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. 2025 Feb 18;61(4):e70023. doi: 10.1111/ejn.70023

Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field Technology (ELF‐EMF) Sculpts Microtubules

Alexandra Lobyntseva 1, Maram Ganaiem 1, Yanina Ivashko‐Pachima 1, Colin J Barnstable 2, Batsheva Weisinger 3, Ana Parabucki 3, Yaron Segal 3, Esther Shohami 4, Illana Gozes 1,✉
PMCID: PMC11835790  PMID: 39966100

ABSTRACT

Aberrant microtubule dynamics coupled with a reduction in Tau‐microtubule interaction are at the core of neuronal injuries resulting in microtubule disruption and aggregates of abnormally phosphorylated Tau. These pathological Tau aggregates define tauopathies such as Alzheimer's disease (ad), as well as the pathological sequelae following traumatic brain injury (TBI), stroke and spinal cord injury (SCI). We hypothesized that differential applications of extremely low‐frequency and low‐intensity electromagnetic field (ELF‐EMF) will change microtubule function. To examine our hypothesis, we pre‐applied ELF‐EMF to a neuroblastoma neuronal cell line later exposed to 4 h of zinc intoxication, modelling Tau‐microtubule dissociation. ELF‐EMF (40 Hz and 1 G; multiple exposure schedules) enhanced microtubule dynamics and increased Tau‐microtubule interaction in the face of zinc toxicity. Complementing these preconditioning neuroprotective effects, concomitant 1 h treatment protocols comparing 3.9 or 40 Hz and 1 G exposure, indicated effects on Tau phosphorylation accentuated with 40 Hz and reduction in beta tubulin isotypes, depending on electromagnetic frequencies, most pronounced at 3.9 Hz. Our results discovered ELF‐EMF modulation on the microtubule cytoskeleton essential for brain health.

Keywords: ELF‐EMF, FRAP, live cell imaging, microtubules (MTs), tau, tubulin microheterogeneity, zinc

Frequency‐specific effects of extremely low frequency and low intensity electromagnetic field (ELF‐EMF) on microtubule dynamics and stability is shown in a schematic overview.

graphic file with name EJN-61-0-g001.jpg

Abbreviations

ad

Alzheimer's disease

Cont

control

Hz

hertz

hr

hour

ECL

enhanced chemiluminescence

ELF‐EMF

extremely low‐frequency and low‐intensity electromagnetic field

FRAP

fluorescence recovery after photobleaching

MT

microtubule

MAP

microtubule associated protein

EB

microtubule end binding protein

P

MT‐associated tubulin

rcf

relative centrifugal force

S

soluble tubulin

SCI

spinal cord injury

TBI

traumatic brain injury

Zn

zinc

1. Introduction

Over the past two decades, noninvasive brain stimulation (NIBS) techniques have significantly advanced the field of neuro‐recovery (Weisinger et al. 2022), demonstrating the ability to facilitate motor recovery via processes that are thought to influence neuronal plasticity. As a subset of NIBS, there is growing evidence suggesting that extremely low‐frequency (0–300 Hz) and low‐intensity (< 100 G) electromagnetic fields (ELF‐EMF) may be related to promoting neurological recovery (Weisinger et al. 2022). Indeed, a recent clinical study employing frequency‐tuned electromagnetic field therapy revealed improved motor function post ischemic stroke (Weisinger et al. 2022). Although ELF‐EMF are not responsible for direct induction of action potentials, a growing body of evidence indicates their ability to modulate various related biological events involved in neurological disease and recovery, including axon outgrowth and synaptogenesis (Dufor et al. 2019), neurogenesis (Piacentini et al. 2008; Cuccurazzu et al. 2010; Gao et al. 2021), apoptosis (Fanelli et al. 1999), inflammation and oxidative stress response (Vincenzi et al. 2017; Patruno et al. 2020), among others. Regardless, despite accumulating evidence of benefit for ELF‐EMF treatments for a variety of neurological and neurodegenerative conditions, including both preclinical (Park et al. 2008; Raus et al. 2013; Segal et al. 2016; Sherrard et al. 2018; Okabe et al. 2023) and clinical studies (Cichon et al. 2017a; Cichon et al. 2017b; Cichon et al. 2018; Cichon et al. 2020; Weisinger et al. 2022), the mechanistic pathways involved have yet to be fully elucidated.

Electromagnetic brain stimulation affects neuronal connectivity, which, from a neurochemical and mechanistic point of view, brings microtubules (MTs) into focus. Briefly, MTs constitute an essential part of the neuronal cytoskeleton, with MT dynamics and integrity being critical for axonal transport and synaptic transmission (Witte, Neukirchen, and Bradke 2008). The most broadly known MT‐associated protein (MAP) is Tau (or MAPT), which is widely expressed in neurons, and serves as an axonal marker (Trojanowski et al. 1989; Lee et al. 1991). Tau directly interacts with MT end‐binding proteins (EBs) (Honnappa et al. 2009). EBs, referred to as part of the MT plus‐end tracking protein (+TIPs) family, strongly decorate freshly polymerized MT plus‐ends (Seetapun et al. 2012) and can directly affect MT dynamics (Mohan et al. 2013). EB1, EB2 and EB3 represent the three mammalian end‐binding proteins (Gouveia and Akhmanova 2010). EB1 and EB3 together generate protein homo‐ and heterodimers, a crucial feature required for the plus‐end tracking behaviour of the EBs (Sen et al. 2013). Furthermore, Tau directly associates with EB1 and EB3 and modulates their localization on the MTs (Sayas et al. 2015). Tau stimulates MT assembly, and physiological and biochemical impairments of Tau have been investigated extensively in a variety of neurodegenerative diseases, referred to as tauopathies (Kneynsberg et al. 2017). We have previously established a successful assessment of single‐cell time‐lapse imaging allowing the examination of Tau‐MT interactions by fluorescence recovery after photobleaching (FRAP) (Ivashko‐Pachima et al. 2019a; Ivashko‐Pachima, Maor‐Nof, and Gozes 2019b). The fluorescence recovery of mCherry‐tagged Tau‐bleached region of interest (ROI) identifies the immobile fractions of bleached molecules which do not release binding sites on MTs for incoming un‐bleached mCherry‐Tau proteins and thus do not contribute to the fluorescence recovery. Accordingly, the immobile mCherry‐Tau fraction reflects the rate of the Tau association with MTs (Nouar et al. 2013). We have further adapted assays assessing the MT subunit tubulin distribution between polymerized and depolymerized MTs (Ivashko‐Pachima and Gozes 2019). Importantly, the MT heterodimer composed of alpha and beta tubulin subunits displays multiple isotypes (microheterogenicity), at the single neuron level (Gozes and Sweadner 1981). Tubulin microheterogenicity (isotype number) increases with brain development (Gozes and Littauer 1978) and is thus associated with brain plasticity. Here, we asked if ELF‐EMF affects tubulin microheterogenicity in the face of neurotoxicity.

Our previous publications have shown significant effects of zinc on Tau‐MT interactions, with excess zinc leading to cell toxicity and death (Oz et al. 2014), an effect which the enhancement of Tau‐MT interactions can protect against (Oz, Ivashko‐Pachima, and Gozes 2012; Ivashko‐Pachima et al. 2017; Ivashko‐Pachima and Gozes 2018, 2019; Ivashko‐Pachima et al. 2019a). Zinc, an essential trace element, plays important roles in the central nervous system (Marger, Schubert, and Bertrand 2014). Zn2+ is abundant in many, but not all, glutamatergic nerve terminals and is released upon neuronal activity (Sensi et al. 2009). Zinc homeostasis is crucial for the control of physiological brain function, and its dyshomeostasis has been implicated in multiple pathophysiological conditions (Sensi et al. 2009; Prakash, Bharti, and Majeed 2015) such as epilepsy (Sensi et al. 2009; Saghazadeh et al. 2015; Doboszewska et al. 2019), ischemia (Tonder et al. 1990; Koh et al. 1996; Jalali‐Yazdi et al. 2018), seizures (Saghazadeh et al. 2015; Li et al. 2017), brain trauma (Jorge and Starkstein 2005; Morris and Levenson 2013) and stroke (Elitt, Fahrni, and Rosenberg 2019). Excess neuronal zinc accumulation after brain injuries leads to neurotoxicity (Zhao et al. 2014; Pan et al. 2015; Qi et al. 2016). For example, synaptically released zinc is increased upon traumatic brain injury (TBI) in the hippocampus of rats (Zhu et al. 2009) and excessive release of zinc from excitatory synaptic vesicles is involved in the pathophysiological processes of TBI (Li et al. 2010; Sun et al. 2013; Zhao et al. 2018; Isaev, Stelmashook, and Genrikhs 2020). Furthermore, Zn2+ dyshomeostasis has been implicated in stroke as well as spinal cord injury (SCI) (Elitt, Fahrni, and Rosenberg 2019), a double‐edged sword with optimal protective concentrations (Heller et al. 2020).

Potential mechanisms of neuronal damage and death induced by excess zinc after brain injury involve an increase in reactive oxygen species (Stork and Li 2016), mitochondrial disruption (Weiss, Sensi, and Koh 2000) and inflammation (Isaev, Stelmashook, and Genrikhs 2020). A recent review (Isaev, Stelmashook, and Genrikhs 2020) expands the above list of diseases with Zn2+ homeostasis disruption‐associated pathophysiology in the brain adding amyotrophic lateral sclerosis (ALS), Wilson's, Creutzfeldt‐Jakob, Parkinson's and Alzheimer's diseases (ad). Furthermore, it is possible that TBI is a risk factor for the development of ad (Isaev, Stelmashook, and Genrikhs 2020). Disruptions of Zn2+ homeostasis play an important role in the mechanisms of pathogenesis of both TBI and ad. There is a synergistic toxic effect of Zn2+ ions on the mitochondria of neurons, and Zn2+ interacts with β‐amyloid (Abeta) and Tau (Isaev, Stelmashook, and Genrikhs 2020). Importantly, the risk of developing cognitive dysfunction after stroke, including mild cognitive impairment, is as high as 80% and is further linked with the development of tauopathy (Back et al. 2020), with increasing tauopathy paralleling cognitive decline (Franzmeier et al. 2020). Furthermore, SCI has also been associated with tauopathy, potentially presenting an early biomarker for disease spreading (Nakhjiri et al. 2020).

Though it is known that the effects of ELF‐EMF can vary greatly depending on the frequency (Loo et al. 2003; Dufor et al. 2019; Wang et al. 2020) and intensity (Moretti and Rodger 2022) of stimulation, such systematic studies of exposure parameters have not yet been conducted. Here, we discovered that the introduction of low‐frequency (3.9 Hz, 1 G) ELF‐EMF in neuron‐like cultures significantly affected beta tubulin distribution in the face of zinc toxicity. Electromagnetic field pre‐exposure of neuron‐like cell cultures to 40 Hz enhanced MT dynamics and minimized zinc disruption of Tau‐MT interactions.

2. Materials and Methods

2.1. Cell Culture

As previously described (Ivashko‐Pachima et al. 2017), mouse neuroblastoma N1E‐115 cell clones (ATCC, Bethesda, MD) were maintained in a standard medium containing Dulbecco's modified Eagle's medium, 10% foetal bovine serum, 2‐mM glutamine and 100 U/mL penicillin, 100 mg/mL streptomycin (Biological Industries, Beit Haemek, Israel). The cells were incubated in 95% air/5% CO2 in a humidified incubator at 37 °C. N1E‐115 cells were differentiated into neuron‐like cells upon transfer into a reduced medium containing fetal bovine serum (2%) and DMSO (1.25%) for 7 days.

2.2. Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field

ELF‐EMF exposure set‐up was composed of two main parts: a circular horizontal coil (18 cm in diameter, 50 turns of copper wire) and a waveform generator with built in amplifier (BK Precision, Yorba Linda, CA, 4045B). The homogeneity of the magnetic field to which cell cultures were exposed was confirmed by an oscilloscope (Hantek, Qingdao, China, DSO5072P) and probe (85 mm in diameter, 730 rounds; induction of 87 microhenry). The coil was placed in the humidified 37°C incubator (95% air/5% CO2 controlled environment, Figure 1) and shielded from external field interactions. The control cell plates (without ELF‐EMF exposure) were cultured under the same condition without exposure to the ELF‐EMF.

FIGURE 1.

FIGURE 1

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A representation of the equipment used to stimulate cell by ELF‐EMF, 1 G and a choice of frequencies (please see text for the complete methodology).

2.3. Microtubule Dynamics

Plasmids expressing mCherry‐EB1 protein (Ivashko‐Pachima et al. 2017) were previously constructed (Oz et al. 2014). Mouse neuroblastoma N1E‐115 cells differentiated as above were transfected with EB1‐red fluorescence protein (Ivashko‐Pachima et al. 2017) expressing plasmids, 48 h before the day of experimentation (Ivashko‐Pachima et al. 2017). Cells were then exposed to the electromagnetic field of 40 Hz and 1 G in the following four different schedules: ‘10 min (24 h)’—double exposure for 10 min: 24 h before the live imaging assessment experiment and on the day of the experiment; ‘1 h (24 h)’—double exposure for 1 h: 24 h before the experiment and on the day of the experiment; ‘10 min (48 h)’—three times of exposure for 10 min: 48 h and 24 h before the experiment and on the day of the experiment; ‘1 h (48 h)’—three times of exposure for 1 h: 48 h and 24 h before the experiment and on the day of the experiment, as illustrated in Figure 2.

FIGURE 2.

FIGURE 2

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A diagrammatic representation of the live imaging MT dynamics experimental design. See text for further details. Notably, MT dynamics was not tested under zinc intoxication and control cells were similarly handled as cells exposed to electromagnetic field stimulation.

Live cell imaging was performed by confocal microscopy (Leica SP8, x63 oil lens). Time‐lapse images were automatically captured every 3 min during a 4 h period using the Leica LAS AF software. The data were collected and analysed by Imaris software. MT dynamicity was evaluated by tracking EB1 proteins, which bind to dynamic plus‐ends of MTs. ‘EB1 Track Length’ reflects the extension of the individual MT polymers and ‘EB1 Comet Speed’ reflects the speed of the MT extension (i.e., MT polymerization). These two parameters describe the MT dynamics (Ivashko‐Pachima et al. 2017).

2.4. Tau‐Microtubule Interactions

To assess the effect of ELF‐EMF on Tau‐MT interaction, we utilized fluorescence recovery after photobleaching (FRAP) assay (Schröder 2013) using zinc (400 μM) as a Tau‐MT dissociation agent (Craddock et al. 2012; Huang et al. 2014). Differentiated N1E‐115 cells were transfected with a plasmid expressing mCherry‐tagged Tau protein, and FRAP imaging was performed after 4 h of cell exposure to zinc (Ivashko‐Pachima and Gozes 2019; Ivashko‐Pachima et al. 2019a). Pretreatments with ELF‐EMF (40 Hz and 1 G) were performed as above (Figure 2) or concomitantly with 1 h zinc treatment. MT regions decorated by mCherry‐Tau were bleached. Fluorescence recovery data values after bleaching were automatically collected by the Leica LAS AF software (120 images every 0.742 s). Fluorescence intensities were measured by ImageJ Fiji (Schindelin et al. 2012). Fluorescence signals were quantified with ImageJ (NIH), obtained data were normalized with easyFRAP (Rapsomaniki et al. 2012), and FRAP recovery curves were fitted by a two‐phase exponential association function using GraphPad Prism 6 (GraphPad software, Inc., La Jolla, CA). It should be noted that live cell imaging and immunocytochemistry techniques are well established in our laboratory protocols (Hadar et al. 2021; Ganaiem et al. 2022).

2.5. Biochemical Separation of Soluble and Microtubule Associated Tubulin and tau

Quantification of tubulin polymerization utilized previously described techniques (Oz, Ivashko‐Pachima, and Gozes 2012; Oz et al. 2014; Ivashko‐Pachima et al. 2017; Ivashko‐Pachima and Gozes 2018, 2019). Briefly, N1E‐115 cells (as above) were plated on 35 mm dishes (81156, 60 μ‐Dish, Ibidi, Martinsried, Germany) at a concentration of 0.3 × 106 cells/2 mL dish and then differentiated with reduced FBS (2%) and DMSO (1.25%) containing medium for 1 week. Zinc was added to the treated plates at a concentration of 400 μM for 1 h; control plates were not treated with zinc (as above in Section 2.4). Incubation was for 1 h for Tau‐tubulin‐MT interactions, in the presence or absence of concomitant ELF‐EMF treatment, 40 or 3.9 Hz, 1 G.

To extract soluble tubulin (S) as well as MT‐associated tubulin (P) (Oz, Ivashko‐Pachima, and Gozes 2012; Ivashko‐Pachima and Gozes 2019), differentiated N1E‐115 cells were subjected to trypsin (5 min) followed by 195 rcf centrifugation and exposure to MT‐buffer (80‐mM PIPES pH 6.8, 1‐mM MgCl2, 2‐mM EGTA, 5% glycerol) at room temperature. After gentle removal of the MT buffer, this procedure was followed by the addition of another aliquot of the MT‐buffer (150 μL) containing 0.5% TritonX‐100 for 5 min while centrifuging at 300 rcf. The resulting supernatant was deemed the soluble tubulin (S) fraction. Pelleted cells were washed once again with equal volume (150 μL) of modified RIPA buffer (50 mM Tris–HCl pH 7.4, 150 mM NaCl, 2 M EGTA, 1% TritonX‐100, 0.1% SDS, 0.1% sodium deoxycholate, protease and phosphatase inhibitors: 1‐mM phenylmethylsulfonyl‐fluoride (PMSF), leupeptin 25 μg/mL, pepstatin 25 μg/mL, Na3VO4 1 mM, NaF 20 mM) at 40°C for 1 h with shaking and then pelleted (40°C, ~18,000 rcf, 10 min). The pellet (cell debris) was discarded, whereas the remaining supernatant represented the polymerized (P) tubulin fraction. The S and P samples were each mixed with the same amount of sample buffer (10‐mM Tris–HCl, pH 6.8, 1.5% SDS, 0.6% DTT and 6% (v/v) glycerol) and heated at 95°C for 5 min. An equal volume of each fraction was analysed by immunoblotting (western blot analysis) with appropriate antibodies (Table 1).

TABLE 1.

Antibodies.

Primary Antibody name (catalogue number) Company (or reference) + dilution
Mouse monoclonal neuronal β‐tubulin‐preferring TUB2.1 (Gozes and Barnstable 1982; Boss, Gozes, and Cowan 1987) (Gozes and Barnstable Stock) (1:100)
Mouse monoclonal α‐β‐tubulin TUB2.5 (Gozes and Barnstable 1982) (Gozes and Barnstable Stock) (1:400)
Mouse monoclonal α‐tubulin T6199 Sigma‐Aldrich, Saint Louis, MO, USA (1:1000)
Rabbit polyclonal phosphorylated Tau (sc32828) Santa Cruz Biotechnology, Dallas, TX, USA (1:1000)
Mouse IgG1 isotype polyclonal Tau antibodies (ahb0042) Thermo Fisher Scientific, Eugene, OR, USA (1:1000)
Mouse monoclonal actin (ab3280) Abcam, Boston MA, USA (1:1000)
Secondary Antibody name (catalogue number) Company + dilution
Peroxidase‐conjugated AffiniPure goat anti‐mouse IgG #1706516 Jackson, Hamburg, Germany (1:5000)
Peroxidase‐conjugated goat anti‐rabbit IgG (ab205718) Abcam, Boston MA, USA (1:5000)
Goat anti‐mouse Alexa Fluor 488‐conjugated (for immunocytochemistry, Section 2.6) (A11001) Invitrogen by Thermo Fisher Scientific, Eugene, OR, USA (1:500)
Anti‐rabbit Alexa Fluor 546‐conjugated (for immunocytochemistry, Section 2.6) (A11010) Invitrogen by Thermo Fisher Scientific, Eugene, OR, USA (1:500)
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For molecular weight determination, we used the markers delineated in: https://bio‐helix.com/products/23 or https://www.biobasic.com/two‐color‐prestained‐protein‐ladder. The results following enhanced chemiluminescence (ECL) development (Pierce Biotechnology, Rockford, IL, # 32106) were quantified by densitometry using ImageJ Fiji software (2.9.0, 2022; National Institutes of Health, Bethesda, MD, USA) using WEB‐based instructions: How to quantify gel bands in imageJ | common quantification mistake ‐ YouTube and https://www.yorku.ca/yisheng/Internal/Protocols/ImageJ.pdf.

2.6. Immunocytochemistry

Cells were plated on 24‐well plates at a concentration of 25 × 104 cells per well. After 7 days with differentiated medium, cells were treated with zinc (400 μM), or ELF‐EMF(40 or 3.9 Hz, 1 G) or ELF‐EMF + zinc for 1 h. Cells were then fixed and immunostained with mouse monoclonal tubulin antibodies (TUB2.1) and rabbit polyclonal antibodies against phosphorylated Tau (diluted 1:100), followed by incubation with goat anti‐mouse Alexa Fluor 488‐conjugated antibodies or Anti‐rabbit Alexa Fluor 546‐conjugated as previously performed (Ganaiem et al. 2022; Ganaiem et al. 2023). Confocal microscopy was carried out as described in the live cell imaging section above. The tubulin and phosphrylated Tau intensity in the cells was measured using ImageJ Fiji software (2.9.0, 2022) (National Institutes of Health, Bethesda, MD, USA) as above. Overall, 250–320 cells (1024 × 1024 pixels/image) were analysed.

2.7. Statistical Considerations

Statistical analyses are outlined per experimental paradigm in the appropriate figure legend. In general, one‐way ANOVA followed by Tukey's honestly significant difference (HSD). Student's t‐test was employed to analyse differences between two groups. Original analysis was by IBM SPSS (version 23, IBM, Armonk, NY, USA). Most results shown used GraphPad Prism 8 (GraphPad Software, Inc., La Jolla, CA).

3. Results

3.1. Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field Pretreatment Stimulates Microtubule Dynamics

Using the previously established MT dynamics live cell imaging system, we found that timed pre‐exposure (Figure 2) to ELF‐EMF (40 Hz, 1 G) enhanced MT dynamics. Specifically, control (Figure 3A) and ELF‐EMF‐pretreatment (Figure 3B) depict selected live imaging microscopy images delineating red fluorescent EB1 comets (EB1‐RFP, left hand side) and tracked comet length (right hand side). Figure 3C shows the quantification of three independent experiments for EB1 comet tracks' length, indicating that the effect was limited to the 10 min (48 h) treatment, namely three 10 min ELF‐EMF pre‐exposures 48 h, 24 h and just prior to live imaging. A more robust effect was measured on EB1 comet speed, further including a 1 h exposure at the above‐mentioned times, named 1 h (48 h), as well as 10 min exposure at 24 h and at 10 min prior to live imaging, 10 min (24 h), (Figure 3D).

FIGURE 3.

FIGURE 3

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MT dynamics were measured by live cell imaging. Experiments were performed as described in Section 2, with experimental design outlined in Figure 2, including timed 10 min pre‐live imaging exposures to ELF‐EMF (40 Hz, 1 G). Three independent experiments were performed with at least 10 samples for each tested group per experiment. (A, B) Immunofluorescence images and fluorescent tracking; (C, D) statistical analyses including one‐way ANOVA (Tukey's HSD). Control (Cont) n = 37; 10 min (24 h) n = 36; 1 h (24 h) n = 38; 10 min (48 h) n = 44; 1 h (48 h) n = 36; **p < 0.01, ***p < 0.001. Results are shown as means ± SEM. The n reported is the number of fields evaluated for the three independent biological repeats, each including a similar number of technical repeats.

3.2. Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field Pretreatment Enhances Tau‐Microtubule Interactions

Using a different and complementary experimental paradigm to the study of MT dynamics (Figure 3) and employing our previously established Tau‐MT FRAP assay in live cells (Section 2.4), we have now shown that pre‐exposure to ELF‐EMF (40 Hz, 1 G, Figure 2) enhanced Tau‐MT interaction. Figure 4 depicts recovery results from the exchange of MT‐bound Tau (carrying bleached mCherry molecules) by free unbound Tau proteins (carrying unbleached mCherry molecules). Thus, an unrecovered fraction of the initial mCherry fluorescence within a given bleached area (Figure 4A, marked squares) indicates the immobile fraction of mCherry‐Tau proteins, reflecting Tau interaction with MTs. Subsequent analysis of the data with a one‐phase exponential association (Figure 4B,C) showed that zinc significantly abated the Tau immobile fraction in comparison to the nontreated control, and pretreatments with ELF‐EMF prevented excessive zinc‐induced Tau release from MTs, at all tested conditions.

FIGURE 4.

FIGURE 4

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Tau‐MT interactions measured by FRAP. Experiments were performed as described in Section 2.4, with experimental design outlined in Figure 2. (A) Marked squares ‘pre‐bleaching’, at bleaching (0′) and recovery (‘after‐bleaching’ at 88′) of mCherry fluorescence intensity were collected and analysed. Fluorescence recovery data values after bleaching were automatically collected (120 images every 0.742 s) by the Leica LAS TCS SP8 Confocal Microscope software. Fluorescence intensities were measured by ImageJ Fiji (Schindelin et al. 2012). Values were normalized with easyFRAP software (Rapsomaniki et al. 2012). FRAP recovery results fitted by a one‐phase association function and recovery curves (B) were built using GraphPad Prism 8 (GraphPad Software, Inc., La Jolla, CA). Samples with R 2 < 0.8 (linear regression) were excluded. The bar graph (C) represents the fitted data (by one‐phase exponential association) of the immobile fractions (collected at 88′ after photobleaching). Statistical analysis was performed by one‐way ANOVA with Tukey's HSD. Statistical significance is presented *p < 0.05, **p < 0.01. Cont., n = 31; Zn400μM, n = 35; Zn400μM + EMF 10 min (24 h), n = 52; Zn400μM + EMF 10 min (48 h), n = 42; Zn400μM + EMF 1 h (24 h), n = 49; Zn400μM + EMF 1 h (48 h), n = 32. Results are shown as means ± SEM. The n reported is the number of fields evaluated for the three independent biological repeats, each with a similar number of technical repeats. Statistical significance for Zn toxicity (Zn versus Control = Cont) was established by Student's t‐test, *p < 0.05, red asterisk. The apparently insignificant trending effect at 1 h (24 h) may be trivial, as this time point did not differ from control, as well as all other EMF treatments.

3.3. Short Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field Cotreatment Does Not Seem to Affect Tau‐MT Interactions

To assess the therapeutic effects of ELF‐EMF we reverted to 1 h zinc concomitant with ELF‐EMF treatment, complementing the ELF‐EMF pretreatment and 4 h zinc incubation (Figure 5A–C). FRAP results showed that the 1 h incubation with zinc was insufficient for Tau removal from the MTs. Surprisingly, albeit with a limited number of samples, under these conditions, zinc slightly enhanced Tau‐MT interactions, whereas concomitant ELF‐EMF did not make a difference (Figure 5C).

FIGURE 5.

FIGURE 5

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Tau‐MT interactions measured by FRAP. (A) Marked squares indicate the prebleaching area, bleaching (at 0′) and recovery (‘after‐bleaching’ at 88′) of mCherry fluorescence intensity were collected and analysed. Fluorescence recovery data values after bleaching were automatically collected as above. (B) FRAP recovery results fitted by a one‐phase association function, and recovery curves were built using GraphPad Prism 8 (GraphPad Software, Inc., La Jolla, CA). Samples with R 2 < 0.8 were excluded. The graph (C) represents the fitted data (by one‐phase exponential association) of the immobile fractions (collected on 88′ after photobleaching). Statistical analysis was performed by one‐way ANOVA with post‐hoc Tukey's HSD. Statistical significance is presented. *p < 0.05, Cont., n = 15; Zn400uM, n = 18; Zn400uM + EMF 1 h, n = 13; F (2, 42) = 3.750.

3.4. Short Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field Treatment at 40 Hz and 1 G Reduces Tau Phosphorylation in the Microtubule Pellet

A 1‐h ELF‐EMF pretreatment was sufficient to exert MT prophylactic effects (Figures 3 and 4) while presenting an insufficient time for the Tau‐MT interaction to reach an equilibrium (Figure 5), as opposed to 4 h as utilized previously in FRAP analysis (Figure 4). Thus, we continued with 1‐h zinc treatment and biochemical fractionations (Section 2.5) for further insights regarding short‐term zinc exposure, looking at Tau interaction with the soluble tubulin (S) and the polymerized MTs (P). Although our results did not show an effect on total Tau distribution (Figure 6A), in agreement with Figure 5 data, a significant reduction in phosphorylated Tau was observed after 1‐h zinc treatment with concomitant exposure to 40 Hz (Hz) and 1 G ELF‐EMF (Figure 6B). Questioning if the observed effect could be reproduced by reduced exposure to 3.9 Hz, 1 G ELF‐EMF, we repeated the experiment, showing no effect (Figure 6C).

FIGURE 6.

FIGURE 6

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ELF‐EMF at 40 Hz reduces Tau hyperphosphorylation. (A) Gel electrophoresis and western blot analyses were performed as described in Section 2.5, with ELF‐EMF exposure of 40 Hz, 1 G. An image of the blot probed by the antibodies (Section 2.5) is shown, p‐Tau = phosphorylated Tau. Actin was used as a control. (B) The graph shows % change in phosphorylated Tau (p‐Tau) in the MT pellet compared with control (no zinc, 100%) and further compared with actin in three independent experiments (A and Figure S1). Notably, the molecular weight of the different Tau species changes upon phosphorylation. Graphs used Prism (as above). Statistical analysis was performed by one‐way ANOVA with post‐hoc Tukey's HSD. Statistical significance is presented. *p < 0.05. (C) The experiment in A and B was repeated with 3.9 Hz, 1 G exposure. Please see Figure S2 for the blot images.

3.5. Beta Tubulin Isotype Reduction (TUB2.1) Is Observed After Extremely Low‐Frequency and Low‐Intensity Electromagnetic Field Treatment, Which Is Accentuated at 3.9 Hz and 1 G Exposure

Considering the pre‐exposure effects on MT dynamics, we evaluated the potential therapeutic effects of 40 Hz, 1 G on tubulin isotype distribution in the soluble and particulate tubulin/MT fractions in comparison to actin as an internal standard (Figure 7A, left panels, western blots). Results suggested that the 1‐h incubation with zinc resulted in a dramatic reduction in TUB2.1 immunoreactivity (detecting neuronal beta tubulin isotypes) (Gozes and Barnstable 1982; Boss, Gozes, and Cowan 1987) only in the particulate (polymerized) MT fraction, which was not resolved by concomitant 40 Hz 1 G treatment (Figure 7A). In contrast, the distribution of alpha tubulin species was not affected as depicted by specific antibodies (α‐tubulin) as well as by the TUB2.5 antibody recognizing both alpha and beta tubulins (Figure 7A left panel, TUB2.5).

FIGURE 7.

FIGURE 7

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(A) Gel electrophoresis and western blot analysis were performed as described in Section 2.5, evaluating different isotypes of tubulin immunoreactivity. Actin was used as a loading control. (B) Densitometric scanning of the TUB2.1 versus actin blots showed enriched beta tubulin isotype reduction (TUB2.1) after ELF‐EMF, which was accentuated in 3.9 Hz, 1 G exposure (three independent repeats, one shown above (upper panel). Two additional independent experimental repeats are shown in Figure S3). Lower panel B shows TUB2.1 versus actin immunoreactivity in the particulate fraction of the 3.9 Hz, 1 G exposure. Statistical analysis was performed by one‐way ANOVA with post‐hoc Tukey's HSD. Statistical significance: **p < 0.01, ***p < 0.001.

We then tested the hypothesis that diverse ELF‐EMF conditions will differentially affect tubulin polymerization and resorted to 3.9 Hz 1 G ELF‐EMF in this paradigm of 1‐h zinc intoxication and concomitant ELF‐EMF exposure (Figure 7A right panels). No dramatic effect was observed on alpha tubulin, whereas some reduction in soluble TUB2.5 immunoreactivity was noted upon zinc exposure and ELF‐EMF treatment (Figure 7A right panels). Furthermore, our data showed significant reduction in TUB2.1 reactive tubulin species (preferring neuronal beta tubulin) (Gozes and Barnstable 1982; Boss, Gozes, and Cowan 1987; Divinski et al. 2006) upon 1 h zinc intoxication coupled with further reduction with ELF‐EMF (Figure 7B, upper panel). Given the significant change in soluble TUB2.1 immunoreactivity in the soluble fraction (which was specific for 3.9 Hz 1 G ELF‐EMF and hence further evaluated), we also looked for significant changes in the particulate tubulin fraction, revealing great variability and no significant change (Figure 7B, lower panel).

The biochemical analyses were complemented by immunocytochemistry, further looking for the direct effects of ELF‐EMF. Total phosphorylated Tau cellular staining after 1‐h incubation with zinc did not change (Figure 8), in agreement with the biochemical results (Figure 6). ELF‐EMF treatment (w/o zinc), 1 G, 3.9 Hz, slightly, but significantly increased Tau phosphorylation, whereas the 1 G, 40 Hz condition did not significantly differ from control but showed decreased phosphorylated Tau staining compared with the 1 G, 3.9 Hz incubation. The co‐incubation with ELF‐EMF and zinc 3.9 Hz further reduced phosphorylated Tau staining (Figure 8), contrasting the 40 Hz treatment, which showed some increase compared with zinc alone or 40 Hz alone, but not differing from control. At the tubulin level (TUB2.1), a reduction was seen in all conditions except for 1 G, 40 Hz + Zinc (Figure 8) also showing a direct ELF‐EMF effect (w/o zinc).

FIGURE 8.

FIGURE 8

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Phospho‐Tau immunostaining (upper panel) was performed as described in Section 2.6. Tubulin (TUB2.1) immunocytochemistry was similarly described in Section 2.6 (lower panel). The experiment was repeated four times. Righthand panels show the quantifications coupled to statistical analysis (Section 2.6).

4. Discussion

To the best of our knowledge, our results showed, for the first time, a significant effect of very low ELF‐EMF treatment on MT dynamics and Tau‐MT interaction. We further detected an apparent change in Tau phosphorylation coupled with differential effects on MT isotype distribution accentuated by frequency‐specific ELF‐EMF exposure. Indeed, we demonstrate here a change in tubulin alpha‐beta distribution in the MT versus soluble fractions resulting from electromagnetic stimulation. Our (IG) original discovery in 1978 (Gozes and Littauer 1978) revealed increased tubulin microheterogeneity (increase in the number of tubulin isotypes) with brain development, coupled with an overall decrease in tubulin amounts (Schmitt, Gozes, and Littauer 1977). These findings were extended to neuronal/glial specificity (Gozes, Saya, and Littauer 1979) and single neuron microheterogeneity (Gozes and Sweadner 1981) further implicating differential distribution of tubulin isotypes within neuronal compartments. The monoclonal antibodies (TUB2.1 and TUB2.5) developed by us (IG and CJB) (Gozes and Barnstable 1982), and used here, differentiate tubulin species. These antibodies were first indicative of beta tubulins that were increasing with brain development (Gozes and Littauer 1978) (e.g., the later named beta 3 tubulin) as neuronal specific (Boss, Gozes, and Cowan 1987). These original findings, reported more than 40 years ago, revealed tubulin in synapses (Gozes and Littauer 1979; Zisapel, Levi, and Gozes 1980) and in myelin structures (Gozes and Richter‐Landsberg 1978). Later independent studies extended the importance of tubulin isotypes and identified specific tubulinopathies (Leca et al. 2023; Zocchi et al. 2023). Our current results suggest that the change in tubulin content and microheterogeneity depends on electrical activity, providing a stimulus for brain development and regeneration. The effect of ELF‐EMF stimulation, to reduce TUB2.1 immunoreactivity, may be construed as a developmental process coupled to a priming, preconditioning effect (Sragovich et al. 2012), toward future recovery and regeneration, and paving the path for future studies of disease modification.

We have used three different systems to study MTs including live cell imaging, biochemical fractionations as well as immunocytochemistry of fixed cells. The differences between the immunocytochemical results and the biochemical fractionation data could be partially explained by the fact that the immunocytochemistry picks up all phosphorylated Tau species regardless of cellular fractionations as well as possibly non‐specific immunoreactive epitopes, which may be controlled by protein fractionation using Western analysis. Furthermore, the level of Tau phosphorylation and tubulin immunoreactivity (TUB2.1) was biochemically controlled by actin (Western analysis). The apparent differences between fixed and live cell imaging might be partly attributed to the nature of the studies proteins, directly linked with cellular shaping. Regardless, the direct effects of ELF‐EMF on the cytoskeleton, coupled to priming (preconditioning) together with frequency‐dependent effects are of basic as well as medical interest.

Our study limitations include a focus on MTs in a specific neuronal‐like cell line and biochemical evaluation after exposure to zinc excess, without venturing into diverse toxicities and additional mechanistic outcomes. However, we and many others have shown the deleterious effects of excess zinc on neurodegeneration much through MT disruption/reduction impacting neuronal survival (Koh et al. 1996; Divinski, Mittelman, and Gozes 2004; Marger, Schubert, and Bertrand 2014; Oz et al. 2014; Li et al. 2017; Jalali‐Yazdi et al. 2018; Isaev, Stelmashook, and Genrikhs 2020; Ivashko‐Pachima and Gozes 2021; Ganaiem et al. 2023), thus the modulation offered here is of biological significance. In this respect, focusing on zinc toxicity, future studies should aim at neurite‐cell body distribution (Konzack et al. 2007) in primary neurons (Divinski et al. 2006), different timelines, dose‐dependency and tubulin post‐translational modification. Indeed, following the original studies described above, it is now well established that both α‐tubulin and β‐tubulin are encoded by multiple genes with distinct expression profiles and functionality. MTs are further differentiated through posttranslational modifications, with the genetic and chemical diversity of tubulin constituting a code that regulates MT properties (McKenna et al. 2023). For example, the most characterized acetylation and methylation site on tubulin, involve the addition of an acetyl and methyl group, respectively, to lysine 40 in α‐tubulin (McKenna et al. 2023), furthermore, detyrosination involves the reversible removal of the terminal tyrosine from α‐tubulin, with all modifications affecting MT dynamics and stability (McKenna et al. 2023). In our case, we did not see a change in α‐tubulin distribution in MT versus soluble tubulin fraction following zinc and ELF‐EMF treatment regardless of the ELF‐EMF conditions used. This finding contrasted the significant effect on β‐tubulin reduction by ELF‐EMF seen here. In this respect, our (IG) original studies also did not see dramatic effects on α‐tubulin tyrosination during brain development, but significant increases in tubulin (emphasized β‐tubulin) microheterogeneity, which is most probably associated with multiple tubulin genes (Gozes and Littauer 1978), regulated by activity‐dependent gene expression (e.g., Amram et al. 2016). Furthermore, our results showed direct effects of ELF‐EMF on TUB2.1 immunostaining as well as preconditioning effects on MT dynamics, which is regulated by β‐tubulin guanosine triphosphate (GTP) capping and GTPase activity (de Forges, Bouissou, and Perez 2012).

The primary antibody used in our study to identify Tau phosphorylation (sc‐32828), is known to specifically recognize the Ser262 phosphorylation site, which is located within the KXGS motif of tau first repeat domain in the MT‐binding region (Chin et al. 2000). Notably, studies have demonstrated that phosphorylation at this site significantly influences Tau toxicity (Ikura et al. 1998). Although evidence suggests that Ser262 phosphorylation/dephosphorylation is not directly associated with Tau aggregation (Despres et al. 2017), it is a key factor in controlling Tau interaction with MTs (Haj‐Yahya et al. 2020). Furthermore, a recent article (Islam et al. 2025), implicates Ser262 and Ser356 as biomarkers of pre‐tangle soluble Tau assemblies in Alzheimer’s disease (AD). Thus, phosphorylation‐dephosphorylation at Ser262 interferes with Tau‐MT interactions and Tau toxicity. Importantly, it is crucial to acknowledge that other phosphorylation sites contribute to Tau deposition, though further research is required to fully elucidate their roles, priming effects to neurodegeneration/neuroprotection. Interestingly, disrupted metal (e.g., zinc) homeostasis is further suggested to contribute to Tau pathology, neurodegeneration (Juan, Daglas, and Adlard 2022).

Lastly, with cytoskeletal function intimately associated with neuromuscular junction function (e.g., Kapitansky et al. 2020), our findings here provide mechanistic insights for the results of the pilot randomized control study suggesting that frequency‐tuned electromagnetic field therapy improves poststroke motor function.

5. Conclusions

Our results revealed differential MT modulation of various electromagnetic frequencies on tubulin microheterogeneity, Tau phosphorylation, Tau‐MT interaction and MT dynamicity. Thus, frequency‐specific ELF‐EMF stimulation may be construed as providing brain plasticity, positioned as a plausible treatment for a variety of neurological and neurodegenerative conditions.

Author Contributions

Conceptualization: I.G., E.S., B.W., A.P.; methodology: I.G., Y.S., C.J.B. and Y.I‐P.; validation: A.L., M.G. and Y.I‐P.; formal analysis: A.L., M.G., Y.I‐P. and I.G.; resources: I.G., C.J.B. and B.W., A.P., Y.S. and E.S., data curation: A.L., M.G., Y.I‐P and I.G.; writing–original draft preparation: I.G.; writing–review and editing: I.G., C.J.B., B.W., A.P., A.L.; visualization: A.L., M.G., Y.I‐P and I.G.; supervision: I.G.; project administration: I.G.; funding acquisition, I.G. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

A.L., M.G. and Y.I‐P. declare no conflict of interest. B.W., A.P. and Y.S. are employed by the study funder, BrainQ Technologies Ltd. E.S. and Y.S. have an ownership interest in BrainQ Technologies Ltd. I.G. serves as the VP Drug Development at ExoNavis Therapeutics Ltd.

Peer Review

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/ejn.70023.

Supporting information

Figure S1. (A, B) Two independent repeats of Figure 5A. (C) An enlargement of Bdepicting clearer protein bands. MW = molecular weight in kDalton. Please see material and methods section 2.4 for the different molecular weight (MW) markers used for all figures.

Figure S2. Three independent experimental repeats for Figure 5C. MW is marked as in Figure S1.

Figure S3. Two additional independent experimental repeats for Figure 6B.

EJN-61-0-s001.pdf (194.7KB, pdf)

Acknowledgements

Funders had no role in the performance of studies, analysis, or interpretation of data. We thank Arielle Hochberg and Shira Reznik Balter for help in developing methodology. We are grateful to Jenna Kirschner (M.Sc. student, Sagol School of Neuroscience) for her help in Figure 8's experiments. This work is in partial fulfilment of the PhD theses of AL and MG at Dr. Miriam and Sheldon G. Adelson School of Graduate Studies at the Faculty of Medical & Health Sciences.

Alexandra Lobyntseva, Maram Ganaiem and Yanina Ivashko‐Pachima contributed equally.

Funding: This work is funded by BrainQ Technologies Ltd. (collaboration contract with Ramot at Tel Aviv University). Research in Prof. Illana Gozes (IG) laboratory at Tel Aviv University is further supported by the Elton laboratory (IG, Director), Drs. Ronith & Armand Stemmer (French Friends of Tel Aviv University), Anne & Alex Cohen, Canadian Friends of Tel Aviv University & AMN Foundation. AL is supported by a Marie Skłodowska‐Curie TClock4AD fellowship aimed to discover pharmacological drugs that improve Alzheimer's disease disrupted circadian rhythmicity & student training (double doctorate degrees). Project#: 101072895, EUROPEAN RESEARCH EXECUTIVE AGENCY (REA) REA. MG is supported by a Neubauer Family Foundation Student Scholarship.

Associate Editor: Yan Zhang

Data Availability Statement

All data are presented here.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1. (A, B) Two independent repeats of Figure 5A. (C) An enlargement of Bdepicting clearer protein bands. MW = molecular weight in kDalton. Please see material and methods section 2.4 for the different molecular weight (MW) markers used for all figures.

Figure S2. Three independent experimental repeats for Figure 5C. MW is marked as in Figure S1.

Figure S3. Two additional independent experimental repeats for Figure 6B.

EJN-61-0-s001.pdf (194.7KB, pdf)

Data Availability Statement

All data are presented here.

Articles from The European Journal of Neuroscience are provided here courtesy of Wiley

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