Exploring Cellular Water Dynamics associated with Potassium Ion Changes Using Magnetic Resonance Imaging

Exploring Cellular Water Dynamics associated with Potassium Ion Changes Using Magnetic Resonance Imaging | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Exploring Cellular Water Dynamics associated with Potassium Ion Changes Using Magnetic Resonance Imaging View ORCID Profile Seong-Min Kim , Kyeongseon Min , Jung Seung Lee , Jang-Yeon Park doi: https://doi.org/10.1101/2025.06.25.661446 Seong-Min Kim 1 Department of Intelligence Precision Healthcare Convergence, Sungkyunkwan University , Suwon, Republic of Korea Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Seong-Min Kim Kyeongseon Min 2 Department of Electrical and Computer Engineering, Seoul National University , Seoul, Republic of Korea Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jung Seung Lee 1 Department of Intelligence Precision Healthcare Convergence, Sungkyunkwan University , Suwon, Republic of Korea 3 Department of Biomedical Engineering, Sungkyunkwan University , Suwon, Republic of Korea Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jang-Yeon Park 1 Department of Intelligence Precision Healthcare Convergence, Sungkyunkwan University , Suwon, Republic of Korea 3 Department of Biomedical Engineering, Sungkyunkwan University , Suwon, Republic of Korea Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Potassium ions play a critical role in modulating cellular physiology, but their direct effects on water dynamics have not been fully explored. Here, we investigated how elevated potassium ion concentrations ([K⁺]) alter intracellular and extracellular water pools in comparison to hypoosmotic stress, using T2 and magnetization transfer (MT) parameters in a close-packed T-lymphocyte cell pellet model. Our findings reveal that the T2 increase primarily reflects an increase in intracellular free water concentration rather than a mere expansion of cell volume. Notably, [K⁺] elevation produced distinct cell swelling profiles and a smaller relative rise in free water at comparable volumetric changes compared to hypoosmotic stress, highlighting more complex mechanisms than straightforward osmotic effects. While T2 proved sensitive to shifts in intracellular water content, the bound pool increased linearly with cell volume expansion. These results underscore that [K⁺]-driven cell swelling diverges functionally from osmotic- driven cell swelling and demonstrate the viability of MRI-based approaches for probing K⁺-dependent cellular events. Introduction Potassium ions play critical roles in cellular physiology, influencing numerous essential cellular processes, including signal transduction, volume regulation, and the maintenance of membrane potential 1 – 4 . Consequently, potassium ion modulation has been extensively employed in research aiming to elicit physiological responses and cellular alterations. As cellular processes predominantly occur within an aqueous environment, physiological phenomena resulting from changes in potassium ion concentrations ([K + ]) significantly affect water dynamics throughout biological systems. Water dynamics in biological contexts exhibit distinct states characterized by unique molecular behaviors and interactions 5 – 7 . Specifically, water can be categorized into dynamically slow interfacial water (or hydration layer), closely associated with macromolecular surfaces, and dynamically fast bulk-like free water, occupying most of the available intracellular and extracellular spaces 8 – 12 . Because both dynamically fast and slow water pools, together with the macromolecular components of cells, can undergo significant changes in a variety of physiological contexts 10 , 13 , 14 , elucidating their linked changes could shed light on how cells work and provide novel contrastive methods for spotting specific physiological events. Recent studies using methods such as Raman spectroscopy, second harmonic generation (SHG), nuclear magnetic resonance (NMR), fluorescence microscopy, and fluorescence spectroscopy have demonstrated that these distinct water pools and macromolecules respond differently to various physiological stimuli 14 – 18 . Notably, SHG studies have reported measurable signal changes due to the reorientation of interfacial water molecules induced by alterations in membrane potential 19 , 20 . Since membrane potential variations are frequently associated with changes in [K + ], these findings highlight that [K + ]-related physiological phenomena, such as membrane potential alterations, can markedly impact water dynamics at cellular interfaces. Among non-invasive imaging techniques, magnetic resonance imaging (MRI) - particularly quantitative magnetization transfer (MT) imaging - can effectively distinguish between free water pool and bound pool by examining the energy transfer dynamics between these pools 21 , 22 . Although MRI does not provide as high spatial resolution as optical microscopy, its non-invasive and wide-ranging imaging capabilities offer substantial practical advantages. MRI-based approaches thus hold considerable potential for monitoring physiological conditions through measurements of water dynamics, potentially providing novel insights into underlying cellular mechanisms in vivo . Previously, our group reported a measurable increase in the spin-spin interaction relaxation time (T2) and a decrease in one of the MT parameters, the pool size ratio (PSR, the ratio of bound to free water pools), in response to increasing [K + ] in both in vitro and in vivo conditions, demonstrating that these MRI parameters are sensitive to changes in cellular physiology 23 . Other studies demonstrated that the increase in T2 associated with cell swelling occurs from dilution effects 24 – 26 , which may also be interpreted in terms of their potential link to increased intracellular free water content. Additionally, some MT studies mentioned that the bound pool includes hydration layers and macromolecules 21 , 27 , 28 . In this study, we explored water dynamics in cellular processes associated with [K + ] changes using MRI. In particular, we attempted to explain the changes in T2 relaxation time and MT parameters in MRI induced by [K + ] changes in terms of cellular water dynamics based on intracellular structural modeling in vitro . In addition, we also investigated whether cell swelling due to [K + ] changes is the sole factor contributing to the changes in these MRI parameters, compared to cell swelling induced by changes in osmolarity as a control condition, and examined whether there were differences in water dynamics between [K+] elevation and hypoosmotic stress conditions. Results One-dimensional (1D) cell pellet imaging & mean cell volume measurements We used T-lymphocyte cells (or Jurkat) in pellet form, where the cells were modeled as close-packed spherical structures. To ensure stable cell volumes following cell volume regulation, sufficient stabilization time was allowed without compromising cell viability. Suspended cells were loaded into the perforated wells of an appropriately shaped acrylic phantom ( Figure 1a ). To induce cell swelling, cells were suspended in media prepared under hypoosmotic stress and [K + ] elevation for an hour. For hypoosmotic stress, additional osmotic concentrations of -10 mM, -20 mM, and -30 mM were added to the control media; for [K + ] elevation, [K + ] of 20 mM, 40 mM, and 80 mM were used. Download figure Open in new tab Figure 1. Acrylic phantom containing cells and MRI signals. a. Photo of a fabricated acrylic phantom with 7 wells. b. Illustration of the acrylic phantom containing cells in pellet form. Each well of the acrylic phantom contains T-lymphocyte cells (Jurkat) suspended under different conditions. Centrifugation was applied to pellet the cells. c. A series of 1D MR images for various echo times (TEs) with respect to position. d. Signal intensity profiles along the red solid line (left) and blue solid line (right) shown in c . Cells were centrifuged to form cell pellets, which were then prepared to a sufficient thickness (> 1 mm) after accumulating under different media conditions ( Figure 1b ). 1D imaging was performed to estimate MT and T2 across cell pellets in these different media. A multi-echo spin-echo sequence with variable echo times (TE) was used for T2 estimation, and Figure 1c shows the 1D images for different TEs. In Figure 1d , an example of 1D signal profile of cell pellets in media with different conditions, contained in separate wells, is shown in the position dimension (along the red solid arrow line in Figure 1c ), together with the signal intensities in the TE dimension (along the blue solid arrow line in Figure 1c ). To estimate cell volume expansion, microscopy images were acquired as shown in Figure 2a . Assuming a spherical cell shape, cell volume was calculated based on the measured cell radius. Figure 2b shows the cell volume distribution obtained by measuring the volume for each of 1,000 cells. These results demonstrate that both media prepared for elevated [K + ] and hypoosmotic stress conditions induced significant levels of cell swelling, leading to an expansion of the average cell volume (〈 V c 〉). Download figure Open in new tab Figure 2. Microscope image and cell volume distribution. a. Microscope image of the cells acquired at 20x magnification. The size of the scale bar at bottom left is 50 μm. b. Cell volume distribution displayed using a violin plot. The radius of each cell cross-section was measured in a to estimate the cell volume distribution. Changes in free water pool by cell swelling To understand cell water dynamics during cell swelling, MT parameters were measured using an inverse recovery multi-echo spin echo sequence. Free water and bound pools were expressed in terms of longitudinal magnetization at equilibrium state ( M f ,∞ and M 𝑏,∞ , respectively, defined in Eqs. [1] and [4] in Materials and Methods). To better understand what the estimated M f ,∞ represents in cell pellet conditions, we first modeled the cell pellet as a close-packed pellet structure as shown in Figure 3a . In this model, when cells expand, their geometric configuration with adjacent cells changes, reducing the number of cells per unit volume (cell density, ρ cell ). In addition, if the unit volume is sufficiently larger than the size of the cell expansion, the ratio of intracellular space per unit volume ( v i ) and the ratio of extracellular space per unit volume (1− v i ) remain constant regardless of changes in the cell volume 29 , 30 . Figure 3a illustrates the increase in average cell volume 〈 V c 〉 and the decrease in cell density ρ cell during cell swelling in a three-dimensional (3D) structure of unit volume. Figure 3b illustrates the two-dimensional (2D) cross section of Figure 3a , including the organelles (orange) inside the cell, before and after cell expansion. The yellow square box represents the boundary of the unit volume cross-section. To better illustrate the maintenance of v i (or 1− v i ) during cell swelling, Figure 3c combines Figures 3a and b , representing the spherical cell volume as a rectangular solid. Download figure Open in new tab Figure 3. Illustration of a close-packed model of cell pellet before (left) and after cell swelling (right). a. Close-packed spherical cell structure of unit volume. b. 2D cross-section including organelles of the 3D spherical cell structure. The yellow square box represents the boundary of the unit volume cross-section in a . It is well shown that after cell swelling, cell density decreases and the density of subcellular structures, including organelles and cell membranes, also decreases. c. Combination of a and b representing the spherical cell volume as a rectangular solid. While the number of cells per unit volume decreases, the intracellular and extracellular space fractions remain constant. As shown in Figure 3 , cell swelling leads not only to a decrease in ρ cell , but also to a decrease in the proportion of subcellular structures, including organelles and cell membranes, per unit volume. In this case, the intracellular space expands due to the influx of free water, and the concentration of intracellular free water pool also increases due to the fixed ratio of v i . This situation corresponds to a phenomenon called ‘dilution’ in previous studies reporting an increase in T2 during cell swelling 25 , 26 . On the other hand, for the extracellular space, since the media used to induce cell swelling in this study differ only in their ionic concentrations on the millimolar scale, it can be assumed that such minor variations would not significantly alter the concentration (or 1 H proton density) of the extracellular free water pool under different conditions. This assumption allows us to ignore concentration changes in the extracellular free water pool. Therefore, given that v i (or 1− v i ) remains constant in the close-packed cell pellet model during cell swelling, the change in M f ,∞ can be best explained by the change in the intracellular free water concentration. Figure 4a shows M f ,∞ evaluated from the data measured in the two conditions used to induce cell swelling, i.e., osmotic changes (ΔOsm) and [K + ] changes, respectively. A significant increase in M f ,∞ was observed in both cases of hypoosmotic stress and [K + ] elevation. In addition, as shown in Figure 4b , cell swelling under the two conditions revealed different relationships between M f ,∞ and 〈 V c 〉. Under hypoosmotic stress, the cell volume became saturated beyond a certain threshold, whereas M f ,∞ increased linearly. These observations can be understood from a cell physiology perspective. In other words, under hypotonic conditions, cells initially swell, but eventually partially recover their size over time through a process called regulatory volume decrease (RVD). Therefore, under high hypoosmotic stress for a sufficient period of time, cells ultimately maintain their volume due to RVD regardless of the degree of stress, whereas the intracellular free water pool concentration adjusts linearly to the external osmotic environment to maintain osmotic balance 33 . In contrast, as [K + ] increased, both cell volume and intracellular free water pool concentration increased linearly. These results may be because, unlike the hypotonic environment mentioned above, high [K + ] conditions do not induce a decrease in cell volume after swelling 1 , 32 , 34 , 35 . As with other ions and osmolytes, the influx or efflux of K + is accompanied by the influx or efflux of free water molecules, as the cell volume expands or contracts, respectively. In summary, these findings demonstrate that two different mechanisms, [K + ] changes and osmotic changes, have distinct trends in cell volume expansion and free water pool concentration changes, which can be measured and analyzed by MRI. Download figure Open in new tab Figure 4. Estimation of free-water pool changes based on quantitative MT and modeling. a. M f ,∞ changes under hypoosmotic stress (left) and [K + ] elevation (right) conditions (n 14 scans). M f ,∞ increased with statistical significance in both cases. b. 〈 V c 〉 changes with respect to M f ,∞ changes. 〈 V c 〉 increased as M f ,∞ increased, but the two conditions showed different trends. Under hypoosmotic stress, 〈 V c 〉 was saturated beyond a certain threshold, but increased linearly under [K + ] elevation. c . T2 changes with respect to M f ,∞ changes. In both cases, T2 increased linearly, but with a steeper slope under [K + ] elevation. The shaded ellipses represent the distribution of data points, with the major and minor axes corresponding to the variance obtained from the principal component analysis (PCA) of each data point. d . T2 changes with respect to 〈 V c 〉 changes. T2 increased linearly with increasing 〈 V c 〉, but under hypoosmotic stress conditions of -20mM and -30mM, a statistically significant difference in T2 was observed despite indistinguishable cell volume increase. Statistical significance was marked with asterisks (*: p < 0.05; **: p < 0.01; ***: p < 0.001). ( M f ,∞ : the longitudinal magnetization of free water pool at equilibrium state, 〈 V c 〉: average cell volume). Figure 4c shows that T2 increased linearly with increasing M f ,∞ in both cases of hypoosmotic stress and [K⁺] elevation, suggesting that the rise in intracellular free water concentration contributed to this T2 increase irrespective of the cell swelling mechanism. If the increase in free water within the intracellular space is regarded as intracellular dilution, this finding is consistent with previous studies. 25 , 26 . The contribution of bound pool to T2 increase may be negligible because bound pool is very localized and T2 is significantly shorter ( 8 ms). On the other hand, for the same level of M f ,∞ increase, elevation of [K+] resulted in a greater increase in T2 than hypoosmotic stress, indicating that the two cell-swelling mechanisms can lead to different T2 changes even at similar levels of intracellular dilution. Since increasing [K + ] resulted in a larger volume at comparable M f ,∞ levels ( Figure 4b ), the higher T2 when increasing [K + ] may be due to the relatively larger intracellular space per cell than when decreasing osmotic pressure (or under hypoosmotic stress). According to previous studies, T2 varies with the size of spatial restriction 36 – 39 , that is, in more open and spacious intracellular environments, T2 is larger than in dense and confined spaces. In summary, T2 changes differed by two different mechanisms, [K + ] changes and osmotic changes, and cell swelling due to increased [K + ] resulted in a larger T2 increase than cell swelling due to decreased osmotic pressure. Figure 4d shows how T2 changes vary with 〈 V c 〉. At the same 〈 V c 〉, the T2 increase under hypoosmotic stress was greater than that under [K + ] elevation. From a cellular physiological perspective, this may be explained by RVD causing greater intracellular dilution (or higher intracellular free water concentration) under hypoosmotic stress, leading to an increase in T2. In particular, when ΔOsm -20 mM or -30 mM, there was a significant difference in T2 increase even with similar 〈 V c 〉, suggesting that T2 can increase by the dilution effect without cell volume expansion. Taken together, the free water pool increased during cell swelling, but the relationship between an increase in M f ,∞ and cell expansion was determined by the mechanisms of cell swelling ( Figure 4b ). In both mechanisms of hypoosmotic stress and [K⁺] elevation, the change in T2 depended linearly on the change in M f ,∞ , the slope of which depended on physiological factors such as cell volume and the associated intracellular dilution. Changes in bound pool per cell As shown in Figure 5a , the ratio of bound to free water pools, PSR, decreased in response to both hypoosmotic stress and [K + ] elevation, consistent with our previous reports 23 . Using PSR and M f ,∞ , the longitudinal magnetization of bound pool at equilibrium state, M 𝑏,∞ , was also calculated ( Figure 5b , for detailed calculations, see the data analysis of Materials and Methods). No significant change in M 𝑏,∞ was observed due to cell swelling under hypoosmotic stress. In contrast, for [K + ] elevation, a statistically significant decrease in M 𝑏,∞ (p < 0.05) was observed when [K + ] was 40 mM and 80 mM. These results suggest that the decrease in PSR under hypoosmotic stress mainly results from the increase in M f ,∞ ( Figure 4a ), whereas the decrease in PSR with increasing [K + ] is due to both the increase in M f ,∞ ( Figure 4a ) and the decrease in M 𝑏,∞ . Download figure Open in new tab Figure 5. Estimation of bound pool changes based on quantitative MT and modeling. a. PSR changes under hypoosmotic stress (left) and [K + ] elevation (right) conditions (n 14 scans). PSR decreased with statistical significance in both cases. b. M 𝑏,∞ changes under hypoosmotic stress (left) and [K + ] elevation (right) conditions (n 14 scans). M f ,∞ was calculated using PSR and M f ,∞ . Unlike the osmotic stress condition, [K+] elevation showed a statistically significant reduction in M 𝑏,∞ at high [K+], but under hypoosmotic stress, no statistically significant decrease was observed. c. 〈 M 𝑏, c 〉 changes with respect to 〈 V c 〉 . 〈 M 𝑏, c 〉 was calculated based on a close-packed cell pellet model. The gray dashed line represents the trend of increasing 〈 M 𝑏, c 〉 proportionally with cell volume expansion. In cases where M 𝑏,∞ decreased, the data points deviated from the gray dashed line. d. Illustration of the close-packed spherical cell pellet model including free water and bound pools. While the total M 𝑏,∞ within a voxel remains constant, 〈 M 𝑏, c 〉 increases as the cell volume expands. Statistical significance was marked with asterisks (-: p > 0.05; *: p < 0.05; **: p < 0.01; ***: p < 0.001). ( M 𝑏,∞ : the longitudinal magnetization of bound pool at equilibrium state, 〈 M 𝑏, c 〉: the average longitudinal magnetization of bound pool per cell). On the other hand, since changes in M 𝑏,∞ , which represents the bound pool within a voxel, do not directly reflect changes in the bound pool of individual cells, we also estimated the average longitudinal magnetization of the bound pool per individual cell, 〈 M 𝑏, c 〉, which is calculated by M 𝑏,∞ / ρ cell (see Eq. [5] in Materials and Methods). Figure 5c shows the increase in 〈 M 𝑏, c 〉 according to the relative change in 〈 V c 〉 under two conditions of hypoosmotic stress and [K + ] elevation, respectively. The increase in 〈 M 𝑏, c 〉 is expected from the results that the decrease in M 𝑏,∞ during cell swelling was about 10 even at maximum, e.g., under high [K+] conditions ( Figure 5b ), whereas the increase in 〈 V c 〉 was about 25 ( Figure 5c ) and thus the decrease in ρ cell was about 25 under the same conditions. The gray dashed line in Figure 3c represents a straight line along which the relative change in 〈 M 𝑏, c 〉 with respect to the initial 〈 M 𝑏, c 〉 0 before cell swelling, Δ〈 M 𝑏, c 〉/〈 M 𝑏, c 〉 0 , is equal to the relative change in 〈 V c 〉 with respect to the initial 〈 V c 〉 0 before cell swelling, (Δ〈 V c 〉/〈 V c 〉 0 ). Hypoosmotic stress conditions where no statistically significant changes in M 𝑏,∞ were observed corresponded to trends in this gray line. The conditions for increasing [K + ] also showed a similar trend overall, but when [K + ] was 40 mM and 80 mM, this trend deviated and the change in 〈 M 𝑏, c 〉 became smaller due to the decrease in M 𝑏,∞ ( Figure 5b ) and tended to be located below the gray line. These results demonstrate that during cell swelling, the bound pool increases proportionally with cell volume expansion and that additional factors appear to contribute to the decrease in the bound pool in high [K + ] environments. Figure 5d illustrates how 〈 M 𝑏, c 〉 grows in a close-packed cell pellet model as 〈 V c 〉 expands and ρ cell decreases accordingly. Discussion In this study, we investigated water dynamics associated with cell swelling under two conditions: [K + ] elevation and hypoosmotic stress in a close-packed cell pellet model, using MT parameters and T2 relaxation time in MRI. In particular, we investigated whether the changes in these MRI parameters due to [K + ] elevation are solely due to cell swelling from a mechanical point of view. According to our results, cell swelling in both conditions induced measurable increases in T2, which were linearly correlated with increases in intracellular free water concentration (or dilution) rather than cell volume per se, consistent with previous studies 24 – 26 . Interestingly, for the same change in cell volume (〈 V c 〉), hypoosmotic stress conditions resulted in higher T2 and larger free water pool ( M f ,∞ ) than elevated [K + ] conditions. In addition, cell swelling due to hypoosmotic stress exhibited cell volume saturation due to RVD, whereas intracellular free water concentration continued to increase linearly with increasing hypoosmotic stress. In contrast, increasing [K + ] induced larger cell volume expansion at the same dilution level compared to hypoosmotic stress, suggesting that cell volume responses to dilution vary depending on the relevant physiological mechanisms. Our results also demonstrated that the PSR decreased significantly in response to both hypoosmotic stress and [K + ] elevation, aligning with our previous findings 40 . This decrease in PSR coincided with a statistically significant increase in M f ,∞ under both conditions. The bound pool ( M 𝑏,∞ ) estimated by PSR and M f ,∞ showed no statistically significant changes under hypoosmotic stress conditions, but showed statistically significant decreases at higher [K + ] (e.g., 40 mM and 80 mM). The relatively larger change in M f ,∞ compared to M 𝑏,∞ indicates that the decrease in PSR primarily reflects an increase in the free water pool rather than a reduction in the bound pool. Examining the change in bound pool per cell (〈 M 𝑏, c 〉), calculated based on a close- packed cell pellet model, we observed an increase in 〈 M 𝑏, c 〉 proportional to cell swelling, which can be interpreted as an adaptive response to the expansion of cell volume, including de novo synthesis of structural proteins, expansion of cell membrane surface area, and consequent growth of interfacial water. A recent study by Watson et al. showed that cells buffer changes in water potential by unfolding intrinsically disordered protein domains, thereby increasing protein surface area and thus expanding the associated slow-exchange hydration layer 13 . Our finding is also consistent with the increase in the slow diffusion pool (SDP) fraction reported in diffusion-functional MRI studies of neuron swelling 41 – 43 . However, under high [K + ] conditions, the increase in 〈 M 𝑏, c 〉 during cell swelling was less pronounced compared to that induced by hypoosmotic stress. These differences are consistent with our observation that under hypoosmotic stress, cell volume expands only up to a certain amount due to the RVD response, whereas under [K⁺] elevation, it increases linearly with increasing [K⁺]. Furthermore, these results support that although both environments of [K⁺] elevation and hypoosmotic stress lead to an overall increase in cell volume, they involve different physiological processes in cell swelling. As one possible physiological process uniquely related to changes in 〈 M 𝑏, c 〉 under [K⁺] elevation, the change in membrane charge gradient due to the rise in [K + ] could affect the dynamics of interfacial polar water molecules that are located near the membrane surface and likely constitute part of the bound pool alongside macromolecules. Previous studies using SHG demonstrated measurable signal changes resulting from reorientation of interfacial water molecules driven by membrane potential variations, including those caused by [K + ] elevation 19 , 20 , 44 , 45 . Additionally, Raman spectroscopy studies have shown that reductions in surface electric potential correlate with decreased interfacial water signals, even in non- biological systems 46 . These studies agree with the results on water dynamics reported in this study. In other words, as a redistribution process, the interfacial water dissociated due to the change in membrane potential may move into the free water pool, thereby decreasing the bound water pool and increasing the signal of the free water pool. Interestingly, one of the quantitative MT parameters not presented above, the MT exchange rate 𝑘 𝑏 f , showed a statistically significant increase upon [K⁺] elevation, but no significant change was detected during hypoosmotic stress (Supplementary Fig. S1b). These differences in 𝑘 𝑏 f may be expected to serve as a potential source of MRI contrast to detect changes in membrane potential. On the other hand, physiological processes that are not related to changes in membrane potential may also be involved. In other words, since K⁺ acts not only as volume regulating ions but also as a pleiotropic signaling factor, physiological processes associated with [K⁺] elevation might also involve other non-exclusive mechanisms, such as selective synthesis or redistribution of intracellular macromolecules required to tolerate sustained high-[K⁺] conditions, or alternative adaptation programs that replace the canonical RVD when cell volume increases beyond the osmotic set point. To clarify whether the differences in 〈 M 𝑏, c 〉 between [K⁺] elevation and hypoosmotic stress conditions are primarily attributed to changes in membrane potential, it would be helpful to perform further studies that include MT studies using artificially controlled cell membranes or proteins whose surface charge can be manipulated without the intervention of complex cellular functions (e.g., homeostatic regulation). Based on these findings, we hypothesize that the relatively smaller increase in 〈 M 𝑏, c 〉 under [K + ] elevation conditions could be due to a decrease in interfacial water caused by changes in membrane potential. This interpretation suggests that interfacial water, modulated by electrical properties of the membrane, may also play a role in the bound pool dynamics in [K + ] elevation-induced cell swelling. To substantiate this hypothesis, future studies should explore the direct relationship between interfacial water and the bound pool measured in qMT experiments. Furthermore, investigating how changes in dynamically slow bound water induced by changes in membrane potential could be leveraged for enhanced contrast in MRI signals could potentially expand the application of MRI in studying cellular and membrane dynamics. For example, some MRI studies have practically applied changes in water dynamics in cases such as multiple sclerosis (MS) or cytotoxic edema 47 – 49 . Finally, the estimated changes in 〈 M 𝑏, c 〉 associated with [K+] elevation in this study may serve as a potential source of MRI contrast to detect nerve impulses that occur in milliseconds with negligible volume change and are accompanied by membrane potential changes during neuronal activity. For example, our simulations based only on the change in 〈 M 𝑏, c 〉 at a fixed cell volume yielded a 1 increase in signal change when 6.9 of the bound pool was redistributed into the free water pool (Supplementary Fig. S2b). This may be because hydrogen protons ( 1 H) in the bound pool, previously ‘invisible’ due to their very short T2, became detectable, effectively increasing the apparent proton density. In conclusion, MT and T2 measurements using MRI revealed that cell swelling induced by either [K + ] elevation or hypoosmotic stress led to an increase in the free water pool and T2, and that in this case, the T2 increase was primarily due to an increase in the intracellular free water pool (or dilution). In addition, for an equivalent increase of cell volume, cell swelling due to [K + ] elevation resulted in a smaller increase in the bound pool per cell, whereas cell swelling due to hypoosmotic stress showed a larger increase in both T2 and M f ,∞ . These findings show that K + -induced cell swelling involves different water dynamics than that of pure osmotic cell swelling, emphasizing the need to focus on the multifaceted cellular actions of K + . Such biophysical insights are expected to not only advance our understanding of basic cell physiology but also suggest potential endogenous MRI contrast mechanisms for detecting specific K + - driven cellular events. Materials and Methods Cell preparation We used non-excitable T-lymphocytes cells (or Jurkat), which have a spherical shape suitable for modeling of cell structure, are stable in terms of membrane potential. Jurkat cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium with 10 (v/v) fetal bovine serum (FBS, Thermo Fisher Scientific, Waltham, MA, USA) and 1 (v/v) penicillin/streptomycin (Thermo Fisher Scientific, Waltham, MA, USA). The composition of the cell medium during MR scanning was: 4.2 mM KCl, 145.8 mM NaCl, 20 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES, Thermo Fisher Scientific, Waltham, MA, USA), 4.5g/L glucose (Thermo Fisher Scientific, Waltham, MA, USA), and 10μM ethylenediaminetetraacetic acid (EDTA, Thermo Fisher Scientific, Waltham, MA, USA) with pH 7.2. To compare the osmotic changes induced by sodium ions (Na + ) and the membrane potential changes induced by potassium ions (K + ), the cells were placed in media with manipulated concentrations of each ion. We prepared three different media containing additional NaCl of -5, -10, and -15 mM, which can derive resulting osmolarity of -10, - 20, and -30 mM, to control the osmotic pressure of each medium. We also prepared three additional media with [K + ] of 20, 40, and 80 mM to control the membrane potential of cells within each medium. For MRI measurements, each cell suspension (prepared to yield sufficient signal for the requested slice thickness) was placed into each cylindrical well perforated into a double-sided spherical acrylic phantom ( Figure 1a ) and centrifuged (1,100 RPM, 5 min) to form a pellet as illustrated in Figure 1b . MRI data acquisition The acrylic phantom with cell pellets was scanned on a 9.4 T animal MRI scanner (BioSpin, Bruker). All data were collected in the form of 1D images with varying echo time (TE) using scan parameters such as spatial resolution 0.25 mm, number of pixels 128, and slice thickness 1 mm ( Figure 1c ). For T2 estimation, MRI signals were acquired using a single spin-echo sequence with a repetition time (TR) of 2000 ms and 40 TEs ranging from 8.1 ms to 85.4 ms on a logarithmic scale. For MT estimation, MRI signals were acquired using a selective inversion recovery multi-echo spin-echo sequence (IR-MESE) with 40 inversion times (TI) ranging from 0.24 ms to 10000 ms on a logarithmic scale and 16 TEs increasing linearly from 8.1 ms to 129.6 ms which can be acquired multiple data points along the T2 relaxation decay curve, thus enabling more precise estimation of MT parameters. To ensure sufficient recovery of longitudinal magnetization, TR was set to 15000ms. Data analysis Assuming that there are two hydrogen proton pools: free water pool and bound pool, the dynamics between two pools can be expressed with their own longitudinal relaxation rates (𝑅 1 f for free water pool and 𝑅 1𝑏 for bound pool) and rates of magnetization transfer (𝑘 𝑏 f , bound pool è free water pool; 𝑘 f 𝑏 , free water pool è bound pool). Assuming that M f 𝑡 and M 𝑏 𝑡 represent the longitudinal magnetizations of the free water pool and bound pool, respectively, M f 𝑡 was given by where M f ,∞ is the longitudinal magnetization at equilibrium state, and R1 ± and bf ± are defined as The ratio M 𝑏 / M 𝑏,∞ was calculated using the Bloch equations, based on the duration of the inversion pulse of the IR-MESE sequence, as demonstrated in previous studies 50 , 51 . The resulting MRI signal acquired with 16 TEs was fitted with mono- exponential decay to yield M f 𝑡 . To avoid stimulated echo contamination inherent to MESE sequences, only even numbered TEs were used for fitting 52 . M f 𝑡 was fitted to yield 𝑏 ± , 𝑅 ± , and M f ,∞ using 40 inversion times (TI) according to Equation (1) . This fitting was performed using a particle swarm optimization algorithm 53 in MATLAB (R2022b, MathWorks Inc., Natick, MA, USA). PSR was estimated by the ratio of the transfer rates 𝑘 f 𝑏 and 𝑘 𝑏 f according to the principle of microscopic reversibility 50 , 51 , 54 . Furthermore, assuming that R1f and R1b are equal, the equation for 𝑘 f 𝑏 /𝑘 𝑏 f simplifies to The detailed method for determining this value was described in previous MT studies 50,51,55. Cell volume measurement To measure cell volume using a microscope, all cells were placed in petri dishes with prepared media, where the osmolarity and [K + ] were controlled. Digital images were captured using an Olympus CKX53 microscope at 20x magnification ( Figure 1d ). The radii of over 1000 cells from the images by medium were analyzed using the “imfindcircles” function, which employs the Circular Hough Transform algorithm to detect circles in MATLAB. Cell volume distributions were plotted assuming spherical shape of the cells ( Figure 2 ). The mean cell volume 〈 V c 〉 was estimated using the cell volume distribution. Modeling We assumed that Jurkat cells with a spherical shape would form a close-packed structure as a result of centrifugation ( Figure 1b ). In this structure, the intracellular space fraction within a voxel ( v i ) is maintained by reducing the number of cells as the cell volume increases with the expansion of the cell radius 29 , 30 . For example, the v i of the FCC (Face Centered Cubic) structure, which has the most effective packing structure, is about 74 . v i can be estimated by the product of the cell number density ( ρ cell ) and the average cell volume (〈 V c 〉) 56 . 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Share Exploring Cellular Water Dynamics associated with Potassium Ion Changes Using Magnetic Resonance Imaging Seong-Min Kim , Kyeongseon Min , Jung Seung Lee , Jang-Yeon Park bioRxiv 2025.06.25.661446; doi: https://doi.org/10.1101/2025.06.25.661446 Share This Article: Copy Citation Tools Exploring Cellular Water Dynamics associated with Potassium Ion Changes Using Magnetic Resonance Imaging Seong-Min Kim , Kyeongseon Min , Jung Seung Lee , Jang-Yeon Park bioRxiv 2025.06.25.661446; doi: https://doi.org/10.1101/2025.06.25.661446 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Biophysics Subject Areas All Articles Animal Behavior and Cognition (7635) Biochemistry (17697) Bioengineering (13894) Bioinformatics (41951) Biophysics (21455) Cancer Biology (18593) Cell Biology (25509) Clinical Trials (138) Developmental Biology (13380) Ecology (19903) Epidemiology (2067) Evolutionary Biology (24322) Genetics (15611) Genomics (22509) Immunology (17737) Microbiology (40398) Molecular Biology (17183) Neuroscience (88619) Paleontology (667) Pathology (2833) Pharmacology and Toxicology (4825) Physiology (7644) Plant Biology (15158) Scientific Communication and Education (2046) Synthetic Biology (4296) Systems Biology (9825) Zoology (2271)