Lamin B1 controls oxidative stress responses via Oct-1

The nuclear lamina underlies the inner nuclear membrane and is therefore an integral part of the nuclear envelope. The major components of the lamina are nuclear lamins, intermediate filament proteins encoded by three genes in humans, LMNA, LMNB1, and LMNB2. The LMNA gene encodes A-type lamins, whereas the B-type lamins, lamin B1 and lamins B2 and B3, are encoded by the LMNB1 and LMNB2 genes, respectively. A-type lamins are developmentally regulated and are expressed in differentiated cells, whereas at least one B-type lamin is expressed in all vertebrate cells (for review see Goldman et al., 2002). The nuclear lamina provides structural support and is involved in anchoring chromatin to the nuclear envelope in DNA replication and repair and in the control of gene expression (Worman and Courvalin, 2005; Tang et al., 2008). It is through these mechanisms that nuclear shape, and thus the nuclear lamina, is associated with the normal aging process as well as with premature aging disorders (Haithcock et al., 2005; Lans and Hoeijmakers, 2006; Scaffidi and Misteli, 2006).

We and others have previously reported that chromatin interactions with the nuclear envelope play important roles in the control of gene expression (Hewitt et al., 2004; Zink et al., 2004; Chuang et al., 2006; Malhas et al., 2007; Guelen et al., 2008). An alternative mechanism by which the nuclear envelope can regulate gene expression is by associating with specific transcription factors (Heessen and Fornerod, 2007), such as AP-1, sterol regulatory element-binding protein, MOK2, and the octamer transcription factor 1 (Oct-1), and modulating their activities (Imai et al., 1997; Dreuillet et al., 2002, 2008; Lloyd et al., 2002; Capanni et al., 2005; Ivorra et al., 2006). Oct-1 is a ubiquitous transcription factor known to have both activating and silencing activities. Two lines of evidence suggest a role for the nuclear lamina in associating with and regulating the activity of Oct-1. First, Oct-1 has been shown to be present in an insoluble nuclear fraction (Kim et al., 1996), suggesting that it may be associated with the nuclear lamina. Second, Imai et al. (1997) have shown that the dissociation of Oct-1 from the nuclear periphery is accompanied by the up-regulation of the interstitial collagenase gene and is associated with cellular aging.

More recently, Tantin et al. (2005) have shown that Oct-1 regulates genes that are essential for the cellular response to stress and that Oct-1–deficient mouse fibroblasts harbored elevated levels of reactive oxygen species (ROS) and were more susceptible to oxidative stress. Given the link between aging and ROS (for review see Finkel and Holbrook, 2000) and that alterations to the nuclear envelope occur during aging, we hypothesized that the nuclear lamina and Oct-1 might have a cooperative role in controlling the expression of genes that are associated with aging and response to oxidative stress. To examine this hypothesis, we first confirmed that lamin B1 is associated with Oct-1 in normal mouse fibroblasts but not in cells lacking normal, full-length lamin B1 (Lmnb1^Δ/Δ cells). We also found that, like Oct-1–deficient fibroblasts, Lmnb1^Δ/Δ cells have elevated ROS levels and that they are more susceptible to oxidative stress than normal mouse fibroblasts as a result of the same gene expression abnormalities. We demonstrate that the release of Oct-1 in the Lmnb1^Δ/Δ cells results in increased occupancy of its binding sites in target genes that are dysregulated in Oct-1– and lamin B1–deficient cells. Collectively, our results provide evidence that lamin B1 at the nuclear lamina directly sequesters Oct-1 and as a result can regulate the expression of genes involved in various processes, including aging and response to oxidative stress.

Western blotting detection of Oct-1 confirmed the presence of two isoforms of the protein at comparable levels in wild-type (WT) mouse embryonic fibroblasts and Lmnb1^Δ/Δ cells that lack the C-terminal 273 amino acids of lamin B1 (Vergnes et al., 2004). Using a previously described nuclear envelope subfractionation protocol involving differential extraction (Maske et al., 2003), we found that in WT cells, Oct-1 is detected in all fractions of increasing extraction stringency, including the 4-M urea fraction. However, in Lmnb1^Δ/Δ cells, more Oct-1 is released in the earlier fractions, and no Oct-1 is detected in the 4 M urea fraction (Fig. 1 A). This profile of extraction is consistent with tight association with the nuclear lamina because in WT cells, this pool contains >40% of the full-length lamin B1 in the nucleus (Maske et al., 2003). Immunoprecipitating lysates from WT cells with an anti–lamin B1 antibody resulted in coimmunoprecipitating Oct-1 (Fig. 1 B). Oct-1 was not coimmunoprecipitated with lamin B1 in lysates of Oct1^−/− cells despite the successful precipitation of lamin B1. The anti–lamin B1 antibody used in immunoprecipitation (IP) was directed toward the C terminus, which is lacking in the Lmnb1^Δ/Δ cells, and therefore, the IP samples of these cell lysates contained neither lamin B1 nor Oct-1 (Fig. 1 B). This provides evidence of a direct interaction between lamin B1 and Oct-1. This was also confirmed by expressing fluorescently tagged Oct-1 in WT and Lmnb1^Δ/Δ cells. Oct-1 is observed at the nuclear periphery in WT cells but not in the Lmnb1^Δ/Δ cells (Fig. 1 C and Fig. S1, available). Fluorescence loss in photobleaching (FLIP) reveals that Oct-1–EGFP shows very slow turnover when expressed in WT cells, with only 8% being exchanged within 100 s (Fig. 1 D). The turnover is faster in Lmnb1^Δ/Δ cells, in which 43% of Oct-1–EGFP is being exchanged within the same time frame. This experiment shows that the stability of Oct-1 association is tighter in the presence of full-length lamin B1 than in the absence of the latter's C terminus.

To test whether the FLIP results are caused by a tight association between Oct-1 and lamin B1, we performed fluorescence resonance energy transfer (FRET) confocal microscopy using the acceptor photobleach method. In brief, the method involves photobleaching an acceptor fluorophore (e.g., Cy3) and looking for an increase in the fluorescence signal detected for the donor (e.g., EGFP). An increase in the donor fluorescence expressed as the FRET efficiency (see Materials and methods) indicates that the two proteins are indeed within 1–10 nm of each other and thus likely interact directly. In this case, the donor was Oct-1–EGFP, and the acceptor was lamin B1 or lamin A/C detected with Cy3-conjugated secondary antibodies. The Förster radius (at which FRET efficiency is half-maximal) is 6.0 nm for the GFP-Cy3 FRET pair (Wouters and Bastiaens, 1999). Using this approach, we found that the fluorescence of Oct-1–EGFP increases after the bleaching of Cy3 used for lamin B1 detection (FRET efficiency of 4.6%; n = 20; Fig. 1 E). However, in the negative control, photobleaching of Cy3 used for lamin A/C detection does not result in an increase in Oct-1–EGFP fluorescence (P < 0.001; Fig. 1 E), confirming the absence of an Oct-1–lamin A FRET signal.

Next, we wanted to investigate whether the Oct-1–lamin B1 association and its loss in Lmnb1^Δ/Δ cells has any functional consequences. Electrophoretic mobility shift assay (EMSA) with a fluorescently labeled Oct-1 consensus oligonucleotide (FAM–Oct-1) was performed using equal amounts of nuclear extracts from WT, Lmnb1^Δ/Δ, and Oct1^−/− cells (Fig. 2). A band shift is observed with the WT and Lmnb1^Δ/Δ but not with the Oct1^−/− nuclear extracts. Furthermore, the intensity of the band obtained with Lmnb1^Δ/Δ extracts is more than that with the WT extracts, suggesting that Oct-1, which has lost its association with the nuclear lamina in Lmnb1^Δ/Δ cells, is now available for binding to its DNA target sequences.

Although the aforementioned experiments show that Oct-1 released from the nuclear lamina in the absence of full-length lamin B1 is now available to bind to its target sequences, they do not prove that this has any consequence in terms of gene expression of Oct-1 targets. To establish this, we first wanted to identify Oct-1 targets that are dysregulated in the Lmnb1^Δ/Δ cells (i.e., genes that are dependent on both lamin B1 and Oct-1 for their normal expression). We compared the gene expression patterns of Lmnb1^Δ/Δ with WT cells using six biological replicates of each and six hybridizations performed with dye swaps. We had previously identified 790 dysregulated genes (P < 0.05 using CyberT) in the absence of normal full-length lamin B1 (ArrayExpress accession no. E-MEXP-538). CyberT is a web-based implementation of a Bayesian probabilistic framework for the analysis of microarray data designed for the analysis of data with high measurement noise and variability and typically low replicate numbers (Baldi and Long, 2001). This Bayesian approach has been shown to be more appropriate for the analysis of microarray data than the significance analysis of microarray (Tusher et. al., 2001) program and the Student's t test when n is small (Choe et al., 2005), although this difference is reduced when n > 5 as in our experiments (Baldi and Long, 2001).

We compared the gene expression changes in the Lmnb1^Δ/Δ cells with those previously reported in Oct1^−/− cells (Gene Expression Omnibus [GEO] accession no. GDS1446; Tantin et al., 2005). We found that 1,937 genes are unchanged in both cell types and are therefore independent of Oct-1 or lamin B1 (Fig. 3, blue region). 54 genes were dysregulated in Oct1^−/− but not in Lmnb1^Δ/Δ cells and are thus dependent on Oct-1 but not lamin B1 for their expression (Fig. 3, yellow regions), whereas 1,030 genes were dysregulated in Lmnb1^Δ/Δ and not Oct1^−/− cells, implying that their expression is dependent on lamin B1 but not Oct-1 (Fig. 3, orange regions). The 57 genes in the white quadrants (Fig. 3) represent those that are dysregulated in both cell types and are therefore dependent on both Oct-1 and lamin B1 for their expression (Table S2, available). To assess the significance of finding this number of genes altered in both experimental conditions, the bootstrapping method was used with 500,000 samples (see Materials and methods). This method shows that the probability of a chance observation of 57 genes that are changed in both experiments is <0.00012 (Fig. S3).

We selected some of the genes identified as Oct-1 targets using the aforementioned gene expression analysis to test whether they have functional Oct-1–binding sites. Putative Oct-1–binding sites within the promoter regions of the genes were selected using an online version of a hidden Markov profile comparison tool (multigenome analysis of positions and patterns of elements of regulation [MAPPER]; http://bio.chip.org/mapper; Fig. S4, available; Marinescu et al., 2005). EMSA using FAM-labeled oligonucleotide duplexes with the predicted Oct-1–binding sequences of Rdm1, Gpx3, Mgst1, and Mmp13 confirms that the sequences can specifically bind Oct-1 because the intensities of the shifted bands are reduced by the inclusion of a nonlabeled oligonucleotide with the Oct-1 consensus sequence in the assay (Fig. 4 A). Increased intensities of the shifted bands are also observed in the Lmnb1^Δ/Δ cell extract assays compared with the WT cell extracts, further confirming that there is an elevated amount of free Oct-1 in the Lmnb1^Δ/Δ cells that can bind to its target sequences in the promoter regions of the tested genes (Fig. 4 B and Fig. S2).

To confirm that this is occurring in the Lmnb1^Δ/Δ cells, we performed ChIP using anti–Oct-1 on WT and Lmnb1^Δ/Δ cells and determined the relative enrichment of Oct-1 occupancy of potential targets using quantitative real-time PCR (qRT-PCR). We selected seven genes for ChIP analysis, including genes previously shown to be regulated by Oct-1 gonadotropin-releasing hormone receptor (Gnrhr) and genes identified in this study as both Oct-1 and lamin B1 dependent. Increases in Oct-1 occupancy of the predicted binding sites of Csnb, Mmp13, Rdm1, Gpx3, Mgst1, and Serping1 were detected in the Lmnb1^Δ/Δ cells relative to the WT cells, whereas no relative increase in occupancy was detected for β-actin, which does not have an Oct-1–binding site (Fig. 5 A). Interestingly, the Oct-1 site in the Gnrhr promoter previously identified using a mobility shift assay showed no change in Oct-1 occupancy Gnrhr 1. To understand this unexpected discrepancy, we examined the Gnrhr promoter region using MAPPER and found additional predicted Oct-1–binding sites with much higher scores (Fig. 5 B). When we repeated the ChIP/qRT-PCR experiment using primer pairs selective for the highest scoring Oct-1 site, we found a significant change in occupancy (Fig. 5, compare Gnrhr 1 with Gnrhr 2).

Some of the genes that are dysregulated in Oct-1 and Lmnb1^Δ/Δ cells are involved in cellular responses to oxidative stress, as shown in Table I. The Oct-1–deficient cells have already been shown to harbor elevated ROS levels and be more susceptible to oxidative stress (Tantin et al., 2005). Cell survival assays in the presence of H₂O₂ showed that the Lmnb1^Δ/Δ cells are also more susceptible to oxidative stress (Fig. 6 A). Using the cell-permeable probe 2′,7′-dichlorodihydrofluorescein diacetate (H₂DCFDA) for ROS level detection (Sanchez Ferrer et al., 1990), the Oct1^−/− and Lmnb1^Δ/Δ cells were found to have significantly elevated levels of ROS compared with the WT cells (Fig. 6, B and C). To demonstrate that this change was directly dependent on lamin B1 function, we reduced its expression acutely in WT cells using Lmnb1 siRNA (Fig. 6, B and C). Cells in which lamin B1 levels were reduced showed increased ROS levels (Fig. 6 C). This effect is not a consequence of siRNA transfection per se because a control siRNA had no effect on ROS levels (Fig. 6 D). As a further control, we repeated ROS measurements in Lmnb1^Δ/Δ cells after restoration of lamin B1 expression (by transfecting cells to express full-length lamin B1) and showed that ROS levels were decreased to WT levels in those transgenic fibroblasts that were expressing lamin B1 (Fig. 6 E).

ROS levels were also reduced to near WT levels in Lmnb1^Δ/Δ cells, whereas Oct-1 levels were reduced using Oct1 siRNA (Fig. 6 C). Furthermore, reduction of Oct-1 levels in Lmnb1^Δ/Δ cells reduced their susceptibility to oxidative stress, whereas overexpression of Oct-1 in WT cells increased their susceptibility in comparison with cells that are transfected with a control siRNA or a control EGFP construct (H2B-EGFP), respectively (Fig. 7 A). These experiments indicate that the elevated ROS levels and susceptibility to oxidative stress in the Lmnb1^Δ/Δ cells is indeed mediated by Oct-1.

Further support for a direct effect of Oct-1 comes from experiments in which Oct-1 levels in Lmnb1^Δ/Δ cells are reduced by siRNA. Fig. 7 B (white bars) shows the effect of Oct1 siRNA on the expression of three genes that are involved in the response to oxidative stress. Two of the genes (Gpx3 and Rdm1) are normally repressed by Oct-1 (and therefore are down-regulated in the Lmnb1^Δ/Δ cells); this down-regulation is reversed when Oct-1 is lowered by siRNA (i.e., control siRNA–normalized fold change greater than one). Similarly, a gene that is activated by Oct-1 and thus up-regulated in Lmnb1^Δ/Δ cells (Mmp13) shows a reversal of this effect when Oct-1 is reduced by siRNA (i.e., control siRNA–normalized fold change less than one). Final confirmation that this is a direct effect of Oct-1 comes from the converse experiment in which Oct-1 is independently overexpressed in WT cells (Fig. 7 B, gray bars). In this case, the genes normally repressed by Oct-1 (Gpx3 and Rdm1) are down-regulated by Oct-1 overexpression, whereas the gene normally activated by Oct-1 shows increased expression.

Given that not all of the gene expression changes observed in the absence of full-length lamin B1 could be explained by altered chromatin–lamina interactions (Malhas et al., 2007), we sought additional mechanisms. In particular, it has previously been reported that Oct-1 colocalizes with lamin B and that the dissociation of Oct-1 from the nuclear periphery results in the up-regulation of the collagenase gene (Imai et al., 1997). Therefore, we considered the possibility that some of the gene expression changes observed in the Lmnb1^Δ/Δ cells might be a result of the dissociation of Oct-1 from the nuclear lamina in the absence of full-length lamin B1.

We first showed that Oct-1 associates with lamin B1, that the loss of this interaction leads to elevated Oct-1 levels in the nucleoplasm, and that the released Oct-1 can bind to its consensus target sequences. We then wanted to investigate whether this increased binding can have a functional effect and therefore sought to identify the genes that are dysregulated in the Lmnb1^Δ/Δ cells as a result of the altered Oct-1 distribution. To test this, we made use of existing data on gene expression in murine Oct-1 knockout cells (Tantin et al., 2005). We found that 1,030 genes are either unchanged or moderately dysregulated in the absence of Oct-1 but are significantly dysregulated in the absence of full-length lamin B1, indicating a dependence on lamin B1 but not Oct-1. This group includes most of the small number of genes we identified as dependent on processed lamin B1 (Malhas et al., 2007) but must also include many genes whose lamin B1 dependence cannot be accounted for by either lamin B1–chromatin interactions or lamin B1–Oct-1 interactions. Efforts are continuing to identify the mechanism by which lack of a stable B-type lamina affects expression of these genes. Only 54 genes are dependent on Oct-1 and not lamin B1 for their normal expression. We surmise that these represent genes with a stringent requirement for low levels of Oct-1 and that in both WT and Lmnb1^Δ/Δ cells, the Oct-1 level exceeds this permissive requirement. We identified 57 genes that are dependent on both lamin B1 and Oct-1 for their normal expression. Several of these genes have been found to be involved in the response to oxidative stress (Tantin et al., 2005). 15 of these genes are also dysregulated in the Lmnb1^Δ/Δ cells (Table I). If the hypothesis that Oct-1 is released from sequestration in Lmnb1^Δ/Δ cells is correct, we would expect Oct-1–dependent genes to show expression changes in opposite directions in Oct1^−/− and Lmnb1^Δ/Δ cells. This is true for 13 of the 15 genes involved in oxidative stress responses. At first glance, one might expect the resulting phenotypes to be opposite (i.e., if there is increased vulnerability to oxidative stress in Oct1^−/− cells, there would be reduced vulnerability in Lmnb1^Δ/Δ cells). However, it is important to note that for six of these genes there is already published evidence that either increased or decreased expression increases vulnerability to oxidative stress (Table I). It is worth noting that the increased Oct-1 occupancy, target gene dysregulation, and the resulting phenotype are caused by Oct-1 release and not its overexpression because the expression of the Oct1 gene itself is unchanged in the Lmnb1^Δ/Δ cells compared with the WTs (both at transcript level and protein level; Fig. 1 A).

Oct-1 is known to have repressive as well as activating effects on gene expression. Oxidative stress response genes that are dysregulated in the Oct1^−/− cells are mostly down-regulated in the Lmnb1 ^Δ/Δ cells (Table I), suggesting that in the WT cells, Oct-1 is sequestered by lamin B1, and thus the oxidative stress response genes that have octamer sequences are expressed at normal levels. In the Lmnb1 ^Δ/Δ cells, where there are higher levels of nucleoplasmic Oct-1 as a result of the loss of the sequestration by lamin B1, Oct-1 moves away from the periphery, binds to the octamer sequences, and down-regulates the target genes involved in response to oxidative stress, which we detect using EMSA, ChIP, and microarray, respectively. As a result, the Lmnb1 ^Δ/Δ cells harbor high levels of ROS and are more susceptible to oxidative stress. Other examples of genes that are repressed by Oct-1 are the Gnrhr gene (Cheng et al., 2002) and the vascular cell adhesion molecule 1 (Vcam1; dela Paz et al., 2007), which are also down-regulated in the Lmnb1 ^Δ/Δ cells (fold ratios of 0.3 and 0.7, respectively).

The Gnrhr gene offers a further interesting insight. An Oct-1–binding site has previously been identified and confirmed using an in vitro mobility shift assay (Cheng et al., 2002), but our ChIP/qRT-PCR analysis failed to detect a change in occupancy at this site in Lmnb1 ^Δ/Δ cells, whereas all other sites tested showed an increase in Oct-1 occupancy. However, this site is very weakly predicted as an Oct-1–binding site by the MAPPER algorithm, and much stronger Oct-1 sites are predicted elsewhere in the promoter region of Gnrhr (Fig. 5 C). When we repeated ChIP and qRT-PCR using primers designed to detect these additional predicted Oct-1 sites, we found a significant increase in Oct-1 occupancy in Lmnb1 ^Δ/Δ cells. We conclude that the relatively modest increase in nucleoplasmic Oct-1 protein levels between WT and Lmnb1^Δ/Δ cells has enabled us to detect subtle differences in the behavior of different Oct-1–binding sites in the same promoter. Fig. 5 B shows site occupancy changes ranging from 1.22 in Csnb to 2.85 in Gpx3, indicating that different Oct-1 sites respond differently to the same increase in Oct-1 level. Because the elevated binding is observed in the EMSA on short duplexes, they cannot depend on the sequence context and steric effects of transcription factor binding to adjacent sites. Moreover, because these differences are still detected by ChIP, they are not abrogated by transcription factor binding in a wider sequence context in intact nuclei.

Oct-1 is also known to function as an activator of expression of some targets, such as the U6 small nuclear RNA and osteopontin (Opn or Spp1; Botquin et al., 1998; Remenyi et al., 2002), which are both up-regulated in the Lmnb1^Δ/Δ cells (fold ratios of 1.7 and 10, respectively). Again, this can be explained by the loss of Oct-1 sequestration and an increase in nucleoplasmic Oct-1, which is now available to promote the transcription of such genes. Imai et al. (1997) observed that an up-regulation of the human interstitial collagenase gene accompanied the loss of Oct-1 from the nuclear periphery during cellular aging. We also observe an up-regulation in the mouse interstitial collagenase gene Mmp13 and an elevated level of Oct-1 occupancy of the Oct-1–binding sequence in its promoter region.

Elevated levels of ROS result in modifications to proteins, lipids, and DNA that are associated with aging (for review see Finkel and Holbrook, 2000), a process that is also linked to defects in nuclear envelope components. Alterations to the nuclear architecture are observed during the normal aging process (Wilson, 2005; Scaffidi and Misteli, 2006), and an extended lifespan in Caenorhabditis elegans has been associated with increased nuclear envelope integrity (Haithcock et al., 2005). Furthermore, mutations in genes coding for nuclear structural components such as lamin A are associated with several diseases, including the premature aging disorder Hutchinson-Gilford progeria syndrome (Eriksson et al., 2003). Several of the abnormalities resulting from nuclear structure defects in both an animal model and cells in culture can be reversed by treatment with farnesyltransferase inhibitors that act by normalizing the nuclear architecture (Glynn and Glover, 2005; Toth et al., 2005; Yang et al., 2006). Thus, there is mounting evidence that nuclear architecture and aging are interrelated and that compromised nuclear architecture might play a central role in the aging process (Haithcock et al., 2005; Wilson, 2005), although the exact mechanisms have yet to be unraveled. The findings we present in this study advance our understanding of this mechanism by demonstrating that disrupting the interactions between lamin B1 and Oct-1 result in the overall down-regulation of oxidative stress response genes and elevated ROS levels, both of which are hallmarks of the normal aging process.

Lamin B1 WT and Lmnb1^Δ/Δ cells were obtained from S. Young (University of California Los Angeles, Los Angeles, CA) and M. Bergö (Sahlgrenska Center for Cardiovascular and Metabolic Research, Göteborg, Sweden), whereas Oct1^−/− cells were provided by D. Tantin (University of Utah, Salt Lake City, UT). All mouse embryonic fibroblasts were cultured in DME supplemented with 10% FCS, l-glutamine, and nonessential amino acids. For cell survival assays, cells were seeded 24 h before treatment with 200 μM or 2 mM H₂O₂ for 24 h. Viable cells were quantified using the CellTiter-Blue cell viability assay (Promega) or manually using a Neubauer hemocytometer (Thermo Fisher Scientific). DNA transfections were performed using Lipofectamine 2000 (Invitrogen), whereas siRNA transfections were performed using transfection reagent (HiPerFect; QIAGEN). All experiments were performed 48 h after transfection. Oct1, Lmnb1, and control siRNA were purchased from Applied Biosystems. Full-length GFP-tagged lamin B1 used in this study has been described previously (Maske et al., 2003). The Oct-1–EGFP construct was provided by S. Murphy (University of Oxford, Oxford, England, UK). Differential nuclear extraction was adapted from the method described previously by Otto et al. (2001). In brief, purified nuclei were resuspended in nuclear isolation buffer (10 mM Hepes, pH 7.4, 2 mM MgCl₂, 25 mM KCl, 250 mM sucrose, 1 mM DTT, and a protease inhibitor cocktail; Sigma-Aldrich) and sonicated for two 5-s bursts at a 10-μm amplitude. Insoluble material was pelleted at 20,000 g for 5 min, resuspended in nuclear extraction buffer (20 mM Hepes, pH 7.4, 1 M NaCl, and protease inhibitor cocktail), and incubated at room temperature with agitation for 20 min. The extraction was repeated using nuclear extraction buffer with 2% Triton X-100 and 4 and 8 M urea in sequential extractions.

Cells were lysed using radio IP assay lysis buffer in the presence of complete protease inhibitor cocktail (Roche). Lysates were precleared twice using protein G PLUS-Agarose (Santa Cruz Biotechnology, Inc.) and immunoprecipitated overnight at 4°C using goat anti–lamin B1 (Santa Cruz Biotechnology, Inc.). IP complexes were captured using protein G PLUS-Agarose, eluted using Laemmli loading buffer, and analyzed by Western blotting using anti–lamin B1 (Santa Cruz Biotechnology, Inc.), anti–Oct-1 (Santa Cruz Biotechnology, Inc.), or donkey anti–goat HRP conjugate (Jackson ImmunoResearch Laboratories).

RNA isolation, gene expression analyses, and validation have been described previously (Malhas et al., 2007). Full details of the slide layout, culture conditions, detailed protocols, and primary extracted data files have been submitted to ArrayExpress (ArrayExpress accession no. E-MEXP-538). The Oct-1 dataset was downloaded from the GEO database, uploaded to BioArray Software Environment (Saal et al., 2002), and analyzed with the lamin B1 dataset for all comparisons.

To calculate the probability of having a particular number of genes changed in both experiments, a repeat sampling bootstrapping method was used. Specifically, for each cycle, 113 genes are randomly drawn from the list of 3,080 common genes, generating set A, and 1,089 genes are drawn randomly from the same 3,080 list, generating set B. Then, the number of genes present in both A and B (n) is recorded. After 500,000 cycles, the values of n were plotted to give a probability distribution histogram. The probability distribution is shown in Fig. S3.

Cells were fixed in 4% PFA and 250 mM Hepes, pH 7.4, on ice for 10 min and in 8% PFA and 250 mM Hepes, pH 7.4, for 50 min at room temperature. Cells were incubated in 25 mM glycine in PBS for 10 min, permeabilized with 0.4% Triton X-100 in PBS for 5 min, and blocked with 0.4% fish skin gelatin in PBS for 30 min at room temperature. Incubations with primary and secondary antibodies were for 1 h each at room temperature. Cells stained with concanavalin A–Alexa Fluor 633 (Con A 633; Invitrogen) were incubated with 100 μg/ml Con A conjugate for 1 h at room temperature. Primary antibodies used were goat anti–lamin B1, mouse monoclonal anti–lamin B1 (8D1; Maske et al., 2003), rabbit anti–Oct-1 (Thermo Fisher Scientific), and mouse anti–lamin A/C (Novocastra). Secondary antibodies used were donkey anti–goat, anti–mouse, and anti–rabbit (Jackson ImmunoResearch Laboratories) conjugated to Alexa Fluor 488, HRP, Cy3, or Cy5. For ROS detection, cells were washed with PBS, incubated with 20 μM H₂DCFDA (EMD) in phenol red-free DME for 30 min, and washed with PBS. All imaging was performed using a microscope (LSM 510 META; Carl Zeiss, Inc.) on an Axio Imager.Z1 (Carl Zeiss, Inc.) with a 63× NA 1.4 oil immersion objective lens. Laser lines used were 405 nm, 488 nm, 543 nm, and 633 nm to excite DAPI, Alexa Fluor 488, Cy3 and Cy5, or Alexa Fluor 633, respectively. Fluorescence was detected using the following filters: base pairs 420–480, base pairs 505–530, base pairs 560–615, and long pass 650. Images were analyzed using MetaMorph (MDS Analytical Technologies) or Image Browser (Carl Zeiss, Inc.) software.

FLIP was performed as described previously (Malhas et al., 2007) except that an inverted microscope (LSM 510 META) was used. In brief, a region of interest (ROI) was photobleached at full laser power while scanning at 4% laser power elsewhere. For quantitative analysis, background intensity was subtracted, and intensities of a specific ROI outside the photobleached area were measured over time and normalized using intensities of an ROI in a transfected but nonbleached cell.

FRET using the acceptor photobleaching method (Kenworthy, 2001) was used after immunolabeling of peripheral lamin B1 with 8D1, anti–mouse conjugated to Cy3 was used as the acceptor, and Oct-1–EGFP was used as the donor. An ROI was selected, and both the donor and acceptor were scanned 10 times (1.61 μs/pixel). The ROI was bleached with the 543-nm laser at 100% laser power. This was followed by scanning to detect any changes in the acceptor and donor intensities. FRET efficiency was calculated using the following formula: 100 × (1−[I_b/I_a]), where I_b and I_a are the intensities of the donor before and after bleaching, respectively.

Cells (∼10⁶ each of Lmnb1^+/+ and Lmnb1^Δ/Δ cells) were fixed with 1% formaldehyde for 10 min and incubated with 125 mM glycine for 5 min at room temperature. All subsequent washes and lysis steps were performed in the presence of complete protease inhibitor cocktail (Roche). Cells were washed with ice-cold PBS, scraped, pelleted, and lysed with 10 mM Tris, 10 mM NaCl, and 0.2% NP-40, pH 8, on ice for 10 min. Nuclei were pelleted and lysed with nuclear lysis buffer (50 mM Tris, 10 mM EDTA, and 1% SDS, pH 8) on ice for 10 min. Chromatin was sonicated to generate DNA fragments ranging from 300 to 1,000 bp as confirmed by electrophoresis. Lysates were diluted 10-fold in ChIP dilution buffer (20 mM Tris, 150 mM NaCl, 2 mM EDTA, and 1% Triton X-100, pH 8), and 1% was kept as the input samples. Lysates were precleared with salmon sperm DNA–blocked protein G agarose (Millipore) and incubated with 4 μg rabbit anti–Oct-1 overnight at 4°C and with protein G agarose for 2 h at 4°C. Precipitated samples were washed once with low salt washing buffer (20 mM Tris, 50 mM NaCl, 2 mM EDTA, 0.1% SDS, and 1% Triton X-100, pH 8), once with high salt washing buffer (low salt buffer with 500 mM NaCl), twice with lithium chloride washing buffer (10 mM Tris, 250 mM lithium chloride, 1 mM EDTA, 0.5% NP-40, and 0.5% SDS, pH 8), and twice with Tris EDTA buffer (10 mM Tris, pH 7.5, and 1 mM EDTA). Protein–DNA complexes were eluted using 0.1 mM NaHCO₃ and 1% SDS (which was also added to the input samples), and cross-links were reversed by heating overnight at 65°C. Samples were treated with 40 μg/ml proteinase K, and DNA was recovered by phenol/chloroform extraction and ethanol precipitation. All immunoprecipitated DNA samples were resuspended in 50 μl of 10 mM Tris-HCl, pH 8.5.

qRT-PCR was performed using a Rotor-Gene 3000 (Corbett Research) and the MESA GREEN qPCR MasterMix Plus for SYBR Assay (Eurogentec). PCR mixtures contained 2 μl immunoprecipitate or input samples and a final primer concentration of 400 nM. Relative gene expression values were determined using the 2^−ΔΔCt method (Livak and Schmittgen, 2001). The C_t values from qRT-PCR were normalized using those of the input samples and were used to calculate the fold enrichment of Oct-1 binding in Lmnb1^Δ/Δ cells compared with WT cells.

Promoter sequences (1,000 bases) of Rdm1, Gpx3, Mmp13, Mgst1, and Serping1 were obtained using BioMart. MAPPER (Marinescu et al., 2005) was used to identify potential Oct-1–binding sites within these sequences, and appropriate primers for qRT-PCR were designed using Oligo Perfect Designer (Invitrogen). Primers for the detection of Csnb and Actb have been described previously (Zhao et al., 2004; Dong and Zhao, 2007). FAM-labeled oligonucleotides and complementary oligonucleotides corresponding to the potential Oct-1–binding sites were synthesized by Invitrogen. The oligonucleotides were annealed in 20 mM Tris-HCl, pH 8, 50 mM NaCl, and 1 mM EDTA by heating to 95°C for 5 min and gradually reducing the temperature (0.5°C/s) to 22°C. The Oct-1 consensus oligonucleotide and the sequences of all other predicted Oct-1–binding sites are provided in Table S1 (available).

Approximately 10⁷ cells were allowed to swell in 10 mM Hepes, pH 7.9, 1.5 mM MgCl₂, 10 mM KCl, 1 mM DTT, and 0.5 mM PMSF and left on ice for 10 min. NP-40 was added to a final concentration of 0.3%, and the lysates were left on ice for a further 20 min. After centrifugation, the resulting pellet was resuspended in 20 mM Hepes, pH 7.9, 25% glycerol, 0.42 M NaCl, 1.5 mM MgCl₂, 1 mM DTT, and 1 mM PMSF, incubated at 4°C with constant agitation, and centrifuged at 16,000 g for 20 min, and the supernatants (nuclear extracts) were used for the gel shift assays. Equal amounts of nuclear extracts (15 μg) were incubated with FAM-labeled oligonucleotides and excess, unlabeled Oct-1 consensus oligonucleotides in EMSA-binding buffer where applicable (final concentrations of 10 mM Tris-HCl, pH 7.5, 10% glycerol, 50 mM KCl, 1 mM MgCl₂, 0.5 mM DTT, and 0.5 mM PMSF) for 40 min at 22°C. Reaction mixtures were run on 8% nondenaturing polyacrylamide gels in 0.5× Tris-borate-EDTA, and the gels were photographed using an imaging system (VersaDoc MP3000; Bio-Rad Laboratories).

Fig. S1 shows lamin B1–Oct-1 colocalization using antibodies, Fig. S2 shows more extensive EMSA data, Fig. S3 shows calculated probability distribution for two microarray datasets having n genes in common, and Fig. S4 shows the Oct-1–binding sequence patterns identified by the MAPPER algorithm. In addition, Table S1 shows the oligonucleotide sequences used in the EMSA experiments, and Table S2 lists the genes that are dysregulated in both datasets.

We wish to record our gratitude to Stephen Young and Martin Bergo for providing both the WT and lamin B1 hypomorph transgenic mouse embryonic fibroblasts used in this study and in previous studies (Maske et al., 2003; Malhas et al., 2007), to Dr. S. Murphy for providing the Oct-1–EGFP construct, and to Professor D. Tantin for providing the WT and Oct1^−/− cells. We wish to acknowledge the BioImaging Facility (Sir William Dunn School of Pathology) and the Computational Biology Research Group (Medical Sciences Division at the University of Oxford) for use of their services in this project.

This work was funded by grants from the Edward Penley Abraham Trust and by Tim and Kit Kemp. A.N. Malhas is a Kemp Postdoctoral Fellow of Lincoln College at the University of Oxford.