|Home | About | Journals | Submit | Contact Us | Français|
Compelling evidence exists that magnetic fields modulate living systems. To date, however, rigorous studies have focused on identifying the molecular-level biosensor (e.g., radical ion pairs or membranes) or on the behavior of whole animals leaving a gap in understanding how molecular effects are translated into tissue-wide and organism-level responses. This study begins to bridge this gulf by investigating static magnetic fields (SMF) through global mRNA profiling in human embryonic cells coupled with software analysis to identify the affected signaling pathways.
Software analysis of gene expression in cells exposed to 0.23–0.28 T SMF showed that nine signaling networks responded to SMF; of these, detailed biochemical validation was performed for the network linked to the inflammatory cytokine IL-6. We found the short-term (<24 h) activation of IL-6 involved the coordinate up-regulation of toll-like receptor-4 (TLR4) with complementary changes to NEU3 and ST3GAL5 that reduced ganglioside GM3 in a manner that augmented the activation of TLR4 and IL-6. Loss of GM3 also provided a plausible mechanism for the attenuation of cellular responses to SMF that occurred over longer exposure periods. Finally, SMF-mediated responses were manifest at the cellular level as morphological changes and biochemical markers indicative of pre-oligodendrocyte differentiation.
This study provides a framework describing how magnetic exposure is transduced from a plausible molecular biosensor (lipid membranes) to cell-level responses that include differentiation toward neural lineages. In addition, SMF provided a stimulus that uncovered new relationships – that exist even in the absence of magnetic fields – between gangliosides, the time-dependent regulation of IL-6 signaling by these glycosphingolipids, and the fate of embryonic cells.
Life exists amid an electromagnetic background and it is therefore not surprising that biological systems are finely tuned to detect and react to static magnetic fields (SMF) of various strengths. In a well known example from nature, the migration of birds is guided by very low strength geomagnetic fields [1-5]. In humans, there are intriguing reports – exemplified by an anecdotal Harvard study that showed severely depressed manic depressive patients experienced dramatic mood swings towards happiness during MRI  and pilot pain management clinical trials [7,8] – that magnetic fields can benefit health. In more rigorously controlled animal studies, beneficial effects on pain reduction , hypertension , wound healing , inflammation , and microvascular circulation  have been reported. To facilitate the translation of these early results to efficacious therapeutic modalities, a greater understanding of the underlying biological basis of magnetic exposure is required . Accordingly, in this paper we take steps towards bridging the gap between the established biophysical effects of magnetic fields on sub-cellular macromolecular components and reported tissue-level and whole organism responses by exploring whether SMF can function as a novel stimulus for signaling pathways at the cell level.
The premise that SMF can modulate signaling networks is based on reports that establish lipid bilayers as the most compelling molecular biosensors capable of responding to magnetic exposure. Specifically, moderate strength SMF can change biophysical properties of membranes that include hyperpolarization , redox potential , and fluidity  thereby altering flux through sodium (Na+)  and calcium (Ca2+) [13,16] channels. As a result, changes in cytosolic concentrations of the calcium ion – which serves as a second messenger in several signaling pathways – occurs ubiquitously in cells exposed to SMF . In addition to altering ion channel flux, biophysical changes to membranes may also affect lipid raft microdomains in ways that modulate downstream signaling; an example of this phenomenon is the impact of ethanol on lipid rafts and the concomitant changes to toll like receptor 4 (TLR4) activity . In contrast to ethanol – which increases membrane domain fluidity – SMF exposure increases membrane rigidity, an effect that has been coupled to the promotion of differentiation in osteoblast-like cells .
In the first part this study, mRNA profiling of SMF-treated cells coupled with analysis of the microarray data by the Ingenuity Pathway Analysis software tool [21-23] verified that anticipated transcriptional changes – qualitatively consistent with the impact of altered Ca2+ flux or membrane domain fluidity on signaling pathways – did occur. Building on this finding, we conducted a detailed molecular and biochemical characterization of cellular elements linked to interleukin-6 (IL-6, which was identified to respond to SMF from the software analysis) in human embryonic cells. As a framework for the ensuing experiments described in this study, these connections are diagrammed in Figure Figure1;1; this figure shows both known connections between IL-6 and other molecular players (e.g., Ca2+ and TLR4) as well previously unappreciated links (e.g., ganglioside involvement in IL-6 activation that acts even in the absence of SMF, offering a new controlling mechanism for IL-6). This study concludes by showing that SMF leads towards oligodendrocyte differentiation in human embryonic cells by preferentially stimulating pre-oligodendrocyte markers over the astrocyte markers usually associated with IL-6 exposure. Together, these results establish SMF as an intriguing means to ultimately (and non-invasively) stimulate cells in an endogenous niche.
To gain evidence for the hypothesis that SMF exposure activates or otherwise modulates signaling networks, human embryoid body derived (hEBD) cells  were exposed to 0.23–0.28 T fields and mRNA microarray profiling was used to determine changes to global patterns of gene expression. In the first tests, 15 min SMF exposure (followed by one day recovery) was tested based on reports that gene expression responded to magnetic exposure this quickly . In our evaluation, however, only two genes were up- and down-regulated with a statistical probability > 95% (Table (Table1)1) and none met the common benchmark of a 2- (or even 1.75-) fold change. Nonetheless, the reproducibility over multiple probes for the same gene indicated that these modest changes were real and provided impetus to investigate longer term exposure.
Indeed, after one day (~24 h) of SMF treatment, 379 genes were up-regulated and 549 were down-regulated with statistical significance (Figure (Figure2A);2A); even greater changes were seen after 4 or 5 days of exposure. The magnitude of the change for most genes, however, was modest (Figure (Figure2B)2B) with only 7 showing up-regulation ≥ 2-fold (Figure (Figure2C)2C) and 20 showing a similar degree of down-regulation (Figure (Figure2D).2D). After 5 days of continuous SMF exposure, the number of genes up-regulated by ≥ 2-fold increased to 85 (Figure (Figure2C)2C) while 94 were down-regulated to a similar extent. Interestingly, in an experiment where the cells were allowed to recover for one day under normal culture conditions after prolonged SMF exposure, the number of genes that remained up-regulated by ≥ 2-fold fell by almost half (from 85 to 47, Figure Figure2C)2C) whereas the number of down-regulated genes increased by 35 (Figure (Figure2D2D).
The microarray results were consistent with the activation of signal transduction pathways over the short term (i.e., in less than one day) leading to an amplified set of genetic changes over the next several days. A simple inspection of transcriptional changes (for example, the top 5 up- and down-regulated genes under each exposure condition listed in Tables Tables2,2, ,3,3, and and4)4) did not lead to any obvious insights into the over-riding effects of SMF however. Therefore, to flesh out this hypothesis, the Ingenuity Pathway Analysis software tool [21,26] was used to analyze the microarray data resulting in the identification of nine networks that responded to SMF exposure in hEDB LVED cells (Table (Table5;5; data analysis is shown for cells subject to five days of continuous SMF exposure and the annotated networks are provided in Additional file 1). Several of these pathways reflected known biological responses to magnetic exposure. For example, changes to intracellular Ca2+ pools observed in cell lines exposed to SMF [18,27] were consistent with interleukin-6 (IL-6) centered signaling responses (ID#2, Table Table5)5) mediated through the ability of this cytokine to be modulated by Ca2+ flux . Similarly, Wnt responses (ID#6, Table Table5)5) can be activated by a non-canonical Ca2+ dependent mechanism . Moving above the cell level, two networks were identified (ID#3 and ID#5) that related to cardiovascular development and hematological function, respectively, and thus dovetail with a recent report by Morris and Skalak where SMF exposure of 0.06–0.14 T for a comparable time period (seven days) facilitated micro-vessel regeneration after surgical intervention . Likewise, Strieth and coauthors have reported that SMF affects the vascular and blood flow  and Okano and coworkers have investigated the modulation of blood vessels by magnetic fields [10,31-33].
Even though the software analysis of the microarray data was consistent with a mechanism wherein SMF acted as a stimulus for signaling pathways, limitations of this methodology precluded any firm conclusions. Signaling pathway responses, for example, are typically measured over time intervals of minutes to hours and require evaluation with closely-spaced time points not practical by microarray profiling over several days. Therefore, to verify that the transcriptional changes we observed represented legitimate responses to SMF, we selected IL-6 for conventional biochemical characterization. Of the nine networks identified by microarray profiling, the selection of IL-6 for additional scrutiny was based on several factors. First, a recent report linked 0.4 T SMF exposure to increased IL-6 production in fibroblasts  and plausible membrane-based modes of activation IL-6 (e.g., through Ca2+ or TLR4) exist. Furthermore, reports that SMF can promote differentiation  – coupled with the propensity of the hEBD LVEC line used in this study to display neural markers  together with reports that IL-6 promotes astrocytogenesis  – offered the possibility that cell-level responses (e.g., differentiation of the hEBD cells to astrocytes) could be observed in these experiments.
Biochemical validation began by quantitative real-time polymerase chain reaction (qRT-PCR) analysis of IL-6 mRNA levels over the first 24 h of SMF exposure, a time frame selected based on the numerous changes seen in the microarray data after one day (Figure (Figure2)2) and literature reports of biphasic IL-6 activation during this time period . In these experiments, IL-6 mRNA levels increased two hours into SMF exposure and remained elevated compared to untreated control cells at 4, 7 and 24 h (Figure (Figure3A).3A). IL-6 secretion into the culture medium followed slower kinetics, first showing a measurable increase at 7 h after which SMF-treated cells out-produced control cells up to 96 h (Figure (Figure3B).3B). The SMF-exposed cells experienced the largest relative increase compared to untreated controls at 48 h, followed by a decline to slightly less than control levels at the end of the six day monitoring period.
Upon verifying that IL-6 was activated by SMF at both the mRNA and protein levels, we sought more detailed insight into this response. As indicated in Figure Figure1A1A &1B (for perspective, Figure Figure11 summarizes the connections between SMF, IL-6 and other pathways elements and cellular outcomes described in this report), IL-6 activation was consistent with the known ability of magnetic fields to alter calcium ion channel flux and reports of Ca2+-dependent up-regulation of IL-6 (the impact of SMF on calcium flux was experimentally verified for currently-used hEBD LVEC cells, Figure Figure3C).3C). In addition, connections IL-6 shares with TLR4 [37-39], combined with the dependence of the signaling activity of Toll-like receptors on their lateral diffusion within membrane microdomains [19,40], suggested a parallel route through which SMF could influence IL-6. Specifically, a sequence of events can be postulated where SMF changes membrane fluidity thereby modulating TLR4 (Figure (Figure1C)1C) and downstream IL-6 responses (Figure (Figure1E)1E) through a Ca2+-dependent mechanism (Figure (Figure1F)1F) or through TLR4-mediated p38 phosphorylation (Figure (Figure1G1G).
Experimentally, because TLR4 transcription is strictly auto-regulated in a stimulus-dependent manner ([38,41] and Figure Figure1D),1D), qRT-PCR can be used to monitor its activation. By monitoring this endpoint, we found that TLR4 transcript levels increased during the first several hours of SMF exposure (Figure (Figure3D).3D). Interestingly, self-activation of TLR4 can lead to either the down-regulation of its mRNA (as seen in rat glial  or murine macrophages ) or to up-regulation (as seen in murine lung  or human monocytes and polymorphonuclear leukocytes ); the current up-regulation of TLR4 mRNA observed in SMF-treated embryonic cells is consistent with results obtained in other types of human cells upon activation of TLRs.
The activation of IL-6 in cells exposed to SMF was consistent with signal transduction through the upstream involvement of TLR4 (Figure (Figure1E1E&1G). To gain biochemical evidence for this connection, we analyzed the phosphorylation of p38, which lies in the pathway that connects TLR4 with IL-6, and found the predicted increase in phosphorylated p38 in SMF treated cells (Figure (Figure4A).4A). This result, in addition to establishing a connection between IL-6 and SMF through TLR4, provided evidence that SMF impinges on MAPK signaling (p38 plays a central role in mediating MAPK responses) prompting us to evaluate changes to proliferation and apoptosis. In these experiments a significant reduction in proliferation was seen for hEBD LVEC cells after three days of SMF exposure; this effect lessened by the sixth day and was lost by the ninth day (Figure (Figure4B).4B). Qualitatively, this short term change in proliferation was consistent with studies where SMF transiently altered proliferation . Annexin/propidium iodide staining assays showed that reduced proliferation during early phases of SMF exposure was not a consequence of increased apoptosis (Figure (Figure4C4C&4D) in agreement with reports that SMF, if anything, is protective against apoptosis [18,45]. Having ruled out that the SMF treated cells were dying, a plausible explanation for the reduced proliferation was that the cells were undergoing differentiation with a concomitant decrease in their growth rate; this possibility was supported by data presented later in this report.
As a brief diversion from the main thrust of this study, which was to connect SMF with cellular responses associated with IL-6 in human embryonic cells, we wish to emphasize that the impact of SMF on other common laboratory cells such as the Jurkat, HeLa, and HEK AD293 lines was surveyed and "obvious" effects such as pronounced changes in proliferation (as seen in Figure Figure4B4B for the hEBD LVEC line) or altered morphology (as shown later in this report) were not observed. For example, representative data is shown for the HEK AD293 line in Figure Figure55 where control and SMF-exposed cells had identical growth rates when measured by either the MTT assay (Panel A) or through cell counting (Panel B). The clear-cut differences seen between the embryonic hEBD LVEC line and cancer lines were not surprising based on reports that even closely-matched cell lines respond uniquely to SMF ; instead these findings support the hypothesis that changes to Ca2+ flux (as shown in Figure Figure3C)3C) – a parameter that is highly cell line dependent  – contributes to the cellular responses we observed in the cells exposed to SMF.
To gain insight into whether regulatory networks beyond TLR4 or calcium flux contributed to the up-regulation of IL-6 in SMF treated cells, we next focused on gangliosides [38,47]. Gangliosides are sialic acid-bearing glycosphingolipids (GSLs) that are integral components of lipid rafts and caveolae of the type surrounding TLR4 that not only organize these microdomains but also regulate the signaling functions of embedded proteins (as discussed in more detail in review articles [48,49]). Consequently, TLR4  and IL-6  can be influenced by the equilibrium between the 'inert' (in this context) GSL lactosylceramide (LacCer) and the suppressive ganglioside GM3 (Figure (Figure1K1K).
Before beginning experiments to probe the impact of SMF exposure on gangliosides, the relationship between GM3 (and its disialylated derivative GD3) and IL-6 was first investigated to establish a baseline for the hEBD LVEC line (before the current study, there was negligible literature precedent for a connection between GSL and IL-6 in human embryonic cells). A long-lasting and substantial (e.g., > 95% at 4 d) reduction in IL-6 mRNA was observed in cells incubated with exogenously-added GM3 or GD3 (Figure (Figure6A).6A). Crosstalk between gangliosides and IL-6 also held in the reverse direction as demonstrated by a dose dependent decrease in GM3 in cells incubated with exogenously-added IL-6 (Figure (Figure6B).6B). By reducing the amount of GM3 present in a cell (Figure (Figure1N),1N), IL-6 can alleviate the suppressive effects of this ganglioside on its transcription (Figure (Figure1L)1L) thus setting up a 'feed-forward' loop that offers an mechanistic explanation for the self-activation of IL-6 described in the literature  and demonstrated for hEBD LVEC cells in this study (Figure (Figure6C).6C). Figure Figure6C6C shows that levels of TLR4 mRNA also increased significantly in IL-6 supplemented cells consistent with the removal of concomitant inhibitory effects of GM3 on TLR4 . Together with the impact of SMF on IL-6 shown in Figure Figure3,3, these results demonstrate that SMF has the capacity for tuning IL-6 signaling by adjusting the relative proportions of the 'active' ganglioside GM3 and its 'inert' asialo counterpart LacCer (Figure (Figure1K)1K) thereby contributing to the transcriptional up-regulation of TLR4 and IL-6 (Figure (Figure1M1M&1N).
Mechanistically, changes to one of two enzymes could explain the shift in equilibrium away from the suppressive ganglioside GM3 to its inert asialo counterpart LacCer (Figure (Figure1K);1K); specifically, an increase in the recycling enzyme NEU3 or a decrease in the biosynthetic enzyme ST3GAL5 (Figure (Figure7A).7A). Despite no previously-known direct links between IL-6 and ST3GAL5 or NEU3, increased phosphorylation of ERK1/2 has been connected with the up-regulation of STGAL5 (, as shown in Figure Figure1P).1P). Therefore, based on a report linking IL-6 and MAPK signaling through JAK/STAT that involved ERK1/2 (Figure (Figure1R)1R) , we reasoned that ERK1/2 could serve as an intermediary to connect IL-6 with ST3GAL5 expression. Accordingly, we tested the phosphorylation of ERK (Figure (Figure7B)7B) and found that pERK1/2 was inhibited by concentrations of IL-6 > 4.0 ng/ml (Figure (Figure7C);7C); the reduced ratio of pERK1/2 to ERK was consistent with dampened mRNA levels for the biosynthetic enzyme ST3GAL5 and the tandem up-regulation of the recycling enzyme NEU3 (Figure (Figure7D).7D). A noteworthy aspect of this study was that, although the effects of NEU3 and ST3GAL5 on "lubricating signaling pathways"  have been previously evaluated separately, to our knowledge this is the first report where both enzymes were monitored simultaneously and found to respond to an external stimulus in a concerted manner that required transcriptional regulation of the biosynthetic and recycling enzymes in opposite directions.
The prolonged down-regulation of ganglioside GM3 upon IL-6 supplementation (Figure (Figure6A)6A) provides a two-pronged mechanistic explanation for long term attenuation of IL-6 and related responses in SMF-treated cells (for example, SMF-enhanced IL-6 levels returned to normal by day 6 (Figure (Figure3B)3B) followed by loss of growth inhibition by day 9 (Figure (Figure4B)).4B)). First, the loss of sialic acid – an important contributor to the carbohydrate-carbohydrate binding interactions that stabilize lipid assemblies  – from GM3 can destabilize CD82-enriched microdomains . Assuming that the TLR4 receptor complex, which is also sensitive to the stability of its local microdomain environment , responds to a reduction in GM3 levels in a similar manner, the signaling pathways activated by SMF over the first day or so of exposure could be 'turned off' by the loss of GM3 over longer time periods. A second mechanism to explain ganglioside-mediated attenuation of IL-6 can be postulated based on the findings by Müthing and colleagues that GSL such as GM3 increase Ca2+ flux through voltage gated channels . In an independent set of experiments, Yang and coworkers reported a strongly stimulatory effect for GM3 on the SR Ca2+-ATPase [55-58]. Together, these findings indicate that the conversion of GM3 to LacCer in SMF-treated cells inhibits Ca2+-dependent signaling pathways in a manner that attenuates the initial multi-pronged up-regulation of IL-6.
The crosstalk between gangliosides and IL-6 (as summarized in Figures Figures1L1L&1N and and7A),7A), combined with the ability of SMF to modulate this cytokine (as shown by the data in Figure Figure3),3), led us to consider whether SMF altered IL-6 via a ganglioside-mediated route (or vice versa). To investigate this possibility, NEU3 and ST3GAL5 – the enzymes that control the equilibrium between GM3 and LacCer (Figure (Figure7A)7A) and thus have the potential to indirectly modulate IL-6 (Figure (Figure1L1L&1N) – were monitored by qRT-PCR during the early stages of SMF exposure. In these experiments, up-regulation of NEU3 and inhibition of ST3GAL5 after one day of SMF exposure (Figure (Figure8A)8A) reminiscent of the effects of IL-6 supplementation (Figure (Figure7D)7D) were observed. Analysis of ganglioside levels in these cells showed that these transcriptional changes again worked in concert to decrease GM3 levels on the cell surface (Figure (Figure8B,8B, top). A similar reduction in GM3 occurred in fixed and permeabilized cells where gangliosides situated in the secretory pathway are also measured (Figure (Figure8B,8B, bottom). By testing both conditions, the possibility that surface changes merely reflected the redistribution of GM3 between the cell surface and intracellular compartments was discounted (this concern was raised by the hypothesis that SMF changes the biophysical properties of lipid bilayers thereby potentially affecting trafficking between surface and intracellular membranes). Interestingly, GD3 – which can modulate the biophysical properties of membrane raft assemblies similar to GM3 (and in essence serves as a reservoir for this monosialylated ganglioside, Figure Figure7A)7A) – was also reduced by SMF (Figure (Figure8C);8C); this result can be explained by the ability of NEU3 to remove both sialic acid residues of GD3.
In order to gain insight into the cause and effect relationships that connect SMF, gangliosides, and IL-6, IL-6 was added to cells in the presence or absence of SMF. In this experiment IL-6 had the same effect on GM3 levels with or without concomitant magnetic exposure (Figure (Figure8E).8E). This result contrasted with the clear reduction in GM3 when IL-6 had been added to cells in the absence of SMF (as shown in Figure Figure6A).6A). One explanation for these disparate results was that SMF activated a sequence of events where IL-6 transcription was first up-regulated leading to increased protein secretion, which in turn reduced GM3. This scenario, however, was discounted by a time course of NEU3 and ST3GAL5 mRNA expression over the first day of SMF exposure (Figure (Figure8F)8F) that showed that the transcriptional changes to these enzymes occurred before measurable IL-6 secretion took place (e.g., before 7 h, see Figure Figure3B).3B). Therefore, SMF independently regulates IL-6 and gangliosides in a way that ultimately impinges on the same molecular mechanism (i.e., through NEU3 and ST3GAL5 transcription and activity). GM3 and GD3 also provide a putative explanation for the biphasic increase in IL-6 mRNA; at early time points a ganglioside-independent sequence of events (presumably involving, but not necessarily limited to, TLR4 activation or Ca2+ flux) occurs. As the initial signal fades, reduction of GM3 and GD3 could contribute to a second 'burst' of IL-6 expression by alleviating the suppressive effects of these gangliosides on IL-6 itself (Figure (Figure1L)1L) or on TLR4 (Figure (Figure1M1M).
As described earlier, hEBD LVEC cells exposed to SMF experienced reduced proliferation without toxicity (Figure (Figure4),4), a response consistent with differentiation. To test if this phenomenon was linked to SMF or IL-6 production, cells were first treated with ≤ 4.0 ng/ml of IL-6 in the absence of SMF. IL-6 supplementation typically resulted in relatively minor (if any) change to cell morphology (Figure (Figure9A9A&9B). Occasionally, however, dendrite-like outgrowths reminiscent of neuronal cells developed in sub-populations of IL-6 treated cells (Panel C). By contrast, close to 100% of the cells attained distinctive morphology when SMF was combined with 4.0 ng/ml of IL-6 (Panel E; SMF alone had a much less pronounced impact on morphology, Panel D).
One explanation for why both SMF and exogenous IL-6 supplementation was needed to elicit noticeable changes to cell morphology was that, because of the relatively small volume of cells (≤ 0.01%) compared to culture medium, any IL-6 secreted in response to SMF would be diluted ~10,000-fold. As a consequence, additional IL-6 supplementation was required to mimic levels achieved by comparable rates of IL-6 production in cells situated within an in vivo niche where the relative cell to interstitial volume ratios are much lower. Another (non-exclusive) explanation, supported by experiments where even 20 ng/ml IL-6 could not reproduce the combined effects of SMF plus 4 ng/ml IL-6 (data not shown), was that SMF-activated networks beyond IL-6 – such as those listed in Table Table55 – contributed to the morphological changes.
To gain greater insight into the morphological changes induced in hEBD LVED cells by a combination of SMF and IL-6, we noted that IL-6 has a role in the regeneration of nervous tissue, usually promoting astrocyte formation  and, accordingly, monitored the transcription of bone morphogenic protein 2 (BMP-2) and myelin basic protein (MBP) (Figure (Figure9F).9F). Interestingly, a decrease in mRNA for BMP-2, a protein that stimulates astrocytogenesis , was observed suggesting that the hEBD cells were not differentiating into astrocytes as expected. To confirm this observation using immunofluorescent microscopy, no increase in the GFAP marker associated with astrocyte formation was observed in SMF and IL-6 treated cells (Figure 10A). Similarly, no increase was seen for NEF (Figure 10B), a marker associated with neuron differentiation.
Based on the lack of astrocyte or neuron differentiation, a third possibility was that the decrease in BMP-2 expression in SMF-treated cells removed the obstacle presented by bone morphogenetic proteins towards differentiation to oligodendrocyte lineages . Indeed, consistent with the decrease in BMP-2, an increase in myelin basic protein (MBP) transcription was observed (Figure (Figure9F)9F) providing a biochemical marker consistent with differentiation to an oligodendrocytes . Additional supporting evidence that SMF, combined with IL-6, leads toward oligodendrocyte progenitor formation was provided by the increased expression of vimentim (Figure 10C) and Gal-C (Figure 10D).
The relationships between SMF, calcium, TLR4, gangliosides (and regulatory enzymes), MAPK pathway elements (p38 and ERK1/2) and IL-6 are outlined in Figure Figure1;1; this diagram, however, does not provide a dynamic view that would provide insight into cause and effect relationships. Therefore, to summarize the time dependence of various aspects of hEBD LVEC cell responses to SMF exposure, early, intermediate, and longer term responses are summarized in Figure Figure11.11. During the first four hours (Panel A), changes to calcium flux occur within minutes as do MAPK responses (e.g., p38 phosphorylation, Figure Figure4A);4A); effects on the transcription of IL-6, TLR4, NEU3, and ST3GAL5 mRNA lag slightly but show a strong response beginning between 2 and 4 hours. By contrast, secreted IL-6 remains unchanged. During the remainder of the first day of exposure (Panel B), mRNA levels of SMF treated cells trend back to control levels (the one exception is the 24 hour point for IL-6, which rebounds after a decline between 4 and 7 hours, this biphasic response mimics the impact of other stimuli on IL-6 ). Also during the first day, while the impact of SMF on transcription of IL-6, TLR4, NEU3, and ST3GAL5 abates, phenotypic effects such as the accumulation of measurable levels of secreted IL-6 began to be manifest. In general, initiating events – for example, the impact of SMF on mRNA levels – were attenuated after the second day (as shown in Panel C) whereas "behavioral" responses (such as the secretion of IL-6 or the effects of SMF on proliferation) followed the same trend but lagged in time. During this multiday time period – while "intermediate" responses were returning to normal – long-lived changes to cell fate arose that included the morphological changes shown in Figure Figure99 and the accumulation of pre-oligodendrocyte markers shown in Figure Figure1010.
Another lesson learned from the data shown in Figure Figure1111 was that SMF treatment set in motion a complex sequence of events that rapidly changed over time; consequently, the original goal of analyzing cellular responses by microarray profiling could have led to erroneous conclusions. For example, the complex and rapidly changing nature of IL-6 mRNA transcription could have led to the conclusion that the microarray results were simply irreproducible, as has been reported for much lower-strength fields . Alternately, the four and five day time points – where IL-6 mRNA levels were actually lower than controls – were not consistent with the strong, multifaceted up-regulation that occurred upon the initial exposure to magnetic stimulus thereby also providing misleading information if regarded in isolation. Therefore, we close by noting the benefits of the robust ability of software tools to uncover signature biological activity – namely, signaling responses associated with IL-6 – even when the key molecular player (i.e., IL-6) is undergoing rapidly changing or oscillatory behavior that would be difficult to understand by itself.
At the outset, we emphasize that this study was not intended to provide a comprehensive account of the cellular effects of SMF. For example, mechanisms other than those based on a lipid biolayer 'biosensor' may contribute to the transcriptional changes observed in this study as direct effects of SMF on protein-DNA interactions have been postulated [63-66] as have changes in enzymatic and biochemical reactions [5,67-69]. Therefore, we reiterate that our goal was to provide a rudimentary framework of one of many parallel or complementary mechanisms through which magnetic stimuli are transduced from molecular level biosensors into cell-level responses. This objective was pursued by mRNA microarray profiling that verified time-dependent global changes in transcription occurred that were consistent with the activation of signaling pathways. Then, to gain insight into the specific networks affected by SMF exposure, which were not obvious by simple inspection of the genes involved, the microarray data was subject to software analysis and signaling networks consistent with tissue- or organ-level responses to magnetic exposure (that include benefits to wound healing  and inflammation ; cardiovascular effects  such as modulation of blood flow and pressure ; and anti-tumor activity [70,71]) were identified.
Although the microarray data identified cellular responses consistent with previously reported biological responses to magnetic exposure, we nonetheless sought to ensure that these associations were not just coincidental or an artefact of the software analysis. Detailed biochemical investigation of all nine pathways (see Table Table5)5) was well beyond the scope of a single study, therefore we selected a single network – IL-6 signaling – for validation and outlined several molecular paths (as shown in Figure Figure1)1) that accounted for the multifaceted up-regulation of IL-6 by SMF that occurred over the first 1 to 3 days of exposure. From the standpoint of disease intervention, the up-regulation of IL-6 by SMF at first seems to be unwanted because IL-6 is generally maintained at low levels in healthy tissue . Moreover, chronically elevated levels of IL-6 are usually deleterious (for example, inflammation and unabated astrocyte differentiation associated with increased IL-6 experienced after brain or spinal cord injury blocks axonal regeneration of neurons and thereby hampers full recovery ). In some cases, however, the short-term activation of IL-6 can be therapeutically beneficial; for example, this pleiotropic cytokine can be neuroprotective immediately after injury . Consequently, successful therapeutic intervention involving IL-6 is contingent upon transient – as experienced in the SMF-treated cells – rather than on prolonged activation to avoid the deleterious consequences of chronic inflammation and other long term consequences of sustained IL-6 production.
In a final set of experiments, we briefly investigated whether SMF-mediated responses associated with IL-6 signaling translated into changes in phenotype observable at the whole cell level. Although IL-6 impacts numerous cell-level and systemic responses, our experimental efforts were focused by reports that IL-6 guides differentiation of neural stem cells primarily to astrocytes . These clues led us to investigate whether evidence of astrocytogenesis was seen in the hEBD LVEC cells, an embryonic line that is predisposed to neural differentiation . Interestingly, responses consistent with differentiation (i.e., slowed proliferation and morphological changes) were not reflected in the biochemical markers indicative of the astrocyte differentiation expected from IL-6. Instead, markers found in oligodendrocyte precursor cells were manifest, indicating that the other pathways modulated by SMF tuned the 'usual' activity of IL-6. Ultimately, if full oligodendrocyte formation can be promoted in vivo by SMF without concomitant astrocyte enhancement (under the current experimental conditions, full differential to oligodendrocytes was not feasible due to the absence of neurons and other glial cells found in the in situ oligodendrocyte microenvironment), this capability could lead to non-invasive therapies for conditions such a multiple sclerosis (MS) linked to oligodendrocyte pathologies.
The human embryoid body derived (hEBD) LVEC cell line  was obtained from the Shamblott Laboratory (JHMI) and was cultured in EGM2MV media (Clonetics, San Diego, CA) that included 5.0% fetal bovine serum (FBS), hydrocortisone, human basic fibroblast growth factor, human vascular epidermal growth factor, R(3)-insulin-like growth factor I, ascorbic acid, human epidermal growth factor, heparin, gentamycin, and amphotericin. The HEK AD293 line was obtained from the ATCC (Manassas, VA) and incubated in DMEM supplemented with 10% FBS under established conditions . Cells were cultured on tissue culture (T.C.) plastic coated with bovine collagen I (Collaborative Biomedical Products, Bedford, MA; 10 μg/cm2) in a water-saturated, 37°C incubator with 5.0% CO2.
Cell exposure to SMF was conducted for time intervals up to a maximum of 9 days using a device obtained from the Advanced Magnetic Research Institute, International (AMRIi, Calgary, AB) that fit into a standard T. C. incubator with sufficient clearance on all sides so that incubator functions (i.e., circulation of CO2 and water saturated air) were not affected. The device was designed based on principles derived from clinical testing of SMF (Diabetic Peripheral Neuropathy (ClinicalTrials.gov Identifier: NCT00134524) and Chronic Low Back Pain (NCT00325377)) that the magnetic field must be unidirectional with no reverse field passing through the sample . It was embedded with four 1" × 4" × 6" (inch) permanent neodymium (NdFeB) rectangular block magnets with two located above and two below the central cavity (Additional file 2: Figure S10). The device produced a field with a magnetic flux gradient of < 1.0 mT/mm in the portion of the central cavity where the cells were maintained during experiments. This arrangement contrasts with experimental set-ups where each well of a T. C. plate has been supplied with SMF exposure by using a separate magnet; in these cases (or in experiments specifically designed to test gradient responses) the periphery of the treatment areas were subject to much higher magnetic flux gradients of 20, 21, or 28 mT/mm [31-33,74] that resulted in different cellular responses than observed in the more uniform portions of the magnetic fields.
As just explained, the SMF conditions used in the current experiments were not expected to elicit gradient effects because the gradient used was much shallower than previously reported (i.e., < 1.0 mT/mm compared to 20–28 mT/mm). Nevertheless, to ensure that gradient effects – or other artefacts of the exposure conditions – did not account for the effects observed in hEBD LVEC cells in this study, several control experiments were conducted. First, the direction of the flux (i.e., whether the device was oriented upright so that the field was superimposed on the Earth's magnetic field or oriented upside down so that the applied field countered the background field) was tested and found not to have an impact on the parameters under investigation in hEBD LVEC cells. Second, differences in field strength (i.e., whether the cells were exposed to field at the extreme top or bottom of the treatment device when six T. C. plates – the maximum capacity of the device – were stacked on top of each other) did not measurably affect the outcome of the experimental parameters reported in this study. Finally, the orientation of the T. C. plates (e.g., whether the plates were placed as shown in Figure S10 (Additional file 2) or at 90°, 180°, or 270° angles) did not alter experimental outcomes.
Despite the lack of variation in IL-6 related outcomes, the experiments described in this report were always performed with the induced static magnetic field superimposed in the same direction as the ambient field, the SMF-treated cells were maintained in the central portion of the device oriented as shown in Figure S10 (Additional file 2) in the region the where magnetic flux density ranged between 0.23 and 0.28 T (as measured by a gaussmeter, Type 181002, Thyssen Magnet-und komponententechnik, Dortmund, Germany). Control cells were kept in an identical incubator where the ambient magnetic field was ~52 μT (which was within 1 μT of the background levels measured by us or reported by the National Geophysical Data Center for the location where these experiments were conducted (i.e., 52,359.0 nT at a latitude of 39° 19' 35" and a longitude of – 76° 36' 17",. http://ngdc.noaa.gov/geomagmodels/IGRFWMM.jsp?defaultModel=IGRF).
In all cases, the cells subjected to microarray profiling were obtained from the same initial culture batch and were subsequently cultured for a total of six days before RNA was isolated and analyzed. Subconfluent (70%–80%) undifferentiated hEBD LVEC (passage 11) cells were trypsinized, resuspended, and replated at 5.0 × 105 cells in 10 ml medium in 10 cm T. C. dishes on "Day 0". All cells were allowed to recover from the plating process by incubating them under normal culture conditions for one day after which time four conditions were investigated. For Group 1, control cells were incubated for five additional days under normal culture conditions. For Group 2, cells were cultured under normal conditions for four additional days and then subjected to one day (~24 h) of SMF exposure in the magnetic treatment device on "Day 6"; mRNA from these cells, as well as from the third group, was isolated for analysis immediately after magnetic exposure ended. For Group 3, cells were subjected to continuous SMF exposure for five days. Finally, for Group 4, cells were exposed to SMF for four days (from Day 2 through Day 5) followed by a 24 h recovery period during which time they were incubated under normal culture conditions. mRNA was isolated from the cells and microarray analysis was done using the Affymetrix Human Genome U133 2.0 Plus Chip using the protocols and facilities available through the Johns Hopkins Cancer Center Microarray Core. All data was obtained in duplicate from independent experiments. Software analysis was performed using the Ingenuity Pathway tool (available through the Microarray Core) using merged data from each set of independent experiments. The microarry data have been deposited in NCBI's Gene Expression Omnibus  and are accessible through GEO Series accession number GSE14474 http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14474.
hEBD LVEC cells were incubated in Ca2+- and Mg2+-free for PBS for up to four hours (longer time points decreased cell viability making the assay results unreliable) with or without SMF exposure. Intra- and extra-cellular calcium levels were measured separately after the cells were separated from their supernatants by pelleting with a 300 g, 2 min centrifugation step followed by lysis by sonication with a GE130PB ultrasonic processor (General Electric, New York, NY). Analysis of the supernatants and cell lysates was then conducted using a calcium reagent set (Pointe Scientific Inc., Canton, MI) and published methods .
The basic procedure for ganglioside supplementation followed published procedures . Briefly, cells were plated in 6-well tissue culture dishes and incubated until they reached 60% confluence. GM3 or GD3 (Matreya LLC, Pleasant Gap, PA) was resuspended in serum-free medium and briefly sonicated to ensure appropriate micellar suspension and cellular incorporation of these gangliosides. Cells were then incubated in culture medium containing 1.0, 5.0, 10, 20, or 50 μM GM3 or GD3 for varying periods of times (as specified in the Results section and accompanying figures). In each case, results were compared with a "solvent control," where an equal volume of medium was added to cells without ganglioside.
The mRNA levelsofST3GAL5, NEU3, TLR4, IL-6andglyceraldehyde-3-phosphatedehydrogenase(GAPDH)wereanalyzedbyquantitativereal-timepolymerasechain reaction (qRT-PCR) [77,78]. Primers (listed in Table Table6),6), were designed by using the Primer3 software made available through the Broad Institute http://genecruiser.broadinstitute.org/science/software and obtained from MWG-Biotech (High Point, NC). The basic protocol followed for qRT-PCR experiments began with the isolation of total RNA from 5.0 × 106 cells with the RNeasy Mini Kit (Qiagen, Valencia, CA) or by the TRIzol (Invitrogen) method. RNA quality was assessed by agarose gel electrophoresis (1.8% gels run with TAE buffer followed by nucleic acid band visualization under UV illumination after ethidium bromide staining) and quantified by A260/A280 OD readings. RNA integrity was confirmed using 18 S rRNA primers, and samples were standardized based on equal levels of β-actin cDNA. Quantitative real-time PCR was performed in an ABI Prism 7000 sequence detector (Applied Biosystems) using SYBR Green PCR Master Mix reagent (Applied Biosystems). Reactions were performed in 20 μl of a mixture containing a 2.0 μl cDNA dilution, 1.0 μl (10 pmol/μl) of primer, and 10 μl of 2× SYBR master mix containing Amplitaq Gold DNA polymerase, reaction buffer, a dNTP mixture with dUTP, passive reference, and the SYBR Green I. qRT-PCR conditions were as follows: one cycle of 2.0 min at 50°C, 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 1.0 min. Specific PCR products were detected with the fluorescent double-stranded DNA binding dye, SYBR Green. qRT-PCR amplification was performed in quadruplicate for each sample (typically values for the replicates were within 2% of each other) and the results were replicated in at least three independent experiments. Gel electrophoresis and melting curve analyses were performed to confirm correct PCR product sizes and the absence of nonspecific bands. The expression level of each gene was normalized against β-actin using the comparative CT method  according to the manufacturer's protocols.
The method used for the analysis of cell surface GM3 and GD3 expression by flow cytometry was adapted from published protocols . Briefly, these tests were performed by detaching hEBD LVEC cells by trypsinization and washing them with washing buffer (1.0% bovine serum albumin, 0.1% NaN3 in phosphate-buffered saline). Cells (1.0 × 106) were stained with 20 μg/ml of a mouse monoclonal antibody against GM3 (NBT-M101/M102, isotype IgM, clone M2590; Cosmo Bio Co., Ltd., Tokyo, Japan) and detected with fluorescein isothiocyanate-conjugated Affinipure rabbit anti-mouse IgM (Jackson Immunoresearch, West Grove, PA). A similar procedure was used for GD3 analysis, except cells were stained with mouse anti-human ganglioside GD3 monoclonal antibody (Product number 371440, clone 110.14F9, isotype IgG3; Calbiochem) diluted 1:50 in washing buffer and detected with a donkey anti-mouse IgG antibody conjugated to fluorescein (Jackson Immunoresearch). Control samples stained with secondary antibody alone were analyzed in parallel in each experiment. Samples were analyzed with a FACScan flow cytometer and Cell Quest software (BD Immunocytometry Systems, San Diego, CA), and a minimum of 5000 events were acquired for each sample. Analysis of total (i.e., surface and intracellular) GM3 and GD3 was tested in fixed and permeabilized cells  by adaptation of a method used to quantify intracellular levels of p21WAF1 . Briefly, before completing the staining procedure described above, cells were fixed by incubation in 4.0% paraformaldehyde in phosphate-buffered saline for 10 min at room temperature followed by
An equal amount of protein from each sample (20 μg) was incubated for 5.0 min at 100°C in Laemmli buffer (Bio-Rad), separated on a 7–11% SDS-polyacrylamide discontinuous gel, and then electrophoretically transferred to a nitrocellulose membrane (Bio-Rad). The membrane was blocked with Tris-buffered saline containing 5.0% nonfat milk and 0.1% Tween 20 for 1.0 h at room temperature and then incubated overnight with rabbit phospho-p44/42 MAPK (i.e., pERK1/2) monoclonal antibody and p44/42 MAPK (i.e., ERK1/2) antibody (1:1000 dilution) or phospho-p38 MAPK and p38 MAPK (1:2000) or phospho-stat3 (Tyr705) and Stat3 rabbit antibody (1:1000) (Cell Signaling Technology, Beverly, MA) at 4.0°C, followed by anti-rabbit or anti-mouse IgG, horseradish peroxidase-linked antibody (1:2000) for 1.0 h. Bound antibody on the membrane was detected using the SuperSignal West Dura Extended Duration Substrate (Pierce) according to the protocols supplied by the manufacturer. Quantification of bands was performed by using the NIH ImageJ software (available on the World Wide Web at rsb.info.nih.gov/nih-image) following a published method [82,83].
For proliferation assays, control or SMF-exposed hEBD LVEC cells were added to 96-well tissue culture plates at 3000 cells/well in serum-containing medium and cultured for up to nine days with the culture medium replenished every 3rd day. To quantify cell proliferation by measuring metabolic activity, 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT, (Sigma) was added to each well (0.5 mg/ml). After incubation for 3.0 h at 37°C, the supernatants were aspirated, and 100 μl of n-propyl alcohol containing 0.1% Nonidet P-40 and 4.0 mM HCl were added. The colorimetric reaction was quantified by using an automatic plate reader, μ Quant (Bio-tek Instrument Inc., Winooski, VT) to measure absorbance at 570 nm with a reference filter of 690 nm. Each MTT assay was carried out in triplicate. In all cases, measurement of proliferation through cell counting by using a Coulter Z2 instrument (as described in our previous publications ) yielded identical results.
The Annexin V/propidium iodide flow cytometry method was used for the detection and quantification of apoptosis by following the procedure previously reported for Jurkat cells [85,86] with the added step of trypsinizing the adherent hEBD LVEC cells (the previously-tested Jurkat cells grow in suspension and did not require this step). After trypsinization and resuspension in complete medium, cells were counted with a Coulter Z2 instrument, 1.0 × 106 cells from each sample were pelleted by centrifugation, washed by gentle resuspension in Dulbecco's phosphate-buffered saline, centrifuged again, and suspended in staining buffer. The cells were stained with fluorescein isothiocyanate-labeled Annexin V and propidium iodide and analyzed by flow cytometry as described previously [85,86].
Cells were seeded in triplicate in a 96 well culture plate at 6000 cells/well in 200 μl of medium. After two days, cells were exposed to SMF and supernatant was collected over the time course indicated in the Results section and the concentration of IL-6 was determined by an ELISA kit designed for this purpose (eBioscience, San Diego, CA) following the protocol provided by the manufacturer.
hEBD LVEC cells (1.0 × 105 in 2.0 ml of medium) were plated on collagen coated 35 mm glass bottom dishes (35 mm, MatTek Corporation, Ashland, MA) and either exposed to SMF during culture or subject to normal cultivation. On day 4 the monolayers were fixed in reagent A and permeabilized in reagent B (Fix & Perm, Reagents A and B, Caltag Laboratories, Burlingame, CA) followed by washing with 3.0% BSA in PBS. Cells were incubated with anti-galactocerebroside (Gal-C, 1:100) (Sigma, Saint Louis, MO); anti-NEF 70 kD (1:100) (Chemicon, Temecula, CA); anti-GFAP (1:100) (Santa Cruz, Los Angeles, CA); or anti-vimentin (anti-Vim, 1:500) (BD Pharmingen, San Diego, CA) for 2.0 h at RT. The secondary antibody used to stain anti-GFAP, anti-NEF, and anti-Vim was Cy3-conjugated Donkey anti-mouse IgG(H+L) and Cy3–conjugated Donkey anti-Rabbit IgG(H+L) was the secondary anti-body used for anti-Gal-C (both were obtained from Jackson ImmunoResearch Labs, West Grove, PA and used at a 1:100). In all cases, a solution of the high-affinity probe for F-actin Oregon Green® 488 phalloidin (1:100) (Molecular Probes, now Invitrogen, Eugene, OR, Cat. No. O7466) was added to the monolayers and incubated for 20 min and the monolayers were stained with nuclear-localizing dye DAPI (1.0 μg/mL) for 10 min at RT. The monolayers were then mounted using ProLong Gold® anti-fade reagent (Molecular Probes, Eugene, OR, Cat. No.P36934) and imaged by using a Zeiss 510 Meta confocal microscope.
GD3: ganglioside GM3 (Neu5Acα3Galβ4GlcCer); GM3: ganglioside GD3 (Neu5Acα8Neu5Acα3Galβ4GlcCer); hEBD LVEC: the human embryoid body derived LVEC cell line; IL-6: interleukin-6; LacCer: lactosylceramide (Galβ4GlcCer); NEU3: neuramindase 3; qRT-PCR: quantitative real-time polymerase chain reaction; SD: standard deviation; SMF: static magnetic field(s); ST3GAL5: β-galactoside α-2,3-sialyltransferase 5; TLR4: toll-like receptor 4.
KJY was the principal investigator on this project, AS performed the microarray experiments and analysis, ZW designed, supervised, and carried out the majority of the cell, molecular, and biochemical assays performed in this study (P-LC provided substantial assistance in the design and execution of these experiments).
Annotation of the signaling networks identified to respond to SMF exposure in hEBD LVEC cells. The Ingenuity Pathway Analysis software tool was used to annotate the networks listed in Table Table55 and the resulting diagrams are provided in Figures S1 through S9 (corresponding to ID#1–9, respectively).
Description of the SMF treatment device. The device used to treat cells with 0.23 to 0.28 T static magnetic fields is shown (in Figure S10) along with field orientation and strength.
Funding for the bulk of this project was provided by Arnold and Mabel Beckman Foundation with the analysis of IL-6-mediated and ganglioside-associated responses funded the National Institutes of Health (NIBIB, grant 5R01EB5692). The hEDB LVEC cell line was generously donated by Michael Shamblott (JHMI). We are grateful for technical assistance with the microarray experiments and pathway analysis from Conover Talbot (JHMI Microarray Core Facility), for helpful discussions with Wayne Bonlie, and for the gift of the magnetic treatment device from AMRI International (Calgary, AB).