal transduction (30%), cell adhesion (20%), and growth and cell cycle (10%). These studies indicate that MAM and HN2 target distinct classes of genes in neurons even though both agents alkylate DNA (i.e., the N 7 site on guanine) and induce a similar global effect on neuronal gene expression. The selective targeting of these functional classes of genes by HN2 and MAM may be related to the different types of DNA lesions generated by these two gentotoxicants; notably, HN2 induces lethal cross-links between opposing N7-alkylguanines (i.e., GMOH) (Osborne et al. 1995; Povirk and Shuker 1994; Tokuda and Bodell 1987), whereas MAM induces methylated DNA lesions (e.g., N7-mG and O⁶-mG) (Esclaire et al. 1999; Matsumoto and Higa 1966; Nagata and Matsumoto 1969). The insensitivity of cerebellar neurons to similar concentrations of 2-chloroethylamine (CEA; data not shown), a monofunctional analogue of HN2 that does not induce cross-links (Tokuda and Bodell 1987; Wijen et al. 2000) and the elevated levels of N7-mG DNA lesions in MAM-treated cortical neurons with disturbed tau gene expression (Esclaire et al. 1999) are consistent with this hypothesis.

Functional classes targeted by MAM and HN2

Even though the majority of genes influenced by sublethal concentrations of MAM or HN2 were of unknown function (63 and 77%, respectively), analysis of the known genes perturbed by MAM (225 genes) or HN2 (141 genes) revealed prominent changes in several different categories (Figure 3C,D), indicating that the molecular networks targeted by these two genotoxicants are quite distinct. As shown in Figure 3C, MAM had a greater influence on genes involved in neuronal differentiation, the stress and immune response, signal transduction, and transcriptional regulation. In contrast, HN2 primarily targeted genes involved in apoptosis and protein synthesis. As expected, MAM had a predominant effect on neuronal differentiation, which was demonstrated by the targeting of a large number of genes that control the growth and maturation of neurons (Table 1). Genes that maintain the structural integrity of neurons (Prfn2, Sdfr1, Catna1, Stmb2), cellular transport (Slc6a6, Kif1A), protein degradation (Usp5, Ufd1l, Usp2l, Psmd12), or synaptic function (Vamp4, Cplx2) were specifically targeted by MAM. The increased expression of genes that activate the depolymerization of actin (Prfn2) and micro-tubules (Stmb2) (Grenningloh et al. 2004; Yarmola and Bubb 2006) is consistent with the ability of MAM to disrupt the outgrowth of axons (Hoffman et al. 1996) and to alter the inward and vertical migration of granule cells through the developing molecular and Purkinje cell layers of the neonatal cerebellum (Ferguson et al. 1996; Kisby et al. 2004). The strong up-regulation of the serine–threonine kinase Ulk1 and the zeta isoform of protein kinase c (Prkcz), which are important regulators of neurite sprouting (Naik et al. 2000; Tomoda et al. 2004), is additional evidence of how this genotoxicant may impede the migration of immature neurons (Hatten 2002).

Although a majority of the genes targeted by MAM were involved in neuronal differentiation, the strongest response was observed for chromatin remodeling (H3f3a) (Frank et al. 2003) and energy metabolism (e.g., complex I, glycolytic enzymes) genes. The pronounced targeting of H3f3a suggests that MAM may influence transcription by disturbing the nucleosome structure through a chromatin remodeling mechanism (McKittrick et al. 2004). Therefore, the protein encoded by this histone gene may function to maintain chromatin integrity in immature neurons or might be involved with transcription or DNA repair. A corresponding increase in the expression of Ezh2, a gene that controls the expression of genes through methylation of H3 (Kirmizis et al. 2004), is consistent with this notion. Unexpectedly, MAM also produced a pronounced effect on the expression of two catalytic subunits (i.e., Ndufc1, Ndufs5) of complex I (Kirby et al. 2004; Loeffen et al. 1998) and several glycolytic enzymes (Idh, Pk3), indicating that this genotoxicant also disturbs energy metabolism. The influence of MAM on energy metabolism may explain how this genotoxicant induced lipid peroxidation in the colon and liver of rats (Deschner and Zedeck 1986) and why this effect was counteracted by pretreatment with the antioxidant quercetin (Deschner et al. 1991, 1993).

Even though MAM and HN2 both alkylated neuronal DNA, the genes specifically targeted by HN2 were quite distinct from those targeted by MAM. The most striking difference is that HN2 primarily targeted genes that regulate protein turnover and apoptosis (Figure 3D). Genes that influence the synthesis (Metap2, Mobp), modification (Galnt9), or degradation (Psme3) of neuronal proteins were down-regulated by HN2 (Table 2). The increased expression of apoptosis-inducing factor (Pdcd8), a flavoprotein that translocates from the mitochondrial intermembrane space to the nucleus to induce caspase-independent DNA fragmentation of cerebellar neurons (Slagsvold et al. 2003) and the targeting of several mitochondrial genes (Cox7a2) suggests that HN2-induced neuronal death results from disturbances in mitochondrial function. A concomitant increase in the proteasomal 19s lid component Psmd7 (or RPN8), which has dual roles in both proteolysis and mitochondrial integrity (Rinaldi et al. 2004), is consistent with this mechanism. However, HN2 had the greatest influence on adenine deaminase (Ampd3), an enzyme that maintains steady-state levels of ATP in CNS neurons (Knecht et al. 2001). Because increased AMPD activity is associated with oxidative stress and disturbed calcium homeostasis (Ronquist et al. 2001), HN2 may also induce cell death by disturbing neuronal ATP pools. The concomitant influence of HN2 on Ca²⁺-dependent enzymes (Calm1, Calm2) may have contributed to the increased expression of AMPD (Mahnke and Sabina 2005).

Although MAM and HN2 targeted distinct neuronal genes, there were a number of genes that were common targets for both genotoxicants (Table 3). As shown in Table 3, a majority of the genes targeted by both MAM and HN2 were down-regulated. The functional classes of genes specifically targeted by both genotoxicants were also quite distinct from those targeted by each genotoxicant. The strongest response was observed for genes involved in transport (5.7%), development (2.9%), and transcription (2.9%). The targeting of these genes by both genotoxicants may be a signature of a generalized response of neurons to DNA-damaging agents.

Transcriptional regulatory network analysis

We further analyzed microarray data using the promoter analysis tool PAINT (promoter analysis and interaction network tool) (Vadigepalli et al. 2003) to identify the biologically relevant transcription factor binding sites within the regulatory regions of the genes targeted by HN2 and MAM. Using the unique genes differentially regulated by at least a factor of two after MAM (n = 115) or HN2 treatment (n = 136), we examined the 5′-flanking regions of these targeted genes (2000 bp upstream of the transcription start site) for enrichment of commonly expressed transcriptional regulatory elements (TRE). The total number of TREs among the unique genes targeted by MAM (n = 78) was greater than those targeted by HN2 (n = 60). Only TREs that were significantly enriched (p < 0.01) in either MAM- or HN2-targeted genes (Figure 4A and 4B, respectively) and occurring in at least 5% of the promoters are shown. Note that no overlap occurred between the TREs enriched in the promoter regions of genes targeted by MAM and HN2 (compare Figure 4A,B). Several MAM-targeted genes were highly enriched for SRF, Nrf2, and Pax6, whereas Staf, HNF1 and Cre-BP1 were primarily enriched in HN2-targeted genes. SRF is required for neuronal activity–induced gene expression and synaptic plasticity (Ramanan et al. 2005), Nrf2 is a key regulator of oxidative stress and chemical carcinogen inducible genes (Motohashi and Yamamoto 2004) and Pax6 controls the polarization and migration of CNS neurons (Yamasaki et al. 2001). Several genes involved in neuronal differentiation and migration (e.g., Pafah1b2, Stmb2, Actb, Sdrf1, Pex1) were highly enriched with these TREs, thereby suggesting that these regulatory regions may be important targets by which MAM disrupts cerebellar development. In contrast, Staf, HNF1, and Cre-BP1 (or ATF2) were especially enriched in HN2-targeted genes involved in protein turnover (e.g., Cstf2), the cellular response to DNA damage (Ishiguchi et al. 2004), or cell death mechanisms (Pearson et al. 2005). The enrichment of distinct TREs within MAM- or HN2-targeted genes is additional evidence that these two genotoxicants exert their influence on gene expression in immature neurons by different mechanisms.

Discussion Top

Increasing evidence indicates that biomarkers of genetic damage (including DNA lesions) occur in children and newborns exposed to environmental pollutants (Neri et al. 2006). A consistent finding among these studies is the frequent association between the level of DNA lesions and impaired growth during the pre-natal or postnatal period. The increased level of genetic damage reported in these children could also have important adverse health effects on the brain, especially during early development. Consistent with this hypothesis, we have recently shown that DNA damage (i.e., N7-mG) and the perturbation of developmentally regulated genes occurs well before the neurodevelopmental changes induced by the genotoxicant MAM (Kisby et al. 2005). These studies suggest that DNA damage may be responsible for the neurodevelopmental changes induced by the genotoxicant MAM. Thus, our focus in the present studies was to investigate the putative link between genotoxicant-induced DNA damage and neuronal function by identifying the genes in immature neurons specifically targeted by different genotoxicants (i.e., MAM, HN2).

As shown in previous in vivo studies (Kisby et al. 2005), we show here that immature cerebellar neurons (i.e., granule cells) are very sensitive to genotoxicants and that this effect was associated with the accumulation of DNA lesions (i.e., N7-mG, GMOH). Our studies also suggest that the DNA damage in the cerebellum of MAM-treated neonatal mice had accumulated in immature granule cells. The greater sensitivity of granule cells compared with astrocytes to either genotoxicant is evidence that neurons are especially vulnerable to genotoxicants and are inefficient at repairing DNA damage. This appears to be a characteristic response of cerebellar neurons to genotoxicants because granule cells are also very sensitive to chemotherapeutic agents that alkylate DNA (e.g., chloronitrosourea) or induce cross-links (e.g., cisplatin) (Fujimori et al. 1992; Jones and Gardner 1976; Wick et al. 2004), whereas glial cell (e.g., astrocytes) loss is not commonly found (Cattaneo et al. 1995; Necchi et al. 1997). This differential sensitivity to genotoxicants is also shared by immature neurons and astrocytes in other brain regions because N7-mG DNA lesions persisted in the cerebrum of neonatal rats after a single in utero injection of MAM (Kisby et al. 1999) or related alkylating agents (Buecheler and Kleihues 1977; Kleihues and Bucheler 1977), whereas glial changes were unremarkable (Eriksdotter-Nilsson et al. 1986). Thus, these in vitro studies complement previous in vivo work by demonstrating that the DNA of immature neurons appears to be an important target for genotoxicants. Moreover, the inefficient removal of DNA lesions in granule cells could also explain why the cerebellum is specifically targeted by genotoxicants (Fonnum and Lock 2000; Jirakulsomchok et al. 1982; Mehl et al. 2000; Singh et al. 1983; Smith et al. 1987) and why cerebellar function is disturbed in both neuro-developmental and DNA repair disorders (Fiore et al. 2004; Wallace et al. 2003).

As noted above, DNA lesions appear to persist in immature neurons of genotoxicant-treated animals. This could explain why the developing cerebellum is a prime target in several human neurodevelopmental disorders (Ahsgren et al. 2005; Bauman and Kemper 2005; Guerrini and Filippi 2005; Hatten 2002). Because DNA lesions (e.g., alkyl or bulky) can influence gene transcription either up or down, depending on the sequence context (Scicchitano et al. 2004), it is conceivable that the DNA lesions formed by MAM or HN2 profoundly influenced the expression of developmentally regulated neuronal genes. Like previous microarray studies of the cerebellum (Kisby et al. 2005), we show that MAM targeted a large number of critically important genes that control the maturation and differentiation of neurons. However, little overlap occurred between the genes targeted by HN2 and MAM, indicating that the different types of DNA lesions (methyl vs. cross-links) produced by these genotoxicants could have been an important contributing factor. This notion is consistent with the distinct gene expression profiles produced in murine cells after treatment with various classes of genotoxicants. In one study, methylating agents (e.g., methyl methane sulfonate), cross-linking agents (e.g., mitomycin C), or agents that form bulky DNA lesions (e.g., benzo[a]pyrene) were compared and found to induce gene expression profiles quite distinct from each other and other non-genotoxicants (Newton et al. 2004). Hu and colleagues (2004) reached similar conclusions after examining the gene expression profiles of murine lymphoma cells lines treated for 4 hr and 20 hr with similar classes of genotoxicants. Like the present study, they used concentrations of genotoxicants that induced minimal toxicity (10–30%) so as to avoid the activation of cell death pathways. Therefore, our data indicate that the distinct gene expression changes induced by MAM or HN2 may be due to the influence of DNA lesions produced by these genotoxicants on transcription. Recent microarray studies support this hypothesis by showing that the decline in gene expression within the aging human brain is associated with a corresponding increase in DNA lesions (i.e., 8-oxodexoyguanosine) within the promoter region of key genes involved in learning, memory, and neuronal survival (i.e., synaptic plasticity) (Lu et al. 2004).

Studies on human neuronal migration disorders indicate that defects in migration as well as in proliferation, survival, and differentiation may contribute to neurodevelopmental disorders (Ross and Walsh 2001). The molecular and genetic basis of neuronal migration disorders suggests that the key steps depend on proper actin, microtubule cytoskeletal alterations as well as proper transduction of extra-cellular signals by migrating neurons. One key finding of the present studies is that the molecular pathways controlling neuronal migration and maturation were predominantly targeted by MAM but not by the related genotoxicant HN2. More specifically, MAM had a significant influence on several genes that control the development of neuronal processes (i.e., axons, dendrites) that would markedly impair neuronal growth cone motility and its pathfinding ability (Hatten 1999). The preferential targeting of neuronal differentiation by MAM is also consistent with the ability of this genotoxicant to disrupt unique molecular networks during either fetal (Hoffman et al. 1996) or postnatal (Kisby et al. 2005) neuronal development. The unexpected strong influence of MAM on several genes involved with chromatin remodeling or energy metabolism suggests that these cellular processes may play an important role in the ensuing neurodevelopmental deficits. Consequently, early-life exposure to genotoxicants would be expected to have a pronounced influence on neuronal development and thus, induce long-term changes in CNS function.

In summary, the present studies demonstrate that immature neurons are especially vulnerable to genotoxicants and that this vulnerability is associated with the accumulation of specific DNA lesions and distinct alterations in gene expression. The preferential targeting of genes involved in such diverse functions such as differentiation, stress and immune response, cell signaling, transcriptional regulation by MAM and apoptosis and protein synthesis by HN2 suggests that genotoxicants target distinct neuronal networks and they are likely to induce completely different effects on the developing brain. This is supported by the increased vulnerability of mature neurons to HN2 (Sullivan et al. 1982) but not to MAM (Sullivan-Jones et al. 1994). The preferential targeting of apoptotic networks by HN2 suggests that cross-links (formed between two opposing GMOH DNA lesions) are more likely to activate cell death mechanisms. Consequently, the targeting of specific molecular networks by different gentoxicants may explain the differential response of the developing CNS to different genotoxicants.

Figures and Tables Top

Figure 1.

Comparative sensitivity of neurons and astrocytes to MAM or HN2. Representative epifluorescence micrographs of cultures of cerebellar neurons (A) and astrocytes (B). Bars = 50 μm (A) and 100 μm (B). Cultures of murine cerebellar granule cells (C,E) and astrocytes (D,F) were treated with various concentrations of MAM (10–1,000 μM) or HN2 (0.1–20 μM) for 24 hr, incubated with calcein acetoxymethyl ester and the cells examined for fluorescence. Values represent the mean percent survival of controls ± SE (n = 6/treatment, 2–3 experiments).

Significantly different from control cells (*p < 0.01) or genotoxicant-treated astrocytes (**p < 0.01 by ANOVA).

Figure 2.

In situ DNA damage of cerebellar neurons treated with MAM or HN2. (A–C) Representative light micrographs of cerebellar neurons treated for 24 hr with various concentrations of MAM or HN2 and examined for the extent of DNA fragmentation by TUNEL labeling (A) or N 7-alkylguanine DNA lesions induced by 100 μM MAM (B) or 0.1–10 μM HN2 (C). Note the extensive labeling of neurons treated with 10μM HN2 or 1,000 μM MAM. Bar = 50 μm.

Significantly different from control-treated neurons (*p < 0.05 or **p < 0.01 by ANOVA).

Figure 3.

Effect of MAM and HN2 on global gene expression in cultured cerebellar neurons. Mouse cerebellar granule cell cultures were treated with MAM (100 μM) or HN2 (1.0 μM) for 24 hr. (A) Gene expression changes were induced by MAM or HN2. All genes with log₂ MAM/control or HN2/control gene expression ratios > 1 or < –1 were normalized by the absolute valued of the maximum fold change for the gene and grouped by hierarchical clustering using Euclidean distances. (n = 606 genes for MAM and 617 genes for HN2). (B) Venn diagram depicting the overlap between MAM- and HN2-responsive genes. Up-regulated (red): numbers represent all genes with significant differences between MAM or HN2 and control-treated neurons and log₂ (MAM or HN2/control) > 1. Down-regulated (green): significant differences between MAM or HN2 and control-treated neurons and log₂ (MAM or HN2/control) < –1. (C) Functional classes of the genes influenced by MAM. (D) Functional classes of the genes influenced by HN2. Named genes with functional annotations in the Unigene database (http://www.ncbi.nlm.nih.gov/UniGene) were categorized by broad functional class.

Figure 4.

Analysis of the promoter regions of gene sets from MAM and HN2 treated cerebellar neurons for enriched transcriptional regulatory elements (TRE). The 5’-flanking regions (2 kb) of genes that were differentially regulated (factor > 2.0) in cerebellar neurons by MAM (A) or HN2 (B) were analyzed by PAINT v3.0 to identify overrepresented transcription regulatory elements (TREs). The genes (rows) and motifs (columns) were individually clustered and a subset of those that were found in > 5% of all promoters were used to generate an interaction matrix. Differences in color intensity (i.e., red) indicate the relative frequency of each TRE among the gene sets.

Table 1.

Selected MAM-responsive genes in cerebellar neurons.

Table 2.

Selected HN2-responsive genes in cerebellar neurons.

Table 3.

Selected MAM- and HN2-responsive genes in mouse cerebellar neurons.

Supplemental Material Top

(420 KB) PDF.

References Top

1. Ahsgren I, Baldwin I, Goetzinger-Falk C, Erikson A, Flodmark O, Gillberg C 2005. Ataxia, autism, and the cerebellum: a clinical study of 32 individuals with congenital ataxia Dev Med Child Neurol 47:193–198. Find this article online
2. Alam ZI, Jenner A, Daniel SE, Lees AJ, Cairns N, Marsden CD, et al. 1997. Oxidative DNA damage in the Parkinsonian brain: an apparent selective increase in 8-hydroxyguanine levels in substantia nigra J Neurochem 69:1196–1203. Find this article online
3. Amin RP, Hamadeh HK, Bushel PR, Bennett L, Afshari CA, Paules RS 2002. Genomic interrogation of mechanism(s) underlying cellular responses to toxicants Toxicology 181–182:555–563. Find this article online
4. Balduini W, Cimino M, Lombardelli G, Abbracchio MP, Peruzzi G, Cecchini T, et al. 1986. Microencephalic rats as a model for cognitive disorders Clin Neuropharmacol 9:S8–S18. Find this article online
5. Baraban SC, Schwartzkroin PA 1996. Flurothyl seizure susceptibility in rats following prenatal methylazoxymethanol treatment Epilepsy Res 23:189–194. Find this article online
6. Bauman ML, Kemper TL 2005. Neuroanatomic observations of the brain in autism: a review and future directions Int J Dev Neurosci 23:183–187. Find this article online
7. Becker AJ, Wiestler OD, Blumcke I 2002. Functional genomics in experimental and human temporal lobe epilepsy: powerful new tools to identify molecular disease mechanisms of hippocampal damage Prog Brain Res 135:161–173. Find this article online
8. Benjamini Y, Hochberg Y 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing J R Stat Soc Ser B-Methodol 57:289–300. Find this article online
9. Branum AM, Collman GW, Correa A, Keim SA, Kessel W, Kimmel CA, et al. 2003. The National Children’s Study of environmental effects on child health and development Environ Health Perspect 111:642–646. Find this article online
10. Buecheler J, Kleihues P 1977. Excision of O⁶-methylguanine from DNA of various mouse tissues following a single injection of N-methylnitrosourea Chem Biol Interact 16:325–333. Find this article online
11. Cattabeni F, Di Luca M 1997. Developmental models of brain dysfunctions induced by targeted cellular ablations with methylazoxymethanol Physiol Rev 77:199–215. Find this article online
12. Cattaneo E, Reinach B, Caputi A, Cattabeni F, Di Luca M 1995. Selective in vitro blockade of neuroepithelial cell proliferation by methylazoxymethanol, a molecule capable of inducing long lasting functional impairments J Neurosci Res 41:640–647. Find this article online
13. Chevassus-Au-Louis N, Jorquera I, Ben-Ari Y, Represa A 1999. Abnormal connections in the malformed cortex of rats with prenatal treatment with methylazoxymethanol may support hyperexcitability Dev Neurosci 21:385–392. Find this article online
14. Children's Health Act 2000. Public Law 106-310
15. Colacitti C, Sancini G, DeBiasi S, Franceschetti S, Caputi A, Frassoni C, et al. 1999. Prenatal methylazoxymethanol treatment in rats produces brain abnormalities with morphological similarities to human developmental brain dysgeneses J Neuropathol Exp Neurol 58:92–106. Find this article online
16. Dabrowska MI, Becks LL, Lelli JL Jr, Levee MG, Hinshaw DB 1996. Sulfur mustard induces apoptosis and necrosis in endothelial cells Toxicol Appl Pharmacol 141:568–583. Find this article online
17. Dacre JC, Goldman M 1996. Toxicology and pharmacology of the chemical warfare agent sulfur mustard Pharmacol Rev 48:289–326. Find this article online
18. DeFeo MR, Mecarelli O, Ricci GF 1995. Seizure susceptibility in immature rats with microencephaly induced by prenatal exposure to methylazoxymethanol acetate Pharmacol Res 31:109–114. Find this article online
19. Deschner EE, Ruperto J, Wong G, Newmark HL 1991. Quercetin and rutin as inhibitors of azoxymethanol-induced colonic neoplasia Carcinogenesis 12:1193–1196. Find this article online
20. Deschner EE, Ruperto JF, Wong GY, Newmark HL 1993. The effect of dietary quercetin and rutin on AOM-induced acute colonic epithelial abnormalities in mice fed a high-fat diet Nutr Cancer 20:199–204. Find this article online
21. Deschner EE, Zedeck MS 1986. Lipid peroxidation in liver and colon of methylazoxymethanol treated rats Cancer Biochem Biophys 9:25–29. Find this article online
22. Eizirik DL, Kisby GE 1995. Cycad toxin-induced damage of rodent and human pancreatic β-islet cells Biochem Pharmacol 50:355–365. Find this article online
23. Eriksdotter-Nilsson M, Jonsson G, Dahl D, Björklund H 1986. Astroglial development in microencephalic rat brain after fetal methylazoxymethanol treatment Int J Dev Neurosci 4:353–362. Find this article online
24. Esclaire F, Kisby GE, Milne J, Lesort M, Spencer P, Hugon J 1999. The Guam cycad toxin methylazoxymethanol damages neuronal DNA and modulates tau mRNA expression and excitotoxicity Exp Neurol 155:11–21. Find this article online
25. Ferguson SA 1996. Neuroanatomical and functional alterations resulting from early postnatal cerebellar insults in rodents Pharmacol Biochem Behav 55:663–671. Find this article online
26. Ferguson SA, Holson RR 1997. Methylazoxymethanol-induced microencephaly in the brown Norway strain: behavior and brain weight Int J Dev Neurosci 15:75–86. Find this article online
27. Ferguson SA, Paule MG, Holson RR 1996. Functional effects of methylzoxymethanol-induced cerebellar hypoplasia in rats Neurotox Teratol 18:529–537. Find this article online
28. Fiore M, Grace AA, Korf J, Stampachiacchiere B, Aloe L 2004. Impaired brain development in the rat following prenatal exposure to methylazoxymethanol acetate at gestational day 17 and neurotrophin distribution Neuroreport 15:1791–1795. Find this article online
29. Flagstad P, Glenthoj BY, Didriksen M 2005. Cognitive deficits caused by late gestational disruption of neurogenesis in rats: a pre-clinical model of schizophrenia Neuropsychopharmacology 30:250–260. Find this article online
30. Fonnum F, Lock EA 2000. Cerebellum as a target for toxic substances Toxicol Lett 113:9–16. Find this article online
31. Frank D, Doenecke D, Albig W 2003. Differential expression of human replacement and cell cycle dependent H3 histone genes Gene 312:135–43. Find this article online
32. Fujimori K, Inoue K, Nakazawa K, Maekawa A, Shibutani M, Takanaka A 1992. Neurochemical and histological analysis of motor dysfunction observed in rats with methylnitrosourea-induced experimental cerebellar hypoplasia Neurochem Res 17:223–231. Find this article online
33. Gleeson JG 2001. Neuronal migration disorders Ment Retard Dev Disabil Res Rev 7:167–171. Find this article online
34. Graef I, Karnofsky DA, Jager VB, Krichesky B, Smith HW 1948. The clinical and pathologic effects of the nitrogen and sulfur mustards in laboratory animals Am J Pathol 24:1–47. Find this article online
35. Grenningloh G, Soehrman S, Bondallaz P, Ruchti E, Cadas H 2004. Role of the microtubule destabilizing proteins SCG10 and stathmin in neuronal growth J Neurobiol 58(1):60–69. Find this article online
36. Guerrini R, Filippi T 2005. Neuronal migration disorders, genetics, and epileptogenesis J Child Neurol 20:287–299. Find this article online
37. Hatten ME 1999. Central nervous system neuronal migration Annu Rev Neurosci 22:511–539. Find this article online
38. Hatten ME 2002. New directions in neuronal migration Science 297:1660–1663. Find this article online
39. Hoffman JR, Boyne LJ, Levitt P, Fischer I 1996. Short exposure of methylazoxymethanol causes a long-term inhibition of axonal outgrowth from cultured embryonic rat hippocampal neurons J Neurosci Res 46:349–359. Find this article online
40. Hu T, Gibson DP, Carr GJ, Torontali SM, Tiesman JP, Chaney JG, et al. 2004. Identification of a gene expression profile that discriminates indirect-acting genotoxins from direct-acting genotoxins Mutat Res 549:5–27. Find this article online
41. Hur GH, Kim YB, Choi DS, Kim JH, Shin S 1998. Apoptosis as a mechanism of 2-chloroethylethyl sulfide-induced cytotoxicity Chem Biol Interact 110:57–70. Find this article online
42. Ishigaki S, Niwa J, Ando Y, Yoshihara T, Sawada K, Doyu M, et al. 2002. Differentially expressed genes in sporadic amyotrophic lateral sclerosis spinal cords-screening by molecular indexing and subsequent cDNA microarray analysis FEBS Lett 531:354–358. Find this article online
43. Ishiguchi H, Izumi H, Torigoe T, Yoshida Y, Kubota H, Tsuji S, et al. 2004. ZNF143 activates gene expression in response to DNA damage and binds to cisplatin-modified DNA Int J Cancer 111:900–909. Find this article online
44. Jacobs KM, Kharazia VN, Prince DA 1999. Mechanisms underlying epileptogenesis in cortical malformations Epilepsy Res 36:165–188. Find this article online
45. Jirakulsomchok S, Chronister RB, Yielding KL 1982. Focal cerebellar dystrophy caused by transplacental administration of methylnitrosourea Brain Res Bull 8:45–52. Find this article online
46. Jones MZ, Gardner E 1976. Pathogenesis of methylazoxy-methanol-induced lesions in the postnatal mouse cerebellum J Neuropathol Exp Neurol 35:413–444. Find this article online
47. Kirby DM, Salemi R, Sugiana C, Ohtake A, Parry L, Bell KM, et al. 2004. NDUFS6 mutations are a novel cause of lethal neonatal mitochondrial complex I deficiency J Clin Invest 114:837–845. Find this article online
48. Kirmizis A, Bartley SM, Kuzmichev A, Margueron R, Reinberg D, Green R, et al. 2004. Silencing of human polycomb target genes is associated with methylation of histone H3 Lys 27 Genes Dev 18:1592–1605. Find this article online
49. Kisby GE, Kabel H, Hugon J, Spencer P 1999. Damage and repair of nerve cell DNA in toxic stress Drug Metab Rev 31:589–618. Find this article online
50. Kisby GE, Lesselroth H, Olivas A, Samson L, Gold B, Tanaka K, et al. 2004. Role of nucleotide- and base-excision repair in genotoxin-induced neuronal cell death DNA Repair 3:617–627. Find this article online
51. Kisby GE, Springer N, Spencer PS 2000. In vitro neurotoxic and DNA-damage properties of nitrogen mustard (HN2) J Appl Toxicol 20:S35–S41. Find this article online
52. Kisby GE, Standley M, Lu X, O’Malley J, Lin B, Muniz J, et al. 2005. Molecular networks perturbed in a developmental animal model of brain injury Neurobiol Dis 19:108–118. Find this article online
53. Kleihues P, Bucheler J 1977. Long-term persistence of O⁶-methyl-guanine in rat brain DNA Nature 269:625–626. Find this article online
54. Knecht K, Wiesmuller KH, Gnau V, Jung G, Meyermann R, Todd KG, et al. 2001. AMP deaminase in rat brain: localization in neurons and ependymal cells J Neurosci Res 66:941–950. Find this article online
55. Landrigan PJ, Kimmel CA, Correa A, Eskenazi B 2004. Children’s health and the environment: public health issues and challenges for risk assessment Environ Health Perspect 112:257–265. Find this article online
56. Loeffen J, van den Heuvel L, Smeets R, Triepels R, Sengers R, Trijbels F, et al. 1998. cDNA sequence and chromosomal localization of the remaining three human nuclear encoded iron sulphur protein (IP) subunits of complex I: the human IP fraction is completed Biochem Biophys Res Commun 247:751–758. Find this article online
57. Lu T, Pan Y, Kao SY, Li C, Kohane I, Chan J, et al. 2004. Gene regulation and DNA damage in the ageing human brain Nature 429(6994):883–91. Find this article online
58. Lyras L, Cairns NJ, Jenner A, Jenner P, Halliwell B 1997. An assessment of oxidative damage to proteins, lipids, and DNA in brain from patients with Alzheimer’s disease J Neurochem 68:2061–2069. Find this article online
59. Mahnke DK, Sabina RL 2005. Calcium activates erythrocyte AMP deaminase [isoform E (AMPD3)] through a protein-protein interaction between calmodulin and the N-terminal domain of the AMPD3 polypeptide Biochemistry 44:5551–5559. Find this article online
60. Mandel S, Grunblatt E, Maor G, Youdim MB 2002. Early and late gene changes in MPTP mice model of Parkinson’s disease employing cDNA microarray Neurochem Res 27:1231–1243. Find this article online
61. Matijasevic S, Boosalis M, Mackay W, Samson L, Ludlum D 1993. Protection against chloroethylnitrosourea cytotoxicity by eukaryotic 3-methyladenine DNA glycosylase Proc Natl Acad Sci USA 90:11855–11859. Find this article online
62. Matsumoto H, Higa HH 1966. Studies on methylazoxymethanol, the aglycone of cycasin: methylation of nucleic acids in vitro Biochem J 98:20C–22C. Find this article online
63. Matsumoto H, Spatz M, Laqueur GL 1972. Quantitative changes with age in the DNA content of methylazoxymethanol-induced microencephalic rat brain J Neurochem 19:297–306. Find this article online
64. McDonald TP, Asano M 1961. Effects of nitrogen mustard on the mouse brain Am J Pathol 38:695–709. Find this article online
65. McKittrick E, Gafken PR, Ahmad K, Henikoff S 2004. Histone H3.3 is enriched in covalent modifications associated with active chromatin Proc Natl Acad Sci USA 101:1525–1530. Find this article online
66. Mecocci P, Beal MF, Cecchetti R, Polidori MC, Cherubini A, Chionne F, Avellini L, Romano G, Senin U 1997. Mitochondrial membrane fluidity and oxidative damage to mitochondrial DNA in aged and AD human brain Mol Chem Neuropathol 31:53–64. Find this article online
67. Mecocci P, MacGarvey MS, Beal MF 1994. Oxidative damage to mitochondrial DNA is increased in Alzheimer’s Disease Ann Neurol 36:747–751. Find this article online
68. Mehl A, Rolseth V, Gordon S, Bjoraas M, Seeberg E, Fonnum F 2000. Brain hypoplasia caused by exposure to trichlorfon and dichlorvos during development can be ascribed to DNA alkylation damage and inhibition of DNA alkyltransferase repair Neurotoxicology 21:165–173. Find this article online
69. Meier HL, Millard CB 1998. Alterations in human lymphocyte DNA caused by sulfur mustard can be mitigated by selective inhibitors of poly(ADP-ribose) polymerase Biochim Biophys Acta 1404:367–376. Find this article online
70. Meira LB, Devaraj S, Kisby GE, Burns DK, Daniel RL, Hammer RE, et al. 2001. Heterozygosity for the mouse APEX gene results in phenotypes associated with oxidative stress Cancer Res 61:5552–5557. Find this article online
71. Mirnics K, Middleton FA, Marquez A, Lewis DA, Levitt P 2000. Molecular characterization of schizophrenia viewed by microarray analysis of gene expression in prefrontal cortex Neuron 28:53–67. Find this article online
72. Mody M, Cao Y, Cui Z, Tay KY, Shyong A, Shimizu E, et al. 2001. Genome-wide gene expression profiles of the developing mouse hippocampus Proc Natl Acad Sci USA 98:8862–8867. Find this article online
73. Motohashi H, Yamamoto M 2004. Nrf2-Keap1 defines a physiologically important stress response mechanism Trends Mol Med 10:549–557. Find this article online
74. Nagata Y, Matsumoto H 1969. Studies on methylazoxymethanol: Methylation of nucleic acids in the fetal rat brain Proc Soc Exp Biol Med 132:383–385. Find this article online
75. Naik MU, Benedikz E, Hernandez I, Libien J, Hrabe J, Valsamis M, et al. 2000. Distribution of protein kinase M zeta and the complete protein kinase C isoform family in rat brain J Comp Neurol 426(2):243–258. Find this article online
76. Necchi D, Scherini E, Bernocchi G 1997. Glial cell reaction to cis-dichlorodiammine platinum treatment in the immature rat cerebellum Exp Neurol 144:219–226. Find this article online
77. Neri M, Ugolini D, Bonassi S, Fucic A, Holland N, Knudsen LE, et al. 2006. Children’s exposure to environmental pollutants and biomarkers of genetic damage II. Results of a comprehensive literature search and meta-analysis Mutat Res 612:14–39. Find this article online
78. Newton RK, Aardema M, Aubrecht J 2004. The utility of DNA microarrays for characterizing genotoxicity Environ Health Perspect 112:420–422. Find this article online
79. Nishioka N, Arnold SE 2004. Evidence for oxidative DNA damage in the hippocampus of elderly patients with chronic schizophrenia Am J Geriatr Psychiatry 12:167–175. Find this article online
80. Osborne MR, Wilman DEV, Lawley PD 1995. Alkylation of DNA by the nitrogen mustard bis(2-chloroethyl) methylamine Chem Res Toxicol 8:316–320. Find this article online
81. Pasinetti GM 2001. Use of cDNA microarray in the search for molecular markers involved in the onset of Alzheimer’s disease dementia J Neurosci Res 65:471–476. Find this article online
82. Pearson AG, Curtis MA, Waldvogel HJ, Faull RL, Dragunow M 2005. Activating transcription factor 2 expression in the adult human brain: association with both neurodegeneration and neurogenesis Neuroscience 133:437–451. Find this article online
83. Poguet AL, Legrand C, Feng X, Yen PM, Meltzer P, Samarut J, et al. 2003. Microarray analysis of knockout mice identifies cyclin D2 as a possible mediator for the action of thyroid hormone during the postnatal development of the cerebellum Dev Biol 254:188–199. Find this article online
84. Povirk LF, Shuker DE 1994. DNA damage and mutagenesis induced by nitrogen mustards Mutat Res 318:205–226. Find this article online
85. Ramanan N, Shen Y, Sarsfield S, Lemberger T, Schutz G, Linden DJ, et al. 2005. SRF mediates activity-induced gene expression and synaptic plasticity but not neuronal viability Nat Neurosci 8:759–767. Find this article online
86. Rinaldi T, Pick E, Gambadoro A, Zilli S, Maytal-Kivity V, Frontali L, et al. 2004. Participation of the proteasomal lid subunit Rpn11 in mitochondrial morphology and function is mapped to a distinct C-terminal domain Biochem J 381:275–285. Find this article online
87. Ronquist G, Rudolphi O, Engstrom I, Waldenstrom A 2001. Familial phosphofructokinase deficiency is associated with a disturbed calcium homeostasis in erythrocytes J Intern Med 249:85–95. Find this article online
88. Ross ME, Walsh CA 2001. Human brain malformations and their lessons for neuronal migration Annu Rev Neurosci 24:1041–1070. Find this article online
89. Scicchitano DA, Mellon I 1997. Transcription and DNA damage: a link to a kink Environ Health Perspect 105(suppl 1):145–153. Find this article online
90. Scicchitano DA, Olesnicky EC, Dimitri A 2004. Transcription and DNA adducts: what happens when the message gets cut off? DNA Repair 3:1537–1548. Find this article online
91. Shiraki H, Yase Y 1975. Amyotrophic lateral sclerosis in Japan. In: Handbook of Clinical Neurology (Vinken PJ, Bruyn GW, eds). Vol 22. System Disorders and Atrophy, Part 2. New York: American Elsevier, 353–419
92. Singh S, Datta AN, Singh G 1983. Retarded recovery of Purkinje cells in rats following cyclophosphamide treatment in early postnatal period Indian J Exp Biol 21:539–545. Find this article online
93. Slagsvold HH, Rosseland CM, Jacobs C, Khuong E, Kristoffersen N, Gaarder M, et al. 2003. High molecular weight DNA fragments are processed by caspase sensitive or caspase independent pathways in cultures of cerebellar granule neurons Brain Res 984:111–121. Find this article online
94. Smith SB, Brown CB, Wright ME, Yielding KL 1987. Late-onset cerebellar degeneration in mice induced transplacentally by methylnitrosourea Teratog Carcinog Mutagen 7:449–463. Find this article online
95. Somani SM, Babu SR 1989. Toxicodynamics of sulfur mustard Int J Clin Pharmacol Ther Toxicol 27:419–435. Find this article online
96. Spencer PS, Daniels JL, Kisby GE 1999. Mustard Warfare Agents and Related Substances, in Experimental and Chemical Neurotoxicology, 2nd ed (Spencer PS, Schaumburg HH, eds). New York:Oxford University Press
97. Spencer PS, Kisby GE, Ludolph AC 1991. Slow toxins, biologic markers, and long-latency neurodegenerative disease in the western Pacific region Neurology 41:62–66. Find this article online
98. Sullivan KM, Storb R, Shulman HM, Shaw CM, Spence A, Beckham C, et al. 1982. Immediate and delayed neurotoxicity after mechlorethamine preparation for bone marrow transplantation Ann Int Med 97:182–189. Find this article online
99. Sullivan-Jones P, Gouch AB, Holson RR 1994. Postnatal methyl-azoxymethanol: sensitive periods and regional selectivity of effects Neurotoxicol Teratol 16:631–637. Find this article online
100. Sun J, Wang YX, Sun MJ 1999. Apoptosis and necrosis induced by sulfur mustard in Hela cells Acta Pharmacol Sin 20:445–448. Find this article online
101. Talamini LM, Koch T, Luiten PG, Koolhaas JM, Korf J 1999. Interruptions of early cortical development affect limbic association areas and social behaviour in rats; possible relevance for neurodevelopmental disorders Brain Res 847:105–120. Find this article online
102. Talamini LM, Koch T, Ter Horst GJ, Korf J 1998. Methylazoxy-methanol acetate-induced abnormalities in the entorhinal cortex of the rat; parallels with morphological findings in schizophrenia Brain Res 789:293–306. Find this article online
103. Tokuda K, Bodell WJ 1987. Cytotoxicity and sister chromatid exchanges in 9L cells treated with monofunctional and bifunctional nitrogen mustards Carcinogenesis 8:1697–1701. Find this article online
104. Tomoda T, Kim JH, Zhan C, Hatten ME 2004. Role of Unc51.1 and its binding partners in CNS axon outgrowth Genes Dev 18:541–558. Find this article online
105. Vadigepalli R, Chakravarthula P, Zak DE, Schwaber JS, Gonye GE 2003. PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification OMICS 7:235–252. Find this article online
106. Vorhees CV, Fernandez K, Dumas RM, Haddad RK 1984. Pervasive hyperactivity and long-term learning impairments in rats with induced microencephaly from prenatal exposure to methyla-zoxymethanol Dev Brain Res 15:1–10. Find this article online
107. Wallace CS, Reitzenstein J, Withers GS 2003. Diminished experience-dependent neuroanatomical plasticity: evidence for an improved biomarker of subtle neurotoxic damage to the developing rat brain Environ Health Perspect 111:1294–1298. Find this article online
108. Wick A, Wick W, Hirrlinger J, Gerhardt E, Dringen R, Dichgans J, et al. 2004. Chemotherapy-induced cell death in primary cerebellar granule neurons but not in astrocytes: in vitro paradigm of differential neurotoxicity J Neurochem 91:1067–1074. Find this article online
109. Wijen JP, Nivard MJ, Vogel EW 2000. The in vivo genetic activity profile of the monofunctional nitrogen mustard 2-chloroethylamine differs drastically from its bifunctional counterpart mechlorethamine Carcinogenesis 21:1859–1867. Find this article online
110. Witke W 2004. The role of profilin complexes in cell motility and other cellular processes Trends Cell Biol 14:461–469. Find this article online
111. Yamasaki T, Kawaji K, Ono K, Bito H, Hirano T, Osumi N, et al. 2001. Pax6 regulates granule cell polarization during parallel fiber formation in the developing cerebellum Development 128:3133–3144. Find this article online
112. Yarmola EG, Bubb MR 2006. Profilin: emerging concepts and lingering misconceptions Trends Biochem Sci 31(4):197–205. Find this article online
113. Zhang ZX, Anderson DW, Mantel N, Román GC 1996. Motor neuron disease on Guam: geographic and familial occurrence, 1956–85 Acta Neurol Scand 94:51–59. Find this article online